university of manchester the role of microtubule

University of Manchester

The role of microtubule-associated protein 1S

(MAP1S) in regulating autophagy

in the heart

A thesis submitted to the University of Manchester for the degree of Doctor of Philosophy in the Faculty of Biology,

Medicine and Health

2019

Yulia Suciati Kohar

School of Medical Sciences Division of Cardiovascular Sciences

2

TABLE OF CONTENTS

List of Figures ............................................................................................................... 6

List of Tables ............................................................................................................... 10

Abbreviations ............................................................................................................. 12

Abstract ...................................................................................................................... 16

Declaration ................................................................................................................. 18

Copyright statement .................................................................................................. 19

Acknowledgments ...................................................................................................... 20

1. INTRODUCTION .................................................................................................. 22

1.1. The Global Burden of Cardiovascular Disease ........................................... 22

1.2. Coronary artery disease and myocardial infarction................................... 24

1.3. Molecular mechanism of heart failure and myocardial infarction ............ 26

1.4. General overview of cardiac cell death ...................................................... 29

1.4.1. Apoptosis ............................................................................................ 30

1.4.2. Necrosis ............................................................................................... 33

1.4.3. Autophagy- dependent cell death ...................................................... 34

1.5. Autophagy ..................................................... Error! Bookmark not defined.

1.5.1. Types of autophagy ............................................................................. 34

1.5.2. Molecular mechanism of autophagy .................................................. 36

1.5.3. Autophagic flux ................................................................................... 45

1.6. The role of autophagy in cardiac homeostasis .......................................... 47

1.6.1. Autophagy in cardiomyocyte .............................................................. 47

1.6.2. Autophagy in cardiac pathological conditions .................................... 48

1.7. MAP1S ........................................................................................................ 53

1.7.1. Structure and biological function of MAP1 family of proteins ........... 53

1.7.2. Structure and biological function of MAP1S protein .......................... 56

1.7.3. The role of MAP1S in regulating autophagy and other pathologies .. 57

3

1.8. Summary of literature study ...................................................................... 60

1.9. Hypothesis .................................................................................................. 60

1.10. Aim ............................................................................................................. 61

2. MATERIALS AND METHODS ............................................................................... 63

2.1. Generation of MAP1S KO Mice .................................................................. 63

2.2. Molecular analysis ...................................................................................... 64

2.2.1. DNA Extraction .................................................................................... 64

2.2.2. PCR ...................................................................................................... 65

2.2.3. Gel electrophoresis ............................................................................. 66

2.2.4. Isolation of NRCM ............................................................................... 66

2.2.5. Isolation of MSF .................................................................................. 67

2.2.6. Protein expression analysis ................................................................. 68

2.2.7. Protein extraction ............................................................................... 68

2.2.8. Adenovirus productions ...................................................................... 72

2.2.9. siRNA Transfection .............................................................................. 78

2.2.10. pAd GFP-LC3 Transduction ................................................................. 79

2.2.11. pAdKeima, pAdParkin Transduction ................................................... 80

2.2.12. pAd/MAP1S Transduction ................................................................... 80

2.2.13. Lysotracker Analysis ............................................................................ 81

2.2.14. MitoTracker Analysis ........................................................................... 82

2.2.15. Seahorse XF Assay ............................................................................... 83

2.2.16. MTT assay ............................................................................................ 86

2.3. Animal work ............................................................................................... 86

2.3.1. Rapamycin and Chloroquine IP Injection ............................................ 87

2.3.2. TEM ..................................................................................................... 87

2.3.3. Mouse model of myocardial infarction .............................................. 88

4

2.3.4. cTnI analysis ........................................................................................ 88

2.3.5. Echocardiography ............................................................................... 89

2.4. Histological analysis ................................................................................... 91

2.4.1. Tissue fixation with formaldehyde, embedding and sectioning ......... 91

2.4.2. Masson’s Trichrome staining .............................................................. 93

2.4.3. TUNEL staining .................................................................................... 93

2.4.4. H&E staining ........................................................................................ 94

2.5. Statistical analysis ...................................................................................... 95

3. THE ROLE OF MAP1S IN MODULATING AUTOPHAGIC FLUX IN CARDIOMYOCYTES ..................................................................................................... 97

3.1. Background ................................................................................................ 97

3.2. Hypothesis .................................................................................................. 98

3.3. Aims and Objectives ................................................................................... 98

3.4. Results ........................................................................................................ 99

3.4.1. MAP1S is expressed in cardiomyocytes and in cardiac fibroblasts .... 99

3.4.2. MAP1S gene silencing in NRCM ........................................................ 100

3.4.3. Molecular cascade of LC3 activation ................................................ 101

3.4.4. Studies using MAP1S knockout (KO) mice ........................................ 111

3.4.5. The modulation effect of autophagic flux in NRCM’s lysosome ...... 120

3.5. Discussion ................................................................................................. 123

4. THE ROLE OF MAP1S IN REGULATING MITOPHAGY ........................................ 127

4.1. Background .............................................................................................. 127

4.2. Hypothesis ................................................................................................ 129

4.3. Aims and Objectives ................................................................................. 130

4.4. Results ...................................................................................................... 131

4.4.1. MAP1S gene silencing prevents binding of autophagosome with damaged mitochondria ..................................................................... 131

5

4.4.2. MAP1S gene silencing affects mitochondrial organizational network …………………………………………………………………………………………………….135

4.4.3. MAP1S gene silencing displayed reduced mitochondrial function .. 138

4.4.4. MAP1S gene silencing affects apoptotic pathway ............................ 144

4.5. Discussion ................................................................................................. 150

5. THE EFFECTS OF MAP1S GENETIC ABLATION DURING MYOCARDIAL INFARCTION ............................................................................................................. 154

5.1. Background .............................................................................................. 154

5.2. Hypothesis ................................................................................................ 155

5.3. Aims and Objectives ................................................................................. 155

5.4. Results ...................................................................................................... 156

5.4.1. Expression of MAP1S in mouse model with pathological condition in the heart ........................................................................................... 156

5.4.2. Analysis of MAP1S-/- cardiac phenotype after 4 weeks of MI .......... 158

5.4.3. Analysis of heart phenotype at 3 days post MI ................................ 168

5.5. Discussions ............................................................................................... 177

6. GENERAL DISCUSSION ...................................................................................... 181

6.1. Overall conclusions .................................................................................. 186

6.2. Future direction ....................................................................................... 186

6.3. Study limitations ...................................................................................... 187

7. References ........................................................................................................ 189

Word count: 37.207

6

List of Figures

Figure 1.1. Distribution of major causes of death including CVDs ............................ 22

Figure 1.2. CVD Mortality rate of men and women based on the BHF statistical

report, ........................................................................................................................ 23

Figure 1.3. Pathophysiology of ventricular remodelling post-acute myocardial

Infarction. ................................................................................................................... 29

Figure 1.4. The caspase cascade in apoptosis pathways. .......................................... 31

Figure 1.5. Cardiac remodelling following myocardial infarction. ............................. 33

Figure 1.6. The different types of autophagy. ........................................................... 35

Figure 1.7. Molecular mechanism of autophagy. ...................................................... 38

Figure 1.8. Schematic model of the major pathways in the regulation of the

autophagic machinery ................................................................................................ 42

Figure 1.9. Schematic image on autophagic flux. ...................................................... 45

Figure 1.10. Dynamic regulation of autophagy. ......................................................... 46

Figure 1.11. Quantification of autophagic flux. ......................................................... 47

Figure 1.12. How the heart reacts under several pathological conditions. ............... 49

Figure 1.13. Domain organization and posttranslational processing of mammalian

MAP1-family proteins. ............................................................................................... 55

Figure 1.14. A model showing the function of MAP1S. ............................................. 59

Figure 2.1. Generation of MAP1S knockout mice. ..................................................... 63

Figure 2.2. Breeding strategy used to generate MAP1S knockout and control mice 64

Figure 2.3. pENTR/D-TOPO map used for generating entry clone. ........................... 73

Figure 2.4. pAd/CMV/V5-DEST Vector map. .............................................................. 74

Figure 2.5. Restriction enzyme product of pAd/MAP1S, pAd/Keima, pAd/Parkin. ... 75

Figure 2.6. OCR of the Agilent Seahorse Mito Stress Test obtained from SeaHorse XF

Analyser. ..................................................................................................................... 83

Figure 2.7. Diagram on modulation of the compound used in the experiment. ....... 85

Figure 2.8. M-mode echocardiography image of the heart....................................... 90

Figure 2.9. The method used to section the heart tissue in this study. .................... 92

Figure 3.1. MAP1S expression levels in NRCM and cardiac fibroblasts under basal

conditions. ................................................................................................................ 100

Figure 3.2. siRNA mediated MAP1S gene silencing in NRCM. ................................. 101

7

Figure 3.3. Higher autophagosome formation in MAP1S-deficient cardiomyocytes.

.................................................................................................................................. 103

Figure 3.4. Expression of LC3II and other autophagy markers in NRCM. ................ 106

Figure 3.5. MSF wild type and MSF MAP1S -/- isolation. ........................................ 107

Figure 3.6. Derivation of WT and KO MSF from WT and KO earsnips. .................... 107

Figure 3.7. Higher autophagosome formation in MAP1S deficient MSF. ................ 109

Figure 3.8. LC3II and other autophagy marker expression levels in MSF. ............... 111

Figure 3.9. Generation of MAP1S global KO mice. .................................................. 112

Figure 3.10. Breeding strategy for MAP1S mice. ..................................................... 113

Figure 3.11. Initial formation of autophagosome as shown by TEM. ...................... 114

Figure 3.12. Accumulation of lysosome structures and autophagosomes .............. 115

Figure 3.13. MAP1S KO mice exhibit more lysosome structures in response to RC

Intraperitoneal (IP) Injection. ................................................................................... 116

Figure 3.14. Reduction in LC3II expression levels in MAP1S- deletion mice compared

to WT control. .......................................................................................................... 118

Figure 3.15. No difference in several autophagy markers after RC administration.

.................................................................................................................................. 119

Figure 3.16. Higher Lysotracker intensity in MAP1S-deficient cardiomyocytes with

fluorescence microscope imaging. ........................................................................... 121

Figure 3.17. Higher Lysotracker intensity in MAP1S-deficient cardiomyocytes using

FACS. ......................................................................................................................... 122

Figure 4.1. A model on MAP1S interaction .............................................................. 129

Figure 4.2. GFP-LC3 co-localisation with Red MitoTracker in NRCMs. .................... 132

Figure 4.3. Dual excitation of Keima in response to changing environmental pH. . 133

Figure 4.4. More red signal emitted from siRNA control cardiomyocytes than in

MAP1S-deficient cardiomyocytes. ........................................................................... 134

Figure 4.5. Increased mitochondrial fragmentation in MAP1S-deficient

cardiomyocytes. ....................................................................................................... 136

Figure 4.6. More apparent mitochondrial network fragmentation in MAP1S-

depleted MSF. .......................................................................................................... 137

Figure 4.7. Schematic diagram illustrating the Seahorse XF Cell Mito Stress test

experiment. .............................................................................................................. 139

8

Figure 4.8. OCR traces in response to several compounds. .................................... 140

Figure 4.9. OCR in basal state. ................................................................................. 141

Figure 4.10. OCR after rapamycin treatment........................................................... 142

Figure 4.11. OCR after H2O2 administration. ........................................................... 143

Figure 4.12. TUNEL Assays in NRCMs indicated higher apoptosis level in MAP1S-

deficient cardiomyocytes. ........................................................................................ 146

Figure 4.13. Analysis of apoptosis markers indicates higher apoptosis levels in

MAP1S deficient cardiomyocytes. ........................................................................... 147

Figure 4.14. Other apoptosis markers were not significantly different between

groups. ...................................................................................................................... 148

Figure 4.15. MTT assay showed no significant difference in cellular viability after

H2O2 treatment in MAP1S NRCM. ............................................................................ 149

Figure 5.1. MAP1S cardiac expression levels in following TAC-stimulation for 5

weeks. ...................................................................................................................... 156

Figure 5.2. Higher MAP1S expression levels were observed in WT mice following

acute MI compared to sham operated mice. .......................................................... 157

Figure 5.3. Kaplan-Meier analysis to assess mouse survival following MI. ............. 158

Figure 5.4. Reduced cardiac function in both genotypes after 4 week MI. ............. 159

Figure 5.5. Left ventricular structures are more responsive to hypertrophy induction

in WT mice compared to MAP1S-/- mice 4 weeks post MI. ..................................... 160

Figure 5.6. Infarct size measurement in MAP1S-/- mice and wild type controls after 4

weeks. ...................................................................................................................... 163

Figure 5.7. Analysis of cardiac size at 4 weeks post-MI. .......................................... 164

Figure 5.8. Less hypertrophic response in MAP1S-/- mice after chronic MI. ........... 166

Figure 5.9. Apoptosis assessment by TUNEL assay at 4 weeks post MI. ................. 168

Figure 5.10. Reduced cardiac function in both genotypes 3 days post MI. ............. 169

Figure 5.11. Left ventricular structure showed no difference between 4

experimental groups 3 days post MI. ...................................................................... 171

Figure 5.12. Infarct size measurement shows significant increase in infarct size in MI

operated wild type and MAP1S-/- mice compared to their sham operated controls.

.................................................................................................................................. 172

9

Figure 5.13. Cardiomyocyte cross sectional area assessment using Haematoxylin

Eosin staining from four different groups after 3 day MI. ....................................... 175

Figure 5.14. Apoptosis assessment by TUNEL assay at 3 days post MI. .................. 176

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List of Tables

Table 1.1. Key autophagic factors and their regulatory roles. ................................... 44

Table 1.2. Pharmacological and genetic studies implicating autophagy or mitophagy in cardiovascular pathology in vivo ............................................................................ 53

Table 1.3. Interacting partners of MAP1-family proteins .......................................... 54

Table 2.1. PCR Master Mix components for each sample. ........................................ 65

Table 2.2. Primers sequences used in PCR reaction .................................................. 65

Table 2.3. PCR cycling conditions for genotyping reactions. ..................................... 66

Table 2.4. Solutions for separating gel used for SDS- Polyacrylamide Gel Electrophoresis. .......................................................................................................... 70

Table 2.5. Solutions for stacking gel used for SDS-Polyacrylamide Gel Electrophoresis. .......................................................................................................... 71

Table 2.6. Primary antibodies used for western blot analysis. .................................. 72

Table 2.7. Secondary antibodies used for western blot analysis. .............................. 72

Table 2.8. Restriction enzymes for inserting the mutant to entry clone. .................. 72

Table 2.9. Reaction components for the insertion of the mutant clone into the entry clone. .......................................................................................................................... 73

Table 2.10. Components used in LR reaction. ........................................................... 74

Table 2.11. T7 and V5 primers for pAd/CMV/V5-DEST sequencing. ......................... 75

Table 2.12. Components used for primary adenovirus production. ......................... 76

Table 2.13. Dilutions for determining Adenovirus titration. ..................................... 78

Table 2.14. Volumes of siRNA transfection reagents used to reach 25nM final concentration. ............................................................................................................ 79

Table 2.15. Terms used in determining the parameters in Seahorse analyser experiment. ................................................................................................................ 84

Table 2.16. Components used for Seahorse XF Analyzer experiment ....................... 86

Table 2.17. Parameters used to analyse cardiac function in sham and MI groups in both genotypes. ......................................................................................................... 91

Table 2.18. Tissue processing protocols used in this study. ...................................... 92

11

Table 5.1. Echocardiography parameters taken from 4 experimental groups at 4 weeks post MI or sham surgery. .............................................................................. 161

Table 5.2. Echocardiography parameters taken from 4 experimental groups 3 days post MI / sham surgery. .......................................................................................... 170

12

Abbreviations

AMPK AMP- activated protein kinase

ANOVA Analysis of variance

Apaf-1 Apoptotic protease-activating factor 1

ATG Autophagy related genes

ATP Adenosine Triphosphate

Bad Bcl2-xL/Bcl-2 associated death protein

Bak Bcl-2 -antagonist/killer-1

Bax Bcl-2-associated-X protein

BCA Bicinchoninic acid

Bcl-2 B-cell lymphoma-2

Bcl-xL B cell leukaemia/lymphoma-x, long isoform

BD Binding domain

Beclin-1 Coiled-coiled, myosin-like Bcl-2 interacting protein-1

BSA Bovine serum albumin

BW Body weight

BZ Border zone

BZ Border Zone

Ca Calcium

CAD Coronary artery disease

CCCP Carbonyl cyanide m-chlorophenylhydrazone

cTnI Cardiac troponin I

CVDs Cardiovascular diseases

DAMPs Danger associated molecular patterns

DAPI 4',6 -diamidino-2-phenylindole

dATP Deoxyadenosine triphosphate

DISC Death inducing signalling complex

dIVS Thickness of interventricular septum in diastole

dLVD Diastolic left ventricular diameter

dLVPW Diastolic left ventricular posterior wall thickness

13

DMEM Dulbecco’s modified eagle’s medium

DMSO Dimethyl sulfoxide

ECL Enhanced chemiluminescence

eEF2 eukaryotic elongation factor-2

EF Ejection Fraction

EGF Epidermal growth factor

ER Endoplasmic reticulum

FADD Fass- associated death domain

FCCP Carbonil cyanide p-triflouromethoxyphenylhydrazone

FIP200 RB1-inducible coiled- coil protein 1

FL Full Length

FS Fractional shortening

GABARAPs γ- aminobutyric acid receptor-associated proteins

GAPDH Glyceraldehyde-3-phosphate dehydrogenase

HC High Chain

HEK Human embryonic kidney

HEPES 4-(2-hydroxyethyl)-1-piperazineethanesulfonic acid

HF Heart failure

HRP Horseradish peroxidase

HW Heart weight

I.p Intraperitoneal

IMS Industrial methylated spirit

kDa kilo Daltons

LAD Left anterior descending artery

LAMP2 Lysosomal membrane protein 2

LC Light chain

14

LC3 Microtubule-associated protein 1A/1B-light chain 3

LRPPRC leucine-rich PPR motif containing protein

LVM/BW Left Ventricular Mass over Body Weight

MAP1S Microtubules-associated protein 1S

MAPs Microtubules-associated proteins

MI Myocardial Infarction

MOI Multiplicity of infection

MPT Mitochondrial permeability transition

MPTP Mitochondrial permeability transition pore

mRNA Messanger RNA

mTOR mammalian target of rapamycin

mt-ROS Mitochondrial reactive oxygen species

MTT Thiazoyl blue tetrazodium bromide

NCDs Non-communicable diseases

NRCM Neonatal rat cardiomyocyte

O2- Superoxide ion

OCR Oxygen consumption rate

PBS Phosphate buffered saline

PCR Polymerase chain reaction

PE Phosphatidylethanolamine

PI3KC1 Phosphoinositide 3-kinase complex 1

PVDF Polyvinylidene fluoride

RASSF1A Ras-association domain family protein 1A

SDS-PAGE Sodium dodecyl sulphate polyacrylamide gel electrophoresis

SEM Standard error of the mean

siRNA small interfering RNA

sIVS Thickness of interventricular septum in systole

15

sLVD Systolic left ventricular diameter

sLVPW Systolic left ventricular posterior wall thickness

TAC Transverse aortic constriction

TBS-T Tris-Buffered Saline containing 0.05% Tween 20

TE Tris-EDTA

TEM Transmission electron microscopy

TGF-β Tumour growth factor-β

TL Tibia length

TMB Tetramethylbenzidine

TNFα Tumour necrosis factor α

TSC2 Tuberous sclerosing complex 2

TUNEL Terminal deoxynucleotidyl transferase mediated nick end labelling

ULK Unc-51-like-kinase

ULK1 Unc-51-like kinase 1

UVRAG Ultraviolent irradiation resistance- associated gene

WIPI2 WD repeat domain phosphoinositide- interacting proteins

16

Abstract

A thesis submitted to the University of Manchester by Yulia Suciati Kohar for the

degree of Doctor of Philosophy entitled

“The role of microtubule-associated protein 1S (MAP1S) in regulating autophagy in the heart”

June 2019

Autophagy is an important process to maintain cellular homeostasis in many cell

types including cardiomyocytes. One type of selective autophagy which degrades

defective mitochondria is called mitophagy. In the heart, defective autophagy

and/or mitophagy in response to pathological stimuli may lead to the development

of adverse cardiac remodelling and eventually heart failure. The microtubule-

associated protein 1S (MAP1S) has previously been identified as an interacting

partner of the major autophagy regulator LC3; however, its role in the heart is still

unknown. In this study I hypothesised that MAP1S may play an essential role in

regulating autophagy in the heart.

I used mice with genetic knockout of the Map1s gene (MAP1S-/-) and neonatal rat

cardiomyocytes (NRCM) with siRNA-mediated gene silencing to study the role of

MAP1S in the heart and in cardiomyocytes. In response to autophagic stimulation

using rapamycin and chloroquine treatment (Rap/Chl), MAP1S-deficient

cardiomyocytes displayed reduction in autophagic flux with an indication of

autophagososme-lysosome fusion impairment. This finding was supported by data

from electron microscopy analysis of Rap/Chl- induced MAP1S-/- mice, which

showed evidence of higher numbers of lysosomal structures as well as indications

of altered autophagosome-lysosome fusion in MAP1S-/- mice. Furthermore, in vitro

analyses using GFP-LC3 + MitoTracker co-staining and an mt-mKeima reporter

system suggested that MAP1S-deficient cardiomyocytes were characterized by

impairment of mitochondrial binding with autophagosomes. In addition, analysis of

mitochondrial function using a Seahorse analyser showed that MAP1S depletion

17

resulted in the reduction of mitochondrial function. Equally important, MAP1S-

knockdown cardiomyocytes exhibited increased apoptosis.

To study the role of MAP1S in pathological conditions in vivo, I subjected MAP1S-/-

mice to myocardial infarction. Following MI, there was significantly higher mortality

in MAP1S-/- mice than in WT controls, despite a comparable degree of infarction

between groups as assessed by cTnI level and the fibrotic infarct area.

Echocardiography analysis also suggested a reduction in ejection fraction in MAP1S-

/- mice compared to WT after MI. Importantly, TUNEL assay indicated higher

apoptosis in MAP1S-/- mice which might contribute to the low survival rate. This

phenotype might be attributable to altered autophagy or mitophagy in the

knockout animals.

Taken together, my findings indicate that MAP1S plays an essential role in

regulating autophagy and mitophagy in the heart. Ablation of MAP1S reduces

survival and leads to the severe impairment of cardiac function after MI.

18

Declaration

I declare that no portion of the work referred to in this thesis has been submitted in

support of an application for another degree or qualification of this or any other

university or other institute of learning.

Yulia Suciati Kohar

Division of Cardiovascular Sciences

School of Medicine

Faculty of Biology, Medicine and Health

19

Copyright statement

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20

Acknowledgments

I would like to take this opportunity to thank my supervisor Dr Delvac Oceandy for

his continuous support and guidance throughout my PhD programme. He has

always been able to help me scientifically and encourage me morally. I would never

have had this experience if not for his help.

I would also like to thank my co-supervisor Prof Xin Joy Wang and my advisor Dr

Chantal Hillarby for their support and help. I also want to thank Dr Elizabeth

Cartwright for her support with my in vivo project.

Furthermore, I am extremely grateful to Dr Nicholas Stafford for his immense help

and support for all the experimental and scientific aspects of my project. In

addition, I would like to thank Dr Min Zi, Mr Sukhpal Prehar and Mrs Florence

Baudoin for their help with the in vivo and in vitro aspects of my project.

I know that my PhD life would not have been enjoyable without the friendship I

have with my friends: Alex, Bayu, Efta, Farrah, Thuy and Vera. We shared not only

our support but also our lunches, nibbles and digestive biscuits.

I would also like to thank LPDP (Indonesia Endowment Fund for Education) and the

Indonesian Ministry of Finance for the PhD programme scholarship.

Finally and foremost, I give all my gratitude and massive thanks to my three real-life

supporters, my husband, Dr Riza Setiawan, and my two dear boys, Thiflan and

Sultan. I am very sure that without their immense support and unconditional love, I

would not be where I am today.

Last but not least, I also want to thank my late-Mummy for being the role model of

how a hard-working woman should be. I miss her immensely. Thank you also to my

parents Papa, Ibu and Bapak for all your support and love.

21

CHAPTER 1

Introduction

22

1. INTRODUCTION

1.1. The Global Burden of Cardiovascular Disease

Accounting for 71% of all deaths, non-communicable diseases (NCDs) are the

leading global cause of death and a large burden on human health worldwide (WHO

2018). These diseases comprise cardiovascular diseases (including heart disease and

stroke), diabetes, cancer and chronic respiratory diseases (including chronic

obstructive pulmonary disease and asthma) (WHO 2018; Bloom & Cafiero 2012).

Among these groups, cardiovascular diseases (CVDs) are defined as those involving

the heart, vascular diseases of the brain, and diseases of blood vessels (Mendis et

al. 2011; Gaziano et al. 2010).

Figure 1.1. Distribution of major causes of death including CVDs ; adapted from (WHO 2018).

According to the 2018 WHO report, CVDs are responsible for over 17.9 million

deaths per year and are the leading causes of death worldwide (WHO 2018; Mendis

et al. 2011; Mendis & Chestnov 2014) (Figure 1.1).

23

In the UK, CVDs remain a significant cause of mortality, where they are linked to

28% of all female deaths and 29% of all male deaths (Bhatnagar et al. 2015). Among

CVDs, heart failure (HF) as a result of coronary artery disease and myocardial

infarction is the most common. Coronary heart disease is responsible for almost

70,000 deaths in the UK each year. On average, 190 people die each day, or one

death occurs every eight minutes. More than 6.8 billion pounds were spent on

treating CVD in England in 2012/2013 (Bhatnagar et al. 2015). The British Heart

Foundation (BHF) recently reported that in 2018, an average of 420 people died

each day due to cardiovascular diseases, equating to one death every three minutes

(BHF 2018).

Figure 1.2. CVD Mortality rate of men and women based on the BHF statistical report, 2016.

The 2016 BHF statistical report showed that coronary heart disease is the major

cause of CVD mortality in men (26.4%), while a lower percentage is shown for

women (16.9%) out of all CVD mortalities (Figure 1.2).

0 5 10 15 20 25 30

Chronic rheumatic heart dieseases

Hypertensive diseases

Coronary heart disease

Other heart diseases

Stroke

Diseases of arteries, arterioles andcaplilaries

Diseases of veins, lymphatic vessels andlymph nodes

The mortality rate of CVD between men and women in UK,BHF statistical report 2016 (percentage)

Men women

24

According to the American Heart Association report in 2015, CVD appears to be the

underlying cause of death for 31.3% (786,641) out of 2,515,458 deaths, or ≈1 of

every 3 deaths, in the United States annually. More than 2150 Americans die of

CVD each day, an average of 1 death every 40 seconds (Mozaffarian et al. 2014).

From the same report, 1 in 9 death certificates (284,388 deaths) in the United

States mentioned HF as the main cause. By 2030, more than 8 million people in the

United States (1 in every 33) will have HF and projections shows that the prevalence

of HF will increase by 46% from 2012 to 2030 (Mozaffarian et al. 2015; Bluemke et

al. 2014), while the total direct medical costs of HF are projected to increase from

$21 billion to $53 billion (Bluemke et al. 2014).

The primary goals for heart failure treatment are to improve clinical status,

functional capacity, quality of life, reduce mortality and minimise hospitalisation

(Ponikowski et al. 2016). Although the significant progress in primary prevention of

HF has led to reduced mortality rates in developed countries, the burden of

hospitalization among patients living with HF is still the major problem to address

(Luepker 2017). In UK alone, half a million of HF patients spent 1-2% of the NHS

budget, and over 60%- 70% is spent on hospitalization costs (Cowie 2017).

Therefore, in order to reduce the number of hospitalization and related costs,

further studies on the mechanisms underlying the development of HF and how to

prevent, or even reverse it, are needed.

1.2. Coronary artery disease and myocardial infarction

Heart failure is characterised by the inability of the heart to cope with the

metabolic demands of the periphery. It is the common end-stage of many frequent

cardiac diseases and is characterized by a persistent progression of anatomical and

physiological transformations (Ritter & Neyses 2003; Ponikowski et al. 2016; Heart

et al. 2014; Wilkins et al. 2017; Cowie 2017; Luepker 2017). In most cases of HF,

excessive cardiac workload leads to a pathological enlargement of the heart in an

endeavour to manage the increased metabolic demands (Barry et al. 2008).

In terms of classification, HF has been classified into three subtypes according to

the ejection fraction, natriuretic peptide levels, the presence of structural heart

25

disease, and diastolic dysfunction. They are classified into HF with reduced ejection

fraction (HFrEF) with EF <40%, HF with preserved ejection fraction (HFpEF) EF≥ 50%

and HF mid-range ejection fraction (HFmrEF) with EF between 40%-49%

(Ponikowski et al. 2016). Despite advances in treatments to manage symptoms in

HF patients, to date HF still is a global pandemic. Treatment strategies such as

using neuro-hormonal antagonists (Angiotensin Converting Enzyme inhibitor, Beta-

blocker, Mineralocorticoid antagonists) have been shown to improve survival, but

do not stop the progression of HF. In fact, several drugs used in the treatment of HF

have shown detrimental effects on long term outcomes, even though they have

beneficial effects in shorter-term to reduce the symptoms (Ponikowski et al. 2016).

Therefore, the molecular mechanisms underlying this condition are a major focus of

investigation.

Chronic heart failure is multifactorial (Neubauer 2007; Breckenridge 2010). One of

the factors that may play a major role in the progression of HF is the deprivation of

cardiac energy. This condition may be due to the disruption of blood flow to the

myocardial region, which is important in supplying oxygen and nutrition, thereby

causing myocardial infarction (Chen-scarabelli et al. 2014). The most frequent cause

of heart failure is myocardial infarction (Kanamori et al. 2013). The post myocardial

infarction remodelling process may cause the heart to gradually dilate to maintain

cardiac output (Kanamori et al. 2013). The prolonged ischemic phase stimulates

several molecular and structural changes that can damage the cells and alter

myocardial function (Chen-scarabelli et al. 2014). The ischemic phase of myocardial

infarction leads to the deprivation of several important factors, such as oxygen,

nutrients and survival factors, as well as the accumulation of metabolic waste

(Whelan et al. 2010). The late remodelling process during the chronic phase leads

to a decrease in cardiac function, cell death and heart failure. Permanent coronary

occlusion can cause myocardial cell death. Cardiac myocyte death during

permanent coronary occlusion can occur via apoptosis or necrosis, and may also be

associated with autophagy (Whelan et al. 2010).

26

1.3. Molecular mechanism of heart failure and myocardial infarction

After myocardial infarction, the ventricle responds with progressive remodelling,

comprising both physiological and anatomical changes (Gajarsa & Kloner 2011).

There is a consensus statement defining remodelling as ‘‘the genomic expression

resulting in molecular, cellular, and interstitial changes that are manifested clinically

as changes in size, shape, and function of the heart after cardiac injury” (Gajarsa &

Kloner 2011). The remodelling process results in increased loading conditions,

triggering activation of intracellular signalling processes that initiate changes such

as dilatation, hypertrophy and the formation of collagenous scars. The remodelling

process occurs not only in the infarcted area but also in non-infarcted areas. In the

infarcted area, the damage to and loss of myocytes initiates an inflammatory

response by recruiting inflammatory cells such as neutrophils, leucocytes and

macrophages which localize to the infarcted site (Sutton & Sharpe 2000). This is

illustrated in Figure 1.3. This process mostly occurs in the early phase of myocardial

infarction. This early phase (before 72 hours) involves infarct expansion, while the

late phase of myocardial infarction (beyond 72 hours) involves dilatation, changes

in ventricular shape, and hypertrophy (Sutton & Sharpe 2000).

The healing of cardiomyocytes following acute sudden death in the infarcted heart

occurs in three overlapping phase: the inflammatory phase, the proliferative phase

and the maturation phase (Seropian et al. 2014; Frangogiannis 2014). The

molecular and cellular changes of these phases are described below.

Inflammation in cardiac remodelling. Cardiomyocyte loss following cardiac injury

rapidly activates an innate immune response that subsequently triggers an

inflammatory response (Gajarsa & Kloner 2011; Frangogiannis 2014; Sutton &

Sharpe 2000; French & Kramer 2007; Seropian et al. 2014; Burchfield et al. 2013).

The dying cardiomyocytes release intracellular proteins into the circulation and

initiate this response. Inflammatory cells such as neutrophils, monocytes,

macrophage and lymphocytes infiltrate the infarcted tissue to remove dead cells

and extracellular matrix debris (Burchfield et al. 2013; Frangogiannis 2014; Sutton &

Sharpe 2000). This phase is actively repressed to prepare for the proliferative phase

of healing.

27

Infarct expansion, cardiac fibrosis and hypertrophy. During this phase, infarct

expansion occurs as a result of several conditions. Degradation of inter myocyte

collagen struts by serine protease and activation of matrix metalloproteinases

(MMPs) released by neutrophils mark this phase. This degradation allows cellular

movement. The infarcted left ventricle dilates regionally during this expansion,

resulting in wall thinning and ventricular dilatation. The wall thinning occurs mainly

by a mechanism called slippage, characterised by a sliding movement of the

myocytes as a consequence of collagen struts degradation (Gajarsa & Kloner 2011).

As the infarct expands, mononuclear cells and macrophages secrete growth factors

that recruit and activate cardiac fibroblasts, which proliferate and secrete vast

amounts of extracellular matrix proteins such as collagen I, (Gajarsa & Kloner 2011;

Frangogiannis 2014; Burchfield et al. 2013). This results in a tightly cross-linked

fibrotic scar with high tensile strength to prevent rupture. The Increased wall stress

in this phase, mediated by mechanoreceptors and intracellular signalling such as

angiotensin II release, is a powerful stimulus for hypertrophy. The non-infarcted

cardiomyocytes respond to the increased wall stress by eccentric hypertrophy. This

adaptive hypertrophy to compensate the functional loss of infarcted

cardiomyocytes is beneficial at first, however, over time, with sustainable wall

stress, it becomes detrimental leading to cardiac dysfunction and heart failure

(Gajarsa & Kloner 2011).

Mitochondrial dysfunction, apoptosis, and autophagy in cardiac remodelling. All the

mechanisms involved in the cardiac remodelling are potentially related with

mitochondrial dysfunction (Schirone et al. 2017). As an organelle that are crucial for

generation of ATP for continuous contraction of the heart, mitochondria also

physiologically generate mitochondrial reactive oxygen species (mt-ROS). These by-

products of mitochondrial phosphorylative oxidation are important and act as

intracellular messengers, however at high levels, they can be responsible for

mitochondrial damage. Angiotensin II has been reported to increase mt-ROS in

mice, and contribute to development of cardiac fibrosis and hypertrophy (Schirone

et al. 2017). Several studies have shown that mt-ROS can induce cardiac

remodelling and overexpression of an enzyme that reduces ROS has been shown to

28

improve LV remodelling (Schirone et al. 2017). The ROS elevation is one of many

factors that can trigger apoptosis in the failing ischaemic or overloaded heart,

beside stimulations from tumour necrosis factor α (TNFα), Fas/Fas ligand (FASL),

granzymes, and anti-cancer drugs (Hojo et al. 2012).

While necrosis is believed to be the main mechanism in the initial phase post

cardiac injury, cardiac remodelling progresses beyond this. Apoptosis has been

demonstrated at every stage, but its pathophysiological role is more apparent in

the later phase where it is believed to be the cause of progressive myocyte loss and

LV dilatation (Abbate et al. 2002). A high rate of apoptosis has been reported in the

peri-infarct area, while in the remote region (unaffected by the infarction) it is

lower but still higher than in the control heart, and was found to be associated with

cardiac remodelling (Abbate et al. 2006).

Another mechanism that has recently been correlated to development of cardiac

remodelling is autophagy. As an evolutionarily conserved mechanism for cellular

homeostasis, it has been shown that induction of autophagy exerts

cardioprotective effects in several cardiovascular pathologies (Schirone et al. 2017).

The adaptive mechanism of autophagy in response to stress conditions is believed

to be utilised in the stress-induced heart. However, studies on the role of

autophagy in cardiovascular disease have proven that autophagy’s intensity,

duration and activation with other signalling pathways are the important aspects in

regulating the cardiac response to pathogenic stimuli. A prolonged state of high

level autophagy activation has been reported to be detrimental, while upregulation

of this mechanism has also been reported to be adaptive in nutrient deprivation,

oxidative stress and hypoxia. Therefore, investigation into autophagic responses in

cardiac remodelling is important to improve our understanding on how this

mechanism responds to the failing heart.

29

Figure 1.3. Pathophysiology of ventricular remodelling post-acute myocardial Infarction. Inflammation plays an important role in ventricular remodelling post myocardial infraction. The inflammatory cells leave the bloodstream via endothelial cell junctions and clear damaged cardiomyocytes, while cardiac fibroblasts produce a collagen deposition. In early remodelling, infarct expansion occurs within hours of myocyte injury, causing left ventricular thinning and ventricular dilatation (left). Another ventricular response is compensatory hypertrophy in the non-infarcted area of the left ventricle (right). Under continuous stimuli and adverse remodelling, ventricular dilatation and thinning lead to ejection fraction reduction and heart failure (bottom). Adapted from (Seropian et al. 2014).

1.4. General overview of cardiac cell death

Cell death can be classified in several ways, however, based on the morphotypes of

the fragment to be disposed of, cell death classification is divided into three

different forms: Type I cell death or apoptosis, exhibiting cytoplasmic shrinkage,

chromatin condensation, nuclear fragmentation, and plasma membrane blebbing,

formation of apoptotic bodies that are efficiently degraded within lysosomes; type

30

II cell death or autophagy, which exhibits cytoplasmic vacuolisation, phagocytic

uptake and lysosomal degradation; type III cell death or necrosis, displaying no

features of type I and II cell death, where disposal of cell corpses occurs without

lysosomal involvement (Galluzzi et al. 2018; Whelan et al. 2010). Each of these

types will be discussed below.

1.4.1. Apoptosis

Apoptosis is an actively regulated form of cell death (also known as programmed

cell death). There are two main pathways regulating apoptosis, namely the intrinsic

and extrinsic pathways. The intrinsic pathway involves mitochondria and the

endoplasmic reticulum (ER), while the extrinsic pathways are regulated by cell

surface receptors. These pathways lead to caspase activation. Apoptosis pathways

cause the cell to shrink, later leading to plasma membrane blebbing, nuclear

condensation, and eventually the fragmentation of both cytoplasm and nucleus

into membrane-enclosed apoptotic bodies. The final process of apoptosis involves

macrophage mediated phagocytosis of the apoptotic bodies, avoiding the induction

of inflammatory responses (Whelan et al. 2010).

The common downstream pathway of apoptosis involves activation of proteins

called caspases. These proteins are a class of cysteine proteases that hydrolyse

peptide bonds following aspartic acid residues (Whelan et al. 2010). The inactive

forms of these molecules (the procaspases) are activated to active caspases by

several different ways. Procaspase 2, 8, 9 and 10 are the upstream procaspases that

need to dimerize to be activated and hence perform their function. Conversely,

procaspase 3, 6, and 7 are already dimerized. They are activated by cleavage of the

precursor proteins. Activation of the downstream caspase will bring about cellular

demise by cleaving hundreds of structural and regulatory proteins (Whelan et al.

2010).

31

Figure 1.4. The caspase cascade in apoptosis pathways. Apoptosis is mediated by an extrinsic pathway involving cell surface death receptors and by an intrinsic pathway that utilizes the mitochondria and endoplasmic reticulum. The extrinsic pathway (left side of the diagram) induces apoptosis via binding of extracellular molecules (death ligands) to death receptors on the cell surface, leading to the formation of a death inducing signalling complex (DISC). This activates caspase 3 via the activation of caspase 8. Activation of caspase 8 leads to the activation of caspase 3/7 as the effector for cellular apoptosis. The intrinsic pathway (right side of the diagram) induces apoptosis by activation of Bax, Bak and other pro-apoptotic molecules inside the cell. This promotes the release of cytochrome c and other apoptogens from mitochondria. Cytochrome c interacts with the apoptotic protease-activating factor 1 (Apaf-1) and dATP (deoxyadenosinetriphosphate), thereby facilitating the recruitment of caspase-9 and formation of the apoptosome. This ultimately leads to the activation of caspase-3/7 (Whelan et al. 2010).

The extrinsic signalling pathways that initiate apoptosis involve transmembrane

receptor-mediated interactions. These involve death receptors that are members of

the tumour necrosis factor (TNF) receptor gene superfamily (Susan 2007). This

protein family shares similar cysteine-rich extracellular domains. There are 80

amino acids within the cytoplasmic domain called the death domain. This domain

plays an important role in transmitting the signal from the extracellular to the

intracellular signalling pathways. FasL/FasR (Fas ligand/Fas receptor) is thought to

32

be the best characterised ligand along with TNF-α/TNFR1 (Tumor necrosis factor

receptor 1), Apo3L/DR3 (Apo3 ligand/ Death receptor3), Apo2L/ DR4 (Apo2 ligand/

Death receptor4) and Apo2L/DR5 (Apo2 ligand/ Death receptor5) (Susan 2007).

Binding of the Fas ligand to the Fas receptor results in binding of the adapter

protein FADD (Fas-associated protein with death domain). FADD then associates

with procaspase 8 via the dimerization of the death effector domain. At this point, a

death-inducing signalling complex (DISC) is formed, resulting in the auto-catalytic

activation of procaspase 8; once procaspase 8 is activated, the downstream effector

is stimulated (Susan 2007).

The intrinsic signalling pathway is considered a non-receptor mediated and

mitochondrial-initiated event. It is also responsible for transducing most apoptotic

stimuli such as hypoxia, oxidative stress, nutrient stress, proteotoxic stress, DNA

damage, and chemical and physical toxins (Whelan et al. 2010; Susan 2007). All of

these stimuli cause a loss of the transmembrane potential resulting from opening of

the mitochondrial permeability transition (MPT) pore. Therefore, some apoptogens

are released to the cytosol and trigger the initiation of the cascade. Cytochrome c is

one of the apoptogens that can induce the formation of apoptosome by binding to

the adaptor protein Apaf-1 (apoptotic protease activating factor-1) along with

dATP, which is already present in the cytosol. Procaspase-9 in the apoptosome is

then activated and subsequently undergoes autocleavage, subsequently activating

downstream procaspases (Figure 1.4)(Whelan et al. 2010; Susan 2007).

Apoptosis is reported as a key molecular feature in the pathophysiology of

myocardial infarction and heart failure (Abbate et al. 2006; Di Sciascio et al. 2002).

It has also been reported that apoptosis is the major form of myocardial damage as

a result of coronary artery occlusion. Necrosis follows apoptosis and occurs mostly

in cells with an activated apoptotic cascade, and thus performs a secondary role

(Kajstura et al. 1996). The presence of apoptotic myocytes in the infarct border

region has been reported (Di Sciascio et al. 2002). It has been suggested that even

when the blood supply might still be sufficient to protect the myocyte from

necrosis, the inflammatory mediators, recurrent ischemia and stretch stress could

eventually trigger apoptosis.

33

Figure 1.5. Cardiac remodelling following myocardial infarction. Apoptosis occurs at every stage of the remodelling. It is apparent that while necrosis is certainly very important as a means of cell loss in the earlier stages, it appears to not play a role in the following stages. Infarct expansion is typical of the early period and is characterized by an acute, necrosis- enlargement and bulging of the infarct area. It is thought to be dependent, at least in part, on the side-to-side slippage of myocytes and the apoptosis of surrounding myocytes. Progressive dilation, however, may occur up to several months after AMI. In the latter case, myocyte loss due to apoptosis is present and abnormal collagen turnover, fibrosis and inflammation also occur (Abbate et al. 2002).

1.4.2. Necrosis

Different from apoptosis, necrosis is traditionally known as unregulated cell death.

However, some emerging evidence shows that necrosis can also be regulated. It is

initiated by the activation of death receptors along with caspase inhibition. The

features of necrosis include a loss of plasma membrane integrity and a depletion of

cellular ATP. As a result of plasma membrane dysfunction, necrotic cells become

swollen, which is different from the shrunken appearance shown by apoptotic cells

(Biala & Kirshenbaum 2014).

Recent investigation into necrosis molecular pathways suggests that two distinct

complexes are involved. First is the binding of TNF to TNFR1 (TNF receptor 1) to

stimulate formation of complex I, which also includes the adaptor TRADD

[TNFRSF1A (TNF receptor superfamily 1A)-associated via death domain], the

serine/threonine kinase RIP1 (receptor interacting protein 1), TRAF2 (TNF receptor-

34

associated factor 2), and the cellular inhibitor of apoptosis proteins (cIAP) 1 and 2,

which possess E3-ubiquitin ligase activity. In conjunction with TRAF2, cIAP1/2

stimulates K63 polyubiquitination of RIP1 and TRAF2 (Whelan et al. 2010).

Following myocardial infarction, necrosis has been recognized as an immediate cell

death mechanism in the first 24-48 hours (Abbate et al. 2006). It has been reported

that stimulation of the inflammatory response post myocardial infarction is

triggered by necrotic and ischaemic myocytes. Neuromodulation in this early stage

of remodelling affects myocytes and non-myocytes and leads to early phases of

ventricular remodelling (Seropian et al. 2014).

1.4.3. Autophagy- dependent cell death

In contrast to apoptosis and necrosis, autophagy is known as a cell survival

mechanism. It is also known as a type of the regulated cell death that relies on the

autophagic machinery, which responds–under translational and post translational

regulation- to induce adaptation to stress, therefore mediating cytoprotective

rather that cytotoxic effects (Galluzzi et al. 2018). It is considered as an intracellular

recycling process that recycles some of the damaged organelles, proteins and lipids.

Therefore, this process is a crucial process for maintaining cellular homeostasis.

This type of cell death is the main focus for the study and it is described in more

detail, below.

1.4.4. Types of autophagy

As mentioned earlier, autophagy is a process involved in the maintenance of

homeostatic balance within cells by removing unwanted materials, such as

misfolded proteins or dysfunctional organelles that may otherwise harm the cells.

In the basal state, this process is beneficial. Under nutrient deprivation, it can be

altered to provide the building blocks for energy production through the

degradation of cellular constituents and by eliminating the defective or damaged

organelles (Wang et al. 2010).

There are three types of autophagy: macroautophagy, chaperone mediated

autophagy and microautophagy (Figure 1.6). Macroautophagy, commonly referred

as autophagy, is the main form of autophagy, involving autophagosome formation,

35

elongation and fusion to the lysosome. Chaperone mediated autophagy is a process

that employs molecular chaperones to move soluble cytoplasmic proteins to the

lysosome, rather than forming an autophagosome. Microautophagy involves the

uptake of cargo into the lysosome directly (Maejima et al. 2015).

Figure 1.6. The different types of autophagy. Macroautophagy, in the upper panel, is characterized by the sequestration of structures targeted for destruction into double-membrane vesicles called autophagosomes. Complete autophagosomes first fuse with endosomes before finally exposing their content to the hydrolytic interior of lysosomes. The resulting metabolites are transported into the cytoplasm and are used either for the synthesis of new macromolecules or as a source of energy. During chaperone-mediated autophagy (lower left panel), proteins carrying the pentapeptide KFERQ-like sequence are recognized by the Hsc70 chaperone, which then associates with the integral lysosome membrane protein LAMP-2A, triggering its oligomerization. This event leads to the translocation of the bound protein into the lysosome interior through a process that requires Hsc70. Microautophagy (lower right panel) entails the recruitment of targeted components in proximity with the lysosomal membrane, which subsequently invaginates (Boya et al. 2013).

36

The process of autophagy is initiated with the formation of a phagophore and ends

with the fusion of the autophagosome to the lysosome. Autophagy related genes

(ATGs) play an important role in mediating this process. To date, genetic screening

in yeast has found more than 30 ATGs that are essential in regulating the autophagy

process (Mizushima et al. 2011; Wang et al. 2010; Stolz et al. 2014).

1.4.5. Molecular mechanism of autophagy

Autophagy is well established as a major cellular catabolic process responsible for

cell homeostasis. Thereby, the extent of autophagy needs to be tightly regulated.

This regulation is necessary to avoid the destruction of proteins and organelles that

are important for cell survival. The main key regulator in mammals for this purpose

is mTOR (mammalian TOR). There are two different mTOR protein complexes,

mTORC1 and mTORC2; however, to date, mTORC1 has been reported to regulate

autophagy (Abada & Elazar 2014). Inhibition of mTORC1 by AMPK (5' AMP-

activated protein kinase) through phosphorylation of TSC2 (Tuberous Sclerosis

Complex 2) and raptor results in the decrease of Ulk1 Ser 757 phosphorilation,

which then subsequently interact and be phosphorylated by AMPK and initiates

autophagy (Kim et al. 2011). Several extracellular and intracellular signals to induce

or inhibit autophagy have been investigated, some of which are discussed below.

1.4.5.1. Extracellular signal

Amino acid starvation. Very low concentrations of certain amino acids, such as

leucine and glutamine in particular, have been reported to strongly induce

autophagy (Abada & Elazar 2014). This deprivation stimulates autophagy through

plasma membrane sensing, and eventually, decreases in mTORC activity. During

starvation, the low amino acid concentration is sensed by Rag GTPase on the

surface of lysosomes, at which active mTORC1 is mainly localized. The inactivation

of the Rag complex under low amino acid concentrations causes the detachment of

raptor (part of mTORC1 complex), Rheb, followed by the separation of mTOR from

the lysosome surface, resulting in autophagic stimulation (Abada & Elazar 2014).

Another mTORC1 signalling pathway to induce autophagy is through the ULK1

complex. The ULK1 complex consists of several proteins including Atg13, ULK and

FIP200, and is directly regulated by mTORC1 by direct binding and phosphorylation

37

of Atg13 and Ulk1. When mTORC1 is inactive, the ULK1 complex is activated and

triggers the complex to initiate autophagosome formation (Figure 1.7) (Moyzis et al.

2015; Abada & Elazar 2014).

Insulin and glucose starvation. Under high glucose and insulin concentrations,

autophagy is inhibited through binding of insulin to its receptor, activating the

phosphoinositide 3-kinase complex 1 (PI3KC1), leading to Akt activation. This leads

to activation of mTORC1, thus inhibiting autophagy. In low glucose concentrations,

the regulation has been reported to occur through Hexokinase II, an enzyme that is

suggested to bind directly to mTORC1 and leads to mTORC1 inhibition. This

inhibition is prevented when the concentration of glucose is high and glucose-6-

phosphate, an enzyme responsible for glycolysis, is active (Abada & Elazar 2014).

AMPK has also been activated under glucose deprivation. The active AMPK inhibits

mTORC1 by phosphorilatingTSC2 and raptor, and phosphorylates Ulk1 directly on

several phosphorylation sites to induces autophagy (Egan et al. 2011).

Epidermal growth factor and Toll-like receptors. EGF phosphorylation and

subsequent dimerization with STAT3 has been reported to induce autophagy. In

contrast, EGFR phosphorylation of Beclin1 inhibits autophagy (Abada & Elazar

2014). Another signalling pathway implicated in autophagy is Toll-like receptor-

mediated signalling. It is an important part of the innate immune system, and is also

suggested as mediator of autophagy. Polyubiquitination of beclin1 by E3 ligase

TRAF6 leads to beclin1 detachment from Bcl-2. This eventually initiates autophagy

by binding to other autophagy regulatory proteins Atg14, , Vps15 and Vps34 to

form a complex which initiates autophagosomal biogenesis (Wang et al. 2010;

Abada & Elazar 2014).

38

Figure 1.7. Molecular mechanism of autophagy. Signals that activate the autophagic process (initiation) typically originate from various conditions of stress, such as starvation, hypoxia, oxidative stress, protein aggregation, endoplasmic reticulum (ER) stress and others. The common target of these signalling pathways is the Unc-51-like kinase 1 (ULK1) complex (consisting of ULK1, autophagy-related protein 13 (ATG13), FIP200 and ATG101, which then triggers nucleation of the phagophore by phosphorylation of components of the class III PI3K (PI3KC3) complex I (consisting of class III PI3K, vacuolar protein sorting 34 (VPS34), Beclin 1, ATG14, activating molecule in Beclin 1-regulated autophagy protein 1 (AMBRA1) and general vesicular transport factor (p115)), which in turn activates local phosphatidylinositol-3-phosphate (PI3P) production at a characteristic ER structure called the omegasome. PI3P then recruits the PI3P effector proteins WD repeat domain phosphoinositide- interacting proteins (WIPI2) and zinc-finger FYVE domain-containing protein 1 (DFCP1) to the omegasome via interaction with their PI3P-binding domains. WIPI2 was recently shown to bind ATG16L1 directly , thus recruiting the ATG12~ATG5–ATG16L1 complex, which enhances the ATG3-mediated conjugation of ATG8 family proteins (ATG8s), including microtubule-associated protein light chain 3 (LC3) proteins and γ- aminobutyric acid receptor-associated proteins (GABARAPs) to membrane-resident phosphatidylethanolamine (PE), thus forming the membrane-bound, lipidated forms. Sealing of the autophagosomal membrane gives rise to a double-layered vesicle called the autophagosome, which matures (including stripping of the ATG proteins) and finally fuses with the lysosome. Acidic hydrolases in the lysosome degrade the autophagic cargo, and salvaged nutrients are released back to the cytoplasm to be used again by the cell (Dikic & Elazar 2018).

39

1.4.5.2. Intracellular signal

Energy levels. The energy level of the cell is normally sensed by the ATP/AMP ratio

and is mainly regulated by AMPK (adenosine mono phosphate kinase). Under low

levels of energy, the concentration of AMPK is high, and this leads to mTORC1

inhibition.

Oxidative stress. Reactive oxygen species, as a by-product of cellular processes, are

potentially hazardous molecules that need to be eliminated. The main molecules

that participate in autophagy signalling are H2O2 and O2-. These molecules are

elevated in mitochondria upon starvation and directly regulate Atg4, an enzyme

that regulates LC3 lipidation (Abada & Elazar 2014). ROS production can also be a

source for mitochondrial signalling to degrade damaged mitochondria.

Ca2+. As a well-established cell signalling molecule in numerous cellular processes,

intracellular Ca2+concentration is tightly regulated. The ER and mitochondria served

primarily for Ca2+ storage. The release of this molecule from ER due to ER stress is

suggested to regulate autophagy in many stages, but the process is still poorly

understood.

1.4.5.3. Autophagosome biogenesis

Induction and phagophore nucleation. The origin of the membrane for the first step

of autophagosome biogenesis (nucleation) has been an interesting question for

many years. It has been hypothesized that this membrane originates from the

endoplasmic reticulum (ER) (Abada & Elazar 2014; Dikic & Elazar 2018). Other

sources of phagophore formation have also been reported, such as plasma

membrane, mitochondria, Golgi, ER-mitochondrial contact site, and recycling

endosomes (Abada & Elazar 2014). During starvation, mTORC1 binding sites on

ULK1 are dephosphorylated and ULK1 is detached from mTORC1. Subsequently,

ULK1 undergoes autophosphorylation, followed by the phosphorylation of ATG13

and FIP200. This process triggers nucleation of the phagophore by phosphorylation

of class III PI3K (PI3KC3) complex I (consisting of class III PI3K , vacuolar protein

sorting 34 (VPS34), Beclin 1, ATG14, activating molecule in Beclin 1-regulated

autophagy protein 1 (AMBRA1) and general vesicular transport factor (p115), which

40

in turn activates local phosphatidylinositol-3-phosphate (PI3P) production at a

characteristic ER structure called the omegasome. PI3P then recruits the PI3P

effector proteins WD repeat domain phosphoinositide- interacting proteins (WIPI2)

and zinc-finger FYVE domain-containing protein 1 (DFCP1) to the omegasome via

interaction with their PI3P-binding domains (Abada & Elazar 2014; Kawabata &

Yoshimori 2016; Dikic & Elazar 2018).

Phagophore expansion. The step for the elongation of the phagophore or

autophagosome formation starts with the activation of ATG 12 by ATG7, a ubiquitin

E1-like enzyme, then transferred to ATG10, a Ubiquitin e2-like enzyme. ATG12 then

covalently conjugates to ATG5 and ATG16. Nascent pro Ubiquitin-like enzyme

ATG8/LC3 is synthesised in an inactive form, and needs to be processed at the C-

terminus by the cysteine protease, ATG4, to expose the glycine residue that is

essential for its conjugation with phosphatidylethanolamine (PE). ATG8/LC3 are

then activated by ATG7 and followed by conjugation with PE by ATG3 and

converting ATG8/LC3 from a freely diffusing form (LC3-I), to a phagophore-

membrane attached, lipidated form, LC3-II (Wang et al. 2010; Dikic & Elazar 2018).

The conjugation of ATG8s to PE promotes phagophore expansion, and possibly the

sealing of the phagophore to become autophagosome (Dikic & Elazar 2018).

ATG8 proteins is widely used to investigate autophagic activity and in human,

comprise three subfamilies: LC3 (MAP1LC3A, MAP1LC3B, MAP1LC3B2, MAP1LC3C),

GABARAP or γ-aminobutyric acid receptor-associated protein (GABARAP and

GABARAPL1), GATE-16. All ATG8 proteins have a unique structural characteristic

which contain two amino-terminal α-helices in addition to their carboxy-terminal

ubiquitin core. The ubiquitin core of ATG8 proteins are conserved and considered

to have a role in protein-protein interaction and responsible for ATG8 protein

interaction characteristic (Egan et al. 2011).

Autophagosome maturation and fusion with lysosome. Following the expansion and

sealing of the phagophore, the autophagosome becomes a mature

autophagosome. A gradual clearance of the ATG proteins occurs and the lysosome

fusion machinery is recruited. It has been demonstrated in several studies that

41

several proteins are responsible for this process. Syntaxin17 (STX17), synaptosomal-

associated protein (SNAP29) along with additional SNARE proteins are required in

the autophagosomal part, while vesicle-associated membrane protein 8 (VAMP8) is

needed on the lysosome to mediate autophagosomal/ lysosomal fusion (Itakura et

al. 2012; Diao et al. 2015; Dikic & Elazar 2018). Another study has also

demonstrated that acetylated microtubules are required for fusion of the

autophagosome with the lysosome to form the autolysosome (Xie et al. 2010).

Degradation of cargo. Acidic hydrolases in the lysosome degrades the autophagic

cargo, and salvaged nutrients are released back to the cytoplasm to be used again

by the cell (Dikic & Elazar, 2018).

42

Figure 1.8. Schematic model of the major pathways in the regulation of the autophagic machinery . The inset figure represents of the ATGs proteins regulation in the initial phase of autophagosome formation. ATG12 is activated by a ubiquitin E1-like enzyme, ATG7, and transferred to a ubiquitin E2-like enzyme, ATG10. ATG12 is then covalently conjugated to ATG5. The ATG12-ATG5 complex interacts with ATG16. Another ATG protein, LC3, is first cleaved by ATG4 to expose a C-terminal glycine. This LC3-I is then activated by ATG7, the E1-like enzyme. After being transferred by the E2-like enzyme ATG3 and the ATG12,5,16 complex, LC3-I is attached to a PE molecule and localized to the phagophore membrane (LC3-II). Adapted from Maejima et al. (2015).

43

Table 1.1 summarizes the key autophagic factors and their regulation.

Protein Mechanism of regulation Function

Initiation and phagophore nucleation

ULK1 and ATG1

Stress and nutrient (via mTORC1, AMPK and LKB1); TFEB and several miRNAs machinery

Serine/threonine kinase; initiates autophagy by phosphorylating components of the autophagy machinery

FIP2000 ULK1 and miRNAs Component of the ULK complex (possibly scaffolding function)

ATG13 ULK1, mTORC1 and AMPK Adaptor mediating the interaction between ULK1 and FIP200; enhances ULK1 kinase activity

ATG101 ULK1 Component of the ULK complex; recruitment of downstream ATG proteins

VSP34 AMPK, ULK1 and p300 (acetylation)

Catalytic component of PI3KC3–C1; generates PI3P in the phagophore and stabilizes the ULK complex

Beclin1 Activation: AMPK, ULK1, UVRAG Inhibition: Bcl-2, Akt, EFGR

Promotes formation of PI3KC3–C1 and regulates the lipid kinase VPS34

ATG14 mTORc1 PI3KC3–C1 targeting to the PAS and expanding phagophore

ATG9 ULK1 Complex Delivery of membrane material to the phagophore

WIPI2 TFEB and ZKSCAN3

PI3P-binding protein that recruits ATG12~ATG5– ATG16L to the phagophore; retrieval of ATG9 from early autophagosomal membranes

Phagophore expansion

ATG4 ULK1 and ROS Cysteine protease that processes pro-ATG8s; also, deconjugation of lipidated LC3 and ATG8s

ATG7 miRNAs E1-like enzyme; activation of ATG8; conjugation of ATG12 to ATG5

ATG3 miRNAs E2-like enzyme; conjugation of activated ATG8s to membranal PE

ATG10 miRNAs E2-like enzyme that conjugates ATG12 to ATG5

ATG12-ATG5-ATG16L

CSNK2 E3-like complex that couples ATG8s to PE

PE-Conjugated ATG8s

ULK1, PKA, ATG4, and mTOR

Scaffold for assembly of the ULK1 complex; supports membrane tethering and hemifusion events for phagophore expansion

ATG9 ULK1 Delivery of membrane material to the phagophore

44

Cargo sequestration

Ubiquitin PINK (phosphorylation) Cargo labelling

Cardiolipin and ceramide

Phosphorylation Cargo labelling

OPTN TBK1 Autophagy receptor

NBR1 TBK1 Autophagy receptor

NDP52 TBK1 Autophagy receptor

PE-conjugated LC3

ULK1, PKA, ATG4 and mTOR Interaction with autophagy receptors; also phagophore expansion and sealing

Membrane sealing

Lc3s and GABARAPs

Unclear Unclear

Autophagosome maturation

ATG4 Unknown Removal of ATG8s from the surface of the autophagosome

PE-conjugated LC3s and GABARAPs

Unknown Linking the autophagosome to microtubule- based kinesin motor

Fusion with lysosome

PE-conjugated LC3s and GABARAPs

STK3 and STK4 Mediates autophagosome–lysosome fusion upon phosphorylation through PLEKHM1 and HOPS

ATG4 Unknown Promotes SNARE-driven membrane fusion

Rab GTPase RAB7

Unknown Unclear

Table 1.1. Key autophagic factors and their regulatory roles. ATG, autophagy- related protein; AMPK , 5′ AMP- activated protein kinase; CSNK2, casein kinase 2; DAPK , death- associated protein kinase; EGFR , epidermal growth factor receptor ; FIP200, RB1-inducible coiled- coil protein 1; GABARAP, γ- aminobutyric acid receptor- associated protein; HOPS, homotypic fusion and protein sorting; LC3, light chain 3; LKB1, liver kinase B1; MAPKAPK, MAPK- activated protein kinase; miRNA , microRNA ; NBR1, neighbour of BRCA1 gene; NDP52, nuclear dot protein 52; OPTN, optineurin; p62, also known as SQSTM1; p300, histone acetyltransferase 300; PAS, phagophore assembly site; PE, phosphatidylethanolamine; PI3P, phosphatidylinositol-3-phosphate; PINK , PTEN- induced putative kinase 1; PIPKIγi5, type Iγ PIP kinase isoform 5; PI3KC3, class III PI3K; PKA , protein kinase A ; PLEKHM1, pleckstrin homology domain- containing protein family member 1; RAB, Ras- related protein; ROS, reactive oxygen species; STK, serine/threonine protein kinase; TBK1, TANK- binding kinase 1; TFEB, transcription factor EB; ULK1, Unc-51-like kinase 1; UVRAG, ultraviolent irradiation resistance- associated gene; VPS34, class III PI3K vacuolar protein sorting 34; WIPI2, WD repeat domain phosphoinositide- interacting protein 2; ZKSCAN3, zinc- finger protein with KRAB and SCAN domains 3 (Dikic & Elazar 2018).

45

1.4.6. Autophagic flux

The term autophagic flux defined as a measure of the rate of autophagic

degradation activity. The processes defined by autophagic flux include

autophagosome synthesis, sequestration of material, delivery of autophagic cargo

to the lysosome, and degradation of autophagic cargo inside the lysosome (Figure

1.9)(Jimenez et al. 2014; Loos et al. 2014). It is important to note that an increase in

the number of autophagosomes does not necessarily indicate an increased rate of

autophagy (Maejima et al. 2015). In fact, increased numbers of autophagosomes

may indicate either the enhancement of autophagosome formation or inhibition of

the autophagic pathways downstream of autophagosome formation.

Figure 1.9. Schematic image on autophagic flux. Autophagic flux is defined as the rate of autophagosomal degradation activity. Since autophagy is a dynamic process, it is important to understand the overall autophagic process from the formation of the autophagosome until its degradation (Hofmeyr 2014).

Assessing autophagic flux is a more accurate indicator of autophagic activity in cells

and tissue than measurement of the numbers of autophagosome forming

(Hariharan et al. 2011; Iwai-Kanai et al. 2008; Perry et al. 2009). The most accepted

method to evaluate autophagic flux is by counting autophagosomes, for example by

measuring the formation of GFP labelled -LC3 puncta (a commonly used reporter

for autophagosome formation) in the presence or absence of chloroquine, an

inhibitor of autophagosome- lysosome fusion. The increasing number of

46

autophagosomes in the presence of chloroquine indicates that it can augment

autophagosome formation or flux (Maejima et al. 2015). However, given that the

atuophagosome is an intermediate structure in a dynamic pathway, the number of

autophagosomes observed at any specific time point is basically a result of the rate

of their generation and the rate of their conversion into autolysosomes. Or in other

words, autophagosome accumulation may represent either autophagic induction or

suppression of their conversion to autolysosomes (Mizushima et al. 2010) (Figure

1.10).

Figure 1.10. Dynamic regulation of autophagy. Adapted from (Mizushima et al. 2010).

Activation of autophagy can be measured using different assays including analysing

expression levels of the autophagy-related marker LC3. LC3 is initially synthesized

as proLC3, which is converted to LC3-I and finally PE-conjugated LC3II. LC3II is the

protein marker that is reliably associated with the completed autophagosome.

Changing amounts of LC3II in the presence or absence of autophagic inhibitors can

47

be monitored by western blot, and thus can be used to measure autophagic flux

(Figure 1.11) (Caro et al. 2018).

Figure 1.11. Quantification of autophagic flux. An example of western blot measuring LC3II levels from wild type and KO tissue, in the presence or absence of lysosome inhibitor, and the equation for calculation of autophagic flux is provided (Caro et al. 2018).

1.5. The role of autophagy in cardiac homeostasis

1.5.1. Autophagy in cardiomyocyte

Cardiomyocytes are a terminally differentiated cell type. Therefore, any cellular

process to maintain cellular homeostasis is very important. Autophagy is one of the

major mechanisms to maintain cellular homeostasis in cardiomyocytes through the

degradation of long-lived cytosolic proteins. Autophagy is also the only known

process for degradation and recycling of damaged organelles (Matsui et al. 2007).

Thus, it is clear that autophagy is essential in the heart and in cardiomyocytes, in

both basal conditions as well as following stress stimuli (Matsui et al. 2009). It has

been demonstrated that the heart significantly upregulates autophagosome

formation following starvation (Mizushima 2004). Another study showed that the

deletion of ATG5 in the adult heart results in the accumulation of damaged

mitochondria and rapid cardiac dysfunction as indicated by cardiac hypertrophy,

chamber dilatation, and contractile dysfunction (Nishida et al. 2007). This suggests

that autophagy is a key mechanism to maintain overall cardiac size, structure and

function in the adult heart (Nishida et al. 2007). In a different study, mice with a

48

deficiency in lysosome-associated membrane protein-2 (lamp-2), a protein

important for autophagosomal fusion to the lysosome, had a significant

accumulation of autophagosomes, leading to a significant decrease in cardiac

function, similar to that seen in human Danon disease, which is caused by a

mutation in the lamp-2 gene (Jimenez et al. 2014).

1.5.2. Autophagy in cardiac pathological conditions

The role of autophagy in ischaemic heart disease is an interesting subject of study.

It remains unclear whether autophagy is beneficial or detrimental in this condition

(Nishida et al. 2007; Przyklenk et al. 2012). The heart is an organ that requires a

constant supply of oxygen. In organs that critically depend on continuous oxygen

supply, it is well understood that adaptive responses are required when they face

oxygen deprivation (Figure 1.12) (Nishida et al. 2009). In cardiomyocytes, it was

found that hypoxia activates many kinds of cellular survival mechanisms as well as

autophagy (Nishida et al. 2009; Chen-scarabelli et al. 2014).

49

Figure 1.12. How the heart reacts under several pathological conditions. A normal heart responds to several pathological stimulations, such as myocardial infarction or chronic pressure overload. This stimulation can trigger the heart to respond by induction of remodelling processes to cope with the conditions. Heart failure is developed in the persistent stress stimulation. This encompasses cellular changes, including formation of oxygen free radicals that can elevate oxidative stress and cause an imbalance of cellular homeostasis. Therefore, it is important for cells to have a stress sensor system to cope with this condition. Autophagy is one of the mechanisms that are believed to respond to this condition.

In myocardial ischemia, it is suggested that the induction of autophagy is triggered

by a depletion of cellular ATP. A significant depletion in ATP/ADP followed by an

increased level of AMP during myocardial ischemia stimulates AMPK (AMP

activated protein kinase). This is the main energy sensor within cells that responds

to energy deprivation (Qi & Young 2015; Takagi et al. 2007). Activation of AMPK

causes phosphorylation of TSC2 (tuberous sclerosing complex 2), which leads to

mTOR (mammalian target of rapamycin) inhibition, leading to autophagy activation

(Matsui et al, 2008). Under anoxic conditions, the regulation is slightly different,

whereby the activation of AMPK causes an inhibition of protein synthesis through

the phosphorylation of eukaryotic elongation factor-2 (eEF2), rather than by the

inhibition of mTOR (Takagi et al. 2007). Since eEF2 kinase, which phosphorylates

50

eEF2, regulates autophagy, ischemia-induced autophagy may be mediated by the

AMPK-eEF2 kinase pathway rather than through the AMPK-induced inhibition of

mTOR (Takagi et al. 2007; Matsui et al. 2009). AMPK may also stabilize p27 through

phosphorylation, which in turn mediates autophagy (Matsui et al. 2009). In one

study using mice with a transgenic overexpression of dominant-negative AMPK

(DN-AMPK), it was found that after prolonged ischemia, the infarct size was larger

in the transgenic mice compared to wild type. Interestingly, autophagosome

formation was decreased in the transgenic mice (Takagi et al. 2007). These data

suggest that autophagy plays a protective role during myocardial ischemia (Whelan

et al. 2010) .

However, the mechanism of autophagy during cardiac reperfusion phase seems to

be different. As AMPK is rapidly inactivated upon reperfusion, it is unlikely that the

increasing number of autophagosomes is mediated by this kinase (Takagi et al.

2007). There is evidence showing a dramatic up-regulation of beclin 1 following the

reperfusion phase in the mouse model of ischemia/reperfusion (Nishida et al. 2009;

Jimenez et al. 2014; Wang et al. 2010). Importantly, a study by Matsui et al. (2007)

showed that in beclin 1 heterozygous mutant mice, autophagy and cardiac injury

were significantly attenuated compared to the wild type controls. Upregulation of

beclin 1 also seen in other tissues such as the brain and kidney, contributes to the

supra-physiological induction of autophagy (Nishida et al. 2009). Another study

showed that in an in vitro system using neonatal cardiomyocytes and adult

cardiomyocytes, the ischaemia/reperfusion condition activated cell death and

autophagy. Consequently, in the presence of an PI3K inhibitor (3-metyladenine),

cell viability was improved (Wang et al. 2010). Taken together, these data show

that upregulation of beclin 1 may be responsible for autophagy regulation during

myocardial reperfusion (Matsui et al. 2009; Wang et al. 2010).

Another important regulator of autophagy during cardiac ischemia/reperfusion

injury is BNIP3. BNIP3 is significantly induced by prolonged hypoxia, causing

mitochondrial dysfunction and cell death in neonatal rat cardiomyocytes. Similarly,

in HL-1 cells, BNIP3 is both necessary and sufficient to induce I/R mediated

autophagy (Matsui et al. 2009). BNIP3 is an integral part of the mitochondrial

51

membrane protein; therefore, BNIP3 may induce mitochondrial damage. It is also

possible that BNIP3 is able to titrate Bcl-2 and/or Bcl-XL away from Beclin 1, which

can lead to the induction of autophagy (Matsui et al. 2009). A study by Matsui et al.

provides evidence that BNIP3 induces mitochondrial fragmentation and autophagy.

Consistently, suppression of BNIP3 using a dominant-negative mutant protein

protects against Ischemia /Reperfusion (I/R) injury (Wang et al. 2010). These

findings suggest that BNIP3 contributes to cell death during I/R injury. Taken

together, during the reperfusion phase, it is suggested that the induction of Beclin 1

and BNIP3 activity may enhance autophagy to the supra-physiologic level and may

have a detrimental effect on the heart (Matsui et al. 2009; Wang et al. 2010; Takagi

et al. 2007; Nishida et al. 2009).

In a recent study on post myocardial infarction, it was suggested that autophagy

has a protective role during the remodelling phase (Kanamori et al. 2011). This

study showed that autophagic activity was elevated, commensurate with significant

autophagosome and lysosome formation following ischaemia-reperfusion injury in

the mouse heart. This was followed by significantly exacerbated cardiac dysfunction

and remodelling after treatment with bafilomycin A1, an autophagy inhibitor. In

contrast, treatment with rapamycin, an autophagy inducer, augmented autophagic

activity and significantly mitigated cardiac dysfunction and remodelling.

52

Table 1.2 below shows several studies implicating autophagy or mitophagy in

cardiac pathology in vivo.

Model Intervention Specificity Observations

MI (mice) Becn1+/− Whole body, nonregulated

Reduced cardiac damage at reperfusion when compared with WT mice

MI (mice) Bnip3−/− Whole body, nonregulated

Reduced cell death in the peri-infarct region, coupled to reduced ventricular remodeling and improved cardiac performance

MI (mice)

Fundc1−/− Platelets, nonregulated

Cardioprotection associated with reduced platelet activation secondary to the accumulation of dysfunctional mitochondria

MI (mice)

Mfn1−/− Mfn2−/−

Cardiomyocytes, in adults

Reduction in infarct size associated with decreased mitochondrial Ca2+ overload and ROS generation

MI (mice)

Park2−/− Whole body, nonregulated

Aggravated cardiac injury and reduced survival linked to mitophagy deficits and accumulation of damaged mitochondria

MI (mice)

Pgam5−/− Whole body, nonregulated

Increased infarct size when compared with WT mice, correlating with inhibited mitophagy and necrotic RCD

MI (mice)

Stk4−/− Whole body, nonregulated

Cardioprotection coupled to increased autophagic responses in the heart

MI (mice)

RHEBtg Cardiomyocytes, nonregulated

Increased infarct size when compared with WT mice, which could be reversed by systemic rapamycin administration

MI (mice)

miR-188-3p– coding adenovirus

Systemic Reduction in infarct size coupled to ATG7 downregulation

MI (mice)

CR Systemic Reduction in infarct size that could be annihilated by BafA1 administration

MI (mice)

Rapamycin Systemic Attenuated postinfarction cardiac remodeling and dysfunction

MI (mice)

Resveratrol Systemic Reduction in infarct size coupled to improved postischemic recovery of left ventricular contractile function

MI (mice)

Simvastatin Systemic Reduction in infarct size, lost in Park2−/− mice

MI (mice)

Mdivi-1 Systemic Limited myocardial infarct size coupled to reduced mitochondrial fission

MI (mice)

3-MA Systemic Exacerbated postinfarction cardiac remodeling and dysfunction

53

MI (mice)

BafA1 Systemic Increase in infarct size that could be annihilated by CR

MI (rabbits)

SAHA Systemic Cardioprotection achieved as pre- and post-ischemia, associated with autophagy activation in the myocardium

MI (pigs) Chloramphenicol

Systemic Cardioprotective effects achieved as pre- and postischemic intervention

Table 1.2. Pharmacological and genetic studies implicating autophagy or mitophagy in cardiovascular pathology in vivo (Bravo-San Pedro et al. 2017).

1.6. MAP1S

1.6.1. Structure and biological function of MAP1 family of proteins

Microtubules are highly dynamic polymers containing αβ-tubulin that are important

for the eukaryotic cell cytoskeleton components, organelle trafficking and

chromosome segregation (Brouhard & Rice 2018; Howard & Hyman 2003). Dynamic

instability occurs in microtubules via loss (shrinkage) or addition (growth) in the

microtubules’ plus end (Howard & Hyman 2003). It has been reported that

Microtubule-associated proteins (MAPs) selectively target specific tubulin

conformations to regulate microtubule dynamics (Brouhard & Rice 2018).

Microtubules-associated proteins (MAPs) are attached to the microtubules. There

are three members of MAP1 family proteins: MAP1A, MAP1B, and MAP1S, and they

are encoded by separate genes. The MAP1 genes consist of multiple exons and

have some alternative splicing sites within the genes (Figure 1.13) (Halpain &

Dehmelt 2006).

It is understood that MAP1A and MAP1B proteins bind along the length of

microtubules and are thought to stabilize microtubules by altering this dynamic

behaviour. There are various classes of microtubule-associated proteins expressed

in eukaryotic cells. Several members of microtubulesassociated proteins bind to the

microtubules plus or minus ends, while others bind to the microtubule lattice

(Halpain & Dehmelt 2006). The MAP1 family of proteins is part of the latter group

and is best known for its microtubule-stabilizing activity (Table 1.3).

54

Interacting protein Proposed function of interaction

MAP1A Microtubules Stabilization of microtubules

F-actin Integration of microtubule and F-actin cytoskeletons

EPAC Enhancement of Rap1 GTPase activity and cell

adhesion

DISC1 Linking of DISC1 to microtubules; pathogenesis of

schizophrenia

PSD-93 Linking of PSD-93 to microtubules

CK1delta Interaction with and phosphorylation of the MAP1A

light chain LC2 in vitro

BKCa potassium channel Association of the channel with the cytoskeleton

MAP1B Microtubules Stabilization of microtubules


Mapmodulin Modulation of neurite extension

Myelin-associated

glycoprotein Enhanced MAP1B expression and phosphorylation

GABA(C) receptor Linking of GABA(C) receptors to the cytoskeleton

FMR1 Interaction with MAP1B mRNA and repression of its

translation

ee3 Alteration of the stability or folding of ee3

LIS1 Interference with the LIS1-dynein interaction

Gigaxonin

Enhanced stabilization of microtubules by MAP1B;

control of MAP1B light chain degradation; potential

role in giant axonal neuropathy

GRIP1 Localization of AMPA receptors to synaptic sites

LC3 Microtubules Regulation of the microtubule binding of MAP1A and

MAP1B

Caldendrin Transduction of calcium signals

MAP1S Microtubules Stabilization of microtubules


RASSF1A Regulation of mitotic progression

Table 1.3. Interacting partners of MAP1-family proteins (Halpain & Dehmelt 2006)

55

Following protein translation, MAP1 proteins undergo post-translational

modification, notably proteolytic cleavage, which leads to the generation of the

heavy and the light chain variants of each specific protein. The heavy chain of

MAP1A is 350 kDa in size, while the light chain (LC2) is 28 kDa. The molecular

weight of MAP1B heavy chain is 300 kDa, whereas the light chain (LC1) is 32 kDa,

while in MAP1S, the heavy chain molecular weight is 100kDa and its light chain

(MAP1S-LC) is 26 kDa (Halpain & Dehmelt 2006). The structural details of these

proteins are largely unknown. However, there are reports suggesting that MAP1A is

a flexible and elongated protein, while MAP1B appears to be a rod-shaped,

elongated molecule with a terminal round globular domain.

Figure 1.13. Domain organization and posttranslational processing of mammalian MAP1-family proteins. MAP1A, MAP1B and MAP1S contain microtubule and F-actin-binding sequences in their carboxyl termini, and additional microtubule-binding sites have been mapped to the amino termini of MAP1A and MAP1B. A separate gene encodes an additional light chain, LC3, which is also found in mature MAP1A or MAP1B complexes. Modified from (Orbán-Németh et al. 2005; Halpain & Dehmelt 2006).

56

MAP1A and MAP1B are predominantly expressed in the brain and are involved in

microtubule stabilizing in the nervous system. This process contributes to axon

guidance and synaptic function. However, the other member of the family, MAP1S,

is slightly different compared to MAP1A and MAP1B.

1.6.2. Structure and biological function of MAP1S protein

The sequencing of human and mouse genomes has shown that the MAP1S gene

contains seven exons, like MAP1A and MAP1B. However, there is a variation in the

size of MAP1S and other MAP1 family members because the length of the exon 5

sequence is different, while the remaining exons have almost the same length. In

the human genome, MAP1S is located in chromosome 19 (19p13.12) and in the

mouse genome it is located in chromosome 8 (Orbán-Németh et al. 2005).

MAP1S is also called as VCY2IP1 or C19ORF5. It has a smaller size compared to the

other MAP1 proteins. MAP1S protein expression is readily detected not only in

neurons but also in other tissues, such as spleen, testis, heart, lung, kidney, salivary

gland and liver (Orbán-Németh et al. 2005). It plays a key role in maintaining

microtubule stability during cell division (Tegha-Dunghu et al. 2014). MAP1S

contains all the three hallmark domains of the microtubule-associated family but

only very few additional sequences. The homology sequence in this MAP1 family

are MH1 (a region of 500 AA in the amino terminus of heavy chain), MH2 (a region

of 120 AA in the carboxyl terminus of heavy chain), and MH3 (a region of 120 AA in

the half carboxyl terminus of the light chain). MAP1S is synthesized as a precursor

protein that is subsequently cleaved to produce the heavy light chain. The light

chain binds, bundles and stabilizes microtubules. It also binds to actin. The heavy

chain regulates the activity of the light chain. The study by Orban-Nemeth et al.

(2005) showed that the ectopic expression of MAP1S in PtK2 cells results in

microtubule transformation into the cellular microtubule network, induction of

long, wavy microtubule bundle formation, and stabilizing of the microtubules

against the effect of colchicine. This study also showed that the heavy chain of

MAP1S displays a regulatory function in the heavy chain- light chain complex.

Phosphorylation, binding of additional regulatory proteins, or any posttranslational

modification can trigger conformational changes in the heavy chain, which can alter

57

light chain activity. RASSF1A is a potential candidate involved in the regulation of

MAP1S. It has been reported that RASSF1A interacts with MAP1S. RASS1FA is

known as a tumour suppressor that has a pivotal role in regulating important

processes within the cell such as apoptosis, cell growth, viability and the cell cycle

(Mohamed et al. 2014). RASSF1A overexpression can induce the bundling and

stabilization of microtubules, and it has been suggested that by binding to

endogenous MAP1S, it can trigger conformational changes that are important in

light chain activation (Dallol et al. 2004; Orbán-Németh et al. 2005).

1.6.3. The role of MAP1S in regulating autophagy and other pathologies

The role of MAP1S in regulating autophagy has been investigated for almost a

decade. Most of the studies have demonstrated that MAP1S has a positive role in

regulating autophagy. A deficiency or deletion of the MAP1S gene is attributed to

many detrimental effects observed (Rui Xie, Wang, et al. 2011; Zou et al. 2014; Yue

et al. 2017; Xie et al. 2010; Zou et al. 2013; Jiang et al. 2015; Rui et al. 2011; Liu et

al. 2019). One study showed that ablation of the MAP1S gene in mice leads to

areduction in Bcl-2/xl and cyclin dependent kinase inhibitor 1B (P27) expression, an

increased number of defective mitochondria, and severe defects, such as reduced

survival in starved MAP1S-deficient neonates under nutritive deprivation (Rui et al.

2011). The study also suggested that MAP1S ablation correlates with a defect in

autophagosomal formation and clearance (Rui et al. 2011). Another study using the

chemical carcinogen DEN (Dietilnitrosamin), which causes oxidative stress, found

that the expression level of MAP1S was dramatically elevated in mouse livers

following DEN treatment (Rui et al. 2011). The acute elevation of MAP1S levels in

mouse liver leads to the activation of autophagy. Subsequently, in the MAP1S-

knockout mice, p62 and g-H2AX, which are markers for genome instability,

accumulate in the liver tumour foci. It has been shown that the p62 protein can

bind to the ubiqutinated toxic protein and defective organelles, including

mitochondria. Its level represents the amount of aggregated proteins and

dysfunctional organelles which are accumulated in the cells (Komatsu et al. 2007).

The data suggest that this phenotype is due to ineffective autophagy machinery in

the absence of MAP1S (Rui et al. 2011).

58

Investigations into the mechanisms by which MAP1S regulates autophagy are being

studied by many groups. One of the leading groups investigating the role of MAP1S

in autophagy, Liu et al. (2012), suggested that regulation of autophagy is achieved

through its interaction with LC3I and LC3II, binding to mitochondrion-associated

leucine-rich PPR motif containing protein (LRPPRC), which also interacts with

mitophagy-related protein PARKIN and PINK1 and docks a dysfunctional

mitochondrion into an autophagosome through the interaction with internal LC3II

(Rui et al. 2011; Rui et al. 2011; Liu et al. 2012). The other connection of MAP1S is

with tumour suppressor RASSF1A. The tumour suppressor Ras-association domain

family protein 1A (RASSF1A) is an inhibitor of cardiac hypertrophy. RASSF1A inhibits

the pro-hypertrophic Raf1-ERK1/2 pathway (Oceandy et al. 2009; Mohamed et al.

2014). It was also reported that MAP1S is a main interacting molecule with

RASSF1A, which bridges autophagosomes to microtubules and healthy

mitochondria to microtubules (Liu et al. 2012).

These interactions suggest that MAP1S may play essential roles in integrating

autophagic machinery and mitochondria with the microtubules during the

formation of the autophagosome. It also has an important role in suppressing

genome instability and tumorigenesis (Zou et al. 2014; Rui et al. 2011). MAP1S

appears to be a key molecule in bridging microtubules and mitochondria with the

phagophore (Figure 1.14). This is an important process during autophagic and

mitophagic initiation, maturation, trafficking and lysosomal clearance (Liu et al.

2012).

59

Figure 1.14. A model showing the function of MAP1S. MAP1S bridges healthy mitochondria to microtubules for trafficking with the assistance of RASSF1A; MAP1S interacts with external LC3-II and bridges autophagosomes to microtubules for trafficking with the assistance of RASSF1A; and MAP1S binds with mitochondrion-associated LRPPRC and docks a dysfunctional mitochondrion into an autophagosome through the interaction with internal LC3-II (Adapted from Liu et al. 2012).

Other studies have also demonstrated that MAP1S has a role in regulating

phagocytosis. One study shows that MAP1S is expressed primarily in the

macrophage, among other cells involved in immune responses, such as T and B

lymphocytes, natural killer (NK) cells, dendritic cells and white blood cells (Shi et al.

2016). MAP1S also interacts directly with MyD88, a key adaptor of toll-like

receptors (TLRs), upon TLR activation and affects the TLR signalling pathway. Under

60

activation of TLR, MyD88 participates in autophagy processing in a MAP1S-

dependent manner by co-localizing with LC3 (Shi et al. 2016).

As a tumour suppressor protein, MAP1S has also been demonstrated to have a

potential role in regulating tumorigenesis. Acute elevation of MAP1S post

administration of DEN-induced HCC (hepatocellular carcinoma), leading to the

activation of autophagy in order to suppress tumorigenesis, has been demonstrated

(Rui et al. 2011; Liu et al. 2012).

1.7. Summary of literature study

To summarise, it is known that myocardial infarction is the main cause for heart

failure. The pathophysiological mechanisms underlying this event are discussed

earlier, where defective mitochondria are a potential source of oxidative stress that

can induce cellular responses leading to apoptosis and myocyte death.

As an important survival pathway to remove damaged organelles, such as defective

mitochondria, autophagy and/or mitophagy are essential in the stress-induced

heart. MAP1S has recently been identified as an important player in regulating

autophagy and mitophagy, but its role in the heart is unknown. Therefore, it is

important to investigate the role of MAP1S in regulating autophagy in the heart.

1.8. Hypothesis

The genetic ablation of MAP1S has been demonstrated to have a detrimental

effect. MAP1S depleted mice have also displayed damaged mitochondria in the

heart, which might be related to impairment of cardiac autophagy and mitophagy.

The mechanism by which MAP1S regulates autophagy in the heart is also still

unknown. Therefore, the main hypothesis to be tested is that MAP1S plays a major

role in regulating autophagy in the heart, and that the deletion of this gene would

have detrimental effect in the heart, particularly in a pathological setting.

61

1.9. Aim

The main aim of this project is to investigate the role of MAP1S in regulating

autophagy and mitophagy in the heart, both in vitro and in vivo.

Specific objectives of this study are stated as follows:

To investigate the effects of MAP1S depletion in the regulation of autophagy

in cardiomyocytes.

To study the effect of MAP1S depletion in the fusion of the autophagosome

to defective mitochondria in cardiomyocytes.

To analyse the effect of MAP1S depletion on mitochondrial function.

To asses MAP1S expression levels in different pathological conditions in

mouse hearts.

To investigate the effects of MAP1S ablation following myocardial infarction

in mice

62

CHAPTER 2

Materials and

methods

63

2. MATERIALS AND METHODS

2.1. Generation of MAP1S KO Mice

To investigate the role of MAP1S in regulating autophagy in the heart, MAP1S

global knockout mice were used. These mice were kindly provided by Dr. Leyuan Liu

(Texas, US) and were originally generated using Cre-loxP recombination technology

(Rui et al. 2011). The background strain used to generate this knockout was C5BL/6

mice. To produce MAP1S knockout mice by Cre–loxP recombination technology,

mice with an insertion of loxP sites Flanking exon 4 and exon 5 were crossed with

transgenic Nestin-Cre mice to remove MAP1S in the germline, as shown in Figure

2.1 (Rui et al. 2011).

Figure 2.1. Generation of MAP1S knockout mice. The figure shows the MAP1S gene in wild type mice, which show all exons, the floxed allele, and the null allele with the deletion of exons 4 and 5. The Cre enzyme (scissors) and its target sequence loxP (red arrowheads) are shown on the floxed allele. Hind III and EcoRI restriction sites are shown, along with the PGKneo cassette used for positive selection during homologous recombination. Finally, the primer positions for PNeo, P31, and P32 are shown on the MAP1S gene, which were used to perform PCR genotyping (Liu et al 2012).

The mice were bred and housed in a standard housing facility according to the

Animals (Scientific Procedures) Act (ASPA) 1986 under a project license granted to

Dr. Elizabeth Cartwright, University of Manchester, UK and approved by the

University of Manchester Ethics Committee. The mice used for breeding pairs were

64

heterozygote mice, therefore three mouse genotypes were obtained as a result,

namely wild type, MAP1S knockout and heterozygous mice, as seen in Figure 2.2.

Figure 2.2. Breeding strategy used to generate MAP1S knockout and control mice (A) MAP1S heterozygous mice (MAP1S +/-) were bred to produce wildtype (MAP1S +/+) and knockout mice (MAP1S -/-) used in this study. (B). Example PCR electrophoresis gel demonstrating the animal genotypes used in this study. The upper panel of the PCR electrophoresis image shows a 200bp band produced by the wildtype allele, and the lower panel shows the Map1s- band at 400 bp.

2.2. Molecular analysis

2.2.1. DNA Extraction

DNA for genotyping was extracted from ear snips of each animal. Each

sample was incubated at 56°C overnight in 200µL Lysis buffer (0.5% SDS, 50mM

Tris-HCl pH 8 and 100mM EDTA) with 10µL 10mg/mL Proteinase K for digestion. The

sample was then centrifuged at 13000 rpm to remove the debris. The supernatant

was then transferred to a clean tube. The DNA was precipitated using isopropanol

and centrifuged at 13000 for 5 minutes. The remaining DNA was washed using

200µl of 70% Ethanol and centrifuged at 13000 rpm for 5 minutes. Following this,

the DNA was dissolved in 50-200µL TE Buffer depending on the pellet size.

65

2.2.2. PCR

Table 2.1 shows the PCR enzyme master mix along with other components

and the volumes used for each sample. Each DNA sample was run twice; once with

the P31 primer and P32 primer to detect the wild type allele and once with the P32

primer and PNeo to detect the knockout allele (Table 2.2). Polymerase chain

reaction (PCR) was then performed to amplify the products of interest on a Veriti

96-well thermal cycler (Applied Biosystems). Cycling conditions and primer

sequences are shown in Tables 2.2 and 2.3 below.

Component Volume

Forward primer (10µM in nuclease free water) 1µL

Reverse primer (10µM in nuclease free water) 1µL

Nuclease free water 12µL

Reddymix PCR Master Mix (Thermo Scientific) 15µL

Genomic DNA 1µL

Total volume 30µL

Table 2.1. PCR Master Mix components for each sample.

Primer Sequence Genotype

P31-forward (Sigma) CACCTGCCTAAGCCATCTGTGTC Wild Type

P32- reverse (Sigma) CTCAGTCTGTCTGAGACAAGGTC

PNeo- forward (Sigma) GGTAGAATTGGTCGAGGTCGAC KO

P32- reverse (Sigma) CTCAGTCTGTCTGAGACAAGGTC

Table 2.2. Primers sequences used in PCR reaction

66

MAP1S +/+ MAP1S -/-

Steps Temperature Time Cycle Temperature Time Cycle

Enzyme

Activation

95°C 10 min 1 cycle 95°C 10 min 1 cycle

Denaturation 94°C 45 sec 35

cycle

94°C 45 sec 35

cycle Annealing 60°C 1 min 58°C 1 min

Extension 72°C 2 min 72°C 2 min

Final

Extension

72°C 10 min 1 cycle 72°C 10 min 1 cycle

4°C Forever 4°C Forever

Table 2.3. PCR cycling conditions for genotyping reactions.

2.2.3. Gel electrophoresis

Gel electrophoresis was used to separate the amplified PCR products based on their

size. Amplified PCR products were run at 100V on 2% agarose gel (2g agarose

dissolved in 100µL TAE containing 40mM Tris base, 20mM acetic acid, 1mM EDTA)

stained with 6µL Midori Green /100mL 2% agarose gel. HyperLadder™ I (Bioline)

DNA ladder was used and the gel viewed using a ChemiDoc™ XRS+ imaging system

(Bio-Rad).

2.2.4. Isolation of NRCM

Following collection from 2-3 day old Sprague Dawley rat pups, hearts were put in

ice cold ADS (containing 6.8g NaCl, 4.76g HEPES, 0.12g NaH2PO4, 1.0g Glucose, 0.4g

KCL, 0.1g MgSO4 made up to 1L with dH2O, adjusted to pH 7.35 with 1N NaOH and

stored at 4 ᵒC after being vacuum filtered into a sterile container). The next process

was heart tissue digestion. Hearts were transferred to a glass bottle containing

100mg/75mL ADS Collagenase A (Roche 0103586) and 0.5g/5mL ADS Pancreatin

67

(Sigma P-3292), and the digestion was started in a shaking incubator for 5 minutes

at 37 °C. Following this, the solution was triturated around 30 times using a 25mL

stripette. The solution from the first digestion was discarded into Virkon, and 3mL

FBS (Gibco) was added to stop enzyme digestion. The digestion step was then

repeated, except this time the digested solution was carefully collected to a new

sterile bottle using a cell strainer to prevent debris passing through, and maintained

at 37 ᵒC. This process was further repeated until all heart tissue was completely

digested.

The digested heart suspension was divided equally into two falcon tubes, and spun

at 1200 rpm for 5 minutes at room temperature. After this the supernatant was

discarded, the pellet was resuspended with Pre-plating media (204mL DMEM

(Gibco), 51mL M199 (Gibco), 30mL Horse Serum (Gibco), 15mL FBS (Gibco), 3mL

Fungizone, and the suspension pipetted up and down to avoid cell clumps.

Following this, the cells were plated in 10 mL in a 40mm tissue culture dish, for 30-

60 minutes to allow fibroblasts to attach. Then the cells were gently disturbed and

transferred into one falcon tube for counting. The cells were then diluted with 40µL

plating media (204mL DMEM (Gibco), 51mL M199 (Gibco), 30mL Horse Serum

(Gibco), 15mL FBS (Gibco), 3mL Fungizone, 300uL BRDU) and plated to specialised

plates (Corning, PrimariaTM) for cardiomyocytes at the desired density. Cells were

kept in a sterile incubator at 37°C, with 5% CO2. The media was changed to

maintenance media the following day (400mL DMEM, 100mL M199, 50mL FBS, 5mL

Fungizone, 500µL BRDU).

2.2.5. Isolation of MSF

Biopsies were taken from mouse ear skin from wild type and MAP1S knockout

mice. The biopsies were then washed in absolute ethanol followed by washing in

Dulbecco’s phosphate-buffered saline (DPBS) solution (Gibco). The hair from skin

biopsies was then removed by scalpel before mincing. Following this, the minced

skin biopsy fragments were placed underneath sterile glass coverslips in a 6 well

plate to reduce movement. The biopsies were then cultured using DMEM medium

with an additional 20% FBS. Media was changed every two days until the skin

fibroblasts could be seen appearing from the biopsies. Once the mouse skin

68

fibroblasts (MSFs) were confluent the glass coverslips were removed and the cells

were washed with DPBS. They were then trypsinised using TrypLE Express (Gibco)

and the cell suspension transferred to larger flasks with fresh MSF media. The cells

were passaged until passage 3, after which they were either used for experiments

or frozen in liquid nitrogen for further use.

For freezing the cells, DPBS was used to wash the cells followed by incubation with

5mL TrypLE Express in a 175mL tissue culture flask (Cellstar cell culture flask) for 5

minutes. Once the cells were detached, 10mL MSF medium (DMEM + 20% FBS) was

added to neutralise the TrypLE Express. Following this, the cell suspension was

centrifuged at 1000 rpm for 5 minutes, and the supernatant was discarded. The cell

pellet was resuspended with freezing medium (50 % FBS, 10% DMSO

[dimethylsulphate], 40% DMEM). The cells were then placed in cryovials, 1.000.000

cells per vial. Cryovials were placed in a Nalgene Mr Frosty freezing container

(Thermo-Scientific) and kept for 24 hours at -80°C before being transferred to liquid

nitrogen for long term storage.

2.2.6. Protein expression analysis

Western blot is a commonly used method to analyse protein expression. It can

analyse particular proteins by separating them based on their molecular weight by

electrophoresis, and then targeting the protein of interest by an immunological

approach using a specific antibody against the target protein.

2.2.7. Protein extraction

Protein was collected from cells and tissue using RIPA buffer (containing 1x PBS, 1%

IGEPAL CA-630, 0.5% sodium deoxycholate, 0.1% SDS, 0.5mM PMSF, 500ng/ml

Leupeptin, 1μg/ml Aprotinin, 2.5μg/ml Pepstatin A). The heart tissue (about half of

the whole heart) was homogenised in 400µL- 500µL RIPA buffer using a tissue

homogeniser (Dounce homogeniser), while cell lysates were scraped and collected

after 30 minutes incubation in RIPA buffer on a shaker in the cold room. Protein

lysates were then centrifuged at 3000 rpm for 10 min at 4°C. The supernatant was

then collected for protein concentration measurement using BCA Assay (Bio-Rad)

and stored at -80°C.

69

Measuring total protein concentration

BCA Assay is a detergent-compatible formulation based on bicinchoninic acid (BCA)

for the colorimetric detection and quantitation of the total protein. It uses the well-

known biuret reaction whereby proteins reduce Cu2+ to Cu1+ in alkaline medium.

The purple colour of this reaction is formed by the chelation of two molecules of

BCA with one cuprous ion, and it gives a strong absorbance at 520 nm which is

linear to the increasing concentration of protein over the range of 20-2000µg/mL.

Standards and samples were loaded in triplicate onto a 96 well plate, incubated for

30 minutes at 37°C following the addition of the BCA reagent, and mean

absorbance was measured on an optical plate reader (Thermo Labsystems).

Western Blot Analysis

To analyse the target protein expression using western blot, an equal quantity of

protein samples (30-50µg) along with 2x or 6x Laemmli buffer (Sigma Aldrich) were

heated up to 95°C for 5 minutes in a heat block. Several concentrations of gels (8%-

15% polyacrylamide) were made according to the recipes detailed in Table 2.4,

dependent upon the molecular weight of the target protein to be analysed. The

protein samples were then loaded into the stacking gel (Table 2.5) along with a

standard, or molecular weight marker (Bio-Rad Precision Plus Protein Dual Colour

Standards) in one of the wells. Gels were then arranged in an electrophoresis tank

filled to the top mark with Tris glycine running buffer and allowed to run at 130 V

for 1 hour 30 minutes. Thereafter the protein was blotted from the gel onto PVDF

(polyvinylidene fluoride) membrane (Millipore) using the semi-dry transfer method

for 2h at 200mA in the presence of transfer buffer containing 25 mM Tris Base, 0.25

M glycine and 20% methanol or using a TransBlot Turbo system (Bio-Rad) for 7 min

at 25V and 2.5A. The transferred membrane was then blocked for 1 hour with 3-5%

Bovine Serum Albumin (Sigma Aldrich) or 1%- 5% Skimmed Milk (Sigma Aldrich)

diluted in TBS, dependent upon the primary antibody. Following this, the

membrane was incubated with primary antibody diluted in the blocking solution

(1:1000) overnight on an orbital shaker at 4°C. Details of primary antibodies used

along with blocking conditions are shown in Table 2.6. The following day the

membrane was washed for 3x 10 minutes with TBST (Tris-buffered saline with 10

70

mM Tris base, 150 mM NaCl and 0.05% Tween-20), before being incubated under

agitation for 2 hours at room temperature with Horseradish Peroxidase-linked Anti-

rabbit or Anti-mouse secondary antibody (diluted 1:5000 in TBST, see Table 2.7),

dependent upon the primary antibody used. The membrane was then washed for

3x10 minutes with TBST followed by detection of bound antibodies by addition of

enhanced chemiluminescence (ECL) Western blotting detection reagent (GE

healthcare) containing 1 μL/mL H2O2 (Amersham Biosciences) for 1 minute.

ChemiDoc XRS+ imaging system (Bio-Rad, UK) was used for imaging. For the

detection of housekeeping proteins, the membrane was stripped of secondary

antibodies using a stripping buffer (0.1 M glycine solution, pH 2.5) for 30 minutes.

The membrane was washed 3 times with TBST for 10 minutes before it was

incubated with the control antibody (HRP-linked GAPDH, beta actin or alpha

tubulin), which was diluted 1:5000 in TBST. Protein bands were detected as for the

protein of interest. To quantify target protein expression, band intensity was

measured using ImageJ software and normalised to the control bands (GAPDH, beta

actin or alpha tubulin) obtained from the same sample.

Separating gel 8% 10% 12% 15%

H2O 2.3 mL 2.0 mL 1.7 mL 1.2 mL

30% Acrylamide gel 1.3 mL 1.7 mL 2.0 mL 2.5 mL

1.5M Tris (pH 8.8) 1.3 mL 1.3 mL 1.3 mL 1.3 mL

10% SDS 0.005 mL 0.005 mL 0.005 mL 0.005 mL

10% APS 0.005 mL 0.005 mL 0.005 mL 0.005 mL

TEMED 0.0003 mL 0.0002 mL 0.0002 mL 0.0002 mL

Table 2.4. Solutions for separating gel used for SDS- Polyacrylamide Gel Electrophoresis.

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Stacking gel Volume

H2O 0.68 mL

30% Acrylamide gel 0.17 mL

1.0 M Tris (pH 6.8) 0.13 mL

10% SDS 0.01 mL

10% APS 0.01 mL

TEMED 0.001 mL

Table 2.5.Solutions for stacking gel used for SDS-Polyacrylamide Gel Electrophoresis.

Primary

antibody Supplier Diluent

Dilution

factor

Secondary

antibody

MAP1S Precision

Antibody 1% Skim Milk 1: 1000 Anti-Mouse

LC3 Novus

Biological 5% Skim Milk 1: 1000 Anti-Rabbit

Beclin Santa Cruz 3% BSA 1: 1000 Anti-Rabbit

P62/SQM Santa Cruz 3% BSA 1: 1000 Anti-Rabbit

PINK1 Novus

Biological 3% BSA 1: 1000 Anti-Rabbit

Caspase 3 Cell Signalling 3% BSA 1: 1000 Anti-Rabbit

Cleave

caspase Cell Signalling 3% BSA 1: 1000 Anti-Rabbit

Bcl-xL Cell Signalling 3% BSA 1: 1000 Anti-Rabbit

Bcl2 Cell Signalling 3% BSA 1: 1000 Anti-Rabbit

pBcl-xL 3% BSA 1: 1000 Anti-Mouse

Cyt c Cell Signalling 3% BSA 1: 1000 Anti-Rabbit

Bax Cell Signalling 3% BSA 1: 1000 Anti-Rabbit

Bad Cell Signalling 3% BSA 1: 1000 Anti-Rabbit

Alpha

tubulin-HRP

linked

Abcam TBST 1: 1000 None

72

Beta Actin

HRP- linked Abcam TBST 1: 1000 None

GAPDH HRP-

linked Cell Signalling TBST 1: 1000 None

Table 2.6. Primary antibodies used for western blot analysis.

Secondary Antibody Supplier Dilution Factor

HRP-Linked Anti Rabbit Antibody Cell Signalling 1: 5000

HRP-Linked Anti Mouse Antibody Cell Signalling 1: 5000

Table 2.7. Secondary antibodies used for western blot analysis.

2.2.8. Adenovirus productions

Generation of AdMAP1S, AdKeima and AdParkin

This study used the Invitrogen Gateway and ViraPower™ Adenoviral Expression

Systems as per the manufacturer protocols to overexpress MAP1S, Keima and

Parkin in cardiomyocytes. The first step involved generating an entry clone (Figure

2.3) using adenovirus shuttle pENTRTM11, into which was inserted pMAP1S, pKeima

or pParkin following digestion with restriction enzymes as shown in Table 2.8.

Insertion was achieved in a thermo cycler machine set at 23°C for 5 hours using a

ligase reaction, the components of which are listed in Table 2.9.

Mutant Size Restriction enzymes

Map1s 2300 bp NcoI and KpnI

Keima 4700 bp Bam HI and XbaI

Parkin 6100 bp KpnI

Table 2.8. Restriction enzymes for inserting the mutant to entry clone.

73

Figure 2.3. pENTRTM11 map used for generating entry clone.

Components Volume

Ligation buffer 1 µL

pENTR 1 µL

T4 Ligase 1 µL

pMAP1S 2 µL

H2O 5 µL

Table 2.9. Reaction components for the insertion of the mutant clone into the entry clone.

The next step involved transfering the DNA into bacteria by a process called

transformation. The generated pENTR-MAP1S, pENTR-Keima, pENTR-Parkin were

mixed with 30 µL competent cells and incubated for 30 minutes on ice followed by

heat shock incubation at 42°C for 2 min 30 sec. Following this, 100 µL LB Broth was

added to each plasmid, and all plasmids were incubated for 1 hour at 37°C in a

shaking incubator set to 150rpm. Following this, the mixture was transferred onto

74

LB-agar plates containing 50μg/ml Kanamycin for positive selection and left

overnight at 37°C. The entry clone was then collected and amplified using the

PureLink® HiPure Plasmid Filter Maxiprep Kit (Invitrogen) according to the

manufacturer’s protocol. DNA concentration was quantified with a nanodrop, and

50ng was transferred into a pAd/CMV/V5-DEST vector (Invitrogen V493-20) by an

LR recombination reaction. The pAd/CMV/V5-DEST map is shown in Figure 2.4, and

the components used for the LR recombination are shown in Table 2.10.

Figure 2.4. pAd/CMV/V5-DEST Vector map.

Components Volume

Entry clone (~50ng/ reaction) 2 µL

Destination vector (pAd/CMV/DEST) 1 µL

TE buffer 5 µL

LR clonase II enzyme (Invitrogen 11791-020) 2 µL

Table 2.10. Components used in LR reaction.

75

The reaction was incubated at 25°C for 24h, prior to addition of 1μl proteinase K

(20mg/ml, Invitrogen) and subsequent incubation at 37°C for 10min. LB agar plates

containing 100μg/ml Ampicillin were used for clone selection by incubating

overnight at 37°C. The resulting plasmid was then amplified by maxi-prep. To

confirm that the gene of interest was in the correct orientation, all three maxiprep

DNA products were amplified and sequenced using the T7 and V5 primers as shown

in Table 2.11, and run on 0.8% agarose gel by electrophoresis for 45 minutes to

observe the corresponding bands (Figure 2.5).

Vector Primer Sequence

pAd/CMV/V5-

DEST™

T7 promoter/priming

site 5’-TAATACGACTCACTATAGGG-3′

V5(C-term) reverse

priming site 5’-ACCGAGGAGAGGGTTAGGGAT-3′

Table 2.11. T7 and V5 primers for pAd/CMV/V5-DEST sequencing.

Figure 2.5. Restriction enzyme product of pAd/MAP1S, pAd/Keima, pAd/Parkin.

10µg of purified pAd/MAP1S, pAd/Keima, pAd/Parkin were digested with PacI

restriction enzyme overnight at 37°C. The following day, 60µL absolute ethanol was

added to the digested product, and mixed and centrifuged at 13000 rpm for 10

minutes at room temperature. The supernatant was discarded and the DNA pellets

76

air dried for 30 minutes, then resuspended with 10µL water. This constituted the

stock DNA used to infect HEK 293 cells to produce primary adenovirus stock.

Generation of AdGFP-LC3

The GFP-LC3 adenovirus construct was generated by Dr. Delvac Oceandy. To

generate adenovirus expressing GFP-LC3, pAd/CMV/V5-Dest vector (Invitrogen)

was used. The GFP-LC3 cDNA was kindly provided by Dr Tamotsu Yoshimori

(National Institute for Basic Biology, Okazaki, Japan). The GFP-LC3 cDNA was cloned

into the pAd/CMV/V5-DEST vector. The protocols followed to produce pAd GFP-LC3

adenovirus were as described in the previous section.

Producing adenovirus in HEK 293 cells

To amplify the recombinant adenovirus for primary adenoviral stock, 20μl of PacI-

digested vector in 480μl OptiMEM (Life Technologies) was combined with a mixture

of 480μl OptiMEM and 20μl Lipofectamine 2000 (Life Technologies) and incubated

at RT for 20 min. The mixture was added to one T25 flask containing Human

Embryonic Kidney 293 (HEK293) cells as indicated in Table 2.12. The media was

replaced with fresh media (containing Dulbecco’s Modified Eagle Medium (DMEM)

(Invitrogen) with 1% non-essential amino acids, 10% foetal bovine serum (FBS) and

1% penicillin/streptomycin) before the mixture was added. The transfected cells

were trypsinised the following day, transferred to a T75 flask and maintained until

comet-like streaks of cells could be observed throughout the flask (normally around

day 7 of the procedure). All cells were then collected and pelleted by centrifugation

at 1200 rpm for 5 min, and resuspended in 1ml PBS (Life Technologies) before being

stored as primary viral stock at -80°C.

Components Amount

HEK 293 cells in T25 flask 1x 106 (>95% confluence)

Pac I-digested

PAdMAP1S/PAdGFP-LC3/pAdKeima/pAdPArkin 20µL + 480µL OptiMem

Lipofectamine 20µL + 480µL OptiMem

Pre-warmed fresh medium 10mL

Table 2.12. Components used for primary adenovirus production.

77

The second viral amplification used 2 fully confluent T175 flasks of HEK cells. To

each flask, 25µL primary viral stock from the previous amplification step was added.

After 72h, transduced cells were pelleted by centrifugation at 1200 rpm for 5 min

and then resuspended in 1ml PBS. The resulting secondary viral stock was aliquoted

and stored at -80°C for further amplification. The third step to amplify the AdGFP-

LC3 used 8 fully confluent T175 flasks of HEK 293 cells. As with the second viral

amplification, 25µL of secondary adenovirus was gently added to each flask. After

48 hours, the cells were collected and pelleted by centrifugation at 1200 rpm for 5

min, then resuspended in 3mL dPBS. The resulting tertiary viral stock was aliquoted

and stored at -80°C.

In order to use the AdGFP-LC3 to transduce target cells, cells from the tertiary

adenovirus stock were lysed through 3 freeze/thaw cycles. Tertiary stock was

defrosted in a 37°C waterbath for 10 min, followed by freezing at -80°C for 1 h 30

min. This process was repeated, thawing for 10 min at 37°C and freezing at -80°C

for 2h. Following a third thawing of adenovirus stock at 37°C in the waterbath for

10 min, 1 mL chloroform was added per 1mL adenovirus crude stock solution, in a

15 mL falcon tube. The mixture was shaken vigorously for 2 min until two layers

formed in the solution, one clear and one denser. The clear solution containing

ready to use AdGFP-LC3 was aliquoted and stored at -80°C for further use.

AdGFP-LC3 titration.

For determining the adenovirus concentration, 5000 HEK293 cells in 100 µL

medium were plated in 69 wells of a 96 well plate. 24 hours after the cells were

plated, the medium was replaced with pre-warmed media containing serially

diluted adenovirus. Dilutions were prepared in triplicate according to the

concentrations shown in table 2-13. After 15 minutes’ incubation at 37°C in the viral

incubator, the plate was swirled gently to ensure even distribution across the cell

monolayer. The following day, 100 µL pre-warmed fresh media were added to each

well. The media was changed every 3 days and on the eighth day, the most dilute

concentration showing plaque formation was used to determine virus

concentration in pfu/ml. To transfect cells at desired multiplicity of infection (MOI)

values, the amount of virus needed to sufficiently transfect a known cell number

78

could be calculated from the following equation: MOI= Virus concentration (pfu/ml)

× Volume(ml)/ Number of transfected cells.

Well number

Dilution pfu/ml

Well number

Dilution pfu/ml

1 1 x 10-2 1 x 103 13 3.91 x 10-9 2.56 x 109

2 1 x 10-3 1 x 104 14 1.95 x 10-9 5.12 x 109

3 1 x 10-4 1 x 105 15 9.77 x 10-10 1.02 x 1010

4 1 x 10-5 1 x 106 16 4.88 x 10-10 2.05 x 1010

5 1 x 10-6 1 x 107 17 2.44 x 10-10 4.1 x 1010

6 5 x 10--7 2 x 107 18 1.22 x 10-10 8.19 x 1010

7 2.5 x 10-7 4 x 107 1 9 6.1 x 10-11 1.64 x 1011

8 1.25 x 10-7 8 x 107 20 3.05 x 10-11 3.28 x 1011

9 6.25 x 10-8 1.6 x 108 21 1.53 x 10-11 6.55 x 1011

10 3.12 x 10-8 3.2 x 108 22 7.63 x 10-12 1.31 x 1012

11 1.56 x 10-8 6.4 x 108 23 3.81 x 10-12 2.62 x 1012

12 7.81 x 10-9 1.28 x 109 24 (-) Control (-) Control

Table 2.13. Dilutions for determining Adenovirus titration.

2.2.9. siRNA Transfection

Using siRNA transfection to trigger an RNAi response and silence target protein

expression has been widely used in mammalian cells (G.J. & J.J. 2004). Small

Interfering RNAs (siRNA) are 21-23 nucleotide double-stranded RNA molecules that

can be used to silence expression of a particular gene. Once incorporated into RISC

(RNA-induced silencing complex), a siRNA-directed endonuclease, it will catalyse

cleavage of a single phosphodiester bond on the target mRNA and may affect the

translation of the targeted gene.

79

MAP1S siRNA (Sigma-Aldrich; SASI_Rn02_00215332) was used to knock down

MAP1S in cardiomyocytes. A scrambled non-targeting siRNA (Sigma-Aldrich) was

used as control. To achieve 25nM final concentration as per the manufacturer’s

recommendation, 10µL of 5µM MAP1S siRNA stock was diluted with 190µL serum

free-medium (OptiMem, Gibco), whilst 5µL of DharmaFECT transfection reagent

was diluted with 195 µL serum free-medium (OptiMem, Gibco). After 5 minutes

incubation for each tube, the diluted MAP1S and control siRNA were combined

with the DharmaFECT solution very gently. After being pipetted up and down to

mix, the solutions were incubated for 20 minutes before adding the total solution

(400µL) to the fully attached cardiomyocytes in designated 6 well plates, which

already contained 1600µL maintenance medium. Cells were incubated for 72 hours

to achieve knockdown before further experiments were performed. Volumes used

for transfection of 6- and 24-well plates are shown in Table 2.14.

Diluted

siRNA (uL/well)

Diluted

DharmaFECT

(uL/well)

Plating

format

(wells/plate)

Vol. of

5uM

siRNA

(uL)

OptiMem

(uL)

Vol of

Dharma

FECT

reagent

(uL)

OptiMem

(uL)

Maintenance

Medium

(uL/well)

Total

transfection

volume

(uL/well)

24 2.5 47.5 1.25 48.75 400 500

6 10 190 5 195 1600 2000

Table 2.14. Volumes of siRNA transfection reagents used to reach 25nM final concentration.

2.2.10. pAd GFP-LC3 Transduction

Following 72 hours of MAP1S or control siRNA transfection, 3μL of pAd GFP-LC3

was added to each well. The plate was then incubated in the viral incubator at 37°C

with 5% CO2 for 24 hours. The following day, 3mM chloroquine and 5mM

rapamycin were added to designated wells for 2 hours to induce autophagy. The

cells were then washed twice using PBS and fixed with 3.7% Formaldehyde for 10

80

minutes. The nuclei were stained with DAPI (Life Technologies). The coverslip was

then mounted on a slide using Vectashield mounting media (Vector Laboratories,

Inc) and images were collected on a Zeiss Axioimager.D2 upright microscope using a

63x / 0.5 EC Plan-Neofluar Objective and captured using a Coolsnap HQ2 camera

(Photometrics) through Micromanager software v1.4.23. Specific band pass filter

sets for DAPI and FITC were used. Images were then processed and analysed using

Fiji ImageJ (http://imagej.net/Fiji/Downloads).

2.2.11. pAdKeima, pAdParkin Transduction

In order to investigate mitophagy in cardiomyocytes, 1µL pAdKeima and 1µL

pAdParkin were transduced into MAP1S or control siRNA treated cells in a 24 well

plate for 24 hours. Following this, 10µM carbonyl cyanide m-chlorophenyl

hydrazine (cccp), known as a mitochondrial uncoupling agent, was added to

designated wells in each treatment group for 4 hours. The cells were then washed

twice using PBS and fixed with 3.7% Formaldehyde for 10 minutes. The nuclei were

stained with DAPI (Life Technologies). The coverslip was then mounted on a slide

using Vectashield mounting media (Vector Laboratories, Inc) and images were

collected on a Zeiss Axioimager.D2 upright microscope using a 63x / 0.5 EC Plan-

Neofluar Objective and captured using a Coolsnap HQ2 camera (Photometrics)

through Micromanager software v1.4.23. Specific band pass filter sets for DAPI,

FITC and Texas Red were used. Images were then processed and analysed using Fiji

ImageJ (http://imagej.net/Fiji/Downloads).

2.2.12. pAd/MAP1S Transduction

To verify that previously generated pAd/MAP1S could successfully overexpress

MAP1S in cardiomyocytes, 6 well plates of fully attached isolated NRCM were

transduced with 10µL pAd/MAP1S or pAd/LacZ as a control for 48 hours. Following

this, protein was extracted and western blot analysis for MAP1S expression was

performed.

http://imagej.net/Fiji/Downloads


81

2.2.13. Lysotracker Analysis

Because autophagic flux is reflective of the overall autophagy process, and in order

to investigate whether MAP1S knockdown impacts lysosomal formation,

lysotracker was used to stain lysosomes. The analysis employed two different

methods, immunofluorescence and flow cytometry, to analyse lysotracker density

in control and MAP1S siRNA-treated NRCM.

Following 72 hours siRNA transfection, cardiomyocytes plated in a 24 well plate

were treated with 3mM chloroquine and 5mM rapamycin for 2 hours, followed by

cell staining with LysoTracker® probes (Life technologies). The LysoTracker® probes,

which consist of a fluorophore linked to a weak base that is only partially

protonated at neutral pH, are freely permeant to cell membranes and typically

concentrate in spherical organelles. After the cells were washed with DPBS, 50nM

Red LysoTracker® probes diluted in pre-warmed medium were added to each well.

Following this the cardiomyocytes were incubated for 30 min in the 37°C, 5% CO2

incubator. The cells were then washed twice using PBS and fixed with 3.7%

Formaldehyde for 10 min. The nuclei were stained with DAPI (Life Technologies).

The coverslip was then mounted on a slide using Vectashield mounting media

(Vector Laboratories, Inc) and images were collected on a Zeiss Axioimager D2

upright microscope using a 20x /0.5 EC Plan-Neofluar Objective and captured using

a Coolsnap HQ2 camera (Photometrics) through Micromanager software v1.4.23.

Specific band pass filter sets for DAPI and Texas Red were used. Images were then

processed and analysed using Fiji ImageJ (http://imagej.net/Fiji/Downloads).

Similar protocols were used to prepare cardiomyocytes for a FACS experiment.

However, before the cells were stained, cell detachment reagent (StemPro-

Accutase, Life Technologies) was added in order to have cardiomyocytes in

suspension. 50nM Red LysoTracker® probes diluted in pre-warmed maintenance

media was added to the cell suspensions for 30 minutes, under agitation in the 37°C

shaking waterbath. Following the incubation, the cells were centrifuged at 1000

rpm for 5 minutes. The cardiomyocyte pellets were then resuspended with 500µL

dPBS in sterile Eppendorf tubes and taken to the FACS facility straight away.


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2.2.14. MitoTracker Analysis

To analyse differences in mitochondrial structure between control and MAP1S

siRNA-treated cells, transfected cardiomyocytes were treated with 10µM cccp for 4

hours. Cells were then stained with a MitoTracker probe. MitoTracker® probes, a

mitochondrion-selective stains that are concentrated by active mitochondria and

retained during cell fixation. MitoTracker® probes (MitoTracker® Mitochondrion-

Selective Probes, Invitrogen) contain a mildly thiol-reactive chloromethyl moiety,

which passively diffuses across the plasma membrane and accumulates in active

mitochondria. When this probe enters an actively respiring cell, it is oxidized to

MitoTracker® fluorescent conjugate and sequestered in the mitochondria, where it

reacts with thiols on proteins and peptides to form an aldehyde-fixable conjugate.

For a stock solution, lyophilized MitoTracker® product was dissolved in anhydrous

dimethylsulfoxide (DMSO) to a final concentration of 1 mM. 150nM Mitotracker

green (Thermo Fischer) was diluted in maintenance media for 30 minutes.

Following this, the cells were washed with DPBS, and the nuclei were stained with

DAPI (Life Technologies). The cells were then washed twice using PBS then fixed

with 3.7% Formaldehyde for 10 minutes. The nuclei were stained with DAPI (Life

Technologies). The coverslip was then mounted on a slide using Vectashield

mounting media (Vector Laboratories, Inc) and images were collected on a Zeiss

Axioimager with DAPI and FITC filters.

Another experiment using this probe was performed using cardiomyocytes

transduced with pAdGFP-LC3 in siRNA control and MAP1S siRNA-treated cells.

Following 3mM chloroquine and 5mM Rapamycin treatment to induce

autophagosome formation, 150nM MitoTracker red (Thermo Fisher) diluted in

maintenance media were added for 30 minutes. Following this, the cells were

washed with DPBS, and the nuclei were stained with DAPI (Life Technologies). The

cells were then washed twice using PBS then fixed with 3.7% Formaldehyde for 10

minutes. The nuclei were stained with DAPI (Life Technologies). The coverslip was

then mounted on a slide using Vectashield mounting media (Vector Laboratories,

Inc) and images were collected on a Zeiss Axioimager with DAPI, FITC and Texas Red

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filter. Images were then processed and analysed using Fiji ImageJ

(http://imagej.net/Fiji/Downloads).

2.2.15. Seahorse XF Assay

The Agilent Seahorse XF Cell Mito Stress Test is an assay to measure parameters of

mitochondrial function by directly measuring the Oxygen Consumption Rate (OCR)

of cells (Agilent Technologies 2017). Several compounds are sequentially injected to

measure basal respiration, ATP production, proton leak, maximal respiration, spare

respiratory capacity and non-mitochondrial respiration (Figure 2.6).

Figure 2.6. OCR of the Agilent Seahorse Mito Stress Test obtained from SeaHorse XF Analyser.


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Table 2.15 below shows the terminology of the mitochondrial function parameters

obtained from the assay (Agilent Technologies 2017).

Parameters Definition

Basal respiration Oxygen consumption used to meet cellular ATP demand and

resulting from mitochondrial proton leak. Shows energetic

demand of the cell under baseline conditions.

ATP production The decrease in oxygen consumption rate upon injection of

the ATP synthase inhibitor oligomycin represents the portion

of basal respiration that was being used to drive ATP

production. Shows ATP produced by the mitochondria that

contributes to meeting the energetic needs of the cell.

H+ (Proton) leak Remaining basal respiration not coupled to ATP production.

Proton leak can be a sign of mitochondrial damage or can be

used as a mechanism to regulate the mitochondrial ATP

production.

Maximal

respiration

The maximal oxygen consumption rate attained by adding the

uncoupler FCCP. FCCP mimics a physiological “energy

demand” by stimulating the respiratory chain to operate at

maximum capacity, which causes rapid oxidation of substrates

(sugars, fats, amino acids) to meet this metabolic challenge.

Shows the maximum rate of respiration that the cell can

achieve.

Spare respiratory

capacity

This measurement indicates the capability of the cell to

respond to an energetic demand as well as how closely the

cell is to respiring to its theoretical maximum. The cell's ability

to respond to demand can be an indicator of cell fitness or

flexibility.

Nonmitochondrial

respiration

Oxygen consumption that persists due to a subset of cellular

enzymes that continue to consume oxygen after rotenone and

antimycin A addition. This is important for getting an accurate

measure of mitochondrial respiration.

Table 2.15. Terms used in determining the parameters in Seahorse analyser experiment.

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Processes in the electron transport chain (ETC) in the mitochondria targeted by the

compounds used in the experiment are shown in Figure 2.7.

Figure 2.7. Diagram on modulation of the compound used in the experiment.

The assay was performed following the manufacturer’s protocol. 30000 NRCM/well

in 80µL maintenance media were seeded onto a 96 well plate, which had been

previously coated with Laminin for 2 hours. One day before the experiment was to

be performed, the Agilent Seahorse XF Analyzer was turned on. The sensor

cartridge was hydrated in the calibrant solution and placed in a 37°C non-CO2

incubator overnight. On the day of the assay, XF Base medium was added with

pyruvate, glutamine and glucose, and the compounds were prepared as shown in

the Table 2.16. Following loading of compounds into the designated well in the

cartridge, the cartridge was then placed in the Agilent Seahorse XF Analyzer to

programme the software. During the setting and calibration of the cartridge, the

cardiomyocytes medium was changed to the pre-warmed assay medium, followed

by placing the 96 well plate into the machine. Following 3 hours of assay, the

cardiomyocytes were washed with PBS twice, and 10µL RIPA buffer was added to

each well. After 30 minutes incubation at 4°C under agitation, a BCA assay was

performed on each well to measure the protein concentration for normalisation of

the assay parameters.

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Item Supplier

XF Base Medium Agilent technologies

The XFe

96 Flux Assay Kit :

Sensor cartridge, Cartridge lid, Calibrant solution

Agilent technologies

Seahorse 96-well XF Cell Culture Microplate Agilent technologies

100 mM Pyruvate Sigma

200 mM Glutamine Sigma

2.5 M Glucose Sigma

Sterile filter

Table 2.16. Components used for Seahorse XF Analyzer experiment

2.2.16. MTT assay

In a 24-well cell culture plate, NRCMs (250.000 cells/well) were transfected with

siRNA control or MAP1S siRNA. After 24h, media was aspirated and replaced by

Maintenance media or media supplemented with 200µM H2O2 to induce oxidative

stress for 1 hour in a 37°C incubator. To assess cell survival, 100μl Thiazolyl Blue

Tetrazolium Blue (MTT Sigma, 5mg/ml in DPBS, filter-sterilised) was added to all

wells. The plate was incubated at 37°C for 2h. During this time, live cells converted

MTT to dark purple formazan crystals, which were dissolved by administration of

500μl Solubilisation solution (0.1N HCl in Isopropanol). Formazan product was then

quantified by absorbance of light at 570nm using a spectrophotometer, as a

readout for the number of surviving cells. Results were expressed as % of cells

viability compared to untreated control.

2.3. Animal work

All animals used in this study were resultant offspring from the breeding set up as

described in the subchapter Generation of MAP1S KO mice, and were housed in the

BSF animal unit at the University of Manchester. After being genotyped, batches of

mice were designated for further experimentation using the procedures described

below.

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2.3.1. Rapamycin and Chloroquine IP Injection

The administration of rapamycin and chloroquine or vehicle (for the control group)

was achieved via intraperitoneal (ip) injection. The doses used for the ip injection

were rapamycin (2mg/Kg) and chloroquine (10mg/Kg). Rapamycin was first diluted

in a small quantity of DMSO and then further with saline, whilst chloroquine was

diluted with saline, to a final stock solution concentration of 1µg/µL 5µg/µL for

rapamycin and chloroquine, respectively. Saline was used for control injections at a

dose of 0.1mL/Kg. Injections were performed using a 1mL needle. Following

injection, the animals were placed back in their cages in the animal unit with

normal conditions of food, water and husbandry. Two hours after injection, the

animals were sacrificed and cardiac tissue was harvested immediately and stored in

-80°C for further experiments.

2.3.2. TEM

Transmission electron microscopy was carried out to analyse the mitochondrial

structure in heart tissue. Heart tissues were collected from mice and then

immediately fixed in 2.5% glutaraldehyde and 0.1M HEPES buffer (pH 7.2)

containing 4% formaldehyde. Following tissue fixation, the tissues were processed

in 0.1 M cacodylate buffer (pH 7.2) with 1% osmium tetroxide and 1.5% potassium

ferrocyanide for 1 hour before treatment with 0.1 M cacodylate buffer (pH 7.2) and

1% uranyl acetate for a further 1 hour. Finally, tissues were treated with 1% uranyl

acetate for 1 hour. After the fixation and treatment, the tissues were dehydrated

using ethanol and then embedded in TAAB 812 resin and polymerised at 60 ºC for

24 hours. Finally, a Reichert Ultracut ultramicrotome was used to cut the tissue

sections, which were then examined with an FEI Tecnai 12 Biotwin microscope at

100 kV accelerating voltage. A Gatan Orius SC1000 CCD camera was used to take

images of the sample sections at random areas. The preparation and imaging of the

tissue sections were processed by Dr Aleksandr Mironov at the bioimaging facility

at University of Manchester.

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2.3.3. Mouse model of myocardial infarction

Left anterior descending coronary artery (LAD) ligation was used to induce

myocardial infarction in vivo in 12-14 weeks old wild type and MAP1S ablated mice.

The surgery was performed by Dr Min Zi, an experienced and licenced colleague in

the group. Before performing surgery, mice were induced with 3% isoflurane

inhalation anaesthetic with supplemental oxygen at a flow rate of 1L/min.

Following this, 0.1mg/kg buprenorphine was administered via i.p. injection to

provide post-operative analgesia. The mice were then intubated and placed on a

ventilator set to 200 breaths per minute at a tidal volume of 0.1ml (Minivent 845,

Harvard Apparatus). Anaesthesia was maintained at 1.5-3% isoflurane in 100%

oxygen throughout the surgery. Following this, a 5mm incision of the skin was made

at the left sternal border using a binocular stereomicroscope (Olympus), 2mm

below the armpit level. Left minithoracotomy through the 4th intercostal space was

then performed to expose the heart and the coronary arteries. Following this, the

LAD coronary artery was permanently ligated with 8-0 nylon suture (ETHILON) at

the level of the left atrial appendage. Successful ligation was confirmed once the

wall of the left ventricle became pale. The chest was then closed in layers using 6-0

prolene suture and the animals were left to recover. Upon recovery they were

administered 0.1ml/30g body weight of sterile saline i.p. and then placed in an

incubator at 30°C where they were closely monitored and kept for the first twenty-

four hours post-surgery. Sham operated controls underwent the same surgical

procedures except the LAD coronary artery was not ligated. Mashed food was given

to all animals for three to five days post-surgery.

2.3.4. cTnI analysis

24 hours post MI and sham surgery, blood was collected from the lateral tail vein of

each mouse. Anaesthetic cream (EMLA) was used to achieve local pain relief and

after ~20 minutes, the mice were placed on a heated water mat to vasodilate the

tail vein. The mice were then placed in a restraint tube in order to minimise

movement during blood collection. Povidone-Iodine was applied to the tail before

an incision was made using a sterile scalpel. 40 µL 3.2 % sodium citrate was used as

anticoagulant and mixed with an equal volume of blood, with samples kept at 4°C.

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Once all the blood samples were collected, the blood was centrifuged at 8000 rpm

for 6 minutes at 4°C. Following this, the plasma-containing supernatant was

collected to new Eppendorf tubes and stored at -80 °C until the assay was

performed.

To confirm occurrence of MI in the mouse models used in the study, plasma levels

of cTnI were assessed 24h post-surgery. In order to confirm this, a high sensitivity

mouse cTnI ELISA kit (Life Diagnostics) was used, as per the manufacturer’s

guidelines. The mouse plasma samples were diluted with five volumes of plasma

diluent. Standards were prepared of known cTnI concentrations. Using specialised

96 well plates provided in the kit, the standards and diluted plasma samples were

incubated for one hour at room temperature under agitation to expose CTnI

antigens to HRP-linked antibodies. Following this, the microtiter wells were washed

with a wash solution. Tetramethylbenzidine (TMB), which is an HRP substrate, was

then added to the wells and incubated for 20 minutes under agitation. A resultant

blue colour was formed, which changed to yellow upon addition of 1N HCl to stop

the reaction. Absorbance at 450nm was measured using a plate reader, which

corresponds to the cTnI concentration.

2.3.5. Echocardiography

A Visualsonics Vevo 770 machine fitted with a 30 MHz transducer was used to

perform echocardiography on the MAP1S knockout mice in this project.

Echocardiography was performed to assess the heart function, chamber dimensions

and wall thickness in the mice after acute MI, chronic MI and sham surgeries. This

was performed 3 days or 4 weeks after MI to assess the acute and chronic response

to MI in MAP1S knockout mice.

The mice were prepared by removing the hair in the area of measurement. Hair

removal cream was applied to the left hemithorax of the mice. Following this, mice

were induced with 3% isoflurane, and placed on a heat pad before reducing the

anaesthesia to 1% isoflurane with additional oxygen for the Echo measurement.

Ultrasound transmission gel was applied to the chest, and an M-mode image of the

heart was generated in the parasternal short-axis view.

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Cardiac examination was performed by assessing two-dimensional images of the

heart at different levels along both the parasternal long axis and parasternal short

axis. Using the parasternal short axis, several M mode images were recorded at the

level with the largest left ventricular view lying between the papillary muscles and

the bicuspid valve. The M mode images (Figure 2.7) provide a one dimensional view

of the left ventricle over time, which allows the measurement of systolic and

diastolic ventricular parameters and the calculation of cardiac contractility as

shown in Table 2.15.

Figure 2.8. M-mode echocardiography image of the heart. Echocardiography image from parasternal short axis view. Different measurements were taken from this image. Posterior wall (PW), left ventricular internal diameter (LVID) and intra-ventricular septum (IVS) at diastole (d) and systole (s) were used to quantify cardiac function.

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Parameters Formula

Fractional Shortening (FS %) [(dLVD- sLVD/ dLVD)] x 100

Ejection Fraction (EF %) [(EDV-ESV)/EDV] x 100

Left Ventricular Mass (LVM) 1.055 x[(dLVD + dPW + dIVS)3 – dLVD3]

Relative Wall Thickness (RWT) (dIVS + dPW) / dLVD

Table 2.17. Parameters used to analyse cardiac function in sham and MI groups in both genotypes. Note: 1.055 is the specific gravity of the myocardium (g/mL), dLVD: Left Ventricle end-diastolic Diameter, sLVD: Left Ventricle end-systolic Diameter, EDV: end-diastolic volume, ESV: end systolic volume.

2.4. Histological analysis

2.4.1. Tissue fixation with formaldehyde, embedding and sectioning

At the end of MI experiments, mice were sacrificed by cervical dislocation and

whole heart tissue was extracted from the chest cavity and cleaned of blood clots

by washing with DPBS several times. The heart tissue was then dried using blue roll

tissue and weighed to establish heart weight. Following this, the heart tissue was

placed in a bijou tube containing 4% paraformaldehyde (Sigma) for 24 hours in the

cold room under agitation to evenly distribute the fixative. Following this the heart

tissue was placed in a histology cassette to hold it in place during tissue processing.

The cassette was then placed in 70% IMS solution before being transferred to a

Leica ASP300 tissue processor in the Histology facility overnight. The tissue

processor uses different concentrations of industrial methylated spirits (IMS) for

tissue dehydration, as well as xylene and molten-wax. The protocol is shown in

Table 2.16.

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Reagent Time (min) Reagent Time (min)

1. 70% alcohol 20 8. Xylene 20



4. 90% alcohol 60 11. Wax 70

5. 100% alcohol 30 12. Wax 70

6. 100% alcohol 45 13. Wax 70

7. 100% alcohol 60 Proceeded for tissue embedding

Table 2.18. Tissue processing protocols used in this study.

The next day each heart was embedded in paraffin wax. 5μm thick histological

sections were then prepared from 6-8 different levels of the heart starting from the

apex, using an automated rotary microtome (Leica 2255) with 500μm intervals

between each level (Figure 2.8). These were then mounted onto poly-l-lysine-

coated slides (VWR), dried at 37°C overnight and then stored at room temperature

ready for staining as described in the following sub chapters.

Figure 2.9. The method used to section the heart tissue in this study.

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2.4.2. Masson’s Trichrome staining

The assessment of cardiac fibrosis was performed by Masson’s trichrome staining.

Briefly, dewaxed and rehydrated sections were treated in Bouin’s fixative (Sigma)

for 2h at room temperature then washed until clear in tap water. Harris’

Haematoxylin was added to sections for 3 min to stain nuclei. After washing with

water, sections were briefly differentiated in 1%HCl in 70% Ethanol solution and

washed in warm running tap water for 5min. Red solution (each 100ml contains

90ml of 1% w/v Biebrich Scarlet (Sigma) in ddH2O and 10ml of 1% of Fuchsin

(Sigma) in ddH2O was then used to stain muscle for 5min and sections were then

treated with 2.5% (W/v) phosphomolybdic acid (Sigma) for 15min to differentiate

red stain from connective tissue. Next, the collagen was stained with Aniline blue

(Sigma, 2.5% w/v solution in 2% acetic acid) solution for 3 min, and sections then

treated with 1% acetic acid for 2min. All sections were then sequentially

dehydrated in 50%, 75% and 100% ethanol solution for 5 min each. Finally, all slides

were cleared in xylene for 20min and mounted with Eukitt® Quick-hardening

mounting medium (Sigma). Areas of fibrosis were calculated using area

measurement that use total % of fibrosis area in left ventricle divided by total area

of left ventricle in all level.

2.4.3. TUNEL staining

Terminal deoxynucleotidyl transferase mediated nick end labelling (TUNEL), a

specific dye that labels DNA strand breaks, has been widely used to assess

cardiomyocyte death in histological sections (Scarabelli et al. 1999). Dewaxed and

rehydrated sections were incubated with 3% H2O2 for 15min then washed 3 times

in PBS for 10min each. After that, all sections were first incubated in proteinase K

(20ug/ml in PBS, Invitrogen) for 15min at 37°C. A second round of permeabilisation

was performed in a solution containing 0.1% Triton X and 0.1% Sodium citrate for

8min at room temperature. All sections were incubated with TUNEL mixture

containing enzyme solution in 1:20 dilution in labelling agent (Roche) for 1h at 37°C.

All sections were then blocked in 1% BSA for 1h at room temperature followed by

overnight incubation with α-actinin (Sigma, 1:100 in PBS). Secondary Alexa Fluor

647-conjugated anti-mouse IgG antibody (1:100 in PBS) was added to PBS-washed

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sections for 1h at room temperature followed by nuclei counterstaining by 50nM

4’,6’-diamidino-2-phenylindole (DAPI, Invitrogen). The stained sections were

imaged using a ZeissTM fluorescence microscope (Carl Zeiss, Jena, Germany) and

analysed by ImageJ software.

2.4.4. H&E staining

Haematoxylin and eosin staining (H&E) is a common method of staining cells for

histological analysis. This method was used to evaluate the cell size of the

cardiomyocytes to assess hypertrophy induced by cardiac stress. For haematoxylin

and eosin staining, the slides were heated on a heat block for 1 minute, then

immersed in xylene for 5 minutes 3 times to dissolve and remove the excess wax.

Subsequently, the sections were rehydrated using graded concentrations of

industrial methylated spirit (IMS) (100%, 90% and 70%) for 2 minutes in each, then

rinsed under tap water for 5 minutes. After the rehydration, the prepared slides

were immersed in haematoxylin (Sigma) for 5 minutes to stain the nuclei a dark

blue colour. The stained slides were then rinsed under running tap water, followed

by differentiation with acid alcohol (1% HCL in 70% ethanol) for 5 seconds to

decrease non-specific background colouration, and another rinse under running tap

water for 5 minutes. Subsequently, the slides were dropped in eosin (Sigma) for 5

minutes to stain the cytoplasm with a pink colour and rinsed under running tap

water for 5 minutes. The sections were dehydrated using graded concentrations of

IMS (90%, 95%, and 100%) for 2 minutes for each one. Finally, the slides were

cleared in xylene for 5 minutes 3 times and cover slipped after mounting with the

mounting medium DPX Distyrene, plasticizer and xylene (Sigma). The slides were

placed in a fume hood overnight to dry and then the imaging was performed using

the Pannoramic slide scanner (3DHISTECH). For the cross-sectional area

measurement, the Pannoramic Viewer software was used and the mean value of

the size of 100 cells per section was considered.

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2.5. Statistical analysis

All data, presented as mean ± SEM, was first screened under the Shapiro-Wilk

normality test for statistical distribution. Unpaired t-test, one-way ANOVA or two-

way ANOVA followed by Tukey Post-hoc test were used to compare means

between different groups of samples based on specific experimental design. Values

of p < 0.05 indicated statistically significant difference.

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CHAPTER 3

97

3. THE ROLE OF MAP1S IN MODULATING AUTOPHAGIC FLUX IN

CARDIOMYOCYTES

3.1. Background

Autophagy is a vital process responsible for the removal of damaged organelles and

senescence proteins that could otherwise harm the cell.

In this way, autophagy plays a key role in maintaining cellular homeostasis.

Therefore, in the heart, as an organ with a constitutively high energy demand, this

process is crucial. Any condition that leads to homeostatic imbalance in

cardiomyocytes could have severe pathogenic consequences, and thus it is crucial

that autophagy is tightly regulated within the cell.

The role of MAP1S in regulating autophagy has been studied recently. It has been

reported that MAP1S binds to the major autophagy regulator LC3, and this complex

is subsequently translocated to microtubules. MAP1S also interacts with tumour

suppressor RASSF1A and with mitochondrion-associated leucine rich PPR motif

containing proteins (LRPPRC). The latter interacts with the mitophagy initiator

Parkin (Liu et al. 2012; Zou et al. 2013). These interactions suggest that MAP1S may

play an essential role in integrating autophagic machinery and mitochondria with

the microtubules during the formation of autophagosomes. MAP1S also has an

important role in suppressing genome instability and tumorigenesis (Rui et al. 2011;

Zou et al. 2014). Therefore, MAP1S appears to be a key molecule in bridging

microtubules and mitochondria with the phagophore (Liu et al. 2012; Rui et al.

2011). This is an important process during autophagic and mitophagic initiation,

maturation, trafficking and lysosomal clearance (Liu et al. 2012).

Taken together, it is well understood that autophagy is an important process to

maintain cellular homeostasis. MAP1S is a new member of MAP1 family protein

that has been identified to have a role in autophagy (Liu et al. 2012). However, its

specific role in regulating autophagy in the heart is still unknown. Thus, the primary

focus of this chapter is to investigate the role of MAP1S in regulating cardiac

autophagy.

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3.2. Hypothesis

MAP1S plays an important role in regulating autophagy in cardiomyocytes and in

whole heart. Genetic inhibition of MAP1S will alter cardiac autophagy.

3.3. Aims and Objectives

The main aim of chapter 3 is to investigate the role of MAP1S in regulating

autophagy in cardiomyocytes and in the whole heart. Addressing this goal can be

divided into three primary objectives:

• To investigate MAP1S expression in a neonatal rat cardiomyocytes (NRCM)

and cardiac fibroblasts

• To establish genetic inhibition of MAP1S expression in NRCM using a gene

silencing approach

• To investigate the effects of MAP1S genetic inhibition in the regulation of

autophagy in cardiomyocytes and the whole heart

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3.4. Results

3.4.1. MAP1S is expressed in cardiomyocytes and in cardiac fibroblasts

The heart consists of several different types of cells, such as cardiomyocytes,

fibroblasts, endothelial cells and perivascular cells (Zhou & Pu 2017).

Cardiomyocytes constitute around 30-40% of total cellular content by number, yet

occupy 70-80% of the volume of the mammalian heart (Zhou & Pu 2017). Both

myocytes and non-myocytes respond to physiological and pathological stress.

To investigate MAP1S expression levels in two primary cell types in the heart,

Neonatal Rat Cardiomyocytes (NRCM) and neonatal cardiac fibroblasts were

isolated by enzymatic digestion as described in the materials and methods (2.2.4-5).

It has been reported that MAP1S-Heavy Chain (MAP1S-HC) is expressed in many

organs including in the heart (Orbán-Németh et al. 2005). In this study, Western

blot anaysis showed that endogenous MAP1S was expressed both in NRCM and in

cardiac fibroblast (Figure 3.1). It showed both the uncleaved full-length polyprotein

precursor (MAP1S-FL) along with the heavy chain (MAP1S-HC) in both cell types.

The ratio of cleaved to uncleaved MAP1S varied between tissues. The smaller

fragment of the MAP1S protein is the light chain variant (MAP1S-LC). However, this

form of cleaved MAP1S was not observed in our western blot result, presumably

due to its low molecular weight (26kDa).

100

Figure 3.1. MAP1S expression levels in NRCM and cardiac fibroblasts under basal conditions. A. Western blot images indicated that endogenous MAP1S (MAP1S-FL and MAP1S-HC) were expressed in NRCM and cardiac fibroblasts. B-C. Band density analysis showing MAP1S-FL and MAP1S-HC expression in NRCM and cardiac fibroblasts. GAPDH was used as a loading control. n= 3-5 independent experiments, *, p<0.05, **, p<0.005, Student’s t-test.

3.4.2. MAP1S gene silencing in NRCM

In order to investigate the role of MAP1S in cardiomyocyte autophagy, a gene

silencing approach was used to knock down MAP1S in NRCM. Scrambled siRNA was

used as a control. The transfection was performed on day 4 following

cardiomyocytes isolation.

After 72 hours of transfection, protein was extracted and MAP1S expression was

measured by Western blot. As seen in Figure 3.2 below, transfection with 5µM of

MAP1S siRNA was sufficient to achieve around 50% reduction of MAP1S expression.

101

Figure 3.2. siRNA mediated MAP1S gene silencing in NRCM. A. Representative Western blots showing MAP1S expression following transfection with siRNA MAP1S and scrambled siRNA in NRCM. B-C. Band density analysis showing the reduced level (around 50%) of relative MAP1S expression compared to control in siRNA treated cells after normalisation to GAPDH. n= 9 independent experiments, **p<0.005, ****p<0.0001, Student’s t-test (B) and two-way ANOVA, followed by multiple comparison test (C).

3.4.3. Molecular cascade of LC3 activation

Previous studies have revealed that MAP1S is involved in regulating autophagy in

different cell types such as Human Embryonic Kidney (HEK) cell lines, macrophages,

hepatocytes, pancreatic cells, intestinal epithelial cell, and clear renal cell

carcinoma (Bai et al. 2017; Liu et al. 2019; Song et al. 2015; W. Li et al. 2016; Xu et

al. 2015; Yue et al. 2017; R. Xie et al. 2011; Rui et al. 2011). To investigate its role in

regulating autophagy in the heart, MAP1S deficient cardiomyocytes were treated

with autophagic inducer rapamycin (5µM). Rapamycin, a lipophilic macrolide

antibiotic, is commonly used to induce autophagy by mTOR inhibition. Rapamycin

stabilize raptor-mTOR complex and eventually inhibits mTOR kinase activity (Figure

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1.7) (Sarkar et al. 2009). Thus, because autophagy is negatively regulated by mTOR,

hence the inhibition of mTOR will initiate the autophagic flux.

Autophagy may also be modulated by inhibition of the fusion between the

lysosome and autophagosome. Several agents, such as chloroquine, have been

used to block the autophagosome-lysosome fusion and increase the signal of

autophagic flux (Mauthe et al. 2018). Thus, there will be an accumulation of

autophagosomes following rapamycin- chloroquine treatment (Klionsky et al.

2016).

LC3 expression is widely used to monitor autophagic flux (Klionsky et al. 2016).

There are multiple assays to assess autophagy using LC3 as marker. One such assay

involves tagging LC3 with GFP so that it can easily be tracked using fluorescence

microscopy. The formation of GFP-LC3 puncta represents the rate of

autophagosome formation and thus can be used as a reporter to analyze

autophagic flux.

To facilitate efficient gene transfer to cardiomyocytes, an adenovirus carrying GFP-

LC3 contruct was generated. NRCM were treated with AdGFP-LC3 3 days after

transfection with siRNA. Following treatment with rapamycin and chloroquine, cells

were fixed in 4% formaldehyde then the formation of GFP puncta was examined

using fluorescence microscopy.

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Figure 3.3. Higher autophagosome formation in MAP1S-deficient cardiomyocytes. A. NRCM were transfected with siRNA control or MAP1S siRNA for 72 hours prior to the addition of AdGFP-LC3 for 24 hours. All cells were treated with rapamycin (5µM) and chloroquine (3µM) for 2 hours. Immunofluorescence images showing staining of the nucleus by DAPI (blue) and GFP-LC3 puncta (green). Scale bar= 20µm, C= Control, RC= rapamycin+ chloroquine. B. Quantification of average number of GFP-LC3 dots in each cell. ImageJ software was used to analyse the images and data are the mean of 90-100 cells at random vision from 7 independent experiments. Error bar shown is standard error mean (SEM), *** p<0.001, ****p<0.0001, two-way ANOVA, followed by multiple comparison test.

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As presented in Figure 3.3, MAP1S-deficient cardiomyocytes displayed higher

numbers of GFP-LC3 puncta compared to control cardiomyocytes. The difference at

basal level was not statistically significant. However, following rapamycin and

chloroquine treament, the number of GFP-LC3 puncta was significantly elevated

indicating that administration of rapamycin induced and chloroquine blocked

autophagy. Importantly, there was a significant increase in GFP-LC3 puncta

formation in MAP1S-deficient cardiomyocytes (almost two times higher) compared

to control cells. This observation indicates that MAP1S is involved in mediating

autophagy in cardiomyocytes. However, since autophagy is a multistep process and

the rate of autophagic flux should not be determined using a single assay, it still

needs further examination to determine definitively whether this elevation was due

to an increase or decrease of overall autophagic activity.

To analyse LC3 expression levels, western blot analysis of cardiomyocyte protein

lysate was performed. Similar doses of rapamycin (5µM) and chloroquine (3µM)

were used to induce autophagy. In addition, NRCM treated with rapamycin only

were used to analyse the effects of autophagic induction without blocking

autophagosome-lysosome fusion in cells lacking MAP1S. As presented in Figure 3-4,

rapamycin was sufficient to induce LC3 expression levels in both groups. Addition of

fusion blocking agent, chloroquine, further increased LC3II expression levels. LC3II is

the active form of two LC3 isoforms; LC3I (cytosolic form) and LC3II (LC3-

phosphatidylethanolamine conjugate). The amount of LC3II is correlated with the

number of autophagosomes (Mizushima & Yoshimori 2014). Significant elevation of

LC3II expression in MAP1S-deficient cardiomyocytes was found after rapamycin and

chloroquine treatment compared to the untreated MAP1S siRNA group. The

increase in LC3II expression level was also higher in the control group but it was not

statistically significant.

The rate of autophagic flux can be measured by calculating the difference in LC3II

formation before and after treatment. Figure 3.4C shows a significant increase of

LC3II in MAP1S-depleted cardiomyocytes compared to control. The higher

autophagic flux in MAP1S-deficient cardiomyocytes after fusion blocker treatment

might correlate to higher inhibition of autophagosome-lysosome fusion. Elevated

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p62 expression level is also shown in the MAP1S-depleted cardiomyocytes after

fusion blocker treatment compared to control cardiomyocytes. Degradation of p62

is another widely used marker to monitor autophagic activity as p62 directly binds

to LC3 and is selectively degraded by autophagy (Yoshii & Mizushima 2017).

However, the expression level of Beclin, a marker for initial autophagic activity was

not different between MAP1S-deficient and control cardiomyocytes.

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Figure 3.4. Expression of LC3II and other autophagy markers in NRCM. A. Protein lysates were extracted from both siRNA control and MAP1S siRNA cardiomyocytes after 2 hours of C (untreated control), R (rapamycin) or RC (rapamycin and chloroquine) administration. Similar amounts of protein (30µg) were loaded in SDS-PADE electrophoresis and incubated with LC-II, p62 and Beclin antibodies. GAPDH was used as loading control. B-F. Densitometry analysis from LC3II, P62 and Beclin expression level between groups following C (untreated control), R (Rapamycin), and RC (Rapamycin and Chloroquine) administration in both siRNA control and MAP1S siRNA cardiomyocytes . GAPDH was used as loading control. n= 6-9 independent experiments. Data shown as mean ± standard error of the mean (SEM), *, p< 0.05, **, p<0.01, two-way ANOVA, followed with multiple comparison test.

Since our siRNA based silencing of MAP1S in NRCM only managed to reduce

endogenous MAP1S expression by approximately 50%, other cells were used to

confirm the finding. Mouse Skin Fibroblasts (MSF) derived from WT and MAP1S-/-

mice were used for thispurpose. Earsnips from both genotypes were taken and MSF

isolation was performed as described in chapter materials and methods (2.2.5).

After 14 days from the isolation day, the WT and MAP1S -/- MSF were ready to be

used for the experiments (Figure 3.5).

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Figure 3.5. MSF wild type and MSF MAP1S -/- isolation. Ear biopsies from WT and KO mice were used as the source of MSF isolation. Representative images from day 4 and day 14 of MSF isolation. The black area is the earsnip tissue where the fibroblasts originated.

After confirming the MAP1S expression level by Western blot as seen in Figure 3.6,

the cells were given the same treatment as described above to induce autophagy.

Figure 3.6. Derivation of WT and KO MSF from WT and KO earsnips. A. Two different genotypes of mice were used for MSF WT and KO isolation. B. MAP1S Immunoblot from 3 different animals each of genotype.

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To assess autophagic flux, WT and MAP1S-/- MSF were transduced with AdGFP-LC3

for 24 hours. Then, rapamycin and chloroquine were used to induce autophagy.

As shown in Figure 3.7, under basal conditions MAP1S-/- MSF displayed no

significant difference to WT MSF. Rapamycin/chloroquine treated MAP1S-/- MSF

showed significantly higher LC3 puncta compared to rapamycin/chloroquine-

treated WT cells. This was consistent with the finding from experiments using

NRCM.

To further asses the autophagic flux, Western blot was performed to analyse the

levels of LC3II, Beclin and p62. However, contrary to the finding in NRCM, there was

no difference in these proteins’ expression level between MAP1S-/- MSF versus WT

MSF (Figure 3.8).

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Figure 3.7. Higher autophagosome formation in MAP1S deficient MSF. A. MSF WT and KO were transduced with AdGFP-LC3 for 24 hours. All cells were treated with rapamycin (5µM) and chloroquine (3µM) for 2 hours. Immunofluorescence images showing staining of the nucleus by DAPI (blue), and autophagosome puncta (green). Scale bar= 20µm, C= control, RC= rapamycin+ chloroquine. B. Quantification of average number of LC3 dots in each cells. ImageJ software was used to analyse the images and data are the mean of 60- 90 cells at random vision from 4 independent experiments. Data shown as mean ± standard error of the mean (SEM), *, p<0.05, ****, p<0.0001, two-way ANOVA, followed by multiple comparison test.

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Western blot results from both cardiomyocytes and MSF cells also showed no

difference in upstream autophagy protein expression (Beclin), and no difference in

p62 expression levels.

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Figure 3.8. LC3II and other autophagy marker expression levels in MSF. A. Protein lysate was extracted from both MSF genotypes after 2 hours of C (untreated control), R (rapamycin) or RC (rapamycin and chloroquine) administration. Similar amount of protein (30 µg) were loaded in SDS-PAGE electrophoresis and incubated with LC3-II, p62 and Beclin antibodies . GAPDH was used as loading control. B-F. Densitometry analysis from each of the protein markers following C (untreated control), R (Rapamycin), and RC (Rapamycin and Chloroquine) administration in both siRNA control and MAP1S siRNA cardiomyocytes . Beta actin was used as loading control showed no difference between groups. n= 3 independent experiments, Data shown as mean ± standard error of the mean (SEM), two-way ANOVA.

3.4.4. Studies using MAP1S knockout (KO) mice

3.4.4.1. Generation of MAP1S KO mice

MAP1S knockout mice had previously been generated and were kindly

provided by Dr Leyuan Liu (Texas, USA). They were generated using Cre–loxP

transgenic technology which is illustrated in Figure 3.9, by crossing mice with an

insertion of loxP sites flanking exon 4 and exon 5 with Nestin-Cre transgenic mice

which express Cre recombinase in the germline. This resulted in the global deletion

of exon 4 and 5 of the MAP1s gene. Further breeding of these animals resulted in

generation of homozygous mutant mice (MAP1S-/-), MAP1S wild-type mice and

MAP1S +/- mice (Figure 3.10A).

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Figure 3.9. Generation of MAP1S global KO mice. The presence of all exons of the MAP1S gene. The LoxP-Cre recombinase technology was used to delete exon 4 and 5 of this gene, and resulted in MAP1S null gene.

3.4.4.2. Genotype confirmation

To confirm the genotype of these animals, ear tissue biopsies from animal were

taken and PCR genotyping was performed. The PCR will produce WT allele band at

~200bp and knockout allele at ~300bp. Heterozygous mice will produce both fragments

as shown in Figure 3.10B.

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Figure 3.10. Breeding strategy for MAP1S mice. A. Breeding strategy for MAP1S mice. B. PCR results showing the genotype of the animals. PCR genotyping confirmed the presence of MAP1S wild type allele (200kb) and MAP1S KO allele (300kb). Heterozygous mice display both bands.

3.4.4.3. The effect of autophaghic induction in MAP1S WT and KO mice hearts

A recently discovered member of microtubules family, MAP1S has been associated

with maintenance of cell homeostasis through regulation of autophagy. Defective

MAP1S function has been associated with many pathological diseases such as

prostate cancer, renal fibrosis and hepatocarcinogenesis (Li et al. 2016; Xu et al.

2016; Jiang et al. 2015). However, the effect of MAP1S knockout in the heart is not

completely understood.

To investigate the effects of MAP1S ablation in the regulation of autophagy in the

heart, MAP1S-/- mice and their WT littermates were subjected to rapamycin and

chloroquine intraperitoneal injection. After 4 hours, the mice were culled and the

heart tissues were used for molecular and microstructural analyses, the latter using

Transmission Electron Microscopy (TEM).

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To see the extent of autophagy in structural detail, the middle part of MAP1S-/- and

WT heart tissues were fixed, sectioned, and imaged according to the TEM protocols

in the methods section. Early autophagosomal formation was evident in some

instances, as shown in Figure 3.11.

Figure 3.11. Initial formation of autophagosome as shown by TEM. These images were obtained from MAP1S KO treated with rapamycin and chloroquine mice. Scale bar = 1µm.

Interestingly, only MAP1S-/- treated mice exhibited the appearance of

autophagosome structures alongside lysosomes, whereas this was absent from

rapamycin/chloroquine treated WT mice. Considering that accumulation of

autophagosomes and lysosomes might indicate impairment in autophagosome

engulfment, these images could indicate blockage of autophagosome-lysosome

fusion in MAP1S-/- mice (Figure 3.12).

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Figure 3.12. Accumulation of lysosome structures and autophagosomes without autolysosome formation indicates that there was a possible blockage of the autophagosome-lysosome fusion. TEM analysis of MAP1S KO cardiac tissue with an accumulation of lysosome structures (yellow arrows) and autophagosome structures (blue arrows). Scale bars = 1 µm in upper left panel and 500 nm in the right upper panel and the lower panel.

Another prominent structure obtained from the TEM images was the lysosome.

Lysosomes were easier to distinguish from other autophagic vacuoles because their

higher density compared to other vacuolar structures such as autophagosomes.

One possible reason for this is the acidic content of the vacuole. As shown in Figure

3.13 below, rapamycin/chloroquine treatment successfully increased the number of

lysosomes in both groups. Importantly, the number of lysosomes in KO mice after

treatment was significantly higher compared to WT treated mice. This finding

suggests that induction of autophagy with rapamycin and blocking the

autophagosome-lysosome fusion process with chloroquine affected the lysosome

number in the cardiomyocytes.

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Figure 3.13. MAP1S KO mice exhibit more lysosome structures in response to RC Intraperitoneal (IP) Injection. A. TEM representative image of cardiac ultrastructure after 5 hours R (rapamycin) and C (chloroquine) Intraperitoneal (IP) Injection show higher number of lysosome structures in MAP1S-/- mice after treatment. Scale bar = 2µm. B. Quantification of the number of lysosomes in each experimental group. n= 3 mice, *p<0.05, *** p<0.001, ****p<0.0001, data shown as mean ± standard error of the mean (SEM), two-way ANOVA, followed with multiple comparison test.

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Next, to investigate whether the increase in lysosome formation was related to an

increase in autophagic activity, Western blot analysis was conducted to examine

the level of LC3II protein.

Following the autophagic stimulation by rapamycin and fusion blockage by

chloroquine), LC3 expression levels were elevated in both genotypes compared to

basal levels indicating that rapamycin/chloroquine treatment successfully induced

autophagic flux. A similar method was used to measure the rate of autophagic flux

in this animal (Figure 3.14). Apparently, in terms of measuring autophagic flux,

MAP1S-/- mice show higher accumulation of LC3-II expression compare to WT mice.

p62 degradation rate was also lower in this group as the level of p62 expression was

higher compared to WT mice after treatment. However, Beclin expression levels

were not altered, which was consistent with the data from the in vitro model.

Taken together, the in vivo data suggested that: i) there were higher levels of

lysosome formation in MAP1S-/- hearts; ii) there was indication that the

autophagosome and lysosome fusion was reduced in MAP1S-/- hearts; ii) a higher

accumulation of LC3-II and p62 in MAP1S-/- mice was observed. These data

indicated that the phenotype might be due to an impairment of autophagic vacuole

degradation rather than due to an increase in autophagic induction.

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Figure 3.14. Reduction in LC3II expression levels in MAP1S- deletion mice compared to WT control. A. Protein lysate was extracted from each animal’s heart directly after sacrifice. Similar amounts of protein (30 ug) were loaded in SDS-PAGE electrophoresis and incubated with LC3-II antibody. GAPDH was used as loading control. B-C. Densitometry analysis from LC3II/GAPDH following saline (-), rapamycin (Rapa) and chloroquine (Chl) or RC (rapamycin+chloroquine) ip injection showed no difference between groups. n= 9 mice per group, * p<0.05, data shown as mean ± standard error of the mean (SEM), two-way ANOVA, followed with multiple comparison test.

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Figure 3.15. No difference in several autophagy markers after RC administration. A. Protein lysate was extracted from each animal’s heart right after sacrifice of the animal. Similar amounts of protein (30 µg) were loaded in SDS-PAGE electrophoresis and incubated with Beclin, p62, PINK1 antibody. GAPDH was used as loading control. B. Densitometry analysis from each of the protein markers LC3II/GAPDH following saline (-), rapamycin (Rapa) and chloroquine (Chl) ip injection showed no difference between groups. n= 6 mice per group, data shown as mean ± standard error of the mean (SEM), two-way ANOVA, p<0.05 indicates statistical significance.

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3.4.5. The modulation effect of autophagic flux in NRCM’s lysosome

The findings from experiments using MAP1S-/- mice suggest that MAP1S may also

play a role in the fusion of autophagosomes and lysosomes. It emerged from the

TEM analysis that the number of lysosomes (without autophagosomes) was

elevated in mice lacking MAP1S, indicating that MAP1S deficiency may lead to a

reduction in their fusion.

To confirm this finding, an in vitro model using cultured NRCM was used.

Cardiomyocytes were stained with lysosome probe (Lysotracker). Then, the

lysosome formation in response to rapamycin/chloroquine treatment was detected

in MAP1S knock down NRCM and control cells using two different approaches:

fluorescence microscopy and FACS analyses.

Fluorescence microscopy, as shown in Figure 3.16, indicated much higher lysosome

formation in NRCM lacking MAP1S at basal conditions as well as following

rapamycin/chloroquine treatment. Consistently, FACS analysis showed significantly

higher signal intensity from MAP1S-deficient cardiomyocytes after rapamycin and

chloroquine treatment (Figure 3.17). This finding suggests high number of

lysosomes that were not fused with autophagosomes, possibly due to MAP1S

deficiency.

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Figure 3.16. Higher Lysotracker intensity in MAP1S-deficient cardiomyocytes with fluorescence microscope imaging. A. Immunofluorescence images of NRCM stained with Lysotracker Red with or without R (rapamycin), C (chloroquine) treatments. Scale bar = 20µm. B. Quantification of Lysotracker intensities with and without rapamycin/choloquine (Rap/Chl) treatment by ImageJ analysis. n= 4 independent experiments, **p<0.01, ***p<0.001, data shown as mean ± standard error of the mean (SEM), two-way ANOVA, followed with multiple comparison test.

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Figure 3.17. Higher Lysotracker intensity in MAP1S-deficient cardiomyocytes using FACS. A. Lysotracker intensities of NRCM stained with Lysotracker Red with or without R (rapamycin), C (chloroquine) treatments using FACS. B. Quantification of Lysotracker intensities with and without rapamycin/choloquine (Rap/Chl) treatment using FACS median values. n= 3 independent experiment, * p<0.05, data shown as mean ± standard error of the mean (SEM), two-way ANOVA, followed with multiple comparison test.

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3.5. Discussion

Autophagy, as a major catabolic pathway to maintain cell survival, is an important

cellular quality control system. Several different stimuli can trigger autophagy in

order to maintain cellular homeostasis. It consists of several steps that make

measuring this process rather challenging. It is regulated by large number of

proteins including MAP1S. The study described in this chapter was aimed to

investigate the role of MAP1S in regulating autophagy in cardiomyocytes and in the

whole heart.

The expression of MAP1S protein was observed in cardiomyocytes and cardiac

fibroblasts. This protein was observed as uncleaved full length MAP1S polyprotein

precursor (MAP1S-FL), along with its high- chain cleaved form (MAP1S-HC).

However, the smaller part of cleaved-MAP1S fragment, i.e. the light chain (MAP1S-

LC), was not detected via Western blot analysis. This is consistent with previous

studies showing that the primary products of the MAP1S gene in cardiac tissue are

the FL and HC fragments (Rui et al. 2011). The possible reason that MAP1S-LC is

difficult to observe might be due to its lower concentration and its weaker affinity

for the MAP1S antibody compared to HC and FL variants.

The other important finding was that the levels of MAP1S-HC and MAP1S-FL were

varied between cardiomyocytes and cardiac fibroblasts. This evidence resembles

previous results showing that the level of the cleaved and uncleaved forms varies

between tissues (Orbán-Németh et al. 2005). The partial cleavage of MAP1S protein

gives provides some possible explanations. It is possible that the post translational

modification of this protein is regulated in cell specific manner. It could also be

possible that the cleavage of this protein depends on the rate of processes that

utilise MAP1S as one of the regulatory proteins. However, evidence that MAP1S is

expressed in cardiomyocytes and cardiac fibroblasts suggests that it is important to

investigate its role in regulating autophagy in the heart as a whole.

siRNA gene silencing was used as a method to knock down MAP1S expression. This

method was reduced MAP1S expression by ~50%. This reduction was observed in

both uncleaved and cleaved forms of MAP1S. This is consistent with the mechanism

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of siRNA, which inhibits gene transcription and is unlikely to affect post

translational modification of this protein. The ~50% reduction of MAP1S expression

using this method might be due to the type of cell used. It is well known that

transfection efficiency in primary cells is relatively low because of the plasma

membrane barrier, resulting in an inefficient cellular uptake of the siRNA-liposome

structure, or even trapping of siRNA in the endosomal vehicle, thus preventing their

release into the cytoplasm (Pancoska et al. 2004; Harborth et al. 2003). The other

possible factor that may affect gene silencing efficiency is the design of the MAP1S

siRNA, which may not be fully specific to the target gene to have a complete MAP1S

silencing effect (McManus & Sharp 2002; Elbashir et al. 2001; Kurreck 2006). Also,

the long half-life of this protein might be another reason for the partial knockdown

of MAP1S protein. Nevertheless, the ~50% ablation of MAP1S in cardiomyocytes

seems to be sufficient in producing a phenotype related to autophagy regulation.

The effect on autophagy stimulation in MAP1S-deficient cardiomyocytes resembles

those of complete knockout mouse skin fibroblasts. Thus, I believe that the siRNA

gene silencing approach is a valid model to investigate the role of MAP1S in

regulating autophagy.

To further understand the mechanism by which MAP1S regulates autophagic flux in

the heart, several experiments were performed using cardiomyocytes and cardiac

fibroblasts. The higher level of GFP-LC3 puncta formation and expression of LC3II

clearly indicated that there was an accumulation of autophagosomes in MAP1S-

deficient cardiomyocytes. On the other hand, p62 levels can be used as a maker of

autophagic vacuole clearance (Rui et al. 2011). However, this was not observed in

MAP1S-deficient cardiomyocytes, suggesting that the level of clearance of the

autophagosomes was impaired. This profile was not observed in MAP1S-/- MSF,

suggesting that autophagic regulation in skin fibroblasts might be different from

cardiomyocytes.

Findings from MAP1S-/- mice support the in vitro data. In response to

rapamycin/chloroquine stimulation, the increase in LC3-II expression and p62

accummulation was higher in the MAP1S-/- mice. There are two possible

explanations for this phenotype: an increase in autophagosome formation or a

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reduction in autophagosome degradation. TEM analysis showed the presence of

autophagosome structures alongside lysosomes in MAP1S-/- mice. This was not

observed in any wild type TEM images. This indicates that the autophagosome-

lysosome fusion process might be impaired in MAP1S-/- mice. Another finding to

support this theory is the data showing that the lysosome density, as detected by

lysotracker staining (cardiomyocytes) and TEM (knockout mice), was increased in

MAP1S-deficient cardiomyocytes and hearts, indicating that ablation of MAP1S

might affect autophagosome-lysosome fusion.

Conclusions

The main conclusions drawn from studies presented in this chapter are:

1. MAP1S is expressed in the two major cell types in the heart: cardiomyocytes

and cardiac fibroblasts

2. Deficiency of MAP1S results in alteration of autophagy regulation in

cardiomyocytes and in the heart. MAP1S may play a role in mediating fusion

and degradation by lysosomes. Thus, inhibition of MAP1S causes

accumulation of autophagic vacuoles as well as increase lysosomes.

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CHAPTER 4

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4. THE ROLE OF MAP1S IN REGULATING MITOPHAGY

4.1. Background

As an active organ, the heart needs perpetual energy supplies to support its

continuous contraction for sustaining systemic circulation and energy supply

throughout all body systems. As mitochondria are the main organelles responsible

for providing most of the energy, it is not surprising that mitochondria are

abundant in cardiomyocytes and occupy about 23% -32% of myocellular volume

(Murphy et al. 2016). Thus, any perturbation of mitochondrial energy production

could lead to an array of cardiovascular pathologies.

Mitochondria are important organelles that have a broad spectrum of functions,

such as in cellular respiration, metabolism, calcium storage, modulation of

inflammation and cell death initiation (Sun et al. 2017) . Alteration in mitochondrial

function is involved in many pathological conditions in the heart, such as

myocardial infarction, ischaemia-reperfusion injury, chronic pressure overload and

other cardiovascular diseases (Murphy et al. 2016; Sun et al. 2017). A growing body

of evidence supports the correlation between damaged mitochondria and an

increased rate of cellular apoptosis (Hall 1969; Mignotte & Vayssiere 1998; Kuwana

& Newmeyer 2003; Ghavami et al. 2014; Wang & Wang 2017). This is thought to be

brought about when damaged mitochondria lose their membrane permeability in

addition to formation of mitochondrial pore. This will in turn release cytochrome c

into the cytosol and induce apoptotic pathways. Therefore, clearance of these

defective organelles is highly important. One cellular process that is responsible for

selective removal of defective mitochondria is mitophagy.

Mitophagy is one of many selective autophagy processes that have been widely

studied. This mitochondrial-specific type of autophagy is essential for removing

senescent or damaged mitochondria that otherwise could be a source of oxidative

stress (Murphy et al. 2016). It shares the same processes in the latter phase of

macroautophagy (engulfment of the cargo, fusion of the autophagosome to

lysosome and degradation of the cargo), however it has highly specific detection

and selection of the target in the initial stages. It is mainly mediated by the cytosolic

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E3 ubiquitin ligase Parkin, and the mitochondrial membrane kinase PINK1 (Tong &

Sadoshima 2016). PINK1 is rapidly degraded in the inner membrane of healthy

mitochondria. However, PINK1 degradation is supressed when the mitochondrial

membrane becomes depolarized, for example in the condition of mitochondrial

senescense or structural damage (Saito & Sadoshima 2015). PINK1 accumulation in

the outer mitochondrial membrane will lead to the recruitment of Parkin which

ubiquitylates mitochondrial proteins. This in turn will trigger the engulfment of the

autophagosomes to digest and clear the damaged organelle.

It has been suggested that MAP1S plays a role in the modulation of mitophagy.

Recent evidence shows that in addition to the interaction with autophagy protein

LC3, MAP1S also interacts with LRPPRC, which links this complex with mitophagy

initiator Parkin, and to RASSF1A to link the healthy mitochondria for trafficking.

MAP1S was shown to be involved in bridging microtubules and mitochondria, in

autophagic initiation, maturation, trafficking and lysosomal clearance (Rui et al.

2011).

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Figure 4.1. A model on MAP1S interaction with other proteins in bridging healthy mitochondria with microtubules for trafficking, and also damaged mitochondria for autophagosomal clearance with other protein interactions. Adapted from (Liu et al. 2012)

Results presented in chapter 3 indicate that MAP1S has a role in regulating

autophagic flux, potentially in the latter stages of the process (autophagososme-

lysosome fusion). MAP1S deficiency alters the autophagic process and cellular

homeostasis. Given that MAP1S is known to interact with both mitochondrial

proteins and autophagic regulators, in chapter 4 I will focus on investigating the

role of MAP1S in mitophagy, in particular in linking the defective mitochondria to

the autophagic vacuoles.

4.2. Hypothesis

MAP1S plays an important role in mitophagy by bridging damaged mitochondria to

autophagosomes. MAP1S deficiency would reduce mitophagy and eventually

disrupt cellular homeostasis.

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The main aim of this chapter is to investigate whether MAP1S is involved in

modulating mitophagy in cardiomyocytes. To address this goal, there are specific

objectives as outlined below:

To study the effect of MAP1S genetic knockdown on the fusion of

autophagosomes to defective mitochondria in cardiomyocytes

To determine whether MAP1S deficiency alters mitochondrial function in

cardiomyocytes

To investigate the effect of MAP1S knockdown on the initiation of apoptosis as

a consequence of mitochondrial damage in cardiomyocytes

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4.4. Results

4.4.1. MAP1S gene silencing prevents binding of autophagosome with damaged

mitochondria

In the previous chapter, it was found that MAP1S is crucial in linking

autophagosomes with lysosomes. Since binding of the autophagosome to its cargo,

such as damaged mitochondria, is very important and because MAP1S is known to

bind both autophagy regulators and mitochondrial proteins, in this chapter I will

assess the role of MAP1S in mitophagy.

In these experiments, cardiomyocytes were stained with a probe called

MitoTracker, to visualize mitochondria. Two different MitoTrackers were used in

this study: red MitoTracker and green MitoTracker.

First, co-localisation between mitochondria and autophagosomes was studied

during mitophagy. NRCM were transduced with AdGFP-LC3 to track the formation

of autophagosomes. MitoTracker red was used to stain the mitochondria. To induce

mitochondrial damage, NRCM were treated with carbonyl cyanide m-

chlorophenylhydrazone CCCP (10 µM). Rapamycin and chloroquine were also used

to stimulate autophagic flux.

As presented in Figure 4.2, both GFP-LC3 and red MitoTracker were effective in

staining autophagosomes and mitochondria respectively, as indicated by

fluorescence microscopy analysis. Consistent with the data in chapter 3, the

number of GFP-LC3 dots was higher in MAP1S-deficient cardiomyocytes compared

to control. The co-localisation of GFP-LC3 and mitochondria were indicated as the

appearance of yellow dots. Quantification of the co-localized GFP-LC3 and

mitochondria is shown in Figure 4-2. MAP1S-deficient cardiomyocytes displayed

significantly less co-localization of GFP-LC3 and MitoTracker signals compared with

control, indicating that MAP1S deficiency might lead to a reduction in the binding of

mitochondria to autophagosomes (Figure 4.2).

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Figure 4.2. GFP-LC3 co-localisation with Red MitoTracker in NRCMs. A. Representative images showing co-localisation of GFP-LC3 and MitoTracker Red in control and in MAP1S siRNA cardiomyoctes treated with rapamycin+ chloroquine (RC) and carbonyl cyanide m-chlorophenyl hydrazine (CCCP). B. Average number of yellow puncta representing GFP-LC3 and mitochondrial co-localisation in control and MAP1S siRNA treated cardiomyocytes. n= 3 independent experiments, ****p<0.0001, data shown as mean ± standard error of the mean (SEM), Student’s t-test.

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Another method that has been recently developed to monitor mitophagy involves

the use of the fluoresecent protein mt-mKeima. mKeima is a molecular sensor that

is derived from a native coral protein. It has a unique characteristic in that it can

emit different signals as a result of changes in pH. It is resistant to lysosomal

protease, which makes it ideal to monitor autophagososme/lysosome fusion.

(Katayama et al. 2011).

Figure 4.3. Dual excitation of Keima in response to changing environmental pH. The emitted signal from acidic pH will be red, with green representing neutral pH.

Keima has an emission spectrum that peaks at 620 nm, but has two different

excitation spectra, peaking at 420 nm in neutral conditions and 586 nm in acidic

conditions (Figure 4.3). Because of its resistance to acid protease, it cannot be

degraded by lysosomal protease. Therefore, transfection or transduction of this

protein will result in the formation of bright puncta structures in 586 nm

wavelength (red punctate).

The mitochondria localization sequence was linked to the mKeima gene and the

resulting construct cloned into an adenoviral vector to enable efficient transfection

in cardiomyocytes as previously described in chapter materials and methods

(2.2.10).

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Figure 4.4. More red signal emitted from siRNA control cardiomyocytes than in MAP1S-deficient cardiomyocytes. A. Representative images of negative control without viral transduction (upper images), and pAdParkin pAd Keima transduction on cardiomyocytes (lower images), showing more red signal in the control group compared to the MAP1S-deficient group. B. Quantification of average green puncta per cell in control vs MAP1S-deficient cardiomyocytes. DAPI was used to stain the nuclei. Scale bars= 20 µm. Student’s t-test, ****p< 0.0001, data shown as mean ± standard error of the mean (SEM), n= 3 independent experiments.

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Figure 4.4 shows representative images from experiments using mt-mKeima sensor.

NRCM lacking MAP1S and control cardiomyocytes were transduced with adenovirus

overexpressing mt-mKeima to monitor mitophagy, and also with adenovirus

overexpressing Parkin to induce mitophagy. As shown in Figure 4-4, it is apparent

that control cardiomyocytes express a higher ratio of red signal compared to

MAP1S depleted cardiomyocytes. The red signals due to the lower pH indicate

mitochondria that have been engulfed to the autophagosome/lysosome. In

contrast, more green signals were displayed in MAP1S-depleted cardiomyocytes

indicating a possible alteration in mitochondrial fusion with

autophagososmes/lysosomes. These data support the finding from the previous

experiment using GFP-LC3 and MitoTracker staining.

4.4.2. MAP1S gene silencing affects mitochondrial organizational network

Since there were indications of alterations in mitophagy in cells lacking MAP1S, the

next objective was to elucidate mitochondrial structure. Mitochondria are situated

in the cytoplasm in populational arrangement. Using a mitochondrial probe, normal

mitochondrial structure will be shown as network tubulation.

As presented in Figure 4.5, MitoTracker green effectively stained mitochondrial

trabeculation both in control and in MAP1S-deficient cardiomyocytes. Carbonyl

cyanide m-chlorophenylhydrazone (CCCP) was used to induce structural damage to

the mitochondria. CCCP is a protonophore that is widely used as mitochondrial

uncoupler (Kubli et al. 2015; Zhang et al. 2016; Kwon et al. 2011). These effects can

be seen by the loss of tubulation in CCCP-treated cells.

A qualitative observation obtained from this experiment indicated that MAP1S-

deficient cardiomyocytes displayed more fragmentation of the mitochondrial

network following CCCP stimulation compared with control cardiomyocytes.

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Figure 4.5. Increased mitochondrial fragmentation in MAP1S-deficient cardiomyocytes. Representative fluorescence microscopy images from control and MAP1S-deficient cardiomyocytes following treatment with CCCP for 2 hours. Cells were subsequently stained with green MitoTracker to monitor mitochondrial trabeculation. DAPI was used to stain the nuclei. Scale bars = 20 µm.

To further analyse the effects of MAP1S knockdown in regulating the mitochondrial

network, Mouse Skin Fibroblasts (MSF) derived from wild type and MAP1S-/- mice

were used. Using MitoTracker red as a probe to observe the mitochondrial

organizational network and CCCP to induce mitochondrial damage, MAP1S-/- MSF

showed higher levels of mitochondrial fragmentation compared to WT MSF (Figure

4.6). These data strongly support the notion that MAP1S plays major role in

mediating mitophagy.

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Figure 4.6. More apparent mitochondrial network fragmentation in MAP1S-depleted MSF. Representative fluorescence microscopy images from WT and MAP1S-deletion MSF treated with CCCP as mitochondrial uncoupler for 2 hours. Cells were subsequently stained with red MitoTracker to see the mitochondrial network organization and DAPI to stain the nuclei. Scale bars = 20 µm

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4.4.3. MAP1S gene silencing displayed reduced mitochondrial function

To assess whether MAP1S deficiency leads to defective mitochondrial function, real

time mitochondrial respiration was analysed using the Seahorse system. Seahorse

XF analyser is capable of measuring real time Oxygen Consumption rate (OCR) in a

multi-well format. This assay can be performed in living cells, hence it can be used

to measure bioenergetics and the extracellular flux of nutrients and small molecules

in the culture media, in real time (Hill et al. 2009; Ferrick et al. 2008). By adding

specific modulators, this system can assess a particular step or process during

mitochondrial respiration. This requires the use of a specialised kit, the Mito Stress

Test, consisting of 4 modulating agents: Rotenone that can inhibit complex I of the

respiratory chain, Antimycin A that can inhibit complex III and Oligomycin that can

modulate complex V (ATPsynthase), and FCCP to uncouple the mitochondrial inner

membrane and allow for maximum electron flux through the electron transport

chain ETC (Figure 4.7A). In this way, the OCR can be measured and several

parameters can be obtained (Figure 4.7B).

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Figure 4.7. Schematic diagram illustrating the Seahorse XF Cell Mito Stress test experiment. A. Modulation of the respiratory chain using several drugs to modulate mitochondrial respiration in cells, which can be read in real time through the Seahorse XF Analyser. B. The read-out OCR obtained from the assay can be used for OCR parameter analysis.

Following oligomycin injection, the OCR represents the amount of ATP production-

OCR. The balance of the basal OCR comprises O2 consumption due to proton leak

and non-mitochondrial sources. Following FCCP injection, it allows protons

movement across the mitochondrial inner membrane and affects the mitochondrial

membrane potential. It results in increased oxygen consumption and allows the

maximal oxygen consumption that is possible at cytochrome c oxidase (Complex

IV). Thus, the addition of FCCP allows estimation of maximum OCR rate. The

difference between the FCCP-stimulated rate and the basal OCR yields an estimate

of the reserve capacity/ spare respiratory capacity of the cells. Rotenone and

antimycin A are injected to inhibit electron flux through Complex I. This prevents

any O2 from being consumed at Complex IV and thus any oxygen consumption yield

would indicate non- mitochondrial respiration (Dranka et al. 2011).

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Figure 4.8 shows that all the compounds used were able to modulate mitochondrial

respiration, as demonstrated by the reduction in OCR after oligomycin

administration, increase in OCR after Carbonil cyanide p-

triflouromethoxyphenylhydrazone (FCCP) administration and eventually massive

OCR decrease after rotenone and antimycin A administration.

Figure 4.8. OCR traces in response to several compounds. OCR read-out from 6 experimental groups (siRNA control and MAP1S siRNA, in control and treated with rapamycin or H2O2) obtained from Seahorse XF Analyser assay. Oligomycin, an inhibitor for complex V respiratory chain reduced the OCR, similar to rotenone and antimycin A, inhibitors for Complex I and III respectively. FCCP, an uncoupler of the respiratory chain, had an effect on OCR elevation.

However, the response from each of treatment group between control and MAP1S-

deficient NRCMs were different. These differences are presented in Figure below.

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Figure 4.9. OCR in basal state. Traces of OCR of cardiomyocytes transfected with scrambled RNA or MAP1S siRNA under basal conditions, as measured with the XF24 metabolic analyzer by sequential, in port additions of mitochondrial effectors at time points indicated by downward arrows. n= 3 independent experiments with 6 -12 replications in each experiment for each group.

There was no difference in OCR between the untreated control and MAP1S

deficient cardiomyocytes (Figure 4.9). This indicates that under basal conditions,

MAP1S knockdown did not alter mitochondrial function.

Next, rapamycin was used to induce autophagic activity and H2O2 to induce

oxidative stress in NRCM. Both substances can induce molecular pathways that

require high energy demands, which should be reflected on the OCR. As presented

in Figure 4.10A and 4.11A, cardiomyocytes lacking MAP1S showed lower OCR

compared to control cardiomyocytes after rapamycin treatment (Figure 4.10A), and

H2O2 treatment (Figure 4.11A).

Not only the graphs from both treatments showed a similar trend of lower OCR in

MAP1S-deficient cardiomyocytes, some of the parameters taken from the graphs

also support the notion that MAP1S-deficient cardiomyocytes show lower levels of

OCR compared to control (Figure 4.10B, 4.11B).

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Figure 4.10. OCR after rapamycin treatment. A. Traces of oxygen consumption rates (OCR) in cardiomyocytes transfected with scrambled RNA or MAP1S siRNA and treated with 5 µM rapamycin, as measured with the XF24 metabolic analyser. (B) Percentages of basal respiration- linked OCR, ATP-linked OCR, proton-leak OCR, spare respiratory capacity- linked OCR, non-mitochondrial OCR and maximal OCR following 5 µM rapamycin (Rapa) administration. n = 3 independent experiments for each group. *, p <0.05 , data shown as mean ± standard error of the mean (SEM), two-way ANOVA followed with multiple comparison test.

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Figure 4.11. OCR after H2O2 administration. A. Traces of oxygen consumption rates (OCR) of cardiomyocytes transfected with scrambled RNA or MAP1S siRNA and treated with 25µM H2O2, as measured with the XF24 metabolic analyser. (B) Percentages of basal respiration- linked OCR, ATP-linked OCR, proton-leak OCR, spare respiratory capacity- linked OCR, non-mitochondrial OCR and maximal OCR following 25µM H2O2 administration. n = 3 independent experiments for each group. *, p <0.05, data shown as mean ± standard error of the mean (SEM), two-way ANOVA followed with multiple comparison test.

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Taken together, all parameters in both drug administration groups indicated that

MAP1S-deficient cardiomyocytes have lower mitochondrial function compared to

control.

4.4.4. MAP1S gene silencing affects apoptotic pathway

Analysis on NRCM lacking MAP1S suggested that a reduction in MAP1S expression

might lead to alterations in mitochondrial function and structure. In addition to the

reduction of ATP production, damaged mitochondria may trigger apoptosis through

the release of cytochrome c.

Apoptosis is known as caspase-mediated programmed cell death (Figure 4.12).

Apoptosis can either be activated through extrinsic stimuli, via activation of the

death receptor-mediated pathway, or through intrinsic stimuli, via activation of the

mitochondria-dependent apoptosis pathway, as well as the endoplasmic reticulum

(ER) stress-induced apoptosis pathways (Chen et al. 2018). The death receptor-

mediated apoptosis pathway is activated by the binding of the ligand (Fas, TNF-α or

TRAIL) to the corresponding death receptors. Following this, the adaptor protein

FADD and pro-caspase8 form a complex called the death-inducing signalling

complex (DISC). Activated caspase-8 will in turn activate downstream caspases

(caspase-3, caspase-6, caspase-7). Activation of these downstream caspases will

bring about cellular demise by cleaving hundreds of structural and regulatory

proteins (Whelan et al. 2010). While in the intrinsic pathways, upon the disruption

of mitochondrial outer membrane permeability by Bcl-2 family proteins,

cytochrome c combines with Apaf-1 to promote caspase-9 activation, which will

activate downstream caspases and subsequently the effector reaction (Chen et al.

2018).

To assess apoptosis levels in MAP1S-deficient cardiomyocytes, TUNEL assay was

performed. This assay evaluates the apoptotic response in cardiomyocytes, using a

terminal deoxynucleotidyl transferase (TdT) deoxyuridine triphosphate (dUTP) nick-

end labeling (TUNEL) to mark the DNA damage that leads to cell apoptosis.

Cardiomyocytes with siRNA-mediated inhibition of MAP1S expression were treated

with 200 µM H2O2 for 2 hours to induce oxidative stress. TUNEL assay was then

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conducted. Staining of the sarcomeric protein alpha actinin was used to specifically

mark cardiomyocytes

As shown in Figure 4.13, MAP1S-depleted cardiomyocytes showed higher levels of

apoptosis (more TUNEL positive cells) after H2O2 administration compared to

control NRCM.

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Figure 4.12. TUNEL Assays in NRCMs indicated higher apoptosis level in MAP1S-deficient cardiomyocytes. A. Immunofluorescence images showing TUNEL staining in the nuclei of apoptotic cells (green) with co-staining of sarcomeric structure by α-actinin antibody (red) and nuclei by DAPI (blue). Scale bar = 50 µm. B. Quantification of cell death persentage following 200µM H2O2 administration in control siRNA and MAP1S siRNA cardiomyocytes. n=3 independent experiments. *, p <0.05, **, p <0.001, data shown as mean ± standard error of the mean (SEM), two-way ANOVA followed with multiple comparison test.

Since defective mitochondria may induce apoptosis by releasing cytochrome c,

levels of cytochrome c were measured by Western blot. Results shown in Figure

4.15 indicated a strong trend towards increased cytochrome c in MAP1S-depleted

cardiomyocytes after H2O2 treatment.

Caspase-3 is one of the main regulators of apoptosis downstream of cytochrome c.

The expression level of cleaved caspase relative to total caspase-3 can be used as

an indicator of apoptosis levels in cells. In this case, even though the MAP1S-

deficient cardiomyocytes showed no statistically significant difference with the

control group, the observed trend indicated that there were higher levels of

cleaved caspase 3 in MAP1S-deficient cells compared to control (Figure 4.14 A-B).

This indicates an induction of apoptotic pathways in MAP1S-deficient NRCM.

(Figure 4.14 C-D).

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Figure 4.13. Analysis of apoptosis markers indicates higher apoptosis levels in MAP1S deficient cardiomyocytes. A. Protein lysates prepared from control and MAP1S-deficient NRCM treated with H2O2. Western Blot analysis was performed to detect cleaved caspase and total caspase 3 using specific antibodies. GAPDH was used as loading control. n=3 independent experiments. B. Densitometry quantification of protein levels in scrambled siRNA and MAP1S siRNA treated NRCM subjected to H2O2 treatment. C. Protein lysates prepared from scrambled siRNA and MAP1S siRNA subjected to H2O2 treatment were examined by Western Blot for cytochrome c using specific antibodies. GAPDH was used as loading control. n=3 independent experiments. D. Densitometry quantification of protein levels in Scrambled siRNA and MAP1S siRNA subjected to H2O2 treatment. two-way ANOVA statistical test. Data shown as mean ± standard error of the mean (SEM), p <0.05 indicates statistical significance.

As shown in Figure 4.12, there are two major pathways of apoptosis induction: the

intrinsic and extrinsic pathways. The intrinsic pathway is characterized by activation

of apoptotic regulators Bcl-xl, Bax and Bak, which induce the release of cytochrome

c via opening of mitochondrial pores. Thus, these proteins act upstream of the

mitochondria. In order to assess the level of these apoptosis regulators, Western

blot analyses detecting Bcl-xL, Bcl-2, Bad and Bax proteins were performed. Bad and

Bax expression levels were not different between treated control and MAP1S siRNA

groups. The pro survival protein Bcl-2 and pBcl-xL/Bcl-xL were also not significantly

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different in control vs MAP1S-deficient NRCM (Figure 4.15 A-E). Together these

findings suggest that MAP1S inhibition did not affect regulation of apoptosis

upstream of cytochrome c, and the induction of apoptosis might be due to mainly

structural mitochondrial damage as a result of altered mitophagy.

Figure 4.14. Other apoptosis markers were not significantly different between groups. A. Protein lysates prepared from control and MAP1S-deficient NRCM treated with H2O2 treatment were examined by Western Blot for pBcl-xL and total Bcl-xL using specific antibodies. GAPDH was used as loading control. n=3 independent experiments. B. Densitometry quantification of protein levels in Scrambled siRNA and MAP1S siRNA subjected to H2O2 treatment. C-E. Protein lysates prepared from Scrambled siRNA and MAP1S siRNA subjected to H2O2 treatment were examined by Western Blot for Bad, Bax and Bcl-xL using specific antibodies followed by densitometry quantification of protein levels. GAPDH was used as loading control. n=3 independent experiments. two-way ANOVA statistical test. Data shown as mean ± standard error of the mean (SEM), p <0.05 was indicative of statistical significance.

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Another experimental approach used is to see the level of cell viability following

administration of the oxidative stress inducer H2O2. MTT assay was used to assess

cell viability. This assay uses chemical compounds that can be easily quantified by

colorimetric analysis. Detail of this assay has been described in chapter materials

and methods (2.2.15)

As seen in Figure 4.16, H2O2 significantly reduced the viability of MAP1S-deficient

cardiomyocytes viability compared to the untreated group. However, there was no

difference between control and MAP1S deficient cardiomyocytes.

Figure 4.15. MTT assay showed no significant difference in cellular viability after H2O2 treatment in MAP1S NRCM. After transfection with Scrambled siRNA or MAP1S siRNA, cells were treated with normal medium or 200 µM H2O2 and then incubated with MTT for another 2 hours. Colorimetric measurement of formazan product was read at 570 nm. n= 3 independent experiments. *, p <0.05, data shown as mean ± standard error of the mean (SEM), two-way ANOVA statistical test followed with multiple comparison test.

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4.5. Discussion

Mitophagy is an essential process for removing dysfunctional or damaged

mitochondria that otherwise could be a source of excessive oxidative stress

(Murphy et al. 2016). Altered mitochondrial quality control has been associated

with many pathological conditions including cardiovascular diseases (Sun et al.

2017).

Binding between cargo proteins/damaged organelles to the phagophores is

mediated by protein motifs such as the LC3-interacting region (LIR) that must be

present in the cargo or in adaptor proteins. This mediates binding to LC3. The

adaptor proteins such as p62, NBR1, CALCOCO2/ NDP52, OPTN, TAX1BP1 and TRIM

(Levine & Kroemer 2019; Kimura et al. 2016) serve as a bridge to link LC3 to the

phagophore membrane (Levine & Kroemer, 2019). Another protein that has been

identified to bridge the cargo to autophagosomes is MAP1S (Rui et al. 2011; Liu et

al. 2012).

The main finding described in this chapter suggests that MAP1S deficiency affects

mitophagy in cardiomyocytes by alterating mitochondrial binding to

autophagosomes. This is based on the results of two experiments: i) co-localisation

of GFP-LC3 and MitoTracker; and ii) analysis using mt-mKeima sensor in MAP1S-

deficient cardiomyocytes. As co-localisation of GFP-LC3 with the mitochondrial

marker provides a reliable indication that the targeted mitochondria are destined

for autophagic degradation (Cherra et al. 2009; Dolman et al. 2013), the finding

indicates that depletion of MAP1S leads to a reduction in binding between

autophagosomes and damaged mitochondria.

Morphology of the mitochondrial network is complex and varied, and this

organisation is crucial for normal cellular function. Nevertheless, the benefits

underlying this fused network are still poorly understood (Hoitzing et al. 2015;

Rafelski 2013). Under normal conditions, mitochondria exist in dynamic networks

that undergo fusion and fission (Rehman et al. 2012). The findings from this study

identified a more fragmented mitochondrial network in MAP1S-deficient

cardiomyocytes and MAP1S-/- MSF. This finding indicates that the mitochondrial

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network disruption and lower mitochondrial dynamic response (such as fission) to

overcome the high number of damaged mitochondria might be due to altered

mitophagy, as a result of MAP1S deficiency. It is important to remember that

induction of mitophagy or autophagy is crucial in mitochondrial remodelling and

network organisation in order to maintain cellular homeostasis (Walczak et al.

2017).

Mitochondrial oxidative phosphorylation is a crucial process in the generation of

ATP. Electron transfer in this chain reaction enables protons to be pumped into the

intramembranous space from the mitochondrial matrix in order to generate an

electrochemical gradient between the mitochondrial matrix and intermembrane

space. This gradient facilitates the translocation of protons back to the

mitochondrial matrix using ATP synthase. This reaction is coupled with ATP

synthesis from ADP (Murphy et al. 2016). Analysis of mitochondrial bioenergetics in

this study showed relatively lower mitochondrial function in MAP1S-deficient

cardiomyocytes. This might be related to inadequate clearance of damaged

mitochondria, which if accumulated, could alter the mitochondrial respiration

process in the whole cell. This evidence resembled previous studies analysing the

effects of ATG7 deletion in several cell types. The study has linked autophagy failure

with pathophysiology of OCR reduction (Redmann et al. 2017).

Since damaged mitochondria may trigger apoptosis through the release of

cytochrome c, the effect of MAP1S deletion on cardiomyocyte apoptosis was also

evaluated. Apoptosis was significantly increased in MAP1S-deficient

cardiomyocytes, as indicated by TUNEL assay. This finding agrees with previous

studies that correlate MAP1S-silencing with higher levels of apoptosis (Bai et al.

2017). Analysis of downstream apoptotic markers such as cleaved caspase3 and

cytochrome c showed a trend towards increased expression in MAP1S-depleted

cardiomyocytes. However, expressions of apoptosis regulators upstream of

mitochondria (Bad, Bax, Bcl2 and Bcl-xL) were not different between MAP1S-

deficient myocytes and control, suggesting that MAP1S might not regulate the

intrinsic pathway of apoptosis upstream of mitochondria. However, a previous

study indicated that MAP1S may regulate apoptosis through Wnt-beta catenin

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pathway (Bai et al. 2017). Therefore, further investigation into the potential

involvement of the Wnt-beta catenin pathway is important to further understand

the regulatory role of MAP1S in this context.

Conclusions

In conclusion, results shown in this chapter suggest that MAP1S plays important

role in mediating cardiomyocyte mitophagy, likely by bridging defective

mitochondria to autophagosomes. MAP1S deficiency may lead to alterations in

mitochondrial function and the induction of apoptosis.

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CHAPTER 5

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5. THE EFFECTS OF MAP1S GENETIC ABLATION DURING MYOCARDIAL

INFARCTION

5.1. Background

MAP1S is a newly identified member of the MAP1 protein family. As previously

described in chapter 1, this protein is expressed not only in the neuronal system but

also in other tissues, such as the lung, heart, liver, testis, kidney and spleen (Orbán-

Németh et al. 2005). Previous studies have linked this protein with autophagy.

MAP1S bridges autophagic components with microtubules and mitochondria to

modulate autophagosomal biogenesis and degradation (Rui et al. 2011).

Several studies have shown deleterious effects of MAP1S gene deletion, both in

mouse models and in human tissues (Xu et al. 2016; Jiang et al. 2015; Wu et al.

2016). For example, increased fibronectin deposition is observed in MAP1S

depleted liver and kidney. The deletion of MAP1S causes impairment of fibronectin

degradation through the autophagy-lysosome system. This condition promotes

renal and liver fibrosis and eventually reduces their life span (Xu et al. 2016; Wu et

al. 2016).

As an organ that really depends on a continuous ATP supply, maintaining

mitochondrial quality is very important in the heart. Autophagy is believed to be an

important system responsible for the mitochondrial quality control process. Since

accumulation of damaged mitochondria often occurs in the heart following

pathological stimuli, any perturbation in autophagy could affect cellular

homeostasis and could eventually trigger other adverse responses that can harm

the cell.

This chapter focuses on studying the role of MAP1S in regulating autophagy and

mitochondrial quality control in the heart in vivo during pathological conditions

such as myocardial infarction (MI).

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5.2. Hypothesis

MAP1S plays an important role in regulating autophagy and mitophagy. Deletion of

this gene will produce detrimental effects in mouse hearts following stress

stimulation (myocardial infarction).


The aim of this chapter is to elucidate the role of MAP1S in the heart during

myocardial infarction. Specific objectives include:

To assess MAP1S expression levels in the heart in pathological conditions

To assess overall survival of MAP1S-/- mice at the chronic (4 weeks) and acute

(3 days) phases of MI

To investigate cardiac function in MAP1S-/- mice at chronic (4 weeks) and acute

(3 days) phases of MI

To investigate cardiac remodelling in MAP1S-/- mice at chronic (4 weeks) and

acute (3 days) phases of MI

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5.4. Results

5.4.1. Expression of MAP1S in mouse model with pathological condition in the

heart

To investigate MAP1S expression levels in the mouse heart in response to several

pathological stimuli, protein extracts from acute MI and chronic TAC models were

used. These samples were kindly provided by Dr Delvac Oceandy and Dr Nicholas

Stafford. Western blot analysis to detect MAP1S expression showed that there was

an upregulation in MAP1S expression in the heart following MI or TAC stimulation.

Figure 5.1. MAP1S cardiac expression levels in following TAC-stimulation for 5 weeks. A. Western blot from WT Sham and 5 weeks TAC. Protein lysates were kindly provided by Dr Oceandy from his previous work. Western blot was performed using MAP1S antibody. Alpha tubulin expression was used as loading control. B-C. Densitometry analysis to assess MAP1S expression levels between groups. Results presented as mean ± SEM, *p<0.05, Student’s t test, n= 5-9 animals.

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It has been reported that MAP1S is initially translated as a full length (FL) protein

precursor and then cleaved to produce the active high chain (HC) and light chain

(LC) variants in a tissue-specific manner (Orbán-Németh et al. 2005). In the chronic

TAC model, MAP1S HC expression was significantly elevated, whereas the

uncleaved MAP1S FL was not changed (Figure 5.1).

In keeping with the finding above, MAP1S expression was also elevated in

response to MI. However, in this model elevation of both FL and HC forms was

observed (Figure 5.2). These results indicate that MAP1S might be involved in

regulating cardiac response to pathological stimuli.

Figure 5.2. Higher MAP1S expression levels were observed in WT mice following acute MI compared to sham operated mice. A. Western blot from acute MI mice. Protein lysates were kindly provided by Dr Nicholas Stafford from his previous work. Western blot was performed using MAP1S antibody, and Alpha tubulin was used as loading control. B-C. Densitometry analysis from MAP1S expression level between groups. Results presented as mean + SEM, *p<0.05, Student’s t test, n= 5 mice.

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5.4.2. Analysis of MAP1S-/- cardiac phenotype after 4 weeks of MI

5.4.2.1. Overall survival at 4 weeks after MI

To investigate the role of MAP1S under cardiac pathological conditions, MAP1S-/-

mice were analysed following MI. MAP1S-/- mice and their WT littermates were

subjected to MI using methods as described in chapter materials and methods

(2.3.3)

To determine whether MAP1S deletion has an impact on survival after MI, Kaplan -

Meier analysis was performed. A Log rank test was used to determine if there were

any significant differences in the survival distribution for the different groups of

mice. Survival rates in four experimental groups were significantly different (Figure

5.3). Notably, it was found that less than 50% of MAP1S-/- mice survived until the

end point.

Figure 5.3. Kaplan-Meier analysis to assess mouse survival following MI.

5.4.2.2. Cardiac Function and structure

To assess cardiac function, morphology and structure, transthoracic

echocardiography was performed at the end of the experiments (4 weeks after

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TAC). Ejection fraction (EF) and Fractional Shortening (FS) were used as parameters

to assess cardiac function. As seen in Figure 5.4, both EF and FS were significantly

reduced in MI groups from both genotypes compared to sham operated controls.

However, there was no difference in EF and FS between wild type and MAP1S-/-

sham.

Figure 5.4. Reduced cardiac function in both genotypes after 4 week MI. Two parameters to show cardiac function were used, (A) Ejection Fraction (EF) and (B) Fractional Shortening (FS). The graphs showed significant reduction in cardiac function in both genotypes after 4 week MI compared to sham operated controls. However, the reductions were not significant in MI operated mice between both genotypes. Data shown as mean ± standard error of the mean (SEM), two-way ANOVA followed with multiple comparison test., ***, p< 0.001, ****, p< 0.0001, n= 4-9 animals.

Other echocardiography data were used to measure cardiac structure, such as

diastolic Left Ventricular Diameter (dLVD) and systolic Left Ventricular Diamater

(sLVD). There were significant changes in the elevation of dLVD and sLVD 4 weeks

post MI in wild type mice compared to sham operated controls, whilst these

changes were not significant in MAP1S-/- mice after 4 weeks MI compared to the

sham control. Left Ventricular Mass over Body Weight (LVM/BW) ratio also showed

similar trend but it did not reach statistical significance (Figure 5.5).

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Figure 5.5. Left ventricular structures are more responsive to hypertrophy induction in WT mice compared to MAP1S-/- mice 4 weeks post MI. The increase of left ventricular mass (A), left ventricular diameter both in diastole (B) and systole (C) after 4 weeks MI are more apparent in the WT group compared to the MAP1S deficient mice group. Left Ventricular Mass (LVM), Body Weight (BW), diastolic Left Ventricular Diameter (dLVD), systolic Left Ventricular Diamater (sLVD). data shown as mean ± standard error of the mean (SEM), two-way ANOVA followed with multiple comparison test., *, p<0.05, **, p< 0.01, n= 4-9 animals.

The Table 5.1 summarizes echocardiography parameters from the four groups of

experiments. All parameters show no significant differences between the two MI

groups.

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Table 5.1. Echocardiography parameters taken from 4 experimental groups at 4 weeks post MI or sham surgery. There are no significant changes in wall thickness and chamber size parameters. Wall thickness parameters: dIVS: diastolic interventricular septal thickness, sIVS: systolic interventricular septal thickness, dLVPW: diastolic LV posterior wall thickness, sLVPW: systolic LV posterior wall thickness, RWT: relative wall thickness, LV mass/BW: left ventricular mass/ body weight. Chamber size parameters: dD: left ventricle diastolic diameter, sD: left ventricle systolic diameter. Data presented using two-way ANOVA, n= 4-9 animals.

5.4.2.2.1 Evaluation of Scar Size after 4 weeks MI

Histological measurements of the infarcted area in cardiac tissue sections from

acute and chronic MI can be used as a standard approach to determine the infarct

size (Takagawa et al. 2009).

Paraffin embedded sections from each animal were stained with Masson’s

trichrome, and the scar sizes were measured in 5-7 different levels of cardiac

sections. An area-based measurement approach on the transverse heart section

was used, and the result was quantified as the percentage of infarct area

normalised to the total myocardial area observed. The area-based measurement

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approach is not an ideal approach to measure the infarcted area as it has been

reported to have a range of decompressed infarct size values, equating to

approximately 0.4 fold, compared to using the length measurement approach

(Takagawa et al. 2009). However, in my experiments the majority of scar area

observed was not transmural. Hence, the length-based measurement approach

cannot be used.

As can be seen in Figure 5.6A and 5.6B, scar area was apparent in the MI model

from both genotypes compared to sham controls. Representative images from 4

groups showed that there were no significant differences in the infarct size

between the MI groups. To confirm that there were similar levels of MI injury at the

initial stage of the experiments, plasma cTnI levels were measured. The plasma was

collected at day 1 post MI. As can be seen in Figure 5.7C, there were no significant

differences in plasma cTnI values between the genotypes, confirming that the MI

surgery procedure gave comparable injury levels in both genotypes at the initial

stage of MI.

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Figure 5.6. Infarct size measurement in MAP1S-/- mice and wild type controls after 4 weeks. A. Representative images of Masson’s trichrome staining in heart tissues from 4 experimental groups. B. Infarct size analysis from each group using area based measurement approach. C. cTnI values taken from tail vein at 24 hours post operation. *, p< 0.05, ****, p<0.0001; data shown as mean ± standard error of the mean (SEM), two-way ANOVA followed with multiple comparison test, n= 4-9 animals.

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5.4.2.2.2 Evaluation of hypertrophic response

Left ventricular remodelling is a process by which ventricular size, shape and

function are regulated to cope with different pathological stimuli affecting the

heart. The triggers could affect biochemical signalling processes that modulate

reparative changes, which include hypertrophy, dilatation and scar formation.

Hypertrophy is an adaptive response post-infarction to compensate for the increase

in cardiac load, to prevent from progressive dilatation and to stabilise cardiac

contractile function (Sutton & Sharpe 2000).

To assess the hypertrophic response 4 weeks following MI, the Heart Weight (HW),

Body Weight (BW) and Tibia Length (TL) from mice in all 4 experimental groups

were measured. As shown in Figure 5.7, MAP1S-/- mice showed reduced

hypertrophic response at 4 weeks following MI as indicated by analysis of HW/TL

and HW/BW ratios.

Figure 5.7. Analysis of cardiac size at 4 weeks post-MI. A. Heart Weight (HW) over Tibia Length (TL) and B. Heart Weight (HW) over Body weight (BW) ratio showed similar pattern of lower hypertrophic response in MAP1S-/- mice compare to wild type at 4 weeks after MI. Data shown as mean ± standard error of the mean (SEM), two-way ANOVA followed with multiple comparison test., *, p<0.05, **, p< 0.01, n= 4-9 animals.

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To further analyse the hypertrophic response, paraffin sections from 4 groups of

mice were stained with Haematoxylin Eosin and the cross-sectional cardiomyocyte

size was measured. For each mouse a mean value derived from 100 cells was

obtained.

As presented in Figure 5.8. the average cell size in the MI-operated groups was

bigger than in the sham control group. The Wild type MI- operated group showed a

significant increase in cardiomyocyte size, especially in the infarct border zone,

compared to sham control, whilst this was not observed in the MAP1S-/- MI group

(Figure 5.8C).

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Figure 5.8. Less hypertrophic response in MAP1S-/- mice after chronic MI. A. Representative images of average cell size from H&E staining from wild type sham and MI, MAP1S-/- sham and MI. B. Average cell size from 4 groups shows that less hypertrophic response was observed from MAP1S-/- mice after 4 weeks of MI. C, D. Cell size was analysed from random areas in sham operated groups as well as from the infarct border zone (BZ) and Remote Region (RR) in MI groups as shown in yellow box in the representative images in the lower panel. Data was analysed using two-way ANOVA followed with multiple comparison test, *, p<0.05, ***, p< 0.001, n= 4-9 animals.

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5.4.2.3. Analysis of apoptosis level at 4 weeks post-MI

To evaluate the apoptotic response in the chronic phase post-MI, terminal

deoxynucleotidyl transferase (TdT) deoxyuridine triphosphate (dUTP) nick-end

labelling (TUNEL) assay was performed on transverse heart sections from wild type

and MAP1S -/- mice, and the number of apoptotic cells was assessed as described in

chapter materials and methods (2.4.3)

Cardiomyocyte apoptosis was elevated in wild type and MAP1S-/-mice post chronic

MI compared to sham operated controls, with significantly higher levels observed in

MAP1S-/- mice compared wild type counterparts. This is presented in Figure 5.9.

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Figure 5.9. Apoptosis assessment by TUNEL assay at 4 weeks post MI. A. Representative images from the four experimental groups are shown. TUNEL (green, indicated by the yellow arrows) detects DNA fragmentation in the nuclei of the cells undergoing apoptosis. Nuclei are also stained with DAPI (blue). Cardiomyocytes are stained with α-actinin (red). Scale bars = 50 μm. B. Analysis of TUNEL positive nuclei from all groups. Results are shown as mean ± SEM; p**< 0.001; two-way ANOVA followed with multiple comparison test, n= 4-5 animals.

5.4.3. Analysis of heart phenotype at 3 days post MI

5.4.3.1. Overall survival at 3 days post- MI

Since more than 50% of the MAP1S-/- mice died in the first week after of surgery,

starting from day 3 – day 5, MI experiments focusing on analysing phenotypes at 3

days post-MI were conducted. A similar surgery procedure was used, but with a

shorter period of time. This procedure is described in chapter 2.

By the end of day 3, only few mice died and there was no difference between wild

type and MAP1S-/- mice.

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5.4.3.2. Cardiac Function and structure

Transthoracic echocardiography was used to analyse cardiac function and structure

at day 3 after MI in all groups. Cardiac function, as indicated by EF and FS values,

was significantly reduced at 3 days post MI in both genotypes compared to the

sham control. When comparing between WT-MI vs MAP1S-/- MI group, there was a

trend towards reduced in EF and FS (p values of 0.067 in EF and p values of 0.08 in

FS) (Figure 5.10).

Figure 5.10. Reduced cardiac function in both genotypes 3 days post MI. Two parameters to show cardiac function were measured; A. Ejection Fraction (EF) and B. Fractional Shortening (FS). The graphs show significant reduction in function in both genotypes after 4 weeks MI compared to their sham controls. The reduction was more significantly apparent in MAP1S-/- mice 3 days post MI compared to sham operated controls. Data were analysed using two-way ANOVA followed with multiple comparison test, *, p< 0.05, ****, p< 0.0001, n= 4-7 animals.

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The other echocardiography parameters measured showed no significant

differences between wild type and MAP1S-/- mice 3 days post MI, as shown in Table

5.2 below.

Table 5.2. Echocardiography parameters taken from 4 experimental groups 3 days post MI / sham surgery. There are no significant changes in wall thickness and chamber size parameters. Wall thickness parameters: dIVS: diastolic interventricular septal thickness, sIVS: systolic interventricular septal thickness, dLVPW: diastolic LV posterior wall thickness, sLVPW: systolic LV posterior wall thickness, RWT: relative wall thickness, LV mass/BW: left ventricular mass/ body weight. Chamber size parameters: dD: left ventricle diastolic diameter, sD: left ventricle systolic diameter.

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Figure 5.11. Left ventricular structure showed no difference between 4 experimental groups 3 days post MI. Diastolic Intra Ventricular Septum, dIVS (A), systolic Intra Ventricular Septum, sIVS (B) after 3 days of MI showed no difference between sham and MI operated animals. Increased (but not statistically significant) Left Ventricular Mass/ Body Weight, LVM/BW, are observed in both MI operated mice compare to sham controls (C). Data shown as mean ± standard error of the mean (SEM), two-way ANOVA followed with multiple comparison test, n= 4-7 animals.

5.4.3.3. Evaluation of scar size after 3 days of MI

To assess whether ventricular remodelling occurred 3 days post MI, a scar area

measurement was performed. Scar formation in the acute phase of MI is part of

ventricular remodelling. Figures 5.12 show a significant difference in scar size was

observed in post-MI groups compared to the sham-operated groups in both

genotypes.

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Figure 5.12. Infarct size measurement shows significant increase in infarct size in MI operated wild type and MAP1S-/- mice compared to their sham operated controls. A. Representative images from 4 experimental groups. B. Infarct size analysis from each group using area based measurement approach. C. cTnI values taken from tail vein 24 hour post operation. Results are shown as mean ± SEM; ***, p< 0.001; two-way ANOVA followed with multiple comparison test, n= 4-9 animals.

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5.4.3.4. Evaluation of hypertrophic response

To further assess ventricular remodelling in terms of hypertrophic response,

Haematoxylin and Eosin staining was performed on transverse heart sections,

followed by the measurement of the cardiomyocyte cross-sectional area. For each

mouse a mean value from 100 cells was obtained.

As shown in Figure 5.13, the average cell size of MI operated mice increased, but

this was not significant compared to sham-operated mice. When the area of cell

size measurement was divided into a Border Zone (area near the infarct site) and a

Remote Region (area distant from the infarct site), a significant increase was more

apparent in the wild type MI operated group compared to sham controls, while this

was not observed in the MAP1S-/- mice MI group (Figure 5.13C).

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Figure 5.13. Cardiomyocyte cross sectional area assessment using Haematoxylin Eosin staining from four different groups after 3 day MI. A. Representative image of the histological sections for the cardiomyocyte cross-sectional area from each group; scale bars are 50 μm area for each group. The lower panel shows (D) two different area of measurements, Border Zone (BZ), the area near the infarct zone, while the Remote Region (RR) is a distant area from the infarct zone as indicated with the yellow boxes. B. The mean size of 100 cells was calculated for each section using Panoramic Viewer software and the graph presenting the mean cell sizes for each group generated. Results are shown as mean ± SEM; *, p< 0.05; two-way ANOVA followed with multiple comparison test, n= 4-5 animals.

5.4.3.5. Measurement of apoptosis at 3 days post-MI

To evaluate the apoptotic response in the acute phase post-MI, a terminal

deoxynucleotidyl transferase (TdT) deoxyuridine triphosphate (dUTP) nick-end

labeling (TUNEL) assay was performed on transverse heart sections from wild type

and MAP1S-/- mice, and the number of apoptotic cells was assessed as described in

chapter materials and methods (2.4.3)

There was a highly significant increase in TUNEL positive nuclei in MAP1S-/- mice

after 3 days of MI, and this elevation was also significantly higher than that seen in

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their wild type counterparts (Figure 5.14). This might indicate that the ablation of

MAP1S could affect left ventricular remodelling and increase the rate of apoptosis.

Figure 5.14. Apoptosis assessment by TUNEL assay at 3 days post MI. A. Representative images from the four experimental groups are shown. TUNEL (green, indicated by the yellow arrows) detects DNA fragmentation in the nuclei of the cells undergoing apoptosis. Nuclei are also stained with DAPI (blue). Cardiomyocytes are stained with α-actinin (red). Scale bars = 50 μm. B. Analysis of TUNEL positive nuclei from all groups. Results are shown as mean ± SEM; **, p< 0.001; ****, p< 0.0001; two-way ANOVA followed with multiple comparison test, n= 4-5 animals.

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5.5. Discussions

This chapter is focused on examining the effects of several pathological inductions

in the heart using in wild type and MAP1S-/- mice. The experiments were conducted

using several pathophysiological inductions inclusing 5 week TAC (samples were

provided), 4 weeks MI and 3 days MI.

The upregulation in MAP1S expression after TAC and acute MI in wild type mice

indicates that this protein may have a role in the cardiac pathophysiological

response to stress, that resembles previous studies using different stress stimuli

(Rui et al. 2011). There was a difference in the pattern of increased MAP1S

expression between TAC and MI models. In the TAC model, only the HC fragment

was upregulated, whereas in MI model, both the precursor (FL) and HC fragments

of MAP1S were elevated. This may indicate different mechanisms of upregulation,

i.e. in the TAC model, the overexpression might be due to modification of post-

translational processing, whereas in the MI model, the level of MAP1S protein

translation that might be affected. Analysis of mRNA levels is important to

understand whether mRNA expression at transcriptional level is also affected.

Unfortunately, the mRNA samples for this analysis were not available.

Since MAP1S is essential in mediating autophagy and mitophagy, it is possible that

the increased expression of this protein is an adaptive response designed to induce

autophagy and mitophagy to remove protein aggregrates, damaged protein and

dysfunctional mitochondrial that accumulate in the heart following pathological

stimuli (Maejima et al. 2015).

Using MI as a stimulus to induce stress response in the heart, it was found that

MAP1S-/- mice showed lower survival rate compared to the wild type mice. Death in

the acute phase post-MI was mainly due to Left Venticular (LV) rupture, pulmonary

oedema, LV dilatation or massive infarct size (Hochhauser et al. 2007). Cardiac

rupture is the most drastic and severe complication of acute MI. A previous study

has reported that cardiac apoptosis contributes significantly to cardiac rupture

(Matsusaka et al. 2006). Thus, analysis of apoptosis levels at both acute (3 days) and

chronic (4 weeks) phases post-MI is very important. Data shown in Figures 5.9 and

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5.14 confirm that the cause of high mortality in MAP1S-/- mice after MI might be

due to high level of cardiomyocyte apoptosis that eventually induces cardiac

rupture. High levels of apoptosis might relate to the impairment of the cellular

response to remove damaged mitochondria and subsequent accumulation of

oxidative stress products as consequences of homeostatic imbalance. However,

several additional experiments need to be done to validate this possible

mechanism.

Transthoracic echocardiography is routinely used to characterise the left ventricular

remodelling process. The most common parameters used to measure cardiac

function are Fractional Shortening (FS) and Ejection Fraction (EF) (Benavides-Vallve

et al. 2012). The massive reduction in EF and FS in the acute phase post MI indicates

severe maladaptive response in MAP1S-/- mice. Considering the high level of

apoptosis observed in MAP1S-/- mice following MI, it is possible that the reduction

of the cardiac function is caused by high levels of apoptosis. Relatively improved

cardiac function observed in the chronic phase in wild type and MAP1S-/- mice,

which also correlates with the lower levels of apoptosis compared to the acute MI

group, might be due to the adaptive ventricular remodelling that has been shown

to occur.

The loss of myocytes in the early hours post infarct also may affect the non-

infarcted area of the heart. Interesting evidence was observed in the hypertrophic

response of MAP1S-/- mice following MI. Analyses of HW/BW and HW/TL ratios

suggested a lower hypertrophic response in MAP1S-/- mice. As hypertrophy is one of

the adaptive responses to pathological stimuli, impaired hypertrophic response in

MAP1S-/- might indicate the importance of MAP1S in modulating cardiomyocyte

hypertrophy. Deletion of this protein leads to impairment of the hypertrophic

response post MI surgery. However, the details of the downstream molecular

pathways regulated by MAP1S that are involved in mediating hypertrophy remain

to be elucidated.

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Conclusions

Evidence from MI experiments show that deletion of MAP1S leads to increased

cardiomyocyte death, thereby increasing the chance of left ventricular rupture,

leading to high numbers of deaths following MI-surgery. Since MAP1S regulates

autophagy and mitophagy (as shown in chapter 3 and 4), the increase in

cardiomyocyte apoptosis in MAP1S-/- mice might be associated with an impaired

autophagy/mitophagy process. However, further studies need to be done to prove

this hypothesis. In addition, MAP1S ablation also led to impaired hypertrophic

response post-MI. This finding indicates that MAP1S may also play a role in the

regulation of cardiac hypertrophy.

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CHAPTER 6

General Discussion

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6. GENERAL DISCUSSION

Myocardial infarction is a major health problem worldwide. Despite advances in its

treatment, the prevalence of heart failure, one of the major long term

consequences post-MI, remains high. Investigating mechanisms to delay or even

reverse the development of heart failure post-MI remains one of the major focuses

of research.

Autophagy is known as a cell survival mechanism. In basal conditions, autophagy is

essential in maintaining cellular homeostasis. It is considered as an intracellular

recycling process to recycle some of the damaged organelles, proteins, and lipids.

Organelle-specific degradation, also called selective autophagy, occurs and is

named based on the organelle being degraded. Mitophagy is a selective form of

autophagy that is very important in the field of cardiac biology; this is due to the

importance of the mitochondrial function as an energy generator to produce ATP in

the heart and in cardiomyocytes.

MAP1S is understood to play a major role in autophagy and mitophagy by bridging

the autophagosome to the mitochondria. Its role in autophagy has been reported in

many studies; however, the role of MAP1S in the heart is still unknown.

The major aim of this project is to investigate the role of MAP1S in regulating

autophagy in the heart. Several in vitro and in vivo experiments were performed in

order to test the hypothesis that MAP1S regulates autophagy and mitophagy in the

heart. The findings are discussed below.

As previously reported, MAP1S is expressed in many tissues with differential

isoform expression (Orbán-Németh et al. 2005; Rui et al. 2011). Using neonatal rat

cardiomyocytes and cardiac fibroblasts, it was shown that MAP1S is expressed in

these two main cell types in the heart. The variation of MAP1S-FL and MAP1S-HC

expression levels between cardiomyocytes and cardiac fibroblasts indicates that

there might be a different regulatory process at the post-transcriptional or post-

translational level in different cell types.

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Considering that MAP1S has been reported to have a role in regulating autophagy,

evidence of MAP1S expression in cardiomyocytes and cardiac fibroblasts suggests

that it is important to investigate its role in regulating autophagy in the heart.

As described in the introduction, autophagic flux is defined as a rate of autophagic

activity from the formation of the autophagosome up to its degradation. This

illustrates the whole autophagy process. The evidence observed in this study

suggested that autophagic flux was altered in MAP1S depleted cardiomyocytes

after stimulation with rapamycin and block with chloroquine.

The significant increase in GFP-LC3 puncta formation and the increase in LC3II

expression in MAP1S depleted cardiomyocytes might indicate that MAP1S

inhibition either increases autophagic initiation or inhibits autophagosome

degradation (Mizushima et al. 2010). The increasing number of GFP-LC3 puncta can

be caused by not only an increase in autophagosomal formation, but also by a

reduction in autophagosomal degradation (Klionsky et al. 2016; Mizushima et al.

2010). The finding that the level of p62 was preserved in MAP1S deficient cells

might indicate that the phenotype was due to deterioration in the degradation

phase. This is because the level of p62 represents the amount of aggregated

proteins and dysfunctional organelles accumulated in the cells (Rui et al. 2011).

Thus, unchanged levels of p62, as indicated in Figure 3.4E, suggests an incomplete

autophagy process in MAP1S deficient cells. Also, the expression of Beclin, an

indicator of autophagic initiation, was not different between the MAP1S depleted

cardiomyocytes and control cardiomyocytes. Together, these findings indicate that

MAP1S may not regulate the initiation phase of autophagy, but its depletion is

more likely to affect the degradation of autophagosomes.

Furthermore, evidence from fluorescence microscopy and FACS analysis using

lysotracker dye indicates that there is an alteration in the later step of autophagy

upon MAP1S depletion. The reason for this might be related to the impairment of

autophagosome-lysosome fusion, which results in an increased number of

autophagosomes (as seen by the GFP-LC3 puncta) and an increased lysotracker

density (as seen in the lysotracker images and FACS).

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Taken together, the evidence shown in this study indicates that the deletion of

MAP1S in cardiomyocytes alters autophagic flux. There is an indication of

impairment in autophagososme-lysosome fusion rather than alterations in the

initiation of autophagy.

Data presented in chapter 3 show that MAP1S is expressed in the heart and in

cardiomyocytes under basal conditions. This indicates that MAP1S plays an

important role in maintaining cardiac function physiologically. The expression of

MAP1S under basal conditions has also been reported from many cell lines and

mouse tissue in several studies (Rui et al. 2011; Bai et al. 2017; Orbán-Németh et al.

2005). Interestingly, MAP1S cardiac expression is upregulated following

pathological stress such as pressure overload and myocardial infarction. The

upregulation in MAP1S expression indicates that this protein plays some part in the

response to pathological stimuli. The differences in subunit upregulation (FL vs HC)

between different stimuli might be due to the differential regulation in

transcriptional, translational or post-translational modification of this protein in

response to different stimuli. However, further studies need to be conducted to

fully understand this process.

Another study has reported that MAP1S expression is upregulated in

adenocarcinoma. The increased expression is beneficial to supress oxidative stress

and genomic instability (Jiang et al. 2015). In pathological heart models such as MI

and TAC, the level of oxidative stress is also elevated and autophagy, as the

mechanism responding to this stimulus, has been initiated. In general, the

increased expression of MAP1S might be a response related to the induction of

autophagy in order to remove protein aggregates and ubiquininated proteins that

accumulate in the heart following pathological stimuli (Maejima et al. 2015).

Following MI, it was found that more MAP1S-/- mice died within the first week after

surgery compared to wild type mice. The high level of cardiomyocyte apoptosis in

MAP1S-/- mice that is observed at day 3 post-MI is likely to induce cardiac rupture,

which may cause the higher mortality rates in knockout mice. A massive reduction

in EF and FS in the acute phase post MI was also observed, indicating a severe

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maladaptive response in MAP1S-/- mice. It is worth considering that the reduction in

cardiac function may also be due to the high level of apoptosis.

Taken together, the high level of apoptosis might relate to impairment of the

cellular response to remove damaged mitochondria, and accumulation of oxidative

stress products as a consequence of homeostatic imbalance due to attenuated

autophagy and mitophagy following MAP1S depletion.

To further elucidate the function of MAP1S in the heart, I focus my observation on

the role of MAP1S in regulating mitophagy. Mitochondria are important organelles

in cardiomyocytes. They are responsible for supplying energy for continuous heart

contraction. Mitophagy is known as a mitochondrial quality control system to

remove damaged, dysfunctional, or senescent mitochondria that could otherwise

potentially harm the cell.

From this study, it was found that MAP1S deficiency affects cellular mitophagy,

likely by alteration of the binding of damaged mitochondria to autophagosomes.

This is based on the data showing that MAP1S deficiency resulted in less co-

localisation of autophagic puncta and mitochondria as detected by GFP-LC3

reporter and mitotracker dye, respectively. In addition, analysis using the mt-

mKeima reporter showed a lower red signal in MAP1S deficient cardiomyocytes,

suggesting lower numbers of mitochondria in acidic environments. Co-localisation

of GFP-LC3 with mitochondrial markers and increased signal of acidic mt-mKeima

provides a reliable indication that the targeted mitochondria are fused with

lysosomes and destined for autophagic degradation. (Cherra et al. 2009; Dolman et

al. 2013), Thus, this finding indicates that depletion of MAP1S leads to alterations in

the binding between autophagosomes and damaged-mitochondria.

The findings of this study show that the genetic ablation of MAP1S in

cardiomyocytes could potentially reduce mitochondrial function, affect the

mitochondrial structure, and alter mitophagic flux. The significant reduction in

mitochondrial function, as indicated by Seahorse analysis, shows that the depletion

of MAP1S could impact mitochondrial homeostasis. This condition can be explained

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by previous findings reporting that MAP1S bridges autophagic components and

mitochondria in autophagosomal biogenesis (Rui et al. 2011; Liu et al. 2012).

As mitochondrial damage could lead to the loss of membrane integrity and release

of cytochrome c, this can trigger stimulation of apoptotic pathways and eventually

cell death. As the data indicate that there was an alteration in mitophagic flux, the

investigation then focused on its effect on apoptosis. TUNEL analysis on MAP1S

deficient cardiomyocytes showed an increase in the percentage of TUNEL positive

cells compared to control cardiomyocytes. However, the expression of the

apoptosis markers such as Bad, Bax and Bcl2 showed no significant difference. This

suggests that MAP1S might not regulate the upstream pathway of apoptosis.

However, a previous study indicated that there is correlation between MAP1S and

apoptosis through the Wnt-beta catenin pathway (Bai et al. 2017). Therefore,

analysis of the Wnt-beta catenin pathway is also important to be investigated.

Generally, this study confirms that deletion of MAP1S in cardiomyocytes leads to

alterations of mitochondrial function, likely due to the disruption of mitophagy. This

may eventually result in the accumulation of damaged-mitochondria and triggering

of apoptosis. It could be suggested that MAP1S has a role in cardiomyocyte

mitophagy by bridging defective mitochondria to autophagosome.

Importantly, the data from experiments using MAP1S-/- mice injected

intraperitoneally with autophagy inducer supports the idea that MAP1S deletion

reduces autophagic and mitophagic flux in the heart in vivo.

Induction of autophagy in vivo in mice was successfully achieved, as indicated by

significantly increased levels of LC3II in wild type and MAP1S-/- after injection with

Rapamycin and chloroquine intraperitoneally. However, the rate of autophagic flux

was altered in MAP1S-/- mice, as the rate of LC3II degradation (LC3II level after

Rap/Chl treatment subtracted by LC3II level at basal condition) in this genotype was

lower compared to WT mice. As mentioned previously, the increased number of

autophagosomes or the increased level of LC3II expression can be caused by either

an increase rate of autophagic formation or a lower rate of autophagosome

degradation. The finding from electron microscopy analysis indicated that the latter

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might be the responsible factor. Electron microscopy images indicated some

autophagosome structures alongside lysosome structures in MAP1S-/- mice, whilst

this was not observed in any wild type EM images. This indicates that the

autophagosomes are formed but the fusion is impaired, hence we can observe this

structure in MAP1S-/-, but not in the wild type mice.

6.1. Overall conclusions

MI is one of the biggest killers worldwide, and continues to be the main cause of

HF. Despite the emergence of advanced treatments for acute MI, there is a distinct

absence of any mechanism to prevent or even stop the remodelling process. This

study was performed with the aim to examine the molecular regulation of

autophagy as a potential process that could be modulated to protect the heart from

adverse effects following MI. MAP1S is reported to be one of the proteins that

regulate autophagy. The role of MAP1S in regulating autophagy in the heart has

been shown in this study.

In vitro studies showed that the deletion of MAP1S alters autophagy and mitophagy

in cardiomyocytes. This eventually leads to reduced mitochondrial function and

increased levels of apoptosis. In vivo studies suggested that MAP1S deletion in mice

induces a maladaptive response following MI. MAP1S-/- mice exhibited lower

survival rate, less hypertrophic response, higher apoptosis levels and reduction in

cardiac contractile function compared to WT mice, supporting the notion that

MAP1S has a protective role in the heart likely by modulation of autophagy and

mitophagy.

6.2. Future direction

This study has provided insight into the role of MAP1S in regulating autophagy and

mitophagy in the heart. Deletion of this protein in cardiomyocytes and in the whole

heart in vivo reduces autophagy and interferes with mitophagy. Consistently, in

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response to myocardial infarction, MAP1S deletion produces deleterious effects in

the heart.

Although the in vitro study to elucidate the mechanism(s) by which MAP1S

mediates autophagy and mitophagy is relatively extensive, a number of studies

using MAP1S-/- hearts still need to be done to fully elucidate and confirm the

mechanism(s) underlying the cardiac phenotype of MAP1S-/- mice. These include

analysis mitochondrial structural analysis using TEM in mice following MI as well as

analysis of mitochondrial functions in heart tissues. Mitochondrial structural

investigation following stress-induced stimuli in the heart will give a clearer

understanding if MAP1S deletion alters the mitochondrial quality control system in

the heart following MI, as well as explaining the cause of lower survival rate,

impairment of cardiac function and the increase in apoptosis levels in MAP1S-/-

mice following MI.

With regard to the role of MAP1S in regulating apoptosis, investigation of other

potential pathways that might be regulated by MAP1S is needed. Since recent

studies showed that MAP1S may regulate apoptosis through the Wnt-beta catenin

pathway (Bai et al. 2017) further investigation on the involvement of the Wnt-beta

catenin pathway is needed to further understand the regulatory role of MAP1S.

As this study mainly uses knockout and knockdown models to study MAP1S role, it

is also important to conduct in vitro and in vivo experiments using overexpression

models in the future. It would be very interesting to know if MAP1S over activation

will produce beneficial effects in the heart in the pathological setting. This will be an

important study that can lay scientific foundation for targeting MAP1S for

therapeutic purpose in the future.

6.3. Study limitations

The main limitation of this study is the lack of mechanistic analysis in the in vivo

study. This is due to the low number of animals available at the time of the study.

The breeding of MAP1S-/- mice was increased, and breeding trios instead of

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breeding pairs were set up. However, this was still insufficient to provide enough

animals for conducting complete mechanistic analysis, such as electron microscopy

analysis post MI to see the structure of the mitochondria in the heart. Since all of

the heart tissue post MI was used for histological analysis (Masson’s trichrome,

H&E staining and TUNEL assay), there were no tissues left to perform

molecular/biochemical analysis, e.g. to evaluate the levels of autophagy/apoptosis

markers.

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