about omics group - d2cax41o7ahm5l.cloudfront.net omics group ... 19.6 - 90.0 sm:15g 20 25 30 35 40...

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http://homepage.univie.ac.at/stefanie.wienkoop//

Stefanie Wienkoop

Comprehensive Protein turnover analysis of a partial 15N stable isotope metabolic labelling experiment In Planta

RT: 19.6 - 90.0 SM: 15G

20 25 30 35 40 45 50 55 60 65 70 75 80 85 90

Time (min)

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Re

lative

Ab

un

da

nce

56.8

56.6

NL: 6.22E6

TIC F: + p SRM ms2 [email protected] [ 200.65-923.75] MS Contol_standard_800fmol4

NL: 6.58E4


RT: 19.6 - 90.0 SM: 15G

20 25 30 35 40 45 50 55 60 65 70 75 80 85 90

Time (min)

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lative

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38.5

38.8

NL: 6.73E7


NL: 6.74E4


Chicago, Proteomics-2014

Stefanie Wienkoop – Plant Systems Interaction

http://www.univie.ac.at/mosys/

http://www.univie.ac.at/

Stefanie Wienkoop

Molecular Systems Biology and

The Molecular Plant Phenotype

Molecular Phenotype

Metabolomics

Genotype-Phenotype Relationship

Analytics

in vivo Dynamics

Genotype (genome sequence) : metabolic and regulatory reconstruction of the whole species

Proteomics

Integration of the data, biostatistics and modelling

Environmental Perturbation

Genomics Phenomics




Stefanie Wienkoop

ProteomicsAnalyses

Data mining

Unbiased relative quantification (2.2.1)

Targeted absolute quantification (2.2.2)

Database dependentprotein ID

Database independent peptide ID (MAPA)

Modelling

Metabolomics - Proteomics dataintegration and transformsation (2.4)

Interpretation and visualisation(HIC, PCA, ICA)

Biomarker discovery

Genomicdatabase

Public Sources

organelle/membraneenrichment

Comparative analyses (2.2)

Improved genomeannotation (2.3)

Localisation studies

Profiling analyses (2.1)

ProteomicsAnalyses

Data mining





Modelling



Biomarker discovery

Genomicdatabase

Public Sources






Wienkoop et al. JProt (2010)

Proteomics Toolbox




Stefanie Wienkoop

ProteomicsAnalyses

Data mining





Modelling



Biomarker discovery

Genomicdatabase

Public Sources






ProteomicsAnalyses

Data mining





Modelling



Biomarker discovery

Genomicdatabase

Public Sources






Wienkoop et al. JProt (2010)

ProtMAX

Mass Western

ProMEX

Selpex & CamelCropper

Turnover & Degradation

Proteomics Toolbox




Stefanie Wienkoop

SILIP- Drought Recovery Experiment

Experimental Setup Medicago truncatula

Drought Recovery (96 h) Experiment

In Planta

Gel-free Shotgun-LC/MS/MS

5 TP

2 h

24 h

48 h

72 h

96 h

6 rep. C vs D

Re-Watering 15N (2.5 mM NH4 NO3)

7 week old plants

10 days of drought stress

non-symbiotic (nodule free) Same set:

14N (2.5 mM NH4 NO3)


FWF Project P23441-B20



Stefanie Wienkoop

Drought -> Drought Recovery

0

100

200

300

400

500

gs [m

mol

H2O

m-2

S-1]

C

DR

-2

-1.5

-1

-0.5

0 0 2 48 96

ᴪ w [M

Pa]

hours of drought recovery

stomatal conductance

water potential (predawn)

water re-supply

drought drought recovery




shoot

root

705

708

251

454

456

NSAF

Total: 1161

LC-Orbitrap MS/MS

Stefanie Wienkoop

HIC: Protein and Metabolite Cluster Analysis

Roots (278) Shoots (174) Significant changed only (DR/C)!

≥ 2 fold change

p ≤ 0.05

n = 6

Proteins Metabolites

2 24 48 72 96


2 24 48 72 96



Stefanie Wienkoop

Protein and Metabolote Response Overview

Proteins 140 132 126 115 142 Metabolites 20 20 17 13 3

Roots

fold change (DR/C) 2 24 48 72 96

Proteins 43 50 60 47 51 Metabolites 21 13 7 10 0 Shoots

Metabolites fully recover!




Stefanie Wienkoop

Correlation Network & Functional GO Analysis


Biol. Process: TRANSLATION

2 h

96 h



Stefanie Wienkoop

Regulatory Relevant Protein Correlation-Cluster

2h after Re-Watering

Cluster A

Cluster B

Root Shoot

Group 1:

Time point 1

up-regulation

Cluster C

Cluster D

Cluster L

Group 3:

Time point 1

down-regulation

Cluster K

Root Shoot

Cluster H

Group 5: Time point 5

up- or down-regulation




Stefanie Wienkoop

Relative cluster proportion of stress recovery response proteins

Cluster A 5%

Cluster B 20%

Cluster C 10%

Cluster D 5%

Cluster E 5%

Cluster F 10%

Cluster G 5%

Cluster H 11%

Cluster I 4%

Cluster J 9%

Cluster K 3%

Cluster L 13%

Cluster A 2%

Cluster B 11%

Cluster C 1%

Cluster D 1%

Cluster E 0%

Cluster F 13%

Cluster G 5%

Cluster H 25%

Cluster I 11%

Cluster J 14%

Cluster K 4%

Cluster L 13%

Roots Shoots




Stefanie Wienkoop

First Conclusions

• Translational Regulation within first 2 hours of rewatering.

• While physiological and metabolic levels fully recovered

after 96 hours, protein regulation still in process




Stefanie Wienkoop

Why studying protein turnover?

1. Transcript and protein measurements are poorly

correlated in experiments of abundance and stability when exposed to environmental perturbations.

2. Understanding the mechanisms controlling whole plant nitrogen-to-protein incorporation and protein-to-nitrogen breakdown will advance our knowledge of plant nitrogen

acquisition and allocation.




Stefanie Wienkoop

How studying protein turnover?

1. 15N stable isotope metabolic labeling is one of the major approaches for Mass Spectrometry based proteomics.

2. Additionally to protein turnover, AA turnover can be monitored.

3. Protein turnover analysis involves the partial-labeling strategy.




Stefanie Wienkoop

1. Partial metabolic labelling => high complexity!

2. Identification of all proteinogenic AAs => possible?

3. Absolute levels from all proteinogenic AAs => very difficult!

4. Absolute levels of all identified proteins => possible?

5. Proteotypic peptides (>2) for all proteins => possible?

Challenge 1




root

C = control

D = drought-recovery

* = display for marked AA

2 24 48 72 96 h 2 24 48 72 96 h

C

D

* *

2 24 48 72 96 h

C

D

C

D

C

D

*

*

*

2 24 48 72 96 h

C

D

C

D

C

D

*

*

* n.d.

n.a.

*

2 24 48 72 96 h

C

D

*

2 24 48 72 96 h

C

D

C

D

C

D

*

* *

2 24 48 72 96 h 2 24 48 72 96 h

2 24 48 72 96 h

2 24 48 72 96 h

C

D

* *

2 24 48 72 96 h

C

D

C

D

C D

*

*

*

2 24 48 72 96 h

C

D

C

D

C

D

*

*

* 2 24 48 72 96 h

C

D

*

n.d.

2 24 48 72 96 h

2 24 48 72 96 h

C

D

C

D

C

D

C

D

*

*

* *

2 24 48 72 96 h

2 24 48 72 96 h

shoot

C = control

D = drought-recovery

* = display for marked AA

GC-MS amalysis of 15N incorporation into Amino Acids

RIA0 14N/15NNA

C

D

No labelling 15N labelling RIA of 15N enrichment

roots


Stefanie Wienkoop

How to retrieve the relative isotope abundance (RIA)

of partial metaboloc labelling

from MS data?

Callenge 2




CamelCropper

David Lyon

FWF Project P23441-B20

Stefanie Wienkoop

SelPEx- Selective Peptide Extraction

List of identified peptides with high quality MS properties:

- Robust and reproducible MS signals / peak shape

- m/z ratio, RT and ID CamelCropper

- Calculation of all possible m/z values of the 15N isotope pattern for each peptide.

- Ancoring to the monoisotopic precursor (MIP0)

- ID of the „Camel neck“ and „Camel back“

- Calculation of eg RIA [H]/ [H+L] for calculation protein synthesis and degradation

MS data upload into CamelCropper

Castillecho et al. 2013

IN: Plant Proteomics Methods and Protocols. Ed. J.V. Jorrin Novo, S. Komatsu, S. Wienkoop, W. Weckwerth: Springer New York.

CamelCropper for 15N partial labelling – protein turnover detection




Stefanie Wienkoop

Workflow

samples

LC/MS

RAW data

mzML

picked data points

peptide label ratios

search input (ID)

SelPEX (AAseq, charge, RT)

Upload of 1394 peptide sequences (430 proteins)




Stefanie Wienkoop

PCA Plot: RIA Intensities of Shoot Proteins

96 72 48 24 0

control

drought




Stefanie Wienkoop

Cluster Analysis: RIA ration DR vs. C




Stefanie Wienkoop

Cluster Analysis of PS: RIA ration DR vs. C




Stefanie Wienkoop

BoxPlot LSU




Stefanie Wienkoop

BoxPlot SSU




Stefanie Wienkoop

Protein Levels vs. Turnover

0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8

0 24 48 72 96 prot

. abu

ndan

ce D

/C

h of DR

SSU LSU

RSUs abundance did not significantly change during drought recovery!

0

0.1

0.2

0.3

0.4

0.5

0.6

0 24 48 72 96

RIA

Ho15N

SSU LSU

0

0.1

0.2

0.3

0.4

0.5

0.6

0 24 48 72 96

RIA

HAS

SSU LSU

RIA

C DR

RSUs RIAs did significantly increase during drought recovery!

=> Equal Synthesis and Degradation Rates!




Stefanie Wienkoop

Protein Levels vs. Turnover

0

0.1

0.2

0.3

0.4

0.5

0.6

0 24 48 72 96

RIA

Ho15N

SSU LSU

0

0.1

0.2

0.3

0.4

0.5

0.6

0 24 48 72 96

RIA

HAS

SSU LSU

RIA

C D

RSUs RIAs did significantly increase during drought recovery!

=> RuBisCO turnover ~2 fold higher during drought recovery!


Av. RSU synthesis rates per 24 h: Contol = 0.05

DR= 0.13

Av. RSU degradation rates per 24 h: Control = 0.06

DR= 0.12



Stefanie Wienkoop

Second Conclusion

1) AA turnover increased within first 24 h of drought recovery. -> AA

levels increased within 48 h -> direct incorporation into proteins

2) A strong increase in protein turnover was observed along drought

recovery (synthesis and degradation rates)

variation in isotope composition can be caused by multiple

assimilation events, organ specific loss of nitrogen, and resorption

and reallocation of nitrogen.

Reduced N-uptake during drought caused decreased AA levels




Thanks to the Team!!!

Christiana Staudinger Vlora Mehmeti Wolfgang Hohenwarter Lena Fragner Luis Recuenco-Muñoz David Lyon Reinhard Turetschek MA Castillejo (Selpex)

Wolfram Weckwerth and others + Green team!!

[P23441-B20] [P24870-B22]

Getinet Desalegn Hans-Peter Kaul


Let Us Meet Again

We welcome you all to our future conferences of OMICS Group

International

Please Visit: www.omicsgroup.com

www.conferenceseries.com www.proteomicsconference.com

http://www.omicsgroup.com/

http://www.conferenceseries.com/

http://www.proteomicsconference.com/

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