proteomics in analysis of bacterial pathogens tina guina university of washington, seattle

Proteomics in Analysis of Bacterial PathogensProteomics in Analysis of Bacterial Pathogens

Tina Guina

University of Washington, Seattle

Postgenomic studies of Pseudomonas in context of

lung infection in patients with cystic fibrosis

Study of bacterial posttranslational regulation by

monitoring changes in protein subcellular localization

OutlineOutline

Gram-negative environmental bacterium (soil, water)

Invades plants, animals; causes disease in immunocompromised

humans and chronic lung disease in cystic fibrosis patients

Cystic fibrosis (CF): most common genetic disease in Caucasians

caused by a mutation in chloride channel CFTR

Chronic Pseudomonas lung infection is a major cause of morbidity in

CF patients

Bacteria persist and multiply in lung (up to 109 cfu/g of sputum)

Pseudomonas aeruginosa Pseudomonas aeruginosa and Cystic Fibrosisand Cystic Fibrosis

Environmental P. aeruginosa

Model of Chronic Model of Chronic Pseudomonas aeruginosaPseudomonas aeruginosa Infection in Cystic FibrosisInfection in Cystic Fibrosis



PA colonization - ASYMPTOMATICPA colonization - ASYMPTOMATIC

CFTR-CFTR-UnknownUnknown

Innate Innate immune immune

defectdefect


Innate Immune Selective Pressure

Bacterial Adaptation

PA colonization - ASYMPTOMATICPA colonization - ASYMPTOMATIC




defectdefect

Environmental Pseudomonas



Unique surface modifications

Increased airway

inflammation

Resistance to antimicrobials

ChronicLung

Disease

PA colonization - ASYMPTOMATICPA colonization - ASYMPTOMATIC Increased bacterial burden - SYMPTOMATICIncreased bacterial burden - SYMPTOMATIC




defectdefect

Bacterial Bacterial AdaptationAdaptation

ChronicLung

Disease



?

Bacterial Bacterial AdaptationAdaptation

ChronicLung

Disease



?

Intervention

Can we characterize stages of bacterial adaptation to the lung ?

Can we use characteristics of these stages to develop assays

to predict CF patients’ clinical outcome ?

Can drugs be developed that would arrest adaptation ?

Can Pseudomonas “staging” be used for therapy ?

Questions:Questions:

Approaches for Studying Approaches for Studying PseudomonasPseudomonas Adaptation Adaptation in CF Lungin CF Lung

• Analysis of laboratory-adapted Pseudomonas strains grown under

conditions that promote phenotypes typical to the clinical isolates

• Analysis of Pseudomonas clinical isolates from CF airway

- serial isolates from young children with CF

- isolates from patients with mild vs. severe disease symptoms

• Analysis of bacterial phenotypes: morphology, surface properties,

production of secreted factors

• Postgenomic analysis: whole genome sequencing, genome typing,

transcriptional profiling, protein expression profiling

Analysis of Analysis of PseudomonasPseudomonas Clinical Isolates From Clinical Isolates From Young Children With CF Young Children With CF

Natural history study to determine infection and inflammation in

young children, three centers in US

– Early isolates from 29 children, 4 to 36 months of age, 2 to 30 isolates for each patient

– Later isolates from 11/29 children enrolled into the original study, currently up to 9 years of age

– Isolates from upper airway (OP) and lower airway (BAL)

(Rosenfeld et al. 2001)

Postgenomic Analysis of Postgenomic Analysis of PseudomonasPseudomonas in CF in CF

Environmental isolates

Clinical CF Isolates

Microarray Analysis

Proteomic Analysis

Bioinformatics

Identification of CF-unique Characteristics

PhenotypicAnalysis

GenomicAnalysis

Pseudomonas Pseudomonas Adapt to the Cystic Fibrosis Adapt to the Cystic Fibrosis Lung EnvironmentLung Environment

CF Isolate-Specific Characteristics:CF Isolate-Specific Characteristics:Outer Membrane LPS Modifications Outer Membrane LPS Modifications

LPS modifications are induced in:

- all early isolates from infants with CF (as early as 4 months of age)

- laboratory-adapted strain PAO1 during magnesium limitation and

anaerobic growth

2) Increased Proinflammatory

Signaling Through Tlr4

O

O

O

O

O

O

O

O

O

O

O

O

O

P

P

O

O

O

OH

NH

NHHO

OH

OH

O

HO

O

HO

NH2

OH

aminoarabinose

O

NH2

O-

OH

3-OH C10

3-OH

C12

C12

OHO

O

3-OH C12

3-OH C12

O

C16

1) Increased Antimicrobial

Peptide Resistance

(Ernst et al. 1999, Hajjar et al. 2002)

Whole genome analysis using DNA microarrays

- 13 CF, 4 environmental, and 3 clinical non-CF isolates

- 38 common chromosomal islands divergent or absent (N >1)

when compared to PAO-1

Results:

Suggest no selection of a Pseudomonas subpopulation from the

environment in colonization of the CF airways.

I. Adaptation to the CF Lung: Is Genomic I. Adaptation to the CF Lung: Is Genomic Organization of Organization of PseudomonasPseudomonas CF Infant and CF Infant and

Environmental Isolates Similar?Environmental Isolates Similar?

(Ernst et al. 2003)

II. Adaptation to the CF Lung : Is Genomic Organization II. Adaptation to the CF Lung : Is Genomic Organization of Longitudinal of Longitudinal PseudomonasPseudomonas CF Isolates Similar? CF Isolates Similar?

Isolates from 6 months to 8 years of age

CF416 (6 months): 4.0 X coverage

CF5296 (8 years): 4.0 X coverage

Results:

40 point mutations/deletions between

early and late isolate

< 6 mo 60 mo

96 mo

Sequencing of parentally-related Pseudomonas isolates from a CF patient

(Smith, Olson et al.)

Analysis of 40 Chromosomal Regions:Analysis of 40 Chromosomal Regions:Comparison of Longitudinal CF IsolatesComparison of Longitudinal CF Isolates

Key Age (months) <6 <9 24 27 30 30 33 36 36 60 96 96

1 2 Case \ Strain 416 547 1328 1438 1543 1546 1590 1638 1642 190383 5295 5296

No changes 17 1 1 1 1 1 1 1 1 1 1No changes 14 1 1 1 1 1 1 1 1 1 1 1

C - 1 1 1 1 1 1 1 1 1 1 1 2 2C T 2 1 1 1 1 1 1 1 1 1 2 2

C T 5 1 1 1 1 1 1 1 1 1 1 2 2C T 6 1 1 1 1 1 1 1 1 2 2

G T 7 1 1 1 1 1 1 1 1 1 1 2 2G A 12 1 1 1 1 1 1 1 1 1 1 2 2

G A 18 1 1 1 1 1 1 1 1 2 2T C 19 1 1 1 1 1 1 1 1 1 1 2 2

C T 21 1 1 1 1 1 1 1 1 1 1 2 2CGG --- 22 1 1 1 1 1 1 1 1 2 2

C T 23 1 1 1 1 1 1 1 1 1 1 2 2T C 25 1 1 1 1 1 1 1 1 1 1 2 2

C - 27 1 1 1 1 1 1 1 1 1 1 2 2C A 29 1 1 1 1 1 1 1 1 1 1 2 2

G - 31 1 1 1 1 1 1 1 1 1 2 2G C 39 1 1 1 1 1 1 1 1 1 1 2

T C 32 1 1 1 1 1 1 1 1 1 1 2A G 11 1 1 1 1 1 1 1 1 1 1 2

-- CC 4 1 1 1 1 1 1 1 1 1 1 2G - 35 1 1 1 1 1 1 1 1 1 1 2

C T 36 1 1 1 1 1 1 1 1 1 1 2C G 37 1 1 1 1 1 1 1 1 1 1 2

T - 38 1 1 1 1 1 1 1 1 2G A 34 1 1 1 1 1 1 1 2 2

C T 40 1 1 1 1 1 1 1 1 1 1 2 2G A 33 1 1 1 1 1 1 1 1 1 2 2

A G 16 1 1 1 1 1 1 1 1 1 2 2 2A C 10 1 1 1 1 1 1 2 2

C T 9 1 1 1 1 1 1 1 1 1 2 2C T 28 1 1 1 1 1 1 1 1 1 2 2 2

C - 26 1 1 1 1 1 1 1 1 2 2 2C T 3 1 1 1 1 1 1 2 1 1 2 2

A C 24 1 1 1 1 1 2 2 1 1 2 2 2A T 8 1 1 1 1 1 2 2 1 1 2 2 2

7 Cs 6 Cs 13 1 1 1 1 1 2 2 1 1 2 2 2A G 15 1 1 1 1 1 2 2 1 1 2 2

A G 20 1 1 1 1 1 2 2 1 2 2 2 2C T 30 1 1 1 1 1 2 2 2 2 2 2

CF-activated genes

PA1290: probable transcriptional regulator 5

PA5095: ABC transporter permease 5

CF-repressed genes

PA1008: bacterioferritin comigratory protein 5

PA1244: hypothetical gene 5

PA1708: popB - translocator protein 5



# of patients (N=5)

III. Adaptation to the CF Lung : Is There a Gene Expression III. Adaptation to the CF Lung : Is There a Gene Expression Pattern Unique to the Infant CF Isolates?Pattern Unique to the Infant CF Isolates?

Transcriptional (mRNA) profiling using DNA microarrays

(Ernst et al.)

Results: Mode of regulation for 7 genes is unique to a subsetof clinical isolates

Cellular Protein Levels Do Not Always Correlate With Cellular Protein Levels Do Not Always Correlate With Levels of the Corresponding Gene TranscriptsLevels of the Corresponding Gene Transcripts

Anaerobic regulation in PAO1: Postgenomic Analysis

Regulated Genes

209 Regulated Proteins

122

QuantifiedProteins

553

1342

Genes/ProteinsTotal QuantifiedRegulatedInduced Represed

Microarray Analysis5600209108101

Proteomic Analysis5531225468

IV. Adaptation to the CF Lung : Is There a Protein IV. Adaptation to the CF Lung : Is There a Protein Expression Pattern Unique to the Infant CF Isolates?Expression Pattern Unique to the Infant CF Isolates?

Quantitative protein profiling of differentially labeled whole cell protein

Whole cell Whole cell proteinprotein+ + IICCAATT

Strain/Condition AStrain/Condition A

Combine and Combine and proteolyzeproteolyze

LC-MS/MSLC-MS/MS

in silicoin silico analysis analysisIICCAATT-peptide-peptidemixturemixture

Strain/Condition BStrain/Condition B[Protein X in [Protein X in AA]]

[Protein X in [Protein X in BB]]

Pseudomonas aeruginosaPseudomonas aeruginosa Proteome Analysis: Proteome Analysis: Regulation by Low Magnesium Stress Induces CF isolate- Regulation by Low Magnesium Stress Induces CF isolate-

Specific Surface ModificationsSpecific Surface Modifications

Laboratory-adapted Pseudomonas strain PAO-1

8 M Mg2+

CF-like phenotype1 mM Mg2+

Differential protein labeling

MS/in silico protein identification and quantitative analysis

Qualitative proteomic analysis: 1331 proteins identified

Quantitative analysis (ICAT): 546 proteins quantified

76 proteins induced

69 proteins repressed

~ 50% correlation with transcriptional profiling data

Transcriptional Profiling: ~2250 (40%) genes expressed

650 genes regulated

Postgenomic Analysis of Postgenomic Analysis of PseudomonasPseudomonas During Mg LimitationDuring Mg Limitation

Fold increase

Conserved low Mg stress-response proteins

two-component response regulator PhoP 10.3

magnesium transport ATPase MgtA 5.8

MgtC homologue 4.0

CF-specific surface modifications, resistance to antimicrobial peptides

PmrH homologue 2.8

PmrF homologue 2.3

PmrI homologue 6.1

Enzymes for synthesis of quorum sensing signal PQS

PA0996, PA0997, PA0998, PA0999 1.5 - 2.0

Selected Proteins Induced During Growth of Selected Proteins Induced During Growth of PseudomonasPseudomonas in Low Mg in Low Mg

Quorum Sensing: Bacterial Intercellular Communication ViaQuorum Sensing: Bacterial Intercellular Communication Via Small Signaling MoleculesSmall Signaling Molecules

C4-HSL

C12-HSL

PQS

Quorum Sensing: Secretion of Toxins, Virulence FactorsQuorum Sensing: Secretion of Toxins, Virulence Factors

Quorum Sensing: Biofilm, Antibiotic ResistanceQuorum Sensing: Biofilm, Antibiotic Resistance

AB

AB

AB

AB

S-adenosylmethionine(SAM)

Butyryl-ACP

Dodecanoyl-ACP

C4-HSL

C12-HSL

RhlI

LasI

-keto-decanoic acidPQS

Acyl-homoserine lactones

WT PQS -

Mg2+

Conc. 8 M

1 m

M8 M

1 m

M

PQS Production by Laboratory Strain of PQS Production by Laboratory Strain of Pseudomonas Pseudomonas Is Increased During Growth in Low MgIs Increased During Growth in Low Mg

PAO-1

PQS -

blood

UTICF1

CF2CF3

CF4CF5

High Levels of PQS Are Produced by CF High Levels of PQS Are Produced by CF PseudomonasPseudomonas Isolates Grown in High MgIsolates Grown in High Mg

190 isolates from 25 children

up to 3 years of age analyzed for

PQS production

Bacteria were grown in medium

with high [Mg2+]

Patient # of isolates Age (mo)1 3 4 to 362 4 12 to 213 5 3 to 364 20 9 to 366 5 21 to 367 15 6 to 338 4 18 to 279 27 6 to 3610 10 12 to 36

102 8 27 to 36103 2 27 to 33104 10 18 to 36105 2 27 to 33107 1 33108 6 12 to 21109 5 30 to 36111 3 12 to 24201 2 15 to 18202 6 24 to 36203 6 18 to 36204 2 33205 17 15 to 36206 8 12 to 33209 2 21 to 30211 11 12 to 36212 6 12 to 36

PQS Production by PQS Production by PseudomonasPseudomonas Isolates From Isolates FromInfants with Cystic FibrosisInfants with Cystic Fibrosis

PQS Production by Isolates from Infants with CF PQS Production by Isolates from Infants with CF

Patients (N=25)Isolates producing

high PQS levels

12 > 75%

7 50-74%

2 25-49%

4 < 25%

Similar to CF-specific surface modifications, most Pseudomonas clinical isolates from young children with CF produce high PQS levels

Environmental Pseudomonas

PA colonization-ASYMPTOMATICPA colonization-ASYMPTOMATIC



• Alginate/mucoidy

• Auxotrophy

Increased bacteria - SYMPTOMATICIncreased bacteria - SYMPTOMATIC

Lung

Disease• surface modifications

• Increased PQS

(biofilm, virulence,

antibiotic resistance)


Natural History Study:Natural History Study:Infant patients isolates,8-yr vs. early isolates Mild vs. Severe StudyMild vs. Severe Study

Genome sequencingGenome sequencingDNA Microarray, Proteomic AnalysesDNA Microarray, Proteomic Analyses

To Identify Additional MarkersTo Identify Additional Markers


Develop tests for broad screening of large CF populationsDevelop tests for broad screening of large CF populations

to validate markers specific for to validate markers specific for PseudomonasPseudomonas adaptation adaptation




Develop tests for broad screening of large CF populationsDevelop tests for broad screening of large CF populations

to validate markers specific for to validate markers specific for PseudomonasPseudomonas adaptation adaptation

Correlate with the disease outcomeCorrelate with the disease outcome

Disease outcome predictionDisease outcome predictionVaccine/drug developmentVaccine/drug development



Bacterial Posttranslational Regulation Study:Bacterial Posttranslational Regulation Study:

PseudomonasPseudomonas Envelope Remodeling During Growth Envelope Remodeling During Growth

In Low MgIn Low Mg

Gram-negative Bacterial MembraneGram-negative Bacterial Membrane

Magnesium Stabilizes Gram-negative Outer MembraneMagnesium Stabilizes Gram-negative Outer Membrane

OO OOH O

OHOH

OHO

O

OO

HO

O

OO O

P

OHNH

O

O-O

O

NHP

O

OO OOH O

OHOH

O-O

O

OO

HO

O

OO

O

P

OHNH

O

OHO

O

NHP

O

Mg

Growth in low magnesium Membrane stressMembrane remodeling

Growth in low magnesium Membrane stressMembrane remodeling

Lipid A

Gram-Negative Envelope Remodeling Gram-Negative Envelope Remodeling During Magnesium LimitationDuring Magnesium Limitation

PagP PagCPagN

PgtE OprH

PmrF

Environmental sensing

Lipid A acylation

MgtA MgtC

Small molecule transportNutrient acquisition

LPS modifications

PhoQ PmrB

Proteases

Modulation and resistance to the host innate immune defense:

Alteration in outermembrane proteins

OM

IM

ICAT Analysis of ICAT Analysis of PseudomonasPseudomonas Membrane and Whole Cell Membrane and Whole Cell Protein During Mg LimitationProtein During Mg Limitation

Pseudomonas strain PAO-1

8 8 M MgM Mg2+2+

membranemembrane1 mM Mg1 mM Mg2+2+

membranemembrane

IICCAATT analysis analysis

163 proteins163 proteins

8 8 M MgM Mg2+2+

whole cellwhole cell1 mM Mg1 mM Mg2+2+

whole cellwhole cell

IICCAATT analysis analysis

486 proteins486 proteins

106 proteins were quantified in both experiments:106 proteins were quantified in both experiments:Compare relative protein levels in membrane vs. in whole cellCompare relative protein levels in membrane vs. in whole cell

FI* membrane/FI whole cellEnergy metabolism

succinate dehydrogenase (A, B subunits) 1.6 - 2.4

2-oxoglutarate dehydrogenase (E1 subunit) SucA 3.0

phosphoenolpyruvate synthase 3.1

ATP synthase subunits 1.5 – 1.8

cytochrome c5 1.6

GroEL chaperone 3.0

Translation machinery30S ribosomal proteins (S2, S4, S13, S5) 1.5 – 1.8

elongation and ribosome recycling factor G 2.0

PseudomonasPseudomonas Metabolic Enzymes and Protein Translation Machinery Metabolic Enzymes and Protein Translation MachineryConcentrate at the Membrane During Growth in Low MagnesiumConcentrate at the Membrane During Growth in Low Magnesium

*FI = fold induction

Bacterial ribosomal fractions

Cytoplasmic

Soluble protein synthesis

Membrane-associated

Membrane and secreted protein synthesis

Bacterial ribosomal fractions

Cytoplasmic

Low Mg2+ membrane stress

Soluble protein synthesis

Membrane-associated

Increased membrane and secreted protein synthesis

Low Mg2+ membrane stress

Membrane lipid and protein remodelingDecreased membrane permeability

Resistance to various antimicrobials

Formation of stress-induced multienzyme complexes

Advantages:

• Useful tool for analysis of bacteria for which there are little

or no genetic tools available

• Analysis of posttranscriptional regulation

• Analysis of protein compartmentalization, posttranslational regulation

Disadvantages:

• Still expensive, time/labor intensive

• Need for “dishwasher-like technology”, for improved data analysis software

Proteomic Analysis in Studying Bacterial Pathogens:Proteomic Analysis in Studying Bacterial Pathogens:SummarySummary

Manhong Wu

Robert Ernst

Hai Nguyen

Sam Miller

Jane Burns

Eric Smith

Maynard Olson

AcknowledgementsAcknowledgements

David Goodlett

Sam Purvine

Ruedi Aebersold

Jimmy Eng

CFF

NIH

proteomics in analysis of bacterial pathogens tina guina university of washington, seattle

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