proteomics in analysis of bacterial pathogens
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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
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
Environmental P. aeruginosa
Innate Immune Selective Pressure
Bacterial Adaptation
PA colonization - ASYMPTOMATICPA colonization - ASYMPTOMATIC
Model of Chronic Model of Chronic Pseudomonas aeruginosaPseudomonas aeruginosa Infection in Cystic FibrosisInfection in Cystic Fibrosis
CFTR-CFTR-UnknownUnknown
Innate Innate immune immune
defectdefect
Environmental Pseudomonas
Innate Immune Selective Pressure
Bacterial Adaptation
Unique surface modifications
Increased airway
inflammation
Resistance to antimicrobials
ChronicLung
Disease
PA colonization - ASYMPTOMATICPA colonization - ASYMPTOMATIC Increased bacterial burden - SYMPTOMATICIncreased bacterial burden - SYMPTOMATIC
Model of Chronic Model of Chronic Pseudomonas aeruginosaPseudomonas aeruginosa Infection in Cystic FibrosisInfection in Cystic Fibrosis
CFTR-CFTR-UnknownUnknown
Innate Innate immune immune
defectdefect
Bacterial Bacterial AdaptationAdaptation
ChronicLung
Disease
PA colonization - ASYMPTOMATICPA colonization - ASYMPTOMATIC Increased bacterial burden - SYMPTOMATICIncreased bacterial burden - SYMPTOMATIC
Model of Chronic Model of Chronic Pseudomonas aeruginosaPseudomonas aeruginosa Infection in Cystic FibrosisInfection in Cystic Fibrosis
?
Bacterial Bacterial AdaptationAdaptation
ChronicLung
Disease
PA colonization - ASYMPTOMATICPA colonization - ASYMPTOMATIC Increased bacterial burden - SYMPTOMATICIncreased bacterial burden - SYMPTOMATIC
Model of Chronic Model of Chronic Pseudomonas aeruginosaPseudomonas aeruginosa Infection in Cystic FibrosisInfection in Cystic Fibrosis
?
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
PA1752: hypothetical gene 5
PA2461: hypothetical gene 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
Model of Chronic Model of Chronic Pseudomonas aeruginosaPseudomonas aeruginosa Infection in Cystic FibrosisInfection in Cystic Fibrosis
Bacterial Adaptation
• Alginate/mucoidy
• Auxotrophy
Increased bacteria - SYMPTOMATICIncreased bacteria - SYMPTOMATIC
Lung
Disease• surface modifications
• Increased PQS
(biofilm, virulence,
antibiotic resistance)
Innate Immune Selective Pressure
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
Natural History Study:Natural History Study:Infant patients isolates,8-yr vs. early isolates Mild vs. Severe StudyMild vs. Severe Study
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
Genome sequencingGenome sequencingDNA Microarray, Proteomic AnalysesDNA Microarray, Proteomic Analyses
To Identify Additional MarkersTo Identify Additional Markers
Natural History Study:Natural History Study:Infant patients isolates,8-yr vs. early isolates Mild vs. Severe StudyMild vs. Severe Study
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
Genome sequencingGenome sequencingDNA Microarray, Proteomic AnalysesDNA Microarray, Proteomic Analyses
To Identify Additional MarkersTo Identify Additional Markers
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
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