Proteomics in Analysis of Bacterial Pathogens Tina Guina

Proteomics in Analysis of Bacterial Pathogens Tina Guina

Proteomics in Analysis of Bacterial Pathogens Tina Guina University of Washington, Seattle Outline 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 Pseudomonas aeruginosa and Cystic Fibrosis 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) Model of Chronic Pseudomonas aeruginosa Infection in Cystic Fibrosis Environmental P. aeruginosa Model of Chronic Pseudomonas aeruginosa Infection in Cystic Fibrosis Environmental P. aeruginosa CFTR- Unknown Innate immune defect PA colonization - ASYMPTOMATIC Model of Chronic Pseudomonas aeruginosa

Infection in Cystic Fibrosis Environmental P. aeruginosa CFTR- Unknown Innate immune defect Bacterial Adaptation Innate Immune Selective Pressure PA colonization - ASYMPTOMATIC Model of Chronic Pseudomonas aeruginosa Infection in Cystic Fibrosis Environmental Pseudomonas CFTR- Unknown Innate immune defect Bacterial Adaptation Increased airway inflammation Unique surface modifications Resistance to antimicrobials

Chronic Lung Disease Innate Immune Selective Pressure PA colonization - ASYMPTOMATIC Increased bacterial burden - SYMPTOMATIC Model of Chronic Pseudomonas aeruginosa Infection in Cystic Fibrosis Bacterial Adaptation Chronic Lung Disease ? PA colonization - ASYMPTOMATIC Increased bacterial burden - SYMPTOMATIC Model of Chronic Pseudomonas aeruginosa Infection in Cystic Fibrosis Intervention Bacterial Adaptation Chronic Lung Disease ? PA colonization - ASYMPTOMATIC Increased bacterial burden - SYMPTOMATIC Questions: 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 ? Approaches for Studying Pseudomonas Adaptation in 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 Pseudomonas Clinical Isolates From 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 Pseudomonas in CF

Environmental isolates Clinical CF Isolates Phenotypic Analysis Genomic Microarray Analysis Analysis Proteomic Analysis Bioinformatics Identification of CF-unique Characteristics Pseudomonas Adapt to the Cystic Fibrosis Lung Environment CF Isolate-Specific Characteristics: Outer Membrane LPS Modifications aminoarabinose NH 2 O OH O HO OH O O

P O OH O O NH O O O HO HO O O O O NH O O O NH O O O P O O 3-OH

C12 C12 C16 - OH OH HO 3-OH C10 O 2 1) Increased Antimicrobial Peptide Resistance 2) Increased Proinflammatory Signaling Through Tlr4 3-OH C12 3-OH C12 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 (Ernst et al. 1999, Hajjar et al. 2002) I. Adaptation to the CF Lung: Is Genomic Organization of Pseudomonas CF Infant and Environmental Isolates Similar? 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. (Ernst et al. 2003) II. Adaptation to the CF Lung : Is Genomic Organization of Longitudinal Pseudomonas CF Isolates Similar? Sequencing of parentally-related Pseudomonas isolates from a CF patient < 6 mo 60 mo 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 96 mo early and late isolate (Smith, Olson et al.) Analysis of 40 Chromosomal Regions: Comparison of Longitudinal CF Isolates Key Age (months) <6 1 24 27 416 547 1328

1438 17 14 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 Case \ Strain No changes No changes <9 30 33

1543 1546 30 1590 60 96 96 1638 1642 190383 36 36 5295 5296 1 1 1 1 1 C C T 1 2 1

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

5 6 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 G G

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

1 1 1 1 1 1 1 1 1 1 2 2 2 2 1 2 2 2 2 2 2 2 2 2 2 2

2 2 III. Adaptation to the CF Lung : Is There a Gene Expression Pattern Unique to the Infant CF Isolates? Transcriptional (mRNA) profiling using DNA microarrays CF-activated genes PA1290: probable transcriptional regulator PA5095: ABC transporter permease CF-repressed genes PA1008: bacterioferritin comigratory protein PA1244: hypothetical gene PA1708: popB - translocator protein PA1752: hypothetical gene PA2461: hypothetical gene # of patients (N=5) 5 5 5 5 5 5 5 Results: Mode of regulation for 7 genes is unique to a subset of clinical isolates (Ernst et al.) Cellular Protein Levels Do Not Always Correlate With Levels of the Corresponding Gene Transcripts Anaerobic regulation in PAO1: Postgenomic Analysis Genes/Proteins Total Quantified Regulated Induced Represed Regulated

Genes 209 42 Microarray Analysis 5600 209 108 101 13 Regulated Proteins 122 Proteomic Analysis 553 122 54 68 Quantified Proteins 553 IV. Adaptation to the CF Lung : Is There a Protein Expression Pattern Unique to the Infant CF Isolates? Quantitative protein profiling of differentially labeled whole cell protein Strain/Condition A Whole cell protein + ICAT LC-MS/MS Combine and proteolyze

Strain/Condition B ICAT-peptide mixture in silico analysis [Protein X in A] [Protein X in B] Pseudomonas aeruginosa Proteome Analysis: Regulation by Low Magnesium Stress Induces CF isolateSpecific Surface Modifications Laboratory-adapted Pseudomonas strain PAO-1 8 M Mg2+ CF-like phenotype 1 mM Mg2+ Differential protein labeling MS/in silico protein identification and quantitative analysis Postgenomic Analysis of Pseudomonas During Mg Limitation Transcriptional Profiling: ~2250 (40%) genes expressed 650 genes regulated Qualitative proteomic analysis: 1331 proteins identified Quantitative analysis (ICAT): 546 proteins quantified 76 proteins induced 69 proteins repressed ~ 50% correlation with transcriptional profiling data Selected Proteins Induced During Growth of Pseudomonas in Low Mg

Fold increase Conserved low Mg stress-response proteins two-component response regulator PhoP magnesium transport ATPase MgtA MgtC homologue 10.3 5.8 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 Quorum Sensing: Bacterial Intercellular Communication Via Small Signaling Molecules C4-HSL C12-HSL PQS Quorum Sensing: Secretion of Toxins, Virulence Factors Quorum Sensing: Biofilm, Antibiotic Resistance AB AB AB AB -keto-decanoic acid

Butyryl-ACP S-adenosylmethionine (SAM) Dodecanoyl-ACP PQS RhlI C4-HSL Acyl-homoserine lactones LasI C12-HSL PQS Production by Laboratory Strain of Pseudomonas Is Increased During Growth in Low Mg Mg2+ Conc. M M M m M m 8 1 8 1 WT PQS - High Levels of PQS Are Produced by CF Pseudomonas Isolates Grown in High Mg -1 S - od TI F1 F2 F3 F4 F5 O Q lo U C C C C C A b

P P PQS Production by Pseudomonas Isolates From Infants with Cystic Fibrosis Patient 1 2 3 4 6 7 8 9 10 102 103 104 105 107 108 109 111 201 202 203 204 205 206 209 211 212 # of isolates Age (mo) 3 4 5 20

5 15 4 27 10 8 2 10 2 1 6 5 3 2 6 6 2 17 8 2 11 6 4 to 36 12 to 21 3 to 36 9 to 36 21 to 36 6 to 33 18 to 27 6 to 36 12 to 36 27 to 36 27 to 33 18 to 36 27 to 33 33 12 to 21 30 to 36 12 to 24

15 to 18 24 to 36 18 to 36 33 15 to 36 12 to 33 21 to 30 12 to 36 12 to 36 190 isolates from 25 children up to 3 years of age analyzed for PQS production Bacteria were grown in medium with high [Mg2+] 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 Model of Chronic Pseudomonas aeruginosa Infection in Cystic Fibrosis Environmental Pseudomonas Bacterial Adaptation Lung Disease surface modifications Alginate/mucoidy Increased PQS Auxotrophy (biofilm, virulence, antibiotic resistance) Innate Immune Selective Pressure PA colonization-ASYMPTOMATIC Increased bacteria - SYMPTOMATIC Natural History Study: Infant patients isolates, 8-yr vs. early isolates Mild vs. Severe Study Genome sequencing DNA Microarray, Proteomic Analyses To Identify Additional Markers Natural History Study: Infant patients isolates, 8-yr vs. early isolates Mild vs. Severe Study Genome sequencing

DNA Microarray, Proteomic Analyses To Identify Additional Markers Develop tests for broad screening of large CF populations to validate markers specific for Pseudomonas adaptation Natural History Study: Infant patients isolates, 8-yr vs. early isolates Mild vs. Severe Study Genome sequencing DNA Microarray, Proteomic Analyses To Identify Additional Markers Develop tests for broad screening of large CF populations to validate markers specific for Pseudomonas adaptation Correlate with the disease outcome Disease outcome prediction Vaccine/drug development Bacterial Posttranslational Regulation Study: Pseudomonas Envelope Remodeling During Growth In Low Mg Gram-negative Bacterial Membrane Magnesium Stabilizes Gram-negative Outer Membrane O HO P O OH O O O O

O O NH O HO O O O P OO NH O O O O OH OH OH O - P O OH Mg Growth in low magnesium Growth in low magnesium O O O O O O O NH O HOO

P OH O NH O O O O OH OH OH Membrane stress Membrane stress Membrane remodeling Lipid A Membrane remodeling Gram-Negative Envelope Remodeling During Magnesium Limitation Lipid A acylation Alteration in outer membrane proteins Proteases PagP PagC PagN PgtE OprH OM IM PmrF

LPS modifications PhoQ PmrB Environmental sensing MgtA MgtC Small molecule transport Nutrient acquisition Modulation and resistance to the host innate immune defense: ICAT Analysis of Pseudomonas Membrane and Whole Cell Protein During Mg Limitation Pseudomonas strain PAO-1 8 M Mg2+ membrane 1 mM Mg2+ membrane 8 M Mg2+ whole cell 1 mM Mg2+ whole cell ICAT analysis ICAT analysis 163 proteins

486 proteins 106 proteins were quantified in both experiments: Compare relative protein levels in membrane vs. in whole cell Pseudomonas Metabolic Enzymes and Protein Translation Machinery Concentrate at the Membrane During Growth in Low Magnesium FI* membrane/FI whole cell Energy 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 machinery 30S ribosomal proteins (S2, S4, S13, S5) 1.5 1.8 elongation and ribosome recycling factor G

2.0 *FI = fold induction Bacterial ribosomal fractions Cytoplasmic Membrane-associated Soluble protein synthesis Membrane and secreted protein synthesis Bacterial ribosomal fractions Low Mg2+ membrane stress Cytoplasmic Membrane-associated Low Mg2+ membrane stress Soluble protein synthesis Increased membrane and secreted protein synthesis Formation of stress-induced multienzyme complexes Membrane lipid and protein remodeling Decreased membrane permeability Resistance to various antimicrobials Proteomic Analysis in Studying Bacterial Pathogens: Summary 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 Acknowledgements Manhong Wu Robert Ernst Hai Nguyen Sam Miller Jane Burns Eric Smith Maynard Olson David Goodlett Sam Purvine Ruedi Aebersold Jimmy Eng CFF NIH

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