protws2 4572

Information about protws2 4572

Published on October 29, 2007

Author: Danielle

Source: authorstream.com

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Slide1:  Proteomics in Analysis of Bacterial Pathogens Tina Guina University of Washington, Seattle Slide2:  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 Outline Slide3:  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 and Cystic Fibrosis Slide4:  Environmental P. aeruginosa Model of Chronic Pseudomonas aeruginosa Infection in Cystic Fibrosis Slide5:  Environmental P. aeruginosa Model of Chronic Pseudomonas aeruginosa Infection in Cystic Fibrosis PA colonization - ASYMPTOMATIC CFTR- Unknown Innate immune defect Slide6:  Environmental P. aeruginosa Innate Immune Selective Pressure Bacterial Adaptation PA colonization - ASYMPTOMATIC Model of Chronic Pseudomonas aeruginosa Infection in Cystic Fibrosis CFTR- Unknown Innate immune defect Slide7:  Environmental Pseudomonas Innate Immune Selective Pressure Bacterial Adaptation Unique surface modifications Increased airway inflammation Resistance to antimicrobials Chronic Lung Disease PA colonization - ASYMPTOMATIC Increased bacterial burden - SYMPTOMATIC Model of Chronic Pseudomonas aeruginosa Infection in Cystic Fibrosis CFTR- Unknown Innate immune defect Slide8:  Bacterial Adaptation Chronic Lung Disease PA colonization - ASYMPTOMATIC Increased bacterial burden - SYMPTOMATIC Model of Chronic Pseudomonas aeruginosa Infection in Cystic Fibrosis ? Slide9:  Bacterial Adaptation Chronic Lung Disease PA colonization - ASYMPTOMATIC Increased bacterial burden - SYMPTOMATIC Model of Chronic Pseudomonas aeruginosa Infection in Cystic Fibrosis ? Intervention Slide10:  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: Slide11:  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 :  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) Slide13:  Postgenomic Analysis of Pseudomonas in CF Environmental isolates Clinical CF Isolates Microarray Analysis Proteomic Analysis Bioinformatics Identification of CF-unique Characteristics Phenotypic Analysis Genomic Analysis Slide14:  Pseudomonas Adapt to the Cystic Fibrosis Lung Environment Slide15:  CF Isolate-Specific Characteristics: 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 1) Increased Antimicrobial Peptide Resistance (Ernst et al. 1999, Hajjar et al. 2002) Slide16:  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 Organization of Pseudomonas CF Infant and Environmental Isolates Similar? (Ernst et al. 2003) II. Adaptation to the CF Lung : Is Genomic Organization of Longitudinal Pseudomonas CF Isolates Similar?:  II. Adaptation to the CF Lung : Is Genomic Organization of Longitudinal Pseudomonas 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 Sequencing of parentally-related Pseudomonas isolates from a CF patient (Smith, Olson et al.) Analysis of 40 Chromosomal Regions: Comparison of Longitudinal CF Isolates:  Analysis of 40 Chromosomal Regions: Comparison of Longitudinal CF Isolates Slide19:  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 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 subset of clinical isolates Slide20:  Cellular Protein Levels Do Not Always Correlate With Levels of the Corresponding Gene Transcripts Anaerobic regulation in PAO1: Postgenomic Analysis Regulated Genes 209 Regulated Proteins 122 Quantified Proteins 553 13 42 Slide21:  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 Whole cell protein + ICAT Strain/Condition A Combine and proteolyze mLC-MS/MS in silico analysis Strain/Condition B [Protein X in A] [Protein X in B] Slide22:  Pseudomonas aeruginosa Proteome Analysis: Regulation by Low Magnesium Stress Induces CF isolate- Specific Surface Modifications Laboratory-adapted Pseudomonas strain PAO-1 8 mM Mg2+ CF-like phenotype 1 mM Mg2+ Differential protein labeling MS/in silico protein identification and quantitative analysis Slide23:  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 Pseudomonas During Mg Limitation Slide24:  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 Pseudomonas in Low Mg Slide25:  Quorum Sensing: Bacterial Intercellular Communication Via Small Signaling Molecules C4-HSL C12-HSL PQS Slide26:  Quorum Sensing: Secretion of Toxins, Virulence Factors Slide27:  Quorum Sensing: Biofilm, Antibiotic Resistance AB AB AB AB Slide28:  S-adenosylmethionine (SAM) Butyryl-ACP Dodecanoyl-ACP C4-HSL C12-HSL RhlI LasI b-keto-decanoic acid PQS Acyl-homoserine lactones Slide29:  PQS Production by Laboratory Strain of Pseudomonas Is Increased During Growth in Low Mg Slide30:  High Levels of PQS Are Produced by CF Pseudomonas Isolates Grown in High Mg Slide31:  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 Pseudomonas Isolates From Infants with Cystic Fibrosis Slide32:  PQS Production by Isolates from Infants with CF Similar to CF-specific surface modifications, most Pseudomonas clinical isolates from young children with CF produce high PQS levels Slide33:  Environmental Pseudomonas PA colonization-ASYMPTOMATIC Model of Chronic Pseudomonas aeruginosa Infection in Cystic Fibrosis Bacterial Adaptation Alginate/mucoidy Auxotrophy Increased bacteria - SYMPTOMATIC Lung Disease surface modifications Increased PQS (biofilm, virulence, antibiotic resistance) Innate Immune Selective Pressure Slide34:  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 Slide35:  Natural History Study: Infant patients isolates, 8-yr vs. early isolates Mild vs. Severe Study Develop tests for broad screening of large CF populations to validate markers specific for Pseudomonas adaptation Genome sequencing DNA Microarray, Proteomic Analyses To Identify Additional Markers Slide36:  Natural History Study: Infant patients isolates, 8-yr vs. early isolates Mild vs. Severe Study 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 Genome sequencing DNA Microarray, Proteomic Analyses To Identify Additional Markers Slide37:  Bacterial Posttranslational Regulation Study: Pseudomonas Envelope Remodeling During Growth In Low Mg Slide38:  Gram-negative Bacterial Membrane Slide39:  Magnesium Stabilizes Gram-negative Outer Membrane O O O OH O OH OH OH O O O O HO O O O O P OH NH O O -O O NH P O O O O OH O OH OH O- O O O O HO O O O O P OH NH O O HO O NH P O Mg Growth in low magnesium Membrane stress Membrane remodeling Growth in low magnesium Membrane stress Membrane remodeling Lipid A Slide40:  Gram-Negative Envelope Remodeling During Magnesium Limitation PagP PagC PagN PgtE OprH PmrF Environmental sensing Lipid A acylation MgtA MgtC Small molecule transport Nutrient acquisition LPS modifications PhoQ PmrB Proteases Modulation and resistance to the host innate immune defense: Alteration in outer membrane proteins OM IM Slide41:  ICAT Analysis of Pseudomonas Membrane and Whole Cell Protein During Mg Limitation Pseudomonas strain PAO-1 8 mM Mg2+ membrane 1 mM Mg2+ membrane ICAT analysis 163 proteins 8 mM Mg2+ whole cell 1 mM Mg2+ whole cell ICAT analysis 486 proteins 106 proteins were quantified in both experiments: Compare relative protein levels in membrane vs. in whole cell Slide42:  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 Pseudomonas Metabolic Enzymes and Protein Translation Machinery Concentrate at the Membrane During Growth in Low Magnesium *FI = fold induction Slide43:  Bacterial ribosomal fractions Cytoplasmic Soluble protein synthesis Membrane-associated Membrane and secreted protein synthesis Slide44:  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 remodeling Decreased membrane permeability Resistance to various antimicrobials Formation of stress-induced multienzyme complexes Slide45:  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: Summary Slide46:  Manhong Wu Robert Ernst Hai Nguyen Sam Miller Jane Burns Eric Smith Maynard Olson Acknowledgements David Goodlett Sam Purvine Ruedi Aebersold Jimmy Eng CFF NIH

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