Using informatics to focus bacterial pathogenicity studies
description
Transcript of Using informatics to focus bacterial pathogenicity studies
![Page 1: Using informatics to focus bacterial pathogenicity studies](https://reader036.fdocuments.in/reader036/viewer/2022062803/568146de550346895db415e9/html5/thumbnails/1.jpg)
Using informatics to focusbacterial pathogenicity studies
![Page 2: Using informatics to focus bacterial pathogenicity studies](https://reader036.fdocuments.in/reader036/viewer/2022062803/568146de550346895db415e9/html5/thumbnails/2.jpg)
Goal:
Use informatic analyses to generate new testable hypotheses about pathogen protein function and pathogenicity mechanisms
Test the hypotheses in the laboratory
Using informatics to focusbacterial pathogenicity studies
![Page 3: Using informatics to focus bacterial pathogenicity studies](https://reader036.fdocuments.in/reader036/viewer/2022062803/568146de550346895db415e9/html5/thumbnails/3.jpg)
• Gramicidine S (Consden et al., 1947), partial insulin sequence (Sanger and Tuppy, 1951)
• First codon assignment UUU/phe (Nirenberg and Matthaei, 1961)
• 3.5 kb RNA bacteriophage MS2 (Fiers et al., 1976) 5.4 kb bacteriophage X174 (Sanger et al., 1977)
• Early databases: Dayhoff, 1972; Erdmann, 1978
Need for informatics in biology: origins
![Page 4: Using informatics to focus bacterial pathogenicity studies](https://reader036.fdocuments.in/reader036/viewer/2022062803/568146de550346895db415e9/html5/thumbnails/4.jpg)
(from the National Centre for Biotechnology Information)
![Page 5: Using informatics to focus bacterial pathogenicity studies](https://reader036.fdocuments.in/reader036/viewer/2022062803/568146de550346895db415e9/html5/thumbnails/5.jpg)
Explosion of data
22 of the 33 publicly available microbial genome sequences are for bacterial pathogens
Approximately 18,000 pathogen genes with no known function!
>95 bacterial pathogen genome projects in progress…
![Page 6: Using informatics to focus bacterial pathogenicity studies](https://reader036.fdocuments.in/reader036/viewer/2022062803/568146de550346895db415e9/html5/thumbnails/6.jpg)
- Pseudomonas aeruginosa
- Three dimensional comparative protein modeling
- Phylogenetic analysis of gene families
- Other analyses: Regulatory network complexity
- Pathogenomics Project
- Detecting eukaryote:pathogen homologs
- Detecting pathogenicity islands
Pathogen Informatics
![Page 7: Using informatics to focus bacterial pathogenicity studies](https://reader036.fdocuments.in/reader036/viewer/2022062803/568146de550346895db415e9/html5/thumbnails/7.jpg)
Pseudomonas aeruginosa• Found in soil, water, plants, animals
• Common cause of hospital acquired infection: ICU patients, Burn victims, cancer patients
• Almost all cystic fibrosis (CF) patients infected by age 10
• Intrinsically resistant to many antibiotics
• No vaccine
![Page 8: Using informatics to focus bacterial pathogenicity studies](https://reader036.fdocuments.in/reader036/viewer/2022062803/568146de550346895db415e9/html5/thumbnails/8.jpg)
Outer membrane protein OprF
• Nonspecific porin
• Required for– Maintenance of cell shape – Growth in low-osmolarity environments
• OprF- clinical mutant with multiple antimicrobial resistance being characterized
• Adhesin in plant colonizing Pseudomonas species
• Proposed vaccine component
![Page 9: Using informatics to focus bacterial pathogenicity studies](https://reader036.fdocuments.in/reader036/viewer/2022062803/568146de550346895db415e9/html5/thumbnails/9.jpg)
POREPORIN
Peptidoglycan
LPS Mg++
Outermembrane
Cytoplasmicmembrane
Gram Negative Cell Envelope
Periplasm
![Page 10: Using informatics to focus bacterial pathogenicity studies](https://reader036.fdocuments.in/reader036/viewer/2022062803/568146de550346895db415e9/html5/thumbnails/10.jpg)
Structure of the outer membrane protein A transmembrane domain
Pautsch and Schulz (1998).Nature Structural Biology 5:1013-1017
No channel formation detected
![Page 11: Using informatics to focus bacterial pathogenicity studies](https://reader036.fdocuments.in/reader036/viewer/2022062803/568146de550346895db415e9/html5/thumbnails/11.jpg)
OprF 1 -QGQNSVEIEAFGKRYFTDSVRNMKN-------ADLYGGSIGYFLTDDVELALSYGEYHOmpA 1 APKDNTWYTGAKLGWSQYHDTGLINNNGPTHENKLGAGAFGGYQVNPYVGFEMGYDWLG * * * * ** * *
OprF 52 DVRGTYETGNKKVHGNLTSLDAIYHFGTPGVGLRPYVSAGLA-HQNITNINSDSQGRQQOmpA 60 RMPYKGSVENGAYKAQGVQLTAKLGYPIT-DDLDIYTRLGGMVWRADTYSNVYGKNHDT * * * * * * * *
OprF 110 MTMANIGAGLKYYFTENFFAKASLDGQYGLEKRDNGHQG--EWMAGLGVGFNFGOmpA 118 GVSPVFAGGVEYAITPEIATRLEYQWTNNIGDAHTIGTRPDNGMLSLGVSYRFG * * * * *** **
OprF and OmpA share only 15% identity
![Page 12: Using informatics to focus bacterial pathogenicity studies](https://reader036.fdocuments.in/reader036/viewer/2022062803/568146de550346895db415e9/html5/thumbnails/12.jpg)
Model of the N-terminus of OprF based on OmpA
Brinkman, Bains and Hancock (2000). Journal of Bacteriology 182:5251-5255
![Page 13: Using informatics to focus bacterial pathogenicity studies](https://reader036.fdocuments.in/reader036/viewer/2022062803/568146de550346895db415e9/html5/thumbnails/13.jpg)
OprF model (yellow and green) aligned with the crystal structure of OmpA (blue)
Many residues are in the same three dimensional environment, though on different strands
![Page 14: Using informatics to focus bacterial pathogenicity studies](https://reader036.fdocuments.in/reader036/viewer/2022062803/568146de550346895db415e9/html5/thumbnails/14.jpg)
OprF 1 -QGQNSVEIEAFGKRYFTDSVRNMKN-------ADLYGGSIGYFLTDDVELALSYGEYHOmpA 1 APKDNTWYTGAKLGWSQYHDTGLINNNGPTHENKLGAGAFGGYQVNPYVGFEMGYDWLG * * * * ** * *
OprF 52 DVRGTYETGNKKVHGNLTSLDAIYHFGTPGVGLRPYVSAGLA-HQNITNINSDSQGRQQOmpA 60 RMPYKGSVENGAYKAQGVQLTAKLGYPIT-DDLDIYTRLGGMVWRADTYSNVYGKNHDT * * * * * * * *
OprF 110 MTMANIGAGLKYYFTENFFAKASLDGQYGLEKRDNGHQG--EWMAGLGVGFNFGOmpA 118 GVSPVFAGGVEYAITPEIATRLEYQWTNNIGDAHTIGTRPDNGMLSLGVSYRFG * * * * *** **
OprF and OmpA similarity
![Page 15: Using informatics to focus bacterial pathogenicity studies](https://reader036.fdocuments.in/reader036/viewer/2022062803/568146de550346895db415e9/html5/thumbnails/15.jpg)
Residues implicated in blocking channel formation in OmpA are not conserved in OprF
![Page 16: Using informatics to focus bacterial pathogenicity studies](https://reader036.fdocuments.in/reader036/viewer/2022062803/568146de550346895db415e9/html5/thumbnails/16.jpg)
BathingSolution
PlanarBilayer
Membrane
VoltageSource
CurrentAmplifier
Protein
Planar Lipid Bilayer Apparatus
![Page 17: Using informatics to focus bacterial pathogenicity studies](https://reader036.fdocuments.in/reader036/viewer/2022062803/568146de550346895db415e9/html5/thumbnails/17.jpg)
The N-terminus of OprF forms channels in a lipid bilayer membrane
0
5
10
15
20
25
30
35
40
0.2
0.4
0.6
0.8 1
1.2
1.4
1.6
1.8 2
2.2
2.4
2.6
2.8 3
Single channel conductance (nS)
No
. o
f ev
ents
![Page 18: Using informatics to focus bacterial pathogenicity studies](https://reader036.fdocuments.in/reader036/viewer/2022062803/568146de550346895db415e9/html5/thumbnails/18.jpg)
Upstream of OprF is a probable sigma factor gene, sigX
sigX oprF
Promoter
Transcription terminator
![Page 19: Using informatics to focus bacterial pathogenicity studies](https://reader036.fdocuments.in/reader036/viewer/2022062803/568146de550346895db415e9/html5/thumbnails/19.jpg)
Disruption of sigX reduces expression of OprF
1. Marker2. Wildtype3. sigX- mutant4. oprF- mutant
P. aeruginosa P. fluorescens
![Page 20: Using informatics to focus bacterial pathogenicity studies](https://reader036.fdocuments.in/reader036/viewer/2022062803/568146de550346895db415e9/html5/thumbnails/20.jpg)
oprF
oprF
No SigX expression:
SigX expression:
sigX
sigX
![Page 21: Using informatics to focus bacterial pathogenicity studies](https://reader036.fdocuments.in/reader036/viewer/2022062803/568146de550346895db415e9/html5/thumbnails/21.jpg)
18 ECF sigma factors in the P. aeruginosa genome
![Page 22: Using informatics to focus bacterial pathogenicity studies](https://reader036.fdocuments.in/reader036/viewer/2022062803/568146de550346895db415e9/html5/thumbnails/22.jpg)
![Page 23: Using informatics to focus bacterial pathogenicity studies](https://reader036.fdocuments.in/reader036/viewer/2022062803/568146de550346895db415e9/html5/thumbnails/23.jpg)
0 1000 2000 3000 4000 5000 6000 7000Number of Genes
0
2
4
6
8
10R
egu
lato
rs (
%)
Percent Regulators as a Function of Genome Size
12 3
4 567
89 10
1112
13Specialized environmentsFree-living
Genomes represented: 1, Mycoplasma genitalium; 2, Chlamydia trachomatis; 3, Treponema pallidum; 4, Borrelia burgdorferi; 5, Chlamydia pneumoniae; 6, Helicobacter pylori ---; 7, Helicobacter pylori---; 8, Haemophilus influenzae; 9, Neisseria meningitidis; 10, Mycobacterium tuberculosis; 11, Bacillus subtilis; 12, Escherichia coli; 13, Pseudomonas aeruginosa.
![Page 24: Using informatics to focus bacterial pathogenicity studies](https://reader036.fdocuments.in/reader036/viewer/2022062803/568146de550346895db415e9/html5/thumbnails/24.jpg)
OprM Family of putative Efflux and Type I secretion proteins (18 members)
OprD Family of putative Amino acid, Peptide and Aromatic compound transporters (19 members)
TonB Family of putative iron-siderophore receptors (34 members)
P. aeruginosa Genome Sequence Analysis: Outer Membrane Proteins (OMPs)
Approximately 150 OMPs predicted including three large paralogous families:
![Page 25: Using informatics to focus bacterial pathogenicity studies](https://reader036.fdocuments.in/reader036/viewer/2022062803/568146de550346895db415e9/html5/thumbnails/25.jpg)
AprFOpmM
OpmH
OpmFOpmKOpmL
OpmN
OpmQ
OpmD
OprN
OpmE
OpmJOpmA
OprM OprJ
OpmB
OpmGOpmI
OprMFamily
(MultidrugEfflux?)
ProteinSecretion? TolC
![Page 26: Using informatics to focus bacterial pathogenicity studies](https://reader036.fdocuments.in/reader036/viewer/2022062803/568146de550346895db415e9/html5/thumbnails/26.jpg)
OprM structural model based on TolC
![Page 27: Using informatics to focus bacterial pathogenicity studies](https://reader036.fdocuments.in/reader036/viewer/2022062803/568146de550346895db415e9/html5/thumbnails/27.jpg)
OprM structural model based on TolC
![Page 28: Using informatics to focus bacterial pathogenicity studies](https://reader036.fdocuments.in/reader036/viewer/2022062803/568146de550346895db415e9/html5/thumbnails/28.jpg)
OprM structural model based on TolC
![Page 29: Using informatics to focus bacterial pathogenicity studies](https://reader036.fdocuments.in/reader036/viewer/2022062803/568146de550346895db415e9/html5/thumbnails/29.jpg)
Future Developments
• Modeling of other outer membrane proteins in Neisseria species.
• Developing a better algorithms for secondary structure prediction
![Page 30: Using informatics to focus bacterial pathogenicity studies](https://reader036.fdocuments.in/reader036/viewer/2022062803/568146de550346895db415e9/html5/thumbnails/30.jpg)
Pathogenomics
Goal:
Identify previously unrecognized mechanisms of microbial pathogenicity using a unique combination of informatics, evolutionary biology, microbiology and genetics.
![Page 31: Using informatics to focus bacterial pathogenicity studies](https://reader036.fdocuments.in/reader036/viewer/2022062803/568146de550346895db415e9/html5/thumbnails/31.jpg)
Pathogenicity
Processes of microbial pathogenicity at the molecular level are still minimally understood
Pathogen proteins identified that manipulate host cells by interacting with, or mimicking, host proteins.
Idea: Could we identify novel virulence factors by identifying pathogen genes more similar to host genes than you would expect based on phylogeny?
![Page 32: Using informatics to focus bacterial pathogenicity studies](https://reader036.fdocuments.in/reader036/viewer/2022062803/568146de550346895db415e9/html5/thumbnails/32.jpg)
Eukaryotic-like pathogen genes
- YopH, a protein-tyrosine phosphatase, of Yersinia pestis
- Enoyl-acyl carrier protein reductase (involved in lipid metabolism) of Chlamydia trachomatis
0.1
Aquifex aeolicus
Haemophilus influenza
Escherichia coli
Anabaena
Synechocystis
Chlamydia trachomatis
Petunia x hybrida
Nicotiana tabacum
Brassica napus
Arabidopsis thaliana
Oryza sativa
100
100
100
96
63
64
52
83
99
![Page 33: Using informatics to focus bacterial pathogenicity studies](https://reader036.fdocuments.in/reader036/viewer/2022062803/568146de550346895db415e9/html5/thumbnails/33.jpg)
Pathogens Anthrax Necrotizing fasciitis Cat scratch disease Paratyphoid/enteric feverChancroid Peptic ulcers and gastritisChlamydia Periodontal diseaseCholera PlagueDental caries PneumoniaDiarrhea (E. coli etc.) SalmonellosisDiphtheria Scarlet feverEpidemic typhus ShigellosisMediterranean fever Strep throatGastroenteritis SyphilisGonorrhea Toxic shock syndromeLegionnaires' disease Tuberculosis Leprosy TularemiaLeptospirosis Typhoid feverListeriosis UrethritisLyme disease Urinary Tract InfectionsMeliodosis Whooping cough Meningitis Hospital-acquired infections
![Page 34: Using informatics to focus bacterial pathogenicity studies](https://reader036.fdocuments.in/reader036/viewer/2022062803/568146de550346895db415e9/html5/thumbnails/34.jpg)
Pathogens
Chlamydophila psittaci Respiratory disease, primarily in birdsMycoplasma mycoides Contagious bovine pleuropneumoniaMycoplasma hyopneumoniae Pneumonia in pigsPasteurella haemolytica Cattle shipping feverPasteurella multicoda Cattle septicemia, pig rhinitisRalstonia solanacearum Plant bacterial wiltXanthomonas citri Citrus cankerXylella fastidiosa Citrus variegated chlorosis
Bacterial wilt
![Page 35: Using informatics to focus bacterial pathogenicity studies](https://reader036.fdocuments.in/reader036/viewer/2022062803/568146de550346895db415e9/html5/thumbnails/35.jpg)
Informatics/Bioinformatics
• BC Genome Sequence Centre
• Centre for Molecular Medicine and Therapeutics
Evolutionary Theory
• Dept of Zoology
• Dept of Botany
• Canadian Institute for Advanced Research
Pathogen Functions
• Dept. Microbiology
• Biotechnology Laboratory
• Dept. Medicine
• BC Centre for Disease Control
Host Functions
• Dept. Medical Genetics
• C. elegans Reverse Genetics Facility
• Dept. Biological Sciences SFU
Interdisciplinary group
![Page 36: Using informatics to focus bacterial pathogenicity studies](https://reader036.fdocuments.in/reader036/viewer/2022062803/568146de550346895db415e9/html5/thumbnails/36.jpg)
Prioritize for biological study. - Previously studied biologically? - Can UBC microbiologists study it? - C. elegans homolog?
Screen for candidate genes.Search pathogen genes against sequence databases. Identify those with eukaryotic similarity/motifs
Rank candidates.- how much like host protein?- info available about protein?
Modify screening method /algorithm
Approach
Evolutionary significance.- Horizontal transfer? - Similar by chance?
![Page 37: Using informatics to focus bacterial pathogenicity studies](https://reader036.fdocuments.in/reader036/viewer/2022062803/568146de550346895db415e9/html5/thumbnails/37.jpg)
Bacterium Eukaryote Horizontal Transfer
0.1
Bacillus subtilis
Escherichia coli
Salmonella typhimurium
Staphylococcua aureus
Clostridium perfringens
Clostridium difficile
Trichomonas vaginalis
Haemophilus influenzae
Acinetobacillus actinomycetemcomitans
Pasteurella multocida
N-acetylneuraminate lyase (NanA) of the protozoan Trichomonas vaginalis is 92-95% similar to NanA of Pasteurellaceae bacteria.
![Page 38: Using informatics to focus bacterial pathogenicity studies](https://reader036.fdocuments.in/reader036/viewer/2022062803/568146de550346895db415e9/html5/thumbnails/38.jpg)
N-acetylneuraminate lyase – role in pathogenicity?
Pasteurellaceae
•Mucosal pathogens of the respiratory tract
T. vaginalis
•Mucosal pathogen, causative agent of the STD Trichomonas
![Page 39: Using informatics to focus bacterial pathogenicity studies](https://reader036.fdocuments.in/reader036/viewer/2022062803/568146de550346895db415e9/html5/thumbnails/39.jpg)
N-acetylneuraminate lyase (sialic acid lyase, NanA)
Involved in sialic acid metabolism
Role in Bacteria: Proposed to parasitize the mucous membranes of animals for nutritional purposes
Role in Trichomonas: ?
Hydrolysis of glycosidic linkages of terminal sialic residues in glycoproteins, glycolipids Sialidase
Free sialic acid
Transporter
Free sialic acid NanA
N-acetyl-D-mannosamine + pyruvate
![Page 40: Using informatics to focus bacterial pathogenicity studies](https://reader036.fdocuments.in/reader036/viewer/2022062803/568146de550346895db415e9/html5/thumbnails/40.jpg)
Eukaryote Bacteria Horizontal Transfer?
0.1Rat
Human
Escherichia coli
Caenorhabditis elegans
Pig roundworm
Methanococcus jannaschii
Methanobacterium thermoautotrophicum
Bacillus subtilis
Streptococcus pyogenes
Aquifex aeolicus
Acinetobacter calcoaceticus
Haemophilus influenzae
Chlorobium vibrioforme
GMP reductase of E. coli is 81% similar to the corresponding enzyme studied in humans and rats
Role in virulence not yet investigated
![Page 41: Using informatics to focus bacterial pathogenicity studies](https://reader036.fdocuments.in/reader036/viewer/2022062803/568146de550346895db415e9/html5/thumbnails/41.jpg)
Eukaryote Bacteria Horizontal Transfer?
Ralstonia solanacearum cellulase (ENDO-1,4-BETA-GLUCANASE) is 56% similar to endoglucanase present in a number of fungi.
Demonstrated virulence factor for plant bacterial wilt
Hypocrea jecorina EGLII
Trichoderma viride EGL2
Penicillium janthinellum EGL2
Macrophomina phaseolina EGL2
Cryptococcus flavus CMC1
Ralstonia solanacearum egl
Humicola insolens CMC3
Humicola grisea CMC3
Aspergillus aculeatus CMC2
Aspergillus nidulans EGLA
Macrophomina phaseolina egl1
Aspergillus aculeatus CEL1
Aspergillus niger EGLB
Vibrio species manA
![Page 42: Using informatics to focus bacterial pathogenicity studies](https://reader036.fdocuments.in/reader036/viewer/2022062803/568146de550346895db415e9/html5/thumbnails/42.jpg)
World Research Community
Functional studiesPrioritized candidates
Study function of similar gene in model host, C. elegans.
Study function of gene.
Investigate role of bacterial gene in disease: Infection study in model host
C. elegans
DATABASE
Contact other groups for possible collaborations.
![Page 43: Using informatics to focus bacterial pathogenicity studies](https://reader036.fdocuments.in/reader036/viewer/2022062803/568146de550346895db415e9/html5/thumbnails/43.jpg)
Pathogenicity Islands
• Virulence genes commonly in clusters
• Associated with– tRNA sequences– Transposases, Integrases and other mobility
genes– Flanked by repeats
![Page 44: Using informatics to focus bacterial pathogenicity studies](https://reader036.fdocuments.in/reader036/viewer/2022062803/568146de550346895db415e9/html5/thumbnails/44.jpg)
G+C Analysis: Identifying Pathogenicity Islands
Yellow circle = high %G+C
Pink circle = low %G+C
tRNA gene lies between the two dots
rRNA gene lies between the two dots
Both tRNA and rRNA lie between the two dots
Dot is named a transposase
Dot is named an integrase
![Page 45: Using informatics to focus bacterial pathogenicity studies](https://reader036.fdocuments.in/reader036/viewer/2022062803/568146de550346895db415e9/html5/thumbnails/45.jpg)
Neisseria meningitidis serogroup B strain MC58 Mean %G+C: 51.37 STD DEV: 7.57
%G+C SD Location Strand Product 37.22 -1 1831577..1832527 + pilin gene inverting 39.95 -1 1834676..1835113 + VapD-related 51.96 1835110..1835211 - cryptic plasmid A-related 39.13 -1 1835357..1835701 + hypothetical 40.00 -1 1836009..1836203 + hypothetical 42.86 -1 1836558..1836788 + hypothetical 34.74 -2 1837037..1837249 + hypothetical 43.96 1837432..1838796 + conserved hypothetical 40.83 -1 1839157..1839663 + conserved hypothetical 42.34 -1 1839826..1841079 + conserved hypothetical 47.99 1841404..1843191 - put. hemolysin activ. HecB 45.32 1843246..1843704 - put. toxin-activating 37.14 -1 1843870..1844184 - hypothetical 31.67 -2 1844196..1844495 - hypothetical 37.57 -1 1844476..1845489 - hypothetical 20.38 -2 1845558..1845974 - hypothetical 45.69 1845978..1853522 - hemagglutinin/hemolysin-rel. 51.35 1854101..1855066 + transposase, IS30 family
![Page 46: Using informatics to focus bacterial pathogenicity studies](https://reader036.fdocuments.in/reader036/viewer/2022062803/568146de550346895db415e9/html5/thumbnails/46.jpg)
%G+C of ORFs: Analysis of Variance
• %G+C variance is similar within a given species
• Low %G+C variance correlates with an intracellular lifestyle for the bacterium and a clonal nature (P = 0.004)
• Neisseria meningitidis +/- 7%• Chlamydia species +/- 2%
Intracellular bacteria ecologically isolated?
![Page 47: Using informatics to focus bacterial pathogenicity studies](https://reader036.fdocuments.in/reader036/viewer/2022062803/568146de550346895db415e9/html5/thumbnails/47.jpg)
Future Developments
• Identify eukaryotic motifs and domains in pathogen genes
• Identify further motifs associated with• Pathogenicity islands• Virulence determinants
• Functional tests for new potential virulence factors
www.pathogenomics.bc.ca
![Page 48: Using informatics to focus bacterial pathogenicity studies](https://reader036.fdocuments.in/reader036/viewer/2022062803/568146de550346895db415e9/html5/thumbnails/48.jpg)
Informatics as a focus
• Outer membrane protein modeling: Focus mutational studies and studies of surface exposed sequences
• Phylogenetic analyses: Focus study of gene mutants under certain environmental conditions
• Other analyses - Regulatory network complexity: Change focus of regulation studies
• Eukaryote:pathogen homologs: Focus identification of “mimics”
• Pathogenicity islands: Focus identification of recently obtained virulence determinants
![Page 49: Using informatics to focus bacterial pathogenicity studies](https://reader036.fdocuments.in/reader036/viewer/2022062803/568146de550346895db415e9/html5/thumbnails/49.jpg)
Acknowledgements• Pathogenomics group: Ann Rose, Steven
Jones, Ivan Wan, Hans Greberg, Yossef Av-Gay, David Baillie, Bob Brunham, Stefanie Butland, Rachel Fernandez, Brett Finlay, Patrick Keeling, Audrey de Koning, Sarah Otto, Francis Ouellette, Peter Wall Institute
• Pseudomonas Genome Project: PathoGenesis Corp. (Ken Stover) and University of Washington (Maynard Olsen)
• Outer membrane proteins: Manjeet Bains, Kendy Wong, Canadian Cystic Fibrosis Foundation
• Bob Hancock