Pathogens being Studied

1
Pathogenomics An interdisciplinary approach for
the study of infectious disease Fiona S. L.
Brinkman 1,2, Yossef Av-Gay 3, David L. Baillie
4, Stefanie Butland 5, Rachel C. Fernandez2, B.
Brett Finlay 2,6, Robert E.W. Hancock 2, Christy
Haywood-Farmer 7, Steven J. Jones 8, Audrey de
Koning 7, Don G. Moerman 7,9, Sarah P. Otto 7, B.
Francis Ouellette 5, Iain E. P. Taylor 10, and
Ann M. Rose 1. 1 Dept of Medical Genetics, 2
Dept of Microbiology and Immunology, 3 Dept of
Medicine, 6 Biotechnology Laboratory, 7 Dept of
Zoology, 9 C. elegans Reverse Genetics Facility,
10 Dept of Botany, University of British
Columbia, 4 Dept of Biological Sciences, Simon
Fraser University, 5 Centre for Molecular
Medicine and Therapeutics and 8 BC Genome
Sequence Centre, Centre for Integrated Genomics,
Vancouver, British Columbia, Canada.
Goal This project brings together a unique
combination of UBC researchers and affiliates
who, through exchange of new data and ideas, and
capitalizing on new genomic and bioinformatic
tools, will develop an automated approach to
identify previously unrecognized mechanisms of
pathogenicity.
Pathogens being Studied (selected
examples) Pathogen Primary Disease Bordetella
pertussis Whooping cough Borrelia burgdorferi
Lyme disease Campylobacter jejuni Gastroenterit
is Chlamydia pneumoniae Chlamydial
pneumonia Chlamydia trachomatis
Chlamydia Escherichia coli Diarrheal and
urinary tract infections Haemophilus
influenzae Upper respiratory infections and
Meningitis Helicobacter pylori Peptic ulcers
and gastritis Leishmania major Leishmaniasis
(kala azar) Listeria monocytogenes Listeriosis M
ycoplasma pneumoniae Mycoplasmal
pneumonia Mycobacterium tuberculosis
Tuberculosis Neisseria gonorrhoeae Gonorrhea Nei
sseria meningitidis Meningitis Plasmodium
falciparum Malaria Pseudomonas
aerguinosa Variety of mucosal infections
(opportunistic) Rickettsia prowazekii Epidemic
typhus Salmonella typhi Typhoid
fever Streptococcus pyogenes Strep throat,
scarlet fever, necrotizing fasciitis Treponema
pallidum Syphillis Ureaplasma
urealyticum Urethritis Vibrio cholerae
Cholera Yersinia pestis Plague
Project Summary We are utilizing bioinformatics
tools to identify pathogen genes which interact
with their host proteins and pathways. A unique
combination of informatics, evolutionary biology,
microbiology and eukaryotic genetics is being
exploited to identify pathogen genes which are
more similar to host genes than expected, and
likely to interact with, or mimic, their hosts
gene functions. We are building a database of the
sequences of these proteins, based on the
increasing number of pathogen genomes which have
been, or are currently being, sequenced.
Candidate functions identified by our informatics
approach will be tested in the laboratory (see
flow chart) to investigate their role in pathogen
infection and host interaction. All information
will be eventually made available in a public
Pathogenomics Database.

• Rationale and Power of the Approach
• The processes of microbial pathogenicity at the
  molecular level are still minimally understood.
  Genomics and bioinformatics provide powerful new
  tools for the study of pathogenicity, hence the
  initiation at UBC by Dr. Julian Davies of a new
  field, Pathogenomics. The specific approach we
  are proposing is anchored in the fact that, as
  part of the infectivity process, many pathogens
  make use of host cellular processes. We
  hypothesize that some pathogen genes involved in
  such processes will be more similar to host genes
  than would be expected (based on phylogeny). We
  will identify such genes by applying specific
  bioinformatic and evolutionary analysis tools to
  sequenced genome datasets, and further examine
  such genes in the laboratory (both the pathogen
  gene and homolgous model host gene). We
  hypothesize that this approach will reveal new
  mechanisms of pathogen-host interaction, leading
  to a deeper understanding of the fundamentals of
  pathogenicity.
• Power of the Approach
• Expression-independent method for identifying
  possible pathogenicity factors.
• Interdisciplinary team fosters unique ideas and
  collaborations.
• Automated approach can be continually updated.
• Enables better understanding of both the pathogen
  gene and homologous host/model host gene.
• Provides insight into horizontal gene transfer
  events and the evolution of pathogen-host
  interactions.
• Public database of findings, to be developed,
  will enable other researchers to capitalize on
  the findings and promote further collaboration.

Examples Selected examples of pathogen proteins
with higher than expected similarity to
host/eukaryotic proteins Yop proteins of
Yersinia species The Yop virulon is an integrated
system allowing extracellular Yersinia bacteria
to disarm host cells involved in the immune
response, to disrupt their communications (or
even to induce their apoptosis) by the injection
of bacterial effector proteins (for review, see
Cornelis, 1998). YopH, a protein-tyrosine
phosphatase, is a member of this system and it
shares higher than expected similarity to
eukaryotic protein-tyrosine phosphatases.
Isoleucyl-tRNA synthetase of Staphylococcus
aureus and others Resistance to mupirocin, a
topical antimicrobial agent used against S.
aureus, appears to be mediated by amino-acid
substitutions in isoleucyl-tRNA synthetase (ITS)
which mupirocin normally inactivates. The source
of this mutant ITS is not recent random mutation
of S. aureus ITS, but rather a plasmid containing
an ITS gene that is more similar to eukaryotic
ITS than organism phylogeny would predict (Brown
et al., 1998). Other bacteria have been
identified that contain this mutant ITS (that is
similar to eukaryotic ITS), and all of these
bacteria share resistance to mupirocin. Based on
phylogenetic analysis, Brown et al., propose that
a eukaryotic ITS gene was transferred to an
unknown bacteria shortly after Eukarya and
Archaea divergence, and that this gene was then
recently transferred via a plasmid to S. aureus.
Since Pseudomonas fluorescens naturally produces
mupirocin (as pseudomonic acid), resistance to
this compound may have conferred a competitive
advantage to specific bacteria. Enoyl-ACP
reductase of Chlamydia trachomatis C. trachomatis
contains a number of eukaryotic-like genes
involved in functions such as fatty acid
biosynthesis. Most of these group
phylogenetically with plant proteins (see tree
below). Stephens et al. (1998) have proposed that
the evolution of chlamydiae as intracellular
parasites started with an opportunistic
interaction with amoebal hosts, and the
protochlamydiae became amoebal parasites or
symbionts for a period long enough to acquire the
"plant-like" genes, whose origin may actually be
amoebal.
Initial screen for candidate genes. Search
pathogen proteins against sequence databases.
Are the results inconsistent with the phylogeny
(i.e. does the protein match more strongly the
host, or its relatives, than you would expect?)
Use low complexity filtering such as SEG.
Rank candidates. Rank pathogen protein in terms
of how much more they resemble their host phyla
than their own (e.g. the difference in BLAST
score, through phylogenetic tree building, and by
identifying unusual codon usage). Is the gene or
gene's pathway a usual component of the pathogens
phyla? Also rank based on other factors such
whether the candidate gene encodes a probable
surface-exposed or secreted protein.
Iteratively refine the initial screening methods
and candidate ranking.
Evolutionary significance. Manually inspect
candidates. Are these valid cases of horizontal
transfer, convergance and co-evolution or are
they similar by chance? If horizontal transfer
may be involved, when did this transfer occur?
Prioritize for further biological study. Has the
candidate pathogen gene or a eukaryotic homolog
been previously studied biologically? Can a
putative function be inferred from its sequence?
Is there a C. elegans homolog? Is the pathogen
currently studied by UBC functional pathogenomics
bacterial group? Has the genetic pathway of the
host protein been dissected?
Above Small subunit rRNA tree for organisms
whose genomes are completed (plus selected
reference eukaryotes). Neighbor-joining tree
constructed using Ribosomal Database Project
(www.cme.msu.edu/RDP/html) alignments.
An Interdisciplinary Team Our team
comprises an unique group of Bioinformaticians,
Evolutionary Theorists/Mathematical Modelers,
Microbiologists, Geneticists and an Ethicist
(not all are shown above).
If C. elegans homolog exists target gene for
knockout by knockout facility.
If pathogen being studied by UBC functional
pathogenomics bacterial group Examine
subcellular localization and obtain a knockout of
the gene.
If pathogen is not a focus of UBC group Contact
other groups regarding results instigate
collaboration for further study.
Acknowledgements This project is funded by the
Peter Wall Institute for Advanced Studies, which
supports fundamental, interdisciplinary research
and creative activities, which have the potential
to result in significant advances to
knowledge.
Analysis of knockout through expression chip, and
susceptibility to infection by pathogen.

• References
• Felsenstein, J.. 1996. Methods Enzymol. 266
  418-427.
• Stephens, R.S., S. Kalman, C. Lammel, J. Fan, R.
  Marathe, L. Aravind, W. Mitchell, L. Olinger,
  R.L. Tatusov, Q. Zhao, E.V. Koonin, R.W. Davis.
  1998. Science 282 754 759.
• Brown, J.R., J. Zhang, J.E. Hodgson. 1998.
  Current Bio. 8R365-R367.
• Cornelis, G.R. A. Boland, A.P. Boyd, C. Geuijen,
  M. Iriarte, C. Neyt, M.P. Sory, I. Stainier.
  1998. Microbiol Mol Biol Rev 621315-1352.

Analysis of knockout and gene through expression
chip analysis and infectivity in an animal/tissue
culture model, and C. elegans model if appropriate
Target for GFP fusion analysis to see when and
where the gene is expressed in C. elegans
Aquifex aeolicus
96
Left Phylogeny of chlamydial enoyl-acyl carrier
protein reductase (a protein involved in lipid
metabolism) using the neighbor-joining distance
method (Felsenstein, 1996). Numbers at forks
indicate the number of times out of 100 that the
given node was observed.
Haemophilus influenza
100
Escherichia coli
Continually exchange C. elegans gene information
with microbiologists studying homologous pathogen
gene
Continually exchange pathogen gene information
with collaborators and with eukaryotic
geneticists studying homologous gene in C.
elegans
Anabaena
100
Synechocystis
100
Chlamydia trachomatis
63
Petunia x hybrida
64
Nicotiana tabacum
83
Database development. Create and maintain a
database of pathogen-host interactions.
Establish this as a platform for accelerating the
study of pathogenicity and the identification of
therapeutic drug targets.
Brassica napus
99
Arabidopsis thaliana
0.1
52
Oryza sativa