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Computational tools to aid identification of potential horizontally transferred genes involved in pathogenicity
Fiona S. L. Brinkman 1,2, Hans Greberg 1,3, Ivan Wan 1,3, Yossef Av-Gay 4, David L. Baillie 5, Robert Brunham 6, Rachel C. Fernandez 2, B. Brett Finlay 2,8, Robert
E.W. Hancock 2, Audrey de Koning 9, Patrick Keeling 10, Emma Macfarlane 2, Don G. Moerman 9,11, Sarah P. Otto 9, B. Francis Ouellette 7, Hong Yan 2,
Ann
M. Rose 1, and Steven J. Jones 3.
1 Dept of Medical Genetics, 2 Dept of Microbiology and Immunology, 4 Dept of Medicine, 8 Biotechnology Laboratory, 9 Dept of Zoology, 11 C. elegans Reverse Genetics Facility, 10 Dept of Botany, University of British Columbia, 5 Dept
of Biological Sciences, Simon Fraser University, 7 Centre for Molecular Medicine and Therapeutics, 6 UBC Centre for Disease Control and 3 Genome Sequence Centre, BC Cancer Agency, Vancouver, British Columbia, Canada.
www.pathogenomics.bc.ca
Abstract
Evidence is increasing that pathogens often develop virulence though the
acquisition of sequences encoding virulence factors that are horizontally
transferred. The Pathogenomics Project funded by the Peter Wall Institute
for Advanced Studies is developing software to aid identification of
horizontally transferred sequences of relevance to pathogenicity. Candidate
virulence genes identified are being targeted for further functional study as
part of this interdisciplinary project. Our approach has enabled us to not only
identify new potential virulence factors, but also gain insight into the
frequency of horizontal gene transfer within the Bacteria, and between the
three domains of life of Bacteria, Eukarya, and Archaea.
Tool 1: “IslandPath” – aiding identification of
pathogenicity islands
Rationale: Pathogenicity islands in genomes tend to have atypical %G+C,
contain mobility genes (i.e. transposases, integrases), and are associated
with tRNA sequences. Combined identification of such features could
facilitate the identification of genes in new genomes sequences that are
involved in virulence, or have horizontal origins.
Tool 2: “TransBAE” - Identifying CrossDomain Lateral Transfer
Rationale: Pathogen proteins have been identified that manipulate
host cells by interacting with, or mimicking, host proteins. We
wondered whether we could identify selected novel virulence factors by
identifying bacterial pathogen genes more similar to host genes than
you would expect based on phylogeny. The tool we developed
investigates this, and is also useful for identifying cross-domain lateral
gene transfer events (i.e. Trans - Bacteria, Archaea and Eukarya).
Description: Proteins in a given pathogen genome that are more
similar to eukaryote proteins than other proteins (and vice versa) are
identified through BLAST analysis, followed by a scoring system we
developed. Various taxonomic levels of organisms are filtered from the
BLAST results to identify putative lateral transfers that occurred before
or after species, genus, family etc… divergence. This analysis has also
been expanded to analyze all bacterial genomes, and to make all
cross-domain comparisons between Bacteria, Archaea and Eukarya.
A
We have found that most cases of probable recent
cross-domain gene transfer involve movement of a
bacterial gene to a unicellular eukaryote. It has been
proposed that such eukaryotes may obtain bacterial
genes through ingestion of bacteria (the “you are what
you eat” hypothesis; 3). We have found no cases to
date of recent (since the divergence of humans from
mammals) lateral gene exchange between
multicellular eukaryotes and bacteria, suggesting that
such occurrences are rare. This has significance for
both the evolution of mechanisms of pathogen host
mimicry, and also for movement of genes of relevant to
the use of genetically modified foods.
Example: (Below) Portion of the graphic and (edited) table for the Neisseria
meningitidis MC58 genome is shown, illustrating the location of a cluster of
genes that may be involved in pathogenicity (1).
B
%G+C
24.40
46.35
44.33
46.41
37.22
39.95
51.96
39.13
40.00
42.86
34.74
43.96
40.83
42.34
47.99
45.32
37.14
31.67
37.57
20.38
45.69
51.35
SD
-2
-1
-1
-1
-1
-1
-2
-1
-1
-1
-2
-1
-2
Location
Strand Product
1827729..1828019
+
hypothetical
1828060..1829565
+
tspB protein, putative
1829566..1829856
+
conserved hypothetical
1829866..1830951
+
conserved hypothetical
1831577..1832527
+
pilin gene inverting PivNM-2
1834676..1835113
+
virulence assoc. pro. homolog
1835110..1835211
cryptic plasmid A-related
1835357..1835701
+
hypothetical
1836009..1836203
+
hypothetical
1836558..1836788
+
hypothetical
1837037..1837249
+
hypothetical
1837432..1838796
+
conserved hypothetical
1839157..1839663
+
conserved hypothetical
1839826..1841079
+
conserved hypothetical
1841404..1843191
put. hemolysin activ. HecB
1843246..1843704
put. toxin-activating
1843870..1844184
hypothetical
1844196..1844495
hypothetical
1844476..1845489
hypothetical
1845558..1845974
hypothetical
1845978..1853522
hemagglutinin/hemolysin-rel.
1854101..1855066
+
transposase, IS30 family
1. Correlation between variance of ORF G+C in a
genome and clonality of the pathogen. %G+C
analysis of genome ORFs, used to identify
pathogenicity islands, revealed the following trend:
Low variance of the mean G+C of ORFs for a given
genome correlates with an intracellular lifestyle for the
bacterium and a clonal nature (Two-tailed P value of
0.004, for a nonparametric correlation). Variance is
similar within a given species. Variance of %G+C for
ORFs may therefore be a useful marker for
investigating the clonality of bacteria. Its relationship
with intracellular lifestyle may reflect the ecological
isolation of intracellular bacteria, as was previously
proposed to explain the lack of chromosome
rearrangement for Chlamydia species (2).
2. Detecting lateral gene transfer between Bacteria
and Eukarya. While our primary focus is to identify
new genes or pathways involved in virulence, our
approach has also identified the strongest cases of
lateral gene transfer between bacteria and eukaryotes
identified to date, and facilitates the identification of
organellar genes that have moved to the nucleus (due
to the bacterial origin of organellar genes).
Description: Each dot in a graphic corresponds to a predicted proteincoding ORF in the genome. Dot colours indicate if an ORF has a higher or
lower %G+C than cutoffs you set (default settings are plus or minus 1 Std.
Dev. from the mean %G+C for all genes in the genome). You may click on a
dot to view a portion of an annotation table presented below the graphic.
Neisseria meningitidis serogroup B strain MC58
Mean %G+C: 51.37
STD DEV: 7.57
Using the Tools: Some Trends
Using the Tools: Examples of interesting
genes identified
The protozoan pathogen Trichomonas
vaginalis appears to have obtained the gene
for N-acetylneuraminate lyase (NanA) from
an ancestor of pathogenic Pasterellaceae
bacteria (based on phylogenetic analysis
and 92-95% sequence similarity; 5). NanA is
involved in sialic acid metabolism and is
used by some bacteria to parasitize the
mucous membranes of animals for
nutritional purposes. It is possible that T.
vaginalis acquired this gene to aid its
parasitization of animal/human tissues.
A Streptomyces gene may be the “missing link” to explain the
occurrence of some sensor histidine kinases (NIK and FIK) in
Candida sp. and Fusarium sp. pathogenic fungi (Brinkman et al.,
submitted). Histidine kinases are common in bacteria but relatively
uncommon in eukaryotes, and phylogenetic analysis suggests that
these virulence-associated histidine kinases in the fungi were
obtained by lateral gene transfer from bacteria. All orthologs of this
gene (LemA, GacS, etc…) examined to date have a role in
virulence.
In most cases, the “plant-like” genes reported previously in the
Chlamydia sp. genomes (6) may have plastid origins, as
Synechocystis sp., a relative of the ancestor of the plastid, also
shares notable similarity to these genes.
Other Genes: New, potential, islands of horizontally transferred
genes, containing “hypothetical genes”, were identified in almost
all microbial genomes examined to date. “Odd” bacterial genes
with notable similarity to animal (metazoan) genes were identified,
however, in most cases more sampling of sequences from other
organisms is needed to identify whether the genes are a case of
horizontal gene transfer, selective gene maintenance and gene
loss, or of organellar origin. Promising genes are in the process of
being investigated further.
Tool 3: “PhyloBLAST” – aiding
phylogenetic analysis
C
Acknowledgements
This project is funded by the Peter
Wall Institute for Advanced Studies.
PhyloBLAST compares your protein sequence to a
SWISSPROT/ TREMBL database using BLAST2 and then
allows you to perform user-defined phylogenetic analyses
based on user-selected proteins listed in the BLAST
output (4). PhyloBLAST was initially developed to aid
analysis of lateral gene transfer events detected by
“TransBAE”, but is now available on the internet as its own
web-based application at:
www.pathogenomics.bc.ca/phyloBLAST
Some Features
Example: (Above) Screenshot A: Overview of no. of proteins
identified from each pathogen genome that are most similar to
eukaryotic proteins. Screen B: List of further information about a
subset of proteins (H. influenzae proteins in this case) and the
eukaryotic proteins they are similar to. Screen C: Colourized
summary of BLAST analysis for a M. tuberculosis protein of interest.
- Organism information and phylogenetic distance
measures are added to the BLAST output and subsequent
phylogenetic trees
- You may select BLAST hits for further phylogenetic
analysis, or you may input your own sequences or
alignments. Analyses vary from obtaining a FASTA file of
the sequences, a ClustalW alignment, or user-defined
phylogenetic trees (based on PHYLIP).
References
1.
Tettelin H, et al., 2000. Science 287:1809-1815.
2.
Read TD, et al. 2000. Nucleic Acids Res. 28:1397-1406.
3.
Doolittle WF. 1998. Trends Genet. 14:307-311.
4.
Brinkman FSL, et al. 2001. Bioinformatics. In Press.
5.
de Koning A, et al., 2000. Mol. Biol. Evol. 17:1769-1773.
6.
Stephens RS, et al. 1998. Science. 282:754-759.