Nucleic Acids Research Advance Access published online on October 20, 2009
Nucleic Acids Research, doi:10.1093/nar/gkp851
© The Author(s) 2009. Published by Oxford University Press.
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.5/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
TriTrypDB: a functional genomic resource for the Trypanosomatidae
Martin Aslett1,
Cristina Aurrecoechea2,
Matthew Berriman1,
John Brestelli3,
Brian P. Brunk3,
Mark Carrington4,
Daniel P. Depledge1,
Steve Fischer3,
Bindu Gajria3,
Xin Gao3,
Malcolm J. Gardner5,6,
Alan Gingle7,
Greg Grant3,
Omar S. Harb3,*,
Mark Heiges2,
Christiane Hertz-Fowler1,*,
Robin Houston1,
Frank Innamorato3,
John Iodice3,
Jessica C. Kissinger2,8,
Eileen Kraemer9,
Wei Li3,
Flora J. Logan1,
John A. Miller9,
Siddhartha Mitra5,
Peter J. Myler5,6,10,
Vishal Nayak3,
Cary Pennington2,
Isabelle Phan5,
Deborah F. Pinney3,
Gowthaman Ramasamy5,
Matthew B. Rogers1,
David S. Roos11,
Chris Ross2,
Dhileep Sivam5,
Deborah F. Smith12,
Ganesh Srinivasamoorthy2,
Christian J. Stoeckert, Jr3,
Sandhya Subramanian5,
Ryan Thibodeau2,
Adrian Tivey1,
Charles Treatman3,
Giles Velarde1 and
Haiming Wang2
1Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, Cambridgeshire CB10 1SA, UK, 2Center for Tropical and Emerging Global Diseases, University of Georgia, Athens, GA 30602, 3Penn Center for Bioinformatics, University of Pennsylvania, Philadelphia, PA 19104 USA, 4Department of Biochemistry, University of Cambridge, Cambridge CB2 1GA, UK, 5Seattle Biomedical Research Institute, Seattle, WA 98109, 6Department of Global Health, University of Washington, Seattle, WA 98195, 7Center for Applied Genetic Technologies, 8Department of Genetics, 9Department of Computer Science, University of Georgia, Athens, GA 30602, 10Department of Medical Education and Biomedical Informatics, University of Washington, Seattle, WA 98195, 11Department of Biology, University of Pennsylvania, Philadelphia, PA 19104 USA and 12Centre for Immunology and Infection, Department of Biology, University of York, Heslington, York YO10 5YW, UK
*To whom correspondence should be addressed. Tel: +1 215 746 7019; Fax: +1 215 573 3111; Email: oharb{at}pcbi.upenn.edu Correspondence may also be addressed to Christiane Hertz-Fowler. Tel: +44 (0)1223 834244; Fax: +44 (0)1223 494919; Email: chf{at}sanger.ac.uk
Received August 15, 2009. Accepted September 23, 2009.
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ABSTRACT
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TriTrypDB (
http://tritrypdb.org) is an integrated database providing
access to genome-scale datasets for kinetoplastid parasites,
and supporting a variety of complex queries driven by research
and development needs. TriTrypDB is a collaborative project,
utilizing the GUS/WDK computational infrastructure developed
by the Eukaryotic Pathogen Bioinformatics Resource Center (EuPathDB.org)
to integrate genome annotation and analyses from GeneDB and
elsewhere with a wide variety of functional genomics datasets
made available by members of the global research community,
often pre-publication. Currently, TriTrypDB integrates datasets
from
Leishmania braziliensis, L. infantum, L. major, L. tarentolae, Trypanosoma brucei and
T. cruzi. Users may examine individual
genes or chromosomal spans in their genomic context, including
syntenic alignments with other kinetoplastid organisms. Data
within TriTrypDB can be interrogated utilizing a sophisticated
search strategy system that enables a user to construct complex
queries combining multiple data types. All search strategies
are stored, allowing future access and integrated searches.
‘User Comments’ may be added to any gene page, enhancing
available annotation; such comments become immediately searchable
via the text search, and are forwarded to curators for incorporation
into the reference annotation when appropriate.
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INTRODUCTION
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The
Trypanosomatidae are a group of unicellular, flagellated,
obligate parasites, including many important pathogens of humans
and animals. African trypanosomes (
Trypanosoma brucei, T. congolense and
T. vivax) are endemic in rural areas of sub-Saharan Africa,
where they cause sleeping sickness in humans, and wasting disease
(nagana) in cattle. These diseases are invariably fatal if left
untreated (
1). In 2004, 17 580 cases of human infection were
reported, but due to chronic under-reporting in poor, rural
areas, actual infection rates are thought to reach 300 000 new
cases annually (
2,
3). Millions of cattle are also at risk, and
trypanosomiasis severely constrains cattle grazing in endemic
regions.
Trypanosoma cruzi is endemic in south and central America,
causing Chagas disease (American Trypanosomiasis) in approximately
8–9 million infected individuals, and
14 000 deaths annually
(
4).
Leishmania parasites are found throughout the world (old
world:
L. major; new world:
L. infantum and
L. braziliensis),
infecting an estimated 12 million individuals, with approximately
2 million new cases reported annually (
5). These parasites exhibit
a variety of spectral pathologies, including severely debilitating
cutaneous disease, and visceral symptoms that may be fatal.
The genomes of multiple Trypanosomatidae have been sequenced (6–9) and are available from sources such as GeneDB (http://GeneDB.org) (10) and the primary sequence nucleotide databases (DDBJ, EMBL and GenBank); genome projects are also underway for a variety of other species of biological and evolutionary interest. Whilst GeneDB specializes in the display of highly-curated annotation, it has been difficult to integrate this information with other available ‘omics’ datasets: expression profiling data, proteomics results, etc., hindering the research on these organisms, including the development of new therapies and diagnostics. To this end, the TriTrypDB initiative was undertaken as a collaborative effort between the EuPathDB team at the Universities of Pennsylvania and Georgia (http://EuPathDB.org) (11), the GeneDB group at the Wellcome Trust Sanger Institute and researchers from the Seattle Biomedical Research Institute, culminating in the release of the first version of TriTrypDB (http://TriTrypDB.org) in early 2009. This collaboration has proved to be an effective means for providing the scientific community with up-to-date annotation and curation, and access to tools enabling sophisticated queries against genomic scale datasets.
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DATA IN THE CURRENT RELEASE
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TriTrypDB (release 1.1) houses the genome sequences of
T. brucei TREU 927 strain [11 chromosomes, 26 megabases (Mb)] (
6);
T. cruzi CL Brener, Esmeraldo and non-Esmeraldo-like haplotypes
(41 chromosomes, 67 Mb) (
7,
12);
L. major Friedlin strain (36
chromosomes, 32.8 Mb) (
8),
L. infantum JPCM5 strain (36 chromosomes,
32 Mbs) (
9);
L. braziliensis Viannia strain (35 chromosomes,
32 Mb) (
9); and
L. tarentolae (sequence kindly provided in advance
of publication, by Marc Ouellette, Université Laval,
and Martin Olivier from McGill University). TriTrypDB also includes
selected transcript and proteomics expression data (with more
to follow over the coming months). Transcript expression information
is derived from both microarray data (
L. infantum differentiation
time series and data provided pre-publication by Dan Zilberstein
and Peter Myler) and expressed sequence tags (EST libraries
from
T. brucei,
T. cruzi,
L. braziliensis,
L. infantum and
L. major extracted from dbEST;
http://www.ncbi.nlm.nih.gov/dbEST).
Protein expression data based on tandem mass spectrometry of
whole parasites and subcellular fractions is available for
T. brucei (
13),
T. cruzi (
14),
L. braziliensis,
L. infantum and
L. major [(
15), and Marc Ouellette, pre-publication].
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USING TriTrypDB
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The home page of TriTrypDB is based on the recently re-designed
EuPathDB web page, and includes five main sections (
Figure 1).
The top of the page is an interactive banner (
Figure 1A), which
appears on all pages and includes (i) the TriTrypDB logo, (ii)
windows for ID and text searches, (iii) links providing quick
access to useful pages (help and information pages, a ‘Contact
Us’ link and links for registration/login) and (iv) a
tool bar (grey) with links to access diverse searches (see below),
the user’s personal search history, tools, downloads,
data sources and other links. The left side of the home page
(
Figure 1B) provides a series of expandable windows presenting
news items (such as release notes), tutorials (demonstrating
website usage), community resources and additional information
and help. New items added since the user’s last visits
are indicated by yellow numbers. Three panels in the middle
of the page provide access to searches and tools: the panel
indicated as
Figure 1C includes diverse searches pertaining
to genes;
Figure 1D accesses searches against other data types
(assemblies, ESTs, Open Reading Frame (ORFs), etc., with more
data types to follow, as already implemented for other EuPathDB
component databases);
Figure 1E provides links to tools such
as BLAST, sequence retrieval and a genome browser.
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Figure 1. Screen shot of the TriTrypDB home page. (A) Interactive banner present on all TriTrypDB web pages, including quick search windows and a tool bar (grey). (B) Side bar components contain expandable sections for release notes, community resources, tutorials and help (new items are highlighted with a yellow alert). (C) Gene searches; clicking on ‘+’ symbols reveals a list of searches available within each category. (D) Searches of non-gene entities, such as ESTs and ORFs of genome sequence. (E) Links to available tools, including the genome browser (based on GBrowse), BLAST against TriTrypDB, the sequence retrieval tool and recent PubMed records pertaining to TriTrypDB organisms.
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Visitors to TriTrypDB may select from approximately 80 different
searches against the TriTryp genomes and datasets. Importantly,
searches can be combined in an integrated and graphical manner
(
Figure 2A and B), and results are displayed in tabular lists
below the growing search strategy (
Figure 2C and D). In the
example presented as
Figure 2, the search strategy begins with
a text search for the word kinase using either the ‘Gene
Text Search’ window in the interactive banner (
Figure 1A),
or accessing the text search query page from ‘Identify
Genes by’ section (
Figure 1C). The latter provides a greater
range of user options, such as defining which fields to search.
All searches are also accessible by positioning the (mouse)
cursor over ‘New Search’ in the banner tool bar
(
Figure 1A); for example, users seeking kinases may also wish
to consider searching GO annotations, Interpro domains, etc.
The text query presented in
Figure 2 yields 1986 gene records,
in any of the species supported by TriTrypDB, which contain
the word kinase, and is displayed as a graphical image in the
search strategy window (step 1 of
Figure 2A).
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Figure 2. Screen shot of the search strategy and results summary page. (A) The expanding search strategy—a search strategy is built by adding steps, which constitute a search combined with the previous step using Boolean operators (intersect, union and minus). Any step in a strategy may be revised, deleted or expanded—the insert in the red box shows the effect of revising the first step in the strategy in A. (B) An example of a nested strategy—the search feeding into Step 3 in (A) was expanded to include other searches without the need to re-run the entire strategy. (C) The filter table, which represents a summary of results in all species represented in TriTrypDB, provides a bird’s-eye view of all results and allows quick access to those results by simply clicking on the cells in the table. (D) Tabular representation of results [highlighted in yellow in the strategy in (A) and table in (C)—this table is interactive allowing the addition, deletion and reordering of columns]. Results of searches may be downloaded by clicking on the download results link (red circle).
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The user may be satisfied with this result, or may wish to revise
or combine it with other searches: for example, how many of
these kinases are predicted to be secreted? Clicking on the
‘add step’ button opens a pop-up window containing
all available searches, from which the user can select the ‘cellular
location’ query ‘predicted signal peptide’
(data not shown), specify appropriate parameters (or accept
the defaults) and select how to combine this search with the
previous one in the strategy (i.e. which Boolean operator to
use: intersection, union or minus). Intersecting genes predicted
to contain a signal peptide with those containing the word kinase
are displayed, along with a Venn diagram representing how these
searches were combined, in step 2 (
Figure 2A). This strategy
can be further expanded by asking which of these results is
supported by proteomics evidence in general or by proteomics
evidence from specific parasite life cycle stages as shown in
Figure 2 (Step 3).
This search yields a limited number of hits, for several reasons, including the limited amount of functional genomics evidence available. The search can readily be expanded, however, as indicated in the main body of Figure 2. For example, the signal peptide search can be expanded to consider genes that contain a signal peptide and/or a transmembrane domain (as it is not clear that all secreted proteins are properly annotated and accurately recognized by SignalP). Similarly, expression data can be expanded by considering genes with either proteomics evidence or EST support (this information appears as a nested ‘sub-strategy’ 3 in Figure 2B). The ability to apply an ortholog transform on any search result (i.e. identify orthologs for a set of genes), based on orthologs identified by OrthoMCL (http://orthomcl.org) (16), provides another powerful method for expanding searches. In the strategy shown, an ortholog transform identifies any secreted kinetoplastid parasite gene for which expression evidence is available for an ortholog in any other member of the kinetoplastida (Step 3, Figure 2A).
All steps, in all searches, may be revised, renamed, transformed, deleted or expanded as nested sub-strategies. Nested strategies allow a user to expand a specific step as a separate branch of the strategy. For example, revising the first step in Figure 1 to substitute phosphatase for kinase results in changes which are propagated through all subsequent steps (red inset).
The results of a search strategy are summarized by species (filter table) (Figure 2C), and displayed as an interactive gene list (Figure 2D). The filter table provides a bird’s-eye view of results of a search across all species in TriTypDB, and allows the user to click on any results in this table to display a particular species in the gene list shown below. Similarly, clicking on the results shown in any of the graphical icons in Figure 2A and B changes the table and gene list (Figure 2C and D). The gene list may also be modified, by adding, deleting or moving columns (by dragging them to the preferred position). Finally, all results can also be downloaded by clicking on the ‘download results’ link.
Viewing a gene page can be achieved by either entering a specific gene ID in the ID search window in the interactive banner (Figure 1A), or the ID search query (Figure 1C) or by clicking on the gene ID in the results table of a search strategy (Figure 2D). The gene page (Figure 3A) contains all available information for a gene displayed on a single page, including synteny maps (Figure 3B), information on orthologs and paralogs (Figure 3C), EC (enzyme commission) numbers and genome ontology associations (Figure 3D), proteomics (Figure 3E), microarray and EST data (Figure 3F) and the actual sequence (amino acid and nucleotide) of the displayed gene (data not shown). In addition, links to User Comments (and access to the gene-specific comment form; green insert in Figure 3A) and linkouts to the gene record on GeneDB (blue insert in Figure 3A) are available through the gene page. Similarly, GeneDB provides links to appropriate records in TriTrypDB.
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Figure 3. Screen shot of a gene record page in TriTrypDB. (A) The gene page, with all data ‘hidden’; any available data type can be viewed by clicking on ‘show’. Display preferences (and prior queries) are saved for registered users. (B) Genomic context view, showing SynView (19) synteny map between organisms supported in TriTrypDB. (C) Orthologs and paralogs table. (D) Tables representing EC (enzyme commission) numbers and GO (Genome Ontology) associations. (E) Protein features, including mapped peptides from proteomics experiments, InterPro domain predictions, hydropathy plots and BlastP results. (F) Evidence of transcript expression, from microarray experiments.
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CURATION
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We have implemented a synergistic approach to annotation, integrating
the staff and expertise available as part of the GeneDB and
EuPathDB projects with invaluable help from the broader scientific
community. Annotators and curators at three sites [Seattle Biomedical
Research Institute (USA), University of Georgia, Athens (USA)
and the Wellcome Trust Sanger Institute (UK)] are all able to
remotely curate, using Virtual Private Network connections to
the Gene Builder interface of the Artemis annotation tool (
17),
which reads and writes directly to a Chado relational database
at GeneDB (
18). Curation currently focuses on preparing new
sequence releases, updates to gene structure and function annotation
and mutant phenotype annotations. This process is aided by providing
members of the trypanosomatid research community the ability
to directly add annotations to genes in TriTrypDB in the form
of User Comments (green insert in
Figure 3A). Comments made
by scientific community members are forwarded to the annotators,
in addition to immediately appearing on the gene record page
in TriTrypDB. The comment form is designed to allow the user
to input information into structured fields helpful to an annotator
(in essence an expert opinion to guide the annotator), such
as synonyms, experimentally-validated gene coordinates, gene
product functional characterization, PubMed IDs, GenBank accession
numbers and related genes (whereby the comment is replicated
on related gene pages). We have found this to be a valuable
forum for community input into TriTrypDB, of considerable use
to curators working to improve gene annotations. Updates, committed
to the GeneDB Chado database, set a flag on the relevant page
in TriTrypDB, alerting users to updated annotations, a process
mediated by web-services. These changes are propagated to TriTrypDB
as part of the subsequent data update and release. To date,
this collaborative effort has yielded modifications of 1159
gene records, including changes to the gene product name, gene
structure, addition of untranslated regions and the addition
of functional information and PubMed citations.
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FUTURE DIRECTIONS
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TriTrypDB will continue to expand both in functionality and
data content over the coming years. Data types for which we
anticipate storing and providing a query interface include expression
data from proteomics experiments and transcriptome analysis
(by microarrays and RNA-Seq); DNA-binding data (ChIP-chip and
ChIP-seq); metabolomic data and metabolic pathway reconstructions;
new genome sequences and annotation, including genome variation
data; and re-assemblies of current genome sequences.
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FUNDING
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Grant from the Bill & Melinda Gates Foundation to develop
a TriTrypDB component of the EuPathDB project (Grant Number
50097 to D.S.R., J.C.K., C.J.S. and P.J.M.); Wellcome Trust
(Grant Number WT085822MA to M.C., D.F.S., M.B. and D.S.R.);
Core funding from of the Wellcome Trust Sanger Institute by
the Wellcome Trust (Grant Number WT085775/Z/08/Z). EuPathDB,
which provides the infrastructure upon which TriTrypDB was constructed,
is funded with federal funds from the National Institute of
Allergy and Infectious Diseases, National Institutes of Health,
Department of Health and Human Services, under Contract No.
HHSN266200400037C (to D.S.R., C.J.S. and J.C.K.). Funding for
open access charge: Bill and Melinda Foundation (Grant Number
50096) and The Wellcome Trust (Grant Number WT085775).
Conflict of interest statement. None declared.
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ACKNOWLEDGEMENTS
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The authors wish to acknowledge the contribution of numerous
members of the trypanosomatid research community, in the form
of advice, suggestions and/or data—often made available
to the community via TriTrypDB in advance to publication.
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REFERENCES
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ABSTRACT
INTRODUCTION