Nucleic Acids Research Advance Access published online on October 3, 2008
Nucleic Acids Research, doi:10.1093/nar/gkn652
© 2008 The Author(s)
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
TB database: an integrated platform for tuberculosis research
T. B. K. Reddy1,*,
Robert Riley2,
Farrell Wymore1,
Phillip Montgomery2,
Dave DeCaprio2,
Reinhard Engels2,
Marcel Gellesch2,
Jeremy Hubble3,
Dennis Jen2,
Heng Jin1,
Michael Koehrsen2,
Lisa Larson2,
Maria Mao3,
Michael Nitzberg1,
Peter Sisk2,
Christian Stolte2,
Brian Weiner2,
Jared White2,
Zachariah K. Zachariah1,
Gavin Sherlock3,
James E. Galagan2,4,5,
Catherine A. Ball1 and
Gary K. Schoolnik6
1Department of Biochemistry, Stanford University, CA 94305, 2Broad Institute of MIT and Harvard, Cambridge, MA 02142, 3Department of Genetics, Stanford University, CA 94305, 4Department of Biomedical Engineering, Boston University, Boston, MA 02215, 5National Emerging Infectious Diseases Lab, Boston University, Boston MA 02118 and 6Department of Microbiology & Immunology, Stanford University, CA 94305, USA
*To whom correspondence should be addressed. Tel: 650 736 0075; Fax: 650 724 3701; Email: tbreddy{at}stanford.edu
Received August 14, 2008. Revised September 17, 2008. Accepted September 18, 2008.
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ABSTRACT
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The effective control of tuberculosis (TB) has been thwarted
by the need for prolonged, complex and potentially toxic drug
regimens, by reliance on an inefficient vaccine and by the absence
of biomarkers of clinical status. The promise of the genomics
era for TB control is substantial, but has been hindered by
the lack of a central repository that collects and integrates
genomic and experimental data about this organism in a way that
can be readily accessed and analyzed. The Tuberculosis Database
(TBDB) is an integrated database providing access to TB genomic
data and resources, relevant to the discovery and development
of TB drugs, vaccines and biomarkers. The current release of
TBDB houses genome sequence data and annotations for 28 different
Mycobacterium tuberculosis strains and related bacteria. TBDB
stores pre- and post-publication gene-expression data from
M. tuberculosis and its close relatives. TBDB currently hosts data
for nearly 1500 public tuberculosis microarrays and 260 arrays
for
Streptomyces. In addition, TBDB provides access to a suite
of comparative genomics and microarray analysis software. By
bringing together
M. tuberculosis genome annotation and gene-expression
data with a suite of analysis tools, TBDB (
http://www.tbdb.org/)
provides a unique discovery platform for TB research.
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INTRODUCTION
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In humans, tuberculosis (TB) is caused by the bacterium
Mycobacterium tuberculosis and primarily targets the lungs (as pulmonary TB),
but can also affect other organs, including the brain and meninges,
lymph nodes, bone and joints, the genitourinary system and the
intestine and liver. TB is today the second highest cause of
death from infectious diseases after HIV/AIDS (
1) and is the
biggest killer of people infected with HIV (
2). The World Health
Organization's most recent global data (from 2005) show that
every year 8 million people become ill with tuberculosis and
2 million people die of the disease. A third of the world's
population has been exposed to TB, making this disease one of
the greatest global health challenges facing us today (
3). A
remarkable feature of TB is its ability to enter an asymptomatic
latent phase lasting years or even decades. Activation of a
latent infection can be precipitated by changes in the physiological
and immune status of the host owing to declining cell-mediated
immunity associated with senescence, malnutrition and diabetes
or the occurrence of other diseases, especially HIV/AIDS (
4).
Chemotherapy for active TB due to drug-sensitive strains entails
the use of multiple antibiotics administered for 6 months. This
complicated and frequently toxic treatment regimen often results
in poor patient compliance. This in turn has led to the emergence
of antibiotic resistant strains that require longer treatment
courses, the use of less effective and more toxic drugs and
higher failure rates (
5). As a result, TB remains a widespread
and deadly disease whose control will require more effective
public health measures and the development of new drugs and
vaccines. Recent developments in genomics and the availability
of the complete
M. tuberculosis genome sequence (
6) has led
to the use of genome-wide expression profiling and comparative
genomics methods to better understand
M. tuberculosis pathology,
latency, emerging drug resistance and evolution. However, despite
the wide-spread use of functional and comparative genomics to
study
M. tuberculosis, there has been no single repository for
these large-scale datasets, complete with high-quality experimental
annotation, and connected to up-to-date gene annotation and
comparative genomic information. Instead, much of these data
have been located in disparate sites like GenoMycDB: a database
for comparative analysis of mycobacterial genes and genomes
(
7) and MGDD:
M. tuberculosis genome divergence database (
8)
that employ diverse and often incompatible formats and analytical
tools. The Tuberculosis Database (TBDB) was developed to address
this gap. TBDB uses software from the Stanford Microarray Database
(SMD) (
9) and the Broad Institute's Calhoun system (
10,
11),
and houses gene-expression data paired with genome sequence
and annotation data. Uniting experimental data with genome sequence
data enables researchers to ask complex questions and draw inferences
that would otherwise be impossible by looking at individual
small datasets. In this context, TBDB brings together powerful
genomics tools to advance
M. tuberculosis research in ways that
will contribute to the identification of new drug targets, vaccine
antigens, diagnostics and host biomarkers.
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TBDB OVERVIEW
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TBDB is an integrated database that houses both annotated genome
sequence data and microarray and RT–PCR expression data
from
in vitro experiments and TB-infected tissues. TBDB houses
genome sequence data for several
M. tuberculosis strains as
well as data for numerous related species. These data and annotations
include publicly available sequences from a number of sequencing
centers and groups, including sequences being produced by the
Broad Institute's Microbial Sequencing Center. The microarray
data within TBDB are predominantly from
M. tuberculosis, but
we are in the process of incorporating
in vivo data from infected
host tissues (principally human, primate and murine) into TBDB.
Experimental data may be deposited into TBDB by any TB researcher
prior to publication providing prepublication access to tools
for the analysis, annotation, visualization and sharing of data.
The data are then made public at the author's request or following
publication, whichever is first. In addition, TBDB curators
search the literature for publications containing relevant TB
or host microarray data. The primary data are then requested
from the authors of such publications and are entered into TBDB,
where the experiments are annotated and made public so other
researchers can reanalyze the data (often in conjunction with
other datasets within TBDB) using TBDB tools.
Table 1 lists
TBDB statistics, including the number of annotated genomes in
TBDB, microarray experiments, publications and other data types.
The first route of entry into TBDB is the
Quick Search feature,
which allows a user to search all objects in TBDB by gene name,
gene sequence name, author name, title or any other keyword.
The result page of a
Quick Search provides a count of genes,
microarray experiments, operons, gene families and other database
objects that match the query. Links from this results page provide
direct access to pages with detailed information about particular
objects, such as the Gene Detail and Publication pages.
Quick Search is available at the top of every TBDB page, and thus
provides an easily accessible single integrated access point
to all genome annotation and expression data in TBDB.
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TBDB GENOMES
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TBDB currently houses genome sequence data for
M. tuberculosis strain H37Rv (a standard prototype strain long used for experimental
and animal infection studies), as well as other
M. tuberculosis strains and bacteria from related taxa, focusing on members
of the Actinomycetes family of high G+C content, Gram-positive
organisms of which
M. tuberculosis is a member. These genomes
sequences have been annotated with a variety of genomic features
including genes, operons, sequence similarity to GenBank sequences
using BLAST (
12), transfer RNAs using tRNAScan (
13), protein
domains and families using PFAM (
14) and noncoding RNAs based
on RFAM (
15). Known immune epitopes have also been mapped through
collaboration with BioHealthBase (
16). A suite of analytical
tools is also provided to allow comparative genomic analysis
of
M. tuberculosis.
Table 2 lists the genomes in TBDB for which
sequence data are available along with their size and the number
of annotated genes. Access to the annotated genome sequences
and comparative data is provided through several search interfaces,
some of which are described subsequently.
Feature detail pages
All information about annotated features on any genome sequence
is available through Feature Detail pages, of which the Gene
Detail page is the most common example (
Figure 1). Information
presented in the Gene Detail page is organized into different
sections. These include,
Gene Info, Gene Expression, Functional Annotation, Transcript Info, Sequence and genome display options.
The Gene Info section provides complete details about
Locus Name, Gene Symbol, Synonyms, Gene Name, Gene Product Names, Gene Family, Location, Protein Domains, External Links to related
databases including TubercuList (
17), TB Structural Genomics
Consortium (TBSGC) Protein Structure Information (
18) and the
Proteome 2D-PAGE Database.
Figure 1 shows the gene detail page
for
dosR (devR, Rv3133c), which encodes the response regulator
of a two-component signal transduction system that tightly controls
a well-studied
M. tuberculosis regulon that is activated by
oxygen limitation or exposure to nitric oxide (
19).
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Figure 1. TBDB Gene Detail page. The Gene Detail page provides at-a-glance information for a given gene, including known names and synonyms, predicted function(s) and protein domains. It also serves as a jumping off point to various sequence tools, and to expression data for that gene. In addition, it provides several links to external resources such as TubercuList, TBSGC Protein Structure Information, Proteome 2D-PAGE Database at Max Planck Institute.
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Genome visualization and comparative analysis
Researchers can retrieve DNA or protein sequence for segments
of any of the genome sequences in TBDB from many locations within
the site, including the
Browse Regions search tool. The sequences
can then be visualized using a number of different tools. The
Argo Genome Browser (an interactive applet) and the
Feature Map (a lighter weight version of the
Argo Genome Browser) provide
linear views of genome sequences along with all associated annotated
features. Argo in particular provides a dynamic interface to
visualizing genome data that allows users to zoom from whole
chromosomes to individual nucleotides, navigate within sequences,
and select individual features to retrieve additional information.
A
Circular Genome Viewer provides a circular plot of genome
sequences along with a plot of the density of particular features,
GC content and GC skew. Finally, the
Genome Map tool provides
a dynamic linear view of one or more genome sequences and associated
annotations, and displays conserved synteny between the displayed
genomes for regions selected by the user (
Figure 2).
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Figure 2. Genome Map tool. This tool provides a linear view of one or more genome sequences and associated annotations as well as conserved synteny between genomes. Annotations are provided as tracks above (forward strand) and below (reverse strand) the midline. When zoomed out, annotations are viewed as density plots; when zoomed in individual features are displayed. Users may select regions of a genome sequence by dragging along the midline. Syntenic regions in the other sequences associated with the selection are then displayed as red bands.
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An additional number of tools are also provided specifically
for comparative analyses between genome sequences, including
the
Synteny Map,
Dot Plot,
Operon Browser (
Figure 3) and
Gene Family Search. The
Synteny Map uses precomputed genome alignments
to graphically display regions of genomic similarity between
a single reference genome and one or more other genomes—in
effect providing the results of an
in silico genome hybridization
between sets of genomes. Using this tool, the user can select
regions of interest and then click a region to zoom in and view
genes, genome sequence, and features. The
Dot Plot displays
a navigable map of computed synteny between genomes in the form
of dot-plot lines. When comparing multiple genomes, the color
of the plotted synteny indicates which genome is aligned to
the reference at that position. The
Operon Browser is a tool
that simultaneously displays the expression correlation between
genes in a genomic region of the
M. tuberculosis H37Rv strain
while showing syntenic gene order of orthologs in related species.
A heatmap derived from expression correlation data is provided
along with an alignment of syntenic areas. Mousing over the
genes provides additional information such as locus ID, gene
symbol and description. Color coding of genes indicate orthologous
relationships across different species. Finally, the
Gene Family Search displays phylogenetic trees and sequence alignments of
predicted orthologous gene families within the genome sequences
in TBDB. The basic search feature lets the user choose the number
of genomes to query and whether to limit the search to strict
orthologs or not. In addition, an advanced search option chooses
which genomes to include or exclude.
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Figure 3. Comparative genome analysis. The Genomes Synteny Map (A), Dot Plot (B) and Operon Map Browser (C) provide different ways to access comparative genomic data between M. tuberculosis reference genome and selected related species. These tools provide an interactive means to explore comparative genomic data.
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TBDB GENE EXPRESSION DATA
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TBDB houses public and prepublication microarray and RT–PCR
expression data. Public data are freely accessible and can be
downloaded or reanalyzed using TBDB analysis tools. Access to
prepublication data is restricted to the researchers who generated
the data until they publish or decide to make their data public.
TBDB users can establish a free user account to enter microarray
data, share prepublication microarray or RT–PCR data with
colleagues or store datasets for analysis in a data repository.
Data in the repository can be shared with other researchers
at the discretion of the TBDB user.
Expression data in TBDB can be accessed by searching for data from individual microarrays or RT–PCR assays or by searching for data from a publication. For a novice user, the publication search is an easy place to start exploring expression data in TBDB. The expression Basic Search is an interactive search option that queries TBDB via publication, organism or dataset. The expression Advanced Search finds microarray data by experimenter, category, subcategory and organism. The Gene Search for Expression searches for genes or reporter sequences used on microarrays. Reporter sequences correspond to a piece of DNA deposited on a microarray slide. This search returns all microarray spots associated with a reporter sequence or gene, and the search results link to the Spot History page that lets users explore all associated microarray data.
Expression connection
Using Expression Connection, researchers can visualize and explore clustered microarray datasets from publications whose data are present within TBDB. Clustering organizes expression data for genes or reporter sequences into groups that have similar expression profiles. This enables a user to directly view and explore already clustered data within TBDB without needing to go through the data analysis pipeline. As shown in Figure 4, a publication detail page can be accessed by following TB Expression 
Gene Expression Publications ‘Data in TBDB’. Interactive clustered data images for a publication can be navigated using GeneXplorer (20), which provides views of the most correlated genes for a gene of interest or searches for genes using text queries (Figure 4). Thus, this option enables a user to explore and interrogate TBDB for expression data from publications.
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Figure 4. Publication microarray data and expression connection. Researchers can access the full raw microarray data associated with a publication, either for download, or retrieval through the data retrieval and analysis pipeline. In addition, users can explore clustered microarrays data, whereby they can search for particular genes, or identify which genes show coexpression across a particular dataset.
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Data analysis
TBDB provides a suite of microarray data analysis tools for
its users. All tools are freely available to analyze both public
and prepublication data in TBDB. A typical data analysis process
at TBDB involves several steps in the following order: Experiment
Selection
Gene Selection and Annotation
Data Filtering Options
Data Retrieval
Gene Filtering
Clustering and Image Generation.
At each step, a user is presented with various options that
allow them to filter and cluster the data according to their
needs. For example, a user can employ either the
Basic or
Advanced Expression Search to choose a set of microarray data for further
analysis. Clicking on the ‘Data Retrieval and Analysis’
option invokes the data analysis pipeline, where a user can
select various microarray data filtering and transformation
options. Many microarray data analysis tools can be applied
to datasets, including hierarchical clustering, imputation of
missing values, Gene Set Enrichment Analysis (
21), Singular
Value Decomposition (
22) and pathway analyses. All SMD analysis
tools [many described previously (
9)] have been made available
through TBDB. At each step in the data analysis, pipeline a
link to a relevant ‘Help’ page is provided, which
explains in detail the various available options. In addition,
the TBDB data repository provides access to the suite of gene-expression
analysis tools provided through the Gene Pattern software (
23).
Literature curation
Curating microarray expression data from publications is an important part of TBDB's efforts. We actively search PubMed for relevant publications containing microarray experiments, then obtain the raw data from researchers and load them into TBDB, with detailed experimental annotations.
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FUTURE DIRECTIONS
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We are working to increase the quality and quantity of data
within TBDB and to incorporate additional data types. One of
our priorities is to acquire host expression data from
M. tuberculosis-infected
tissues (mouse, primate and human), and we also plan to expand
TBDB's capacity to house and analyze RT–PCR data and will
develop tools for comparative analysis of RT–PCR and microarray
expression data. We will also implement tools such as GO::TermFinder
(
24), which allows users to determine whether there are biological
themes associated with a list of genes of interest, and tools
for the analysis of replicate microarray experiments. We are
also working to improve the depth and quality of our genome
annotations. We are currently curating TB literature and associating
these data with genes and other genomics features. Moreover,
we have implemented and will deploy a community annotation infrastructure
to allow TB researchers to submit additions and improvements
to existing annotations through the TBDB website. We are also
using the comparative sequence integrated into TBDB to improve
on the accuracy of structural gene annotations and to predict
additional potential noncoding genes. Finally, as new TB sequences
are produced by the Broad Microbial Sequencing Center, they
will be deposited and made publicly available in TBDB. Ultimately,
we hope that TBDB will serve as a community hub for TB research;
a TB research community information page will be implemented
with a listing of TB research labs and colleagues; this will
also provide a forum for the community of users including feedback
and suggestions from the community that will help us better
serve them.
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CONCLUSION
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TBDB contains annotated genome and expression (microarray and
RT–PCR) data and a suite of data analysis tools designed
to serve as a unique resource for TB research and for the discovery
of new drugs, vaccines and biomarkers. Data within the TBDB
and all analysis tools are freely available to researchers.
Only prepublication gene-expression data require a password.
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FUNDING
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The Bill and Melinda Gates Foundation. Funding for open access
charge: The Bill and Melinda Gates Foundation.
Conflict of interest statement. None declared.
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ACKNOWLEDGEMENTS
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We are grateful to the research community for their valuable
input and suggestions in building and maintaining this database.
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ABSTRACT
INTRODUCTION