The Comparative Toxicogenomics Database (CTD).
ABSTRACT The Mount Desert Island Biological Laboratory in Salsbury Cove, Maine, USA, is developing the Comparative Toxicogenomics Database (CTD), a community-supported genomic resource devoted to genes and proteins of human toxicologic significance. CTD will be the first publicly available database to a) provide annotated associations among genes, proteins, references, and toxic agents, with a focus on annotating data from aquatic and mammalian organisms; b) include nucleotide and protein sequences from diverse species; c) offer a range of analysis tools for customized comparative studies; and d) provide information to investigators on available molecular reagents. This combination of features will facilitate cross-species comparisons of toxicologically significant genes and proteins. These comparisons will promote understanding of molecular evolution, the significance of conserved sequences, the genetic basis of variable sensitivity to environmental agents, and the complex interactions between the environment and human health. CTD is currently under development, and the planned scope and functions of the database are described herein. The intent of this report is to invite community participation in the development of CTD to ensure that it will be a valuable resource for environmental health, molecular biology, and toxicology research.
- Environ Health Perspect. 01/2013; 19:19.
- [Show abstract] [Hide abstract]
ABSTRACT: Toxicogenomics has recently emerged in the field of toxicology and the DNA microarray technique has become common strategy for predictive toxicology which studies molecular mechanism caused by exposure of chemical or environmental stress. Although microarray experiment offers extensive genomic information to the researchers, yet high dimensional characteristic of the data often makes it hard to extract meaningful result. Therefore we developed toxicant enrichment analysis similar to the common enrichment approach. We also developed web-based system graPT to enable considerable prediction of toxic endpoints of experimental chemical.Genomics & Informatics. 01/2006; 4(3).
- [Show abstract] [Hide abstract]
ABSTRACT: High Throughput Screening (HTS) assays that measure the in vitro toxicity of environmental compounds have been widely applied as an alternative to in vivo animal tests of chemical toxicity. Current HTS studies provide the community with rich toxicology information that has the potential to be integrated into toxicity research. The available in vitro toxicity data is updated daily in structured formats (e.g., deposited into PubChem and other data sharing web portals) or in unstructured way (papers, laboratory reports, toxicity website updates etc). The information derived from the current toxicity data is so large and complex that it becomes difficult to process using available database management tools or traditional data processing applications. For this reason, it is necessary to develop a "big data" approach when conducting modern chemical toxicity research. In vitro data for a compound, obtained from meaningful bioassays, can be viewed as a response profile that gives detailed information about the compound's ability to affect relevant biological proteins/receptors. This information is critical for the evaluation of complex bio-activities (e.g., animal toxicities) and grows rapidly as "big data" in toxicology communities. This review focuses mainly on the existing structured in vitro data (e.g., PubChem datasets) as response profiles for compounds of environmental interest (e.g., potential human/animal toxicants). Potential modeling and mining tools to use the current big data pool in chemical toxicity research are also described.Chemical Research in Toxicology 09/2014; · 4.19 Impact Factor
Approximately 75,000 chemicals are
currently listed in the U.S. Environmental
Protection Agency (U.S. EPA) Toxic
Substances Control Act Chemical Substances
Inventory (U.S. EPA 2003); however, the
toxic potential and the molecular mecha-
nisms underlying the action of many of
these chemicals are not well understood.
Scientists have long exploited diverse
experimental models to understand the
complexity of gene–environment interac-
tions. With the rising number of pub-
licly available sequences and completely
sequenced genomes, comparative studies are
proving to be essential for elucidating bio-
logical systems (Koonin et al. 2000) and
annotating accumulating genomic and
proteomic data (Whelan et al. 2001).
Comparisons of more distantly related verte-
brate and invertebrate species may be
of particular value for identifying con-
served genetic and molecular mechanisms
(Wittbrodt et al. 2002). It is on this premise
that the Comparative Toxicogenomics
Database (CTD) is being developed.
CTD will facilitate comparisons of
sequences and functions of toxicologically
significant genes and proteins from diverse
organisms, with an emphasis on aquatic
and mammalian species. The goal is to pro-
vide unique insights into the significance of
conserved sequences and polymorphisms,
the genetic basis of variable sensitivity,
molecular evolution, and adaptation. The
potential value of such comparisons is
demonstrated by studies of the aryl hydro-
carbon receptor (AhR) (Hahn 2002;
Thomas et al. 2002), which modulates the
toxic action of the environmental contami-
(TCDD) (Poland and Knutson 1982;
Schmidt and Bradfield 1996). Mammals,
fishes, and aquatic invertebrates exhibit dif-
ferent toxicity profiles (Hahn 2002).
Studies of AhR in these organisms identi-
fied duplication events in fishes and differ-
ences in sequence identity, TCDD-binding
capacity, and activation of downstream tar-
gets (Hahn 2002; Thomas et al. 2002).
Although the physiologic roles of AhR are
still not well understood, correlations
between AhR sequences and functions in
distantly related organisms may provide
valuable information about the evolution-
ary impact on this gene, possible insights
into the genetic basis of toxicity, and
directions for future research.
There is a strong precedent for compar-
ative studies with aquatic organisms. The
recent sequencing of the pufferfish (Fugu
rubripes) genome has resulted in the discov-
ery of nearly 1,000 human genes not
described previously in the public domain
(Aparicio et al. 2002). The anticipated
sequences for zebrafish (Danio rerio) and
spotted green pufferfish (Tetraodon
nigroviridis) genomes will likely make addi-
tional contributions to the annotation of
the human genome. Evolutionarily diverse
aquatic organisms have become important
models for studying human disease. For
example, membrane transporters that are
the sites of action of diuretic drugs, includ-
ing the bumetanide-sensitive Na-K-Cl
cotransporter and the thiazide-sensitive
NaCl cotransporter, were first cloned from
specialized organs in marine species
(Gamba et al. 1993; Xu et al. 1994).
Mutagenesis studies in teleosts have gener-
ated a spectrum of biologically relevant and
nonoverlapping phenotypes (Wittbrodt
et al. 2002). Large-scale genetic screens
have produced more than 500 zebrafish
mutants, many with phenotypes similar to
human disorders (Dooley and Zon 2000).
Medaka (Oryzias latipes) are routinely used
for studies in carcinogenesis and environ-
mental health (Wittbrodt et al. 2002). The
more distantly related elasmobranchs have
provided unique insight into conserved
functional domains of genes associated
with human liver function (Ballatori and
Villalobos 2002; Cai et al. 2001, 2002) and
cystic fibrosis (Aller et al. 1999).
The growing body of genomic informa-
tion available to the scientific community
has led to an increase in the number and
scope of biological databases. A recent
review (Baxevanis 2002) estimated a total
of 335 existing databases in 2002, an
increase from 281 in 2001. These data-
bases address a range of complex chal-
lenges for biologists, such as managing
comprehensive repositories of genomic
and proteomic data (Benson et al. 2002;
O’Donovan et al. 2002), annotating
species-specific genomes (Blake et al.
2002; Sprague et al. 2001), and identify-
ing protein families and conserved
domains (Baxevanis 2002). Existing toxi-
cology databases have cataloged chemical
and physical properties of toxic agents,
mutagenicity data, environmental health
and regulatory information, ecologic data,
and scientific references (Russom 2002;
Wexler 2001; Young 2002). It is impotant
to note that there is no existing publicly
available resource that provides toxicologic
Environmental Health Perspectives • VOLUME 111 | NUMBER 6 | May 2003
The Comparative Toxicogenomics Database (CTD)
Carolyn J. Mattingly,1,2,3Glenn T. Colby,1,2,3John N. Forrest,2,3,4and James L. Boyer2,3,4
1Department of Bioinformatics, 2Center for Membrane Toxicity Studies, and 3Center for Marine Functional Genomic Studies, Mount
Desert Island Biological Laboratory, Salsbury Cove, Maine, USA; 4Department of Medicine, Yale University School of Medicine,
New Haven, Connecticut, USA
Address correspondence to C.J. Mattingly, Dept. of
Bioinformatics, Mount Desert Island Biological
Laboratory, Salsbury Cove, ME 04672 USA.
Telephone: (207) 288-3605. Fax: (207) 288-2130.
We thank N. Ballatori, J. Blake, J. Eppig, B.
Forbush, and D. Towle for insightful feedback and
support. This project is funded by National
Institute of Environmental Health Sciences grants
ES11267-02 and ES03828-17.
Inquiries about CTD may be sent to
Received 30 September 2002; accepted 12
The Mount Desert Island Biological Laboratory in Salsbury Cove, Maine, USA, is developing the
Comparative Toxicogenomics Database (CTD), a community-supported genomic resource
devoted to genes and proteins of human toxicologic significance. CTD will be the first publicly
available database to a) provide annotated associations among genes, proteins, references, and
toxic agents, with a focus on annotating data from aquatic and mammalian organisms; b) include
nucleotide and protein sequences from diverse species; c) offer a range of analysis tools for cus-
tomized comparative studies; and d) provide information to investigators on available molecular
reagents. This combination of features will facilitate cross-species comparisons of toxicologically
significant genes and proteins. These comparisons will promote understanding of molecular evo-
lution, the significance of conserved sequences, the genetic basis of variable sensitivity to environ-
mental agents, and the complex interactions between the environment and human health. CTD
is currently under development, and the planned scope and functions of the database are
described herein. The intent of this report is to invite community participation in the develop-
ment of CTD to ensure that it will be a valuable resource for environmental health, molecular
biology, and toxicology research. Key words: aquatic, comparative, database, environmental
health, fishes, genomic, health, toxicogenomics, toxicology. Environ Health Perspect 111:793–795
(2003). doi:10.1289/txg.6028 available via http://dx.doi.org/ [Online 13 February 2003]
annotation of genomic and proteomic
data from diverse species. In addition to
CTD, another public toxicogenomic
database is being developed by the
National Center for Toxicogenomics at
the National Institute of Environmental
Health Sciences (NIEHS). The Chemical
Effects in Biological Systems (CEBS)
Knowledge Base will capture and integrate
global molecular expression data with
pathway and regulatory network informa-
tion related to toxicology and human dis-
ease (Waters et al. 2003). It is the goal of
both development groups that CTD and
CEBS be complementary in focus and
Biologic features and strategic plan. CTD
is being developed at the Mount Desert
Island Biological Laboratory (MDIBL) in
Salsbury Cove, Maine, USA, in collaboration
with investigators at NIEHS Marine and
Freshwater Biomedical Sciences (MFBS)
centers and other scientists with expertise in
molecular biology, toxicology, and bioinfor-
matics. CTD will include curated informa-
tion about nucleotide and protein sequences,
associated references, toxic agents, reagents,
and taxonomy. Tools for data analysis,
manipulation, and visualization for compara-
tive studies will also be provided. This scope
of features dictates a phased implementation
approach that will combine automated and
manual curation strategies. The first year
(September 2002–August 2003) will include
three implementation phases.
Phase I will focus on the acquisition
and integration of sequences, references to
the scientific literature, and toxic agents.
Although annotation will focus on genes and
proteins with associated toxicologic data, an
inclusive set of sequence data will be stored
locally in CTD to a) maximize the value of
comparative sequence analyses that may be
performed using integrated computational
tools, b) prevent exclusion of sequences
with potential toxicological significance,
c) allow querying of annotated features, and
d) provide integration with data from other
sources. Subsets of nucleotide sequences will
be acquired from the National Center
for Biotechnology Information (NCBI;
http://www.ncbi.nlm.nih.gov). CTD will store
all nucleotide reference sequences for human
(Homo sapiens), mouse (Mus musculus), rat
(Rattus norvegicus), and fruitfly (Drosophila
melanogaster), thereby providing a nonredun-
dant set of sequences for these particular
species (Pruitt and Maglott 2001). All
nucleotide sequences for other vertebrates
and invertebrates will be loaded from
Sitemap/index.html GenBank; Benson et al.
2002). Protein sequences for the corre-
sponding organisms will be acquired from
which provides a comprehensive, annotated,
and nonredundant protein sequence data set
(O’Donovan et al. 2002). Direct submis-
sions of sequence data to CTD will not be
accepted to avoid duplication of informa-
tion loaded from GenBank and SWISS-
PROT. Information will be updated from
these databases frequently to ensure that
CTD remains current and comprehensive.
During phase I, references associated
with genes and proteins will be identified
from GenBank and SWISS-PROT sequence
records and the NCBI literature database
associations between genes, proteins, and
toxic agents will be identified using queries
to search the titles, abstracts, and Medical
Subject Headings (MeSH) of references
(Lipscomb 2000; Young 2002) included in
CTD. For queries of genes and proteins,
nomenclature inconsistencies will be
accounted for initially by including syn-
onyms identified in public biologic databases
also addressing this issue, such as Locus Link
the Mouse Genome Informatics databases
(http://www.informatics.jax.org/). Queries for
toxic agents will be constructed using a hier-
archical vocabulary that will enhance
MeSH’s Chemicals Index and Chemicals
and Drugs category by supplementing it
with chemical information from the U.S.
EPA, the U.S. Fish and Wildlife Service,
and the National Toxicology Program.
Criteria for queries will be established in col-
laboration with investigators from other
NIEHS MFBS centers and other investiga-
tors from the scientific community with
expertise in molecular biology and toxicology.
All associations between data sets in CTD
will be labeled “not reviewed” until a curator
has confirmed their accuracy.
During phase II, we will evaluate
and integrate analysis tools for sequence
similarity searches (e.g., WU-BLAST)
(Altschul et al. 1990), multiple alignments
(e.g., ClustalW) (Thompson et al. 1994),
and phylogenetic analysis (e.g., PHYLIP)
(Felsenstein 1993). Currently, many web
sites offer BLAST capabilities against stati-
cally defined data sets that include sequences
from specific organisms, groups of organ-
isms, or databases. These data sets are often
either too inclusive, resulting in an over-
abundance of “hits,” or exclude organisms
of interest. By storing sequences and related
data locally in a relational database, it will be
possible for users to define customized data
sets. This capability will permit highly
focused sequence analysis, such as restricting
BLAST searches to a specific combination of
taxa. In addition, large-scale automated
sequence analysis will be possible.
During phase III, we will develop a
World Wide Web (WWW) interface for
CTD that will include user registration and
comment forms, basic and advanced query
options to access data for sequences, refer-
ences, and toxic agents, and a platform for
analyzing sequences. At the completion of
phase III, CTD will be made accessible to
collaborators and participating members of
the community to evaluate its functionality
and test the system. On the basis of feed-
back from the scientific community, we
will then work with MFBS center investi-
gators in subsequent years to continue the
data curation process and prioritize the
inclusion of additional data sets such as
expressed sequence tags, single nucleotide
polymorphisms, and data from microarray
Toxicogenomics|Mattingly et al.
VOLUME 111 | NUMBER 6 | May 2003 • Environmental Health Perspectives
Figure 1. Software development life cycle. The CTD system will be implemented in stages. A data model
was designed prior to developing functional specifications and a prototype system. Biologists will evalu-
ate content and functionality throughout the development life cycle.
Implementation. CTD is being designed
using a data-driven approach in which the
data model is developed prior to specifying
system functions (Figure 1). This approach
will a) promote reusability of data, b) estab-
lish a consistent set of names and defini-
tions for data, c) determine what functions
the system will support, and d) provide a
concise overview of the system’s scope
(Simsion 1994). CTD will be implemented
in an Oracle relational database. The cur-
rent data model includes 40 entities with
well-documented definitions, including text
descriptions of all entities and attributes,
data types, constraint definitions, and repre-
sentative values. CTD will include a cura-
tion tool and WWW user interface. Oracle
Forms Developer will be used to develop
the first generation of the curation tool,
which will be used to annotate and modify
data. This tool is tightly integrated with the
Oracle database and provides client-side
validation, reusable components, and rapid
prototyping capability. The WWW inter-
face will be developed using the Python
World Wide Web interface. The CTD
WWW interface will combine the familiar
paradigms of NCBI and Mouse Genome
Informatics databases. Simple and advanced
query forms will be available to retrieve
information about genes, including nucleo-
tide and protein sequences, as well as refer-
ences, toxic agents, reagents, and taxonomy.
Each of these major categories will have a
resource page providing a description of
associated data and links to resources with
supplemental information. Data will be
highly integrated within CTD and with
Community involvement. MDIBL is
committed to involving the scientific com-
munity in the development of CTD. To
this end, we are formally collaborating with
investigators at each of the NIEHS MFBS
centers; hosting conferences to evaluate the
progress and strategic plan of CTD;
attending national meetings to promote
awareness of and participation in CTD
development; and planning online mecha-
nisms for feedback and data submissions.
From its inception, CTD has benefited
from significant community support. In
April 2000, 45 biologists and bioinformat-
ics experts attended a conference at
MDIBL (MDIBL 2000) to address the
application of bioinformatics in toxicology
research. Discussions at this meeting for-
mulated the initial plan for a toxicoge-
nomics database and were the foundation
for the NIEHS-phased innovation grant
application that now funds CTD. In May
2002 MDIBL hosted a workshop (MDIBL
2002) to promote dialog about genomic
databases in the scientific community and
to seek feedback about the progress of
CTD. Because of the success and utility of
these meetings, another conference is
planned for 2004.
To ensure that CTD is a valuable resource
for the scientific community, we invite par-
ticipation in its development. Specific chal-
lenges for which we encourage feedback
include addressing nomenclature inconsis-
tencies, clustering sequence data from
diverse species, and determining the role of
microarray data in CTD. Defining strate-
gies to meet these challenges will have
broad implications for molecular biologists
Altschul SF, Gish W, Miller W, Myers EW, Lipman DJ.
1990. Basic local alignment search tool. J Mol
Aller SG, Lombardo ID, Bhanot S, Forrest JN, Jr. 1999.
Cloning, characterization, and functional expres-
sion of a CNP receptor regulating CFTR in the
shark rectal gland. Am J Physiol 276:C442–C449.
Aparicio S, Chapman J, Stupka E, Putnam N, Chia
JM, Dehal P, et al. 2002. Whole-genome shotgun
assembly and analysis of the genome of Fugu
rubripes. Science 297:1301–1310.
Ballatori N, Villalobos AR. 2002. Defining the molecu-
lar and cellular basis of toxicity using compara-
tive models. Toxicol Appl Pharmacol 183:207–220.
Baxevanis AD. 2002. The Molecular Biology Database
Collection: 2002 update. Nucleic Acids Res 30:1–12.
Benson DA, Karsch-Mizrachi I, Lipman DJ, Ostell J,
Rapp BA, Wheeler DL. 2002. GenBank. Nucleic
Acids Res 30:17–20.
Blake JA, Richardson JE, Bult CJ, Kadin JA, Eppig JT.
2002. The Mouse Genome Database (MGD): the
model organism database for the laboratory
mouse. Nucleic Acids Res 30:113–115.
Cai SY, Wang W, Ballatori N, Boyer JL. 2001. Bile salt
export pump is highly conserved during verte-
brate evolution and its expression is inhibited by
PFIC type II mutations. Am J Physiol Gastrointest
Liver Physiol 281:G316–322.
Cai SY, Wang W, Soroka CJ, Ballatori N, Boyer JL.
2002. An evolutionarily ancient Oatp: insights into
conserved functional domains of these proteins.
Am J Physiol Gastrointest Liver Physiol
Dooley K, Zon LI. 2000. Zebrafish: a model system for
the study of human disease. Curr Opin Genet Dev
Felsenstein J. 1993. PHYLIP Phylogeny Inference
Package 3.5. Seattle, WA:The University of
Gamba G, Saltzberg SN, Lombardi M, Miyanoshita A,
Lytton J, Hediger MA, et al. 1993. Primary struc-
ture and functional expression of a cDNA encod-
ing the thiazide-sensitive, electroneutral
sodium-chloride cotransporter. Proc Natl Acad
Sci USA 90:2749–2753.
Hahn M. 2002. Aryl hydrocarbon receptors: diversity
and evolution. Chem Biol Interact 141:131–160.
Koonin EV, Aravind L, Kondrashov AS. 2000. The
impact of comparative genomics on our under-
standing of evolution. Cell 101:573–576.
Lipscomb CE. 2000. Medical Subject Headings
(MeSH). Bull Med Libr Assoc 88:265–266.
MDIBL (Mount Desert Island Biological Laboratory).
2002. Conference on Bioinformatics of Genes and
ESTs Relevant to Membrane Cellular Toxicology,
28–29 April 2000, Salsbury Cove, ME.
MDIBL (Mount Desert Island Biological Laboratory).
2002. Conference on Community Participation in
Genomic Databases, 3–5 May 2002, Salsbury
O’Donovan C, Martin MJ, Gattiker A, Gasteiger E,
Bairoch A, Apweiler R. 2002. High-quality protein
knowledge resource: SWISS-PROT and TrEMBL.
Brief Bioinform 3:275–284.
Poland A, Knutson JC. 1982. 2,3,7,8-Tetrachlorodibenzo-
p-dioxin and related halogenated aromatic hydro-
carbons: examination of the mechanism of toxicity.
Annu Rev Pharmacol Toxicol 22:517–554.
Pruitt KD, Maglott, DR. 2001. RefSeq and LocusLink:
NCBI gene-centered resources. Nucleic Acids
Russom CL. 2002. Mining environmental toxicology
information: web resources. Toxicology 173:75–88.
Schmidt JV, Bradfield CA. 1996. Ah receptor signaling
pathways. Annu Rev Cell Dev Biol 12:55–89.
Simsion G. 1994. Data Modeling Essentials: Analysis,
Design, and Innovation. London:International
Thomson Computer Press.
Sprague J, Doerry E, Douglas S, Westerfield M. 2001.
The Zebrafish Information Network (ZFIN): a
resource for genetic, genomic and developmen-
tal research. Nucleic Acids Res 29:87–90.
Thomas RS, Penn SG, Holden K, Bradfield CA, Rank
DR. 2002. Sequence variation and phylogenetic
history of the mouse Ahr gene. Pharmacogenetics
Thompson JD, Higgins DG, Gibson TJ. 1994.
CLUSTAL W: improving the sensitivity of progres-
sive multiple sequence alignment through
sequence weighting, position-specific gap penal-
ties and weight matrix choice. Nucleic Acids Res
U.S. EPA. New Chemicals Program. Washington,
DC:U.S. Environmental Protection Agency.
invntory.htm [accessed 27 January 2003].
Waters M, Boorman G, Bushel P, Cunningham M,
Irwin R, Merrick A, et al. 2003. Systems
Toxicology and the Chemical Effects in Biological
Systems (CEBS) Knowledge Base. Environ Health
Perspect 111:811–824 (2003).
Wexler P. 2001. TOXNET: an evolving web resource
for toxicology and environmental health informa-
tion. Toxicology 157:3–10.
Whelan S, Lio P, Goldman N. 2001. Molecular phylo-
genetics: state-of-the-art methods for looking
into the past. Trends Genet 17:262–272.
Wittbrodt J, Shima A, Schartl M. 2002. Medaka—a
model organism from the Far East. Nat Rev Genet
Xu JC, Lytle C, Zhu TT, Payne JA, Benz E, Forbush B.
1994. Molecular cloning and functional expression
of the bumetanide-sensitive Na-K-Cl cotrans-
porter. Proc Natl Acad Sci USA 91:2201–2205.
Young RR. 2002. Genetic toxicology: web resources.
Toxicogenomics|A resource for comparative studies in toxicology
Environmental Health Perspectives • VOLUME 111 | NUMBER 6 | May 2003