TY - JOUR
T1 - Aquatic models, genomics and chemical risk management
AU - Cheng, Keith C.
AU - Hinton, David E.
AU - Mattingly, Carolyn J.
AU - Planchart, Antonio
N1 - Funding Information:
The foundation of this work was presented at the 5th Aquatic Animal Models for Human Disease meeting in Corvalis, Oregon. The authors acknowledge funding from NIH ( R24RR017441 , R01CA242956 , and R01AR052535 to KC), NIEHS ( R21ES016892 to AP, R01ES019604 and P42 ES10356 to DH); NIEHS and NLM ( R01ES014065 to CM), and NSF and U.S. EPA ( EF-0830093 to DH). KC acknowledges the work of D. Clark, J. Copper, X. Xin, and S. Peckins in his lab, and his colleagues P La Riviere and G. Kindlmann at U. Chicago, F. De Carlo, X. Xiao at the Advanced Photon Source at Argonne National Laboratory, I. Foster and R. Kettimuthu of the Mathematics and Computer Science Division at Argonne, and V. Agarwala and A. Spanier of Penn State for critical contributions and discussion of unpublished work.
PY - 2012/1
Y1 - 2012/1
N2 - The 5th Aquatic Animal Models for Human Disease meeting follows four previous meetings (Nairn et al., 2001; Schmale, 2004; Schmale et al., 2007; Hinton et al., 2009) in which advances in aquatic animal models for human disease research were reported, and community discussion of future direction was pursued. At this meeting, discussion at a workshop entitled Bioinformatics and Computational Biology with Web-based Resources (20 September 2010) led to an important conclusion: Aquatic model research using feral and experimental fish, in combination with web-based access to annotated anatomical atlases and toxicological databases, yields data that advance our understanding of human gene function, and can be used to facilitate environmental management and drug development. We propose here that the effects of genes and environment are best appreciated within an anatomical context - the specifically affected cells and organs in the whole animal. We envision the use of automated, whole-animal imaging at cellular resolution and computational morphometry facilitated by high-performance computing and automated entry into toxicological databases, as anchors for genetic and toxicological data, and as connectors between human and model system data. These principles should be applied to both laboratory and feral fish populations, which have been virtually irreplaceable sentinals for environmental contamination that results in human morbidity and mortality. We conclude that automation, database generation, and web-based accessibility, facilitated by genomic/transcriptomic data and high-performance and cloud computing, will potentiate the unique and potentially key roles that aquatic models play in advancing systems biology, drug development, and environmental risk management.
AB - The 5th Aquatic Animal Models for Human Disease meeting follows four previous meetings (Nairn et al., 2001; Schmale, 2004; Schmale et al., 2007; Hinton et al., 2009) in which advances in aquatic animal models for human disease research were reported, and community discussion of future direction was pursued. At this meeting, discussion at a workshop entitled Bioinformatics and Computational Biology with Web-based Resources (20 September 2010) led to an important conclusion: Aquatic model research using feral and experimental fish, in combination with web-based access to annotated anatomical atlases and toxicological databases, yields data that advance our understanding of human gene function, and can be used to facilitate environmental management and drug development. We propose here that the effects of genes and environment are best appreciated within an anatomical context - the specifically affected cells and organs in the whole animal. We envision the use of automated, whole-animal imaging at cellular resolution and computational morphometry facilitated by high-performance computing and automated entry into toxicological databases, as anchors for genetic and toxicological data, and as connectors between human and model system data. These principles should be applied to both laboratory and feral fish populations, which have been virtually irreplaceable sentinals for environmental contamination that results in human morbidity and mortality. We conclude that automation, database generation, and web-based accessibility, facilitated by genomic/transcriptomic data and high-performance and cloud computing, will potentiate the unique and potentially key roles that aquatic models play in advancing systems biology, drug development, and environmental risk management.
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U2 - 10.1016/j.cbpc.2011.06.009
DO - 10.1016/j.cbpc.2011.06.009
M3 - Article
C2 - 21763781
AN - SCOPUS:81855207489
SN - 1532-0456
VL - 155
SP - 169
EP - 173
JO - Comparative Biochemistry and Physiology - C Toxicology and Pharmacology
JF - Comparative Biochemistry and Physiology - C Toxicology and Pharmacology
IS - 1
ER -