Integrating microbial signal transduction pathways and their metabolic targets

Award Information
Agency:
Department of Health and Human Services
Branch
n/a
Amount:
$99,500.00
Award Year:
2008
Program:
SBIR
Phase:
Phase I
Contract:
1R43GM083177-01
Award Id:
89162
Agency Tracking Number:
GM083177
Solicitation Year:
n/a
Solicitation Topic Code:
n/a
Solicitation Number:
n/a
Small Business Information
AGILE GENOMICS, LLC, 2488 Cotton Creek Dr., Mt Pleasant, SC, 29466
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
N
Duns:
782774314
Principal Investigator:
() -
Business Contact:
() -
luke@agilegenomics.com
Research Institute:
n/a
Abstract
DESCRIPTION (provided by applicant): Signal transduction systems regulate the majority of cellular activities including the metabolism, development, host-recognition, biofilm production, virulence, and antibiotic resistance of human pathogens. Thus, knowle dge of the proteins and interactions that comprise these communication networks is an essential component to furthering biomedical discovery. The proliferation of genomic data from high-throughput sequencing projects has dramatically accelerated biological discovery, yet there is an ever-increasing need for computational approaches to synthesize meaningful higher-order knowledge from this data. The inherent complexity of signal transduction systems has impeded efforts to elucidate the higher-order prope rties of these critical regulatory networks at the genomic level. The goal of the proposed research is to develop an effective, computational approach for deriving microbial signal transduction pathways from genomic data and linking these systems to their respective regulatory and metabolic targets. The proposed solution to computationally inferring signal transduction pathways involves a bottom-up approach that begins with analyzing signal transduction proteins at the domain level, followed by establishi ng clusters of orthologous domains, and finally grouping functionally associated two-component proteins into pathways using genomic context methods. The final product will be a comprehensive database of microbial signal transduction systems and their assoc iated metabolic networks. Knowledge of the signaling systems responsible for the virulence of human pathogens will promote our understanding of bacteria-host interactions, the immune response, novel antibiotic drug discovery, and therapeutic applications f or treating disease. Because of the critical role of signal transduction in bacteria, this project will significantly impact and contribute to biomedical discovery, public health care, bioremediation, and agriculture.

* information listed above is at the time of submission.

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