Source: GEORGIA INSTITUTE OF TECHNOLOGY submitted to
DEVELOPMENT OF A METAGENOMICS-BASED METHOD FOR IMPROVED DETECTION OF FOODBORNE PATHOGENS
Sponsoring Institution
Agricultural Research Service/USDA
Project Status
ACTIVE
Funding Source
Reporting Frequency
Annual
Accession No.
0427089
Grant No.
(N/A)
Cumulative Award Amt.
(N/A)
Proposal No.
(N/A)
Multistate No.
(N/A)
Project Start Date
Aug 28, 2014
Project End Date
Jul 31, 2016
Grant Year
(N/A)
Program Code
[(N/A)]- (N/A)
Project Director
CARTER M Q
Recipient Organization
GEORGIA INSTITUTE OF TECHNOLOGY
(N/A)
ATLANTA,GA 30332
Performing Department
MICROBIAL FOOD SAFETY RESEARCH UNIT
Non Technical Summary
(N/A)
Animal Health Component
20%
Research Effort Categories
Basic
70%
Applied
20%
Developmental
10%
Classification

Knowledge Area (KA)Subject of Investigation (SOI)Field of Science (FOS)Percent
71214301100100%
Goals / Objectives
1. Identify and test the discriminatory power of gene signatures for Shiga toxin-producing Escherichia coli (STEC) to establish biomarkers that robustly distinguish STEC from innocuous relatives adapted to environmental niches; 2. Establish bioinformatics protocols that enable reliable detection of these biomarkers in produce-associated microbial community through sequence-based, culture-independent diagnostic tests; 3. Apply the developed method to characterize the interactions between produce-associated microbial communities and STECs under pre- and post-harvested conditions.
Project Methods
Biomarkers for Shiga toxin-producing Escherichia coli (STEC) will be generated by comparatively analyzing a large number STEC genomes with other E. coli genomes deposited in GenBank. A corresponding bioinformatics pipeline will be developed at GIT for accurate identification of STEC biomarkers in produce-associated metagenomic samples. The detection limit and sensitivity of the method will be evaluated using a ¿spiked¿ system on leafy greens, which will be carried out at the Agricultural Research Service. The interactions between STECs with produce-associated microflora under pre- and post-harvest conditions will be investigated using the developed metagenomic tools.