자료유형 | 학위논문 |
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서명/저자사항 | High-Throughput Characterization of Foodborne Pathogens using Next-Generation Sequencing. |
개인저자 | Carroll, Laura M. |
단체저자명 | Cornell University. Food Science and Technology. |
발행사항 | [S.l.]: Cornell University., 2019. |
발행사항 | Ann Arbor: ProQuest Dissertations & Theses, 2019. |
형태사항 | 229 p. |
기본자료 저록 | Dissertations Abstracts International 81-05B. Dissertation Abstract International |
ISBN | 9781088324028 |
학위논문주기 | Thesis (Ph.D.)--Cornell University, 2019. |
일반주기 |
Source: Dissertations Abstracts International, Volume: 81-05, Section: B.
Advisor: Wiedmann, Martin. |
이용제한사항 | This item must not be sold to any third party vendors. |
요약 | Next-generation sequencing (NGS) is being increasingly employed to characterize food-associated microbes and communities, including those which pose a threat to human health. As the amount of publicly available genomic data from these organisms increases, (i) rapid, scalable methods for inferring biological function from large amounts of NGS data are needed, and (ii) meaningful biological conclusions derived using these methods can be leveraged to improve safety along the food supply chain. The studies reported here detail the application of whole-genome sequencing (WGS) to two groups of organisms which differ in terms of the challenges they pose to human health: (i) non-typhoidal Salmonella enterica, a well-characterized, Gram-negative foodborne pathogen which boasts a large repertoire of established computational methods for analyzing WGS data derived from it, and (ii) the lesser-sequenced Bacillus cereus group, which consists of closely related, Gram-positive, spore-forming species which vary in their ability to cause disease in humans. For Salmonella enterica, antimicrobial resistance (AMR) was of particular concern |
일반주제명 | Microbiology. Bioinformatics. Food science. |
언어 | 영어 |
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