文献类型：期刊文献

英文题名：Time-Resolved Transposon Insertion Sequencing Reveals Genome-Wide Fitness Dynamics during Infection

作者：Yang, Guanhua[1];Billings, Gabriel[3,4,5];Hubbard, Troy P.[3,4,5];Park, Joseph S.[3,4,5];Leung, Ka Yin[1,6];Liu, Qin[1,2];Davis, Brigid M.[3,4,5];Zhang, Yuanxing[1];Wang, Qiyao[1,2];Waldor, Matthew K.[1,3,4,5]

机构：[1]East China Univ Sci & Technol, State Key Lab Bioreactor Engn, Shanghai, Peoples R China;[2]Qingdao Natl Lab Marine Sci & Technol, Qingdao, Peoples R China;[3]Dept Microbiol & Immunobiol, Boston, MA USA;[4]Harvard Med Sch, Brigham & Womens Hosp, Boston, MA USA;[5]Howard Hughes Med Inst, Boston, MA 02115 USA;[6]Trinity Western Univ, Dept Biol, Langley, BC, Canada

年份：2017

卷号：8

期号：5

外文期刊名：MBIO

收录：;WOS:【SCI-EXPANDED(收录号:WOS:000416271100082)】；

基金：This study was supported by National Natural Science Foundation of China grant no. 31430090 (Y.X.Z.), Ministry of Agriculture of China grant no. CRAS-47 (Q.Y.W.), and Shanghai Pujiang Program grant no. 16PJD018 (Q.Y.W.). The Waldor lab is supported by Howard Hughes Medical Institute (HHMI) grant no. 063101 and National Institutes of Health grants AI R37-042347 (M.K.W.) and F31 AI-120 665 (T.P.H.). K.Y.L. was supported by a Natural Sciences and Engineering Research Council of Canada (NSERC) Discovery grant (06385-2014).

语种：英文

外文关键词：Edwardsiella piscicida; live attenuated vaccine; pattern analysis of conditional essentiality (PACE); transposon insertion sequencing; fitness dynamics and profiles

摘要：Transposon insertion sequencing (TIS) is a powerful high-throughput genetic technique that is transforming functional genomics in prokaryotes, because it enables genome-wide mapping of the determinants of fitness. However, current approaches for analyzing TIS data assume that selective pressures are constant over time and thus do not yield information regarding changes in the genetic requirements for growth in dynamic environments (e.g., during infection). Here, we describe structured analysis of TIS data collected as a time series, termed pattern analysis of conditional essentiality (PACE). From a temporal series of TIS data, PACE derives a quantitative assessment of each mutant's fitness over the course of an experiment and identifies mutants with related fitness profiles. In so doing, PACE circumvents major limitations of existing methodologies, specifically the need for artificial effect size thresholds and enumeration of bacterial population expansion. We used PACE to analyze TIS samples of Edwardsiella piscicida (a fish pathogen) collected over a 2-week infection period from a natural host (the flatfish turbot). PACE uncovered more genes that affect E. piscicida's fitness in vivo than were detected using a cutoff at a terminal sampling point, and it identified subpopulations of mutants with distinct fitness profiles, one of which informed the design of new live vaccine candidates. Overall, PACE enables efficient mining of time series TIS data and enhances the power and sensitivity of TIS-based analyses. IMPORTANCE Transposon insertion sequencing (TIS) enables genome-wide mapping of the genetic determinants of fitness, typically based on observations at a single sampling point. Here, we move beyond analysis of endpoint TIS data to create a framework for analysis of time series TIS data, termed pattern analysis of conditional essentiality (PACE). We applied PACE to identify genes that contribute to colonization of a natural host by the fish pathogen Edwardsiella piscicida. PACE uncovered more genes that affect E. piscicida's fitness in vivo than were detected using a terminal sampling point, and its clustering of mutants with related fitness profiles informed design of new live vaccine candidates. PACE yields insights into patterns of fitness dynamics and circumvents major limitations of existing methodologies. Finally, the PACE method should be applicable to additional "omic" time series data, including screens based on clustered regularly interspaced short palindromic repeats with Cas9 (CRISPR/Cas9).