Application of an Integrated Community Analysis Approach for Microbial Source Tracking in a Coastal Creek

被引:14
作者
Cao, Yiping [3 ]
Van De Werfhorst, Laurie C. [1 ,2 ]
Sercu, Bram [1 ,2 ]
Murray, Jill L. S. [4 ]
Holden, Patricia A. [1 ,2 ]
机构
[1] Univ Calif Santa Barbara, Donald Bren Sch Environm Sci & Management, Santa Barbara, CA 93106 USA
[2] Univ Calif Santa Barbara, Earth Res Inst, Santa Barbara, CA 93106 USA
[3] So Calif Coastal Water Res Project, Costa Mesa, CA 92626 USA
[4] City Santa Barbara, Santa Barbara, CA 93102 USA
关键词
RIBOSOMAL-RNA GENES; FECAL POLLUTION; MARKERS; DIVERSITY; WATER; BACTERIA; IDENTIFICATION; OPTIMIZATION; PARADIGM;
D O I
10.1021/es201118r
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
High fecal indicator bacterial (FIB) concentrations signal urban coastal water quality impairments that can threaten public health. However, FIB (total and fecal coliform plus Enterococcus sp.) concentrations are not specific to human waste, and thus, microbial source tracking (MST) is employed to assess public health risks and remediation alternatives. Currently, water quality diagnosis requires several simultaneous MST assays. Relatively unexplored is a community analysis approach for MST where the overall microbial community composition is compared, through multivariate analysis, to link sources and sinks of microbial pollution. In this research, an urban coastal creek and drain sampling transect, previously diagnosed as human-waste-contaminated, were evaluated for bacterial community composition relative to fecal sources; a laboratory spiking study was also performed to assess method sensitivity and specificity. Multivariate statistical analysis of community profiles clearly distinguished different fecal sources, indicated a high sensitivity for sewage spikes, and confirmed creekcontamination sources. This work demonstrates that molecular microbial community analysis multivariate statistical analyses is an effective addition to the MST tool box. combined with appropriate
引用
收藏
页码:7195 / 7201
页数:7
相关论文
共 44 条
  • [31] Advances in the use of terminal restriction fragment length polymorphism (T-RFLP) analysis of 16S rRNA genes to characterize microbial communities
    Schutte, Ursel M. E.
    Abdo, Zaid
    Bent, Stephen J.
    Shyu, Conrad
    Williams, Christopher J.
    Pierson, Jacob D.
    Forney, Larry J.
    [J]. APPLIED MICROBIOLOGY AND BIOTECHNOLOGY, 2008, 80 (03) : 365 - 380
  • [32] Storm Drains are Sources of Human Fecal Pollution during Dry Weather in Three Urban Southern California Watersheds
    Sercu, Brain
    Van De Werfhorst, Laurie C.
    Murray, Jill
    Holden, Patricia A.
    [J]. ENVIRONMENTAL SCIENCE & TECHNOLOGY, 2009, 43 (02) : 293 - 298
  • [33] Community Structures of Fecal Bacteria in Cattle from Different Animal Feeding Operations
    Shanks, Orin C.
    Kelty, Catherine A.
    Archibeque, Shawn
    Jenkins, Michael
    Newton, Ryan J.
    McLellan, Sandra L.
    Huse, Susan M.
    Sogin, Mitchell L.
    [J]. APPLIED AND ENVIRONMENTAL MICROBIOLOGY, 2011, 77 (09) : 2992 - 3001
  • [34] Assessment of equine fecal contamination: the search for alternative bacterial source-tracking targets
    Simpson, JM
    Domingo, JWS
    Reasoner, DJ
    [J]. FEMS MICROBIOLOGY ECOLOGY, 2004, 47 (01) : 65 - 75
  • [35] Using DNA microarrays to identify library-independent markers for bacterial source tracking
    Soule, M
    Kuhn, E
    Loge, F
    Gay, J
    Call, DR
    [J]. APPLIED AND ENVIRONMENTAL MICROBIOLOGY, 2006, 72 (03) : 1843 - 1851
  • [36] Stewart Jill R., 2003, Journal of Water and Health, V1, P225
  • [37] Ter Braak CJF, 2012, CANOCO REFERENCE MAN
  • [38] Soil microbial community analysis using terminal restriction fragment length polymorphisms
    Thies, Janice E.
    [J]. SOIL SCIENCE SOCIETY OF AMERICA JOURNAL, 2007, 71 (02) : 579 - 591
  • [39] United States Environmental Protection Agency, 2005, MICR SOURC TRACK GUI, P150
  • [40] Use of Barcoded Pyrosequencing and Shared OTUs To Determine Sources of Fecal Bacteria in Watersheds
    Unno, Tatsuya
    Jang, Jeonghwan
    Han, Dukki
    Kim, Joon Ha
    Sadowsky, Michael J.
    Kim, Ok-Sun
    Chun, Jongsik
    Hur, Hor-Gil
    [J]. ENVIRONMENTAL SCIENCE & TECHNOLOGY, 2010, 44 (20) : 7777 - 7782