Comparison of microbial source tracking efficacy for detection of cattle fecal contamination by quantitative PCR

被引:5
|
作者
Xue, Jia [1 ]
Feng, Yucheng [1 ]
机构
[1] Auburn Univ, Dept Crop Soil & Environm Sci, Auburn, AL 36849 USA
基金
美国食品与农业研究所;
关键词
CowM2; CowM3; qPCR; Fecal contamination; Microbial source tracking; Water quality; REAL-TIME PCR; BACTEROIDALES GENETIC-MARKERS; POLYMERASE-CHAIN-REACTION; POLLUTION SOURCES; FRESH-WATER; PERFORMANCE; RUMINANT; ASSAYS; DNA; PERSISTENCE;
D O I
10.1016/j.scitotenv.2019.06.091
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Identification of fecal contamination sources in surface water has become heavily dependent on quantitative PCR (qPCR) because this technique allows for the rapid enumeration of fecal indicator bacteria as well as the detection and quantification of fecal source-associated genetic markers in the environment. Identification of contamination sources in impaired waters is a prerequisite for developing best management practices to reduce future pollution. Proper management decisions rely on the quality and interpretation of qPCR data. In this study, we developed a method to determine analytical and process lower limits of detection (LLOD) and quantification (LLOQ) using two cattle-associated genetic markers targeting Bacteroidales. Analytical LLOD (A(LLOD)) for both CowM2 and CowM3 genetic markers in the qPCR assay were five gene copies per reaction. Using composite fecal DNA, the analytical LLOQ (A(LLOQ)) determined for CowM2 and CowM3 were 78 and 195 gene copies/reaction, respectively. When plasmid DNA was used, the A(LLOQ) for CowM2 and CowM3 were 46 and 20 gene copies/reaction, respectively. The process LLOD (P-LLOD) for CowM2 and CowM3 were 0.4 and 0.02 mg feces/filter (wet weight), respectively. Using the standard deviation value of 0.25 as a cut-off point for LLOQ in regression analysis, the process LLOQ (P-LLOQ) for CowM2 and CowM3 were 3.2 and 0.3 mg feces/filter, respectively. These results indicate that CowM3 exhibited superior performance characteristics compared with CowM2 for fecal samples collected from our geographical region. Moreover, the method for calculating LLOD and LLOQ developed here can be applied to other microbial source tracking studies. (C) 2019 Elsevier B.V. All rights reserved.
引用
收藏
页码:1104 / 1112
页数:9
相关论文
共 50 条
  • [31] Validation and application of high-throughput quantitative PCR for the simultaneous detection of microbial source tracking markers in environmental water
    Raya, Sunayana
    Malla, Bikash
    Thakali, Ocean
    Angga, Made Sandhyana
    Segawa, Takahiro
    Sherchand, Jeevan B.
    Haramoto, Eiji
    SCIENCE OF THE TOTAL ENVIRONMENT, 2024, 940
  • [32] Microbial Source Tracking of Fecal Indicating Bacteria in Coral Reef Waters, Recreational Waters, and Groundwater of Saipan by Real-Time Quantitative PCR
    Sinigalliano, Christopher
    Kim, Kiho
    Gidley, Maribeth
    Yuknavage, Kathy
    Knee, Karen
    Palacios, Dean
    Bautista, Charito
    Bonacolta, Anthony
    Lee, Hyo Won
    Maurin, Larry
    FRONTIERS IN MICROBIOLOGY, 2021, 11
  • [33] Canine Scent Detection and Microbial Source Tracking of Human Waste Contamination in Storm Drains
    Van De Werfhorst, Laurie C.
    Murray, Jill L. S.
    Reynolds, Scott
    Reynolds, Karen
    Holden, Patricia A.
    WATER ENVIRONMENT RESEARCH, 2014, 86 (06) : 550 - 558
  • [34] Validation of microbial source tracking markers for the attribution of fecal contamination in indoor-household environments of the Peruvian Amazon
    Schiaffino, Francesca
    Pisanic, Nora
    Colston, Josh M.
    Rengifo, Dixner
    Paredes Olortegui, Maribel
    Shapiama, Valentino
    Penataro Yori, Pablo
    Heaney, Christopher D.
    Davis, Meghan F.
    Kosek, Margaret N.
    SCIENCE OF THE TOTAL ENVIRONMENT, 2020, 743
  • [35] Development of a quantitative PCR assay for the quantitation of bovine polyomavirus as a microbial source-tracking tool
    Hundesa, Ayalkibet
    Bofill-Mas, Silvia
    Maluquer de Motes, Carlos
    Rodriguez-Manzano, Jesus
    Bach, Alex
    Casas, Maribel
    Girones, Rosina
    JOURNAL OF VIROLOGICAL METHODS, 2010, 163 (02) : 385 - 389
  • [36] Microbial source tracking in a rural watershed dominated by cattle
    Graves, A. K.
    Hayedorn, C.
    Brooks, A.
    Hagedorn, R. L.
    Martin, E.
    WATER RESEARCH, 2007, 41 (16) : 3729 - 3739
  • [37] Analysis of human and animal fecal microbiota for microbial source tracking
    Jung Eun Lee
    Sunghee Lee
    Joohon Sung
    GwangPyo Ko
    The ISME Journal, 2011, 5 : 362 - 365
  • [38] Analysis of human and animal fecal microbiota for microbial source tracking
    Lee, Jung Eun
    Lee, Sunghee
    Sung, Joohon
    Ko, GwangPyo
    ISME JOURNAL, 2011, 5 (02): : 362 - 365
  • [39] Quantitative Microbial Risk Assessment with Microbial Source Tracking for Mixed Fecal Sources Contaminating Recreational River Waters, Iowa, USA
    Burch, Tucker R.
    Stokdyk, Joel P.
    Firnstahl, Aaron D.
    Opelt, Sarah A.
    Cook, Rachel M.
    Heffron, Joseph A.
    Brown, Amanda
    Hruby, Claire
    Borchardt, Mark A.
    ACS ES&T WATER, 2024, 4 (07): : 2789 - 2802
  • [40] Comparison of Microbial and Chemical Source Tracking Markers To Identify Fecal Contamination Sources in the Humber River (Toronto, Ontario, Canada) and Associated Storm Water Outfalls
    Staley, Zachery R.
    Grabuski, Josey
    Sverko, Ed
    Edge, Thomas A.
    APPLIED AND ENVIRONMENTAL MICROBIOLOGY, 2016, 82 (21) : 6357 - 6366