Selecting rep-PCR markers to source track fecal contamination in Laguna Lake, Philippines

Author:

Labrador Kevin L.1,Nacario Mae Ashley G.12,Malajacan Gicelle T.12,Abello Joseth Jermaine M.12,Galarion Luiza H.1,Rensing Christopher3,Rivera Windell L.12

Affiliation:

1. Pathogen-Host-Environment Interactions Research Laboratory, Natural Sciences Research Institute, University of the Philippines Diliman, Quezon City, Philippines

2. Institute of Biology, College of Science, University of the Philippines Diliman, Quezon City, Philippines

3. Fujian Provincial Key Laboratory of Soil Environmental Health and Regulation, College of Resources and Environment, Fujian Agriculture and Forestry University, Fuzhou, China

Abstract

Abstract Fecal contamination is one of the factors causing deterioration of Laguna Lake. Although total coliform levels are constantly monitored, no protocol is in place to identify their origin. This can be addressed using the library-dependent microbial source tracking (MST) method, repetitive element sequence-based polymerase chain reaction (rep-PCR) fingerprinting. Serving as a prerequisite in developing the host-origin library, we assessed the discriminatory power of three fingerprinting primers, namely BOX-A1R, (GTG)5, and REP1R-1/2-1. Fingerprint profiles were obtained from 290 thermotolerant Escherichia coli isolated from sewage waters and fecal samples of cows, chickens, and pigs from regions surrounding the lake. Band patterns were converted into binary profiles and were classified using the discriminant analysis of principal components. Results show that: (1) REP1R-1/2-1 has a low genotyping success rate and information content; (2) increasing the library size led to more precise estimates of library accuracy; and (3) combining fingerprint profiles from BOX-A1R and (GTG)5 revealed the best discrimination (average rate of correct classification (ARCC) = 0.82 ± 0.06) in a two-way categorical split; while (4) no significant difference was found between the combined profiles (0.74 ± 0.15) and using solely BOX-A1R (0.76 ± 0.09) in a four-way split. Testing the library by identifying known isolates from a separate dataset has shown that a two-way classification performed better (ARCC = 0.66) than a four-way split (ARCC = 0.29). The library can be developed further by adding more representative isolates per host source. Nevertheless, our results have shown that combining profiles from BOX-A1R and (GTG)5 is recommended in developing the MST library for Laguna Lake.

Funder

Philippine Council for Industry, Energy, and Emerging Technology Research and Development

Publisher

IWA Publishing

Subject

Infectious Diseases,Microbiology (medical),Public Health, Environmental and Occupational Health,Waste Management and Disposal,Water Science and Technology

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3