Occurrence of Traditional and Alternative Fecal Indicators in Tropical Urban Environments under Different Land Use Patterns

This study evaluated the geospatial distribution of fecal indicator bacteria (FIB) (i.e., , spp.) and the alternative fecal indicator pepper mild mottle virus (PMMoV) in tropical freshwater environments under different land use patterns. Results show that the occurrence and concentration of microbia...

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Published in:Applied and environmental microbiology Vol. 84; no. 14; p. e00287-18
Main Authors: Saeidi, Nazanin, Gu, Xiaoqiong, Tran, Ngoc Han, Goh, Shin Giek, Kitajima, Masaaki, Kushmaro, Ariel, Schmitz, Bradley William, Gin, Karina Yew-Hoong
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Language:English
Published: United States American Society for Microbiology 15-07-2018
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Abstract This study evaluated the geospatial distribution of fecal indicator bacteria (FIB) (i.e., , spp.) and the alternative fecal indicator pepper mild mottle virus (PMMoV) in tropical freshwater environments under different land use patterns. Results show that the occurrence and concentration of microbial fecal indicators were higher for urban than for parkland-dominated areas, consistent with land use weightage. Significant positive correlations with traditional FIB indicate that PMMoV is a suitable indicator of fecal contamination in tropical catchments waters (0.549 ≤ rho ≤ 0.612; < 0.01). PMMoV exhibited a strong significant correlation with land use weightage (rho = 0.728; < 0.01) compared to traditional FIB (rho = 0.583; < 0.01). In addition, chemical tracers were also added to evaluate the potential relationships with microbial fecal indicators. The relationships between diverse variables (e.g., environmental parameters, land use coverage, and chemical tracers) and the occurrence of FIB and PMMoV were evaluated. By using stepwise multiple linear regression (MLR), the empirical experimental models substantiate the impact of land use patterns and anthropogenic activities on microbial water quality, and the output results of the empirical models may be able to predict the sources and transportation of human fecal pollution or sewage contamination. In addition, the high correlation between PMMoV data obtained from quantitative real-time PCR (qPCR) and viral metagenomics data supports the possibility of using viral metagenomics to relatively quantify specific microbial indicators for monitoring microbial water quality (0.588 ≤ rho ≤ 0.879; < 0.05). The results of this study may support the hypothesis of using PMMoV as an alternative indicator of human fecal contamination in tropical surface waters from the perspective of land use patterns. The predictive result of the occurrence of human fecal indicators with high accuracy may reflect the source and transportation of human fecal pollution, which are directly related to the risk to human health, and thereafter, steps can be taken to mitigate these risks.
AbstractList This study evaluated the geospatial distribution of fecal indicator bacteria (FIB) (i.e., Escherichia coli , Enterococcus spp.) and the alternative fecal indicator pepper mild mottle virus (PMMoV) in tropical freshwater environments under different land use patterns. Results show that the occurrence and concentration of microbial fecal indicators were higher for urban than for parkland-dominated areas, consistent with land use weightage. Significant positive correlations with traditional FIB indicate that PMMoV is a suitable indicator of fecal contamination in tropical catchments waters (0.549 ≤ rho ≤ 0.612; P < 0.01). PMMoV exhibited a strong significant correlation with land use weightage (rho = 0.728; P < 0.01) compared to traditional FIB (rho = 0.583; P < 0.01). In addition, chemical tracers were also added to evaluate the potential relationships with microbial fecal indicators. The relationships between diverse variables (e.g., environmental parameters, land use coverage, and chemical tracers) and the occurrence of FIB and PMMoV were evaluated. By using stepwise multiple linear regression (MLR), the empirical experimental models substantiate the impact of land use patterns and anthropogenic activities on microbial water quality, and the output results of the empirical models may be able to predict the sources and transportation of human fecal pollution or sewage contamination. In addition, the high correlation between PMMoV data obtained from quantitative real-time PCR (qPCR) and viral metagenomics data supports the possibility of using viral metagenomics to relatively quantify specific microbial indicators for monitoring microbial water quality (0.588 ≤ rho ≤ 0.879; P < 0.05). IMPORTANCE The results of this study may support the hypothesis of using PMMoV as an alternative indicator of human fecal contamination in tropical surface waters from the perspective of land use patterns. The predictive result of the occurrence of human fecal indicators with high accuracy may reflect the source and transportation of human fecal pollution, which are directly related to the risk to human health, and thereafter, steps can be taken to mitigate these risks.
This study evaluated the geospatial distribution of fecal indicator bacteria (FIB) (i.e., Escherichia coli, Enterococcus spp.) and the alternative fecal indicator pepper mild mottle virus (PMMoV) in tropical freshwater environments under different land use patterns. Results show that the occurrence and concentration of microbial fecal indicators were higher for urban than for parkland-dominated areas, consistent with land use weightage. Significant positive correlations with traditional FIB indicate that PMMoV is a suitable indicator of fecal contamination in tropical catchments waters (0.549 ≤ rho ≤ 0.612; P < 0.01). PMMoV exhibited a strong significant correlation with land use weightage (rho = 0.728; P < 0.01) compared to traditional FIB (rho = 0.583; P < 0.01). In addition, chemical tracers were also added to evaluate the potential relationships with microbial fecal indicators. The relationships between diverse variables (e.g., environmental parameters, land use coverage, and chemical tracers) and the occurrence of FIB and PMMoV were evaluated. By using stepwise multiple linear regression (MLR), the empirical experimental models substantiate the impact of land use patterns and anthropogenic activities on microbial water quality, and the output results of the empirical models may be able to predict the sources and transportation of human fecal pollution or sewage contamination. In addition, the high correlation between PMMoV data obtained from quantitative real-time PCR (qPCR) and viral metagenomics data supports the possibility of using viral metagenomics to relatively quantify specific microbial indicators for monitoring microbial water quality (0.588 ≤ rho ≤ 0.879; P < 0.05).
This study evaluated the geospatial distribution of fecal indicator bacteria (FIB) (i.e., , spp.) and the alternative fecal indicator pepper mild mottle virus (PMMoV) in tropical freshwater environments under different land use patterns. Results show that the occurrence and concentration of microbial fecal indicators were higher for urban than for parkland-dominated areas, consistent with land use weightage. Significant positive correlations with traditional FIB indicate that PMMoV is a suitable indicator of fecal contamination in tropical catchments waters (0.549 ≤ rho ≤ 0.612; < 0.01). PMMoV exhibited a strong significant correlation with land use weightage (rho = 0.728; < 0.01) compared to traditional FIB (rho = 0.583; < 0.01). In addition, chemical tracers were also added to evaluate the potential relationships with microbial fecal indicators. The relationships between diverse variables (e.g., environmental parameters, land use coverage, and chemical tracers) and the occurrence of FIB and PMMoV were evaluated. By using stepwise multiple linear regression (MLR), the empirical experimental models substantiate the impact of land use patterns and anthropogenic activities on microbial water quality, and the output results of the empirical models may be able to predict the sources and transportation of human fecal pollution or sewage contamination. In addition, the high correlation between PMMoV data obtained from quantitative real-time PCR (qPCR) and viral metagenomics data supports the possibility of using viral metagenomics to relatively quantify specific microbial indicators for monitoring microbial water quality (0.588 ≤ rho ≤ 0.879; < 0.05). The results of this study may support the hypothesis of using PMMoV as an alternative indicator of human fecal contamination in tropical surface waters from the perspective of land use patterns. The predictive result of the occurrence of human fecal indicators with high accuracy may reflect the source and transportation of human fecal pollution, which are directly related to the risk to human health, and thereafter, steps can be taken to mitigate these risks.
This study evaluated the geospatial distribution of fecal indicator bacteria (FIB) (i.e., Escherichia coli, Enterococcus spp.) and the alternative fecal indicator pepper mild mottle virus (PMMoV) in tropical freshwater environments under different land use patterns. Results show that the occurrence and concentration of microbial fecal indicators were higher for urban than for parkland-dominated areas, consistent with land use weightage. Significant positive correlations with traditional FIB indicate that PMMoV is a suitable indicator of fecal contamination in tropical catchments waters (0.549 ≤ rho ≤ 0.612; P &lt; 0.01). PMMoV exhibited a strong significant correlation with land use weightage (rho = 0.728; P &lt; 0.01) compared to traditional FIB (rho = 0.583; P &lt; 0.01). In addition, chemical tracers were also added to evaluate the potential relationships with microbial fecal indicators. The relationships between diverse variables (e.g., environmental parameters, land use coverage, and chemical tracers) and the occurrence of FIB and PMMoV were evaluated. By using stepwise multiple linear regression (MLR), the empirical experimental models substantiate the impact of land use patterns and anthropogenic activities on microbial water quality, and the output results of the empirical models may be able to predict the sources and transportation of human fecal pollution or sewage contamination. In addition, the high correlation between PMMoV data obtained from quantitative real-time PCR (qPCR) and viral metagenomics data supports the possibility of using viral metagenomics to relatively quantify specific microbial indicators for monitoring microbial water quality (0.588 ≤ rho ≤ 0.879; P &lt; 0.05).IMPORTANCE The results of this study may support the hypothesis of using PMMoV as an alternative indicator of human fecal contamination in tropical surface waters from the perspective of land use patterns. The predictive result of the occurrence of human fecal indicators with high accuracy may reflect the source and transportation of human fecal pollution, which are directly related to the risk to human health, and thereafter, steps can be taken to mitigate these risks.
Author Saeidi, Nazanin
Kitajima, Masaaki
Goh, Shin Giek
Gin, Karina Yew-Hoong
Kushmaro, Ariel
Gu, Xiaoqiong
Tran, Ngoc Han
Schmitz, Bradley William
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  surname: Saeidi
  fullname: Saeidi, Nazanin
  organization: Department of Civil and Environmental Engineering, National University of Singapore, Singapore
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  givenname: Xiaoqiong
  surname: Gu
  fullname: Gu, Xiaoqiong
  organization: Department of Civil and Environmental Engineering, National University of Singapore, Singapore
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  givenname: Ngoc Han
  surname: Tran
  fullname: Tran, Ngoc Han
  organization: NUS Environmental Research Institute (NERI), Singapore
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  givenname: Shin Giek
  surname: Goh
  fullname: Goh, Shin Giek
  organization: Department of Civil and Environmental Engineering, National University of Singapore, Singapore
– sequence: 5
  givenname: Masaaki
  surname: Kitajima
  fullname: Kitajima, Masaaki
  organization: Division of Environmental Engineering, Hokkaido University, Hokkaido, Japan
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  givenname: Ariel
  surname: Kushmaro
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  organization: School of Material Science and Engineering, Nanyang Technological University, Singapore
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  organization: Department of Civil and Environmental Engineering, National University of Singapore, Singapore
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  givenname: Karina Yew-Hoong
  surname: Gin
  fullname: Gin, Karina Yew-Hoong
  email: ceeginyh@nus.edu.sg
  organization: NUS Environmental Research Institute (NERI), Singapore
BackLink https://www.ncbi.nlm.nih.gov/pubmed/29776926$$D View this record in MEDLINE/PubMed
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Copyright Copyright © 2018 American Society for Microbiology.
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DocumentTitleAlternate Relationships between Land Use and Fecal Indicators
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Issue 14
Keywords freshwater environments
land use
fecal indicators
chemical tracers
regression models
Language English
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All Rights Reserved.
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Citation Saeidi N, Gu X, Tran NH, Goh SG, Kitajima M, Kushmaro A, Schmitz BW, Gin KY-H. 2018. Occurrence of traditional and alternative fecal indicators in tropical urban environments under different land use patterns. Appl Environ Microbiol 84:e00287-18. https://doi.org/10.1128/AEM.00287-18.
N.S. and X.G. contributed equally to this work.
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Snippet This study evaluated the geospatial distribution of fecal indicator bacteria (FIB) (i.e., , spp.) and the alternative fecal indicator pepper mild mottle virus...
This study evaluated the geospatial distribution of fecal indicator bacteria (FIB) (i.e., Escherichia coli , Enterococcus spp.) and the alternative fecal...
This study evaluated the geospatial distribution of fecal indicator bacteria (FIB) (i.e., Escherichia coli, Enterococcus spp.) and the alternative fecal...
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StartPage e00287-18
SubjectTerms Anthropogenic factors
Catchments
Contamination
Correlation
E coli
Environmental monitoring
Fecal coliforms
Feces
Freshwater environments
Human influences
Indicators
Land use
Microbiology
Microorganisms
Organic chemistry
Pollution sources
Polymerase chain reaction
Public and Environmental Health Microbiology
Regression analysis
Sewage
Tracers
Urban areas
Urban environments
Viruses
Water pollution
Water quality
Title Occurrence of Traditional and Alternative Fecal Indicators in Tropical Urban Environments under Different Land Use Patterns
URI https://www.ncbi.nlm.nih.gov/pubmed/29776926
https://www.proquest.com/docview/2076376979
https://search.proquest.com/docview/2041624725
https://pubmed.ncbi.nlm.nih.gov/PMC6029086
Volume 84
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