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Biomonitoring along the Tropical Southern Indian Coast with Multiple Biomarkers

We assessed the spatial and temporal variations of pollution indicators and geochemical and trace metal parameters (23 in total) from water and sediment (144 samples) of three different eco-niches (beach, fishing harbor, and estuary) in larger coastal cities of southern India (Cuddalore and Pondiche...

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Autores principales: Vignesh, Sivanandham, Dahms, Hans-Uwe, Muthukumar, Krishnan, Vignesh, Gopalaswamy, James, Rathinam Arthur
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5152820/
https://www.ncbi.nlm.nih.gov/pubmed/27941969
http://dx.doi.org/10.1371/journal.pone.0154105
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author Vignesh, Sivanandham
Dahms, Hans-Uwe
Muthukumar, Krishnan
Vignesh, Gopalaswamy
James, Rathinam Arthur
author_facet Vignesh, Sivanandham
Dahms, Hans-Uwe
Muthukumar, Krishnan
Vignesh, Gopalaswamy
James, Rathinam Arthur
author_sort Vignesh, Sivanandham
collection PubMed
description We assessed the spatial and temporal variations of pollution indicators and geochemical and trace metal parameters (23 in total) from water and sediment (144 samples) of three different eco-niches (beach, fishing harbor, and estuary) in larger coastal cities of southern India (Cuddalore and Pondicherry) for one year. A total of 120 marine Pseudomonas isolates were challenged against different concentrations of copper solutions and 10 different antibiotics in heavy metal and antibiotic resistance approaches, respectively. The study shows that 4.16% of the isolates could survive in 250 mM of copper; 70% were resistant to minimum concentrations. Strains were resistant (98.4%) to at least one antibiotic in Cuddalore compared to the Pondicherry (78.4%) region. Pollution index (PI) (0–14.55) and antibiotic resistance index (ARI) (0.05–0.10) ratio indicated that high bacterial and antibiotic loads were released into the coastal environment. The degree of trace metal contamination in sediments were calculated by enrichment factor (EF), contamination factor (CF), pollution load index (PLI), and geo-accumulation index (I(geo)). Statistical parameters like two-way analysis of variance (ANOVA), correlation, factor analysis and scatter matrix tools were employed between the 23 parameters in order to find sources, pathways, disparities and interactions of environmental pollutants. It indicates that geochemical and biological parameters were not strongly associated with each other (except a few) and were affected by different sources. Factor analysis elucidated, ‘microbe–metal’ interaction (Factor 1–48.86%), ‘anthropogenic’ factor (Factor 2–13.23%) and ‘Pseudomonas–Cadmium’ factor (Factor 3–11.74%), respectively.
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spelling pubmed-51528202016-12-28 Biomonitoring along the Tropical Southern Indian Coast with Multiple Biomarkers Vignesh, Sivanandham Dahms, Hans-Uwe Muthukumar, Krishnan Vignesh, Gopalaswamy James, Rathinam Arthur PLoS One Research Article We assessed the spatial and temporal variations of pollution indicators and geochemical and trace metal parameters (23 in total) from water and sediment (144 samples) of three different eco-niches (beach, fishing harbor, and estuary) in larger coastal cities of southern India (Cuddalore and Pondicherry) for one year. A total of 120 marine Pseudomonas isolates were challenged against different concentrations of copper solutions and 10 different antibiotics in heavy metal and antibiotic resistance approaches, respectively. The study shows that 4.16% of the isolates could survive in 250 mM of copper; 70% were resistant to minimum concentrations. Strains were resistant (98.4%) to at least one antibiotic in Cuddalore compared to the Pondicherry (78.4%) region. Pollution index (PI) (0–14.55) and antibiotic resistance index (ARI) (0.05–0.10) ratio indicated that high bacterial and antibiotic loads were released into the coastal environment. The degree of trace metal contamination in sediments were calculated by enrichment factor (EF), contamination factor (CF), pollution load index (PLI), and geo-accumulation index (I(geo)). Statistical parameters like two-way analysis of variance (ANOVA), correlation, factor analysis and scatter matrix tools were employed between the 23 parameters in order to find sources, pathways, disparities and interactions of environmental pollutants. It indicates that geochemical and biological parameters were not strongly associated with each other (except a few) and were affected by different sources. Factor analysis elucidated, ‘microbe–metal’ interaction (Factor 1–48.86%), ‘anthropogenic’ factor (Factor 2–13.23%) and ‘Pseudomonas–Cadmium’ factor (Factor 3–11.74%), respectively. Public Library of Science 2016-12-12 /pmc/articles/PMC5152820/ /pubmed/27941969 http://dx.doi.org/10.1371/journal.pone.0154105 Text en © 2016 Vignesh et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Vignesh, Sivanandham
Dahms, Hans-Uwe
Muthukumar, Krishnan
Vignesh, Gopalaswamy
James, Rathinam Arthur
Biomonitoring along the Tropical Southern Indian Coast with Multiple Biomarkers
title Biomonitoring along the Tropical Southern Indian Coast with Multiple Biomarkers
title_full Biomonitoring along the Tropical Southern Indian Coast with Multiple Biomarkers
title_fullStr Biomonitoring along the Tropical Southern Indian Coast with Multiple Biomarkers
title_full_unstemmed Biomonitoring along the Tropical Southern Indian Coast with Multiple Biomarkers
title_short Biomonitoring along the Tropical Southern Indian Coast with Multiple Biomarkers
title_sort biomonitoring along the tropical southern indian coast with multiple biomarkers
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5152820/
https://www.ncbi.nlm.nih.gov/pubmed/27941969
http://dx.doi.org/10.1371/journal.pone.0154105
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