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Application of QSAR Approach to Assess the Effects of Organic Pollutants on Bacterial Virulence Factors

The release of a wide variety of persistent chemical contaminants into wastewater has become a growing concern due to their potential health and environmental risks. While the toxic effects of these pollutants on aquatic organisms have been extensively studied, their impact on microbial pathogens an...

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Autores principales: Al Haj Ishak Al Ali, Roukaya, Mondamert, Leslie, Berjeaud, Jean-Marc, Jandry, Joelle, Crépin, Alexandre, Labanowski, Jérôme
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10301662/
https://www.ncbi.nlm.nih.gov/pubmed/37374877
http://dx.doi.org/10.3390/microorganisms11061375
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author Al Haj Ishak Al Ali, Roukaya
Mondamert, Leslie
Berjeaud, Jean-Marc
Jandry, Joelle
Crépin, Alexandre
Labanowski, Jérôme
author_facet Al Haj Ishak Al Ali, Roukaya
Mondamert, Leslie
Berjeaud, Jean-Marc
Jandry, Joelle
Crépin, Alexandre
Labanowski, Jérôme
author_sort Al Haj Ishak Al Ali, Roukaya
collection PubMed
description The release of a wide variety of persistent chemical contaminants into wastewater has become a growing concern due to their potential health and environmental risks. While the toxic effects of these pollutants on aquatic organisms have been extensively studied, their impact on microbial pathogens and their virulence mechanisms remains largely unexplored. This research paper focuses on the identification and prioritization of chemical pollutants that increase bacterial pathogenicity, which is a public health concern. In order to predict how chemical compounds, such as pesticides and pharmaceuticals, would affect the virulence mechanisms of three bacterial strains (Escherichia coli K12, Pseudomonas aeruginosa H103, and Salmonella enterica serovar. Typhimurium), this study has developed quantitative structure–activity relationship (QSAR) models. The use of analysis of variance (ANOVA) functions assists in developing QSAR models based on the chemical structure of the compounds, to predict their effect on the growth and swarming behavior of the bacterial strains. The results showed an uncertainty in the created model, and that increases in virulence factors, including growth and motility of bacteria, after exposure to the studied compounds are possible to be predicted. These results could be more accurate if the interactions between groups of functions are included. For that, to make an accurate and universal model, it is essential to incorporate a larger number of compounds of similar and different structures.
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spelling pubmed-103016622023-06-29 Application of QSAR Approach to Assess the Effects of Organic Pollutants on Bacterial Virulence Factors Al Haj Ishak Al Ali, Roukaya Mondamert, Leslie Berjeaud, Jean-Marc Jandry, Joelle Crépin, Alexandre Labanowski, Jérôme Microorganisms Article The release of a wide variety of persistent chemical contaminants into wastewater has become a growing concern due to their potential health and environmental risks. While the toxic effects of these pollutants on aquatic organisms have been extensively studied, their impact on microbial pathogens and their virulence mechanisms remains largely unexplored. This research paper focuses on the identification and prioritization of chemical pollutants that increase bacterial pathogenicity, which is a public health concern. In order to predict how chemical compounds, such as pesticides and pharmaceuticals, would affect the virulence mechanisms of three bacterial strains (Escherichia coli K12, Pseudomonas aeruginosa H103, and Salmonella enterica serovar. Typhimurium), this study has developed quantitative structure–activity relationship (QSAR) models. The use of analysis of variance (ANOVA) functions assists in developing QSAR models based on the chemical structure of the compounds, to predict their effect on the growth and swarming behavior of the bacterial strains. The results showed an uncertainty in the created model, and that increases in virulence factors, including growth and motility of bacteria, after exposure to the studied compounds are possible to be predicted. These results could be more accurate if the interactions between groups of functions are included. For that, to make an accurate and universal model, it is essential to incorporate a larger number of compounds of similar and different structures. MDPI 2023-05-24 /pmc/articles/PMC10301662/ /pubmed/37374877 http://dx.doi.org/10.3390/microorganisms11061375 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Al Haj Ishak Al Ali, Roukaya
Mondamert, Leslie
Berjeaud, Jean-Marc
Jandry, Joelle
Crépin, Alexandre
Labanowski, Jérôme
Application of QSAR Approach to Assess the Effects of Organic Pollutants on Bacterial Virulence Factors
title Application of QSAR Approach to Assess the Effects of Organic Pollutants on Bacterial Virulence Factors
title_full Application of QSAR Approach to Assess the Effects of Organic Pollutants on Bacterial Virulence Factors
title_fullStr Application of QSAR Approach to Assess the Effects of Organic Pollutants on Bacterial Virulence Factors
title_full_unstemmed Application of QSAR Approach to Assess the Effects of Organic Pollutants on Bacterial Virulence Factors
title_short Application of QSAR Approach to Assess the Effects of Organic Pollutants on Bacterial Virulence Factors
title_sort application of qsar approach to assess the effects of organic pollutants on bacterial virulence factors
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10301662/
https://www.ncbi.nlm.nih.gov/pubmed/37374877
http://dx.doi.org/10.3390/microorganisms11061375
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