High Burden of Multidrug-Resistant Bacteria Detected in Different Water Sources Can Direct the Spread of Antibiotic Resistance Genes in the Environment
{"title":"High Burden of Multidrug-Resistant Bacteria Detected in Different Water Sources Can Direct the Spread of Antibiotic Resistance Genes in the Environment","authors":"H. Hashmi, Nazia Jamil","doi":"10.53560/ppasb(60-sp1)783","DOIUrl":null,"url":null,"abstract":"Antibiotic-resistant bacterial infections are of global concern nowadays. Environmental sources like water and soil are playing a key role in spreading antibiotic-resistance genes to humans, animals, and other environments. Objective: The purpose of this study was to identify and report the presence of multidrug-resistant bacteria (MDRs) in environmental water sources that can direct the spread of resistant genes to other bacteria/environments. Methodology: Environmental water samples were collected from 2 livestock farms and a fish pond. Bacterial isolation and identification were carried out by following Burgey’s manual of systematic bacteriology. Antibiotic susceptibility testing was done using the disk diffusion method and CLSI guidelines. Multiple antibiotic-resistant indexes were calculated. Whole genome sequences of previously reported bacteria were downloaded from NCBI to detect the resistance genes associated with phenotypic drug resistance and compared using the bioinformatics approach. Results: Microbial load was significantly high in all water sources. Following Genera were the most common: Klebsiella, Escherichia, Proteus, Serratia, Acinetobacter, Enterobacter, Pseudomonas, Bacillus, Lactobacillus, and Staphylococcus. Out of 10 classes of antibiotics, resistance against 8 classes were identified. Multiple Antibiotic Resistance (MAR) index range of isolated strains was between 0.4 and 0.9. Key Findings: Resistance against beta-lactam antibiotics was highest in our isolated strains with a MAR index of greater than 0.4 altogether. Conclusion: High burden of multidrug-resistant bacteria were detected in all water samples which can trigger the silent pandemic of antibacterial resistance.","PeriodicalId":36960,"journal":{"name":"Proceedings of the Pakistan Academy of Sciences: Part B","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2023-01-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Pakistan Academy of Sciences: Part B","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.53560/ppasb(60-sp1)783","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Agricultural and Biological Sciences","Score":null,"Total":0}
引用次数: 1
Abstract
Antibiotic-resistant bacterial infections are of global concern nowadays. Environmental sources like water and soil are playing a key role in spreading antibiotic-resistance genes to humans, animals, and other environments. Objective: The purpose of this study was to identify and report the presence of multidrug-resistant bacteria (MDRs) in environmental water sources that can direct the spread of resistant genes to other bacteria/environments. Methodology: Environmental water samples were collected from 2 livestock farms and a fish pond. Bacterial isolation and identification were carried out by following Burgey’s manual of systematic bacteriology. Antibiotic susceptibility testing was done using the disk diffusion method and CLSI guidelines. Multiple antibiotic-resistant indexes were calculated. Whole genome sequences of previously reported bacteria were downloaded from NCBI to detect the resistance genes associated with phenotypic drug resistance and compared using the bioinformatics approach. Results: Microbial load was significantly high in all water sources. Following Genera were the most common: Klebsiella, Escherichia, Proteus, Serratia, Acinetobacter, Enterobacter, Pseudomonas, Bacillus, Lactobacillus, and Staphylococcus. Out of 10 classes of antibiotics, resistance against 8 classes were identified. Multiple Antibiotic Resistance (MAR) index range of isolated strains was between 0.4 and 0.9. Key Findings: Resistance against beta-lactam antibiotics was highest in our isolated strains with a MAR index of greater than 0.4 altogether. Conclusion: High burden of multidrug-resistant bacteria were detected in all water samples which can trigger the silent pandemic of antibacterial resistance.