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Evaluation and Optimization of Antibiotics Resistance Profile against Clostridium perfringens from Buffalo and Cattle in Pakistan

Clostridium perfringens is a serious threat to successful bovine farming. It causes severe damage to the buffalo and cattle health causing a drastic reduction in milk and meat production. In Pakistan, C. perfringens is a constant threat, and for its management, antibiotics are mostly used. Most bovi...

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Autores principales: Khan, Muhammad Umar Zafar, Humza, Muhammad, Yang, Shunli, Iqbal, Muhammad Zahid, Xu, Xiao, Cai, Jianping
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7827476/
https://www.ncbi.nlm.nih.gov/pubmed/33435636
http://dx.doi.org/10.3390/antibiotics10010059
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author Khan, Muhammad Umar Zafar
Humza, Muhammad
Yang, Shunli
Iqbal, Muhammad Zahid
Xu, Xiao
Cai, Jianping
author_facet Khan, Muhammad Umar Zafar
Humza, Muhammad
Yang, Shunli
Iqbal, Muhammad Zahid
Xu, Xiao
Cai, Jianping
author_sort Khan, Muhammad Umar Zafar
collection PubMed
description Clostridium perfringens is a serious threat to successful bovine farming. It causes severe damage to the buffalo and cattle health causing a drastic reduction in milk and meat production. In Pakistan, C. perfringens is a constant threat, and for its management, antibiotics are mostly used. Most bovine farmers use a single antibiotic to suppress the bacterial infection which in turn, increases the antimicrobial resistance (AMR) against the particular antibiotic. To reduce the resistance, the administration of multiple antibiotics in their standard doses at different times can be a possible remedy to manage the AMR and reduce their viability. This study aims to evaluate the effect of 11 commonly used antibiotics at their standard concentrations for inhibiting 33 strains of C. perfringens from five districts of Punjab province in Pakistan. Based on the zone of inhibition, ciprofloxacin, ampicillin, and cefotaxime (CAC) at their standard concentrations effectively inhibited the bacterium. These antibiotics showed appropriate significance statistically, i.e., correlation, Chi-square test, and cluster analysis. Optimization of these antibiotics using response surface methodology (RSM) revealed that the selected antibiotics from medium to high range not only reduce the bacterial propagation but also their population up to a considerable extent. Hence, the health of milk- and meat-producing large animals could be improved, which will be cost-effective and less harmful to the animal, human health, and the environment. Moreover, optimized administration of the selected antibiotics would reduce the impact of drug-resistant superbugs.
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spelling pubmed-78274762021-01-25 Evaluation and Optimization of Antibiotics Resistance Profile against Clostridium perfringens from Buffalo and Cattle in Pakistan Khan, Muhammad Umar Zafar Humza, Muhammad Yang, Shunli Iqbal, Muhammad Zahid Xu, Xiao Cai, Jianping Antibiotics (Basel) Article Clostridium perfringens is a serious threat to successful bovine farming. It causes severe damage to the buffalo and cattle health causing a drastic reduction in milk and meat production. In Pakistan, C. perfringens is a constant threat, and for its management, antibiotics are mostly used. Most bovine farmers use a single antibiotic to suppress the bacterial infection which in turn, increases the antimicrobial resistance (AMR) against the particular antibiotic. To reduce the resistance, the administration of multiple antibiotics in their standard doses at different times can be a possible remedy to manage the AMR and reduce their viability. This study aims to evaluate the effect of 11 commonly used antibiotics at their standard concentrations for inhibiting 33 strains of C. perfringens from five districts of Punjab province in Pakistan. Based on the zone of inhibition, ciprofloxacin, ampicillin, and cefotaxime (CAC) at their standard concentrations effectively inhibited the bacterium. These antibiotics showed appropriate significance statistically, i.e., correlation, Chi-square test, and cluster analysis. Optimization of these antibiotics using response surface methodology (RSM) revealed that the selected antibiotics from medium to high range not only reduce the bacterial propagation but also their population up to a considerable extent. Hence, the health of milk- and meat-producing large animals could be improved, which will be cost-effective and less harmful to the animal, human health, and the environment. Moreover, optimized administration of the selected antibiotics would reduce the impact of drug-resistant superbugs. MDPI 2021-01-08 /pmc/articles/PMC7827476/ /pubmed/33435636 http://dx.doi.org/10.3390/antibiotics10010059 Text en © 2021 by the authors. 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 (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Khan, Muhammad Umar Zafar
Humza, Muhammad
Yang, Shunli
Iqbal, Muhammad Zahid
Xu, Xiao
Cai, Jianping
Evaluation and Optimization of Antibiotics Resistance Profile against Clostridium perfringens from Buffalo and Cattle in Pakistan
title Evaluation and Optimization of Antibiotics Resistance Profile against Clostridium perfringens from Buffalo and Cattle in Pakistan
title_full Evaluation and Optimization of Antibiotics Resistance Profile against Clostridium perfringens from Buffalo and Cattle in Pakistan
title_fullStr Evaluation and Optimization of Antibiotics Resistance Profile against Clostridium perfringens from Buffalo and Cattle in Pakistan
title_full_unstemmed Evaluation and Optimization of Antibiotics Resistance Profile against Clostridium perfringens from Buffalo and Cattle in Pakistan
title_short Evaluation and Optimization of Antibiotics Resistance Profile against Clostridium perfringens from Buffalo and Cattle in Pakistan
title_sort evaluation and optimization of antibiotics resistance profile against clostridium perfringens from buffalo and cattle in pakistan
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7827476/
https://www.ncbi.nlm.nih.gov/pubmed/33435636
http://dx.doi.org/10.3390/antibiotics10010059
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