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Published on: February 23, 2014
Unravelling Antimicrobial Resistance in Mycoplasma hyopneumoniae: Genetic Mechanisms and Future Directions
Raziallah Jafari Jozani1, Mauida F Hasoon Al Khallawi1, Darren Trott1
1Australian Centre for Antimicrobial Resistance Ecology, Faculty of Sciences, Engineering and Technology, School of Animal and Veterinary Science, The University of Adelaide, Adelaide, SA 5005, Australia.
Abstract:
Antimicrobial resistance (AMR) in Mycoplasma hyopneumoniae, the causative agent of Enzootic Pneumonia in swine, poses a significant challenge to the swine industry. This review focuses on the genetic foundations of AMR in M. hyopneumoniae, highlighting the complexity of resistance mechanisms, including mutations, horizontal gene transfer, and adaptive evolutionary processes. Techniques such as Whole Genome Sequencing (WGS) and multiple-locus variable number tandem repeats analysis (MLVA) have provided insights into the genetic diversity and resistance mechanisms of M. hyopneumoniae. The study underscores the role of selective pressures from antimicrobial use in driving genomic variations that enhance resistance. Additionally, bioinformatic tools utilizing machine learning algorithms, such as CARD and PATRIC, can predict resistance traits, with PATRIC predicting 7 to 12 AMR genes and CARD predicting 0 to 3 AMR genes in 24 whole genome sequences available on NCBI. The review advocates for a multidisciplinary approach integrating genomic, phenotypic, and bioinformatics data to combat AMR effectively. It also elaborates on the need for refining genotyping methods, enhancing resistance prediction accuracy, and developing standardized antimicrobial susceptibility testing procedures specific to M. hyopneumoniae as a fastidious microorganism. By leveraging contemporary genomic technologies and bioinformatics resources, the scientific community can better manage AMR in M. hyopneumoniae, ultimately safeguarding animal health and agricultural productivity. This comprehensive understanding of AMR mechanisms will be beneficial in the adaptation of more effective treatment and management strategies for Enzootic Pneumonia in swine.
Insights
Antimicrobial resistance in Mycoplasma hyopneumoniae is driven by genetic factors like mutations and gene transfer. Understanding these mechanisms is key to managing swine enzootic pneumonia and improving animal health.
Area of Science:
- Veterinary Microbiology
- Genomics
- Bioinformatics
Background:
- Antimicrobial resistance (AMR) in Mycoplasma hyopneumoniae, a major swine pathogen, presents a significant economic challenge.
- Genetic factors, including mutations and horizontal gene transfer, underpin AMR in this bacterium.
Purpose of the Study:
- To review the genetic basis of AMR in M. hyopneumoniae.
- To explore advanced techniques for understanding and predicting AMR in swine pathogens.
Main Methods:
- Whole Genome Sequencing (WGS) and Multiple-Locus Variable Number Tandem Repeats analysis (MLVA) were used to study genetic diversity.
- Bioinformatic tools like CARD and PATRIC, employing machine learning, were utilized for AMR gene prediction.
Main Results:
- Selective antimicrobial use drives genomic variations contributing to resistance.
- PATRIC and CARD tools show varying capacities in predicting AMR genes in M. hyopneumoniae.
- Genomic and bioinformatic approaches reveal complex resistance mechanisms.
Conclusions:
- A multidisciplinary approach integrating genomic, phenotypic, and bioinformatics data is essential for effective AMR management.
- Refining genotyping, improving resistance prediction, and standardizing susceptibility testing for M. hyopneumoniae are crucial.
- Leveraging genomic technologies and bioinformatics can enhance strategies against swine enzootic pneumonia.
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