Phenotypic and genotypic perspectives on detection methods for bacterial antimicrobial resistance in a One Health context: research progress and prospects
| dc.contributor.author | Yang, Bingbing | |
| dc.contributor.author | Xin, Xiaoqi | |
| dc.contributor.author | Cao, Xiaoqing | |
| dc.contributor.author | Lubanga, Nasifu | |
| dc.contributor.author | Nie, Zhenlin | |
| dc.contributor.author | He, Bangshun | |
| dc.date.accessioned | 2024-11-20T09:17:54Z | |
| dc.date.available | 2024-11-20T09:17:54Z | |
| dc.date.issued | 2024-09-20 | |
| dc.description.abstract | The widespread spread of bacterial antimicrobial resistance (AMR) and multidrug-resistant bacteria poses a significant threat to global public health. Traditional methods for detecting bacterial AMR are simple, reproducible, and intuitive, requiring long time incubation and high labor intensity. To quickly identify and detect bacterial AMR is urgent for clinical treatment to reduce mortality rate, and many new methods and technologies were required to be developed. This review summarizes the current phenotypic and genotypic detection methods for bacterial AMR. Phenotypic detection methods mainly include antimicrobial susceptibility tests, while genotypic detection methods have higher sensitivity and specificity and can detect known or even unknown drug resistance genes. However, most of the current tests are either genotypic or phenotypic and rarely combined. Combining the advantages of phenotypic and genotypic methods, combined with the joint application of multiple rapid detection methods may be the trend for future AMR testing. Driven by rapid diagnostic technology, big data analysis, and artificial intelligence, detection methods of bacterial AMR are expected to constantly develop and innovate. Adopting rational detection methods and scientific data analysis can better address the challenges of bacterial AMR and ensure human health and social well-being. | |
| dc.description.sponsorship | Jiangsu Health Development Research Center (JSHD2022045) and Jiangsu Provincial Medical Key Discipline Cultivation Unit (JSDW202239). | |
| dc.identifier.citation | Yang, B., Xin, X., Cao, X.,Lubanga, N., Nie, Z., & He, B. (2024). Phenotypic and genotypic perspectives on detection methods for bacterial antimicrobial resistance in a One Health context: research progress and prospects. Archives of Microbiology, 206(10), 409. | |
| dc.identifier.issn | 1432-072X | |
| dc.identifier.uri | https://dir.muni.ac.ug/handle/20.500.12260/705 | |
| dc.language.iso | en | |
| dc.publisher | Springer Nature | |
| dc.subject | Antimicrobial resistance | |
| dc.subject | Genotypic detection methods | |
| dc.subject | Phenotypic detection methods | |
| dc.subject | Resistance testing | |
| dc.title | Phenotypic and genotypic perspectives on detection methods for bacterial antimicrobial resistance in a One Health context: research progress and prospects |