Abstract

Unmasking bacterial defenders: cutting-edge antimicrobial resistance detection innovations

Authors: Muhammad Adil, Qamar Ul Hassan, Adeeba Naseer, Muhammad Shazad Shafiq, Sehrish Gul, Asad Ullah, Farrah Deeba, Ghulam Murtaza, Muhammad Azam Farooq Kasli and Arsalan Said

DOI: http://dx.doi.org/10.71081/cvj/2023.020

Abstract
Antimicrobial resistance (AMR) records a resounding global health alarm, posturing ample challenges to the effectual treatment of bacterial infections. As the predominance of drug-resistant bacteria continues to rise, the improvement and implementation of advanced techniques for AMR detection have become essential. This review offers a broad overview of the up-to-date methodologies employed in the identification and classification of antimicrobial resistance in bacteria. In recent years, genomic approaches have revolutionized AMR detection, allowing for rapid and accurate evaluation of resistance genes and mutations. Whole genome sequencing, coupled with bioinformatics tools, has enabled the chasing of resistance evolution and transmission dynamics. Additionally, transcriptomics and proteomics have explained the underlying mechanisms of AMR, assisting in the development of targeted therapies. Furthermore, advanced phenotypic assays, such as microfluidic systems and mass spectrometry-based techniques, have improved our skill in assessing bacterial susceptibility to antibiotics. The addition of artificial intelligence and machine learning algorithms has simplified data analysis and expectation of resistance profiles with high precision. This review highlights the benefits and restraints of each technique and reflects their potential for clinical and public health applications. The continuing challenges in AMR detection, including the emergence of novel resistance mechanisms and the need for regulation, are also addressed. The review concludes that more accurate, precise, and economical methods are needed to understand the exact situation of resistance to adjust the management strategies accordingly.

Keywords: AMR; resistance; Bacteria; Sensitivity; Antimicrobials