Antimicrobial resistance (AMR) is a major health concern worldwide. A better understanding of the underlying molecular mechanisms is needed. Advances in whole genome sequencing and other high-throughput unbiased instrumental technologies to study the molecular pathogenicity of infectious diseases enable the accumulation of large amounts of data that are amenable to bioinformatic analysis and the discovery of new signatures of AMR. In this work, we review representative methods published in the past five years to define major approaches developed to-date in the understanding of AMR mechanisms. Advantages and limitations for applications of these methods in clinical laboratory testing and basic research are discussed.

Antimicrobial resistance (AMR) contributes to antibiotic (AB) treatment failure and increasing rates of mortality in various infectious diseases. Misuse of specific AB and overuse of broad spectrum AB are attributed to the emergence of AMR, which in some strains results in multidrug resistance (MDR). As MDR organisms become more common in clinical settings, fast and accurate assessment of antibiotic susceptibility is needed to start effective treatment as soon as possible .However, not all molecular mechanisms underlying AMR are uncovered or understood yet, especially in Gram-negative bacteria. This means that currently the most reliable way for evaluating resistance to AB in clinical microbiology laboratories is to grow organisms in culture, expose them to various antibiotic concentrations, and assess the impact on growth. 

This approach can range from a day to several weeks, depending on the growth rate of the pathogen. Some species do not even grow in known culture media. This relatively time consuming process is not in line with current clinical demands on fast decision-making, and thus alternative methods for AMR evaluation based on underlying genetic and molecular information have been the shift in focus.Decades of research into various molecular mechanisms of AMR have revealed scores of antibiotic resistance genes (ARG), or bacterial gene variants associated with phenotypical resistance to AB. An example is the NCBI Bacterial Antimicrobial Resistance Reference Gene Database (NCBI Accession ID: PRJNA313047). Resistance can develop in many ways, depending on the target.

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Lucy Morgan
Editorial Coordinator
Journal of Molecular Sciences
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