Perspective on integrated multi-omics approaches and constraint-based modeling to explore metabolic functionality on the evolution of bacterial antibiotic resistance.

Antimicrobial resistance (AMR) is one of the greatest threats to humanity globally as it has been escalated by the over-prescription and usage of antibiotics for both humans and animals. AMR occurs when the bacteria develop a way of resisting the antimicrobial compounds, thus leading to increased mortality rates, health expenses, and issues of handling infections. The development of AMR occurs through mutations of bacterial genes or through horizontal gene transfer that results in increased minimum inhibitory concentration and bacterial tolerance. Perspectives from evolutionary trade-offs and constraint-based modeling were used to analyze the relationship between mutational changes and antimicrobial resistance. The idea of "adaptive landscape" helps in explaining how microbial traits develop based on selective forces, and the "dimensionality of phenotypic states" looks at how resistance occurs in various biological systems. The omics approaches give multi-dimensional data to focus further on bacterial adaptation factors and explore future antimicrobial resistance trends. Information on condition-dependent resistance and the weakness of the resistant strains is obtained when involving constraint-based modeling and resequencing of the genome. It also involves bacterial metabolic plasticity under antibiotic pressure and provides fresh approaches to combat antimicrobial resistance. This perspective emphasizes the importance of new strategies highlighting the availability of multiple omics approaches to understand the bacterial resistance mechanisms and construct early therapeutic approaches.