Perspective on integrated multi-omics approaches and constraint-based modeling to explore metabolic functionality on

Manish Kumar1, Krishna Kumar Ballamoole2, Veena A Shetty3

  • 1Center for Bioinformatics and Biostatistics, Nitte (Deemed to be University), Mangalore, 575018, Karnataka, India; Central Research Laboratory, KS Hegde Medical Academy, Nitte (Deemed to be University), Mangalore, 575018, Karnataka, India.

Microbial Pathogenesis
|August 23, 2025
PubMed

Insights

Antimicrobial resistance (AMR) is a major global threat driven by antibiotic overuse. Understanding bacterial adaptation through evolutionary perspectives and omics data is key to developing new strategies against resistant infections.

Area of Science:

  • Microbiology
  • Evolutionary Biology
  • Computational Biology

Background:

  • Antimicrobial resistance (AMR) poses a significant global health threat, exacerbated by antibiotic overuse in humans and animals.
  • AMR arises from bacterial genetic mutations or horizontal gene transfer, leading to increased mortality and treatment challenges.
  • Understanding the mechanisms of AMR is crucial for developing effective countermeasures.

Purpose of the Study:

  • To analyze the relationship between bacterial mutational changes and antimicrobial resistance using evolutionary perspectives.
  • To explore how omics approaches and constraint-based modeling can elucidate AMR mechanisms.
  • To identify novel strategies for combating antimicrobial resistance.

Main Methods:

  • Utilized evolutionary trade-offs and constraint-based modeling to study AMR.
  • Applied the concept of the
  • adaptive landscape
  • to explain microbial trait development.
  • Employed omics approaches (genomics, etc.) for multi-dimensional data analysis.

Main Results:

  • Constraint-based modeling and genome resequencing reveal condition-dependent resistance and strain weaknesses.
  • Bacterial metabolic plasticity under antibiotic pressure offers insights into resistance development.
  • Omics data provide a deeper understanding of bacterial adaptation factors and AMR trends.

Conclusions:

  • Multiple omics approaches are vital for understanding bacterial resistance mechanisms.
  • Constraint-based modeling aids in identifying vulnerabilities of resistant strains.
  • Developing novel therapeutic strategies requires a comprehensive understanding of bacterial adaptation and resistance.

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