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Updated: Sep 10, 2025

Design and Use of a Low Cost, Automated Morbidostat for Adaptive Evolution of Bacteria Under Antibiotic Drug Selection
Published on: September 27, 2016
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.
Abstract:
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.
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.
Related Concept Videos
Development of Antibiotic Resistance
Antibiotic Selection
Operon Model
Modern Molecular Taxonomy
Transduction
Coordination of Gene Expression Processes in Bacteria

