| Aspect | Evolutionary Principle | How Pathogens Use It to Evolve Resistance | Specific Ancestor Example | How Medicine Uses Evolution to Counter Resistance |
|---|
| Mutation | Random genetic change introduces variation | Spontaneous mutations in bacterial genes confer resistance (e.g., rpsL) | Mycobacterium tuberculosis H37Rv (pre-streptomycin) | Screen for naturally occurring bacterial compounds (e.g., streptomycin); use mutagenesis to find weak spots in bacteria |
| Natural Selection | Fitter variants survive and reproduce | Drug-resistant strains survive treatment and dominate | Staphylococcus aureus 8325-4 (pre-penicillin resistance) | Use high-throughput evolution models to simulate resistance and pre-select drugs less likely to fail |
| Variation within Populations | Genetic diversity affects survival outcomes | Resistant subpopulations survive while others die | Mycobacterium tuberculosis wild strains (mixed katG variants) | Tailor combination therapy (e.g., rifampin + isoniazid) to minimize survival of diverse resistant clones |
| Adaptation | Populations evolve to changing environments | Enterococcus faecium evolves vancomycin resistance via vanA genes | E. faecium DO (vancomycin-sensitive) | Develop next-generation antibiotics targeting new pathways (e.g., linezolid targeting protein synthesis) |
| Survival of the Fittest | Most fit reproduce in the new environment | MDR strains outcompete sensitive ones in drug-rich environments | Klebsiella pneumoniae ATCC 13883 | Rotate or cycle antibiotics in hospitals to reduce selective pressure on any one resistance trait |
| Selective Pressure | Environmental conditions shape evolution | Antibiotic overuse selects resistant bacteria | E. coli K-12 (pre-fluoroquinolone resistance) | Use antimicrobial stewardship to reduce unnecessary pressure; limit broad-spectrum drug use |
| Co-evolution | Interacting species evolve in response | Bacteria develop β-lactamases, we develop β-lactamase inhibitors | H. influenzae Rd KW20 (non–β-lactamase producer) | Design inhibitors (e.g., clavulanic acid) based on enzyme evolution structure modeling |
| Evolutionary Arms Race | Ongoing adaptations between rivals | Pathogens modify surface proteins to evade immunity | Bordetella pertussis Tohama I | Continuously update vaccine components (e.g., DTaP formulation changes) to match new variants |
| Genetic Drift / Gene Flow | Random changes & horizontal gene transfer | Resistance genes spread across species (e.g., CTX-M plasmids) | E. coli K-12 & Klebsiella MGH 78578 (pre-ESBL) | Use genomic surveillance to monitor plasmid transmission and inform targeted antibiotic policies |
| Predictive Power of Evolution | Evolutionary models can forecast change | Streptococcus pneumoniae shifts to non-vaccine serotypes | S. pneumoniae D39 (serotype 2) | Predict future mutations and preemptively design mRNA or conjugate vaccines (e.g., PCV13, mRNA COVID-19 updates) |
