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Is it possible to identify genotypes underlying resistant phenotypes in Gram-negative pathogens?

Almudena Burillo1,2,3, Julia Serrano-Lobo1,3, Emilio Bouza1,2,3,4

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Linking pathogen genotypes to resistant phenotypes is complex. Integrating phenotypic and genotypic data offers the best strategy for accurate antimicrobial resistance diagnostics.

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Area of Science:

  • Microbiology
  • Genetics
  • Clinical Diagnostics

Background:

  • Antimicrobial resistance (AMR) in Gram-negative pathogens is a growing global health threat.
  • Understanding the genotype-phenotype relationship is crucial for effective treatment and surveillance.
  • Current diagnostic methods have limitations in predicting resistance mechanisms.

Purpose of the Study:

  • To review the relationship between genotypes and resistant phenotypes in Gram-negative pathogens.
  • To assess the predictive accuracy of phenotypic methods for genetic resistance mechanisms.
  • To evaluate genotypic approaches and integrated strategies for improving diagnostic utility.

Main Methods:

  • Review of current literature on genotypic and phenotypic antimicrobial susceptibility testing (AST).
  • Analysis of molecular methods including PCR, microarrays, sequencing, and whole-genome sequencing.
  • Exploration of emerging technologies like real-time sequencing, metagenomics, and machine learning.

Main Results:

  • Phenotypic AST correlates with therapeutic outcomes but often misses underlying genetic resistance.
  • Genotypic methods rapidly detect known resistance genes but struggle with expression and functionality prediction.
  • Whole-genome sequencing offers comprehensive insights but genotype-phenotype discordance persists due to various biological factors.
  • Emerging technologies show promise but require standardization and clinical validation.

Conclusions:

  • Integrating phenotypic and genotypic data is essential for mechanism-informed AMR diagnostics.
  • Artificial intelligence and curated databases can enhance diagnostic accuracy.
  • Clinical validation and harmonized interpretative frameworks are necessary for widespread adoption.
  • Combined approaches are key to actionable diagnostics for managing antimicrobial resistance.