# Understanding in vivo antibiotic resistance in diverse Pseudomonas aeruginosa populations

> **NIH NIH R56** · GEORGIA INSTITUTE OF TECHNOLOGY · 2020 · $508,065

## Abstract

Summary
Cystic fibrosis (CF) is a genetic disease that results in persistent and chronic lung infections
which reduce lung function over time. Pseudomonas aeruginosa (Pa), an opportunistic bacterial
pathogen that infects patients lungs at a young age and persists throughout life, is a major
contributing factor. Aggressive antibiotic regimes have significantly prolonged the lives of CF
patients, yet Pa populations still dominate during end stage lung disease. Why antibiotic
treatments against Pa ultimately fail remains unclear, but one plausible explanation is that Pa
populations in the CF lung gain higher levels of AMR collectively as they become more
phenotypically and genetically diverse over time. Understanding how Pa population
heterogeneity contributes to antimicrobial resistance (AMR), and how Pa population diversity
contributes to the organism’s survival, are important considerations for the future development
of effective diagnostic and treatment strategies. Understanding of in vivo AMR is limited by a
lack of empirical studies focused on how factors such as evolutionary trade-offs and social
interactions between Pa isolates affect heterogeneity and influence AMR. This study will focus
on the impact of intra-species diversity on AMR using a unique set of Pa strain populations
already collected from 50 sputum samples. The main goals are to (i) reveal how the level of
heterogeneity in Pa populations in CF patients determines the extent of AMR; (ii) ascertain
evolutionary factors that leads to AMR heterogeneity; (iii) identify in vivo genomic signatures of
AMR using Genome Wide Association Studies (GWAS). The research described in this project
will provide valuable insights into antimicrobial resistance in chronic CF infection, because it will
introduce novel methodology for antimicrobial susceptibility testing in clinics by taking population
dynamics into account. Outcomes could also lead to new models and platforms for studying the
evolution of virulence and AMR in populations. In the future, the ideas presented here can be
further expanded to include studies on other species important in CF and other polymicrobial
communities.

## Key facts

- **NIH application ID:** 10213951
- **Project number:** 1R56AI153116-01
- **Recipient organization:** GEORGIA INSTITUTE OF TECHNOLOGY
- **Principal Investigator:** Stephen Paul Diggle
- **Activity code:** R56 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $508,065
- **Award type:** 1
- **Project period:** 2020-08-20 → 2021-04-08

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10213951

## Citation

> US National Institutes of Health, RePORTER application 10213951, Understanding in vivo antibiotic resistance in diverse Pseudomonas aeruginosa populations (1R56AI153116-01). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10213951. Licensed CC0.

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