# Parallel phenotyping to dissect genetic determinants of bacterial strain diversity

> **NIH NIH DP2** · UTAH STATE HIGHER EDUCATION SYSTEM--UNIVERSITY OF UTAH · 2024 · $73,911

## Abstract

PROJECT SUMMARY
All pathogens possess genetic diversity that can impact clinically relevant phenotypes such as virulence,
susceptibility to drugs, and vaccine efficacy. In the post-genomic era, our ability to catalog microbial genotypes
has far outstripped our capacity to profile microbial phenotypes. This limits our ability to build genotype-
phenotype maps for traits of interest and hinders the development of broadly effective new antimicrobials,
vaccines, and public health interventions. To address this challenge, I developed a molecular barcoding
approach that permits parallel fitness phenotyping of hundreds of bacterial clinical isolates in a single in vitro or
in vivo experiment. I developed and validated this novel approach in the pathogen Mycobacterium tuberculosis
and uncovered strain-specific differences in bacterial fitness during infection and following vaccination in the
mouse model. Here, I propose to use this novel tool to interrogate the genetic basis of phenotypic
heterogeneity in a related mycobacterial pathogen, Mycobacterium avium (MAC). MAC is an environmental
microbe that can cause chronic and treatment-recalcitrant infections and is increasing in incidence. A major
challenge in the management of MAC disease is the variability in disease course and treatment outcome, and
the bacterial determinants of this variability are unknown. Here, I will leverage my strain barcoding approach
and the natural biodiversity of this microbe to elucidate genetic determinants and molecular mechanisms of
MAC pathogenicity and antibiotic response. These efforts will inform the development of improved diagnostics
and therapeutics for this, and other, chronic bacterial infections. More broadly, this work will provide an
intellectual framework and experimental toolkit to uncover the biological basis of heterogeneity in infectious
disease phenotypes.

## Key facts

- **NIH application ID:** 11049320
- **Project number:** 3DP2AI171122-03S1
- **Recipient organization:** UTAH STATE HIGHER EDUCATION SYSTEM--UNIVERSITY OF UTAH
- **Principal Investigator:** Allison Carey
- **Activity code:** DP2 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $73,911
- **Award type:** 3
- **Project period:** 2022-08-09 → 2025-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/11049320

## Citation

> US National Institutes of Health, RePORTER application 11049320, Parallel phenotyping to dissect genetic determinants of bacterial strain diversity (3DP2AI171122-03S1). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/11049320. Licensed CC0.

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