# Metabolic adaptions of Mycobacterium tuberculosis at diverse host-pathogen interfaces

> **NIH NIH U19** · BRIGHAM AND WOMEN'S HOSPITAL · 2022 · $543,819

## Abstract

Metabolic adaptions of Mycobacterium tuberculosis at diverse host-pathogen interfaces
ABSTRACT
Defining the mechanisms through which Mycobacterium tuberculosis (Mtb) metabolites impact human
tuberculosis (TB) disease, diagnostics and treatment will require the implementation of model animal systems
that are both tractable and faithfully replicate the TB disease states observed in humans. To overcome the
limited genetic and phenotypic diversity shown in standard C57BL/6J, here we propose to leverage the
comprehensive panel of Collaborative Cross (CC) mice, a genetically diverse panel of recombinant inbred
mice. We have previously shown that the CC encompasses a broad spectrum of TB disease traits and
infection microenvironments, exceeding the phenotypic spectrum observed in classical inbred strains. Based
on previous TnSeq studies and as part of the parent TBRU grant (“Metabolic determinants of Mtb virulence,
vulnerability and variation”; 1U19AI162584-02), we have ranked Mtb metabolic genes that were linked to Mtb
virulence or control lipid variation in Mtb strains that infect humans. Of 19 high value Mtb metabolic genes
identified, only one controlled growth in the conventional C57BL/6J (BL6) mouse strain. However, more than
half the mutants studied showed in vivo growth phenotypes when screened across CC mouse strains. Further,
through study of several of the CC host genetic backgrounds in which individual bacterial genes do or do not
control in vivo Mtb survival, we are able to start to define the host factors in control of Mtb response. The
current application will now extend these studies to focus on a targeted bacterial lipid library of CRISPRi
mutants in conjunction with the comprehensive panel of CC mice. By infecting 60 distinct CC genotypes with
the targeted lipid CRISPRi library, the metabolic vulnerabilities of Mtb will be comprehensively defined in
genetically diverse hosts. By using bacterial mutant abundance as a phenotypic trait, we will conduct
quantitative trait loci (QTL) mapping across the CC panel to identify the host loci underlying the lipid
requirements of Mtb infection. Altogether these dual host and pathogen approaches will identify the host-Mtb
lipid interactions that can be targeted for tuberculosis treatment.

## Key facts

- **NIH application ID:** 10630740
- **Project number:** 3U19AI162584-02S1
- **Recipient organization:** BRIGHAM AND WOMEN'S HOSPITAL
- **Principal Investigator:** DAVID Branch MOODY
- **Activity code:** U19 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $543,819
- **Award type:** 3
- **Project period:** 2021-07-01 → 2026-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10630740

## Citation

> US National Institutes of Health, RePORTER application 10630740, Metabolic adaptions of Mycobacterium tuberculosis at diverse host-pathogen interfaces (3U19AI162584-02S1). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10630740. Licensed CC0.

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