# Interrogating complex mycobacterial population structures using single-cell RNA sequencing

> **NIH NIH R21** · WEILL MEDICAL COLL OF CORNELL UNIV · 2024 · $254,250

## Abstract

Project Summary
Tuberculosis (TB) is a leading killer among infectious diseases, and global progress against this pandemic has
been set back by COVID-19. Major difficulties in combating TB are the need for months of multidrug therapy to
ensure a high probability of relapse-free cure, and its ability to survive in the air as infectious aerosols and create
a large pool of infected people. The requirement for prolonged drug treatment is likely due to the minority of
bacteria that are able to survive antibiotics for a long duration, even in the absence of genetically-encoded
resistance. Such bacteria are termed persisters. Similarly, transmission events rely on the subset of bacteria that
are able to survive aerosolization stress until it reaches a new host. While recent strides have been made in
understanding these subpopulations of cells, a way to interrogate their transcriptional states at a single-cell
resolution in a high-throughput, unbiased manner does not exist. This limits understanding of the biology of these
cells over time, and restricts identification of vulnerabilities that could be exploited to shorten TB treatment
duration or reduce transmission. The aim of this proposal is to apply a method of single-cell RNA sequencing
(sc-RNAseq) that allows for simultaneous comparison of the transcriptomes of thousands of cells of
Mycobacterium tuberculosis (Mtb), the causative agent of TB.
Preliminary data demonstrate that the protocol, which relies on in situ reverse transcription and barcoding with
combinatorial indexing, is feasible in Mtb. In this application, the first aim is to test the limitations and
characteristics of the technique in pre-defined mixtures of Mtb containing different plasmids. Over the first year
of the grant, we will evaluate (1) the number of genes detected per cell, (2) the detection threshold of the smallest
predefined subpopulation, and (3) the concordance of the aggregation of the single-cell transcriptome to bulk
transcriptomes. With these parameters defined, the sc-RNAseq will be applied to biologically relevant in vitro
conditions in the second year, including Mtb exposed to the front-line TB drug rifampin (RIF) and Mtb undergoing
desiccation stress, a model of aerosolization. Here, the clusters of subpopulation transcriptomes found by the
method will be compared with orthogonal, observable, and predictable phenotypes including cultivability and RIF
resistance over time. These two aims will validate baseline characteristics of the assay, lay the foundation for
leveraging this method against more complex biological samples in the future, and begin defining the
fundamental biology of Mtb subpopulation behavior in response to stress.

## Key facts

- **NIH application ID:** 10810194
- **Project number:** 1R21AI176355-01A1
- **Recipient organization:** WEILL MEDICAL COLL OF CORNELL UNIV
- **Principal Investigator:** Christopher David Brown
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $254,250
- **Award type:** 1
- **Project period:** 2024-06-01 → 2026-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10810194

## Citation

> US National Institutes of Health, RePORTER application 10810194, Interrogating complex mycobacterial population structures using single-cell RNA sequencing (1R21AI176355-01A1). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10810194. Licensed CC0.

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