# Deep spatial immune profiling of granulomas and M. tuberculosis adaptation to disease and treatment

> **NIH NIH R01** · EMORY UNIVERSITY · 2024 · $36,083

## Abstract

PROJECT SUMMARY
Granulomas are hallmark pathological features of pulmonary tuberculosis (TB) and contribute to both
containment of Mycobacterium tuberculosis (Mtb) infection and progression to TB disease. However, we do not
understand how the geospatial organization of immune cells and their communication networks impact the host
immune functions that render a granuloma functionally permissive versus restrictive to Mtb. Stresses
encountered by Mtb during infection induce bacterial adaptations that promote Mtb survival and drug tolerance,
but we know little about the bacterial growth and metabolic changes induced within different granuloma
microenvironments during disease or treatment and how the geospatial organization and immune state of the
granuloma impacts bacterial physiology and killing. To understand how cellular networks and granuloma spatial
architecture determine the functional capacities of major granuloma types, we propose to develop a TB
Granuloma Information System (TB-GIS) that will generate a geospatial map for individual granulomas and layer
on additional data related to immunometabolic and antimicrobial functions, as well as Mtb physiology and
adaptation. To characterize granuloma topology, we have exploited and optimized a novel high-plex imaging
modality, t-CyCIF (tissue Cyclic Immunofluorescence), which allows for deep geospatial immune profiling of
tissue (30+ markers). We will leverage our well-established nonhuman primate (NHP) model of aerogenic Mtb
infection which recapitulates the spectrum of human lung pathological lesions and integrate additional cutting-
edge tools and computational modeling to probe the host-pathogen interface in different TB granulomas (Aim 1).
We will also determine how perturbing granuloma topology with host- or pathogen-directed therapies impacts
immune function and Mtb metabolic state (Aim 2). Using the TB-GIS framework, we will quantify the relationship
between specific granuloma features and cellular networks, immune function and Mtb physiology in treated and
untreated animals. We anticipate that these TB-GIS studies will transform our ability to predict granuloma
function and help design new therapies to target granulomas harboring drug-tolerant bacteria that are difficult to
clear with current treatment regimens.

## Key facts

- **NIH application ID:** 11099303
- **Project number:** 3R01AI166305-03S1
- **Recipient organization:** EMORY UNIVERSITY
- **Principal Investigator:** Bree Beardsley Aldridge
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $36,083
- **Award type:** 3
- **Project period:** 2021-12-01 → 2026-11-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/11099303

## Citation

> US National Institutes of Health, RePORTER application 11099303, Deep spatial immune profiling of granulomas and M. tuberculosis adaptation to disease and treatment (3R01AI166305-03S1). Retrieved via AI Analytics 2026-05-21 from https://api.ai-analytics.org/grant/nih/11099303. Licensed CC0.

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