Immune Determinants of the Course of Mycobacterium tuberculosis infection and Disease

Project 2

P2

Administrative Core
Systems Biology Core
Clinical Core

Scientific Aims

Overview

Between the initial encounter of Mycobacterium tuberculosis (Mtb) with alveolar macrophages (AM) and the development of active disease lies a continuum in which asymptomatic infection may progress to tuberculosis (TB) disease over an extended timeframe. The host response that must evolve as the infection progresses toward disease has not been defined. Equally unclear is the role of Mtb-intrinsic factors in modulating the host response and consequently, the kinetics of the progression of infection to disease. We have characterized a biomarker signature (PREDICT29) that can predict the risks for progression from infection.

Immune Determinants of the Course of Mycobacterium Tuberculosis Infection and Disease

Clinical epidemiological studies identified 2 classes of Mtb based on the capacity of the bacilli from index cases to be transmitted to cause infection in household contacts (HHC): Mtb-HT (high transmission) and Mtb-LT (low transmission). Chest x-ray of Mtb-HT Index Cases displayed an increased frequency of cavitary disease. Analysis of Mtb-HT and Mtb-LT in C3HeB/FeJ mice revealed remarkable differences among the 2 strains in

  1. The responses elicited in AM;
  2. The immunopathological patterns, with lung necrotic lesions only apparent in Mtb-HT infected mice;
  3. The T cell response during the chronic phase of infection; and
  4. The expression of phthiocerol dimycocerosate (PDIM), an Mtb cell envelope lipid.

These characteristics of Mtb-HT and Mtb-LT may thus link Mtb-intrinsic factors to differential regulation of the early innate immune response (the Mtb-AM interaction) that leads to the development of distinct adaptive immunity that in turn, governs the kinetics and frequency with which asymptomatic infection progresses to disease. PREDICT29 (segregates progressors vs nonprogressors), in conjunction with the ACS-COR signature (identifies individuals at a later phase of infection), enables the placement of subjects in our cohorts infected with Mtb-HT and Mtb-LT at the early phase of infection that are progressors or nonprogressors or late phase of infection. A combination of ex vivo cellular systems, singe-cell RNA-seq analysis, hi-dimensional mass cytometry, and Nanostring technology will be employed to characterize the immune response exhibited by these various subgroups.

Scientific Aims

We propose to test the following hypothesis:

1.

Mtb-HT and Mtb-LT elicit differential AM response

2.

Disparate T cell and antibody response in Household Contacts infected with Mtb-HT and Mtb-LT differentially regulate the immunopathology and progression to disease

3.

Memory T cells play a role in regulating infection progression

Immunological analysis of these subgroups comprising Mtb-HT and Mtb-LT infected subjects in specific phase of infection, with a focus on the early Mtb-AM interaction, adaptive T cell and antibody response, will provide a large body of information that will shed light on the mechanisms that regulate infection and disease outcomes in the context of progressors and nonprogressors and Mtb- intrinsic factors.

References

Cross-validation of existing signatures and derivation of a novel 29-gene transcriptomic signature predictive of progression to TB in a Brazilian cohort of household contacts of pulmonary TB
​Leong S, Zhao Y, Ribeiro-Rodrigues R, Jones-López EC, Acuña-Villaorduña C, Rodrigues PM, Palaci M, Alland D, Dietze R, Ellner JJ, Johnson WE, Salgame P. Cross-validation of existing signatures and derivation of a novel 29-gene transcriptomic signature predictive of progression to TB in a Brazilian cohort of household contacts of pulmonary TB. Tuberculosis (Edinb). 2020 Jan;120:101898. doi: 10.1016/j.tube.2020.101898. Epub 2020 Jan 7. PMID: 32090859.

Development and validation of a parsimonious TB gene signature using the digital NanoString nCounter platform
Development and validation of a parsimonious TB gene signature using the digital NanoString nCounter platform. Kaipilyawar V, Zhao Y, Wang X, Joseph NM, Knudsen S, Babu SP, Muthaiah M, Hochberg NS, Sarkar S, Horsburgh CR Jr, Ellner JJ, Johnson WE, Salgame P. Clin Infect Dis. 2022 Jan 7:ciac010. doi: 10.1093/cid/ciac010. Online ahead of print. PMID: 35015839

Early alveolar macrophage response and IL-1R-dependent T cell priming determine transmissibility of Mycobacterium tuberculosis strains
Early alveolar macrophage response and IL-1R-dependent T cell priming determine transmissibility of Mycobacterium tuberculosis strains. Lovey A, Verma S, Kaipilyawar V, Ribeiro-Rodrigues R, Husain S, Palaci M, Dietze R, Ma S, Morrison RD, Sherman DR, Ellner JJ, Salgame P. Nat Commun. 2022 Feb 16;13(1):884. doi: 10.1038/s41467-022-28506-2. PMID: 35173157.