Single-cell analysis reveals a weak macrophage subpopulation response to Mycobacterium tuberculosis infection.

Mycobacterium tuberculosis (Mtb) infection remains one of society's greatest human health challenges. Macrophages integrate multiple signals derived from ontogeny, infection, and the environment. This integration proceeds heterogeneously during infection. Some macrophages are infected, while others are not; therefore, bulk approaches mask the subpopulation dynamics. We establish a modular, targeted, single-cell protein analysis framework to study the immune response to Mtb. We demonstrate that during Mtb infection, only a small fraction of resting macrophages produce tumor necrosis factor (TNF) protein. We demonstrate that Mtb infection results in muted phosphorylation of p38 and JNK, regulators of inflammation, and leverage our single-cell methods to distinguish between pathogen-mediated interference in host signaling and weak activation of host pathways. We demonstrate that the inflammatory signal magnitude is decoupled from the ability to control Mtb growth. These data underscore the importance of developing pathogen-specific models of signaling and highlight barriers to activation of pathways that control inflammation.

TLR2 is non-redundant in the population and subpopulation responses to Mycobacterium tuberculosis in macrophages and in vivo.

Tuberculosis (TB), caused by the pathogenic bacterium Mycobacterium tuberculosis (Mtb), is a global health threat. Targeting host pathways that modulate protective or harmful components of inflammation has been proposed as a therapeutic strategy that could aid sterilization or mitigate TB-associated permanent tissue damage. In purified form, many Mtb components can activate innate immune pathways. However, knowledge of the pathways that contribute most to the observed response to live Mtb is incomplete, limiting the possibility of precise intervention. We took a systematic, unbiased approach to define the pathways that drive the earliest immune response to Mtb. Using a macrophage model of infection, we compared the bulk transcriptional response to infection with the response to a panel of Mtb-derived putative innate immune ligands. We identified two axes of response: an NF-kB-dependent response similarly elicited by all Mtb pathogen-associated molecular patterns (PAMPs) and a type I interferon axis unique to cells infected with live Mtb. Consistent with growing literature data pointing to TLR2 as a dominant Mtb-associated PAMP, the TLR2 ligand PIM6 most closely approximated the NF-kB-dependent response to the intact bacterium. Quantitatively, the macrophage response to Mtb was slower and weaker than the response to purified PIM6. On a subpopulation level, the TLR2-dependent response was heterogeneously induced, with only a subset of infected cells expressing key inflammatory genes known to contribute to the control of infection. Despite potential redundancies in Mtb ligand/innate immune receptor interactions during in vivo infection, loss of the TLR2/PIM6 interaction impacted the cellular composition of both the innate and adaptive compartments. IMPORTANCE Tuberculosis (TB) is a leading cause of death globally. Drug resistance is outpacing new antibiotic discovery, and even after successful treatment, individuals are often left with permanent lung damage from the negative consequences of inflammation. Targeting host inflammatory pathways has been proposed as an approach that could either improve sterilization or improve post-treatment lung health. However, our understanding of the inflammatory pathways triggered by Mycobacterium tuberculosis (Mtb) in infected cells and lungs is incomplete, in part because of the complex array of potential molecular interactions between bacterium and host. Here, we take an unbiased approach to identify the pathways most central to the host response to Mtb. We examine how individual pathways are triggered differently by purified Mtb products or infection with the live bacterium and consider how these pathways inform the emergence of subpopulation responses in cell culture and in infected mice. Understanding how individual interactions and immune pathways contribute to inflammation in TB opens the door to the possibility of developing precise therapeutic interventions.

Flow Cytometry Analysis of Mycobacteria and Mycobacteria-Infected Immune Cells.

Flow cytometry enables the measurement of tens of features on individual cells from complex mixtures. Flow cytometry enables high-throughput quantification of cell size, gene and protein expression. In the case of studies of host-pathogen interactions, this tool provides a facile way of identifying cells that have been successfully infected by a pathogen. Several recent technological advances have greatly improved throughput and the number of features that can be simultaneously monitored by this technique. Here, we describe common workflows to study Mycobacterium tuberculosis heterogeneity and host-M. tuberculosis interactions using flow cytometry and related technologies.

Uncovering complex molecular networks in host-pathogen interactions using systems biology.

Interactions between pathogens and their hosts can induce complex changes in both host and pathogen states to privilege pathogen survival or host clearance of the pathogen. To determine the consequences of specific host-pathogen interactions, a variety of techniques in microbiology, cell biology, and immunology are available to researchers. Systems biology that enables unbiased measurements of transcriptomes, proteomes, and other biomolecules has become increasingly common in the study of host-pathogen interactions. These approaches can be used to generate novel hypotheses or to characterize the effects of particular perturbations across an entire biomolecular network. With proper experimental design and complementary data analysis tools, high-throughput omics techniques can provide novel insights into the mechanisms that underlie processes from phagocytosis to pathogen immune evasion. Here, we provide an overview of the suite of biochemical approaches for high-throughput analyses of host-pathogen interactions, analytical frameworks for understanding the resulting datasets, and a vision for the future of this exciting field.