Do chance encounters between heterogeneous cells shape the outcome of tuberculosis infections?

Spatial segregation and aging of metabolic processes underlie phenotypic heterogeneity in mycobacteria

Individual cells within clonal populations of mycobacteria vary in size, growth rate, and antibiotic susceptibility. Heterogeneity is, in part, determined by LamA, a protein found exclusively in mycobacteria. LamA localizes to sites of new cell wall synthesis where it recruits proteins important for polar growth and establishing asymmetry. Here, we report that in addition to this function, LamA interacts with complexes involved in oxidative phosphorylation (OXPHOS) at a subcellular location distinct from cell wall synthesis. Importantly, heterogeneity depends on a unique extension of the mycobacterial ATP synthase, and LamA mediates the coupling between ATP production and cell growth in single cells. Strikingly, as single cells age, concentrations of proteins important for oxidative phosphorylation become less abundant, and older cells rely less on oxidative phosphorylation for growth. Together, our data reveal that central metabolism is spatially organized within a single mycobacterium and varies within a genetically identical population of mycobacteria. Designing therapeutic regimens to account for this heterogeneity may help to treat mycobacterial infections faster and more completely.

Preexisting Heterogeneity of Inducible Nitric Oxide Synthase Expression Drives Differential Growth of Mycobacterium tuberculosis in Macrophages

Mycobacterium tuberculosis infection is initiated by the inhalation and implantation of bacteria in the lung alveoli, where they are phagocytosed by macrophages. Even a single bacterium may be sufficient to initiate infection. Thereafter, the clinical outcome is highly variable between individuals, ranging from sterilization to active disease, for reasons that are not well understood. Here, we show that the rate of intracellular bacterial growth varies markedly between individual macrophages, and this heterogeneity is driven by cell-to-cell variation of inducible nitric oxide synthase (iNOS) activity. At the single-cell level, iNOS expression fluctuates over time, independent of infection or activation with gamma interferon. We conclude that chance encounters between individual bacteria and host cells randomly expressing different levels of an antibacterial gene can determine the outcome of single-cell infections, which may explain why some exposed individuals clear the bacteria while others develop progressive disease. IMPORTANCE In this report, we demonstrate that fluctuations in the expression of antimicrobial genes can define how single host cells control bacterial infections. We show that preexisting cell-to-cell variation in the expression of a single gene, that for inducible nitric oxide synthase, is sufficient to explain why some macrophages kill intracellular M. tuberculosis while others fail to control bacterial replication, possibly leading to disease progression. We introduce the concept that chance encounters between heterogeneous bacteria and host cells can determine the outcome of a host-pathogen interaction. This concept is particularly relevant for all the infectious diseases in which the number of interacting pathogens and host cells is small at some point during the infection.

High-resolution imaging of protein secretion at the single-cell level using plasmon-enhanced FluoroDOT assay

Secreted proteins mediate essential physiological processes. With conventional assays, it is challenging to map the spatial distribution of proteins secreted by single cells, to study cell-to-cell heterogeneity in secretion, or to detect proteins of low abundance or incipient secretion. Here, we introduce the "FluoroDOT assay," which uses an ultrabright nanoparticle plasmonic-fluor that enables high-resolution imaging of protein secretion. We find that plasmonic-fluors are 16,000-fold brighter, with nearly 30-fold higher signal-to-noise compared with conventional fluorescence labels. We demonstrate high-resolution imaging of different secreted cytokines in the single-plexed and spectrally multiplexed FluoroDOT assay that revealed cellular heterogeneity in secretion of multiple proteins simultaneously. Using diverse biochemical stimuli, including Mycobacterium tuberculosis infection, and a variety of immune cells such as macrophages, dendritic cells (DCs), and DC-T cell co-culture, we demonstrate that the assay is versatile, facile, and widely adaptable for enhancing biological understanding of spatial and temporal dynamics of single-cell secretome.

Microfluidics as a Novel Technique for Tuberculosis: From Diagnostics to Drug Discovery

Tuberculosis (TB) remains a global healthcare crisis, with an estimated 5.8 million new cases and 1.5 million deaths in 2020. TB is caused by infection with the major human pathogen Mycobacterium tuberculosis, which is difficult to rapidly diagnose and treat. There is an urgent need for new methods of diagnosis, sufficient in vitro models that capably mimic all physiological conditions of the infection, and high-throughput drug screening platforms. Microfluidic-based techniques provide single-cell analysis which reduces experimental time and the cost of reagents, and have been extremely useful for gaining insight into monitoring microorganisms. This review outlines the field of microfluidics and discusses the use of this novel technique so far in M. tuberculosis diagnostics, research methods, and drug discovery platforms. The practices of microfluidics have promising future applications for diagnosing and treating TB.