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Biology subjects

Arnett, E.

Publications and source records attributed to Arnett, E..

3 recordsLinked to original sources

Timing matters in Macrophage / CD4+ T cell interactions: An agent-based model comparing Mycobacterium tuberculosis host-pathogen interactions between latently infected and naïve individuals

Tuberculosis (TB), caused by Mycobacterium tuberculosis (Mtb), remains a significant health challenge. Clinical manifestations of TB exist across a spectrum with a majority of infected individuals remaining asymptomatic, commonly referred to as latent TB infection (LTBI). In vitro models have demonstrated that cells from individuals with LTBI can better control Mtb growth, and form granuloma-like structures more quickly, compared to cells from uninfected (Mtb-naive) individuals. These in vitro results agree with animal and clinical evidence that LTBI protects, to some degree, against reinfection. However, the mechanisms by which LTBI might offer protection against reinfection remain unclear, and quantifying the relative contributions of multiple control mechanisms is challenging using experimental methods alone. To complement in vitro models, we have developed an in silico agent-based model to help elucidate host responses that might contribute to protection against reinfection. Our simulations indicate that earlier contact between macrophages and CD4+ T cells leads to LTBI simulations having more activated CD4+ T cells and, in turn, more activated infected macrophages which all contribute to decreased bacterial load early on. Our simulations also demonstrate that granuloma-like structures support this early macrophage activation in LTBI simulations. We find that differences between LTBI and Mtb-naive simulations are driven by TNF and IFN{gamma}-associated mechanisms as well as macrophage phagocytosis and killing mechanisms. Together, our simulations show how important the timing of the first interactions between innate and adaptive immune cells is, how this impacts infection progression, and why cells from LTBI individuals might be faster to respond to reinfection. ImportanceTuberculosis (TB) remains a significant global health challenge, with millions of new infections and deaths annually. Despite extensive research, the mechanisms by which latent TB infection (LTBI) confers protection against reinfection remain unclear. In this study, we developed an in silico agent-based model to simulate early immune responses to Mycobacterium tuberculosis (Mtb) infection based on experimental in vitro infection of human donor cells. Our simulations reveal that early interactions between macrophages and CD4+ T cells, driven by TNF and IFN{gamma}, are critical for bacterial control and granuloma formation in LTBI. These findings offer new insights into the immune processes involved in TB, which could inform the development of targeted vaccines and host-directed therapies. By integrating experimental data with computational predictions, our research provides a robust framework for understanding TB immunity and guiding future interventions to mitigate the global TB burden.

immunology↗

A new tractable method for generating Human Alveolar Macrophage Like cells in vitro to study lung inflammatory processes and diseases

Alveolar macrophages (AMs) are unique lung resident cells that contact airborne pathogens and environmental particulates. The contribution of human AMs (HAM) to pulmonary diseases remains poorly understood due to difficulty in accessing them from human donors and their rapid phenotypic change during in vitro culture. Thus, there remains an unmet need for cost-effective methods for generating and/or differentiating primary cells into a HAM phenotype, particularly important for translational and clinical studies. We developed cell culture conditions that mimic the lung alveolar environment in humans using lung lipids, i.e., Infasurf (calfactant, natural bovine surfactant) and lung-associated cytokines (GM-CSF, TGF-{beta}, and IL-10) that facilitate the conversion of blood-obtained monocytes to an AM-Like (AML) phenotype and function in tissue culture. Similar to HAM, AML cells are particularly susceptible to both Mycobacterium tuberculosis and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections. This study reveals the importance of alveolar space components in the development and maintenance of HAM phenotype and function, and provides a readily accessible model to study HAM in infectious and inflammatory disease processes, as well as therapies and vaccines. IMPORTANCEMillions die annually from respiratory disorders. Lower respiratory track gas-exchanging alveoli maintain a precarious balance between fighting invaders and minimizing tissue damage. Key players herein are resident AMs. However, there are no easily accessible in vitro models of HAMs, presenting a huge scientific challenge. Here we present a novel model for generating AML cells based on differentiating blood monocytes in a defined lung component cocktail. This model is non-invasive, significantly less costly than performing a bronchoalveolar lavage, yields more AML cells than HAMs per donor and retains their phenotype in culture. We have applied this model to early studies of M. tuberculosis and SARS-CoV-2. This model will significantly advance respiratory biology research.

immunology↗

Human alveolar macrophage response to Mycobacterium tuberculosis: immune characteristics underlying large inter-individual variability

Mycobacterium tuberculosis (M.tb) establishes residence and growth in human alveolar macrophages (AMs). Large inter-individual variation in M.tb-AM interactions is a potential early indicator of TB risk and efficacy of therapies and vaccines. Herein, we systematically analyze interactions of a virulent M.tb strain with freshly isolated human AMs from 28 healthy adult donors, measuring host RNA expression and secreted candidate proteins associated with TB pathogenesis over 72h. We observe large inter-individual differences in bacterial uptake and growth, with tenfold variation in M.tb load at 72h, reflected by large variation of gene expression programs. Systems analysis of differential and variable RNA and protein expression identifies TB-associated genes and networks (e.g., IL1B and IDO1). RNA time profiles document early stimulation of M1-type macrophage gene expression followed by emergence of an M2-type profile. The fine-scale resolution of this work enables the separation of genes and networks regulating early M.tb growth dynamics, and development of potential markers of individual susceptibility to M.tb infection and response to therapies.

systems biology↗