A virtual host model of Mycobacterium tuberculosis infection identifies early immune events as predictive of infection outcomes

Joslyn, Louis R.; Linderman, Jennifer J.; Kirschner, Denise E.

doi:10.1016/j.jtbi.2022.111042

Title: A virtual host model of Mycobacterium tuberculosis infection identifies early immune events as predictive of infection outcomes

Journal Article · Fri Apr 01 00:00:00 EDT 2022 · Journal of Theoretical Biology

DOI:https://doi.org/10.1016/j.jtbi.2022.111042· OSTI ID:1842864

; Linderman, Jennifer J.; Kirschner, Denise E.

Tuberculosis (TB), caused by infection with Mycobacterium tuberculosis (Mtb), is one of the world’s deadliest infectious diseases and remains a significant global health burden. TB disease and pathology can present clinically across a spectrum of outcomes, ranging from total sterilization of infection to active disease. Much remains unknown about the biology that drives an individual towards various clinical outcomes as it is challenging to experimentally address specific mechanisms driving clinical outcomes. Furthermore, it is unknown whether numbers of immune cells in the blood accurately reflect ongoing events during infection within human lungs. Herein, we utilize a systems biology approach by developing a whole-host model of the immune response to Mtb across multiple physiologic and time scales. This model, called HostSim, tracks events at the cellular, granuloma, organ, and host scale and represents the first whole-host, multi-scale model of the immune response following Mtb infection. We show that this model can capture various aspects of human and non-human primate TB disease and predict that biomarkers in the blood may only faithfully represent events in the lung at early time points after infection. We posit that HostSim, as a first step toward personalized digital twins in TB research, offers a powerful computational tool that can be used in concert with experimental approaches to understand and predict events about various aspects of TB disease and therapeutics.

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Research Organization:: Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States). National Energy Research Scientific Computing Center (NERSC)

Sponsoring Organization:: USDOE Office of Science (SC); National Science Foundation (NSF); National Institutes of Health (NIH)

Grant/Contract Number:: ACI-1053575; AC02-05CH11231; R01AI123093; R01 AI50684; U01 HL131072; MCB-140228

OSTI ID:: 1842864

Alternate ID(s):: OSTI ID: 1981696

Journal Information:: Journal of Theoretical Biology, Journal Name: Journal of Theoretical Biology Vol. 539 Journal Issue: C; ISSN 0022-5193

Publisher:: ElsevierCopyright Statement

Country of Publication:: United Kingdom

Language:: English

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59 BASIC BIOLOGICAL SCIENCES
Life sciences & biomedicine
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Title: A virtual host model of Mycobacterium tuberculosis infection identifies early immune events as predictive of infection outcomes

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