Cross-species transcriptomics translation reveals a role for the unfolded protein response in Mycobacterium tuberculosis infection

Numerous studies have identified similarities in blood transcriptomic signatures of tuberculosis (TB) phenotypes between mice and humans, including type 1 interferon production and innate immune cell activation. However, murine infection pathophysiology is distinct from human disease. We hypothesized that this is partly due to differences in the relative importance of biological pathways across species. To address this animal-to-human gap, we applied a systems modeling framework, Translatable Components Regression, to identify the axes of variation in the preclinical data most relevant to human TB disease state. Among the pathways our cross-species model pinpointed as highly predictive of human TB phenotype was the infection-induced unfolded protein response. To validate this mechanism, we confirmed that this cellular stress pathway modulates immune functions in Mycobacterium tuberculosis-infected mouse macrophages. Our work demonstrates how systems-level computational models enhance the value of animal studies for elucidating complex human pathophysiology.

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Publication Details

Journal
npj Systems Biology and Applications
Published
2025-02-15
DOI
https://doi.org/10.1038/s41540-024-00487-6
Citations
2
Primary Topic
RNA and protein synthesis mechanisms
Type
article
Field-Weighted Citation Impact
1.61

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article

Cross-species transcriptomics translation reveals a role for the unfolded protein response in Mycobacterium tuberculosis infection

Charlotte J. Reames, Seung-Hyun B Ko, Douglas A. Lauffenburger, Ryan Finethy et al.
2 citations
npj Systems Biology and Applications
RNA and protein synthesis mechanisms
1.61
article

Cross-species transcriptomics translation reveals a role for the unfolded protein response in Mycobacterium tuberculosis infection

Charlotte J. Reames, Seung-Hyun B Ko, Douglas A. Lauffenburger, Ryan Finethy, Christopher M. Sassetti, Krista M. Pullen
article en
2 citations

Abstract

Numerous studies have identified similarities in blood transcriptomic signatures of tuberculosis (TB) phenotypes between mice and humans, including type 1 interferon production and innate immune cell activation. However, murine infection pathophysiology is distinct from human disease. We hypothesized that this is partly due to differences in the relative importance of biological pathways across species. To address this animal-to-human gap, we applied a systems modeling framework, Translatable Components Regression, to identify the axes of variation in the preclinical data most relevant to human TB disease state. Among the pathways our cross-species model pinpointed as highly predictive of human TB phenotype was the infection-induced unfolded protein response. To validate this mechanism, we confirmed that this cellular stress pathway modulates immune functions in Mycobacterium tuberculosis-infected mouse macrophages. Our work demonstrates how systems-level computational models enhance the value of animal studies for elucidating complex human pathophysiology.

npj Systems Biology and ApplicationsVol. 11(1)
UMass Memorial Health Care (US), University of Massachusetts Chan Medical School (US), Massachusetts Institute of Technology (US)
National Science Foundation, Siebel Scholars Foundation, National Institutes of Health, Institute for Collaborative Biotechnologies
Good health and well-being
Openalex Percentile: Top 19%
RNA and protein synthesis mechanisms
1.61
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