Cross-species blood transcriptional correlates of BCG-mediated protection against tuberculosis include innate and adaptive immune processes
Kate Bridges, Denis Awany, Anele Gela, Temwa-Dango Mwambene, Sherry L. Kurtz, Richard E. Baker, Karen L. Elkins, Christopher M. Sassetti, Thomas J. Scriba, Douglas A. Lauffenburger
Kate Bridges, Denis Awany, Anele Gela, Temwa-Dango Mwambene, Sherry L. Kurtz, Richard E. Baker, Karen L. Elkins, Christopher M. Sassetti, Thomas J. Scriba, Douglas A. Lauffenburger
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Research Article Immunology Infectious disease

Cross-species blood transcriptional correlates of BCG-mediated protection against tuberculosis include innate and adaptive immune processes

Abstract

The immune mechanisms induced by the Bacillus Calmette-Guérin (BCG) vaccine, and the subset of which that mediate protection against tuberculosis (TB), remain poorly understood. This is further complicated by difficulties in verifying vaccine-induced protection in humans. Although research in animal models, namely mice and nonhuman primates (NHPs), has begun to close this knowledge gap, discrepancies in the relative importance of biological pathways across species limit the utility of animal model–derived biological insights in humans. To address these challenges, we applied a systems modeling framework, Translatable Components Regression (TransCompR), to identify human blood transcriptional variability that could predict Mycobacterium tuberculosis challenge outcomes in BCG-vaccinated NHPs. These protection-associated pathways included both innate and adaptive immune activation mechanisms, along with signaling via type I IFNs and antimycobacterial Th cytokines. We further partially validated the associations between these mechanisms and protection in humans using publicly available microarray data collected from BCG-vaccinated infants who either developed TB or remained healthy during 2 years of follow-up. Overall, our work demonstrates how species translation modeling can leverage animal studies to generate hypotheses about the mechanisms that underlie human infectious disease and vaccination outcomes, which may be difficult or impossible to ascertain using human data alone.

Authors

Kate Bridges, Denis Awany, Anele Gela, Temwa-Dango Mwambene, Sherry L. Kurtz, Richard E. Baker, Karen L. Elkins, Christopher M. Sassetti, Thomas J. Scriba, Douglas A. Lauffenburger

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Figure 3

Human-derived principal components can predict post–M. tuberculosis challenge bacterial burden in NHPs.

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Human-derived principal components can predict post–M. tuberculosis chal...
(A) Bar graphs showing explained variance captured by projecting the NHP bulk RNA-seq data, restricted to orthologous genes, into hPC space (right) as a percentage of total variance preserved for each postvaccination NHP dataset and (left) as distributed across each hPC in the TransCompR model. (B) Bar graphs showing (top) 5-fold logistic regression coefficients (summary data presented as mean ± SD) and (bottom) distribution of corresponding P values from univariate regression of each hPC against post–M. tuberculosis challenge bacterial burden (CFU). For each fold, P values are calculated by Wald’s test. The dotted line denotes P = 0.05. (C) Venn diagram detailing overlap of hPCs, which were found to be significantly associated with protection in the dose (B) and route (Supplemental Figure 5B) cohorts of NHPs and with BCG-specific immune cytokine expression in the South African infant cohort (Figure 2C). hPC4 is highlighted in red to indicate its unexpected correspondence between high bacterial burden in NHPs and high BCG-specific T cell response in infants.