Published January 8, 2024 | Version v1
Journal article Open

A pairwise cytokine code explains the organism-wide response to sepsis

Description

Sepsis is a systemic response to infection with life-threatening consequences. Our understanding of the molecular and cellular impact of sepsis across organs remains rudimentary. Here, we characterize the pathogenesis of sepsis by measuring dynamic changes in gene expression across organs. To pinpoint molecules controlling organ states in sepsis, we compare the effects of sepsis on organ gene expression to those of 6 singles and 15 pairs of recombinant cytokines. Strikingly, we find that the pairwise effects of tumor necrosis factor plus interleukin (IL)-18, interferon-gamma or IL-1β suffice to mirror the impact of sepsis across tissues. Mechanistically, we map the cellular effects of sepsis and cytokines by computing changes in the abundance of 195 cell types across 9 organs, which we validate by whole-mouse spatial profiling. Our work decodes the cytokine cacophony in sepsis into a pairwise cytokine message capturing the gene, cell and tissue responses of the host to the disease.

Data availability

The sequencing data generated during this study have been deposited in the Gene Expression Omnibus under accession number GSE224146. Preprocessed datasets are available at https://doi.org/10.5281/zenodo.10158368.

All scripts are publicly available at https://doi.org/10.5281/zenodo.10158368.

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Additional details

Identifiers

DOI
10.1038/s41590-023-01722-8
Other
oai:uchicago.tind.io:10352

Funding

Astellas Foundation for Research on Metabolic Disorders
National Science Foundation
Graduate Research Fellowship
National Institutes of Health
DP2-AI145100
National Institutes of Health
U01-AI160418
CZI
DAF2020-217464
Chan Zuckerberg Initiative
DAF
University of Chicago
Comprehensive Cancer Center (UCCCC) Janet D. Rowley Discovery Fund
University of Chicago
Center for Interdisciplinary Study of Inflammatory Intestinal Disorders
Chicago Immunoengineering Innovation Center
University of Chicago
Pritzker School of Molecular Engineering

UChicago Information

Division(s)
Biological Sciences Division, Physical Sciences Division, Pritzker School of Molecular Engineering
Department(s)
Human Genetics, Statistics