ABSTRACT
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-1ß 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.
Subject(s)
Cytokines , Sepsis , Mice , Animals , Interleukin-6/genetics , Tumor Necrosis Factor-alpha/metabolism , Interferon-gamma , Sepsis/geneticsABSTRACT
Sepsis is a systemic response to infection with life-threatening consequences. Our understanding of the impact of sepsis across organs of the body is rudimentary. Here, using mouse models of sepsis, we generate a dynamic, organism-wide map of the pathogenesis of the disease, revealing the spatiotemporal patterns of the effects of sepsis across tissues. These data revealed two interorgan mechanisms key in sepsis. First, we discover a simplifying principle in the systemic behavior of the cytokine network during sepsis, whereby a hierarchical cytokine circuit arising from the pairwise effects of TNF plus IL-18, IFN-γ, or IL-1ß explains half of all the cellular effects of sepsis on 195 cell types across 9 organs. Second, we find that the secreted phospholipase PLA2G5 mediates hemolysis in blood, contributing to organ failure during sepsis. These results provide fundamental insights to help build a unifying mechanistic framework for the pathophysiological effects of sepsis on the body.
ABSTRACT
The immune system makes decisions in response to combinations of multiple microbial inputs. We do not understand the combinatorial logic governing how higher-order combinations of microbial signals shape immune responses. Here, using coculture experiments and statistical analyses, we discover a general property for the combinatorial sensing of microbial signals, whereby the effects of triplet combinations of microbial signals on immune responses can be predicted by combining the effects of single and pairs. Mechanistically, we find that singles and pairs dictate the information signaled by triplets in mouse and human DCs at the levels of transcription, chromatin, and protein secretion. We exploit this simplifying property to develop cell-based immunotherapies prepared with adjuvant combinations that trigger protective responses in mouse models of cancer. We conclude that the processing of multiple input signals by innate immune cells is governed by pairwise effects, which will inform the rationale combination of adjuvants to manipulate immunity.
Subject(s)
Immunity, Innate/physiology , Immunity/physiology , Receptors, Pattern Recognition/physiology , Adjuvants, Immunologic/pharmacology , Animals , Female , Immunity/immunology , Immunity, Innate/immunology , Immunotherapy/methods , Male , Mice , Mice, Inbred C57BL , Receptors, Pattern Recognition/immunologyABSTRACT
The immune system operates at the scale of the whole organism in mammals. We currently lack experimental approaches to systematically track and study organism-wide molecular processes in mice. Here we describe an integrated toolkit for measuring gene expression in whole tissues, 3-prime mRNA extension sequencing, that is applicable to most mouse organs and any mouse model of interest. Further, the methods of RNA-seq described in this protocol are broadly applicable to other sample types beyond whole organs, such as tissue samples or isolated cell populations. We report procedures to collect, store and lyse a dozen organ types using conditions compatible with the extraction of high-quality RNA. In addition, we detail protocols to perform high-throughput and low-cost RNA extraction and sequencing, as well as downstream data analysis. The protocol takes 5 d to process 384 mouse organs from collecting tissues to obtaining raw sequencing data, with additional time required for data analysis and mining. The protocol is accessible to individuals with basic skills in (i) mouse perfusion and dissection for sample collection and (ii) computation using Unix and R for data analysis. Overall, the methods presented here fill a gap in our toolbox for studying organism-wide processes in immunology and physiology.