In vivo analysis of secretory pathways driving… (R03AI202285) – Project Grant to Loyola University Of Chicago

Abstract: Local inflammatory responses often propagate systemically through the dissemination of secreted mediators, driving acute syndromes such as sepsis and cytokine storm, as well as chronic pathologies including metabolic and autoimmune disease. To identify therapeutic targets to mitigate systemic inflammation and secondary organ damage, IT is essential to define the secreted factors and the cellular sources that initiate inflammatory responses and pinpoint the mediators that propagate inflammation. This R03 application will develop secretome reporter mouse models to define, in vivo, the proteins that drive systemic inflammation with cell-type and pathway specificity. Secreted proteins bearing signal-peptides are released via the endoplasmic reticulum(ER)-golgi pathway, exemplified by pro-inflammatory cytokines interleukin-6 and TNF-α, whereas signal-peptide lacking cytoplasmic proteins such as interleukin-1Β (IL-1Β), and galectin-3 are released via ER-golgi independent mechanisms collectively termed unconventional cytoplasmic protein secretion (ucps). Current measurement of secreted factors in vivo relies largely on mass spectrometry-based proteomics of circulating proteins, which lack cell- and pathway-specific resolution. In contrast, secretomics of cultured cells enables cellular and pathway resolution but lacks native context. To bridge this GAP and achieve pathway- and cell-type-specific resolution in vivo, we will utilize secretome reporter mice that harbor proximity biotinylating enzymes localized either to the ER, thereby labeling conventionally secreted proteins, or to the cytoplasm, thereby labeling ucps cargoes. Existing "secretome mouse" models have demonstrated feasibility by identifying conventionally secreted proteins using ER-resident bira or related proximity biotyinlation enzymes. However, these models are limited by the slow kinetics of the enzymes used, which likely miss transient, rapidly released inflammatory cargo, and by the kdel-mediated ER retention strategy, which results in secretion of the biotinylating enzyme itself and confounds interpretation of labeling sites. Moreover, these models cannot capture ucps cargo such as IL-1Β, which do not enter the ER. This R03 will overcome these limitations by 1) generating a CRE-inducible, ER-membrane-anchored turboid mouse model, which will provide ER spatial confinement and increase labelling speed by ~100-fold, enabling detection of transient inflammatory cargo and assignment of cellular provenance; and 2) testing whether an existing cytoplasm-resident turboid mouse model labels ucps cargo, and directly comparing cyto-turboid and ER-turboid in their ability to identify distinct secreted proteins in vivo. We will use a liver inflammation- driven model of systemic inflammation as a proof-of-principle to test these tools. We expect these tools will be broadly applicable for the study of secretory pathways and secreted proteins that drive infectious, metabolic, and autoimmune diseases.

In vivo analysis of secretory pathways driving systemic inflammation

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