Inferring Tissue-Specific, TLR4-Dependent Type 17 Immune Interactions in Experimental Trauma/Hemorrhagic Shock and Resuscitation Using Computational Modeling

Abstract

Trauma/hemorrhagic shock followed by resuscitation (T/HS-R) results in multi-system inflammation and organ dysfunction, in part driven by binding of damage-associated molecular pattern molecules to Toll-like Receptor 4 (TLR4). We carried out experimental T/HS-R (pseudo-fracture plus 2 h of shock followed by 0-22 h of resuscitation) in C57BL/6 (wild type [WT]) and TLR4-null (TLR4-/-) mice, and then defined the dynamics of 20 protein-level inflammatory mediators in the heart, gut, lung, liver, spleen, kidney, and systemic circulation. Cross-correlation and Principal Component Analysis (PCA) on data from the 7 tissues sampled suggested that TLR4-/- samples express multiple inflammatory mediators in a small subset of tissue compartments as compared to the WT samples, in which many inflammatory mediators were localized non-specifically to nearly all compartments. We and others have previously defined a central role for type 17 immune cells in human trauma. Accordingly, correlations between IL-17A and GM-CSF (indicative of pathogenic Th17 cells); between IL-17A and IL-10 (indicative of non-pathogenic Th17 cells); and IL-17A and TNF (indicative of memory/effector T cells) were assessed across all tissues studied. In both WT and TLR4-/- mice, positive correlations were observed between IL-17A and GM-CSF, IL-10, and TNF in the kidney and gut. In contrast, the variable and dynamic presence of both pathogenic and non-pathogenic Th17 cells was inferred in the systemic circulation of TLR4-/- mice over time, suggesting a role for TLR4 in efflux of these cells into peripheral tissues. Hypergraph analysis – used to define dynamic, cross compartment networks – in concert with PCA-suggested that IL-17A was present persistently in all tissues at all sampled time points except for its absence in the plasma at 0.5h in the WT group, supporting the hypothesis that T/HS-R induces efflux of Th17 cells from the circulation and into specific tissues. These analyses suggest a complex, context-specific role for TLR4 and type 17 immunity following T/HS-R.

Central role for neurally dysregulated IL-17A in dynamic networks of systemic and local inflammation in combat casualties

“…While a recent study that defined civilian trauma endotypes using a multi-omic approach pointed to IL-17A as one biomarker of a trauma endotype enriched for TBI 13 , this is the first study in humans specifically linking TBI in combat trauma to elevated wound and systemic IL-17A. As such, our study links injury-associated Th17 immune responses 13 , 17 , 21 , 24 , 46 to the well-established negative impact of TBI on trauma outcomes 47 – 49 . Our studies may also connect the emerging role of IL-17A and Th17 immune responses in wound healing 50 to the documented but not yet fully elucidated impact of systemic inflammatory responses on local inflammation in the wound 23 .…”

“…Furthermore, CD4 + /CD8 + effector/memory T cells co-express IL-17A and TNF-α 41 , 42 . We have previously utilized Spearman rank correlation analysis of IL-17A vs. GM-CSF, IL-10, or TNF-α to infer the presence of these three IL-17A-producing cell subsets 17 , 21 , 24 , 43 , with positive and negative correlations being interpreted as increases or decreases, respectively, in these Th17 cell subsets.…”

“…We have previously employed static hypergraph analysis to gain insights into the spatiotemporal spread of inflammation across multiple tissues following experimental trauma/hemorrhage and resuscitation 24 . We expanded this methodology to gain an understanding of the processes that might regulate the interaction of wound-localized and systemic inflammation in combat casualties and have termed this novel method Dynamic Hypergraph (DyHyp) analysis.…”

“…A hypergraph is a type of nodal graph model in which edges have the special property of connecting more than two nodes 24 , 32 – 35 . Here, we define edges as inflammatory mediators and nodes to be tissue compartments (either serum or wound effluent).…”

“…A key, unanswered question centers around how systemic inflammation impacts injury-induced local inflammatory responses in wounds on systemic inflammation and vice versa, i.e., if inflammation in one compartment modulates the response in the other 23 . We have begun to address this question in experimental paradigms of trauma/hemorrhage via multiple computational approaches including hypergraph analysis, a graph-theory approach to modeling multi-compartment trends in inflammation 24 .…”