In silico modeling of endothelial cell and neutrophil dysfunction to identify therapeutics for treating sepsis

Abstract

Sepsis is defined as life-threatening organ dysfunction caused by the body’s dysregulated host response to an infection. An early feature of sepsis is the dysregulated activation of endothelial cells; this process initiates a cascade of inflammatory events by releasing mediators, leading to leukocyte (e.g., neutrophil) adhesion, migration, tissue damage and multiple organ dysfunction syndrome. Therapeutic approaches for the treatment of sepsis are largely supportive, but there are no specific therapeutics that sustain neutrophil-endothelium function. All sepsis drugs developed in mice models have failed in clinical trials. Thus, novel methods leveraging recent developments in omics are needed to evaluate the neutrophil-endothelium response to therapeutics in sepsis. In this work, bioinformatics, proteomics and network modeling tools were employed to investigate proteomics in organ-specific endothelial cells (e.g., lungs, liver and kidneys) under inflammatory conditions and in neutrophils from sepsis patients. I hypothesized that the network models and the subsequent identification of drug targets for the repurposing of therapeutics will provide novel insight on the role of proteins in predicting pathological responses in endothelial cells and neutrophils under inflammatory/septic conditions. In Aim 1, using in vitro and in silico analysis, mouse lung, liver and kidney endothelial cells were exposed to inflammatory conditions to mimic sepsis over time to investigate endothelial cell differential protein expression and the underlying mechanisms contributing to inflammation. Critical findings included the lung having the highest number of differentially expressed proteins across time, processes such as cell adhesion, apoptosis and angiogenesis impacting organs (other than defense and immune processes) and a uniformity in protein expression being observed across time. In Aim 2, neutrophil immunophenotyping was performed using our Organ-on-Chip to identify three functional phenotypes (Hyperimmune, Hypoimmune and Hybrid) based on ex vivo adhesion and migration patterns on endothelial cells. Proteomics was used to identify unique signatures that correlated with disease severity; for example, two phenotypes (Hyperimmune and Hybrid) had similar protein expression across different protein classes (e.g., higher protein expression in neutrophil adhesion, cytoskeleton and defense classes) compared to the Hypoimmune phenotype. This novel approach could advance precision medicine for sepsis patients. In Aim 3, not only was functional enrichment analysis performed to identify critical processes/pathways in the neutrophil functional phenotypes from Aim 2, but in silico modeling was used to identify Food and Drug Administration approved drugs for treating sepsis. Specifically, network model(s) were built to investigate protein connectivity between those proteins that are targeted by Food and Drug Administration approved drugs and those that are potential druggable candidates. Furthermore, a degree-centric approach was used to rank the proteins in the network models to determine their role in regulating network functionality in the different processes/pathways associated with sepsis. Proteins that were highly ranked in each phenotype included Isocitrate Dehydrogenase (NAD(+)) 3 Catalytic Subunit Alpha (IDH3A - Hybrid), Cytochrome B5 Reductase (CYB5R3 – Hypoimmune) and Palmitoyl-Protein Thioesterase (PPT1 - Hyperimmune phenotype). Drugs targeting the highly ranked proteins included Palmitic acid (targeting PPT1 in Hyperimmune), NADH and FAD (targeting CYB5R3 in Hypoimmune) and NADH, Copper and Manganese (targeting IDH3A in Hybrid). Thus, these proteins should be further validated experimentally in each phenotype using our Organ-on-Chip.