APOE Protects Against Severe Infection with by Restraining Production of Neutrophil Extracellular Traps.

While neutrophils are the predominant cell type in the lungs of humans with active tuberculosis (TB), they are relatively scarce in the lungs of most strains of mice that are used to study the disease. However, similar to humans, neutrophils account for approximately 45% of CD45+ cells in the lungs of mice on a high-cholesterol (HC) diet following infection with (Mtb). We hypothesized that the susceptibility of HC mice might arise from an unrestrained feed-forward loop in which production of neutrophil extracellular traps (NETs) stimulates production of type I interferons by pDCs which in turn leads to the recruitment and activation of more neutrophils, and demonstrated that depleting neutrophils, depleting plasmacytoid dendritic cells (pDCs), or blocking type I interferon signaling, improved the outcome of infection.

Systems-level reconstruction of kinase phosphosignaling networks regulating endothelial barrier integrity using temporal data.

Phosphosignaling networks control cellular processes. We built kinase-mediated regulatory networks elicited by thrombin stimulation of brain endothelial cells using two computational strategies: Temporal Pathway Synthesizer (TPS), which uses phosphoproteomics data as input, and Temporally REsolved KInase Network Generation (TREKING), which uses kinase inhibitor screens. TPS and TREKING predicted overlapping barrier-regulatory kinases connected with unique network topology.

Systems-level reconstruction of kinase phosphosignaling networks regulating endothelial barrier integrity using temporal data.

Phosphosignaling networks control cellular processes. We built kinase-mediated regulatory networks elicited by thrombin stimulation of brain endothelial cells using two computational strategies: Temporal Pathway Synthesizer (TPS), which uses phosphoproetiomics data as input, and Temporally REsolved KInase Network Generation (TREKING), which uses kinase inhibitor screens. TPS and TREKING predicted overlapping barrier-regulatory kinases connected with unique network topology.

Automated, image-based quantification of peroxisome characteristics with perox-per-cell.

Summary: perox-per-cell automates cumbersome, image-based data collection tasks often encountered in peroxisome research. The software processes microscopy images to quantify peroxisome features in yeast cells. It uses off-the-shelf image processing tools to automatically segment cells and peroxisomes and then outputs quantitative metrics including peroxisome counts per cell and spatial areas.