Epithelial cell–derived secreted and transmembrane 1a signals to activated neutrophils during pneumococcal pneumonia

Airway epithelial cell responses are critical to the outcome of lung infection. In this study, we aimed to identify unique contributions of epithelial cells during lung infection. To differentiate genes induced selectively in epithelial cells during pneumonia, we compared genome-wide expression profiles from three sorted cell populations: epithelial cells from uninfected mouse lungs, epithelial cells from mouse lungs with pneumococcal pneumonia, and nonepithelial cells from those same infected lungs. Of 1,166 transcripts that were more abundant in epithelial cells from infected lungs compared with nonepithelial cells from the same lungs or from epithelial cells of uninfected lungs, 32 genes were identified as highly expressed secreted products. Especially strong signals included two related secreted and transmembrane (Sectm) 1 genes, Sectm1a and Sectm1b. Refinement of sorting strategies suggested that both Sectm1 products were induced predominantly in conducting airway epithelial cells. Sectm1 was induced during the early stages of pneumococcal pneumonia, and mutation of NF-kB RelA in epithelial cells did not diminish its expression. Instead, type I IFN signaling was necessary and sufficient for Sectm1 induction in lung epithelial cells, mediated by signal transducer and activator of transcription 1. For target cells, Sectm1a bound to myeloid cells preferentially, in particular Ly6GbrightCD11bbright neutrophils in the infected lung. In contrast, Sectm1a did not bind to neutrophils from uninfected lungs. Sectm1a increased expression of the neutrophil-attracting chemokine CXCL2 by neutrophils from the infected lung. We propose that Sectm1a is an epithelial product that sustains a positive feedback loop amplifying neutrophilic inflammation during pneumococcal pneumonia

Invoking "ARTeMIS" — The multi-objective hunt for diverse and robust alternative solutions

The Automated Red Teaming Multiobjective Innovation Seeker (ARTeMIS) is a novel software application that implements a self-adaptive evolutionary algorithm that is designed to search for a diverse set of robust solutions in a multi-objective problem space. We present the details of our implementation and demonstrate its use on a simulation case study that considers two objectives.NPS Naval Research Program N16M16