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PNAS Papers on Mycobacterium Tuberculosis, Atlantic Cod, Heart Valve Remodeling Network

Editor's Note: Some of the articles described below are not yet available at the PNAS site but are scheduled to be posted this week.

For a paper slated to appear in PNAS this week, researchers at Georgia State University, Albert Einstein College of Medicine, and other centers in the US and UK describe genetic pathways that attenuated versions of the Mycobacterium tuberculosis pathogen that are missing some ESX-3 secretion system genes that they rely on in the absence of iron supplementation. Using whole-genome sequencing, RNA sequencing, and other approaches, the team characterized M. tuberculosis isolates containing suppressor mutations making them virulent in mice without additional iron. "Whole-genome sequencing identified two mechanisms of suppression, the disruption of an ESX-3 paralogous region encoding EsxR and EsxS, and a massive 38- to 60-fold gene amplification of this same region," the authors report. "These data are significant because they reveal a previously unrecognized iron acquisition regulon and inform mechanisms of [M. tuberculosis] chromosome evolution."

A team from Norway and Sweden explores population history and selection patterns in the Atlantic cod, Gadus morhua. With genotyping profiles for more than 750 Atlantic cod at 16 sampling sites, along with whole-genome resequencing on 11 representatives, the researchers saw stabilizing selection at several so-called "supergenes" marked by chromosomal inversion-based polymorphisms that tend to cluster by location. The genomic data also pointed to past population declines going back around 1,000 years in Atlantic cod in the northern Atlantic Ocean. "Our results support an early onset of the marine Anthropocene in the North Sea system," they write, "with long-term human impacts shaping species and ecosystem trajectories."

Investigators at Clemson University and elsewhere explore cellular networks underlying patient-specific extracellular matrix remodeling in heart valve myofibroblasts in individuals with aortic valve stenosis. The team's computational modeling approach picked up personalized signaling clues using gene expression, drug screening profiles, and other insights gleaned from valve myofibroblast models exposed to sera from individuals with aortic valve stenosis. "We have built a computational model of the cell biochemical network that regulates valve remodeling, which enables virtual predictions of valve scarring given patient-specific biochemical levels," the researchers write. "With this model, we ran personalized drug screens to predict each patient's response to particular therapies, and follow-up cell culture experiments validated our predictions with over 80 percent accuracy."

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