Disrupting circadian control of peripheral myogenic reactivity mitigates cardiac injury following myocardial infarction.

AIMS: Circadian rhythms orchestrate important functions in the cardiovascular system: the contribution of microvascular rhythms to cardiovascular disease progression/severity is unknown. This study hypothesized that (i) myogenic reactivity in skeletal muscle resistance arteries is rhythmic and (ii) disrupting this rhythmicity would alter cardiac injury post-myocardial infarction (MI). METHODS AND RESULTS: Cremaster skeletal muscle resistance arteries were isolated and assessed using standard pressure myography. Circadian rhythmicity was globally disrupted with the ClockΔ19/Δ19 mutation or discretely through smooth muscle cell-specific Bmal1 deletion (Sm-Bmal1 KO). Cardiac structure and function were determined by echocardiographic, hemodynamic and histological assessments. Myogenic reactivity in cremaster muscle resistance arteries is rhythmic. This rhythm is putatively mediated by the circadian modulation of a mechanosensitive signalosome incorporating tumour necrosis factor and casein kinase 1. Following left anterior descending coronary artery ligation, myogenic responsiveness is locked at the circadian maximum, although circadian molecular clock gene expression cycles normally. Disrupting the molecular clock abolishes myogenic rhythmicity: myogenic tone is suspended at the circadian minimum and is no longer augmented by MI. The reduced myogenic tone in ClockΔ19/Δ19 mice and Sm-Bmal1 KO mice associates with reduced total peripheral resistance (TPR), improved cardiac function and reduced infarct expansion post-MI. CONCLUSIONS: Augmented microvascular constriction aggravates cardiac injury post-MI. Following MI, skeletal muscle resistance artery myogenic reactivity increases specifically within the rest phase, when TPR would normally decline. Disrupting the circadian clock interrupts the MI-induced augmentation in myogenic reactivity: therapeutics targeting the molecular clock, therefore, may be useful for improving MI outcomes.

Stabilizing Cellular Barriers: Raising the Shields Against COVID-19.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its clinical manifestation (COVID-19; coronavirus disease 2019) have caused a worldwide health crisis. Disruption of epithelial and endothelial barriers is a key clinical turning point that differentiates patients who are likely to develop severe COVID-19 outcomes: it marks a significant escalation in respiratory symptoms, loss of viral containment and a progression toward multi-organ dysfunction. These barrier mechanisms are independently compromised by known COVID-19 risk factors, including diabetes, obesity and aging: thus, a synergism between these underlying conditions and SARS-CoV-2 mechanisms may explain why these risk factors correlate with more severe outcomes. This review examines the key cellular mechanisms that SARS-CoV-2 and its underlying risk factors utilize to disrupt barrier function. As an outlook, we propose that glucagon-like peptide 1 (GLP-1) may be a therapeutic intervention that can slow COVID-19 progression and improve clinical outcome following SARS-CoV-2 infection. GLP-1 signaling activates barrier-promoting processes that directly oppose the pro-inflammatory mechanisms commandeered by SARS-CoV-2 and its underlying risk factors.

Functional genetic discovery of enzymes using full-scan mass spectrometry metabolomics 1.

Our understanding of metabolic networks is incomplete, and new enzymatic activities await discovery in well-studied organisms. Mass spectrometric measurement of cellular metabolites reveals compounds inside cells that are unexplained by current maps of metabolic reactions, and existing computational models are unable to account for all activities observed within cells. Additional large-scale genetic and biochemical approaches are required to elucidate metabolic gene function. We have used full-scan mass spectrometry metabolomics of polar small molecules to examine deletion mutants of candidate enzymes in the model yeast Saccharomyces cerevisiae. We report the identification of 25 genes whose deletion results in focal metabolic changes consistent with loss of enzymatic activity and describe the informatic approaches used to enrich for candidate enzymes from uncharacterized open reading frames. Triumphs and pitfalls of metabolic phenotyping screens are discussed, including estimates of the frequency of uncharacterized eukaryotic genes that affect metabolism and key issues to consider when searching for new enzymatic functions in other organisms.

Systematic analysis of complex genetic interactions.

To systematically explore complex genetic interactions, we constructed ~200,000 yeast triple mutants and scored negative trigenic interactions. We selected double-mutant query genes across a broad spectrum of biological processes, spanning a range of quantitative features of the global digenic interaction network and tested for a genetic interaction with a third mutation. Trigenic interactions often occurred among functionally related genes, and essential genes were hubs on the trigenic network. Despite their functional enrichment, trigenic interactions tended to link genes in distant bioprocesses and displayed a weaker magnitude than digenic interactions. We estimate that the global trigenic interaction network is ~100 times as large as the global digenic network, highlighting the potential for complex genetic interactions to affect the biology of inheritance, including the genotype-to-phenotype relationship.

A global genetic interaction network maps a wiring diagram of cellular function.

We generated a global genetic interaction network for Saccharomyces cerevisiae, constructing more than 23 million double mutants, identifying about 550,000 negative and about 350,000 positive genetic interactions. This comprehensive network maps genetic interactions for essential gene pairs, highlighting essential genes as densely connected hubs. Genetic interaction profiles enabled assembly of a hierarchical model of cell function, including modules corresponding to protein complexes and pathways, biological processes, and cellular compartments. Negative interactions connected functionally related genes, mapped core bioprocesses, and identified pleiotropic genes, whereas positive interactions often mapped general regulatory connections among gene pairs, rather than shared functionality. The global network illustrates how coherent sets of genetic interactions connect protein complex and pathway modules to map a functional wiring diagram of the cell.