The metabolic state of a cell is influenced by cell-extrinsic factors, including nutrient availability and growth factor signaling. Here, we present extracellular matrix (ECM) remodeling as another fundamental node of cell-extrinsic metabolic regulation. Unbiased analysis of glycolytic drivers identified the hyaluronan-mediated motility receptor as being among the most highly correlated with glycolysis in cancer. Confirming a mechanistic link between the ECM component hyaluronan and metabolism, treatment of cells and xenografts with hyaluronidase triggers a robust increase in glycolysis. This is largely achieved through rapid receptor tyrosine kinase-mediated induction of the mRNA decay factor ZFP36, which targets TXNIP transcripts for degradation. Because TXNIP promotes internalization of the glucose transporter GLUT1, its acute decline enriches GLUT1 at the plasma membrane. Functionally, induction of glycolysis by hyaluronidase is required for concomitant acceleration of cell migration. This interconnection between ECM remodeling and metabolism is exhibited in dynamic tissue states, including tumorigenesis and embryogenesis.

Abstract*Correspondence, page proofs, and reprint requests to: James D. Tucker, Ph.D., Department of Biological Sciences, 1370 Biological Sciences Building, 5047 Gullen Mall, Wayne State University, Detroit, TEL: (313) 577-2783, FAX: (313) 577-3602, EMAIL: E-mail: jtucker@biology.biosci.wayne.edu. z Retired Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. Chromosome translocations in peripheral blood lymphocytes of normal, healthy humans increase with age, but the effects of gender, race, and cigarette smoking on background translocation yields have not been examined systematically. Further, the shape of the relationship between age and translocation frequency (TF) has not been definitively determined. We collected existing data from sixteen laboratories in North America, Europe, and Asia on TFs measured in peripheral blood lymphocytes by fluorescence in situ hybridization whole chromosome painting among 1933 individuals. In Poisson regression models, age, ranging from newborns (cord blood) to 85 years, was strongly associated with TF and this relationship showed significant upward curvature at older ages vs. a linear relationship (p <0.001). Ever smokers had significantly higher TFs than non-smokers (rate ratio (RR) = 1.19, 95% confidence interval (CI), 1.09-1.30) and smoking modified the effect of age on TFs with a steeper age-related increase among ever smokers compared to non-smokers (p<0.001). TFs did not differ by gender. Interpreting an independent effect of race was difficult owing to laboratory variation. Our study is three times larger than any pooled effort to date, confirming a suspected curvilinear relationship of TF with age. The significant effect of cigarette smoking has not been observed with previous pooled studies of TF in humans. Our data provide stable estimates of background TF by age, gender, race, and smoking status and suggest an acceleration of chromosome damage above age 60 and among those with a history of smoking cigarettes. NIH Public Access

A.J. performed transthoracic injections. G.A. performed a portion of the CT scans. M.M. and S.T.B. performed IHC staining and analyzed data. M.M. J.T.L. and A.J. performed in vitro 18 FBnTP uptake assays. M.M. did TMRE staining and western blots. M.C.F is a board-certified anatomic pathologist who performed the pathological analysis. L.S. and O.S. performed and guided respirometry experiments. S.S., C.M.W., A.G. and T.H. performed radio-tracer synthesis. D.D. and C.K. performed biochemical analysis of mitochondria. E.S. and H.C. performed metabolic analysis of lung tumors. S.M.D. contributed resources and critical feedback on the project. Data availability Source data for Western blots are provided with the paper as Supplementary Figure 1. Source data for Figures 1b-d; Figures 2d-g; Figures 3b, 3d, 3e; ED Figures 3c-e; ED Figures 4c, 4d; ED Figure 9a are provided with the paper. The data that support the findings of this study are available from the corresponding author upon reasonable request.

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Highlights d GSK3 and Axin1 normally repress macropinocytosis in basal cellular conditions d GSK3 inhibition or Axin1 mutation triggers macropinocytosis and metabolite changes d Macropinocytosis induces acidification and catabolic activity of lysosomes d Lysosomal activation by Wnt signaling is independent of new protein synthesis

Viruses hijack host cell metabolism to acquire the building blocks required for replication. Understanding how SARS-CoV-2 alters host cell metabolism may lead to potential treatments for COVID-19. Here we profile metabolic changes conferred by SARS-CoV-2 infection in kidney epithelial cells and lung air-liquid interface (ALI) cultures, and show that SARS-CoV-2 infection increases glucose carbon entry into the TCA cycle via increased pyruvate carboxylase expression. SARS-CoV-2 also reduces oxidative glutamine metabolism while maintaining reductive carboxylation. Consistent with these changes, SARS-CoV-2 infection increases the activity of mTORC1 in cell lines and lung ALI cultures. Lastly, we show evidence of mTORC1 activation in COVID-19 patient lung tissue, and that mTORC1 inhibitors reduce viral replication in kidney epithelial cells and lung ALI cultures. Our results suggest that targeting mTORC1 may be a feasible treatment strategy for COVID-19 patients, although further studies are required to determine the mechanism of inhibition and potential efficacy in patients.

Zika virus is a pathogen that poses serious consequences, including congenital microcephaly. Although many viruses reprogram host cell metabolism, whether Zika virus alters cellular metabolism and the functional consequences of Zika-induced metabolic changes remain unknown. Here, we show that Zika virus infection differentially reprograms glucose metabolism in human versus C6/36 mosquito cells by increasing glucose use in the tricarboxylic acid cycle in human cells versus increasing glucose use in the pentose phosphate pathway in mosquito cells. Infection of human cells selectively depletes nucleotide triphosphate levels, leading to elevated AMP/ATP ratios, AMP-activated protein kinase (AMPK) phosphorylation, and caspase-mediated cell death. AMPK is also phosphorylated in Zika virus-infected mouse brain. Inhibiting AMPK in human cells decreases Zika virus-mediated cell death, whereas activating AMPK in mosquito cells promotes Zika virus-mediated cell death. These findings suggest that the differential metabolic reprogramming during Zika virus infection of human versus mosquito cells determines whether cell death occurs.

Targeted proteomics enables hypothesis-driven research by measuring the cellular expression of protein cohorts related by function, disease, or class after perturbation. Here, we present a pathway-centric approach and an assay builder resource for targeting entire pathways of up to 200 proteins selected from >10,000 expressed proteins to directly measure their abundances, exploiting sample multiplexing to increase throughput by 16-fold. The strategy, termed GoDig, requires only a single-shot LC-MS analysis, ~1 µg combined peptide material, a list of up to 200 proteins, and real-time analytics to trigger simultaneous quantification of up to 16 samples for hundreds of analytes. We apply GoDig to quantify the impact of genetic variation on protein expression in mice fed a high-fat diet. We create several GoDig assays to quantify the expression of multiple protein families (kinases, lipid metabolism- and lipid droplet-associated proteins) across 480 fully-genotyped Diversity Outbred mice, revealing protein quantitative trait loci and establishing potential linkages between specific proteins and lipid homeostasis.