The glutamate-cystine antiporter SLC7A11 plays a role in anti-viral immunity
Julia Blay, Department of Biomedicine
J. Blay-Cadanet1, M. B. Iversen1, A. L. Thielke1, D. Olagnier1, A. Massie2, C. K. Holm1 1Biomedicine, Aarhus University, Aarhus, Denmark,
2Neuro-Aging & Viro-Immunotherapy, Vrije Universiteit Brussels, Brussels, Belgium
Pathogenic viruses alter the cellular metabolism of the infected host cell to ensure sufficient levels of energy and biomolecules for de novo production of progeny viruses.
Such alterations lead to virus-induced changes in the flux across central metabolic pathways and in the abundancy of distinct metabolites. If chances in metabolite abundancy is sensed by the host to induce anti-viral responses is still unclear. Here we demonstrate that glutamate is accumulated and secreted in keratinocytes upon infection with herpes simplex virus, both in vitro and in vivo. This, prompts an efficient anti-viral program that includes formation of anti-viral glutathione through a process that depends on the NRF2-induced glutamate-cysteine antiporter SLC7A11, also known as xCT. The overall expression of xCT is relatively restricted with the highest expression levels in the CNS and parts of the immune system. Moreover, elevated expression of xCT has also been reported in cancer. However, it has not previously been associated with anti-viral
mechanisms. Here we demonstrate that the glutamate/cysteine anti-porter xCT is part of an anti-viral cellular program as suppression of xCT increases viral replication. In line with that, increasing the expression of xCT by CRISPR activation increases glutamate secretion, glutathione formation and impaired viral replication. In this manner, the host counters the incoming virus with metabolic changes that suppress viral replication. Finding new ways to target antiviral mechanisms can help to develop new anti-viral strategies.
Keywords: Infection, Inflammation, Cell biology
First-in-human in vivo non-invasive assessment of cardiac metabolism during adenosine stress test
Steen Jørgensen, Department of Clinical Medicine
ESS. Hansen, The MR-Research Centre AU; C. Laustsen, The MR-Research Centre AU; H.
Wiggers, Department of Cardiology AUH
INTRODUCTION: Hyperpolarized [1-13C]pyruvate cardiac magnetic resonance imaging (HP CMR) is an emerging, non-invasive method with the ability to detect cardiac
metabolism in vivo, beyond tissue glucose uptake. HP CMR visualizes the intracellular conversion of pyruvate to lactate in areas of ischemia and pyruvate to bicarbonate in areas of viable myocardium. The aim of the present study was to study feasibility of HP CMR during an adenosine stress test in the human heart.
METHODS: Healthy volunteers underwent CINE-CMR and HP CMR at rest and during an adenosine stress test. Kinetic modelling of pyruvate metabolism was used to measure rate of pyruvate conversion to lactate (kPL) and bicarbonate (kPB) at rest and during stress.
Semi-quantitative assessment of first-pass myocardial [1-13C]pyruvate perfusion was used to measure time-to-peak (TTP) in the myocardium as a marker of perfusion.
RESULTS: Six healthy volunteers were recruited. No major side effects were observed.
Myocardial perfusion was significantly increased during stress with reduction in TTP from 6.2 ± 2.8 sec to 2.7 ± 1.3 sec, p=0.04. The kPL increased statistically significant from 0.011 ± 0.009 sec-1 to 0.020 ± 0.010 sec-1, p=0.04. The kPB increased statistically significant from 0.004 ± 0.004 sec-1 to 0.012 ± 0.007 sec-1, p=0.008.
DISCUSSION: Our data represent the first human study of HP CMR during an adenosine stress test. We observed an increased carbohydrate oxidation during cardiac stress in the healthy human heart. The present study translates HP CMR to the clinic and forms a basis for comparisons in future studies of cardiac diseases.
Keywords: Cardiovascular system, Medical technology and diagnostic techniques, Molecular metabolism and endocrinology
Genome Mapped as Image (GMI)
Mateo Sokac, Department of Clinical Medicine, MoMA
Nicolai Juul Birkbak
Deep learning is widely used in many applications including medical imaging, speech recognition and language processing. However, large quantities of our data come in tabular form where we do not assume spatial connectivity between observations. In multi- omics analysis all of the data is structured as a table where a single row represents a single observation. In most cases, using this type of data is computationally heavy on statistical analyses which have to be corrected for false discovery rate. Furthermore, advanced machine learning models are not popular in research because they lack interpretability as they are often described as “black box” models. Here we present a framework with
multiple options for integrating multi-omics data by transforming the data into new
spatially dependent space which can be utilized in deep learning models and finally used for inference.
Keywords: Oncology, Epidemiology and biostatistics, Cell biology
Cellular and Subcellular Muscle Glycogen Metabolism and High-Intensity Exercise Performance
Jeppe F. Vigh-Larsen, Department of Public Health, Section for Sport Science
Niels Ørtenblad, Department of Sports Science and Clinical Biomechanics; Ole Emil Andersen, Department of Public Health; Kristian Overgaard, Department of Public Health;
Magni Mohr, Department of Sports Science and Clinical Biomechanics
Muscle glycogen is the major fuel during high-intensity exercise (HIE) and large declines can occur after relatively short durations; however, the relationship between muscle glycogen and HIE performance has not been studied in a placebo-controlled design.
Moreover, glycogen is stored in distinct subcellular compartments and specific depletion of these fractions may be a key aspect in any relationship between muscle glycogen and performance. PURPOSE: To investigate the effects of low muscle glycogen on repeated sprint ability (RSA) using a double-blinded design with special emphasis on subcellular glycogen. METHODS: Eighteen well-trained subjects performed glycogen-depleting cycling exercise; three periods of 10x45 s at ~110% VO2max with 135 s of passive rest between bouts and 15 min between periods. After exercise subjects were randomized to a low (LOW) or high (HIGH) carbohydrate intake for 5 hours. At baseline, after each period and following the diet intake RSA (5x6 s sprints separated by 24 s of rest) was evaluated and muscle biopsies and blood samples obtained. RESULTS: After recovery glycogen levels were 176±99 vs. 292±78 mmol·kg-1 dw in LOW and HIGH, respectively (P<0.05), whereas blood glucose concentrations were indifferent (P>0.05). This was accompanied by an impaired RSA only in LOW (8±6% reduction, P<0.05). Moreover, an overall moderate correlation was present between muscle glycogen content and RSA (P<0.05). Ongoing analyses of subcellular glycogen contents will be included in the final presentation of the data. CONCLUSIONS: Low muscle glycogen is associated with impaired RSA, which may be a result of specific depletion of subcellular glycogen fractions.
Keywords: Cell biology, Other, Other