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Genome-scale metabolic modelling of SARS-CoV-2 in cancer cells reveals an increased shift to glycolytic energy production.
Yaneske, Elisabeth; Zampieri, Guido; Bertoldi, Loris; Benvenuto, Giuseppe; Angione, Claudio.
  • Yaneske E; School of Computing, Engineering and Digital Technologies, Teesside University, Middlesbrough, UK.
  • Zampieri G; School of Computing, Engineering and Digital Technologies, Teesside University, Middlesbrough, UK.
  • Bertoldi L; Department of Biology, University of Padua, Italy.
  • Benvenuto G; BMR Genomics, Padua, Italy.
  • Angione C; BMR Genomics, Padua, Italy.
FEBS Lett ; 595(18): 2350-2365, 2021 09.
Article in English | MEDLINE | ID: covidwho-1363632
ABSTRACT
Cancer is considered a high-risk condition for severe illness resulting from COVID-19. The interaction between severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) and human metabolism is key to elucidating the risk posed by COVID-19 for cancer patients and identifying effective treatments, yet it is largely uncharacterised on a mechanistic level. We present a genome-scale map of short-term metabolic alterations triggered by SARS-CoV-2 infection of cancer cells. Through transcriptomic- and proteomic-informed genome-scale metabolic modelling, we characterise the role of RNA and fatty acid biosynthesis in conjunction with a rewiring in energy production pathways and enhanced cytokine secretion. These findings link together complementary aspects of viral invasion of cancer cells, while providing mechanistic insights that can inform the development of treatment strategies.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: SARS-CoV-2 / COVID-19 / Glycolysis / Models, Biological / Neoplasms Type of study: Prognostic study Topics: Long Covid Limits: Humans Language: English Journal: FEBS Lett Year: 2021 Document Type: Article Affiliation country: 1873-3468.14180

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Full text: Available Collection: International databases Database: MEDLINE Main subject: SARS-CoV-2 / COVID-19 / Glycolysis / Models, Biological / Neoplasms Type of study: Prognostic study Topics: Long Covid Limits: Humans Language: English Journal: FEBS Lett Year: 2021 Document Type: Article Affiliation country: 1873-3468.14180