Plasma metabolomics and gene regulatory networks analysis reveal the role of nonstructural SARS-CoV-2 viral proteins in metabolic dysregulation in COVID-19 patients

Standard

Plasma metabolomics and gene regulatory networks analysis reveal the role of nonstructural SARS-CoV-2 viral proteins in metabolic dysregulation in COVID-19 patients. / Ivanisenko, V. A.; Gaisler, E. V.; Basov, N. V. et al.

In: Scientific Reports, Vol. 12, No. 1, 19977, 12.2022.

Research output: Contribution to journal › Article › peer-review

BibTeX

@article{00e9e1ae68f44b3f81014f8b57507ead,

title = "Plasma metabolomics and gene regulatory networks analysis reveal the role of nonstructural SARS-CoV-2 viral proteins in metabolic dysregulation in COVID-19 patients",

abstract = "Metabolomic analysis of blood plasma samples from COVID-19 patients is a promising approach allowing for the evaluation of disease progression. We performed the metabolomic analysis of plasma samples of 30 COVID-19 patients and the 19 controls using the high-performance liquid chromatography (HPLC) coupled with tandem mass spectrometric detection (LC–MS/MS). In our analysis, we identified 103 metabolites enriched in KEGG metabolic pathways such as amino acid metabolism and the biosynthesis of aminoacyl-tRNAs, which differed significantly between the COVID-19 patients and the controls. Using ANDSystem software, we performed the reconstruction of gene networks describing the potential genetic regulation of metabolic pathways perturbed in COVID-19 patients by SARS-CoV-2 proteins. The nonstructural proteins of SARS-CoV-2 (orf8 and nsp5) and structural protein E were involved in the greater number of regulatory pathways. The reconstructed gene networks suggest the hypotheses on the molecular mechanisms of virus-host interactions in COVID-19 pathology and provide a basis for the further experimental and computer studies of the regulation of metabolic pathways by SARS-CoV-2 proteins. Our metabolomic analysis suggests the need for nonstructural protein-based vaccines and the control strategy to reduce the disease progression of COVID-19.",

keywords = "Humans, SARS-CoV-2/genetics, COVID-19, Gene Regulatory Networks, Chromatography, Liquid, Tandem Mass Spectrometry, Plasma, Viral Proteins/genetics, Disease Progression",

author = "Ivanisenko, {V. A.} and Gaisler, {E. V.} and Basov, {N. V.} and Rogachev, {A. D.} and Cheresiz, {S. V.} and Ivanisenko, {T. V.} and Demenkov, {P. S.} and Mishchenko, {E. L.} and Khripko, {O. P.} and Khripko, {Yu I.} and Voevoda, {S. M.} and Karpenko, {T. N.} and Velichko, {A. J.} and Voevoda, {M. I.} and Kolchanov, {N. A.} and Pokrovsky, {A. G.}",

note = "Funding Information: The bioinformatics analysis was supported by the budget project “Systems biology and bioinformatics: reconstruction, analysis and modeling of the structural and functional organization and evolution of human, animal, plant and microorganism gene networks” (No. FWNR-2022-0020). Plasma sample collection and processing were supported by RFBR grant 20-04-60314. Metabolomic analyses were supported by the state contract FSUS-2020-0035. Publisher Copyright: {\textcopyright} 2022, The Author(s).",

year = "2022",

month = dec,

doi = "10.1038/s41598-022-24170-0",

language = "English",

volume = "12",

journal = "Scientific Reports",

issn = "2045-2322",

publisher = "Nature Publishing Group",

number = "1",

}

RIS

TY - JOUR

T1 - Plasma metabolomics and gene regulatory networks analysis reveal the role of nonstructural SARS-CoV-2 viral proteins in metabolic dysregulation in COVID-19 patients

AU - Ivanisenko, V. A.

AU - Gaisler, E. V.

AU - Basov, N. V.

AU - Rogachev, A. D.

AU - Cheresiz, S. V.

AU - Ivanisenko, T. V.

AU - Demenkov, P. S.

AU - Mishchenko, E. L.

AU - Khripko, O. P.

AU - Khripko, Yu I.

AU - Voevoda, S. M.

AU - Karpenko, T. N.

AU - Velichko, A. J.

AU - Voevoda, M. I.

AU - Kolchanov, N. A.

AU - Pokrovsky, A. G.

N1 - Funding Information: The bioinformatics analysis was supported by the budget project “Systems biology and bioinformatics: reconstruction, analysis and modeling of the structural and functional organization and evolution of human, animal, plant and microorganism gene networks” (No. FWNR-2022-0020). Plasma sample collection and processing were supported by RFBR grant 20-04-60314. Metabolomic analyses were supported by the state contract FSUS-2020-0035. Publisher Copyright: © 2022, The Author(s).

PY - 2022/12

Y1 - 2022/12

N2 - Metabolomic analysis of blood plasma samples from COVID-19 patients is a promising approach allowing for the evaluation of disease progression. We performed the metabolomic analysis of plasma samples of 30 COVID-19 patients and the 19 controls using the high-performance liquid chromatography (HPLC) coupled with tandem mass spectrometric detection (LC–MS/MS). In our analysis, we identified 103 metabolites enriched in KEGG metabolic pathways such as amino acid metabolism and the biosynthesis of aminoacyl-tRNAs, which differed significantly between the COVID-19 patients and the controls. Using ANDSystem software, we performed the reconstruction of gene networks describing the potential genetic regulation of metabolic pathways perturbed in COVID-19 patients by SARS-CoV-2 proteins. The nonstructural proteins of SARS-CoV-2 (orf8 and nsp5) and structural protein E were involved in the greater number of regulatory pathways. The reconstructed gene networks suggest the hypotheses on the molecular mechanisms of virus-host interactions in COVID-19 pathology and provide a basis for the further experimental and computer studies of the regulation of metabolic pathways by SARS-CoV-2 proteins. Our metabolomic analysis suggests the need for nonstructural protein-based vaccines and the control strategy to reduce the disease progression of COVID-19.

AB - Metabolomic analysis of blood plasma samples from COVID-19 patients is a promising approach allowing for the evaluation of disease progression. We performed the metabolomic analysis of plasma samples of 30 COVID-19 patients and the 19 controls using the high-performance liquid chromatography (HPLC) coupled with tandem mass spectrometric detection (LC–MS/MS). In our analysis, we identified 103 metabolites enriched in KEGG metabolic pathways such as amino acid metabolism and the biosynthesis of aminoacyl-tRNAs, which differed significantly between the COVID-19 patients and the controls. Using ANDSystem software, we performed the reconstruction of gene networks describing the potential genetic regulation of metabolic pathways perturbed in COVID-19 patients by SARS-CoV-2 proteins. The nonstructural proteins of SARS-CoV-2 (orf8 and nsp5) and structural protein E were involved in the greater number of regulatory pathways. The reconstructed gene networks suggest the hypotheses on the molecular mechanisms of virus-host interactions in COVID-19 pathology and provide a basis for the further experimental and computer studies of the regulation of metabolic pathways by SARS-CoV-2 proteins. Our metabolomic analysis suggests the need for nonstructural protein-based vaccines and the control strategy to reduce the disease progression of COVID-19.

KW - Humans

KW - SARS-CoV-2/genetics

KW - COVID-19

KW - Gene Regulatory Networks

KW - Chromatography, Liquid

KW - Tandem Mass Spectrometry

KW - Plasma

KW - Viral Proteins/genetics

KW - Disease Progression

UR - http://www.scopus.com/inward/record.url?scp=85142294430&partnerID=8YFLogxK

UR - https://www.mendeley.com/catalogue/59c46f0e-9ea0-3aa2-b06e-e03a38f8a9d7/

U2 - 10.1038/s41598-022-24170-0

DO - 10.1038/s41598-022-24170-0

M3 - Article

C2 - 36404352

AN - SCOPUS:85142294430

VL - 12

JO - Scientific Reports

JF - Scientific Reports

SN - 2045-2322

IS - 1

M1 - 19977

ER -

ID: 39707325