Gene expression profiling of host lipid metabolism in SARS-CoV-2 infected patients: a systematic review and integrated bioinformatics analysis.
Bioinformatics
Gene expression
Lipid metabolism
Next-generation sequencing
SARS-CoV-2
Journal
BMC infectious diseases
ISSN: 1471-2334
Titre abrégé: BMC Infect Dis
Pays: England
ID NLM: 100968551
Informations de publication
Date de publication:
23 Jan 2024
23 Jan 2024
Historique:
received:
03
08
2023
accepted:
03
01
2024
medline:
24
1
2024
pubmed:
24
1
2024
entrez:
23
1
2024
Statut:
epublish
Résumé
The Coronavirus disease 2019 (COVID-19) pandemic occurred due to the dispersion of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Severe symptoms can be observed in COVID-19 patients with lipid-related comorbidities such as obesity and diabetes. Yet, the extensive molecular mechanisms of how SARS-CoV-2 causes dysregulation of lipid metabolism remain unknown. Here, an advanced search of articles was conducted using PubMed, Scopus, EBSCOhost, and Web of Science databases using terms from Medical Subject Heading (MeSH) like SARS-CoV-2, lipid metabolism and transcriptomic as the keywords. From 428 retrieved studies, only clinical studies using next-generation sequencing as a gene expression method in COVID-19 patients were accepted. Study design, study population, sample type, the method for gene expression and differentially expressed genes (DEGs) were extracted from the five included studies. The DEGs obtained from the studies were pooled and analyzed using the bioinformatics software package, DAVID, to determine the enriched pathways. The DEGs involved in lipid metabolic pathways were selected and further analyzed using STRING and Cytoscape through visualization by protein-protein interaction (PPI) network complex. The analysis identified nine remarkable clusters from the PPI complex, where cluster 1 showed the highest molecular interaction score. Three potential candidate genes (PPARG, IFITM3 and APOBEC3G) were pointed out from the integrated bioinformatics analysis in this systematic review and were chosen due to their significant role in regulating lipid metabolism. These candidate genes were significantly involved in enriched lipid metabolic pathways, mainly in regulating lipid homeostasis affecting the pathogenicity of SARS-CoV-2, specifically in mechanisms of viral entry and viral replication in COVID-19 patients. Taken together, our findings in this systematic review highlight the affected lipid-metabolic pathways along with the affected genes upon SARS-CoV-2 invasion, which could be a potential target for new therapeutic strategies study in the future.
Sections du résumé
BACKGROUND
BACKGROUND
The Coronavirus disease 2019 (COVID-19) pandemic occurred due to the dispersion of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Severe symptoms can be observed in COVID-19 patients with lipid-related comorbidities such as obesity and diabetes. Yet, the extensive molecular mechanisms of how SARS-CoV-2 causes dysregulation of lipid metabolism remain unknown.
METHODS
METHODS
Here, an advanced search of articles was conducted using PubMed, Scopus, EBSCOhost, and Web of Science databases using terms from Medical Subject Heading (MeSH) like SARS-CoV-2, lipid metabolism and transcriptomic as the keywords. From 428 retrieved studies, only clinical studies using next-generation sequencing as a gene expression method in COVID-19 patients were accepted. Study design, study population, sample type, the method for gene expression and differentially expressed genes (DEGs) were extracted from the five included studies. The DEGs obtained from the studies were pooled and analyzed using the bioinformatics software package, DAVID, to determine the enriched pathways. The DEGs involved in lipid metabolic pathways were selected and further analyzed using STRING and Cytoscape through visualization by protein-protein interaction (PPI) network complex.
RESULTS
RESULTS
The analysis identified nine remarkable clusters from the PPI complex, where cluster 1 showed the highest molecular interaction score. Three potential candidate genes (PPARG, IFITM3 and APOBEC3G) were pointed out from the integrated bioinformatics analysis in this systematic review and were chosen due to their significant role in regulating lipid metabolism. These candidate genes were significantly involved in enriched lipid metabolic pathways, mainly in regulating lipid homeostasis affecting the pathogenicity of SARS-CoV-2, specifically in mechanisms of viral entry and viral replication in COVID-19 patients.
CONCLUSIONS
CONCLUSIONS
Taken together, our findings in this systematic review highlight the affected lipid-metabolic pathways along with the affected genes upon SARS-CoV-2 invasion, which could be a potential target for new therapeutic strategies study in the future.
Identifiants
pubmed: 38263024
doi: 10.1186/s12879-024-08983-0
pii: 10.1186/s12879-024-08983-0
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
124Subventions
Organisme : Ministry of Higher Education, Malaysia
ID : FRGS/1/2021/SKK0/USIM/02/2; USIM/FRGS/FPSK/KPT/50321
Organisme : Ministry of Higher Education, Malaysia
ID : FRGS/1/2021/SKK0/USIM/02/2; USIM/FRGS/FPSK/KPT/50321
Organisme : Ministry of Higher Education, Malaysia
ID : FRGS/1/2021/SKK0/USIM/02/2; USIM/FRGS/FPSK/KPT/50321
Organisme : Ministry of Higher Education, Malaysia
ID : FRGS/1/2021/SKK0/USIM/02/2; USIM/FRGS/FPSK/KPT/50321
Organisme : Ministry of Higher Education, Malaysia
ID : FRGS/1/2021/SKK0/USIM/02/2; USIM/FRGS/FPSK/KPT/50321
Organisme : Ministry of Higher Education, Malaysia
ID : FRGS/1/2021/SKK0/USIM/02/2; USIM/FRGS/FPSK/KPT/50321
Organisme : USIM Internal Grant Scheme, USIM
ID : PPPI/FPSK/0121/USIM/16121
Organisme : USIM Internal Grant Scheme, USIM
ID : PPPI/FPSK/0121/USIM/16121
Organisme : USIM Internal Grant Scheme, USIM
ID : PPPI/FPSK/0121/USIM/16121
Organisme : USIM Internal Grant Scheme, USIM
ID : PPPI/FPSK/0121/USIM/16121
Informations de copyright
© 2024. The Author(s).
Références
Zhu N, Zhang D, Wang W, Li X, Yang B, Song J, et al. A novel coronavirus from patients with pneumonia in China, 2019. N Engl J Med. 2020;382(8):727–33. https://doi.org/10.1056/NEJMoa2001017
doi: 10.1056/NEJMoa2001017
pubmed: 31978945
pmcid: 7092803
Lake MA. What we know so far: COVID-19 current clinical knowledge and research. Clin Med. 2020;20(2):124. https://doi.org/10.7861/clinmed.2019-coron
doi: 10.7861/clinmed.2019-coron
Wu F, Zhao S, Yu B, Chen Y-M, Wang W, Song Z-G, et al. A new coronavirus associated with human respiratory disease in China. Nature. 2020;579(7798):265–9. https://doi.org/10.1038/s41586-020-2008-3
doi: 10.1038/s41586-020-2008-3
pubmed: 32015508
pmcid: 7094943
Li C-x, Chen J, Lv S-k, Li J-h, Li L-l, Hu X. Whole-transcriptome RNA sequencing reveals significant differentially expressed mRNAs. miRNAs, and lncRNAs and related regulating biological pathways in the peripheral blood of COVID-19 patients. Mediat Inflamm. 2021;2021:6635925. https://doi.org/10.1155/2021/6635925 .
doi: 10.1155/2021/6635925
Gagliardi S, Poloni ET, Pandini C, Garofalo M, Dragoni F, Medici V, et al. Detection of SARS-CoV-2 genome and whole transcriptome sequencing in frontal cortex of COVID-19 patients. Brain Behav Immun. 2021;97:13–21. https://doi.org/10.1016/j.bbi.2021.05.012
doi: 10.1016/j.bbi.2021.05.012
pubmed: 34022369
pmcid: 8132498
Al Heialy S, Hachim MY, Senok A, Gaudet M, Abou Tayoun A, Hamoudi R, et al. Regulation of angiotensin- converting enzyme 2 in obesity: implications for COVID-19. Front Physiol. 2020;11. https://doi.org/10.3389/fphys.2020.555039
Painter SD, Ovsyannikova IG, Poland GA. The weight of obesity on the human immune response to vaccination. Vaccine. 2015;33(36):4422–9. https://doi.org/10.1016/j.vaccine.2015.06.101
doi: 10.1016/j.vaccine.2015.06.101
pubmed: 26163925
pmcid: 4547886
Wang X, Zhao Y, Yan F, Wang T, Sun W, Feng N, et al. Viral and host transcriptomes in SARS-CoV-2-Infected human lung cells. J Virol. 2021;95(18):e00600–21. https://doi.org/10.1128/JVI.00600-21
doi: 10.1128/JVI.00600-21
pubmed: 34106002
pmcid: 8387032
Aguilar-Lemarroy A, López-Uribe A, Sánchez-Corona J, Jave-suárez LF. Severe acute respiratory syndrome coronavirus 2 ORF3a induces the expression of ACE2 in oral and pulmonary epithelial cells and the food supplement Vita Deyun® diminishes this effect. Exp Ther Med. 2021;21(5):485. https://doi.org/10.3892/etm.2021.9916
doi: 10.3892/etm.2021.9916
pubmed: 33790994
pmcid: 8005676
Sun C, Sun Y, Wu P, Ding W, Wang S, Li J, et al. Longitudinal multi-omics transition associated with fatality in critically ill COVID-19 patients. Intensive Care Medicine Experimental. 2021;9(1):13. https://doi.org/10.1186/s40635-021-00373-z
doi: 10.1186/s40635-021-00373-z
pubmed: 33721144
pmcid: 7957447
Blanco-Melo D, Nilsson-Payant BE, Liu W-C, Uhl S, Hoagland D, Møller R, et al. Imbalanced host response to SARS-CoV-2 drives development of COVID-19. Cell. 2020;181(5):1036–45.e9.
doi: 10.1016/j.cell.2020.04.026
pubmed: 32416070
pmcid: 7227586
Gill SE, dos Santos CC, O’Gorman DB, Carter DE, Patterson EK, Slessarev M, et al. Transcriptional profiling of leukocytes in critically ill COVID19 patients: implications for interferon response and coagulation. Intensive Care Medicine Experimental. 2020;8(1):75. https://doi.org/10.1186/s40635-020-00361-9
doi: 10.1186/s40635-020-00361-9
pubmed: 33306162
pmcid: 7729690
Liao M, Liu Y, Yuan J, Wen Y, Xu G, Zhao J, et al. Single-cell landscape of bronchoalveolar immune cells in patients with COVID-19. Nat Med. 2020;26(6):842–4. https://doi.org/10.1038/s41591-020-0901-9
doi: 10.1038/s41591-020-0901-9
pubmed: 32398875
Lieberman NAP, Peddu V, Xie H, Shrestha L, Huang M-L, Mears MC, et al. In vivo antiviral host transcriptional response to SARS-CoV-2 by viral load, sex, and age. PLoS Biol. 2020;18(9):e3000849. https://doi.org/10.1371/journal.pbio.3000849
doi: 10.1371/journal.pbio.3000849
pubmed: 32898168
pmcid: 7478592
Liu C, Martins AJ, Lau WW, Rachmaninoff N, Chen J, Imberti L, et al. Time-resolved systems immunology reveals a late juncture linked to fatal COVID-19. Cell. 2021;184(7):1836–57.e22.
doi: 10.1016/j.cell.2021.02.018
pubmed: 33713619
pmcid: 7874909
Aromataris E, Munn Z, editors. JBI manual for evidence synthesis. JBI, 2020. Available from https://synthesismanual.jbi.global . https://doi.org/10.46658/JBIMES-20-01
Huang da W, Sherman BT, Lempicki RA. Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources. Nat Protoc. 2009;4(1):44–57. https://doi.org/10.1038/nprot.2008.211
doi: 10.1038/nprot.2008.211
pubmed: 19131956
Sherman BT, Hao M, Qiu J, Jiao X, Baseler MW, Lane HC, et al. DAVID: a web server for functional enrichment analysis and functional annotation of gene lists (2021 update). Nucleic Acids Res. 2022;50(W1):W216–21. https://doi.org/10.1093/nar/gkac194
doi: 10.1093/nar/gkac194
pubmed: 35325185
pmcid: 9252805
Szklarczyk D, Gable AL, Nastou KC, Lyon D, Kirsch R, Pyysalo S, et al. The STRING database in 2021: customizable protein-protein networks, and functional characterization of user-uploaded gene/measurement sets. Nucleic Acids Res. 2021;49(D1):D605–d12. https://doi.org/10.1093/nar/gkaa1074
doi: 10.1093/nar/gkaa1074
pubmed: 33237311
Shannon P, Markiel A, Ozier O, Baliga NS, Wang JT, Ramage D, et al. Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res. 2003;13(11):2498–504. https://doi.org/10.1101/gr.1239303
doi: 10.1101/gr.1239303
pubmed: 14597658
pmcid: 403769
Bader GD, Hogue CW. An automated method for finding molecular complexes in large protein interaction networks. BMC Bioinformatics. 2003;4:2. https://doi.org/10.1186/1471-2105-4-2
doi: 10.1186/1471-2105-4-2
pubmed: 12525261
pmcid: 149346
Zhang H, Alford T, Liu S, Zhou D, Wang J. Influenza virus causes lung immunopathology through down-regulating PPARγ activity in macrophages. Front Immunol. 2022;13. https://doi.org/10.3389/fimmu.2022.958801
Li S, He C, Nie H, Pang Q, Wang R, Zeng Z, et al. G Allele of the rs1801282 polymorphism in PPARγ gene confers an increased risk of obesity and hypercholesterolemia, while T allele of the rs3856806 polymorphism displays a protective role against dyslipidemia: a systematic review and meta-analysis. Front Endocrinol. 2022;13. https://doi.org/10.3389/fendo.2022.919087
Sikder K, Shukla SK, Patel N, Singh H, Rafiq K. High Fat Diet upregulates fatty acid oxidation and ketogenesis via intervention of PPAR-γ. Cell Physiol Biochem. 2018;48(3):1317–31. https://doi.org/10.1159/000492091
doi: 10.1159/000492091
pubmed: 30048968
Janani C, Ranjitha Kumari BD. PPAR gamma gene– a review. Diabetes & Metabolic Syndrome. Clin Res Reviews. 2015;9(1):46–50. https://doi.org/10.1016/j.dsx.2014.09.015
doi: 10.1016/j.dsx.2014.09.015
Bassaganya-Riera J, Song R, Roberts PC, Hontecillas R. PPARγ activation as an anti-inflammatory therapy for respiratory virus infections. Viral Immunol. 2010;23(4):343–52. https://doi.org/10.1089/vim.2010.0016
doi: 10.1089/vim.2010.0016
pubmed: 20712478
Yang J, Chen C, Chen W, et al. Proteomics and metabonomics analyses of Covid-19 complications in patients with pulmonary fibrosis. Sci Rep. 2021;11(1):14601. https://doi.org/10.1038/s41598-021-94256-8 . Published 2021 Jul 16.
doi: 10.1038/s41598-021-94256-8
pubmed: 34272434
pmcid: 8285535
Pagliari F, Marafioti MG, Genard G, et al. ssRNA virus and host lipid rearrangements: is there a role for lipid droplets in SARS-CoV-2 infection? Front Mol Biosci. 2020;7:578964. https://doi.org/10.3389/fmolb.2020.578964 . Published 2020 Oct 8.
doi: 10.3389/fmolb.2020.578964
pubmed: 33134318
pmcid: 7579428
Kim K, Calabrese P, Wang S, Qin C, Rao Y, Feng P, et al. The roles of APOBEC-mediated RNA editing in SARS-CoV-2 mutations, replication and fitness. Sci Rep. 2022;12(1):14972. https://doi.org/10.1038/s41598-022-19067-x
doi: 10.1038/s41598-022-19067-x
pubmed: 36100631
pmcid: 9470679
Moris A, Murray S, Cardinaud S. AID and APOBECs span the gap between innate and adaptive immunity. Front Microbiol. 2014;5. https://doi.org/10.3389/fmicb.2014.00534
Khan MA, Goila-Gaur R, Kao S, Miyagi E, Walker RC, Strebel K. Encapsidation of APOBEC3G into HIV-1 virions involves lipid raft association and does not correlate with APOBEC3G oligomerization. Retrovirology. 2009;6(1):99. https://doi.org/10.1186/1742-4690-6-99
doi: 10.1186/1742-4690-6-99
pubmed: 19886996
pmcid: 2776001
Ma J, Li X, Xu J, Zhang Q, Liu Z, Jia P, et al. The cellular source for APOBEC3G’s incorporation into HIV-1. Retrovirology. 2011;8(1):2. https://doi.org/10.1186/1742-4690-8-2
doi: 10.1186/1742-4690-8-2
pubmed: 21211018
pmcid: 3024284
Regino-Zamarripa NE, Ramírez-Martínez G, Jiménez-Álvarez LA, Cruz-Lagunas A, Gómez-García IA, Ignacio-Cortés S, et al. Differential leukocyte expression of IFITM1 and IFITM3 in patients with severe pandemic influenza A(H1N1) and COVID-19. J Interferon Cytokine Res. 2022;42(8):430–43. https://doi.org/10.1089/jir.2022.0036
doi: 10.1089/jir.2022.0036
pubmed: 35708622
pmcid: 9422779
Lee J, Robinson ME, Ma N, Artadji D, Ahmed MA, Xiao G, et al. IFITM3 functions as a PIP3 scaffold to amplify PI3K signalling in B cells. Nature. 2020;588(7838):491–7. https://doi.org/10.1038/s41586-020-2884-6
doi: 10.1038/s41586-020-2884-6
pubmed: 33149299
pmcid: 8087162
Palatini M, Müller SF, Kirstgen M, Leiting S, Lehmann F, Soppa L, et al. IFITM3 interacts with the HBV/HDV receptor NTCP and modulates virus entry and infection. Viruses. 2022;14(4):727. https://doi.org/10.3390/v14040727
doi: 10.3390/v14040727
pubmed: 35458456
pmcid: 9027621
Rahman K, Datta SAK, Beaven AH, Jolley AA, Sodt AJ, Compton AA. Cholesterol binds the amphipathic helix of IFITM3 and regulates antiviral activity. J Mol Biol. 2022;434(19):167759. https://doi.org/10.1016/j.jmb.2022.167759
doi: 10.1016/j.jmb.2022.167759
pubmed: 35872070
pmcid: 9342930
Franz S, Pott F, Zillinger T, Schüler C, Dapa S, Fischer C, et al. Human IFITM3 restricts Chikungunya virus and Mayaro virus infection and is susceptible to virus-mediated counteraction. Life Sci Alliance. 2021;4(7):e202000909. https://doi.org/10.26508/lsa.202000909
doi: 10.26508/lsa.202000909
pubmed: 34078739
pmcid: 8200292
Chen YM, Zheng Y, Yu Y, et al. Blood molecular markers associated with COVID-19 immunopathology and multi-organ damage. EMBO J. 2020;39(24):e105896. https://doi.org/10.15252/embj.2020105896
doi: 10.15252/embj.2020105896
pubmed: 33140861
pmcid: 7737620
Samad A, Jafar T, Rafi JH. Identification of angiotensin-converting enzyme 2 (ACE2) protein as the potential biomarker in SARS-CoV-2 infection-related lung cancer using computational analyses. Genomics. 2020;112(6):4912–23. https://doi.org/10.1016/j.ygeno.2020.09.002
doi: 10.1016/j.ygeno.2020.09.002
pubmed: 32916258