Welcome to Francis Academic Press

International Journal of Frontiers in Medicine, 2023, 5(7); doi: 10.25236/IJFM.2023.050704.

Metabolomics in the Research of Viral Infectious Disease Mechanisms

Author(s)

Tingting Zhang1, Pengbo Yu2, Yaping Li3, Yufeng Zhang4, Huiling Deng1,5

Corresponding Author:
Huiling Deng
Affiliation(s)

1School of Public Health, Shaanxi University of Chinese Medicine, Xianyang, China

2Department of Virus Disease Prevention and Control, Shaanxi Provincial Centre for Disease Control and Prevention, Xi'an, China

3Infectious Disease, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, China

4Infectious Disease, Xi'an Children’s Hospital, Xi'an, China

5Childhood Infectious Disease, Xi'an Central Hospital, Xi'an, China

Abstract

Viral invasion of the body causes metabolic changes involving pathways such as gluconeogenesis, amino acid metabolism, lipid metabolism, the TCA cycle, and energy metabolism and affects vital bodily processes such as nucleic acid, protein, and lipid synthesis. During antiviral therapy, the immune response is closely related to the metabolic balance, and numerous metabolites, including glycolytic metabolites, amino acids, and nucleotides, can influence the immune response. Monitoring metabolites by metabolomics technology can aid in continuously optimizing the efficacy of medications used to treat viral infectious diseases. It also provides diagnostic and prognostic value in the clinic, making it a valuable technological platform. This review concentrates on applying metabolomics technologies to study viral infectious disease pathogenesis and treatment.

Keywords

Metabolomics; Viral Infectious Diseases; Hand-foot-mouth disease (HFMD); Influenza; Coronavirus disease 2019 (COVID-19)

Cite This Paper

Tingting Zhang, Pengbo Yu, Yaping Li, Yufeng Zhang, Huiling Deng. Metabolomics in the Research of Viral Infectious Disease Mechanisms. International Journal of Frontiers in Medicine (2023), Vol. 5, Issue 7: 19-26. https://doi.org/10.25236/IJFM.2023.050704.

References

[1] Ma J, Deng Y, Zhang M, et al. The role of multi-omics in the diagnosis of COVID-19 and the prediction of new therapeutic targets[J]. Virulence, 2022, 13(1): 1101-1110. 

[2] Yang Qianchun, Li S-N, Chen Shuo, et al. The use of metabolomics and its research progress[J]. Journal of Clinical Rational Drug Use, 2020, 13(2): 176-178. 

[3] Liu W, Kou G. Overview of metabolomics research techniques and their applications[J]. Teaching Biology, 2018, 9(2): 4. 

[4] Shivani K Thaker, James Ch'ng, Heather R Christofk. Viral hijacking of cellular metabolism[J]. Bmc Biology, 2019, 17(1): 1-15. 

[5] Joshua Munger, Sunil U Bajad, Hilary A Coller, et al. Dynamics of the cellular metabolome during human cytomegalovirus infection[J]. Plos Pathogens, 2006, 2(12): e132. 

[6] Asim M, Sathian B, Banerjee I, et al. A contemporary insight of metabolomics approach for COVID-19: Potential for novel therapeutic and diagnostic targets[J]. Nepal Journal of Epidemiology, 2020, 10(4): 923. 

[7] Danuta Dudzik, Cecilia Barbas-Bernardos, Antonia García, et al. Quality assurance procedures for mass spectrometry untargeted metabolomics. a review[J]. Journal of Pharmaceutical and Biomedical Analysis, 2018, 147: 149-173. 

[8] Nunes E C, Canuto G A B. Metabolomics applied in the study of emerging arboviruses caused by Aedes aegypti mosquitoes: A review[J]. Electrophoresis, 2020, 41(24): 2102-2113. 

[9] Tian H., Tax G. Hou. Advances in mass spectrometry-based metabolomics analysis[J]. Biotechnology Bulletin, 2021, 37(1): 24-31. 

[10] Katharina A Mayer, Johannes Stöckl, Gerhard J Zlabinger, et al. Hijacking the supplies: metabolism as a novel facet of virus-host interaction[J]. Frontiers in Immunology, 2019: 1533. 

[11] Adriano Queiroz, Isabella Fernanda Dantas Pinto, Maricélia Lima, et al. Lipidomic analysis reveals serum alteration of plasmalogens in patients infected with ZIKA virus[J]. Frontiers in Microbiology, 2019, 10: 753. 

[12] Nunes E C, Filippis A M B, Pereira T E S, et al. Untargeted metabolomics insights into newborns with congenital Zika infection[J]. Pathogens, 2021, 10(4): 468. 

[13] Pang H, Jiang Y, Li J, et al. Aberrant NAD+ metabolism underlies Zika virus–induced microcephaly[J]. Nature Metabolism, 2021, 3(8): 1109-1124. 

[14] Jinjun Shan, Wenjuan Qian, Cunsi Shen, et al. High-resolution lipidomics reveals dysregulation of lipid metabolism in respiratory syncytial virus pneumonia mice[J]. Rsc Advances, 2018, 8(51): 29368-29377. 

[15] Turi K N, Romick-Rosendale L, Gebretsadik T, et al. Using urine metabolomics to understand the pathogenesis of infant respiratory syncytial virus (RSV) infection and its role in childhood wheezing[J]. Metabolomics, 2018, 14: 1-13. 

[16] Zhang X, Peng D, Zhang X, et al. Serum metabolomic profiling reveals important difference between infants with and without subsequent recurrent wheezing in later childhood after RSV bronchiolitis[J]. Apmis, 2021, 129(3): 128-137. 

[17] JE Kyle, KE Burnum-Johnson, JP Wendler, et al. Plasma lipidome reveals critical illness and recovery from human Ebola virus disease[J]. Proceedings of the National Academy of Sciences, 2019, 116(9): 3919-3928. 

[18] Shanmuganathan M, Sarfaraz M O, Kroezen Z, et al. A cross-platform metabolomics comparison identifies serum metabolite signatures of liver fibrosis progression in chronic hepatitis c patients[J]. Frontiers in Molecular Biosciences, 2021, 8: 676349. 

[19] Kumari S, Ali A, Roome T, et al. Metabolomics approach to understand the hepatitis C virus induced hepatocellular carcinoma using LC-ESI-MS/MS[J]. Arabian Journal of Chemistry, 2021, 14(1): 102907. 

[20] Wu Yunfeng, Liu Qing. Analysis of influenza epidemic characteristics before and after the prevention and control of novel coronavirus infection[J]. Laboratory Medicine and Clinics, 2023, 20(8): 1025-1028, 1032. 

[21] Tian X, Zhang K, Min J, et al. Metabolomic analysis of influenza A virus A/WSN/1933 (H1N1) infected A549 cells during first cycle of viral replication[J]. Viruses, 2019, 11(11): 1007. 

[22] Tao P, Xiao W, Zhou P, et al. Metabolic profiles in Madin–Darby canine kidney cell lines infected with H3N2 canine influenza viruses[J]. Viral Immunology, 2020, 33(9): 573-584. 

[23] Song LJ. Correlation between disease severity and fatty acid metabolism after H7N9 infection[D]. Tianjin Medical University, 2019, 000547

[24] Zhang Jing. Analysis of epidemiological trends and dynamic series of pathogenic changes of hand, foot and mouth disease in China from 2008-2017[J]. Chinese Journal of Epidemiology, 2019, 40(2): 147-154. 

[25] Ren Minrui, Cui Jinzhao, Nie Taoran, et al. Epidemiological characteristics of severe cases of hand, foot and mouth disease in China from 2008-2018[J]. Chinese Journal of Epidemiology, 2020, 41(11): 1802-1807. 

[26] Huichun Shi, Siyuan Liu, Zhimi Tan, et al. Proteomic and metabonomic analysis uncovering Enterovirus A71 reprogramming host cell metabolic pathway[J]. Proteomics, 2022: 2200362. 

[27] Jinzhun WU, Caiming WU, Bizhen ZHU, et al. Metabolomics study on biomarkers of hand, foot and mouth disease[J]. Chinese Pediatric Emergency Medicine, 2019: 895-900. 

[28] Xu Rui. Metabolomics in childhood dwarfism and hand, foot and mouth disease_Xu Rui [D]. Xiamen University, 2019

[29] Cheng Lu, Xinru Liu, Xiaorong Ding, et al. A metabolomics profiling study in hand-foot-and-mouth disease and modulated pathways of clinical intervention using liquid chromatography/quadrupole time-of-flight mass spectrometry[J]. Evidence-based Complementary and Alternative Medicine, 2013, 2013. 

[30] Zijiao Zou, Jessica Oi-Ling Tsang, Bingpeng Yan, et al. Metabolic profiling reveals significant perturbations of intracellular glucose homeostasis in enterovirus-infected cells[J]. Metabolites, 2020, 10(8): 302. 

[31] Tiffany Thomas, Davide Stefanoni, Julie A Reisz, et al. COVID-19 infection alters kynurenine and fatty acid metabolism, correlating with IL-6 levels and renal status[J]. Jci Insight, 2020, 5(14). 

[32] Bo Shen, Xiao Yi, Yaoting Sun, et al. Proteomic and metabolomic characterization of COVID-19 patient sera[J]. Cell, 2020, 182(1): 59-72. e15. 

[33] Krishnan S, Nordqvist H, Ambikan A T, et al. Metabolic perturbation associated with COVID-19 disease severity and SARS-CoV-2 replication[J]. Molecular & Cellular Proteomics, 2021, 20. 

[34] Nan Xiao, Meng Nie, Huanhuan Pang, et al. Integrated cytokine and metabolite analysis reveals immunometabolic reprogramming in COVID-19 patients with therapeutic implications[J]. Nature Communications, 2021, 12(1): 1-13. 

[35] Yang Z, Wu D, Lu S, et al. Plasma metabolome and cytokine profile reveal glycylproline modulating antibody fading in convalescent COVID-19 patients[J]. Proc Natl Acad Sci U S A, 2022, 119(34): e2117089119. 

[36] Miriam Sindelar, Ethan Stancliffe, Michaela Schwaiger-Haber, et al. Longitudinal metabolomics of human plasma reveals prognostic markers of COVID-19 disease severity[J]. Cell Reports Medicine, 2021, 2(8): 100369. 

[37] Snider J M, You J K, Wang X, et al. Group IIA secreted phospholipase A2 plays a central role in the pathobiology of COVID-19[J]. MedRxiv, 2021: 2021.02. 22.21252237. 

[38] Jeany Delafiori, Luiz Claudio Navarro, Rinaldo Focaccia Siciliano, et al. Covid-19 automated diagnosis and risk assessment through metabolomics and machine learning[J]. Analytical Chemistry, 2021, 93(4): 2471-2479. 

[39] Shen Li, Feiyang Ma, Tomohiro Yokota, et al. Metabolic reprogramming and epigenetic changes of vital organs in SARS-CoV-2-induced systemic toxicity[J]. Jci Insight, 2021, 6(2). 

[40] Halef O Doğan, Onur Şenol, Serkan Bolat, et al. Understanding the pathophysiological changes via untargeted metabolomics in COVID- 19 patients[J]. Journal of Medical Virology, 2021, 93(4): 2340-2349. 

[41] Di Wu, Ting Shu, Xiaobo Yang, et al. Plasma metabolomic and lipidomic alterations associated with COVID-19[J]. National Science Review, 2020, 7(7): 1157-1168. 

[42] Fraser D D, Slessarev M, Martin C M, et al. Metabolomics profiling of critically ill coronavirus disease 2019 patients: identification of diagnostic and prognostic biomarkers[J]. Critical Care Explorations, 2020, 2(10). 

[43] Sofia Appelberg, Soham Gupta, Sara Svensson Akusjärvi, et al. Dysregulation in Akt/mTOR/HIF-1 signaling identified by proteo-transcriptomics Dysregulation in Akt/mTOR/HIF-1 signaling identified by proteo-transcriptomics of SARS-CoV-2 infected cells[J]. Emerging Microbes & Infections, 2020, 9(1): 1748-1760. 

[44] Jin-Wen Song, Sin Man Lam, Xing Fan, et al. Omics-driven systems interrogation of metabolic dysregulation in COVID-19 pathogenesis[J]. Cell Metabolism, 2020, 32(2): 188-202. e5.