Understanding metabolic alterations after SARS-CoV-2 infection: insights from the patients' oral microenvironmental metabolites

Abstract

Background: Coronavirus disease 2019 is a type of acute infectious pneumonia and frequently confused with influenza since the initial symptoms. When the virus colonized the patient's mouth, it will cause changes of the oral microenvironment. However, few studies on the alterations of metabolism of the oral microenvironment affected by SARS-CoV-2 infection have been reported. In this study, we explored metabolic alterations of oral microenvironment after SARS-CoV-2 infection.

Methods: Untargeted metabolomics (UPLC-MS) was used to investigate the metabolic changes between oral secretion samples of 25 COVID-19 and 30 control participants. To obtain the specific metabolic changes of COVID-19, we selected 25 influenza patients to exclude the metabolic changes caused by the stress response of the immune system to the virus. Multivariate analysis (PCA and PLS-DA plots) and univariate analysis (students' t-test) were used to compare the differences between COVID-19 patients and the controls. Online hiplot tool was used to perform heatmap analysis. Metabolic pathway analysis was conducted by using the MetaboAnalyst 5.0 web application.

Results: PLS-DA plots showed significant separation of COVID-19 patients and the controls. A total of 45 differential metabolites between COVID-19 and control group were identified. Among them, 35 metabolites were defined as SARS-CoV-2 specific differential metabolites. Especially, the levels of cis-5,8,11,14,17-eicosapentaenoic acid and hexanoic acid changed dramatically based on the FC values. Pathway enrichment found the most significant pathways were tyrosine-related metabolism. Further, we found 10 differential metabolites caused by the virus indicating the body's metabolism changes after viral stimulation. Moreover, adenine and adenosine were defined as influenza virus-specific differential metabolites.

Conclusions: This study revealed that 35 metabolites and tyrosine-related metabolism pathways were significantly changed after SARS-CoV-2 infection. The metabolic alterations of oral microenvironment in COVID-19 provided new insights into its molecular mechanisms for research and prognostic treatment.

Keywords: COVID-19; Influenza; Metabolic pathways; Metabolomics; Oral microenvironment.

Fig. 1

The workflow for data analysis of oral metabolomics of COVID-19

Fig. 2

PLS-DA score plot and cross-validation plot of metabolic profiling analysis. A PLS-DA score plot of Control, Influenza and COVID-19 group in positive mode. Green nodes: Control subjects, blue nodes: Influenza subjects, red nodes: COVID-19 subjects. B PLS-DA score plot of Control, Influenza and COVID-19 group in negative mode. Green nodes: Control subjects, blue nodes: Influenza subjects, red nodes: COVID-19 subjects. C PLS-DA score plot of Control and COVID-19 group in positive mode. Green nodes: Control subjects, red nodes: COVID-19 subjects. D PLS-DA score plot of Control and COVID-19 group in negative mode. Green nodes: Control subjects, red nodes: COVID-19 subjects. E Cross-validation plot in positive mode. F Cross-validation plot in negative mode

Fig. 3

Identification, screening and classification of metabolites between COVID-19 and control group. A The venn diagrams of the different features obtained with VIP > 1, p < 0.5 and FC ≥ 1.2 or ≤ 0.83 in different groups, 35 metabolites showed no significant differences in control and influenza, 10 metabolites showed significant differences in control and influenza. B Classification donut chart of 35 identified differential metabolites. C The heatmap of 35 metabolites dramatically changed in COVID-19 and control. D The box plots of cis-5,8,11,14,17-eicosapentaenoic acid, nicotinuric acid, guanosine 5′-monophosphate and proline based on the FC value greater than 100 in COVID-19. Green: Control subjects, blue: Influenza subjects, red: COVID-19 subjects. E. The box plots of hexanoic acid, heptanoic acid, 17α-hydroxyprogesterone and hexanoylcarnitine were screened out based on the FC value less than 0.02 in COVID-19. Green: Control subjects, blue: Influenza subjects, red: COVID-19 subjects

Fig. 4

Metabolic pathways in COVID-19, especially tyrosine-related metabolism pathway. A Metabolic topological analysis diagram of COVID-19 metabolomics. B The box plots of L-glutamic acid, proline and leucylproline in control, influenza and COVID-19. Green: Control subjects, blue: Influenza subjects, red: COVID-19 subjects. C The interactive network of tyrosine-related metabolic pathways. D The box plots of 4-hydroxyphenylpyruvic acid, dopamine, epinephrine, and 3-methoxytyramine in control, influenza and COVID-19. Green: Control subjects, blue: Influenza subjects, red: COVID-19 subjects. *p < 0.05, **p < 0.01, *** p < 0.0001

Fig. 5

Changes in metabolites caused by the body's feedback to the virus. A Relative amounts of 10 metabolites in control, influenza and COVID-19 might reflect the body’s feedback after virus infection. B PLS-DA score plot of Influenza and COVID-19 group in positive mode. Blue nodes: Influenza subjects, red nodes: COVID-19 subjects. C PLS-DA score plot of Influenza and COVID-19 group in negative mode. Blue nodes: Influenza subjects, red nodes: COVID-19 subjects. D Cross-validation plot in positive mode. E Cross-validation plot in positive mode. F Relative amounts of 2 metabolites significantly decreased in Influenza group. *p < 0.05, **p < 0.01, ***p < 0.0001