Unraveling metabolic signatures in SARS-CoV-2 variant infections using multiomics analysis

Abstract

Introduction: The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants, notably delta and omicron, has significantly accelerated the global pandemic, worsening conditions worldwide. However, there is a lack of research concerning the molecular mechanisms related to immune responses and metabolism induced by these variants.

Methods: Here, metabolomics combined with transcriptomics was performed to elucidate the immunometabolic changes in the lung of hamsters infected with delta and omicron variants.

Results: Both variants caused acute inflammation and lung pathology in intranasally infected hamsters. Principal component analysis uncovered the delta variant significantly altered lung metabolite levels between the pre- and post-infection states. Additionally, metabolic pathways determined by assessment of metabolites and genes in lung revealed significant alterations in arginine biosynthesis, glutathione metabolism, and tryptophan metabolism upon infection with both variants and closely linked to inflammatory cytokines, indicating immune activation and oxidative stress in response to both variants. These metabolic changes were also evident in the serum, validating the presence of systemic alterations corresponding to those identified in lung. Notably, the delta variant induced a more robust metabolic regulation than the omicron variant.

Discussion: The study suggests that multi-omics is a valuable approach for understanding immunometabolic responses to infectious diseases, and providing insights for effective treatment strategies.

Keywords: SARS-CoV-2; immune response; metabolic pathway; metabolomics; transcriptomics.

Figure 1

Hamsters infected with the delta and omicron variants exhibit an acute inflammatory response and lung pathology. (A) Study design of the Golden Syrian hamster infection model. Hamsters (n=5 per group) were intranasally infected with SARS-CoV-2 variants, specifically delta and omicron. The hamsters were sacrificed at 0 dpi, 4 dpi, and 7 dpi to obtain lung tissues for metabolic and transcriptomic analysis. (B) Body weight changes in hamsters after viral infection. Significant differences in delta and omicron variant groups compared to control group on each day are denoted using Mann-Whitney test by *p < 0.05, **p < 0.01, ****p < 0.0001. (C) The fold changes of lung viral load after delta and omicron infections compared to control group. (D) The histopathological lesions in the lungs assessed by using hematoxylin and eosin (H&E) staining.

Figure 2

Lung metabolite profile of Golden Syrian hamsters infected with the delta and omicron variants. (A) Principal component analysis (PCA) score plots of lung tissue analysis shown for positive ion mode (delta variant: R²X = 0.482, Q² = 0.257; omicron variant: R²X = 0.621, Q² = 0.318) and for negative ion mode (delta variant: R²X = 0.606, Q² = 0.281; omicron variant: R²X = 0.608, Q² = 0.281). (B) Heat map derived for 88 identified lung metabolites showing the metabolite content changes over time after infection. (C) Pathway enrichment analysis of lung metabolites for infection with each variant, revealing the most associated metabolic pathways via pathway impact and adjusted p value analysis.

Figure 3

Metabolic and transcriptomic alterations in the key metabolic pathways after delta and omicron infection. The log2-fold changes in metabolite levels within significantly altered metabolic pathways after delta and omicron infections compared to those at the pre-infection state in lung tissue (A, B) and serum (C, D). Significance of differences between pre- and post-infection in each group determined using Tukey’s multiple comparisons post hoc test is denoted by *p < 0.05, **p < 0.01, ***p < 0.001 for the delta group and #p < 0.05, ##p < 0.01, ###p < 0.001 for the omicron group. The log2-fold changes in gene expression within significantly altered metabolic pathways after delta (E) and omicron (F) infections compared to those at the pre-infection state. Significance of differences between pre- and post-infection in each group determined using DEG analysis is denoted by *q < 0.05, **q < 0.01, ***q < 0.001 for the delta group.

Figure 4

Integrated metabolic pathways combined with metabolites and genes from lungs infected with the delta and omicron variants. (A) Arginine biosynthesis. (B) Glutathione metabolism. (C) Tryptophan metabolism. Colored red or blue letters represent increased or decreased levels after infection for the delta variant at 7 dpi or the omicron variant at 4 dpi compared to those at 0 dpi, respectively. The pathways were modified from those in the KEGG database (http://www.genome.jp/kegg/). Significance of differences between pre- and post-infection in each group determined by using Tukey’s multiple comparisons post hoc test for metabolite levels (*p < 0.05, **p < 0.01, ***p < 0.001 for the delta group; #p < 0.05 for the omicron group) and for DEGs (*q < 0.05, **q < 0.01, ***q < 0.001 for the delta group).

Figure 5

Correlation networks of inflammatory cytokines with metabolites and genes in the key metabolic pathways. Co-expression network analyses of the key regulatory metabolites and genes assigned to arginine biosynthesis, glutathione metabolism and tryptophan metabolism for the delta (A) and omicron (B) variants. Octagons, circles, squares and rhombi indicate metabolic pathways, metabolites, genes and cytokines, respectively. Edges depict the association between each node, with red or blue denoting positive or negative correlations, respectively. The thickness of each edge represents the strength of the correlation between factors.