Integrated metabolomics and transcriptomics analyses reveal changes in metabolites and their associated gene expression in the blood of patients with recurrent HSV‑2 genital herpes

Introduction

Herpes simplex virus (HSV), including types HSV-1 and HSV-2, is the primary agent of genital herpes (GH) and is a globally prevalent virus. HSV-1 and HSV-2 are large double-stranded DNA viruses that belong to the Herpesviridae family, which can be found in several populations, in both urban and remote areas (1,2). HSV-1 commonly causes painful orofacial herpes, as well as life-threatening meningitis, keratitis, encephalitis and neonatal infections (3). GH, caused by HSV-1 or HSV-2, is a prevalent and highly communicable sexually transmitted infection, which is commonly characterized by recurrent, self-limited genital ulcers (4,5). Notably, GH is associated with notable psychological and physiological burdens on affected individuals. In addition to the acute symptoms, GH commonly results in emotional, social, relational and sexual distress. However, evidence regarding the most effective interventions for improving health-related quality of life is still lacking (6). Both HSV-2 and HSV-1 can cause genital ulcers, with HSV-2 being the predominant sexually transmitted type and a major risk factor for increased human immunodeficiency virus 1 (HIV-1) acquisition during co-infection (7–9). Although there is currently no cure, antiviral therapies such as acyclovir can improve symptoms, decrease the frequency of outbreaks, and reduce the risk of transmission to partners (10). Therefore, a comprehensive understanding of the biological mechanisms underlying GH recurrence is essential for improving clinical management and treatment strategies.

Metabolism, encompassing glycolysis, oxidative phosphorylation (OXPHOS) and fatty acid oxidation metabolic pathways, can affect the phenotypes and functions of immune cells. Metabolic regulation of the immune system serves a crucial role in the development and progression of numerous diseases, including cancer, autoimmune disorders and metabolic conditions (11–13). Alterations in metabolite profiles reflect physiological states, and also provide critical insights into cellular functions, tissue metabolism and disease progression (14). Advancements in metabolomics, the comprehensive study of metabolites within biological systems, have enabled the identification of disease-specific pathophysiological characteristics (14–17). Therefore, the present study aimed to investigate serum metabolite changes in patients with recurrent HSV-2 GH, thus offering novel insights into its pathogenesis.

Based on the aforementioned evidence linking metabolism, immunity and disease pathogenesis (10–13), it was hypothesized that metabolic alterations could contribute to GH recurrence via modulating immune cell function. To evaluate this hypothesis, a comprehensive analysis integrating metabolomics, transcriptomics and single-cell RNA-sequencing (scRNA-seq) was carried out to identify metabolic pathways associated with HSV-2 GH recurrence. Through these comprehensive analyses, the current study aimed to uncover the potential molecular mechanisms underlying GH pathogenesis, and to identify novel biomarkers and therapeutic targets.

Materials and methods

Sample preparation

Blood samples were collected from 14 patients with recurrent HSV-2 GH and 14 healthy volunteers at Sir Run Run Shaw Hospital (Hangzhou, China) between March and June 2024. All individuals provided written informed consent prior to study enrollment. For untargeted metabolomics analysis, serum samples were collected after centrifugation at 12,000 × g and 4°C for 15 min, and were stored at −80°C. Peripheral blood mononuclear cells (PBMCs) were isolated through density gradient centrifugation at 400 × g and 25°C for 30 min, and were utilized for RNA-seq and scRNA-seq. To control for potential hormonal confounding factors, this study exclusively enrolled female participants. The inclusion criteria for patients with GH were as follows: Female participants, aged 18-35 years (mean ± SD, 25.9±4.8 years; median, 25 years); clinically confirmed recurrent GH with HSV-2 PCR positivity and ≥3 annual recurrences; absence of comorbidities; and no prior HSV vaccination. The exclusion criteria were as follows: Pregnant women; treatment with antiviral medications or immunosuppressants within the past 2 weeks; and those with any history of HSV vaccination, diabetes, metabolic syndrome or autoimmune diseases. The inclusion criteria for the participants in the healthy control (HC) group were: Female participants, aged 18-35 years (mean ± SD, 26.6±4.9 years; median, 27 years); no history of GH; negative for HSV infection; and no prior HSV vaccination. The demographic and clinical characteristics of the study participants are listed in Table SI.

Untargeted metabolomics profiling

Serum samples were stored at −80°C and untargeted metabolomics profiling was performed by LC-Bio Technologies (Hangzhou) Co., Ltd. Samples were randomized based on GH and HC. Following centrifugation at 13,800 × g for 15 min at 4°C, the supernatant was carefully collected into fresh glass vials for subsequent analysis. For quality control (QC) purposes, an aliquot from each biological replicate was pooled to create a representative QC sample.

Chromatographic separation was performed using a Thermo Vanquish Flex UPLC system (Thermo Fisher Scientific, Inc.) equipped with an ACQUITY UPLC T3 column (100×2.1 mm, 1.8 µm; Waters Corporation) maintained at 40°C with a constant flow rate of 0.35 ml/min, using mobile phase A (5 mmol/l ammonium acetate and 5 mmol/l acetic acid in water) and B (LC-MS grade acetonitrile) with the following gradient program: 0.0-0.5 min (99-1% B), 0.5-6.5 min (1-99% B), 6.5-8.0 min (99% B), 8.0-8.5 min (99-1% B) and 8.5-10.0 min (1% B). High-resolution mass spectrometry analysis was conducted on an Orbitrap Exploris 120 instrument (Thermo Fisher Scientific, Inc.) operating in alternating positive (+3,800 V) and negative (−3,400 V) ionization modes with optimized source parameters [sweep gas 1, auxiliary gas 12, sheath gas 50 (arbitrary units), source temperature 350°C]. Data-dependent acquisition was performed with full MS scans (70-1,050 m/z) at 60,000 resolution (200 m/z) using standard automatic gain control (AGC) and automatic maximum injection time, selecting the top four most intense precursor ions (intensity threshold >5,000) for MS/MS fragmentation at 15,000 resolution with custom AGC and injection time settings (6 sec dynamic exclusion). System stability was monitored by analyzing quality control samples every 10 injections, with inter-QC mass deviation used for batch correction.

The analysis was carried out on the Triple TOF 5,600 Plus high-resolution tandem mass spectrometer system (MS/MS; SCIEX) in both positive and negative ion modes. Chromatographic separation was achieved using an ultra-performance liquid chromatography system (SCIEX ExionLC 2.0+ system), and the resulting LC-MS data were preprocessed using XCMS software version 3.8.5 (https://github.com/sneumann/xcms). All data from the untargeted platform (semi-quantitative) were normalized based on the minimum level detected for each metabolite/run and were reported as log2 signal-to-noise ratios. Kyoto Encyclopedia of Genes and Genomes (KEGG) metabolic pathway enrichment analysis were performed using the MetaboAnalyst (https://www.metaboanalyst.ca/) database. The metabolomics data are listed in Table SII.

Total RNA extraction, library construction and bulk-RNA sequencing

Blood samples were collected from patients with recurrent HSV-2 GH and healthy volunteers. After density gradient centrifugation, the PBMC were immediately immersed in liquid nitrogen for freezing. The frozen samples were then thoroughly ground using a pre-cooled mortar. Subsequently, cells were lysed with 1 ml TRIzol® reagent (Invitrogen; Thermo Fisher Scientific, Inc.). Following the addition of 200 µl chloroform, the mixture was vigorously shaken for 15 sec, followed by incubation at room temperature for 2 min. The samples were then centrifuged at 12,000 × g for 15 min at 4°C, and the supernatant was transferred to a new tube. To precipitate RNA, each tube was supplemented with 0.5 ml isopropyl alcohol, followed by gently mixing prior to incubation at room temperature for 10 min. After a second centrifugation at 12,000 × g for 10 min at 4°C, the supernatant was discarded. The RNA pellet was then washed with 1 ml 75% ethanol and the supernatant was discarded following centrifugation at 7,500 × g for 5 min at 4°C. After air drying, total RNA was dissolved in DEPC-treated water.

For second-generation sequencing, libraries were prepared as previously described (18). In brief, RNA quantity and integrity were assessed using the Qubit™ 3.0 Fluorometer (cat. no. Q33216; Thermo Fisher Scientific, Inc.) and Agilent 5300 Fragment Analyzer System (cat. no. M5310AA; Agilent Technologies) respectively. RNA samples demonstrating high purity (A260/A280 ratio 1.8-2.2) and RNA integrity numbers >7.0 were selected for subsequent library preparation using Illumina-compatible protocols. mRNA was purified from 2 µg total RNA using mRNA Capture Beads 2.0 (cat. no. 12629ES; Shanghai Yeasen Biotechnology Co., Ltd.) through two rounds of poly(A) selection.

Purified mRNA was fragmented in magnesium-containing fragmentation buffer (cat. no. 12340ES97; Shanghai Yeasen Biotechnology Co., Ltd.) at 94°C for 5 min. First-strand cDNA was synthesized using random hexamer-primed reverse transcription (SuperScript™ IV Reverse Transcriptase; Thermo Fisher Scientific, Inc.). Second-strand cDNA was generated using a dUTP incorporation strategy with E. coli DNA Polymerase I, RNase H and dUTP solution (cat. no. 12340ES97; Shanghai Yeasen Biotechnology Co., Ltd.). Blunt-ended cDNA fragments were adenylated at 3′ ends using Klenow Fragment (3′-5′ exo-) and ligated to Illumina-compatible forked adapters containing T-overhangs. PCR products were size-selected (400±50 bp inserts) using Hieff NGS DNA Selection Beads (cat. no. 12601ES75; Shanghai Yeasen Biotechnology Co., Ltd.). Strand specificity was maintained through dUTP-based strand marking and uracil excision. Libraries were sequenced in 2×150 bp paired-end mode on an Illumina NovaSeq™ X Plus platform (LC-bio Technologies Hangzhou Co. Ltd.) following manufacturer-recommended protocols.

Differentially expressed gene (DEG) analysis

To identify DEGs between patients with GH and healthy volunteers, the ‘DESeq2’ R package (version 4.5; http://bioconductor.org/packages/release/bioc/html/DESeq2.html) in R (version 4.4.3; http://www.R-project.org/) was utilized. Genes showing log2 fold change of ≥1.0 and an adjusted P-value of <0.05 were considered significantly differentially expressed. The RNA-seq data are presented in Table SIII.

KEGG pathway enrichment analysis

KEGG (http://www.genome.jp/kegg/), a comprehensive database for understanding biological systems at the genomic and molecular levels, DEGs of scRNA-seq data was used for pathway enrichment analysis. This resource integrates genomic, chemical and systematic information on biological interactions, reactions and disease pathways.

Gene Set Enrichment Analysis (GSEA)

GSEA was performed based on the detected metabolites using KEGG metabolite sets (19). The analysis aims to identify significant pathways that are associated with the metabolite profiles. The criteria for selecting significant pathways were set as follows: Pathways with an absolute normalized enrichment score (|NES|) >1 and a P-value <0.05 were considered statistically significant. These thresholds help to filter out the most relevant pathways that show a strong association with the metabolic differences observed in the study.

scRNA-seq

scRNA-seq of PBMCs and neutrophils from GH (n=4) and healthy controls (n=4) was performed using the Chromium Single Cell 3′ Chip and 10× Genomics Chromium Single-Cell 3′ Kit v3 (10× Genomics, LC-Bio Technologies) as previously described (20). The sequencing data were then deposited in the Genome Sequence Archive for human database. Bioinformatics analysis utilized Cell Ranger (v7.1.0; 10× Genomics; http://www.10×genomics.com/support/software/cell-ranger) and Seurat (v4.3.0; Satija Lab; http://satijalab.org/seurat) for data processing, clustering, and differential expression analysis. Nonlinear dimensionality reduction was performed using t-distributed Stochastic Neighbor Embedding implemented in Seurat v4.3.0.

Reverse transcription-quantitative PCR (RT-qPCR)

Total RNA was isolated from PBMCs using TRIzol® Reagent (cat. no. 15596018CN; Invitrogen; Thermo Fisher Scientific, Inc.). cDNA was synthesized from 1 µg RNA using oligo dT primer and the PrimeScript RT PCR master mix Kit (cat. no. RR036A; Takara Biotechnology Co., Ltd.) under the following conditions: 37°C for 15 min and 85°C for 5 min. qPCR analysis was carried out using the SYBR Green Master Mix kit (cat. no. 04707516001; Roche Diagnostics) with 95°C for 5 min (initial denaturation) and 40 cycles of 95°C for 5 sec (denaturation) and 60°C for 1 min (annealing and extension). The relative gene expression levels are expressed as fold changes relative to control samples, and were quantified using the 2−ΔΔCq comparative threshold cycle method (21). ACTB, a housekeeping gene, served as an endogenous reference to normalize target gene expression levels across all experimental groups. The primer sequences are listed in Table SIV.

Statistical analysis

All data were analyzed using SPSS statistics software (version 25.0; IBM Corp.). The results are presented as the mean ± standard error of the mean. The differences were compared using an unpaired Student's t-test. P<0.05 was considered to indicate a statistically significant difference.

Results

Metabolic changes in the blood of patients with recurrent HSV-2 GH

To investigate the alterations in metabolites associated with recurrent HSV-2 GH, peripheral blood samples were collected and serum was isolated for comprehensive metabolic assays. The analysis identified a total of 78 upregulated and 100 downregulated metabolites in patients with GH (Fig. 1A). Notably, the top five downregulated metabolites were Deferiprone, ANTHOTHECOL Glabranin, 9(S)-HOTrE and Farrerol; conversely, 2-Ketobutyric acid, Butanal, L-sorbose, PSICOSE and 5-Methoxypsoralen were the five most significantly upregulated metabolites in the serum of patients with recurrent GH (Fig. 1B). To further explore the functional implications of these differentially expressed metabolites, KEGG enrichment analysis on the metabolomics data was performed. The top 20 KEGG-enriched pathways in serum included ‘Glycerophospholipid metabolism’, ‘Choline metabolism in cancer’, ‘Retrograde endocannabinoid signaling’, ‘Cholesterol metabolism’ and ‘Linoleic acid metabolism’ (Fig. 1C). Notably, key metabolites in the Glycerophospholipid metabolism pathway, including O-phosphocholine, PS (18:0/20:4(8Z,11Z,14Z,17Z)) and PE (16:0/18:2), were markedly upregulated in the serum of patients with GH compared with HCs (Fig. 1D). However, the majority of cholesterol-related metabolites were downregulated in patients with GH compared with HCs, except O-phosphocholine (Fig. 1D). Additionally, the levels of metabolites associated with the linoleic acid synthesis pathway, such as 9R,10S-EpOME, PC (18:3/20:1), PC [20:0/14:1(9Z)], 9-KODE and PC [22:0/14:1(9Z)], were significantly reduced in the serum of patients with recurrent GH compared with HCs (Fig. 1D). Overall, these results could provide novel insights into the metabolic alterations associated with GH.

Figure 1. Metabolomics analysis of blood samples from patients with recurrent herpes simplex virus type 2 GH. (A) Volcano plot depicting differentially expressed metabolites in the serum of patients with GH (n=14) vs. healthy controls (n=14). Red dots represent significantly upregulated metabolites, blue dots represent significantly downregulated metabolites; key metabolites are labelled for reference. (B) Heatmap of the top15 metabolites up or downregulated in GH compared with healthy controls. (C) KEGG enrichment scatter plot of the significantly altered metabolites in the serum of patients with GH (n=14) vs. healthy controls (n=14). (D) Heatmap of significantly altered metabolites in glycerophospholipid, cholesterol and linoleic acid metabolism pathways. FC, fold change; GH, genital herpes; KEGG, Kyoto Encyclopedia of Genes and Genomes.

GSEA of metabolites in patients with recurrent HSV-2 GH

GSEA of the metabolomics data revealed significant differences in the activation of particular metabolic pathways between patients with recurrent HSV-2 GH and HCs. As shown in Fig. 2A, among the top 30 metabolic pathways, 24 were notably enriched in the GH group, while six were enriched in the normal control group. Notably, pathways, such as ‘Biosynthesis of amino acids’, ‘Biosynthesis of phenylpropanoids’, ‘Tropane, piperidine and pyridine alkaloid biosynthesis’, ‘2-Oxocarboxylic acid metabolism’ and ‘Glycine, serine and threonine metabolism’ were significantly enriched in the GH group (Fig. 2A and B). Conversely, the ‘neuroactive ligand-receptor interaction pathway’ was markedly downregulated in patients with recurrent HSV-2 GH compared with HCs (Fig. 2A and C). Metabolomics heatmap data indicated that metabolites associated with neuroactive ligand-receptor interactions, such as palmitoylethanolamide, melatonin and sphingosine-1 phosphate, were all downregulated in the serum samples of patients with recurrent HSV-2 GH compared with HCs (Fig. 2D). Furthermore, the levels of metabolites involved in amino acid biosynthesis, including 4-aminobenzoic acid, 6,7-dihydroxycoumarin, L-tryptophan, bergapten and 5-methoxypsoralen, were notably enhanced in the GH group compared with HCs (Fig. 2D).

Figure 2. GSEA of metabolites in patients with herpes simplex virus type 2 GH. (A) GSEA results of the metabolites in the serum of patients with GH (n=14) vs. healthy controls (n=14). GSEA enrichment in (B) biosynthesis of amino acids and (C) neuroactive ligand-receptor interaction. (D) Heatmap showing metabolites in neuroactive ligand-receptor interaction and biosynthesis of amino acids and phenylpropanoids. GH, genital herpes; GSEA, Gene Set Enrichment Analysis.

RNA-seq analysis of the significant metabolic pathways in PBMCs of patients with recurrent HSV-2 GH

To elucidate the potential mechanisms underlying GH-related morbidity and to explore the association between metabolic changes and transcriptional profiles, RNA-seq analysis was conducted on blood cells from healthy individuals and patients with recurrent HSV-2 GH. The results of RNA-seq analysis revealed significant gene expression alterations in patients with recurrent HSV-2 GH, particularly upregulation of genes associated with glycerophospholipid metabolism, cholesterol metabolism and amino acid biosynthesis pathways (Fig. 3A-F). These results were consistent with those obtained in the metabolomics analysis. Several genes associated with the glycerophospholipid pathway, including ETNK1, CRLS1, PLA2G4A, GPD2, PISD, AGPAT5, PLPP3, GPAT3, PLA2G4C and DGKK, were significantly upregulated in the blood cells of patients with recurrent GH compared with HCs (Fig. 3A and B). Similarly, genes associated with cholesterol metabolism, such as SOS1, PLA2G4A, PDGFB, PIK3R3, PDGFC, WASF3, SLC44A1 and PLPP3, were also notably upregulated in the same samples (Fig. 3C and D). In terms of the amino acid biosynthesis pathway, the expression of several genes was also significantly increased in the GH group compared with in the HC group, including that of IDH1, PSAT1, ACO1, RPE, GOT1, GPT2, PRPS2, PSPH and SHMT1 (Fig. 3E and F). RT-qPCR analysis also verified that ETNK1, PLA2G4A, SOS1, GPD2, IDH1 and PSAT1 were significantly upregulated in blood cells from patients with recurrent HSV-2 GH compared with in the HC group (Fig. 3G). These results, combined with the metabolomic data, revealed significant changes in the expression of several metabolites and the activation status of relevant pathways, including those of glycerophospholipid metabolism, cholesterol metabolism and amino acid biosynthesis, in patients with recurrent HSV-2 GH.

Figure 3. RNA-sequencing analysis of the significant metabolic pathways in PBMCs from patients with recurrent herpes simplex virus type 2 GH. (A) Volcano plot and (B) heatmap showing DEGs related to glycerophospholipid metabolism in the PBMCs of patients with GH (n=14) vs. healthy controls (n=14). (C) Volcano plot and (D) heatmap showing DEGs related to cholesterol metabolism in the PBMCs of patients with GH (n=14) vs. healthy controls (n=14). (E) Volcano plot and (F) heatmap showing DEGs related to biosynthesis of amino acids in the PBMCs of patients with GH (n=14) vs. healthy controls (n=14). (G) Reverse transcription-quantitative PCR analysis of the mRNA expression levels of ETNK1, PLA2G4A, SOS1, GPD2, IDH1 and PSAT1 in the PBMCs of patients with GHP. P-values were determined by unpaired Student's t-test: **P<0.01, ***P<0.001. DEGs, differentially expressed genes; FC, fold change; GH, genital herpes; PBMCs, peripheral blood mononuclear cells.

scRNA-seq analysis of the significant metabolic pathway-related genes in patients with recurrent HSV-2 GH

To identify the cell population with enhanced expression of differentially expressed metabolism-related genes, the scRNA-seq data in patients with recurrent HSV-2 GH and HC was analyzed, and the clusters of cells in the PBMCs and neutrophils were observed (Fig. 4A). The results demonstrated that IDH1 was highly expressed in monocytes, dendritic cells (DCs) and plasmacytoid DCs (pDCs), with notably elevated expression in monocytes from the GH group (Fig. 4B and C). GOT1 and GOT2 were also markedly upregulated in pDCs and DCs (Fig. 4B and C). Additionally, ETNK1 was highly expressed in B cells, monocytes, DCs and pDCs (Fig. 4B and C). Overall, the scRNA-seq analysis revealed distinct metabolic gene expression patterns across various immune cell subpopulations, including T cells, B cells, monocytes, neutrophils and DCs.

Figure 4. scRNA-seq analysis of the significant metabolic pathway-associated genes in patients with recurrent herpes simplex virus type 2 GH. (A) t-SNE of scRNA-seq data showing clusters of cells in the PBMCs and neutrophils of patients with GH (n=4) and healthy controls (n=4). (B) Dot plot of scRNA-seq data showing key metabolite-associated genes in the clusters of cells in the PBMCs and neutrophils of patients with GH (n=4) and healthy controls (n=4). (C) Violin plots of scRNA-seq data showing key metabolite-associated genes the clusters of cells in the PBMCs and neutrophils of patients with GHP (n=4) and healthy controls (n=4). GH, genital herpes; PBMCs, peripheral blood mononuclear cells; scRNA-seq, single-cell RNA-sequencing; t-SNE, t-distributed Stochastic Neighbor Embedding.

KEGG enrichment analysis of metabolic genes identified by RNA-seq analysis

Subsequently, KEGG enrichment analysis of the metabolism-related genes, which were identified by RNA-seq analysis, was carried out. Several significantly enriched pathways were detected, including ‘carbon metabolism’, ‘folate biosynthesis’, ‘valine, leucine and isoleucine degradation’ and ‘alanine, aspartate and glutamate metabolism’ (Fig. 5A). The volcano plot for carbon metabolism revealed a significant number of upregulated genes (n=31) and a few downregulated genes (n=2); among the significantly upregulated genes were IDH1, PSAT1 and RPE, which all have crucial roles in various metabolic processes (22–24) (Fig. 5B). The alanine, aspartate and glutamate metabolism pathway also showed significant changes, with eight upregulated and one downregulated gene. Key genes, such as GOT1 and GPT2, were significantly upregulated in patients with recurrent HSV-2 GH, thus supporting their potential role in the altered metabolic state associated with GH recurrence (Fig. 5C). The folate biosynthesis pathway also exhibited significant changes, with eight upregulated genes and one downregulated gene. Notably, CBR1 and DHFR were significantly altered, suggesting their involvement in the metabolic dysregulation associated with GH recurrence (Fig. 5D). The valine, leucine and isoleucine degradation pathway had 15 upregulated genes, with ACADM and ALDH6A1 being particularly significant (Fig. 5E). The pronounced upregulation of these genes could indicate a shift in amino acid metabolism in patients with recurrent HSV-2 GH. The aforementioned findings underscored the complex metabolic reprogramming associated with GH recurrence, with multiple pathways being significantly affected.

Figure 5. KEGG enrichment analysis of metabolism-associated DEGs from RNA-seq data in patients with recurrent herpes simplex virus type 2 GH. (A) Scatter plot of KEGG enrichment showing metabolism-associated DEGs in metabolic pathways from RNA-Seq data of the PBMC of GHP (n=14) and healthy controls (n=14). Volcano plots showing DEGs in (B) carbon metabolism, (C) alanine, aspartate and glutamate, (D) folate biosynthesis and (E) valine, leucine and isoleucine degradation. DEGs, differentially expressed genes; FC, fold change; GH, genital herpes; KEGG, Kyoto Encyclopedia of Genes and Genomes; RNA-seq, RNA-sequencing.

KEGG enrichment analysis of metabolic genes detected by scRNA-seq analysis

To further analyze the metabolic profiles in different immune cells, the scRNA-seq data were further assessed using KEGG enrichment analysis. All immune cells were highly enriched in the ‘Oxidative phosphorylation’ pathway (Fig. 6A, C, E and G). Monocytes displayed a significant enrichment in the ‘Oxidative phosphorylation’ and ‘Pyrimidine metabolism’ pathways. Furthermore, almost all of the mitochondrial genes, including MT-CYB, MT-ND4 and MT-CO3, were highly expressed in monocytes from patients with recurrent HSV-2 GH, thus indicating robust metabolic activity, particularly within the OXPHOS pathway (Fig. 6A and B). In addition, significant upregulation of mitochondrial genes associated with OXPHOS, such as MT-CYB and MT-ND4, were recorded in T and B cells, and DCs (Fig. 6C-H). These findings suggested that the OXPHOS pathway-associated mitochondrial genes could display functional roles and responses during this viral infection.

Figure 6. KEGG enrichment analysis of metabolism-associated DEGs from scRNA-seq data in patients with recurrent herpes simplex virus type 2 GH. (A) Scatter plot of KEGG enrichment analysis showing metabolism-associated DEGs, and (B) dot plot of scRNA-seq data showing oxidate phosphorylation pathway-associated DEGs in monocytes from the PBMCs and neutrophils of patients with GH (n=4) and healthy controls (n=4). (C) Scatter plot of KEGG enrichment analysis showing metabolism-associated DEGs, and (D) dot plot of scRNA-seq data showing oxidate phosphorylation pathway-associated DEGs in dendritic cells. (E) Scatter plot of KEGG enrichment analysis showing metabolism-associated DEGs, and (F) dot plot of scRNA-seq data showing oxidate phosphorylation pathway-associated DEGs in T cells. (G) Scatter plot of KEGG enrichment analysis showing metabolism-associated DEGs, and (H) dot plot of scRNA-seq data showing oxidate phosphorylation pathway-associated DEGs in B cells. DEGs, differentially expressed genes; H, genital herpes; KEGG, Kyoto Encyclopedia of Genes and Genomes; scRNA-seq, single-cell RNA-sequencing.

Discussion

By integrating multiple approaches, including transcriptomics, metabolomics and scRNA-seq analyses, significant changes in pathways associated with lipid metabolism, amino acid biosynthesis and cholesterol metabolism were identified in patients with GH. Genes associated with the alanine, aspartate and glutamate, and valine, leucine and isoleucine metabolism pathways were significantly upregulated in patients with recurrent HSV-2 GH. In addition, several metabolism-related genes were upregulated in PBMCs from patients with GH, including IDH1 and ETNK1, the expression of which was notably increased in DCs and monocytes. Additionally, mitochondrial genes involved in OXPHOS, such as MT-CYB and MT-CO3, were significantly elevated across monocytes, DCs, T cells and B cells. Overall, these findings indicated metabolic reprogramming in patients with recurrent HSV-2 GH, thus providing potential biomarkers and therapeutic targets for the development of future treatment strategies.

Glycerophospholipid remodeling serves a critical role in several diseases, including orthoflavivirus infection, brain injury, Pseudomonas infections and cancer (25–27). A previous study demonstrated that viral infections can hijack the host cell glycerophospholipid metabolism to acquire lipid components for viral envelope synthesis, such as phosphatidylserine and phosphatidylinositol. Inhibiting related metabolic enzymes, such as those related to phosphatidylinositol biosynthesis, could markedly reduce viral titers and cytopathic effects (25,28). The present study showed that glycerophospholipid metabolism was upregulated in patients with GH, thus indicating that glycerolipid biosynthesis could represent a conserved host dependency factor exploited by this evolving virus. Dysregulated cholesterol metabolism in arterial macrophages has long been known to be pathogenic in atherosclerosis, and in an ILC2-driven airway inflammation model lipid metabolism dysregulation can also be found (29,30). The present data also found downregulation of cholesterol-related metabolites, which further supported the occurrence of a potential lipid metabolism dysfunction in patients with GH.

Amino acids, the fundamental building blocks of proteins, and related metabolites, derived from both microorganisms and host cells, serve a crucial role in regulating immune cell activation and antibody production, thus markedly affecting several biological processes, such as inflammation and immune responses (31,32). Recent studies have identified key intermediate metabolites in the aromatic amino acid pathways that undergo alterations during sepsis, influenza and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections (33–35). Herein, the results showed a significant upregulation of amino acid biosynthesis in patients with recurrent HSV-2 GH, thus suggesting that aberrant amino acid biosynthesis could be involved in the pathophysiology of this disease. A previous Mendelian randomization study revealed that SARS-CoV-2 infection can affect susceptibility to HSV-1 and HSV-2. While SARS-CoV-2 infection could suppress HSV-1 reactivation via inducing a type I interferon response, it could also promote HSV-2 infection via immunosuppression or an inflammatory environment (36). Based on the results of this study, the effects between SARS-CoV-2 and GH could also be mediated by several metabolic pathways.

A previous study reported that serum amino acid metabolism varies at different time points during influenza virus infection (35). The levels of several amino acids, such as valine, proline, citrulline, isoleucine, asparagine and arginine, and their derivatives may be altered following viral infection, and these changes could be associated with disease severity (37). In the present study, the RNA-seq results also revealed that several amino acid metabolic pathways, such as alanine, aspartate and glutamate, and valine, leucine and isoleucine pathways, were enriched in recurrent HSV-2 GH samples. These amino acid metabolism profiles could indicate GH relapse. Furthermore, Zhang et al (38) revealed that SARS-CoV-2 exploits folate and one-carbon metabolism to promote its replication. Consistently, the present study also revealed that folate biosynthesis metabolism was upregulated in patients with recurrent HSV-2 GH. Overall, the aforementioned findings suggested that targeting host metabolic pathways could be a promising therapeutic approach against future GH infection.

OXPHOS is a vital mitochondrial metabolic pathway, which is involved in the generation of adenosine triphosphate through the electron transport chain and chemiosmosis (39). Emerging evidence has suggested that viruses can manipulate host OXPHOS to regulate immune responses, thus enhancing their survival and replication (40). For example, a previous study demonstrated that HIV can preferentially target glycolytic CD4+ T cells by relying on elevated OXPHOS activity regardless of their differentiation and activation status (41). Additionally, liver biopsies from patients with chronic hepatitis C virus have revealed defects in OXPHOS, along with increased expression of oxidative stress-related markers (42). In patients with SARS-CoV-2, the levels of OXPHOS regulators, such as those of mitochondrial nuclear retrograde regulator 1, have been shown to be reduced in heart tissues, potentially contributing to cardiac complications. Furthermore, the expression levels of core mitochondrial genes are also decreased during SARS-CoV-2 infection in both rodent and human hosts (43,44). Herein, the results showed that the expression levels of mitochondrial genes involved in OXPHOS, including MT-CYB, MT-ND4 and MT-CO3 were significantly elevated in monocytes, T cells and B cells derived from patients with GH. Another study revealed that HSV could dysregulate lipid synthesis and induce ferroptosis via enhancing glucose-mediated OXPHOS and glutamine-dependent reductive carboxylation (45). Additionally, a previous study demonstrated that following viral infection, pDCs can retain their ability to secrete type I interferons through lactate dehydrogenase B-dependent metabolic adaptation (46). Overall, these findings suggested that OXPHOS modulation could be viral- and cell type-specific.

Although the current study provided valuable insights, there are several limitations that warrant consideration. Firstly, the sample size was not sufficient to generalize the findings across diverse populations, thus highlighting the need for further research to validate the identified biomarkers. Additionally, although associations between metabolic changes and gene expression were recorded, the underlying causal associations remain to be fully elucidated. Future studies should focus on investigating the functional roles of these metabolites and genes, as well as their interactions within the immune system. Investigating tissue-specific metabolic changes and their effect on immune cell function could yield a more comprehensive understanding of the disease. Furthermore, longitudinal studies should be performed to assess how metabolic alterations evolve over time, and how these changes could be involved in disease progression and recurrence. The current study offers compelling evidence of systemic metabolic reprogramming in recurrent HSV-2 GH and highlights novel potential therapeutic targets. However, the research cohort specifically comprised patients diagnosed with HSV-2-positive GH. Clinically, the recurrence rate of HSV-1 GH is markedly lower than that of HSV-2, primarily due to a reduced propensity for neuronal infection (47). Over the past two decades, HSV-1 has increasingly become the predominant causative agent of first-episode GH in multiple countries, reflecting a shifting epidemiological landscape (48,49). Future studies incorporating rigorous HSV typing are essential to elucidate potential subtype-specific metabolic vulnerabilities.

In conclusion, the current study revealed significant metabolic and transcriptional alterations in patients with recurrent HSV-2 GH, thus providing a foundation for future studies on metabolic interventions for HSV-2 GH recurrence and highlighting potential biomarkers for therapeutic interventions.

Supplementary Material

Supporting Data

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Acknowledgements

Not applicable.

Funding

The present study was supported by grants from the Natural Science Foundation of China (grant nos. 82373491 and 82471846) and Peterson's Lab MED Translational Medicine Fund (grant no. 20240131).

Availability of data and materials

The RNA-seq data generated in the present study may be found in the Sequence Read Archive database under accession number PRJNA1267039 or at the following URL: (https://www.ncbi.nlm.nih.gov/bioproject/?term=PRJNA1267039). The metabolomics data generated in the present study may be found in the National Genomics Data Center database under accession number PRJCA040378 or at the following URL: (https://ngdc.cncb.ac.cn/search/specific?db=bioproject&q=PRJCA040378). The scRNA-seq data generated in the present study may be found in the ScienceDB database (https://www.scidb.cn/en/detail?dataSetId=690475ca10ed4424bdc0f69c3b5cd701).

Authors' contributions

JH, YX, HC and YS conceived and designed the study. JH, CF, JZ and YC performed the experiments. JH, YX and SC analyzed the data. JH, HC and JZ wrote and reviewed the manuscript. YS and HC assume overall responsibility for the manuscript. JH and HC confirm the authenticity of all the raw data. YS and HC were responsible for study supervision and funding acquisition. All authors read and approved the final manuscript.

Ethics approval and consent to participate

The present study was approved by the Ethics Committee of Sir Run Run Shaw Hospital, affiliated with Zhejiang University School of Medicine (approval no. 20240106). Written informed consent was obtained from all participants prior to their inclusion in the study.

Patient consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

References