Comparative proteomic analysis of HFF-1 cells between lytic HSV-1 and HSV-2 infection: Insights into differences in pathogenicity specific to serotypes

Comparative proteomic analysis of HFF-1 cells between lytic HSV-1 and HSV-2 infection: Insights into differences in pathogenicity specific to serotypes | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Comparative proteomic analysis of HFF-1 cells between lytic HSV-1 and HSV-2 infection: Insights into differences in pathogenicity specific to serotypes Xiaohong Pan, Jiaxin Xie, Zhidang Zhang, Xiaomei Guo, Jixiong Li, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6065975/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 14 Jul, 2025 Read the published version in Virology Journal → Version 1 posted 8 You are reading this latest preprint version Abstract Herpes simplex virus type 1 (HSV-1) and type 2 (HSV-2) exhibit distinct clinical manifestations, yet the molecular basis of their serotype-specific pathogenicity remains unclear. This study presents a comparative proteomic analysis of human foreskin fibroblast (HFF-1) cells during lytic HSV-1 and HSV-2 infections to elucidate host-pathogen interactions driving differential virulence. Using data-independent acquisition mass spectrometry (DIA-MS), we identified 280 and 219 differentially expressed proteins (DEPs) in HSV-1- and HSV-2-infected cells, respectively. Key DEPs, validated via qPCR and Western blot, revealed serotype-specific modulation: HSV-1 upregulated antiviral effectors (ISG20, IRF7) while downregulating chemokine signaling (CXCL12, DEF8) and promoting lipid metabolism (PTDSS1). In contrast, HSV-2 upregulated inflammatory effectors (IGHV3-9, SERPINA1), enhanced NF-κB signaling (BCL3), and altered glycometabolism (GYS1, FBN1). Pathway enrichment analysis showed that HSV-1 suppressed inflammatory and antigen presentation pathways to evade immune responses, whereas HSV-2 induced stronger pro-inflammatory responses and metabolic reprogramming related to lipid and glycometabolism. These distinct strategies may explain HSV-1’s neurotropism and HSV-2’s genital tropism. Our findings provide a proteomic roadmap for understanding serotype-specific pathogenesis. This study underscores the role of host proteome remodeling in HSV divergence and informs strategies for serotype-specific interventions. HSV-1 HSV-2 proteomics viral pathogenesis metabolic reprogramming antiviral immunity Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Background Herpes simplex virus (HSV) is one of the most highly infectious human pathogens, with 3.8 billion people under the age of 50 (64%) worldwide infected with herpes simplex virus type 1 (HSV-1) and 520 million people aged 15–49 (13%) infected with herpes simplex virus type 2 (HSV-2), according to the World Health Organization (WHO) in 2024.Epidemiological investigations of herpes simplex virus type 1 (HSV-1) in Australia and New Zealand have demonstrated distinct seroprevalence patterns. Notably, Australia exhibits significantly higher HSV-1 seropositivity rates compared to other Western nations. Furthermore, surveillance data from both countries reveal a notable epidemiological shift: a progressive decline in childhood oral HSV-1 infections has been accompanied by a concurrent rise in adolescent genital HSV-1 acquisition[ 1 ]. HSV belongs to the Herpesviridae family, subfamily Alphaherpesvirinae, and is a neurotropic, double-stranded DNA-enveloped virus [2]. It is primarily classified into two types, HSV-1 and HSV-2. While HSV-1 is mainly associated with orofacial lesions and encephalitis, HSV-2 is linked to genital ulcers and neonatal infections. Despite their close genetic relationship, HSV-1 and HSV-2 differ in clinical manifestations, tissue tropism, and pathogenicity. Although they share 83% amino acid identity in glycoprotein B, their distinct tissue tropism and clinical outcomes suggest divergent host interaction strategies. Current models focus on viral gene polymorphisms; however, emerging evidence highlights the critical role of host proteome remodeling in serotype-specific pathogenesis. Understanding how HSV-1 and HSV-2 differentially manipulate host cells may provide insights into their distinct clinical presentations and tissue tropism. Emerging research suggests that HSV-1 contribute to Alzheimer’s disease pathology through amyloid-beta accumulation [3,4]. HSV-2 also plays a significant role in HIV pathogenesis and serves as a key cofactor in HIV infection and transmission [ 5 ]. Both HSV-1 and HSV-2 infect epithelial cells in the oral, nasal, and genital regions through microabrasions. After entry, they undergo retrograde transport along neuronal axons to sensory and autonomic neurons, establishing lifelong latency [ 6 ]. Upon immunosuppression, latent HSV-1 in the trigeminal ganglion or HSV-2 in the sacral ganglia reactivates, leading to viral shedding, mucocutaneous lesions, and recurrent infections [ 7 ]. This cyclical pattern of latency and reactivation complicates complete viral eradication. Currently, the treatment of herpes simplex virus with oral and topical medications is still limited, and although there are various vaccines, such as live attenuated vaccines, protein vaccines, and mRNA vaccines against herpes viruses, there is still no vaccine that can be used in humans to prevent or minimize herpes simplex virus-associated diseases [8]. HSV gene expression is tightly regulated by both viral and host proteins. HSV-1 and HSV-2 possess large, linear, double-stranded DNA genomes ranging from 150–154 kb, encoding over 80 proteins [ 9 ]. Their replication follows a strictly controlled cascade of immediate-early, early, and late viral genes, which hijack host cellular machinery. However, differences in host proteome modulation between HSV-1 and HSV-2 during lytic infection remain unclear. Most individuals acquire HSV-1 through oral mucosal transmission in early life, whereas HSV-2 is primarily transmitted sexually. The most common clinical presentation of HSV-1 is oral herpes, while HSV-2 predominantly causes genital herpes. Despite belonging to the same viral family, HSV-1 and HSV-2 exhibit significant differences in clinical manifestations and pathogenicity, including: 1) Site of infection: HSV-1 primarily affects the oral and nasal regions, whereas HSV-2 predominantly infects the external genitalia. However, cases of reverse infections, though rare, have been documented [10]. 2) Recurrence rates: HSV-2 exhibits a higher recurrence rate (~ 95%) and is more challenging to treat, while HSV-1 has a lower recurrence rate (~ 50%). A deeper understanding of the fundamental biological differences between HSV-1 and HSV-2 can enhance knowledge of their distinct clinical presentations and pathogenesis. This, in turn, may provide novel insights for developing targeted clinical interventions. Here, we performed comparative proteomic study of HSV-1- and HSV-2-infected human foreskin fibroblast (HFF-1) cells, a model for early lytic infection due to its highly susceptibility to HSV infection. Data-independent acquisition mass spectrometry (DIA-MS) has emerged as a high-throughput, accurate, and reproducible quantitative proteomics technique. Mass spectrometry-based proteomics has been extensively applied to studying virus-host interactions, including those involving HSV and varicella-zoster virus (VZV) [ 11 ]. These studies have provided comprehensive insights into global host protein changes. For instance, proteomic analysis of HSV-1-infected human corneal epithelial cells has elucidated host protein expression differences between early and late infection stages [ 12 ]. Additionally, proteomic changes following HSV-1 infection have offered new perspectives on diagnosing herpes simplex encephalitis [ 13 ]. However, the specific differences in how HSV-1 and HSV-2 interact with the host proteome during lytic infection remain poorly understood. The distinct clinical symptoms and pathogenesis associated with these two serotypes are not fully characterized. Proteomic studies can help identify key host and viral proteins that contribute to these differences. Here, we conducted a comparative proteomic study of HSV-1- and HSV-2-infected HFF-1 cells using DIA-MS, aiming to delineate serotype-specific host proteome remodeling and its implications for viral tropism and pathogenicity. Materials and methods Cells and Viruses Human foreskin fibroblast (HFF-1) cells were purchased from OriCells Biotechnology Co., Ltd. (Shanghai, China) and cultured in Dulbecco’s Modified Eagle’s Medium (DMEM, Vivacell) supplemented with 15% fetal bovine serum (FBS; Gibco, cat. no. 10091148) and penicillin-streptomycin (100 U/mL) at 37°C in a 5% CO₂ atmosphere. Vero cells were cultured in DMEM (Vivacell) supplemented with 8% FBS (Vivacell, cat. no. 10091148) and penicillin-streptomycin (100 U/mL) under the same conditions. HSV-1 strain 17 and HSV-2 strain G (ATCC: VR-3393) were amplified and titrated. The virus stocks were subjected to three freeze-thaw cycles, centrifuged at 5000×g for 10 min at 4°C, and the supernatant was collected, fractionated, and stored at -80°C. Sample preparation for Mass-Spectrometry HFF-1 cells were cultured in nine T225 flasks at 37°C (5 × 10⁶ cells/flask) until reaching 95% confluency. Cells in three flasks were infected with HSV-1 strain 17, three with HSV-2 strain G, and three served as mock-infected controls. The multiplicity of infection (MOI) was set at 0.5 for both viruses. After one hour of incubation at 37°C with 5% CO₂, the medium was replaced with DMEM containing 2% FBS and penicillin-streptomycin (100 U/mL). At 24 hours post-infection, the medium was removed, and cell culture flasks were washed twice with pre-cooled PBS. Then, 5 mL of pre-cooled PBS was added to each flask. Using a cell scraper, cells were collected to one side of the flask. All steps were performed on ice to prevent protein degradation. Cells were transferred to centrifuge tubes, spun at 1000 rpm for 3 min to remove the supernatant, and subjected to a freeze-thaw cycle in liquid nitrogen for 10 s. Samples were stored at -80°C for subsequent experiments. After thawing, SDT buffer (4% SDS, 100 mM Tris-HCl, pH 7.6) was added. The lysates were sonicated and boiled for 15 min. Following centrifugation at 14,000×g for 40 min, the supernatant was quantified using a BCA Protein Assay Kit (P0012, Beyotime). A total of 15 µg of protein per sample was mixed with 5× loading buffer and boiled for 5 min. Proteins were separated on a 4%-20% SDS-PAGE gel (constant voltage 180V, 45 min) and visualized using Coomassie Blue R-250 staining. Three independent biological replicates were performed, with randomized sample processing to minimize batch effects. Filter-aided sample preparation (FASP Digestion) procedure Dithiothreitol (DTT; 40 mM) was added to each sample and mixed at 600 rpm for 1.5 h at 37°C. After cooling to room temperature, iodoacetamide (IAA) was added to a final concentration of 20 mM to block reduced cysteine residues, followed by incubation in darkness for 30 min. Samples were transferred to Microcon units (10 kDa) and washed three times with 100 µL Urea-Alkylating(UA) buffer, followed by two washes with 100 µL of 25 mM NH₄HCO₃ buffer. Trypsin was then added at a trypsin-to-protein ratio of 1:50 (wt/wt), and samples were incubated at 37°C overnight (15–18 h). Peptides were collected as filtrates, desalted using C18 cartridges (Empore™ SPE Cartridges MCX, 30 µm, Waters), concentrated by vacuum centrifugation, and reconstituted in 40 µL of 0.1% (v/v) formic acid. Peptide content was estimated by UV absorbance at 280 nm. For DIA experiments, indexed retention time (iRT) calibration peptides were spiked into the samples. Mass Spectrometry measurement Mass spectrometry analysis was conducted by Shanghai Applied Protein Technology Co., Ltd. (Shanghai, China). Peptides from each sample were analyzed using an Orbitrap™ Astral™ mass spectrometer (Thermo Scientific) coupled with a Vanquish Neo liquid chromatography system (Thermo Scientific) in data-independent acquisition (DIA) mode. Precursor ions were scanned over a mass range of 380–980 m/z with an MS1 resolution of 240,000 at 200 m/z, a normalized AGC target of 500%, and a maximum injection time (IT) of 5 ms. The DIA mode employed 299 windows for MS2 scanning, with an isolation window of 2 m/z, a higher-energy collisional dissociation (HCD) collision energy of 25 eV, a normalized AGC target of 500%, and a maximum IT of 3 ms. DIA Data Processing DIA data were analyzed using DIA-NN 1.8.1. The main software parameters were set as follows: enzyme-trypsin, maximum missed cleavages-1, fixed modification-carbamidomethylation (C), dynamic modifications-oxidation (M) and acetylation (protein N-terminal). Protein identification was reported at a 99% confidence level, with a false discovery rate (FDR) ≤ 1%. Peptide identification was performed with an FDR of 1% at both peptide and protein levels. Global median scaling was used for normalization. Serotype-specific differentially expressed proteins (DEPs) were defined as those exhibiting significant expression changes (P 1.5 (upregulation > 1.5-fold or downregulation < 0.67-fold). GO and KEGG pathway enrichment analyses Hierarchical clustering analysis was conducted using Cluster 3.0 ( http://bonsai.hgc.jp/mdehoon/software/cluster/software.htm ) and visualized with Java TreeView ( http://jtreeview.sourceforge.net ). The Euclidean distance algorithm was used for similarity measurement, while the average linkage clustering algorithm (centroid-based clustering) was applied. A heatmap was generated as a visual aid alongside the dendrogram. Subcellular localization predictions were performed using CELLO ( http://cello.life.nctu.edu.tw/ ), a multi-class support vector machine (SVM)-based classification system. The protein sequences of selected DEPs were locally searched using the NCBI BLAST + client software (ncbi-blast-2.2.28+-win32.exe) and InterProScan to identify homologous sequences. Gene Ontology (GO) terms were assigned, and sequence annotation was conducted using Blast2GO. GO annotation results were visualized using R scripts. Following GO annotation, studied proteins were mapped against the Kyoto Encyclopedia of Genes and Genomes (KEGG) database ( https://www.genome.jp/kegg/ ) to obtain KEGG orthology identifications and pathway assignments. Enrichment analysis was conducted using Fisher’s exact test, with the complete set of quantified proteins as the background dataset. Multiple testing corrections were applied using the Benjamini-Hochberg method, and only functional categories and pathways with adjusted P-values < 0.05 were considered significant. Western blot HFF-1 cells were infected with HSV-1 or HSV-2 at an MOI of 0.5. Mock-infected HFF-1 cells served as controls. At 24 hours post-infection (hpi), cells were harvested, washed twice with pre-cooled PBS, and lysed on ice for 30 min using RIPA buffer (Proteintech, PR20001-100 mL) containing PMSF (Solarbio, P0100-10 mL). Lysates were centrifuged at 12,500×g for 5 min at 4°C, and the supernatant was transferred to a new Eppendorf tube while discarding cellular debris. Protein concentrations were quantified using the BCA kit (Beyotime, P0010), mixed with 5× loading buffer (Solarbio, P1040), and boiled at 100°C for 10 min to denature proteins. Denatured proteins were separated on SDS-PAGE gels (GeneScript, M00928) and transferred onto PVDF membranes (Millipore, IPVH00010). Membranes were blocked with 5% skimmed milk for at least 2 h, followed by incubation overnight at 4°C with primary antibodies diluted in antibody dilution buffer (Beyotime, P0256-500 mL). The following primary antibodies were used: PIBF1 (Polyclonal, Proteintech, 14413-1-AP, 1:5000), TFPI2 (Recombinant, Proteintech, 83279-1-RR, 1:5000), KIF22 (Polyclonal, Proteintech, 13403-1-AP, 1:2000), Cystatin C (Recombinant, Proteintech, 82441-1-RR, 1:5000), PLXNB1 (Abmart, PK35830, 1:1000), COX2/Cyclooxygenase 2/PTGS2 (Polyclonal, Proteintech, 12375-1-AP, 1:4000), Podocalyxin (Polyclonal, Proteintech, 18150-1-AP, 1:1000), MID1 (Abmart, PA7018S, 1:4000), ICP5 (Abcam, ab6508, 1:1000), β-actin (Proteintech, 66009-1-Ig, 1:20000). Following overnight incubation, membranes were washed four times with TBST and incubated with secondary antibodies for 2 h at room temperature. Membranes were washed again with TBST, developed using a chemiluminescence system (Bio-Rad, USA), and analyzed using ImageJ software for relative protein quantification. Normalized values (target protein/β-actin ratio) were compared across biological replicates. Real-time qPCR HFF-1 cells were infected with HSV-1 or HSV-2 at an MOI of 0.5, with mock-infected HFF-1 cells serving as controls. At 24 hpi, cells were washed twice with pre-cooled PBS in 6-well plates. Total RNA was extracted using Trizol reagent (Invitrogen) and reverse-transcribed into cDNA using the GoScript™ Reverse Transcription Kit (Promega, USA) following the manufacturer's instructions. Real-time quantitative PCR (qPCR) was performed to quantify the relative expression of target genes. The relative expression levels were calculated using the ∆∆Ct method with glyceraldehyde-3-phosphate dehydrogenase ( GAPDH ) as the internal control. All qPCR assays were conducted using the CFX-96 Real-Time Quantification System (Bio-Rad). A complete list of qPCR primers used in this study is provided in Table S11 . Results Establishment of HSV lytic infection model To obtain cell samples suitable for DIA-MS analysis, HFF-1 cells were infected with HSV-1 or HSV-2 at different multiplicities of infection (MOI). At 24 hours post-infection (hpi), viral protein expression and cytopathic effects (CPE) were clearly observed ( Fig. 1 ) , confirming effective HSV-1 and HSV-2 infection in HFF-1 cells. This validated HFF-1 as an optimal model for HSV lytic infection. At the viral protein expression level, the viral capsid protein ICP5 was significantly expressed in HSV-1- or HSV-2-infected HFF-1 cells at MOIs of 0.1, 0.5, and 1 ( Fig. 1 A, B ) . Notably, ICP5 expression levels were comparable between HSV-1 and HSV-2 at an MOI of 0.5. Regarding CPE severity, HSV-1-infected cells exhibited CPE at all tested MOIs without substantial cell detachment ( Fig. 1 C ) . In contrast, HSV-2-infected cells at an MOI of 1 became rounded and crumpled, with imminent detachment, making them unsuitable for subsequent proteomic sample collection ( Fig. 1 D ) . ICP5 expression and CPE severity at 24 hpi confirmed comparable infection efficiency between HSV-1 and HSV-2 at MOI 0.5. Based on these findings, 0.5 MOI at 24 hpi was identified as the optimal condition for proteomic analysis. This condition maintained high viral protein expression while ensuring significant CPE in most cells. Infecting cells with HSV-1 and HSV-2 at the same MOI ensured comparable infection rates. Focusing on 24 hpi, the peak of lytic replication, ensured the detection of host-pathogen interactions specific to active viral replication, avoiding potential confounding effects from host proteins associated with later stages of infection (e.g., cellular stress responses to prolonged infection) or reactivation from latency,thereby capturing early host-pathogen interactions critical for viral tropism establishment. Differential proteomics between HSV-1-infected and mock-infected HFF-1 cells To investigate the impact of lytic HSV-1 infection on host protein expression, DIA-MS analysis was performed. First, HSV-1 infection was confirmed by significant CPE and viral protein expression ( Fig. 2 A and 2 B ) in three independent experiments (Table S1 ) using a standardized MS workflow ( Fig. 2 C ) . The DIA-MS data have been deposited in the ProteomeXchange database under accession number PXD062161. By comparing protein abundance between HSV-1-infected and mock-infected cells, we identified 280 differentially expressed proteins (DEPs), including 81 upregulated and 199 downregulated proteins (Table S2 ) . Interestingly, 31 host proteins were specifically induced by HSV-1 infection, while 38 host proteins were completely absent post-infection ( Table 1 and Table S3 ) . Among the 280 DEPs, 55 proteins were uniquely upregulated (e.g., RSAD2, OL12A1), and 128 were uniquely downregulated (e.g., PPFIBP2, F11R) in HSV-1-infected cells compared to HSV-2. These virus-induced and suppressed host proteins may play crucial roles in HSV-1 pathogenesis. To explore expression patterns across groups, hierarchical clustering analysis was performed using KEGG signaling pathways. Differentially expressed proteins involved in antiviral response, metabolism, and immune pathways were identified ( Fig. 2 D ) . Collectively, proteomic comparison between HSV-1-infected and mock-infected HFF-1 cells revealed key protein changes associated with viral pathogenicity and host immune response. Table 1 Summary of induced and not detected proteins after HSV infection Group Proteins induced by HSV Not detected proteins HSV-1 vs. mock FARP2, CDC37, POTEM, EREG, GPR39, HMMR, NES, ZNF143, EVC, KIF5A, ZBTB17, GRB10, CEP55, PCNX4, SAMD1, MED13L, SLC36A1, ZFHX4, HYCC2, OR6Q1, ETNPPL, IRF7, ORAI1, MASTL, TONSL, EYA3, PKMYT1, WDR54, FRMD4A, SUCO, ZNF225 COX2, USP19, CCP110, CBFA2T2, FZD6, JCHAIN, GNAO1, COL11A2, S100A7, TPD52, PTS, NR1H3, MAP7, NFE2L1, HIF1A, RTN1, LDLRAP1, GSTA5, TAF8, MAGI2, CAMK1D, KATNAL2, CPXM2, LRRC20, FNIP1, PIGB, CLIP3, PLPPR2, MAGED4, ZNF385A, ALKBH3, NFKBIZ, ZFAND3, MID1IP1, CRIPT, PHF11, RPUSD1, LRP12 HSV-2 vs. mock IGHV3-9, ANKHD1, POTEM, EREG, GRID2, PALM, CNIH1, SERPINA1, GABRA1, TNNI3, SNCA, ZNF143, PLP1, ZBTB17, GRB10, SNCB, CEP55, PCNX4, ARHGAP11A, SAMD1, SLC36A1, CDH24, ABCA13, NRAC, USP38, OR6Q1, ETNPPL, DSCAML1, ORAI1, MASTL, TONSL, EYA3, PKMYT1, ADAM7, WDR54, FRMD4A, ZNF225, DENND2A USP19, HLA-C, MITA, SIPA1L1, METAP2, COL12A1, CFLAR, CCP110, PRICKLE3, SLC4A1, LYN, COL11A2, CCNE1, CDKN2B, SLC6A9, CLCN5, PLTP, ERVK-19, ACTG1, CREM, IFT88, GRB7, HIF1A, ATP2B3, BBS9, LONRF3, ACT, PLEKHG4, LDLRAP1, SLC35D2, STRADA, PEX26, R3HCC1L, TAF8, TRPT1, HOMER1, CPXM2, STXBP6, GIPC2, STON2, TOPBP1, RIPOR3, ZNF385A, LXN, PAPOLG, NFKBIZ, RBKS, ZFAND3, UCK1, CHST12, ALKBH4, CGN, TNIK Functional enrichment analysis of DEPs in lytic HSV-1 infection To further explore the biological roles of DEPs in HSV-1 infection, Gene Ontology (GO) and KEGG pathway enrichment analyses were performed. GO analysis identified 832 significantly enriched GO categories (P < 0.05) spanning biological processes, molecular functions, and cellular components ( Fig. 2 E and Table S4 ) . Among the most significantly enriched biological processes were: Humoral immune response (GO:0006959, GO:0006955), Adaptive immune response (GO:0002460, GO:0002250, GO:0002819), Positive regulation of immune response (GO:0050778, GO:0002684, GO:0002821), Leukocyte-mediated immunity (GO:0002443), Regulation of complement activation (GO:0030449), Positive regulation of acute inflammatory response (GO:0002675), Neuroinflammatory response (GO:0150076). These results suggest that HSV-1 infection primarily affects cellular immunity, inflammation, and metabolic processes, contributing to its pathogenic effects ( Fig. 2 F and Table S4 ). KEGG pathway analysis identified 13 significantly enriched pathways (P < 0.05) ( Fig. 2 G and Table S5 ) , highlighting pathways dysregulated by HSV-1 infection. Notably, the most significantly altered pathways included: PPAR signaling pathway (hsa03320), Cholesterol metabolism (hsa04979), Tyrosine metabolism (hsa00350), Viral protein interaction with cytokines and cytokine receptors (hsa04061). These findings underscore the involvement of immune response, signal transduction, and metabolic pathways in HSV-1 pathogenicity ( Fig. 2 H and Table S5 ) . This functional enrichment analysis provides valuable insights into the molecular mechanisms underlying HSV-1 infection and its interaction with host cells. The detection of these GO terms underscores the systemic consequences of local HSV infection and the versatility of fibroblasts in shaping host-pathogen dynamics. Differential proteomics between HSV-2-infected and mock-infected HFF-1 cells To investigate the impact of lytic HSV-2 infection on host protein expression, DIA-MS analysis was performed. First, HSV-2 infection was confirmed by significant cytopathic effects (CPE) and viral protein expression ( Fig. 3 A, B ) . DIA-MS consistently detected 7,943 human proteins across three independent experiments ( Fig. 3 C and Table S6 ) . By comparing protein abundance between HSV-2-infected and mock-infected cells, 219 differentially expressed proteins (DEPs) were identified, including 70 upregulated and 149 downregulated proteins (Table S7 ) . The selection criteria were p 1.5-fold and a downregulation threshold of < 0.67-fold (fold change refers to the ratio of protein expression intensity). Notably, 18 serotype-specific DEPs were uniquely induced by HSV-2 infection, while 43 serotype-specific DEPs were absent following infection ( Table 1 and Table S8 ) . These serotype-specific DEPs may play crucial roles in HSV-2 pathogenesis. To analyze expression patterns across groups, a hierarchical clustering algorithm was applied based on KEGG signaling pathways, with a focus on proteins involved in antiviral response, metabolism, and immune pathways ( Fig. 3 D ) . The results categorized the differentially expressed proteins into two distinct clusters. In HSV-2-infected cells, DIA-MS identified 219 DEPs (70 upregulated, 149 downregulated) with distinct pathway enrichments compared to HSV-1, particularly in complement cascades and lipid metabolism. These findings reveal significant changes in protein expression associated with viral pathogenicity and host cellular responses in HSV-2 infection. Functional enrichment analysis of DEPs in lytic HSV-2 infection To further explore the biological significance of DEPs in lytic HSV-2 infection, GO and KEGG enrichment analyses were performed. GO analysis identified 779 significantly enriched GO categories (P < 0.05) spanning biological processes, molecular functions, and cellular components ( Fig. 3 E and Table S9 ) . The most significantly dysregulated biological processes included: Nervous system processes (GO:0050877, GO:0007600, GO:0050906), Regulation of immune system processes (GO:0050777, GO:0002682, GO:0002250, GO:0002253), Inflammatory response (GO:0006954, GO:0050778), Positive regulation of TGF-β production (GO:0071636), Interleukin-27-mediated signaling pathway (GO:0070106), Regulation of chemokine production (GO:0032642), Regulation of lymphocyte apoptosis (GO:0070228), Positive regulation of dendritic cell apoptosis (GO:2000670), Negative regulation of intrinsic apoptotic signaling pathway (GO:2001243). These findings suggest that HSV-2 infection primarily affects cellular immunity, inflammatory responses, and apoptotic pathways, contributing to its pathogenesis ( Fig. 3 F and Table S9 ) . KEGG pathway analysis identified 9 significantly enriched pathways (P < 0.05) ( Fig. 3 G and Table S10 ) , highlighting key pathways dysregulated by HSV-2 infection. The most notable pathways included: Complement and coagulation cascades (hsa04610), Cholesterol metabolism (hsa04979), Platelet activation (hsa04611). These findings underscore the involvement of complement and coagulation cascades, platelet activation, signal transduction, and metabolic pathways in HSV-2 pathogenicity ( Fig. 3 H and Table S10 ) . This functional enrichment analysis provides new insights into the molecular mechanisms underlying HSV-2 infection. Validation of dysregulated proteins by real-time qPCR and Western blot To verify the DIA-MS results, we independently validated dysregulated proteins during lytic HSV infection using complementary approaches: Western blot and quantitative real-time PCR (qRT-PCR). For HSV-1-infected HFF-1 cells, we prioritized five proteins, including PIBF1 (3.15 fold), TFPI2 (2.19 fold), CST3 (0.65 fold), KIF22 (2.11 fold), and PLXNB1(0.65 fold) for Western blotanalysis based on antibody accessibility, while simultaneously measuring mRNA levels of six corresponding genes (TFPI2, KIF22, PIBF1, IL6ST, PLXNB1, and CST3) through qRT-PCR. As showed in Fig. 4 , coordinated upregulation of PIBF1, TFPI2, and KIF22 was observed at both transcriptional (mRNA) and translational (protein) levels, while CST3 and PLXNB1 exhibited concordant downregulation across these molecular tiers. Notably, IL6ST displayed transcriptional suppression. These differential expression patterns showed strong concordance with DIA-MS quantification data, substantially reinforcing the validity of our mass spectrometry profiling. To establish methodological robustness, parallel investigations in HSV-2-infected cellular models validated three differentially expressed proteins, including PTGS2 (2.19 fold), PODXL (1.91 fold), MID1(0.66 fold) through Western blot, complemented by transcriptional profiling of six associated genes (PTGS2, AHSG, PODXL, TNXB, MID1, GYS1) using qRT-PCR. The orthogonal validation outcomes presented in Fig. 5 revealed substantial methodological concordance between complementary biochemical approaches (Western blot/qRT-PCR) and initial DIA-MS datasets. This multi-platform verification strategy—combining transcriptional and post-translational analyses—provides rigorous confirmation of proteomic changes induced by HSV infection. Comparative proteomic analysis between lytic HSV-1 and HSV-2 Infection Quantitative proteomic profiling revealed distinct host protein modulation patterns during lytic HSV-1 and HSV-2 infections in HFF-1 cells. DIA-MS consistently detected 8,444 human proteins across all samples (Table S1 ) . By comparing HSV-1- and HSV-2-infected cells to mock controls, 280 and 219 differentially expressed proteins (DEPs) were identified, respectively (fold change > 1.5 or < 0.67, P < 0.05). (1) Serotype-Specific Protein Responses in HSV-1 Infection. HSV-1 infection specifically induced 13 serotype-specific DEPs, including FARP2, CDC37, and GPR39 ( Table 3 ) . These proteins were mainly associated with: Immunity (IRF7), Autophagy (SUCO), Metabolism and Signal Transduction (CDC37, GPR39, HYCC2), Cell Migration and Cytoskeletal Regulation (FARP2, HMMR, KIF5A). These results suggest that HSV-1 primarily triggers early activation of immune responses, autophagy, metabolism, and signal transduction pathways.Notably, 55 DEPs were uniquely upregulated in HSV-1 infection (e.g., RSAD2, OL12A1), while 128 were uniquely downregulated (e.g., PPFIBP2, F11R) ( Table 2 ) . The upregulated proteins were primarily involved in: Immunity and Inflammation (RSAD2, ISG20, CD274, IRF7), Cell Cycle and Division (TPX2, KIF22, PRC1, AURKB, CCNA2, TOP2A), Hippo Signaling Pathway (WWC3, SAV1, PRC1), Epigenetics and Chromatin Regulation (NSD2, HELLS, SMURF2), Metabolism and Transport (SLC36A1, KDELR2, PTDSS1). Conversely, the 128 uniquely downregulated proteins were primarily involved in: Inflammatory Response (IL6ST, C3), Antigen Presentation (HLA-DRB3), Chemokine Signaling (CXCL12, DEF8), Apoptosis Regulation (BNIP3L, CASP14), DNA Repair and Epigenetics (SETX, REV3L, KDM4B, ARID5B), Protein Folding and Degradation (EDEM2, PSMG3). (2) Serotype-Specific Protein Responses in HSV-2 Infection. In contrast, HSV-2 infection specifically induced 18 serotype-specific DEPs, including IGHV3-9, ANKHD1, and GRID2 ( Table 3 ) . These proteins were primarily associated with: Immunity and Inflammation (IGHV3-9, SERPINA1), Neurodevelopment and Function (GRID2, GABRA1, SNCA, PLP1, DSCAML1), Metabolism and Transport (ABCA13, CNIH1). Additionally, HSV-2 infection uniquely upregulated 43 serotype-specific DEPs, including NTAQ1, RTN1, and DNAJB5 ( Table 2 ) . These proteins were mainly involved in: Immunity and Inflammation (BCL3, PLG, SLFN11), Oxidative Stress Response (MAFF, HMOX1), Unfolded Protein Response (DNAJB5), Neuroscience and Development (SEMA5A, ANKS1A, NEXN). Conversely, HSV-2 infection specifically downregulated 78 serotype-specific DEPs, including UEVLD, CYP27A1, and ACT ( Table 2 ). These proteins were primarily involved in: Interferon Signaling (IFI44, MX1, OAS1, OASL, IFIH1), Antigen Processing and Presentation (HLA-A, HLA-B, HLA-C, TAP2), Immune Checkpoint Regulation (LGALS9), Inflammatory Response (SERPIND1, ASAH1, TXNIP), Lipid Metabolism (CYP27A1, ELOVL5), Glycometabolism (GYS1, FBN1), Amino Acid and Energy Metabolism (SLC25A15, SLC25A3), Protein Modification and Degradation (UBE2E2, RNF181, PGGT1B), DNA Repair and Epigenetics (MED25, ZYG11B). Overall, these findings indicate that HSV-1 and HSV-2 induce serotype-specific DEPs and modulate distinct signaling pathways, potentially contributing to their differences in tropism, immune evasion, and pathogenicity. HSV-1 primarily affects immune activation, autophagy, and metabolic processes, while HSV-2 modulates inflammatory responses, oxidative stress, and neurodevelopmental pathways. (3) Common Protein Responses in HSV-1 and HSV-2 Infection. From our MS results, HSV-1 and HSV-2 induced 20 serotype-specific proteins, including POTEM, EREG, PALM et al. (Table 3 ). These proteins were primarily associated withtranscriptional regulation (POTEM, ZNF143, ZBTB17, ZNF225), growth factors and receptor signaling (GRB10), cell cycle and DNA damage repair (MASTL, PKMYT1, TONSL), ion channels and metabolism(ORAI1, ETNPPL). Additionally, HSV-1 and HSV-2 infection upregulated 25 common DEPs, including THBD, TRANK1, SNRNP27 et al. (Table 2 ). These proteins were mainly involved incell cycle and proliferation regulation (UHRF1, MKI67, ANLN, CHAF1A and KPNA2), as well as signaling and receptors (FOSL1, SHCBP1, GPR68 and PTGS2), cytoskeleton and motility (KIFC1, SMTN and NEFM), extracellular matrix and migration (MMP3, PODXL), DNA/RNA metabolism (TYMS, SNRNP27), neural and ion regulation (GJC1, SLC20A2), glycosylation and modification (GALNT6). Conversely, HSV-1 and HSV-2 infection specifically downregulated 64 common DEPs, including GAS1, ACBD6, PACS2 et al. (Table 2 ). These proteins were primarily involved in extracellular matrix (ECM) and structural proteins (FBLN1, FBN2, COL1A1/COL3A1/COL5A1/COL5A2/COL12A1, DCN, SPARC, EFEMP1 and PCOLCE), growth factors and receptor signaling (GFRA1, EGFL6, ACKR3 and ADGRD1), inflammation and immune regulation (PTX3, HLA-DRB1, C1R/C1S/SERPING1, CFB, IL4I1 and C4A), metabolism and transport (ADH1B, SLC39A8, SELENOI and HPX), neural and muscle function (DYNC2H1, TOR1AIP2, DPYSL4 and HNMT), cancer and cell migration(GPNMB, ADAMTS2, S100P and ITM2B). Overall, these results indicated that HSV-1 and HSV-2 induced cell cycle and proliferation transcriptional regulation, signal transduction, cytoskeleton and exoskeleton motility, metabolism, inflammation and immune regulation. Table 2 Unique DEPs and common DEPs between HSV-1 and HSV-2 Specific to HSV-1 Specific to HSV-2 Common DEPs Up-regulation RSAD2, OL12A1, PIBF1, TPX2, CLEC16A, LIMS1, ISG20, NSD2, KLK11, TFPI2, KIF22, ANKRD52, RGPD5, WWC3, ECT2, PRC1, DESI2, LIN9, SAV1, ST3GAL4, NAV3, TOP2A, DNLZ, KANK1, TRAP1, BAZ1A, ITGA2, SERPINB2, TMEM51, RTN4, SEC14L1, TDRKH, KDELR2, CCNA2, LRRC8C, AURKB, TECPR1, CD274, PTDSS1, LY6K, RASSF8, SH3BP4,I GHD, SMURF2, RRBP1, MICAL2, HELLS, INA, C2orf69, VKORC1L1, COX17, ITPRIP, SEC11C, PGAM5, CDH2 NTAQ1, RTN1, DNAJB5, BCL3, FOXP1, SEMA5A, AHSG, IVNS1ABP, PIK3IP1, CBX4, ANKS1A, RAVER1, GREM1, AMBP, TFAP2C, NEXN, MAFF, PLG, SLFN11, MYO3B, PLS1, GAPDHS, UTP23, EIF4H, RHBDF2, CCNT2, UBIAD1, CDCA3, IGFBP3, EIF4G1, MAP2K3, TOP1MT, DGKZ, YIF1B, HMOX1, PBK, LRIG3, CEMIP, HERC2, SRBD1, SERPINE2, IFT22, KIF23 THBD, TRANK1, SNRNP27, FOSL1, SHCBP1, MMP3, KIFC1,SMTN, UHRF1, GPR68, ANLN, PTGS2, TYMS, PRSS3P2, GJC1, PODXL, NTM, GALNT6, PPP2R2D, GRAMD1B, CHAF1A, MKI67, SLC20A2, KPNA2, NEFM Down-regulation PPFIBP2, PAPPA, F11R, SDC3, PLEKHF2, CA12, FTH1, LBH, IL6ST, FAM110B, DYM, RABEPK, CST3, MAGED1, KDM4B, PLXNB1, PCDH18, COL18A1, AEBP1, NOSIP, DYNC2LI1, SNED1, RPS29, ARRDC3, EIF4EBP2, AZI2, AMOTL2, OXLD1, ITPK1, SUMO3, PSMG3, CDKN2A, BNIP3L, TRIM29, CDR2L, CLIP1, APOC3, MORF4L1, HLA-DRB3, MACO1, TMEM59, PLG, APP, C3, SMPDL3A, FADS1, HYI, MXRA5, POLR2K, PDLIM2, TCEA1, ATF2, ARID5B, ATP2A3, PKIG, FRAS1, NAB2, PHC3, C5orf22, PREPL, CRIP1, STC2, CXCL12, CRIM1, SHC3, TPM4, ALDH3A1, APOB, OLFML3, FBXO2, EDEM2, ZFAND6, SSBP2, ADAMTS1, LIX1L, PLBD1, FABP3, RTL8C, PARG, FGFR1, FLYWCH2, HMCES, C1RL, SFN, REV3L, IGFBP4, PRUNE2, TPM1, FNBP1L, RHOBTB3, SETX, LUM, FADS2, SOD3, LRRC32, CLU, BGN, ITIH3, GGACT, SERPINF1, KYNU, EP300, ALKBH7, FAU, JAM2, IFNGR1, CPE, MAP3K3, DEF8, C1QTNF5, MRFAP1, MB, SCD, ITM2C, CA2, DPH2, RPS6KB2, VDR, CASP14, NUDT18, COL1A2, A2M, ARHGEF19, BBS9, LTF, CTHRC1, PZP, REPIN1 UEVLD, CYP27A1, ACT, MID1, SERPIND1, ANKRD31, GYS1, NBEAL1, GTSE1, PECR, SAP30L, HSPA2, PODN, IFI44, TRIM27, IFIH1, CARD6, AKR1C1, RPP25L, UBE2E2, STON1, MEMO1, FYN, SHFL, FLRT2, FN3K, RNF181, LGMN, ZYG11B, SON, HLA-B, ARHGAP24, TEPSIN, OAS1, SERF2, SLC25A15, MX1, GPATCH1, HLA-C, KIT, MT-CO1, CBLB, PGGT1B, AKTIP, HABP2, LGSN, TAP2, NCAM2, OASL, TSEN34, SLC15A3, CD302, STK39, ZFYVE21, PDCD7, LGALS9, ASAH1, HLA-A, RDH10, FBN1, HVCN1, MED25, SERPINB7, GULP1, NME4, TXNIP, SPDL1, DDHD2, ERAP1, SLC25A3, KLF4, LMOD2, ELOVL5, IFI6, PLEKHM1, GAPVD1, BBS5, CRIPT GAS1, ACBD6, PACS2, CD248, XG, ADH1B, FBLN1, GPNMB, ADAMTS2, GFRalpha-1, SLC39A8, PSG1, FSTL1, PHPT1, TNXB, GFRA1, LRRC41, LY75, TOR1AIP2, CLN6, FBN2, SPRYD3, MFSD12, HLA-DRB1, DYNC2H1, ADGRD1, CREG1, SERPING1, TCEAL4, C1R, SVEP1, ITM2B, CUTC, PCOLCE, COL5A1, COL12A1, SMIM11, C1S, DCN, BNIP3, COL5A2, EGFL6, ITIH5, SBSN, SPARC, SELENOI, IL4I1, GSN, APBA3, COL1A1, CLK2, HNMT, DPYSL4, EFEMP1, CFB, COL3A1, PTX3, ACKR3, S100P, HBA2, APOH, C6orf89, HPX,C4A Table 3 Induced and not detected proteins specific to different HSV serotypes Type Specific to HSV-1 Specific to HSV-2 Common DEPs Induced expression FARP2, CDC37, GPR39, HMMR, USH2A, NES, EVC, KIF5A, MED13L, ZFHX4, HYCC2, IRF7, SUCO IGHV3-9, ANKHD1, GRID2, CNIH1, SERPINA1, GABRA1, TNNI3, SNCA, PLP1, SNCB, ARHGAP11A, CDH24, ABCA13, NRAC, USP38, DSCAML1, ADAM7, DENND2A POTEM, EREG, PALM, ZNF143, ZBTB17, GRB10, CEP55, PCNX4, SAMD1, SLC36A1, OR6Q1, ETNPPL, ORAI1, MASTL, TONSL, EYA3, PKMYT1, WDR54, FRMD4A, ZNF225 Not detected COX2, CBFA2T2, FZD6, JCHAIN, GNAO1, S100A7, TPD52, PTS, NR1H3, MAP7, NFE2L1, RTN1, GSTA5, MAGI2, CAMK1D, KATNAL2, LRRC20, FNIP1, PIGB, CLIP3, PLPPR2, MAGED4, ALKBH3, MID1IP1, CRIPT, PHF11, RPUSD1, LRP12 HLA-C, MITA, SIPA1L1, METAP2, L12A1, CFLAR, PRICKLE3, SLC4A1, LYN, CCNE1, CDKN2B, SLC6A9, CLCN5, PLTP, ERVK-19, ACTG1, CREM, IFT88, GRB7, ATP2B3, BBS9, LONRF3, ACT, PLEKHG4, SLC35D2, STRADA, PEX26, R3HCC1L, TRPT1, HOMER1, STXBP6, GIPC2, STON2, TOPBP1, RIPOR3, LXN, PAPOLG, RBKS, UCK1, CHST12, ALKBH4, CGN, TNIK Insights into Pathogenicity Differences Pathway enrichment (KEGG) highlighted divergent host proteins and related signaling pathways, which are potentially responsible for viral pathogenicity differences. And all the mentioned proteins were shown in Tables 2 and Table 3 . 1) Divergent Immune Modulation : HSV-1 more effectively suppresses inflammatory response (IL6ST, C3), antigen presentation (HLA-DRB3), and chemokine signaling (CXCL12, DEF8) compared to HSV-2. HSV-2 induces a stronger pro-inflammatory response (BCL3, PLG, SLFN11) than HSV-1. 2) Metabolic Reprogramming as a Serotype Signature : HSV-1 upregulates PTDSS1 (Phosphatidylserine Synthase 1) to enhance lipid metabolism, while HSV-2 moderately promotes lipid metabolism (CYP27A1, ELOVL5), glycometabolism (GYS1, FBN1), and amino acid/energy metabolism (SLC25A15, SLC25A3). 3) Apoptosis and Cell Survival : HSV-1 may suppress pro-apoptotic signals (BNIP3L, CASP14) to prolong cell survival, whereas HSV-2 may trigger apoptosis earlier. 4) Cellular Stress Responses : HSV-1 may induce cell autophagy to create a favorable environment for viral replication, whereas HSV-2 may activate oxidative stress (MAFF, HMOX1) and the unfolded protein response (DNAJB5) to enhance the host immune response. 5) Serotype-Specific Host Protein Interactions : Comparative analysis may reveal serotype-specific interactions with host proteins. For example, HSV-1 may interact more strongly with certain host factors involved in: Immunity and Inflammation (RSAD2, ISG20, CD274, IRF7, IL6ST, C3), Hippo signaling (WWC3, SAV1, PRC1), Antigen presentation (HLA-DRB3), Chemokine signaling (CXCL12, DEF8), Apoptosis regulation (BNIP3L, CASP14), DNA repair and epigenetics (SETX, REV3L, KDM4B, ARID5B, NSD2, HELLS, SMURF2), Protein folding and degradation (EDEM2, PSMG3). HSV-2 may interact more strongly with host factors involved in: Immunity and Inflammation (IGHV3-9, SERPINA1, BCL3, PLG, SLFN11, SERPIND1, ASAH1, TXNIP), Oxidative stress (MAFF, HMOX1), Unfolded protein response (DNAJB5), Metabolism and Transport (ABCA13, CNIH1), Lipid metabolism (CYP27A1, ELOVL5), Glycometabolism (GYS1, FBN1), Amino acid and energy metabolism (SLC25A15, SLC25A3), Protein modification and degradation (UBE2E2, RNF181, PGGT1B), DNA repair and epigenetics (MED25, ZYG11B). Taken together, these differential strategies suggest HSV-1 prioritizes immune evasion through ISG interference, whereas HSV-2 accelerates host inflammatory responses, potentially explaining clinical variations in lesion severity and recurrence rates. These findings provide proteomic-level insights into how closely related viral strains (sharing ~ 83% glycoprotein homology) manifest distinct pathogenic outcomes, offering mechanistic clues for subsequent pathogenesis investigations. Through comparative analysis of host proteomic alterations induced by representative strains from two viral serotypes, we establish novel mechanistic associations between serotype-specific post-infection responses and their corresponding clinical manifestations, thereby advancing our understanding of viral pathogenesis determinants. To strengthen the clinical relevance of our findings, we compared our HFF-1 proteomic data with published datasets from HSV-infected neuronal and genital epithelial cells. Our proteomic data from HFF-1 cells align with Niko Hensel et al. [ 14 ], who observed 28 host factors that may dampen the inflammasome response and modulate intracellular vesicle transport to promote HSV infection of the brain, suggesting a universal host response strategy across cell types. Conversely, Cheng J et al. [ 15 ] reported global proteomic changes in the brain tissue of BALB/c mice vaginally infected with HSV-2, suggesting that synaptic structure and function alterations, as well as autophagy, may contribute to the development of neurologic abnormalities following HSV-2 infection. Our observation of HSV-2-induced lipid metabolism reprogramming contrasts with Cheng J et al. [ 15 ], who reported synaptic dysfunction in HSV-2-infected mouse brains. This discrepancy may reflect tissue-specific adaptations, highlighting the need for comparative proteomic analyses across multiple models. Discussion This study provides a comprehensive and comparative proteomic characterization of alterations occurring during lytic HSV-1 and HSV-2 infection in HFF-1 cells. The results revealed significant changes in the abundance of proteins involved in immune, inflammatory, and metabolic pathways in response to HSV infection. These findings help further understanding molecular differences in serotype-specific HSV pathogenicity and open new avenues for investigating viral pathogenesis mechanisms and host antiviral responses. Some researchers have used cerebrospinal fluid proteomics to compare the proteomic profiles of patients with meningitis or encephalitis caused by HSV-2 and varicella-zoster virus (VZV) [ 11 ]. Kulej et al. conducted a time-resolved multi-omics analysis of HSV-1 infection, encompassing the host and viral proteome, phosphoproteome, chromatin-bound proteome, and histone post-translational modifications (PTMs). While their study focused on post-translational modifications (PTMs), our DIA-MS approach revealed global proteome remodeling during HSV lytic infection[ 16 ]. Consistent with Kulej et al., who reported HSV-1-induced phosphorylation in HFF-1 cells, our proteomic data confirm broad suppression of antigen presentation (e.g., HLA-DRB3) and metabolic reprogramming. However, our study uniquely demonstrates that HSV-1 prioritizes lipid metabolism (PTDSS1) and immune evasion, whereas HSV-2 amplifies inflammatory signaling (BCL3, PLG), suggesting serotype-specific strategies for host manipulation. In contrast to Wan et al. [ 17 ], who investigated subcellular proteome dynamics (cytoplasmic and nuclear fractions) during HSV-1 infection in HEK 293T cells, emphasizing host protein regulation independent of interferon signaling. Our study instead focused on looking at the overall changes in host proteins after HSV-1 or HSV-2 infection. Soh et al. [ 18 ] recently investigated temporal proteome dynamics during HSV-1 infection in human keratinocytes (HaCaT), emphasizing virus-induced degradation of host proteins (e.g., GOPC) and cell-surface remodeling mediated by HSV-1 pUL56. However, no prior research has addressed why the two HSV serotypes lead to distinct clinical manifestations. This study aims to explore the reasons underlying the serotype-specific clinical symptoms of herpes simplex virus (HSV) infections, providing new insights for future therapeutic approaches. We firstly determined the optimal infection conditions by analyzing cell morphology during lesion development and detecting viral protein expression. While MOI 0.5 ensured comparability of CPE severity and viral protein expression between HSV-1 and HSV-2, it may introduce heterogeneity in infection stages across the cell population. Future studies employing synchronized infection models (e.g., high MOI with centrifugal enhancement or time-resolved proteomics) will further resolve temporal host responses during early lytic infection. Samples were collected at this optimized time point, and mass spectrometry was performed to identify host proteomic changes during the lytic infection of HFF-1 cells by both HSV-1 and HSV-2. While HFF-1 cells serve as a well-established model for lytic infection, they lack the specialized microenvironment of neurons (HSV-1 latency site) or genital epithelial cells (HSV-2 tropism). Future studies should validate key findings in these clinically relevant cell types to confirm their clinical significance. HSV infection causes widespread alterations in various signaling pathways, including immune modulation, inflammatory responses, and cellular metabolism. The three proteins selected for upregulation analysis following HSV-1 infection revealed key insights: Progesterone-induced blocking factor 1 (PIBF1) is an endogenous luteinizing hormone immunomodulatory factor. PIBF1 levels remain consistently elevated during pregnancy [ 19 ]. It mediates the immunomodulatory effects of progesterone, promotes the proliferation and motility of triple-negative breast cancer cells, and is targeted by microRNA-203 in gastric cancer growth inhibition [ 20 ]. PIBF1 plays a significant role in cell cycle regulation and invasion control. Tissue factor pathway inhibitor (TFPI) is an endogenous anticoagulant protein secreted by endothelial cells and macrophages. It regulates the coagulation cascade and significantly influences the pathophysiology of blood disorders [ 21 , 22 , 23 ]. TFPI expression fluctuates in tumors, inflammatory diseases, and cardiovascular disorders [ 24 ]. Kinesin family member 22 (KIF22), a member of the kinesin superfamily, plays a role in intracellular transport and is implicated in bladder cancer, oral cancer, and melanoma [ 25 – 28 ]. Its methylation status is linked to immune modulation and chemokine signaling. Conversely, proteins that were downregulated following HSV-1 infection included gp130, PLXNB1, and cystatin C. Gp130 (IL6ST) is a transmembrane protein and a common signaling receptor subunit of the IL-6 cytokine family [ 29 ]. It is expressed in various organs such as the spleen, lungs, heart, and liver [ 30 ]. Gp130 has demonstrated anti-tumor, anti-inflammatory, and tissue-protective effects. Targeting gp130 has shown potential in anti-cancer therapy [ 31 , 32 ]. Cystatin C is a low-molecular-weight protein secreted by nucleated cells, present in nearly all tissues and body fluids [ 33 ]. While primarily used as a biomarker for kidney function [ 34 , 35 ], recent studies suggest its involvement in immune regulation and apoptosis [ 36 ]. Plexin B1 (PLXNB1) is a cell surface receptor belonging to the proteoglycan receptor family, with high affinity for signaling element 4D (SEMA4D). PLXNB1-mediated interactions regulate immune responses and cancer progression [ 37 ]. These findings suggest that HSV-1 infection primarily affects membrane-bound and nuclear proteins, initiating distinct immune response pathways. Consistent with previous proteomic studies in corneal epithelial cells [ 12 ], our data confirm HSV-1-mediated suppression of antigen presentation pathways (e.g., HLA-DRB3 downregulation). This aligns with HSV-1’s known immune evasion mechanisms, such as ICP47-mediated inhibition of TAP-dependent peptide transport [ 38 ]. This strategy may contribute to HSV-1 persistence in neuronal tissues, facilitating viral latency and recurrent infections. Proteins that are elevated after HSV-2 infection include PTGS2, AHSG, and PODXL. PTGS2, also known as cyclooxygenase-2 (COX2), plays a key role in inflammation, pain, angiogenesis, and cancer progression [ 39 ]. COX2 is a key enzyme in the conversion of arachidonic acid to prostaglandins I2, E2 and thromboxane A2. The PTGS2/COX2-PGE2 signaling axis is considered a major driver of inflammation and a direct cause of inflammatory responses [ 39 ]. AHSG (Fetuin-A) is a glycoprotein synthesized by hepatocytes and found in human serum [ 40 ]. It is associated directly or indirectly with cell growth and is believed to reduce inflammatory responses, though its precise role remains unclear [ 41 ]. PODXL (Podocalyxin-like protein 1) is a transmembrane sialomucin that acts as either an anti-adhesion or pro-adhesion molecule, depending on the cellular environment. It can activate intracellular signaling pathways to promote cancer metastasis and plays a role in immune evasion [ 42 , 43 ]. MID1 is an E3 ubiquitin ligase and has been reported as a promising therapeutic target in Huntington’s disease [ 44 ]. It is also implicated in antiviral immune responses, where it suppresses innate immunity by ubiquitinating IRF3 [ 45 ].Tenascin-X (TNXB) is an extracellular matrix glycoprotein expressed in skin, muscle, tendons, and blood vessels. It has anti-adhesion functions and is primarily involved in skin tissue homeostasis, likely by limiting keratinocyte formation and fibroblast proliferation/migration [ 46 , 47 ]. Glycogen synthase 1 (GYS1), encoded by the GYS1 gene, is a core enzyme in glycogen synthesis, widely expressed in glycogen-producing tissues [ 48 ]. It plays a central role in energy homeostasis. The antiviral effect of HSV-1 infection is primarily mediated through alterations in cellular immunoregulation, involving proteins such as PIBF1, KIF22, and TFPI. In contrast, HSV-2 enhances its lytic replication by modulating cell membrane proteins such as PLXNB1 and transmembrane proteins such as gp130. Additionally, cystatin C, a protein found in all tissues and body fluids, is one of the most important extracellular inhibitors of cysteine proteases, preventing extracellular protein degradation [ 36 ]. HSV-2-infected cells likely downregulate surface proteins, transmembrane proteins, and extracellular matrix-disintegrating enzymes to facilitate viral replication and widespread infection [ 36 ]. Among the three proteins upregulated after HSV-2 infection, AHSG and PODXL were also upregulated in HSV-1-infected cells, though they did not rank among the top 20 differentially expressed proteins. PTGS2, a prostaglandin peroxidase synthase, is a key component of the PTGS2/COX2-PGE2 signaling axis, which serves as a major driver of inflammation. PODXL, a transmembrane sialomucin, functions as either an anti-adhesion or pro-adhesion molecule, depending on the cellular context [ 43 ]. These findings suggest that PTGS2 and PODXL do not exhibit identical responses to inflammatory factors during HSV-1 and HSV-2 infections. Among the three proteins downregulated after HSV-2 infection, TNXB was also downregulated in HSV-1-infected cells, though to a lesser extent. TNXB, an extracellular matrix protein, is primarily expressed in skin, muscle, vasculature, and blood vessels. It has anti-adhesion functions and likely regulates keratinocyte and fibroblast proliferation/migration [ 47 ]. AHSG (α2-HS glycoprotein, also known as fetuin A) is a glycoprotein with multiple biological functions and plays a key role in inflammation regulation and tumor progression[ 40 ]. Its upregulation in HSV-2-infected cells suggests a role in HSV-2-induced cellular damage. MID1, as an E3 ubiquitin ligase, has been previously linked to viral infection and ubiquitin-mediated regulatory pathways [ 49 ]. GYS1, a key enzyme in glycogen metabolism [ 48 ], suggests that HSV-2 infection alters cellular energy metabolism by modulating glycogen synthase activity. While our study identifies PTDSS1 as a key antiviral protein upregulated during HSV-1 infection, future research should utilize genetic or pharmacological inhibition of PTDSS1 to determine its necessity for HSV-1 propagation, particularly in lipid-dependent processes such as viral envelope formation. Similarly, employing neuronal or genital epithelial models would clarify whether these findings extend beyond fibroblasts to clinically relevant cell types. While our study focused on prototypical HSV-1 and HSV-2 strains, future investigations should validate these findings across diverse clinical isolates to assess strain-specific adaptations. While our study focused on host proteome remodeling, future work will include temporal viral proteomics (e.g., immediate-early/early/late protein kinetics) to precisely map replication stages. This will further strengthen correlations between viral activity and host responses. In conclusion, this study presents the high-resolution comparative proteomic atlas of HSV-1 and HSV-2 infections, mapping host pathways hijacked for serotype-specific pathogenesis. Despite the model's simplicity, our data reveal actionable targets (PTDSS1, BCL3) and biomarkers (FARP2, IGHV3-9) with translational potential. Future research must focus on in vivo validation and therapeutic exploitation, ultimately bridging the gap between molecular insights and clinical solutions for HSV-related morbidity. Conclusion Our study provides a novel perspective on HSV pathogenesis by elucidating serotype-specific host proteome rewiring, highlighting the critical role of host metabolic and immune remodeling in driving viral tropism and clinical manifestations. The proteomic signatures identified—such as the upregulation of PTDSS1 (linked to lipid metabolism in HSV-1) and BCL3 (associated with NF-κB activation in HSV-2)—reveal actionable targets for serotype-specific therapeutic interventions. For instance: Pharmacological inhibition of PTDSS1, a phosphatidylserine synthase essential for viral envelope formation, could disrupt HSV-1 replication in neuronal tissues. Targeting BCL3-mediated NF-κB signaling may mitigate HSV-2-induced inflammatory damage in genital mucosa. These findings, combined with the differential expression of immune checkpoints (e.g., CD274) and metabolic regulators (e.g., GYS1), provide a foundation for developing precision therapies, such as small-molecule inhibitors or monoclonal antibodies tailored to serotype-specific host-virus interactions. Future studies should prioritize validating these targets in in vivo models and clinical isolates, bridging mechanistic insights into therapeutic applications. Abbreviations HSV-1 herpes simplex virus type 1 HSV-2 herpes simplex virus type 2 HFF-1 human foreskin fibroblast DEPs differentially expressed proteins DIA-MS data-independent acquisition mass spectrometry WHO World Health Organization VZV varicella-zoster virus DMEM Dulbecco’s Modified Eagle’s Medium FBS fetal bovine serum MOI multiplicity of infection FASP Filter-aided sample preparation IAA iodoacetamide UA Urea-Alkylating iRT indexed retention time IT injection time HCD higher-energy collisional dissociation FDR false discovery rate GO Gene Ontology KEGG Kyoto Encyclopedia of Genes and Genomes SVM support vector machine hpi hours post-infection CPE cytopathic effects PIBF1 progesterone-induced blocking factor 1 TFPI tissue factor pathway inhibitor KIF22 kinesin family member 22 PLXNB1 Plexin B1 GYS1 Glycogen synthase 1 PODXL Podocalyxin-like protein 1 COX2 cyclooxygenase-2 PTM post-translational modifications Declarations Funding This study was supported by the Natural Science Foundation of Yunnan Province (202401AS070048, 202401BC070008), the Chinese Academy of Medical Sciences (CAMS) Innovation Fund for Medical Sciences (CIFMS) (2022-12M-CoV19-002), the Innovation Team Project of Yunnan Science and Technology Department (202105AE160020). Ethics approval and consent to participate Ethical approval was waived as the study utilized commercially available cell lines (HFF-1, Ao Rui Cell) without human or animal experimentation. Consent for publication All authors approved the final manuscript and consented to its submission. Availability of data and materials The DIA-MS data have been deposited in the ProteomeXchange database under accession number PXD062161. Competing interests The authors declare no competing interests. Authors ’ contributions SJD and PXH designed and performed research. XJX, ZZD, GXM, LJX, QY, XJW, HYZ and LD contributed new reagents and analytic tools. SJD and PXH analyzed data. SJD and PXH wrote the manuscript. All authors read and approved the final version. References AlMukdad, S.; Harfouche, M.; Farooqui, U. S.; Aldos, L.; Abu-Raddad, L. J., Epidemiology of herpes simplex virus type 1 and genital herpes in Australia and New Zealand: systematic review, meta-analyses and meta-regressions. 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Ubiquitin E3 ligase MID1 inhibits the innate immune response by ubiquitinating IRF3. Immunology 2021 ;163(3):278-292. Valcourt U, Alcaraz LB, Exposito J-Y, Lethias C, Bartholin L. Tenascin-X: beyond the architectural function. Cell Adhesion & Migration 2015 ;9(1-2):154-65. Miller WL. Tenascin-X-Discovery and Early Research. Frontiers In Immunology 2020;11:612497. Chen J, Ji X, Gao J, Huang J, Ren J. gys1 regulates maternal glycogen reserve essential for embryonic development in zebrafish. Heliyon 2024 ;10(10):e31149. Tian H, Yu K, He L, Xu H, Han C, Zhang X, Wang X, Zhang X, Zhang L, Gao G, Deng H. RNF213 modulates γ-herpesvirus infection and reactivation via targeting the viral Replication and Transcription Activator. Proceedings of the National Academy of Sciences of the United States of America 2023 ;120(12):e2218825120. Additional Declarations No competing interests reported. Supplementary Files TableS1.OverviewofidentifiedproteinsinHSV1andmockinfectedHFF1cells.xlsx TableS2.DEPsbetweenHSV1andmockinfectedHFF1cells.xlsx TableS3.SummaryofinducedorunexpressedproteinsafterHSV1infection.xlsx TableS4.GOfunctionalenrichmentanalysisofDEPsafterHSV1infection.xlsx TableS5.KEGGpathwayenrichmentanalysisofDEPsafterHSV1infection.xlsx TableS6.OverviewofidentifiedproteinsinHSV2andmockinfectedHFF1cells.xlsx TableS7.DEPsbetweenHSV2andmockinfectedHFF1cells.xlsx TableS8.SummaryofinducedorunexpressedproteinsafterHSV2infection.xlsx TableS9.GOfunctionalenrichmentanalysisofDEPsafterHSV2infection.xlsx TableS10.KEGGpathwayenrichmentanalysisofDEPsafterHSV2infection.xlsx TableS11.RealtimeqPCRprimersusedinthisstudy.docx AdditionalfilesLegends.docx Cite Share Download PDF Status: Published Journal Publication published 14 Jul, 2025 Read the published version in Virology Journal → Version 1 posted Editorial decision: Revision requested 24 Apr, 2025 Reviews received at journal 24 Apr, 2025 Reviews received at journal 22 Apr, 2025 Reviewers agreed at journal 07 Apr, 2025 Reviewers agreed at journal 07 Apr, 2025 Reviewers invited by journal 07 Apr, 2025 Submission checks completed at journal 07 Apr, 2025 First submitted to journal 05 Apr, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6065975","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":439774937,"identity":"128ccd85-571c-4151-a6de-e00125a90457","order_by":0,"name":"Xiaohong Pan","email":"","orcid":"","institution":"Chinese Academy of Medical Sciences and Peking Union Medical College","correspondingAuthor":false,"prefix":"","firstName":"Xiaohong","middleName":"","lastName":"Pan","suffix":""},{"id":439774939,"identity":"a4f1b32d-6843-4e12-a0ad-397f287e7f43","order_by":1,"name":"Jiaxin Xie","email":"","orcid":"","institution":"Chinese Academy of Medical 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16:53:23","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6065975/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6065975/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12985-025-02803-w","type":"published","date":"2025-07-14T15:56:55+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":80288239,"identity":"a3c07fab-af9b-47f4-bae2-44af7cf13e60","added_by":"auto","created_at":"2025-04-10 07:19:55","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":2083295,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eEstablishment of HSV lytic infection model in HFF-1 cells. \u003c/strong\u003e(A) Immunoblot analysis of ICP5 expression in HSV-1-infected cells at multiplicities of infection (MOIs: 0.1, 0.5, 1) at 24 hpi. (B) Comparative ICP5 expression profiles in HSV-2-infected cells under identical MOI conditions. (C) Phase-contrast micrographs illustrating progressive cytopathic effects (CPEs) induced by HSV-1 infection at graded MOIs. (D) Parallel documentation of HSV-2-mediated CPEs under equivalent infection parameters.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-6065975/v1/d5622119a8ea102a87ada64c.png"},{"id":80288279,"identity":"d7162e0e-e9f6-4ec0-82d7-0f39cfded213","added_by":"auto","created_at":"2025-04-10 07:19:59","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":817057,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eProteomic profiling of HSV-1-infected HFF-1 cells and functional enrichment analysis of HSV-1-modulated proteome. \u003c/strong\u003e(A) Representative images of CPEs at MOI 0.5 (24 hpi). (B) Immunoblot validation of viral ICP5 protein expression confirming infection efficiency. (C) Schematic workflow outlining the quantitative proteomic pipeline. (D) Hierarchically clustered heatmap depicting protein abundance patterns in antiviral, immune, and metabolic pathways. (E) GO Level2 classification showing Molecular Function (MF), Cellular Component (CC), and Biological Process (BP) distributions. (F) Enriched BP terms visualized as bubble plots, with bubble size reflecting protein counts, color intensity indicating enrichment factor (≤1), and x-axis representing -log10(p-value). (G) KEGG pathway enrichment of upregulated (red) and downregulated (blue) proteins. (H) Bubble plot of KEGG pathways with significance (-log10(p-value)), enrichment factor, and differential protein counts.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-6065975/v1/a622b3425ce280350eb0b52d.png"},{"id":80288245,"identity":"ae0c20f1-83b7-4413-8a8e-a458f4201e17","added_by":"auto","created_at":"2025-04-10 07:19:56","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":759551,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eProteomic characterization of HSV-2-infected HFF-1 cells and enrichment landscape of HSV-2-regulated proteins. \u003c/strong\u003e(A) Morphological CPEs at MOI 0.5 (24 hpi). (B) Viral protein detection validating HSV-2 infection. (C) Proteomic workflow identical to Fig. 2C. (D) Heatmap clustering of pathway-associated proteins. (E–H) Mirroring the analytical framework of Fig. 2, detailing GO and KEGG enrichment profiles specific to HSV-2 infection.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-6065975/v1/6f38c6b65ff4c361df287490.png"},{"id":80288254,"identity":"bec683ad-7b55-4b86-9ef8-2bf916edfb30","added_by":"auto","created_at":"2025-04-10 07:19:56","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":364392,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eVerification of HSV-1-induced protein dysregulation. \u003c/strong\u003e(A) Western blot quantification of PIBF1, TFPI2, CST3, KIF22, and PLXNB1 expression with densitometric analysis. (B) qPCR confirmation of transcriptional changes in PIBF1, TFPI2, KIF22, PLXNB1, IL6ST, and CST3. The grayscale quantification was performed using the ImageJ software. The data are presented as mean±standard deviation values of three independent experiments.\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-6065975/v1/069c1ff22ba42620f9267034.png"},{"id":80288280,"identity":"ab172062-b234-4787-b3af-86ea913e1b7c","added_by":"auto","created_at":"2025-04-10 07:19:59","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":322523,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eVerification of HSV-2-induced protein dysregulation. \u003c/strong\u003e(A) Immunoblot analysis of PTGS2, PODXL, and MID1 expression with grayscale quantification. (B) qPCR validation of PTGS2, PODXL, AHSG, MID1, TNXB, and GYS1 mRNA levels. The grayscale quantification was performed using the ImageJ software. The data are presented as mean±standard deviation values of three independent experiments.\u003c/p\u003e","description":"","filename":"Figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-6065975/v1/e8c5f5d06651c8c8afe4dde9.png"},{"id":87219321,"identity":"8d053dc9-f528-4394-9654-1639a0732b39","added_by":"auto","created_at":"2025-07-21 16:03:30","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":7349489,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6065975/v1/85d67faf-b7c0-4a5b-9e28-75026109eb86.pdf"},{"id":80288243,"identity":"e3f7251f-5433-4d31-8510-662df2337b19","added_by":"auto","created_at":"2025-04-10 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07:19:57","extension":"xlsx","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":146411,"visible":true,"origin":"","legend":"","description":"","filename":"TableS5.KEGGpathwayenrichmentanalysisofDEPsafterHSV1infection.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-6065975/v1/6d516d68d315d7e7d5915666.xlsx"},{"id":80288249,"identity":"78f3efea-6a92-4d40-9220-7e423d38715f","added_by":"auto","created_at":"2025-04-10 07:19:56","extension":"xlsx","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":3960363,"visible":true,"origin":"","legend":"","description":"","filename":"TableS6.OverviewofidentifiedproteinsinHSV2andmockinfectedHFF1cells.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-6065975/v1/2e4c07efbd209e7c27645d20.xlsx"},{"id":80288247,"identity":"bcff26af-d345-4444-aeb6-f3727b07a1c0","added_by":"auto","created_at":"2025-04-10 07:19:56","extension":"xlsx","order_by":7,"title":"","display":"","copyAsset":false,"role":"supplement","size":3948926,"visible":true,"origin":"","legend":"","description":"","filename":"TableS7.DEPsbetweenHSV2andmockinfectedHFF1cells.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-6065975/v1/20e915b4397ba6831fa0348c.xlsx"},{"id":80289508,"identity":"0680b864-d513-496d-8443-678ac5c434f3","added_by":"auto","created_at":"2025-04-10 07:27:55","extension":"xlsx","order_by":8,"title":"","display":"","copyAsset":false,"role":"supplement","size":54444,"visible":true,"origin":"","legend":"","description":"","filename":"TableS8.SummaryofinducedorunexpressedproteinsafterHSV2infection.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-6065975/v1/d21f7ad9977d628324013f28.xlsx"},{"id":80288266,"identity":"b5e1689c-dc92-4254-9628-83d2df26c9ba","added_by":"auto","created_at":"2025-04-10 07:19:57","extension":"xlsx","order_by":9,"title":"","display":"","copyAsset":false,"role":"supplement","size":2893456,"visible":true,"origin":"","legend":"","description":"","filename":"TableS9.GOfunctionalenrichmentanalysisofDEPsafterHSV2infection.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-6065975/v1/a4d0ceb7ef3ef04ee5999b07.xlsx"},{"id":80288260,"identity":"f5f681c1-8cd1-49ae-9e9d-3360ee7e3bb3","added_by":"auto","created_at":"2025-04-10 07:19:56","extension":"xlsx","order_by":10,"title":"","display":"","copyAsset":false,"role":"supplement","size":100600,"visible":true,"origin":"","legend":"","description":"","filename":"TableS10.KEGGpathwayenrichmentanalysisofDEPsafterHSV2infection.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-6065975/v1/1c170ac90bf38fe303b5a43f.xlsx"},{"id":80289520,"identity":"dc150f5a-466e-4e5e-83e1-947c530c0b6b","added_by":"auto","created_at":"2025-04-10 07:27:57","extension":"docx","order_by":11,"title":"","display":"","copyAsset":false,"role":"supplement","size":16490,"visible":true,"origin":"","legend":"","description":"","filename":"TableS11.RealtimeqPCRprimersusedinthisstudy.docx","url":"https://assets-eu.researchsquare.com/files/rs-6065975/v1/3702e2f61aed07d6a3c2f945.docx"},{"id":80288240,"identity":"7334b3f5-5399-4747-80f3-d7a12b960388","added_by":"auto","created_at":"2025-04-10 07:19:55","extension":"docx","order_by":12,"title":"","display":"","copyAsset":false,"role":"supplement","size":13860,"visible":true,"origin":"","legend":"","description":"","filename":"AdditionalfilesLegends.docx","url":"https://assets-eu.researchsquare.com/files/rs-6065975/v1/ca7ac4981ff553f2995a32b0.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Comparative proteomic analysis of HFF-1 cells between lytic HSV-1 and HSV-2 infection: Insights into differences in pathogenicity specific to serotypes","fulltext":[{"header":"Background","content":"\u003cp\u003eHerpes simplex virus (HSV) is one of the most highly infectious human pathogens, with 3.8\u0026nbsp;billion people under the age of 50 (64%) worldwide infected with herpes simplex virus type 1 (HSV-1) and 520\u0026nbsp;million people aged 15\u0026ndash;49 (13%) infected with herpes simplex virus type 2 (HSV-2), according to the World Health Organization (WHO) in 2024.Epidemiological investigations of herpes simplex virus type 1 (HSV-1) in Australia and New Zealand have demonstrated distinct seroprevalence patterns. Notably, Australia exhibits significantly higher HSV-1 seropositivity rates compared to other Western nations. Furthermore, surveillance data from both countries reveal a notable epidemiological shift: a progressive decline in childhood oral HSV-1 infections has been accompanied by a concurrent rise in adolescent genital HSV-1 acquisition[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. HSV belongs to the Herpesviridae family, subfamily Alphaherpesvirinae, and is a neurotropic, double-stranded DNA-enveloped virus [2]. It is primarily classified into two types, HSV-1 and HSV-2. While HSV-1 is mainly associated with orofacial lesions and encephalitis, HSV-2 is linked to genital ulcers and neonatal infections. Despite their close genetic relationship, HSV-1 and HSV-2 differ in clinical manifestations, tissue tropism, and pathogenicity. Although they share 83% amino acid identity in glycoprotein B, their distinct tissue tropism and clinical outcomes suggest divergent host interaction strategies. Current models focus on viral gene polymorphisms; however, emerging evidence highlights the critical role of host proteome remodeling in serotype-specific pathogenesis. Understanding how HSV-1 and HSV-2 differentially manipulate host cells may provide insights into their distinct clinical presentations and tissue tropism.\u003c/p\u003e \u003cp\u003eEmerging research suggests that HSV-1 contribute to Alzheimer\u0026rsquo;s disease pathology through amyloid-beta accumulation [3,4]. HSV-2 also plays a significant role in HIV pathogenesis and serves as a key cofactor in HIV infection and transmission [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Both HSV-1 and HSV-2 infect epithelial cells in the oral, nasal, and genital regions through microabrasions. After entry, they undergo retrograde transport along neuronal axons to sensory and autonomic neurons, establishing lifelong latency [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Upon immunosuppression, latent HSV-1 in the trigeminal ganglion or HSV-2 in the sacral ganglia reactivates, leading to viral shedding, mucocutaneous lesions, and recurrent infections [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. This cyclical pattern of latency and reactivation complicates complete viral eradication. Currently, the treatment of herpes simplex virus with oral and topical medications is still limited, and although there are various vaccines, such as live attenuated vaccines, protein vaccines, and mRNA vaccines against herpes viruses, there is still no vaccine that can be used in humans to prevent or minimize herpes simplex virus-associated diseases [8].\u003c/p\u003e \u003cp\u003eHSV gene expression is tightly regulated by both viral and host proteins. HSV-1 and HSV-2 possess large, linear, double-stranded DNA genomes ranging from 150\u0026ndash;154 kb, encoding over 80 proteins [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Their replication follows a strictly controlled cascade of immediate-early, early, and late viral genes, which hijack host cellular machinery. However, differences in host proteome modulation between HSV-1 and HSV-2 during lytic infection remain unclear. Most individuals acquire HSV-1 through oral mucosal transmission in early life, whereas HSV-2 is primarily transmitted sexually. The most common clinical presentation of HSV-1 is oral herpes, while HSV-2 predominantly causes genital herpes. Despite belonging to the same viral family, HSV-1 and HSV-2 exhibit significant differences in clinical manifestations and pathogenicity, including: 1) Site of infection: HSV-1 primarily affects the oral and nasal regions, whereas HSV-2 predominantly infects the external genitalia. However, cases of reverse infections, though rare, have been documented [10]. 2) Recurrence rates: HSV-2 exhibits a higher recurrence rate (~\u0026thinsp;95%) and is more challenging to treat, while HSV-1 has a lower recurrence rate (~\u0026thinsp;50%).\u003c/p\u003e \u003cp\u003eA deeper understanding of the fundamental biological differences between HSV-1 and HSV-2 can enhance knowledge of their distinct clinical presentations and pathogenesis. This, in turn, may provide novel insights for developing targeted clinical interventions. Here, we performed comparative proteomic study of HSV-1- and HSV-2-infected human foreskin fibroblast (HFF-1) cells, a model for early lytic infection due to its highly susceptibility to HSV infection. Data-independent acquisition mass spectrometry (DIA-MS) has emerged as a high-throughput, accurate, and reproducible quantitative proteomics technique. Mass spectrometry-based proteomics has been extensively applied to studying virus-host interactions, including those involving HSV and varicella-zoster virus (VZV) [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. These studies have provided comprehensive insights into global host protein changes. For instance, proteomic analysis of HSV-1-infected human corneal epithelial cells has elucidated host protein expression differences between early and late infection stages [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Additionally, proteomic changes following HSV-1 infection have offered new perspectives on diagnosing herpes simplex encephalitis [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eHowever, the specific differences in how HSV-1 and HSV-2 interact with the host proteome during lytic infection remain poorly understood. The distinct clinical symptoms and pathogenesis associated with these two serotypes are not fully characterized. Proteomic studies can help identify key host and viral proteins that contribute to these differences. Here, we conducted a comparative proteomic study of HSV-1- and HSV-2-infected HFF-1 cells using DIA-MS, aiming to delineate serotype-specific host proteome remodeling and its implications for viral tropism and pathogenicity.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eCells and Viruses\u003c/h2\u003e \u003cp\u003eHuman foreskin fibroblast (HFF-1) cells were purchased from OriCells Biotechnology Co., Ltd. (Shanghai, China) and cultured in Dulbecco\u0026rsquo;s Modified Eagle\u0026rsquo;s Medium (DMEM, Vivacell) supplemented with 15% fetal bovine serum (FBS; Gibco, cat. no. 10091148) and penicillin-streptomycin (100 U/mL) at 37\u0026deg;C in a 5% CO₂ atmosphere. Vero cells were cultured in DMEM (Vivacell) supplemented with 8% FBS (Vivacell, cat. no. 10091148) and penicillin-streptomycin (100 U/mL) under the same conditions. HSV-1 strain 17 and HSV-2 strain G (ATCC: VR-3393) were amplified and titrated. The virus stocks were subjected to three freeze-thaw cycles, centrifuged at 5000\u0026times;g for 10 min at 4\u0026deg;C, and the supernatant was collected, fractionated, and stored at -80\u0026deg;C.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eSample preparation for Mass-Spectrometry\u003c/h3\u003e\n\u003cp\u003eHFF-1 cells were cultured in nine T225 flasks at 37\u0026deg;C (5 \u0026times; 10⁶ cells/flask) until reaching 95% confluency. Cells in three flasks were infected with HSV-1 strain 17, three with HSV-2 strain G, and three served as mock-infected controls. The multiplicity of infection (MOI) was set at 0.5 for both viruses. After one hour of incubation at 37\u0026deg;C with 5% CO₂, the medium was replaced with DMEM containing 2% FBS and penicillin-streptomycin (100 U/mL). At 24 hours post-infection, the medium was removed, and cell culture flasks were washed twice with pre-cooled PBS. Then, 5 mL of pre-cooled PBS was added to each flask. Using a cell scraper, cells were collected to one side of the flask. All steps were performed on ice to prevent protein degradation. Cells were transferred to centrifuge tubes, spun at 1000 rpm for 3 min to remove the supernatant, and subjected to a freeze-thaw cycle in liquid nitrogen for 10 s. Samples were stored at -80\u0026deg;C for subsequent experiments. After thawing, SDT buffer (4% SDS, 100 mM Tris-HCl, pH 7.6) was added. The lysates were sonicated and boiled for 15 min. Following centrifugation at 14,000\u0026times;g for 40 min, the supernatant was quantified using a BCA Protein Assay Kit (P0012, Beyotime). A total of 15 \u0026micro;g of protein per sample was mixed with 5\u0026times; loading buffer and boiled for 5 min. Proteins were separated on a 4%-20% SDS-PAGE gel (constant voltage 180V, 45 min) and visualized using Coomassie Blue R-250 staining. Three independent biological replicates were performed, with randomized sample processing to minimize batch effects.\u003c/p\u003e\n\u003ch3\u003eFilter-aided sample preparation (FASP Digestion) procedure\u003c/h3\u003e\n\u003cp\u003eDithiothreitol (DTT; 40 mM) was added to each sample and mixed at 600 rpm for 1.5 h at 37\u0026deg;C. After cooling to room temperature, iodoacetamide (IAA) was added to a final concentration of 20 mM to block reduced cysteine residues, followed by incubation in darkness for 30 min. Samples were transferred to Microcon units (10 kDa) and washed three times with 100 \u0026micro;L Urea-Alkylating(UA) buffer, followed by two washes with 100 \u0026micro;L of 25 mM NH₄HCO₃ buffer. Trypsin was then added at a trypsin-to-protein ratio of 1:50 (wt/wt), and samples were incubated at 37\u0026deg;C overnight (15\u0026ndash;18 h). Peptides were collected as filtrates, desalted using C18 cartridges (Empore\u0026trade; SPE Cartridges MCX, 30 \u0026micro;m, Waters), concentrated by vacuum centrifugation, and reconstituted in 40 \u0026micro;L of 0.1% (v/v) formic acid. Peptide content was estimated by UV absorbance at 280 nm. For DIA experiments, indexed retention time (iRT) calibration peptides were spiked into the samples.\u003c/p\u003e\n\u003ch3\u003eMass Spectrometry measurement\u003c/h3\u003e\n\u003cp\u003eMass spectrometry analysis was conducted by Shanghai Applied Protein Technology Co., Ltd. (Shanghai, China). Peptides from each sample were analyzed using an Orbitrap\u0026trade; Astral\u0026trade; mass spectrometer (Thermo Scientific) coupled with a Vanquish Neo liquid chromatography system (Thermo Scientific) in data-independent acquisition (DIA) mode. Precursor ions were scanned over a mass range of 380\u0026ndash;980 m/z with an MS1 resolution of 240,000 at 200 m/z, a normalized AGC target of 500%, and a maximum injection time (IT) of 5 ms. The DIA mode employed 299 windows for MS2 scanning, with an isolation window of 2 m/z, a higher-energy collisional dissociation (HCD) collision energy of 25 eV, a normalized AGC target of 500%, and a maximum IT of 3 ms.\u003c/p\u003e\n\u003ch3\u003eDIA Data Processing\u003c/h3\u003e\n\u003cp\u003eDIA data were analyzed using DIA-NN 1.8.1. The main software parameters were set as follows: enzyme-trypsin, maximum missed cleavages-1, fixed modification-carbamidomethylation (C), dynamic modifications-oxidation (M) and acetylation (protein N-terminal). Protein identification was reported at a 99% confidence level, with a false discovery rate (FDR)\u0026thinsp;\u0026le;\u0026thinsp;1%. Peptide identification was performed with an FDR of 1% at both peptide and protein levels. Global median scaling was used for normalization. Serotype-specific differentially expressed proteins (DEPs) were defined as those exhibiting significant expression changes (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) in one viral infection but not the other, with a fold-change threshold of \u0026gt;\u0026thinsp;1.5 (upregulation\u0026thinsp;\u0026gt;\u0026thinsp;1.5-fold or downregulation\u0026thinsp;\u0026lt;\u0026thinsp;0.67-fold).\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eGO and KEGG pathway enrichment analyses\u003c/h2\u003e \u003cp\u003eHierarchical clustering analysis was conducted using Cluster 3.0 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://bonsai.hgc.jp/mdehoon/software/cluster/software.htm\u003c/span\u003e\u003cspan address=\"http://bonsai.hgc.jp/mdehoon/software/cluster/software.htm\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) and visualized with Java TreeView (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://jtreeview.sourceforge.net\u003c/span\u003e\u003cspan address=\"http://jtreeview.sourceforge.net\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). The Euclidean distance algorithm was used for similarity measurement, while the average linkage clustering algorithm (centroid-based clustering) was applied. A heatmap was generated as a visual aid alongside the dendrogram.\u003c/p\u003e \u003cp\u003eSubcellular localization predictions were performed using CELLO (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://cello.life.nctu.edu.tw/\u003c/span\u003e\u003cspan address=\"http://cello.life.nctu.edu.tw/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), a multi-class support vector machine (SVM)-based classification system. The protein sequences of selected DEPs were locally searched using the NCBI BLAST\u0026thinsp;+\u0026thinsp;client software (ncbi-blast-2.2.28+-win32.exe) and InterProScan to identify homologous sequences. Gene Ontology (GO) terms were assigned, and sequence annotation was conducted using Blast2GO. GO annotation results were visualized using R scripts.\u003c/p\u003e \u003cp\u003eFollowing GO annotation, studied proteins were mapped against the Kyoto Encyclopedia of Genes and Genomes (KEGG) database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.genome.jp/kegg/\u003c/span\u003e\u003cspan address=\"https://www.genome.jp/kegg/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) to obtain KEGG orthology identifications and pathway assignments. Enrichment analysis was conducted using Fisher\u0026rsquo;s exact test, with the complete set of quantified proteins as the background dataset. Multiple testing corrections were applied using the Benjamini-Hochberg method, and only functional categories and pathways with adjusted P-values\u0026thinsp;\u0026lt;\u0026thinsp;0.05 were considered significant.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eWestern blot\u003c/h3\u003e\n\u003cp\u003eHFF-1 cells were infected with HSV-1 or HSV-2 at an MOI of 0.5. Mock-infected HFF-1 cells served as controls. At 24 hours post-infection (hpi), cells were harvested, washed twice with pre-cooled PBS, and lysed on ice for 30 min using RIPA buffer (Proteintech, PR20001-100 mL) containing PMSF (Solarbio, P0100-10 mL). Lysates were centrifuged at 12,500\u0026times;g for 5 min at 4\u0026deg;C, and the supernatant was transferred to a new Eppendorf tube while discarding cellular debris. Protein concentrations were quantified using the BCA kit (Beyotime, P0010), mixed with 5\u0026times; loading buffer (Solarbio, P1040), and boiled at 100\u0026deg;C for 10 min to denature proteins. Denatured proteins were separated on SDS-PAGE gels (GeneScript, M00928) and transferred onto PVDF membranes (Millipore, IPVH00010). Membranes were blocked with 5% skimmed milk for at least 2 h, followed by incubation overnight at 4\u0026deg;C with primary antibodies diluted in antibody dilution buffer (Beyotime, P0256-500 mL). The following primary antibodies were used: PIBF1 (Polyclonal, Proteintech, 14413-1-AP, 1:5000), TFPI2 (Recombinant, Proteintech, 83279-1-RR, 1:5000), KIF22 (Polyclonal, Proteintech, 13403-1-AP, 1:2000), Cystatin C (Recombinant, Proteintech, 82441-1-RR, 1:5000), PLXNB1 (Abmart, PK35830, 1:1000), COX2/Cyclooxygenase 2/PTGS2 (Polyclonal, Proteintech, 12375-1-AP, 1:4000), Podocalyxin (Polyclonal, Proteintech, 18150-1-AP, 1:1000), MID1 (Abmart, PA7018S, 1:4000), ICP5 (Abcam, ab6508, 1:1000), β-actin (Proteintech, 66009-1-Ig, 1:20000). Following overnight incubation, membranes were washed four times with TBST and incubated with secondary antibodies for 2 h at room temperature. Membranes were washed again with TBST, developed using a chemiluminescence system (Bio-Rad, USA), and analyzed using ImageJ software for relative protein quantification. Normalized values (target protein/β-actin ratio) were compared across biological replicates.\u003c/p\u003e\n\u003ch3\u003eReal-time qPCR\u003c/h3\u003e\n\u003cp\u003eHFF-1 cells were infected with HSV-1 or HSV-2 at an MOI of 0.5, with mock-infected HFF-1 cells serving as controls. At 24 hpi, cells were washed twice with pre-cooled PBS in 6-well plates. Total RNA was extracted using Trizol reagent (Invitrogen) and reverse-transcribed into cDNA using the GoScript\u0026trade; Reverse Transcription Kit (Promega, USA) following the manufacturer's instructions. Real-time quantitative PCR (qPCR) was performed to quantify the relative expression of target genes. The relative expression levels were calculated using the ∆∆Ct method with glyceraldehyde-3-phosphate dehydrogenase (\u003cem\u003eGAPDH\u003c/em\u003e) as the internal control. All qPCR assays were conducted using the CFX-96 Real-Time Quantification System (Bio-Rad). A complete list of qPCR primers used in this study is provided in \u003cb\u003eTable \u003cspan refid=\"MOESM11\" class=\"InternalRef\"\u003eS11\u003c/span\u003e\u003c/b\u003e.\u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec12\" class=\"Section2\"\u003e\n \u003ch2\u003eEstablishment of HSV lytic infection model\u003c/h2\u003e\n \u003cp\u003eTo obtain cell samples suitable for DIA-MS analysis, HFF-1 cells were infected with HSV-1 or HSV-2 at different multiplicities of infection (MOI). At 24 hours post-infection (hpi), viral protein expression and cytopathic effects (CPE) were clearly observed \u003cstrong\u003e(\u003c/strong\u003eFig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e\u003cstrong\u003e)\u003c/strong\u003e, confirming effective HSV-1 and HSV-2 infection in HFF-1 cells. This validated HFF-1 as an optimal model for HSV lytic infection. At the viral protein expression level, the viral capsid protein ICP5 was significantly expressed in HSV-1- or HSV-2-infected HFF-1 cells at MOIs of 0.1, 0.5, and 1 \u003cstrong\u003e(\u003c/strong\u003eFig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eA, B\u003cstrong\u003e)\u003c/strong\u003e. Notably, ICP5 expression levels were comparable between HSV-1 and HSV-2 at an MOI of 0.5. Regarding CPE severity, HSV-1-infected cells exhibited CPE at all tested MOIs without substantial cell detachment \u003cstrong\u003e(\u003c/strong\u003eFig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eC\u003cstrong\u003e)\u003c/strong\u003e. In contrast, HSV-2-infected cells at an MOI of 1 became rounded and crumpled, with imminent detachment, making them unsuitable for subsequent proteomic sample collection \u003cstrong\u003e(\u003c/strong\u003eFig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003eD\u003cstrong\u003e)\u003c/strong\u003e. ICP5 expression and CPE severity at 24 hpi confirmed comparable infection efficiency between HSV-1 and HSV-2 at MOI 0.5. Based on these findings, 0.5 MOI at 24 hpi was identified as the optimal condition for proteomic analysis. This condition maintained high viral protein expression while ensuring significant CPE in most cells. Infecting cells with HSV-1 and HSV-2 at the same MOI ensured comparable infection rates. Focusing on 24 hpi, the peak of lytic replication, ensured the detection of host-pathogen interactions specific to active viral replication, avoiding potential confounding effects from host proteins associated with later stages of infection (e.g., cellular stress responses to prolonged infection) or reactivation from latency,thereby capturing early host-pathogen interactions critical for viral tropism establishment.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e\n \u003ch2\u003eDifferential proteomics between HSV-1-infected and mock-infected HFF-1 cells\u003c/h2\u003e\n \u003cp\u003eTo investigate the impact of lytic HSV-1 infection on host protein expression, DIA-MS analysis was performed. First, HSV-1 infection was confirmed by significant CPE and viral protein expression \u003cstrong\u003e(\u003c/strong\u003eFig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eA and \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eB\u003cstrong\u003e)\u003c/strong\u003e in three independent experiments \u003cstrong\u003e(Table \u003cspan class=\"InternalRef\"\u003eS1\u003c/span\u003e)\u003c/strong\u003e using a standardized MS workflow \u003cstrong\u003e(\u003c/strong\u003eFig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eC\u003cstrong\u003e)\u003c/strong\u003e. The DIA-MS data have been deposited in the ProteomeXchange database under accession number PXD062161. By comparing protein abundance between HSV-1-infected and mock-infected cells, we identified 280 differentially expressed proteins (DEPs), including 81 upregulated and 199 downregulated proteins \u003cstrong\u003e(Table \u003cspan class=\"InternalRef\"\u003eS2\u003c/span\u003e)\u003c/strong\u003e. Interestingly, 31 host proteins were specifically induced by HSV-1 infection, while 38 host proteins were completely absent post-infection \u003cstrong\u003e(\u003c/strong\u003eTable \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e \u003cstrong\u003eand Table \u003cspan class=\"InternalRef\"\u003eS3\u003c/span\u003e)\u003c/strong\u003e. Among the 280 DEPs, 55 proteins were uniquely upregulated (e.g., RSAD2, OL12A1), and 128 were uniquely downregulated (e.g., PPFIBP2, F11R) in HSV-1-infected cells compared to HSV-2. These virus-induced and suppressed host proteins may play crucial roles in HSV-1 pathogenesis. To explore expression patterns across groups, hierarchical clustering analysis was performed using KEGG signaling pathways. Differentially expressed proteins involved in antiviral response, metabolism, and immune pathways were identified \u003cstrong\u003e(\u003c/strong\u003eFig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eD\u003cstrong\u003e)\u003c/strong\u003e. Collectively, proteomic comparison between HSV-1-infected and mock-infected HFF-1 cells revealed key protein changes associated with viral pathogenicity and host immune response.\u0026nbsp;\u003c/p\u003e\n \u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eSummary of induced and not detected proteins after HSV infection\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eGroup\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eProteins induced by HSV\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eNot detected proteins\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHSV-1 vs. mock\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFARP2, CDC37, POTEM, EREG, GPR39, HMMR, NES, ZNF143, EVC, KIF5A, ZBTB17, GRB10, CEP55, PCNX4, SAMD1, MED13L, SLC36A1, ZFHX4, HYCC2, OR6Q1, ETNPPL, IRF7, ORAI1, MASTL, TONSL, EYA3, PKMYT1, WDR54, FRMD4A, SUCO, ZNF225\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCOX2, USP19, CCP110, CBFA2T2, FZD6, JCHAIN, GNAO1, COL11A2, S100A7, TPD52, PTS, NR1H3, MAP7, NFE2L1, HIF1A, RTN1, LDLRAP1, GSTA5, TAF8, MAGI2, CAMK1D, KATNAL2, CPXM2, LRRC20, FNIP1, PIGB, CLIP3, PLPPR2, MAGED4, ZNF385A, ALKBH3, NFKBIZ, ZFAND3, MID1IP1, CRIPT, PHF11, RPUSD1, LRP12\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHSV-2 vs. mock\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIGHV3-9, ANKHD1, POTEM, EREG, GRID2, PALM, CNIH1, SERPINA1, GABRA1, TNNI3, SNCA, ZNF143, PLP1, ZBTB17, GRB10, SNCB, CEP55, PCNX4, ARHGAP11A, SAMD1, SLC36A1, CDH24, ABCA13, NRAC, USP38, OR6Q1, ETNPPL, DSCAML1, ORAI1, MASTL, TONSL, EYA3, PKMYT1, ADAM7, WDR54, FRMD4A, ZNF225, DENND2A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUSP19, HLA-C, MITA, SIPA1L1, METAP2, COL12A1, CFLAR, CCP110, PRICKLE3, SLC4A1, LYN, COL11A2, CCNE1, CDKN2B, SLC6A9, CLCN5, PLTP, ERVK-19, ACTG1, CREM, IFT88, GRB7, HIF1A, ATP2B3, BBS9, LONRF3, ACT, PLEKHG4, LDLRAP1, SLC35D2, STRADA, PEX26, R3HCC1L, TAF8, TRPT1, HOMER1, CPXM2, STXBP6, GIPC2, STON2, TOPBP1, RIPOR3, ZNF385A, LXN, PAPOLG, NFKBIZ, RBKS, ZFAND3, UCK1, CHST12, ALKBH4, CGN, TNIK\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\n \u003ch2\u003eFunctional enrichment analysis of DEPs in lytic HSV-1 infection\u003c/h2\u003e\n \u003cp\u003eTo further explore the biological roles of DEPs in HSV-1 infection, Gene Ontology (GO) and KEGG pathway enrichment analyses were performed. GO analysis identified 832 significantly enriched GO categories (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) spanning biological processes, molecular functions, and cellular components \u003cstrong\u003e(\u003c/strong\u003eFig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eE \u003cstrong\u003eand Table \u003cspan class=\"InternalRef\"\u003eS4\u003c/span\u003e)\u003c/strong\u003e. Among the most significantly enriched biological processes were: Humoral immune response (GO:0006959, GO:0006955), Adaptive immune response (GO:0002460, GO:0002250, GO:0002819), Positive regulation of immune response (GO:0050778, GO:0002684, GO:0002821), Leukocyte-mediated immunity (GO:0002443), Regulation of complement activation (GO:0030449), Positive regulation of acute inflammatory response (GO:0002675), Neuroinflammatory response (GO:0150076). These results suggest that HSV-1 infection primarily affects cellular immunity, inflammation, and metabolic processes, contributing to its pathogenic effects \u003cstrong\u003e(\u003c/strong\u003eFig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eF \u003cstrong\u003eand Table \u003cspan class=\"InternalRef\"\u003eS4\u003c/span\u003e).\u003c/strong\u003e KEGG pathway analysis identified 13 significantly enriched pathways (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) \u003cstrong\u003e(\u003c/strong\u003eFig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eG \u003cstrong\u003eand Table \u003cspan class=\"InternalRef\"\u003eS5\u003c/span\u003e)\u003c/strong\u003e, highlighting pathways dysregulated by HSV-1 infection. Notably, the most significantly altered pathways included: PPAR signaling pathway (hsa03320), Cholesterol metabolism (hsa04979), Tyrosine metabolism (hsa00350), Viral protein interaction with cytokines and cytokine receptors (hsa04061). These findings underscore the involvement of immune response, signal transduction, and metabolic pathways in HSV-1 pathogenicity \u003cstrong\u003e(\u003c/strong\u003eFig. \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003eH \u003cstrong\u003eand Table \u003cspan class=\"InternalRef\"\u003eS5\u003c/span\u003e)\u003c/strong\u003e. This functional enrichment analysis provides valuable insights into the molecular mechanisms underlying HSV-1 infection and its interaction with host cells. The detection of these GO terms underscores the systemic consequences of local HSV infection and the versatility of fibroblasts in shaping host-pathogen dynamics.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\n \u003ch2\u003eDifferential proteomics between HSV-2-infected and mock-infected HFF-1 cells\u003c/h2\u003e\n \u003cp\u003eTo investigate the impact of lytic HSV-2 infection on host protein expression, DIA-MS analysis was performed. First, HSV-2 infection was confirmed by significant cytopathic effects (CPE) and viral protein expression \u003cstrong\u003e(\u003c/strong\u003eFig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eA, B\u003cstrong\u003e)\u003c/strong\u003e. DIA-MS consistently detected 7,943 human proteins across three independent experiments \u003cstrong\u003e(\u003c/strong\u003eFig. \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eC \u003cstrong\u003eand Table \u003cspan class=\"InternalRef\"\u003eS6\u003c/span\u003e)\u003c/strong\u003e.\u003c/p\u003e\n \u003cp\u003eBy comparing protein abundance between HSV-2-infected and mock-infected cells, 219 differentially expressed proteins (DEPs) were identified, including 70 upregulated and 149 downregulated proteins \u003cstrong\u003e(Table \u003cspan class=\"InternalRef\"\u003eS7\u003c/span\u003e)\u003c/strong\u003e. The selection criteria were p\u0026thinsp;\u0026lt;\u0026thinsp;0.05, with an upregulation threshold of \u0026gt;\u0026thinsp;1.5-fold and a downregulation threshold of \u0026lt;\u0026thinsp;0.67-fold (fold change refers to the ratio of protein expression intensity). Notably, 18 serotype-specific DEPs were uniquely induced by HSV-2 infection, while 43 serotype-specific DEPs were absent following infection \u003cstrong\u003e(\u003c/strong\u003eTable \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e \u003cstrong\u003eand Table \u003cspan class=\"InternalRef\"\u003eS8\u003c/span\u003e)\u003c/strong\u003e. These serotype-specific DEPs may play crucial roles in HSV-2 pathogenesis.\u003c/p\u003e\n \u003cp\u003eTo analyze expression patterns across groups, a hierarchical clustering algorithm was applied based on KEGG signaling pathways, with a focus on proteins involved in antiviral response, metabolism, and immune pathways \u003cstrong\u003e(\u003c/strong\u003eFig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eD\u003cstrong\u003e)\u003c/strong\u003e. The results categorized the differentially expressed proteins into two distinct clusters. In HSV-2-infected cells, DIA-MS identified 219 DEPs (70 upregulated, 149 downregulated) with distinct pathway enrichments compared to HSV-1, particularly in complement cascades and lipid metabolism. These findings reveal significant changes in protein expression associated with viral pathogenicity and host cellular responses in HSV-2 infection.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec16\" class=\"Section2\"\u003e\n \u003ch2\u003eFunctional enrichment analysis of DEPs in lytic HSV-2 infection\u003c/h2\u003e\n \u003cp\u003eTo further explore the biological significance of DEPs in lytic HSV-2 infection, GO and KEGG enrichment analyses were performed. GO analysis identified 779 significantly enriched GO categories (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) spanning biological processes, molecular functions, and cellular components \u003cstrong\u003e(\u003c/strong\u003eFig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eE \u003cstrong\u003eand Table \u003cspan class=\"InternalRef\"\u003eS9\u003c/span\u003e)\u003c/strong\u003e. The most significantly dysregulated biological processes included: Nervous system processes (GO:0050877, GO:0007600, GO:0050906), Regulation of immune system processes (GO:0050777, GO:0002682, GO:0002250, GO:0002253), Inflammatory response (GO:0006954, GO:0050778), Positive regulation of TGF-\u0026beta; production (GO:0071636), Interleukin-27-mediated signaling pathway (GO:0070106), Regulation of chemokine production (GO:0032642), Regulation of lymphocyte apoptosis (GO:0070228), Positive regulation of dendritic cell apoptosis (GO:2000670), Negative regulation of intrinsic apoptotic signaling pathway (GO:2001243). These findings suggest that HSV-2 infection primarily affects cellular immunity, inflammatory responses, and apoptotic pathways, contributing to its pathogenesis \u003cstrong\u003e(\u003c/strong\u003eFig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eF \u003cstrong\u003eand Table \u003cspan class=\"InternalRef\"\u003eS9\u003c/span\u003e)\u003c/strong\u003e. KEGG pathway analysis identified 9 significantly enriched pathways (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05) \u003cstrong\u003e(\u003c/strong\u003eFig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eG \u003cstrong\u003eand Table \u003cspan class=\"InternalRef\"\u003eS10\u003c/span\u003e)\u003c/strong\u003e, highlighting key pathways dysregulated by HSV-2 infection. The most notable pathways included: Complement and coagulation cascades (hsa04610), Cholesterol metabolism (hsa04979), Platelet activation (hsa04611). These findings underscore the involvement of complement and coagulation cascades, platelet activation, signal transduction, and metabolic pathways in HSV-2 pathogenicity \u003cstrong\u003e(\u003c/strong\u003eFig.\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003eH \u003cstrong\u003eand Table \u003cspan class=\"InternalRef\"\u003eS10\u003c/span\u003e)\u003c/strong\u003e. This functional enrichment analysis provides new insights into the molecular mechanisms underlying HSV-2 infection.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec17\" class=\"Section2\"\u003e\n \u003ch2\u003eValidation of dysregulated proteins by real-time qPCR and Western blot\u003c/h2\u003e\n \u003cp\u003eTo verify the DIA-MS results, we independently validated dysregulated proteins during lytic HSV infection using complementary approaches: Western blot and quantitative real-time PCR (qRT-PCR). For HSV-1-infected HFF-1 cells, we prioritized five proteins, including PIBF1 (3.15 fold), TFPI2 (2.19 fold), CST3 (0.65 fold), KIF22 (2.11 fold), and PLXNB1(0.65 fold) for Western blotanalysis based on antibody accessibility, while simultaneously measuring mRNA levels of six corresponding genes (TFPI2, KIF22, PIBF1, IL6ST, PLXNB1, and CST3) through qRT-PCR. As showed in Fig. \u003cspan class=\"InternalRef\"\u003e4\u003c/span\u003e, coordinated upregulation of PIBF1, TFPI2, and KIF22 was observed at both transcriptional (mRNA) and translational (protein) levels, while CST3 and PLXNB1 exhibited concordant downregulation across these molecular tiers. Notably, IL6ST displayed transcriptional suppression. These differential expression patterns showed strong concordance with DIA-MS quantification data, substantially reinforcing the validity of our mass spectrometry profiling. To establish methodological robustness, parallel investigations in HSV-2-infected cellular models validated three differentially expressed proteins, including PTGS2 (2.19 fold), PODXL (1.91 fold), MID1(0.66 fold) through Western blot, complemented by transcriptional profiling of six associated genes (PTGS2, AHSG, PODXL, TNXB, MID1, GYS1) using qRT-PCR. The orthogonal validation outcomes presented in Fig. \u003cspan class=\"InternalRef\"\u003e5\u003c/span\u003e revealed substantial methodological concordance between complementary biochemical approaches (Western blot/qRT-PCR) and initial DIA-MS datasets. This multi-platform verification strategy\u0026mdash;combining transcriptional and post-translational analyses\u0026mdash;provides rigorous confirmation of proteomic changes induced by HSV infection.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec18\" class=\"Section2\"\u003e\n \u003ch2\u003eComparative proteomic analysis between lytic HSV-1 and HSV-2 Infection\u003c/h2\u003e\n \u003cp\u003eQuantitative proteomic profiling revealed distinct host protein modulation patterns during lytic HSV-1 and HSV-2 infections in HFF-1 cells. DIA-MS consistently detected 8,444 human proteins across all samples \u003cstrong\u003e(Table \u003cspan class=\"InternalRef\"\u003eS1\u003c/span\u003e)\u003c/strong\u003e. By comparing HSV-1- and HSV-2-infected cells to mock controls, 280 and 219 differentially expressed proteins (DEPs) were identified, respectively (fold change\u0026thinsp;\u0026gt;\u0026thinsp;1.5 or \u0026lt;\u0026thinsp;0.67, P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). (1) \u003cstrong\u003eSerotype-Specific Protein Responses in HSV-1 Infection.\u003c/strong\u003e HSV-1 infection specifically induced 13 serotype-specific DEPs, including FARP2, CDC37, and GPR39 \u003cstrong\u003e(\u003c/strong\u003eTable\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e\u003cstrong\u003e)\u003c/strong\u003e. These proteins were mainly associated with: Immunity (IRF7), Autophagy (SUCO), Metabolism and Signal Transduction (CDC37, GPR39, HYCC2), Cell Migration and Cytoskeletal Regulation (FARP2, HMMR, KIF5A). These results suggest that HSV-1 primarily triggers early activation of immune responses, autophagy, metabolism, and signal transduction pathways.Notably, 55 DEPs were uniquely upregulated in HSV-1 infection (e.g., RSAD2, OL12A1), while 128 were uniquely downregulated (e.g., PPFIBP2, F11R) \u003cstrong\u003e(\u003c/strong\u003eTable\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e\u003cstrong\u003e)\u003c/strong\u003e. The upregulated proteins were primarily involved in: Immunity and Inflammation (RSAD2, ISG20, CD274, IRF7), Cell Cycle and Division (TPX2, KIF22, PRC1, AURKB, CCNA2, TOP2A), Hippo Signaling Pathway (WWC3, SAV1, PRC1), Epigenetics and Chromatin Regulation (NSD2, HELLS, SMURF2), Metabolism and Transport (SLC36A1, KDELR2, PTDSS1). Conversely, the 128 uniquely downregulated proteins were primarily involved in: Inflammatory Response (IL6ST, C3), Antigen Presentation (HLA-DRB3), Chemokine Signaling (CXCL12, DEF8), Apoptosis Regulation (BNIP3L, CASP14), DNA Repair and Epigenetics (SETX, REV3L, KDM4B, ARID5B), Protein Folding and Degradation (EDEM2, PSMG3). \u003cstrong\u003e(2) Serotype-Specific Protein Responses in HSV-2 Infection.\u003c/strong\u003e In contrast, HSV-2 infection specifically induced 18 serotype-specific DEPs, including IGHV3-9, ANKHD1, and GRID2 \u003cstrong\u003e(\u003c/strong\u003eTable\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e\u003cstrong\u003e)\u003c/strong\u003e. These proteins were primarily associated with: Immunity and Inflammation (IGHV3-9, SERPINA1), Neurodevelopment and Function (GRID2, GABRA1, SNCA, PLP1, DSCAML1), Metabolism and Transport (ABCA13, CNIH1). Additionally, HSV-2 infection uniquely upregulated 43 serotype-specific DEPs, including NTAQ1, RTN1, and DNAJB5 \u003cstrong\u003e(\u003c/strong\u003eTable\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e\u003cstrong\u003e)\u003c/strong\u003e. These proteins were mainly involved in: Immunity and Inflammation (BCL3, PLG, SLFN11), Oxidative Stress Response (MAFF, HMOX1), Unfolded Protein Response (DNAJB5), Neuroscience and Development (SEMA5A, ANKS1A, NEXN). Conversely, HSV-2 infection specifically downregulated 78 serotype-specific DEPs, including UEVLD, CYP27A1, and ACT \u003cstrong\u003e(\u003c/strong\u003eTable\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e\u003cstrong\u003e).\u003c/strong\u003e These proteins were primarily involved in: Interferon Signaling (IFI44, MX1, OAS1, OASL, IFIH1), Antigen Processing and Presentation (HLA-A, HLA-B, HLA-C, TAP2), Immune Checkpoint Regulation (LGALS9), Inflammatory Response (SERPIND1, ASAH1, TXNIP), Lipid Metabolism (CYP27A1, ELOVL5), Glycometabolism (GYS1, FBN1), Amino Acid and Energy Metabolism (SLC25A15, SLC25A3), Protein Modification and Degradation (UBE2E2, RNF181, PGGT1B), DNA Repair and Epigenetics (MED25, ZYG11B). Overall, these findings indicate that HSV-1 and HSV-2 induce serotype-specific DEPs and modulate distinct signaling pathways, potentially contributing to their differences in tropism, immune evasion, and pathogenicity. HSV-1 primarily affects immune activation, autophagy, and metabolic processes, while HSV-2 modulates inflammatory responses, oxidative stress, and neurodevelopmental pathways. \u003cstrong\u003e(3) Common Protein Responses in HSV-1 and HSV-2 Infection.\u003c/strong\u003e From our MS results, HSV-1 and HSV-2 induced 20 serotype-specific proteins, including POTEM, EREG, PALM et al. (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e). These proteins were primarily associated withtranscriptional regulation (POTEM, ZNF143, ZBTB17, ZNF225), growth factors and receptor signaling (GRB10), cell cycle and DNA damage repair (MASTL, PKMYT1, TONSL), ion channels and metabolism(ORAI1, ETNPPL). Additionally, HSV-1 and HSV-2 infection upregulated 25 common DEPs, including THBD, TRANK1, SNRNP27 et al. (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). These proteins were mainly involved incell cycle and proliferation regulation (UHRF1, MKI67, ANLN, CHAF1A and KPNA2), as well as signaling and receptors (FOSL1, SHCBP1, GPR68 and PTGS2), cytoskeleton and motility (KIFC1, SMTN and NEFM), extracellular matrix and migration (MMP3, PODXL), DNA/RNA metabolism (TYMS, SNRNP27), neural and ion regulation (GJC1, SLC20A2), glycosylation and modification (GALNT6). Conversely, HSV-1 and HSV-2 infection specifically downregulated 64 common DEPs, including GAS1, ACBD6, PACS2 et al. (Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e). These proteins were primarily involved in extracellular matrix (ECM) and structural proteins (FBLN1, FBN2, COL1A1/COL3A1/COL5A1/COL5A2/COL12A1, DCN, SPARC, EFEMP1 and PCOLCE), growth factors and receptor signaling (GFRA1, EGFL6, ACKR3 and ADGRD1), inflammation and immune regulation (PTX3, HLA-DRB1, C1R/C1S/SERPING1, CFB, IL4I1 and C4A), metabolism and transport (ADH1B, SLC39A8, SELENOI and HPX), neural and muscle function (DYNC2H1, TOR1AIP2, DPYSL4 and HNMT), cancer and cell migration(GPNMB, ADAMTS2, S100P and ITM2B). Overall, these results indicated that HSV-1 and HSV-2 induced cell cycle and proliferation transcriptional regulation, signal transduction, cytoskeleton and exoskeleton motility, metabolism, inflammation and immune regulation.\u003c/p\u003e\n \u003ctable border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 2\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eUnique DEPs and common DEPs between HSV-1 and HSV-2\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSpecific to HSV-1\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSpecific to HSV-2\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCommon DEPs\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUp-regulation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRSAD2, OL12A1, PIBF1, TPX2, CLEC16A, LIMS1, ISG20, NSD2, KLK11, TFPI2, KIF22, ANKRD52, RGPD5, WWC3, ECT2, PRC1, DESI2, LIN9, SAV1, ST3GAL4, NAV3, TOP2A, DNLZ, KANK1, TRAP1, BAZ1A, ITGA2, SERPINB2, TMEM51, RTN4, SEC14L1, TDRKH, KDELR2, CCNA2, LRRC8C, AURKB, TECPR1, CD274, PTDSS1, LY6K, RASSF8, SH3BP4,I GHD, SMURF2, RRBP1, MICAL2, HELLS, INA, C2orf69, VKORC1L1, COX17, ITPRIP, SEC11C, PGAM5, CDH2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNTAQ1, RTN1, DNAJB5, BCL3, FOXP1, SEMA5A, AHSG, IVNS1ABP, PIK3IP1, CBX4, ANKS1A, RAVER1, GREM1, AMBP, TFAP2C, NEXN, MAFF, PLG, SLFN11, MYO3B, PLS1, GAPDHS, UTP23, EIF4H, RHBDF2, CCNT2, UBIAD1, CDCA3, IGFBP3, EIF4G1, MAP2K3, TOP1MT, DGKZ, YIF1B, HMOX1, PBK, LRIG3, CEMIP, HERC2, SRBD1, SERPINE2, IFT22, KIF23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTHBD, TRANK1, SNRNP27, FOSL1, SHCBP1, MMP3, KIFC1,SMTN, UHRF1, GPR68, ANLN, PTGS2, TYMS, PRSS3P2, GJC1, PODXL, NTM, GALNT6, PPP2R2D, GRAMD1B, CHAF1A, MKI67, SLC20A2, KPNA2, NEFM\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDown-regulation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePPFIBP2, PAPPA, F11R, SDC3, PLEKHF2, CA12, FTH1, LBH, IL6ST, FAM110B, DYM, RABEPK, CST3, MAGED1, KDM4B, PLXNB1, PCDH18, COL18A1, AEBP1, NOSIP, DYNC2LI1, SNED1, RPS29, ARRDC3, EIF4EBP2, AZI2, AMOTL2, OXLD1, ITPK1, SUMO3, PSMG3, CDKN2A, BNIP3L, TRIM29, CDR2L, CLIP1, APOC3, MORF4L1, HLA-DRB3, MACO1, TMEM59, PLG, APP, C3, SMPDL3A, FADS1, HYI, MXRA5, POLR2K, PDLIM2, TCEA1, ATF2, ARID5B, ATP2A3, PKIG, FRAS1, NAB2, PHC3, C5orf22, PREPL, CRIP1, STC2, CXCL12, CRIM1, SHC3, TPM4, ALDH3A1, APOB, OLFML3, FBXO2, EDEM2, ZFAND6, SSBP2, ADAMTS1, LIX1L, PLBD1, FABP3, RTL8C, PARG, FGFR1, FLYWCH2, HMCES, C1RL, SFN, REV3L, IGFBP4, PRUNE2, TPM1, FNBP1L, RHOBTB3, SETX, LUM, FADS2, SOD3, LRRC32, CLU, BGN, ITIH3, GGACT, SERPINF1, KYNU, EP300, ALKBH7, FAU, JAM2, IFNGR1, CPE, MAP3K3, DEF8, C1QTNF5, MRFAP1, MB, SCD, ITM2C, CA2, DPH2, RPS6KB2, VDR, CASP14, NUDT18, COL1A2, A2M, ARHGEF19, BBS9, LTF, CTHRC1, PZP, REPIN1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUEVLD, CYP27A1, ACT, MID1, SERPIND1, ANKRD31, GYS1, NBEAL1, GTSE1, PECR, SAP30L, HSPA2, PODN, IFI44, TRIM27, IFIH1, CARD6, AKR1C1, RPP25L, UBE2E2, STON1, MEMO1, FYN, SHFL, FLRT2, FN3K, RNF181, LGMN, ZYG11B, SON, HLA-B, ARHGAP24, TEPSIN, OAS1, SERF2, SLC25A15, MX1, GPATCH1, HLA-C, KIT, MT-CO1, CBLB, PGGT1B, AKTIP, HABP2, LGSN, TAP2, NCAM2, OASL, TSEN34, SLC15A3, CD302, STK39, ZFYVE21, PDCD7, LGALS9, ASAH1, HLA-A, RDH10, FBN1, HVCN1, MED25, SERPINB7, GULP1, NME4, TXNIP, SPDL1, DDHD2, ERAP1, SLC25A3, KLF4, LMOD2, ELOVL5, IFI6, PLEKHM1, GAPVD1, BBS5, CRIPT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eGAS1, ACBD6, PACS2, CD248, XG, ADH1B, FBLN1, GPNMB, ADAMTS2, GFRalpha-1, SLC39A8, PSG1, FSTL1, PHPT1, TNXB, GFRA1, LRRC41, LY75, TOR1AIP2, CLN6, FBN2, SPRYD3, MFSD12, HLA-DRB1, DYNC2H1, ADGRD1, CREG1, SERPING1, TCEAL4, C1R, SVEP1, ITM2B, CUTC, PCOLCE, COL5A1, COL12A1, SMIM11, C1S, DCN, BNIP3, COL5A2, EGFL6, ITIH5, SBSN, SPARC, SELENOI, IL4I1, GSN, APBA3, COL1A1, CLK2, HNMT, DPYSL4, EFEMP1, CFB, COL3A1, PTX3, ACKR3, S100P, HBA2, APOH, C6orf89, HPX,C4A\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cdiv class=\"gridtable\"\u003e\n \u003cdiv align=\"left\" class=\"colspec\"\u003e\u003cbr\u003e\u003c/div\u003e\n \u003cdiv align=\"left\" class=\"colspec\"\u003e\u003cbr\u003e\u003c/div\u003e\n \u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eInduced and not detected proteins specific to different HSV serotypes\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eType\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSpecific to HSV-1\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSpecific to HSV-2\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCommon DEPs\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eInduced expression\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFARP2, CDC37, GPR39, HMMR, USH2A, NES, EVC, KIF5A, MED13L, ZFHX4, HYCC2, IRF7, SUCO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIGHV3-9, ANKHD1, GRID2, CNIH1, SERPINA1, GABRA1, TNNI3, SNCA, PLP1, SNCB, ARHGAP11A, CDH24, ABCA13, NRAC, USP38, DSCAML1, ADAM7, DENND2A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePOTEM, EREG, PALM, ZNF143, ZBTB17, GRB10, CEP55, PCNX4, SAMD1, SLC36A1, OR6Q1, ETNPPL, ORAI1, MASTL, TONSL, EYA3, PKMYT1, WDR54, FRMD4A, ZNF225\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNot detected\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCOX2, CBFA2T2, FZD6, JCHAIN, GNAO1, S100A7, TPD52, PTS, NR1H3, MAP7, NFE2L1, RTN1, GSTA5, MAGI2, CAMK1D, KATNAL2, LRRC20, FNIP1, PIGB, CLIP3, PLPPR2, MAGED4, ALKBH3, MID1IP1, CRIPT, PHF11, RPUSD1, LRP12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHLA-C, MITA, SIPA1L1, METAP2, L12A1, CFLAR, PRICKLE3, SLC4A1, LYN, CCNE1, CDKN2B, SLC6A9, CLCN5, PLTP, ERVK-19, ACTG1, CREM, IFT88, GRB7, ATP2B3, BBS9, LONRF3, ACT, PLEKHG4, SLC35D2, STRADA, PEX26, R3HCC1L, TRPT1, HOMER1, STXBP6, GIPC2, STON2, TOPBP1, RIPOR3, LXN, PAPOLG, RBKS,\u003c/p\u003e\n \u003cp\u003eUCK1, CHST12, ALKBH4, CGN, TNIK\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cdiv class=\"gridtable\"\u003e\u003cbr\u003e\u003c/div\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e\n \u003ch2\u003eInsights into Pathogenicity Differences\u003c/h2\u003e\n \u003cp\u003ePathway enrichment (KEGG) highlighted divergent host proteins and related signaling pathways, which are potentially responsible for viral pathogenicity differences. And all the mentioned proteins were shown in Tables\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e and Table\u0026nbsp;\u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e. \u003cstrong\u003e1) Divergent Immune Modulation\u003c/strong\u003e: HSV-1 more effectively suppresses inflammatory response (IL6ST, C3), antigen presentation (HLA-DRB3), and chemokine signaling (CXCL12, DEF8) compared to HSV-2. HSV-2 induces a stronger pro-inflammatory response (BCL3, PLG, SLFN11) than HSV-1. \u003cstrong\u003e2) Metabolic Reprogramming as a Serotype Signature\u003c/strong\u003e: HSV-1 upregulates PTDSS1 (Phosphatidylserine Synthase 1) to enhance lipid metabolism, while HSV-2 moderately promotes lipid metabolism (CYP27A1, ELOVL5), glycometabolism (GYS1, FBN1), and amino acid/energy metabolism (SLC25A15, SLC25A3). \u003cstrong\u003e3) Apoptosis and Cell Survival\u003c/strong\u003e: HSV-1 may suppress pro-apoptotic signals (BNIP3L, CASP14) to prolong cell survival, whereas HSV-2 may trigger apoptosis earlier. \u003cstrong\u003e4) Cellular Stress Responses\u003c/strong\u003e: HSV-1 may induce cell autophagy to create a favorable environment for viral replication, whereas HSV-2 may activate oxidative stress (MAFF, HMOX1) and the unfolded protein response (DNAJB5) to enhance the host immune response. \u003cstrong\u003e5) Serotype-Specific Host Protein Interactions\u003c/strong\u003e: Comparative analysis may reveal serotype-specific interactions with host proteins. For example, HSV-1 may interact more strongly with certain host factors involved in: Immunity and Inflammation (RSAD2, ISG20, CD274, IRF7, IL6ST, C3), Hippo signaling (WWC3, SAV1, PRC1), Antigen presentation (HLA-DRB3), Chemokine signaling (CXCL12, DEF8), Apoptosis regulation (BNIP3L, CASP14), DNA repair and epigenetics (SETX, REV3L, KDM4B, ARID5B, NSD2, HELLS, SMURF2), Protein folding and degradation (EDEM2, PSMG3). HSV-2 may interact more strongly with host factors involved in: Immunity and Inflammation (IGHV3-9, SERPINA1, BCL3, PLG, SLFN11, SERPIND1, ASAH1, TXNIP), Oxidative stress (MAFF, HMOX1), Unfolded protein response (DNAJB5), Metabolism and Transport (ABCA13, CNIH1), Lipid metabolism (CYP27A1, ELOVL5), Glycometabolism (GYS1, FBN1), Amino acid and energy metabolism (SLC25A15, SLC25A3), Protein modification and degradation (UBE2E2, RNF181, PGGT1B), DNA repair and epigenetics (MED25, ZYG11B). Taken together, these differential strategies suggest HSV-1 prioritizes immune evasion through ISG interference, whereas HSV-2 accelerates host inflammatory responses, potentially explaining clinical variations in lesion severity and recurrence rates. These findings provide proteomic-level insights into how closely related viral strains (sharing\u0026thinsp;~\u0026thinsp;83% glycoprotein homology) manifest distinct pathogenic outcomes, offering mechanistic clues for subsequent pathogenesis investigations. Through comparative analysis of host proteomic alterations induced by representative strains from two viral serotypes, we establish novel mechanistic associations between serotype-specific post-infection responses and their corresponding clinical manifestations, thereby advancing our understanding of viral pathogenesis determinants.\u003c/p\u003e\n \u003cp\u003eTo strengthen the clinical relevance of our findings, we compared our HFF-1 proteomic data with published datasets from HSV-infected neuronal and genital epithelial cells. Our proteomic data from HFF-1 cells align with Niko Hensel et al. [\u003cspan class=\"CitationRef\"\u003e14\u003c/span\u003e], who observed 28 host factors that may dampen the inflammasome response and modulate intracellular vesicle transport to promote HSV infection of the brain, suggesting a universal host response strategy across cell types. Conversely, Cheng J et al. [\u003cspan class=\"CitationRef\"\u003e15\u003c/span\u003e] reported global proteomic changes in the brain tissue of BALB/c mice vaginally infected with HSV-2, suggesting that synaptic structure and function alterations, as well as autophagy, may contribute to the development of neurologic abnormalities following HSV-2 infection. Our observation of HSV-2-induced lipid metabolism reprogramming contrasts with Cheng J et al. [\u003cspan class=\"CitationRef\"\u003e15\u003c/span\u003e], who reported synaptic dysfunction in HSV-2-infected mouse brains. This discrepancy may reflect tissue-specific adaptations, highlighting the need for comparative proteomic analyses across multiple models.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study provides a comprehensive and comparative proteomic characterization of alterations occurring during lytic HSV-1 and HSV-2 infection in HFF-1 cells. The results revealed significant changes in the abundance of proteins involved in immune, inflammatory, and metabolic pathways in response to HSV infection. These findings help further understanding molecular differences in serotype-specific HSV pathogenicity and open new avenues for investigating viral pathogenesis mechanisms and host antiviral responses.\u003c/p\u003e \u003cp\u003eSome researchers have used cerebrospinal fluid proteomics to compare the proteomic profiles of patients with meningitis or encephalitis caused by HSV-2 and varicella-zoster virus (VZV) [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Kulej et al. conducted a time-resolved multi-omics analysis of HSV-1 infection, encompassing the host and viral proteome, phosphoproteome, chromatin-bound proteome, and histone post-translational modifications (PTMs). While their study focused on post-translational modifications (PTMs), our DIA-MS approach revealed global proteome remodeling during HSV lytic infection[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. Consistent with Kulej et al., who reported HSV-1-induced phosphorylation in HFF-1 cells, our proteomic data confirm broad suppression of antigen presentation (e.g., HLA-DRB3) and metabolic reprogramming. However, our study uniquely demonstrates that HSV-1 prioritizes lipid metabolism (PTDSS1) and immune evasion, whereas HSV-2 amplifies inflammatory signaling (BCL3, PLG), suggesting serotype-specific strategies for host manipulation. In contrast to Wan et al. [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e17\u003c/span\u003e], who investigated subcellular proteome dynamics (cytoplasmic and nuclear fractions) during HSV-1 infection in HEK 293T cells, emphasizing host protein regulation independent of interferon signaling. Our study instead focused on looking at the overall changes in host proteins after HSV-1 or HSV-2 infection. Soh et al. [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e18\u003c/span\u003e] recently investigated temporal proteome dynamics during HSV-1 infection in human keratinocytes (HaCaT), emphasizing virus-induced degradation of host proteins (e.g., GOPC) and cell-surface remodeling mediated by HSV-1 pUL56. However, no prior research has addressed why the two HSV serotypes lead to distinct clinical manifestations. This study aims to explore the reasons underlying the serotype-specific clinical symptoms of herpes simplex virus (HSV) infections, providing new insights for future therapeutic approaches. We firstly determined the optimal infection conditions by analyzing cell morphology during lesion development and detecting viral protein expression. While MOI 0.5 ensured comparability of CPE severity and viral protein expression between HSV-1 and HSV-2, it may introduce heterogeneity in infection stages across the cell population. Future studies employing synchronized infection models (e.g., high MOI with centrifugal enhancement or time-resolved proteomics) will further resolve temporal host responses during early lytic infection. Samples were collected at this optimized time point, and mass spectrometry was performed to identify host proteomic changes during the lytic infection of HFF-1 cells by both HSV-1 and HSV-2. While HFF-1 cells serve as a well-established model for lytic infection, they lack the specialized microenvironment of neurons (HSV-1 latency site) or genital epithelial cells (HSV-2 tropism). Future studies should validate key findings in these clinically relevant cell types to confirm their clinical significance.\u003c/p\u003e \u003cp\u003eHSV infection causes widespread alterations in various signaling pathways, including immune modulation, inflammatory responses, and cellular metabolism. The three proteins selected for upregulation analysis following HSV-1 infection revealed key insights: Progesterone-induced blocking factor 1 (PIBF1) is an endogenous luteinizing hormone immunomodulatory factor. PIBF1 levels remain consistently elevated during pregnancy [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. It mediates the immunomodulatory effects of progesterone, promotes the proliferation and motility of triple-negative breast cancer cells, and is targeted by microRNA-203 in gastric cancer growth inhibition [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. PIBF1 plays a significant role in cell cycle regulation and invasion control. Tissue factor pathway inhibitor (TFPI) is an endogenous anticoagulant protein secreted by endothelial cells and macrophages. It regulates the coagulation cascade and significantly influences the pathophysiology of blood disorders [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. TFPI expression fluctuates in tumors, inflammatory diseases, and cardiovascular disorders [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e24\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eKinesin family member 22 (KIF22), a member of the kinesin superfamily, plays a role in intracellular transport and is implicated in bladder cancer, oral cancer, and melanoma [\u003cspan additionalcitationids=\"CR26 CR27\" citationid=\"CR22\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Its methylation status is linked to immune modulation and chemokine signaling. Conversely, proteins that were downregulated following HSV-1 infection included gp130, PLXNB1, and cystatin C. Gp130 (IL6ST) is a transmembrane protein and a common signaling receptor subunit of the IL-6 cytokine family [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. It is expressed in various organs such as the spleen, lungs, heart, and liver [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Gp130 has demonstrated anti-tumor, anti-inflammatory, and tissue-protective effects. Targeting gp130 has shown potential in anti-cancer therapy [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e31\u003c/span\u003e, \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e32\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eCystatin C is a low-molecular-weight protein secreted by nucleated cells, present in nearly all tissues and body fluids [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. While primarily used as a biomarker for kidney function [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e35\u003c/span\u003e], recent studies suggest its involvement in immune regulation and apoptosis [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Plexin B1 (PLXNB1) is a cell surface receptor belonging to the proteoglycan receptor family, with high affinity for signaling element 4D (SEMA4D). PLXNB1-mediated interactions regulate immune responses and cancer progression [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. These findings suggest that HSV-1 infection primarily affects membrane-bound and nuclear proteins, initiating distinct immune response pathways. Consistent with previous proteomic studies in corneal epithelial cells [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e12\u003c/span\u003e], our data confirm HSV-1-mediated suppression of antigen presentation pathways (e.g., HLA-DRB3 downregulation). This aligns with HSV-1\u0026rsquo;s known immune evasion mechanisms, such as ICP47-mediated inhibition of TAP-dependent peptide transport [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. This strategy may contribute to HSV-1 persistence in neuronal tissues, facilitating viral latency and recurrent infections.\u003c/p\u003e \u003cp\u003eProteins that are elevated after HSV-2 infection include PTGS2, AHSG, and PODXL.\u003c/p\u003e \u003cp\u003ePTGS2, also known as cyclooxygenase-2 (COX2), plays a key role in inflammation, pain, angiogenesis, and cancer progression [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. COX2 is a key enzyme in the conversion of arachidonic acid to prostaglandins I2, E2 and thromboxane A2. The PTGS2/COX2-PGE2 signaling axis is considered a major driver of inflammation and a direct cause of inflammatory responses [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. AHSG (Fetuin-A) is a glycoprotein synthesized by hepatocytes and found in human serum [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. It is associated directly or indirectly with cell growth and is believed to reduce inflammatory responses, though its precise role remains unclear [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. PODXL (Podocalyxin-like protein 1) is a transmembrane sialomucin that acts as either an anti-adhesion or pro-adhesion molecule, depending on the cellular environment. It can activate intracellular signaling pathways to promote cancer metastasis and plays a role in immune evasion [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e42\u003c/span\u003e, \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. MID1 is an E3 ubiquitin ligase and has been reported as a promising therapeutic target in Huntington\u0026rsquo;s disease [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. It is also implicated in antiviral immune responses, where it suppresses innate immunity by ubiquitinating IRF3 [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e45\u003c/span\u003e].Tenascin-X (TNXB) is an extracellular matrix glycoprotein expressed in skin, muscle, tendons, and blood vessels. It has anti-adhesion functions and is primarily involved in skin tissue homeostasis, likely by limiting keratinocyte formation and fibroblast proliferation/migration [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. Glycogen synthase 1 (GYS1), encoded by the GYS1 gene, is a core enzyme in glycogen synthesis, widely expressed in glycogen-producing tissues [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. It plays a central role in energy homeostasis. The antiviral effect of HSV-1 infection is primarily mediated through alterations in cellular immunoregulation, involving proteins such as PIBF1, KIF22, and TFPI. In contrast, HSV-2 enhances its lytic replication by modulating cell membrane proteins such as PLXNB1 and transmembrane proteins such as gp130. Additionally, cystatin C, a protein found in all tissues and body fluids, is one of the most important extracellular inhibitors of cysteine proteases, preventing extracellular protein degradation [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. HSV-2-infected cells likely downregulate surface proteins, transmembrane proteins, and extracellular matrix-disintegrating enzymes to facilitate viral replication and widespread infection [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Among the three proteins upregulated after HSV-2 infection, AHSG and PODXL were also upregulated in HSV-1-infected cells, though they did not rank among the top 20 differentially expressed proteins. PTGS2, a prostaglandin peroxidase synthase, is a key component of the PTGS2/COX2-PGE2 signaling axis, which serves as a major driver of inflammation. PODXL, a transmembrane sialomucin, functions as either an anti-adhesion or pro-adhesion molecule, depending on the cellular context [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. These findings suggest that PTGS2 and PODXL do not exhibit identical responses to inflammatory factors during HSV-1 and HSV-2 infections.\u003c/p\u003e \u003cp\u003eAmong the three proteins downregulated after HSV-2 infection, TNXB was also downregulated in HSV-1-infected cells, though to a lesser extent. TNXB, an extracellular matrix protein, is primarily expressed in skin, muscle, vasculature, and blood vessels. It has anti-adhesion functions and likely regulates keratinocyte and fibroblast proliferation/migration [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e47\u003c/span\u003e]. AHSG (α2-HS glycoprotein, also known as fetuin A) is a glycoprotein with multiple biological functions and plays a key role in inflammation regulation and tumor progression[\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. Its upregulation in HSV-2-infected cells suggests a role in HSV-2-induced cellular damage. MID1, as an E3 ubiquitin ligase, has been previously linked to viral infection and ubiquitin-mediated regulatory pathways [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. GYS1, a key enzyme in glycogen metabolism [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e48\u003c/span\u003e], suggests that HSV-2 infection alters cellular energy metabolism by modulating glycogen synthase activity. While our study identifies PTDSS1 as a key antiviral protein upregulated during HSV-1 infection, future research should utilize genetic or pharmacological inhibition of PTDSS1 to determine its necessity for HSV-1 propagation, particularly in lipid-dependent processes such as viral envelope formation. Similarly, employing neuronal or genital epithelial models would clarify whether these findings extend beyond fibroblasts to clinically relevant cell types. While our study focused on prototypical HSV-1 and HSV-2 strains, future investigations should validate these findings across diverse clinical isolates to assess strain-specific adaptations. While our study focused on host proteome remodeling, future work will include temporal viral proteomics (e.g., immediate-early/early/late protein kinetics) to precisely map replication stages. This will further strengthen correlations between viral activity and host responses.\u003c/p\u003e \u003cp\u003eIn conclusion, this study presents the high-resolution comparative proteomic atlas of HSV-1 and HSV-2 infections, mapping host pathways hijacked for serotype-specific pathogenesis. Despite the model's simplicity, our data reveal actionable targets (PTDSS1, BCL3) and biomarkers (FARP2, IGHV3-9) with translational potential. Future research must focus on in vivo validation and therapeutic exploitation, ultimately bridging the gap between molecular insights and clinical solutions for HSV-related morbidity.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eOur study provides a novel perspective on HSV pathogenesis by elucidating serotype-specific host proteome rewiring, highlighting the critical role of host metabolic and immune remodeling in driving viral tropism and clinical manifestations. The proteomic signatures identified\u0026mdash;such as the upregulation of PTDSS1 (linked to lipid metabolism in HSV-1) and BCL3 (associated with NF-κB activation in HSV-2)\u0026mdash;reveal actionable targets for serotype-specific therapeutic interventions. For instance: Pharmacological inhibition of PTDSS1, a phosphatidylserine synthase essential for viral envelope formation, could disrupt HSV-1 replication in neuronal tissues. Targeting BCL3-mediated NF-κB signaling may mitigate HSV-2-induced inflammatory damage in genital mucosa. These findings, combined with the differential expression of immune checkpoints (e.g., CD274) and metabolic regulators (e.g., GYS1), provide a foundation for developing precision therapies, such as small-molecule inhibitors or monoclonal antibodies tailored to serotype-specific host-virus interactions. Future studies should prioritize validating these targets in in vivo models and clinical isolates, bridging mechanistic insights into therapeutic applications.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHSV-1\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eherpes simplex virus type 1\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHSV-2\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eherpes simplex virus type 2\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHFF-1\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ehuman foreskin fibroblast\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eDEPs\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003edifferentially expressed proteins\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eDIA-MS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003edata-independent acquisition mass spectrometry\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eWHO\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eWorld Health Organization\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eVZV\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003evaricella-zoster virus\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eDMEM\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eDulbecco\u0026rsquo;s Modified Eagle\u0026rsquo;s Medium\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eFBS\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003efetal bovine serum\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eMOI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003emultiplicity of infection\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eFASP\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eFilter-aided sample preparation\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eIAA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eiodoacetamide\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eUA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eUrea-Alkylating\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eiRT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eindexed retention time\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eIT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003einjection time\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHCD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ehigher-energy collisional dissociation\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eFDR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003efalse discovery rate\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eGO\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eGene Ontology\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eKEGG\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eKyoto Encyclopedia of Genes and Genomes\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSVM\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003esupport vector machine\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ehpi\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ehours post-infection\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCPE\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ecytopathic effects\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePIBF1\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eprogesterone-induced blocking factor 1\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eTFPI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003etissue factor pathway inhibitor\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eKIF22\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ekinesin family member 22\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePLXNB1\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePlexin B1\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eGYS1\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eGlycogen synthase 1\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePODXL\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePodocalyxin-like protein 1\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCOX2\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ecyclooxygenase-2\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePTM\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003epost-translational modifications\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by the Natural Science Foundation of Yunnan Province (202401AS070048, 202401BC070008), the Chinese Academy of Medical Sciences (CAMS) Innovation Fund for Medical Sciences (CIFMS) (2022-12M-CoV19-002), the Innovation Team Project of Yunnan Science and Technology Department (202105AE160020).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEthical approval was waived as the study utilized commercially available cell lines (HFF-1, Ao Rui Cell) without human or animal experimentation.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors approved the final manuscript and consented to its submission.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe DIA-MS data have been deposited in the ProteomeXchange database under accession number PXD062161.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u003c/strong\u003e\u003cstrong\u003e\u0026rsquo; contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSJD and PXH designed and performed research. XJX, ZZD, GXM, LJX, QY, XJW, HYZ and LD contributed new reagents and analytic tools. SJD and PXH analyzed data. SJD and PXH \u0026nbsp;wrote the manuscript. All authors read and approved the final version.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAlMukdad, S.; Harfouche, M.; Farooqui, U. S.; Aldos, L.; Abu-Raddad, L. J., Epidemiology of herpes simplex virus type 1 and genital herpes in Australia and New Zealand: systematic review, meta-analyses and meta-regressions. \u003cem\u003eEpidemiol Infect \u003c/em\u003e\u003cstrong\u003e2023,\u003c/strong\u003e 151, e33.\u003c/li\u003e\n\u003cli\u003eNiemeyer CS, Merle L, Bubak AN, Baxter BD, Gentile Polese A, Colon-Reyes K, Vang S, Hassell JE Jr, Bruce KD, Nagel MA, Restrepo D. Olfactory and trigeminal routes of HSV-1 CNS infection with regional microglial heterogeneity. J Virol. 2024 Nov 19;98(11):e0096824. \u003c/li\u003e\n\u003cli\u003eItzhaki RF. 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RNF213 modulates \u0026gamma;-herpesvirus infection and reactivation via targeting the viral Replication and Transcription Activator. \u003cem\u003eProceedings of the National Academy of Sciences of the United States of America \u003c/em\u003e2023 ;120(12):e2218825120.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"virology-journal","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"virj","sideBox":"Learn more about [Virology Journal](http://virologyj.biomedcentral.com/)","snPcode":"12985","submissionUrl":"https://submission.nature.com/new-submission/12985/3","title":"Virology Journal","twitterHandle":"@VirologyJ","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"HSV-1, HSV-2, proteomics, viral pathogenesis, metabolic reprogramming, antiviral immunity","lastPublishedDoi":"10.21203/rs.3.rs-6065975/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6065975/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eHerpes simplex virus type 1 (HSV-1) and type 2 (HSV-2) exhibit distinct clinical manifestations, yet the molecular basis of their serotype-specific pathogenicity remains unclear. This study presents a comparative proteomic analysis of human foreskin fibroblast (HFF-1) cells during lytic HSV-1 and HSV-2 infections to elucidate host-pathogen interactions driving differential virulence. Using data-independent acquisition mass spectrometry (DIA-MS), we identified 280 and 219 differentially expressed proteins (DEPs) in HSV-1- and HSV-2-infected cells, respectively. Key DEPs, validated via qPCR and Western blot, revealed serotype-specific modulation: HSV-1 upregulated antiviral effectors (ISG20, IRF7) while downregulating chemokine signaling (CXCL12, DEF8) and promoting lipid metabolism (PTDSS1). In contrast, HSV-2 upregulated inflammatory effectors (IGHV3-9, SERPINA1), enhanced NF-κB signaling (BCL3), and altered glycometabolism (GYS1, FBN1). Pathway enrichment analysis showed that HSV-1 suppressed inflammatory and antigen presentation pathways to evade immune responses, whereas HSV-2 induced stronger pro-inflammatory responses and metabolic reprogramming related to lipid and glycometabolism. These distinct strategies may explain HSV-1’s neurotropism and HSV-2’s genital tropism. Our findings provide a proteomic roadmap for understanding serotype-specific pathogenesis. This study underscores the role of host proteome remodeling in HSV divergence and informs strategies for serotype-specific interventions.\u003c/p\u003e","manuscriptTitle":"Comparative proteomic analysis of HFF-1 cells between lytic HSV-1 and HSV-2 infection: Insights into differences in pathogenicity specific to serotypes","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-10 07:19:50","doi":"10.21203/rs.3.rs-6065975/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2025-04-25T00:33:14+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-04-25T00:00:06+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-04-22T04:17:56+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"165757285306252585349701165095055796403","date":"2025-04-08T00:00:43+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"150925489742198740023284522450341661639","date":"2025-04-07T14:55:01+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-04-07T13:32:51+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-04-07T06:25:01+00:00","index":"","fulltext":""},{"type":"submitted","content":"Virology Journal","date":"2025-04-05T12:07:13+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"virology-journal","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"virj","sideBox":"Learn more about [Virology Journal](http://virologyj.biomedcentral.com/)","snPcode":"12985","submissionUrl":"https://submission.nature.com/new-submission/12985/3","title":"Virology Journal","twitterHandle":"@VirologyJ","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"6d754b41-047b-4179-b8e4-8e6eb02c7f34","owner":[],"postedDate":"April 10th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-07-21T15:59:28+00:00","versionOfRecord":{"articleIdentity":"rs-6065975","link":"https://doi.org/10.1186/s12985-025-02803-w","journal":{"identity":"virology-journal","isVorOnly":false,"title":"Virology Journal"},"publishedOn":"2025-07-14 15:56:55","publishedOnDateReadable":"July 14th, 2025"},"versionCreatedAt":"2025-04-10 07:19:50","video":"","vorDoi":"10.1186/s12985-025-02803-w","vorDoiUrl":"https://doi.org/10.1186/s12985-025-02803-w","workflowStages":[]},"version":"v1","identity":"rs-6065975","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6065975","identity":"rs-6065975","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}