Microarray analysis of novel genes involved in HSV-2 infection

doi:10.21203/rs.3.rs-517057/v1

Background: Herpes simplex virus type 2 infects the body and becomes an incurable and recurring disease. The pathogenesis of HSV-2 infection is not completely clear.

Methods: We analyze the GSE18527 dataset in the GEO database in this paper to obtain distinctively displayed genes(DDGs)in the total sequential RNA of the biopsies of normal and lesioned skin groups, healed skin and lesioned skin groups of genital herpes patients, respectively.The related data of 3 cases of normal skin group, 4 cases of lesioned group and 6 cases of healed group were analyzed.The histospecific gene analysis , functional enrichment and protein interaction network analysis of the differential genes were also performed, and the critical components were selected.

Results: 40 up-regulated genes and 43 down-regulated genes were isolated by differential performance assay.

Histospecific gene analysis of DDGs suggested that the most abundant system for gene expression was the skin, immune system and the nervous system.Through the construction of core gene combinations, protein interaction network analysis and selection of histospecific distribution genes, 17 associated genes were selected：CXCL10,MX1,ISG15,IFIT1,IFIT3,IFIT2,OASL,ISG20,RSAD2,GBP1,IFI44L,DDX58,USP18,CXCL11,GBP5,GBP4 and CXCL9.The above genes are mainly located in the skin, immune system, nervous system and reproductive system.

Conclusion:This paper elucidates an effective approach for a new mechanism of HSV-2 infection, and the molecular mechanism of the selected core genes in the process of HSV-2 infection requires future experimental studies.

Biomedical Engineering

HSV-2 infection

Microarray analysis

Histospecific gene expression

Herpes simplex virus type 2 (HSV-2) infection is a widespread infectious disease that is the primary cause of most clinical cases of genital ulcers worldwide; it can be activated repeatedly after infection. HSV-2 can cause meningitis, encephalitis, sacral radiculitis and myelitis.HSV-2 can cause multi-system diseases after infecting the body, and the etiology is complicated[1]. However, the pathogenesis of HSV-2 infection is not fully understood.

IFN-β plays a key role in antiviral activity in early-induced defenses to limit viral replication and transmission after HSV-2 enters the genital epithelium; previous studies confirm the inhibition of IFNβ production during HSV-2 infection. Multiple viral components during HSV-2 infection produce immune escape by inhibiting type I interferon expression through inhibition of the DNA receptor pathway, resulting in lifelong infection of the organism[2].

There was a large infiltration of T cells, monocytes/macrophages, numerous myeloid cells and a small number of plasmacytoid dendritic cells, low expression of type I interferons (IFNα and IFNβ), as well as detection of large amounts of HSV-2 antigen and HSV-2 RNA within skin lesion biopsy specimens in the acute phase of HSV-2 infection[3].Data analysis and exploration of genes associated with low expression of type I interferon during HSV-2 infection are still insufficient.Genes associated with low expression of type I interferon after HSV-2 infection were selected in this paper by database analysis and data exploration.

Therefore, we used statistical analysis and data mining to reveal the genes responsible for the low expression of type I interferon associated with HSV-2 infection. We used the GSE18527 dataset created by whole genome analysis analysis of skin biopsies during HSV-2 activation in the skin mucosa by Peng T et al. to obtain DDGs between normal and lesioned skin groups, healed skin and lesioned skin group, and then the integration of the 2 groups is taken.

This study contributes to the understanding of the etiology of immune escape after HSV-2 infection in the organism and provide new thinking for the clinical management of HSV-2 infection.

Distinctively displayed genes

The GSE18527 dataset was imported at the GEO database and differentially expressed mRNAs were analyzed in R software using the Limma package (version: 3.40.2). Adjusted P values were analyzed in GEO to correct for false positive results; "Adjusted -P < 0.05 and log2 (fold change) > 4" was defined as the threshold to screen for DDGs. 49 upper-regulated genes and 192 lower-regulated genes were isolated in the normal and lesioned skin groups; 110 upper-regulated genes and 43 lower-regulated genes were isolated in the healed and lesioned skin groups.40 upper-regulated genes and 43 lower-regulated genes were recognized after taking crossovers for the 2 subgroups. As Table 1 shows, 36 of the 83 DDGs (43.4%, 31 up-regulated and 5 down-regulated) were mainly distributed in the skin, and most of the above genes were concerned with epidermal development, skin development, keratin-forming cell differentiation and other functions; 21 genes (fcer1a, cd1a, fpr1, fcn1, etc.) were relevant to the immune system. CXCL10 gene expression was significantly down-regulated with a significantly lower P value (P < 0.0001). Figure 1 displays the Venn diagram and heat map of the DDGs.

Histospecific Gene analysis

Histospecific representation of DDGs were investigated by genecards database. The most histospecific expressed systems were the skin system (43.4%, 36/83); the blood/immune system was next (25.3%, 21/83); the nervous system (7%, 6/83); the reproductive system (2%, 2/83); and the visceral and digestive systems were the least enriched (1%, 1/83) (Table 2).

Functional and pathway enrichment analysis of DDGs

GO and KEGG enrichment assay of underlying mRNAs was performed using the ClusterProfiler suite of programs in R software.Expression heat maps were presented by the R package pheatmap. 3 functional enrichment aliases, 328 enriched GO species and 21 KEGG pathways were isolated.Table 3 lists the enrichment aliases with P < 0.000005; they include Viral protein interaction with cytokine and cytokine receptor (P = 1.51065E-09) and IL-17 signaling pathway (P = 4.47045E-07 ); the MF class of chemokine receptor binding (P = 1.85516E-08 ) and G protein-coupled receptor binding (P = 5.19828E-07 ). In addition, nine enriched keywords were included, including epidermis development (1.19541E-17); response to virus (5.02351E-12), etc. Figure 2 illustrates the P values and gene counts of the 12 enriched functional items.

PPI network analysis of DDGs

A PPI network having 82 nodes as well as 429 edges was computed from the STRING database; the interaction score of this network was > 0.4 (Fig. 3A). The dots stand for genes and the edges stand for the linkage between genes. Red means upper-regulated genes and blue means lower-regulated genes.

We used MCODE,cytoHubba in Cytoscape to carry out gene clustering to recognize critical PPI network segments. As displayed in Fig. 3B,C,D, 3 critical segments were isolated. The above 3 critical segments are mainly concerned with the response to the virus, the development of the epidermis, and the structural components of the cytoskeleton(Table 3).

Characterization of genes of interest

We used the MCODE plugin in cytoscape to identify the top 20 genes by the MCC method, of which 8 down-regulated genes (IFIT2,IFIT3,RSAD2,gbp1,ifi44l,gbp4,GBP5,cxcl8 ) were connected to the immune system.

PPI network analysis screened a critical combination of 21 genes (DDX58, CD163, EPSTI1, OASL, MX1, USP18, ISG15, GBP1, CCL8, IL6, GBP4, ISG20, IFIT3, IFIT1, CXCL9, IFIT2, RSAD2, CXCL11, CXCL10, GBP5, IFI44L).Type I interferon plays a key role in suppressing HSV-2 infection. Using the genecards database, we screened four genes (gbp1, gbp4, ifit3, rsad2) associated with the expression of type I interferon.In addition, a few other underlying relevant genes among the histospecific displayed genes were singled out using the genecards database.Table 4 exhibits all genes of interest.

In this research, we based on the GSE18527 dataset in the GEO database to recognize the distinctively displayed genes(DDGs) of the total RNA after sequencing of normal skin of controls and lesioned skin of genital herpes patients, healed skin biopsies and lesioned skin, respectively; and took the crossover of the 2 sets of samples to minimize and enhance the potential pathogenic genes in HSV-2, selecting a couple of novant genes to be correlated with this disease that have not been investigated yet.

Previous studies have shown that RNA sequencing of lesion biopsies from the same sites during healing of HSV-2-infected skin tissue and at 2 and 4 weeks after healing showed no HSV-2 nucleic acids or antigens; however, IFN-γ was consistently expressed and IFN-β and IFN-α levels were very low; HSV-2 preventing the innate immune system from producing type I interferon may be a major factor in allowing the virus to break through the host mucosal defenses[3].In our study, we found a significant decrease in the expression level of type I interferon-related genes, which proves the accuracy of the method of this study.

We identified 83 DEGs in HSV-2-infected patients, including 40 up-regulated and 43 down-regulated genes, with the most differentially expressed genes in the cutaneous system, followed by the immune, nervous and reproductive systems, and the differential tissue expression could explain the life history after HSV-2 infection of the organism.HSV-2 virus invades through exposure to supraepithelial cells to produce initial infection and duplicates within the supraepithelial cells, after which HSV-2 ascends through the periaxonal sheaths of sensory nerves to the sacral ganglia of the host nervous system, where it becomes a reservoir for future outbreaks and subclinical genital viral shedding[4].

The differential genes were most expressed in the cutaneous system, suggesting that the skin is the primary barrier against HSV-2 infection and exerts a crucial role in innate and acquired immunity.Although HSV-2 can infect skin epithelial cells, immune cells and neuronal cells, it first infects mucosal epithelial cells during sexual transmission; keratinocytes are the main cells involved in HSV-2 clinical damage.Keratin-forming cells in the skin epidermis are considered to be immunologically active cells that not only act as a physical barrier, but also recognize the source of infection and initiate the innate immune response, including secretion of various cytokines (e.g., interleukins, interferons, clone-stimulating factors, growth factors, etc.), expression of cytokine receptors, recruitment of immune cells, enhancement of acquired immunity, and indirect elimination of the initial infection and prevention of subsequent infections[5].

PPI network and critical components analysis selected four genes (gbp1, gbp4, ifit3, rsad2) associated with type I interferon expression. the GBPS family is induced by both type I and type II IFNs, and according to the uniprot database annotation gbp1 hydrolyzes GTP to GMP; gbp4 hydrolyzes GTP by binding GTP, GDP and GMP. The cGAS-STING pathway performs a core role in the generation of type I interferon after identification of double-stranded DNA virus; the cyclic GMP-AMP (CGAMP) synthase (CGAS) upstream of the pathway is a cytoplasmic DNA sensor that triggers downstream STING by catalyzing the synthesis of cyclic GMP-AMP (CGAMP) from ATP and GTP, which ultimately leads to transcriptional elicitation of type I interferon[6].Studies have confirmed that endogenous GBPS levels can induce the release of DNA from exposed bacteria in the cytoplasm, which in turn is sensed by cGAS[7].

ifit3 is an IFN-inducible antiviral protein that enhances the MAVS-mediated host antiviral response by acting as an articulator linking TBK1 to MAVS, leading to TBK1 activation and IRF3 phosphorylation, with phosphorylated IRF3 translocating into the nucleus to promote antiviral gene transcription[8].Also known as interferon-induced iron-sulfur (4FE-4S) cluster-binding antiviral protein, rsad2 functions predominantly in the type I and type II interferon-induced cellular anti-virus status and inhibits a broad diversity of DNA and RNA viruses[9].These information indicate that disorders of gbp1, gbp4, ifit3, and rsad2 may contribute to the suppression of type I interferon expression leading to the production of HSV-2 immune escape.

Myelitis and encephalitis caused by HSV-2 infection are common in HSV-2 infection. We identified four upregulated genes ephb6,nfix,mlana,tyrp1 and two downregulated genes wars1,mx1 by screening for genes specifically expressed in nervous system tissues.ephb6 regulates cell adhesion and migration by binding to ephrin-B1 and ephrin-B2[10].NFIX identifies and combines the palindromic sequence 5'-TTGGCNNNNGCCAA-3' present in viral and cytosolic promoters as with the adenoviral type 2 replication motif[11]. Mlana is engaged in melanin production and plays a crucial role in the production, maintenance, export and machining of the melanocyte protein PMEL, which is essential for the generation of phase II melanosomes[12].Tyrp1 plays a role in melanin biosynthesis and can regulate or influence the type of melanin that is synthesized[13].Studies have confirmed that melanocytes are melanin-producing cells with emerging innate immune functions, including the expression of antiviral type I interferon cytokines[14]. Tryptophanyl-tRNA synthetase 1 (WARS1) is an endogenous ligand of mammalian Toll-like receptors (TLR2 and TLR4). Microarray data, using mRNA from WARS1-treated human peripheral blood mononuclear cells (PBMCs), had indicated WARS1 to mainly activate innate inflammatory responses[15].Mx1 synthesizes interferon-inducible kinesin-like GTPases with antiviral activity against a variety of RNA viruses and some DNA viruses[16].Their imbalance may contribute significantly in the etiology of HSV-2-induced CNS infections.

HSV-2 infection is mainly transmitted through sexual contact, and we identified the pla2g2a and mamdc2 gene to be distributed mainly in the genital system.pla2g2a synthesizes secreted calcium-dependent phospholipases that primarily target extracellular phospholipids and are associated with host antimicrobial defense, inflammatory response and tissue regeneration; contributing to lipid remodeling of cell membranes and production of lipid mediators involved in pathogen clearance[17]. Also, by disrupting the integrity of the mitochondrial membrane, it promotes the release of effective damage-related molecular pattern molecules in the circulation, thereby activating the innate immune response[18].Single-cell RNA sequencing analysis confirms host-length non-coding RNA MAMDC2-AS1 as a cofactor for HSV-1 nuclear transport[19].The role of pla2g2a and mamdc2 in the pathogenesis of HSV-2 infection needs to be confirmed by further experiments.

Genes associated with type I interferon expression were identified from GO enrichment analysis, including IFIT2, IFIT3, ISG20, MMP12, MX1, ISG15, and RSAD2.RSAD2 was significantly downregulated 3.246-fold and 3.103-fold in the control-lesioned and healed-lesioned groups, respectively.RSAD2 is an ancient mechanism of protection against viral infection and serves an essential and many-sided role in the innate autoimmune reaction to viral infection; RSAD2 protein interacts with viral proteins and RSAD2 protein fosters the antiviral response by directly challenging viral proteins for decay and also contributes to the ubiquitin-dependent proteasomal decay of some of the antiviral proteins with which it interacts[20].In one study, immunohistochemical staining of vaginal tissue after systemic injection of 2'3'-cGAMP in mice revealed strong expression of RSAD2 protein in cells in the induced mesenchyme; epithelial cells close to the basement membrane were positive for RSAD2 protein, while epithelial cells located on the luminal side of the canal expressed less. Vaginal tissues of mice locally infected with HSV2 had strong RSAD2 protein expression in cells at the site of infection. A few cells co-expressed RSAD2 protein and HSV-2 antigen, but cells surrounding HSV-2 infected cells expressed high levels of RSAD2 protein suggesting that RSAD2 protein is involved in the body's immune response to HSV2 infection[21].ISG15 was significantly downregulated 4.401-fold and 2.203-fold in control-lesioned and healed-lesioned, respectively.ISG15 can inhibit viral translation, replication and release.ISG15 was found to preferentially co-translationally bind to newly synthesized proteins, suggesting that ISGization may be a general, non-specific host defense mechanism[22].A study found that isg15-/- mice were prone to infection with influenza A and B, HSV-1 and Sindbis virus[23].

In this study, we employed finding-driven analysis to identify DDGs and selected four genes (gbp1, gbp4, ifit3, rsad2) associated with type I interferon expression by building a PPI network and recognizing critical components. The association of these genes with HSV-2 infection needs to be further investigated.

This research used the GSE18527 dataset of the GEO database to screen distinctively displayed genes in the overall RNA of skin biopsy sequences from genital herpes patients at different stages, followed by histospecific Gene analysis, feature enrichment and protein-protein interaction network analysis to define critical components. The most enriched system for histospecific Gene expression was the skin, and then the immune system and the nervous system. Functional and pathway enrichment analysis of differential genes was performed for nine enrichment keywords, including epidermal development; response to viruses, etc. We used Cytoscape for gene clustering to pinpoint critical PPI network components and defined three key components. We used the MCODE plugin in Cytoscape to identify the top 20 genes, and on basis of the genecards database, we artificially pinpointed four genes associated with type I interferon expression.

Microarray data

The GSE18527 dataset created from Peng T et al. was downloaded at GEO database.The dataset was derived from the GPL6255 Illumina humanRef-8 v2.0 expression beadchip platform,the experiment contained 19 samples, including 3 pre-treatment normal skin, 4 pre-treatment lesioned skin, 6 post-healing group lesioned skin biopsies and 6 post-healing group normal skin biopsies. Since this is a public dataset, age, health status and medication use of these individuals are not available. Annotated files for GPL6255 were also downloaded from GEO.

Differential expression analysis

The data were downloaded in MINiML format. Differentially expressed mRNAs were studied using the Limma software package (version: 3.40.2) of R. Adjusted P values were analyzed in GEO to correct for false positive results, and differentially expressed mRNAs were screened at a threshold defined by Adjusted P < 0.05 and logFC > 4. We divided the samples into 2 groups, normal skin biopsy and lesioned skin group, and healed skin and lesioned skin group, and gain the DDGs after taking the crossovers for the two subgroups.Venn diagrams of DDGs were produced with web-based facility Venny (https://www.xiantao.love), and expression heat maps were presented by the R package pheatmap.

Histospecific Gene analysis

Histospecific expression of differential genes were analyzed by genecards database. Transcripts from individual tissues that meet the following quasi-assays are considered extremely histospecific: based on RNA-seq from GTEx reads to obtain a list of tissues with positive differential gene expression, ploidy change values were calculated for each sample using DESeq software, and each sample read was compared to all GTEx sample reads, and genes with ploidy change values > 4 in the tissue were defined as being positively differentially expressed in that tissue. Genes with maximum read counts below 5 across tissues were excluded from the calculation.

Functional enrichment Analysis of DDGs

Latent functions of Latent targets were identified through functional enrichment analysis of the data. Gene ontology (GO) containing molecular functions (MF), biological pathways (BP) and cellular components (CC) is widely used to provide indications of genes with defined functions.kEGG enrichment analysis is practical available for analyzing gene functions as well as related high-level genomic functional information. The ClusterProfiler in R was utilized to profile the GO function of latent mRNAs and enrich the KEGG pathway. Box line plots were performed by the R package ggplot2; PCA plots were performed by the R package ggord.

Protein interaction (PPI) network profiling

PPI network profiling was performed via the STRING database. The DDGs were uploaded to the STRING database and the threshold of the score of the correlation was adjusted to > 0.4.

In addition, PPI networks were visualized and constructed using Cytoscape(v 3.6.0) software, and the node with the highest number of interactions with neighboring nodes was called the central node.

To identify critical PPI network components, gene network clustering analysis was performed using cytohubba and MCODE in the Cytoscape software package. Critical components were defined by sensitivity thresholds of P < 0.05.

Statistical analysis

All statistical analyses were performed with R statistical software. For all assays, two-sided P value of less than 0.05 indicated a statistically significant difference.

Acknowledgements

The authors gratefully acknowledge the Gene Expression Omnibus (GEO) database which made the data available.

Authors’ contributions

This research was conducted in collaboration with all authors. Zhang Hao performed the data curation and analysis. Zhang Hao analyzed and interpreted the results. Zhang Hao and Liu Tao drafted and reviewed the manuscript. All authors read and approved the final manuscript.

Funding

We are very grateful for the support of the Wuxi Medical Development Discipline - Infectious Disease Development Discipline Fund (Grant number: FZXK006).

Availability of data and materials

The raw data of this study are derived from the GEO database (https:// www. ncbi. nlm. nih. gov/ geo/), which are publicly available databases.

Ethics approval and consent to participate

Not necessary.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

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TABLE 1 Differentially expressed genes in HSV-2 infection. The genes marked with an asterisk are mainly located in the skin.

gene symbol adjusted p-value Fold change Gene title Location

control-lesioned healed-lesioned control-lesioned healed-lesioned

up regulated genes

AXIN2* 2.40E-04 6.21E-05 2.555 2.334 Axin2 Chr17

TUFT1* 5.99E-04 2.03E-05 2.364 2.154 Tuftelin 1 Chr1

WFDC5* 6.55E-04 4.45E-05 2.121 2.247 WAP four-disulfide core domain 5 Chr20

KRT15* 1.10E-03 1.32E-04 3.336 3.286 keratin 15 Chr17

APCDD1* 1.24E-03 3.12E-05 2.768 2.547 APC down-regulated 1 Chr18

EXPH5* 1.35E-03 2.57E-04 2.587 2.065 Exophilin 5 Chr11

NMU* 1.36E-03 4.83E-05 2.389 2.661 Neuromedin U Chr4

CDHR1* 1.44E-03 4.30E-05 2.787 2.360 Cadherin related family member 1 Chr10

COL7A1 1.66E-03 4.38E-05 2.573 2.358 Collagen type VII alpha 1 chain Chr3

RAPGEFL1* 1.66E-03 2.03E-05 2.456 2.695 Rap guanine nucleotide exchange factor like 1 Chr17

EPHB6 1.74E-03 3.12E-05 2.531 2.508 EPH receptor B6 Chr7

MLANA 2.15E-03 2.31E-04 2.516 2.484 Melan-A Chr9

ALDH3A1* 2.23E-03 3.11E-05 2.136 2.642 Aldehyde dehydrogenase 3 family member A1 Chr17

DCT* 2.23E-03 3.37E-04 2.833 2.379 Dopachrome tautomerase Chr13

IL20RB* 2.36E-03 1.13E-04 2.544 2.223 Interleukin 20 Receptor Subunit Beta Chr3

PHGDH* 3.03E-03 8.07E-05 2.417 3.026 Phosphoglycerate dehydrogenase Chr1

POU3F1* 3.10E-03 1.04E-04 2.174 2.036 POU class 3 homeobox 1 Chr1

NFIX 3.74E-03 2.48E-04 2.035 2.054 Nuclear factor I X Chr19

CTNNBIP1* 3.95E-03 1.59E-03 2.404 2.168 Catenin beta interacting protein 1 Chr1

SOX21* 4.75E-03 8.14E-05 2.496 2.748 SRY-box transcription factor 21 Chr13

AADACL2* 4.87E-03 4.72E-05 2.012 2.702 Arylacetamide deacetylase like 2 Chr3

FCER1A 8.74E-03 6.83E-04 2.096 2.437 Fc fragment of IgE receptor Ia Chr1

GPNMB* 9.64E-03 2.18E-04 2.198 2.197 Glycoprotein nmb Chr7

SERPINA12*1.37E-02 2.65E-03 2.774 2.477 SERPINA12 Chr14

DSC1* 1.41E-02 2.26E-04 2.271 2.779 Desmocollin 1 Chr18

MAMDC2 1.68E-02 7.13E-04 2.054 2.173 MAM domain containing 2 Chr9

FLG2* 2.23E-02 2.10E-04 2.946 3.650 Filaggrin family member 2 Chr1

KRT31* 2.80E-02 1.47E-02 2.029 3.492 keratin 31 Chr17

PMEL* 2.89E-02 3.35E-04 2.137 2.746 Premelanosome protein Chr12

CD1A 2.99E-02 8.10E-03 2.107 2.007 CD1a molecule Chr1

LCE2D* 3.99E-02 4.71E-04 2.790 3.490 LCE2D Chr1

TYRP1 4.53E-02 9.88E-04 2.531 2.769 Tyrosinase Related Protein 1 Chr9

LCE5A* 4.65E-02 1.93E-03 2.088 2.350 Late Cornified Envelope 5A Chr1

LOR* 5.81E-02 5.06E-04 2.077 2.733 Loricrin Cornified Envelope Precursor Protein Chr1

HLA-DQB2*8.11E-02 2.74E-02 2.542 2.220 HLA Class II Histocompatibility Antigen Chr6

DQ Beta 2 Chain

LCE1B* 9.39E-02 5.27E-04 2.410 3.423 Late Cornified Envelope 1B Chr1

LCE2B* 9.87E-02 2.21E+00 0.001 2.877 Late Cornified Envelope 2B Chr1

LCE1C * 9.96E-02 2.93E-04 2.033 3.154 Late Cornified Envelope 1C Chr1

LCE2A* 1.06E-01 6.24E-04 2.167 3.249 Late Cornified Envelope 2A Chr1

LCE2C* 1.23E-01 1.38E-03 2.166 3.046 Late Cornified Envelope 2C Chr1

Down regulated genes

KRT16 4.90E-06 3.97E-02 4.917 2.151 Keratin 16 Chr17

CXCL10 5.85E-06 4.42E-05 7.199 3.841 C-X-C Motif Chemokine Ligand 10 Chr4

FPR1 1.28E-05 5.83E-07 3.739 2.992 Formyl Peptide Receptor 1 Chr19

KRT6C* 3.14E-05 3.07E-02 5.158 2.324 Keratin 6C Chr12

CXCL9 3.64E-05 6.27E-04 6.408 3.299 C-X-C Motif Chemokine Ligand 9 Chr4

S100A9* 4.02E-05 6.55E-02 5.395 2.876 S100 Calcium Binding Protein A9 Chr1

FCN1 4.22E-05 2.28E-04 3.891 2.604 Ficolin 1 Chr9

EPSTI1 7.55E-05 7.06E-04 4.462 2.381 Epithelial Stromal Interaction 1 Chr13

GZMB 7.55E-05 2.91E-04 3.640 2.481 Granzyme B Chr14

CCL8 2.28E-04 1.43E-03 5.669 3.972 C-C Motif Chemokine Ligand 8 Chr17

WARS 2.28E-04 1.77E-05 4.916 3.317 Tryptophanyl-TRNA Synthetase 1 Chr14

MX1 2.28E-04 2.07E-04 4.226 2.127 MX Dynamin Like GTPase 1 Chr21

CXCL11 2.28E-04 9.99E-06 5.839 4.824 C-X-C Motif Chemokine Ligand 11 Chr4

GBP1 2.28E-04 2.96E-05 5.033 3.027 Guanylate Binding Protein 1 Chr1

LILRB3 2.64E-04 3.03E-04 3.604 2.433 Leukocyte Immunoglobulin Like Chr19

Receptor B3

GBP5 2.67E-04 5.61E-05 4.203 3.133 Guanylate Binding Protein 5 Chr1

GBP4 3.35E-04 1.32E-04 3.997 2.397 Guanylate Binding Protein 4 Chr1

CXCL8 3.88E-04 4.13E-03 3.064 2.684 C-X-C Motif Chemokine Ligand 8 Chr4

IFI44L 4.55E-04 3.18E-03 3.881 2.085 Interferon Induced Protein 44 Like Chr1

ISG20 4.55E-04 5.79E-05 3.968 2.150 Interferon Stimulated Exonuclease Chr15

Gene 20

ISG15 5.29E-04 1.31E-03 4.401 2.203 ISG15 Ubiquitin Like Modifier Chr1

UBD* 6.77E-04 4.87E-04 4.368 2.879 Ubiquitin D Chr6

IFI30 8.01E-04 3.07E-04 3.894 2.260 IFI30 Lysosomal Thiol Reductase Chr19

FCER1G 8.34E-04 1.64E-04 3.631 2.360 Fc Fragment Of IgE Receptor Ig Chr1

KRT6A* 8.74E-04 1.38E-02 3.884 2.337 Keratin, Type II Cytoskeletal 6A Chr12

IFIT3 1.02E-03 6.49E-05 2.870 2.039 Interferon Induced Protein With Chr19

Tetratricopeptide Repeats 3

SERPINB1 1.10E-03 1.49E-04 3.408 2.104 Serpin Family B Member 1 Chr6

IFIT2 1.25E-03 9.84E-05 3.138 2.101 Interferon Induced Protein With Chr10

Tetratricopeptide Repeats 2

CCR7 1.44E-03 1.78E-04 2.403 2.009 C-C Motif Chemokine Receptor 7 Chr17

SELE 2.31E-03 2.90E-02 2.683 2.055 Selectin E Chr1

IL6 2.36E-03 8.74E-02 3.504 2.623 Interleukin 6 Chr7

RSAD2 2.61E-03 7.12E-05 3.246 3.103 Radical S-Adenosyl Methionine Chr2

Domain Containing 2

PLEK 2.69E-03 1.37E-03 3.676 2.155 Pleckstrin Chr2

IDO1 2.90E-03 3.32E-04 4.047 3.335 Indoleamine 2,3-Dioxygenase 1 Chr8

CD163 5.68E-03 9.86E-04 3.102 2.105 CD163 Molecule Chr12

IL1B 8.36E-03 1.06E-03 2.912 2.671 Interleukin 1 Beta Chr2

ADAMTS4 1.02E-02 6.27E-02 3.592 2.361 ADAM Metallopeptidase With Chr1

Thrombospondin Type 1 Motif 4

PLA2G2A 1.06E-02 2.35E-03 2.845 2.436 Phospholipase A2 Group IIA Chr1

DEFB4A 1.14E-02 1.14E-02 4.951 3.447 Defensin Beta 4A Chr8

CCL19 1.17E-02 3.49E-03 3.336 2.886 C-C Motif Chemokine Ligand 19 Chr9

MMP12 2.16E-02 3.31E-03 2.638 2.464 Matrix Metallopeptidase 12 Chr11

KRT17* 2.38E-02 1.37E-02 3.444 2.210 Keratin 17 Chr17

MMP1 1.16E-01 1.59E-02 2.179 2.107 Matrix Metallopeptidase 1 Chr11

Table 2 Histospecific genes identified by genecards .

System Genes

Hematologic/immune fcer1a,cd1a,fpr1,fcn1,epsti1,gzmb,lilrb3,gbp5, cxcl8,ifi44l,gbp4

Ubd,fcer1g,ifit3, serpinb1,ifit2,ccr7,rsad2，plek，ccl19,gbp1

Neurologic ephb6,nfix,mlana,tyrp1,wars,mx1

Skin axin2,tuftelin 1,wfdc5,keratin 15,apcdd1,exph5,nmu ,cdhr1,rapgefl1

aldh3a1,dct,phgdh,pou3f1,ctnnbip1,sox21 ,aadacl2,gpnmb,serpina12

flg2 ,krt31,pmel,lce2d,lce5a,Lor,hla-dqb2,lce1b,lce1c,lce2a,lce2c

il20rb,lce2b,krt6c,s100a9, krt6a，krt17,dsc1

Muscle ccl8，il1b，mmp1

Respiratory cxcl10,cxcl9,cxcl11,,isg20,isg15，ido1

Secretory IFI30，sele，il6，adamts4，defb4a，mmp12,krt16

Digestive col7a1

Reprodutive mamdc2,pla2g2a

Internal cd163

Table 3 The enriched terms for DDGs.

ONTOLOGY ID Description p-value geneID Count

BP GO:0008544 epidermis development 1.19541E-17 COL7A1/DCT/DSC1/KRT6A/KRT15/KRT16 22

/ keratinocyte differentiation KRT17/KRT31/LOR/POU3F1/SOX21/EXPH5

LCE2B/APCDD1/LCE5A/KRT6C/LCE1B/LCE1C

LCE2A/LCE2C/LCE2D/FLG2 BP GO:0009615 response to virus 5.02351E-12 GBP1/IFIT2/IFIT3/IL1B/IL6/CXCL10/ISG20/RSAD2

CXCL9/MMP12/MX1/CCL8/CCL19/ISG15/IFI44L 15

BP GO:0030593 neutrophil chemotaxis 1.69908E-11 CCR7/FCER1G/IL1B/CXCL8 10

CXCL10/CXCL9/S100A9/CCL8

CCL19/CXCL11

KEGG hsa04061 Viral protein interaction 1.51065E-09 CCR7/IL6/CXCL8/CXCL10/CXCL9 9

with cytokine and CCL8/CCL19 CXCL11/IL20RB

cytokine receptor

MF GO:0042379 chemokine receptor 1.85516E-08 DEFB4A/CXCL8/CXCL10/CXCL9 7

binding

CCL8/CCL19/CXCL11

BP GO:0006959 humora limmune 2.69486E-08 CCR7/DEFB4A/FCN1/IL1B/IL6 12

response CXCL8/CXCL10/KRT6A/CXCL9

BP GO:0070098 chemokine-mediated 8.16999E-08 CCR7/CXCL8/CXCL10/CXCL9 7

signaling pathway CCL8/CCL19/CXCL11

BP GO:0060337 type I interferon 1.3893E-07 IFIT2/IFIT3/ISG20/MMP12 7

signaling pathway MX1/ISG15/RSAD2

KEGG hsa04657 IL-17 signaling pathway 4.47045E-07 DEFB4A/IL1B/IL6/CXCL8/CXCL10/MMP1/S100A9 7

MF GO:0001664 G protein-coupled 5.19828E-07 DEFB4A/FCN1/FPR1/CXCL8/CXCL10 10

receptor binding CXCL9/CCL8/CCL19/CXCL11/NMU

MF GO:0005200 structural constituent 6.72691E-06 KRT6A/KRT15/KRT16/KRT17/KRT31/LOR 6

of cytoskeleton

Table 4 Genes of interest.

Up-regulated Down-regulated

Gene Fold change Gene Fold change

Control-lesioned Heal-lesioned Control-lesioned Heal-lesioned

Immune

fcer1a 2.096 2.437 fpr1 3.739 2.992

cd1a 2.107 2.007 fcn1 3.891 2.604

Epst 4.462 2.381

Gzmb 3.640 2.481

gbp5 4.203 3.133

cxcl8 3.064 2.684

ifi44l 3.881 2.085

gbp4 3.997 2.397

gbp1 5.033 3.027

Ubd 4.368 2.879

fcer1g 3.631 2.360

ifit3 2.870 2.039

serpinb1 3.408 2.104

ifit2 3.138 2.101

ccr7 2.403 2.009

rsad2 3.246 3.103

Plek 3.676 2.155

ccl19 3.336 2.886

Neurologic

ephb6 2.531 2.508 wars 4.916 3.317

Nfix 2.035 2.054 mx1 4.226 2.127

Mlana 2.516 2.484

tyrp1 2.531 2.769

Reprodutive

mamdc2 2.054 2.173 pla2g2a 2.845 2.436

Rawdata.csv

Microarray analysis of novel genes involved in HSV-2 infection

Status:

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Abstract

Figures

Background

Results

Discussion

Conclusion

Materials And Methods

Declarations

References

Tables

Supplementary Files

Status:

Version 1