Prediction method for potential target and mechanism of acrolein-induced skin injury

Abstract

The invention discloses a method for predicting potential targets and mechanisms of acrolein-induced skin injury, and relates to the field of acrolein injury prediction. According to the method, skin injury differential expression genes and acrolein related targets are obtained through a bioinformatics method, protein relation interaction network analysis of intersection of the skin injury differential expression genes and the acrolein related targets is carried out, and a potential mechanism of acrolein-induced skin injury is predicted. GO functional clustering analysis results show that acrolein is mainly subjected to biological processes such as reaction of cells to lipopolysaccharide and reaction of cells to bacterial molecules; a KEGG key signal channel enrichment analysis result shows that acrolein can induce skin injury through signal channels such as interaction of receptors among cell factors, chemotactic factor signal channels, interaction of virus proteins and cell factors and cell factor receptors and the like. The key genes obtained through prediction comprise CXCL1, CXCL8 and IL1beta, and a new target is provided for subsequent research on a prevention and treatment mechanism of acrolein-induced skin injury.

Description

Technical Field

[0001] The invention relates to the field of acrolein damage prediction, and in particular to a method for predicting potential targets and mechanisms of acrolein-induced skin damage. Background Art

[0002] The skin is the most widely distributed organ in the human body, with a large vascular bed, and is often associated with many vasculitis syndromes. Among them, small-vessel vasculitis (SVV) is an inflammation involving small intraparenchymal arteries, arterioles, capillaries, venules and veins, and is also a major manifestation of skin lesions. According to the 2012 Revisited International Chapel Hill Consensus Conference Vasculitis Nomenclature, cutaneous vasculitis was included in the SVV and single-organ vasculitis nomenclature group. The incidence rate of SVV patients with typical joint pain and cryoglobulinemia but no fever is about 10%. In addition, the SVV rash is polymorphic, and the typical rash is palpable purpura. In severe cases, blood blisters, blisters, shallow ulcers, etc. may occur. Skin lesions usually have no subjective symptoms, but may also cause itching, pain, and burning. It may be accompanied by fever, joint pain and other discomforts. As the only organ involved, the skin can also involve various systems in the body and show corresponding symptoms. Histopathology includes swelling of vascular endothelial cells, deposition of fibrinoid material in and around the vascular wall, infiltration of inflammatory cells, and extravasation of red blood cells. Direct immunofluorescence of fresh skin lesions shows IgG, IgM, C3, and fibrin deposition around the blood vessels. Cutaneous vasculitis can be a primary (idiopathic) disease or a secondary disease caused by drug administration (such as β-lactam antibiotics, thiazide diuretics, or nonsteroidal anti-inflammatory drugs). In addition, diseases such as food or food additives, infection or connective tissue disease, inflammatory bowel disease, paraproteinemia, and malignant tumors may all trigger the occurrence of SVV at the skin level. SVV may clinically manifest as localized skin lesions with a benign course, which can sometimes progress rapidly, concomitantly, or sequentially to systemic diseases. It can be specifically divided into three categories: acute, chronic, and recurrent. The diagnostic evaluation of SVV patients will be appropriately treated according to the specific clinical manifestations.

[0003] Although the underlying mechanisms of different types of SVV are still unclear, vascular wall inflammation has been proven by domestic and foreign scholars to be an important common feature. The most common histological manifestation of SVV is leukocytoclastic vasculitis, which involves the dermal postcapillary venules, in which neutrophils release powerful inflammatory mediators. The respiratory burst of activated neutrophils produces excessive reactive oxygen species (ROS), which damage macromolecules. Depending on the type and diffusion distance, ROS can induce oxidative damage to nucleic acids, proteins, and lipids. The peroxidation of polyunsaturated fatty acids (PUFAs) can trigger a chain reaction of lipid peroxidation, change the fluidity and function of the membrane, and form active aldehydes mainly acrolein. In vivo, acrolein can also be formed during the catabolism of polyamines and amino acids, or as a metabolite of certain drugs (such as cyclophosphamide). Due to its electrophilic properties, acrolein can effectively bind to DNA and proteins and form adducts, thereby changing their structure and function. There is evidence that acrolein is a highly flammable liquid that has acute reproductive toxicity and carcinogenicity by oral administration, inhalation, and skin absorption. Contact with eyes or skin can cause severe damage or burns. Acrolein is easily absorbed through the skin, and its stabilizer, hydroquinone, can cause skin allergies. Acrolein vapor may form explosive mixtures in the air. Acrolein can react with oxidants, acids, and bases, and may polymerize when unstable. Therefore, oxidative stress, redox signaling, and the resulting lipid peroxidation are associated with various pathological states of SVV, and inhibiting the occurrence of the above reactions plays a vital role in maintaining normal skin function.

[0004] Environmental pollutants enter the atmosphere and water bodies through various pathways and have certain toxic effects on the body. Many common chronic diseases are closely related to them. As the smoking dose increases, cigarette smoke penetrates into the dermis and triggers the production of ROS, thereby promoting damage to DNA, lipids and proteins, further leading to the production of inflammatory mediators, and ultimately leading to cell apoptosis. Related experimental studies have shown that cigarette smoke has a dose-dependent effect on protein carbonyls in HACAT keratinocytes, causing oxidative damage to HACAT cells through the oxidative stress pathway. Therefore, cigarette smoke, as an important environmental source of human exposure to acrolein, can induce protein carbonylation and dysfunction, which will serve as the basis for susceptibility to SVV-related gene mutations. Therefore, smoking is likely to be a major risk factor for SVV. The World Health Organization's Framework Convention on Tobacco Control (FCTC) strongly recommends that acrolein be included in the nine harmful ingredients that need to be reduced in tobacco products. Since acrolein is a volatile organic pollutant, it is a common atmospheric pollutant and is closely related to the occurrence of skin damage induced by direct contact. Epidemiological surveys have shown that how to mitigate the toxic side effects of acrolein has become a common concern because acrolein can cause neurological damage, genetic damage, and potential carcinogenicity. Given the damaging effects of acrolein on the skin, screening for possible signaling pathways and key targets in acrolein-induced skin damage has become a major research hotspot.

[0005] Bioinformatics, as an interdisciplinary subject integrating information technology and biotechnology, is committed to applying and developing information technology to solve practical problems in biology and medicine. In recent years, with the rapid development of big data and artificial intelligence technology, bioinformatics research has made great progress. With the help of bioinformatics prediction technology, the development of the biological field has been greatly promoted. At present, the specific mechanism and key targets of acrolein-induced skin damage are still unclear. Therefore, the present invention predicts the potential signal pathways and key targets in the process of skin damage induced by the environmental pollutant acrolein through bioinformatics technology, providing new targets and new ideas for the prevention and treatment of acrolein-induced skin damage. Summary of the invention

[0006] The purpose of the present invention is to provide a possible damage mechanism and key prevention and treatment targets for acrolein-induced skin damage, to provide data support for the study of the damage mechanism of acrolein, and to provide new ideas and targets for the prevention and treatment of related diseases induced by acrolein.

[0007] The technical solution adopted by the present invention is as follows: a method for predicting potential targets and mechanisms of acrolein-induced skin damage, the steps of which are:

[0008] 1) Visualization analysis of differentially expressed genes:

[0009] 1.1) Select a skin injury dataset from the database, obtain differentially expressed genes as disease targets of skin injury based on the set screening conditions, and draw a volcano plot to represent the differential expression of genes in the dataset.

[0010] The database is the GEO database, and the skin injury dataset is GSE183820; the set screening conditions are Adj.PValue<0.05,|log2FC|>1.5.

[0011] 1.2) Obtain targets related to acrolein damage in the CTD database, and screen the common intersections between acrolein and skin damage datasets through Venn diagrams.

[0012] 2) Construction of protein interaction network and GO functional clustering analysis:

[0013] 2.1) The targets obtained in step 1.2) were imported into Cytoscape software. The isolated nodes in the preliminary protein interaction network needed to be deleted. After removing the individual nodes, a protein interaction network of potential targets was constructed to analyze the potential mechanism of acrolein-induced skin damage.

[0014] 2.2) Perform GO functional clustering analysis on potential targets to obtain molecular function, MF, biological process, BP and cellular component, CC.

[0015] 3) Enrichment of KEGG key signaling pathways and analysis of Hub genes;

[0016] 3.1) The differentially expressed genes obtained in step 1.2) were subjected to KEGG signaling pathway enrichment analysis to predict the biological processes and signal transduction pathways that may be involved in the process of acrolein-induced skin damage.

[0017] Possible pathways for acrolein to induce skin lesions include cytokine-receptor interactions, rheumatoid arthritis, interactions of viral proteins with cytokines and cytokine receptors, TNF signaling, amebiasis, chemokine signaling, epithelial cell signaling in Helicobacter pylori infection, major immunodeficiency, Chagas disease, and IL-17 signaling.

[0018] 3.2) Using the MCC algorithm in the Cytohubba plug-in, the top 5% of Hub genes in the protein interaction network were selected for GO functional clustering and KEGG signaling pathway enrichment analysis, and key targets were screened including CXCL1, CXCL8 and IL1β genes.

[0019] The beneficial effects of the present invention are:

[0020] The present invention uses network toxicology methods to screen potential targets related to acrolein-induced skin damage, and predicts possible biological processes and signal transduction pathways, providing a new perspective for in-depth understanding of the molecular mechanism of acrolein-induced skin damage, and laying a theoretical foundation for the development of targeted intervention strategies. Compared with traditional experimental methods, the present invention greatly shortens the research cycle, improves the accuracy and comprehensiveness of screening, provides a theoretical basis and experimental basis for revealing the mechanism of acrolein-induced skin damage and its prevention and treatment, provides a reference method for the toxicity assessment of other toxic chemicals, and promotes the development of the field of toxicology research. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] Figure 1 Volcano plot of gene expression in skin lesions and common targets between acrolein and skin lesions;

[0022] Among them, A is the volcano map of skin damage gene expression; B is the common target of acrolein and skin damage.

[0023] Figure 2 To construct protein interaction network and conduct GO functional clustering analysis;

[0024] Among them, A is the protein interaction network; B is the GO functional clustering analysis.

[0025] Figure 3 To obtain and analyze the enrichment of KEGG key signaling pathways and Hub genes;

[0026] Among them, A is the bubble diagram of KEGG key signaling pathway enrichment analysis of acrolein-induced skin damage targets; B is the acquisition and analysis diagram of Hub genes of acrolein-induced skin damage targets. DETAILED DESCRIPTION

[0027] Embodiment 1:

[0028] This example uses the GEO database and the CTD database as data sources to predict potential signaling pathways and targets for acrolein-induced skin damage. The specific experimental steps are as follows:

[0029] 1) Visual analysis of differentially expressed genes (volcano plot and Venn diagram analysis)

[0030] The skin injury dataset GSE183820 was selected from the GEO database (https: / / www.ncbi.nlm.nih.gov / geo / ), and 619 differentially expressed genes were obtained based on the screening conditions of Adj.P Value<0.05,|log2FC|>1.5 as disease targets of skin injury, and a volcano map was drawn to represent the differential expression of genes in the dataset. Figure 1As can be seen in A, red represents up-regulated genes, blue represents down-regulated genes, and gray represents genes with |log2FC| < 1.5. At the same time, 2373 targets related to acrolein damage were obtained from the CTD database (https: / / ctdbase.org / ). The common intersection of acrolein and skin damage datasets was screened through the Venn diagram, and the results are as follows: Figure 1 As shown in B, the 53 common targets shared by the two may play an important role in the process of acrolein-induced skin damage.

[0031] II) Construction of protein interaction network and GO functional clustering analysis

[0032] The 53 targets of acrolein-induced skin damage were imported into Cytoscape software. The isolated nodes in the initial protein interaction network needed to be deleted. After removing the three isolated nodes, a protein interaction network containing 50 targets was constructed to analyze the potential mechanism of acrolein-induced skin damage. GO functional clustering analysis was performed on the 50 potential targets. The results are shown in Figure 2. Figure 2 As shown in Figure 2, Gene Ontology can be divided into three parts: Molecular Function (MF), Biological Process (BP) and Cellular Component (CC). Figure 2 As shown in Figure B, the BP results showed that through various molecular activities, the acrolein-induced skin damage targets mainly completed biological processes such as "cell response to lipopolysaccharide" and "cell response to bacterial molecules". The CC results showed that the cell structure location of the acrolein-induced skin damage targets when performing functions was mainly in the "outside of the plasma membrane" and "lectin-coated vesicle membrane"; MF found that "chemokine activity" and "chemokine receptor binding" played a significant role in the molecular function of acrolein-induced skin damage.

[0033] III) KEGG key signaling pathway enrichment and Hub gene acquisition analysis

[0034] The above 53 differentially expressed genes were subjected to KEGG signaling pathway enrichment analysis to predict the biological processes and signal transduction pathways that may be involved in acrolein-induced skin damage. Figure 3It can be seen from the A that through the KEGG key signaling pathway enrichment analysis, it was found that the interaction between cytokine receptors, rheumatoid arthritis, the interaction between viral proteins and cytokines and cytokine receptors, TNF signaling pathway, amebiasis, chemokine signaling pathway, epithelial cell signaling in Helicobacter pylori infection, major immune deficiency, Chagas disease and IL-17 signaling pathway were significantly enriched, and the Adj.PValue was lower, which was statistically significant, indicating that the above three pathways may play an important role in acrolein-induced skin damage. Using the MCC algorithm in the Cytohubba plug-in, the top 5% (3 in total) Hub genes in the protein interaction network were taken for subsequent analysis. From Figure 3 As can be seen from B, the three Hub genes are all enriched in signal pathways related to acrolein-induced skin damage targets, among which CXCL1, CXCL8 and IL1B are significantly enriched in many signal pathways such as cytokine receptor interactions, rheumatoid arthritis, and IL-17 signaling pathways, which will help to further explore the potential mechanism of acrolein-induced skin damage.

Claims

1. A method for predicting potential targets and mechanisms of acrolein-induced skin damage, characterized in that: The steps are: 1) Visualization analysis of differentially expressed genes: 1.1) Select a skin injury dataset from the database, obtain differentially expressed genes as disease targets of skin injury based on the set screening conditions, and draw a volcano map to represent the differential expression of genes in the dataset; 1.2) Obtain targets related to acrolein damage in the database, and screen the common intersections of acrolein and skin damage datasets through Venn diagrams; 2) Construction of protein interaction network and GO functional clustering analysis: 2.1) The targets obtained in step 1.2) were imported into Cytoscape software. The isolated nodes in the preliminary protein interaction network needed to be deleted. After removing the individual nodes, a protein interaction network of potential targets was constructed to analyze the potential mechanism of acrolein-induced skin damage; 2.2) Perform GO functional clustering analysis on potential targets to obtain molecular function, MF, biological process, BP and cellular component, CC; 3) Enrichment of KEGG key signaling pathways and analysis of Hub genes; 3.1) performing KEGG signaling pathway enrichment analysis on the differentially expressed genes obtained in step 1.2) to predict the biological processes and signal transduction pathways that may be involved in the process of acrolein-induced skin damage; 3.2) Using the MCC algorithm in the Cytohubba plug-in, the top 5% of Hub genes in the protein interaction network were selected for GO functional clustering and KEGG signaling pathway enrichment analysis, and key targets were screened including CXCL1, CXCL8 and IL1β genes.

2. The method for predicting potential targets and mechanisms of acrolein-induced skin damage according to claim 1, characterized in that: In the above 1.1), the database is the GEO database, and the skin injury dataset is GSE183820.

3. The method for predicting potential targets and mechanisms of acrolein-induced skin damage according to claim 1, characterized in that: In the above 1.1), the screening conditions are set as Adj.P Value<0.05,|log2FC|>1.

5.

4. The method for predicting potential targets and mechanisms of acrolein-induced skin damage according to claim 1, characterized in that: In the above 1.2), the database is the CTD database.

5. The method for predicting potential targets and mechanisms of acrolein-induced skin damage according to claim 1, characterized in that: In the above 3.1), possible pathways for acrolein to induce skin damage include the interaction between cytokine receptors, rheumatoid arthritis, the interaction between viral proteins and cytokines and cytokine receptors, TNF signaling pathway, amebiasis, chemokine signaling pathway, epithelial cell signaling in Helicobacter pylori infection, major immunodeficiency, Chagas disease and IL-17 signaling pathway.

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