Bioinformatics Methods Research Articles

Identification of Potential Therapeutic Drugs for Diabetic Cardiomyopathy

This study focused on identifying potential therapeutic drugs and mechanisms of action for diabetic cardiomyopathy (DCM). Using gene expression profiles from the GSE197850 dataset, we applied Weighted Correlation Network Analysis, Limma, and Gene Set Variation Analysis (GSVA) to uncover DCM-related gene sets and pathways. Subsequently, we conducted protein interaction network analysis with String and identified 10 hub genes through Cytoscape: ACTN2, ITGA1, CASP3, PXN, PCNA, CAV1, GAPDH, FEN1, PTPN11, and ESR1. In vitro validation using Rat H9C2 cardiomyocytes showed upregulation of FEN1, PCNA, PTPN11, CAV1, GAPDH, CASP3, PXN, and ACTN2, and downregulation of ESR1 and ITGA11 in high-glucose conditions. We further performed immune infiltration analysis with CIBERSORT and explored potential therapeutic agents through molecular docking with Autodock Vina. Our findings identified estradiol, valproic acid, acetaminophen, and resveratrol as potential drugs for DCM. Among these, resveratrol showed promise by promoting autophagy. This study leveraged comprehensive bioinformatic and experimental methods to pinpoint DCM-related genes, elucidate key hub genes, and propose resveratrol as a latent drug for DCM.

Identifying Oxidative Stress-Related Genes (OSRGs) as Potential Target for Treating Periodontitis Based on Bioinformatics Analysis.

Periodontitis (PD) is a multifactorial inflammatory disease that is closely associated with periodontopathic bacteria. Numerous studies have demonstrated oxidative stress (OS) contributes to inflammation and is a prime factor in the development of PD. It is imperative to explore the function of newly discovered hub genes associated with OS in the advancement of PD, thereby identifying potential targets for therapeutic intervention. The goal of the current study was to identify the oxidative-stress-related genes (OSRGs) associated with periodontitis (PD) development using an integrated bioinformatics method. DEGs from GEO gene-expression data were identified using the "limma" package. We obtained OSRGs from GeneCards and utilized a Venn diagram to uncover differentially expressed OSRGs (DEOSRGs). After receiving the DEOSRGs, we employed Gene Ontology (GO), Kyoto Encyclopaedia of Genes and Genomes (KEGG), and protein-protein interaction (PPI) analytical tools to examine their possible functions and pathways in PD. Receiver operating characteristic (ROC) curves screened for hub genes of PD. RT-qPCR and western blot analysis were used to detect DEOSRG expression in mouse ligature-induced periodontitis gingival tissues. The investigation identified 273 OSRGs. Based on PPI analysis, we recognized 20 OSRGs as hub genes. GO and KEGG enrichment analysis indicated that these hub genes were predominantly enriched in leukocyte migration, lymphocyte proliferation, and humoral immune response, and associated with leukocyte trans-endothelial migration, cytokine-cytokine receptor interaction, and NF-κB signaling pathway. Following ROC analysis, VCAM1, ITGAM, FCGR3A, IL1A, PECAM1, and VCAM1were identified as PD prognostic gene. RT-qPCR and western blot analyses confirmed that the expression ITGAM, FCGR3A, and PECAM1 were significantly elevated in the gingival tissues obtained from mice. This investigation revealed that ITGAM, FCGR3A, and PECAM1 may have a crucial function in the advancement of PD.

Single-cell transcriptomics: background, technologies, applications, and challenges.

Single-cell sequencing was developed as a high-throughput tool to elucidate unusual and transient cell states that are barely visible in the bulk. This technology reveals the evolutionary status of cells and differences between populations, helps to identify unique cell subtypes and states, reveals regulatory relationships between genes, targets and molecular mechanisms in disease processes, tumor heterogeneity, the state of the immune environment, etc. However, the high cost and technical limitations of single-cell sequencing initially prevented its widespread application, but with advances in research, numerous new single-cell sequencing techniques have been discovered, lowering the cost barrier. Many single-cell sequencing platforms and bioinformatics methods have recently become commercially available, allowing researchers to make fascinating observations. They are now increasingly being used in various industries. Several protocols have been discovered in this context and each technique has unique characteristics, capabilities and challenges. This review presents the latest advancements in single-cell transcriptomics technologies. This includes single-cell transcriptomics approaches, workflows and statistical approaches to data processing, as well as the potential advances, applications, opportunities and challenges of single-cell transcriptomics technology. You will also get an overview of the entry points for spatial transcriptomics and multi-omics.

Unraveling the Significance of Nanog in the Generation of Embryonic Stem-like Cells from Spermatogonia Stem Cells: A Combined In Silico Analysis and In Vitro Experimental Approach.

Embryonic stem-like cells (ES-like cells) are promising for medical research and clinical applications. Traditional methods involve "Yamanaka" transcription (OSKM) to derive these cells from somatic cells in vitro. Recently, a novel approach has emerged, obtaining ES-like cells from spermatogonia stem cells (SSCs) in a time-related process without adding artificial additives to cell cultures, like transcription factors or small molecules such as pten or p53 inhibitors. This study aims to investigate the role of the Nanog in the conversion of SSCs to pluripotent stem cells through both in silico analysis and in vitro experiments. We used bioinformatic methods and microarray data to find significant genes connected to this derivation path, to construct PPI networks, using enrichment analysis, and to construct miRNA-lncRNA networks, as well as in vitro experiments, immunostaining, and Fluidigm qPCR analysis to connect the dots of Nanog significance. We concluded that Nanog is one of the most crucial differentially expressed genes during SSC conversion, collaborating with critical regulators such as Sox2, Dazl, Pou5f1, Dnmt3, and Cdh1. This intricate protein network positions Nanog as a pivotal factor in pathway enrichment for generating ES-like cells, including Wnt signaling, focal adhesion, and PI3K-Akt-mTOR signaling. Nanog expression is presumed to play a vital role in deriving ES-like cells from SSCs in vitro. Finding its pivotal role in this path illuminates future research and clinical applications.

Cloning and Functional Analysis of CsROP5 and CsROP10 Genes Involved in Cucumber Resistance to Corynespora cassiicola.

The cloning of resistance-related genes CsROP5/CsROP10 and the analysis of their mechanism of action provide a theoretical basis for the development of molecular breeding of disease-resistant cucumbers. The structure domains of two Rho-related guanosine triphosphatases from plant (ROP) genes were systematically analyzed using the bioinformatics method in cucumber plants, and the genes CsROP5 (Cucsa.322750) and CsROP10 (Cucsa.197080) were cloned. The functions of the two genes were analyzed using reverse-transcription quantitative PCR (RT-qPCR), virus-induced gene silencing (VIGS), transient overexpression, cucumber genetic transformation, and histochemical staining technology. The conserved elements of the CsROP5/CsROP10 proteins include five sequence motifs (G1-G5), a recognition site for serine/threonine kinases, and a hypervariable region (HVR). The knockdown of CsROP10 through VIGS affected the transcript levels of ABA-signaling-pathway-related genes (CsPYL, CsPP2Cs, CsSnRK2s, and CsABI5), ROS-signaling-pathway-related genes (CsRBOHD and CsRBOHF), and defense-related genes (CsPR2 and CsPR3), thereby improving cucumber resistance to Corynespora cassiicola. Meanwhile, inhibiting the expression of CsROP5 regulated the expression levels of ROS-signaling-pathway-related genes (CsRBOHD and CsRBOHF) and defense-related genes (CsPR2 and CsPR3), thereby enhancing the resistance of cucumber to C. cassiicola. Overall, CsROP5 and CsROP10 may participate in cucumber resistance to C. cassiicola through the ROS and ABA signaling pathways.

Biological functions of Circular RNA_LARP4/ Upstream frameshift 1 in development of gastric cancer.

Recently, the progression of gastric cancer (GC), as one of the most ordinary malignant tumors, has been reported to be associated with circular RNAs. This study aimed to identify the role of circular RNA_LARP4 in GC. We performed real-time quantitative polymerase chain reaction (RT-qPCR) in 46 paired GC patients and GC cell lines to detect the expression of circular RNA_LARP4. Moreover, the role of circular RNA_LARP4 in GC proliferation was identified through proliferation assay and colony formation assay, while the role of circular RNA_LARP4 in GC metastasis was measured through scratch wound assay and transwell assay. Furthermore, the potential targets of circular RNA_LARP4 were predicted through bioinformatics methods and further identified by western blot assay and RT-qPCR. Circular RNA_LARP4 expression was remarkably lower in GC tissues compared with that in adjacent samples. Besides, cell proliferation of GC was inhibited after overexpression of circular RNA_LARP4, while cell migration and invasion of GC was inhibited after overexpression of circular RNA_LARP4. Furthermore, Upstream frameshift 1 (UPF1) was predicted as the potential target of circular RNA_LARP4 and was upregulated via overexpression of circular RNA_LARP4 in GC. Circular RNA_LARP4 inhibits GC cell proliferation and metastasis via targeting UPF1 in vitro, which might provide a new tumor suppressor in GC development.

Identification of ceRNA networks in type H and L vascular endothelial cells through integrated bioinformatics methods.

Type H blood vessels are a subtype of bone-specific microvessels (CD31hiEmcnhi) that play an important regulatory role in the coupling of angiogenesis and osteogenesis. Despite reports on the distinct roles of type H and L vessels under physiological and pathological bone conditions, their genetic differences remain to be elucidated. This study aims to construct a competitive endogenous RNA (ceRNA) network of key gene for differencial expression (DE) in type H and L vascular endothelial cells (ECs) through integrated bioinformatic methods. We downloaded relevant raw data from the ArrayExpress and the Gene Expression Omnibus (GEO) database and used the Limma R-Bioconductor package to screen for DE lncRNAs, DE miRNAs, and DE mRNAs between type H and L vascular ECs. A total ceRNA network was constructed based on their interactions, followed by refinement using protein-protein interaction (PPI) networks to select upregulated and downregulated key genes. Enrichment analysis was performed on these key genes. Random validation was conducted using flow cytometry and real-time RT-PCR. A total of 1 761 DE mRNAs, 187 DE lncRNAs, and 159 DE miRNAs were identified, and a comprehensive ceRNA network was constructed based on their interactions. Six upregulated (Itga5, Kdr, Tjp1, Pecam1, Cdh5, and Ptk2) and 2 downregulated (Csf1r and Il10) key genes were selected via PPI network to construct a subnetwork of ceRNAs related to these key genes. Upregulated key genes were mainly enriched in negative regulation of angiogenesis and vascular apoptosis. Results from flow cytometry and real-time RT-PCR were consistent with bioinformatics analysis. This study proposes a ceRNA network associated with upregulated and downregulated type H and L vascular ECs based on selected key genes, providing new insights into the regulatory mechanisms of type H and L vascular ECs in bone metabolism.

Association of polymorphic variants of cytokines genes, endothelial growth factor and matrix metalloproteinases with the development of uterine fibroids among russian women

One of the factors in the development of uterine fibroids is a genetic predisposition to its occurrence in some women, but the real molecular genetic mechanisms of this phenomenon remain unknown. Aim of the study was the distribution analysis of gene polymorphism of cytokines TNFα, IL-1β, IL-4, IL-6, IL-10, factors of angiogenesis (vascular endothelial growth factor, VEGF) and remodeling of extracellular matrix (metalloproteinases MMP2, MMP3, MMP9), which are associated with their levels. Material and methods. Genotyping was performed by real-time PCR using commercial test systems SYBR GreenI (Litech, Russia) and TaqMan (Syntol, Russia) in accordance with the instructions of the developer. Cytokine content in blood serum was determined by flow cytometry using microspheres coated with monoclonal antibodies to cytokines (Bio-Plex ProTM Human Cytokine 27-plex Assay), according to the instructions for Bio-Plex 200 (Bio-Rad Laboratories, USA).To evaluate the results obtained, in addition to the generally accepted methods of statistical processing for case – control studies, computational methods of bioinformatics were used for comparative analysis of the diagnostic value of various combined genetic traits. Results. It was shown that the maximum odds ratio value of uterine fibroids development are combined genetic traits that include representatives of all four regulatory factors: cytokines with pro-inflammatory activity, cytokines with anti-inflammatory activity, vascular endothelial growth factors and metalloproteinases (p = 0.002). Conclusions. The presented data reveal the real mechanisms of manifestation of the genetic predisposition of individual women to the uterine fibroids development, associated with the presence of polymorphism of certain genes in their genome, which provide features of the structure of cytokine networks with the predominance of certain activities in the regulation of tissue processes in the uterus. In addition to purely scientific interest, these results indicate the real possibility of their clinical application in the form of prognostic criteria with a certain level of prognostic significance.

Genome‑wide identification and expression analysis of the UBC gene family in wheat (Triticum aestivum L.)

BackgroundUbiquitination is an important regulatory step of selective protein degradation in the plant UPS (ubiquitin–proteasome system), which is involved in various biological processes in eukaryotes. Ubiquitin-conjugating enzymes play an intermediate role in the process of protein ubiquitination reactions and thus play an essential role in regulating plant growth and response to adverse environmental conditions. However, a genome-wide analysis of the UBC gene family in wheat (Triticum aestivum L.) has not yet been performed.ResultsIn this study, the number, physiochemical properties, gene structure, collinearity, and phylogenetic relationships of TaUBC family members in wheat were analyzed using bioinformatics methods. The expression pattern of TaUBC genes in different tissues/organs and developmental periods, as well as the transcript levels under abiotic stress treatment, were analyzed using RNA-Seq data and qRT-PCR. Meanwhile, favorable haplotypes of TaUBC25 were investigated based on wheat resequencing data of 681 wheat cultivars from the Wheat Union Database. The analyses identified a total of 93 TaUBC family members containing a UBC domain in wheat genome. These genes were unevenly distributed across 21 chromosomes, and numerous duplication events were observed between gene members. Based on phylogenetic analysis, the TaUBC family was divided into 13 E2 groups and a separate UEV group. We investigated the expression of TaUBC family genes under different tissue/organ and stress conditions by quantitative real-time PCR (qRT-PCR) analysis. The results showed that some TaUBC genes were specifically expressed in certain tissues/organs and that most TaUBC genes responded to NaCl, PEG6000, and ABA treatment with different levels of expression. In addition, we performed association analysis for the two haplotypes based on key agronomic traits such as thousand-kernel weight (TKW), kernel length (KL), kernel weight (KW), and kernel thickness (KT), examining 122 wheat accessions at three environmental sites. The results showed that TaUBC25-Hap II had significantly higher TKW, KL, KW, and KT than TaUBC25-Hap I. The distribution analysis of haplotypes showed that TaUBC25-Hap II was preferred in the natural population of wheat.ConclusionOur results identified 93 members of the TaUBC family in wheat, and several genes involved in grain development and abiotic stress response. Based on the SNPs detected in the TaUBC sequence, two haplotypes, TaUBC25-Hap I and TaUBC25-Hap II, were identified among wheat cultivars, and their potential value for wheat breeding was validated by association analysis. The above results provide a theoretical basis for elucidating the evolutionary relationships of the TaUBC gene family and lay the foundation for studying the functions of family members in the future.

Dynamic Changes of Environment and Gut Microbial Community of Litopenaeus vannamei in Greenhouse Farming and Potential Mechanism of Gut Microbial Community Construction

The aim of this study was to investigate the dynamic changes in the microbial communities of both the environment and gut of Litopenaeus vannamei, as well as to elucidate the mechanisms underlying microbial community assembly in greenhouse farming. 16S rDNA high-throughput sequencing and bioinformatics methods were used to carry out the research on the community structure of the microorganisms under greenhouse culture conditions in water, sediment, and gut microorganisms; correlations pertaining to environmental factors; the feasibility of using Source Tracker; and the mechanisms of community construction. The results show that the dominant microorganisms in water, sediment, and gut farming in a greenhouse environment varied and were subject to dynamic change. A variety of beneficial microbiota such as Bacillus were found in the gut, whereas a variety of microorganisms such as Marivita and Pseudomonas, which function as nitrogen and phosphorus removers, were present in water. Source Tracker and environmental correlation analyses showed that changes in the gut were associated with eutrophication indicators (total nitrogen, total phosphorus, ammonia nitrogen) and changes in environmental microorganisms (in water and sediment). The results of the community-building mechanism analysis show that stochastic processes determine the community-building directions of environmental and gut microorganisms. These findings will help us to understand the microbiota characteristics of shrimp ponds under greenhouse farming conditions, and the complex interactions between the shrimp gut and the environmental microbiota and environmental variables, as well as revealing the changing rules of the gut microbiota.

Research on the potential mechanism of Deapioplatycodin D against pulmonary fibrosis based on bioinformatics and experimental verification

BackgroundPulmonary fibrosis (PF) is a group of respiratory diseases that are extremely complex and challenging to treat. Due to its high mortality rate and short survival, it's often referred to as a “tumor-like disease” that poses a serious threat to human health. ObjectiveWe aimed validate the potential of Deapioplatycodin D (DPD) to against PF and clarify the underlying mechanism of action of DPD for the treatment of PF based on bioinformatics and experimental verification. This finding provides a basis for the development of safe and effective therapeutic PF drugs based on DPD. MethodsWe used LPS-induced early PF rats as a PF model to test the overall efficacy of DPD in vivo. Then, A variety of bioinformatics methods, such as WGCNA, LASSO algorithm and immune cell infiltration (ICI), were applied to analyze the gene microarray related to PF obtained from Gene Expression Omnibus (GEO) to obtained key targets of PF. Finally, an in vitro PF model was constructed based on BEAS-2B cells while incorporating rat lung tissues to validate the regulatory effects of DPD on critical genes. ResultsDPD can effectively alleviate inflammatory and fibrotic markers in rat lungs. WGCNA analysis resulted in a total of six expression modules, with the brown module having the highest correlation with PF. Subsequently, seven genes were acquired by intersecting the genes in the brown module with DEGs. Five key genes were identified as potential biomarkers of PF by LASSO algorithm and validation dataset verification analysis. In the ICI analysis, infiltration of activated B cell, immature B cell and natural killer cells were found to be more crucial in PF. Ultimately, it was observed that DPD could modulate key genes to achieve anti-PF effects. ConclusionIn short, these comprehensive analysis methods were employed to identify critical biomarkers closely related to PF, which helps to elucidate the pathogenesis and potential immunotherapy targets of PF. It also provides essential support for the potential of DPD against PF.

Identification and expression analysis of the HSP70 gene family under abiotic stresses in Litchi chinensis

HSP70 protein, as an important member of the heat shock protein (HSP) family, plays an important role in plant growth, development, and response to biotic and abiotic stresses. In order to explore the role of HSP70 gene family members in Litchi chinensis under low temperature, high temperature, drought, and salt stress, bioinformatics methods were used to identify the HSP70 gene family members within the entire L. chinensis genome. The expression of these genes under various abiotic stresses was then detected using quantitative real-time PCR (qRT-PCR). The results showed that the LcHSP70 gene family consisted of 18 members, which were unevenly distributed across ten L. chinensis chromosomes. The LcHSP70 protein contained 479-851 amino acids, with isoelectric points ranging from 5.07 to 6.95, and molecular weights from 52.44 kDa to 94.07 kDa. The predicted subcellular localization showed that LcHSP70 protein was present in the nucleus, cytoplasm, endoplasmic reticulum, mitochondria, and chloroplast. Phylogenetic analysis divided the LcHSP70 proteins into five subgroups, namely Ⅰ, Ⅱ, Ⅲ, Ⅳ, and Ⅵ. The promoter regions of the LcHSP70 genes contained various cis-acting elements related to plant growth, development, hormone response, and stress response. Moreover, the expression of LcHSP70 genes displayed distint tissue-specific expression level, categorized into universal expression and specific expression. From the selected 6 LcHSP70 genes (i.e., LcHSP70-1, LcHSP70-5, LcHSP70-10, LcHSP70-14, LcHSP70-16, and LcHSP70-18), their relative expression levels were assessed under different abiotic stresses using qRT-PCR. The results indicated that the gene family members exhibited diverse responses to low temperature, high temperature, drought, and salt stress, with significant variations in their expression levels across different time periods. These results provide a foundation for further exploration of the function of the LcHSP70 gene family.

Identification and expression profiling of SAPK gene family members in Dendrobium officinale

To investigate the potential roles of stress-activated protein kinase (SAPK) gene family members in Dendrobium officinale, we employed multiple bioinformatics methods to identify the members of this family. The physicochemical properties, chromosomal localization, phylogenetic relationship, gene structure, and cis-acting elements of each D. officinale SAPK (DoSAPK) member were analyzed. In addition, their expression profiles in different tissues and under the low-temperature or salt stress treatment were determined by real-time fluorescence quantitative PCR. The results showed that D. officinale carried eight DoSAPK family members, which belonged to three groups (groups Ⅰ, Ⅱ, and Ⅲ). These genes were located on seven chromosomes, and there were two pairs of genes with replication. The DoSAPK members within the same group had similar gene structures, conserved motifs, and secondary structures. The cis-acting elements in the promoter regions of DoSAPK genes included abundant hormone and stress response elements. DoSAPK family members presented tissue-specific expression in D. officinale. Furthermore, they were differentially expressed under the low-temperature or salt stress treatment, which suggested that they might be involved in the responses to low-temperature and salt stress. Intriguingly, DoSAPK1 might play a role in the abiotic stress responses. The results laid a foundation for in-depth study of the members and roles of the DoSAPK gene family.

Pluronic F127 hydrogel-loaded extracellular vesicles from adipose-derived mesenchymal stem cells promote tracheal cartilage regeneration via SCNN1B delivery

Extracellular vesicles (EVs) derived from adipose-derived mesenchymal stem cells (AMSC-EVs) have been highlighted as a cell-free therapy due to their regenerative capability to enhance tissue and organ regeneration. Herein, we aimed to examine the mechanism of PF127-hydrogel@AMSC-EVs in promoting tracheal cartilage defect repair. Based on bioinformatics methods, SCNN1B was identified as a key gene for the osteogenic differentiation of AMSCs induced by AMSC-EVs. EVs were isolated from rat AMSCs and then loaded onto thermo-sensitive PF-127 hydrogel to develop PF127-hydrogel@AMSC-EVs. It was established that PF127-hydrogel@AMSC-EVs could effectively deliver SCNN1B into AMSCs, where SCNN1B promoted AMSC osteogenic differentiation. The promotive effect was evidenced by enhanced ALP activity, extracellular matrix mineralization, and expression of s-glycosaminoglycan, RUNX2, OCN, collagen II, PERK, and ATF4. Furthermore, the in vivo experiments revealed that PF127-hydrogel@AMSC-SCNN1B-EVs stimulated tracheal cartilage regeneration in rats through PERK/ATF4 signaling axis activation. Therefore, PF127-hydrogel@AMSC-SCNN1B-EVs may be a novel cell-free biomaterial to facilitate tracheal cartilage regeneration and cartilage injury repair.

Identification of Key lncRNAs Associated with Immune Infiltration and Prognosis in Gastric Cancer.

Long non-coding RNAs (lncRNAs), as promising novel biomarkers for cancer treatment and prognosis, can function as tumor suppressors and oncogenes in the occurrence and development of many types of cancer, including gastric cancer (GC). However, little is known about the complex regulatory system of lncRNAs in GC. In this study, we systematically analyzed lncRNA and miRNA transcriptomic profiles of GC based on bioinformatics methods and experimental validation. An lncRNA-miRNA interaction network related to GC was constructed, and the nine crucial lncRNAs were identified. These 9 lncRNAs were found to be associated with the prognosis of GC patients by Cox proportional hazards regression analysis. Among them, the expression of lncRNA SNHG14 can affect the survival of GC patients as a potential prognostic marker. Moreover, it was shown that SNHG14 was involved in immune-related pathways and significantly correlated with immune cell infiltration in GC. Meanwhile, we found that SNHG14 affected immune function in many cancers, such as breast cancer and esophageal carcinoma. Such information revealed that SNHG14 may serve as a potential target for cancer immunotherapy. As well, our study could provide practical and theoretical guiding significance for clinical application of non-coding RNAs.

The oncogenic role and regulatory mechanism of ACAA2 in human ovarian cancer.

Acetyl-CoAacyltransferase2 (ACAA2) is a key enzyme in the fatty acid oxidation pathway that catalyzes the final step of mitochondrial β oxidation, which plays an important role in fatty acid metabolism. The expression of ACAA2 is closely related to the occurrence and malignant progression of tumors. However, the function of ACAA2 in ovarian cancer is unclear. The expression level and prognostic value of ACAA2 were analyzed by databases. Gain and loss of function were carried out to explore the function of ACAA2 in ovarian cancer. RNA-seq and bioinformatics methods were applied to illustrate the regulatory mechanism of ACAA2. ACAA2 overexpression promoted the growth, proliferation, migration, and invasion of ovarian cancer, and ACAA2 knockdown inhibited the malignant progression of ovarian cancer as well as the ability of subcutaneous tumor formation in nude mice. At the same time, we found that OGT can induce glycosylation modification of ACAA2 and regulate the karyoplasmic distribution of ACAA2. OGT plays a vital role in ovarian cancer as a function of oncogenes. In addition, through RNA-seq sequencing, we found that ACAA2 regulates the expression of DIXDC1. ACAA2 regulated the malignant progression of ovarian cancer through the WNT/β-Catenin signaling pathway probably. ACAA2 is an oncogene in ovarian cancer and has the potential to be a target for ovarian cancer therapy.

Analysis and prediction of interactions between transmembrane and non-transmembrane proteins

BackgroundMost of the important biological mechanisms and functions of transmembrane proteins (TMPs) are realized through their interactions with non-transmembrane proteins(nonTMPs). The interactions between TMPs and nonTMPs in cells play vital roles in intracellular signaling, energy metabolism, investigating membrane-crossing mechanisms, correlations between disease and drugs.ResultsDespite the importance of TMP-nonTMP interactions, the study of them remains in the wet experimental stage, lacking specific and comprehensive studies in the field of bioinformatics. To fill this gap, we performed a comprehensive statistical analysis of known TMP-nonTMP interactions and constructed a deep learning-based predictor to identify potential interactions. The statistical analysis describes known TMP-nonTMP interactions from various perspectives, such as distributions of species and protein families, enrichment of GO and KEGG pathways, as well as hub proteins and subnetwork modules in the PPI network. The predictor implemented by an end-to-end deep learning model can identify potential interactions from protein primary sequence information. The experimental results over the independent validation demonstrated considerable prediction performance with an MCC of 0.541.ConclusionsTo our knowledge, we were the first to focus on TMP-nonTMP interactions. We comprehensively analyzed them using bioinformatics methods and predicted them via deep learning-based solely on their sequence. This research completes a key link in the protein network, benefits the understanding of protein functions, and helps in pathogenesis studies of diseases and associated drug development.

Decoding cardiovascular risks: analyzing type 2 diabetes mellitus and ASCVD gene expression.

ASCVD is the primary cause of mortality in individuals with T2DM. A potential link between ASCVD and T2DM has been suggested, prompting further investigation. We utilized linear and multivariate logistic regression, Wilcoxon test, and Spearman's correlation toanalyzethe interrelation between ASCVD and T2DM in NHANES data from 2001-2018.The Gene Expression Omnibus (GEO) database and Weighted Gene Co-expression Network Analysis (WGCNA) wereconducted to identify co-expression networks between ASCVD and T2DM. Hub genes were identified using LASSO regression analysis and further validated in two additional cohorts. Bioinformatics methods were employed for gene ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, along with the prediction of candidate small molecules. Our analysis of the NHANES dataset indicated a significant impact of blood glucose on lipid levels within diabetic cohort, suggesting that abnormal lipid metabolism is a critical factor in ASCVD development. Cross-phenotyping analysis revealed two pivotal genes, ABCC5 and WDR7, associated with both T2DM and ASCVD. Enrichment analyses demonstrated the intertwining of lipid metabolism in both conditions, encompassing adipocytokine signaling pathway, fatty acid degradation and metabolism, and the regulation of adipocyte lipolysis. Immune infiltration analysis underscored the involvement of immune processes in both diseases. Notably, RITA, ON-01910, doxercalciferol, and topiramate emerged as potential therapeutic agents for both T2DM and ASCVD, indicating their possible clinical significance. Our findings pinpoint ABCC5 and WDR7 as new target genes between T2DM and ASCVD, with RITA, ON-01910, doxercalciferol, and topiramate highlighted as promising therapeutic agents.

Genome-wide characterization of DNA methyltransferase family genes implies GhDMT6 improving tolerance of salt and drought on cotton

BackgroundDNA methylation is an important epigenetic mode of genomic DNA modification and plays a vital role in maintaining epigenetic content and regulating gene expression. Cytosine-5 DNA methyltransferase (C5-MTase) are the key enzymes in the process of DNA methylation. However, there is no systematic analysis of the C5-MTase in cotton so far, and the function of DNMT2 genes has not been studied.MethodsIn this study, the whole genome of cotton C5-MTase coding genes was identified and analyzed using a bioinformatics method based on information from the cotton genome, and the function of GhDMT6 was further validated by VIGS experiments and subcellular localization analysis.Results33 C5-MTases were identified from three cotton genomes, and were divided into four subfamilies by systematic evolutionary analysis. After the protein domain alignment of C5-MTases in cotton, 6 highly conserved motifs were found in the C-terminus of 33 proteins involved in methylation modification, which indicated that C5-MTases had a basic catalytic methylation function. These proteins were divided into four classes based on the N-terminal difference, of which DNMT2 lacks the N-terminal regulatory domain. The expression of C5-MTases in different parts of cotton was different under different stress treatments, which indicated the functional diversity of cotton C5-MTase gene family. Among the C5-MTases, the GhDMT6 had a obvious up-regulated expression. After silencing GhDMT6 with VIGS, the phenotype of cotton seedlings under different stress treatments showed a significant difference. Compared with cotton seedlings that did not silence GhDMT6, cotton seedlings silencing GhDMT6 showed significant stress resistance.ConclusionThe results show that C5-MTases plays an important role in cotton stress response, which is beneficial to further explore the function of DNMT2 subfamily genes.

Identification of osteoporosis ferroptosis-related markers and potential therapeutic compounds based on bioinformatics methods and molecular docking technology

Research background and purposeOsteoporosis (OP) is one of the most common bone diseases worldwide, characterized by low bone mineral density and susceptibility to pathological fractures, especially in postmenopausal women and elderly men. Ferroptosis is one of the newly discovered forms of cell death regulated by genes in recent years. Many studies have shown that ferroptosis is closely related to many diseases. However, there are few studies on ferroptosis in osteoporosis, and the mechanism of ferroptosis in osteoporosis is still unclear. This study aims to identify biomarkers related to osteoporosis ferroptosis from the GEO (Gene Expression Omnibus) database through bioinformatics technology, and to mine potential therapeutic small molecule compounds through molecular docking technology, trying to provide a basis for the diagnosis and treatment of osteoporosis in the future.Materials and methodsWe downloaded the ferroptosis-related gene set from the FerrDb database (http://www.zhounan.org/ferrdb/index.html), downloaded the data sets GSE56815 and GSE7429 from the GEO database, and used the R software “limma” package to screen differentially expressed genes (DEGs) from GSE56815, and intersected with the ferroptosis gene set to obtain ferroptosis-related DEGs. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were performed by the R software “clusterProfiler” package. The random forest model was further screened to obtain essential ferroptosis genes. R software “corrplot” package was used for correlation analysis of essential ferroptosis genes, and the Wilcox test was used for significance analysis. The lncRNA-miRNA-mRNA-TF regulatory network was constructed using Cytoscape software. The least absolute shrinkage and selection operator (LASSO) was used to construct a disease diagnosis model, and a Receiver operating characteristic (ROC) curve was drawn to evaluate the diagnostic performance, and then GSE7429 was used to verify the reliability of the diagnosis model. Molecular docking technology was used to screen potential small molecule compounds from the Drugbank database. Finally, a rat osteoporosis model was constructed, and peripheral blood mononuclear cells were extracted for qRT-PCR detection to verify the mRNA expression levels of crucial ferroptosis genes.ResultSix DEGs related to ferroptosis were initially screened out. GO function and KEGG pathway enrichment analysis showed that ferroptosis-related DEGs were mainly enriched in signaling pathways such as maintenance of iron ion homeostasis, copper ion binding function, and ferroptosis. The random forest model identified five key ferroptosis genes, including CP, FLT3, HAMP, HMOX1, and SLC2A3. Gene correlation analysis found a relatively low correlation between these five key ferroptosis genes. The lncRNA-miRNA-mRNA-TF regulatory network shows that BAZ1B and STAT3 may also be potential molecules. The ROC curve of the disease diagnosis model shows that the model has a good diagnostic performance. Molecular docking technology screened out three small molecule compounds, including NADH, Midostaurin, and Nintedanib small molecule compounds. qRT-PCR detection confirmed the differential expression of CP, FLT3, HAMP, HMOX1 and SLC2A3 between OP and normal control group.ConclusionThis study identified five key ferroptosis genes (CP, FLT3, HAMP, HMOX1, and SLC2A3), they were most likely related to OP ferroptosis. In addition, we found that the small molecule compounds of NADH, Midostaurin, and Nintedanib had good docking scores with these five key ferroptosis genes. These findings may provide new clues for the early diagnosis and treatment of osteoporosis in the future.