Bioinformatics Methods Research Articles

Identification of potential biomarkers for neuromyelitis optica by quantitative proteomics.

Neuromyelitis optica (NMO) was a serious autoimmune inflammatory condition affecting the central nervous system. Currently, there was a lack of diagnostic biomarkers for AQP4-IgG-negative NMO patients. A comparative proteomic analysis was conducted on the CSF of 10 patients with NMO and 10 patients with non-inflammatory neurological disorders (NND) using tandem mass tagging technology. Differentially expressed proteins (DEPs) were analyzed using bioinformatic methods. The candidate proteins were then validated through ELISAs in a subsequent cohort of 160 samples, consisting of paired CSF and plasma samples from 50 NMO patients, CSF samples from 30 NND patients, and plasma samples from 30 healthy individuals. We identified 389 proteins via proteomics, screening 79 DEPs. NCAM1, SST and AHSG were selected as candidate molecules for further validation. Compared to NND patients, there were decreased levels of AHSG in CSF and increased levels of NCAM1 and SST in NMO patients. The ELISA results revealed significantly higher levels of AHSG, SST and NCAM1 in the CSF of the NMO group compared to the NND group. Similarly, the serum levels of these three proteins were also higher in the NMO group compared to the healthy control group. It was found that serum NCAM1 levels significantly decreased in patients with non-relapsed NMO compared to patients with relapsed NMO and CSF NCAM1 level increased in patients with bilateral NMO compared to patients with unilateral NMO. Furthermore, CSF SST levels increased in AQP4 antibody-positive NMO patients compared to AQP4 antibody-negative patients. CSF NCAM1, serum NCAM1 and serum SST may serve as potential biomarkers for NMO patients and aid in the diagnosis of AQP4 antibody-negative NMO patients.

Screening of key immune-related gene in Parkinson's disease based on WGCNA and machine learning.

Abnormal immune system activation and inflammation are crucial in causing Parkinson's disease. However, we still don't fully understand how certain immune-related genes contribute to the disease's development and progression. This study aims to screen key immune-related gene in Parkinson's disease based on weighted gene co-expression network analysis (WGCNA) and machine learning. This study downloaded the gene chip data from the Gene Expression Omnibus (GEO) database, and used WGCNA to screen out important gene modules related to Parkinson's disease. Genes from important modules were exported and a Venn diagram of important Parkinson's disease-related genes and immune-related genes was drawn to screen out immune related genes of Parkinson's disease. Gene ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) were used to analyze the the functions of immune-related genes and signaling pathways involved. Immune cell infiltration analysis was performed using the CIBERSORT package of R language. Using bioinformatics method and 3 machine learning methods [least absolute shrinkage and selection operator (LASSO) regression, random forest (RF), and support vector machine (SVM)], the immune-related genes of Parkinson's disease were further screened. A Venn diagram of differentially expressed genes screened using the 4 methods was drawn with the intersection gene being hub nodes (hub) gene. The downstream proteins of the Parkinson's disease hub gene was identified through the STRING database and a protein-protein interaction network diagram was drawn. A total of 218 immune genes related to Parkinson's disease were identified, including 45 upregulated genes and 50 downregulated genes. Enrichment analysis showed that the 218 genes were mainly enriched in immune system response to foreign substances and viral infection pathways. The results of immune infiltration analysis showed that the infiltration percentages of CD4+ T cells, NK cells, CD8+ T cells, and B cells were higher in the samples of Parkinson's disease patients, while resting NK cells and resting CD4+ T cells were significantly infiltrated in the samples of Parkinson's disease patients. ANK1 was screened out as the hub gene. The analysis of the protein-protein interaction network showed that the ANK1 translated and expressed 11 proteins which mainly participated in functions such as signal transduction, iron homeostasis regulation, and immune system activation. This study identifies the Parkinson's disease immune-related key gene ANK1 via WGCNA and machine learning methods, suggesting its potential as a candidate therapeutic target for Parkinson's disease.

The mechanism of action and experimental verification of Gan-song Yin on renal clear cell carcinoma based on network pharmacology and bioinformatics

BackgroundGan-song Yin (GSY) is originated from the scripture “Gan-song Pills”, a medical work of the Ningxia ethnic minorities, and its treatment of kidney diseases has good results. Its method of treating Renal clear cell carcinoma (KIRC) is still unknown, nevertheless.MethodsFirstly, utilizing a network pharmacology strategy to screen GSY for active components and targets and looking up KIRC-related targets in GeneCards and GEO databases. Secondly, protein interaction networks were constructed and analyzed for GO and KEGG enrichment. Molecular docking was then performed and clinical and other correlations of the network pharmacology results were analyzed using bioinformatic analysis methods. Finally, we performed in vitro cellular experiments with 786-O cells and ACHN cells to validate the results of network pharmacology and bioinformatic analysis.ResultsWith the help of network pharmacological analysis, six hub targets were eliminated. Bioinformatics study revealed that the hub targets has clinically significant clinical guiding importance. The results showed that GSY inhibited the proliferation of 786-O cells and ACHN cells, induced cell apoptosis, blocked cell cycle, and reduced cell colony formation ability. qRT-PCR results showed that GSY promoted the expression of ALB and CASP3 genes, and inhibited the expression of EGFR, JUN, MYC and VEGFA genes. Western blot results showed that GSY could promote the expression of ALB and CASP3 protein, and inhibit the expression of EGFR, JUN, MYC and VEGFA protein.ConclusionsNetwork pharmacology and bioinformatics analysis showed that GSY could act on multiple targets through a variety of components to achieve the effect of treating KIRC. In this study, we confirmed that GSY inhibits KIRC by regulating the expression of core targets through in vitro cellular experiments, thus providing a reference for subsequent related studies.

Comprehensive Analysis Based on the TCGA Database Identified SCIN as a Key DNA Methylation-Driver Gene in Epstein-Barr Virus-Associated Gastric Cancer.

An important feature of EBV-associated gastric cancer (EBVaGC) is extensive methylation of viral and host genomes. This study aims to analyze DNA methylation-driven genes (DMDG) in EBVaGC through bioinformatics methods, providing an important bioinformatics basis for the differential diagnosis and treatment of potential methylation biomarkers in EBVaGC. We downloaded the mRNA expression profiles and methylation datasets of EBVaGC and EBV-negative gastric cancer (EBVnGC) through the TCGA database to screen methylated-differentially expressed genes (MDEGs). DNA methylation-driver genes were identified based on MethylMix algorithm and key genes were further identified by LASSO regression and Random Forest algorithm. Then, we performed gene enrichment analysis for key genes and validated them by GEO database. Gene expression differences in EBVaGC and EBVnGC cell lines was determined by quantitative real-time PCR (qRT-PCR) and western blotting and in GT38 cell and SNU719 cell which all treated by 5-Aza-CdR. Finally, the effect of key gene on the migration and proliferation capacity of EBVaGC cells was determined by Transwells assay and Cell counting Kit-8 (CCK-8) assay. We obtained a total of 687 hypermethylation-low expression genes (Hyper-LGs) and further obtained 53 DNA methylation-driver genes based on the MethylMix algorithm. A total of six key genes (SCIN, ETNK2, PCDH20, PPP1R3C, MATN2, and HOXA5) were identified by LASSO regression and Random Forest algorithm. Among them, SCIN expression was significantly lower in EBVaGC cell lines than in EBVnGC cell lines, and its expression was significantly recovered in EBVaGC cell lines treated with 5-Aza-CdR. Overexpression of SCIN can promote the proliferation and migration capacity of EBVaGC cells. Our study will provide some bioinformatics basis for the study of EBVaGC-related methylation. SCIN may be used as potential methylation biomarkers for the diagnosis and treatment of EBVaGC.

Genome-Wide Identification of Vascular Plant One-Zinc-Finger Gene Family in Six Cucurbitaceae Species and the Role of CmoVOZ2 in Salt and Drought Stress Tolerance.

As a plant-specific transcription factor, the vascular plant one-zinc-finger (VOZ) plays a crucial role in regulating various biological processes. In this study, a total of 17 VOZ genes in the Cucurbitaceae family were investigated using various bioinformatics methods. The 17 VOZ genes in Cucurbitaceae are distributed across 16 chromosomes. Based on the affinity of VOZ proteins to AtVOZ proteins, these 17 proteins were categorized into two groups: group I encompassed eight VOZ members, while group II comprised nine VOZ members. The expression profiles of CmoVOZs under various hormonal and abiotic stresses indicated that these genes were induced differentially by JA, ABA, GA, salt, and drought stress. Subsequently, CmoVOZ1 and CmoVOZ2 were found to be transcriptionally active, with the CmoVOZ2 protein being located mainly in the nucleus. Further experiments revealed that yeast cells expressing CmoVOZ2 gene showed increased tolerance to salt stress and drought stress. These results suggest that the VOZ gene family is not only important for plant growth and development but also that this mechanism may be universal across yeast and plants.

Fusobacterium nucleatum dysregulates inflammatory cytokines and NLRP3 inflammasomes in oral cells.

This study aimed to clarify the difference in Fusobacterium nucleatum (F. nucleatum) induced inflammatory cytokines and nod-like receptor protein 3 (NLRP3) inflammasomes dysregulation among three periodontal cells. Oral epithelial cells (HIOECs), THP-1 macrophages, and human gingival fibroblasts (HGFs) were exposed to F. nucleatum with/without adenosine triphosphate (ATP) and nigericin (Nig). Cell morphology was assessed by scanning electron microscopy. qRT-PCR, protein microarrays, and bioinformatic methods were used to evaluate the cytokines and their complex interplay. NLRP3 inflammasomes activation was detected by western blotting and ELISA. F. nucleatum adhered to and invaded cells. In HIOECs, F. nucleatum enhanced interleukin (IL)-1α/1β/6/10/13, TNF-α, and interferon (IFN)-γ expression. In THP-1 macrophages, F. nucleatum up-regulated IL-1α/1β/6/10 and TNF-α levels. In HGFs, F. nucleatum increased IL-6 levels. F. nucleatum and ATP synergistically boosted IFN-γ level in THP-1 macrophages and IL-13 level in HGFs. IL-1α/1β/6, and TNF-α served as epicenters of the inflammatory response. Additionally, F. nucleatum activated NLRP3 inflammasomes in HIOECs, and ATP/Nig boosted the activation. F. nucleatum also triggered NLRP3 inflammasomes in THP-1 macrophages, but in HGFs, only NLRP3 and caspase-1 levels were elevated. F. nucleatum infiltrated periodontal supporting cells and dysregulated inflammatory cytokines and NLRP3 inflammasomes.

In-silico screening of bioactive compounds from nut grass (Cyperus rotundus) to inhibit the α-bungarotoxin from Kraits (Bungarus spp.) venom

ABSTRACT Kraits (Bungarus spp.) are the snakes that commonly cause fatal bites in Tropical Asia due to their neurotoxic venom. The complex process of antivenom production contributes to the lack of available antivenom and amplifies the burden of snakebite in that region. Thus, the victims seek traditional medicine such as root extract from nut grass (Cyperus rotundus). In the present study, we utilized bioinformatics methods to analyze the potential inhibitory activity of bioactive compounds from nut grass (Cyperus rotundus) against kraits’ α-bungarotoxin. Twenty-one bioactive compounds were screened using ADMET, membrane permeability prediction, molecular docking and molecular dynamics simulations. Among these bioactive compounds, we found that alpha-cyperone, cyperol, cyperusol, rotundine A, rotundine B and 4,6,3’,4’-Tetramethoxyaurone had inhibitory activity by presenting a good ability to pass phospholipid bilayer and could bind stably into active sites of α-bungarotoxin with minimum energy required. Importantly, the neutralization property of these bioactive compounds resides in their combinational function, underscoring the crucial significance of their combined action rather than individual contributions. In conclusion, this study identifies a combination of six bioactive compounds from C. rotundus with a potential as an alternative antivenom based on in-silico screening and provides essential data for the development of a plant-based antivenom.

Transcriptomic responses of cumulus granulosa cells to SARS-CoV-2 infection during controlled ovarian stimulation.

Cumulus granulosa cells (CGCs) play a crucial role in follicular development, but so far, no research has explored the impact of SARS-CoV-2 infection on ovarian function from the perspective of CGCs. In the present study, we compared the cycle outcomes between infected and uninfected female patients undergoing controlled ovarian stimulation, performed bulk RNA-sequencing of collected CGCs, and used bioinformatic methods to explore transcriptomic changes. The results showed that women with SARS-CoV-2 infection during stimulation had significantly lower number of oocytes retrieved and follicle-oocyte index, while subsequent fertilization and embryo development were similar. CGCs were not directly infected by SARS-CoV-2, but exhibited dramatic differences in gene expression (156 up-regulated and 65 down-regulated). Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses demonstrated a high enrichment in antiviral, immune and inflammatory responses with necroptosis. In addition, the pathways related to telomere organization and double strand break repair were significantly affected by infection in gene set enrichment analysis. Further weighted gene co-expression network analysis identified a key module associated with ovarian response traits, which was mainly enriched as a decrease of leukocyte chemotaxis and migration in CGCs. For the first time, our study describes how SARS-CoV-2 infection indirectly affects CGCs at the transcriptional level, which may impair oocyte-CGC crosstalk and consequently lead to poor ovarian response during fertility treatment.

Updated Insights into Probiotics and Hepatobiliary Diseases.

Hepatobiliary diseases have a high prevalence worldwide, with a wide range of diseases involved in the liver and biliary system. Modifications in gut microbiota have been proven to have an association with unbalanced intestinal homeostasis and the dysfunction of host metabolism and the immune system, which can be the risk factors for many hepatobiliary diseases, such as nonalcoholic fatty liver disease (NAFLD), alcoholic liver disease (ALD), nonalcoholic fatty steatohepatitis (NASH), hepatitis, cirrhosis, hepatocellular carcinoma (HCC) and cholestasis, as well as infection due to liver transplantation. Probiotics are commonly used gut microbiota-targeted strategies to treat dysbiosis and intestinal dysfunction, as well as the gut-liver axis, which can enhance the effectiveness of probiotics in the management of liver diseases. Recent studies have explored more potential single or mixed strains of probiotics, and bioinformatics methods can be used to investigate the potential mechanisms of probiotics on liver diseases. In this review, we summarize the preclinical and clinical studies on the role of probiotics in hepatobiliary diseases from 2018 to 2023, revealing the possible mechanism of probiotics in the treatment of hepatobiliary diseases and discussing the limitations of probiotics in treating hepatobiliary diseases. This review provides updated evidence for the development of probiotic products, exploration of new probiotic strains, and support for clinical studies. Further studies should focus on the safety, viability, and stability of probiotics, as well as medication dosage and duration in clinical practice.

Integrated analysis and validation of ferroptosis-related genes and immune infiltration in acute myocardial infarction

BackgroundAcute myocardial infarction (AMI) is indeed a significant cause of mortality and morbidity in individuals with coronary heart disease. Ferroptosis, an iron-dependent cell death, is characterized by the accumulation of intracellular lipid peroxides, which is implicated in cardiomyocyte injury. This study aims to identify biomarkers that are indicative of ferroptosis in the context of AMI, and to examine their potential roles in immune infiltration.MethodsFirstly, the GSE59867 dataset was used to identify differentially expressed ferroptosis-related genes (DE-FRGs) in AMI. We then performed gene ontology (GO) and functional enrichment analysis on these DE-FRGs. Secondly, we analyzed the GSE76591 dataset and used bioinformatic methods to build ceRNA networks. Thirdly, we identified hub genes in protein–protein interaction (PPI) network. After obtaining the key DE-FRGs through the junction of hub genes with ceRNA and least absolute shrinkage and selection operator (LASSO). ImmucellAI was applied to estimate the immune cell infiltration in each sample and examine the relationship between key DE-FRGs and 24 immunocyte subsets. The diagnostic performance of these genes was further evaluated using the receiver operating characteristic (ROC) curve analysis. Ultimately, we identified an immune-related ceRNA regulatory axis linked to ferroptosis in AMI.ResultsAmong 56 DE-FRGs identified in AMI, 41 of them were integrated into the construction of competitive endogenous RNA (ceRNA) networks. TLR4 and PIK3CA were identified as key DE-FRGs and PIK3CA was confirmed as a diagnostic biomarker for AMI. Moreover, CD4_native cells, nTreg cells, Th2 cells, Th17 cells, central-memory cells, effector-memory cells, and CD8_T cells had higher infiltrates in AMI samples compared to control samples. In contrast, exhausted cells, iTreg cells, and Tfh cells had lower infiltrates in AMI samples. Spearman analysis confirmed the correlation between 24 immune cells and PIK3CA/TLR4. Ultimately, we constructed an immune-related regulatory axis involving XIST and OIP5-AS1/miR-216a/PIK3CA.ConclusionOur comprehensive analysis has identified PIK3CA as a robust and promising biomarker for this condition. Moreover, we have also identified an immune-related regulatory axis involving XIST and OIP5-AS1/miR-216a/PIK3CA, which may play a key role in regulating ferroptosis during AMI progression.

Leucine rich repeat LGI family member 3: Integrative analyses support its prognostic association with pancreatic adenocarcinoma.

Leucine rich repeat LGI family member 3 (LGI3) is a member of the LGI protein family. Previous studies of our group have reported that LGI3 is expressed in adipose tissue, skin and brain, and serves as a multifunctional cytokine. LGI3 may also be involved in cytokine networks in various cancers. This study aimed to analyze differentially expressed genes in pancreatic adenocarcinoma (PAC) tissues and PAC cohort data in order to evaluate the prognostic role of LGI3. The expression microarray and the PAC cohort data were analyzed by bioinformatic methods for differential expression, protein-protein interactions, functional enrichment and pathway analyses, gene co-expression network analysis, and prognostic association analysis. Results showed that LGI3 expression was significantly reduced in PAC tissues. Nineteen upregulated genes and 31 downregulated genes in PAC tissues were identified as LGI3-regulated genes. Protein-protein interaction network analysis demonstrated that 92% (46/50) of the LGI3-regulated genes that were altered in PACs belonged to a protein-protein interaction network cluster. Functional enrichment and gene co-expression network analyses demonstrated that these genes in the network cluster were associated with various processes including inflammatory and immune responses, metabolic processes, cell differentiation, and angiogenesis. PAC cohort analyses revealed that low expression levels of LGI3 were significantly associated with poor PAC prognosis. Analysis of favorable or unfavorable prognostic gene products in PAC showed that 93 LGI3-regulated genes were differentially associated with PAC prognosis. LGI3 expression was correlated with the tumor-infiltration levels of various immune cells. Taken together, these results suggested that LGI3 may be a potential prognostic marker of PAC.

Analysis of Chemical Constituents of Miao Ethnomedicine Heiguteng Zhuifeng Huoluo Capsule (HZFC) and the Discovery of Active Substances in the Treatment of Rheumatoid Arthritis.

In this study, the chemical substances of Heiguteng Zhuifeng Huoluo Capsule (HZFC) and its potential active ingredients for the treatment of rheumatoid arthritis (RA) were characterized and analyzed by medicinal chemistry combined with bioinformatics methods. Also, the potential active ingredients of HZFC against RA were verified by lipopolysaccharide (LPS)-induced macrophage activation model. The results showed that 79 chemical constituents were successfully identified, mainly including phenylpropanoids, flavonoids, and alkaloids. Among them, 13 active components were closely related to the nine core targets (FASN, ALOX5, EGFR, MMP1, CYP2D6, CNR1, AR, MAOA, and FKBP5) of HZFC in the treatment of RA. Molecular docking further proved that 13 active components had strong docking activity with 9 core targets. In the verification experiment of the LPS-induced RAW 264.7 macrophage model, the verified components (magnoflorine, N-feruloyltyramine, canadine, rutin, quercetin-3-O-glucoside, and pseudocolumbamine) all showed a clear inhibitory effect on the secretion of inflammatory factors in model cells. The above research results suggest that 13 components such as stepharanine, rutin, quercetin-3-O-glucoside, corydine methyl ether, canadine, 8-oxoepiberberine, disinomenine, deosinomenine glucoside, tuduranine, magnoflorine, isosinomenine, pseudocolumbamine, and N-feruloyltyramine may be the main active substances of HZFC in the treatment of RA.

Bioinformatics Analysis of Immunoglobulin ε (IgE) Heavy Chain

Immunoglobulin ε is a key immunoglobulin that plays an important role in the immune system. IgE is usually associated with allergic reactions such as food allergies, allergic rhinitis, and allergic dermatitis. In this project, this article Use NCBI or https://www.uniprot.org/ Website to obtain immunoglobulins ε Heavy chain related nucleotide sequences. Using relevant websites and software to analyze and predict immunoglobulins using bioinformatics methods ε Bioinformatics analysis of heavy chains includes physical and chemical properties, structural functions, positional expression, phylogenetic relationships, protein interactions, etc. Understanding the bioinformatics analysis of IgE can help reveal its function in the immune system and its relationship with allergies and other diseases, promote the improvement of diagnosis and treatment methods for allergic diseases, and advance in the field of immunotherapy.

A novel bioinformatic method for the identification of antimicrobial peptides in metagenomes.

This study aimed to develop a new bioinformatic approach for the identification of novel antimicrobial peptides (AMPs), which did not depend on sequence similarity to known AMPs held within databases, but on structural mimicry of another antimicrobial compound, in this case an ultrashort, synthetic, cationic lipopeptide (C12-OOWW-NH2). When applied to a collection of metagenomic datasets, our outlined bioinformatic method successfully identified several short (8-10aa) functional AMPs, the activity of which was verified via disk diffusion and minimum inhibitory concentration assays against a panel of 12 bacterial strains. Some peptides had activity comparable to, or in some cases, greater than, those from published studies that identified AMPs using more conventional methods. We also explored the effects of modifications, including extension of the peptides, observing an activity peak at 9-12aa. Additionally, the inclusion of a C-terminal amide enhanced activity in most cases. Our most promising candidate (named PB2-10aa-NH2) was thermally stable, lipid-soluble, and possessed synergistic activity with ethanol but not with a conventional antibiotic (streptomycin). While several bioinformatic methods exist to predict AMPs, the approach outlined here is much simpler and can be used to quickly scan huge datasets. Searching for peptide sequences bearing structural similarity to other antimicrobial compounds may present a further opportunity to identify novel AMPs with clinical relevance, and provide a meaningful contribution to the pressing global issue of AMR.

Genome-wide identification and analysis of SPL gene family in chickpea (Cicer arietinum L.).

A transcription factor in plants encodes SQUAMOSA promoter binding protein-like (SPL) serves a broad spectrum of important roles for the plant, like, growth, flowering, and signal transduction. A gene family that encodes SPL proteins is documented in various model plant species, including Arabidopsis thaliana and Oryza sativa. Chickpea (Cicer arietinum), a leguminous crop, has not been thoroughly explored with regard to the SPL protein-encoding gene family. Chickpea SPL family genes were located and characterized computationally using a genomic database. Gene data of chickpea were obtained from the phytozome repository and was examined using bioinformatics methods. For investigating the possible roles of SPLs in chickpea, genome-wide characterization, expression, as well as structural analyses of this SPL gene family were performed. Cicer arietinum genome had 19 SPL genes, whereas, according to phylogenetic analysis, the SPLs in chickpea are segregated among four categories: Group-I has 2 introns, Group-II and IV have 1-2 introns (except CaSPL13 and CaSPL15 having 3 introns), and Group-III has 9 introns (except CaSPL1 and CaSPL11 with 1 and 8 introns, respectively). The SBP domain revealed that SPL proteins featured two zinc-binding sites, i.e., C3H and C2HC and one nuclear localization signal. All CaSPL proteins are found to contain highly conserved motifs, i.e., Motifs 1, 2, and 4, except CaSPL10 in which Motifs 1 and 4 were absent. Following analysis, it was found that Motifs 1 and 2 of the chickpea SBP domain are Zinc finger motifs, and Motif 4 includes a nuclear localization signal. All pairs of CaSPL paralogs developed by purifying selection. The CaSPL promoter investigation discovered cis-elements that are responsive to stress, light, and phytohormones. Examination of their expression patterns highlighted major CaSPLs to be evinced primarily among younger pods and flowers. Indicating their involvement in the plant's growth as well as development, along with their capacity to react as per different situations by handling the regulation of target gene's expression, several CaSPL genes are also expressed under certain stress conditions, namely, cold, salt, and drought. The majority of the CaSPL genes are widely expressed and play crucial roles in terms of the plant's growth, development, and responses to the environmental-stress conditions. Our work provides extensive insight into the gene family CaSPL, which might facilitate further studies related to the evolution and functions of the SPL genes for chickpea and other plant species.

RNA-binding proteins signature is a favorable biomarker of prognosis, immunotherapy and chemotherapy response for cervical cancer

Cervical squamous cell carcinoma and endocervical adenocarcinoma (CESC) still present a huge threaten to women’s health, especially the local advanced patients. Hence, developing more effectiveness prognostic signatures is urgently needed. This study constructed and verified a robust RNA-binding proteins (RBPs) related signature through a series of bioinformatics methods and explored the biological function of hub RBP in vitro experiments. As a result, the 10 RBPs signature was successfully established and could act as an independent prognostic biomarker in CESC patients, which displayed the highest sensitivity and specificity in prognosis prediction compared with other clinicopathological parameters. The risk model also presented good performance in risk stratification among CESC patients. Besides, a nomogram was constructed based on pathological stage and the risk signature and exhibited satisfactory accuracy in prognosis prediction. Functional enrichment indicated that the risk signature mainly participated in immune-related pathways and cancer-related pathways, and the infiltration level of immune cells and immune checkpoints showed a significantly higher degree in low-risk patients compared with high-risk patients. Notably, the 10 RBPs signature act as a novel biomarker in immunotherapy and chemotherapy response. In addition, PRPF40B was selected as hub RBP and its transcription and translation levels were obviously increased in CESC tissues, as well as Hela and Siha cells. Knockdown of PRPF40B inhibits the proliferation, migration and invasion of Hela and Siha cells in vitro. In conclusion, our research provides a noticeable strategy in prognostic prediction among CESC patients, which may illuminate the prospect of CESC patients’ clinical outcome.

A novel peroxisome-related gene signature predicts clinical prognosis and is associated with immune microenvironment in low-grade glioma.

Low-grade glioma (LGG), a common primary tumor, mainly originates from astrocytes and oligodendrocytes. Increasing evidence has shown that peroxisomes function in the regulation of tumorigenesis and development of cancer. However, the prognostic value of peroxisome-related genes (PRGs) in LGG has not been reported. Therefore, it is necessary to construct a prognostic risk model for LGG patients based on the expression profiles of peroxisome-related genes. Our study mainly concentrated on developing a peroxisome-related gene signature for overall survival (OS) prediction in LGG patients. First, according to these peroxisome-related genes, all LGG patients from The Cancer Genome Atlas (TCGA) database could be divided into two subtypes. Univariate Cox regression analysis was used to find prognostic peroxisome-related genes in TCGA_LGG dataset, and least absolute shrinkage and selection operator Cox regression analysis was employed to establish a 14-gene signature. The risk score based on the signature was positively associated with unfavorable prognosis. Then, multivariate Cox regression incorporating additional clinical characteristics showed that the 14-gene signature was an independent predictor of LGG. Time-dependent ROC curves revealed good performance of this prognostic signature in LGG patients. The performance about predicting OS of LGG was validated using the GSE107850 dataset derived from the Gene Expression Omnibus (GEO) database. Furethermore, we constructed a nomogram model based on the gene signature and age, which showed a better prognostic power. Gene ontology (GO) and Kyoto Encylopedia of Genes and Genomes (KEGG) analyses showed that neuroactive ligand-receptor interaction and phagosome were enriched and that the immune status was decreased in the high-risk group. Finally, cell counting kit-8 (CCK8) were used to detect cell proliferation of U251 and A172 cells. Inhibition of ATAD1 (ATPase family AAA domain-containing 1) and ACBD5 (Acyl-CoA binding-domain-containing-5) expression led to significant inhibition of U251 and A172 cell proliferation. Flow cytometry detection showed that ATAD1 and ACBD5 could induce apoptosis of U251 and A172 cells. Therefore, through bioinformatics methods and cell experiments, our study developed a new peroxisome-related gene signature that migh t help improve personalized OS prediction in LGG patients.

Identification and characterization analysis of the HDM gene family in melon (Cucumis melo L.).

Histone demethylase (HDM) play crucial roles in regulating plant growth and environmental adaptation. In this study, the HDM gene family in melon was identified by bioinformatics methods and the expression patterns of the CmHDM family members in different melon tissues were analyzed using transcriptome data. The results showed that 20 CmHDM genes were identified in the melon genome, which were unevenly distributed across each chromosome. These members fall into two major categories: LSD1 and JmjC. The JmjC group could be further divided into five subgroups with different numbers. The results of collinearity analysis of intraspecific and interspecific relationships showed that there were only one pair of segmental duplication in melon HDM genes, and more collinearity in genetic relationship of HDM genes between melon and tomato. The numbers of conserved domains, exons and introns in each member vary and various cis-acting elements responding to hormones and environmental signals existed in the respective promoter regions. Expression analysis showed that the respective gene members were expressed at different levels in male flowers, female flowers, roots, stems, leaves, ovary, and mature fruits of melon. These results will contribute to the understanding on the potential functions of the HDM genes and their potential functions in regulating melon growth and environmental adaptation.

Identification and verification of inflammatory biomarkers for primary Sjögren’s syndrome

IntroductionPrimary Sjögren’s syndrome (pSS) is an autoimmune disease characterized by inflammatory infiltration, and dysfunction of the salivary and lacrimal glands. This research aimed to explore the disease pathogenesis and improve the diagnosis and treatment of pSS by mining inflammation-associated biomarkers.MethodsFive pSS-related datasets were retrieved from the Gene Expression Omnibus (GEO) database. Inflammation-associated biomarkers were determined by the least absolute shrinkage and selection operator (LASSO) and support vector machines recursive feature elimination (SVM-RFE). Single sample gene set enrichment analysis (ssGSEA) was implemented to profile the infiltration levels of immune cells. Real-time quantitative PCR (RT-qPCR) verified the expression of biomarkers in clinical samples.ResultsFour genes (LY6E, EIF2AK2, IL15, and CXCL10) were screened as inflammation-associated biomarkers in pSS, the predictive performance of which were determined among three pSS-related datasets (AUC > 0.7). Functional enrichment results suggested that the biomarkers were involved in immune and inflammation-related pathways. Immune infiltration analysis revealed that biomarkers were notably connected with type 2 T helper cells, regulatory T cells which were significantly expressed between pSS and control. TESTOSTERONE and CYCLOSPORINE were predicted to take effect by targeting CXCL10 and IL15 in pSS, respectively.ConclusionFour inflammation-associated biomarkers (LY6E, EIF2AK2, IL15, and CXCL10) were explored, and the underlying regulatory mechanisms and targeted drugs associated with these biomarkers were preliminarily investigated according to a series of bioinformatics methods based on the online datasets of pSS, which provided a reference for understanding the pathogenesis of pSS.Key Points• Inflammation-associated biomarkers (LY6E, EIF2AK2, IL15, and CXCL10) were firstly identified in Sjögren’s syndrome based on LASSO and SVM-RFE analyses.• CXCL10, EIF2AK2 and LY6E were prominently positively correlated with immature B cells, while IL15 were significantly negatively correlated with memory B cells in Sjögren’s syndrome.• LY6E, EIF2AK2, IL15, and CXCL10 were significantly more highly expressed in clinical Sjögren’s syndrome samples compared to healthy control samples, which was consistent with the analysis results of the GEO database. •LY6E, EIF2AK2, IL15, and CXCL10 might be used as the biomarkers for the treatment and diagnosis of Sjögren’s syndrome.

Comprehensive Analysis of the GRAS Gene Family in Paulownia fortunei and the Response of DELLA Proteins to Paulownia Witches' Broom.

The GRAS (GAI\RGA\SCL) gene family encodes plant-specific transcription factors that play crucial roles in plant growth and development, stress tolerance, and hormone network regulation. Plant dwarfing symptom is mainly regulated by DELLA proteins of the GRAS gene subfamily. In this study, the association between the GRAS gene family and Paulownia witches' broom (PaWB) was investigated. A total of 79 PfGRAS genes were identified using bioinformatics methods and categorized into 11 groups based on amino acid sequences. Tandem duplication and fragment duplication were found to be the main modes of amplification of the PfGRAS gene family. Gene structure analysis showed that more than 72.1% of the PfGRASs had no introns. The genes PfGRAS12/18/58 also contained unique DELLA structural domains; only PfGRAS12, which showed significant response to PaWB phytoplasma infection in stems, showed significant tissue specificity and responded to gibberellin (GA3) in PaWB-infected plants. We found that the internodes were significantly elongated under 100 µmol·L-1 GA3 treatment for 30 days. The subcellular localization analysis indicated that PfGRAS12 is located in the nucleus and cell membrane. Yeast two-hybrid (Y2H) and bimolecular fluorescence complementation (BiFC) assays confirmed that PfGRAS12 interacted with PfJAZ3 in the nucleus. Our results will lay a foundation for further research on the functions of the PfGRAS gene family and for genetic improvement and breeding of PaWB-resistant trees.