Molecular Function Terms Research Articles

Proteomics analysis in myocardium of spontaneously hypertensive rats

Hypertension-related left ventricular hypertrophy is recognized as a good predictor of adverse cardiovascular events. However, the underlying mechanism of left ventricular hypertrophy is still not fully understood. This study employed liquid chromatography coupled with tandem mass spectrometry to investigate global changes in protein profile in myocardium of spontaneously hypertensive rat, a classical animal model of essential hypertension. There were 369 differentially expressed proteins in myocardium between spontaneously hypertensive rats and normotensive rats. Xenobiotic catabolic process, cholesterol binding and mitochondrial proton-transporting ATP synthase were found to be the most significantly enriched biological process, molecular function and cellular component terms of Gene Ontology, respectively. Drug metabolism-cytochrome P450 was revealed to be the most significantly enriched Kyoto Encyclopedia of Genes and Genomes pathways. FYN proto-oncogene, Src family tyrosine kinase was found to have the most interactions with other proteins. Differentially expressed proteins involved in xenobiotic catabolic process, lipid transport and metabolism, mitochondrial function might be targets for further study of hypertension-related left ventricular hypertrophy.

Transcriptome analysis reveals differential transcription in tomato (Solanum lycopersicum) following inoculation with Ralstonia solanacearum

Tomato (Solanum lycopersicum L.) is a major Solanaceae crop worldwide and is vulnerable to bacterial wilt (BW) caused by Ralstonia solanacearum during the production process. BW has become a growing concern that could enormously deplete the tomato yield from 50 to 100% and decrease the quality. Research on the molecular mechanism of tomato regulating BW resistance is still limited. In this study, two tomato inbred lines (Hm 2–2, resistant to BW; and BY 1–2, susceptible to BW) were used to explore the molecular mechanism of tomato in response to R. solanacearum infection by RNA-sequencing (RNA-seq) technology. We identified 1923 differentially expressed genes (DEGs) between Hm 2–2 and BY 1–2 after R. solanacearum inoculation. Among these DEGs, 828 were up-regulated while 1095 were down-regulated in R-3dpi (Hm 2–2 at 3 days post-inoculation with R. solanacearum) vs. R-mock (mock-inoculated Hm 2–2); 1087 and 2187 were up- and down-regulated, respectively, in S-3dpi (BY 1–2 at 3 days post-inoculation with R. solanacearum) vs. S-mock (mock-inoculated BY 1–2). Moreover, Gene Ontology (GO) enrichment analysis revealed that the largest amount of DEGs were annotated with the Biological Process terms, followed by Cellular Component and Molecular Function terms. A total of 114, 124, 85, and 89 regulated (or altered) pathways were identified in R-3dpi vs. R-mock, S-3dpi vs. S-mock, R-mock vs. S-mock, and R-3dpi vs. S-3dpi comparisons, respectively, by Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway analysis. These clarified the molecular function and resistance pathways of DEGs. Furthermore, quantitative RT-PCR (qRT-PCR) analysis confirmed the expression patterns of eight randomly selected DEGs, which suggested that the RNA-seq results were reliable. Subsequently, in order to further verify the reliability of the transcriptome data and the accuracy of qRT-PCR results, WRKY75, one of the eight DEGs was silenced by virus-induced gene silencing (VIGS) and the defense response of plants to R. solanacearum infection was analyzed. In conclusion, the findings of this study provide profound insight into the potential mechanism of tomato in response to R. solanacearum infection, which lays an important foundation for future studies on BW.

HLA variants have different preferences to present proteins with specific molecular functions which are complemented in frequent haplotypes.

Human leukocyte antigen (HLA) genes are the most polymorphic loci in the human genome and code for proteins that play a key role in guiding adaptive immune responses by presenting foreign and self peptides (ligands) to T cells. Each person carries up to 6 HLA class I variants (maternal and paternal copies of HLA-A, HLA-B and HLA-C genes) and also multiple HLA class II variants, which cumulatively define the landscape of peptides presented to T cells. Each HLA variant has its own repertoire of presented peptides with a certain sequence motif which is mainly defined by peptide anchor residues (typically the second and the last positions for HLA class I ligands) forming key interactions with the peptide-binding groove of HLA. In this study, we aimed to characterize HLA binding preferences in terms of molecular functions of presented proteins. To focus on the ligand presentation bias introduced specifically by HLA-peptide interaction we performed large-scale in silico predictions of binding of all peptides from human proteome for a wide range of HLA variants and established which functions are characteristic for proteins that are more or less preferentially presented by different HLA variants using statistical calculations and gene ontology (GO) analysis. We demonstrated marked distinctions between HLA variants in molecular functions of preferentially presented proteins (e.g. some HLA variants preferentially present membrane and receptor proteins, while others - ribosomal and DNA-binding proteins) and reduced presentation of extracellular matrix and collagen proteins by the majority of HLA variants. To explain these observations we demonstrated that HLA preferentially presents proteins enriched in amino acids which are required as anchor residues for the particular HLA variant. Our observations can be extrapolated to explain the protective effect of certain HLA alleles in infectious diseases, and we hypothesize that they can also explain susceptibility to certain autoimmune diseases and cancers. We demonstrate that these differences lead to differential presentation of HIV, influenza virus, SARS-CoV-1 and SARS-CoV-2 proteins by various HLA alleles. Taking into consideration that HLA alleles are inherited in haplotypes, we hypothesized that haplotypes composed of a combination of HLA variants with different presentation preferences should be more advantageous as they allow presenting a larger repertoire of peptides and avoiding holes in immunopeptidome. Indeed, we demonstrated that HLA-A/HLA-B and HLA-A/HLA-C haplotypes which have a high frequency in the human population are comprised of HLA variants that are more distinct in terms of functions of preferentially presented proteins than the control pairs.

Clinical identification of expressed proteins in adrenal medullary hyperplasia detected with hypertension.

Hypertension remains a challenging public health problem worldwide, and adrenal gland-related diseases are one class of the major causes for secondary hypertension. Among them, one relatively rare pattern is adrenal hyperplastic hypertension caused by adrenal medullary hyperplasia (AMH), leading to excessive secretion of autonomic catecholamine. Given that the pathological changes of adrenal medulla are not well correlated to the onset and even severity of secondary hypertension, the molecular basis why some AMH patients are accompanied with hypertension remains unclear and is worth exploring. For this reason, this study aims at investigating differentially expressed proteins in clinical AMH tissue, with special focus on the potential contribution of these differentially expressed proteins to AMH development, in order to have a better understanding of mechanisms how AMH leads to secondary hypertension to some extent. To this end, AMH specimens were successfully obtained and verified through computed tomography (CT) and haematoxylin-eosin (HE) staining. Proteomic analyses of AMH and control tissues revealed 782 kinds of differentially expressed proteins. Compared with the control tissue, there were 357 types of upregulated proteins and 425 types of downregulated proteins detected in AMH tissue. Of interest, these differentially expressed proteins were significantly enriched in 60 gene ontology terms (P < 0.05), including 28 biological process terms, 14 molecular function terms, and 18 cellular component terms. Pathway analysis further indicated that 306 proteins exert their functions in at least one Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway. Western blotting showed enhanced expression of phenylethanolamine N- methyltransferase (PNMT), myelin protein zero (MPZ), and Ras-related protein Rab-3C (RAB3C), and reduced expression of cluster of differentiation 36 (CD36) observed in AMH tissue in comparison with controls. Clinical AMH specimens display a different proteomic profile compared to control tissue. Of note, PNMT, MPZ, RAB3C, and CD36 are found to differentially expressed and can be potential targets for AMH, providing a theoretical basis for mechanistic exploration of AMH along with hypertension.

Unique and Shared Proteome Responses of Rice Plants (Oryza sativa) to Individual Abiotic Stresses.

Food safety of staple crops such as rice is of global concern and is at the top of the policy agenda worldwide. Abiotic stresses are one of the main limitations to optimizing yields for sustainability, food security and food safety. We analyzed proteome changes in Oryza sativa cv. Nipponbare in response to five adverse abiotic treatments, including three levels of drought (mild, moderate, and severe), soil salinization, and non-optimal temperatures. All treatments had modest, negative effects on plant growth, enabling us to identify proteins that were common to all stresses, or unique to one. More than 75% of the total of differentially abundant proteins in response to abiotic stresses were specific to individual stresses, while fewer than 5% of stress-induced proteins were shared across all abiotic constraints. Stress-specific and non-specific stress-responsive proteins identified were categorized in terms of core biological processes, molecular functions, and cellular localization.

Transcriptome profile of the anterior pituitary gland in pigs during maternal recognition of pregnancy

The activity of the pituitary gland determines the success of female reproduction. The knowledge regarding the reproductive-status-related changes in the transcriptome of the porcine pituitary is limited. This study aimed to determine and compare the transcriptome profile of the pituitary gland collected from pigs during maternal recognition of pregnancy, i.e. on days 12–13 of pregnancy and during the respective days of the estrous cycle. Analysis indicated 482 differentially expressed genes (DEGs) with an FC > 1.5 (P < 0.05) in the pituitary of pregnant vs. estrous-cyclic pigs. Among them, 68 were up-regulated and 414 were down-regulated. The evaluated DEGs were annotated into 39 gene ontology (GO) biological process terms, 13 GO cellular component terms, and 10 GO molecular function terms. Among the evaluated DEGs were selected genes coding for proteins potentially involved in the regulation of early pregnancy in pigs and used for gene interaction analysis and validation of microarray results. An analysis of the relationships among DEGs in pituitaries collected during maternal recognition of pregnancy showed that some of them are connected with, for example, TGFβ signaling pathway, PRL synthesis, adipocytokines pathway and immune response during maternal recognition of pregnancy. These findings expand the knowledge regarding the molecular mechanisms appearing in the porcine pituitary during the maternal recognition period of pregnancy.

Differentially Expressed Proteins in Transfusion-Dependent Thalassemia (TDT) and Their Role in Tdt Disease Severity

Introduction: The management of transfusion-dependent thalassemia (TDT) has seen essential improvements; however, still several challenges to controlling the incidence worldwide. Limitations of available current treatment modalities in resource-limited countries are the driving force to investigate the novel diagnostic and therapeutic options for better clinical management of these patients. Proteomics may be a potential technique to identify novel biomarkers of disease severity and understand the pathophysiological mechanisms of TDT, as proven in many other diseases. Understanding the inter-relationships of proteins affected by the disease process, such as oxidative stress in TDT patients, can help to elucidate the mechanisms involved in the disease pathophysiology. However, plasma proteome profile studies in TDT are limited. This study aimed to investigate the differentially expressed proteins (novel proteins) in serum from TDT to understand the pathophysiology of TDT and determine their role in TDT severity by performing quantitative serum proteomics profiling. Methods: The sample size was calculated based on the sensitivity and specificity of the protein biomarkers identified in the pilot study. A total of 64 patients were included in this study. A serum sample was collected from 32 TDT patients and 32 non-thalassemia controls. Before the serum samples could be processed for label-free quantification using the liquid chromatography-mass spectrometry/mass spectrometry (LCMS/MS) approach, high abundance proteins such as serum albumin and immunoglobulins were depleted using Pierce™ Albumin/IgG Removal Kit (Thermo Fisher Scientific, USA.) according to the manufacturer's protocols. The protein content in samples after depletion of high abundance proteins was determined using the Bradford assay using the protocol recommended by the manufacturer protocol (BioRad, USA). Each protein sample was prepared for LC-MS/MS analysis using EasyPep™ Mini MS Sample Prep Kit (Thermo Fisher Scientific, USA). Analysis of sera was performed on the Agilent 6560C ion mobility Q-TOF LC/MS system (Agilent, USA). To validate the LCMS/MS results, ELISA was done. Differentially regulated proteins with p-value <0.05 were identified from the dataset and uploaded to online databases PANTHER to classify and identify the proteins' functions. The functional gene ontology (GO) annotation of the identified protein in terms of molecular function, biological process, and cellular component was evaluated using this curated biological database. The statistically significant expressed proteins were submitted to STRING, and a combined score of >0.4 (medium confidence) was considered experimentally validated and statistically significant interactions between proteins. The cluster with the largest number of proteins with strong connections was identified for the pathway enrichment analysis. The identified protein cluster from the STRING database was uploaded to the KEGG online database to acquire the enriched pathway. Results: 51 dysregulated proteins were found between cases and controls (Table). However, only 13 showed statistically significant differential expression (p <0.05) with a fold change >1, and mostly were downregulated. Gene ontology functional annotation analysis showed these proteins were involved in molecular functions, mainly catalytic activities (37%), followed by molecular function regulation (15%). The biological processes primarily involved the cellular (35.5%) and metabolic processes (32.3%). The pathway analysis showed that these proteins were involved mainly in hemostasis. In KEGG pathway analysis, the proteins were involved primarily in fat digestion and absorption and vitamin digestion & absorption. Conclusion: We elucidated the possible biological processes modulated by oxidative stress using the differentially expressed novel proteins and the associated pathways using comprehensive molecular and biocomputational analysis. Interestingly, most of the differentially expressed proteins in this study have not been yet reported in previous studies to be modulated by oxidative stress in TDT patients. Therefore, the identified dysregulated proteins can serve as a potential biomarker to monitor a patient's condition, determine the effect, need for blood transfusion, and help develop novel prognostic and diagnostic methods. Figure 1View largeDownload PPTFigure 1View largeDownload PPT Close modal

Screening Key lncRNAs of Ankylosing Spondylitis Using Bioinformatics Analysis

Long non-coding RNAs (lncRNAs) are important regulators in ankylosing spondylitis (AS). Few studies have examined the lncRNA-RNA binding protein (RBP) interaction in AS. This study performed bioinformatics analysis and clinical verification to identify key lncRNAs and propose their RBP interaction. Three GEO datasets of AS were analyzed by differential expression analysis. The differentially expressed lncRNAs between the AS and control groups were screened out, and the intersecting lncRNAs were regarded as target lncRNAs. Functional was performed to identify target lncRNAs by enrichment analysis, co-expressed RNA analysis, and lncRNA-RBP interaction analysis. Finally, this study analyzed the differential expression level and clinical value of lncRNAs between the AS and control groups. Linc00304, linc00926, and MIAT were differentially expressed and upregulated. Enrichment analysis indicated that the key KEGG terms were the T-cell receptorsignalingpathway and B-cell receptorsignalingpathway. The key molecular function term was protein binding, and the key biological process term was adaptive immune response. In qRT-PCR results, 44 samples were validated. linc00304 expression was positively correlated with bath ankylosing spondylitis disease activity index (BASDAI), bath ankylosing spondylitis functional index (BASFI), erythrocyte sedimentation rate (ESR), and c-reactive protein (CRP). linc00926 expression was only positively correlated with ESR, whereas MIAT expression was positively correlated with BASFI, ESR, and CRP. Logistic regression revealed that linc00304, ESR, and CRP were the independent risk factors for BASDAI activation. The area under the curve (AUC) of serum linc00304 level in the diagnosis of AS was 0.687 (cutoff value: 0.413, specificity: 0.423, sensitivity: 0.900). AUC of linc00926 was 0.664 (cutoff value: 0.299, sensitivity: 0.882, specificity: 0.417). AUC of MIAT was 0.623 (cutoff value: 0.432, specificity: 0.443, sensitivity: 0.890) (all P <0.05). Overall, this study uncovered three novel lncRNAs, which were upregulated in AS, and proposed a new lncRNA-RBP-mRNA interaction that might regulate adaptive immune response.

Whole Exome Sequencing and In Silico Analysis of Human Sertoli in Patients with Non-Obstructive Azoospermia.

Non-obstructive azoospermia (NOA) is a serious cause of male infertility. The Sertoli cell responds to androgens and takes on roles supporting spermatogenesis, which may cause infertility. This work aims to enhance the genetic diagnosis of NOA via the discovery of new and hub genes implicated in human NOA and to better assess the odds of successful sperm extraction according to the individual’s genotype. Whole exome sequencing (WES) was done on three NOA patients to find key genes involved in NOA. We evaluated genome-wide transcripts (about 50,000 transcripts) by microarray between the Sertoli of non-obstructive azoospermia and normal cells. The microarray analysis of three human cases with different non-obstructive azoospermia revealed that 32 genes were upregulated, and the expressions of 113 genes were downregulated versus the normal case. For this purpose, Enrich Shiny GO, STRING, and Cytoscape online evaluations were applied to predict the functional and molecular interactions of proteins and then recognize the master pathways. The functional enrichment analysis demonstrated that the biological process (BP) terms “inositol lipid-mediated signaling”, “positive regulation of transcription by RNA polymerase II”, and “positive regulation of DNA-templated transcription” significantly changed in upregulated differentially expressed genes (DEGs). The BP investigation of downregulated DEGs highlighted “mitotic cytokinesis”, “regulation of protein-containing complex assembly”, “cytoskeleton-dependent cytokinesis”, and the “peptide metabolic process”. Overrepresented molecular function (MF) terms in upregulated DEGs included “ubiquitin-specific protease binding”, “protease binding”, “phosphatidylinositol trisphosphate phosphatase activity”, and “clathrin light chain binding”. Interestingly, the MF analysis of the downregulated DEGs revealed overexpression in “ATPase inhibitor activity”, “glutathione transferase activity”, and “ATPase regulator activity”. Our findings suggest that these genes and their interacting hub proteins could help determine the pathophysiologies of germ cell abnormalities and infertility.

A novel candidate disease gene prioritization method using deep graph convolutional networks and semi-supervised learning

BackgroundSelecting and prioritizing candidate disease genes is necessary before conducting laboratory studies as identifying disease genes from a large number of candidate genes using laboratory methods, is a very costly and time-consuming task. There are many machine learning-based gene prioritization methods. These methods differ in various aspects including the feature vectors of genes, the used datasets with different structures, and the learning model. Creating a suitable feature vector for genes and an appropriate learning model on a variety of data with different and non-Euclidean structures, including graphs, as well as the lack of negative data are very important challenges of these methods. The use of graph neural networks has recently emerged in machine learning and other related fields, and they have demonstrated superior performance for a broad range of problems.MethodsIn this study, a new semi-supervised learning method based on graph convolutional networks is presented using the novel constructing feature vector for each gene. In the proposed method, first, we construct three feature vectors for each gene using terms from the Gene Ontology (GO) database. Then, we train a graph convolution network on these vectors using protein–protein interaction (PPI) network data to identify disease candidate genes. Our model discovers hidden layer representations encoding in both local graph structure as well as features of nodes. This method is characterized by the simultaneous consideration of topological information of the biological network (e.g., PPI) and other sources of evidence. Finally, a validation has been done to demonstrate the efficiency of our method.ResultsSeveral experiments are performed on 16 diseases to evaluate the proposed method's performance. The experiments demonstrate that our proposed method achieves the best results, in terms of precision, the area under the ROC curve (AUCs), and F1-score values, when compared with eight state-of-the-art network and machine learning-based disease gene prioritization methods.ConclusionThis study shows that the proposed semi-supervised learning method appropriately classifies and ranks candidate disease genes using a graph convolutional network and an innovative method to create three feature vectors for genes based on the molecular function, cellular component, and biological process terms from GO data.

Microarray and in silico analysis of DNA repair genes between human testis of patients with nonobstructive azoospermia and normal cells.

DNA repair processes are critical to maintaining genomic integrity. As a result, dysregulation of repair genes is likely to be linked with health implications, such as an increased prevalence of infertility and an accelerated rate of aging. We evaluated all the DNA repair genes (322 genes) by microarray. This study has provided insight into the connection between DNA repair genes, including RAD23B, OBFC2A, PMS1, UBE2V1, ERCC5, SMUG1, RFC4, PMS2L5, MMS19, SHFM1, INO80, PMS2L1, CHEK2, TRIP13, and POLD4. The microarray analysis of six human cases with different nonobstructive azoospermia revealed that RAD23B, OBFC2A, PMS1, UBE2V1, ERCC5, SMUG1, RFC4, PMS2L5, MMS19, SHFM1, and INO80 were upregulated, and expression of PMS2L1, CHEK2, TRIP13, and POLD4 was downregulated versus the normal case. For this purpose, Enrich Shiny GO, STRING, and Cytoscape online evaluation was applied to predict proteins' functional and molecular interactions and then performed to recognize the master pathways. Functional enrichment analysis revealed that the biological process (BP) terms "base-excision repair, AP site formation,""nucleotide-excision repair, DNA gap filling," and "nucleotide-excision repair, preincision complex assembly" was significantly overexpressed in upregulated differentially expressed genes (DEGs). BP analysis of downregulated DEGs highlighted "histone phosphorylation,""DNA damage response, detection DNA response,""mitotic cell cycle checkpoint signaling,"and "double-strand break repair."Overrepresented molecular function (MF) terms in upregulated DEGs included "Oxidized base lesion DNA N-glycosylase activity,""uracil DNA N-glycosylase activity,""bubble DNA binding" and "DNA clamp loader activity."Interestingly, MF investigation of downregulated DEGs showed overexpression in "heterotrimeric G-protein complex,""5'-deoxyribose-5-phosphate lyase activity,""minor groove of adenine-thymine-rich DNA binding," and "histone kinase activity."Our findings suggest that these genes and their interacting hub proteins could help determine the pathophysiology of germ cell abnormalities and infertility.

KIAA0101 and IL2RA Were Identified as Core Genes in Hormone-Resistant Nephropathy.

Objectives To analyze the tissue heterogeneity of hormone-sensitive and drug-resistant nephrotic syndrome genes using a bioinformatics approach and to analyze gene-related functional pathways. Methods The limma package of R software was used to screen differential genes from the nephropathy datasets GSE145969 and GSE189734. The differential genes were analyzed for functional and pathway enrichment in terms of biological processes, cellular components, and molecular functions. The Metascape tool was used to construct protein networks for the differential genes, and the results were imported into Cytoscape software for visualization. The genes were identified as key modules and genes using the MCODE plug-in. Gene set enrichment analysis was performed for the HALLMARK analysis of the two microarray key genes to obtain the relevant pathways. Results GSE145969 screened 351 differential genes, 168 upregulated genes, and 183 downregulated genes. The differential genes were enriched in biological processes, cellular components, and molecular functions, such as myocardial contraction, intracellular nonmembrane organelles, and structural molecular activities. The protein-protein interaction (PPI) network contained 140 nodes, with the highest-scoring module containing seven genes, and the MCODE plug-in calculated the downseed. The key gene was KIAA0101, whose HALLMARK pathway was significantly enriched in the mTORC1 signaling pathway. A total of 263 differential genes were screened by GSE189734, and they were enriched in biological processes, molecular functions, and cellular components, such as immune system processes, signaling receptor binding, and the cytoplasmic matrix. The PPI network contained 253 nodes, with the highest-scoring module containing 37 genes. The seed gene obtained through the MCODE plug-in calculation was IL2RA, whose HALLMARK pathway was significantly enriched in the KRAS signaling pathway. Conclusion By analyzing the gene sets of different tissues in nephropathy, two key genes, namely KIAA0101 and IL2RA, were obtained. Their gene function enrichment is related to cell growth, development, and reproduction. Therefore, IL2RA and KIAA0101 can be used as diagnostic markers for hormone-resistant nephropathy.

Bioinformatic Data Mining for Candidate Drugs Affecting Risk of Bisphosphonate-Related Osteonecrosis of the Jaw (BRONJ) in Cancer Patients.

Background Bisphosphonate-related osteonecrosis of the jaw (BRONJ) leads to significant morbidity. Other coadministered drugs may modulate the risk for BRONJ. The present study aimed to leverage bioinformatic data mining to identify drugs that potentially modulate the risk of BRONJ in cancer. Methods A GEO gene expression dataset of peripheral blood mononuclear cells related to BRONJ in multiple myeloma patients was downloaded, and differentially expressed genes (DEGs) in patients with BRONJ versus those without BRONJ were identified. A protein-protein interaction network of the DEGs was constructed using experimentally validated interactions in the STRING database. Overrepresented Gene Ontology (GO) molecular function terms and KEGG pathways in the network were analysed. Network topology was determined, and ‘hub genes' with degree ≥2 in the network were identified. Known drug targets of the hub genes were mined from the ‘drug gene interaction database' (DGIdb) and labelled as candidate drugs affecting the risk of BRONJ. Results 751 annotated DEGs (log FC ≥ 1.5, p < 0.05) were obtained from the microarray gene expression dataset GSE7116. A PPI network with 633 nodes and 168 edges was constructed. Data mining for drugs interacting with 49 gene nodes was performed. 37 drug interactions were found for 9 of the hub genes including TBP, TAF1, PPP2CA, PRPF31, CASP8, UQCRB, ACTR2, CFLAR, and FAS. Interactions were found for several established and novel anticancer chemotherapeutic, kinase inhibitor, caspase inhibitor, antiangiogenic, and immunomodulatory agents. Aspirin, metformin, atrovastatin, thrombin, androgen and antiandrogen drugs, progesterone, Vitamin D, and Ginsengoside 20(S)-Protopanaxadiol were also documented. Conclusions A bioinformatic data mining strategy identified several anticancer, immunomodulator, and other candidate drugs that may affect the risk of BRONJ in cancer patients.

Mechanism of Zhinao Capsule in Treating Alzheimer's Disease Based on Network Pharmacology Analysis and Molecular Docking Validation.

Objective This study aimed to determine the active components of Zhinao capsule (ZNC) and the targets in treating Alzheimer's disease (AD) so as to investigate and explore the mechanism of ZNC for AD. Methods The active components and targets of ZNC were determined from the traditional Chinese medicine systems pharmacology database (TCMSP). The target genes of AD were searched for in GeneCards. Cytoscape was used to construct an herb-component-target-disease network. A protein-protein interaction (PPI) network was constructed by STRING. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed using the OmicShare. UCSF Chimera and SwissDock were used for molecular docking verification. Finally, four key target genes were validated by Western blotting. Results In total, 55 active components, 287 targets of active components, 1197 disease genes, and 134 common genes were screened, which were significantly enriched in 3975 terms of biological processes (BP), 284 terms of cellular components (CC), 433 terms of molecular functions (MF), and 245 signaling pathways. Caspase-3 (CASP3) and beta-sitosterol, tumor necrosis factor-alpha (TNF-α) and quercetin, vascular endothelial growth factor A (VEGFA) and baicalein, and mitogen-activated protein kinase 1 (MAPK1) and quercetin showed good-to-better docking. Moreover, ZNC not only downregulated CASP3 and TNF-α protein expression but also upregulated the protein expression of VEGFA and MAPK1. Conclusions The active components of ZNC, such as beta-sitosterol, quercetin, and baicalein may act on multiple targets like CASP3, VEGFA, MAPK1, and TNF-α to affect T cell receptor (TCR), TNF, and MAPK signaling pathway, thereby achieving the treatment of AD. This study provides a scientific basis for further exploring the potential mechanism of ZNC in the treatment of AD and a reference for its clinical application.

Identification of differentially expressed genes and pathways in diquat and paraquat poisoning using bioinformatics analysis

Objective: In this study, differentially expressed genes (DEGs) and signaling pathways involved in diquat (DQ) and paraquat (PQ) poisoning were identified via bioinformatics analysis, in order to inform the development of novel clinical treatments. Methods: Raw data from GSE153959 were downloaded from the Gene Expression Omnibus database. DEGs of the DQ vs. control (CON) and PQ vs. CON comparison groups were identified using R, and DEGs shared by the two groups were identified using TBtools. Subsequently, the shared DEGs were searched in the Gene Ontology and Kyoto Encyclopedia of Genes and Genomes (KEGG) databases, using the Database for Annotation, Visualization, and Integrated Discovery. A protein–protein interaction (PPI) network was constructed, and hub genes were identified using the cytoHubba plug-in in Cytoscape software. Finally, circos and contrast plots showing the DEGs shared between mouse and human chromosomes were constructed using TBtools. Results: Thirty-one DEGs shared by the DQ and PQ groups were identified. Enriched biological process terms included positive regulation of cell proliferation and translation. Enriched cellular component terms included extracellular region, intracellular membrane-bounded organelle and mitochondrion. Enriched molecular function terms included transcription factor activity and sequence-specific double-stranded DNA binding. Enriched KEGG pathways included the interleukin-17 signaling pathway, tumor necrosis factor signaling pathway, and human T-cell leukemia virus 1 infection. The top 10 hub genes in the PPI network were prostaglandin-endoperoxide synthase 2 (Ptgs2), chemokine (C-X-C motif) ligand 2 (Cxcl2), colony-stimulating factor 2 (granulocyte-macrophage) (Csf2), matrix metallopeptidase 13 (Mmp13), amphiregulin (Areg), plasminogen activator, urokinase receptor (Plaur), fos-like antigen 1 (Fosl1), epiregulin (Ereg), activating transcription factor 3 (Atf3), and transferrin receptor (Tfrc). Cxcl2, Csf2, and Atf3 played important roles in the mitogen-activated protein kinase (MAPK) signaling pathway. Conclusions: These pathways and DEGs may serve as targets for gene therapy.

Curcumin Prevents the Glycation of Tricarboxylic Acid Cycle and Cell Respiration Proteins in the Heart of Mice Fed with a High-fructose Diet.

A high fructose diet (HFD) induces protein glycation. The latter is related to a higher risk of cardiovascular disease. Curcumin is a natural pleiotropic compound that may possess antiglycant properties. The study aims to analyze the effect of curcumin on the content of glycated proteins in the hearts of 6-week-old mice fed with a HFD for 15 weeks. Mice were allocated into four groups (n = 6/group): a control group that received a standard diet (CT); a group that received 30% w/v fructose in water (F); a group that received 0.75% w/w curcumin supplemented in food (C); a group that received 30% w/v fructose in water and 0.75% w/w curcumin supplemented in food (F+C). The content of glycated proteins in the heart was determined by Western Blot (whereas the spots were detected by 2D-PAGE) using anti-AGE and anti-CML antibodies. Densitometric analysis was performed using the ImageLab software. Glycated proteins were identified by MALDI-TOF-MS, and an ontological analysis was performed in terms of biological processes and molecular function based on the STRING and DAVID databases. Fourteen glycated protein spots were detected, two of them with anti-AGE and the other 12 with anti- CML. In total, eleven glycated proteins were identified, out of which three had decreased glycation levels due to curcumin exposure. The identified proteins participate in processes such as cellular respiration, oxidative phosphorylation, lipid metabolism, carbohydrate metabolism, the tricarboxylic acid cycle (TAC), and the organization of intermediate filaments. Curcumin decreased the fructose-induced glycation level of the ACO2, NDUFS7, and DLAT proteins.

Identification of miR160 family and their target genes in Rehmannia glutinosa in response to endophytic fungus GG22 infection

This study aims to reveal the possible role of miR160 family in Rehmannia glutinosa in response to the infection of endophytic fungus Fusarium oxysporum GG22. Specifically, miR160 precursors and mature miR160 were retrieved from the small RNA database yielded by high-throughput sequencing. RNAfold was used to analyze the precursor structure, and DNAMAN and MEGA to analyze conservation and evolution of miR160 precursors and mature miR160. The target genes of miR160 were predicted and annotated, and the interaction was analyzed. Based on degradome sequencing, the target genes were further identified. The results showed that miR160 precursors had intact stem-loop structures. The precursor and mature sequences were conserved, particularly the 3 rd-16 th bases of the 5'-terminal. According to the phylogenetic tree, R. glutinosa had close evolutionary relationship with Arabidopsis thaliana, Oryza sativa, Salvia miltiorrhiza, and Sesamum indicum. A total of 22 target genes of miR160 were predicted and most of them were auxin response factor(ARF) genes. The target genes were involved in the Gene Ontology(GO) terms of biological processes, cellular components, and molecular functions. According to the degradome sequencing results, four target genes of miR160 were ARF(ARF18, ARF22) genes. R. glutinosa regulated its growth in response to the infection of endophytic fungus by changing the expression of miR160 and the target genes. qRT-PCR result of the differentially expressed rgl-miR160a and rgl-miR160a-3p was consistent with the sequencing result. This study clarifies the molecular mechanism of R. glutinosa in response to GG22 stress, laying a theoretical basis for the improvement and future research of R. glutinosa.

Identification of potential genes in endobronchial tuberculosis after bronchoscopic cryotherapy by transcriptome sequencing.

Bronchoscopic cryotherapy facilitates the treatment of endobronchial tuberculosis (EBTB) and helps suppress progressive bronchial stenosis. However, the molecular mechanism of bronchoscopic cryotherapy in EBTB patients has not been reported. Transcriptome sequencing was performed to explore differentially expressed mRNAs (DEGs) in EBTB patients before and after bronchoscopic cryotherapy. Gene Ontology (GO) and KEGG analyses were carried out. Five genes (MKLN1, HIGD1A, PTGES, SKIL, and MCEMP1) were selected and validated using real-time qPCR (RT- qPCR). In transcriptome analysis, 448 DEGs with p<0.05 and|logFC|>1 were identified; of these, 171 and 277 DEGs were significantly up- and down-regulated after bronchoscopic cryotherapy, respectively. Results displayed 337 biological process (GO-BP), 48 cellular component (GO-CC) and 62 molecular function (GO-MF) terms and 20 KEGG pathways. RT- qPCR results were consistent with the sequencing data. These data provide informative evidence and recommendations for further scientific research on bronchoscopic cryotherapy for EBTB.

Screening the Potential Biomarkers of COVID-19-Related Thrombosis Through Bioinformatics Analysis.

A high proportion of critically ill patients with coronavirus disease 2019 (COVID-19) experience thrombosis, and there is a strong correlation between anticoagulant therapy and the COVID-19 survival rate, indicating that common COVID-19 and thrombosis targets have potential therapeutic value for severe COVID-19.Gene expression profiling data were downloaded from Gene Expression Omnibus (GEO), and common differentially expressed genes (co-DEGs) were identified. The potential biological functions of these co-DEGs were explored by functional enrichment analysis, and protein–protein interaction (PPI) networks were constructed to elucidate the molecular mechanisms of the co-DEGs. Finally, hub genes in the co-DEG network were identified, and correlation analysis was performed.We identified 8320 upregulated genes and 7651 downregulated genes from blood samples of COVID-19 patients and 368 upregulated genes and 240 downregulated genes from blood samples of thrombosis patients. The enriched cellular component terms were mainly related to cytosolic ribosomes and ribosomal subunits. The enriched molecular function terms were mainly related to structural constituents of ribosomes and electron transfer activity. Construction of the PPI network and identification of hub genes ultimately confirmed that RPS7, IGF1R, DICER1, ERH, MCTS1, and TNPO1 were jointly upregulated hub genes, and FLNA and PXN were jointly downregulated hub genes.The identification of novel potential biomarkers provides new options for treating COVID-19-related thrombosis and reducing the rate of severe COVID-19.

Investigation on the differentially expressed circular RNAs in myocardium of mice with diabetic cardiomyopathy

Objective: To identify the differentially expressed circular RNA (circRNA) in the myocardium of diabetic cardiomyopathy (DCM) mice, and analyze their possible biological functions and related regulatory network. Methods: C57BL/6 mice, aged 8 weeks, and weighing were 21-27 g. Eight mice were selected as the control group and 15 mice were selected as the experimental group. The diabetic mice model was established by intraperitoneal injection of streptozotocin in the experimental group. One week after injection, the fasting blood glucose level of mice was measured, and 12 diabetic mice were included in the final experimental group. All mice were fed for 12 weeks under the same laboratory conditions. The cardiac structure and function were detected by echocardiography. Diabetic mice with the left ventricular ejection fraction less than 60% and the E/A less than 1.6 were selected as DCM group (n=3). Mice in DCM group and control group were then sacrificed under deep anesthesia. RNA was extracted from myocardial tissue. High-throughput RNA sequencing technology was used to sequence and identify the RNA in the myocardial tissue of DCM group and normal control group, and the difference was analyzed by DeSeq2. The analysis results were verified at the tissue level by RT-qPCR, and the differential circRNA were analyzed by GO and KEGG pathway analysis. The differentially expressed circRNA-microRNA(miRNA) interaction was predicted by the miRNA target gene prediction software. Results: A total of 63 differentially expressed circRNAs were found in the myocardium of DCM mice. The results of RT-qPCR showed that the tissue level expression of 8 differentially expressed circRNAs was consistent with the sequencing results, of which 7 were up-regulated and 1 was down-regulated. KEGG pathway analysis showed that the up-regulated circRNAs was mainly related to AMPK signal pathway and intercellular adhesion junction pathway, and the down-regulated circRNA was mainly related to cardiomyopathy. Go analysis showed that the up-regulated circRNA was mainly related to the binding process of ions, proteins, kinases and other factors in terms of molecular function, and was involved in regulating the intracellular structure, especially the composition of organelles in terms of cell components. The functional analysis of molecular function and cell components showed that the up-regulated circRNA were related to the cell component origin, recruitment and tissue, and thus participated in the regulation of cell biological process. The down regulated circRNA was related to catalytic activity in terms of molecular function, protein kinase binding process, transferase and calmodulin activity, and was closely related to the components of contractile fibers and the composition of myofibrils. These differentially expressed circRNAs were also related to biological processes such as lysine peptide modification, sarcomere composition, myofibril assembly, morphological development of myocardial tissue, myocardial hypertrophy and so on. Conclusions: In this study, we detected the novel differentially expressed circRNAs in the myocardium of DCM mice, and bioinformatics analysis confirmed that these circRNAs are related to oxidative stress, fibrosis and death of cardiomyocytes, and finally participate in the pathophysiological process of DCM.