Search Tool For The Retrieval Of Interacting Genes/Proteins Research Articles

Pathway mapping reveals antiretroviral treatments' targeted cell cycle regulation in lung cancer

Abstract The human cell cycle is a tightly regulated process with checkpoints in place to ensure genomic integrity. Cyclin/cyclin dependent kinases (CDKs) complexes drive the progression of the cell cycle while CDK-inhibitors (CDKIs) halt the cell cycle. Deregulation of the cell cycle is a hallmark of lung cancer. TP53 and FOXO transcription factors share similar mechanisms in the regulation of the cell cycle. Lung carcinogenesis in the antiretroviral (ARV) era remains to be understood. This study aimed at mapping the biological pathways related to the human cell cycle that are influenced by the ARVs (Efavirenz-EFV and Lopinavir/ritonavir-LPV/r) treatment in A549 and MRC-5 lung cells. For this purpose, Reactome database was used to map these pathways. In addition, the Database for Annotation, Visualisation and Integrated Discovery (DAVID) was used for functional enrichment analysis in a set of genes and to visualise differentially expressed genes within a particular KEGG pathway, and also to perform Gene Ontology. Furthermore, the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database was used to determine the protein-protein interaction of the differentially expressed gene (DEG) targets. Reactome analysis revealed a decrease in DNA replication and an increase in response to external stimuli and DNA repair genes in both normal and adenocarcinoma lung cancer models. A further increase in apoptotic genes is observed in the cancer cells in response to ARV treatment. Interestingly, the FOXO pathway was also shown to be upregulated in the test (ARV) groups. KEGG pathway shows a reduction in cyclin/CDK activity in ARV treated models. STRING analysis illustrates a direct and strong interaction between DNA damage and response (DDR) genes upregulated by ARV exposure. Analysis from all three databases suggests the cytotoxic and anti-proliferative effects of EFV and LPV/r on lung cancer.

Study of the Gastrointestinal Heat Retention Syndrome in Children: From Diagnostic Model to Biological Basis

Gastrointestinal heat retention syndrome (GHRS) refers to a condition that is associated with increased gastrointestinal heat caused by a metabolic block in energy. It is common in children and is closely related to the occurrence and development of recurrent respiratory tract infection, pneumonia, recurrent functional abdominal pain, etc. However, there are no standardized diagnostic criteria to differentiate the GHRS. Therefore, this study is aimed to establish a diagnostic model for children's GHRS and explore the possible biological basis by using systems biology to achieve. Furthermore, Delphi method and the clinical data of Lasso analysis were used to screen out the core symptoms. Nineteen core symptoms of GHRS in children were screened including digestive symptoms such as dry stool, poor appetite, vomiting, and some nervous system symptoms such as night restlessness and irritability. Based on the core symptoms, a GHRS diagnosis model was established using the eXtreme Gradient Boosting (XGBoost) method, and the accuracy of internal verification reached 93.03%. Relevant targets of the core symptoms in the Human Phenotype Ontology (HPO) were retrieved, and target interactions were linked through the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database, and core targets were selected after topological analysis using Cytoscape. Relevant biological processes and pathways were analyzed by applying the DAVID and KEGG databases. The enriched biological processes focused on the cell proliferation, differentiation, apoptosis, and mitochondrial metabolism, which were mainly associated with PI3K-AKT, MAPK network pathways, and the Wnt signaling pathway. In conclusion, we established a diagnosis model of GHRS in children based on the core symptoms and provided an objective standard for its clinical diagnosis. And, the Wnt signaling pathway and the estrogen receptor-activated PI3K-AKT and MAPK network pathways may play important roles in the GHRS processing.

Application of Network Pharmacology to Explore the Mechanism of Yi Xin Tai Formula in Treating Heart Failure

ObjectiveTo explore the possible mechanism of Yi Xin Tai Formula (YXTF) in treating heart failure (HF) by network pharmacology method and to verify the related targets by western blotting. MethodsUsing the traditional Chinese medicine systems pharmacology (TCMSP) database with its analysis platform for HF as a disease model, the active ingredients of YXTF were filtered according to the oral bioavailability (OB) and drug- likeness (DL), and the corresponding targets were predicted. The disease targets of HF were retrieved by Human Phenotype Ontology (HPO) database. Then, “YXTF compounds - Targets - HF” network was constructed in the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database, the network visualized through the Cytoscape software, and the key nodes of the network achieved according to Degree (D), Closeness Centrality (CC), and Betweenness Centrality (BC). Kyoto Encyclopedia of Genes and Genomes (KEGG) gene function enrichment analysis was carried out for the key nodes with the help of GATHER database platform. The rabbit model of HF was established by coarctation of the abdominal aorta and perfusion of propylthiouracil (PTU). The pathological changes and protein expression of transforming growth factor beta (TGF-β) protein were observed by western blotting. Results“YXTF compounds - Targets - HF” network consisted of 403 nodes, 136 key nodes and 10 related KEGG pathways that included focal adhesions, cell cycles, mitogen-activated protein kinase (MAPK) signaling pathways, Toll-like receptor signaling pathways, Cytokine-cytokine receptor interactions, Gap junctions, adherens junctions, TGF-β signaling pathways, apoptosis and Wnt signaling pathways, respectively. The expression of TGF-β protein in myocardium decreased significantly. ConclusionsAccording to the network pharmacology, the treatment of YXTF for HF might be related to 10 metabolic pathways. The effects of the multicompound-multitarget-multi pathways and the synergistic effect drawn from the compounds that act as the monarch, minister, adjuvant, guide medicines were revealed through this study.

Proteome analysis of Mycoplasma fermentans cultured under aerobic and anaerobic conditions

Background and aimsMycoplasmas are ubiquitous pathogens found not only in humans but also in animals, plants, insects and soil. Though they usually grow better in an aerobic environment, mycoplasmas are also facultative anaerobic microorganisms. Following infection, the transition of a microorganism from a normal environment into an anaerobic one (e.g. dead or dying tissue) may result in production of a higher number of bacterial toxins. The resolution of the bacterial proteome during the aerobic/anaerobic switch could thus allow the identification of potential pathogenic determinants and pathways.MethodsWe used two-dimensional gel electrophoresis (2-DE) coupled with matrix-assisted laser desorption/ionization time-of-flight/tandem mass spectroscopy (MALDI-TOF MS/MS) and subsequent mass spectrometric analysis to characterize the liposoluble and hydrosoluble protein fractions of a strain of Mycoplasma fermentans isolated in our lab (MFI), that was cultured under either aerobic or anaerobic conditions.ResultsWe identified the 27 most abundant proteins in the liposoluble fraction and the 30 most abundant proteins in the hydrosoluble fraction and determined their modulation under aerobic and anaerobic growth. By using Protein ANalysis TrougH Evolutionary Relationships (PANTHER) and the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) software analysis tools, we were able to identify, define and organize the function of each protein, as well as to determine the specific interactome.ConclusionsOur work provides the first proteome reference map of Mycoplasma fermentans obtained under aerobic and anaerobic growing conditions. These data may help to better understand the mechanisms of pathogenicity of this microorganism and define new diagnostic targets.

Detection of Prostate Cancer Related Genes using Modified Ford-Fulkerson Algorithm in Protein-to-Protein Interaction Network

Prostate cancer is a malignancy cancer that affects prostate epithelial cells. Presently, prostate cancer is the second leading cause of cancer-related death in men. In this research, a new computational system was proposed for determining the prostate cancer related genes with the shortest path methodology in a Protein to Protein Interaction (PPI) network. Here, a weighted PPI network was constructed on the basis of PPI data from Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database. Totally, eighteen prostate related genes were extracted from the STRING database by using Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway. Then, the shortest path between eighteen genes was identified using modified Ford-Fulkerson algorithm. Generally, the conventional Ford-Fulkerson algorithm was very effective in detecting the shortest path between the prostate cancer-related genes, but the elapsed time was high when the PPI network has more number of genes. In order to reduce the elapsed time, the modified Ford Fulkerson algorithm was developed by eliminating the invalid path in gene connection. In the experimental section, the proposed shortest path approach reduced the elapsed time up to 0.025-0.002 seconds compared to the existing shortest path methodologies.

Comprehensive analysis of an lncRNA-miRNA-mRNA competing endogenous RNA network in pulpitis.

BackgroundPulpitis is a common inflammatory disease that affects dental pulp. It is important to understand the molecular signals of inflammation and repair associated with this process. Increasing evidence has revealed that long noncoding RNAs (lncRNAs), via competitively sponging microRNAs (miRNAs), can act as competing endogenous RNAs (ceRNAs) to regulate inflammation and reparative responses. The aim of this study was to elucidate the potential roles of lncRNA, miRNA and messenger RNA (mRNA) ceRNA networks in pulpitis tissues compared to normal control tissues.MethodsThe oligo and limma packages were used to identify differentially expressed lncRNAs and mRNAs (DElncRNAs and DEmRNAs, respectively) based on expression profiles in two datasets, GSE92681 and GSE77459, from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were further analyzed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. Protein–protein interaction (PPI) networks and modules were established to screen hub genes using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) and the Molecular Complex Detection (MCODE) plugin for Cytoscape, respectively. Furthermore, an lncRNA-miRNA-mRNA-hub genes regulatory network was constructed to investigate mechanisms related to the progression and prognosis of pulpitis. Then, quantitative real-time polymerase chain reaction (qRT-PCR) was applied to verify critical lncRNAs that may significantly affect the pathogenesis in inflamed and normal human dental pulp.ResultsA total of 644 upregulated and 264 downregulated differentially expressed genes (DEGs) in pulpitis samples were identified from the GSE77459 dataset, while 8 up- and 19 downregulated probes associated with lncRNA were identified from the GSE92681 dataset. Protein–protein interaction (PPI) based on STRING analysis revealed a network of DEGs containing 4,929 edges and 623 nodes. Upon combined analysis of the constructed PPI network and the MCODE results, 10 hub genes, including IL6, IL8, PTPRC, IL1B, TLR2, ITGAM, CCL2, PIK3CG, ICAM1, and PIK3CD, were detected in the network. Next, a ceRNA regulatory relationship consisting of one lncRNA (PVT1), one miRNA (hsa-miR-455-5p) and two mRNAs (SOCS3 and PLXNC1) was established. Then, we constructed the network in which the regulatory relationship between ceRNA and hub genes was summarized. Finally, our qRT-PCR results confirmed significantly higher levels of PVT1 transcript in inflamed pulp than in normal pulp tissues (p = 0.03).ConclusionOur study identified a novel lncRNA-mediated ceRNA regulatory mechanisms in the pathogenesis of pulpitis.

Identification of differentially expressed genes between triple and non-triple-negative breast cancer using bioinformatics analysis.

Triple-negative breast cancer (TNBC), defined by lack of expression of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2), is characterized by early recurrence of disease and poor survival. Here, we sought to identify genes associated with TNBC that could provide new insight into gene dysregulation in TNBC and, at the same time, provide additional potential therapeutic targets for breast cancer treatment. Gene expression profiles from accession series GSE76275 were downloaded from the Gene Expression Omnibus database (GEO). The Cancer Genome Atlas (TCGA) was used to validate potential hub genes in the TCGA database. Protein-protein interaction (PPI) networks were identified using STRING (Search Tool for the Retrieval of Interacting Genes/Proteins). Finally, overall survival (OS) and relapse-free survival (RFS) analysis of hub genes was performed using a Kaplan-Meier plotter online tool. A total of 750 genes were identified after analysis of GSE76275. After validation with the TCGA database, a total of 155 differentially expressed genes (DEGs) were consistent with those identified by GSE76275. Based on the STRING database, we constructed a PPI network using the DEGs obtained from GSE76275 datasets. Furthermore, in the prognostic analysis of the 155 DEGs, we found that there were 10 genes associated with OS and 33 genes associated with RFS. Combined with the degree scores from the PPI network, a total of ten genes with the highest degree scores were selected as hub genes pertaining to TNBC. Our research provides new insight into the subnetwork of biomarkers connected with TNBC, which could be useful for prognostication and risk stratification of TNBC patients.

Identification and analysis of genes associated with papillary thyroid carcinoma by bioinformatics methods.

The molecular mechanism of the occurrence and development of papillary thyroid carcinoma (PTC) has been widely explored, but has not been completely elucidated. The present study aimed to identify and analyze genes associated with PTC by bioinformatics methods. Two independent datasets were downloaded from Gene Expression Omnibus (GEO) database. The differentially expressed genes (DEGs) between PTC tissues and matched non-cancerous tissues were identified using GEO2R tool. The common DEGs in the two datasets were screened out by VennDiagram package, and analyzed by the following tools: KOBAS, Database for Annotation, Visualization, and Integrated Discovery (DAVID), Search tool for the retrieval of interacting genes/proteins (STRING), UALCAN and Gene expression profiling interactive analysis (GEPIA). A total of 513 common DEGs, including 259 common up-regulated and 254 common down-regulated genes in PTC, were screened out. These common up-regulated and down-regulated DEGs were most significantly enriched in cytokine–cytokine receptor interaction and metabolic pathways, respectively. Protein–protein interactions (PPI) network analysis showed that the up-regulated genes: FN1, SDC4, NMU, LPAR5 and the down-regulated genes: BCL2 and CXCL12 were key genes. Survival analysis indicated that the high expression of FN1 and NMU genes significantly decreased disease-free survival of patients with thyroid carcinoma. In conclusion, the genes and pathways identified in the current study will not only contribute to elucidating the pathogenesis of PTC, but also provide prognostic markers and therapeutic targets for PTC.

Analysis on mechanisms and medication rules of herbal prescriptions for nonalcoholic fatty liver disease based on methods of data mining and biological information

To explore the medication rules of herbal prescriptions for nonalcoholic fatty liver disease,and analyze the possible drug targets and interactions,in order to explore the mechanisms of the herbs. Randomized controlled trials of herbal prescriptions for treating nonalcoholic fatty liver disease were collected from CNKI,Wan Fang,VIP,Sino Med and PubMed databases. The properties,flavors and meridian tropism of herbs were analyzed by using systematic cluster analysis method with SPSS 19. 0 software. Subsequently,the association rules of herbs were analyzed by using Clementine 12. 0 software. Finally,the interactions between targets and relevant signaling pathways were analyzed by Traditional Chinese Medicine Systems Pharmacology Database(TCMSP),Search Tool for the Retrieval of Interacting Genes/Proteins(STRING) and Kyoto Encyclopedia of Genes and Genomes(KEGG). In the 88 prescriptions screened out,the commonly used herbs were Salvia miltiorrhiza,Bupleurum chinense,Alisma orientale,and Crataegus pinnatifida,and the potential signaling pathways were PPAR signaling pathway and calcium signaling pathway. The results showed that the main effects of herbal prescriptions were to improve blood flow/clear blood stasis,clear heatiness/dampness,promote digestion and strengthen spleen. And its mechanism of action may be achieved through the regulation of PPAR signaling pathway and calcium signaling pathway.

Genome-scale integrated analysis to identify prospective molecular mechanisms and therapeutic targets in isocitrate dehydrogenase 2 R140Q-mutated acute myeloid leukemia.

The aim of the present study was to identify potential molecular mechanisms and therapeutic targets in regards to isocitrate dehydrogenase 2 (IDH2) R140Q-mutated acute myeloid leukemia (AML). An RNA sequencing dataset of IDH2 wild-type and R140Q-mutated adult de novo AML bone marrow samples was obtained from The Cancer Genome Atlas (TCGA) database. The edgeR package was used to screen for the differentially expressed genes (DEGs), and the potential molecular mechanisms and therapeutic targets were identified using Database for Annotation, Visualization, and Integrated Discovery (DAVID) v6.8, Biological Networks Gene Ontology tool, Connectivity Map (CMap), Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) and GeneMANIA. A total of 230 DEGs were identified between the bone marrow tissues of IDH2 R140Q-mutated and wild-type AML patients, of which 31 were significantly associated with overall survival (OS). Functional assessment of DEGs showed significant enrichment in multiple biological processes, including angiogenesis and cell differentiation. STRING and GeneMANIA were used to identify the hub genes of these DEGs. CMap analysis identified 13 potential small-molecule drugs against IDH2 R140Q-mutated adult de novo AML. Genome-wide co-expression network analysis identified several IDH2 R140Q co-expressed genes, of which 56 were significantly associated with AML OS. The difference in IDH2 mRNA expression levels and OS between the IDH2 R140Q-mutated and wild-type AML were not statistically significant in our cohort. In conclusion, we identified several co-expressing genes and potential molecular mechanisms that are instrumental in IDH2 R140Q-mutated adult de novo AML, along with 13 candidate targeted therapeutic drugs.

Comparative Gene Expression Profiles in Parathyroid Adenoma and Normal Parathyroid Tissue.

Parathyroid adenoma is the main cause of primary hyperparathyroidism, which is characterized by enlarged parathyroid glands and excessive parathyroid hormone secretion. Here, we performed transcriptome analysis, comparing parathyroid adenomas with normal parathyroid gland tissue. RNA extracted from ten parathyroid adenoma and five normal parathyroid samples was sequenced, and differentially expressed genes (DEGs) were identified using strict cut-off criteria. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed using DEGs as the input, and protein-protein interaction (PPI) networks were constructed using Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) and visualized in Cytoscape. Among DEGs identified in parathyroid adenomas (n = 247; 45 up-regulated, 202 down-regulated), the top five GO terms for up-regulated genes were nucleoplasm, nucleus, transcription DNA-template, regulation of mRNA processing, and nucleic acid binding, while those for down-regulated genes were extracellular exosome, membrane endoplasmic reticulum (ER), membrane, ER, and melanosome. KEGG enrichment analysis revealed significant enrichment of five pathways: protein processing in ER, protein export, RNA transport, glycosylphosphatidylinositol-anchor biosynthesis, and pyrimidine metabolism. Further, PPI network analysis identified a densely connected sub-module, comprising eight hub molecules: SPCS2, RPL23, RPL26, RPN1, SEC11C, SEC11A, RPS25, and SEC61G. These findings may be helpful in further analysis of the mechanisms underlying parathyroid adenoma development.

Identification of Significant Proteins Associated with Diabetes Mellitus Using Network Analysis of Protein-Protein Interactions

Computation approach to identify significance of proteins related with disease was proposed as one of the solutions from the problem of experimental method application which is generally high cost and time consuming. The case of study was conducted on Diabetes Melitus (DM) type 2 diseases. Identification of significant proteins was conducted by constructing protein-protein interactions network and then analyzing the network topology. Dataset was obtained from Online Mendelian Inheritance in Man (OMIM) and Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) which provided protein data related with a disease and Protein-Protein Interaction (PPI), respectively. The results of topology analysis towards Protein-Protein Interaction (PPI) showed that there were 21 significant protein associated with DM where INS as a network center protein and AKTI, TCF7L2, KCNJ11, PPARG, GCG, INSR, IAPP, SOCS3 were proteins that had close relation directly with INS.

Combining data from TCGA and GEO databases and reverse transcription quantitative PCR validation to identify gene prognostic markers in lung cancer.

BackgroundThe aim of this study was to predict and explore the possible mechanism and clinical value of genetic markers in the development of lung cancer with a combined database to screen the prognostic genes of lung cancer.Materials and methodsCommon differential genes in two gene expression chips (GSE3268 and GSE10072 datasets) were investigated by collecting and calculating from Gene Expression Omnibus and The Cancer Genome Atlas databases using R language. Five markers of gene composition (ribonucleotide reductase regulatory subunit M2 [RRM2], trophoblast glycoprotein [TPBG], transmembrane protease serine 4[TMPRFF4], chloride intracellular channel 3 [CLIC3], and WNT inhibitory factor-1 [WIF1]) were found by the stepwise Cox regression function when we further screened combinations of gene models, which were more meaningful for prognosis. By analyzing the correlation between gene markers and clinicopathological parameters of lung cancer and its effect on prognosis, the TPBG gene was selected to analyze differential expression, its possible pathways and functions were predicted using gene set enrichment analysis (GSEA), and its protein interaction network was constructed using the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) database; then, quantitative PCR and the Oncomine database were used to verify the expression differences of TPBG in lung cancer cells and tissues.ResultsThe expression levels of five genetic markers were correlated with survival prognosis, and the total survival time of the patients with high expression of the genetic markers was shorter than those with low expression (P<0.001). GSEA showed that these high-expression samples enriched the gene sets of cell adhesion, cytokine receptor interaction pathway, extracellular matrix receptor pathway, adhesion pathway, skeleton protein regulation, cancer pathway and TGF-β pathway.ConclusionThe high expression of five gene constituent markers is a poor prognostic factor in lung cancer and may serve as an effective biomarker for predicting metastasis and prognosis of patients with lung cancer.

The Expression of CD83 Would be Increased in CD34-Positive Monocytes Detected in Peripheral Blood Mobilized By G-CSF in Humans

[Background]CD34-positive monocytes (CD34+mono) have recently been identified following mobilization by granulocyte-colony stimulating factor (G-CSF), and have been suggested to have a potential to modulate immune functions in animal models. However, the biological feature of CD34+mono in humans still remains unclear. Thus, we explored the difference between CD34+mono, CD34+cells, and monocytes through the analyses of gene expression profiles (GEP).[Methods]CD34+mono (Lin-CD34+CD33+CD14+CD11b+, Figure1), CD34+cells (Lin-CD34+CD33-CD14-CD11b- ), and monocytes (Lin-CD34-CD33+CD14+CD11b+) were directly sorted into tubes from cryopreserved grafts from three healthy donors. After the extraction of total RNA, microarray analyses were performed with GeneChip™ 3' IVT Pico Kit and analyzed according to the algorithm of Transcriptome Analysis Console (Thermo Fisher Scientific). Condition false discovery rate (FDR) F-test was used for filtering genes, and the threshold was <0.0005 for hierarchical clustering without considering fold changes. In addition, enrichment analyses were performed for gene ontology (GO) and pathways by the Kyoto Encyclopedia of Genes and Genomes (KEGG) through Database for Annotation, Visualization and Integrated Discovery (DAVID). The differentially expressed genes with <0.05 of F-test values and 2 or more fold changes in CD34+mono compared with CD34+cells and monocytes were selected for the enrichment analyses. Thereafter, the protein-protein interaction (PPI) network in CD34+mono was constructed through Search Tool for the Retrieval of Interacting Genes/Proteins (STRING), which is a biological database. This study was approved by the institutional review board of Jichi Medical University and all subjects gave their written informed consent for the cryopreservation and analysis of the blood samples in accordance with the Helsinki Declaration.[Results]CD34+mono resembled con-mono in the appearance, although it might look slightly immature. In fact, the number of differential expressed genes was smaller in the pair of CD34+mono vs. monocytes (n=605) compared with the other pair (n=2136), suggesting that CD34+mono might stand nearby monocytes. However, a principle component analysis of GEP demonstrated that CD34+mono would be categorized into an independent cell type entity. In addition, the hierarchical clustering heat map suggested that CD34+mono would have the interim gene expressions between CD34+ cells and monocytes (Figure 2).GO analysis was also performed using the 203 genes which were differentially expressed in CD34+mono compared with CD34+cells and monocytes. The differentially expressed genes seemed to be significantly involved in the “immune system process” of biological process, followed by “locomotion”, “metabolic process” and “response to stimulus”, because pro-inflammatory genes in CD34+mono like IL6, CCL3, IL8, VEGFA, and IL1A were increased.In addition, PPI analyses indicated that 128 of the 203 differentially expressed genes in CD34+mono had close connections with each other. Especially, IL6, VEGFA, IL8, NFkB1, EGR1, CDKN1A (p21), and CYCS could be considered as a hub gene in CD34+mono. Of them, IL6, IL8, and VEGFA are considered to be pro-inflammatory cytokines. NFkB1, and EGR1 are transcriptional factors, and CDKN1A, and CYCS are considered to regulate cell cycle or apoptosis. Furthermore, simultaneously focusing on the difference in the fold changes of gene expressions between CD34+mono vs. monocytes, CD83 (a membrane protein and immunoglobulin superfamily that regulates antigen presentation) and FOSL1 (a kind of regulators of cell proliferation, differentiation, and transformation) were specifically increased in CD34+mono (Figure3).The increased expression of CD83 strongly suggests antigen presenting cells like mature dendritic cells. CD34+mono might be one of progenitors of dendritic cells, or might have a potential of antigen presentation itself.[Conclusion]In summary, the differentially expressed genes in CD34+mono would be mapped in the immune process, especially against infectious pathogens. In addition, the increased CD83 suggested that CD34+mono might play a role of antigen presentation in the immune response. Further investigations would be necessary to confirm the clinical roles of CD34+mono after transplantation. [Display omitted] DisclosuresNakasone:Phizer: Honoraria; Novartis: Honoraria; Kyowa Hakko Kirin: Honoraria; Celgene: Honoraria; Bristol-Myers Squibb: Honoraria; Janssen: Honoraria; Takeda: Honoraria. Kimura:Astellas: Honoraria; Pfizer: Honoraria; Sumitomo Dainippon Pharma: Honoraria; MSD: Other: Investigator in the institute; Nippon Kayaku: Honoraria; Celgene: Honoraria; Kyowa Hakko Kirin: Honoraria; Takeda: Honoraria. Kako:Takeda Pharmaceutical Company Limited.: Honoraria; Takeda Pharmaceutical Company Limited.: Honoraria; Celgene K.K.: Honoraria; Bristol-Myers Squibb: Honoraria; Sumitomo Dainippon Pharma Co., Ltd.: Honoraria; Chugai Pharmaceutical Co., Ltd.: Honoraria; Otsuka Pharmaceutical Co., Ltd.: Honoraria; Ono Pharmaceutical Co., Ltd.: Honoraria; Janssen Pharmaceutical K.K.: Honoraria. Kanda:Eisai: Consultancy, Honoraria, Research Funding; Dainippon-Sumitomo: Consultancy, Honoraria, Research Funding; MSD: Research Funding; Nippon-Shinyaku: Research Funding; Pfizer: Research Funding; Kyowa-Hakko Kirin: Consultancy, Honoraria, Research Funding; Chugai: Consultancy, Honoraria, Research Funding; Otsuka: Research Funding; Taisho-Toyama: Research Funding; CSL Behring: Research Funding; Tanabe-Mitsubishi: Research Funding; Astellas: Consultancy, Honoraria, Research Funding; Bristol-Myers Squibb: Consultancy, Honoraria; Ono: Consultancy, Honoraria, Research Funding; Taiho: Research Funding; Shionogi: Consultancy, Honoraria, Research Funding; Sanofi: Research Funding; Takeda: Consultancy, Honoraria, Research Funding; Asahi-Kasei: Research Funding; Novartis: Research Funding; Celgene: Consultancy, Honoraria; Mochida: Consultancy, Honoraria; Alexion: Consultancy, Honoraria; Takara-bio: Consultancy, Honoraria.

ITRAQ-Based Analysis of Proteins Co-Regulated by Brassinosteroids and Gibberellins in Rice Embryos during Seed Germination

Seed germination, a pivotal process in higher plants, is precisely regulated by various external and internal stimuli, including brassinosteroid (BR) and gibberellin (GA) phytohormones. The molecular mechanisms of crosstalk between BRs and GAs in regulating plant growth are well established. However, whether BRs interact with GAs to coordinate seed germination remains unknown, as do their common downstream targets. In the present study, 45 differentially expressed proteins responding to both BR and GA deficiency were identified using isobaric tags for relative and absolute quantification (iTRAQ) proteomic analysis during seed germination. The results indicate that crosstalk between BRs and GAs participates in seed germination, at least in part, by modulating the same set of responsive proteins. Moreover, most targets exhibited concordant changes in response to BR and GA deficiency, and gene ontology (GO) indicated that most possess catalytic activity and are involved in various metabolic processes. Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) analysis was used to construct a regulatory network of downstream proteins mediating BR- and GA-regulated seed germination. The mutation of GRP, one representative target, notably suppressed seed germination. Our findings not only provide critical clues for validating BR–GA crosstalk during rice seed germination, but also help to optimise molecular regulatory networks.

Single-Run Mass Spectrometry Analysis Provides Deep Insight into E. coli Proteome.

Single-run mass spectrometry has enabled the detection and quantifications of E. coli proteins. A total of 2068 proteins quantified by intensity-based absolute quantification (iBAQ) Schwanhäusser et al.: (Nature. 473, 337-342, 2011) procedure were obtained with single enzyme-trypsin, without pre-fractionation, by quadruplicate long liquid chromatography runs coupled with high-resolution linear trap quadrupole (LTQ)-Orbitrap Velos mass spectrometry. The single-run of 12h has ability to cover almost 98% of the quadruplicate LC-MS/MS runs of E. coli proteome and is therefore almost equivalent to quadruplicate LC-MS/MS runs. These quantified proteins are about 52% of the total proteins present in E. coli genome according to Uniprot database. The quantified proteins covered almost all of the proteins in folate biosynthesis. Remarkably greater part of Gene Ontology (GO) Barrell et al.: (Nucleic Acids Res. 37, D396-D403, 2009), Ashburner et al.: (Nat. Genet. 25, 25-29, 2000) annotations, signaling pathways along with protein-protein interactions were covered. Some of the important biological processes-cell cycle, DNA repair, ion transport, ubiquinone biosynthetic process, pseudouridine synthesis, peptidoglycan biosynthetic process, RNA processing, and translation-revealed protein-protein interaction network generated by Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) Jensen, et al.:(Nucleic Acids Res 37, D412-D126, 2009) database. Therefore, to achieve the saturation point of detection of maximum number of proteins in single LC-MS/MS run, 12-h liquid chromatography gradient is appropriate. Graphical Abstract ᅟ.

Identification of a perchloric acid-soluble protein (PSP)-like ribonuclease from Trichomonas vaginalis

A perchloric acid-soluble protein (PSP), named here tv-psp1, was identified in Trichomonas vaginalis. It is expressed under normal culture conditions according to expressed sequence tag (EST) analysis. On the other hand, Tv-PSP1 protein was identified by mass spectrometry with a 40% of identity to human PSP (p14.1). Polyclonal antibodies against recombinant Tv-PSP1 (rTv-PSP1) recognized a single band at 13.5kDa in total protein parasite extract by SDS-PAGE and a high molecular weight band analyzed by native PAGE. Structural analysis of Tv-PSP1, using dynamic light scattering, size exclusion chromatography, and circular dichroism spectroscopy, showed a trimeric structure stable at 7M urea with 38% α-helix and 14% β-sheet in solution and a molecular weight of 40.5kD. Tv-PSP1 models were used to perform dynamic simulations over 100ns suggesting a stable homotrimeric structure. Tv-PSP1 was located in the nucleus, cytoplasm, and hydrogenosomes of T. vaginalis, and the in silico analysis by Search Tool for the Retrieval of Interacting Genes/Proteins (STRING) showed interactions with RNA binding proteins. The preliminary results of RNA degradation analysis with the recombinant Tv-PSP1 showed RNA partial deterioration suggesting a possible putative ribonuclease function.

MicroRNA-mRNA regulatory networks underlying chronic mucus hypersecretion in COPD.

Chronic mucus hypersecretion (CMH) is a common feature in chronic obstructive pulmonary disease (COPD) and is associated with worse prognosis and quality of life. This study aimed to identify microRNA (miRNA)-mRNA regulatory networks underlying CMH.The expression profiles of miRNA and mRNA in bronchial biopsies from 63 COPD patients were associated with CMH using linear regression. Potential mRNA targets of each CMH-associated miRNA were identified using Pearson correlations. Gene set enrichment analysis (GSEA) and STRING (search tool for the retrieval of interacting genes/proteins) analysis were used to identify key genes and pathways.20 miRNAs and 539 mRNAs were differentially expressed with CMH in COPD. The expression of 10 miRNAs was significantly correlated with the expression of one or more mRNAs. Of these, miR-134-5p, miR-146a-5p and the let-7 family had the highest representation of CMH-associated mRNAs among their negatively correlated predicted targets. KRAS and EDN1 were identified as key regulators of CMH and were negatively correlated predicted targets of miR-134-5p and let-7a-5p, let-7d-5p, and let-7f-5p, respectively. GSEA suggested involvement of MUC5AC-related genes and several other relevant gene sets in CMH. The lower expression of miR-134-5p was confirmed in primary airway fibroblasts from COPD patients with CMH.We identified miR-134-5p, miR-146a-5p and let-7 family, along with their potential target genes including KRAS and EDN1, as potential key miRNA-mRNA networks regulating CMH in COPD.

Proteomic biomarkers of cognitive impairment in obstructive sleep apnea syndrome.

There are currently no biomarkers that are associated with cognitive impairment (CI) in patients with obstructive sleep apnea syndrome (OSAS). This pilot study performed an exploratory plasma proteomic analysis to discover potential biomarkers and explore proteomic pathways that differentiate OSAS subjects with and without CI. Participants were selected from a cohort of women within 5years of menopause not on hormone replacement therapy between the ages of 45-60years. The Berlin questionnaire was used to select OSAS participants who then completed the MCFSI (Mail-In Cognitive Function Screening Instrument) to measure cognition. Six subjects with the highest MCFSI scores (≥ 5 denoting CI) were compared to six with normal scores. Proteomic analysis was done by Myriad RBM using a targeted ELISA for 254 serum proteins. Pathway analysis of differentially expressed proteins was performed using STRING (Search Tool for the Retrieval of Interacting Genes/Proteins) software. Distinct proteomic signatures were seen in OSAS subjects with CI as compared to those without CI. Proteins including insulin, prostasin, angiopoietin-1, plasminogen activator inhibitor 1, and interleukin-1 beta were overexpressed in OSAS subjects with CI. Proteins underexpressed in CI participants included cathepsin B, ceruloplasmin, and adiponectin. Pathway analysis revealed prominence of insulin-regulated vascular disease biomarkers. Proteomic biomarkers in participants with cognitive impairment suggest roles for insulin, and vascular signaling pathways, some of which are similar to findings in Alzheimer's disease. A better understanding of the pathogenic mechanisms of CI in OSAS will help focus clinical trials needed in this patient population.

Whole-Exome Sequencing Identifies Two Discrete Druggable Signaling Pathways in Follicular Thyroid Cancer

Thyroid cancer is the most common endocrine malignancy, with continuously increasing incidence. Follicular thyroid cancer (FTC) accounts for approximately 10% to 15% of these cases and is known to be associated with several gene mutations. The purpose of this study was to identify novel therapeutic targets in FTC using whole-exome sequencing (WES) and bioinformatics analysis. Whole-exome sequencing was performed on 6 established FTC cell lines. Stringent false-proof filtering and exclusion of synonymous and known polymorphisms yielded novel missense, nonsense, and splice-site single nucleotide variants (SNV). Gene variants were analyzed for structural, functional, and evolutionary properties using GO (Gene Ontology), Pfam (Protein Families), and KEGG (Kyoto Encyclopedia of Genes and Genomes) searches by STRING (Search Tool for the Retrieval of Interacting Genes/Proteins) and GORILLA (Gene Ontology enRIchment anaLysis and visuaLizAtion tool) analyses. A false discovery rate of <0.5 was used to denote significantly enriched signaling pathways. An average of 657 (range 366 to 1,158) SNVs including 31 (range 12 to 53) known cancer driver genes were identified in FTC cell line exomes. The SNV burden, distribution, frequency, and signature followed the known thyroid mutation profiles, without chromosomal bias. Recurrently mutated cancer driver genes included FRG1 (6/6), CDC27, NCOR1, PRSS1 (5/6), AHCTF1, MUC20, PABPC1, and PABPC3 (4/6). Pathway analysis using bioinformatics tools STRING and GORILLA segregated FTC cell lines into 2 druggable signaling groups showing dominant RAS/ERK1-2/AKT and CDK1/CyclinB signaling pathway targets. Next-generation sequencing tools can be used to identify druggable signaling targets for precision treatment of FTCs.