• Title/Summary/Keyword: Protein Ontology

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A case of interdigitating dendritic cell sarcoma studied by whole-exome sequencing

  • Hong, Ki Hwan;Song, Soyoung;Shin, Wonseok;Kang, Keunsoo;Cho, Chun?Sung;Hong, Yong Tae;Han, Kyudong;Moon, Jeong Hwan
    • Genes and Genomics
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    • v.40 no.12
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    • pp.1279-1285
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    • 2018
  • Interdigitating dendritic cell sarcoma (IDCS) is an aggressive neoplasm and is an extremely rare disease, with a challenging diagnosis. Etiology of IDCS is also unknown and most studies with only case reports. In our case, immunohistochemistry showed that the tumor cells were positive for S100, CD45, and CD68, but negative for CD1a and CD21. This study aimed to investigate the causative factors of IDCS by sequencing the protein-coding regions of IDCS. We performed whole-exome sequencing with genomic DNA from blood and sarcoma tissue of the IDCS patient using the Illumina Hiseq 2500 platform. After that, we conducted Sanger sequencing for validation of sarcoma-specific variants and gene ontology analysis using DAVID bioinformatics resources. Through comparing sequencing data of sarcoma with normal blood, we obtained 15 nonsynonymous single nucleotide polymorphisms (SNPs) as sarcoma-specific variants. Although the 15 SNPs were not validated by Sanger sequencing due to tumor heterogeneity and low sensitivity of Sanger sequencing, we examined the function of the genes in which each SNP is located. Based on previous studies and gene ontology database, we found that POLQ encoding DNA polymerase theta enzyme and FNIP1 encoding tumor suppressor folliculin-interacting protein might have contributed to the IDCS. Our study provides potential causative genetic factors of IDCS and plays a role in advancing the understanding of IDCS pathogenesis.

Systems Pharmacological Analysis of Dichroae Radix in Anti-Tumor Metastasis Activity (시스템 약리학적 분석에 의한 상산의 암전이 억제 효과)

  • Jee Ye Lee;Ah Yeon Shin;Hak Koon Kim;Won Gun An
    • Herbal Formula Science
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    • v.31 no.4
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    • pp.295-313
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    • 2023
  • Objectives : While treatments for cancer are advancing, the development of effective treatments for cancer metastasis, the main cause of cancer patient death, remains insufficient. Recent studies on Dichroae Radix have revealed that its active ingredients have the potential to inhibit cancer metastasis. This study aimed to investigate the cancer metastasis inhibitory effect of Dichroae Radix using network pharmacological analysis. Methods : The active compounds of Dichroae Radix have been identified using Traditional Chinese Medicine System Pharmacology Database and Analysis Platform. The UniProt database was used to collect each of information of all target proteins associated with the active compounds. To find the bio-metabolic processes associated with each target, the DAVID6.8 Gene Functional classifier tool was used. Compound-Target and Target-Pathway networks were analyzed via Cytoscape 3.40. Results : In total, 25 active compounds and their 62 non-redundant targets were selected through the TCMSP database and analysis platform. The target genes underwent gene ontology and pathway enrichment analysis. The gene list applied to the gene ontology analysis revealed associations with various biological processes, including signal transduction, chemical synaptic transmission, G-protein-coupled receptor signaling pathways, response to xenobiotic stimulus, and response to drugs, among others. A total of eleven genes, including HSP90AB1, CALM1, F2, AR, PAKACA, PTGS2, NOS2, RXRA, ESR1, ESR2, and NCOA1, were found to be associated with biological pathways related to cancer metastasis. Furthermore, nineteen of the active compounds from Dichroae Radix were confirmed to interact with these genes. Conclusions : The results provide valuable insights into the mechanism of action and molecular targets of Dichroae Radix. Notably, Berberine, the main active ingredient of Dichroae Radix, plays a significant role in degrading AR proteins in advanced prostate cancer. Further studies and validations can provide crucial data to advance cancer metastasis prevention and treatment strategies.

Proteomic Analysis and Extensive Protein Identification from Dry, Germinating Arabidopsis Seeds and Young Seedlings

  • Fu, Qiang;Wang, Bai-Chen;Jin, Xiang;Li, Hong-Bing;Han, Pei;Wei, Kai-Hua;Zhang, Xue-Min;Zhu, Yu-Xian
    • BMB Reports
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    • v.38 no.6
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    • pp.650-660
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    • 2005
  • Proteins accumulated in dry, stratified Arabidopsis seeds or young seedlings, totaled 1100 to 1300 depending on the time of sampling, were analyzed by using immobilized pH gradient 2-DE gel electrophoresis. The molecular identities of 437 polypeptides, encoded by 355 independent genes, were determined by MALDI-TOF or TOF-TOF mass spectrometry. In the sum, 293 were present at all stages and 95 were accumulated during the time of radicle protrusion while another 18 appeared in later stages. Further analysis showed that 226 of the identified polypeptides could be located in different metabolic pathways. Proteins involved in carbohydrate, energy and amino acid metabolism constituted to about 1/4, and those involved in metabolism of vitamins and cofactors constituted for about 3% of the total signal intensity in gels prepared from 72 h seedlings. Enzymes related to genetic information processing increased very quickly during early imbibition and reached highest level around 30 h of germination.

Shortest Path Analyses in the Protein-Protein Interaction Network of NGAL (Neutrophil Gelatinase-associated Lipocalin) Overexpression in Esophageal Squamous Cell Carcinoma

  • Du, Ze-Peng;Wu, Bing-Li;Wang, Shao-Hong;Shen, Jin-Hui;Lin, Xuan-Hao;Zheng, Chun-Peng;Wu, Zhi-Yong;Qiu, Xiao-Yang;Zhan, Xiao-Fen;Xu, Li-Yan;Li, En-Min
    • Asian Pacific Journal of Cancer Prevention
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    • v.15 no.16
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    • pp.6899-6904
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    • 2014
  • NGAL (neutrophil gelatinase-associated lipocalin) is a novel cancer-related protein involves multiple functions in many cancers and other diseases. We previously overexpressed NGAL to analyze its role in esophageal squamous cell carcinoma (ESCC). In this study, a protein-protein interaction (PPI) was constructed and the shortest paths from NGAL to transcription factors in the network were analyzed. We found 28 shortest paths from NGAL to RELA, most of them obeying the principle of extracellular to cytoplasm, then nucleus. These shortest paths were also prioritized according to their normalized intensity from the microarray by the order of interaction cascades. A systems approach was developed in this study by linking differentially expressed genes with publicly available PPI data, Gene Ontology and subcellular localizaton for the integrated analyses. These shortest paths from NGAL to DEG transcription factors or other transcription factors in the PPI network provide important clues for future experimental identification of new pathways.

Protein-protein Interaction Network Analyses for Elucidating the Roles of LOXL2-delta72 in Esophageal Squamous Cell Carcinoma

  • Wu, Bing-Li;Zou, Hai-Ying;Lv, Guo-Qing;Du, Ze-Peng;Wu, Jian-Yi;Zhang, Pi-Xian;Xu, Li-Yan;Li, En-Min
    • Asian Pacific Journal of Cancer Prevention
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    • v.15 no.5
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    • pp.2345-2351
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    • 2014
  • Lysyl oxidase-like 2 (LOXL2), a member of the lysyl oxidase (LOX) family, is a copper-dependent enzyme that catalyzes oxidative deamination of lysine residues on protein substrates. LOXL2 was found to be overexpressed in esophageal squamous cell carcinoma (ESCC) in our previous research. We later identified a LOXL2 splicing variant LOXL2-delta72 and we overexpressed LOXL2-delta72 and its wild type counterpart in ESCC cells following microarray analyses. First, the differentially expressed genes (DEGs) of LOXL2 and LOXL2-delta72 compared to empty plasmid were applied to generate protein-protein interaction (PPI) sub-networks. Comparison of these two sub-networks showed hundreds of different proteins. To reveal the potential specific roles of LOXL2- delta72 compared to its wild type, the DEGs of LOXL2-delta72 vs LOXL2 were also applied to construct a PPI sub-network which was annotated by Gene Ontology. The functional annotation map indicated the third PPI sub-network involved hundreds of GO terms, such as "cell cycle arrest", "G1/S transition of mitotic cell cycle", "interphase", "cell-matrix adhesion" and "cell-substrate adhesion", as well as significant "immunity" related terms, such as "innate immune response", "regulation of defense response" and "Toll signaling pathway". These results provide important clues for experimental identification of the specific biological roles and molecular mechanisms of LOXL2-delta72. This study also provided a work flow to test the different roles of a splicing variant with high-throughput data.

Bioinformatics Analysis of Autophagy and Mitophagy Markers Associated with Delayed Cerebral Ischemia Following Subarachnoid Hemorrhage

  • Youn, Dong Hyuk;Kim, Bong Jun;Hong, Eun Pyo;Jeon, Jin Pyeong
    • Journal of Korean Neurosurgical Society
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    • v.65 no.2
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    • pp.236-244
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    • 2022
  • Objective : To evaluate the interactions among differentially expressed autophagy and mitophagy markers in subarachnoid hemorrhage (SAH) patients with delayed cerebral ischemia (DCI). Methods : The expression data of autophagy and mitophagy-related makers in the cerebrospinal fluid (CSF) cells was analyzed by real-time reverse transcription-polymerase chain reaction and Western blotting. The markers included death-associated protein kinase (DAPK)-1, BCL2 interacting protein 3 like (BNIP3L), Bcl-1 antagonist X, phosphatase and tensin homolog-induced kinase (PINK), Unc-51 like autophagy activating kinase 1, nuclear dot protein 52, and p62. In silico functional analyses including gene ontology enrichment and the protein-protein interaction network were performed. Results : A total of 56 SAH patients were included and 22 (38.6%) of them experienced DCI. The DCI patients had significantly increased mRNA levels of DAPK1, BNIP3L, and PINK1, and increased expression of BECN1 compared to the non-DCI patients. The most enriched biological process was the positive regulation of autophagy, followed by the response to mitochondrial depolarization. The molecular functions ubiquitin-like protein ligase binding and ubiquitin-protein ligase binding were enriched. In the cluster of cellular components, Lewy bodies and the phagophore assembly site were enriched. BECN1 was the most connected gene among the differentially expressed markers related to autophagy and mitophagy in the development of DCI. Conclusion : Our study may provide novel insight into mitochondrial dysfunction in DCI pathogenesis.

Identification of growth trait related genes in a Yorkshire purebred pig population by genome-wide association studies

  • Meng, Qingli;Wang, Kejun;Liu, Xiaolei;Zhou, Haishen;Xu, Li;Wang, Zhaojun;Fang, Meiying
    • Asian-Australasian Journal of Animal Sciences
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    • v.30 no.4
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    • pp.462-469
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    • 2017
  • Objective: The aim of this study is to identify genomic regions or genes controlling growth traits in pigs. Methods: Using a panel of 54,148 single nucleotide polymorphisms (SNPs), we performed a genome-wide Association (GWA) study in 562 pure Yorshire pigs with four growth traits: average daily gain from 30 kg to 100 kg or 115 kg, and days to 100 kg or 115 kg. Fixed and random model Circulating Probability Unification method was used to identify the associations between 54,148 SNPs and these four traits. SNP annotations were performed through the Sus scrofa data set from Ensembl. Bioinformatics analysis, including gene ontology analysis, pathway analysis and network analysis, was used to identify the candidate genes. Results: We detected 6 significant and 12 suggestive SNPs, and identified 9 candidate genes in close proximity to them (suppressor of glucose by autophagy [SOGA1], R-Spondin 2 [RSPO2], mitogen activated protein kinase kinase 6 [MAP2K6], phospholipase C beta 1 [PLCB1], rho GTPASE activating protein 24 [ARHGAP24], cytoplasmic polyadenylation element binding protein 4 [CPEB4], GLI family zinc finger 2 [GLI2], neuronal tyrosine-phosphorylated phosphoinositide-3-kinase adaptor 2 [NYAP2], and zinc finger protein multitype 2 [ZFPM2]). Gene ontology analysis and literature mining indicated that the candidate genes are involved in bone, muscle, fat, and lung development. Pathway analysis revealed that PLCB1 and MAP2K6 participate in the gonadotropin signaling pathway and suggests that these two genes contribute to growth at the onset of puberty. Conclusion: Our results provide new clues for understanding the genetic mechanisms underlying growth traits, and may help improve these traits in future breeding programs.

Characterization of the Alzheimer's disease-related network based on the dynamic network approach (동적인 개념을 적용한 알츠하이머 질병 네트워크의 특성 분석)

  • Kim, Man-Sun;Kim, Jeong-Rae
    • Journal of the Korean Institute of Intelligent Systems
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    • v.25 no.6
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    • pp.529-535
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    • 2015
  • Biological networks have been handled with the static concept. However, life phenomena in cells occur depending on the cellular state and the external environment, and only a few proteins and their interactions are selectively activated. Therefore, we should adopt the dynamic network concept that the structure of a biological network varies along the flow of time. This concept is effective to analyze the progressive transition of the disease. In this paper, we applied the proposed method to Alzheimer's disease to analyze the structural and functional characteristics of the disease network. Using gene expression data and protein-protein interaction data, we constructed the sub-networks in accordance with the progress of disease (normal, early, middle and late). Based on this, we analyzed structural properties of the network. Furthermore, we found module structures in the network to analyze the functional properties of the sub-networks using the gene ontology analysis (GO). As a result, it was shown that the functional characteristics of the dynamics network is well compatible with the stage of the disease which shows that it can be used to describe important biological events of the disease. Via the proposed approach, it is possible to observe the molecular network change involved in the disease progression which is not generally investigated, and to understand the pathogenesis and progression mechanism of the disease at a molecular level.

A Method for Protein Functional Flow Configuration and Validation (단백질 기능 흐름 모델 구성 및 평가 기법)

  • Jang, Woo-Hyuk;Jung, Suk-Hoon;Han, Dong-Soo
    • Journal of KIISE:Computing Practices and Letters
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    • v.15 no.4
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    • pp.284-288
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    • 2009
  • With explosively growing PPI databases, the computational approach for a prediction and configuration of PPI network has been a big stream in the bioinformatics area. Recent researches gradually consider physicochemical properties of proteins and support high resolution results with integration of experimental results. With regard to current research trend, it is very close future to complete a PPI network configuration of each organism. However, direct applying the PPI network to real field is complicated problem because PPI network is only a set of co-expressive proteins or gene products, and its network link means simple physical binding rather than in-depth knowledge of biological process. In this paper, we suggest a protein functional flow model which is a directed network based on a protein functions' relation of signaling transduction pathway. The vertex of the suggested model is a molecular function annotated by gene ontology, and the relations among the vertex are considered as edges. Thus, it is easy to trace a specific function's transition, and it can be a constraint to extract a meaningful sub-path from whole PPI network. To evaluate the model, 11 functional flow models of Homo sapiens were built from KEGG, and Cronbach's alpha values were measured (alpha=0.67). Among 1023 functional flows, 765 functional flows showed 0.6 or higher alpha values.

Stage specific transcriptome profiles at cardiac lineage commitment during cardiomyocyte differentiation from mouse and human pluripotent stem cells

  • Cho, Sung Woo;Kim, Hyoung Kyu;Sung, Ji Hee;Han, Jin
    • BMB Reports
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    • v.54 no.9
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    • pp.464-469
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    • 2021
  • Cardiomyocyte differentiation occurs through complex and finely regulated processes including cardiac lineage commitment and maturation from pluripotent stem cells (PSCs). To gain some insight into the genome-wide characteristics of cardiac lineage commitment, we performed transcriptome analysis on both mouse embryonic stem cells (mESCs) and human induced PSCs (hiPSCs) at specific stages of cardiomyocyte differentiation. Specifically, the gene expression profiles and the protein-protein interaction networks of the mESC-derived platelet-derived growth factor receptor-alpha (PDGFRα)+ cardiac lineage-committed cells (CLCs) and hiPSC-derived kinase insert domain receptor (KDR)+ and PDGFRα+ cardiac progenitor cells (CPCs) at cardiac lineage commitment were compared with those of mesodermal cells and differentiated cardiomyocytes. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses revealed that the genes significantly upregulated at cardiac lineage commitment were associated with responses to organic substances and external stimuli, extracellular and myocardial contractile components, receptor binding, gated channel activity, PI3K-AKT signaling, and cardiac hypertrophy and dilation pathways. Protein-protein interaction network analysis revealed that the expression levels of genes that regulate cardiac maturation, heart contraction, and calcium handling showed a consistent increase during cardiac differentiation; however, the expression levels of genes that regulate cell differentiation and multicellular organism development decreased at the cardiac maturation stage following lineage commitment. Additionally, we identified for the first time the protein-protein interaction network connecting cardiac development, the immune system, and metabolism during cardiac lineage commitment in both mESC-derived PDGFRα+ CLCs and hiPSC-derived KDR+PDGFRα+ CPCs. These findings shed light on the regulation of cardiac lineage commitment and the pathogenesis of cardiometabolic diseases.