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1.
Gene ; 720: 144103, 2019 Dec 15.
Artigo em Inglês | MEDLINE | ID: mdl-31491435

RESUMO

Clear cell renal cell carcinoma (ccRCC) is a highly invasive urological malignant tumor that results in shorter patient survival. At present, the mechanism of ccRCC metastasis is not clear. We explored the possible mechanisms of ccRCC metastasis by analyzing the transcriptome of ccRCC patients from the Cancer Genome Atlas (TCGA) database. Comparing the differences in transcriptome in patients with and without metastasis, we found 323 differential genes (|log2FoldChange| > 1 and P < 0.001). KEGG and GO enrichment analyses of differentially expressed genes (DEGs) suggest that the transfer mechanism of ccRCC may be related to complement and coagulation cascades and cholesterol metabolism. To explore the key genes affecting tumor metastasis, we analyzed the association of these genes with patient survival time and found that 16 genes were significantly associated (P < 0.05). We compared the differences in expression of these 16 genes between ccRCC patients and the normal population, and the results showed that TF and B4GALNT1 were overexpressed in patients. Co-expression gene analysis indicated that TF may participate in the metastasis of cancer through the complement system and mucopolysaccharide biosynthesis. B4GALNT1 may affect metastasis through focal adhesion, calcium signaling pathways, and Hippo signaling pathways. Our studies suggest that the complement system and the coagulation cascade, cholesterol metabolism, calcium pathway and iron transport may be associated in the mechanism of metastasis. TF and B4GALNT1 may be the key genes for metastasis, and they may be potential diagnostic markers and therapeutic targets for ccRCC.


Assuntos
Biomarcadores Tumorais/genética , Carcinoma de Células Renais/genética , Biologia Computacional/métodos , Regulação Neoplásica da Expressão Gênica , Neoplasias Renais/genética , Transcriptoma , Biomarcadores Tumorais/metabolismo , Carcinoma de Células Renais/metabolismo , Carcinoma de Células Renais/secundário , Estudos de Casos e Controles , Feminino , Perfilação da Expressão Gênica , Redes Reguladoras de Genes , Humanos , Neoplasias Renais/metabolismo , Neoplasias Renais/patologia , Masculino , Prognóstico , Mapas de Interação de Proteínas , Transdução de Sinais , Taxa de Sobrevida
2.
Gene ; 720: 144088, 2019 Dec 15.
Artigo em Inglês | MEDLINE | ID: mdl-31476404

RESUMO

BACKGROUND: Secretory leukocyte protease inhibitor (SPLI) was a secreted protein which belongs to a member of whey acidic protein four-disulfide core family. In breast cancer (BC) it may inhibit cell proliferation and promote cancer metastasis. In this study, a comprehensive bioinformatics analysis was performed to identify the expression and prognostic value of SLPI in breast cancer. METHODS: SLPI expression in breast cancer was analyzed in Oncomine online database, which was subsequently confirmed by quantitative PCR (qPCR) in 18 BC samples and western blotting in 26 BC samples. Breast cancer gene-expression miner v4.1 was used to access the expression level with clinicopathological parameters in breast cancer patients. The prognostic values of SLPI in breast cancer were evaluated using the PrognoScan database. RESULTS: Our results indicated that SLPI was downregulated in breast cancer than in normal tissues. SLPI expression was found to be negatively correlated with estrogen receptor (ER) and progesterone receptor (PR) status. SLPI expression level was decreased in negative basal-like status patients compared with positive basal-like status. Meanwhile, triple-negative breast cancer status positive correlated with SLPI. We confirmed a positive correlation between SLPI and interleukin 17 receptor B (IL17RB) express in breast cancer tissues via oncomine co-expression analysis. Ten proteins: Elastase, Granulin, Lipocalin, Defensin beta 103B, Defensin beta 103A, Tubulin, Heparin-binding EGF-like growth factor, Interleukin 6, Epidermal growth factor, Phospholipid scramblase 1 were determinate interactions with SLPI by STRING. CONCLUSION: SLPI could as a biomarker to predict the prognosis values of breast cancer. However, further comprehensive study and mining more evidence are needed to clarify our results.


Assuntos
Biologia Computacional/métodos , Regulação Neoplásica da Expressão Gênica , Inibidor Secretado de Peptidases Leucocitárias/genética , Neoplasias de Mama Triplo Negativas/genética , Adulto , Idoso , Feminino , Humanos , Pessoa de Meia-Idade , Prognóstico , Mapas de Interação de Proteínas , Inibidor Secretado de Peptidases Leucocitárias/metabolismo , Neoplasias de Mama Triplo Negativas/metabolismo , Neoplasias de Mama Triplo Negativas/patologia
3.
Chem Commun (Camb) ; 55(69): 10192-10213, 2019 Aug 22.
Artigo em Inglês | MEDLINE | ID: mdl-31411602

RESUMO

Light is unsurpassed in its ability to modulate biological interactions. Since their discovery, chemists have been fascinated by photosensitive molecules capable of switching between isomeric forms, known as photoswitches. Photoswitchable peptides have been recognized for many years; however, their functional implementation in biological systems has only recently been achieved. Peptides are now acknowledged as excellent protein-protein interaction modulators and have been important in the emergence of photopharmacology. In this review, we briefly explain the different classes of photoswitches and summarize structural studies when they are incorporated into peptides. Importantly, we provide a detailed overview of the rapidly increasing number of examples, where biological modulation is driven by the structural changes. Furthermore, we discuss some of the remaining challenges faced in this field. These exciting proof-of-principle studies highlight the tremendous potential of photocontrollable peptides as optochemical tools for chemical biology and biomedicine.


Assuntos
Descoberta de Drogas , Peptídeos/química , Peptídeos/farmacologia , Sequência de Aminoácidos , Animais , Antibacterianos/química , Antibacterianos/metabolismo , Antibacterianos/farmacologia , Morte Celular/efeitos dos fármacos , Descoberta de Drogas/métodos , Humanos , Isomerismo , Luz , Modelos Moleculares , Ácidos Nucleicos/metabolismo , Peptídeos/metabolismo , Processos Fotoquímicos , Mapas de Interação de Proteínas/efeitos dos fármacos
4.
Medicine (Baltimore) ; 98(33): e16807, 2019 Aug.
Artigo em Inglês | MEDLINE | ID: mdl-31415393

RESUMO

BACKGROUND: Sepsis is a serious clinical condition with a poor prognosis, despite improvements in diagnosis and treatment.Therefore, novel biomarkers are necessary that can help with estimating prognosis and improving clinical outcomes of patients with sepsis. METHODS: The gene expression profiles GSE54514 and GSE63042 were downloaded from the GEO database. DEGs were screened by t test after logarithmization of raw data; then, the common DEGs between the 2 gene expression profiles were identified by up-regulation and down-regulation intersection. The DEGs were analyzed using bioinformatics, and a protein-protein interaction (PPI) survival network was constructed using STRING. Survival curves were constructed to explore the relationship between core genes and the prognosis of sepsis patients based on GSE54514 data. RESULTS: A total of 688 common DEGs were identified between survivors and non-survivors of sepsis, and 96 genes were involved in survival networks. The crucial genes Signal transducer and activator of transcription 5A (STAT5A), CCAAT/enhancer-binding protein beta (CEBPB), Myc proto-oncogene protein (MYC), and REL-associated protein (RELA) were identified and showed increased expression in sepsis survivors. These crucial genes had a positive correlation with patients' survival time according to the survival analysis. CONCLUSIONS: Our findings indicate that the genes STAT5A, CEBPB, MYC, and RELA may be important in predicting the prognosis of sepsis patients.


Assuntos
Proteína beta Intensificadora de Ligação a CCAAT/metabolismo , Proteínas Proto-Oncogênicas c-myc/metabolismo , Fator de Transcrição STAT5/metabolismo , Sepse/genética , Sepse/mortalidade , Fator de Transcrição RelA/metabolismo , Proteínas Supressoras de Tumor/metabolismo , Idoso , Idoso de 80 Anos ou mais , Biologia Computacional , Bases de Dados Genéticas , Regulação para Baixo , Feminino , Marcadores Genéticos , Humanos , Masculino , Pessoa de Meia-Idade , Prognóstico , Mapas de Interação de Proteínas , Fatores de Tempo , Transcriptoma , Regulação para Cima
5.
Gene ; 717: 143998, 2019 Oct 30.
Artigo em Inglês | MEDLINE | ID: mdl-31381951

RESUMO

Eid1 is a member of the EID protein family, which regulates differentiation, transcription and acetyltransferase activity. Accumulating evidence suggests that Eid1 is relevant to neurological disorder, but the main function of Eid1 is still unclear, especially in the brain. To better understand this issue, we generated Eid1-knockout (Eid1-KO) mice and profiled its gene expression changes in the brain by RNA sequencing. This study identified 2531 genes differentially expressed in Eid1-KO mice compared with the wild-type, then qRT-PCR verification demonstrated that the transcriptomic data are reliable. By protein-protein interaction cluster analysis, 'regulation of cell proliferation' were unexpectedly discovered as important Eid1 functions. We then isolated neural progenitor cells (NPCs) and showed that the number of neurospheres and the proliferation rate of Eid1-KO NPCs were obviously lower than that in the control group, furthermore, CCK-8 and immunofluorescence assay clearly demonstrated that the Eid1-KO NPCs showed significantly less cell proliferation than the control group. To the best of our knowledge, this is the first comprehensive report of the Eid1-KO transcriptome of mice brain. Our analysis and experimental data provide a foundation for further studies on understanding function of Eid1 in the brain.


Assuntos
Encéfalo/citologia , Proteínas Nucleares/genética , Proteínas Nucleares/metabolismo , Proteínas Repressoras/genética , Proteínas Repressoras/metabolismo , Animais , Encéfalo/embriologia , Encéfalo/fisiologia , Proliferação de Células/genética , Feminino , Perfilação da Expressão Gênica , Camundongos Endogâmicos C57BL , Camundongos Knockout , Células-Tronco Neurais/citologia , Células-Tronco Neurais/fisiologia , Gravidez , Mapas de Interação de Proteínas , Análise de Sequência de RNA
6.
Medicine (Baltimore) ; 98(34): e16922, 2019 Aug.
Artigo em Inglês | MEDLINE | ID: mdl-31441876

RESUMO

BACKGROUND: Circular RNAs (circRNAs) have displayed dysregulated expression in several types of cancer. Nevertheless, their function and underlying mechanisms in cervical cancer remains largely unknown. This study aimed to describe the regulatory mechanisms in cervical cancer. METHODS: We downloaded the circRNAs expression profiles from Gene Expression Omnibus database, and RNAs expression profiles from The Cancer Genome Atlas database. We established a circRNA-miRNA-mRNA and circRNA-miRNA-hubgene network. The interactions between proteins were analyzed using the STRING database and hubgenes were identified using MCODE plugin. Then, we conducted a circRNA-miRNA-hubgenes regulatory module. Functional and pathway enrichment analyses were conducted using R packages "Clusterprofile". RESULTS: Six circRNAs, 15 miRNAs, and 158 mRNAs were identified to construct the ceRNA network of cervical cancer. PPI (protein-protein interaction) network and module analysis identified 7 hubgenes. Then, a circRNA-miRNA-hubgene subnetwork was constructed based on the 1 DEcircRNAs, 3 DEmiRNAs, and 3 DEmRNAs. The KEGG pathway analysis indicated DEmRNAs are involved in progesterone-mediated oocyte maturation, cell cycle, and oocyte meiosis. CONCLUSION: These ceRNAs are critical in the pathogenesis of cervical and may serve as future therapeutic biomarkers.


Assuntos
Regulação Neoplásica da Expressão Gênica/genética , Redes Reguladoras de Genes/genética , RNA/genética , Neoplasias do Colo do Útero/genética , Biomarcadores Tumorais/genética , Feminino , Humanos , Mapas de Interação de Proteínas , RNA/metabolismo
7.
Life Sci ; 234: 116788, 2019 Oct 01.
Artigo em Inglês | MEDLINE | ID: mdl-31445935

RESUMO

Livin is an important member of the human inhibitor of apoptosis proteins (IAPs) family. IAPs are proteins with antiapoptotic abilities, and their functions are different from the Bcl-2 (B-cell lymphoma-2) family proteins. However, the precise role of Livin in colon cancer progression remains unclear. The purpose of this study is to assess the effect of overexpression Livin in colon cancer cells and to examine its molecular mechanism. We demonstrated that Livin induced a colon cancer phenotype, including proliferation and migration, by regulating H2A.XY39ph (histone family 2A variant (H2AX) phosphorylated on the 39th serine site). We elucidated that Livin degraded Jumonji-C domain-containing 6 protein (JMJD6), which was mediated by the proteasome murine double minute 2 (MDM2), thereby regulating H2A.XY39ph. Above all, the overexpression of JMJD6 recovered H2A.XY39ph in colon cancer cells with a high level of Livin, thus inhibiting colon cancer malignancy progression. These results reveal a previously unrecognized role for Livin in regulating the tumor-initiating capacity in colon cancer and provide a novel treatment strategy in cancer via the interruption of H2A.XY39ph function and the interaction between H2A.XY39ph and JMJD6.


Assuntos
Proteínas Adaptadoras de Transdução de Sinal/metabolismo , Neoplasias do Colo/patologia , Histonas/metabolismo , Proteínas Inibidoras de Apoptose/metabolismo , Histona Desmetilases com o Domínio Jumonji/metabolismo , Proteínas de Neoplasias/metabolismo , Mapas de Interação de Proteínas , Proteínas Adaptadoras de Transdução de Sinal/genética , Carcinogênese/genética , Carcinogênese/metabolismo , Carcinogênese/patologia , Linhagem Celular Tumoral , Neoplasias do Colo/genética , Neoplasias do Colo/metabolismo , Progressão da Doença , Regulação Neoplásica da Expressão Gênica , Histonas/genética , Humanos , Proteínas Inibidoras de Apoptose/genética , Histona Desmetilases com o Domínio Jumonji/genética , Proteínas de Neoplasias/genética , Proteólise
8.
BMC Bioinformatics ; 20(1): 422, 2019 Aug 14.
Artigo em Inglês | MEDLINE | ID: mdl-31412768

RESUMO

BACKGROUND: One of the main issues in the automated protein function prediction (AFP) problem is the integration of multiple networked data sources. The UNIPred algorithm was thereby proposed to efficiently integrate -in a function-specific fashion- the protein networks by taking into account the imbalance that characterizes protein annotations, and to subsequently predict novel hypotheses about unannotated proteins. UNIPred is publicly available as R code, which might result of limited usage for non-expert users. Moreover, its application requires efforts in the acquisition and preparation of the networks to be integrated. Finally, the UNIPred source code does not handle the visualization of the resulting consensus network, whereas suitable views of the network topology are necessary to explore and interpret existing protein relationships. RESULTS: We address the aforementioned issues by proposing UNIPred-Web, a user-friendly Web tool for the application of the UNIPred algorithm to a variety of biomolecular networks, already supplied by the system, and for the visualization and exploration of protein networks. We support different organisms and different types of networks -e.g., co-expression, shared domains and physical interaction networks. Users are supported in the different phases of the process, ranging from the selection of the networks and the protein function to be predicted, to the navigation of the integrated network. The system also supports the upload of user-defined protein networks. The vertex-centric and the highly interactive approach of UNIPred-Web allow a narrow exploration of specific proteins, and an interactive analysis of large sub-networks with only a few mouse clicks. CONCLUSIONS: UNIPred-Web offers a practical and intuitive (visual) guidance to biologists interested in gaining insights into protein biomolecular functions. UNIPred-Web provides facilities for the integration of networks, and supplies a framework for the imbalance-aware protein network integration of nine organisms, the prediction of thousands of GO protein functions, and a easy-to-use graphical interface for the visual analysis, navigation and interpretation of the integrated networks and of the functional predictions.


Assuntos
Biologia Computacional/métodos , Internet , Mapas de Interação de Proteínas , Proteínas/metabolismo , Software , Algoritmos , Interface Usuário-Computador
9.
BMC Bioinformatics ; 20(Suppl 13): 381, 2019 Jul 24.
Artigo em Inglês | MEDLINE | ID: mdl-31337329

RESUMO

BACKGROUND: How can we obtain fast and high-quality clusters in genome scale bio-networks? Graph clustering is a powerful tool applied on bio-networks to solve various biological problems such as protein complexes detection, disease module detection, and gene function prediction. Especially, MCL (Markov Clustering) has been spotlighted due to its superior performance on bio-networks. MCL, however, is skewed towards finding a large number of very small clusters (size 1-3) and fails to detect many larger clusters (size 10+). To resolve this fragmentation problem, MLR-MCL (Multi-level Regularized MCL) has been developed. MLR-MCL still suffers from the fragmentation and, in cases, unrealistically large clusters are generated. RESULTS: In this paper, we propose PS-MCL (Parallel Shotgun Coarsened MCL), a parallel graph clustering method outperforming MLR-MCL in terms of running time and cluster quality. PS-MCL adopts an efficient coarsening scheme, called SC (Shotgun Coarsening), to improve graph coarsening in MLR-MCL. SC allows merging multiple nodes at a time, which leads to improvement in quality, time and space usage. Also, PS-MCL parallelizes main operations used in MLR-MCL which includes matrix multiplication. CONCLUSIONS: Experiments show that PS-MCL dramatically alleviates the fragmentation problem, and outperforms MLR-MCL in quality and running time. We also show that the running time of PS-MCL is effectively reduced with parallelization.


Assuntos
Algoritmos , Proteínas/metabolismo , Análise por Conglomerados , Cadeias de Markov , Mapas de Interação de Proteínas , Proteínas/química
10.
Yakugaku Zasshi ; 139(7): 969-973, 2019.
Artigo em Japonês | MEDLINE | ID: mdl-31257254

RESUMO

Translesion DNA synthesis (TLS) is an emergency system activated to inhibit cell death caused by DNA damage-induced replication arrest. Thus, TLS enables cancer cells to acquire resistance to alkylate anticancer drugs. REV7 functions as the hub protein that interacts with both the inserter DNA polymerase REV1 and the extender DNA polymerase REV3 in TLS. REV7-mediated protein-protein interactions (PPIs) are essential for the activation of TLS, and are therefore attractive targets for anticancer drug development. To clarify the REV7-REV3 and REV7-REV1 PPIs, we determined the structures of REV7-REV3 and REV7-REV3-REV1 complexes. In the structures of REV7-REV3 and REV7-REV3-REV1 complexes, REV7 wraps around the REV3 fragment, and the REV1-binding interface is distinct from the REV3-binding site of REV7. We also identified a novel REV7 binding protein, transcription factor II-I (TFII-I), which is required for TLS. Of note, TFII-I binds the REV7-REV3-REV1 complex, suggesting that REV7-TFII-I PPIs are independent of other REV7-mediated PPIs. Furthermore, we found a small-molecule compound that inhibits TLS by targeting the REV7-REV3 PPIs. Lastly, we determined the structure of REV7 in complex with chromosome alignment maintaining phosphoprotein (CAMP), a known kinetochore-microtubule attachment protein. The overall structure of the REV7-CAMP complex is similar to that of the REV7-REV3 complex, but the REV7-CAMP PPIs are markedly different from the REV7-REV3 PPIs. These findings improve our understanding of multifunctional hub proteins, and are helpful for designing small-molecule compounds for novel anticancer drug development.


Assuntos
Antineoplásicos , Descoberta de Drogas , Proteína Semelhante a ELAV 2/química , Cristalografia por Raios X , DNA/biossíntese , Dano ao DNA , Proteínas de Ligação a DNA/química , DNA Polimerase Dirigida por DNA/química , Humanos , Proteínas Mad2/química , Peso Molecular , Proteínas Nucleares/química , Nucleotidiltransferases/química , Ligação Proteica , Mapas de Interação de Proteínas , Estrutura Terciária de Proteína
11.
J Agric Food Chem ; 67(32): 8746-8755, 2019 Aug 14.
Artigo em Inglês | MEDLINE | ID: mdl-31322881

RESUMO

The underlying mechanisms of the higher photosynthetic efficiency of cultivated cassava relative to its wild species are poorly understood. In the present study, proteins in leaves and chloroplasts were analyzed to compare the differences among the cultivar SC205, its wild ancestor W14, and the related species Glaziovii. The functions of differential proteins are associated with 10 ontology groups including photosynthesis, carbohydrate and energy metabolism, as well as potential signal pathway. The protein-protein networks among 41 differential proteins showed that PGK1 is a hub protein and protein cross-interactions affected the differentiation of photosynthetic rate. Anatomy patterns and PEPC detection suggested that SC205 has more C4 photosynthesis characteristics than Glaziovii and W14. Finally, a mechanism model of the efficient photosynthesis was proposed based on the remarkable variations in photosynthetic parameters and protein functions in the domestic cultivars.


Assuntos
Manihot/metabolismo , Fotossíntese , Cloroplastos/metabolismo , Manihot/classificação , Folhas de Planta/metabolismo , Proteínas de Plantas/metabolismo , Ligação Proteica , Mapas de Interação de Proteínas
12.
Medicine (Baltimore) ; 98(27): e16277, 2019 Jul.
Artigo em Inglês | MEDLINE | ID: mdl-31277155

RESUMO

Kaposi sarcoma (KS) is an endothelial tumor etiologically related to Kaposi sarcoma herpesvirus (KSHV) infection. The aim of our study was to screen out candidate genes of KSHV infected endothelial cells and to elucidate the underlying molecular mechanisms by bioinformatics methods. Microarray datasets GSE16354 and GSE22522 were downloaded from Gene Expression Omnibus (GEO) database. the differentially expressed genes (DEGs) between endothelial cells and KSHV infected endothelial cells were identified. And then, functional enrichment analyses of gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) pathway analysis were performed. After that, Search Tool for the Retrieval of Interacting Genes (STRING) was used to investigate the potential protein-protein interaction (PPI) network between DEGs, Cytoscape software was used to visualize the interaction network of DEGs and to screen out the hub genes. A total of 113 DEGs and 11 hub genes were identified from the 2 datasets. GO enrichment analysis revealed that most of the DEGs were enrichen in regulation of cell proliferation, extracellular region part and sequence-specific DNA binding; KEGG pathway enrichments analysis displayed that DEGs were mostly enrichen in cell cycle, Jak-STAT signaling pathway, pathways in cancer, and Insulin signaling pathway. In conclusion, the present study identified a host of DEGs and hub genes in KSHV infected endothelial cells which may serve as potential key biomarkers and therapeutic targets, helping us to have a better understanding of the molecular mechanism of KS.


Assuntos
Biomarcadores Tumorais/genética , Biologia Computacional/métodos , Células Endoteliais/metabolismo , Regulação Neoplásica da Expressão Gênica , Herpesvirus Humano 8 , Mapas de Interação de Proteínas/genética , Sarcoma de Kaposi/genética , Biomarcadores Tumorais/biossíntese , DNA de Neoplasias/genética , Células Endoteliais/patologia , Células Endoteliais/virologia , Perfilação da Expressão Gênica/métodos , Ontologia Genética , Humanos , Mapeamento de Interação de Proteínas/métodos , Sarcoma de Kaposi/metabolismo , Sarcoma de Kaposi/virologia
13.
Zhongguo Zhong Yao Za Zhi ; 44(9): 1904-1910, 2019 May.
Artigo em Chinês | MEDLINE | ID: mdl-31342720

RESUMO

Xixian Tongshuan Capsules with functions of promoting blood circulation and removing blood stasis,dispelling wind and resolving phlegm,relaxing muscles and activating collaterals,restoring consciousness and inducing resuscitation,has significant effects on main and concurrently symptoms of apoplexy. In this research,908 chemical compounds of Xixian Tongshuan Capsules were collected,and 337 potential targets were discovered by pharmacophore based reverse target identification. Protein interaction network( PIN)was then constructed and Identifying Protein Complex Algorithm( IPCA) was used to obtain the modules of the capsule and analyze the potential action mechanism. According to the research,Xixian Tongshuan Capsules could play a therapeutic role for hyperlipidemia and hypertension by regulating lipid metabolic process and blood pressure,the most direct risk factors of apoplexy. It could be used to treat the cerebral thrombosis and irreversible death of nerve tissue caused by insufficient supply of cerebral tissue blood and oxygen,in a way of regulating blood circulation system and nervous system. Xixian Tongshuan Capsules could also treat stroke-induced inflammation and inflammatory immune response through its regulatory effect on inflammatory immune response. Based on the network analysis,the antiinflammatory activity of Xixian Tongshuan Capsules extracts was investigated by measuring the NO release with Griess reagent method through LPS-induced in vitro inflammation model of RAW264. 7 cells. The results showed that Xixian Tongshuan Capsules extracts inhibited the secretion of NO by LPS-induced RAW264. 7 cells,indicating favorable anti-inflammatory activity. This research illuminates the mechanism of Xixian Tongshuan Capsules based on the PIN analysis at molecular network level,providing a scientific basis for its clinical application.


Assuntos
Medicamentos de Ervas Chinesas/farmacologia , Inflamação/tratamento farmacológico , Acidente Vascular Cerebral/tratamento farmacológico , Animais , Cápsulas , Humanos , Camundongos , Óxido Nítrico/metabolismo , Mapas de Interação de Proteínas , Células RAW 264.7
14.
BMC Bioinformatics ; 20(1): 393, 2019 Jul 16.
Artigo em Inglês | MEDLINE | ID: mdl-31311505

RESUMO

BACKGROUND: MicroRNAs (miRNAs) are small RNAs that regulate gene expression at a post-transcriptional level and are emerging as potentially important biomarkers for various disease states, including pancreatic cancer. In silico-based functional analysis of miRNAs usually consists of miRNA target prediction and functional enrichment analysis of miRNA targets. Since miRNA target prediction methods generate a large number of false positive target genes, further validation to narrow down interesting candidate miRNA targets is needed. One commonly used method correlates miRNA and mRNA expression to assess the regulatory effect of a particular miRNA. The aim of this study was to build a bioinformatics pipeline in R for miRNA functional analysis including correlation analyses between miRNA expression levels and its targets on mRNA and protein expression levels available from the cancer genome atlas (TCGA) and the cancer proteome atlas (TCPA). TCGA-derived expression data of specific mature miRNA isoforms from pancreatic cancer tissue was used. RESULTS: Fifteen circulating miRNAs with significantly altered expression levels detected in pancreatic cancer patients were queried separately in the pipeline. The pipeline generated predicted miRNA target genes, enriched gene ontology (GO) terms and Kyoto encyclopedia of genes and genomes (KEGG) pathways. Predicted miRNA targets were evaluated by correlation analyses between each miRNA and its predicted targets. MiRNA functional analysis in combination with Kaplan-Meier survival analysis suggest that hsa-miR-885-5p could act as a tumor suppressor and should be validated as a potential prognostic biomarker in pancreatic cancer. CONCLUSIONS: Our miRNA functional analysis (miRFA) pipeline can serve as a valuable tool in biomarker discovery involving mature miRNAs associated with pancreatic cancer and could be developed to cover additional cancer types. Results for all mature miRNAs in TCGA pancreatic adenocarcinoma dataset can be studied and downloaded through a shiny web application at https://emmbor.shinyapps.io/mirfa/ .


Assuntos
MicroRNAs/metabolismo , Neoplasias Pancreáticas/genética , Proteínas/genética , Interface Usuário-Computador , Automação , Humanos , Estimativa de Kaplan-Meier , MicroRNAs/genética , Neoplasias Pancreáticas/mortalidade , Neoplasias Pancreáticas/patologia , Mapas de Interação de Proteínas , Proteínas/metabolismo , RNA Mensageiro/metabolismo
15.
Science ; 365(6449): 120-121, 2019 07 12.
Artigo em Inglês | MEDLINE | ID: mdl-31296755
16.
BMC Bioinformatics ; 20(1): 355, 2019 Jun 24.
Artigo em Inglês | MEDLINE | ID: mdl-31234779

RESUMO

BACKGROUND: Essential proteins are distinctly important for an organism's survival and development and crucial to disease analysis and drug design as well. Large-scale protein-protein interaction (PPI) data sets exist in Saccharomyces cerevisiae, which provides us with a valuable opportunity to predict identify essential proteins from PPI networks. Many network topology-based computational methods have been designed to detect essential proteins. However, these methods are limited by the completeness of available PPI data. To break out of these restraints, some computational methods have been proposed by integrating PPI networks and multi-source biological data. Despite the progress in the research of multiple data fusion, it is still challenging to improve the prediction accuracy of the computational methods. RESULTS: In this paper, we design a novel iterative model for essential proteins prediction, named Randomly Walking in the Heterogeneous Network (RWHN). In RWHN, a weighted protein-protein interaction network and a domain-domain association network are constructed according to the original PPI network and the known protein-domain association network, firstly. And then, we establish a new heterogeneous matrix by combining the two constructed networks with the protein-domain association network. Based on the heterogeneous matrix, a transition probability matrix is established by normalized operation. Finally, an improved PageRank algorithm is adopted on the heterogeneous network for essential proteins prediction. In order to eliminate the influence of the false negative, information on orthologous proteins and the subcellular localization information of proteins are integrated to initialize the score vector of proteins. In RWHN, the topology, conservative and functional features of essential proteins are all taken into account in the prediction process. The experimental results show that RWHN obviously exceeds in predicting essential proteins ten other competing methods. CONCLUSIONS: We demonstrated that integrating multi-source data into a heterogeneous network can preserve the complex relationship among multiple biological data and improve the prediction accuracy of essential proteins. RWHN, our proposed method, is effective for the prediction of essential proteins.


Assuntos
Mapeamento de Interação de Proteínas/métodos , Proteínas de Saccharomyces cerevisiae/metabolismo , Saccharomyces cerevisiae/metabolismo , Algoritmos , Domínios Proteicos , Mapas de Interação de Proteínas , Proteínas de Saccharomyces cerevisiae/química
17.
Gen Physiol Biophys ; 38(3): 205-214, 2019 May.
Artigo em Inglês | MEDLINE | ID: mdl-31184307

RESUMO

Polycystic ovary syndrome (PCOS) is the most common hormonal and metabolic disorder among women of reproductive age, but the mechanisms underlying this unique pathogenesis remain unknown. This study was therefore designed to identify candidate genes involved in the pathogenesis of PCOS, using bioinformatics analysis. The gene expression profiles of GSE34526 from 7 PCOS patients and 3 controls were downloaded from Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were identified using GCBI online tool. Expression levels of candidate genes were verified using quantitative RT-PCR (qRT-PCR) and Western blot. 426 DEGs were identified by GCBI, including 418 up-regulated and 8 down-regulated genes. Function and pathway enrichment analyses showed that these DEGs were significantly enriched in inflammation and immune-related pathways. Additionally, protein-protein interaction (PPI) network and module analyses showed that two modules involved the Toll-like receptor signaling pathway were ranked among the most upregulated modules, and the candidate genes involved in this signaling pathway consisted of TLR1, TLR2, TLR8, and CD14. Finally, expression levels of TLR2, TLR8 and CD14 were significantly increased in samples from PCOS patients. Collectively, the results suggested that the Toll-like receptor signaling pathway might play an important role in the pathogenesis of PCOS.


Assuntos
Biologia Computacional , Síndrome do Ovário Policístico/genética , Síndrome do Ovário Policístico/metabolismo , Feminino , Perfilação da Expressão Gênica , Redes Reguladoras de Genes , Humanos , Mapas de Interação de Proteínas
18.
Food Chem ; 295: 129-137, 2019 Oct 15.
Artigo em Inglês | MEDLINE | ID: mdl-31174741

RESUMO

Heat stress causes oxidative damage and quality reduction in poultry. Here, a tandem mass tag proteomic approach was applied to investigate the proteomic differences in duck meat from birds exposed to heat stress. Altogether 212 differential proteins were identified, including 178 down-regulated and 34 up-regulated proteins, compared to the control. Malondialdehyde and carbonyl content and cooking loss of the chest muscle significantly increased under heat stress. The proteomic analysis indicated that heat stress suppressed mitochondrial functions and respiratory chains, which might be responsible for the higher oxidation level. The results also revealed potential protective proteins involved in the defensive mechanisms against heat stress in duck muscles, such as sarcoplasmic/endoplasmic reticulum calcium ATPases, Mn-superoxide dismutase, heat shock protein family B member 7, methyltransferase like 21C, myosin-binding protein C, and carbonic anhydrase 3. These results provide potential targets for the research and identification of oxidative meat products due to heat stress.


Assuntos
Carne/análise , Estresse Oxidativo , Proteoma/análise , Proteômica/métodos , Animais , ATPases Transportadoras de Cálcio/genética , ATPases Transportadoras de Cálcio/metabolismo , Culinária , Patos/metabolismo , Proteínas de Choque Térmico HSP27/genética , Proteínas de Choque Térmico HSP27/metabolismo , Masculino , Músculo Esquelético/metabolismo , Mapas de Interação de Proteínas , Superóxido Dismutase/genética , Superóxido Dismutase/metabolismo
19.
BMC Bioinformatics ; 20(Suppl 12): 319, 2019 Jun 20.
Artigo em Inglês | MEDLINE | ID: mdl-31216984

RESUMO

BACKGROUND: Real biological and social data is increasingly being represented as graphs. Pattern-mining-based graph learning and analysis techniques report meaningful biological subnetworks that elucidate important interactions among entities. At the backbone of these algorithms is the enumeration of pattern space. RESULTS: We propose an efficient algorithm for enumerating all connected induced subgraphs of an undirected graph. Building on this enumeration approach, we propose an algorithm for mining all maximal cohesive subgraphs that integrates vertices' attributes with subgraph enumeration. To efficiently mine all maximal cohesive subgraphs, we propose two pruning techniques that remove futile search nodes in the enumeration tree. CONCLUSIONS: Experiments on synthetic and real graphs show the effectiveness of the proposed algorithm and the pruning techniques. On enumerating all connected induced subgraphs, our algorithm is several times faster than existing approaches. On dense graphs, the proposed approach is at least an order of magnitude faster than the best existing algorithm. Experiments on protein-protein interaction network with cancer gene dysregulation profile show that the reported cohesive subnetworks are biologically interesting.


Assuntos
Algoritmos , Mapas de Interação de Proteínas , Humanos , Fatores de Tempo
20.
Nat Commun ; 10(1): 2727, 2019 06 21.
Artigo em Inglês | MEDLINE | ID: mdl-31227708

RESUMO

A fundamental challenge in medical microbiology is to characterize the dynamic protein-protein interaction networks formed at the host-pathogen interface. Here, we generate a quantitative interaction map between the significant human pathogen, Streptococcus pyogenes, and proteins from human saliva and plasma obtained via complementary affinity-purification and bacterial-surface centered enrichment strategies and quantitative mass spectrometry. Perturbation of the network using immunoglobulin protease cleavage, mixtures of different concentrations of saliva and plasma, and different S. pyogenes serotypes and their isogenic mutants, reveals how changing microenvironments alter the interconnectivity of the interaction map. The importance of host immunoglobulins for the interaction with human complement proteins is demonstrated and potential protective epitopes of importance for phagocytosis of S. pyogenes cells are localized. The interaction map confirms several previously described protein-protein interactions; however, it also reveals a multitude of additional interactions, with possible implications for host-pathogen interactions involving other bacterial species.


Assuntos
Anticorpos Antibacterianos/metabolismo , Proteínas de Bactérias/metabolismo , Interações Hospedeiro-Patógeno/imunologia , Infecções Estreptocócicas/imunologia , Streptococcus pyogenes/imunologia , Anticorpos Antibacterianos/imunologia , Antígenos de Bactérias/imunologia , Antígenos de Bactérias/metabolismo , Proteínas de Bactérias/imunologia , Cromatografia de Afinidade , Proteínas do Sistema Complemento/imunologia , Proteínas do Sistema Complemento/metabolismo , Mapeamento de Epitopos , Voluntários Saudáveis , Humanos , Espectrometria de Massas , Proteínas Opsonizantes/imunologia , Proteínas Opsonizantes/metabolismo , Ligação Proteica , Mapeamento de Interação de Proteínas , Mapas de Interação de Proteínas/imunologia , Infecções Estreptocócicas/sangue , Infecções Estreptocócicas/microbiologia , Streptococcus pyogenes/metabolismo
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