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Prediction of the anti-inflammatory mechanisms of curcumin by module-based protein interaction network analysis

Acta Pharmaceutica Sinica B 2015年第6期5卷 590-595页

作者： Yanxiong Gan Shichao Zheng Jan P.A.Baak Silei Zhao Yongfeng Zheng Nini Luo Wan Liao Chaomei Fu State Key Laboratory Breeding Base of Systematic Research Development and Utilization of Chinese Medicine ResourcesSchool of PharmacyChengdu University of Traditional Chinese Medicine School of Chinese Pharmacy Beijing University of Chinese Medicine Faculty of Sports Sciences and Medicine Technical University Munich

Curcumin,the medically active component from Curcuma longa(Turmeric),is widely used to treat inflammatory diseases.protein interaction network(PIN) analysis was used to predict its mechanisms of molecular action.Targets of curcumin were obtained based on ChE MBL and STITCH databases.protein–protein interactions(PPIs) were extracted from the String database.The PIN of curcumin was constructed by Cytoscape and the function modules identified by gene ontology(GO) enrichment analysis based on molecular complex detection(MCODE).A PIN of curcumin with 482 nodes and 1688 interactions was constructed,which has scale-free,small world and modular properties.Based on analysis of these function modules,the mechanism of curcumin is proposed.Two modules were found to be intimately associated with inflammation.With function modules analysis,the anti-inflammatory effects of curcumin were related to SMAD,ERG and mediation by the TLR family.TLR9 may be a potential target of curcumin to treat inflammation.

关键词： Curcumin protein interaction network Module Anti-inflammatory Molecular mechanism Gene ontology enrichment analysis Molecular complex detection Cytoscape

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HPC-Atlas:Computationally Constructing A Comprehensive Atlas of Human protein Complexes

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Genomics, Proteomics & Bioinformatics 2023年第5期21卷 976-990页

作者： Yuliang Pan Ruiyi Li Wengen Li Liuzhenghao Lv Jihong Guan Shuigeng Zhou Department of Computer Science and Technology College of Electronic and Information EngineeringTongji UniversityShanghai 201804China Translational Medical Center for Stem Cell Therapy Shanghai East HospitalSchool of MedicineTongji UniversityShanghai 200120China Shanghai Key Laboratory of Intelligent Information Processing School of Computer ScienceFudan UniversityShanghai 200433China

A fundamental principle of biology is that proteins tend to form complexes to play important roles in the core functions of cells.For a complete understanding of human cellular functions,it is crucial to have a comprehensive atlas of human protein complexes.Unfortunately,we still lack such a comprehensive atlas of experimentally validated protein complexes,which prevents us from gaining a complete understanding of the compositions and functions of human protein complexes,as well as the underlying biological mechanisms.To fill this gap,we built Human protein Complexes Atlas(HPC-Atlas),as far as we know,the most accurate and comprehensive atlas of human protein complexes available to date.We integrated two latest protein interaction networks,and developed a novel computational method to identify nearly 9000 protein complexes,including many previously uncharacterized complexes.Compared with the existing methods,our method achieved outstanding performance on both testing and independent datasets.Furthermore,with HPC-Atlas we identified 751 severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)-affected human protein complexes,and 456 multifunctional proteins that contain many potential moonlighting proteins.These results suggest that HPC-Atlas can serve as not only a computing framework to effectively identify biologically meaningful protein complexes by integrating multiple protein data sources,but also a valuable resource for exploring new biological findings.The HPCAtlas webserver is freely available at http://www.***.top/HPC-Atlas.

关键词： Human protein complex protein interaction network SARS-CoV-2-affected complex Multifunctional protein Complex identification method

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Prognostic biomarkers and immune cell infiltration characteristics in small cell lung cancer

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Cancer Pathogenesis and Therapy 2023年第1期1卷 18-24页

作者： Jun Ni Xiaoyan Si Hanping Wang Xiaotong Zhang Li Zhang Department of Pulmonary and Critical Care Medicine Peking Union Medical College HospitalChinese Academy of Medical Science&Peking Union Medical CollegeBeijing 100730China

Background Small cell lung cancer(SCLC)is a highly malignant and aggressive neuroendocrine tumor.With the rise of immunotherapy,it has provided a new direction for SCLC.However,due to the lack of prognostic biomarkers,the median overall survival of SCLC is still to be improved.This study aimed to explore novel biomarkers and tumor-infiltrating immune cell characteristics that may serve as potential diagnostic and prognostic markers in SCLC.Methods Gene expression profiles from patients with SCLC were downloaded from the Gene Expression Omnibus(GEO)database,and tumor microenvironment(TME)infiltration profile data were obtained using CIBERSORT.The robust rank aggregation(RRA)method was utilized to integrate three SCLC microarray datasets downloaded from the GEO database and identify robust differentially expressed genes(DEGs)between normal and tumor tissue samples.Gene Ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)enrichment analyses were performed to explore the functions of the robust DEGs.Subsequently,protein-protein interaction networks and key modules were constructed by Cytoscape,and hub genes were selected from the whole network using the plugin cytoHubba.Survival analysis of hub genes was performed by Kaplan-Meier plotter in 18 patients with extensive-stage SCLC.Results A total of 312 robust DEGs,including 55 upregulated and 257 downregulated genes,were screened from 129 SCLC tissue samples and 44 normal tissue samples.GO and KEGG enrichment analyses revealed that the robust DEGs were predominantly involved in human T-cell leukemia virus 1 infection,focal adhesion,complement and coagulation cascades,tumor necrosis factor(TNF)signaling pathway,and ECM-receptor interaction,which are closely associated with the development and progression of SCLC.Subsequently,three DEGs modules and six hub genes(ITGA10,DUSP12,PTGS2,FOS,TGFBR2,and ICAM1)were identified through screening with the Cytoscape plugins MCODE and cytoHubba,respectively.Immune cell infiltration analysis by the CIBERSORT algorithm reveale

关键词： Bioinformatics analysis Small cell lung cancer Immune cell infiltration Tumor microenvironment Hub genes protein interaction network Gene expression omnibus database

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LPS和Poly I:C激后短蛸（Amphioctopus fangsiao）血淋巴转录组分析及免疫关键基因的挖掘

LPS和Poly I:C激后短蛸（Amphioctopus fangsiao）血淋巴转录组分...

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作者：陈希盼鲁东大学

学位级别：硕士

Amphioctopus fangsiao is an economically important species in the coastal waters of China,with a delicious taste,richness in arginine,and high economic value.In recent years,due to the continuous increase of market demand and the increasing of offshore catch,the resources of wild A.fangsiao are gradually becoming exhausted.In order to protect the resources of wild A.fangsiao and meet the market demand,large-scale cultivation of A.fangsiao has become the focus of solving the problem.In invertebrates,innate immunity is the main mechanism that the body performs immune prevention and control.It plays the dual functions of cellular immunity and humoral immunity,which is important for recognizing and killing exogenous invading pathogens.That hemolymph cells can accurately recognize PAMPs(Pathogenassociated molecular patterns in pathogenic microorganisms),such as LPS(Lipopolysaccharide)and Poly I:C(Polyinosinic-polycytidylic acid)to initiate innate immune responses and produce immune responses can resist the invasion of pathogenic microorganisms.That the immune response mechanisms of A.fangsiao hemolymph stimulated by these two PAMPs can help us understand the innate immune response mechanisms of A.fangsiao and even cephalopods,which is of great value for the prevention and control of A.fangsiao aquaculture diseases.At present,transcriptome sequencing and analysis technology has been widely used in immunological research.That using this technology to analyze the RNA expression differences of hemolymph in A.fangsiao under the stimulation of different PAMPs is a convenient method to predict and reveal the functions of differential genes.This process can help identify the key genes and response mechanisms in the immune process.In this research,we conducted transcriptome analysis of hemolymph in A.fangsiao treated with LPS and Poly I:C,followed by WGCNA(weighted gene coexpression network analysis).The hemolymph were collected at 6h and 24 h after LPS stimulation,and 1,312 differentially expressed genes(DEGs)were identified.

关键词： Amphioctopus fangsiao LPS Poly I:C Immune response RNA-seq protein interaction network WGCNA

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