Mass spectrometry based proteomics profiling of human monocytes  

作　　者：Yong Zeng Fei-Yan Deng Wei Zhu Lan Zhang Hao He Chao Xu Qing Tian Ji-Gang Zhang Li-Shu Zhang Hong-Gang Hu Hong-Wen Deng 

机构地区：[1]College of Life Sciences and Bioengineering, Beijing Jiaotong University, Beijing 100044, China [2]Center of Bioinformatics and Genomics, Tulane University School of Public Health and Tropical Medicine, New Orleans LA 70112, USA [3]College of Life Sciences, Hunan Normal University, Changsha 410081, China [4]Laboratory of Proteins and Proteomics, Department of Epidemiology, Soochow University School of Public Health, Suzhou 205123, China

出　　处：《Protein & Cell》2017年第2期123-133,共11页蛋白质与细胞（英文版）

基　　金：ACKNOWLEDGEMENTS HW.D., Y.Z. and FY.D. conceived the idea and designed the study. Y. Z., W.Z. and FY.D. performed the experiments to obtain the in vivo data. Y.Z. and HW.D. wrote and revised the paper. All of the authors participated in data analysis. We thank our laboratory members for the collaboration and helpful discussion. We also thank Min-Sik Kim and his collaborators who published and released the in vitro dataset. This study was partially supported by Grants from NIH （Nos. P50AR055091, R01AR057049, R01AR059781, and R01MH1046 80）, and Edward G. Schlieder Endowment. The study also benefited from the grant from the National Natural Science Foundation of China （No. 31371194）.

摘　　要：Human monocyte is an important cell type which is involved in various complex human diseases. To better understand the biology of human monocytes and facilitate further studies, we developed the first comprehensive proteome knowledge base specifically for human monocytes by integrating both in vivo and in vitro datasets. The top 2000 expressed genes from in vitro datasets and 779 genes from in vivo experiments were integrated into this study. Altogether, a total of 2237 unique monocyte-expressed genes were cataloged. Biological functions of these monocyte-expressed genes were annotated and classified via Gene Ontology （GO） analysis. Furthermore, by extracting the overlapped genes from in vivo and in vitro datasets, a core gene list including 541 unique genes was generated. Based on the core gene list, further gene-disease associations, pathway and network analyses were performed. Data analyses based on multiple bioinformatics tools produced a large body of biologically meaningful information, and revealed a number of genes such as SAMHDI, G6PD, GPD2 and EN01, which have been reported to be related to immune response, blood biology, bone remodeling, and cancer respectively. As a unique resource, this study can serve as a reference map for future in-depth research on monocytes biology and monocyte-involved human diseases.Human monocyte is an important cell type which is involved in various complex human diseases. To better understand the biology of human monocytes and facilitate further studies, we developed the first comprehensive proteome knowledge base specifically for human monocytes by integrating both in vivo and in vitro datasets. The top 2000 expressed genes from in vitro datasets and 779 genes from in vivo experiments were integrated into this study. Altogether, a total of 2237 unique monocyte-expressed genes were cataloged. Biological functions of these monocyte-expressed genes were annotated and classified via Gene Ontology （GO） analysis. Furthermore, by extracting the overlapped genes from in vivo and in vitro datasets, a core gene list including 541 unique genes was generated. Based on the core gene list, further gene-disease associations, pathway and network analyses were performed. Data analyses based on multiple bioinformatics tools produced a large body of biologically meaningful information, and revealed a number of genes such as SAMHDI, G6PD, GPD2 and EN01, which have been reported to be related to immune response, blood biology, bone remodeling, and cancer respectively. As a unique resource, this study can serve as a reference map for future in-depth research on monocytes biology and monocyte-involved human diseases.

关 键 词：human monocytes proteomics knowledgebase gene ontology gene-disease association network analysis 

分 类 号：Q51[生物学—生物化学] TS207.4[轻工技术与工程—食品科学]