Dataset Information

Mass spectrometry based proteomics profiling of human monocytes.

ABSTRACT: 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 SAMHD1, G6PD, GPD2 and ENO1, 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.

SUBMITTER: Zeng Y

PROVIDER: S-EPMC5291777 | biostudies-literature | 2017 Feb

REPOSITORIES: biostudies-literature

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Mass spectrometry based proteomics profiling of human monocytes.

Zeng Yong Y Deng Fei-Yan FY Zhu Wei W Zhang Lan L He Hao H Xu Chao C Tian Qing Q Zhang Ji-Gang JG Zhang Li-Shu LS Hu Hong-Gang HG Deng Hong-Wen HW

Protein & cell 20161122 2

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 ...[more]

PMID: 27878450

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Project description:Malaria is a mosquito borne infectious disease caused by protozoa of genus Plasmodium. There are five species of Plasmodium that are found to infect humans. Plasmodium falciparum can cause severe malaria leading to higher morbidity and mortality of malaria than the other four species. Antimalarial resistance is the major obstacle to control malaria. Mefloquine was used in combination with Artesunate for uncomplicated P. falciparum in South East Asia and it has developed and established mefloquine resistance in this region. Here, gel-enhanced liquid chromatography/tandem mass spectrometry (GeLC-MS/MS)-based proteomics and label-free quantification were used to explore the protein profiles of mefloquine-sensitive and -induced resistant P. falciparum. A Thai P. falciparum isolate (S066) was used as a model in this research. Our data revealed for the first time that 69 proteins exhibited at least 2-fold differences in their expression levels between the two parasite lines. Of these, 36 were up-regulated and 33 were down-regulated in the mefloquine-resistant line compared with the mefloquine-sensitive line. These findings are consistent with those of past studies, where the multidrug resistance protein Pgh1 showed an up-regulation pattern consistent with that expected from its average 3-copy pfmdr1 gene number. Pgh1 and eight other up-regulated proteins (i.e., histo-aspartyl protease protein, exportin 1, eukaryotic translation initiation factor 3 subunit 8, peptidyl-prolyl cis-trans isomerase, serine rich protein homologue, exported protein 1, ATP synthase beta chain and phospholipid scramblase 1) were further validated for their expression levels using reverse transcriptase quantitative real-time PCR. The data support the up-regulation status in the mefloquine-resistant parasite line of all the candidate genes referred to above. Therefore, GeLC-MS/MS-based proteomics combined with label-free quantification is a reliable approach for exploring mefloquine resistance biomarkers in P. falciparum. Identification of these proteins leads to better understanding of mefloquine resistant mechanisms in malaria parasites.

Dataset Information

Mass spectrometry based proteomics profiling of human monocytes.

Publications

Mass spectrometry based proteomics profiling of human monocytes.

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