Comment[ArrayExpressAccession] E-GEOD-25913 Public Release Date 2011-05-01 Investigation Title Gene expression profiling of the classical (CD14++CD16-), intermediate (CD14++CD16+) and nonclassical (CD14+CD16+) human monocyte subsets Comment[Submitted Name] Gene expression profiling of the classical (CD14++CD16-), intermediate (CD14++CD16+) and nonclassical (CD14+CD16+) human monocyte subsets Experiment Description The new official nomenclature subdivides human monocytes into three subsets, classical (CD14++CD16-), intermediate (CD14++CD16+) and nonclassical (CD14+CD16+). Here, we comprehensively define relationships and unique characteristics of the three human monocyte subsets using microarray and flow cytometry analysis. Our analysis revealed that the intermediate and nonclassical monocyte subsets were most closely related. For the intermediate subset, majority of genes and surface markers were expressed at an intermediary level between the classical and nonclassical subset. There features therefore indicate a close and direct lineage relationship between the intermediate and nonclassical subset. From gene expression profiles, we define unique characteristics for each monocyte subset. Classical monocytes were functionally versatile, due to the expression of a wide range of sensing receptors and several members of the AP-1 transcription factor family. The intermediate subset was distinguished by high expression of MHC class II associated genes. The nonclassical subset were most highly differentiated and defined by genes involved in cytoskeleton rearrangement that explains their highly motile patrolling behavior in vivo. Additionally, we identify unique surface markers, CLEC4D, IL-13RA1 for classical, GFRA2, CLEC10A for intermediate and GPR44 for nonclassical. Our study hence defines the fundamental features of monocyte subsets necessary for future research on monocyte heterogeneity. Three human monocyte subsets, the CD14++CD16- classical, the CD14++CD16+ intermediate and CD14+CD16+ nonclassical subsets were purified using fluorescence activated cell sorting from peripheral blood mononuclear cells. RNA was processed from the three monocyte subsets from 4 individual donors in duplicates, giving a total of 24 samples. Date of Experiment Term Source Name EFO Term Source Version Term Source File http://bar.ebi.ac.uk:8080/trac/browser/branches/curator/ExperimentalFactorOntology/ExFactorInOWL/currentrelease/eforelease/efo.owl Person Last Name Wong Wong Tai Yeap Wong Han Kourilsky Wong Person First Name Kok Loon Kok Jing Wei Wing Hao Philippe Siew Person Mid Initials L Y H C C Person Email wong_kok_loon@immunol.a-star.edu.sg Person Affiliation A*STAR Person Phone Person Fax Person Address A*STAR, 8A Biomedical Grove, Biopolis, Singapore, Singapore Person Roles submitter Person Roles Term Source REF Person Roles Term Accession Number Normalization Type Normalization Term Accession Number Normalization Term Source REF Replicate Type Replicate Term Accession Number Replicate Term Source REF Experimental Design Experimental Design Term Accession Number Experimental Design Term Source REF Quality Control Type Quality Control Term Accession Number Quality Control Term Source REF Protocol Name P-GSE25913-1 P-GSE25913-6 P-GSE25913-5 P-GSE25913-2 P-GSE25913-3 P-GSE25913-4 P-GSE25913-7 Protocol Description ID_REF =
VALUE = Quantile and scaling method normalized signal intensity
Detection_Pval = Standard Illumina scanning protocol Standard Illumina hybridization protocol Classical (CD14++CD16-), intermediate (CD14++CD16+) and nonclassical (CD14+CD16+) monocyte subsets purified using fluorescence activated cell sorting based on relative CD14 and CD16 expression RNA was isolated using Trizol extraction followed by Qiagen RNeasy mini kit according to the manufacturer's protocol. RNA quality was confirmed using the Agilent 2100 Bioanalyser. Using Illumina® TotalPrep RNA Amplification Kit according to the manufacturer's protocol. A quantile normalization variant was applied to the duplicates profiles, followed by the scaling method applied across all profiles to equalize medians readings. The data processing software is an in-house developed Matlab code. This method is elaborated in this published report "Wong WC, Loh M, Eisenhaber F. On the necessity of different statistical treatment for Illumina BeadChip and Affymetrix GeneChip data and its significance for biological interpretation. Biol Direct. 2008 Jun 3;3:23." (PMID: 18522715). Protocol Software Protocol Hardware Protocol Contact Protocol Type bioassay_data_transformation image_aquisition hybridization specified_biomaterial_action nucleic_acid_extraction labeling feature_extraction Protocol Term Source REF Protocol Term Accession Number Experimental Factor Name DONOR MONOCYTE SUBSET REP Experimental Factor Type donor monocyte subset rep Experimental Factor Term Source REF Experimental Factor Term Accession Number Publication Title Publication Author List PubMed ID Publication DOI Publication Status Publication Status Term Source REF Publication Status Term Accession Number Comment[SecondaryAccession] GSE25913 Comment[GEOLastUpdateDate] 2011-05-01 Comment[AEExperimentType] transcription profiling by array Comment[GEOReleaseDate] 2011-04-30 Comment[ArrayExpressSubmissionDate] 2010-12-08 SDRF File E-GEOD-25913.sdrf.txt