GEO Logo
   NCBI > GEO > Accession DisplayHelp Not logged in | LoginHelp
GEO help: Mouse over screen elements for information.
Series GSE118974 Query DataSets for GSE118974
Status Public on Dec 14, 2018
Title Quantitative mass spectrometry-based proteomics reveals the dynamic protein landscape during initiation of human Th17 cell polarization
Organism Homo sapiens
Experiment type Expression profiling by high throughput sequencing
Summary CD4+ T cells play a key role in the adaptive immune system. Their subset, Th17 cells contribute to pathogenesis of inflammatory and autoimmune diseases and cancer. To reveal the Th17 cell-specific proteomic signature regulating Th17 cell differentiation and function in human we used a label-free mass spectrometry-based approach. To determine the degree of similarities and differences between the transcript and the protein levels, we performed a comprehensive analysis of the transcript-protein relationships. Comparison of the proteomics and RNA-sequencing data generated in this study during human Th17 differentiation revealed a high degree of overlap between the datasets. However, we found very limited overlap between the proteins differentially regulated in response to Th17 differentiation in human and mouse. Of the 758 and 397 proteins differentially regulated at 72h during Th17 specification in human and in mouse, respectively, only 33 were detected as differentially regulated in a similar fashion in both species. We validated a panel of selected proteins with known and unknown functions. Finally, using RNA interference (RNAi), we showed that SATB1 negatively regulates of human Th17 cell differentiation. To our knowledge, this study is the first to illustrate a comprehensive picture of the global protein landscape during early human Th17 cell differentiation. Poor overlap with recently reported mouse data underlines the importance of human studies for translational research.
Overall design In this study, the proteomic landscape of differentiating Th17 cells were compared to those of naive CD4+ T cells (Thp) and to those of only TCR-activated T cells (Th0) at 24 and 72h during Th17 polarization. Furthermore, transcriptomic analysis of Th17 and Th0 cells was performed at 72h post initiation of polarization and compared to the proteomic findings of the same timepoint. Finally, the proteomic dataset between Th17 and Th0 at 72h were compared to a mouse dataset (Mohammad, I., Nousiainen, K., Bhosale, S.D., Starskaia, I., Moulder, R., Rokka, A., Cheng, F., Mohanasundaram, P., Eriksson, J.E., Goodlett, D.R., et al. (2018). Quantitative proteomic characterization and comparison of T helper 17 and induced regulatory T cells. PLoS Biol. 2018 May 31;16(5):e2004194).
Contributor(s) Tripathi SK, Välikangas T, Shetty A, Khan MM, Bhosale SD, Moulder R, Komsi E, Salo V, De Albuquerque RS, Rasool O, Galande S, Elo LE, Lahesmaa R
Citation(s) 30641411
Submission date Aug 23, 2018
Last update date Feb 20, 2019
Contact name Tommi Välikangas
Organization name University of Turku
Department Turku Centre for Biotechnology
Lab Medical Bioinformatics Centre
Street address Huhkonmaantie 26 as.11
City Turku
ZIP/Postal code 20380
Country Finland
Platforms (1)
GPL21290 Illumina HiSeq 3000 (Homo sapiens)
Samples (10)
GSM3355215 180036_MK198_1_Th0_D1_S81_L005_R1_001
GSM3355216 180036_MK198_1_Th0_D2_S81_L005_R1_001
GSM3355217 180036_MK198_1_Th0_D3_S81_L005_R1_001
BioProject PRJNA487597
SRA SRP158686

Download family Format
SOFT formatted family file(s) SOFTHelp
MINiML formatted family file(s) MINiMLHelp
Series Matrix File(s) TXTHelp

Supplementary file Size Download File type/resource
GSE118974_RAW.tar 25.5 Mb (http)(custom) TAR (of TXT)
GSE118974_Th0_Th17_RNASeq_72h_Processed_Data.csv.gz 997.9 Kb (ftp)(http) CSV
SRA Run SelectorHelp
Raw data are available in SRA
Processed data provided as supplementary file
Processed data are available on Series record

| NLM | NIH | GEO Help | Disclaimer | Accessibility |
NCBI Home NCBI Search NCBI SiteMap