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GEO help: Mouse over screen elements for information. |
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| 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
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| 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.
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| 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).
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| 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 |
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| Submission date |
Aug 23, 2018 |
| Last update date |
Feb 20, 2019 |
| Contact name |
Tommi Välikangas |
| E-mail(s) |
tsvali@utu.fi
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| Organization name |
University of Turku
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| Department |
Turku Centre for Biotechnology
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| Lab |
Medical Bioinformatics Centre
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| Street address |
Huhkonmaantie 26 as.11
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| City |
Turku |
| ZIP/Postal code |
20380 |
| Country |
Finland |
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| Platforms (1) |
| GPL21290 |
Illumina HiSeq 3000 (Homo sapiens) |
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| Samples (10)
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| Relations |
| BioProject |
PRJNA487597 |
| SRA |
SRP158686 |
| 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 Selector |
| Raw data are available in SRA |
| Processed data provided as supplementary file |
| Processed data are available on Series record |
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