Please use this identifier to cite or link to this item:
doi:10.22028/D291-35995
Title: | Quantitative and time-resolved miRNA pattern of early human T cell activation |
Author(s): | Diener, Caroline Hart, Martin Kehl, Tim Rheinheimer, Stefanie Ludwig, Nicole Krammes, Lena Pawusch, Sarah Lenhof, Kerstin Tänzer, Tanja Schub, David Sester, Martina Walch-Rückheim, Barbara Keller, Andreas Lenhof, Hans-Peter Meese, Eckart |
Language: | English |
Title: | Nucleic Acids Research |
Volume: | 48 |
Issue: | 18 |
Pages: | 10164–10183 |
Publisher/Platform: | Oxford University Press |
Year of Publication: | 2020 |
DDC notations: | 004 Computer science, internet 610 Medicine and health |
Publikation type: | Journal Article |
Abstract: | T cells are central to the immune response against various pathogens and cancer cells. Complex networks of transcriptional and post-transcriptional regulators, including microRNAs (miRNAs), coordinate the T cell activation process. Available miRNA datasets, however, do not sufficiently dissolve the dynamic changes of miRNA controlled networks upon T cell activation. Here, we established a quantitative and time-resolved expression pattern for the entire miRNome over a period of 24 h upon human Tcell activation. Based on our time-resolved datasets, we identified central miRNAs and specified common miRNA expression profiles. We found the most prominent quantitative expression changes for miR155-5p with a range from initially 40 molecules/cell to 1600 molecules/cell upon T-cell activation. We established a comprehensive dynamic regulatory network of both the up- and downstream regulation of miR155. Upstream, we highlight IRF4 and its complexes with SPI1 and BATF as central for the transcriptional regulation of miR-155. Downstream of miR-155-5p, we verified 17 of its target genes by the time-resolved data recorded after T cell activation. Our data provide comprehensive insights into the range of stimulus induced miRNA abundance changes and lay the ground to identify efficient points of intervention for modifying the T cell response. |
DOI of the first publication: | 10.1093/nar/gkaa788 |
Link to this record: | urn:nbn:de:bsz:291--ds-359955 hdl:20.500.11880/32795 http://dx.doi.org/10.22028/D291-35995 |
ISSN: | 1362-4962 0305-1048 |
Date of registration: | 13-Apr-2022 |
Description of the related object: | Supplementary Data |
Related object: | https://oup.silverchair-cdn.com/oup/backfile/Content_public/Journal/nar/48/18/10.1093_nar_gkaa788/2/gkaa788_supplemental_file.pdf?Expires=1652875503&Signature=ac2Jn3upeF0x5vQJbG7eJWE1YYq2-Q3DmDp-fFeHCXgACJA65-aS14cXLjtGAKDYgd4xKSORo0PNpR5r53FMzNyA7QKJyOLbq07N7LX9qNFcCmueNDvSxiCyymdpQrRqrYP6MB~~0PNl90DJo8Ql8ve8ov6V5Gu7qaNDIBBRumm12kdZ7KHTzsppdOWwB-8CF0sE5goiWynT7HGCca0cy8~ppDkI6CSJfkjKFNUOpxBoRhQGQeKISuUk-5fEYMz3F7eNGj8TM42TrE64Ol1ycAXPlU35kNnP763dxSZr8~kTOTmhFJlk9-rTTiStDN58zZZxrtvtCAt-T~lWO3M5Rw__&Key-Pair-Id=APKAIE5G5CRDK6RD3PGA |
Faculty: | M - Medizinische Fakultät MI - Fakultät für Mathematik und Informatik |
Department: | M - Humangenetik M - Infektionsmedizin M - Medizinische Biometrie, Epidemiologie und medizinische Informatik MI - Informatik |
Professorship: | M - Univ.-Prof. Dr. Andreas Keller M - Prof. Dr. Eckhart Meese M - Prof. Dr. Martina Sester MI - Prof. Dr. Hans-Peter Lenhof |
Collections: | SciDok - Der Wissenschaftsserver der Universität des Saarlandes |
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gkaa788.pdf | 6,72 MB | Adobe PDF | View/Open |
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