Biochemistry and Biophysics ReportsMolecular BiologyPeer-reviewed journal article
Epitranscriptomic profiling of VSMC phenotypes reveals uridine modifications linked to post-transcriptional regulation
Tobias ReinbergeriD, Ayat IsmailiD, Torben FalkiD, Janina FußiD, Anja Wiechert, Elke HammeriD, Tanja ZelleriD, Inken WohlersiD
Abstract
BackgroundVascular smooth muscle cells (VSMCs) phenotypic plasticity can modulate atherosclerosis progression. Although several gene regulatory steps towards pro-inflammatory phenotypes have been well-studied, epitranscriptomic changes during this transition and their regulatory roles remain unexplored. Methods and ResultsPrimary human VSMCs stimulated with TGF-{beta}1 to induce atheroprotective, contractile, and matrix-producing state and with IL1-{beta} plus PDGF-BB to induce a highly energetic, pro-inflammatory state, confirmed by Illumina bulk RNA sequencing and proteomics. Untargeted screening of mRNA base modifications using Oxford Nanopore Technologies direct RNA sequencing and xPore analysis revealed enhanced uridine modification within a GUUUU motif in pro-inflammatory VSMCs. Modified uridines were enriched in 3-UTR and accessible RNA structures, with implications on Poly(A) tail dynamics and miRNA binding. ConclusionsAtheroprotective and pro-atherogenic treatments induce distinct epitranscriptomic landscapes composed of different modification types, often co-localized in the transcript. Modified uridines in mRNAs are abundant in a high-energy, pro-inflammatory VSMC state and associated with post-transcriptional regulation. n summary, epitranscriptomics adds a novel regulatory layer to VSMC phenotypic transitions critical for atherosclerosis development and progression. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=74 SRC="FIGDIR/small/694735v2_ufig1.gif" ALT="Figure 1"> View larger version (19K): org.highwire.dtl.DTLVardef@933071org.highwire.dtl.DTLVardef@151564borg.highwire.dtl.DTLVardef@f862e9org.highwire.dtl.DTLVardef@125c509_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOGraphic AbstractC_FLOATNO C_FIG
- organism: human
- assay: bulk RNA-seq
- assay: proteomics
- assay: long-read sequencing
- research focus: differential expression
- research focus: gene regulatory network inference
- approach: statistical model
- approach: experimental assay
- Citations
- 0
- FWCI
- 0.00
- Field percentile
- top 34%
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