Biology subjects

Bressin, A.

Publications and source records attributed to Bressin, A..

2 recordsLinked to original sources

bioRxiv2026

ELOF1 is a core component of the promoter-proximal paused RNA polymerase II complex

Metazoan RNA polymerase II is prone to pause in the promoter-proximal region of genes. This pausing involves DRB Sensitivity-Inducing Factor (DSIF) and Negative Elongation Factor (NELF). DSIF and NELF, however, are insufficient to fully reconstitute the degree of promoter-proximal pausing observed in cells. Their negative effects are counteracted by transcription initiation factor TFIIF or by physiological nucleotide concentrations, indicating an additional factor is required. Here, we report that Elongation Factor Homolog 1 (ELOF1) is this missing factor. ELOF1 is enriched in the promoter-proximal region of genes, and its rapid degradation reduces pause duration in cells. In reconstituted assays, ELOF1 potently enhances pausing induced by DSIF and NELF at physiological nucleotide concentrations. Cryo-EM structures reveal that DSIF-NELF-ELOF1 sterically clashes with the position of TFIIF on RNA polymerase II. Accordingly, RNA polymerase II-DSIF-NELF-ELOF1, but not RNA polymerase II-DSIF-NELF, counteracts the positive effects of TFIIF. Our results establish ELOF1 as a core component of promoter-proximal paused RNA polymerase II.

molecular biology↗

bioRxiv2018

TriPepSVM - de novo prediction of RNA-binding proteins based on short amino acid motifs

In recent years hundreds of novel RNA-binding proteins (RBPs) have been identified leading to the discovery of novel RNA-binding domains (RBDs). Furthermore, unstructured or disordered low-complexity regions of RBPs have been identified to play an important role in interactions with nucleic acids. However, these advances in understanding RBPs are limited mainly to eukaryotic species and we only have limited tools to faithfully predict RNA-binders from bacteria. Here, we describe a support vector machine (SVM)-based method, called TriPepSVM, for the classification of RNA-binding proteins and non-RBPs. TriPepSVM applies string kernels to directly handle protein sequences using tri-peptide frequencies. Testing the method in human and bacteria, we find that several RBP-enriched tripeptides occur more often in structurally disordered regions of RBPs. TriPepSVM outperforms existing applications, which consider classical structural features of RNA-binding or homology, in the task of RBP prediction in both human and bacteria. Finally, we predict 66 novel RBPs in Salmonella Typhimurium and validate the bacterial proteins ClpX, DnaJ and UbiG to associate with RNA in vivo.

bioinformatics↗