Biology subjects

Bethune, J.

Publications and source records attributed to Bethune, J..

7 recordsLinked to original sources

bioRxiv2025

Proximity labeling reveals ZFP36L1 as a central hub for post-transcriptional regulation networks in T cells

Effective T cell responses against pathogens require a rapid yet tightly controlled remodeling of the proteome, and RNA binding proteins (RBPs) are key in this process. For instance, the RBP ZFP36L1 prevents excessive protein production and thereby limits immunopathology. ZFP36L1 is primarily known to mediate mRNA decay, but it can also regulate other processes. How its mode of action relates to its interaction partners is, however, not well-understood. Here, we mapped the ZFP36L1 interactome in primary human T cells. Using proximity labeling, we identified known and new interactors that regulate 3UTR-mediated RNA degradation, deadenylation, stress granule/p-body formation, as well as 5UTR-mediated translation repression and mRNA decapping. Snapshot analysis uncovered the ZFP36L1 interactome dynamics and RNA (in)dependency throughout T cell activation. Intriguingly, proximity labeling also uncovered regulators of ZFP36L1 protein expression: This included the helicase UPF1, which not only interacts with ZFP36L1 protein but also promotes its protein expression. Altogether, this comprehensive interactome map underlines the versatility of interactions with ZFP36L1 and their possible role in cellular function.

molecular biology↗

bioRxiv2021

A method to build extended sequence context models of point mutations and indels

The mutation rate of a specific position in the human genome depends on the sequence context surrounding it. Modeling the mutation rate by estimating a rate for each possible k-mer, however, only works for small values of k since the data becomes too sparse for larger values of k. Here we propose a new method that solves this problem by grouping similar k-mers using IUPAC patterns. We refer to the method as k-mer pattern partition and have implemented it in a software package called kmerPaPa. We use a large set of human de novo mutations to show that this new method leads to improved prediction of mutation rates and makes it possible to create models using wider sequence contexts than previous studies. Revealing that for some mutation types, the mutation rate of a position is significantly affected by nucleotides that are up to four base pairs away. As the first method of its kind, it does not only predict rates for point mutations but also indels. We have additionally created a software package called Genovo that, given a k-mer pattern partition model, predicts the expected number of synonymous, missense, and other functional mutation types for each gene. Using this software, we show that the created mutation rate models increase the statistical power to detect genes containing disease-causing variants and to identify genes under strong constraint, e.g. haploinsufficient genes.

bioinformatics↗

bioRxiv2021

ultraID: a compact and efficient enzyme for proximity-dependent biotinylation in living cells

Proximity-dependent biotinylation (PDB) combined with mass spectrometry analysis has established itself as a key technology to study protein-protein interactions in living cells. A widespread approach, BioID, uses an abortive variant of the E. coli BirA biotin protein ligase, a quite bulky enzyme with slow labeling kinetics. To improve PDB versatility and speed, various enzymes have been developed by different approaches. Here we present a novel small-size engineered enzyme: ultraID. We show its practical use to probe the interactome of Argonaute-2 after a 10 min labeling pulse and expression at physiological levels. Moreover, using ultraID, we provide a membrane-associated interactome of coatomer, the coat protein complex of COPI vesicles. To date, ultraID is the smallest and most efficient biotin ligase available for PDB and offers the possibility of investigating interactomes at a high temporal resolution.

biochemistry↗

bioRxiv2020

A paralog-specific role of the COPI pathway in the neuronal differentiation of murine pluripotent cells

Coat protein complex I (COPI)-coated vesicles mediate membrane trafficking between Golgi cisternae as well as retrieval of proteins from the Golgi to the endoplasmic reticulum. There are several flavors of the COPI coat defined by paralogous subunits of the protein complex coatomer. However, whether paralogous COPI proteins have specific functions is currently unknown. Here we show that the paralogous coatomer subunits {gamma}1-COP and {gamma}2-COP are differentially expressed during the neuronal differentiation of mouse pluripotent cells. Moreover, through a combination of genome editing experiments, we demonstrate that whereas {gamma}-COP paralogs are largely functionally redundant, {gamma}1-COP specifically promotes neurite outgrowth. Our work stresses a role of the COPI pathway in neuronal polarization and provides evidence for distinct functions for coatomer paralogous subunits in this process.

cell biology↗

bioRxiv2017

GIGYF2 mediates post-transcriptional mRNA repression through recruitment of the CCR4/NOT complex

Initially identified as a factor involved in tyrosine kinase receptor signalling, GRB10-interacting GYF protein 2 (GIGYF2) has later been shown to interact with the 5 cap-binding protein m4EHP as part of a translation repression complex, and to mediate post-transcriptional repression of tethered reporter mRNAs. We recently observed that GIGYF2 also interacts with the miRNA-induced silencing complex and modulates its translation repression activity. Here we have further investigated how GIGYF2 represses mRNA function. In RNA tethering reporter assays we show that GIGYF2 exerts its action through a combination of translational repression and stimulated mRNA decay. Using truncation variants we identify two distinct effector domains within GIGYF2. In this assay GIGYF2-mediated repression is independent of m4EHP but dependent on the deadenylation activity of the CCR4/NOT complex. We further show that GIGYF2 interacts with multiple subunits of the CCR4/NOT complex and interestingly depletion of the CNOT1 scaffold subunit does not affect GIGYF2-mediated repression. Finally, we identify endogenous mRNA targets of GIGYF2 that recapitulate m4EHP - independent repression. Altogether, we propose that GIGYF2 has two distinct mechanisms of repression: one depends on m4EHP binding and affects translation, the other is m4EHP-independent and relies on the deadenylation activity of the CCR4/NOT complex.

biochemistry↗

bioRxiv2017

SEA: The Small RNA Expression Atlas

We present the Small RNA Expression Atlas (SEA), a web application that allows for the interactive querying, visualization, and analysis of known and novel small RNAs across ten organisms. It contains sRNA and pathogen expression information for over 4,200 published samples with standardized search terms and ontologies. In addition, SEA allows for the interactive visualization and re-analysis of 879 differential expression and 514 classification comparisons. SEAs user model enables sRNA researchers to compare and re-analyze user-specific and published datasets, highlighting common and distinct sRNA expression patterns.\n\nWe provide evidence for SEAs fidelity by (i) generating a set of 591 tissue specific miRNAs across 30 tissues, (ii) finding known and novel bacterial and viral infections across diseases, and (iii) determining a Parkinsons disease-specific blood biomarker signature using novel data.\n\nWe believe that SEAs simple semantic search interface, the flexible interactive reports, and the user model with rich analysis capabilities will enable researchers to better understand the potential function and diagnostic value of sRNAs or pathogens across tissues, diseases, and organisms.\n\nAvailability and ImplementationSEA is implemented in Java, J2EE, spring, Django, html5, css3, JavaScript, Bootstrap, Vue.js, D3, mongodb and neo4j. It is freely available at http://sea.ims.bio/.

bioinformatics↗

bioRxiv2017

Oasis2.0: improved online analysis of small RNA-seq data

Oasis 2 is a new main release of the Oasis web application for the detection, differential expression, and classification of small RNAs in deep sequencing data. Compared to its predecessor Oasis, Oasis 2 features a novel and speed-optimized sRNA detection module that supports the identification of small RNAs in any organism with higher accuracy. Next to the improved detection of small RNAs in a target organism, the software now also recognizes potential cross-species miRNAs and viral and bacterial sRNAs in infected samples. In addition, novel miRNAs can now be queried and visualized interactively, providing essential information for over 700 high-quality miRNA predictions across 14 organisms. Robust biomarker signatures can now be obtained using the novel enhanced classification module. Oasis 2 enables biologists and medical researchers to rapidly analyze and query small RNA deep sequencing data with improved precision, recall, and speed, in an interactive and user-friendly environment.\n\nAvailability and Implementation: Oasis 2 is implemented in Java, J2EE, mysql, Python, R, PHP and JavaScript. It is freely available at http://oasis.dzne.de

bioinformatics↗