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Biology subjects

Pelletier, A.

Publications and source records attributed to Pelletier, A..

2 recordsLinked to original sources

Intrinsic control of muscle attachment sites matching

How a stereotypic muscle pattern is established, and adapted to fit locomotion behaviour is a fascinating question. Here we set up the targeted deletion of cis-regulatory modules (CRMs) controlling the transcription of Drosophila muscle identity transcription factors (iTF) to generate larval muscle identity mutants. By focusing on one muscle transcription and morphology, we show that selection of muscle attachment sites and the precision of muscle/muscle matching is intrinsic to muscle identity. It involves propagation of the iTF expression code from a founder myoblast to the other syncytial nuclei after fusion. Live imaging indicates that the precise staggered muscle attachment pattern involves attraction to tendon cells and homotypic repulsion. Unbalance leads to the formation of abnormal, branched muscles. Single muscle morphology shifts induce subtle locomotor behaviour. Together this work highlights that CRM deletion is an effective setting for creating muscle-specific defects and branched muscles, as new paradigms to study the development of human myopathies affecting subsets of muscles. Highlights- First muscle-identity mutants, via deletion of specific cis-regulatory modules - Reprogramming of syncytial nuclei is key to muscle morphological identity - Selection of muscle attachment sites; attraction and retraction intrinsic to muscle identity - Genetically controlled formation of branched muscles, a new paradigm for functional studies - Single muscle morphology shift induces subtle locomotor behaviour modification

developmental biology

TargetSeeker-MS: A computational method for drug target discovery using protein separation coupled to mass spectrometry

When coupled to mass spectrometry (MS), energetics-based protein separation (EBPS) techniques, such as thermal shift assay, have shown great potential to identify the targets of a drug on a proteome scale. Nevertheless, the computational analyses assessing the confidence of drug target predictions made by these methods have remained rudimentary and significantly differ depending on the protocol used to produce the data. To identify drug targets in datasets produced using different EBPS-MS techniques, we have developed a novel flexible computational approach named TargetSeeker-MS. We showed that TargetSeeker-MS reproducibly identifies known and novel drug targets in C. elegans and HEK293 samples that were treated with the fungicide benomyl and processed using two different EBPS techniques. We also validated a novel benomyl target in vitro. TargetSeeker-MS, which is available online, allows for the confident identification of targets of a drug on a proteome scale, thereby facilitating the evaluation of its clinical viability.

bioinformatics