Biology subjects

Cailleret, M.

Publications and source records attributed to Cailleret, M..

3 recordsLinked to original sources

bioRxiv2025

Integrative Analysis of Drug-Gene Expression Signatures in Human Pluripotent Stem Cells Identifies Novel Drug Candidates for ALS and Monogenic Diseases

The classical paradigm of drug screening often faces significant limitations due to the challenges associated with identifying molecular or cellular read-outs that are relevant to specific diseases. This issue is particularly pronounced for the thousands of diseases of genetic origin, given the abundance of databases listing disease-associated changes in gene expression and various transcripts, indicating that potential read-outs may be concealed within these resources. To remedy this, an alternative approach was tested: compounds were evaluated for their effects on gene expression and alternative splicing in a healthy cell model, and the resulting data were matched to molecular signatures of diseases. A subset of 50 FDA-approved drugs was tested on mesenchymal stem cells derived from a human pluripotent stem cell line. Over half of the compounds altered gene expression, many affecting pathways linked to monogenic diseases. One hit, increased SQSTM1 expression induced by prazosin, was further validated in ALS models caused by SQSTM1 haploinsufficiency, including patient-derived fibroblasts, SQSTM1-depleted hiPSC-derived motor neurons, and a zebrafish model. Extending this paradigm could involve testing diverse cell types and larger drug libraries. One Sentence SummaryA novel drug screening approach for monogenic diseases integrating human pluripotent stem cell derivatives and RNA sequencing to profile gene expression.

genomics↗

bioRxiv2024

Alternative splicing of SORBS1 affects neuromuscular junction formation and stability in myotonic dystrophy type 1

Myotonic dystrophy type 1 (DM1) is a multisystemic neuromuscular disease characterized by a CTG repeat expansion in the 3" untranslated region of the gene coding for the dystrophia myotonica protein kinase (DMPK). Presence of expanded CTG repeats in DMPK-mRNAs leads to the sequestration of RNA binding factors such as the Muscleblind like (MBNL) proteins resulting in widespread splicing defects contributing to progressive muscle weakness and myotonia. Here, we show that abnormal splicing of SORBS1 exon 25 found in skeletal muscle of myotonic dystrophy type 1 patients is a critical contributor to neuromuscular junction (NMJ) formation and maintenance. Forced exclusion of SORBS1 exon 25 in mice results in NMJ degeneration with marked denervation and postsynaptic destabilization. In zebrafish, misregulation of sorbs1 exon 25 results in reduced motor function and abnormal AChR cluster morphology. Finally, we observed that forcing SORBS1 exon 25 exclusion in hiPSC-derived skeletal muscle cells reduces the formation of large AChR clusters upon agrin stimulation. Thus, our study identifies MBNL regulated SORBS1 alternative splicing during skeletal muscle development as a critical event for NMJ formation and maintenance. The aberrant splicing of SORBS1 exon 25 in DM1 expands our understanding of how splicing dysregulation compromises neuromuscular system communication, shedding light on the broader impact of mRNA splicing regulation on NMJ integrity.

molecular biology↗

bioRxiv2020

Beyond forest succession: a gap model to study ecosystem functioning and tree community composition under climate change

Climate change impacts forest functioning and dynamics, and large uncertainties remain regarding the interactions between species composition, demographic processes, and environmental drivers. There are few robust tools available to link these processes, which precludes accurate projections and recommendations for long-term forest management. Forest gap-models present a balance between complexity and generality and are widely used in predictive forest ecology. However, their relevance to tackle questions about the links between species composition, climate and forest functioning is unclear. In this regard, demonstrating the ability of gap-models to predict the growth of forest stands at the annual time scale - representing a sensitive and integrated signal of tree functioning and mortality risk - appears as a fundamental step. In this study, we aimed at assessing the ability of a gap-model to accurately predict forest growth in the short-term and potential community composition in the long-term, across a wide range of species and environmental conditions. To do so, we present the gap-model ForCEEPS, calibrated using an original parameterization procedure for the main tree species in France. ForCEEPS was shown to satisfactorily predict forest annual growth (averaged over a few years) at the plot level from mountain to Mediterranean climates, regardless the species. Such an accuracy was not gained at the cost of losing precision for long-term predictions, as the model showed a strong ability to predict potential community composition along a gradient of sites with contrasted conditions. The mechanistic relevance of ForCEEPS parameterization was explored by showing the congruence between the values of key model parameter and species functional traits. We further showed that accounting for the spatial configuration of crowns within forest stands, the effects of climatic constraints and the variability of shade tolerances in the species community are all crucial to better predict short-term productivity with gap-models. The dual ability of predicting short-term functioning and long-term community composition, as well as the balance between generality and realism (i.e., predicting accuracy) of the new generation of gap-models may open great perspectives for the exploration of the biodiversity-ecosystem functioning relationships, species coexistence mechanisms, and the impacts of climate change on forest ecosystems.

ecology↗