Biology subjects

Vuidel, A.

Publications and source records attributed to Vuidel, A..

3 recordsLinked to original sources

bioRxiv2023

Pharmacological modulation of developmental and synaptic phenotypes in human SHANK3 deficient stem cell-derived neuronal models

One sentence summaryThis study describes the use of SHANK3 deficient stem cell-derived neuronal models to screen and characterize small molecules that partially rescued developmental and synaptic defects related to Phelan-McDermid syndrome (PMDS). Phelan-McDermid syndrome (PMDS) arises from mutations in the terminal region of chromosome 22q13, impacting the SHANK3 gene. The resulting deficiency of the postsynaptic density scaffolding protein SHANK3 is associated with autism spectrum disorder (ASD). We examined 12 different PMDS patient and CRISPR-engineered stem cell-derived neuronal models and controls and found that reduced expression of SHANK3 leads to neuronal hyperdifferentiation, increased synapse formation, and decreased neuronal activity. We performed automated imaging-based screening of 7,120 target-annotated small molecules and identified three compounds that rescued SHANK3-dependent neuronal hyperdifferentiation. One compound, Benproperine, rescued the decreased colocalization of Actin Related Protein 2/3 Complex Subunit 2 (ARPC2) with {beta}-actin and rescued increased synapse formation in SHANK3 deficient neurons when administered early during differentiation. Neuronal activity was only mildly affected, highlighting Benproperines effects as a neurodevelopmental modulator. This study demonstrates that small molecular compounds that reverse developmental phenotypes can be identified in human neuronal PMDS models.

neuroscience↗

bioRxiv2022

UBAP2L-dependent coupling of PLK1 localization and stability during mitosis

PLK1 is an important regulator of mitosis whose protein levels and activity fluctuate during the cell cycle. PLK1 dynamically localizes to various mitotic structures to regulate chromosome segregation. However, the signaling pathways linking localized PLK1 activity to its protein stability remain elusive. Here, we identify the Ubiquitin-Binding Protein 2-Like (UBAP2L) that controls both, the localization and the protein stability of PLK1.We demonstrate that UBAP2L is a spindle-associated protein whose depletion leads to severe mitotic defects. UBAP2L depleted cells are characterized by increased PLK1 protein levels and abnormal PLK1 accumulation in several mitotic structures such as kinetochores, centrosomes and mitotic spindle. UBAP2L deficient cells exit mitosis and enter the next interphase in the presence of aberrant PLK1 kinase activity. The C-terminal domain of UBAP2L mediates its function on PLK1 independently of its role in stress response signaling. Importantly, the mitotic defects of UBAP2L depleted cells are largely rescued upon chemical inhibition of PLK1. Overall, our data suggest that UBAP2L is required to finetune the ubiquitin-mediated PLK1 turnover during mitosis as a means to maintain genome fidelity.

cell biology↗

bioRxiv2022

Machine learning-aided multidimensional phenotyping of Parkinson's disease patient stem cell-derived midbrain dopaminergic neurons

Combining multiple Parkinsons disease (PD) relevant cellular phenotypes might increase the accuracy of midbrain dopaminergic (mDA) in vitro models. We differentiated patient-derived induced pluripotent stem cells (iPSCs) with a LRRK2 G2019S mutation, isogenic control and genetically unrelated iPSCs into mDA neurons. Using automated fluorescence microscopy in 384-well plate format, we identified elevated levels of -synuclein and Serine 129 phosphorylation (pS129), reduced dendritic complexity, and mitochondrial dysfunction. Next, we measured additional image-based phenotypes and used machine learning (ML) to accurately classify mDA neurons according to their genotype. Additionally, we show that chemical compound treatments, targeting LRRK2 kinase activity or -synuclein levels, are detectable when using ML classification based on multiple image-based phenotypes. We validated our approach using a second isogenic patient derived SNCA gene triplication mDA neuronal model. This phenotyping and classification strategy improves the exploitability of mDA neurons for disease modelling and the identification of novel PD drug targets.

neuroscience↗