Biology subjects

Meijer, D. H.

Publications and source records attributed to Meijer, D. H..

3 recordsLinked to original sources

bioRxiv2025

A teneurin-3 microphthalmia mutation disrupts trans adhesion for specific alternative splicing isoforms

Microphthalmia (MCOP) is a developmental eye disorder in which one or both eyes are abnormally small. This condition is often accompanied by cognitive impairments. Teneurin-3, a cell adhesion molecule with important functions in axon pathfinding and synaptic organization, has been repeatedly implicated with MCOP, suggesting its potential role in the etiology of this complex developmental disorder. It was previously shown that two small alternatively spliced exons - inserts A and B - instigate large structural reorganizations of the teneurin-3 covalent homodimer. Here, we map the MCOP mutation R2579W to an intramolecular interface specific to splice insert A-containing isoforms. We demonstrate that the MCOP mutation leads to a loss of transcellular adhesion, predominantly affecting these isoforms. Using small-angle X-ray scattering we establish that, despite these functional disruptions, the structural compactness of all mutant isoforms is preserved. Molecular dynamics simulations predict a global stabilization of the A1 mutant molecule compared to its wildtype counterpart, due to changes in local compact dimer interactions around the mutated residue. We experimentally validate these findings with biophysical assays. With cryo-EM analysis, we confirm the overall compactness with reduced conformational flexibility and reveal that the mutant tryptophan binds to a hydrophobic pocket in the structure. With these data, we provide a model for how increased stability in cis disrupts trans oligomerization needed for cellular adhesion. Altogether, we demonstrate that the MCOP-associated mutation in teneurin-3 causally disrupts cellular adhesion in an isoform-specific manner, thereby likely directly contributing to the development of the disease in MCOP patients.

molecular biology↗

bioRxiv2024

autoMEA: Machine learning-based burst detection for multi-electrode array datasets

Neuronal activity in the highly organized networks of the central nervous system is the vital basis for various functional processes, such as perception, motor control, and cognition. Understanding interneuronal connectivity and how activity is regulated in the neuronal circuits is crucial for interpreting how the brain works. Multi-electrode arrays (MEAs) are particularly useful for studying the dynamics of neuronal network activity and their development as they allow for real-time, high-throughput measurements of neural activity. At present, the key challenge in the utilization of MEA data is the sheer complexity of the measured datasets. Available software offers semi-automated analysis for a fixed set of parameters that allow for the definition of spikes and bursts. However, this analysis remains time-consuming, user-biased, and limited by pre-defined parameters. Here, we present autoMEA, software for machine learning-based automated burst detection in MEA datasets. We exemplify autoMEA efficacy on neuronal network activity of primary hippocampal neurons from wild-type mice monitored using 24-well multiwell MEA plates. To validate and benchmark the software, we showcase its application using wild-type neuronal networks and two different neuronal networks modeling neurodevelopmental disorders to assess network phenotype detection. Detection of network characteristics typically reported in literature, such as synchronicity and rhythmicity, could be accurately detected compared to manual analysis using the autoMEA software. Additionally, autoMEA could detect reverberations, a more complex burst dynamic present in hippocampal cultures. Furthermore, autoMEA burst detection was sufficiently sensitive to detect changes in the synchronicity and rhythmicity of networks modeling neurodevelopmental disorders as well as detecting changes in their burst dynamics. Thus, we show that autoMEA reliably analyses neural networks measured with the multi-well MEA setup with the precision and accuracy compared to that of a human expert.

neuroscience↗

bioRxiv2023

Alternative splicing controls teneurin-3 compact dimer formation for neuronalrecognition

Neuronal network formation is facilitated by recognition between synaptic cell adhesion molecules (CAMs) at the cell surface. Alternative splicing of CAMs provides additional specificity in forming neuronal connections. For the teneurin family of CAMs, alternative splicing of the EGF-repeats and NHL domain controls protein-protein interactions at the synapse. Here we present a 3.2 [A] cryo-EM structure of the compact dimeric ectodomain of teneurin-3 harbouring both splice inserts. This dimer is stabilised by an EGF8-ABD contact between subunits. Cryo-EM reconstructions of all four splice variants, together with SAXS and negative stain EM, reveal compacted dimers for each, with variant-specific dimeric arrangements. This results in specific trans-cellular interactions, as tested in cell clustering and stripe assays. The compact conformations provide a structural basis for teneurin homo- and heterophilic interactions. Altogether, our findings demonstrate how alternative splicing results in rearrangements of the dimeric subunits, influencing neuronal recognition and circuit wiring.

biochemistry↗