Hooper, P. J. | Search bioRxiv

bioRxiv2024

Graphene microelectrode arrays, 4D structured illumination microscopy, and a machine learning-based spike sorting algorithm permit the analysis of ultrastructural neuronal changes during neuronal signalling in a model of Niemann-Pick disease type C

Simultaneously recording network activity and ultrastructural changes of the synapse is essential for advancing our understanding of the basis of neuronal functions. However, the rapid millisecond-scale fluctuations in neuronal activity and the subtle sub-diffraction resolution changes of synaptic morphology pose significant challenges to this endeavour. Here, we use graphene microelectrode arrays (G-MEAs) to address these challenges, as they are compatible with high spatial resolution imaging across various scales as well as high temporal resolution electrophysiological recordings. Furthermore, alongside G-MEAs, we deploy an easy-to-implement machine learning-based algorithm to efficiently process the large datasets collected from MEA recordings. We demonstrate that the combined use of G-MEAs, machine learning (ML)-based spike analysis, and four-dimensional (4D) structured illumination microscopy (SIM) enables the monitoring of the impact of disease progression on hippocampal neurons which have been treated with an intracellular cholesterol transport inhibitor mimicking Niemann-Pick disease type C (NPC) and show that synaptic boutons, compared to untreated controls, significantly increase in size, which leads to a loss in neuronal signalling capacity.

neuroscience↗

bioRxiv2019

Extent of N-terminus exposure by altered long-range interactions of monomeric alpha-synuclein determines its aggregation propensity

As an intrinsically disordered protein, monomeric alpha synuclein (aSyn) constantly reconfigures and probes the conformational space. Long-range interactions across the protein maintain its solubility and mediate this dynamic flexibility, but also provide residual structure. Certain conformations lead to aggregation prone and non-aggregation prone intermediates, but identifying these within the dynamic ensemble of monomeric conformations is difficult. Herein, we used the biologically relevant calcium ion to investigate the conformation of monomeric aSyn in relation to its aggregation propensity. By using calcium to perturb the conformational ensemble, we observe differences in structure and intra-molecular dynamics between two aSyn C-terminal variants, D121A and pS129, and the aSyn familial disease mutants, A30P, E46K, H50Q, G51D, A53T and A53E, compared to wild-type (WT) aSyn. We observe that the more exposed the N-terminus and the beginning of the NAC region are, the more aggregation prone monomeric aSyn conformations become. N-terminus exposure occurs upon release of C-terminus interactions when calcium binds, but the level of exposure is specific to the aSyn mutation present. There was no correlation between single charge alterations, calcium affinity, or the number of ions bound on aSyns aggregation propensity, indicating that sequence or post-translation modification (PTM)-specific conformational differences between the N- and C-termini and the specific local environment mediate aggregation propensity instead. Understanding aggregation prone conformations of monomeric aSyn and the environmental conditions they form under will allow us to design new therapeutics targeted to the monomeric protein, to stabilise aSyn in non-aggregation prone conformations, by either preserving long-range interactions between the N- and C-termini or by protecting the N-terminus from exposure.

biophysics↗