Neurophysiological treatment effects of mesdopetam, pimavanserin and clozapine in a rodent model of Parkinson's disease psychosis.

Psychosis in Parkinson's disease is a common phenomenon associated with poor outcomes. To clarify the pathophysiology of this condition and the mechanisms of antipsychotic treatments, we have here characterized the neurophysiological brain states induced by clozapine, pimavanserin, and the novel prospective antipsychotic mesdopetam in a rodent model of Parkinson's disease psychosis, based on chronic dopaminergic denervation by 6-OHDA lesions, levodopa priming, and the acute administration of an NMDA antagonist. Parallel recordings of local field potentials from eleven cortical and sub-cortical regions revealed shared neurophysiological treatment effects for the three compounds, despite their different pharmacological profiles, involving reversal of features associated with the psychotomimetic state, such as a reduction of aberrant high-frequency oscillations in prefrontal structures together with a decrease of abnormal synchronization between different brain regions. Other drug-induced neurophysiological features were more specific to each treatment, affecting network oscillation frequencies and entropy, pointing to discrete differences in mechanisms of action. These findings indicate that neurophysiological characterization of brain states is particularly informative when evaluating therapeutic mechanisms in conditions involving symptoms that are difficult to assess in rodents such as psychosis, and that mesdopetam should be further explored as a potential novel antipsychotic treatment option for Parkinson psychosis.

Verification of multi-structure targeting in chronic microelectrode brain recordings from CT scans.

BACKGROUND: Large-scale microelectrode recordings offer a unique opportunity to study neurophysiological processes at the network level with single cell resolution. However, in the small brains of many experimental animals, it is often technically challenging to verify the correct targeting of the intended structures, which inherently limits the reproducibility of acquired data. NEW METHOD: To mitigate this problem, we have developed a method to programmatically segment the trajectory of electrodes arranged in larger arrays from acquired CT-images and thereby determine the position of individual recording tips with high spatial resolution, while also allowing for coregistration with an anatomical atlas, without pre-processing of the animal samples or post-imaging histological analyses. RESULTS: Testing the technical limitations of the developed method, we found that the choice of scanning angle influences the achievable spatial resolution due to shadowing effects caused by the electrodes. However, under optimal acquisition conditions, individual electrode tip locations within arrays with 250 µm inter-electrode spacing were possible to reliably determine. COMPARISON TO EXISTING METHODS: Comparison to a histological verification method suggested that, under conditions where individual wires are possible to track in slices, a 90% correspondence could be achieved in terms of the number of electrodes groups that could be reliably assigned to the same anatomical structure. CONCLUSIONS: The herein reported semi-automated procedure to verify anatomical targeting of brain structures in the rodent brain could help increasing the quality and reproducibility of acquired neurophysiological data by reducing the risk of assigning recorded brain activity to incorrectly identified anatomical locations. DATA AVAILABILITY: The tools developed in this study are freely available as a software package at: https://github.com/NRC-Lund/ct-tools.

Effect of FKBP12-Derived Intracellular Peptides on Rapamycin-Induced FKBP-FRB Interaction and Autophagy.

Intracellular peptides (InPeps) generated by proteasomes were previously suggested as putative natural regulators of protein-protein interactions (PPI). Here, the main aim was to investigate the intracellular effects of intracellular peptide VFDVELL (VFD7) and related peptides on PPI. The internalization of the peptides was achieved using a C-terminus covalently bound cell-penetrating peptide (cpp; YGRKKRRQRRR). The possible inhibition of PPI was investigated using a NanoBiT® luciferase structural complementation reporter system, with a pair of plasmids vectors each encoding, simultaneously, either FK506-binding protein (FKBP) or FKBP-binding domain (FRB) of mechanistic target of rapamycin complex 1 (mTORC1). The interaction of FKBP-FRB within cells occurs under rapamycin induction. Results shown that rapamycin-induced interaction between FKBP-FRB within human embryonic kidney 293 (HEK293) cells was inhibited by VFD7-cpp (10-500 nM) and FDVELLYGRKKRRQRRR (VFD6-cpp; 1-500 nM); additional VFD7-cpp derivatives were either less or not effective in inhibiting FKBP-FRB interaction induced by rapamycin. Molecular dynamics simulations suggested that selected peptides, such as VFD7-cpp, VFD6-cpp, VFAVELLYGRKKKRRQRRR (VFA7-cpp), and VFEVELLYGRKKKRRQRRR (VFA7-cpp), bind to FKBP and to FRB protein surfaces. However, only VFD7-cpp and VFD6-cpp induced changes on FKBP structure, which could help with understanding their mechanism of PPI inhibition. InPeps extracted from HEK293 cells were found mainly associated with macromolecular components (i.e., proteins and/or nucleic acids), contributing to understanding InPeps' intracellular proteolytic stability and mechanism of action-inhibiting PPI within cells. In a model of cell death induced by hypoxia-reoxygenation, VFD6-cpp (1 µM) increased the viability of mouse embryonic fibroblasts cells (MEF) expressing mTORC1-regulated autophagy-related gene 5 (Atg5), but not in autophagy-deficient MEF cells lacking the expression of Atg5. These data suggest that VFD6-cpp could have therapeutic applications reducing undesired side effects of rapamycin long-term treatments. In summary, the present report provides further evidence that InPeps have biological significance and could be valuable tools for the rational design of therapeutic molecules targeting intracellular PPI.

Differential effects of skilled reaching training on the temporal and spatial organization of somatosensory input to cortical and striatal motor circuits.

It has been hypothesized that to perform sensorimotor transformations efficiently, somatosensory information being fed back to a particular motor circuit is organized in accordance with the mechanical loading patterns of the skin that result from the motor activity generated by that circuit. Rearrangements of sensory information to different motor circuits could in this respect constitute a key component of sensorimotor learning. We here explored whether the organization of tactile input from the plantar forepaw of the rat to cortical and striatal circuits is affected by a period of extensive sensorimotor training in a skilled reaching and grasping task. Our data show that the representation of tactile stimuli in terms of both temporal and spatial response patterns changes as a consequence of the training and that spatial changes particularly involve the primary motor cortex. Based on the observed reorganization, we propose that reshaping of the spatiotemporal representation of the tactile afference to motor circuits is an integral component of the learning process that underlies skill acquisition in reaching and grasping.NEW & NOTEWORTHY Sensorimotor transformations are fundamental to the function of the nervous system and determine how patterns of sensory input are converted into appropriate movements. We here investigated the extent to which experience-dependent processes can reshape the organization of somatosensory input feeding into cortico-basal ganglia motor structures. Our data point to a particularly important role for the primary motor cortex in the functional adaptions associated with skilled motor learning.

Prediction of kinetics of protein folding with non-redundant contact information.

Motivation: The majority of the inter-residue distances in a protein structure are correlated given a fixed topology. Here, we investigate whether we are able to predict a structure's folding rate, which is known to depend on the complexity of its fold, while considering only a small, uncorrelated fraction of its contacts. Results: We define an expression for the probabilistic information content associated to the relative position of a pair of amino acid residues in a protein structure. By means of fitting the protein chain to a self-avoiding random walk model, we derive a probability distribution for the distance between residues as a function of their separation along the sequence. We then show that the average information content for all residue pairs in a structure, considered as an estimate of its fold's complexity, is well correlated to the logarithm of its folding rate. Moreover, the same information content measure may be exploited to rank contacts and identify redundancies, allowing the prediction the structure's folding rate with similar accuracy while taking into account less than 5% of its contacts. Availability and implementation: An implementation of the described model and the experimental data are available at http://github.com/luciano-censoni/sarw-lnkf.

A network model predicts the intensity of residue-protein thermal coupling.

MOTIVATION: The flow of vibrational energy in proteins has been shown not to obey expectations for isotropic media. The existence of preferential pathways for energy transport, with probable connections to allostery mechanisms, has been repeatedly demonstrated. Here, we investigate whether, by representing a set of protein structures as networks of interacting amino acid residues, we are able to model heat diffusion and predict residue-protein vibrational couplings, as measured by the Anisotropic Thermal Diffusion (ATD) computational protocol of modified molecular dynamics simulations. RESULTS: We revisit the structural rationales for the precise definition of a contact between amino acid residues. Using this definition to describe a set of proteins as contact networks where each node corresponds to a residue, we show that node centrality, particularly closeness centrality and eigenvector centrality , correlates to the strength of the vibrational coupling of each residue to the rest of the structure. We then construct an analytically solvable model of heat diffusion on a network, whose solution incorporates an explicit dependence on the connectivity of the heated node, as described by a perturbed graph Laplacian Matrix. AVAILABILITY AND IMPLEMENTATION: An implementation of the described model is available at http://leandro.iqm.unicamp.br/atd-scripts . CONTACT: leandro@iqm.unicamp.br.