Regulation of Zbp1 by miR-99b-5p in microglia controls the development of schizophrenia-like symptoms in mice.

Current approaches to the treatment of schizophrenia have mainly focused on the protein-coding part of the genome; in this context, the roles of microRNAs have received less attention. In the present study, we analyze the microRNAome in the blood and postmortem brains of schizophrenia patients, showing that the expression of miR-99b-5p is downregulated in both the prefrontal cortex and blood of patients. Lowering the amount of miR-99b-5p in mice leads to both schizophrenia-like phenotypes and inflammatory processes that are linked to synaptic pruning in microglia. The microglial miR-99b-5p-supressed inflammatory response requires Z-DNA binding protein 1 (Zbp1), which we identify as a novel miR-99b-5p target. Antisense oligonucleotides against Zbp1 ameliorate the pathological effects of miR-99b-5p inhibition. Our findings indicate that a novel miR-99b-5p-Zbp1 pathway in microglia might contribute to the pathogenesis of schizophrenia.

Postnatal expression of the lysine methyltransferase SETD1B is essential for learning and the regulation of neuron-enriched genes.

In mammals, histone 3 lysine 4 methylation (H3K4me) is mediated by six different lysine methyltransferases. Among these enzymes, SETD1B (SET domain containing 1b) has been linked to syndromic intellectual disability in human subjects, but its role in the mammalian postnatal brain has not been studied yet. Here, we employ mice deficient for Setd1b in excitatory neurons of the postnatal forebrain, and combine neuron-specific ChIP-seq and RNA-seq approaches to elucidate its role in neuronal gene expression. We observe that Setd1b controls the expression of a set of genes with a broad H3K4me3 peak at their promoters, enriched for neuron-specific genes linked to learning and memory function. Comparative analyses in mice with conditional deletion of Kmt2a and Kmt2b histone methyltransferases show that SETD1B plays a more pronounced and potent role in regulating such genes. Moreover, postnatal loss of Setd1b leads to severe learning impairment, suggesting that SETD1B-dependent regulation of H3K4me levels in postnatal neurons is critical for cognitive function.

Protein-RNA interactions: structural characteristics and hotspot amino acids.

Structural information about protein-RNA complexes supports the understanding of crucial recognition processes in the cell, and it can allow the development of high affinity ligands to interfere with these processes. In this respect, the identification of amino acid hotspots is particularly important. In contrast to protein-protein interactions, in silico approaches for protein-RNA interactions lag behind in their development. Herein, we report an analysis of available protein-RNA structures. We assembled a data set of 322 crystal and NMR structures and analyzed them regarding interface properties. In addition, we describe a computational alanine-scanning approach which provides interaction scores for interface amino acids, allowing the identification of potential hotspots in protein-RNA interfaces. We have made the computational approach available as an online tool, which allows interaction scores to be calculated for any structure of a protein-RNA complex by uploading atomic coordinates to the PRI HotScore web server (https://pri-hotscore.labs.vu.nl).

Spatiotemporal imaging of small GTPases activity in live cells.

Ras-like small GTPases function as molecular switches and regulate diverse cellular events. To examine the dynamics of signaling requires spatiotemporal visualization of their activity in the cell. Current small GTPase sensors rely on specific effector domains that are available for only a small number of GTPases and compete for endogenous regulator/effector binding. Here, we describe versatile conformational sensors for GTPase activity (COSGAs) based on the conserved GTPase fold. Conformational changes upon GDP/GTP exchange were directly observed in solution, on beads, and in live cells by Förster resonance energy transfer (FRET). The COSGAs allow for monitoring of Rab1 and K-Ras activity in live cells using fluorescence lifetime imaging microscopy. We found that Rab1 is largely active in the cytoplasm and inactive at the Golgi, suggesting that the Golgi serves as the terminal of the Rab1 functional cycle. K-Ras displays polarized activity at the plasma membrane, with less activity at the edge of the cell and membrane ruffles.

Active Site Hydrophobicity and the Convergent Evolution of Paraoxonase Activity in Structurally Divergent Enzymes: The Case of Serum Paraoxonase 1.

Serum paraoxonase 1 (PON1) is a native lactonase capable of promiscuously hydrolyzing a broad range of substrates, including organophosphates, esters, and carbonates. Structurally, PON1 is a six-bladed ß-propeller with a flexible loop (residues 70-81) covering the active site. This loop contains a functionally critical Tyr at position 71. We have performed detailed experimental and computational analyses of the role of selected Y71 variants in the active site stability and catalytic activity in order to probe the role of Y71 in PON1's lactonase and organophosphatase activities. We demonstrate that the impact of Y71 substitutions on PON1's lactonase activity is minimal, whereas the kcat for the paraoxonase activity is negatively perturbed by up to 100-fold, suggesting greater mutational robustness of the native activity. Additionally, while these substitutions modulate PON1's active site shape, volume, and loop flexibility, their largest effect is in altering the solvent accessibility of the active site by expanding the active site volume, allowing additional water molecules to enter. This effect is markedly more pronounced in the organophosphatase activity than the lactonase activity. Finally, a detailed comparison of PON1 to other organophosphatases demonstrates that either a similar "gating loop" or a highly buried solvent-excluding active site is a common feature of these enzymes. We therefore posit that modulating the active site hydrophobicity is a key element in facilitating the evolution of organophosphatase activity. This provides a concrete feature that can be utilized in the rational design of next-generation organophosphate hydrolases that are capable of selecting a specific reaction from a pool of viable substrates.

Enzyme Architecture: Modeling the Operation of a Hydrophobic Clamp in Catalysis by Triosephosphate Isomerase.

Triosephosphate isomerase (TIM) is a proficient catalyst of the reversible isomerization of dihydroxyacetone phosphate (DHAP) to d-glyceraldehyde phosphate (GAP), via general base catalysis by E165. Historically, this enzyme has been an extremely important model system for understanding the fundamentals of biological catalysis. TIM is activated through an energetically demanding conformational change, which helps position the side chains of two key hydrophobic residues (I170 and L230), over the carboxylate side chain of E165. This is critical both for creating a hydrophobic pocket for the catalytic base and for maintaining correct active site architecture. Truncation of these residues to alanine causes significant falloffs in TIM's catalytic activity, but experiments have failed to provide a full description of the action of this clamp in promoting substrate deprotonation. We perform here detailed empirical valence bond calculations of the TIM-catalyzed deprotonation of DHAP and GAP by both wild-type TIM and its I170A, L230A, and I170A/L230A mutants, obtaining exceptional quantitative agreement with experiment. Our calculations provide a linear free energy relationship, with slope 0.8, between the activation barriers and Gibbs free energies for these TIM-catalyzed reactions. We conclude that these clamping side chains minimize the Gibbs free energy for substrate deprotonation, and that the effects on reaction driving force are largely expressed at the transition state for proton transfer. Our combined analysis of previous experimental and current computational results allows us to provide an overview of the breakdown of ground-state and transition state effects in enzyme catalysis in unprecedented detail, providing a molecular description of the operation of a hydrophobic clamp in triosephosphate isomerase.

Increased Conformational Flexibility of a Macrocycle-Receptor Complex Contributes to Reduced Dissociation Rates.

Constraining a peptide in its bioactive conformation by macrocyclization represents a powerful strategy to design modulators of challenging biomolecular targets. This holds particularly true for the development of inhibitors of protein-protein interactions which often involve interfaces lacking defined binding pockets. Such flat surfaces are demanding targets for traditional small molecules rendering macrocyclic peptides promising scaffolds for novel therapeutics. However, the contribution of peptide dynamics to binding kinetics is barely understood which impedes the design process. Herein, we report unexpected trends in the binding kinetics of two closely related macrocyclic peptides that bind their receptor protein with high affinity. Isothermal titration calorimetry, 19 F NMR experiments and molecular dynamics simulations reveal that increased conformational flexibility of the macrocycle-receptor complex reduces dissociation rates and contributes to complex stability. This observation has impact on macrocycle design strategies that have so far mainly focused on the stabilization of bioactive ligand conformations.

CNA web server: rigidity theory-based thermal unfolding simulations of proteins for linking structure, (thermo-)stability, and function.

The Constraint Network Analysis (CNA) web server provides a user-friendly interface to the CNA approach developed in our laboratory for linking results from rigidity analyses to biologically relevant characteristics of a biomolecular structure. The CNA web server provides a refined modeling of thermal unfolding simulations that considers the temperature dependence of hydrophobic tethers and computes a set of global and local indices for quantifying biomacromolecular stability. From the global indices, phase transition points are identified where the structure switches from a rigid to a floppy state; these phase transition points can be related to a protein's (thermo-)stability. Structural weak spots (unfolding nuclei) are automatically identified, too; this knowledge can be exploited in data-driven protein engineering. The local indices are useful in linking flexibility and function and to understand the impact of ligand binding on protein flexibility. The CNA web server robustly handles small-molecule ligands in general. To overcome issues of sensitivity with respect to the input structure, the CNA web server allows performing two ensemble-based variants of thermal unfolding simulations. The web server output is provided as raw data, plots and/or Jmol representations. The CNA web server, accessible at http://cpclab.uni-duesseldorf.de/cna or http://www.cnanalysis.de, is free and open to all users with no login requirement.

NMSim web server: integrated approach for normal mode-based geometric simulations of biologically relevant conformational transitions in proteins.

The NMSim web server implements a three-step approach for multiscale modeling of protein conformational changes. First, the protein structure is coarse-grained using the FIRST software. Second, a rigid cluster normal-mode analysis provides low-frequency normal modes. Third, these modes are used to extend the recently introduced idea of constrained geometric simulations by biasing backbone motions of the protein, whereas side chain motions are biased toward favorable rotamer states (NMSim). The generated structures are iteratively corrected regarding steric clashes and stereochemical constraint violations. The approach allows performing three simulation types: unbiased exploration of conformational space; pathway generation by a targeted simulation; and radius of gyration-guided simulation. On a data set of proteins with experimentally observed conformational changes, the NMSim approach has been shown to be a computationally efficient alternative to molecular dynamics simulations for conformational sampling of proteins. The generated conformations and pathways of conformational transitions can serve as input to docking approaches or more sophisticated sampling techniques. The web server output is a trajectory of generated conformations, Jmol representations of the coarse-graining and a subset of the trajectory and data plots of structural analyses. The NMSim webserver, accessible at http://www.nmsim.de, is free and open to all users with no login requirement.

A Single-Cell Transcriptomic Analysis of the Mouse Hippocampus After Voluntary Exercise.

Exercise has been recognized as a beneficial factor for cognitive health, particularly in relation to the hippocampus, a vital brain region responsible for learning and memory. Previous research has demonstrated that exercise-mediated improvement of learning and memory in humans and rodents correlates with increased adult neurogenesis and processes related to enhanced synaptic plasticity. Nevertheless, the underlying molecular mechanisms are not fully understood. With the aim to further elucidate these mechanisms, we provide a comprehensive dataset of the mouse hippocampal transcriptome at the single-cell level after 4 weeks of voluntary wheel-running. Our analysis provides a number of interesting observations. For example, the results suggest that exercise affects adult neurogenesis by accelerating the maturation of a subpopulation of Prdm16-expressing neurons. Moreover, we uncover the existence of an intricate crosstalk among multiple vital signaling pathways such as NF-κB, Wnt/ß-catenin, Notch, and retinoic acid (RA) pathways altered upon exercise in a specific cluster of excitatory neurons within the Cornu Ammonis (CA) region of the hippocampus. In conclusion, our study provides an important resource dataset and sheds further light on the molecular changes induced by exercise in the hippocampus. These findings have implications for developing targeted interventions aimed at optimizing cognitive health and preventing age-related cognitive decline.

PRDM16-DT: A Brain and Astrocyte-Specific lncRNA Implicated in Alzheimer's Disease.

Astrocytes provide crucial support for neurons, contributing to synaptogenesis, synaptic maintenance, and neurotransmitter recycling. Under pathological conditions, deregulation of astrocytes contributes to neurodegenerative diseases such as Alzheimer's disease (AD), highlighting the growing interest in targeting astrocyte function to address early phases of AD pathogenesis. While most research in this field has focused on protein-coding genes, non-coding RNAs, particularly long non-coding RNAs (lncRNAs), have emerged as significant regulatory molecules. In this study, we identified the lncRNA PRDM16-DT as highly enriched in the human brain, where it is almost exclusively expressed in astrocytes. PRDM16-DT and its murine homolog, Prdm16os , are downregulated in the brains of AD patients and in AD models. In line with this, knockdown of PRDM16-DT and Prdm16os revealed its critical role in maintaining astrocyte homeostasis and supporting neuronal function by regulating genes essential for glutamate uptake, lactate release, and neuronal spine density through interactions with the RE1-Silencing Transcription factor (Rest) and Polycomb Repressive Complex 2 (PRC2). Notably, CRISPR-mediated overexpression of Prdm16os mitigated functional deficits in astrocytes induced by stimuli linked to AD pathogenesis. These findings underscore the importance of PRDM16-DT in astrocyte function and its potential as a novel therapeutic target for neurodegenerative disorders characterized by astrocyte dysfunction.

Spin-crossover complex on Au(111): structural and electronic differences between mono- and multilayers.

Submono-, mono- and multilayers of the Fe(II) spin-crossover (SCO) complex [Fe(bpz)2 (phen)] (bpz=dihydrobis(pyrazolyl)borate, phen=1,10-phenanthroline) have beenprepared by vacuum deposition on Au(111) substrates and investigated with near edge X-ray absorption fine structure (NEXAFS) spectroscopy and scanning tunneling microscopy (STM). As evidenced by NEXAFS, molecules of the second layer exhibit a thermal spin crossover transition, although with a more gradual characteristics than in the bulk. For mono- and submonolayers of [Fe(bpz)2 (phen)] deposited on Au(111) substrates at room temperature both NEXAFS and STM indicate a dissociation of [Fe(bpz)2 (phen)] on Au(111) into four-coordinate complexes, [Fe(bpz)2 ], and phen molecules. Keeping the gold substrate at elevated temperatures ordered monolayers of intact molecules of [Fe(bpz)2 (phen)] are formed which can be spin-switched by electron-induced excited spin-state trapping (ELIESST).

Correction to "Micelle Maker: An Online Tool for Generating Equilibrated Micelles as Direct Input for Molecular Dynamics Simulations".

[This corrects the article DOI: 10.1021/acsomega.7b00820.].

How good are state-of-the-art docking tools in predicting ligand binding modes in protein-protein interfaces?

Protein-protein interfaces (PPIs) are an important class of drug targets. We report on the first large-scale validation study on docking into PPIs. DrugScore-adapted AutoDock3 and Glide showed good success rates with a moderate drop-off compared to docking to "classical targets". An analysis of the binding energetics in a PPI allows identifying those interfaces that are amenable for docking. The results are important for deciding if structure-based design approaches can be applied to a particular PPI.

DrugScorePPI webserver: fast and accurate in silico alanine scanning for scoring protein-protein interactions.

Protein-protein complexes play key roles in all cellular signal transduction processes. We have developed a fast and accurate computational approach to predict changes in the binding free energy upon alanine mutations in protein-protein interfaces. The approach is based on a knowledge-based scoring function, DrugScore(PPI), for which pair potentials were derived from 851 complex structures and adapted against 309 experimental alanine scanning results. Based on this approach, we developed the DrugScore(PPI) webserver. The input consists of a protein-protein complex structure; the output is a summary table and bar plot of binding free energy differences for wild-type residue-to-Ala mutations. The results of the analysis are mapped on the protein-protein complex structure and visualized using J mol. A single interface can be analyzed within a few minutes. Our approach has been successfully validated by application to an external test set of 22 alanine mutations in the interface of Ras/RalGDS. The DrugScore(PPI) webserver is primarily intended for identifying hotspot residues in protein-protein interfaces, which provides valuable information for guiding biological experiments and in the development of protein-protein interaction modulators. The DrugScore(PPI) Webserver, accessible at http://cpclab.uni-duesseldorf.de/dsppi, is free and open to all users with no login requirement.

Engineered skeletal muscle recapitulates human muscle development, regeneration and dystrophy.

BACKGROUND: Human pluripotent stem cell-derived muscle models show great potential for translational research. Here, we describe developmentally inspired methods for the derivation of skeletal muscle cells and their utility in skeletal muscle tissue engineering with the aim to model skeletal muscle regeneration and dystrophy in vitro. METHODS: Key steps include the directed differentiation of human pluripotent stem cells to embryonic muscle progenitors followed by primary and secondary foetal myogenesis into three-dimensional muscle. To simulate Duchenne muscular dystrophy (DMD), a patient-specific induced pluripotent stem cell line was compared to a CRISPR/Cas9-edited isogenic control line. RESULTS: The established skeletal muscle differentiation protocol robustly and faithfully recapitulates critical steps of embryonic myogenesis in two-dimensional and three-dimensional cultures, resulting in functional human skeletal muscle organoids (SMOs) and engineered skeletal muscles (ESMs) with a regeneration-competent satellite-like cell pool. Tissue-engineered muscle exhibits organotypic maturation and function (up to 5.7 ± 0.5 mN tetanic twitch tension at 100 Hz in ESM). Contractile performance could be further enhanced by timed thyroid hormone treatment, increasing the speed of contraction (time to peak contraction) as well as relaxation (time to 50% relaxation) of single twitches from 107 ± 2 to 75 ± 4 ms (P < 0.05) and from 146 ± 6 to 100 ± 6 ms (P < 0.05), respectively. Satellite-like cells could be documented as largely quiescent PAX7+ cells (75 ± 6% Ki67- ) located adjacent to muscle fibres confined under a laminin-containing basal membrane. Activation of the engineered satellite-like cell niche was documented in a cardiotoxin injury model with marked recovery of contractility to 57 ± 8% of the pre-injury force 21 days post-injury (P < 0.05 compared to Day 2 post-injury), which was completely blocked by preceding irradiation. Absence of dystrophin in DMD ESM caused a marked reduction of contractile force (-35 ± 7%, P < 0.05) and impaired expression of fast myosin isoforms resulting in prolonged contraction (175 ± 14 ms, P < 0.05 vs. gene-edited control) and relaxation (238 ± 22 ms, P < 0.05 vs. gene-edited control) times. Restoration of dystrophin levels by gene editing rescued the DMD phenotype in ESM. CONCLUSIONS: We introduce human muscle models with canonical properties of bona fide skeletal muscle in vivo to study muscle development, maturation, disease and repair.

The Coding and Small Non-coding Hippocampal Synaptic RNAome.

Neurons are highly compartmentalized cells that depend on local protein synthesis. Messenger RNAs (mRNAs) have thus been detected in neuronal dendrites, and more recently in the pre- and postsynaptic compartments as well. Other RNA species such as microRNAs have also been described at synapses where they are believed to control mRNA availability for local translation. A combined dataset analyzing the synaptic coding and non-coding RNAome via next-generation sequencing approaches is, however, still lacking. Here, we isolate synaptosomes from the hippocampus of young wild-type mice and provide the coding and non-coding synaptic RNAome. These data are complemented by a novel approach for analyzing the synaptic RNAome from primary hippocampal neurons grown in microfluidic chambers. Our data show that synaptic microRNAs control almost the entire synaptic mRNAome, and we identified several hub microRNAs. By combining the in vivo synaptosomal data with our novel microfluidic chamber system, our findings also support the hypothesis that part of the synaptic microRNAome may be supplied to neurons via astrocytes. Moreover, the microfluidic system is suitable for studying the dynamics of the synaptic RNAome in response to stimulation. In conclusion, our data provide a valuable resource and point to several important targets for further research.

Exercise as a model to identify microRNAs linked to human cognition: a role for microRNA-409 and microRNA-501.

MicroRNAs have been linked to synaptic plasticity and memory function and are emerging as potential biomarkers and therapeutic targets for cognitive diseases. Most of these data stem from the analysis of model systems or postmortem tissue from patients which mainly represents an advanced stage of pathology. Due to the in-accessibility of human brain tissue upon experimental manipulation, it is still challenging to identify microRNAs relevant to human cognition, which is however a key step for future translational studies. Here, we employ exercise as an experimental model for memory enhancement in healthy humans with the aim to identify microRNAs linked to memory function. By analyzing the circulating smallRNAome we find a cluster of 18 microRNAs that are highly correlated to cognition. MicroRNA-409-5p and microRNA-501-3p were the most significantly regulated candidates. Functional analysis revealed that the two microRNAs are important for neuronal integrity, synaptic plasticity, and morphology. In conclusion, we provide a novel approach to identify microRNAs linked to human memory function.

Interferon-driven brain phenotype in a mouse model of RNaseT2 deficient leukoencephalopathy.

Infantile-onset RNaseT2 deficient leukoencephalopathy is characterised by cystic brain lesions, multifocal white matter alterations, cerebral atrophy, and severe psychomotor impairment. The phenotype is similar to congenital cytomegalovirus brain infection and overlaps with type I interferonopathies, suggesting a role for innate immunity in its pathophysiology. To date, pathophysiological studies have been hindered by the lack of mouse models recapitulating the neuroinflammatory encephalopathy found in patients. In this study, we generated Rnaset2-/- mice using CRISPR/Cas9-mediated genome editing. Rnaset2-/- mice demonstrate upregulation of interferon-stimulated genes and concurrent IFNAR1-dependent neuroinflammation, with infiltration of CD8+ effector memory T cells and inflammatory monocytes into the grey and white matter. Single nuclei RNA sequencing reveals homeostatic dysfunctions in glial cells and neurons and provide important insights into the mechanisms of hippocampal-accentuated brain atrophy and cognitive impairment. The Rnaset2-/- mice may allow the study of CNS damage associated with RNaseT2 deficiency and may be used for the investigation of potential therapies.

Long Time-Scale Atomistic Simulations of the Structure and Dynamics of Transcription Factor-DNA Recognition.

Recent years have witnessed an explosion of interest in computational studies of DNA binding proteins, including both coarse-grained and atomistic simulations of transcription factor-DNA recognition, to understand how these transcription factors recognize their binding sites on the DNA with such exquisite specificity. The present study performs microsecond time scale all-atom simulations of the dimeric form of the lactose repressor (LacI), both in the absence of any DNA and in the presence of both specific and nonspecific complexes, considering three different DNA sequences. We examine, specifically, the conformational differences between specific and nonspecific protein-DNA interactions, as well as the behavior of the helix-turn-helix motif of LacI when interacting with the DNA. Our simulations suggest that stable LacI binding occurs primarily to bent A-form DNA, with a loss of LacI conformational entropy and optimization of correlated conformational equilibria across the protein. In addition, binding to the specific operator sequence involves a slightly larger number of stabilizing DNA-protein hydrogen bonds (in comparison to nonspecific complexes), which may account for the experimentally observed specificity for this operator. In doing so, our simulations provide a detailed atomistic description of potential structural drivers for LacI selectivity.