Using the Allen gene expression atlas of the adult mouse brain to gain further insight into the physiological significance of TAG-1/Contactin-2

A novel blood-based epigenetic biosignature in first-episode schizophrenia patients through automated machine learning

Schizophrenia (SCZ) is a chronic, severe, and complex psychiatric disorder that affects all aspects of personal functioning. While SCZ has a very strong biological component, there are still no objective diagnostic tests. Lately, special attention has been given to epigenetic biomarkers in SCZ. In this study, we introduce a three-step, automated machine learning (AutoML)-based, data-driven, biomarker discovery pipeline approach, using genome-wide DNA methylation datasets and laboratory validation, to deliver a highly performing, blood-based epigenetic biosignature of diagnostic clinical value in SCZ. Publicly available blood methylomes from SCZ patients and healthy individuals were analyzed via AutoML, to identify SCZ-specific biomarkers. The methylation of the identified genes was then analyzed by targeted qMSP assays in blood gDNA of 30 first-episode drug-naïve SCZ patients and 30 healthy controls (CTRL). Finally, AutoML was used to produce an optimized disease-specific biosignature based on patient methylation data combined with demographics. AutoML identified a SCZ-specific set of novel gene methylation biomarkers including IGF2BP1, CENPI, and PSME4. Functional analysis investigated correlations with SCZ pathology. Methylation levels of IGF2BP1 and PSME4, but not CENPI were found to differ, IGF2BP1 being higher and PSME4 lower in the SCZ group as compared to the CTRL group. Additional AutoML classification analysis of our experimental patient data led to a five-feature biosignature including all three genes, as well as age and sex, that discriminated SCZ patients from healthy individuals [AUC 0.755 (0.636, 0.862) and average precision 0.758 (0.690, 0.825)]. In conclusion, this three-step pipeline enabled the discovery of three novel genes and an epigenetic biosignature bearing potential value as promising SCZ blood-based diagnostics.

Biomimetic-inspired piezoelectric ovalbumin/BaTiO3 scaffolds synergizing with anisotropic topology for modulating Schwann cell and DRG behavior

The treatment of peripheral nerve injury is a clinical challenge that tremendously affected the patients' health and life. Anisotropic topographies and electric cues can simulate the regenerative microenvironment of nerve from physical and biological aspects, which show promising application in nerve regeneration. However, most studies just unilaterally emphasize the effect of sole topological- or electric- cue on nerve regeneration, while rarely considering the synergistic function of both cues simultaneously. In this study, a biomimetic-inspired piezoelectric topological ovalbumin/BaTiO3 scaffold that can provide non-invasive electrical stimulation in situ was constructed by combining piezoelectric BaTiO3 nanoparticles and surface microtopography. The results showed that the incorporation of piezoelectric nanoparticles could improve the mechanical properties of the scaffolds, and the piezoelectric output of the scaffolds after polarization was significantly increased. Biological evaluation revealed that the piezoelectric topological scaffolds could regulate the orientation growth of SCs, promote axon elongation of DRG, and upregulate the genes expression referring to myelination and axon growth, thus rapidly integrated chemical-mechanical signals and transmitted them for effectively promoting neuronal myelination, which was closely related to peripheral neurogenesis. The study suggests that the anisotropic surface topology combined with non-invasive electronic stimulation of the ovalbumin/BaTiO3 scaffolds possess a promising application prospect in the repair and regeneration of peripheral nerve injury.

Contactin 2 homophilic adhesion structure and conformational plasticity

The cell-surface attached glycoprotein contactin 2 is ubiquitously expressed in the nervous system and mediates homotypic cell-cell interactions to organize cell guidance, differentiation, and adhesion. Contactin 2 consists of six Ig and four fibronectin type III domains (FnIII) of which the first four Ig domains form a horseshoe structure important for homodimerization and oligomerization. Here we report the crystal structure of the six-domain contactin 2Ig1-6 and show that the Ig5-Ig6 combination is oriented away from the horseshoe with flexion in interdomain connections. Two distinct dimer states, through Ig1-Ig2 and Ig3-Ig6 interactions, together allow formation of larger oligomers. Combined size exclusion chromatography with multiangle light scattering (SEC-MALS), small-angle X-ray scattering (SAXS) and native MS analysis indicates contactin 2Ig1-6 oligomerizes in a glycan dependent manner. SAXS and negative-stain electron microscopy reveals inherent plasticity of the contactin 2 full-ectodomain. The combination of intermolecular binding sites and ectodomain plasticity explains how contactin 2 can function as a homotypic adhesion molecule in diverse intercellular environments.

Prediction and Ranking of Biomarkers Using multiple UniReD

Protein–protein interactions (PPIs) are of key importance for understanding how cells and organisms function. Thus, in recent decades, many approaches have been developed for the identification and discovery of such interactions. These approaches addressed the problem of PPI identification either by an experimental point of view or by a computational one. Here, we present an updated version of UniReD, a computational prediction tool which takes advantage of biomedical literature aiming to extract documented, already published protein associations and predict undocumented ones. The usefulness of this computational tool has been previously evaluated by experimentally validating predicted interactions and by benchmarking it against public databases of experimentally validated PPIs. In its updated form, UniReD allows the user to provide a list of proteins of known implication in, e.g., a particular disease, as well as another list of proteins that are potentially associated with the proteins of the first list. UniReD then automatically analyzes both lists and ranks the proteins of the second list by their association with the proteins of the first list, thus serving as a potential biomarker discovery/validation tool.

Single-Cell Transcriptomics-Based Study of Transcriptional Regulatory Features in the Mouse Brain Vasculature

Background

The critical role of vascular health on brain function has received much attention in recent years. At the single-cell level, studies on the developmental processes of cerebral vascular growth are still relatively few. Techniques for constructing gene regulatory networks (GRNs) based on single-cell transcriptome expression data have made significant progress in recent years. Herein, we constructed a single-cell transcriptional regulatory network of mouse cerebrovascular cells.

Methods

The single-cell RNA-seq dataset of mouse brain vessels was downloaded from GEO (GSE98816). This cell clustering was annotated separately using singleR and CellMarker. We then used a modified version of the SCENIC method to construct GRNs. Next, we used a mouse version of SEEK to assess whether genes in the regulon were coexpressed. Finally, regulatory module analysis was performed to complete the cell type relationship quantification.

Results

Single-cell RNA-seq data were used to analyze the heterogeneity of mouse cerebrovascular cells, whereby four cell types including endothelial cells, fibroblasts, microglia, and oligodendrocytes were defined. These subpopulations of cells and marker genes together characterize the molecular profile of mouse cerebrovascular cells. Through these signatures, key transcriptional regulators that maintain cell identity were identified. Our findings identified genes like Lmo2, which play an important role in endothelial cells. The same cell type, for instance, fibroblasts, was found to have different regulatory networks, which may influence the functional characteristics of local tissues.

Conclusions

In this study, a transcriptional regulatory network based on single-cell analysis was constructed. Additionally, the study identified and profiled mouse cerebrovascular cells using single-cell transcriptome data as well as defined TFs that affect the regulatory network of the mouse brain vasculature.

The Spatial and Cell-Type Distribution of SARS-CoV-2 Receptor ACE2 in the Human and Mouse Brains

By engaging angiotensin-converting enzyme 2 (ACE2 or Ace2), the novel pathogenic severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) invades host cells and affects many organs, including the brain. However, the distribution of ACE2 in the brain is still obscure. Here, we investigated the ACE2 expression in the brain by analyzing data from publicly available brain transcriptome databases. According to our spatial distribution analysis, ACE2 was relatively highly expressed in some brain locations, such as the choroid plexus and paraventricular nuclei of the thalamus. According to cell-type distribution analysis, nuclear expression of ACE2 was found in many neurons (both excitatory and inhibitory neurons) and some non-neuron cells (mainly astrocytes, oligodendrocytes, and endothelial cells) in the human middle temporal gyrus and posterior cingulate cortex. A few ACE2-expressing nuclei were found in a hippocampal dataset, and none were detected in the prefrontal cortex. Except for the additional high expression of Ace2 in the olfactory bulb areas for spatial distribution as well as in the pericytes and endothelial cells for cell-type distribution, the distribution of Ace2 in the mouse brain was similar to that in the human brain. Thus, our results reveal an outline of ACE2/Ace2 distribution in the human and mouse brains, which indicates that the brain infection of SARS-CoV-2 may be capable of inducing central nervous system symptoms in coronavirus disease 2019 (COVID-19) patients. Potential species differences should be considered when using mouse models to study the neurological effects of SARS-CoV-2 infection.