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NMDA-type glutamate receptors (NMDARs) are tetrameric channel complex composed of two subunits of GluN1, which is encoded by a single gene and diversified by alternative splicing, and two subunits from four subtypes of GluN2, leading to various combinations of subunits and channel specificities. However, there is no comprehensive quantitative analysis of GluN subunit proteins for relative comparison, and their compositional ratios at various regions and developmental stages have not been clarified. Here we prepared six chimeric subunits, by fusing an N-terminal side of the GluA1 subunit with a C-terminal side of each of two splicing isoforms of GluN1 subunit and four GluN2 subunits, with which titers of respective NMDAR subunit antibodies could be standardized using common GluA1 antibody, thus enabling quantification of relative protein levels of each NMDAR subunit by western blotting. We determined relative protein amounts of NMDAR subunits in crude, membrane (P2) and microsomal fractions prepared from the cerebral cortex, hippocampus and cerebellum in adult mice. We also examined amount changes in the three brain regions during developmental stages. Their relative amounts in the cortical crude fraction were almost parallel to those of mRNA expression, except for some subunits. Interestingly, a considerable amount of GluN2D protein existed in adult brains, although its transcription level declines after early postnatal stages. GluN1 was larger in quantity than GluN2 in the crude fraction, whereas GluN2 increased in the membrane component-enriched P2 fraction, except in the cerebellum. These data will provide the basic spatio-temporal information on the amount and composition of NMDARs.

Alzheimer’s disease (AD) is the leading cause of dementia among the elderly. Neuropathologically, AD is characterized by the deposition of a 39- to 42-amino acid long β-amyloid (Aβ) peptide in the form of senile plaques. Several post-translational modifications (PTMs) in the N-terminal domain have been shown to increase the aggregation and cytotoxicity of Aβ, and specific Aβ proteoforms (e.g., Aβ with isomerized D7 (isoD7-Aβ)) are abundant in the senile plaques of AD patients. Animal models are indispensable tools for the study of disease pathogenesis, as well as preclinical testing. In the presented work, the accumulation dynamics of Aβ proteoforms in the brain of one of the most widely used amyloid-based mouse models (the 5xFAD line) was monitored. Mass spectrometry (MS) approaches, based on ion mobility separation and the characteristic fragment ion formation, were applied. The results indicated a gradual increase in the Aβ fraction of isoD7-Aβ, starting from approximately 8% at 7 months to approximately 30% by 23 months of age. Other specific PTMs, in particular, pyroglutamylation, deamidation, and oxidation, as well as phosphorylation, were also monitored. The results for mice of different ages demonstrated that the accumulation of Aβ proteoforms correlate with the formation of Aβ deposits. Although the mouse model cannot be a complete analogue of the processes occurring in the human brain in AD, and several of the observed parameters differ significantly from human values supposedly due to the limited lifespan of the model animals, this dynamic study provides evidence on at least one of the possible mechanisms that can trigger amyloidosis in AD, i.e., the hypothesis on the relationship between the accumulation of isoD7-Aβ and the progression of AD-like pathology.

Magnetic resonance spectroscopy (MRS) is a noninvasive technique for measuring metabolite concentration. It can be used for preclinical small animal brain studies using rodents to provide information about neurodegenerative diseases and metabolic disorders. However, data acquisition from small volumes in a limited scan time is technically challenging due to its inherently low sensitivity. To mitigate this problem, this study investigated the feasibility of a low-rank denoising method in enhancing the quality of single voxel multinuclei (31P and 1H) MRS data at 9.4 T. Performance was evaluated using in vivo MRS data from a normal mouse brain (31P and 1H) and stroke mouse model (1H) by comparison with signal-to-noise ratios (SNRs), Cramer-Rao lower bounds (CRLBs), and metabolite concentrations of a linear combination of model analysis results. In 31P MRS data, low-rank denoising resulted in improved SNRs and reduced metabolite quantification uncertainty compared with the original data. In 1H MRS data, the method also improved the SNRs, CRLBs, but it performed better for 31P MRS data with relatively simpler patterns compared to the 1H MRS data. Therefore, we suggest that the low-rank denoising method can improve spectra SNR and metabolite quantification uncertainty in single-voxel in vivo 31P and 1H MRS data, and it might be more effective for 31P MRS data. The main contribution of this study is that we demonstrated the effectiveness of the low-rank denoising method on small-volume single-voxel MRS data. We anticipate that our results will be useful for the precise quantification of low-concentration metabolites, further reducing data acquisition voxel size, and scan time in preclinical MRS studies.

Background Evidence indicates that Gα12, Gα13, and its downstream effectors, RhoA and Rac1, regulate neuronal morphology affected by stress. This study was aimed at investigating whether repeated stress influences the expression of proteins related to the Gα12/13 intracellular signaling pathway in selected brain regions sensitive to the effects of stress. Furthermore, the therapeutic impact of β(1)adrenergic receptors (β1AR) blockade was assessed. Methods Restraint stress (RS) model in mice (2 h/14 days) was used to assess prolonged stress effects on the mRNA expression of Gα12, Gα13, RhoA, Rac1 in the prefrontal cortex (PFC), hippocampus (HIP) and amygdala (AMY). In a separate study, applying RS model in rats (3–4 h/1 day or 14 days), we evaluated stress effects on the expression of Gα12, Gα11, Gαq, RhoA, RhoB, RhoC, Rac1/2/3 in the HIP. Betaxolol (BET), a selective β1AR antagonist, was introduced (5 mg/kg/p.o./8–14 days) in the rat RS model to assess the role of β1AR in stress effects. RT-qPCR and Western Blot were used for mRNA and protein assessments, respectively. Results Chronic RS decreased mRNA expression of Gα12 and increased mRNA for Rac1 in the PFC of mice. In the mice AMY, decreased mRNA expression of Gα12, Gα13 and RhoA was observed. Fourteen days of RS exposure increased RhoA protein level in the rats’ HIP in the manner dependent on β1AR activity. Conclusions Together, these results suggest that repeated RS affects the expression of genes and proteins known to be engaged in neural plasticity, providing potential targets for further studies aimed at unraveling the molecular mechanisms of stress-related neuropsychiatric diseases.

Genome-wide gene expression analyses are invaluable tools for increasing our knowledge of biological and disease processes, allowing a hypothesis-free comparison of gene expression profiles across experimental groups, tissues and cell types. Traditionally, transcriptomic data analysis has focused on gene-level effects found by differential expression. In recent years, network analysis has emerged as an important additional level of investigation, providing information on molecular connectivity, especially for diseases associated with a large number of linked effects of smaller magnitude, like neuropsychiatric disorders and their risk factors, including stress. In this manuscript, we describe how combined differential expression and prior-knowledge-based differential network analysis can be used to explore complex datasets. As an example, we analyze the transcriptional responses following administration of the glucocorticoid/stress hormone receptor agonist dexamethasone in C57Bl/6 mice, in 8 brain regions important for stress processing: the prefrontal cortex, the amygdala, the paraventricular nucleus of the hypothalamus, the cerebellar cortex, and sub regions of the hippocampus: the dorsal and ventral Cornu Ammonis 1, the dorsal and ventral dentate gyrus. By applying a combination of differential network- and differential expression-analyses, we find that these explain distinct but complementary aspects and biological mechanisms of the responses to the stimulus. In addition, network analysis identifies new differentially connected partners of important genes and can be used to generate hypotheses on specific molecular pathways affected. With this work, we provide an analysis framework and a publicly available resource for the study of the transcriptional landscape of the mouse brain: DiffBrainNet (http://diffbrainnet.psych.mpg.de), which can identify molecular pathways important for basic functioning and response to glucocorticoids in a brain-region specific manner.

Objective: Vanishing white matter (VWM) is a genetic brain white matter disorder caused by mutations in eIF2B. eIF2B is central in the integrated stress response (ISR), during which its activity is inhibited by various cellular stresses. VWM is a chronic progressive disease with episodes of rapid neurological deterioration provoked by stresses. VWM patients and VWM mouse models show ISR deregulation in brain, correlating with chronic disease development. ISR inhibition ameliorates the chronic disease in VWM mice. The subacute deteriorations have not been modeled yet. We hypothesized that ISR activation could worsen disease progression in mice and model the episodic neurological deterioration. Method: We chose to activate the ISR by subjecting wild-type (wt) and VWM mice to an isocaloric low protein diet. This model would allow us to investigate the contribution of ISR activation in subacute decline in VWM. Results: We found that the low protein diet did not significantly affect amino acid levels nor ISR levels in wt and VWM mouse brain. Our study serendipitously led to the discovery of increased levels of glycine, asparagine and Fgf21 mRNA in VWM mouse brain irrespective of the dietary protein content. Strikingly, the ISR was not activated by the low protein diet in the liver of VWM in contrast to wt mice, due to a modest ISR deregulation in this organ. Discussion: A model for subacute neurological deterioration in VWM was not established. Possibly, ISR deregulation in VWM results in reduced ISR responsiveness.

Segmenting the fine structure of the mouse brain on magnetic resonance (MR) images is critical for delineating morphological regions, analyzing brain function, and understanding their relationships. Compared to a single MRI modality, multimodal MRI data provide complementary tissue features that can be exploited by deep learning models, resulting in better segmentation results. However, multimodal mouse brain MRI data is often lacking, making automatic segmentation of mouse brain fine structure a very challenging task. To address this issue, it is necessary to fuse multimodal MRI data to produce distinguished contrasts in different brain structures. Hence, we propose a novel disentangled and contrastive GAN-based framework, named MouseGAN++, to synthesize multiple MR modalities from single ones in a structure-preserving manner, thus improving the segmentation performance by imputing missing modalities and multi-modality fusion. Our results demonstrate that the translation performance of our method outperforms the state-of-the-art methods. Using the subsequently learned modality-invariant information as well as the modality-translated images, MouseGAN++ can segment fine brain structures with averaged dice coefficients of 90.0% (T2w) and 87.9% (T1w), respectively, achieving around +10% performance improvement compared to the state-of-the-art algorithms. Our results demonstrate that MouseGAN++, as a simultaneous image synthesis and segmentation method, can be used to fuse cross-modality information in an unpaired manner and yield more robust performance in the absence of multimodal data. We release our method as a mouse brain structural segmentation tool for free academic usage at https://github.com/yu02019., IEEE Transactions on Medical Imaging (IEEE-TMI) 2022

Registering mouse brain microscopy images to a reference atlas is crucial to determine the locations of anatomical structures in the brain, which is an essential step for understanding the function of brain circuits. Most existing registration pipelines assume the identity of the reference plate – to which the image slice is to be registered – is known beforehand. This might not always be the case due to three main challenges in microscopy image data: missing image regions (partial data), different cutting angles compared to the atlas plates and a large number of high-resolution images to be identified. Manual identification of reference plates as an initial step requires highly experienced personnel and can be biased, tedious and resource intensive. On the other hand, registering images to all atlas plates can be slow, limiting the application of automated registration methods when dealing with high-resolution image data. This work proposes to perform the image identification by learning a low-dimensional space that captures the similarity between microscopy images and the reference atlas plates. We employ Convolutional Neural Networks (CNNs), in the Siamese network configuration, to first obtain low-dimensional embeddings of microscopy image data and atlas plates. These embeddings are contrasted with positive and negative examples in order to learn a semantically meaningful space that can be used for identifying corresponding 2D atlas plates. At inference, atlas plates that are closest to the microscopy image data in the learned embedding space are presented as candidates for registration. Our method achieved TOP-3 and TOP-5 accuracy of 83.3% and 100%, respectively, compared to the SimpleElastix-based baseline which obtained 25% in both the Top-3 and Top-5 accuracy (Source code is available at https://github.com/Justinas256/2d-mouse-brain-identification ).

Mobile microrobots hold remarkable potential to revolutionize health care by enabling unprecedented active medical interventions and theranostics, such as active cargo delivery and microsurgical manipulations in hard-to-reach body sites. High-resolution imaging and control of cell-sized microrobots in the in vivo vascular system remains an unsolved challenge toward their clinical use. To overcome this limitation, we propose noninvasive real-time detection and tracking of circulating microrobots using optoacoustic imaging. We devised cell-sized nickel-based spherical Janus magnetic microrobots whose near-infrared optoacoustic signature is enhanced via gold conjugation. The 5-, 10-, and 20-μm-diameter microrobots are detected volumetrically both in bloodless ex vivo tissues and under real-life conditions with a strongly light-absorbing blood background. We further demonstrate real-time three-dimensional tracking and magnetic manipulation of the microrobots circulating in murine cerebral vasculature, thus paving the way toward effective and safe operation of cell-sized microrobots in challenging and clinically relevant intravascular environments., Science Advances, 8 (19), ISSN:2375-2548

The ever-expanding availability and evolution of microscopy tools has enabled ground-breaking discoveries in neurobiology, particularly with respect to the analysis of cell-type density and distribution. Widespread implementation of many of the elegant image processing tools available continues to be impeded by the lack of complete workflows that span from experimental design, labeling techniques, and analysis workflows, to statistical methods and data presentation. Additionally, it is important to consider open science principles (e.g., open-source software and tools, user-friendliness, simplicity, and accessibility). In the present methodological article, we provide a compendium of resources and a FIJI-ImageJ-based workflow aimed at improving the quantification of cell density in mouse brain samples using semi-automated open-science-based methods. Our proposed framework spans from principles and best practices of experimental design, histological and immunofluorescence staining, and microscopy imaging to recommendations for statistical analysis and data presentation. To validate our approach, we quantified neuronal density in the mouse barrel cortex using antibodies against pan-neuronal and interneuron markers. This framework is intended to be simple and yet flexible, such that it can be adapted to suit distinct project needs. The guidelines, tips, and proposed methodology outlined here, will support researchers of wide-ranging experience levels and areas of focus in neuroscience research.

Autism is a neurodevelopmental disorder for which the cause and treatment have yet not been determined. The polyunsaturated fatty acid (PUFA) levels change rapidly in the blood or cerebrospinal fluid of autistic children and PUFAs are closely related to autism spectrum disorder (ASD). This finding suggests that changes in lipid metabolism are associated with ASD and result in an altered distribution of phospholipids in cell membranes. To further understand ASD, it is necessary to analyze phospholipids in organs consisting of nerve cells, such as the brain. In this study, we investigated the phospholipid distribution in the brain tissue of valproic acid-induced autistic mice using matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI). Phospholipids including phosphatidylcholine, phosphatidylethanolamine, and phosphatidylserine were identified in each brain region and exhibited differences between the ASD and control groups. These phospholipids contain docosahexaenoic acid and arachidonic acid, which are important PUFAs for cell signaling and brain growth. We expect that the differences in phospholipids identified in the brain tissue of the ASD model with MALDI-MSI, in conjunction with conventional biological fluid analysis, will help to better understand changes in lipid metabolism in ASD.

The brain modulates specific functions in its various regions. Understanding the organization of different cells in the whole brain is crucial for investigating brain functions. Previous studies have focused on several regions and have had difficulty analyzing serial tissue samples. In this study, we introduced a pipeline to acquire anatomical and histological information quickly and efficiently from serial sections. First, we developed a serial brain-slice-staining method to stain serial sections and obtained more than 98.5% of slices with high integrity. Subsequently, using the self-developed analysis software, we registered and quantified the signals of imaged sections to the Allen Mouse Brain Common Coordinate Framework, which is compatible with multimodal images and slant section planes. Finally, we validated the pipeline with immunostaining by analyzing the activity variance in the whole brain during acute stress in aging and young mice. By removing the problems resulting from repeated manual operations, this pipeline is widely applicable to serial brain slices from multiple samples in a rapid and convenient manner, which benefits to facilitate research in life sciences.

Purpose To assess the effect of a variety of anesthetic regimes on T 2 ∗ -weighted MRI of the mouse brain and to determine the optimal regimes to perform T 2 ∗ -weighted MRI of the mouse cerebrovasculature without a contrast agent. Methods Twenty mice were imaged with a 3D T 2 ∗ -weighted sequence under isoflurane, dexmedetomidine, or ketamine-xylazine anesthesia with a fraction of inspired oxygen varied between 10% and 95% + 5% CO2 . Some mice were also imaged after an injection of an iron oxide contrast agent as a positive control. For every regime, whole brain vessel conspicuity was visually assessed and the apparent vessel density in the cortex was quantified and compared. Results The commonly used isoflurane anesthetic leads to poor vessel conspicuity for fraction of inspired oxygen higher or equal to 21%. Dexmedetomidine and ketamine-xylazine enable the visualization of a significantly larger portion of the vasculature for the same breathing gas. Under isoflurane anesthesia, the fraction of inspired oxygen must be lowered to between 10% and 14% to obtain similar vessel conspicuity. Initial results on automatic segmentation of veins and arteries using the iron oxide positive control are also reported. Conclusion T 2 ∗ -weighted MRI in combination with an appropriate anesthetic regime can be used to visualize the mouse cerebrovasculature without a contrast agent. The differences observed between regimes are most likely caused by blood-oxygen level dependent effects, highlighting the important impact of the anesthetic regimes on cerebral blood oxygenation of the mouse brain at rest.

Disabilities resulting from traumatic brain injury (TBI) strongly correlate with the cytoarchitectonic part of the brain damaged, lesion area, and type of lesion. We developed a Web application to estimate the location of the lesion on mouse cerebral cortex caused by TBI induced by lateral fluid-percussion injury. The application unfolds user-determined TBI lesion measurements, e.g., from histologic sections to a reference template, and estimates the total lesion area, including the percentage of cortex damaged in different cytoarchitectural cortical regions. The resulting lesion can be visualized on a two-dimensional map of mouse cerebral cortex. The application also visualizes the development of the lesion over time when measurements from multiple time points are available. The web application was validated by comparing its performance to the manual method. The total area of the cortical lesion was similar between the manual (9.19 ± 0.66 mm2, range 4.25–14.93 mm2) and the automated analysis (9.27 ± 0.66 mm2, range 4.50–15.10 mm2) (p = 0.938). The results of the manual and automated analyses were strongly correlated (r = 0.999, p

Glial cell line-derived neurotrophic factor (GDNF) plays a critical role in neuronal survival and function. GDNF has two major splice variants in the brain, α-pro-GDNF and β-pro-GDNF, and both isoforms have strong neuroprotective effects on dopamine neurons. However, the expression of the GDNF splice variants in dopaminergic neurons in the brain remains unclear. Therefore, in this study, we investigated the mRNA and protein expression of α- and β-pro-GDNF in the mouse brain by real-time quantitative polymerase chain reaction, using splice variant-specific primers, and western blot analysis. At the mRNA level, β-pro-GDNF expression was significantly greater than that of α-pro-GDNF in the mouse brain. In contrast, at the protein level, α-pro-GDNF expression was markedly greater than that of β-pro-GDNF. To clarify the mechanism underlying this inverse relationship in mRNA and protein expression levels of the GDNF splice variants, we analyzed the expression of sorting protein-related receptor with A-type repeats (SorLA) by real-time quantitative polymerase chain reaction. At the mRNA level, SorLA was positively associated with β-pro-GDNF expression, but not with α-pro-GDNF expression. This suggests that the differential expression of α- and β-pro-GDNF in the mouse brain is related to SorLA expression. As a sorting protein, SorLA could contribute to the inverse relationship among the mRNA and protein levels of the GDNF isoforms. This study was approved by the Animal Ethics Committee of Xuzhou Medical University, China on July 14, 2016.

Background Physical exercises have been shown to be a surprisingly effective strategy to take advantage of the brain's natural capacity for plasticity, and prevent brain degeneration in mouse histological studies. In vivo magnetic resonance microscopy (MRM) provides highly resolved anatomical images and allows quantitative assessment of brain atrophy in the aged mouse model. Objective The aim of the present study was to investigate, through the effects of 10 weeks voluntary wheel running, the mouse's brain atrophy. Methods Sixteen C57BL/6J mice, aged 21 months, were randomized to the exercise or sedentary group. Each mouse was scanned in a 7.0-T MRM scanner at two time points: 22 months old baseline and a follow-up three months later. Multi-atlas based brain segmentation approach was used to obtain volumes of 39 brain regions. Results The results showed that mice in the exercise group had less brain atrophy compared with the mice in the sedentary group. Conclusions The results provide new insights into exercise induced brain plasticity in aged animals.

The heparan sulfate 6-O-endosulfatases, Sulfatase 1 (Sulf1), and Sulfatase 2 (Sulf2), are extracellular enzymes that regulate cellular signaling by removing 6-O-sulfate from the heparan sulfate chain. Although previous studies have revealed that Sulfs are essential for normal development, their functions in the adult brain remain largely unknown. To gain insight into their neural functions, we used in situ hybridization to systematically examine Sulf1/2 mRNA expression in the adult mouse brain. Sulf1 and Sulf2 mRNAs showed distinct expression patterns, which is in contrast to their overlapping expression in the embryonic brain. In addition, we found that Sulf1 was distinctly expressed in the nucleus accumbens shell, the posterior tail of the striatum, layer 6 of the cerebral cortex, and the paraventricular nucleus of the thalamus, all of which are target areas of dopaminergic projections. Using double-labeling techniques, we showed that Sulf1-expressing cells in the above regions coincided with cells expressing the dopamine D1 and/or D2 receptor. These findings implicate possible roles of Sulf1 in modulation of dopaminergic transmission and dopamine-mediated behaviors.

ATP and other nucleotides are important glio-/neurotransmitters in the central nervous system. They bind to purinergic P2X and P2Y receptors that are ubiquitously expressed in various brain regions modulating various physiological and pathophysiological processes. P2X receptors are ligand-gated ion channels mediating excitatory postsynaptic responses whereas P2Y receptors are G protein-coupled receptors mediating slow synaptic transmission. A variety of P2X and P2Y subtypes with distinct neuroanatomical localization provide the basis for a high diversity in their function. There is increasing evidence that P2 receptor signaling plays a prominent role in learning and memory and thus, in hippocampal neuronal plasticity. Learning and memory are time-of-day-dependent. Moreover, extracellular ATP shows a diurnal rhythm in rodents. However, it is not known whether P2 receptors have a temporal variation in the hippocampus. This study provides a detailed systematic analysis on spatial and temporal distribution of P2 in the mouse hippocampus. We found distinct spatial and temporal distribution patterns of the P2 receptors in different hippocampal layers. The temporal distribution of P2 receptors can be segregated into two large time domains, the early to mid-day and the mid to late night. This study provides an important basis for understanding dynamic P2 purinergic signaling in the hippocampal glia/neuronal network.

The heparan sulfate 6-O-endosulfatases, Sulfatase 1 (Sulf1), and Sulfatase 2 (Sulf2), are extracellular enzymes that regulate cellular signaling by removing 6-O-sulfate from the heparan sulfate chain. Although previous studies have revealed that Sulfs are essential for normal development, their functions in the adult brain remain largely unknown. To gain insight into their neural functions, we used in situ hybridization to systematically examine Sulf1/2 mRNA expression in the adult mouse brain. Sulf1 and Sulf2 mRNAs showed distinct expression patterns, which is in contrast to their overlapping expression in the embryonic brain. In addition, we found that Sulf1 was distinctly expressed in the nucleus accumbens shell, the posterior tail of the striatum, layer 6 of the cerebral cortex, and the paraventricular nucleus of the thalamus, all of which are target areas of dopaminergic projections. Using double-labeling techniques, we showed that Sulf1-expressing cells in the above regions coincided with cells expressing the dopamine D1 and/or D2 receptor. These findings implicate possible roles of Sulf1 in modulation of dopaminergic transmission and dopamine-mediated behaviors.

Acquisition of detailed anatomical and molecular knowledge from intact biological samples while preserving their native three-dimensional structure is still a challenging issue for imaging studies aiming to unravel a system’s functions. Three-dimensional micro-CT X-ray imaging with a high spatial resolution in minimally perturbed naive non-transparent samples has recently gained increased popularity and broad application in biomedical research. Here, we describe a novel X-ray-based methodology for analysis of β-galactosidase (lacZ) reporter-driven gene expression in an intact murine brain ex vivo by micro-CT. The method relies on detection of bromine molecules in the product of the enzymatic β-galactosidase reaction. Enhancement of the X-ray signal is observed specifically in the regions of the murine brain where expression of the lacZ reporter gene is also detected histologically. We performed quantitative analysis of the expression levels of lacZ reporter activity by relative radiodensity estimation of the β-galactosidase/X-gal precipitate in situ. To demonstrate the feasibility of the method, we performed expression analysis of the Tsen54-lacZ reporter gene in the murine brain in a semi-quantitative manner. Human mutations in the Tsen54 gene cause pontocerebellar hypoplasia (PCH), a group of severe neurodegenerative disorders with both mental and motor deficits. Comparing relative levels of Tsen54 gene expression, we demonstrate that the highest Tsen54 expression is observed in anatomical brain substructures important for the normal motor and memory functions in mice.

We have developed an open-source software called bi-channel image registration and deep-learning segmentation (BIRDS) for the mapping and analysis of 3D microscopy data and applied this to the mouse brain. The BIRDS pipeline includes image preprocessing, bi-channel registration, automatic annotation, creation of a 3D digital frame, high-resolution visualization, and expandable quantitative analysis. This new bi-channel registration algorithm is adaptive to various types of whole-brain data from different microscopy platforms and shows dramatically improved registration accuracy. Additionally, as this platform combines registration with neural networks, its improved function relative to the other platforms lies in the fact that the registration procedure can readily provide training data for network construction, while the trained neural network can efficiently segment-incomplete/defective brain data that is otherwise difficult to register. Our software is thus optimized to enable either minute-timescale registration-based segmentation of cross-modality, whole-brain datasets or real-time inference-based image segmentation of various brain regions of interest. Jobs can be easily submitted and implemented via a Fiji plugin that can be adapted to most computing environments., eLife digest Mapping all the cells and nerve connections in the mouse brain is a major goal of the neuroscience community, as this will provide new insights into how the brain works and what happens during disease. To achieve this, researchers must first capture three-dimensional images of the brain. These images are then processed using computational tools that can identify distinct anatomical features and cell types within the brain. Various microscopy techniques are used to capture three-dimensional images of the brain. This has led to an increasing number of computational programs that can extract data from these images. However, these tools have been specifically designed for certain microscopy techniques. For example, some work on whole-brain datasets while others are built to analyze specific brain regions. Developing a more flexible, standardized method for annotating microscopy images of the brain would therefore enable researchers to analyze data more efficiently and compare results across experiments. To this end, Wang, Zeng, Yang et al. have designed an open-source software program for extracting features from three-dimensional brain images which have been captured using different microscopes. Similar to other tools, the program uses an ‘image registration’ method that is able to recognize and annotate features in the brain. These tools, however, are limited to whole-brain datasets in which the complete anatomy of each feature must be present in order to be recognized by the software. To overcome this, Wang et al. combined the image registration method with a deep-learning algorithm which uses pixels in the image to identify features in isolated regions of the brain. Although these neural networks do not require whole-brain images, they do need large datasets to ‘learn’ from. Therefore, the image registration method also benefits the neural network by providing a dataset of annotated features that the algorithm can train on. Wang et al. showed that their software program, named BIRDS, could accurately recognize pixel-level brain features within imaging datasets of brain regions, as well as whole-brain images. The deep-learning algorithm could also adapt to analyze various types of imaging data from different microscopy platforms. This open-source software should make it easier for researchers to share, analyze and compare brain imaging datasets from different experiments.

N-glycosylation is a ubiquitous posttranslational modification that affects protein structure and function, including those of the central nervous system. N-glycans attached to cell membrane proteins play crucial roles in all aspects of biology, including embryogenesis, development, cell–cell recognition and adhesion, and cell signaling and communication. Although brain function and behavior are known to be regulated by the N-glycosylation state of numerous cell surface glycoproteins, our current understanding of brain glycosylation is limited, and glycan variations associated with functional brain regions remain largely unknown. In this work, we used a well-established cell surface glycomic nanoLC-Chip-Q-TOF platform developed in our laboratory to characterize the N-glycome of membrane fractions enriched in cell surface glycoproteins obtained from specific functional brain areas. We report the cell membrane N-glycome of two major developmental divisions of mice brain with specific and distinctive functions, namely the forebrain and hindbrain. Region-specific glycan maps were obtained with ∼120 N-glycan compositions in each region, revealing significant differences in “brain-type” glycans involving high mannose, bisecting, and core and antenna fucosylated species. Additionally, the cell membrane N-glycome of three functional regions of the forebrain and hindbrain, the cerebral cortex, hippocampus, and cerebellum, was characterized. In total, 125 N-glycan compositions were identified, and their region-specific expression profiles were characterized. Over 70 N-glycans contributed to the differentiation of the cerebral cortex, hippocampus, and cerebellum N-glycome, including bisecting and branched glycans with varying degrees of core and antenna fucosylation and sialylation. This study presents a comprehensive spatial distribution of the cell-membrane enriched N-glycomes associated with five discrete anatomical and functional brain areas, providing evidence for the presence of a previously unknown brain glyco-architecture. The region-specific molecular glyco fingerprints identified here will enable a better understanding of the critical biological roles that N-glycans play in the specialized functional brain areas in health and disease., Graphical Abstract, Highlights • Cell membrane N-glycome maps of functional mouse brain areas were obtained. • Highly diverse N-glycome varies in a region-specific manner. • 75+ glycan motives discriminate region-specific cell membrane N-glycome., In Brief We have characterized the cell-membrane N-glycome of two major developmental divisions of the brain, the forebrain and hindbrain, and three functional derivatives from them, including the cerebral cortex, hippocampus, and cerebellum, revealing an extraordinary diversity of N-glycans expressed in a global and functional region-specific manner in the adult mouse. Furthermore, we identified +25 N-glycans able to differentiate the forebrain and hindbrain N-glycome. Additionally, over 35 N-glycans distinguished the cortex, hippocampus, and cerebellum N-glycomes and may serve as region-specific glycan biomarkers.

Mice were exposed to ambient PM particles 8 h per day, 6 days per week, for twenty-four weeks in enrichment chambers, with real-time mass concentration of PM2.5 around 70 µg/m3, and the number of PM0.1 about 10,000-20,000/m3. The component analysis of PM particles by inductive coupled plasma emission spectrometer detected low concentrations of species associated with crustal materials, metalloid, transition metals, and heavy metals originating from industrial emission. High-performance liquid chromatography (HPLC) detected 22 polycyclic aromatic hydrocarbons originating from traffic exhausts. We found that PM particles from dirty air entered mouse brain which were visualized by field emission scanning electron microscopy (FE-SEM) and were counted by femtosecond pulsed laser illumination microscopy. FE-SEM of brain tissues from dirty air (n=8), and filtered air (control) (n=8) revealed ultrastructural hallmarks of neuroinflammation, enlarged perivascular space, and the attachment of inflammatory cells to the endothelium of blood vessels in brain. Exposure to dirty air containing ambient PM particles resulted in amyloid deposits and formation of neurofibrillary tangles and plaques. Desorption electrospray ionization mass spectrometry imaging enabled label-free elucidation of the spatial distribution of metabolites and lipids in brain tissue samples without any pretreatment. Ceramide Cer(t18:0/34:0(34OH)), m/z 822.54, and sulfatides, ST18:0, m/z 806.54; ST(d18:1/h22:0), m/z 878.60; ST(24:1), m/z 888.62, and ST(d18:1/h24:0), m/z 906.62 showed upregulation with significant differences in brain tissue from mice exposed to dirty air as compared to filtered air (control). The upregulation of ceramide resulted in formation of neurofibrillary tangles and plaques. Moreover, upregulation of sulfatides might enhance the leakiness of the blood brain barrier by weakening myelin sheaths. Although limited by sample number, our results strongly suggest that prolonged exposure to dirty air contributes to the observed increase in the incidence of cognitive decline and dementia, such as Alzheimer's disease.

Genome-wide association studies have demonstrated significant links between human brain structure and common DNA variants. Similar studies with rodents have been challenging because of smaller brain volumes. Using high field MRI (9.4 T) and compressed sensing, we have achieved microscopic resolution and sufficiently high throughput for rodent population studies. We generated whole brain structural MRI and diffusion connectomes for four diverse isogenic lines of mice (C57BL/6J, DBA/2J, CAST/EiJ, and BTBR) at spatial resolution 20,000 times higher than human connectomes. We measured narrow sense heritability (h2) I.e. the fraction of variance explained by strains in a simple ANOVA model for volumes and scalar diffusion metrics, and estimates of residual technical error for 166 regions in each hemisphere and connectivity between the regions. Volumes of discrete brain regions had the highest mean heritability (0.71 ± 0.23 SD, n = 332), followed by fractional anisotropy (0.54 ± 0.26), radial diffusivity (0.34 ± 0.022), and axial diffusivity (0.28 ± 0.19). Connection profiles were statistically different in 280 of 322 nodes across all four strains. Nearly 150 of the connection profiles were statistically different between the C57BL/6J, DBA/2J, and CAST/EiJ lines. Microscopic whole brain MRI/DTI has allowed us to identify significant heritable phenotypes in brain volume, scalar DTI metrics, and quantitative connectomes.

The mouse is the most important animal model within neuroscientific research, a position strengthened by the wide-spread use of transgenic mouse models. Discoveries in animals are followed by corroboration in humans, and the interchange between these fields of research is essential to our understanding of the human brain. With the advent of advanced technologies such as single-cell transcriptomics, epigenetic profiling and diffusion MRI, many prominent research institutes and collaborations have emerged, aiming to construct complete human or mouse brain atlases with data on gene expression, connectivity and cell types. These initiatives are indispensable resources, but frequently require extensive, time-consuming development, and rely on updates by the provider. They often come in the shape of applications which require practice or prior technical know-how. Importantly, none of them place the human and the mouse brain next to each other to allow for immediate comparison. We present BrainWiki, a user-friendly, web-based atlas that links the human and the mouse brain together, side-by-side. The platform gives the user a simple overview of brain anatomy along with published articles relating to each brain region that allows the user to delve deeper into the current state of research concerning circuitry, brain functions and pathology. The website relies on interactivity and supports user contributions resulting in a dynamic website that evolves at the pace of neuroscience. It is designed to allow for constant updates and new features in the future which will contain data such as gene expression and neuronal cell types.

Accurate removal of magnetic resonance imaging (MRI) signal outside the brain, a.k.a., skull stripping, is a key step in the brain image pre-processing pipelines. In rodents, this is mostly achieved by manually editing a brain mask, which is time-consuming and operator dependent. Automating this step is particularly challenging in rodents as compared to humans, because of differences in brain/scalp tissue geometry, image resolution with respect to brain-scalp distance, and tissue contrast around the skull. In this study, we proposed a deep-learning-based framework, U-Net, to automatically identify the rodent brain boundaries in MR images. The U-Net method is robust against inter-subject variability and eliminates operator dependence. To benchmark the efficiency of this method, we trained and validated our model using both in-house collected and publicly available datasets. In comparison to current state-of-the-art methods, our approach achieved superior averaged Dice similarity coefficient to ground truth T2-weighted rapid acquisition with relaxation enhancement and T2∗-weighted echo planar imaging data in both rats and mice (all p < 0.05), demonstrating robust performance of our approach across various MRI protocols.

Recently, circular RNAs (circRNAs) have been revealed to be an important non-coding element of the transcriptome. The brain contains the most abundant and widespread expression of circRNA. There are also indications that the circular transcriptome undergoes dynamic changes as a result of brain ageing. Diminished cognitive function with increased age reflects the dysregulation of synaptic function and ineffective neurotransmission through alterations of the synaptic proteome. Here, we present changes in the circular transcriptome in ageing synapses using a mouse model. Specifically, we observed an accumulation of uniquely expressed circular transcripts in the synaptosomes of aged mice compared to young mice. Individual circRNA expression patterns were characterized by an increased abundance in the synaptosomes of young or aged mice, whereas the opposite expression was observed for the parental gene linear transcripts. These changes in expression were validated by RT-qPCR. We provide the first comprehensive survey of the circular transcriptome in mammalian synapses, thereby paving the way for future studies. Additionally, we present 16 genes that express solely circRNAs, without linear RNAs co-expression, exclusively in young and aged synaptosomes, suggesting a synaptic gene network that functions along canonical splicing activity.

The visualization of multiple gene expressions in well-preserved tissues is crucial for the elucidation of physiological and pathological processes. In situ hybridization chain reaction (HCR) is a method to visualize specific mRNAs in diverse organisms by applying a HCR that is an isothermal enzyme-free nucleotide polymerization method using hairpin DNAs. Although in situ HCR is a versatile method, this method is not widely used by researchers because of their higher cost than conventional in situ hybridization (ISH). Here, we redesigned hairpin DNAs so that their lengths were half the length of commonly used hairpin DNAs. We also optimized the conjugated fluorophores and linkers. Modified in situ HCR showed sufficient fluorescent signals to detect various mRNAs such as Penk, Oxtr, Vglut2, Drd1, Drd2, and Moxd1 in mouse neural tissues with a high signal-to-noise ratio. The sensitivity of modified in situ HCR in detecting the Oxtr mRNA was better than that of fluorescent ISH using tyramide signal amplification. Notably, the modified in situ HCR does not require proteinase K treatment so that it enables the preservation of morphological structures and antigenicity. The modified in situ HCR simultaneously detected the distributions of c-Fos immunoreactivity and Vglut2 mRNA, and detected multiple mRNAs with a high signal-noise ratio at subcellular resolution in mouse brains. These results suggest that the modified in situ HCR using short hairpin DNAs is cost-effective and useful for the visualization of multiple mRNAs and proteins.

1H MRI maps brain structure and function non-invasively through versatile contrasts that exploit inhomogeneity in tissue micro-environments. Inferring histopathological information from MRI findings, however, remains challenging due to absence of direct links between MRI signals and cellular structures. Here, we show that deep convolutional neural networks, developed using co-registered multi-contrast MRI and histological data of the mouse brain, can estimate histological staining intensity directly from MRI signals at each pixel. The results provide three-dimensional maps of axons and myelin with tissue contrasts that closely mimics target histology and enhanced sensitivity and specificity compared to conventional MRI markers. Furthermore, the relative contribution of each MRI contrast within the networks can be used to optimize multi-contrast MRI acquisition. We anticipate our method to be a starting point for translation of MRI results into easy-to-understand virtual histology for neurobiologists and provide resources for validating novel MRI techniques.

Background Epigenetic (including DNA and histone) modifications occur in a variety of neurological disorders. If epigenetic features of brain autopsy material are to be studied, it is critical to understand the post-mortem stability of the modifications. Methods Pig and mouse brain tissue were formalin-fixed and paraffin-embedded, or frozen after post-mortem delays of 0, 24, 48, and 72 h. Epigenetic modifications frequently reported in the literature were studied by DNA agarose gel electrophoresis, DNA methylation enzyme-linked immunosorbent assays, Western blotting, and immunohistochemistry. We constructed a tissue microarray of human neocortex samples with devitalization or death to fixation times ranging from

Non-invasive high-resolution imaging of the cerebral vascular anatomy and function is key for the study of intracranial aneurysms, stenosis, arteriovenous malformations, and stroke, but also neurological pathologies, such as degenerative diseases. Direct visualization of the microvascular networks in the whole brain remains however challenging in vivo.In this work, we performed 3D ultrafast ultrasound localization microscopy (ULM) using a 2D ultrasound matrix array and mapped the whole-brain microvasculature and flow at microscopic resolution in C57Bl6 mice in vivo.We demonstrated that the mouse brain vasculature can be imaged directly through the intact skull at a spatial resolution of 20 µm and over the whole brain depth and at high temporal resolution (750 volumes.sWe show the potential of 3D ULM to provide new insights into whole-brain vascular flow in mice models at unprecedented vascular scale for an in vivo technique. This technology is highly translational and has the potential to become a major tool for the clinical investigation of the cerebral microcirculation.This study was supported by the European Research Council under the European Union's Seventh Framework Program (FP/2007-2013) / ERC Grant Agreement n° 311025 and by the Fondation Bettencourt-Schueller under the program "Physics for Medicine". We acknowledge the ART (Technological Research Accelerator) biomedical ultrasound program of INSERM.

PET scans of the mouse brain are usually performed with anesthesia to immobilize the animal. However, it is desirable to avoid the confounding factor of anesthesia in mouse-brain response. Methods: We developed and validated brain PET imaging of awake, freely moving mice. Head-motion tracking was performed using radioactive point-source markers, and we used the tracking information for PET-image motion correction. Regional F-18-FDG brain uptake in a test, retest, and memantine-challenge study was measured in awake (n = 8) and anesthetized (n = 8) C57BL/6 mice. An awake uptake period was considered for the anesthesia scans. Results: Awake (motion-corrected) PET images showed an F-18-FDG uptake pattern comparable to the pattern of anesthetized mice. The test-retest variability (represented by the intraclass correlation coefficient) of the regional SUV quantification in the awake animals (0.424-0.555) was marginally lower than that in the anesthetized animals (intraclass correlation coefficient, 0.491-0.629) over the different regions. The increased memantine-induced F-18-FDG uptake was more pronounced in awake (+63.6%) than in anesthetized (+24.2%) animals. Additional behavioral information, acquired for awake animals, showed increased motor activity on a memantine challenge (total distance traveled, 18.2 +/- 5.28 m) compared with test-retest (6.49 +/- 2.21 m). Conclusion: The present method enables brain PET imaging on awake mice, thereby avoiding the confounding effects of anesthesia on the PET reading. It allows the simultaneous measurement of behavioral information during PET acquisitions. The method does not require any additional hardware, and it can be deployed in typical high-throughput scan protocols.

Antisense oligonucleotides (AONs) are versatile molecules that can be used to modulate gene expression by binding to RNA. The therapeutic potential of AONs appears particularly high in the central nervous system, due to excellent distribution and uptake in brain cells, as well as good tolerability in clinical trials thus far. Nonetheless, immune stimulation in response to AON treatment in the brain remains a concern. For this reason we performed RNA sequencing analysis of brain tissue from mice treated intracerebroventricularly with phosphorothioate, 2'-O-methyl modified AONs. A significant upregulation of immune system associated genes was observed in brains of AON treated mice, with the striatum showing largest transcriptional changes. Strongest upregulation was seen for the antiviral enzyme 2'-5'-oligoadenylate synthase-like protein 2 (Oasl2) and Bone marrow stromal antigen 2 (Bst2). Histological analysis confirmed activation of microglia and astrocytes in striatum. The upregulation of immune system associated genes was detectable for at least 2 months after the last AON administration, consistent with a continuous immune response to the AON.

γ-Ethyl-γ-phenyl-butyrolactone (EFBL) is a structural combination of the anticonvulsant γ-hydroxy-γ-ethyl-γ-phenylbutyramide (HEPB) and the hypnotic γ-butyrolactone (GBL), which inherits both properties. To clarify its mechanism of action, the effects of EFBL, GBL and HEPB on dopamine (DA) and noradrenaline (NA) brain levels were investigated. Influences of chlorpromazine, phenelzine and aminooxyacetic acid were also studied. EFBL increased DA in a dose-dependent manner, remaining enhanced by 80 % over a period of 24 h and augmented NA by 54 % one hour after treatment. HEPB increased DA and NA approximately 2-fold after the first hour. GBL raised DA and NA after three and 24 h, resp. EFBL reversed chlorpromazine effects but potentiated those of phenelzine on DA. Amino-oxyacetic modified neither DA nor NA brain levels, not even in the presence of EFBL. The anticonvulsant and hypnotic properties of EFBL are attributed to its effect on presynaptic dopaminergic receptors and its lasting effect on ethyl and phenyl radicals that hinder its degradation. The results support the role of DA and NA in regulating seizure activity in the brain and indicate that EFBL offers a potential treatment for refractory epilepsy without complementary drugs and Parkinson’s disease, without the drawbacks of oral therapies.

Genome-wide association studies (GWAS) for schizophrenia have identified over 100 loci encoding >500 genes. It is unclear whether any of these genes, other than dopamine receptor D2, are immediately relevant to antipsychotic effects or represent novel antipsychotic targets. We applied an in vivo molecular approach to this question by performing RNA sequencing of brain tissue from mice chronically treated with the antipsychotic haloperidol or vehicle. We observed significant enrichments of haloperidol-regulated genes in schizophrenia GWAS loci and in schizophrenia-associated biological pathways. Our findings provide empirical support for overlap between genetic variation underlying the pathophysiology of schizophrenia and the molecular effects of a prototypical antipsychotic.

Brain growth and function are regulated by insulin-like growth factors I and II (IGF-I and IGF-II) but also by IGF-binding proteins (IGFBPs), including IGFBP-2. In addition to modulating IGF activities, IGFBP-2 interacts with a number of components of the extracellular matrix and cell membrane via a Cardin–Weintraub sequence or heparin binding domain (HBD1). The nature and the signalling elicited by these interactions are not fully understood. Here, we examined transgenic mice (H1d-hBP2) overexpressing a mutant human IGFBP-2 that lacks a specific heparin binding domain (HBD1) known as the Cardin–Weintraub sequence. H1d-hBP2 transgenic mice have the genetic background of FVB mice and are characterized by severe deficits in brain growth throughout their lifetime (p < 0.05). In tissue lysates from brain hemispheres of 12–21 day old male mice, protein levels of the GTPase dynamin-I were significantly reduced (p < 0.01). Weight reductions were also found in distinct brain regions in two different age groups (12 and 80 weeks). In the younger group, impaired weights were observed in the hippocampus (− 34%; p < 0.001), cerebellum (− 25%; p < 0.0001), olfactory bulb (− 31%; p < 0.05) and prefrontal cortex (− 29%; p < 0.05). At an age of 12 weeks expression of myelin basic protein was reduced (p < 0.01) in H1d-BP-2 mice in the cerebellum but not in the hippocampus. At 80 weeks of age, weight reductions were similarly present in the cerebellum (− 28%; p < 0.001) and hippocampus (− 31; p < 0.05). When mice were challenged in the elevated plus maze, aged but not younger H1d-hBP2 mice displayed significantly less anxiety-like behaviour, which was also observed in a second transgenic mouse model overexpressing mouse IGFBP-2 lacking HBD1 (H1d-mBP2). These in vivo studies provide, for the first time, evidence for a specific role of IGFBP-2 in brain functions associated with anxiety and risk behaviour. These activities of IGFBP-2 could be mediated by the Cardin–Weintraub/HBD1 sequence and are altered in mice expressing IGFBP-2 lacking the HBD1.

The visualization of multiple gene expressions in well-preserved tissues is crucial for the elucidation of physiological and pathological processes. In situ hybridization chain reaction (HCR) is a method to visualize specific mRNAs in diverse organisms by applying a HCR that is an isothermal enzyme-free nucleotide polymerization method using hairpin DNAs. Although in situ HCR is a versatile method, this method is not widely used by researchers because of their higher cost than conventional in situ hybridization (ISH). Here, we redesigned hairpin DNAs so that their lengths were half the length of commonly used hairpin DNAs. We also optimized the conjugated fluorophores and linkers. Modified in situ HCR showed sufficient fluorescent signals to detect various mRNAs such as Penk, Oxtr, Vglut2, Drd1, Drd2, and Moxd1 in mouse neural tissues with a high signal-to-noise ratio. The sensitivity of modified in situ HCR in detecting the Oxtr mRNA was better than that of fluorescent ISH using tyramide signal amplification. Notably, the modified in situ HCR does not require proteinase K treatment so that it enables the preservation of morphological structures and antigenicity. The modified in situ HCR simultaneously detected the distributions of c-Fos immunoreactivity and Vglut2 mRNA, and detected multiple mRNAs with a high signal-noise ratio at subcellular resolution in mouse brains. These results suggest that the modified in situ HCR using short hairpin DNAs is cost-effective and useful for the visualization of multiple mRNAs and proteins.

Learning has been proposed to coincide with changes in connections between brain regions. In the present study, we used resting-state fMRI (rsfMRI) to map brain-wide functional connectivity (FC) in mice that were trained in the hidden-platform version of the Morris water maze. C57BL6 mice were investigated in a small animal MRI scanner following 2, 10, or 15 days of acquisition learning, or 5 days of reversal learning. Spatial learning coincided with progressive and changing FC between telencephalic regions that have been implemented in spatial learning (such as hippocampus, cingulate, visual, and motor cortex). Search strategy assessment demonstrated that the use of cognitively advanced spatial strategies correlated positively with extensive telencephalic connectivity, whereas non-spatial strategies correlated negatively with connectivity. FC patterns were different and more extensive after reversal learning compared with after extended acquisition learning, which could explain why reversal learning has been shown to be more sensitive to subtle functional defects. ispartof: CEREBRAL CORTEX vol:29 issue:11 pages:4519-4529 ispartof: location:United States status: published

Heightened neuronal plasticity expressed during early postnatal life has been thought to permanently decline once critical periods have ended. For example, monocular deprivation is able to shift ocular dominance in the mouse visual cortex during the first months of life, but this effect is lost later in life. However, various treatments, such as the antidepressant fluoxetine, can reactivate a critical period‐like plasticity in the adult brain. When monocular deprivation is supplemented with chronic fluoxetine administration, a major shift in ocular dominance is produced after the critical period has ended. In the current study, we characterized the temporal patterns of fluoxetine‐induced plasticity in the adult mouse visual cortex, using in vivo optical imaging. We found that artificially induced plasticity in ocular dominance extended beyond the duration of the naturally occurring critical period and continued as long as fluoxetine was administered. However, this fluoxetine‐induced plasticity period ended as soon as the drug was not given. These features of antidepressant‐induced plasticity may be useful when designing treatment strategies involving long‐term antidepressant treatment in humans., Various treatments including antidepressant fluoxetine can reinstate developmental‐like plasticity in adult animals. In the current study, we describe patterns of fluoxetine‐induced plasticity in the mouse visual cortex using in vivo optical imaging.

Derived from arachidonic acid (AA), the endogenous cannabinoid (eCB) 2-arachidonoyl glycerol (2-AG) is a substrate for α/β hydrolase domain-12 (ABHD12). Loss-of-function mutations of ABHD12 are associated with the neurodegenerative disorder polyneuropathy, hearing loss, ataxia, retinitis pigmentosa, and cataract (PHARC). ABHD12 knockout (KO) mice show PHARC-like behaviors in older adulthood. Here, we test the hypothesis that ABHD12 deletion age-dependently regulates bioactive lipids in the CNS. Lipidomics analysis of the brainstem, cerebellum, cortex, hippocampus, hypothalamus, midbrain, striatum and thalamus from male young (3-4 months) and older (7 months) adult ABHD12 KO and age-matched wild-type (WT) mice was performed on over 80 lipids via HPLC/MS/MS, including eCBs, lipoamines, 2-acyl glycerols, free fatty acids, and prostaglandins (PGs). Aging and ABHD12 deletion drove widespread changes in the CNS lipidome; however, the effects of ABHD12 deletion were similar between old and young mice, meaning that many alterations in the lipidome precede PHARC-like symptoms. AA-derived lipids were particularly sensitive to ABHD12 deletion. 2-AG increased in the striatum, hippocampus, cerebellum, thalamus, midbrain, and brainstem, whereas the eCB N-arachidonoyl ethanolamine (AEA) increased in all 8 brain regions, along with at least 2-PGs. Aging also had a widespread effect on the lipidome and more age-related changes in bioactive lipids were found in ABHD12 KO mice than WT suggesting that ABHD12 deletion exacerbates the effects of age. The most robust effects of aging (independent of genotype) across the CNS were decreases in N-acyl GABAs and N-acyl glycines. In conclusion, levels of bioactive lipids are dynamic throughout adulthood and deleting ABHD12 disrupts the wider lipidome, modulating multiple AA-derived lipids with potential consequences for neuropathology.

N-glycosylation is essential for many biological processes in mammals. A variety of N-glycan structures exist, of which, the formation of bisecting N-acetylglucosamine (GlcNAc) is catalyzed by N-acetylglucosaminyltransferase-III (GnT-III, encoded by the Mgat3 gene). We previously identified various bisecting GlcNAc-modified proteins involved in Alzheimer’s disease and cancer. However, the mechanisms by which GnT-III acts on the target proteins are unknown. Here, we performed comparative glycoproteomic analyses using brain membranes of wild type (WT) and Mgat3-deficient mice. Target glycoproteins of GnT-III were enriched with E4-phytohemagglutinin (PHA) lectin, which recognizes bisecting GlcNAc, and analyzed by liquid chromatograph-mass spectrometry. We identified 32 N-glycosylation sites (Asn-Xaa-Ser/Thr, Xaa ≠ Pro) that were modified with bisecting GlcNAc. Sequence alignment of identified N-glycosylation sites that displayed bisecting GlcNAc suggested that GnT-III does not recognize a specific primary amino acid sequence. The molecular modeling of GluA1 as one of the good cell surface substrates for GnT-III in the brain, indicated that GnT-III acts on N-glycosylation sites located in a highly flexible and mobile loop of GluA1. These results suggest that the action of GnT-III is partially affected by the tertiary structure of target proteins, which can accommodate bisecting GlcNAc that generates a bulky flipped-back conformation of the modified glycans.

Background: Luminescent rare-earth-based nanoparticles have been increasingly used in nanomedicine due to their excellent physicochemical properties, such as biomedical imaging agents, drug carriers, and biomarkers. However, biological safety of the rare-earth-based nanomedicine is of great significance for future development in practical applications. In particular, biological effects of rare-earth nanoparticles on human’s central nervous system are still unclear. This study aimed to investigate the potential toxicity of rare-earth nanoparticles in nervous system function in the case of continuous exposure. Methods: Adult ICR mice were randomly divided into seven groups, including control group (receiving 0.9% normal saline) and six experimental groups (10 mice in each group). Luminescent rare-earth-based nanoparticles were synthesized by a reported co-precipitation method. Two different sizes of the nanoparticles were obtained, and then exposed to ICR mice through caudal vein injection at 0.5, 1.0, and 1.5 mg/kg body weight in each day for 7 days. Next, a Morris water maze test was employed to evaluate impaired behaviors of their spatial recognition memory. Finally, histopathological examination was implemented to study how the nanoparticles can affect the brain tissue of the ICR mice. Results: Two different sizes of rare-earth nanoparticles have been successfully obtained, and their physical properties including luminescence spectra and nanoparticle sizes have been characterized. In these experiments, the rare-earth nanoparticles were taken up in the mouse liver using the magnetic resonance imaging characterization. Most importantly, the experimental results of the Morris water maze tests and histopathological analysis clearly showed that rare-earth nanoparticles could induce toxicity on mouse brain and impair the behaviors of spatial recognition memory. Finally, the mechanism of adenosine triphosphate quenching by the rare-earth nanoparticles was provided to illustrate the toxicity on the mouse brain. Conclusions: This study suggested that long-term exposure of high-dose bare rare-earth nanoparticles caused an obvious damage on the spatial recognition memory in the mice. Key words: Mouse Brain; Rare-earth Nanoparticles; Spatial Recognition Memory

// Pan Fang 1 , Xin-jian Wang 2 , Yu Xue 3 , Ming-qi Liu 1 , Wen-feng Zeng 4 , Yang Zhang 1 , Lei Zhang 1 , Xing Gao 1 , Guo-quan Yan 3 , Jun Yao 1 , Hua-li Shen 1, 5 , Peng-yuan Yang 1, 3, 5 1 Minhang Hospital and Institutes of Biomedical Sciences, Fudan University, Shanghai, China 2 State Key Laboratory of Medical Neurobiology, Institutes of Brain Science, and Collaborative Innovation Center for Brain Science, Fudan University, Shanghai, China 3 Department of Chemistry, Fudan University, Shanghai, China 4 Key Laboratory of Intelligent Information Processing of Chinese Academy of Sciences (CAS), Institute of Computing Technology, CAS, Beijing, China 5 Department of Systems Biology for Medicine and School of Basic Medical Sciences, Fudan University, Shanghai, China Correspondence to: Hua-li Shen, email: shenhuali@fudan.edu.cn Peng-yuan Yang, email: pyyang@fudan.edu.cn Keywords: N-glycoproteomics, mouse brain, mass spectrometry, brain physiological activities, disease biomarker Received: January 25, 2016 Accepted: April 26, 2016 Published: May 31, 2016 ABSTRACT N-glycosylation is one of the most prominent and abundant posttranslational modifications of proteins. It is estimated that over 50% of mammalian proteins undergo glycosylation. However, the analysis of N-glycoproteins has been limited by the available analytical technology. In this study, we comprehensively mapped the N-glycosylation sites in the mouse brain proteome by combining complementary methods, which included seven protease treatments, four enrichment techniques and two fractionation strategies. Altogether, 13492 N-glycopeptides containing 8386 N-glycosylation sites on 3982 proteins were identified. After evaluating the performance of the above methods, we proposed a simple and efficient workflow for large-scale N-glycosylation site mapping. The optimized workflow yielded 80% of the initially identified N-glycosylation sites with considerably less effort. Analysis of the identified N-glycoproteins revealed that many of the mouse brain proteins are N-glycosylated, including those proteins in critical pathways for nervous system development and neurological disease. Additionally, several important biomarkers of various diseases were found to be N-glycosylated. These data confirm that N-glycosylation is important in both physiological and pathological processes in the brain, and provide useful details about numerous N-glycosylation sites in brain proteins.

The presence of networks of correlation between regional gray matter volume as measured across subjects in a group of individuals has been consistently described in several human studies, an approach termed structural covariance MRI (scMRI). Complementary to prevalent brain mapping modalities like functional and diffusion-weighted imaging, the approach can provide precious insights into the mutual influence of trophic and plastic processes in health and pathological states. To investigate whether analogous scMRI networks are present in lower mammal species amenable to genetic and experimental manipulation such as the laboratory mouse, we employed high resolution morphoanatomical MRI in a large cohort of genetically-homogeneous wild-type mice (C57Bl6/J) and mapped scMRI networks using a seed-based approach. We show that the mouse brain exhibits robust homotopic scMRI networks in both primary and associative cortices, a finding corroborated by independent component analyses of cortical volumes. Subcortical structures also showed highly symmetric inter-hemispheric correlations, with evidence of distributed antero-posterior networks in diencephalic regions of the thalamus and hypothalamus. Hierarchical cluster analysis revealed six identifiable clusters of cortical and sub-cortical regions corresponding to previously described neuroanatomical systems. Our work documents the presence of homotopic cortical and subcortical scMRI networks in the mouse brain, thus supporting the use of this species to investigate the elusive biological and neuroanatomical underpinnings of scMRI network development and its derangement in neuropathological states. The identification of scMRI networks in genetically homogeneous inbred mice is consistent with the emerging view of a key role of environmental factors in shaping these correlational networks.

Despite vast numbers of studies of stained cells in the mouse brain, no current brain atlas provides region-by-region neuron counts. In fact, neuron numbers are only available for about 4% of brain of regions and estimates often vary by as much as 3-fold. Here we provide a first 3D cell atlas for the whole mouse brain, showing cell positions constructed algorithmically from whole brain Nissl and gene expression stains, and compared against values from the literature. The atlas provides the densities and positions of all excitatory and inhibitory neurons, astrocytes, oligodendrocytes, and microglia in each of the 737 brain regions defined in the AMBA. The atlas is dynamic, allowing comparison with previously reported numbers, addition of cell types, and improvement of estimates as new data is integrated. The atlas also provides insights into cellular organization only possible at this whole brain scale, and is publicly available.

The natural sciences always and only enhance the human condition by producing knowledge which empowers us to control the natural world, where otherwise it would control us. Nowhere is the power of uncontrollable natural phenomena to curb or limit human well-being more pervasive than in the human mind itself. Monoamines are a class of neurotransmitters consistently implicated in the etiology of nonvolitional neuropsychological phenomena. They are a cornerstone of those mental functions which humans most desire, but are least able to control. Unsurprisingly, drugs targeting these neurotransmitter systems are widely used in clinical, therapeutic, performance-enhancing, and recreational contexts. To the detriment of patients and users, however, currently available drugs are strongly lacking in terms of effect amplitude, reliability, and persistence, as well as suitability for long-term use. We present novel research, which advances the descriptive understanding of drug-naïve monoaminergic function and of monoaminergic drug effects. Our work includes methods development, the investigation of functional monoaminergic neurophenotypes, and the imaging-based profiling of longitudinal drug treatment. The neurobiological representations we put forward are instrumental to refining the understanding of psychopharmacological intervention profiles and the phenomena which they are able to modulate. Methodologically, we tackle technological impediments to large-scale (longitudinal, multi-cohort, and multi-center) preclinical brain imaging. Our first article deals with the challenge of automatically and reliably preparing preclinical magnetic resonance imaging (MRI) data for sharing and analysis. Our second article deals with the improvement of mouse brain registration and the definition of a reference space. Both of the above, as well as further relevant data analysis, rely heavily on high-level software tools. We consequently make an excursion into neuroscientific software management, which needs to be as accessible, reproducible, and transparent as the research it supports. In our third article we present the first whole-brain read-out of ventral tegmental area (VTA) dopaminergic signalling in the mouse. We perform a multivariate analysis of experiment parameters, and formulate specific guidelines for assay reuse or refinement. In our fourth article we apply a previously established serotonergic activity read-out to a longitudinal selective serotonin reuptake inhibitor (SSRI) drug treatment. We produce the first functional neuroimaging profile of longitudinal serotonergic drug effects, and we identify distinct brain clusters based on longitudinal activation trajectories. Our findings both support the autoinhibition down-regulation theory for the SSRI action mechanism, and complement it, by suggesting a prominent role for brainstem involvement. As all trajectories show significant treatment but no post-treatment effects, we also provide neuroimaging evidence strongly suggesting that the intervention fails to elicit persistent homeostatic shifts in healthy subjects. We openly share all acquired data, and all code required to reproduce our analyses. We suggest that the novel methods and the neurophenotypical profiling concept which we put forward may revitalize psychopharmacological research. Our work ultimately serves to advance the understanding of monoaminergic function and its manipulation, as is needed to fulfill the increasing need for the betterment of the human mind, in and outside of the clinical context.

Toll-like receptors (TLRs) are widely expressed in mammalian brain. Involvement in neurodegeneration and hypoxia has been evidenced for several microglial TLRs. In order to investigate interplay of specific microglial and neuronal transmembrane proteins and its potential role in neurodegeneration, we use TLR2 knock-out (KO ) mice (C57BL/6 TLR2-/-).Our preliminary findings indicate different expression of synaptic transmembrane protein neuroplastin (Np) in brain tissue of TLR2 KO mice in comparison with wild- type littermates (WT).Neuroplastin, a cell- adhesion molecule found in two isoforms (Np65 and Np55) is an essential auxiliary subunit of plasma membrane Ca2+ ATPase (PMCA ). In addition, Np is influenced by glycosphingolipid environment of the membrane, which is also the case for another ion pumping enzyme, Na+/K+-ATPase (NKA). Since Np, PMCA and NKA all seem to favor specific lipid milieu in order to function optimally, and at least some of them are confirmed to interact with one another, we investigated the expression of these proteins in TLR2 KO compared to WT across different brain regions.We isolated membrane fractions from cortical, hippocampal and cerebellar tissue of 5 WT and 5 KO animals, and analyzed the expression of Np, NKA and PMCA by Western blotting. Data revealed increased expression level of Np isoforms and PMCA in cortex and hippocampus in TLR2 KO, and decreased expression of Np55 and PMCA in the cerebellum. NKA exhibited the same expression pattern in TLR2 KO vs WT, and increased expression in all regions analyzed (cortex, hippocampus, cerebellum). Furthermore, we investigated the cortical NKA activity which is lower in TLR2 KO mice.This data together with ongoing immunohistochemistry and transcriptional analysis will enable more detailed neurobiochemical characterization of TLR2 KO model, and give insight into functional implications of differential regional distribution of here analyzed proteins involved in synaptic plasticity and membrane ion transport.

Recent advances in viral vector and nanomaterial sciences have opened the way for new cutting-edge approaches to investigate or manipulate the central nervous system (CNS). However, further optimization of these technologies would benefit from methods allowing rapid and streamline determination of the extent of CNS and cell-specific targeting upon administration of viral vectors or nanoparticles in the body. Here, we present a protocol that takes advantage of the high throughput and multiplexing capabilities of flow cytometry to allow a straightforward quantification of different cell subtypes isolated from mouse brain or spinal cord, namely microglia/macrophages, lymphocytes, astrocytes, oligodendrocytes, neurons and endothelial cells. We apply this approach to highlight critical differences between two tissue homogenization methods in terms of cell yield, viability and composition. This could instruct the user to choose the best method depending on the cell type(s) of interest and the specific application. This method is not suited for analysis of anatomical distribution, since the tissue is homogenized to generate a single-cell suspension. However, it allows to work with viable cells and it can be combined with cell-sorting, opening the way for several applications that could expand the repertoire of tools in the hands of the neuroscientist, ranging from establishment of primary cultures derived from pure cell populations, to gene-expression analyses and biochemical or functional assays on well-defined cell subtypes in the context of neurodegenerative diseases, upon pharmacological treatment or gene therapy.

International audience; To develop a Compressed Sensing (CS)-MP2RAGE sequence to drastically shorten acquisition duration and then detect and measure the T1 of brain metastases in mice at 7 T.METHODS:The encoding trajectory of the standard Cartesian MP2RAGE sequence has been modified (1) to obtain a variable density Poisson disk under-sampling distribution along the ky -kz plane, and (2) to sample the central part of the k-space exactly at TI1 and TI2 inversion times. In a prospective study, the accuracy of the T1 measurements was evaluated on phantoms containing increasing concentrations of gadolinium. The CS acceleration factors were increased to evaluate their influence on the contrast and T1 measurements of brain metastases in vivo. Finally, the 3D T1 maps were acquired with at 4-fold increased spatial resolution. The volumes and T1 values of the metastases were measured while using CS to reduce scan time.RESULTS:The implementation of the CS-encoding trajectory did not affect the T1 measurements in vitro. Accelerating the acquisition by a factor of 2 did not alter the contrast or the T1 values of the brain metastases. 3D T1 maps could be obtained in < 1 min using a CS factor of 6. Increasing the spatial resolution enabled more accurately measurement of the metastasis volumes while maintaining an acquisition duration below 5 min.CONCLUSION:The CS-MP2RAGE sequence could be of great interest in oncology to either rapidly obtain mouse brain 3D T1 maps or to increase the spatial resolution with no penalty on the scan duration.

Confocal detection in digital scanned laser light-sheet fluorescence microscopy (DSLM) has been established as a gold standard method to improve image quality. The selective line detection of a complementary metal-oxide-semiconductor camera (CMOS) working in rolling shutter mode allows the rejection of out-of-focus and scattered light, thus reducing background signal during image formation. Most modern CMOS have two rolling shutters, but usually only a single illuminating beam is used, halving the maximum obtainable frame rate. We report on the capability to recover the full image acquisition rate via dual confocal DSLM by using an acoustooptic deflector. Such a simple solution enables us to independently generate, control and synchronize two beams with the two rolling slits on the camera. We show that the doubling of the imaging speed does not affect the confocal detection high contrast. (C) The Authors. Published by SPIE under a Creative Commons Attribution 4.0 Unported License.