The Allen Mouse Brain Common Coordinate Framework: A 3D Reference Atlas.

Recent large-scale collaborations are generating major surveys of cell types and connections in the mouse brain, collecting large amounts of data across modalities, spatial scales, and brain areas. Successful integration of these data requires a standard 3D reference atlas. Here, we present the Allen Mouse Brain Common Coordinate Framework (CCFv3) as such a resource. We constructed an average template brain at 10 µm voxel resolution by interpolating high resolution in-plane serial two-photon tomography images with 100 µm z-sampling from 1,675 young adult C57BL/6J mice. Then, using multimodal reference data, we parcellated the entire brain directly in 3D, labeling every voxel with a brain structure spanning 43 isocortical areas and their layers, 329 subcortical gray matter structures, 81 fiber tracts, and 8 ventricular structures. CCFv3 can be used to analyze, visualize, and integrate multimodal and multiscale datasets in 3D and is openly accessible (https://atlas.brain-map.org/).

HCR spectral imaging: 10-plex, quantitative, high-resolution RNA and protein imaging in highly autofluorescent samples.

Signal amplification based on the mechanism of hybridization chain reaction (HCR) provides a unified framework for multiplex, quantitative, high-resolution imaging of RNA and protein targets in highly autofluorescent samples. With conventional bandpass imaging, multiplexing is typically limited to four or five targets owing to the difficulty in separating signals generated by fluorophores with overlapping spectra. Spectral imaging has offered the conceptual promise of higher levels of multiplexing, but it has been challenging to realize this potential in highly autofluorescent samples, including whole-mount vertebrate embryos. Here, we demonstrate robust HCR spectral imaging with linear unmixing, enabling simultaneous imaging of ten RNA and/or protein targets in whole-mount zebrafish embryos and mouse brain sections. Further, we demonstrate that the amplified and unmixed signal in each of the ten channels is quantitative, enabling accurate and precise relative quantitation of RNA and/or protein targets with subcellular resolution, and RNA absolute quantitation with single-molecule resolution, in the anatomical context of highly autofluorescent samples.

Benchmarking mapping algorithms for cell-type annotating in mouse brain by integrating single-nucleus RNA-seq and Stereo-seq data.

Limited gene capture efficiency and spot size of spatial transcriptome (ST) data pose significant challenges in cell-type characterization. The heterogeneity and complexity of cell composition in the mammalian brain make it more challenging to accurately annotate ST data from brain. Many algorithms attempt to characterize subtypes of neuron by integrating ST data with single-nucleus RNA sequencing (snRNA-seq) or single-cell RNA sequencing. However, assessing the accuracy of these algorithms on Stereo-seq ST data remains unresolved. Here, we benchmarked 9 mapping algorithms using 10 ST datasets from four mouse brain regions in two different resolutions and 24 pseudo-ST datasets from snRNA-seq. Both actual ST data and pseudo-ST data were mapped using snRNA-seq datasets from the corresponding brain regions as reference data. After comparing the performance across different areas and resolutions of the mouse brain, we have reached the conclusion that both robust cell-type decomposition and SpatialDWLS demonstrated superior robustness and accuracy in cell-type annotation. Testing with publicly available snRNA-seq data from another sequencing platform in the cortex region further validated our conclusions. Altogether, we developed a workflow for assessing suitability of mapping algorithm that fits for ST datasets, which can improve the efficiency and accuracy of spatial data annotation.

Merged magnetic resonance and light sheet microscopy of the whole mouse brain.

We have developed workflows to align 3D magnetic resonance histology (MRH) of the mouse brain with light sheet microscopy (LSM) and 3D delineations of the same specimen. We start with MRH of the brain in the skull with gradient echo and diffusion tensor imaging (DTI) at 15 µm isotropic resolution which is ~ 1,000 times higher than that of most preclinical MRI. Connectomes are generated with superresolution tract density images of ~5 µm. Brains are cleared, stained for selected proteins, and imaged by LSM at 1.8 µm/pixel. LSM data are registered into the reference MRH space with labels derived from the ABA common coordinate framework. The result is a high-dimensional integrated volume with registration (HiDiver) with alignment precision better than 50 µm. Throughput is sufficiently high that HiDiver is being used in quantitative studies of the impact of gene variants and aging on mouse brain cytoarchitecture and connectomics.

Ultrafast two-photon fluorescence imaging of cerebral blood circulation in the mouse brain in vivo.

Characterizing blood flow dynamics in vivo is critical to understanding the function of the vascular network under physiological and pathological conditions. Existing methods for hemodynamic imaging have insufficient spatial and temporal resolution to monitor blood flow at the cellular level in large blood vessels. By using an ultrafast line-scanning module based on free-space angular chirped enhanced delay, we achieved two-photon fluorescence imaging of cortical blood flow at 1,000 two-dimensional (2D) frames and 1,000,000 one-dimensional line scans per second in the awake mouse. This orders-of-magnitude increase in temporal resolution allowed us to measure cerebral blood flow at up to 49 mm/s and observe pulsatile blood flow at harmonics of heart rate. Directly visualizing red blood cell (RBC) flow through vessels down to >800 µm in depth, we characterized cortical layer­dependent flow velocity distributions of capillaries, obtained radial velocity profiles and kilohertz 2D velocity mapping of multifile blood flow, and performed RBC flux measurements from penetrating blood vessels.

A diffusion MRI-based spatiotemporal continuum of the embryonic mouse brain for probing gene-neuroanatomy connections.

The embryonic mouse brain undergoes drastic changes in establishing basic anatomical compartments and laying out major axonal connections of the developing brain. Correlating anatomical changes with gene-expression patterns is an essential step toward understanding the mechanisms regulating brain development. Traditionally, this is done in a cross-sectional manner, but the dynamic nature of development calls for probing gene-neuroanatomy interactions in a combined spatiotemporal domain. Here, we present a four-dimensional (4D) spatiotemporal continuum of the embryonic mouse brain from E10.5 to E15.5 reconstructed from diffusion magnetic resonance microscopy (dMRM) data. This study achieved unprecedented high-definition dMRM at 30- to 35-µm isotropic resolution, and together with computational neuroanatomy techniques, we revealed both morphological and microscopic changes in the developing brain. We transformed selected gene-expression data to this continuum and correlated them with the dMRM-based neuroanatomical changes in embryonic brains. Within the continuum, we identified distinct developmental modes comprising regional clusters that shared developmental trajectories and similar gene-expression profiles. Our results demonstrate how this 4D continuum can be used to examine spatiotemporal gene-neuroanatomical interactions by connecting upstream genetic events with anatomical changes that emerge later in development. This approach would be useful for large-scale analysis of the cooperative roles of key genes in shaping the developing brain.

Sex matters: The MouseX DW-ALLEN Atlas for mice diffusion-weighted MR imaging.

Overcoming sex bias in preclinical research requires not only including animals of both sexes in the experiments, but also developing proper tools to handle such data. Recent work revealed sensitivity of diffusion-weighted MRI to glia morphological changes in response to inflammatory stimuli, opening up exciting possibilities to characterize inflammation in a variety of preclinical models of pathologies, the great majority of them available in mice. However, there are limited resources dedicated to mouse imaging, like those required for the data processing and analysis. To fill this gap, we build a mouse MRI template of both structural and diffusion contrasts, with anatomical annotation according to the Allen Mouse Brain Atlas, the most detailed public resource for mouse brain investigation. To achieve a standardized resource, we use a large cohort of animals in vivo, and include animals of both sexes. To prove the utility of this resource to integrate imaging and molecular data, we demonstrate significant association between the mean diffusivity from MRI and gene expression-based glia density. To demonstrate the need of equitable sex representation, we compared across sexes the warp fields needed to match a male-based template, and our template built with both sexes. Then, we use both templates for analysing mice imaging data obtained in animals of different ages, demonstrating that using a male-based template creates spurious significant sex effects, not present otherwise. All in all, our MouseX DW-ALLEN Atlas will be a widely useful resource getting us one step closer to equitable healthcare.

A Spatial Transcriptomics Browser for Discovering Gene Expression Landscapes across Microscopic Tissue Sections.

A crucial feature of life is its spatial organization and compartmentalization on the molecular, cellular, and tissue levels. Spatial transcriptomics (ST) technology has opened a new chapter of the sequencing revolution, emerging rapidly with transformative effects across biology. This technique produces extensive and complex sequencing data, raising the need for computational methods for their comprehensive analysis and interpretation. We developed the ST browser web tool for the interactive discovery of ST images, focusing on different functional aspects such as single gene expression, the expression of functional gene sets, as well as the inspection of the spatial patterns of cell-cell interactions. As a unique feature, our tool applies self-organizing map (SOM) machine learning to the ST data. Our SOM data portrayal method generates individual gene expression landscapes for each spot in the ST image, enabling its downstream analysis with high resolution. The performance of the spatial browser is demonstrated by disentangling the intra-tumoral heterogeneity of melanoma and the microarchitecture of the mouse brain. The integration of machine-learning-based SOM portrayal into an interactive ST analysis environment opens novel perspectives for the comprehensive knowledge mining of the organization and interactions of cellular ecosystems.

Hybridization chain reaction enables a unified approach to multiplexed, quantitative, high-resolution immunohistochemistry and in situ hybridization.

RNA in situ hybridization based on the mechanism of the hybridization chain reaction (HCR) enables multiplexed, quantitative, high-resolution RNA imaging in highly autofluorescent samples, including whole-mount vertebrate embryos, thick brain slices and formalin-fixed paraffin-embedded tissue sections. Here, we extend the benefits of one-step, multiplexed, quantitative, isothermal, enzyme-free HCR signal amplification to immunohistochemistry, enabling accurate and precise protein relative quantitation with subcellular resolution in an anatomical context. Moreover, we provide a unified framework for simultaneous quantitative protein and RNA imaging with one-step HCR signal amplification performed for all target proteins and RNAs simultaneously.

Molecular tracking of interactions between progenitor and endothelial cells via Raman and FTIR spectroscopy imaging: a proof of concept of a new analytical strategy for in vitro research.

Circulating endothelial cell progenitors originating from the bone marrow are considered to be a powerful tool in the repair of endothelium damage. Due to their unique properties, endothelial progenitors are now broadly investigated to assess their clinical significance in diseases e.g., associated with brain endothelial dysfunction. However, their distinction in terms of the expression of specific markers remains ambiguous. Additionally, endothelial progenitor cells may change their repertoire of markers depending on the microenvironment of the tissue in which they are currently located. Here, we applied the label-free Raman and FTIR imaging to discriminate mice brain endothelium and endothelial progenitors. Cells cultured separately showed distinctly different spectral signatures extracted from the whole cellular interior as well as the detected intracellular compartments (nucleus, cytoplasm, perinuclear area, and lipid droplets). Then, we used these spectroscopic signals to examine the cells co-cultured for 24 h. Principal cluster analysis showed their grouping with the progenitor cells and segregation from brain endothelium at a level of the entire cell machinery (in FTIR images) which resulted from biochemical alternations in the cytoplasm and lipid droplets (in Raman images). The models included in partial least square regression indicated that lipid droplets are the key element for the classification of endothelial progenitor-brain endothelial cells interactions.

Sleep deprivation boosts O2·- levels in the brains of mice as visualized by a Golgi apparatus-targeted ratiometric fluorescence nanosensor.

Sleep deprivation (SD) is highly prevalent in the modern technological world. Emerging evidence shows that sleep deprivation is associated with oxidative stress. At the organelle level, the Golgi apparatus actively participates in the stress response. In this study, to determine whether SD and Golgi apparatus stress are correlated, we rationally designed and fabricated a novel Golgi apparatus-targeted ratiometric nanoprobe called Golgi dots for O2·- detection. This probe exhibits high sensitivity and selectivity in cells and brain slices of sleep-deprived mice. Golgi dots can be readily synthesized by coprecipitation of Golgi-F127, an amphiphilic polymer F127 modified with a Golgi apparatus targeting moiety, caffeic acid (CA), the responsive unit for O2·-, and red emissive carbon nanodots (CDs), which act as the reference signal. The fluorescence emission spectrum of the developed nanoprobe showed an intense peak at 674 nm, accompanied by a shoulder peak at 485 nm. As O2·- was gradually added, the fluorescence at 485 nm continuously increased; in contrast, the emission intensity at 674 nm assigned to the CDs remained constant, resulting in the ratiometric sensing of O2·-. The present ratiometric nanoprobe showed high selectivity for O2·- monitoring due to the specific recognition of O2·- by CA. Moreover, the Golgi dots exhibited good linearity with respect to the O2·- concentration within 5 to 40 µM, and the limit of detection (LOD) was ~ 0.13 µM. Additionally, the Golgi dots showed low cytotoxicity and an ability to target the Golgi apparatus. Inspired by these excellent properties, we then applied the Golgi dots to successfully monitor exogenous and endogenous O2·- levels within the Golgi apparatus. Importantly, with the help of Golgi dots, we determined that SD substantially elevated O2·- levels in the brain.

IP-LC-MSMS Enables Identification of Three Tau O-GlcNAcylation Sites as O-GlcNAcase Inhibition Pharmacodynamic Readout in Transgenic Mice Overexpressing Human Tau.

O-ß-linked N-acetylglucosaminylation (O-GlcNAcylation) modulates tau phosphorylation and aggregation: the pharmacological increase of tau O-GlcNAcylation upon treatment with inhibitors of O-GlcNAc hydrolase (OGA) constitutes a potential strategy to tackle neurodegenerative diseases. Analysis of tau O-GlcNAcylation could potentially be used as a pharmacodynamic biomarker both in preclinical and clinical studies. The goal of the current study was to confirm tau O-GlcNAcylation at S400 as a pharmacodynamic readout of OGA inhibition in P301S transgenic mice overexpressing human tau and treated with the OGA inhibitor Thiamet G and to explore if additional O-GlcNAcylation sites on tau could be identified. As a first step, an immunoprecipitation-liquid chromatography-mass spectrometry (IP-LC-MS) methodology was developed to monitor changes in O-GlcNAcylation around S400 of tau in mouse brain homogenate (BH) extracts. Second, additional O-GlcNAc sites were identified in in-house produced recombinant O-GlcNAcylated human tau at relatively high concentrations, thereby facilitating collection of informative LC-MS data for identification of low-concentration O-GlcNAc-tryptic tau peptides in human transgenic mouse BH extracts. This strategy enabled, for the first time, identification of three low abundant N-terminal and mid-domain O-GlcNAc sites of tau (at S208, S191, and S184 or S185) in human transgenic mouse BH. Data are openly available at data.mendeley.com (doi: 10.17632/jp57yk9469.1; doi: 10.17632/8n5j45dnd8.1; doi: 10.17632/h5vdrx4n3d.1).

Mouse Model of Fragile X Syndrome Analyzed by Quantitative Proteomics: A Comparison of Methods.

Multiple methods for quantitative proteomics are available for proteome profiling. It is unclear which methods are most useful in situations involving deep proteome profiling and the detection of subtle distortions in the proteome. Here, we compared the performance of seven different strategies in the analysis of a mouse model of Fragile X Syndrome, involving the knockout of the fmr1 gene that is the leading cause of autism spectrum disorder. Focusing on the cerebellum, we show that data-independent acquisition (DIA) and the tandem mass tag (TMT)-based real-time search method (RTS) generated the most informative profiles, generating 334 and 329 significantly altered proteins, respectively, although the latter still suffered from ratio compression. Label-free methods such as BoxCar and a conventional data-dependent acquisition were too noisy to generate a reliable profile, while TMT methods that do not invoke RTS showed a suppressed dynamic range. The TMT method using the TMTpro reagents together with complementary ion quantification (ProC) overcomes ratio compression, but current limitations in ion detection reduce sensitivity. Overall, both DIA and RTS uncovered known regulators of the syndrome and detected alterations in calcium signaling pathways that are consistent with calcium deregulation recently observed in imaging studies. Data are available via ProteomeXchange with the identifier PXD039885.

Using mesoscopic tract-tracing data to guide the estimation of fiber orientation distributions in the mouse brain from diffusion MRI.

Diffusion MRI (dMRI) tractography is the only tool for non-invasive mapping of macroscopic structural connectivity over the entire brain. Although it has been successfully used to reconstruct large white matter tracts in the human and animal brains, the sensitivity and specificity of dMRI tractography remained limited. In particular, the fiber orientation distributions (FODs) estimated from dMRI signals, key to tractography, may deviate from histologically measured fiber orientation in crossing fibers and gray matter regions. In this study, we demonstrated that a deep learning network, trained using mesoscopic tract-tracing data from the Allen Mouse Brain Connectivity Atlas, was able to improve the estimation of FODs from mouse brain dMRI data. Tractography results based on the network generated FODs showed improved specificity while maintaining sensitivity comparable to results based on FOD estimated using a conventional spherical deconvolution method. Our result is a proof-of-concept of how mesoscale tract-tracing data can guide dMRI tractography and enhance our ability to characterize brain connectivity.

Towards reliable reconstruction of the mouse brain corticothalamic connectivity using diffusion MRI.

Diffusion magnetic resonance imaging (dMRI) tractography has yielded intriguing insights into brain circuits and their relationship to behavior in response to gene mutations or neurological diseases across a number of species. Still, existing tractography approaches suffer from limited sensitivity and specificity, leading to uncertain interpretation of the reconstructed connections. Hence, in this study, we aimed to optimize the imaging and computational pipeline to achieve the best possible spatial overlaps between the tractography and tracer-based axonal projection maps within the mouse brain corticothalamic network. We developed a dMRI-based atlas of the mouse forebrain with structural labels imported from the Allen Mouse Brain Atlas (AMBA). Using the atlas and dMRI tractography, we first reconstructed detailed node-to-node mouse brain corticothalamic structural connectivity matrices using different imaging and tractography parameters. We then investigated the effects of each condition for accurate reconstruction of the corticothalamic projections by quantifying the similarities between the tractography and the tracer data from the Allen Mouse Brain Connectivity Atlas (AMBCA). Our results suggest that these parameters significantly affect tractography outcomes and our atlas can be used to investigate macroscopic structural connectivity in the mouse brain. Furthermore, tractography in mouse brain gray matter still face challenges and need improved imaging and tractography methods.

Evaluation of eGFP expression in the ChAT-eGFP transgenic mouse brain.

BACKGROUND: A historically definitive marker for cholinergic neurons is choline acetyltransferase (ChAT), a synthesizing enzyme for acetylcholine, (ACh), which can be found in high concentrations in cholinergic neurons, both in the central and peripheral nervous systems. ChAT, is produced in the body of the neuron, transported to the nerve terminal (where its concentration is highest), and catalyzes the transfer of an acetyl group from the coenzyme acetyl-CoA to choline, yielding ACh. The creation of bacterial artificial chromosome (BAC) transgenic mice that express promoter-specific fluorescent reporter proteins (green fluorescent protein-[GFP]) provided an enormous advantage for neuroscience. Both in vivo and in vitro experimental methods benefited from the transgenic visualization of cholinergic neurons. Mice were created by adding a BAC clone into the ChAT locus, in which enhanced GFP (eGFP) is inserted into exon 3 at the ChAT initiation codon, robustly and supposedly selectively expressing eGFP in all cholinergic neurons and fibers in the central and peripheral nervous systems as well as in non-neuronal cells. METHODS: This project systematically compared the exact distribution of the ChAT-eGFP expressing neurons in the brain with the expression of ChAT by immunohistochemistry using mapping and also made comparisons with in situ hybridization (ISH). RESULTS: We qualitatively described the distribution of ChAT-eGFP neurons in the mouse brain by comparing it with the distribution of immunoreactive neurons and ISH data, paying special attention to areas where the expression did not overlap, such as the cortex, striatum, thalamus and hypothalamus. We found a complete overlap between the transgenic expression of eGFP and the immunohistochemical staining in the areas of the cholinergic basal forebrain. However, in the cortex and hippocampus, we found small neurons that were only labeled with the antibody and not expressed eGFP or vice versa. Most importantly, we found no transgenic expression of eGFP in the lateral dorsal, ventral and dorsomedial tegmental nuclei cholinergic cells. CONCLUSION: While the majority of the forebrain ChAT expression was aligned in the transgenic animals with immunohistochemistry, other areas of interest, such as the brainstem should be considered before choosing this particular transgenic mouse line.

Prenatal heroin exposure alters brain morphology and connectivity in adolescent mice.

The United States is experiencing a dramatic increase in maternal opioid misuse and, consequently, the number of individuals exposed to opioids in utero. Prenatal opioid exposure has both acute and long-lasting effects on health and wellbeing. Effects on the brain, often identified at school age, manifest as cognitive impairment, attention deficit, and reduced scholastic achievement. The neurobiological basis for these effects is poorly understood. Here, we examine how in utero exposure to heroin affects brain development into early adolescence in a mouse model. Pregnant C57BL/6J mice received escalating doses of heroin twice daily on gestational days 4-18. The brains of offspring were assessed on postnatal day 28 using 9.4 T diffusion MRI of postmortem specimens at 36 µm resolution. Whole-brain volumes and the volumes of 166 bilateral regions were compared between heroin-exposed and control offspring. We identified a reduction in whole-brain volume in heroin-exposed offspring and heroin-associated volume changes in 29 regions after standardizing for whole-brain volume. Regions with bilaterally reduced standardized volumes in heroin-exposed offspring relative to controls include the ectorhinal and insular cortices. Regions with bilaterally increased standardized volumes in heroin-exposed offspring relative to controls include the periaqueductal gray, septal region, striatum, and hypothalamus. Leveraging microscopic resolution diffusion tensor imaging and precise regional parcellation, we generated whole-brain structural MRI diffusion connectomes. Using a dimension reduction approach with multivariate analysis of variance to assess group differences in the connectome, we found that in utero heroin exposure altered structure-based connectivity of the left septal region and the region that acts as a hub for limbic regulatory actions. Consistent with clinical evidence, our findings suggest that prenatal opioid exposure may have effects on brain morphology, connectivity, and, consequently, function that persist into adolescence. This work expands our understanding of the risks associated with opioid misuse during pregnancy and identifies biomarkers that may facilitate diagnosis and treatment.

Comparison of two types of microscopic diffusion anisotropy in mouse brain.

Two distinct types of microscopic diffusion anisotropy (MA) are compared in brain for both normal control and transgenic (3xTg-AD) mice, which develop Alzheimer's disease pathology. The first type of MA is the commonly used microscopic fractional anisotropy (µFA), and the second is a new MA measure referred to as µFA'. These two MA parameters have different symmetry properties that are central to their physical interpretations. Specifically, µFA is invariant with respect to local rotations of compartmental diffusion tensors while µFA' is invariant with respect to global diffusion tensor deformations. A key distinction between µFA and µFA' is that µFA is affected by the same type of orientationally coherent diffusion anisotropy as the conventional fractional anisotropy (FA) while µFA' is not. Furthermore, µFA can be viewed as having independent contributions from FA and µFA', as is quantified by an equation relating all three anisotropies. The normal control and transgenic mice are studied at ages ranging from 2 to 15 months, with double diffusion encoding MRI being used to estimate µFA and µFA'. µFA and µFA' are nearly identical in low FA brain regions, but they show notable differences when FA is large. In particular, µFA and FA are found to be strongly correlated in the fimbria, but µFA' and FA are not. In addition, both µFA and µFA' are seen to increase with age in the corpus callosum and external capsule, and modest differences between normal control and transgenic mice are observed for µFA and µFA' in the corpus callosum and for µFA in the fimbria. The triad of FA, µFA, and µFA' is proposed as a useful combination of parameters for assessing diffusion anisotropy in brain.

Region-specific mouse brain ganglioside distribution revealed by an improved isobaric aminoxyTMT labeling strategy with automated data processing.

Gangliosides are specialized glycosphingolipids most abundant in the central nervous system. Their complex amphiphilic structure is essential to the formation of membrane lipid rafts and for molecular recognition. Dysfunction of lipid rafts and ganglioside metabolism has been linked to cancer, metabolic disorders, and neurodegenerative disorders. Changes in ganglioside concentration and diversity during the progression of disease have made them potential biomarkers for early detection and shed light on disease mechanisms. Chemical derivatization facilitates whole ion analysis of gangliosides while improving ionization, providing rich fragmentation spectra, and enabling multiplexed analysis schemes such as stable isotope labeling. In this work, we report improvement to our previously reported isobaric labeling methodology for ganglioside analysis by increasing buffer concentration and removing solid-phase extraction desalting for a more complete and quantitative reaction. Identification and quantification of gangliosides are automated through MS-DIAL with an in-house ganglioside derivatives library. We have applied the updated methodology to relative quantification of gangliosides in six mouse brain regions (cerebellum, pons/medulla, midbrain, thalamus/hypothalamus, cortex, and basal ganglia) with 2 mg tissue per sample, and region-specific distributions of 88 ganglioside molecular species are described with ceramide isomers resolved. This method is promising for application to comparative analysis of gangliosides in biological samples.

Characterization of N-glycome profile in mouse brain tissue regions by MALDI-TOF/MS.

Glycosylation is one of the most common types of post-translational modifications in mammals. It is well known that N-glycans play a key role in cell adhesion, differentiation, synapsis, and myelination during the development of the mammalian central nervous system (CNS). Neuropathological symptoms (such as epilepsy and Alzheimer's disease) are usually accompanied by N-glycosylation changes. In this study, we extracted N-glycan chains from eight regions of the mouse brain, and combined high-throughput, high-resolution matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF/MS) with the Fmoc N-hydroxysuccinimide ester (Fmoc-OSU) derivatization method to improve the sensitivity of glycan detection to characterize the total N-glycans in the mouse brain. A total of 96 N-glycan moieties were detected. An exhaustive examination of the relative abundance of N-glycans, coupled with a comparative analysis of differences, has uncovered discernible variations of statistical significance, including high mannose, fucosylated, sialylated, and galactosylated N-glycans. According to our investigations, a thorough and regionally specific cartography of glycans within the brain can facilitate the investigation of glycan-mediated mechanisms related to both the developmental trajectory and functional output of the brain. Additionally, this approach may serve as a basis for identifying potential biomarkers that are relevant to various brain-associated pathologies.