Sensitive detection of multiple blood biomarkers via immunomagnetic exosomal PCR for the diagnosis of Alzheimer's disease.

Blood exosomes are emerging as potential biomarkers for diagnosing brain diseases such as Alzheimer's disease (AD). There is currently a lack of an ultrasensitive technology for identifying core AD biomarkers in blood exosomes to optimize the utility of biomarkers in clinical practice. Here, an immunomagnetic exosomal polymerase chain reaction (iMEP) platform was developed using DNA-conjugated antibodies for the rapid detection of amyloid-ß (Aß1-40 and Aß1-42) and phosphorylated tau (p-tau396,404 and p-tau181) in clinical blood exosomes. The toehold shift-mediated DNA affinity pulldown eliminates the high detection background, which allows the detection of biomarkers at concentrations down to 10 femtograms per milliliter. With the iMEP assay, exosomal Aß1-42 was more accurate in differentiating patients with AD from healthy individuals compared with exosomal p-tau181 and p-tau396,404, with a sensitivity of 95.0% and a specificity of 95.0%. The iMEP technique is also adept at quantifying the levels of different exosomal biomarkers associated with disease pathogenesis.

Whole-brain spatial organization of hippocampal single-neuron projectomes.

Mapping single-neuron projections is essential for understanding brain-wide connectivity and diverse functions of the hippocampus (HIP). Here, we reconstructed 10,100 single-neuron projectomes of mouse HIP and classified 43 projectome subtypes with distinct projection patterns. The number of projection targets and axon-tip distribution depended on the soma location along HIP longitudinal and transverse axes. Many projectome subtypes were enriched in specific HIP subdomains defined by spatial transcriptomic profiles. Furthermore, we delineated comprehensive wiring diagrams for HIP neurons projecting exclusively within the HIP formation (HPF) and for those projecting to both intra- and extra-HPF targets. Bihemispheric projecting neurons generally projected to one pair of homologous targets with ipsilateral preference. These organization principles of single-neuron projectomes provide a structural basis for understanding the function of HIP neurons.

Non-invasive modulation of meningeal lymphatics ameliorates ageing and Alzheimer's disease-associated pathology and cognition in mice.

Meningeal lymphatic vessels (mLVs) have been shown to be involved in amyloid beta (Aß) clearance, which is considered as a potential therapeutic target for Alzheimer's disease (AD). In this study, based on the superficial spatial distribution of mLVs, a near-infrared light is employed to modulate lymphatic drainage, significantly improving cognition of both aged and AD (5xFAD and APP/PS1) mice, and alleviating AD-associated pathology by reducing Aß deposition, neuroinflammation and neuronal damage. Furthermore, transmission electron microscopy imaging and RNA sequencing data indicate amelioration of mitochondrial metabolism and cellular junction of meningeal lymphatic endothelial cells (mLECs) by light modulation. These studies collectively suggest that near-infrared light treatment can improve cognitive function by strengthening scavenging ability of mLVs through restoring mLEC function. In conclusion, lymphatic drainage potentiation by light promotes pathological remission and cognitive enhancement in aging and AD mouse models, which offers a potential amelioration strategy for neurodegenerative diseases.

Microglia regulate sleep through calcium-dependent modulation of norepinephrine transmission.

Sleep interacts reciprocally with immune system activity, but its specific relationship with microglia-the resident immune cells in the brain-remains poorly understood. Here, we show in mice that microglia can regulate sleep through a mechanism involving Gi-coupled GPCRs, intracellular Ca2+ signaling and suppression of norepinephrine transmission. Chemogenetic activation of microglia Gi signaling strongly promoted sleep, whereas pharmacological blockade of Gi-coupled P2Y12 receptors decreased sleep. Two-photon imaging in the cortex showed that P2Y12-Gi activation elevated microglia intracellular Ca2+, and blockade of this Ca2+ elevation largely abolished the Gi-induced sleep increase. Microglia Ca2+ level also increased at natural wake-to-sleep transitions, caused partly by reduced norepinephrine levels. Furthermore, imaging of norepinephrine with its biosensor in the cortex showed that microglia P2Y12-Gi activation significantly reduced norepinephrine levels, partly by increasing the adenosine concentration. These findings indicate that microglia can regulate sleep through reciprocal interactions with norepinephrine transmission.

Triptolide induces apoptosis and cytoprotective autophagy by ROS accumulation via directly targeting peroxiredoxin 2 in gastric cancer cells.

Triptolide, a natural bioactive compound derived from herbal medicine Tripterygium wilfordii, has multiple biological activities including anti-cancer effect, which is being tested in clinical trials for treating cancers. However, the exact mechanism by which Triptolide exerts its cytotoxic effects, particularly its specific protein targets, remains unclear. Here, we show that Triptolide effectively induces cytotoxicity in gastric cancer cells by increasing reactive oxygen species (ROS) levels. Further investigations reveal that ROS accumulation contributes to the induction of Endoplasmic Reticulum (ER) stress, and subsequently autophagy induction in response to Triptolide. Meanwhile, this autophagy is cytoprotective. Interestingly, through activity-based protein profiling (ABPP) approach, we identify peroxiredoxins-2 (PRDX2), a component of the key enzyme systems that act in the defense against oxidative stress and protect cells against hydroperoxides, as direct binding target of Triptolide. By covalently binding to PRDX2 to inhibit its antioxidant activity, Triptolide increases ROS levels. Moreover, overexpression of PRDX2 inhibits and knockdown of the expression of PRDX2 increases Triptolide-induced apoptosis. Collectively, these results indicate PRDX2 as a direct target of Triptolides for inducing apoptosis. Our results not only provide novel insight into the underlying mechanisms of Triptolide-induced cytotoxic effects, but also indicate PRDX2 as a promising potential therapeutic target for developing anti-gastric cancer agents.

Single-neuron projectomes of mouse paraventricular hypothalamic nucleus oxytocin neurons reveal mutually exclusive projection patterns.

Oxytocin (OXT) plays important roles in autonomic control and behavioral modulation. However, it is unknown how the projection patterns of OXT neurons align with underlying physiological functions. Here, we present the reconstructed single-neuron, whole-brain projectomes of 264 OXT neurons of the mouse paraventricular hypothalamic nucleus (PVH) at submicron resolution. These neurons hierarchically clustered into two groups, with distinct morphological and transcriptional characteristics and mutually exclusive projection patterns. Cluster 1 (177 neurons) axons terminated exclusively in the median eminence (ME) and have few collaterals terminating within hypothalamic regions. By contrast, cluster 2 (87 neurons) sent wide-spread axons to multiple brain regions, but excluding ME. Dendritic arbors of OXT neurons also extended outside of the PVH, suggesting capability to sense signals and modulate target regions. These single-neuron resolution observations reveal distinct OXT subpopulations, provide comprehensive analysis of their morphology, and lay the structural foundation for better understanding the functional heterogeneity of OXT neurons.

Designing a Hybrid Chain Reaction Probe for Multiplex Transcripts Assay with High-Level Imaging.

The hybrid chain reaction (HCR), an isothermal and enzyme-free amplification strategy, has found extensive use in fluorescent in situ hybridization (FISH) assays. However, the existing HCRs are limited, being time-consuming processes and low-efficiency imaging due to weak signal, significantly restricting their application in transcriptomic assays. To address the limitations, we developed nine orthogonal HCR hairpin-pair (hp) probes in this study to enable efficient signal amplification for multiplex assays. To enhance the efficiency and imaging quality of multiplex assays using these HCR probes, we employed two strategies. First, we coupled fluorescent molecules to HCR hairpins via disulfide bonds, facilitating easy removal through chemical cleavage. As a result, the workflow was greatly simplified. Second, we combined HCR with in situ rolling circle amplification (ISRCA), creating ISRCA-HCR, which achieved a 17-fold signal amplification. ISRCA-HCR demonstrated a high-level imaging capability for spatial cell type assays. This study shows the application for cell typing based on the developed HCR probes, enabling accurate and high-level signal amplification for multiplex FISH imaging. This provides an effective research tool for transcriptome and spatial cell type analysis.

FastCellpose: A Fast and Accurate Deep-Learning Framework for Segmentation of All Glomeruli in Mouse Whole-Kidney Microscopic Optical Images.

Automated evaluation of all glomeruli throughout the whole kidney is essential for the comprehensive study of kidney function as well as understanding the mechanisms of kidney disease and development. The emerging large-volume microscopic optical imaging techniques allow for the acquisition of mouse whole-kidney 3D datasets at a high resolution. However, fast and accurate analysis of massive imaging data remains a challenge. Here, we propose a deep learning-based segmentation method called FastCellpose to efficiently segment all glomeruli in whole mouse kidneys. Our framework is based on Cellpose, with comprehensive optimization in network architecture and the mask reconstruction process. By means of visual and quantitative analysis, we demonstrate that FastCellpose can achieve superior segmentation performance compared to other state-of-the-art cellular segmentation methods, and the processing speed was 12-fold higher than before. Based on this high-performance framework, we quantitatively analyzed the development changes of mouse glomeruli from birth to maturity, which is promising in terms of providing new insights for research on kidney development and function.

On-line clearing and staining method for the efficient optical imaging of large volume samples at the cellular resolution.

Optical microscopy is a powerful tool for exploring the structure and function of organisms. However, the three-dimensional (3D) imaging of large volume samples is time-consuming and difficult. In this manuscript, we described an on-line clearing and staining method for efficient imaging of large volume samples at the cellular resolution. The optimized cocktail can increase staining and imaging depth to reduce the sectioning and scanning time, more than doubling the operational efficiency of the system. Using this method, we demonstrated the rapid acquisition of Aß plaques in whole mouse brain and obtained a complete set of cytoarchitecture images of an adult porcine hemisphere at 1.625 × 1.625 × 10 µm3 voxel resolution for about 49 hours.

Cerebral Organoid Arrays for Batch Phenotypic Analysis in Sections and Three Dimensions.

Organoids can recapitulate human-specific phenotypes and functions in vivo and have great potential for research in development, disease modeling, and drug screening. Due to the inherent variability among organoids, experiments often require a large sample size. Embedding, staining, and imaging each organoid individually require a lot of reagents and time. Hence, there is an urgent need for fast and efficient methods for analyzing the phenotypic changes in organoids in batches. Here, we provide a comprehensive strategy for array embedding, staining, and imaging of cerebral organoids in both agarose sections and in 3D to analyze the spatial distribution of biomarkers in organoids in situ. We constructed several disease models, particularly an aging model, as examples to demonstrate our strategy for the investigation of the phenotypic analysis of organoids. We fabricated an array mold to produce agarose support with microwells, which hold organoids in place for live/dead imaging. We performed staining and imaging of sectioned organoids embedded in agarose and 3D imaging to examine phenotypic changes in organoids using fluorescence micro-optical sectioning tomography (fMOST) and whole-mount immunostaining. Parallel studies of organoids in arrays using the same staining and imaging parameters enabled easy and reliable comparison among different groups. We were able to track all the data points obtained from every organoid in an embedded array. This strategy could help us study the phenotypic changes in organoids in disease models and drug screening.

3D autofluorescence imaging of hydronephrosis and renal anatomical structure using cryo-micro-optical sectioning tomography.

Rationale: Mesoscopic visualization of the main anatomical structures of the whole kidney in vivo plays an important role in the pathological diagnosis and exploration of the etiology of hydronephrosis. However, traditional imaging methods cannot achieve whole-kidney imaging with micron resolution under conditions representing in vivo perfusion. Methods: We used in vivo cryofixation (IVCF) to fix acute obstructive hydronephrosis (unilateral ureteral obstruction, UUO), chronic spontaneous hydronephrosis (db/db mice), and their control mouse kidneys for cryo-micro-optical sectioning tomography (cryo-MOST) autofluorescence imaging. We quantitatively assessed the kidney-wide pathological changes in the main anatomical structures, including hydronephrosis, renal subregions, arteries, veins, glomeruli, renal tubules, and peritubular functional capillaries. Results: By comparison with microcomputed tomography imaging, we confirmed that IVCF can maintain the status of the kidney in vivo. Cryo-MOST autofluorescence imaging can display the main renal anatomical structures with a cellular resolution without contrast agents. The hydronephrosis volume reached 26.11 ± 6.00 mm3 and 13.01 ± 3.74 mm3 in 3 days after UUO and in 15-week-old db/db mouse kidneys, respectively. The volume of the cortex and inner stripe of the outer medulla (ISOM) increased while that of the inner medulla (IM) decreased in UUO mouse kidneys. Db/db mice also showed an increase in the volume of the cortex and ISOM volume but no atrophy in the IM. The diameter of the proximal convoluted tubule and proximal straight tubule increased in both UUO and db/db mouse kidneys, indicating that proximal tubules were damaged. However, some renal tubules showed abnormal central bulge highlighting in the UUO mice, but the morphology of renal tubules was normal in the db/db mice, suggesting differences in the pathology and severity of hydronephrosis between the two models. UUO mouse kidneys also showed vascular damage, including segmental artery and vein atrophy and arcuate vein dilation, and the density of peritubular functional capillaries in the cortex and IM was reduced by 37.2% and 49.5%, respectively, suggesting renal hypoxia. In contrast, db/db mouse kidneys showed a normal vascular morphology and peritubular functional capillary density. Finally, we found that the db/db mice displayed vesicoureteral reflux and bladder overactivity, which may be the cause of hydronephrosis formation. Conclusions: We observed and compared main renal structural changes in hydronephrosis under conditions representing in vivo perfusion in UUO, db/db, and control mice through cryo-MOST autofluorescence imaging. The results indicate that cryo-MOST with IVCF can serve as a simple and powerful tool to quantitatively evaluate the in vivo pathological changes in three dimensions, especially the distribution of body fluids in the whole kidney. This method is potentially applicable to the three-dimensional visualization of other tissues, organs, and even the whole body, which may provide new insights into pathological changes in diseases.

A corticoamygdalar pathway controls reward devaluation and depression using dynamic inhibition code.

Reward devaluation adaptively controls reward intake. It remains unclear how cortical circuits causally encode reward devaluation in healthy and depressed states. Here, we show that the neural pathway from the anterior cingulate cortex (ACC) to the basolateral amygdala (BLA) employs a dynamic inhibition code to control reward devaluation and depression. Fiber photometry and imaging of ACC pyramidal neurons reveal reward-induced inhibition, which weakens during satiation and becomes further attenuated in depression mouse models. Ablating or inhibiting these neurons desensitizes reward devaluation, causes reward intake increase and ultimate obesity, and ameliorates depression, whereas activating the cells sensitizes reward devaluation, suppresses reward consumption, and produces depression-like behaviors. Among various ACC neuron subpopulations, the BLA-projecting subset bidirectionally regulates reward devaluation and depression-like behaviors. Our study thus uncovers a corticoamygdalar circuit that encodes reward devaluation via blunted inhibition and suggests that enhancing inhibition within this circuit may offer a therapeutic approach for treating depression.

Full-Spectrum Neuronal Diversity and Stereotypy through Whole Brain Morphometry.

We conducted a large-scale study of whole-brain morphometry, analyzing 3.7 peta-voxels of mouse brain images at the single-cell resolution, producing one of the largest multi-morphometry databases of mammalian brains to date. We spatially registered 205 mouse brains and associated data from six Brain Initiative Cell Census Network (BICCN) data sources covering three major imaging modalities from five collaborative projects to the Allen Common Coordinate Framework (CCF) atlas, annotated 3D locations of cell bodies of 227,581 neurons, modeled 15,441 dendritic microenvironments, characterized the full morphology of 1,891 neurons along with their axonal motifs, and detected 2.58 million putative synaptic boutons. Our analysis covers six levels of information related to neuronal populations, dendritic microenvironments, single-cell full morphology, sub-neuronal dendritic and axonal arborization, axonal boutons, and structural motifs, along with a quantitative characterization of the diversity and stereotypy of patterns at each level. We identified 16 modules consisting of highly intercorrelated brain regions in 13 functional brain areas corresponding to 314 anatomical regions in CCF. Our analysis revealed the dendritic microenvironment as a powerful method for delineating brain regions of cell types and potential subtypes. We also found that full neuronal morphologies can be categorized into four distinct classes based on spatially tuned morphological features, with substantial cross-areal diversity in apical dendrites, basal dendrites, and axonal arbors, along with quantified stereotypy within cortical, thalamic and striatal regions. The lamination of somas was found to be more effective in differentiating neuron arbors within the cortex. Further analysis of diverging and converging projections of individual neurons in 25 regions throughout the brain reveals branching preferences in the brain-wide and local distributions of axonal boutons. Overall, our study provides a comprehensive description of key anatomical structures of neurons and their types, covering a wide range of scales and features, and contributes to our understanding of neuronal diversity and its function in the mammalian brain.

Deep self-learning enables fast, high-fidelity isotropic resolution restoration for volumetric fluorescence microscopy.

One intrinsic yet critical issue that troubles the field of fluorescence microscopy ever since its introduction is the unmatched resolution in the lateral and axial directions (i.e., resolution anisotropy), which severely deteriorates the quality, reconstruction, and analysis of 3D volume images. By leveraging the natural anisotropy, we present a deep self-learning method termed Self-Net that significantly improves the resolution of axial images by using the lateral images from the same raw dataset as rational targets. By incorporating unsupervised learning for realistic anisotropic degradation and supervised learning for high-fidelity isotropic recovery, our method can effectively suppress the hallucination with substantially enhanced image quality compared to previously reported methods. In the experiments, we show that Self-Net can reconstruct high-fidelity isotropic 3D images from organelle to tissue levels via raw images from various microscopy platforms, e.g., wide-field, laser-scanning, or super-resolution microscopy. For the first time, Self-Net enables isotropic whole-brain imaging at a voxel resolution of 0.2 × 0.2 × 0.2 µm3, which addresses the last-mile problem of data quality in single-neuron morphology visualization and reconstruction with minimal effort and cost. Overall, Self-Net is a promising approach to overcoming the inherent resolution anisotropy for all classes of 3D fluorescence microscopy.

Rapid and High-Sensitive Phosphoproteomics Elucidated the Spatial Dynamics of the Mouse Brain.

Recent developments in phosphoproteomics have enabled signaling studies where over 10,000 phosphosites can be routinely identified and quantified. Yet, current analyses are limited in sample size, reproducibility, and robustness, hampering experiments that involve low-input samples such as rare cells and fine-needle aspiration biopsies. To address these challenges, we introduced a simple and rapid phosphorylation enrichment method (miniPhos) that uses a minimal amount of the sample to get enough information to decipher biological significance. The miniPhos approach completed the sample pretreatment within 4 h and high effectively collected the phosphopeptides in a single-enrichment format with an optimized enrichment process and miniaturized system. This resulted in an average of 22,000 phosphorylation peptides quantified from 100 µg of proteins and even confidently localized over 4500 phosphosites from as little as 10 µg of peptides. Further application was carried out on different layers of mouse brain micro-sections; our miniPhos method provided quantitative information on protein abundance and phosphosite regulation for the most relevant neurodegenerative diseases, cancers, and signaling pathways in the mouse brain. Surprisingly, the phosphoproteome exhibited more spatial variations than the proteome in the mouse brain. Overall, spatial dynamics of phosphosites are integrated with proteins to gain insights into crosstalk of cellular regulation at different layers, thereby facilitating a more comprehensive understanding of mouse brain development and activity.

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.

scLiverDB: a Database of Human and Mouse Liver Transcriptome Landscapes at Single-Cell Resolution.

The liver is critical for the digestive and immune systems. Although the physiology and pathology of liver have been well studied and many scRNA-seq data are generated, a database and landscape for characterizing cell types and gene expression in different liver diseases or developmental stages at single-cell resolution are lacking. Hence, scLiverDB is developed, a specialized database for human and mouse liver transcriptomes to unravel the landscape of liver cell types, cell heterogeneity and gene expression at single-cell resolution across various liver diseases/cell types/developmental stages. To date, 62 datasets including 9,050 samples and 1,741,734 cells is curated. A uniform workflow is used, which included quality control, dimensional reduction, clustering, and cell-type annotation to analyze datasets on the same platform; integrated manual and automatic methods for accurate cell-type identification and provided a user-friendly web interface with multiscale functions. There are two case studies to show the usefulness of scLiverDB, which identified the LTB (lymphotoxin Beta) gene as a potential biomarker of lymphoid cells differentiation and showed the expression changes of Foxa3 (forkhead box A3) in liver chronic progressive diseases. This work provides a crucial resource to resolve molecular and cellular information in normal, diseased, and developing human and mouse livers.

Deep background-mismodeling-learned reconstruction for high-accuracy fluorescence diffuse optical tomography.

We present a deep background-mismodeling-learned reconstruction framework for high-accuracy fluorescence diffuse optical tomography (FDOT). A learnable regularizer incorporating background mismodeling is formulated in the form of certain mathematical constraints. The regularizer is then learned to obtain the background mismodeling automatically using a physics-informed deep network implicitly. Here, a deep-unrolled FIST-Net for optimizing L1-FDOT is specially designed to obtain fewer learning parameters. Experiments show that the accuracy of FDOT is significantly improved via implicitly learning the background mismodeling, which proves the validity of the deep background-mismodeling-learned reconstruction. The proposed framework can also be used as a general method to improve a class of image modalities based on linear inverse problems with unknown background modeling errors.

Data-Driven Morphological Feature Perception of Single Neuron With Graph Neural Network.

Clarifying the morphological characteristics of neurons can promote the understanding of brain function. However, traditional morphometrics fail to capture the modeling of each point in reconstructed neurons, leading to limited ability to distinguish massive nerve fibers and restricted application scenarios. To address these challenges, we propose MorphoGNN, a single neuron morphological embedding based on a graph neural network in this study. MorphoGNN learns the point-level structure information of reconstructed nerve fibers by considering their nearest neighbors on each hidden layer. This enables MorphoGNN to capture the lower-dimensional representation of a single neuron through an end-to-end model. In order to meet the requirements of various tasks, both supervised and self-supervised training strategies are designed to learn the characteristics that fit artificial semantics or the morphological patterns of neurons, respectively. We quantitatively compare our embeddings with other features in neuron classification and retrieval tasks and demonstrate cutting-edge performance. Additionally, we introduce our embeddings to the task of reconstruction quality classification and neuron clustering, where they can help detect reconstruction errors and obtain similar subtyping results to existing work. Furthermore, our method can be handily combined with other modal features, such as microscopic image features and traditional morphometrics. Ablation and robustness tests are also conducted to analyze the impact of several network components and low-quality reconstructed neurons on the performance of our method. The code is available at https://github.com/fun0515/MorphoGNN.