Biology subjects

Wei, D.

Publications and source records attributed to Wei, D..

At least 55 records · Page 3Linked to original sources

bioRxiv2023

A large-scale volumetric correlated light and electron microscopy study localizes Alzheimer's disease-related molecules in the hippocampus

Connectomics using volume-electron-microscopy enables mapping and analysis of neuronal networks, revealing insights into neural circuit function and dysfunction. In Alzheimers disease (AD), where amyloid-{beta} (A{beta}) and hyperphosphorylated-Tau (pTau) are implicated, connectomics offers an approach to unravel how these molecules contribute to circuit alterations by enabling the study of these molecules within the context of the complete local neuronal and glial milieu. We present a volumetric-correlated-light-and-electron microscopy (vCLEM) protocol using fluorescent nanobodies to localize A{beta} and pTau within a large-scale connectomics dataset from the hippocampus of the 3xTg AD mouse model. A key outcome of this work is a publicly accessible vCLEM dataset, featuring fluorescent labeling of A{beta} and pTau in the ultrastructural context with segmented neurons, glia, and synapses. This dataset provides a unique resource for exploring AD pathology in the context of connectomics and fosters collaborative opportunities in neurodegenerative disease research. As a proof-of-principle, we uncovered new localizations of A{beta} and pTau, including pTau-positive spine-like protrusions at the axon initial segment and changes in the number and size of synapses near A{beta} plaques. Our vCLEM approach facilitates the discovery of both molecular and structural alterations within large-scale EM data, advancing connectomics research in Alzheimers and other neurodegenerative diseases.

neuroscience↗

bioRxiv2023

Functional connectome through the human life span

The lifespan growth of the functional connectome remains unknown. Here, we assemble task-free functional and structural magnetic resonance imaging data from 33,250 individuals aged 32 postmenstrual weeks to 80 years from 132 global sites. We report critical inflection points in the nonlinear growth curves of the global mean and variance of the connectome, peaking in the late fourth and late third decades of life, respectively. After constructing a fine-grained, lifespan-wide suite of system-level brain atlases, we show distinct maturation timelines for functional segregation within different systems. Lifespan growth of regional connectivity is organized along a primary-to-association cortical axis. These connectome-based normative models reveal substantial individual heterogeneities in functional brain networks in patients with autism spectrum disorder, major depressive disorder, and Alzheimers disease. These findings elucidate the lifespan evolution of the functional connectome and can serve as a normative reference for quantifying individual variation in development, aging, and neuropsychiatric disorders.

neuroscience↗

bioRxiv2023

Multiplexed Volumetric CLEM enabled by antibody derivatives provides new insights into the cytology of the mouse cerebellar cortex

Mapping neuronal networks that underlie behavior has become a central focus in neuroscience. While serial section electron microscopy (ssEM) can reveal the fine structure of neuronal networks (connectomics), it does not provide the molecular information that helps identify cell types or their functional properties. Volumetric correlated light and electron microscopy (vCLEM) combines ssEM and volumetric fluorescence microscopy to incorporate molecular labeling into ssEM datasets. We developed an approach that uses small fluorescent single-chain variable fragment (scFv) immuno-probes to perform multiplexed detergent-free immuno-labeling and ssEM on the same samples. We generated eight such fluorescent scFvs that targeted useful markers for brain studies (green fluorescent protein, glial fibrillary acidic protein, calbindin, parvalbumin, voltage-gated potassium channel subfamily A member 2, vesicular glutamate transporter 1, postsynaptic density protein 95, and neuropeptide Y). To test the vCLEM approach, six different fluorescent probes were imaged in a sample of the cortex of a cerebellar lobule (Crus 1), using confocal microscopy with spectral unmixing, followed by ssEM imaging of the same sample. The results show excellent ultrastructure with superimposition of the multiple fluorescence channels. Using this approach we could document a poorly described cell type in the cerebellum, two types of mossy fiber terminals, and the subcellular localization of one type of ion channel. Because scFvs can be derived from existing monoclonal antibodies, hundreds of such probes can be generated to enable molecular overlays for connectomic studies.

neuroscience↗

bioRxiv2023

Murine Alveolar Macrophages Rapidly Accumulate Intranasally Administered SARS-CoV-2 Spike Protein leading to Neutrophil Recruitment and Damage

The trimeric SARS-CoV-2 Spike protein mediates viral attachment facilitating cell entry. Most COVID-19 vaccines direct mammalian cells to express the Spike protein or deliver it directly via inoculation to engender a protective immune response. The trafficking and cellular tropism of the Spike protein in vivo and its impact on immune cells remains incompletely elucidated. In this study we inoculated mice intranasally, intravenously, and subcutaneously with fluorescently labeled recombinant SARS-CoV-2 Spike protein. Using flow cytometry and imaging techniques we analyzed its localization, immune cell tropism, and acute functional impact. Intranasal administration led to rapid lung alveolar macrophage uptake, pulmonary vascular leakage, and neutrophil recruitment and damage. When injected near the inguinal lymph node medullary, but not subcapsular macrophages, captured the protein, while scrotal injection recruited and fragmented neutrophils. Wide-spread endothelial and liver Kupffer cell uptake followed intravenous administration. Human peripheral blood cells B cells, neutrophils, monocytes, and myeloid dendritic cells all efficiently bound Spike protein. Exposure to the Spike protein enhanced neutrophil NETosis and augmented human macrophage TNF- and IL-6 production. Human and murine immune cells employed C-type lectin receptors and Siglecs to help capture the Spike protein. This study highlights the potential toxicity of the SARS-CoV-2 Spike protein for mammalian cells and illustrates the central role for alveolar macrophage in pathogenic protein uptake.

immunology↗

bioRxiv2023

Reconstruction of TrkB complex assemblies and localizing an-tidepressant targets using Artificial Intelligence

Since Major Depressive Disorder (MDD) represents a neurological pathology caused by inter-synaptic messaging errors, membrane receptors, the source of signal cascades, constitute appealing drugs targets. G protein-coupled receptors (GPCRs) and ion channel receptors chelated antidepressants (ADs) high-resolution architectures were reported to realize receptors physical mechanism and design prototype compounds with minimal side effects. Tyrosine kinase receptor 2 (TrkB), a receptor that directly modulates synaptic plasticity, has a finite three-dimensional chart due to its high molecular mass and intrinsically disordered regions (IDRs). Leveraging breakthroughs in deep learning, the meticulous architecture of TrkB was projected employing Alphfold 2 (AF2). Furthermore, the Alphafold Multimer algorithm (AF-M) models the coupling of intra- and extra-membrane topologies to chaperones: mBDNF, SHP2, Etc. Conjugating firmly dimeric transmembrane helix with novel compounds like 2R,6R-hydroxynorketamine (2R,6R-HNK) expands scopes of drug screening to encompass all coding sequences throughout genomes. The operational implementation of TrkB kinase-SHP2, PLC{gamma}1, and SHC1 ensembles has paved the path for machine learning in which it can forecast structural transitions in the self-assembly and self-dissociation of molecules during trillions of cellular mechanisms. In silicon, the cornerstone of the alteration will be artificial intelligence (AI), empowering signal networks to operate at the atomic level and picosecond timescales.

bioinformatics↗

bioRxiv2023

Mapping Neurophysiological Subtypes of Major Depressive Disorder Using Normative Models of the Functional Connectome

Major depressive disorder (MDD) is the most burdensome psychiatric disorder characterized by remarkably heterogeneous clinical phenotypes. It remains challenging to delineate the heterogeneity of neurobiological abnormalities underlying the clinical variance and, on this basis, to identify neurophysiological subtypes of MDD patients. Here, using a large multisite resting-state functional MRI data from 1,148 MDD patients and 1,079 healthy controls, we generated lifespan normative models of functional connectivity strengths, mapped the heterogeneity of patients individual deviations, and identified neurobiological MDD subtypes. MDD patients showed positive deviations mainly in the default mode and subcortical areas, and negative deviations widely distributed over the cortex. However, there was a great inter-subject heterogeneity as indicated by that no more than 3.14% of patients deviated from the normative range for any brain region. Two neurophysiological MDD subtypes were identified. Subtype 1 showed severe deviations with positive deviations in the default mode, limbic, and subcortical areas, and negative deviations in the sensorimotor, dorsal and ventral attention areas, while subtype 2 showed a moderate but conversed deviation pattern. The severe-deviation subtype had older age, higher medicated proportion, and higher Suicide item score, while the moderate-deviation subtype showed higher Work and Activities and Depressed Mood item scores. Moreover, the baseline deviations in the severe-deviation subtype were predictive of 6-month antidepressant treatment effects in a subsample. To our knowledge, the current study is the largest multisite analysis of neurophysiological MDD subtyping to date and the findings shed light on our understanding of the biological mechanisms underlying the intersubject heterogeneity of clinical phenotypes, which are informative for the development of personalized treatments for this disorder.

neuroscience↗

bioRxiv2023

CALCIUM-DEPENDENT PROTEIN KINASE32 regulates cellulose biosynthesis through post-translational modification of cellulose synthase

Cellulose is an economically important source of food, paper, textiles, and biofuel. As an essential component of plant cell walls, cellulose is critical for plant cell growth. Despite its economic and biological significance, the regulation of cellulose biosynthesis is poorly understood. Phosphorylation and dephosphorylation of cellulose synthases (CESAs) were shown to impact the direction and velocity of cellulose synthase complexes (CSCs). Despite a high prevalence of phosphorylation sites in CESAs, the protein kinases that phosphorylate CESAs are largely unknown. Here, we demonstrate that CALCIUM-DEPENDENT PROTEIN KINASE32 (CPK32) regulates cellulose biosynthesis via phosphorylation of CESA3. Phosphorylation of CESA3 is important for the motility and stability of CSCs. Hence, we uncovered a new function of CPKs that regulates cellulose biosynthesis and a novel mechanism by which phosphorylation regulates the stability of CSCs.

plant biology↗

bioRxiv2022

A dedicated hypothalamic oxytocin circuit controls aversive social learning

To survive and thrive in a complex social group, it is essential to not only know who to approach but more importantly who to avoid. After a single defeat, mice learn to stay away from the winning aggressor for weeks. Here, we identify oxytocin neurons in the retrochiasmatic supraoptic nucleus (SOROXT) and oxytocin receptor expressing cells in the anterior subdivision of ventromedial hypothalamus, ventrolateral part (aVMHvlOXTR) as a key circuit motif for defeat-induced social avoidance learning. After defeat, aVMHvlOXTR cells drastically increase their responses to aggressor cues. This response change is functionally important as optogenetic activation of aVMHvlOXTR cells elicits time-locked social avoidance towards a benign social target whereas inactivating the cells suppresses defeat-induced social avoidance. Furthermore, OXTR in the aVMHvl is itself essential for the behavior change. Knocking out OXTR in the aVMHvl or antagonizing the receptor during defeat, but not during post-defeat social interaction, impairs defeat-induced social avoidance. aVMHvlOXTR receives its private source of oxytocin from SOROXT cells, which are highly activated by the noxious somatosensory inputs associated with defeat. Oxytocin released from SOROXT depolarizes aVMHvlOXTR cells and facilitates their synaptic potentiation, and hence, increases aVMHvlOXTR cell responses to aggressor cues. Ablating SOROXT cells impairs defeat-induced social avoidance learning whereas activating the cells promotes social avoidance after a subthreshold defeat experience. Altogether, our study reveals an essential role of SOROXT-aVMHvlOXTR circuit in defeat-induced social learning and highlights the importance of brain oxytocin system in social plasticity.

neuroscience↗

bioRxiv2022

Vimo: Visual Analysis of Neuronal Connectivity Motifs

Recent advances in high-resolution connectomics provide researchers with access to accurate petascale reconstructions of neuronal circuits and brain networks for the first time. Neuroscientists are analyzing these networks to better understand information processing in the brain. In particular, scientists are interested in identifying specific small network motifs, i.e., repeating subgraphs of the larger brain network that are believed to be neuronal building blocks. Although such motifs are typically small (e.g., 2 - 6 neurons), the vast data sizes and intricate data complexity present significant challenges to the search and analysis process. To analyze these motifs, it is crucial to review instances of a motif in the brain network and then map the graph structure to detailed 3D reconstructions of the involved neurons and synapses. We present Vimo, an interactive visual approach to analyze neuronal motifs and motif chains in large brain networks. Experts can sketch network motifs intuitively in a visual interface and specify structural properties of the involved neurons and synapses to query large connectomics datasets. Motif instances (MIs) can be explored in high-resolution 3D renderings. To simplify the analysis of MIs, we designed a continuous focus&context metaphor inspired by visual abstractions. This allows users to transition from a highly-detailed rendering of the anatomical structure to views that emphasize the underlying motif structure and synaptic connectivity. Furthermore, Vimo supports the identification of motif chains where a motif is used repeatedly (e.g., 2 - 4 times) to form a larger network structure. We evaluate Vimo in a user study and an in-depth case study with seven domain experts on motifs in a large connectome of the fruit fly, including more than 21,000 neurons and 20 million synapses. We find that Vimo enables hypothesis generation and confirmation through fast analysis iterations and connectivity highlighting.

neuroscience↗

bioRxiv2022

Running ahead of evolution - AI based simulation for predicting future high-risk SARS-CoV-2 variants

The never-ending emergence of SARS-CoV-2 variations of concern (VOCs) has challenged the whole world for pandemic control. In order to develop effective drugs and vaccines, one needs to efficiently simulate SARS-CoV-2 spike receptor binding domain (RBD) mutations and identify high-risk variants. We pretrain a large protein language model with approximately 408 million protein sequences and construct a high-throughput screening for the prediction of binding affinity and antibody escape. As the first work on SARS-CoV-2 RBD mutation simulation, we successfully identify mutations in the RBD regions of 5 VOCs and can screen millions of potential variants in seconds. Our workflow scales to 4096 NPUs with 96.5% scalability and 493.9x speedup in mixed precision computing, while achieving a peak performance of 366.8 PFLOPS (reaching 34.9% theoretical peak) on Pengcheng Cloudbrain-II. Our method paves the way for simulating coronavirus evolution in order to prepare for a future pandemic that will inevitably take place. Our models are released at https://github.com/ZhiweiNiepku/SARS-CoV-2_mutation_simulation to facilitate future related work. JustificationWe develop a novel multi-constraint variation prediction framework to simulate SARS-CoV-2 RBD mutations, reaching a peak performance of 366.8 PFLOPS with 96.5% scalability and achieving 493.9x speedup. Our method facilitates the prediction and prioritization of future high-risk variants for the early deployment of drugs and vaccines. Performance attributes O_TBL View this table: org.highwire.dtl.DTLVardef@1b1873aorg.highwire.dtl.DTLVardef@25314eorg.highwire.dtl.DTLVardef@1c80130org.highwire.dtl.DTLVardef@1c61b21org.highwire.dtl.DTLVardef@11f21c5_HPS_FORMAT_FIGEXP M_TBL C_TBL Overview of the problemCoronavirus Disease 2019 (COVID-19) has spread rapidly to more than 200 countries or regions since December 2019. Due to its high infectivity, there have been over 645 million confirmed cases, including approximately 6.6 million deaths, reported by the World Health Organization (WHO) as of December 20221. In addition to being a serious threat to human health, COVID-19 has had a catastrophic impact on the global economy.

bioinformatics↗

bioRxiv2022

scCobra: Contrastive cell embedding learning with domain adaptation for single-cell data integration

The rapid development of single-cell technologies has underscored the need for more effective methods in the integration and harmonization of single-cell sequencing data. The prevalent challenge of batch effects, resulting from technical and biological variations across studies, demands accurate and reliable solutions for data integration. Traditional tools often have limitations, both due to reliance on gene expression distribution assumptions and the common issue of over-correction, particularly in methods based on anchor alignments. Here we introduce scCobra, a deep neural network tool designed specifically to address these challenges. By leveraging a deep generative model that combines a contrastive neural network with domain adaptation, scCobra effectively mitigates batch effects and minimizes over-correction without depending on gene expression distribution assumptions. Additionally, scCobra enables online label transfer across datasets with batch effects, facilitating the continuous integration of new data without retraining, and offers features for batch effect simulation and advanced multi-omic batch integration. These capabilities make scCobra a versatile data integration and harmonization tool for achieving accurate and insightful biological interpretations from complex datasets.

bioinformatics↗

bioRxiv2022

Modeling Microtubule-Cytoplasm Interaction in Plant Cells

Although microtubules in plant cells have been extensively studied, the mechanisms that regulate the spatial organization of microtubules are poorly understood. We hypothesize that the interaction between microtubules and cytoplasmic flow plays an important role in the assembly and orientation of microtubules. To test this hypothesis, we developed a new computational modeling framework for microtubules based on theory and methods from the fluid-structure interaction. We employed the immersed boundary method to track the movement of microtubules in cytoplasmic flow. We also incorporated details of the encounter dynamics when two microtubules collide with each other. We verified our computational model through several numerical tests before applying it to the simulation of the microtubule-cytoplasm interaction in a growing plant cell. Our computational investigation demonstrated that microtubules are primarily oriented in the direction orthogonal to the axis of cell elongation. We validated the simulation results through a comparison with the measurement from laboratory experiments. We found that our computational model, with further calibration, was capable of generating microtubule orientation patterns that were qualitatively and quantitatively consistent with the experimental results. The computational model proposed in this study can be naturally extended to many other cellular systems that involve the interaction between microstructures and the intracellular fluid.

cell biology↗

bioRxiv2022

Complement-dependent loss of inhibitory synapses on pyramidal neurons following Toxoplasma gondii infection

The apicomplexan parasite Toxoplasma gondii has developed mechanisms to establish a central nervous system infection in virtually all warm-blooded animals. Acute T. gondii infection can cause neuroinflammation, encephalitis, and seizures. Meanwhile, studies in humans, non-human primates, and rodents have linked chronic T. gondii infection with altered behavior and increased risk for neuropsychiatric disorders, including schizophrenia. We previously demonstrated that T. gondii infection triggers the loss of perisomatic inhibitory synapses, an important source of inhibition on excitatory pyramidal cells, and a type of synapse that is disrupted in neurological and neuropsychiatric disorders. Similar to other instances of inflammation and neurodegeneration, we showed that phagocytic cells (including microglia and infiltrating monocytes) contribute to the loss of these inhibitory synapses. However, in the case of T. gondii-induced synapse loss, phagocytic cells target and ensheath the cell bodies of telencephalic neurons. Here, we show that these phagocytic cells specifically ensheath excitatory pyramidal neurons, leading to the preferential loss of perisomatic synapses on these neurons. In contrast, inhibitory cortical interneuron subtypes are not extensively ensheathed by phagocytic cells following infection. Moreover, we show that infection induces expression of complement C3 protein by these excitatory neurons and that C3 is required for the loss of perisomatic inhibitory synapses, albeit not through activation of the classical complement pathway. Together, these findings provide evidence that T. gondii infection induces changes in excitatory pyramidal neurons that trigger selective removal of inhibitory perisomatic synapses in the infected neocortex and provide a novel role for complement in remodeling of inhibitory circuits in the infected brain.

neuroscience↗

bioRxiv2022

FOXP2 confers oncogenic effects in prostate cancer through activating MET signalling

Identification oncogenes is fundamental to revealing the molecular basis of cancer. Here, we found that FOXP2 is overexpressed in human prostate cancer cells and prostate tumors, but its expression is absent in normal prostate epithelial cells and low in benign prostatic hyperplasia. To date, little is known regarding the link of FOXP2 to prostate cancer. We observed that high FOXP2 expression and frequent amplification are significantly associated with high Gleason score. Ectopic expression of FOXP2 induces malignant transformation of mouse NIH3T3 fibroblasts and human prostate epithelial cell RWPE-1. Conversely, FOXP2 knockdown suppresses the proliferation of prostate cancer cells. Transgenic overexpression of FOXP2 in the mouse prostate causes prostatic intraepithelial neoplasia. Overexpression of FOXP2 aberrantly activates oncogenic MET signalling and inhibitors targeting MET signalling effectively reverts the FOXP2-induced oncogenic phenotype. Additionally, the novel recurrent FOXP2-CPED1 fusion identified in prostate tumors results in high expression of truncated FOXP2, which exhibit a similar capacity for malignant transformation. Together, our data demonstrate for the first time that FOXP2 is an oncogene involved in tumorigenicity of prostate.

cancer biology↗

bioRxiv2022

Two Competing Guilds as a Core Microbiome Signature for Chronic Diseases

Summary ParagraphOver eons of co-evolution, the gut microbiota has become an essential organ for humans1,2. However, it is unclear what core members and their ecological organization ensures the stable provision of this organs essential health-relevant functions to the host. With high quality metagenome-assembled genomes as network nodes, here we identified two competing guilds3 of the most stably and highly connected bacteria that together correlate with a wide range of host health conditions. Genomes in these two guilds kept their ecological relationship unchanged despite experiencing profound abundance changes during a 3-month high fiber intervention and 1-year follow-up in patients with type 2 diabetes (T2DM). The genomes of one guild harbored more genes for plant polysaccharide degradation and butyrate production, while the other guild had more genes for virulence or antibiotic resistance. A Random Forest regression model showed that the abundance distributions of these genomes were associated with 41 out of 43 bio-clinical parameters in the study cohort. With these genomes as reference, Random Forest modeling successfully classified case and control of T2DM, atherosclerotic cardiovascular disease, liver cirrhosis, inflammatory bowel diseases, colorectal cancer, ankylosing spondylitis, schizophrenia, and Parkinsons disease in 12 independent metagenomic datasets from 1,816 participants across ethnicity and geography. This core microbiome signature may serve as a common target for health recovery.

microbiology↗

bioRxiv2022

Combined effects of 12-week yoga warm-up on athletic performance in male high school track and field athletes

AO_SCPLOWBSTRACTC_SCPLOWO_ST_ABSBackgroundC_ST_ABSPracticing yoga could improve balance and flexibility, but its positive significance as a long-term warm-up for formal training was uncertain. We hypothesized that practicing yoga during warm-up might positively affect balance, flexibility, and speed performance in male high school track and field athletes. MethodsOver a 12-week period, athletes in a yoga group (YG) (n=10) practiced yoga for 15 min 4 times a week during warm-up, while athletes in a dynamic stretching group (DSG) (n=10) practiced 15 min of dynamic stretching. Except for the warm-up activities, the training content of the two groups of students was the same. we tested performance indicators immediately before and after the intervention, including lower extremity flexibility test (right hip active flexion range), lower extremity balance test [using surface electromyography (sEMG) to measure right leg tibialis anterior (TA) activation during one-leg stance (OLS) with eyes closed], and speed performance test (100-meter and 800-meter tests). ResultsWe performed between-group and within-group comparisons for indicators of two groups by using SPSS (version 26.0). Within-group comparisons showed a significant improvement in flexibility (P=0.002) and balance (P=0.003) in YG, but no significant change in DSG, after the 12-week intervention. In addition, speed performance of both YG (100m, P=0.026; 800m, P=0.045) and DSG (100m, P=0.029; 800m, P=0.006) was significantly improved. Between-group comparison showed that YG had a significant advantage in 800m (P=0.045) and flexibility (P=0.031). ConclusionsThese data suggested that practicing yoga as a long-term warm-up could help male high school track and field athletes improve lower body flexibility and 800m speed. In addition, yoga had a certain positive effect on balance, but it was not significant overall.

physiology↗

bioRxiv2022

A cross-sectional study of the commercial plant-based landscape across the US, UK and Canada.

As plant-based foods comprise an ever-increasing proportion of the diet, understanding the nutritional composition of these products is critical. In this study we assess the nutritional content of all commercial plant-based products across multiple sectors (supermarkets, fast food & sit down restaurants, food delivery companies and manufacturers) in the US, UK and Canada. We identified 3488 unique products. Across all sectors, 45% of main meals had >15g protein, 60% had <10%kcal from saturated fat; 29% had >10g fibre per meal; 86% had <1000mg sodium. At restaurants, meat-based main meals were significantly higher in protein and sodium compared to vegetarian and vegan meals. The meat-based options were also significantly higher in saturated fat than the vegan but not vegetarian options. We conclude that plant-based items tend to be lower in saturated fat and sodium than their meat-based counterparts but improvements are needed to optimise their nutritional composition.

scientific communication and education↗

bioRxiv2022

Saturated reconstruction of living brain tissue

Complex wiring between neurons underlies the information-processing network enabling all brain functions, including cognition and memory. For understanding how the network is structured, processes information, and changes over time, comprehensive visualization of the architecture of living brain tissue with its cellular and molecular components would open up major opportunities. However, electron microscopy (EM) provides nanometre-scale resolution required for full in-silico reconstruction1-5, yet is limited to fixed specimens and static representations. Light microscopy allows live observation, with super-resolution approaches6-12 facilitating nanoscale visualization, but comprehensive 3D-reconstruction of living brain tissue has been hindered by tissue photo-burden, photobleaching, insufficient 3D-resolution, and inadequate signal-to-noise ratio (SNR). Here we demonstrate saturated reconstruction of living brain tissue. We developed an integrated imaging and analysis technology, adapting stimulated emission depletion (STED) microscopy6,13 in extracellularly labelled tissue14 for high SNR and near-isotropic resolution. Centrally, a two-stage deep-learning approach leveraged previously obtained information on sample structure to drastically reduce photo-burden and enable automated volumetric reconstruction down to single synapse level. Live reconstruction provides unbiased analysis of tissue architecture across time in relation to functional activity and targeted activation, and contextual understanding of molecular labelling. This adoptable technology will facilitate novel insights into the dynamic functional architecture of living brain tissue.

neuroscience↗