Imaging brain tissue architecture across millimeter to nanometer scales.

Mapping the complex and dense arrangement of cells and their connectivity in brain tissue demands nanoscale spatial resolution imaging. Super-resolution optical microscopy excels at visualizing specific molecules and individual cells but fails to provide tissue context. Here we developed Comprehensive Analysis of Tissues across Scales (CATS), a technology to densely map brain tissue architecture from millimeter regional to nanometer synaptic scales in diverse chemically fixed brain preparations, including rodent and human. CATS uses fixation-compatible extracellular labeling and optical imaging, including stimulated emission depletion or expansion microscopy, to comprehensively delineate cellular structures. It enables three-dimensional reconstruction of single synapses and mapping of synaptic connectivity by identification and analysis of putative synaptic cleft regions. Applying CATS to the mouse hippocampal mossy fiber circuitry, we reconstructed and quantified the synaptic input and output structure of identified neurons. We furthermore demonstrate applicability to clinically derived human tissue samples, including formalin-fixed paraffin-embedded routine diagnostic specimens, for visualizing the cellular architecture of brain tissue in health and disease.

Dense 4D nanoscale reconstruction of living brain tissue.

Three-dimensional (3D) reconstruction of living brain tissue down to an individual synapse level would create opportunities for decoding the dynamics and structure-function relationships of the brain's complex and dense information processing network; however, this has been hindered by insufficient 3D resolution, inadequate signal-to-noise ratio and prohibitive light burden in optical imaging, whereas electron microscopy is inherently static. Here we solved these challenges by developing an integrated optical/machine-learning technology, LIONESS (live information-optimized nanoscopy enabling saturated segmentation). This leverages optical modifications to stimulated emission depletion microscopy in comprehensively, extracellularly labeled tissue and previous information on sample structure via machine learning to simultaneously achieve isotropic super-resolution, high signal-to-noise ratio and compatibility with living tissue. This allows dense deep-learning-based instance segmentation and 3D reconstruction at a synapse level, incorporating molecular, activity and morphodynamic information. LIONESS opens up avenues for studying the dynamic functional (nano-)architecture of living brain tissue.

CHD8 haploinsufficiency links autism to transient alterations in excitatory and inhibitory trajectories.

Mutations in the chromodomain helicase DNA-binding 8 (CHD8) gene are a frequent cause of autism spectrum disorder (ASD). While its phenotypic spectrum often encompasses macrocephaly, implicating cortical abnormalities, how CHD8 haploinsufficiency affects neurodevelopmental is unclear. Here, employing human cerebral organoids, we find that CHD8 haploinsufficiency disrupted neurodevelopmental trajectories with an accelerated and delayed generation of, respectively, inhibitory and excitatory neurons that yields, at days 60 and 120, symmetrically opposite expansions in their proportions. This imbalance is consistent with an enlargement of cerebral organoids as an in vitro correlate of patients' macrocephaly. Through an isogenic design of patient-specific mutations and mosaic organoids, we define genotype-phenotype relationships and uncover their cell-autonomous nature. Our results define cell-type-specific CHD8-dependent molecular defects related to an abnormal program of proliferation and alternative splicing. By identifying cell-type-specific effects of CHD8 mutations, our study uncovers reproducible developmental alterations that may be employed for neurodevelopmental disease modeling.