A data-driven single-cell and spatial transcriptomic map of the human prefrontal cortex

The molecular organization of the human neocortex historically has been studied in the context of its histological layers. However, emerging spatial transcriptomic technologies have enabled unbiased identification of transcriptionally defined spatial domains that move beyond classic cytoarchitecture. We used the Visium spatial gene expression platform to generate a data-driven molecular neuroanatomical atlas across the anterior-posterior axis of the human dorsolateral prefrontal cortex. Integration with paired single-nucleus RNA-sequencing data revealed distinct cell type compositions and cell-cell interactions across spatial domains. Using PsychENCODE and publicly available data, we mapped the enrichment of cell types and genes associated with neuropsychiatric disorders to discrete spatial domains.

Spatiotemporal analysis of gene expression in the human dentate gyrus reveals age-associated changes in cellular maturation and neuroinflammation

The dentate gyrus of the hippocampus is important for many cognitive functions, including learning, memory, and mood. Here, we investigated age-associated changes in transcriptome-wide spatial gene expression in the human dentate gyrus across the lifespan. Genes associated with neurogenesis and the extracellular matrix were enriched in infants, while gene markers of inhibitory neurons and cell proliferation showed increases and decreases in post-infancy, respectively. While we did not find evidence for neural proliferation post-infancy, we did identify molecular signatures supporting protracted maturation of granule cells. We also identified a wide-spread hippocampal aging signature and an age-associated increase in genes related to neuroinflammation. Our findings suggest major changes to the putative neurogenic niche after infancy and identify molecular foci of brain aging in glial and neuropil enriched tissue.

An integrated single-nucleus and spatial transcriptomics atlas reveals the molecular landscape of the human hippocampus

The hippocampus contains many unique cell types, which serve the structure's specialized functions, including learning, memory and cognition. These cells have distinct spatial topography, morphology, physiology, and connectivity, highlighting the need for transcriptome-wide profiling strategies that retain cytoarchitectural organization. Here, we generated spatially-resolved transcriptomics (SRT) and single-nucleus RNA-sequencing (snRNA-seq) data from adjacent tissue sections of the anterior human hippocampus across ten adult neurotypical donors. We defined molecular profiles for hippocampal cell types and spatial domains. Using non-negative matrix factorization and transfer learning, we integrated these data to define gene expression patterns within the snRNA-seq data and infer the expression of these patterns in the SRT data. With this approach, we leveraged existing rodent datasets that feature information on circuit connectivity and neural activity induction to make predictions about axonal projection targets and likelihood of ensemble recruitment in spatially-defined cellular populations of the human hippocampus. Finally, we integrated genome-wide association studies with transcriptomic data to identify enrichment of genetic components for neurodevelopmental, neuropsychiatric, and neurodegenerative disorders across cell types, spatial domains, and gene expression patterns of the human hippocampus. To make this comprehensive molecular atlas accessible to the scientific community, both raw and processed data are freely available, including through interactive web applications.

TCF4 Mutations Disrupt Synaptic Function Through Dysregulation of RIMBP2 in Patient-Derived Cortical Neurons

BACKGROUND

Genetic variation in the TCF4 (transcription factor 4) gene is associated with risk for a variety of developmental and psychiatric conditions, which includes a syndromic form of autism spectrum disorder called Pitt-Hopkins syndrome (PTHS). TCF4 encodes an activity-dependent transcription factor that is highly expressed during cortical development and in animal models has been shown to regulate various aspects of neuronal development and function. However, our understanding of how disease-causing mutations in TCF4 confer pathophysiology in a human context is lacking.

METHODS

To model PTHS, we differentiated human cortical neurons from human induced pluripotent stem cells that were derived from patients with PTHS and neurotypical individuals. To identify pathophysiology and disease mechanisms, we assayed cortical neurons with whole-cell electrophysiology, Ca2+ imaging, multielectrode arrays, immunocytochemistry, and RNA sequencing.

RESULTS

Cortical neurons derived from patients with TCF4 mutations showed deficits in spontaneous synaptic transmission, network excitability, and homeostatic plasticity. Transcriptomic analysis indicated that these phenotypes resulted in part from altered expression of genes involved in presynaptic neurotransmission and identified the presynaptic binding protein RIMBP2 as the most differentially expressed gene in PTHS neurons. Remarkably, TCF4-dependent deficits in spontaneous synaptic transmission and network excitability were rescued by increasing RIMBP2 expression in presynaptic neurons.

CONCLUSIONS

Taken together, these results identify TCF4 as a critical transcriptional regulator of human synaptic development and plasticity and specifically identifies dysregulation of presynaptic function as an early pathophysiology in PTHS.

The gene expression landscape of the human locus coeruleus revealed by single-nucleus and spatially-resolved transcriptomics

Norepinephrine (NE) neurons in the locus coeruleus (LC) make long-range projections throughout the central nervous system, playing critical roles in arousal and mood, as well as various components of cognition including attention, learning, and memory. The LC-NE system is also implicated in multiple neurological and neuropsychiatric disorders. Importantly, LC-NE neurons are highly sensitive to degeneration in both Alzheimer's and Parkinson's disease. Despite the clinical importance of the brain region and the prominent role of LC-NE neurons in a variety of brain and behavioral functions, a detailed molecular characterization of the LC is lacking. Here, we used a combination of spatially-resolved transcriptomics and single-nucleus RNA-sequencing to characterize the molecular landscape of the LC region and the transcriptomic profile of LC-NE neurons in the human brain. We provide a freely accessible resource of these data in web-accessible and downloadable formats.

VistoSeg: Processing utilities for high-resolution images for spatially resolved transcriptomics data

Spatially resolved transcriptomics (SRT) is a growing field that links gene expression to anatomical context. SRT approaches that use next-generation sequencing (NGS) combine RNA sequencing with histological or fluorescent imaging to generate spatial maps of gene expression in intact tissue sections. These technologies directly couple gene expression measurements with high-resolution histological or immunofluorescent images that contain rich morphological information about the tissue under study. While broad access to NGS-based spatial transcriptomic technology is now commercially available through the Visium platform from the vendor 10× Genomics, computational tools for extracting image-derived metrics for integration with gene expression data remain limited. We developed VistoSeg as a MATLAB pipeline to process, analyze and interactively visualize the high-resolution images generated in the Visium platform. VistoSeg outputs can be easily integrated with accompanying transcriptomic data to facilitate downstream analyses in common programing languages including R and Python. VistoSeg provides user-friendly tools for integrating image-derived metrics from histological and immunofluorescent images with spatially resolved gene expression data. Integration of this data enhances the ability to understand the transcriptional landscape within tissue architecture. VistoSeg is freely available at http://research.libd.org/VistoSeg/.

Integrated single cell and unsupervised spatial transcriptomic analysis defines molecular anatomy of the human dorsolateral prefrontal cortex

Generation of a molecular neuroanatomical map of the human prefrontal cortex reveals novel spatial domains and cell-cell interactions relevant for psychiatric disease. The molecular organization of the human neocortex has been historically studied in the context of its histological layers. However, emerging spatial transcriptomic technologies have enabled unbiased identification of transcriptionally-defined spatial domains that move beyond classic cytoarchitecture. Here we used the Visium spatial gene expression platform to generate a data-driven molecular neuroanatomical atlas across the anterior-posterior axis of the human dorsolateral prefrontal cortex (DLPFC). Integration with paired single nucleus RNA-sequencing data revealed distinct cell type compositions and cell-cell interactions across spatial domains. Using PsychENCODE and publicly available data, we map the enrichment of cell types and genes associated with neuropsychiatric disorders to discrete spatial domains. Finally, we provide resources for the scientific community to explore these integrated spatial and single cell datasets at research.libd.org/spatialDLPFC/.

SUFI: an automated approach to spectral unmixing of fluorescent multiplex images captured in mouse and post-mortem human brain tissues

BACKGROUND

Multispectral fluorescence imaging coupled with linear unmixing is a form of image data collection and analysis that allows for measuring multiple molecular signals in a single biological sample. Multiple fluorescent dyes, each measuring a unique molecule, are simultaneously measured and subsequently "unmixed" to provide a read-out for each molecular signal. This strategy allows for measuring highly multiplexed signals in a single data capture session, such as multiple proteins or RNAs in tissue slices or cultured cells, but can often result in mixed signals and bleed-through problems across dyes. Existing spectral unmixing algorithms are not optimized for challenging biological specimens such as post-mortem human brain tissue, and often require manual intervention to extract spectral signatures. We therefore developed an intuitive, automated, and flexible package called SUFI: spectral unmixing of fluorescent images.

RESULTS

This package unmixes multispectral fluorescence images by automating the extraction of spectral signatures using vertex component analysis, and then performs one of three unmixing algorithms derived from remote sensing. We evaluate these remote sensing algorithms' performances on four unique biological datasets and compare the results to unmixing results obtained using ZEN Black software (Zeiss). We lastly integrate our unmixing pipeline into the computational tool dotdotdot, which is used to quantify individual RNA transcripts at single cell resolution in intact tissues and perform differential expression analysis, and thereby provide an end-to-end solution for multispectral fluorescence image analysis and quantification.

CONCLUSIONS

In summary, we provide a robust, automated pipeline to assist biologists with improved spectral unmixing of multispectral fluorescence images.

TCF4 mutations disrupt synaptic function through dysregulation of RIMBP2 in patient-derived cortical neurons

Genetic variation in the transcription factor 4 ( TCF4) gene is associated with risk for a variety of developmental and psychiatric conditions, which includes a syndromic form of ASD called Pitt Hopkins Syndrome (PTHS). TCF4 encodes an activity-dependent transcription factor that is highly expressed during cortical development and in animal models is shown to regulate various aspects of neuronal development and function. However, our understanding of how disease-causing mutations in TCF4 confer pathophysiology in a human context is lacking. Here we show that cortical neurons derived from patients with TCF4 mutations have deficits in spontaneous synaptic transmission, network excitability and homeostatic plasticity. Transcriptomic analysis indicates these phenotypes result from altered expression of genes involved in presynaptic neurotransmission and identifies the presynaptic binding protein, RIMBP2 as the most differentially expressed gene in PTHS neurons. Remarkably, TCF4-dependent deficits in spontaneous synaptic transmission and network excitability were rescued by increasing RIMBP2 expression in presynaptic neurons. Together, these results identify TCF4 as a critical transcriptional regulator of human synaptic development and plasticity and specifically identifies dysregulation of presynaptic function as an early pathophysiology in PTHS.

CaPTure: Calcium PeakToolbox for analysis of in vitro calcium imaging data

BACKGROUND

Calcium imaging is a powerful technique for recording cellular activity across large populations of neurons. However, analysis methods capable of single-cell resolution in cultured neurons, especially for cultures derived from human induced pluripotent stem cells (hiPSCs), are lacking. Existing methods lack scalability to accommodate high-throughput comparisons between multiple lines, across developmental timepoints, or across pharmacological manipulations.

RESULTS

To address this need we developed CaPTure, a scalable, automated Ca2+ imaging analysis pipeline ( https://github.com/LieberInstitute/CaPTure ). CaPTuredetects neurons, classifies and quantifies spontaneous activity, quantifies synchrony metrics, and generates cell- and network-specific metrics that facilitate phenotypic discovery. The method is compatible with parallel processing on computing clusters without requiring significant user input or parameter modification.

CONCLUSION

CaPTure allows for rapid assessment of neuronal activity in cultured cells at cellular resolution, rendering it amenable to high-throughput screening and phenotypic discovery. The platform can be applied to both human- and rodent-derived neurons and is compatible with many imaging systems.

Electrophysiological measures from human iPSC-derived neurons are associated with schizophrenia clinical status and predict individual cognitive performance

Neurons derived from human induced pluripotent stem cells (hiPSCs) have been used to model basic cellular aspects of neuropsychiatric disorders, but the relationship between the emergent phenotypes and the clinical characteristics of donor individuals has been unclear. We analyzed RNA expression and indices of cellular function in hiPSC-derived neural progenitors and cortical neurons generated from 13 individuals with high polygenic risk scores (PRSs) for schizophrenia (SCZ) and a clinical diagnosis of SCZ, along with 15 neurotypical individuals with low PRS. We identified electrophysiological measures in the patient-derived neurons that implicated altered Na+ channel function, action potential interspike interval, and gamma-aminobutyric acid-ergic neurotransmission. Importantly, electrophysiological measures predicted cardinal clinical and cognitive features found in these SCZ patients. The identification of basic neuronal physiological properties related to core clinical characteristics of illness is a potentially critical step in generating leads for novel therapeutics.

Induction of Bdnf from promoter I following electroconvulsive seizures contributes to structural plasticity in neurons of the piriform cortex

BACKGROUND

Electroconvulsive therapy (ECT) efficacy is hypothesized to depend on induction of molecular and cellular events that trigger neuronal plasticity. Investigating how electroconvulsive seizures (ECS) impact plasticity in animal models can help inform our understanding of basic mechanisms by which ECT relieves symptoms of depression. ECS-induced plasticity is associated with differential expression of unique isoforms encoding the neurotrophin, brain-derived neurotrophic factor (BDNF).

HYPOTHESIS

We hypothesized that cells expressing the Bdnf exon 1-containing isoform are important for ECS-induced structural plasticity in the piriform cortex, a highly epileptogenic region that is responsive to ECS.

METHODS

We selectively labeled Bdnf exon 1-expressing neurons in mouse piriform cortex using Cre recombinase dependent on GFP technology (CRE-DOG). We then quantified changes in dendrite morphology and density of Bdnf exon 1-expressing neurons.

RESULTS

Loss of promoter I-derived BDNF caused changes in spine density and morphology in Bdnf exon 1-expressing neurons following ECS.

CONCLUSIONS

Promoter I-derived Bdnf is required for ECS-induced dendritic structural plasticity in Bdnf exon 1-expressing neurons.

Single molecule in situ hybridization reveals distinct localizations of schizophrenia risk-related transcripts SNX19 and AS3MT in human brain

Genome-wide association studies have identified single nucleotide polymorphisms (SNPs) associated with schizophrenia risk. Integration of RNA-sequencing data from postmortem human brains with these risk SNPs identified transcripts associated with increased schizophrenia susceptibility, including a class of exon 9-spliced isoforms of Sorting nexin-19 (SNX19^d9) and an isoform of Arsenic methyltransferase (AS3MT) splicing out exons 2 and 3 (AS3MT^d2d3). However, the biological function of these transcript variants is unclear. Defining the cell types where these risk transcripts are dominantly expressed is an important step to understand function, in prioritizing specific cell types and/or neural pathways in subsequent studies. To identify the cell type-specific localization of SNX19 and AS3MT in the human dorsolateral prefrontal cortex (DLPFC), we used single-molecule in situ hybridization techniques combined with automated quantification and machine learning approaches to analyze 10 postmortem brains of neurotypical individuals. These analyses revealed that both pan-SNX19 and pan-AS3MT were more highly expressed in neurons than non-neurons in layers II/III and VI of DLPFC. Furthermore, pan-SNX19 was preferentially expressed in glutamatergic neurons, while pan-AS3MT was preferentially expressed in GABAergic neurons. Finally, we utilized duplex BaseScope technology, to delineate the localization of SNX19^d9 and AS3MT^d2d3 splice variants, revealing consistent trends in spatial gene expression among pan-transcripts and schizophrenia risk-related transcript variants. These findings demonstrate that schizophrenia risk transcripts have distinct localization patterns in the healthy human brains, and suggest that SNX19 transcripts might disrupt the normal function of glutamatergic neurons, while AS3MT may lead to disturbances in the GABAergic system in the pathophysiology of schizophrenia.

Transcriptome-scale spatial gene expression in the human dorsolateral prefrontal cortex

We used the 10x Genomics Visium platform to define the spatial topography of gene expression in the six-layered human dorsolateral prefrontal cortex. We identified extensive layer-enriched expression signatures and refined associations to previous laminar markers. We overlaid our laminar expression signatures on large-scale single nucleus RNA-sequencing data, enhancing spatial annotation of expression-driven clusters. By integrating neuropsychiatric disorder gene sets, we showed differential layer-enriched expression of genes associated with schizophrenia and autism spectrum disorder, highlighting the clinical relevance of spatially defined expression. We then developed a data-driven framework to define unsupervised clusters in spatial transcriptomics data, which can be applied to other tissues or brain regions in which morphological architecture is not as well defined as cortical laminae. Last, we created a web application for the scientific community to explore these raw and summarized data to augment ongoing neuroscience and spatial transcriptomics research ( http://research.libd.org/spatialLIBD ).

dotdotdot: an automated approach to quantify multiplex single molecule fluorescent in situ hybridization (smFISH) images in complex tissues

Multiplex single-molecule fluorescent in situ hybridization (smFISH) is a powerful method for validating RNA sequencing and emerging spatial transcriptomic data, but quantification remains a computational challenge. We present a framework for generating and analyzing smFISH data in complex tissues while overcoming autofluorescence and increasing multiplexing capacity. We developed dotdotdot (https://github.com/LieberInstitute/dotdotdot) as a corresponding software package to quantify RNA transcripts in single nuclei and perform differential expression analysis. We first demonstrate robustness of our platform in single mouse neurons by quantifying differential expression of activity-regulated genes. We then quantify spatial gene expression in human dorsolateral prefrontal cortex (DLPFC) using spectral imaging and dotdotdot to mask lipofuscin autofluorescence. We lastly apply machine learning to predict cell types and perform downstream cell type-specific expression analysis. In summary, we provide experimental workflows, imaging acquisition and analytic strategies for quantification and biological interpretation of smFISH data in complex tissues.

Assessment of Corneal Stromal Remodeling and Regeneration after Photorefractive Keratectomy

This study utilizes high resolution multi-dimensional imaging to identify temporal and spatial changes in cell/extracellular matrix (ECM) patterning mediating cell migration, fibrosis, remodeling and regeneration during wound healing. Photorefractive keratectomy (PRK) was performed on rabbits. In some cases, 5([4,6-dichlorotriazin-2yl]-amino)fluorescein (DTAF) was applied immediately after surgery to differentiate native vs. cell-secreted collagen. Corneas were assessed 3–180 days postoperatively using in vivo confocal microscopy, and cell/ECM patterning was evaluated in situ using multiphoton and second harmonic generation (SHG) imaging. 7 days post-PRK, migrating fibroblasts below the ablation site were co-aligned with the stromal lamellae. At day 21, randomly patterned myofibroblasts developed on top of the ablation site; whereas cells underneath were elongated, co-aligned with collagen, and lacked stress fibers. Over time, fibrotic tissue was remodeled into more transparent stromal lamellae. By day 180, stromal thickness was almost completely restored. Stromal regrowth occurred primarily below the ablation interface, and was characterized by co-localization of gaps in DTAF labeling with elongated cells and SHG collagen signaling. Punctate F-actin labeling was detected along cells co-aligned with DTAF and non-DTAF labeled collagen, suggesting cell-ECM interactions. Overall, collagen lamellae appear to provide a template for fibroblast patterning during wound healing that mediates stromal repopulation, regeneration and remodeling.