skip to main content


Title: Three-dimensional intact-tissue sequencing of single-cell transcriptional states.
The mammalian brain consists of an intricate tapestry of cell types, with diversity crucial for function that arises from both differential gene expression and circuit-specific anatomy. Yet, retrieving high-content gene-expression information while retaining 3D positional anatomy at cellular resolution has been difficult, limiting integrative understanding of brain structure and function. Here we introduce and apply a technology for 3D intact-tissue RNA sequencing, termed STARmap (Spatially-resolved Transcript Amplicon Readout Mapping), which integrates highly-specific signal amplification, novel hydrogel-tissue chemistry, and an error-reduction sequencing process. The capabilities of STARmap were tested by mapping from 160 to 1,020 distinct genes simultaneously in sections of mouse brain at single-cell resolution with unprecedented efficiency, accuracy and reproducibility. These experiments led to the discovery of multiple new neocortical cell types, with gene markers and spatial patterns of organization not previously described, by comparison of the molecularly-defined architectures of sensory versus cognitive neocortex, and by quantification of expression of activity-regulated genes as a function of stimulation condition, spatial position, and cell typology. By adapting STARmap to thick tissue blocks, we observed and confirmed a novel molecularly-defined gradient distribution of excitatory neuron subtypes across cubic millimeter-scale volumes (>30,000 cells), and discovered a short-range 3D pattern of self-clustering shared by many inhibitory neuron subtypes that was accurately identifiable with a 3D STARmap approach.  more » « less
Award ID(s):
1707261
NSF-PAR ID:
10063217
Author(s) / Creator(s):
Date Published:
Journal Name:
Science
ISSN:
1440-0502
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
More Like this
  1. Fernandez-Valverde, Selene L. (Ed.)
    Both the composition of cell types and their spatial distribution in a tissue play a critical role in cellular function, organ development, and disease progression. For example, intratumor heterogeneity and the distribution of transcriptional and genetic events in single cells drive the genesis and development of cancer. However, it can be challenging to fully characterize the molecular profile of cells in a tissue with high spatial resolution because microscopy has limited ability to extract comprehensive genomic information, and the spatial resolution of genomic techniques tends to be limited by dissection. There is a growing need for tools that can be used to explore the relationship between histological features, gene expression patterns, and spatially correlated genomic alterations in healthy and diseased tissue samples. Here, we present a technique that combines label-free histology with spatially resolved multiomics in unfixed and unstained tissue sections. This approach leverages stimulated Raman scattering microscopy to provide chemical contrast that reveals histological tissue architecture, allowing for high-resolution in situ laser microdissection of regions of interests. These microtissue samples are then processed for DNA and RNA sequencing to identify unique genetic profiles that correspond to distinct anatomical regions. We demonstrate the capabilities of this technique by mapping gene expression and copy number alterations to histologically defined regions in human oral squamous cell carcinoma (OSCC). Our approach provides complementary insights in tumorigenesis and offers an integrative tool for macroscale cancer tissues with spatial multiomics assessments. 
    more » « less
  2. Abstract

    Single‐neuron gene expression studies may be especially important for understanding nervous system structure and function because of the neuron‐specific functionality and plasticity that defines functional neural circuits. Cellular dissociation is a prerequisite technical manipulation for single‐cell and single cell‐population studies, but the extent to which the cellular dissociation process affects neural gene expression has not been determined. This information is necessary for interpreting the results of experimental manipulations that affect neural function such as learning and memory. The goal of this research was to determine the impact of cellular dissociation on brain transcriptomes. We compared gene expression of microdissected samples from the dentate gyrus (DG), CA3, and CA1 subfields of the mouse hippocampus either prepared by a standard tissue homogenization protocol or subjected to enzymatic digestion used to dissociate cells within tissues. We report that compared to homogenization, enzymatic dissociation alters about 350 genes or 2% of the hippocampal transcriptome. While only a few genes canonically implicated in long‐term potentiation and fear memory change expression levels in response to the dissociation procedure, these data indicate that sample preparation can affect gene expression profiles, which might confound interpretation of results depending on the research question. This study is important for the investigation of any complex tissues as research effort moves from subfield level analysis to single cell analysis of gene expression.

     
    more » « less
  3. Abstract

    Objective.Intracortical brain interfaces are an ever evolving technology with growing potential for clinical and research applications. The chronic tissue response to these devices traditionally has been characterized by glial scarring, inflammation, oxidative stress, neuronal loss, and blood-brain barrier disruptions. The full complexity of the tissue response to implanted devices is still under investigation.Approach.In this study, we have utilized RNA-sequencing to identify the spatiotemporal gene expression patterns in interfacial (within 100µm) and distal (500µm from implant) brain tissue around implanted silicon microelectrode arrays. Naïve, unimplanted tissue served as a control.Main results.The data revealed significant overall differential expression (DE) in contrasts comparing interfacial tissue vs naïve (157 DE genes), interfacial vs distal (94 DE genes), and distal vs naïve tissues (21 DE genes). Our results captured previously characterized mechanisms of the foreign body response, such as astroglial encapsulation, as well as novel mechanisms which have not yet been characterized in the context of indwelling neurotechnologies. In particular, we have observed perturbations in multiple neuron-associated genes which potentially impact the intrinsic function and structure of neurons at the device interface. In addition to neuron-associated genes, the results presented in this study identified significant DE in genes which are associated with oligodendrocyte, microglia, and astrocyte involvement in the chronic tissue response.Significance. The results of this study increase the fundamental understanding of the complexity of tissue response in the brain and provide an expanded toolkit for future investigation into the bio-integration of implanted electronics with tissues in the central nervous system.

     
    more » « less
  4. Abstract

    Spinal motor neurons (MNs) integrate sensory stimuli and brain commands to generate movements. In vertebrates, the molecular identities of the cardinal MN types such as those innervating limb versus trunk muscles are well elucidated. Yet the identities of finer subtypes within these cell populations that innervate individual muscle groups remain enigmatic. Here we investigate heterogeneity in mouse MNs using single-cell transcriptomics. Among limb-innervating MNs, we reveal a diverse neuropeptide code for delineating putative motor pool identities. Additionally, we uncover that axial MNs are subdivided into three molecularly distinct subtypes, defined by mediolaterally-biased Satb2, Nr2f2 or Bcl11b expression patterns with different axon guidance signatures. These three subtypes are present in chicken and human embryos, suggesting a conserved axial MN expression pattern across higher vertebrates. Overall, our study provides a molecular resource of spinal MN types and paves the way towards deciphering how neuronal subtypes evolved to accommodate vertebrate motor behaviors.

     
    more » « less
  5. Abstract

    Spatial transcriptomics technologies have shed light on the complexities of tissue structures by accurately mapping spatial microenvironments. Nonetheless, a myriad of methods, especially those utilized in platforms like Visium, often relinquish spatial details owing to intrinsic resolution limitations. In response, we introduce TransformerST, an innovative, unsupervised model anchored in the Transformer architecture, which operates independently of references, thereby ensuring cost-efficiency by circumventing the need for single-cell RNA sequencing. TransformerST not only elevates Visium data from a multicellular level to a single-cell granularity but also showcases adaptability across diverse spatial transcriptomics platforms. By employing a vision transformer-based encoder, it discerns latent image-gene expression co-representations and is further enhanced by spatial correlations, derived from an adaptive graph Transformer module. The sophisticated cross-scale graph network, utilized in super-resolution, significantly boosts the model’s accuracy, unveiling complex structure–functional relationships within histology images. Empirical evaluations validate its adeptness in revealing tissue subtleties at the single-cell scale. Crucially, TransformerST adeptly navigates through image-gene co-representation, maximizing the synergistic utility of gene expression and histology images, thereby emerging as a pioneering tool in spatial transcriptomics. It not only enhances resolution to a single-cell level but also introduces a novel approach that optimally utilizes histology images alongside gene expression, providing a refined lens for investigating spatial transcriptomics.

     
    more » « less