Spatial and temporal heterogeneity in the lineage progression of fine oligodendrocyte subtypes.

BACKGROUND: Oligodendrocytes are glial cells that support and insulate axons in the central nervous system through the production of myelin. Oligodendrocytes arise throughout embryonic and early postnatal development from oligodendrocyte precursor cells (OPCs), and recent work demonstrated that they are a transcriptional heterogeneous cell population, but the regional and functional implications of this heterogeneity are less clear. Here, we apply in situ sequencing (ISS) to simultaneously probe the expression of 124 marker genes of distinct oligodendrocyte populations, providing comprehensive maps of the corpus callosum, cingulate, motor, and somatosensory cortex in the brain, as well as gray matter (GM) and white matter (WM) regions in the spinal cord, at postnatal (P10), juvenile (P20), and young adult (P60) stages. We systematically compare the abundances of these populations and investigate the neighboring preference of distinct oligodendrocyte populations. RESULTS: We observed that oligodendrocyte lineage progression is more advanced in the juvenile spinal cord compared to the brain, corroborating with previous studies. We found myelination still ongoing in the adult corpus callosum while it was more advanced in the cortex. Interestingly, we also observed a lateral-to-medial gradient of oligodendrocyte lineage progression in the juvenile cortex, which could be linked to arealization, as well as a deep-to-superficial gradient with mature oligodendrocytes preferentially accumulating in the deeper layers of the cortex. The ISS experiments also exposed differences in abundances and population dynamics over time between GM and WM regions in the brain and spinal cord, indicating regional differences within GM and WM, and we found that neighboring preferences of some oligodendroglia populations are altered from the juvenile to the adult CNS. CONCLUSIONS: Overall, our ISS experiments reveal spatial heterogeneity of oligodendrocyte lineage progression in the brain and spinal cord and uncover differences in the timing of oligodendrocyte differentiation and myelination, which could be relevant to further investigate functional heterogeneity of oligodendroglia, especially in the context of injury or disease.

Hybridization-based in situ sequencing (HybISS) for spatially resolved transcriptomics in human and mouse brain tissue.

Visualization of the transcriptome in situ has proven to be a valuable tool in exploring single-cell RNA-sequencing data, providing an additional spatial dimension to investigate multiplexed gene expression, cell types, disease architecture or even data driven discoveries. In situ sequencing (ISS) method based on padlock probes and rolling circle amplification has been used to spatially resolve gene transcripts in tissue sections of various origins. Here, we describe the next iteration of ISS, HybISS, hybridization-based in situ sequencing. Modifications in probe design allows for a new barcoding system via sequence-by-hybridization chemistry for improved spatial detection of RNA transcripts. Due to the amplification of probes, amplicons can be visualized with standard epifluorescence microscopes for high-throughput efficiency and the new sequencing chemistry removes limitations bound by sequence-by-ligation chemistry of ISS. HybISS design allows for increased flexibility and multiplexing, increased signal-to-noise, all without compromising throughput efficiency of imaging large fields of view. Moreover, the current protocol is demonstrated to work on human brain tissue samples, a source that has proven to be difficult to work with image-based spatial analysis techniques. Overall, HybISS technology works as a targeted amplification detection method for improved spatial transcriptomic visualization, and importantly, with an ease of implementation.

Evaluation of Immuno-Rolling Circle Amplification for Multiplex Detection and Profiling of Antigen-Specific Antibody Isotypes.

Antibody characterization is essential for understanding the immune system and development of diagnostics and therapeutics. Current technologies are mainly focusing on the detection of antigen-specific immunoglobulin G (IgG) using bulk singleplex measurements, which lack information on other isotypes and specificity of individual antibodies. Digital immunoassays based on nucleic acid amplification have demonstrated superior performance by allowing the detection of single molecules in a multiplex and sensitive manner. In this study, we demonstrate for the first time an immuno-rolling circle amplification (immuno-RCA) assay for the multiplex detection of three antigen-specific antibody isotypes (IgG, IgA, and IgM) and its integration with microengraving. To validate this approach, we used the autoimmune disease immune-mediated thrombotic thrombocytopenic purpura (iTTP) as the model disease with anti-ADAMTS13 autoantibodies as the diagnostic target molecules. To identify the anti-ADAMTS13 autoantibody isotypes, we designed a pool of three unique antibody-oligonucleotide conjugates for identification and subsequent amplification and visualization via RCA. To validate this approach, we first confirmed an assay specificity of >88% and a low limit of detection of 0.3 ng/mL in the spiked buffer. Subsequently, we performed a dilution series of an iTTP plasma sample for the multiplex detection of the three isotypes with higher sensitivity compared to an enzyme-linked immunosorbent assay. Finally, we demonstrated single-cell analysis of human B cells and hybridoma cells for the detection of secreted antibodies using microengraving and achieved a detection of 23.3 pg/mL secreted antibodies per hour. This approach could help to improve the understanding of antibody isotype distributions and their roles in various diseases.

Reference-based cell type matching of in situ image-based spatial transcriptomics data on primary visual cortex of mouse brain.

With the advent of multiplex fluorescence in situ hybridization (FISH) and in situ RNA sequencing technologies, spatial transcriptomics analysis is advancing rapidly, providing spatial location and gene expression information about cells in tissue sections at single cell resolution. Cell type classification of these spatially-resolved cells can be inferred by matching the spatial transcriptomics data to reference atlases derived from single cell RNA-sequencing (scRNA-seq) in which cell types are defined by differences in their gene expression profiles. However, robust cell type matching of the spatially-resolved cells to reference scRNA-seq atlases is challenging due to the intrinsic differences in resolution between the spatial and scRNA-seq data. In this study, we systematically evaluated six computational algorithms for cell type matching across four image-based spatial transcriptomics experimental protocols (MERFISH, smFISH, BaristaSeq, and ExSeq) conducted on the same mouse primary visual cortex (VISp) brain region. We find that many cells are assigned as the same type by multiple cell type matching algorithms and are present in spatial patterns previously reported from scRNA-seq studies in VISp. Furthermore, by combining the results of individual matching strategies into consensus cell type assignments, we see even greater alignment with biological expectations. We present two ensemble meta-analysis strategies used in this study and share the consensus cell type matching results in the Cytosplore Viewer ( https://viewer.cytosplore.org ) for interactive visualization and data exploration. The consensus matching can also guide spatial data analysis using SSAM, allowing segmentation-free cell type assignment.

Profiling spatiotemporal gene expression of the developing human spinal cord and implications for ependymoma origin.

The spatiotemporal regulation of cell fate specification in the human developing spinal cord remains largely unknown. In this study, by performing integrated analysis of single-cell and spatial multi-omics data, we used 16 prenatal human samples to create a comprehensive developmental cell atlas of the spinal cord during post-conceptional weeks 5-12. This revealed how the cell fate commitment of neural progenitor cells and their spatial positioning are spatiotemporally regulated by specific gene sets. We identified unique events in human spinal cord development relative to rodents, including earlier quiescence of active neural stem cells, differential regulation of cell differentiation and distinct spatiotemporal genetic regulation of cell fate choices. In addition, by integrating our atlas with pediatric ependymomas data, we identified specific molecular signatures and lineage-specific genes of cancer stem cells during progression. Thus, we delineate spatiotemporal genetic regulation of human spinal cord development and leverage these data to gain disease insight.

Developmental landscape of human forebrain at a single-cell level identifies early waves of oligodendrogenesis.

Oligodendrogenesis in the human central nervous system has been observed mainly at the second trimester of gestation, a much later developmental stage compared to oligodendrogenesis in mice. Here, we characterize the transcriptomic neural diversity in the human forebrain at post-conception weeks (PCW) 8-10. Using single-cell RNA sequencing, we find evidence of the emergence of a first wave of oligodendrocyte lineage cells as early as PCW 8, which we also confirm at the epigenomic level through the use of single-cell ATAC-seq. Using regulatory network inference, we predict key transcriptional events leading to the specification of oligodendrocyte precursor cells (OPCs). Moreover, by profiling the spatial expression of 50 key genes through the use of in situ sequencing (ISS), we identify regions in the human ventral fetal forebrain where oligodendrogenesis first occurs. Our results indicate evolutionary conservation of the first wave of oligodendrogenesis between mice and humans and describe regulatory mechanisms involved in human OPC specification.

Comprehensive in situ mapping of human cortical transcriptomic cell types.

The ability to spatially resolve the cellular architecture of human cortical cell types over informative areas is essential to understanding brain function. We combined in situ sequencing gene expression data and single-nucleus RNA-sequencing cell type definitions to spatially map cells in sections of the human cortex via probabilistic cell typing. We mapped and classified a total of 59,816 cells into all 75 previously defined subtypes to create a first spatial atlas of human cortical cells in their native position, their abundances and genetic signatures. We also examined the precise within- and across-layer distributions of all the cell types and provide a resource for the cell atlas community. The abundances and locations presented here could serve as a reference for further studies, that include human brain tissues and disease applications at the cell type level.