scholarly journals High-throughput mapping of long-range neuronal projection using in situ sequencing

2018 ◽  
Author(s):  
Xiaoyin Chen ◽  
Yu-Chi Sun ◽  
Huiqing Zhan ◽  
Justus M Kebschull ◽  
Stephan Fischer ◽  
...  
Keyword(s):  
High Throughput ◽  
Spatial Organization ◽  
Neural Circuits ◽  
Cell Types ◽  
Projection Neurons ◽  
Spatially Resolved ◽  
Neuronal Projection ◽  
Depth Analysis ◽  
Organizing Principles

SummaryUnderstanding neural circuits requires deciphering interactions among myriad cell types defined by spatial organization, connectivity, gene expression, and other properties. Resolving these cell types requires both single neuron resolution and high throughput, a challenging combination with conventional methods. Here we introduce BARseq, a multiplexed method based on RNA barcoding for mapping projections of thousands of spatially resolved neurons in a single brain, and relating those projections to other properties such as gene or Cre expression. Mapping the projections to 11 areas of 3579 neurons in mouse auditory cortex using BARseq confirmed the laminar organization of the three top classes (IT, PT-like and CT) of projection neurons. In depth analysis uncovered a novel projection type restricted almost exclusively to transcriptionally-defined subtypes of IT neurons. By bridging anatomical and transcriptomic approaches at cellular resolution with high throughput, BARseq can potentially uncover the organizing principles underlying the structure and formation of neural circuits.

scholarly journals High-Throughput Mapping of Long-Range Neuronal Projection Using In Situ Sequencing

Cell ◽  
2019 ◽  
Vol 179 (3) ◽  
pp. 772-786.e19 ◽  
Author(s):  
Xiaoyin Chen ◽  
Yu-Chi Sun ◽  
Huiqing Zhan ◽  
Justus M. Kebschull ◽  
Stephan Fischer ◽  
...  
Keyword(s):  
Long Range ◽  
High Throughput ◽  
Neuronal Projection

scholarly journals Robust Acquisition of High Resolution Spatial Transcriptomes from Preserved Tissues with Immunofluorescence Based Laser Capture Microdissection

2021 ◽  
Author(s):  
Xiaodan Zhang ◽  
Chuansheng Hu ◽  
Chen Huang ◽  
Ying Wei ◽  
Xiaowei Li ◽  
...  
Keyword(s):  
Laser Capture Microdissection ◽  
Spatial Organization ◽  
Spatial Information ◽  
A Priori ◽  
Rna Degradation ◽  
Spatially Resolved ◽  
Mouse Small Intestine ◽  
Dissociated Cells ◽  
Laser Capture

The functioning of tissues is fundamentally dependent upon not only the phenotypes of the constituent cells but also their spatial organization in the tissue. However, obtaining comprehensive transcriptomic data based on established phenotypes while retaining this spatial information has been challenging. Here we present a general and robust method based on immunofluorescence-guided laser capture microdissection (immuno-LCM-RNAseq) to enable acquisition of finely resolved spatial transcriptomes with as few as tens of cells from snap-frozen or RNAlater-treated tissues, overcoming the long-standing problem of significant RNA degradation during this lengthy process. The efficacy of this approach is exemplified by the characterization of differences at the transcript isoform level between cells at the tip versus the main capillary body of the mouse small intestine lacteal. With the extensive repertoire of phenotype-specific antibodies that are presently available, our method provides a powerful means by which spatially resolved cellular states can be delineated in situ with preserved tissues. Moreover, such high quality spatial transcriptomes defined by immuno-markers can be used to compare with clusters obtained from single-cell RNAseq studies of dissociated cells as well as applied to bead-based spatial transcriptomics approaches that require such information a priori for cell identification.

scholarly journals Spatial charting of single cell transcriptomes in tissues

2021 ◽  
Author(s):  
Nicholas Navin ◽  
Runmin Wei ◽  
Siyuan He ◽  
Shanshan Bai ◽  
Emi Sei ◽  
...  
Keyword(s):  
Single Cell ◽  
Spatial Organization ◽  
Spatial Information ◽  
Ductal Carcinoma ◽  
Single Cells ◽  
Cell Types ◽  
Spatial Structures ◽  
Tissue Sections ◽  
Normal Mouse Brain

Single cell RNA sequencing (scRNA-seq) methods can profile the transcriptomes of single cells but cannot preserve spatial information. Conversely, spatial transcriptomics (ST) assays can profile spatial regions in tissue sections, but do not have single cell genomic resolution. Here, we developed a computational approach called SChart, that combines these two datasets to achieve single cell spatial mapping of cell types, cell states and continuous phenotypes. We applied SChart to reconstruct cellular spatial structures in existing datasets from normal mouse brain and kidney tissues to validate our approach. We also performed scRNA-seq and ST experiments on two ductal carcinoma in situ (DCIS) tissues and applied SChart to identify subclones that were restricted to different ducts, and specific T cell states adjacent to the tumor areas. Our data shows that SChart can accurately map single cells in diverse tissue types to resolve their spatial organization into cellular neighborhoods and tissue structures.

scholarly journals Combined single-cell and spatial transcriptomics reveals the molecular, cellular and spatial bone marrow niche organization

2019 ◽  
Author(s):  
Chiara Baccin ◽  
Jude Al-Sabah ◽  
Lars Velten ◽  
Patrick M. Helbling ◽  
Florian Grünschläger ◽  
...  
Keyword(s):  
Bone Marrow ◽  
Single Cell ◽  
Spatial Organization ◽  
Cell Types ◽  
Bone Marrow Niche ◽  
Cellular Composition ◽  
Spatially Resolved ◽  
Resident Cell ◽  
Cell Gene Expression ◽  
Novel Strategy

SUMMARYThe bone marrow (BM) constitutes the primary site for life-long blood production and skeletal regeneration. However, its cellular composition and the spatial organization into distinct ‘niches’ remains controversial. Here, we combine single-cell and spatially resolved transcriptomics to systematically map the molecular and cellular composition of the endosteal, sinusoidal, and arteriolar BM niches. This allowed us to transcriptionally profile all major BM resident cell types, determine their localization, and clarify the cellular and spatial sources of key growth factors and cytokines. Our data demonstrate that previously unrecognized Cxcl12-abundant reticular (CAR) cell subsets (i.e. Adipo- and Osteo-CAR cells) differentially localize to sinusoidal or arteriolar surfaces, locally act as ‘professional cytokine secreting cells’, and thereby establish distinct peri-vascular micro-niches. Importantly, we also demonstrate that the 3-dimensional organization of the BM can be accurately inferred from single-cell gene expression data using the newly developed RNA-Magnet algorithm. Together, our study reveals the cellular and spatial organization of BM niches, and offers a novel strategy to dissect the complex organization of whole organs in a systematic manner.One Sentence SummaryIntegration of single-cell and spatial transcriptomics reveals the molecular, cellular and spatial organization of bone marrow niches

scholarly journals A spatial atlas of inhibitory cell types in mouse hippocampus

2018 ◽  
Author(s):  
Xiaoyan Qian ◽  
Kenneth D. Harris ◽  
Thomas Hauling ◽  
Dimitris Nicoloutsopoulos ◽  
Ana B. Muñoz-Manchado ◽  
...  
Keyword(s):  
Spatial Organization ◽  
Memory Function ◽  
Expression Patterns ◽  
Ground Truth ◽  
Spatial Arrangement ◽  
Cell Types ◽  
Cell System ◽  
Inhibitory Neurons ◽  
Hippocampal Area

Understanding the function of a tissue requires knowing the spatial organization of its constituent cell types. In the cerebral cortex, single-cell RNA sequencing (scRNA-seq) has revealed the genome-wide expression patterns that define its many, closely related cell types, but cannot reveal their spatial arrangement. Here we introduce probabilistic cell typing by in situ sequencing (pciSeq), an approach that leverages prior scRNA-seq classification to identify cell types using multiplexed in situ RNA detection. We applied this method to map the inhibitory neurons of hippocampal area CA1, a cell system critical for memory function, for which ground truth is available from extensive prior work identifying the laminar organization of subtly differing cell types. Our method confidently identified 16 interneuron classes, in a spatial arrangement closely matching ground truth. This method will allow identifying the spatial organization of fine cell types across the brain and other tissues.

scholarly journals XYZeq: Spatially resolved single-cell RNA sequencing reveals expression heterogeneity in the tumor microenvironment

2021 ◽  
Vol 7 (17) ◽  
pp. eabg4755
Author(s):  
Youjin Lee ◽  
Derek Bogdanoff ◽  
Yutong Wang ◽  
George C. Hartoularos ◽  
Jonathan M. Woo ◽  
...  
Keyword(s):  
Single Cell ◽  
Rna Sequencing ◽  
Spatial Organization ◽  
Cell Types ◽  
Mouse Tumor ◽  
Spatially Resolved ◽  
Distinct Cell ◽  
Single Cell Rna Sequencing ◽  
A Cell ◽  
Anatomical Space

Single-cell RNA sequencing (scRNA-seq) of tissues has revealed remarkable heterogeneity of cell types and states but does not provide information on the spatial organization of cells. To better understand how individual cells function within an anatomical space, we developed XYZeq, a workflow that encodes spatial metadata into scRNA-seq libraries. We used XYZeq to profile mouse tumor models to capture spatially barcoded transcriptomes from tens of thousands of cells. Analyses of these data revealed the spatial distribution of distinct cell types and a cell migration-associated transcriptomic program in tumor-associated mesenchymal stem cells (MSCs). Furthermore, we identify localized expression of tumor suppressor genes by MSCs that vary with proximity to the tumor core. We demonstrate that XYZeq can be used to map the transcriptome and spatial localization of individual cells in situ to reveal how cell composition and cell states can be affected by location within complex pathological tissue.

scholarly journals Liquid-crystal organization of liver tissue

2018 ◽  
Author(s):  
Hernán Morales-Navarrete ◽  
Hidenori Nonaka ◽  
André Scholich ◽  
Fabián Segovia-Miranda ◽  
Walter de Back ◽  
...  
Keyword(s):  
Liquid Crystal ◽  
Self Assembly ◽  
Liver Tissue ◽  
Spatial Organization ◽  
Structural Model ◽  
Cell Types ◽  
Soft Condensed Matter ◽  
Distinct Cell ◽  
Tissue Geometry ◽  
Organizing Principles

AbstractFunctional tissue architecture originates by self-assembly of distinct cell types, following tissue-specific rules of cell-cell interactions. In the liver, a structural model of the lobule was pioneered by Elias in 1949. This model, however, is in contrast with the apparent random 3D arrangement of hepatocytes. Since then, no significant progress has been made to derive the organizing principles of liver tissue. To solve this outstanding problem, we computationally reconstructed 3D tissue geometry from microscopy images and analyzed it applying soft-condensed-matter-physics concepts. Surprisingly, analysis of the spatial organization of cell polarity revealed that hepatocytes are not randomly oriented but follow a long-range liquid-crystal order. This does not depend exclusively on hepatocytes receiving instructive signals by endothelial cells as generally assumed, since silencing Integrin-ß1 disrupted both liquid-crystal order and organization of the sinusoidal network. Our results suggest that bi-directional communication between hepatocytes and sinusoids underlies the self-organization of liver tissue.

scholarly journals SM-Omics: An automated platform for high-throughput spatial multi-omics

2020 ◽  
Author(s):  
Sanja Vickovic ◽  
Britta Lötstedt ◽  
Johanna Klughammer ◽  
Åsa Segerstolpe ◽  
Orit Rozenblatt-Rosen ◽  
...  
Keyword(s):  
High Throughput ◽  
Spatial Organization ◽  
Spatially Resolved ◽  
Automated Platform

AbstractThe spatial organization of cells and molecules plays a key role in tissue function in homeostasis and disease. Spatial Transcriptomics (ST) has recently emerged as a key technique to capture and positionally barcode RNAs directly in tissues. Here, we advance the application of ST at scale, by presenting Spatial Multiomics (SM-Omics) as a fully automated high-throughput platform for combined and spatially resolved transcriptomics and antibody-based proteomics.

scholarly journals Spatial organization of the somatosensory cortex revealed by cyclic smFISH

2018 ◽  
Author(s):  
Simone Codeluppi ◽  
Lars E. Borm ◽  
Amit Zeisel ◽  
Gioele La Manno ◽  
Josina A. van Lunteren ◽  
...  
Keyword(s):  
Single Cell ◽  
Somatosensory Cortex ◽  
Single Molecule ◽  
Spatial Organization ◽  
Spatial Information ◽  
Cell Types ◽  
Cellular Organization ◽  
New Methods ◽  
The Brain

The global efforts towards the creation of a molecular census of the brain using single-cell transcriptomics is generating a large catalog of molecularly defined cell types lacking spatial information. Thus, new methods are needed to map a large number of cell-specific markers simultaneously on large tissue areas. Here, we developed a cyclic single molecule fluorescence in situ hybridization methodology and defined the cellular organization of the somatosensory cortex using markers identified by single-cell transcriptomics.

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