scholarly journals A Method for Cryopreservation and Single Nucleus RNA-sequencing of Normal Adult Human Interventricular Septum Heart Tissue Reveals Cellular Diversity and Function

2020 ◽  
Author(s):  
Amy Larson ◽  
Michael T. Chin
Keyword(s):  
Single Cell ◽  
Human Heart ◽  
Expression Patterns ◽  
Interventricular Septum ◽  
Cell Types ◽  
Heart Tissue ◽  
Gene Expression Patterns ◽  
High Quality ◽  
Normal Human ◽  
Human Heart Tissue

Abstract Background: Single cell sequencing of human heart tissue is technically challenging and methods to cryopreserve heart tissue for obtaining single cell information have not been standardized. Studies published to date have used varying methods to preserve and process human heart tissue, and have generated interesting datasets, but development of a biobanking standard has not yet been achieved. Heart transcription patterns are known to be regionally diverse, and there are few single cell datasets for normal human heart tissue. Methods: Using pig tissue, we developed a rigorous and reproducible method for tissue mincing and cryopreservation that allowed recovery of high quality single nuclei RNA. We subsequently tested this protocol on normal human heart tissue obtained from organ donors and were able to recover high quality nuclei for generation of single nuclei RNA-seq datasets, using a commercially available platform from 10x Genomics. We analyzed these datasets using standard software packages such as CellRanger and Seurat. Results: Human heart tissue preserved with our method consistently yielded nuclear RNA with RNA Integrity Numbers of greater than 8.5. We demonstrate the utility of this method for single nuclei RNA-sequencing of the normal human interventricular septum and delineating its cellular diversity. The human IVS showed unexpected diversity with detection of 23 distinct cell clusters that were subsequently categorized into different cell types. Cardiomyocytes and fibroblasts were the most commonly identified cell types and could be further subdivided into 5 different cardiomyocyte subtypes and 6 different fibroblast subtypes that differed by gene expression patterns. Ingenuity Pathway analysis of these gene expression patterns suggested functional diversity in these cell subtypes. Conclusions: Here we report a simple technical method for cryopreservation and subsequent nuclear isolation of human interventricular septum tissue that can be done with common laboratory equipment. We show how this method can be used to generate single nuclei transcriptomic datasets that rival those already published by larger groups in terms of cell diversity and complexity and suggest that this simple method can provide guidance for biobanking of human myocardial tissue for complex genomic analysis.

scholarly journals A method for cryopreservation and single nucleus RNA-sequencing of normal adult human interventricular septum heart tissue reveals cellular diversity and function

2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Amy Larson ◽  
Michael T. Chin
Keyword(s):  
Single Cell ◽  
Human Heart ◽  
Expression Patterns ◽  
Interventricular Septum ◽  
Cell Types ◽  
Heart Tissue ◽  
Gene Expression Patterns ◽  
High Quality ◽  
Normal Human ◽  
Human Heart Tissue

Abstract Background Single cell sequencing of human heart tissue is technically challenging and methods to cryopreserve heart tissue for obtaining single cell information have not been standardized. Studies published to date have used varying methods to preserve and process human heart tissue, and have generated interesting datasets, but development of a biobanking standard has not yet been achieved. Heart transcription patterns are known to be regionally diverse, and there are few single cell datasets for normal human heart tissue. Methods Using pig tissue, we developed a rigorous and reproducible method for tissue mincing and cryopreservation that allowed recovery of high quality single nuclei RNA. We subsequently tested this protocol on normal human heart tissue obtained from organ donors and were able to recover high quality nuclei for generation of single nuclei RNA-seq datasets, using a commercially available platform from 10× Genomics. We analyzed these datasets using standard software packages such as CellRanger and Seurat. Results Human heart tissue preserved with our method consistently yielded nuclear RNA with RNA Integrity Numbers of greater than 8.5. We demonstrate the utility of this method for single nuclei RNA-sequencing of the normal human interventricular septum and delineating its cellular diversity. The human IVS showed unexpected diversity with detection of 23 distinct cell clusters that were subsequently categorized into different cell types. Cardiomyocytes and fibroblasts were the most commonly identified cell types and could be further subdivided into 5 different cardiomyocyte subtypes and 6 different fibroblast subtypes that differed by gene expression patterns. Ingenuity Pathway analysis of these gene expression patterns suggested functional diversity in these cell subtypes. Conclusions Here we report a simple technical method for cryopreservation and subsequent nuclear isolation of human interventricular septum tissue that can be done with common laboratory equipment. We show how this method can be used to generate single nuclei transcriptomic datasets that rival those already published by larger groups in terms of cell diversity and complexity and suggest that this simple method can provide guidance for biobanking of human myocardial tissue for complex genomic analysis.

scholarly journals A single cell brain atlas in human Alzheimer’s disease

2019 ◽  
Author(s):  
Alexandra Grubman ◽  
Gabriel Chew ◽  
John F. Ouyang ◽  
Guizhi Sun ◽  
Xin Yi Choo ◽  
...  
Keyword(s):  
Gene Expression ◽  
Transcription Factor ◽  
Single Cell ◽  
Cell Fate ◽  
Expression Patterns ◽  
Cell Types ◽  
Gene Expression Patterns ◽  
Cell Type ◽  
Web Resource ◽  
Cell Type Specific

AbstractAlzheimer’s disease (AD) is a heterogeneous disease that is largely dependent on the complex cellular microenvironment in the brain. This complexity impedes our understanding of how individual cell types contribute to disease progression and outcome. To characterize the molecular and functional cell diversity in the human AD brain we utilized single nuclei RNA- seq in AD and control patient brains in order to map the landscape of cellular heterogeneity in AD. We detail gene expression changes at the level of cells and cell subclusters, highlighting specific cellular contributions to global gene expression patterns between control and Alzheimer’s patient brains. We observed distinct cellular regulation of APOE which was repressed in oligodendrocyte progenitor cells (OPCs) and astrocyte AD subclusters, and highly enriched in a microglial AD subcluster. In addition, oligodendrocyte and microglia AD subclusters show discordant expression of APOE. Integration of transcription factor regulatory modules with downstream GWAS gene targets revealed subcluster-specific control of AD cell fate transitions. For example, this analysis uncovered that astrocyte diversity in AD was under the control of transcription factor EB (TFEB), a master regulator of lysosomal function and which initiated a regulatory cascade containing multiple AD GWAS genes. These results establish functional links between specific cellular sub-populations in AD, and provide new insights into the coordinated control of AD GWAS genes and their cell-type specific contribution to disease susceptibility. Finally, we created an interactive reference web resource which will facilitate brain and AD researchers to explore the molecular architecture of subtype and AD-specific cell identity, molecular and functional diversity at the single cell level.HighlightsWe generated the first human single cell transcriptome in AD patient brainsOur study unveiled 9 clusters of cell-type specific and common gene expression patterns between control and AD brains, including clusters of genes that present properties of different cell types (i.e. astrocytes and oligodendrocytes)Our analyses also uncovered functionally specialized sub-cellular clusters: 5 microglial clusters, 8 astrocyte clusters, 6 neuronal clusters, 6 oligodendrocyte clusters, 4 OPC and 2 endothelial clusters, each enriched for specific ontological gene categoriesOur analyses found manifold AD GWAS genes specifically associated with one cell-type, and sets of AD GWAS genes co-ordinately and differentially regulated between different brain cell-types in AD sub-cellular clustersWe mapped the regulatory landscape driving transcriptional changes in AD brain, and identified transcription factor networks which we predict to control cell fate transitions between control and AD sub-cellular clustersFinally, we provide an interactive web-resource that allows the user to further visualise and interrogate our dataset.Data resource web interface:http://adsn.ddnetbio.com

scholarly journals Human CardioChimeras: Creation of a Novel ‘Next Generation’ Cardiac Cell

2019 ◽  
Author(s):  
Fareheh Firouzi ◽  
Sarmistha Sinha Choudhury ◽  
Kathleen Broughton ◽  
Adriana Salazar ◽  
Mark A Sussman
Keyword(s):  
Cell Fusion ◽  
Human Heart ◽  
Sendai Virus ◽  
Hybrid Cell ◽  
Cell Types ◽  
Heart Tissue ◽  
List Type ◽  
Hybrid Cells ◽  
Next Generation ◽  
Human Heart Tissue

AbstractBackgroundCardioChimeras (CCs) produced by fusion of murine c-kit+ cardiac interstitial cells (cCIC) with mesenchymal stem cells (MSCs) promote superior structural and functional recovery in a mouse model of myocardial infarction (MI) compared to either precursor cell alone or in combination. Creation of human CardioChimeras (hCC) represents the next step in translational development of this novel cell type, but new challenges arise when working with cCICs isolated and expanded from human heart tissue samples. The objective of the study was to establish a reliable cell fusion protocol for consistent optimized creation of hCCs and characterize fundamental hCC properties.Methods and ResultsCell fusion was induced by incubating human cCICs and MSCs at a 2:1 ratio with inactivated Sendai virus. Hybrid cells were sorted into 96-well microplates for clonal expansion to derive unique cloned hCCs, which were then characterized for various cellular and molecular properties. hCCs exhibited enhanced survival relative to the parent cells and promoted cardiomyocyte survival in response to serum deprivation in vitro.ConclusionsThe generation of hCC is demonstrated and validated in this study, representing the next step toward implementation of a novel cell product for therapeutic development. Feasibility of creating human hybrid cells prompts consideration of multiple possibilities to create novel chimeric cells derived from cells with desirable traits to promote healing in pathologically damaged myocardium.Clinical Perspective“Next generation” cell therapeutics will build upon initial findings that demonstrate enhanced reparative action of combining distinct cell types for treatment of cardiomyopathic injury.Differential biological properties of various cell types are challenging for optimization of delivery, engraftment, persistence, and synergistic action when used in combination.Creation of a novel hybrid cell called a CardioChimera overcomes limitations inherent to use of multiple cell types.CardioChimeras exhibit unique properties relative to either parental cell anticipated to be advantageous in cellular therapeutic applications.CardioChimeras have now been created and characterized using cells derived from human heart tissue, advancing initial proof of concept previously demonstrated with mice.CardioChimeras represent an engineered solution that can be implemented as a path forward for improving the outcome of myocardial cell therapy.

scholarly journals Comprehensive characterization of tissue-specific chromatin accessibility in L2 Caenorhabditis elegans nematodes

2020 ◽  
Author(s):  
Timothy J. Durham ◽  
Riza M. Daza ◽  
Louis Gevirtzman ◽  
Darren A. Cusanovich ◽  
William Stafford Noble ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Expression Patterns ◽  
Cell Types ◽  
Chromatin Accessibility ◽  
Gene Expression Patterns ◽  
Rna Seq ◽  
Cell Type ◽  
Tissue Specific ◽  
C Elegans

AbstractRecently developed single cell technologies allow researchers to characterize cell states at ever greater resolution and scale. C. elegans is a particularly tractable system for studying development, and recent single cell RNA-seq studies characterized the gene expression patterns for nearly every cell type in the embryo and at the second larval stage (L2). Gene expression patterns are useful for learning about gene function and give insight into the biochemical state of different cell types; however, in order to understand these cell types, we must also determine how these gene expression levels are regulated. We present the first single cell ATAC-seq study in C. elegans. We collected data in L2 larvae to match the available single cell RNA-seq data set, and we identify tissue-specific chromatin accessibility patterns that align well with existing data, including the L2 single cell RNA-seq results. Using a novel implementation of the latent Dirichlet allocation algorithm, we leverage the single-cell resolution of the sci-ATAC-seq data to identify accessible loci at the level of individual cell types, providing new maps of putative cell type-specific gene regulatory sites, with promise for better understanding of cellular differentiation and gene regulation in the worm.

Abstract 16742: Single-Cell Transcriptional and Epigenomic Dissection of Human Heart in Health and Coronary Artery Disease Reveals Cell-type-Specific Driver Genes and Pathways

Circulation ◽  
2020 ◽  
Vol 142 (Suppl_3) ◽  
Author(s):  
Suvi Linna Kuosmanen ◽  
Eloi Schmauch ◽  
Kyriakitsa Galani ◽  
Carles Boix ◽  
Yongjin P Park ◽  
...  
Keyword(s):  
Coronary Artery Disease ◽  
Single Cell ◽  
Human Heart ◽  
Target Genes ◽  
Expression Patterns ◽  
Cell Types ◽  
Heart Cell ◽  
Cell Type ◽  
Cell Type Specific ◽  
Artery Disease

Genome-wide association studies have uncovered over 200 genetic loci underlying coronary artery disease (CAD), providing great hope for a deeper understanding of the causal mechanisms leading to this disease. However, in order to understand CAD at the molecular level, it is necessary to uncover cell-type-specific circuits and to use these circuits to dissect driver variants, genes, pathways, and cell types, in normal and diseased tissues. Here, we provide the most detailed single-cell dissection of human heart cell types, using cardiac biopsies collected during open-heart surgery from healthy, CAD, and CAD-related heart failure donors, and profiling both transcriptional (scRNA-seq) and epigenomic (scATAC-seq) changes. Using this approach, we identify 12 major heart cell types, including typical cardiovascular cells (cardiomyocytes, endothelial cells, fibroblasts), rarer cell types (B cells, neurons, Schwann cells), and previously-unrecognized layer-specific epithelial and endothelial cell types. We define markers for each cell type, providing the first extensive reference set for the living human heart. In addition, we define differential gene expression patterns in CAD relative to control samples, revealing substantial differences in cell-type-specific expression of disease-related genes, emphasizing, for example, the importance of the vascular endothelium in the pathogenesis of CAD. Strikingly, further clustering of the cell types based on specific subtypes revealed important differences in their expression patterns of disease-associated genes. These changes enrich in known CAD genetic loci, enabling us to recognize their likely target genes from scRNA-seq expression changes, candidate driver variants based on scATAC-seq localization and differential DNA accessibility, and candidate upstream regulators based on their enriched motif occurrences in scATAC loci. Overall, our results highlight the relevance and potential of single-cell transcriptional and epigenomic analyses to gain new biological insights into cardiovascular disease, and to recognize novel therapeutic target genes, pathways, and the cell types where they act.

CHOP TMC Single Cell Multiome ATAC + Gene Expression v1

2021 ◽  
Author(s):  
Po Hu ◽  
Liming Pei
Keyword(s):  
Life Span ◽  
Single Cell ◽  
Human Heart ◽  
Human Life ◽  
Molecular Signature ◽  
Normal Heart ◽  
High Quality ◽  
Human Lifespan ◽  
Normal Human ◽  
Human Life Span

The human heart is vital for our survival and health, and it presents remarkable anatomical, cellular and functional heterogeneity. The four chambers of the heart, together with specialized arteries, veins, valves and conduction cells, perform distinct yet essential physiological functions. A significant gap of knowledge is that different cell's molecular signature, spatial distribution and interactions, and functional state remain little understood at the single-cell level. The goal of the heart Organ-Specific Project (OSP) is to address this knowledge gap and generate high quality, single-cell resolution, longitudinal imaging and multiomics data of normal human hearts across the entire human lifespan. To achieve this goal, we propose the following three specific aims: 1) To refine protocols of biospecimen processing, multiomics and imaging assays and define inter-individual variability using our existing banked normal human hearts. 2) To procure, archive and annotate high-quality normal heart samples across the entire human life span. We have established a streamlined procurement and biorepository infrastructure to support our heart OSP. We will procure normal heart and bone from the same donor of 5 different age groups across the entire human life span. 3) To spatially and quantitatively profile normal heart specimens across the entire human lifespan using a set of robust and scalable imaging and single-cell omics assays. In summary, the heart OSP will broadly impact the entire research community and jumpstart basic-science and medical discoveries based on a sophisticated understanding of the key molecular circuits underlying the development and aging of human heart.

scholarly journals Single Cell and Single Nuclei Analysis Human Heart Tissue v1 (protocols.io.veae3ae)

protocols.io ◽  
2018 ◽  
Author(s):  
Monika Litvinukova ◽  
Eric Lindberg ◽  
Henrike Maatz ◽  
Hongbo Zhang ◽  
Michael Radke ◽  
...  
Keyword(s):  
Single Cell ◽  
Human Heart ◽  
Heart Tissue ◽  
Human Heart Tissue

scholarly journals Identifying cell types from single-cell data based on similarities and dissimilarities between cells

2021 ◽  
Vol 22 (S3) ◽  
Author(s):  
Yuanyuan Li ◽  
Ping Luo ◽  
Yi Lu ◽  
Fang-Xiang Wu
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Spectral Clustering ◽  
Incidence Matrix ◽  
Expression Patterns ◽  
Cell Types ◽  
Clustering Method ◽  
Different Types ◽  
Cell Data ◽  
Spectral Clustering Method

Abstract Background With the development of the technology of single-cell sequence, revealing homogeneity and heterogeneity between cells has become a new area of computational systems biology research. However, the clustering of cell types becomes more complex with the mutual penetration between different types of cells and the instability of gene expression. One way of overcoming this problem is to group similar, related single cells together by the means of various clustering analysis methods. Although some methods such as spectral clustering can do well in the identification of cell types, they only consider the similarities between cells and ignore the influence of dissimilarities on clustering results. This methodology may limit the performance of most of the conventional clustering algorithms for the identification of clusters, it needs to develop special methods for high-dimensional sparse categorical data. Results Inspired by the phenomenon that same type cells have similar gene expression patterns, but different types of cells evoke dissimilar gene expression patterns, we improve the existing spectral clustering method for clustering single-cell data that is based on both similarities and dissimilarities between cells. The method first measures the similarity/dissimilarity among cells, then constructs the incidence matrix by fusing similarity matrix with dissimilarity matrix, and, finally, uses the eigenvalues of the incidence matrix to perform dimensionality reduction and employs the K-means algorithm in the low dimensional space to achieve clustering. The proposed improved spectral clustering method is compared with the conventional spectral clustering method in recognizing cell types on several real single-cell RNA-seq datasets. Conclusions In summary, we show that adding intercellular dissimilarity can effectively improve accuracy and achieve robustness and that improved spectral clustering method outperforms the traditional spectral clustering method in grouping cells.

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