scholarly journals Single-cell sequencing of human iPSC-derived cerebellar organoids shows recapitulation of cerebellar development

2020 ◽  
Author(s):  
Samuel Nayler ◽  
Devika Agarwal ◽  
Fabiola Curion ◽  
Rory Bowden ◽  
Esther B.E. Becker
Keyword(s):  
Single Cell ◽  
Growth Dynamics ◽  
Cell Types ◽  
Cerebellar Development ◽  
Biologically Relevant ◽  
Cell Death Pathways ◽  
Single Cell Profiling ◽  
Cerebellar Cell ◽  
Regulation Of Cell Cycle

ABSTRACTCurrent protocols for producing cerebellar neurons from human pluripotent stem cells (hPSCs) are reliant on animal co-culture and mostly exist as monolayers, which have limited capability to recapitulate the complex arrangement of the brain. We developed a method to differentiate hPSCs into cerebellar organoids that display hallmarks of in vivo cerebellar development. Single-cell profiling followed by comparison to an atlas of the developing murine cerebellum revealed transcriptionally-discrete populations encompassing all major cerebellar cell types. Matrigel encapsulation altered organoid growth dynamics, resulting in differential regulation of cell cycle, migration and cell-death pathways. However, this was at the expense of reproducibility. Furthermore, we showed the contribution of basement membrane signalling to both cellular composition of the organoids and developmentally-relevant gene expression programmes. This model system has exciting implications for studying cerebellar development and disease most notably by providing xeno-free conditions, representing a more biologically relevant and therapeutically tractable culture setting.

scholarly journals High-resolution transcriptional landscape of xeno-free human induced pluripotent stem cell-derived cerebellar organoids

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Samuel Nayler ◽  
Devika Agarwal ◽  
Fabiola Curion ◽  
Rory Bowden ◽  
Esther B. E. Becker
Keyword(s):  
Three Dimensional ◽  
Growth Dynamics ◽  
Induced Pluripotent Stem Cell ◽  
Cell Types ◽  
Cerebellar Development ◽  
Disease Genes ◽  
Complex Processes ◽  
Cerebellar Cell ◽  
Induced Pluripotent

AbstractCurrent protocols for producing cerebellar neurons from human pluripotent stem cells (hPSCs) often rely on animal co-culture and mostly exist as monolayers, limiting their capability to recapitulate the complex processes in the developing cerebellum. Here, we employed a robust method, without the need for mouse co-culture to generate three-dimensional cerebellar organoids from hPSCs that display hallmarks of in vivo cerebellar development. Single-cell profiling followed by comparison to human and mouse cerebellar atlases revealed the presence and maturity of transcriptionally distinct populations encompassing major cerebellar cell types. Encapsulation with Matrigel aimed to provide more physiologically-relevant conditions through recapitulation of basement-membrane signalling, influenced both growth dynamics and cellular composition of the organoids, altering developmentally relevant gene expression programmes. We identified enrichment of cerebellar disease genes in distinct cell populations in the hPSC-derived cerebellar organoids. These findings ascertain xeno-free human cerebellar organoids as a unique model to gain insight into cerebellar development and its associated disorders.

scholarly journals Transcriptomic entropy benchmarks stem cell-derived cardiomyocyte maturation against endogenous tissue at single cell level

2021 ◽  
Vol 17 (9) ◽  
pp. e1009305
Author(s):  
Suraj Kannan ◽  
Michael Farid ◽  
Brian L. Lin ◽  
Matthew Miyamoto ◽  
Chulan Kwon
Keyword(s):  
Stem Cell ◽  
Single Cell ◽  
Pancreatic Beta Cells ◽  
Ad Hoc ◽  
Cell Types ◽  
Developmental Trajectory ◽  
Batch Effects ◽  
Biologically Relevant ◽  
Novel Approach

The immaturity of pluripotent stem cell (PSC)-derived tissues has emerged as a universal problem for their biomedical applications. While efforts have been made to generate adult-like cells from PSCs, direct benchmarking of PSC-derived tissues against in vivo development has not been established. Thus, maturation status is often assessed on an ad-hoc basis. Single cell RNA-sequencing (scRNA-seq) offers a promising solution, though cross-study comparison is limited by dataset-specific batch effects. Here, we developed a novel approach to quantify PSC-derived cardiomyocyte (CM) maturation through transcriptomic entropy. Transcriptomic entropy is robust across datasets regardless of differences in isolation protocols, library preparation, and other potential batch effects. With this new model, we analyzed over 45 scRNA-seq datasets and over 52,000 CMs, and established a cross-study, cross-species CM maturation reference. This reference enabled us to directly compare PSC-CMs with the in vivo developmental trajectory and thereby to quantify PSC-CM maturation status. We further found that our entropy-based approach can be used for other cell types, including pancreatic beta cells and hepatocytes. Our study presents a biologically relevant and interpretable metric for quantifying PSC-derived tissue maturation, and is extensible to numerous tissue engineering contexts.

scholarly journals CellTag Indexing: genetic barcode-based sample multiplexing for single-cell genomics

2018 ◽  
Author(s):  
Chuner Guo ◽  
Wenjun Kong ◽  
Kenji Kamimoto ◽  
Guillermo C. Rivera-Gonzalez ◽  
Xue Yang ◽  
...  
Keyword(s):  
Single Cell ◽  
Cell Types ◽  
Data Interpretation ◽  
Cell Technologies ◽  
Cell Engraftment ◽  
Primary Mouse ◽  
Challenges And Opportunities ◽  
Single Cell Profiling

ABSTRACTSingle-cell technologies have seen rapid advancements in recent years, presenting new analytical challenges and opportunities. These high-throughput assays increasingly require special consideration in experimental design, sample multiplexing, batch effect removal, and data interpretation. Here, we describe a lentiviral barcode-based multiplexing approach, ‘CellTag Indexing’, where we transduce and label samples that can then be pooled together for downstream experimentation and analysis. By introducing predefined genetic barcodes that are transcribed and readily detected, we can reliably read out sample identity and transcriptional state via single-cell profiling. We validate and demonstrate the utility of CellTag Indexing by sequencing transcriptomes at single-cell resolution using a variety of cell types including mouse pre-B cells, primary mouse embryonic fibroblasts, and human HEK293T cells. A unique feature of CellTag Indexing is that the barcodes are heritable. This enables cell populations to be tagged, pooled and tracked over time within the same experimental replicate, then processed together to minimize unwanted biological and technical variation. We demonstrate this feature of CellTagging in long-term tracking of cell engraftment and differentiation, in vivo, in a mouse model of competitive transplant into the large intestine. Together, this presents CellTag Indexing as a broadly applicable genetic multiplexing tool that is complementary with existing single-cell technologies.

Single-cell profiling of skeletal muscle reveals a novel senolytic target: CRYAB

2021 ◽  
Author(s):  
Chandani Limbad ◽  
Ryosuke Doi ◽  
Julia McGirr ◽  
Serban Ciotlos ◽  
Kevin Perez ◽  
...  
Keyword(s):  
Skeletal Muscle ◽  
Single Cell ◽  
Cellular Senescence ◽  
Cholesterol Biosynthesis ◽  
Cell Types ◽  
New Class ◽  
Single Cell Profiling ◽  
Key Driver ◽  
And Function

Abstract Skeletal muscle mass and function can decline with aging, resulting in a syndrome known as sarcopenia. This decline is linked to functional alterations in critical cell types within mature muscle, including fibro-adipogenic progenitors (FAPs) and satellite cells (SCs), driven in part by cellular senescence. We utilized single-cell RNA sequencing and isolated FAPs and SCs to identify novel targets responsible for senescent cell killing - senolysis. We identified the small alpha-crystalline heat shock protein CRYAB as a novel senolytic target. Using chemical inhibitor screening of CRYAB, we identified 25-hydroxycholesterol (25HC), an endogenous metabolite of cholesterol biosynthesis, as a potent senolytic capable of killing senescent cells. We validated 25HC as a senolytic in mouse and human cells in culture and in vivo in mouse skeletal muscle. Thus, 25HC represents a potential new class of senolytics, which may be useful in combating diseases or physiologies in which cellular senescence is a key driver.

scholarly journals Single-cell mapping of focused ultrasound-transfected brain

Gene Therapy ◽  
2021 ◽  
Author(s):  
A. S. Mathew ◽  
C. M. Gorick ◽  
R. J. Price
Keyword(s):  
Single Cell ◽  
Focused Ultrasound ◽  
Cell Types ◽  
Brain Cell ◽  
Therapeutic Modality ◽  
Full Potential ◽  
Stress Genes ◽  
Multiple Cell ◽  
Differential Gene

AbstractGene delivery via focused ultrasound (FUS) mediated blood-brain barrier (BBB) opening is a disruptive therapeutic modality. Unlocking its full potential will require an understanding of how FUS parameters (e.g., peak-negative pressure (PNP)) affect transfected cell populations. Following plasmid (mRuby) delivery across the BBB with 1 MHz FUS, we used single-cell RNA-sequencing to ascertain that distributions of transfected cell types were highly dependent on PNP. Cells of the BBB (i.e., endothelial cells, pericytes, and astrocytes) were enriched at 0.2 MPa PNP, while transfection of cells distal to the BBB (i.e., neurons, oligodendrocytes, and microglia) was augmented at 0.4 MPa PNP. PNP-dependent differential gene expression was observed for multiple cell types. Cell stress genes were upregulated proportional to PNP, independent of cell type. Our results underscore how FUS may be tuned to bias transfection toward specific brain cell types in vivo and predict how those cells will respond to transfection.

scholarly journals Selecting single cell clustering parameter values using subsampling-based robustness metrics

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Ryan B. Patterson-Cross ◽  
Ariel J. Levine ◽  
Vilas Menon
Keyword(s):  
Single Cell ◽  
Optimal Parameter ◽  
Clustering Algorithms ◽  
Cell Types ◽  
Parameter Selection ◽  
Data Set ◽  
Biologically Relevant ◽  
Cell Clustering ◽  
Parameter Values ◽  
Robustness Metrics

Abstract Background Generating and analysing single-cell data has become a widespread approach to examine tissue heterogeneity, and numerous algorithms exist for clustering these datasets to identify putative cell types with shared transcriptomic signatures. However, many of these clustering workflows rely on user-tuned parameter values, tailored to each dataset, to identify a set of biologically relevant clusters. Whereas users often develop their own intuition as to the optimal range of parameters for clustering on each data set, the lack of systematic approaches to identify this range can be daunting to new users of any given workflow. In addition, an optimal parameter set does not guarantee that all clusters are equally well-resolved, given the heterogeneity in transcriptomic signatures in most biological systems. Results Here, we illustrate a subsampling-based approach (chooseR) that simultaneously guides parameter selection and characterizes cluster robustness. Through bootstrapped iterative clustering across a range of parameters, chooseR was used to select parameter values for two distinct clustering workflows (Seurat and scVI). In each case, chooseR identified parameters that produced biologically relevant clusters from both well-characterized (human PBMC) and complex (mouse spinal cord) datasets. Moreover, it provided a simple “robustness score” for each of these clusters, facilitating the assessment of cluster quality. Conclusion chooseR is a simple, conceptually understandable tool that can be used flexibly across clustering algorithms, workflows, and datasets to guide clustering parameter selection and characterize cluster robustness.

scholarly journals Systematic comparison of high-throughput single-cell RNA-seq methods for immune cell profiling

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Tracy M. Yamawaki ◽  
Daniel R. Lu ◽  
Daniel C. Ellwanger ◽  
Dev Bhatt ◽  
Paolo Manzanillo ◽  
...  
Keyword(s):  
Single Cell ◽  
High Throughput ◽  
Immune Cell ◽  
Cell Types ◽  
Data Interpretation ◽  
Detection Sensitivity ◽  
Rna Seq ◽  
Cell Recovery

Abstract Background Elucidation of immune populations with single-cell RNA-seq has greatly benefited the field of immunology by deepening the characterization of immune heterogeneity and leading to the discovery of new subtypes. However, single-cell methods inherently suffer from limitations in the recovery of complete transcriptomes due to the prevalence of cellular and transcriptional dropout events. This issue is often compounded by limited sample availability and limited prior knowledge of heterogeneity, which can confound data interpretation. Results Here, we systematically benchmarked seven high-throughput single-cell RNA-seq methods. We prepared 21 libraries under identical conditions of a defined mixture of two human and two murine lymphocyte cell lines, simulating heterogeneity across immune-cell types and cell sizes. We evaluated methods by their cell recovery rate, library efficiency, sensitivity, and ability to recover expression signatures for each cell type. We observed higher mRNA detection sensitivity with the 10x Genomics 5′ v1 and 3′ v3 methods. We demonstrate that these methods have fewer dropout events, which facilitates the identification of differentially-expressed genes and improves the concordance of single-cell profiles to immune bulk RNA-seq signatures. Conclusion Overall, our characterization of immune cell mixtures provides useful metrics, which can guide selection of a high-throughput single-cell RNA-seq method for profiling more complex immune-cell heterogeneity usually found in vivo.

scholarly journals Automated analysis of filopodial length and spatially resolved protein concentration via adaptive shape tracking

2016 ◽  
Vol 27 (22) ◽  
pp. 3616-3626 ◽  
Author(s):  
Tanumoy Saha ◽  
Isabel Rathmann ◽  
Abhiyan Viplav ◽  
Sadhana Panzade ◽  
Isabell Begemann ◽  
...  
Keyword(s):  
Protein Concentration ◽  
Growth Dynamics ◽  
Automated Analysis ◽  
Cell Types ◽  
Control Mechanisms ◽  
Spatially Resolved ◽  
Novel Approach ◽  
Associated Proteins

Filopodia are dynamic, actin-rich structures that transiently form on a variety of cell types. To understand the underlying control mechanisms requires precise monitoring of localization and concentration of individual regulatory and structural proteins as filopodia elongate and subsequently retract. Although several methods exist that analyze changes in filopodial shape, a software solution to reliably correlate growth dynamics with spatially resolved protein concentration along the filopodium independent of bending, lateral shift, or tilting is missing. Here we introduce a novel approach based on the convex-hull algorithm for parallel analysis of growth dynamics and relative spatiotemporal protein concentration along flexible filopodial protrusions. Detailed in silico tests using various geometries confirm that our technique accurately tracks growth dynamics and relative protein concentration along the filopodial length for a broad range of signal distributions. To validate our technique in living cells, we measure filopodial dynamics and quantify spatiotemporal localization of filopodia-associated proteins during the filopodial extension–retraction cycle in a variety of cell types in vitro and in vivo. Together these results show that the technique is suitable for simultaneous analysis of growth dynamics and spatiotemporal protein enrichment along filopodia. To allow readily application by other laboratories, we share source code and instructions for software handling.

scholarly journals Cell type resolved co-expression networks of core clock genes in brain development

2021 ◽  
Author(s):  
Surbhi Sharma ◽  
Asgar Hussain Ansari ◽  
Soundhar Ramasamy
Keyword(s):  
Circadian Clock ◽  
Single Cell ◽  
Radial Glia ◽  
Clock Genes ◽  
Neuronal Cell ◽  
Cell Types ◽  
Developing Brain ◽  
Knock Out

AbstractThe circadian clock regulates vital cellular processes by adjusting the physiology of the organism to daily changes in the environment. Rhythmic transcription of core Clock Genes (CGs) and their targets regulate these processes at the cellular level. Circadian clock disruption has been observed in people with neurodegenerative disorders like Alzheimer’s and Parkinson’s. Also, ablation of CGs during development has been shown to affect neurogenesis in both in vivo and in vitro models. Previous studies on the function of CGs in the brain have used knock-out models of a few CGs. However, a complete catalog of CGs in different cell types of the developing brain is not available and it is also tedious to obtain. Recent advancements in single-cell RNA sequencing (scRNA-seq) has revealed novel cell types and elusive dynamic cell states of the developing brain. In this study by using publicly available single-cell transcriptome datasets we systematically explored CGs-coexpressing networks (CGs-CNs) during embryonic and adult neurogenesis. Our meta-analysis reveals CGs-CNs in human embryonic radial glia, neurons and also in lesser studied non-neuronal cell types of the developing brain.

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