scholarly journals Population-scale single-cell RNA-seq profiling across dopaminergic neuron differentiation

2020 ◽  
Author(s):  
J Jerber ◽  
DD Seaton ◽  
ASE Cuomo ◽  
N Kumasaka ◽  
J Haldane ◽  
...  
Keyword(s):  
Single Cell ◽  
Cell Fate ◽  
Genetic Variants ◽  
Neuronal Development ◽  
Induced Pluripotent Stem Cell ◽  
Great Promise ◽  
Tissue Samples ◽  
Ips Cell ◽  
Common Genetic Variants ◽  
Induced Pluripotent

AbstractCommon genetic variants can have profound effects on cellular function, but studying these effects in primary human tissue samples and during development is challenging. Human induced pluripotent stem cell (iPSC) technology holds great promise for assessing these effects across different differentiation contexts. Here, we use an efficient pooling strategy to differentiate 215 iPS cell lines towards a midbrain neural fate, including dopaminergic neurons, and profile over 1 million cells sampled across three differentiation timepoints using single cell RNA sequencing. We find that the proportion of neuronal cells produced by each cell line is highly reproducible over different experimental batches, and identify robust molecular markers in pluripotent cells that predict line-to-line differences in cell fate. We identify expression quantitative trait loci (eQTL) that manifest at different stages of neuronal development, and in response to oxidative stress, by exposing cells to rotenone. We find over one thousand eQTL that colocalise with a known risk locus for a neurological trait, nearly half of which are not found in GTEx. Our study illustrates how coupling single cell transcriptomics with long-term iPSC differentiation can profile mechanistic effects of human trait-associated genetic variants in otherwise inaccessible cell states.

scholarly journals Single-cell RNA-sequencing of differentiating iPS cells reveals dynamic genetic effects on gene expression

2019 ◽  
Author(s):  
Anna SE Cuomo ◽  
Daniel D Seaton ◽  
Davis J McCarthy ◽  
Iker Martinez ◽  
Marc Jan Bonder ◽  
...  
Keyword(s):  
Single Cell ◽  
Rna Sequencing ◽  
Cell Fate ◽  
Cell Biology ◽  
Population Variation ◽  
Ips Cell ◽  
Cell Fate Decisions ◽  
Common Genetic Variants ◽  
Single Cell Rna Sequencing

AbstractRecent developments in stem cell biology have enabled the study of cell fate decisions in early human development that are impossible to study in vivo. However, understanding how development varies across individuals and, in particular, the influence of common genetic variants during this process has not been characterised. Here, we exploit human iPS cell lines from 125 donors, a pooled experimental design, and single-cell RNA-sequencing to study population variation of endoderm differentiation. We identify molecular markers that are predictive of differentiation efficiency, and utilise heterogeneity in the genetic background across individuals to map hundreds of expression quantitative trait loci that influence expression dynamically during differentiation and across cellular contexts.

scholarly journals Mind the translational gap: using iPS cell models to bridge from genetic discoveries to perturbed pathways and therapeutic targets

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Greta Pintacuda ◽  
Jacqueline M. Martín ◽  
Kevin C. Eggan
Keyword(s):  
Social Interactions ◽  
Genetic Variants ◽  
Induced Pluripotent Stem Cell ◽  
Cell Types ◽  
Autism Spectrum ◽  
Repetitive Behaviors ◽  
Genetic Studies ◽  
Ips Cell ◽  
Rare Genetic Variants ◽  
Induced Pluripotent

AbstractAutism spectrum disorder (ASD) comprises a group of neurodevelopmental disorders characterized by impaired social interactions as well as the presentation of restrictive and repetitive behaviors. ASD is highly heritable but genetically heterogenous with both common and rare genetic variants collaborating to predispose individuals to the disorder. In this review, we synthesize recent efforts to develop human induced pluripotent stem cell (iPSC)-derived models of ASD-related phenotypes. We firstly address concerns regarding the relevance and validity of available neuronal iPSC-derived models. We then critically evaluate the robustness of various differentiation and cell culture protocols used for producing cell types of relevance to ASD. By exploring iPSC models of ASD reported thus far, we examine to what extent cellular and neuronal phenotypes with potential relevance to ASD can be linked to genetic variants found to underlie it. Lastly, we outline promising strategies by which iPSC technology can both enhance the power of genetic studies to identify ASD risk factors and nominate pathways that are disrupted across groups of ASD patients that might serve as common points for therapeutic intervention.

scholarly journals NRF2 is required for structural and metabolic maturation of human induced pluripotent stem cell-derived ardiomyocytes

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Xinyuan Zhang ◽  
Liang Ye ◽  
Hao Xu ◽  
Qin Zhou ◽  
Bin Tan ◽  
...  
Keyword(s):  
Stem Cell ◽  
Oxidative Phosphorylation ◽  
Pluripotent Stem Cell ◽  
Disease Modeling ◽  
Induced Pluripotent Stem Cell ◽  
Metabolic Energy ◽  
Cell Maturation ◽  
Great Promise ◽  
Functional Changes ◽  
Induced Pluripotent

Abstract Background Human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) hold great promise for regenerative medicine and in drugs screening. Despite displaying key cardiomyocyte phenotypic characteristics, they more closely resemble fetal/neonatal cardiomyocytes and are still immature; these cells mainly rely on glucose as a substrate for metabolic energy, while mature cardiomyocytes mainly employ oxidative phosphorylation of fatty acids. Studies showed that the alteration of metabolism pattern from glycolysis to oxidative phosphorylation improve the maturity of hiPSC-CMs. As a transcription factor, accumulating evidences showed the important role of NRF2 in the regulation of energy metabolism, which directly regulates the expression of mitochondrial respiratory complexes. Therefore, we hypothesized that NRF2 is involved in the maturation of hiPSC-CMs. Methods The morphological and functional changes related to mitochondria and cell maturation were analyzed by knock-down and activation of NRF2. Results The results showed that the inhibition of NRF2 led to the retardation of cell maturation. The activation of NRF2 leads to a more mature hiPSC-CMs phenotype, as indicated by the increase of cardiac maturation markers, sarcomere length, calcium transient dynamics, the number and fusion events of mitochondria, and mitochondrial respiration. Bioinformatics analysis showed that in addition to metabolism-related genes, NRF2 also activates the expression of myocardial ion channels. Conclusions These findings indicated that NRF2 plays an important role in the maturation of hiPSC-CMs. The present work provides greater insights into the molecular regulation of hiPSC-CMs metabolism and theoretical basis in drug screening, disease modeling, and alternative treatment.

scholarly journals iPS-Cell Technology and the Problem of Genetic Instability—Can It Ever Be Safe for Clinical Use?

2019 ◽  
Vol 8 (3) ◽  
pp. 288 ◽  
Author(s):  
Stephen Attwood ◽  
Michael Edel
Keyword(s):  
Stem Cells ◽  
Pluripotent Stem Cells ◽  
Embryonic Stem ◽  
Great Promise ◽  
Clinical Use ◽  
Medicinal Products ◽  
Ips Cell ◽  
Factors Affecting ◽  
Induced Pluripotent ◽  
Stem Cell Therapeutics

The use of induced Pluripotent Stem Cells (iPSC) as a source of autologous tissues shows great promise in regenerative medicine. Nevertheless, several major challenges remain to be addressed before iPSC-derived cells can be used in therapy, and experience of their clinical use is extremely limited. In this review, the factors affecting the safe translation of iPSC to the clinic are considered, together with an account of efforts being made to overcome these issues. The review draws upon experiences with pluripotent stem-cell therapeutics, including clinical trials involving human embryonic stem cells and the widely transplanted mesenchymal stem cells. The discussion covers concerns relating to: (i) the reprogramming process; (ii) the detection and removal of incompletely differentiated and pluripotent cells from the resulting medicinal products; and (iii) genomic and epigenetic changes, and the evolutionary and selective processes occurring during culture expansion, associated with production of iPSC-therapeutics. In addition, (iv) methods for the practical culture-at-scale and standardization required for routine clinical use are considered. Finally, (v) the potential of iPSC in the treatment of human disease is evaluated in the light of what is known about the reprogramming process, the behavior of cells in culture, and the performance of iPSC in pre-clinical studies.

scholarly journals Machine Learning Approach to Automated Quality Identification of Human Induced Pluripotent Stem Cell Colony Images

2016 ◽  
Vol 2016 ◽  
pp. 1-15 ◽  
Author(s):  
Henry Joutsijoki ◽  
Markus Haponen ◽  
Jyrki Rasku ◽  
Katriina Aalto-Setälä ◽  
Martti Juhola
Keyword(s):  
Machine Learning ◽  
Stem Cell ◽  
Pluripotent Stem Cell ◽  
Disease Modeling ◽  
Induced Pluripotent Stem Cell ◽  
Patient Specific ◽  
Support Vector ◽  
Ips Cell ◽  
Cell Technology ◽  
Induced Pluripotent

The focus of this research is on automated identification of the quality of human induced pluripotent stem cell (iPSC) colony images. iPS cell technology is a contemporary method by which the patient’s cells are reprogrammed back to stem cells and are differentiated to any cell type wanted. iPS cell technology will be used in future to patient specific drug screening, disease modeling, and tissue repairing, for instance. However, there are technical challenges before iPS cell technology can be used in practice and one of them is quality control of growing iPSC colonies which is currently done manually but is unfeasible solution in large-scale cultures. The monitoring problem returns to image analysis and classification problem. In this paper, we tackle this problem using machine learning methods such as multiclass Support Vector Machines and several baseline methods together with Scaled Invariant Feature Transformation based features. We perform over 80 test arrangements and do a thorough parameter value search. The best accuracy (62.4%) for classification was obtained by using ak-NN classifier showing improved accuracy compared to earlier studies.

Generation of 2.5D lung bud organoid from human induced pluripotent stem cell

2021 ◽  
pp. 1-14
Author(s):  
Xun Xu ◽  
Yan Nie ◽  
Weiwei Wang ◽  
Imran Ullah ◽  
Wing Tai Tung ◽  
...  
Keyword(s):  
Single Cell ◽  
Disease Modeling ◽  
3D Culture ◽  
Induced Pluripotent Stem Cell ◽  
Patient Specific ◽  
Homogeneous Distribution ◽  
Cell Seeding ◽  
Differentiation Potential ◽  
Induced Pluripotent ◽  
Defined Culture

Human induced pluripotent stem cells (hiPSCs) are a promising cell source to generate the patient-specific lung organoid given their superior differentiation potential. However, the current 3D cell culture approach is tedious and time-consuming with a low success rate and high batch-to-batch variability. Here, we explored the establishment of lung bud organoids by systematically adjusting the initial confluence levels and homogeneity of cell distribution. The efficiency of single cell seeding and clump seeding was compared. Instead of the traditional 3D culture, we established a 2.5D organoid culture to enable the direct monitoring of the internal structure via microscopy. It was found that the cell confluence and distribution prior to induction were two key parameters, which strongly affected hiPSC differentiation trajectories. Lung bud organoids with positive expression of NKX 2.1, in a single-cell seeding group with homogeneously distributed hiPSCs at 70%confluence (SC_70%_hom) or a clump seeding group with heterogeneously distributed cells at 90%confluence (CL_90%_het), can be observed as early as 9 days post induction. These results suggest that a successful lung bud organoid formation with single-cell seeding of hiPSCs requires a moderate confluence and homogeneous distribution of cells, while high confluence would be a prominent factor to promote the lung organoid formation when seeding hiPSCs as clumps. 2.5D organoids generated with defined culture conditions could become a simple, efficient, and valuable tool facilitating drug screening, disease modeling and personalized medicine.

scholarly journals Human Induced Pluripotent Stem Cell-Derived Microvesicles Transmit RNAs and Proteins to Recipient Mature Heart Cells Modulating Cell Fate and Behavior

Stem Cells ◽  
2015 ◽  
Vol 33 (9) ◽  
pp. 2748-2761 ◽  
Author(s):  
Sylwia Bobis-Wozowicz ◽  
Katarzyna Kmiotek ◽  
Malgorzata Sekula ◽  
Sylwia Kedracka-Krok ◽  
Elzbieta Kamycka ◽  
...  
Keyword(s):  
Stem Cell ◽  
Cell Fate ◽  
Pluripotent Stem Cell ◽  
Induced Pluripotent Stem Cell ◽  
Heart Cells ◽  
Induced Pluripotent ◽  
And Behavior ◽  
Fate And Behavior

scholarly journals Batch effects and the effective design of single-cell gene expression studies

2016 ◽  
Author(s):  
Po-Yuan Tung ◽  
John D. Blischak ◽  
Chiaowen Joyce Hsiao ◽  
David A. Knowles ◽  
Jonathan E. Burnett ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Induced Pluripotent Stem Cell ◽  
Expression Levels ◽  
Amplification Bias ◽  
Expression Studies ◽  
Cell Gene Expression ◽  
Gene Expression Studies ◽  
Induced Pluripotent ◽  
Gene Expression Levels

AbstractSingle cell RNA sequencing (scRNA-seq) can be used to characterize variation in gene expression levels at high resolution. However, the sources of experimental noise in scRNA-seq are not yet well understood. We investigated the technical variation associated with sample processing using the single cell Fluidigm C1 platform. To do so, we processed three C1 replicates from three human induced pluripotent stem cell (iPSC) lines. We added unique molecular identifiers (UMIs) to all samples, to account for amplification bias. We found that the major source of variation in the gene expression data was driven by genotype, but we also observed substantial variation between the technical replicates. We observed that the conversion of reads to molecules using the UMIs was impacted by both biological and technical variation, indicating that UMI counts are not an unbiased estimator of gene expression levels. Based on our results, we suggest a framework for effective scRNA-seq studies.

scholarly journals Using High-Content Screening Technology as a Tool to Generate Single-Cell Patient-Derived Gene-Corrected Isogenic iPS Clones for Parkinson’s Disease Research

2020 ◽  
Author(s):  
Peter A. Barbuti ◽  
Paul M. Antony ◽  
Bruno F.R. Santos ◽  
François Massart ◽  
Gérald Cruciani ◽  
...  
Keyword(s):  
Single Cell ◽  
Clonal Selection ◽  
Induced Pluripotent Stem Cell ◽  
Alpha Synuclein ◽  
Screening Strategy ◽  
High Content Screening ◽  
Selection Strategy ◽  
Microtiter Plates ◽  
Automated Platform ◽  
Induced Pluripotent

The generation of isogenic induced pluripotent stem cell (iPSC) lines using CRISPR-Cas9 technology is a technically challenging, time-consuming process with variable efficiency. Here we use fluorescence-activated cell sorting (FACS) to sort biallelic CRISPR-Cas9 edited single-cell iPS clones into high-throughput 96-well microtiter plates. We used high-content screening (HCS) technology and generated an in-house developed algorithm to select the correctly edited isogenic clones for continued expansion and validation. In our model we have gene-corrected the iPSCs of a Parkinson’s disease (PD) patient carrying the autosomal dominantly inherited heterozygous c.88G>C mutation in the SNCA gene, which leads to the pathogenic p.A30P form of the alpha-synuclein protein. Undertaking a PCR restriction-digest mediated clonal selection strategy prior to sequencing, we were able to post-sort validate each isogenic clone using a quadruple screening strategy. Subsequent transfection with mRNA encoding excision-only transposase allows for the generation of footprint-free isogenic iPSC lines. These monoclonal isogenic iPSC lines retain a normal molecular genotype, express pluripotency markers and have the ability to differentiate into the three germ layers. This combinatory approach of FACS, HCS and post-sorted restriction digestion facilitates the generation of isogenic cell lines for disease modelling to be scaled-up on an automated platform.

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