Structural Phenotyping of Stem Cell-Derived Cardiomyocytes
Structural phenotyping based on classical image feature detection has been adopted to elucidate the molecular mechanisms behind genetically or pharmacologically induced changes in cell morphology. Here, we developed a set of 11 metrics to capture the increasing sarcomere organization that occurs int...
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| Published in | Stem cell reports Vol. 4; no. 3; pp. 340 - 347 |
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| Main Authors | , , , , |
| Format | Journal Article |
| Language | English |
| Published |
United States
Elsevier Inc
10.03.2015
Elsevier |
| Subjects | |
| Online Access | Get full text |
| ISSN | 2213-6711 2213-6711 |
| DOI | 10.1016/j.stemcr.2015.01.020 |
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| Abstract | Structural phenotyping based on classical image feature detection has been adopted to elucidate the molecular mechanisms behind genetically or pharmacologically induced changes in cell morphology. Here, we developed a set of 11 metrics to capture the increasing sarcomere organization that occurs intracellularly during striated muscle cell development. To test our metrics, we analyzed the localization of the contractile protein α-actinin in a variety of primary and stem-cell derived cardiomyocytes. Further, we combined these metrics with data mining algorithms to unbiasedly score the phenotypic maturity of human-induced pluripotent stem cell-derived cardiomyocytes.
•Image processing metrics for characterizing the contractile cytoskeleton•Unbiased data mining strategies to assess cardiomyocyte maturation•Structural phenotyping of stem cell-derived cardiomyocytes
In this article, Parker and colleagues develop metrics to quantitatively characterize myofibrillogenesis and sarcomerogenesis, the processes by which striated muscle cells assemble their contractile cytoskeleton. Further, they coupled these metrics with machine-learning algorithms to unbiasedly score the phenotypic maturity of primary and stem cell-derived cardiomyocytes. |
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| AbstractList | Structural phenotyping based on classical image feature detection has been adopted to elucidate the molecular mechanisms behind genetically or pharmacologically induced changes in cell morphology. Here, we developed a set of 11 metrics to capture the increasing sarcomere organization that occurs intracellularly during striated muscle cell development. To test our metrics, we analyzed the localization of the contractile protein α-actinin in a variety of primary and stem-cell derived cardiomyocytes. Further, we combined these metrics with data mining algorithms to unbiasedly score the phenotypic maturity of human-induced pluripotent stem cell-derived cardiomyocytes.
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Image processing metrics for characterizing the contractile cytoskeleton
•
Unbiased data mining strategies to assess cardiomyocyte maturation
•
Structural phenotyping of stem cell-derived cardiomyocytes
In this article, Parker and colleagues develop metrics to quantitatively characterize myofibrillogenesis and sarcomerogenesis, the processes by which striated muscle cells assemble their contractile cytoskeleton. Further, they coupled these metrics with machine-learning algorithms to unbiasedly score the phenotypic maturity of primary and stem cell-derived cardiomyocytes. Structural phenotyping based on classical image feature detection has been adopted to elucidate the molecular mechanisms behind genetically or pharmacologically induced changes in cell morphology. Here, we developed a set of 11 metrics to capture the increasing sarcomere organization that occurs intracellularly during striated muscle cell development. To test our metrics, we analyzed the localization of the contractile protein α-actinin in a variety of primary and stem-cell derived cardiomyocytes. Further, we combined these metrics with data mining algorithms to unbiasedly score the phenotypic maturity of human-induced pluripotent stem cell-derived cardiomyocytes. •Image processing metrics for characterizing the contractile cytoskeleton•Unbiased data mining strategies to assess cardiomyocyte maturation•Structural phenotyping of stem cell-derived cardiomyocytes In this article, Parker and colleagues develop metrics to quantitatively characterize myofibrillogenesis and sarcomerogenesis, the processes by which striated muscle cells assemble their contractile cytoskeleton. Further, they coupled these metrics with machine-learning algorithms to unbiasedly score the phenotypic maturity of primary and stem cell-derived cardiomyocytes. Structural phenotyping based on classical image feature detection has been adopted to elucidate the molecular mechanisms behind genetically or pharmacologically induced changes in cell morphology. Here, we developed a set of 11 metrics to capture the increasing sarcomere organization that occurs intracellularly during striated muscle cell development. To test our metrics, we analyzed the localization of the contractile protein α-actinin in a variety of primary and stem-cell derived cardiomyocytes. Further, we combined these metrics with data mining algorithms to unbiasedly score the phenotypic maturity of human-induced pluripotent stem cell-derived cardiomyocytes.Structural phenotyping based on classical image feature detection has been adopted to elucidate the molecular mechanisms behind genetically or pharmacologically induced changes in cell morphology. Here, we developed a set of 11 metrics to capture the increasing sarcomere organization that occurs intracellularly during striated muscle cell development. To test our metrics, we analyzed the localization of the contractile protein α-actinin in a variety of primary and stem-cell derived cardiomyocytes. Further, we combined these metrics with data mining algorithms to unbiasedly score the phenotypic maturity of human-induced pluripotent stem cell-derived cardiomyocytes. Structural phenotyping based on classical image feature detection has been adopted to elucidate the molecular mechanisms behind genetically or pharmacologically induced changes in cell morphology. Here, we developed a set of 11 metrics to capture the increasing sarcomere organization that occurs intracellularly during striated muscle cell development. To test our metrics, we analyzed the localization of the contractile protein α-actinin in a variety of primary and stem-cell derived cardiomyocytes. Further, we combined these metrics with data mining algorithms to unbiasedly score the phenotypic maturity of human-induced pluripotent stem cell-derived cardiomyocytes. |
| Author | Parker, Kevin Kit Pasqualini, Francesco Silvio Sheehy, Sean Paul Aratyn-Schaus, Yvonne Agarwal, Ashutosh |
| AuthorAffiliation | 1 Disease Biophysics Group, Wyss Institute for Biologically Inspired Engineering, School of Engineering and Applied Sciences, Harvard Stem Cell Institute, Harvard University, Cambridge, MA 02138, USA |
| AuthorAffiliation_xml | – name: 1 Disease Biophysics Group, Wyss Institute for Biologically Inspired Engineering, School of Engineering and Applied Sciences, Harvard Stem Cell Institute, Harvard University, Cambridge, MA 02138, USA |
| Author_xml | – sequence: 1 givenname: Francesco Silvio surname: Pasqualini fullname: Pasqualini, Francesco Silvio organization: Disease Biophysics Group, Wyss Institute for Biologically Inspired Engineering, School of Engineering and Applied Sciences, Harvard Stem Cell Institute, Harvard University, Cambridge, MA 02138, USA – sequence: 2 givenname: Sean Paul surname: Sheehy fullname: Sheehy, Sean Paul organization: Disease Biophysics Group, Wyss Institute for Biologically Inspired Engineering, School of Engineering and Applied Sciences, Harvard Stem Cell Institute, Harvard University, Cambridge, MA 02138, USA – sequence: 3 givenname: Ashutosh surname: Agarwal fullname: Agarwal, Ashutosh organization: Disease Biophysics Group, Wyss Institute for Biologically Inspired Engineering, School of Engineering and Applied Sciences, Harvard Stem Cell Institute, Harvard University, Cambridge, MA 02138, USA – sequence: 4 givenname: Yvonne surname: Aratyn-Schaus fullname: Aratyn-Schaus, Yvonne organization: Disease Biophysics Group, Wyss Institute for Biologically Inspired Engineering, School of Engineering and Applied Sciences, Harvard Stem Cell Institute, Harvard University, Cambridge, MA 02138, USA – sequence: 5 givenname: Kevin Kit surname: Parker fullname: Parker, Kevin Kit email: kkparker@seas.harvard.edu organization: Disease Biophysics Group, Wyss Institute for Biologically Inspired Engineering, School of Engineering and Applied Sciences, Harvard Stem Cell Institute, Harvard University, Cambridge, MA 02138, USA |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/25733020$$D View this record in MEDLINE/PubMed |
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| SubjectTerms | Algorithms Animals Biometry - methods Cell Differentiation Cytoskeleton - metabolism Humans Machine Learning Mice Myocytes, Cardiac - cytology Myocytes, Cardiac - metabolism Phenotype Rats Stem Cells - cytology |
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| Title | Structural Phenotyping of Stem Cell-Derived Cardiomyocytes |
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