High-throughput physical phenotyping of cell differentiation
| Autor: | Jonathan Lin, Manjima Dhar, Lillian Peng, Saravanan Karumbayaram, Peter Tseng, Donghyuk Kim, Henry T. Tse, Dino Di Carlo |
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| Rok vydání: | 2017 |
| Předmět: |
0301 basic medicine
Computer science Materials Science (miscellaneous) Cellular differentiation Computational biology Industrial and Manufacturing Engineering 03 medical and health sciences cell mechanics stem cells deformation kinetics morphology Electrical and Electronic Engineering Stem Cell Research - Embryonic - Human Induced pluripotent stem cell Throughput (business) physical phenotype Mesenchymal stem cell deformation Condensed Matter Physics Stem Cell Research Phenotype Atomic and Molecular Physics and Optics Neural stem cell 030104 developmental biology Stem cell Cytometry |
| Zdroj: | Microsystems & nanoengineering, vol 3, iss 1 |
| Popis: | In this report, we present multiparameter deformability cytometry (m-DC), in which we explore a large set of parameters describing the physical phenotypes of pluripotent cells and their derivatives. m-DC utilizes microfluidic inertial focusing and hydrodynamic stretching of single cells in conjunction with high-speed video recording to realize high-throughput characterization of over 20 different cell motion and morphology-derived parameters. Parameters extracted from videos include size, deformability, deformation kinetics, and morphology. We train support vector machines that provide evidence that these additional physical measurements improve classification of induced pluripotent stem cells, mesenchymal stem cells, neural stem cells, and their derivatives compared to size and deformability alone. In addition, we utilize visual interactive stochastic neighbor embedding to visually map the high-dimensional physical phenotypic spaces occupied by these stem cells and their progeny and the pathways traversed during differentiation. This report demonstrates the potential of m-DC for improving understanding of physical differences that arise as cells differentiate and identifying cell subpopulations in a label-free manner. Ultimately, such approaches could broaden our understanding of subtle changes in cell phenotypes and their roles in human biology. |
| Databáze: | OpenAIRE |
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