Deep Learning‐Assisted Automated Single Cell Electroporation Platform for Effective Genetic Manipulation of Hard‐to‐Transfect Cells

Genome engineering of cells using CRISPR/Cas systems has opened new avenues for pharmacological screening and investigating the molecular mechanisms of disease. A critical step in many such studies is the intracellular delivery of the gene editing machinery and the subsequent manipulation of cells....

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Bibliographic Details
Published in:Small (Weinheim an der Bergstrasse, Germany) Vol. 18; no. 20; pp. e2107795 - n/a
Main Authors: Mukherjee, Prithvijit, Patino, Cesar A., Pathak, Nibir, Lemaitre, Vincent, Espinosa, Horacio D.
Format: Journal Article
Language:English
Published: Germany Wiley Subscription Services, Inc 01.05.2022
Wiley Blackwell (John Wiley & Sons)
Subjects:
Algorithms
Automation
CRISPR
CRISPR-Cas Systems - genetics
CRISPR/Cas9
Deep Learning
Electroporation
Electroporation - methods
Gene Editing - methods
Genetic modification
Humans
human‐induced pluripotent stem cells (hiPSCs)
Induced Pluripotent Stem Cells - metabolism
intracellular delivery
Machine learning
Nanotechnology
Screening
single‐cell electroporation
Stem cells
Workflow
single-cell electroporation
deep learning
human-induced pluripotent stem cells (hiPSCs)
CRISPR/Cas9
intracellular delivery
ISSN:1613-6810, 1613-6829, 1613-6829
Online Access:Get full text
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Summary:Genome engineering of cells using CRISPR/Cas systems has opened new avenues for pharmacological screening and investigating the molecular mechanisms of disease. A critical step in many such studies is the intracellular delivery of the gene editing machinery and the subsequent manipulation of cells. However, these workflows often involve processes such as bulk electroporation for intracellular delivery and fluorescence activated cell sorting for cell isolation that can be harsh to sensitive cell types such as human‐induced pluripotent stem cells (hiPSCs). This often leads to poor viability and low overall efficacy, requiring the use of large starting samples. In this work, a fully automated version of the nanofountain probe electroporation (NFP‐E) system, a nanopipette‐based single‐cell electroporation method is presented that provides superior cell viability and efficiency compared to traditional methods. The automated system utilizes a deep convolutional network to identify cell locations and a cell‐nanopipette contact algorithm to position the nanopipette over each cell for the application of electroporation pulses. The automated NFP‐E is combined with microconfinement arrays for cell isolation to demonstrate a workflow that can be used for CRISPR/Cas9 gene editing and cell tracking with potential applications in screening studies and isogenic cell line generation. In this article, the authors present a deep learning‐assisted nanofountain probe electroporation system in combination with microconfinement arrays to trap and transfect single cells. Using the combined platform, the authors demonstrate automated intracellular delivery and genetic perturbation in hard‐to‐transfect cells followed by temporal tracking of the perturbed cell colonies.
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equal contribution
H.D.E. conceived the project. P.M. and C.A.P. contributed equally. P.M. and C.A.P. wrote the automation software. C.A.P. and P.M. developed the image segmentation routines. C.A.P. and P.M. fabricated the micro-well and micro-pattern arrays. P.M., N.P. and V.L. performed the biological experiments. All authors analyzed and interpreted the data. H.D.E., P.M. and C.A.P wrote the manuscript.
Author Contributions
ISSN:1613-6810
1613-6829
1613-6829
DOI:10.1002/smll.202107795