Leveraging AI to work with cells
Nanofountain Probe Electroporation system enables efficient engineering
of stem cells
Date:
March 22, 2022
Source:
Northwestern University
Summary:
New research is moving medical science closer to personalized
care by using artificial intelligence to more efficiently engineer
stem cells.
FULL STORY ==========================================================================
One of the ultimate goals of medical science is to develop personalized
disease diagnostics and therapeutics. With a patient's genetic
information, doctors could tailor treatments to individuals, leading to
safer and more effective care.
========================================================================== Recent work from a team of Northwestern Engineering researchers has
moved the field closer to realizing this future.
Led by Professor Horacio Espinosa, the research team developed a new
version of its Nanofountain Probe Electroporation (NFP-E), a tool used
to deliver molecules into single-cells using electricity. The enhanced
method leverages artificial intelligence (AI) to execute cell engineering
tasks such as cell nuclei localization and probe detection. Other
processes such as probe motion, probe-to-cell contact detection, and electroporation-mediated delivery of foreign cargo into single cells
are also automated, minimizing user intervention.
"NFP-E can handle small starting samples without any significant cell
loss in the entire protocol," said Espinosa, James N. and Nancy J. Farley Professor in Manufacturing and Entrepreneurship at the McCormick School of Engineering and the study's corresponding author. "This is an advantage
over other cell engineering methods such as bulk electroporation, which
require millions of cells and lead to significant cell losses. The
automated NFP-E, combined with its ability to selectively target and
manipulate single cells in micro-arrays, can be useful in fundamental
research, such as deciphering intracellular dynamics and cell-to-cell communication studies as well as biological applications such as cell
line generation." Espinosa and graduate students Prithvijit Mukherjee,
Cesar A. Patino, and Nibir Pathak reported their work in the paper
"Deep Learning Assisted Automated Single Cell Electroporation Platform
for Effective Genetic Manipulation of Hard-to-Transfect Cells" published
March 21 in Small.
"Genetic manipulation of human induced pluripotent stem cells (hiPSCs)
by introducing exogenous cargo has a wide range of applications in
disease diagnostics, therapeutic discovery, and regenerative medicine,"
said Mukherjee, a PhD student in the Espinosa group who is joining the microfluidics group at Illumina.
========================================================================== Probe-based, microfluidic methods, like NFP-E, use hollow nanopipettes
or atomic-force microscopy tips to deliver materials into cells. NFP-E
also allows researchers to selectively manipulate cells of interest,
work with very small starting samples, and deliver both proteins and
plasmids in a variety of animal and human cell types with dosage control.
"The challenge with probe methods, however, is that they require manual operation and produce low throughputs, making them unsuitable for common
cell engineering workflows," said Patino, a PhD student in the Espinosa
group.
"Selective cell manipulation at sufficient throughput is challenging,"
Espinosa said. "Most methods either provide high throughput at the
expense of individual cell control or sacrifice throughput for single
cell selectivity and control." This new work changes that.
The research team's automated NFP-E enables selective cell engineering at higher-throughputs than manual probe-based methods while also reducing experimental variability and enabling more efficient engineering of
hiPSCs.
Using the automated platform NFP-E, Espinosa and his colleagues delivered clustered regularly interspaced short palindromic repeats (CRISPR) RNP to hiPSCs for efficient knockout of genes in a variety of culture formats:
culture plates, micro-patterns, and micro-wells arrays. The automated engineering of cells in micro-arrays using the NFP-E has potential
applications such as isogenic cell line generation from single cells
and studying dynamic cellular processes such as intracellular signaling cascades and cell-cell communication.
Espinosa and his team will next work to automate NFP-E's entire workflow,
which includes steps such as automated cell imaging, cell tracking,
switching probes, and media exchange for cell culture.
"The idea is to establish a fully automated cell line generation workflow
using the combination of the NFP-E and the micro-well arrays," Espinosa
said. "The AI can be further trained to recognize and target specific
cell types in multi- cell co-cultures. This can be useful in understanding dynamics such as disease progression or cell communication." The research
was supported by two NIH grants, awards number 1R43GM128500-01 and 1R21GM132709-01.
========================================================================== Story Source: Materials provided by Northwestern_University. Original
written by Brian Sandalow. Note: Content may be edited for style and
length.
========================================================================== Journal Reference:
1. Prithvijit Mukherjee, Cesar A. Patino, Nibir Pathak, Vincent
Lemaitre,
Horacio D. Espinosa. Deep Learning‐Assisted Automated Single
Cell Electroporation Platform for Effective Genetic Manipulation
of Hard‐to‐Transfect Cells. Small, 2022; 2107795 DOI:
10.1002/ smll.202107795 ==========================================================================
Link to news story:
https://www.sciencedaily.com/releases/2022/03/220322122535.htm
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