CRISPR: Strategy refines genetic base editors
Approach improves avoidance of `bystander' edits in CRISPR-base editor treatments
Date:
November 11, 2021
Source:
Rice University
Summary:
A new strategy seeks to avoid gene-editing errors by fine-tuning
specific CRISPR-base editing parameters in advance.
FULL STORY ==========================================================================
Want to keep the riffraff out of the gene pool party? Sneak in and slam
the gate before they arrive.
========================================================================== That's the central idea of a new strategy by Rice University scientists
who seek to avoid gene-editing errors by fine-tuning specific CRISPR-base editing strategies in advance.
Rice chemical and biomolecular engineer Xue Sherry Gao and chemist
Anatoly Kolomeisky and their labs combined theory and experimentation
for a comprehensive approach to building better base editors, molecular machines that target and fix faulty DNA at single-base resolution.
Their work appears in Nature Communications.
The paper describes the molecular processes that base editors use to
manipulate strands of DNA, cutting them where necessary and making way
for replacement code. When it works, as it increasingly does to treat
genetic diseases like sickle cell anemia and some cancers, the editor
only edits the intended nucleotide.
And when it doesn't, that's because bystander edits can cause undesired effects.
==========================================================================
The Rice strategy primarily seeks to eliminate wayward edits to
bystanders, nucleotides adjacent to the base editor's target. Gao's
lab previously introduced tools to improve the accuracy of CRISPR-based
edits of cytosine mutations up to 6,000-fold.
For the new project, she engaged the Kolomeisky lab to help create a theoretical framework to eliminate trial and error in the design of
a library of editors. These would better target mutations that cause
disease while avoiding bystanders. In the process, the framework could
help scientists better understand the chemical and physical processes
that take place during base editing.
"Sherry and other experimental scientists already had results that
worked," Kolomeisky said, referring to the earlier paper, in which the
lab used its editor to convert cytosines to thymines, correcting the DNA mutations while avoiding otherwise vulnerable cytosines upstream. "But
despite these amazing developments, there's been no microscopic
understanding of what we have to do with these protein systems to
improve editing." He said Qian Wang, a former postdoctoral researcher
in Kolomeisky's lab and now an assistant professor at the University of
Science and Technology of China (USTC), Hefei, took on the challenge,
using Gao's cytosine experiment as a baseline.
"We applied the model for that result and got some important parameters
we then used to design what mutations and where are needed to get precise editing," Kolomeisky said. "Ultimately, this symbiosis of theory and
experiment allows us to work in a smart way." Their strategy combines molecular dynamics simulations and stochastic (aka random) models that
pinpoint the binding energies between molecules required to achieve
maximum editing selectivity. Experiments in Gao's lab validated the
results.
========================================================================== Critically, the framework includes a way to characterize the binding
affinity between deaminases -- enzymes that catalyze the removal of an
amino group from a molecule -- and single-stranded DNA (ssDNA).
Ideally, they said, the deaminase stays on the ssDNA just long enough
to complete the primary edit, and releases before inadvertently editing
a bystander site.
"The important thing here is that one mutation doesn't work for
different systems," Kolomeisky said. "So, for every system, you have to
do this procedure again, but at least it's clear what should be done."
"The model has been very successful in reflecting what has already been
done experimentally," Gao said. "But since then, we've been able to turn
down bystander effects in other base-editing systems.
"Because the number of mutants could be in the thousands, it's unrealistic
for experimentalists alone to verify individual base editors," she
said. "Only this multidisciplinary approach will allow us to build a huge library of editors computationally, then narrow the numbers down to the
most promising candidates for further experimental verifications. That's
what we're working toward." Rice postdoctoral researcher Jie Yang is
co-lead author of the paper with Wang.
Rice undergraduate Jeffrey Vanegas and Zhicheng Zhong, a theoretical
physicist at USTC, are co-authors of the paper. Gao is the Ted N. Law
Assistant Professor of Chemical and Biomolecular Engineering. Kolomeisky
is a professor and chair of the Department of Chemistry and a professor
of chemical and biomolecular engineering.
The USTC Research Funds of the Double First-Class Initiative
(YD2030002006), the National Natural Science Foundation of China
(32000882), the National Science Foundation (NSF) (1953453, 1941106),
the NSF-funded Center for Theoretical Biological Physics (2019745), the
Welch Foundation (C-1559), the National Institutes of Health (R01HL157714)
and the Rice Creative Ventures Fund supported the research.
========================================================================== Story Source: Materials provided by Rice_University. Note: Content may
be edited for style and length.
========================================================================== Journal Reference:
1. Qian Wang, Jie Yang, Zhicheng Zhong, Jeffrey A. Vanegas, Xue Gao,
Anatoly
B. Kolomeisky. A general theoretical framework to design base
editors with reduced bystander effects. Nature Communications,
2021; 12 (1) DOI: 10.1038/s41467-021-26789-5 ==========================================================================
Link to news story:
https://www.sciencedaily.com/releases/2021/11/211111130340.htm
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