# Scalable Development of Custom Genome Editing Technologies

> **NIH NIH DP2** · MASSACHUSETTS GENERAL HOSPITAL · 2022 · $1,512,000

## Abstract

PROJECT SUMMARY
Genome editing technologies have catalyzed major advances across basic and applied biomedical research
fields. Although the adaptation of CRISPR-Cas enzymes for genome editing has facilitated and dramatically
accelerated the ability to edit nucleic acid sequences in living cells, many genetic engineering approaches are
performed using a single enzyme that has notable limitations. The naturally occurring CRISPR-Cas9 effector
from the bacterium Streptococcus pyogenes (SpCas9) can function efficiently for certain editing applications, but
is not a ‘one-size-fits-all’ solution for treating the diversity of sequences that cause genetic disorders. The clinical
potential of SpCas9 is inherently limited due to the natural characteristics of the enzyme, including a requirement
to bind a short DNA motif to initiate editing. This motif only occurs in a fraction of the genome, preventing SpCas9
from editing many disease-causing mutations that do not harbor this sequence. The inability of SpCas9 to target
a broad range of DNA sites, along with other suboptimal characteristics, illustrates the need for innovations to
unlock the wide potential of genome editing in the clinic. One solution to enable more comprehensive genome
targeting is to utilize directed evolution to engineer new forms of SpCas9 that can recognize new motifs.
However, traditional protein engineering approaches remain low-throughput, costly, and laborious. Here we will
close these technological and methodological gaps by optimizing scalable methods to engineer and characterize
novel Cas variants with improved properties. Our proposed research will address prominent limitations of
CRISPR-Cas enzymes by: (1) developing scalable experimental approaches to more rapidly and effectively
engineer and characterize proteins, (2) optimizing machine learning-guided directed evolution to create a catalog
of customizable DNA editors, and (3) as proof-of-concept, thoroughly evaluate a catalog of PAM-selective editors
against mutations that cause common and rare diseases. The long-term vision of this project is to create a
catalog of bespoke editors that together can systematically target the genome without sacrificing other important
properties like specificity. To fully democratize editing, this collection of optimized CRISPR technologies will
create a virtual ‘one-stop-shop’ for researchers and clinicians seeking optimized genetic treatments for patients.
Successful completion of the proposed studies will synergize experimental and computational methods, will
provide novel scalable approaches for characterizing and improving the activities of genome editing
technologies, and will exponentially expand the capabilities within the editing ‘toolbox’. Together, the
development and implementation of a catalog of custom Cas editors and will accelerate and create a blueprint
for the translation of safe and effective CRISPR therapies to benefit patients.

## Key facts

- **NIH application ID:** 10472972
- **Project number:** 1DP2CA281401-01
- **Recipient organization:** MASSACHUSETTS GENERAL HOSPITAL
- **Principal Investigator:** Benjamin Peter Kleinstiver
- **Activity code:** DP2 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $1,512,000
- **Award type:** 1
- **Project period:** 2022-09-20 → 2025-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10472972

## Citation

> US National Institutes of Health, RePORTER application 10472972, Scalable Development of Custom Genome Editing Technologies (1DP2CA281401-01). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10472972. Licensed CC0.

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