Researchers from New York University, Columbia University, and the New York Genome Center have developed TIGER (Targeted Inhibition of Gene Expression via guide RNA design), a deep learning model that combines CRISPR technology with artificial intelligence to precisely control gene expression. This innovative approach shows promise for the development of new CRISPR-based therapies.
CRISPR, a widely used gene editing tool, primarily utilizes the Cas9 enzyme to modify DNA. However, scientists have discovered a variation called Cas13 that targets RNA instead. RNA-targeting CRISPRs have diverse applications, including RNA editing, gene suppression, and drug screening, with the potential to advance our understanding of RNA regulation, non-coding RNAs, and combatting viral infections.
The researchers’ primary objective was to optimize the activity of RNA-targeting CRISPRs on the intended RNA targets while minimizing off-target effects caused by mismatches, insertions, and deletions. Previous studies focused primarily on on-target activity and mismatches, overlooking the impact of insertions and deletions, which contribute significantly to genetic variations in humans.
To address these challenges, the team performed RNA-targeting CRISPR screens on human cells, evaluating 200,000 guide RNAs that targeted essential genes, including both perfect matches and off-target variations. Collaborating with machine learning expert David Knowles’ lab, they developed the TIGER model, a deep learning framework trained on the CRISPR screen data. TIGER surpassed previous models by accurately predicting on-target and off-target activities of RNA-targeting CRISPRs.
The integration of artificial intelligence and RNA-targeting CRISPR screens offers exciting prospects for future advancements. TIGER’s predictions help avoid unintended off-target CRISPR activity, facilitating the development of RNA-targeting therapies. Moreover, TIGER enables precise modulation of gene expression by using mismatched guide RNAs to partially inhibit gene expression. This breakthrough has potential applications in conditions characterized by gene copy number imbalances, such as Down syndrome, specific forms of schizophrenia, Charcot-Marie-Tooth disease, and cancer.
The study’s combination of deep learning and RNA-targeting CRISPR screens introduces TIGER as a powerful tool for precise gene expression control. TIGER’s accurate predictions of on-target and off-target activities provide valuable insights for designing effective therapeutic interventions. The researchers anticipate that TIGER will drive significant advancements in biomedicine and promote further exploration of RNA-targeting CRISPR-based therapies.
Reference:
Hans-Hermann Wessels, Andrew Stirn, Alejandro Méndez-Mancilla, Eric J. Kim, Sydney K. Hart, David A. Knowles, Neville E. Sanjana. Prediction of on-target and off-target activity of CRISPR–Cas13d guide RNAs using deep learning. Nature Biotechnology, 2023; DOI: 10.1038/s41587-023-01830-8
PackGene is a CRO & CDMO technology company that specializes in packaging recombinant adeno-associated virus (rAAV) vectors. Since its establishment in 2014, PackGene has been a leader in the AAV vector CRO service field, providing tens of thousands of custom batches of AAV samples to customers in over 20 countries. PackGene offers a one-stop CMC solution for the early development, pre-clinical development, clinical trials, and drug approval of rAAV vector drugs for cell and gene therapy (CGT) companies that is fast, cost-effective, high-quality, and scalable. Additionally, the company provides compliant services for the GMP-scale production of AAVs and plasmids for pharmaceutical companies, utilizing five technology platforms, including the π-Alpha™ 293 cell AAV high-yield platform and the π-Omega™ plasmid high-yield platform. PackGene’s mission is to make gene therapy affordable and accelerate the launch of innovative gene drugs. The company aims to simplify the challenging aspects of gene therapy development and industrialization processes and provide stable, efficient, and economical rAAV Fast Services to accelerate gene and cell therapy development efforts from discovery phase to commercialization.
Related News
NeuExcell Therapeutics Unveils Breakthrough in Stroke Treatment at ASGCT 2024
In a groundbreaking development, NeuExcell Therapeutics has revealed a significant breakthrough in its NXL-001 product for stroke treatment. The announcement was made at the 2024 American Society of Gene and Cell Therapy (ASGCT) Annual Meeting, where the company...
Unraveling CRISPR Precision: BreakTag Illuminates Pathways to Improved Gene Editing
Introduction:The quest for precision in CRISPR-Cas9 gene editing takes a significant leap forward with the development of BreakTag, a method devised to enhance our understanding of DNA double-strand breaks (DSBs) induced by Cas9. This breakthrough, detailed in a...
Sumitomo Pharma Announces FDA Acceptance of Supplemental New Drug Application for Vibegron in Men with Overactive Bladder Symptoms Receiving Pharmacological Therapy for Benign Prostatic Hyperplasia
–Supplemental New Drug Application (sNDA) submission based on Phase 3 study of vibegron 75mg (GEMTESA) demonstrating statistically significant reductions in daily micturition and urgency episodes– –If approved, vibegron will be the first and only beta-3 agonist for...
Herpes cure with gene editing makes progress in laboratory studies
Herpes simplex virus. Credit: CDCResearchers at Fred Hutch Cancer Center have found in pre-clinical studies that an experimental gene therapy for genital and oral herpes removed 90% or more of the infection and suppressed how much virus can be released from an...
Related Services
Plasmids GMP Services
Multiple scales & grade of solutions of various kind of plasmids suitable for multiple treatments in a fast and cost effective way.
READ MORE
AAV GMP Services
Ranging from small-scale AAV production, to large-scale AAV cGMP manufacturing for animal studies.
READ MORE
Technology Platforms
PackGene’s proprietary π-Alpha™ 293 AAV High-yield Platform increases AAV production by 3 to 8 times that of traditional platforms.
READ MORE