Prediction for targeting efficiency of guide RNA for a gene of interest in bacteria
Keywords
gene silencing, guide efficiency, Cas9, CRISPRi, software, predictive model, machine learning, AI
Invention Novelty
Provided is a machine learning-based tool that improves reliable prediction of targeting efficiency of guide RNA for gene silencing
in bacteria.
Value Proposition
CRISPR interference (CRISPRi) technology is used to block gene expression with a catalytically inactive mutant of Cas9 (dCas9).
This requires a short guide-RNA to target dCas9 to the gene of interest, where it binds and blocks transcription, thus leading to
gene silencing. In general, gene silencing is not complete, and silencing efficiency is affected by several factors, such as basal
gene expression. Available machine learning-based tools for prediction fail to account for gene-specific factors that could influence
guide depletion during training, such as their transcriptional activity or operon structures. In contrast, the offered innovative and
robust methods to produce predictive models for guide efficiency represents an important tool to increase efficacy in a cost-effective
way.
Workflow of prediction of guide efficiency [Yu et al. 2022, modified]
Technology Description
The invention relates to a method for prediction of the
targeting efficiency of guide RNA (gRNA) for gene
targeting by evaluating data obtained in genome-wide
screens. , which provide levels of targeting
characteristics efficiency of guides including levels of
targeting efficiency confounded with gene specific
effects. The method is based on a mixed-effect
random forest regression model that can learn from
multiple datasets and isolates effects manipulable in
guide design, combined with methods from
explainable AI to infer interpretable design rules.
Commercial Opportunity
Enabling technology for basic research as well as for applied biotechnology by enabling precision modification of the bacterial
transcriptome. The technology is offered for licensing.
Development Status
The workflow is provided as a software implementation that can be applied to any bacterium for which a genome wide CRISPRi
screen is available. In addition, a model to predict the guide efficiency of dCas9 has been implemented in E. coli, including a
webserver, and a command-line tool is available.
Patent Situation
Priority application was filed in July 2020, the international (PCT-)application was published in 2022 (WO2022013186),
national/regional applications are pending in Europe and the US.
Further Reading
Yu et al. 2022. bioRxiv preprint: doi.org/10.1101/2022.05.27.493707
Institute of Origin
