Scientists at Oak Ridge National Laboratory have utilized quantum biology and explainable artificial intelligence to advance CRISPR Cas9 technology for genome editing in microorganisms. This breakthrough has enabled more precise genetic modification of microorganisms, opening up possibilities for the production of renewable fuels and chemicals. The research at Oak Ridge National Laboratory has significantly improved the efficiency of CRISPR Cas9 genome editing in microorganisms and contributed to renewable energy development.
CRISPR is a powerful tool for bioengineering, used to modify the genetic code to improve the performance of organisms or correct mutations. ORNL scientists developed a method to improve the accuracy of the CRISPR Cas9 gene editing tool used to modify microorganisms for the production of renewable fuels and chemicals. They have leveraged their expertise in quantum biology, artificial intelligence, and synthetic biology to achieve this.
To improve the modeling and design of guide RNAs, ORNL scientists sought to better understand what is happening at the most fundamental level in the cell nucleus, where genetic material is stored. They turned to quantum biology to study how electronic structure affects the chemical properties and interactions of nucleotides, such as DNA and RNA.
Furthermore, scientists at ORNL have built an explainable artificial intelligence model called iterated random forest, which has been used to train the model on a dataset of about 50,000 guide RNAs targeting the genome of Escherichia coli. This model has provided important features regarding the nucleotides that allow for better selection of guide RNAs.
Improving the CRISPR Cas9 model provides scientists with a high-throughput pipeline for linking genotype to phenotype in functional genomics. This research will impact efforts at the ORNL-led Center for Bioenergy Innovation (CBI), such as improving bioenergy feedstock plants and bacterial fermentation of biomass.
The results of this research significantly improve the prediction of guide RNAs. This represents an exciting advance toward understanding how avoid ‘mistakes’ and improving the ability to use CRISPR tools to predictively modify the DNA of more organisms. The study was funded by SEED SFA and CBI, part of the DOE Office of Science’s Biological and Environmental Research Program, ORNL’s Laboratory-Directed Research and Development Program, and OLCF and Compute’s High Performance Computing Resources and Data Environment for Science, both supported by the Office of Science.
Source: scitechdaily.com
