DNA 3.0: Developing novel enzymes for DNA synthesis with deep learning and combinatorial genetics

Project Summary/AbstractDNA synthesis has played a key role in the biotechnology revolution. The ready availability of synthetic DNA oligonucleotides and of genes assembled from them, has been invaluable for elucidating and unlocking biological function and enabling the new field of synthetic biology which can create novel cells, enzymes, therapeutics, diagnostics and other reagents of commercial value. Despite this impact, DNA synthesis uses chemical strategies developed over 30 years ago which are costly and limited to molecules of 200 nucleotides or less in length.Next-generation enzymatic DNA synthesis technologies are being explored that use template- independent DNA polymerases (TIDPs) for controlled addition of nucleotides to a growing DNA strand. Although advances have been reported recently, enzymatic DNA synthesis is still limited by the low efficiency of available TIDPs, and specifically by the relative inability of these polymerases to incorporate 3andapos;-blocked nucleotides.In this Phase I Small Business Innovation Research (SBIR) project, Primordial Genetics Inc, a synthetic biology company with differentiated combinatorial genetic technology, and Denovium Inc., an artificial intelligence company pioneering novel Al methods for genetic discovery, are joining forces to develop novel and highly efficient TIDPs for enzymatic DNA synthesis in vitro.Denovium will use their computational capabilities based on machine learning algorithms to discover novel TIDPs with the desired activities from proprietary and public databases. Denovium will also perform proprietary artificial intelligence (AI) scans to determine the functional impact of all possible mutations on the selected TIDPs. Primordial Genetics will synthesize and express the resulting collection of sequences, and test them in vitro to identify the most active enzymes. The best 2 enzymes will be diversified using Primordial Geneticsandapos; proprietary Function Generator technology and other randomized diversification methods. Populations of genes encoding enzyme variants will be screened with ultra-high-throughput screens to identify the most active enzymes. The dataset resulting from this work will be used to train Denoviumandapos;s sequence prediction algorithm to accelerate further enzyme improvements in Phase II.The proposed work is a feasibility study for isolating and developing novel enzymes suitable for enzymatic DNA synthesis, and also for creating a pipeline of enzyme optimization tools. The enzymes discovered and in this work will be directly useful for enzymatic DNA synthesis applications, and can be licensed or sold to leading DNA and gene manufaturers.Project Narrative The principal aim of this project is to develop novel and improved DNA polymerases for the industrial synthesis of DNA, which is currently performed by synthetic chemical methods and represents one of the cornerstone technologies of the biotechnology industry. To overcome limitations of the current chemical technology in cost, efficiency and the length of DNA molecules that can be synthesized, there have been widespread attempts to develop specific DNA polymerases as efficient molecular machines for synthesizing DNA. This project will develop novel and more efficient polymerases than are currently available, which will impact the diagnosis, prevention and treatment of human diseases such as cancer, heart disease, HIV and genetic diseases such as cystic fibrosis.