High Throughput Variant Libraries and Machine Learning Yield Design Rules for Retron Gene Editors.

The bacterial retron reverse transcriptase system has served as an intracellular factory for single-stranded DNA in many biotechnological applications. In these technologies, a natural retron non-coding RNA (ncRNA) is modified to encode a template for the production of custom DNA sequences by reverse transcription. The efficiency of reverse transcription is a major limiting step for retron technologies, but we lack systematic knowledge of how to improve or maintain reverse transcription efficiency while changing the retron sequence for custom DNA production. Here, we test thousands of different modifications to the retron-Eco1 ncRNA and measure DNA production in pooled variant library experiments, identifying regions of the ncRNA that are tolerant and intolerant to modification. We apply this new information to a specific application: the use of the retron to produce a precise genome editing donor in combination with a CRISPR-Cas9 RNA-guided nuclease (an editron). We use high-throughput libraries in S. cerevisiae to additionally define design rules for editrons. We extend our new knowledge of retron DNA production and editron design rules to human genome editing to achieve the highest efficiency retron-Eco1 editrons to date.

An experimental census of retrons for DNA production and genome editing.

Retrons are bacterial immune systems that use reverse transcribed DNA as a detector of phage infection. They are also increasingly deployed as a component of biotechnology. For genome editing, for instance, retrons are modified so that the reverse transcribed DNA (RT-DNA) encodes an editing donor. Retrons are commonly found in bacterial genomes; thousands of unique retrons have now been predicted bioinformatically. However, only a small number have been characterized experimentally. Here, we add substantially to the corpus of experimentally studied retrons. We synthesized >100 previously untested retrons to identify the natural sequence of RT-DNA they produce, quantify their RT-DNA production, and test the relative efficacy of editing using retron-derived donors to edit bacterial genomes, phage genomes, and human genomes. We add 62 new empirically determined, natural RT-DNAs, which are not predictable from the retron sequence alone. We report a large diversity in RT-DNA production and editing rates across retrons, finding that top performing editors outperform those used in previous studies, and are drawn from a subset of the retron phylogeny.