Large scale active-learning-guided exploration for in vitro protein production optimization.
basic_science · Level V
Where this comes from
- Record sourced from PubMed, PMID 32312991.
- Also identified by DOI 10.1038/s41467-020-15798-5 and PMC identifier 7170859.
- Licence recorded as CC BY.
- The licence permits redistribution, so the abstract is shown in full and the full text is available from the publisher.
Abstract
Lysate-based cell-free systems have become a major platform to study gene expression but batch-to-batch variation makes protein production difficult to predict. Here we describe an active learning approach to explore a combinatorial space of ~4,000,000 cell-free buffer compositions, maximizing protein production and identifying critical parameters involved in cell-free productivity. We also provide a one-step-method to achieve high quality predictions for protein production using minimal experimental effort regardless of the lysate quality.
Medical subject headings
- Protein Biosynthesis
- Proteins