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Evolutionary Stability Optimizer (ESO): A Novel Approach to Identify and Avoid Mutational Hotspots in DNA Sequences
Itamar Menuhin-Gruman1, Matan Arbel2, Niv Amitay3
1School of Mathematical Sciences, The Raymond and Beverly Sackler Faculty of Exact Sciences, Tel Aviv University, Tel Aviv, Israel 6997801.
ACS Synthetic Biology
|December 20, 2021
Summary
We developed Evolutionary Stability Optimizer (ESO), a software tool that automatically designs stable genetic constructs for synthetic biology. ESO enhances construct longevity and function by minimizing mutations and epigenetic changes while maintaining high gene expression.
Area of Science:
- Synthetic Biology
- Computational Biology
- Molecular Biology
Background:
- Maintaining functional genetic constructs in synthetic biology is crucial but challenging due to cellular energy demands and natural selection leading to loss-of-function mutations.
- Current methods for ensuring construct stability are often manual, small-scale, or focus only on detecting unstable mutation sites.
Purpose of the Study:
- To introduce the Evolutionary Stability Optimizer (ESO), a novel software tool for the large-scale, automated design of evolutionarily stable genetic constructs.
- To address the trade-off between genetic stability and gene expression in synthetic biology applications.
- To provide a flexible platform for directed genetic stability research.
Main Methods:
- Designed the Evolutionary Stability Optimizer (ESO) software for automated generation of evolutionarily stable constructs.
- Incorporated consideration of mutational and epigenetic hotspots, with user-defined avoidance options.
- Integrated guanine-cytosine (GC) content and codon usage analysis to balance stability with host organism gene expression.
Main Results:
- ESO enables large-scale automatic design of evolutionarily stable constructs, addressing both mutational and epigenetic factors.
- The tool successfully balances evolutionary stability with high gene expression by optimizing GC content and codon usage.
- ESO accurately predicts the evolutionary stability of endogenous genes, validating its predictive capabilities.
Conclusions:
- The Evolutionary Stability Optimizer (ESO) is a user-friendly and flexible tool for enhancing genetic construct stability in synthetic biology.
- ESO facilitates the development of more robust and long-lasting genetic systems, revolutionizing synthetic biology applications.
- Directed genetic stability research, empowered by tools like ESO, is poised to drive significant advancements in the field.
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