4.8 Article

Systematic molecular evolution enables robust biomolecule discovery

Journal

NATURE METHODS
Volume 19, Issue 1, Pages 55-+

Publisher

NATURE PORTFOLIO
DOI: 10.1038/s41592-021-01348-4

Keywords

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Funding

  1. MIT Media Laboratory
  2. Alfred P. Sloan Research Fellowship
  3. Reid Hoffman Foundation
  4. National Institute of Digestive and Kidney Diseases [R00 DK102669-01]
  5. National Institute for Allergy and Infectious Diseases [F31 AI145181-01]
  6. Ruth L. Kirschstein NRSA fellowship from the National Cancer Institute [F32 CA247274-01]

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The PRANCE system allows for comprehensive exploration of biomolecular evolution by conducting high-throughput experiments on different types of biomolecules, revealing that evolution is influenced by both random chance and historical environmental changes. This system enhances the reliability of protein engineering and provides insight into how variables affect evolutionary outcomes.
Evolution occurs when selective pressures from the environment shape inherited variation over time. Within the laboratory, evolution is commonly used to engineer proteins and RNA, but experimental constraints have limited the ability to reproducibly and reliably explore factors such as population diversity, the timing of environmental changes and chance on outcomes. We developed a robotic system termed phage- and robotics-assisted near-continuous evolution (PRANCE) to comprehensively explore biomolecular evolution by performing phage-assisted continuous evolution in high-throughput. PRANCE implements an automated feedback control system that adjusts the stringency of selection in response to real-time measurements of each molecular activity. In evolving three distinct types of biomolecule, we find that evolution is reproducibly altered by both random chance and the historical pattern of environmental changes. This work improves the reliability of protein engineering and enables the systematic analysis of the historical, environmental and random factors governing biomolecular evolution. Phage and robotics-assisted near-continuous evolution enables phage-assisted continuous evolution in high throughput, allowing for improved exploration of sequence space and insight into how variables affect evolution outcomes.

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