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Directed Evolution in Drops: Molecular Aspects and Applications

期刊

ACS SYNTHETIC BIOLOGY
卷 10, 期 11, 页码 2772-2783

出版社

AMER CHEMICAL SOC
DOI: 10.1021/acssynbio.1c00313

关键词

droplet microfluidics; directed evolution; enzyme; antibody; aptamer; molecular engineering

资金

  1. European Research Council (ERC) under the European Union's Horizon 2020 research and innovation program [724040]
  2. EMBO Postdoctoral Fellowship Program [1033-2017]
  3. Fondation Bettencourt-Schueller
  4. Horizon 2020 EVOdrops project [813786]
  5. Region Aquitaine
  6. French Government 'Investments for the Future' program, University of Bordeaux Initiative of Excellence (IDEX Bordeaux) [ANR-10-IDEX-03-02]
  7. European Research Council (ERC) [724040] Funding Source: European Research Council (ERC)

向作者/读者索取更多资源

Optimizing the properties of biological molecules is crucial for various industrial and medical applications. Directed evolution is a powerful technique for modifying biomolecules by mimicking natural evolution. Droplet-based microfluidic systems offer a high-throughput solution for enhancing efficiency and overcoming screening limitations.
The process of optimizing the properties of biological molecules is paramount for many industrial and medical applications. Directed evolution is a powerful technique for modifying and improving biomolecules such as proteins or nucleic acids (DNA or RNA). Mimicking the mechanism of natural evolution, one can enhance a desired property by applying a suitable selection pressure and sorting improved variants. Droplet-based microfluidic systems offer a high-throughput solution to this approach by helping to overcome the limiting screening steps and allowing the analysis of variants within increasingly complex libraries. Here, we review cases where successful evolution of biomolecules was achieved using droplet-based microfluidics, focusing on the molecular processes involved and the incorporation of microfluidics to the workflow. We highlight the advantages and limitations of these microfluidic systems compared to low throughput methods and show how the integration of these systems into directed evolution workflows can open new avenues to discover or improve biomolecules according to user-defined conditions.

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