In-depth analysis of biocatalysts by microfluidics: An emerging source of data for machine learning.

Autor: Vasina M; Loschmidt Laboratories, Department of Experimental Biology and RECETOX, Faculty of Science, Masaryk University, 602 00 Brno, Czech Republic; International Clinical Research Centre, St. Anne's University Hospital, 656 91 Brno, Czech Republic., Kovar D; Loschmidt Laboratories, Department of Experimental Biology and RECETOX, Faculty of Science, Masaryk University, 602 00 Brno, Czech Republic; International Clinical Research Centre, St. Anne's University Hospital, 656 91 Brno, Czech Republic., Damborsky J; Loschmidt Laboratories, Department of Experimental Biology and RECETOX, Faculty of Science, Masaryk University, 602 00 Brno, Czech Republic; International Clinical Research Centre, St. Anne's University Hospital, 656 91 Brno, Czech Republic., Ding Y; Institute for Chemical and Bioengineering, ETH Zürich, 8093 Zürich, Switzerland., Yang T; Institute for Chemical and Bioengineering, ETH Zürich, 8093 Zürich, Switzerland; Department of Biochemistry, University of Zurich, 8057 Zurich, Switzerland., deMello A; Institute for Chemical and Bioengineering, ETH Zürich, 8093 Zürich, Switzerland., Mazurenko S; Loschmidt Laboratories, Department of Experimental Biology and RECETOX, Faculty of Science, Masaryk University, 602 00 Brno, Czech Republic; International Clinical Research Centre, St. Anne's University Hospital, 656 91 Brno, Czech Republic. Electronic address: mazurenko@mail.muni.cz., Stavrakis S; Institute for Chemical and Bioengineering, ETH Zürich, 8093 Zürich, Switzerland. Electronic address: stavros.stavrakis@chem.ethz.ch., Prokop Z; Loschmidt Laboratories, Department of Experimental Biology and RECETOX, Faculty of Science, Masaryk University, 602 00 Brno, Czech Republic; International Clinical Research Centre, St. Anne's University Hospital, 656 91 Brno, Czech Republic. Electronic address: zbynek@chemi.muni.cz.
Jazyk: angličtina
Zdroj: Biotechnology advances [Biotechnol Adv] 2023 Sep; Vol. 66, pp. 108171. Date of Electronic Publication: 2023 May 05.
DOI: 10.1016/j.biotechadv.2023.108171
Abstrakt: Nowadays, the vastly increasing demand for novel biotechnological products is supported by the continuous development of biocatalytic applications that provide sustainable green alternatives to chemical processes. The success of a biocatalytic application is critically dependent on how quickly we can identify and characterize enzyme variants fitting the conditions of industrial processes. While miniaturization and parallelization have dramatically increased the throughput of next-generation sequencing systems, the subsequent characterization of the obtained candidates is still a limiting process in identifying the desired biocatalysts. Only a few commercial microfluidic systems for enzyme analysis are currently available, and the transformation of numerous published prototypes into commercial platforms is still to be streamlined. This review presents the state-of-the-art, recent trends, and perspectives in applying microfluidic tools in the functional and structural analysis of biocatalysts. We discuss the advantages and disadvantages of available technologies, their reproducibility and robustness, and readiness for routine laboratory use. We also highlight the unexplored potential of microfluidics to leverage the power of machine learning for biocatalyst development.
Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this review paper.
(Copyright © 2023. Published by Elsevier Inc.)
Databáze: MEDLINE
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