Simple item page
 

Combing Directed Enzyme Evolution with Metabolic Engineering to Develop Efficient Microbial Cell Factories

cris.virtual.author-orcid0000-0001-8372-8459
cris.virtual.author-orcid#PLACEHOLDER_PARENT_METADATA_VALUE#
cris.virtual.author-orcid#PLACEHOLDER_PARENT_METADATA_VALUE#
cris.virtual.author-orcid#PLACEHOLDER_PARENT_METADATA_VALUE#
cris.virtualsource.author-orcid6f5a4155-2edb-48cf-b362-f3180e151169
cris.virtualsource.author-orcid#PLACEHOLDER_PARENT_METADATA_VALUE#
cris.virtualsource.author-orcid#PLACEHOLDER_PARENT_METADATA_VALUE#
cris.virtualsource.author-orcid#PLACEHOLDER_PARENT_METADATA_VALUE#
dc.abstract.enThe booming field of synthetic biology and metabolic engineering provides promising approaches for sustainable manufacturing of chemicals from renewable feedstocks with microbial cell factories. Classical metabolic engineering strategies mainly focus on altering gene expression levels and enzyme concentrations to improve the metabolic fluxes of specific pathways. However, the impact and limitations of enzyme properties, which are usually ignored in classical metabolic engineering efforts, can hinder further optimization of microbial cell factories. Protein engineering and directed evolution are powerful tools for modifying proteins to achieve desirable properties, and they have been integrated into metabolic engineering efforts to build highly efficient metabolic pathways and optimal industrial chassis. In this review, we present traditional and data-driven strategies and techniques of directed evolution, including random library design, semirational design, smart library design, and in vivo continuous evolution. We also discuss how these directed evolution strategies have been applied in metabolic engineering toward superphenotypes that cannot be achieved through simple gene overexpression or knockout. Finally, we discuss the challenges of applying protein engineering in metabolic engineering and the prospects for accelerating the directed evolution workflow using the state-of-art technologies.
dc.affiliationWydział Nauk o Żywności i Żywieniu
dc.affiliation.instituteKatedra Biotechnologii i Mikrobiologii Żywności
dc.contributor.authorRen, Yuyao
dc.contributor.authorCelińska, Ewelina
dc.contributor.authorCai, Peng
dc.contributor.authorZhou, Yongjin J.
dc.date.access2025-12-15
dc.date.accessioned2025-12-15T13:37:56Z
dc.date.available2025-12-15T13:37:56Z
dc.date.copyright2025-05-01
dc.date.issued2025
dc.description.accesstimeat_publication
dc.description.bibliographyil., bibliogr.
dc.description.financepublication_nocost
dc.description.financecost0,00
dc.description.number8
dc.description.points5
dc.description.versionfinal_published
dc.description.volume2
dc.identifier.doi10.1021/cbe.5c00002
dc.identifier.issn2836-967X
dc.identifier.urihttps://sciencerep.up.poznan.pl/handle/item/6400
dc.identifier.weblinkhttps://pubs.acs.org/doi/10.1021/cbe.5c00002
dc.languageen
dc.relation.ispartofChemical and Biological Engineers
dc.relation.pages449-459
dc.rightsCC-BY-NC-ND
dc.sciencecloudnosend
dc.share.typeOPEN_JOURNAL
dc.subject.enprotein engineering
dc.subject.enmetabolic engineering
dc.subject.endirected evolution
dc.subject.enin vivo evolution
dc.subject.enartificial intelligence
dc.subtypeReviewArticle
dc.titleCombing Directed Enzyme Evolution with Metabolic Engineering to Develop Efficient Microbial Cell Factories
dc.typeJournalArticle
dspace.entity.typePublication
oaire.citation.issue8
oaire.citation.volume2