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Quantitative Trait Loci (QTL)-Guided Metabolic Engineering of a Complex Trait.
Maurer, Matthew J; Sutardja, Lawrence; Pinel, Dominic; Bauer, Stefan; Muehlbauer, Amanda L; Ames, Tyler D; Skerker, Jeffrey M; Arkin, Adam P.
Afiliación
  • Maurer MJ; Energy Biosciences Institute and ‡Department of Bioengineering, University of California , Berkeley, California 94720, United States.
  • Sutardja L; Biological Systems and Engineering Division, and ∥Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory , Berkeley, California 94720, United States.
  • Pinel D; Energy Biosciences Institute and ‡Department of Bioengineering, University of California , Berkeley, California 94720, United States.
  • Bauer S; Biological Systems and Engineering Division, and ∥Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory , Berkeley, California 94720, United States.
  • Muehlbauer AL; Energy Biosciences Institute and ‡Department of Bioengineering, University of California , Berkeley, California 94720, United States.
  • Ames TD; Biological Systems and Engineering Division, and ∥Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory , Berkeley, California 94720, United States.
  • Skerker JM; Energy Biosciences Institute and ‡Department of Bioengineering, University of California , Berkeley, California 94720, United States.
  • Arkin AP; Biological Systems and Engineering Division, and ∥Environmental Genomics and Systems Biology Division, Lawrence Berkeley National Laboratory , Berkeley, California 94720, United States.
ACS Synth Biol ; 6(3): 566-581, 2017 03 17.
Article en En | MEDLINE | ID: mdl-27936603
Engineering complex phenotypes for industrial and synthetic biology applications is difficult and often confounds rational design. Bioethanol production from lignocellulosic feedstocks is a complex trait that requires multiple host systems to utilize, detoxify, and metabolize a mixture of sugars and inhibitors present in plant hydrolysates. Here, we demonstrate an integrated approach to discovering and optimizing host factors that impact fitness of Saccharomyces cerevisiae during fermentation of a Miscanthus x giganteus plant hydrolysate. We first used high-resolution Quantitative Trait Loci (QTL) mapping and systematic bulk Reciprocal Hemizygosity Analysis (bRHA) to discover 17 loci that differentiate hydrolysate tolerance between an industrially related (JAY291) and a laboratory (S288C) strain. We then used this data to identify a subset of favorable allelic loci that were most amenable for strain engineering. Guided by this "genetic blueprint", and using a dual-guide Cas9-based method to efficiently perform multikilobase locus replacements, we engineered an S288C-derived strain with superior hydrolysate tolerance than JAY291. Our methods should be generalizable to engineering any complex trait in S. cerevisiae, as well as other organisms.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Saccharomyces cerevisiae / Sitios de Carácter Cuantitativo Tipo de estudio: Prognostic_studies Idioma: En Revista: ACS Synth Biol Año: 2017 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Estados Unidos
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Saccharomyces cerevisiae / Sitios de Carácter Cuantitativo Tipo de estudio: Prognostic_studies Idioma: En Revista: ACS Synth Biol Año: 2017 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Estados Unidos