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A quantitative method for proteome reallocation using minimal regulatory interventions.
Lastiri-Pancardo, Gustavo; Mercado-Hernández, Jonathan S; Kim, Juhyun; Jiménez, José I; Utrilla, José.
Afiliação
  • Lastiri-Pancardo G; Systems and Synthetic Biology Program, Centro de Ciencias Genómicas, Universidad Nacional Autónoma de México, Cuernavaca, Mexico.
  • Mercado-Hernández JS; Systems and Synthetic Biology Program, Centro de Ciencias Genómicas, Universidad Nacional Autónoma de México, Cuernavaca, Mexico.
  • Kim J; Faculty of Health and Medical Sciences, University of Surrey, Guildford, UK.
  • Jiménez JI; Faculty of Health and Medical Sciences, University of Surrey, Guildford, UK.
  • Utrilla J; Systems and Synthetic Biology Program, Centro de Ciencias Genómicas, Universidad Nacional Autónoma de México, Cuernavaca, Mexico. utrilla@ccg.unam.mx.
Nat Chem Biol ; 16(9): 1026-1033, 2020 09.
Article em En | MEDLINE | ID: mdl-32661378
Engineering resource allocation in biological systems is an ongoing challenge. Organisms allocate resources for ensuring survival, reducing the productivity of synthetic biology functions. Here we present a new approach for engineering the resource allocation of Escherichia coli by rationally modifying its transcriptional regulatory network. Our method (ReProMin) identifies the minimal set of genetic interventions that maximizes the savings in cell resources. To this end, we categorized transcription factors according to the essentiality of its targets and we used proteomic data to rank them. We designed the combinatorial removal of transcription factors that maximize the release of resources. Our resulting strain containing only three mutations, theoretically releasing 0.5% of its proteome, had higher proteome budget, increased production of an engineered metabolic pathway and showed that the regulatory interventions are highly specific. This approach shows that combining proteomic and regulatory data is an effective way of optimizing strains using conventional molecular methods.
Assuntos

Texto completo: 1 Bases de dados: MEDLINE Assunto principal: Engenharia Genética / Proteoma / Escherichia coli Tipo de estudo: Prognostic_studies Idioma: En Revista: Nat Chem Biol Assunto da revista: BIOLOGIA / QUIMICA Ano de publicação: 2020 Tipo de documento: Article País de afiliação: México

Texto completo: 1 Bases de dados: MEDLINE Assunto principal: Engenharia Genética / Proteoma / Escherichia coli Tipo de estudo: Prognostic_studies Idioma: En Revista: Nat Chem Biol Assunto da revista: BIOLOGIA / QUIMICA Ano de publicação: 2020 Tipo de documento: Article País de afiliação: México