A codon-based live-cell biomonitoring system for assessing intracellular phenylalanine bioavailability in cyanobacteria.


Journal

Biosensors & bioelectronics
ISSN: 1873-4235
Titre abrégé: Biosens Bioelectron
Pays: England
ID NLM: 9001289

Informations de publication

Date de publication:
15 Jan 2024
Historique:
received: 18 07 2023
revised: 17 10 2023
accepted: 25 10 2023
medline: 22 11 2023
pubmed: 6 11 2023
entrez: 3 11 2023
Statut: ppublish

Résumé

Phenylalanine, as an essential aromatic amino acid, is not only needed for protein and vital molecules such as neurotransmitter and hormone synthesis but also a substrate for the biosynthesis of phenylpropanoids and various bioactive compounds. The metabolism of phenylalanine is dynamic and transitory, which would otherwise inhibit cell growth. Therefore, it is challenging and imperative to monitor intracellular phenylalanine bioavailability in real time, which has great significance for evaluating the effectiveness of introducing pathway-specific genetic modifications to enhance phenylalanine generation. In this study, we proposed a live-cell biomonitoring system to assess phenylalanine bioavailability in real time in cyanobacteria based on codon degeneracy and species-specific usage bias. The biomonitoring system was generated through genetic modification of phenylalanine codons in the chloramphenicol antibiotic resistance gene to wholly preferred and rare codons, in combination with an orthogonal constitutive promoter Trc to express these genes. Cyanobacterial cells equipped with a preferred codon-based gene showed a significant growth advantage over those with rare codons under antibiotic pressure, while the delayed growth caused by rare codon-based genes could be rescued by supplementing phenylalanine in the cultivation medium. Increasing intracellular phenylalanine bioavailability could promote rare codon-based gene containing cell growth to a similar level as wild-type strains harboring preferred codon-based gene, providing a live-cell visualized screening method to relatively define phenylalanine content from either random mutation libraries or pathway-specific engineering cyanobacterial chassis before conducting labor-intensive quantitative measurements.

Identifiants

pubmed: 37922807
pii: S0956-5663(23)00734-0
doi: 10.1016/j.bios.2023.115792
pii:
doi:

Substances chimiques

Phenylalanine 47E5O17Y3R
Codon 0

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

115792

Informations de copyright

Copyright © 2023 Elsevier B.V. All rights reserved.

Déclaration de conflit d'intérêts

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 paper.

Auteurs

Haojie Jin (H)

The Key Laboratory for Silviculture and Conservation of Ministry of Education, College of Forestry, Beijing Forestry University, Beijing, 100083, PR China; Ecological Observation and Research Station of Heilongjiang Sanjiang Plain Wetlands, National Forestry and Grassland Administration, Shuangyashan, 518000, PR China.

Jiaqi Zhang (J)

The Key Laboratory for Silviculture and Conservation of Ministry of Education, College of Forestry, Beijing Forestry University, Beijing, 100083, PR China.

Yan Wang (Y)

Center of Basic Medical Research, Institute of Medical Innovation and Research, Peking University Third Hospital, Beijing, 100191, PR China.

Wanzhao Ge (W)

The Key Laboratory for Silviculture and Conservation of Ministry of Education, College of Forestry, Beijing Forestry University, Beijing, 100083, PR China.

Yike Jing (Y)

The Key Laboratory for Silviculture and Conservation of Ministry of Education, College of Forestry, Beijing Forestry University, Beijing, 100083, PR China.

Xiaoyu Cao (X)

The Key Laboratory for Silviculture and Conservation of Ministry of Education, College of Forestry, Beijing Forestry University, Beijing, 100083, PR China.

Yixin Huo (Y)

Key Laboratory of Molecular Medicine and Biotherapy, School of Life Science, Beijing Institute of Technology, Beijing, 100081, PR China.

Yujie Fu (Y)

The Key Laboratory for Silviculture and Conservation of Ministry of Education, College of Forestry, Beijing Forestry University, Beijing, 100083, PR China; Ecological Observation and Research Station of Heilongjiang Sanjiang Plain Wetlands, National Forestry and Grassland Administration, Shuangyashan, 518000, PR China. Electronic address: yujie_fu@163.com.

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Classifications MeSH