Metabolic impact assessment for heterologous protein production in Streptomyces lividans based on genome-scale metabolic network modeling

被引:8
|
作者
Lule, Ivan [1 ]
D'Huys, Pieter-Jan [1 ]
Van Mellaert, Lieve [2 ]
Anne, Jozef [2 ]
Bernaerts, Kristel [1 ]
Van Impe, Jan [1 ]
机构
[1] Katholieke Univ Leuven, Dept Chem Engn, Chem & Biochem Proc Technol & Control Sect BioTeC, B-3001 Louvain, Belgium
[2] Katholieke Univ Leuven, Dept Microbiol & Immunol, Lab Mol Bacteriol, B-3001 Louvain, Belgium
关键词
Streptomyces lividans; (geometric) Flux balance analysis; Mouse tumor necrosis factor (mTNF-alpha); Heterologous proteins; Genome-scale metabolic network; FLUX BALANCE ANALYSIS; NECROSIS-FACTOR-ALPHA; ESCHERICHIA-COLI; SECRETION; OVEREXPRESSION; COELICOLOR;
D O I
10.1016/j.mbs.2013.08.006
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
The metabolic impact exerted on a microorganism due to heterologous protein production is still poorly understood in Streptomyces lividans. In this present paper, based on exometabolomic data, a proposed genome-scale metabolic network model is used to assess this metabolic impact in S. lividans. Constraint-based modeling results obtained in this work revealed that the metabolic impact due to heterologous protein production is widely distributed in the genome of S. lividans, causing both slow substrate assimilation and a shift in active pathways. Exchange fluxes that are critical for model performance have been identified for metabolites of mouse tumor necrosis factor, histidine, valine and lysine, as well as biomass. Our results unravel the interaction of heterologous protein production with intracellular metabolism of S. lividans, thus, a possible basis for further studies in relieving the metabolic burden via metabolic or bioprocess engineering. (C) 2013 Published by Elsevier Inc.
引用
收藏
页码:113 / 121
页数:9
相关论文
共 50 条
  • [21] Understanding Antimicrobial Resistance Using Genome-Scale Metabolic Modeling
    Alonso-Vasquez, Tania
    Fondi, Marco
    Perrin, Elena
    ANTIBIOTICS-BASEL, 2023, 12 (05):
  • [22] Modeling the metabolic dynamics at the genome-scale by optimized yield analysis
    Luo, Hao
    Li, Peishun
    Ji, Boyang
    Nielsen, Jens
    METABOLIC ENGINEERING, 2023, 75 : 119 - 130
  • [23] A review of genome-scale metabolic flux modeling of anaerobiosis in biotechnology
    Senger, Ryan S.
    Yen, Jiun Y.
    Fong, Stephen S.
    CURRENT OPINION IN CHEMICAL ENGINEERING, 2014, 6 : 33 - 42
  • [24] Enhancing Microbiome Research through Genome-Scale Metabolic Modeling
    Ankrah, Nana Y. D.
    Bernstein, David B.
    Biggs, Matthew
    Carey, Maureen
    Engevik, Melinda
    Garcia-Jimenez, Beatriz
    Lakshmanan, Meiyappan
    Pacheco, Alan R.
    Sulheim, Snorre
    Medlock, Gregory L.
    MSYSTEMS, 2021, 6 (06)
  • [25] Genome-Scale Metabolic Modeling and Its Application to Microbial Communities
    Reed, Jennifer L.
    CHEMISTRY OF MICROBIOMES, 2017, : 85 - 91
  • [26] Bayesian Integrative Modeling of Genome-Scale Metabolic and Regulatory Networks
    Mhamdi, Hanen
    Bourdon, Jeremie
    Larhlimi, Abdelhalim
    Elloumi, Mourad
    INFORMATICS-BASEL, 2020, 7 (01):
  • [27] Protein constraints in genome-scale metabolic models: Data integration, parameter estimation, and prediction of metabolic phenotypes
    Ferreira, Mauricio Alexander de Moura
    da Silveira, Wendel Batista
    Nikoloski, Zoran
    BIOTECHNOLOGY AND BIOENGINEERING, 2024, 121 (03) : 915 - 930
  • [28] Genome-scale metabolic network models for industrial microorganisms metabolic engineering: Current advances and future prospects
    Gong, Zhijin
    Chen, Jiayao
    Jiao, Xinyu
    Gong, Hao
    Pan, Danzi
    Liu, Lingli
    Zhang, Yang
    Tan, Tianwei
    BIOTECHNOLOGY ADVANCES, 2024, 72
  • [29] Integration of expression data in genome-scale metabolic network reconstructions
    Blazier, Anna S.
    Papin, Jason A.
    FRONTIERS IN PHYSIOLOGY, 2012, 3
  • [30] Reconstruction and analysis of the genome-scale metabolic network of Candida glabrata
    Xu, Nan
    Liu, Liming
    Zou, Wei
    Liu, Jie
    Hua, Qiang
    Chen, Jian
    MOLECULAR BIOSYSTEMS, 2013, 9 (02) : 205 - 216