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Absolute Proteome Quantification in the Gas-Fermenting Acetogen Clostridium autoethanogenum

  • Kaspar Valgepea
  • , Gert Talbo
  • , Nobuaki Takemori
  • , Ayako Takemori
  • , Christina Ludwig
  • , Vishnuvardhan Mahamkali
  • , Alexander P. Mueller
  • , Ryan Tappel
  • , Michael Köpke
  • , Séan Dennis Simpson
  • , Lars Keld Nielsen
  • , Esteban Marcellin*
  • *Corresponding author for this work
    • Ehime University
    • Technical University of Munich
    • LanzaTech
    • University of Queensland

    Research output: Contribution to journalJournal articleResearchpeer-review

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    Abstract

    Microbes that can recycle one-carbon (C1) greenhouse gases into fuels and chemicals are vital for the biosustainability of future industries. Acetogens are the most efficient known microbes for fixing carbon oxides CO2 and CO. Understanding proteome allocation is important for metabolic engineering as it dictates metabolic fitness. Here, we use absolute proteomics to quantify intracellular concentrations for >1,000 proteins in the model acetogen Clostridium autoethanogenum grown autotrophically on three gas mixtures (CO, CO+H2, or CO+CO2+H2). We detect the prioritization of proteome allocation for C1 fixation and the significant expression of proteins involved in the production of acetate and ethanol as well as proteins with unclear functions. The data also revealed which isoenzymes are likely relevant in vivo for CO oxidation, H2 metabolism, and ethanol production. The integration of proteomic and metabolic flux data demonstrated that enzymes catalyze high fluxes with high concentrations and high in vivo catalytic rates. We show that flux adjustments were dominantly accompanied by changing enzyme catalytic rates rather than concentrations.
    Original languageEnglish
    Article numbere00026-22
    JournalmSystems
    Volume7
    Issue number2
    Number of pages19
    ISSN2379-5077
    DOIs
    Publication statusPublished - 2022

    Keywords

    • Acetogen
    • Gas fermentation
    • gGenome-scale metabolic modeling
    • Metabolic modeling
    • Metabolomics
    • Proteomics

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