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Fast and easy quantitative characterization of methanotroph-photoautotroph cocultures.
Badr, Kiumars; Whelan, William; He, Q Peter; Wang, Jin.
Afiliação
  • Badr K; Department of Chemical Engineering, Auburn University, Auburn, Alabama, USA.
  • Whelan W; Department of Chemical Engineering, Auburn University, Auburn, Alabama, USA.
  • He QP; Department of Chemical Engineering, Auburn University, Auburn, Alabama, USA.
  • Wang J; Department of Chemical Engineering, Auburn University, Auburn, Alabama, USA.
Biotechnol Bioeng ; 118(2): 703-714, 2021 02.
Article em En | MEDLINE | ID: mdl-33064298
Recent research has demonstrated that synthetic methanotroph-photoautotroph cocultures offer a highly promising route to convert biogas into value-added products. However, there is a lack of techniques for fast and accurate characterization of cocultures, such as determining the individual biomass concentration of each organism in real-time. To address this unsolved challenge, we propose an experimental-computational protocol for fast, easy, and accurate quantitative characterization of the methanotroph-photoautotroph cocultures. Besides determining the individual biomass concentration of each organism in the coculture, the protocol can also obtain the individual consumption and production rates of O2 and CO2 for the methanotroph and photoautotroph, respectively. The accuracy and effectiveness of the proposed protocol was demonstrated using two model coculture pairs, Methylomicrobium alcaliphilum 20ZR-Synechococcus sp. PCC7002 that prefers high pH high salt condition, and Methylococcus capsulatus-Chlorella sorokiniana that prefers low salt and neutral pH medium. The performance of the proposed protocol was compared with a flow cytometry-based cell counting approach. The experimental results show that the proposed protocol is much easier to carry out and delivers faster and more accurate results in measuring individual biomass concentration than the cell counting approach without requiring any special equipment.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Simulação por Computador / Chlorella / Methylococcaceae / Methylococcus capsulatus / Modelos Biológicos Idioma: En Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Simulação por Computador / Chlorella / Methylococcaceae / Methylococcus capsulatus / Modelos Biológicos Idioma: En Ano de publicação: 2021 Tipo de documento: Article