A quantitative evaluation of ethylene production in the recombinant cyanobacterium Synechocystis sp. PCC 6803 harboring the ethylene-forming enzyme by membrane inlet mass spectrometry
Jazyk angličtina Země Anglie, Velká Británie Médium print-electronic
Typ dokumentu časopisecké články, práce podpořená grantem
PubMed
26708481
DOI
10.1016/j.biortech.2015.11.062
PII: S0960-8524(15)01595-3
Knihovny.cz E-zdroje
- Klíčová slova
- Biofuels, Biotechnology, Cyanobacteria, MIMS, Photobioreactor,
- MeSH
- autotrofní procesy MeSH
- ethyleny biosyntéza MeSH
- hmotnostní spektrometrie přístrojové vybavení metody MeSH
- kyslík analýza MeSH
- lyasy metabolismus MeSH
- membrány umělé * MeSH
- metabolické sítě a dráhy MeSH
- rekombinace genetická genetika MeSH
- světlo MeSH
- Synechocystis enzymologie růst a vývoj účinky záření MeSH
- uhlík analýza MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
- Názvy látek
- ethylene forming enzyme MeSH Prohlížeč
- ethylene MeSH Prohlížeč
- ethyleny MeSH
- kyslík MeSH
- lyasy MeSH
- membrány umělé * MeSH
- uhlík MeSH
The prediction of the world's future energy consumption and global climate change makes it desirable to identify new technologies to replace or augment fossil fuels by environmentally sustainable alternatives. One appealing sustainable energy concept is harvesting solar energy via photosynthesis coupled to conversion of CO2 into chemical feedstock and fuel. In this work, the production of ethylene, the most widely used petrochemical produced exclusively from fossil fuels, in the model cyanobacterium Synechocystis sp. PCC 6803 is studied. A novel instrumentation setup for quantitative monitoring of ethylene production using a combination of flat-panel photobioreactor coupled to a membrane-inlet mass spectrometer is introduced. Carbon partitioning is estimated using a quantitative model of cyanobacterial metabolism. The results show that ethylene is produced under a wide range of light intensities with an optimum at modest irradiances. The results allow production conditions to be optimized in a highly controlled setup.
Department of Life Sciences Imperial College London London United Kingdom
Institut für Theoretische Biologie Humboldt Universität zu Berlin Berlin Germany
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