Cho, Bovinille Anye, Moreno-Cabezuelo, José Ángel, Mills, Lauren A., del Río Chanona, Ehecatl Antonio, Lea-Smith, David J. ORCID: https://orcid.org/0000-0003-2463-406X and Zhang, Dongda (2023) Integrated experimental and photo-mechanistic modelling of biomass and optical density production of fast versus slow growing model cyanobacteria. Algal Research, 70. ISSN 2211-9264
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Abstract
Biotechnological exploitation of fast-growing cyanobacterial species is hindered by unavailable mechanistic interpretations for the differing bioconversion rates when exploring strains with similar metabolic pathways and transport systems. This study investigated two strains: Synechococcus sp. PCC 11901, the fastest growing cyanobacterium identified to date, and Synechocystis sp. PCC 6803, under a range of operational light intensities from 300 to 900 μmol photons m−2 s−1, and presents three original contributions. Firstly, strain specific dynamic biomass and optical density (OD750nm) models were constructed incorporating sophisticated photo-mechanistic influences, previously unachieved in OD750nm. Secondly, bootstrapping parameter estimation with 3-fold cross validations was exploited to simultaneously identify the model parameters and confidence intervals, thus enabling probabilistic simulations and thorough validation against experimental data sets. Thirdly, presented mechanistic interpretations for the over two-fold faster growth of PCC 11901 versus PCC 6803 despite PCC 6803's high light utilisation efficiency. These findings will benefit upscaling of future cyanobacterial biotechnology applications and exploitation of Synechococcus sp. PCC 11901 for production of biomass and chemicals of industrial, nutritional and medical importance.
Item Type: | Article |
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Faculty \ School: | Faculty of Science > School of Biological Sciences University of East Anglia Research Groups/Centres > Theme - ClimateUEA |
UEA Research Groups: | Faculty of Science > Research Groups > Molecular Microbiology |
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Depositing User: | LivePure Connector |
Date Deposited: | 26 May 2023 16:31 |
Last Modified: | 09 Mar 2024 11:30 |
URI: | https://ueaeprints.uea.ac.uk/id/eprint/92193 |
DOI: | 10.1016/j.algal.2023.102997 |
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