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Detalle de: Experimental and Modeling Analysis of Synechocystis sp. PCC 6803 Growth

Title Experimental and Modeling Analysis of Synechocystis sp. PCC 6803 Growth
Abstract

<i>Background/Aims:</i> The influence of different parameters such as temperature, irradiance, nitrate concentration, pH, and an external carbon source on <i>Synechocystis </i>PCC 6803 growth was evaluated. <i>Methods:</i> 4.5-ml cuvettes containing 2 ml of culture, a high-throughput system equivalent to batch cultures, were used with gas exchange ensured by the use of a Parafilm™ cover. The effect of the different variables on maximum growth was assessed by a multi-way statistical analysis. <i>Results:</i> Temperature and pH were identified as the key factors. It was observed that <i>Synechocystis</i> cells have a strong influence on the external pH. The optimal growth temperature was 33°C while light-saturating conditions were reached at 40 µE·m<sup>–2</sup>·s<sup>–1</sup>. <i>Conclusion:</i> It was demonstrated that <i>Synechocystis</i> exhibits a marked difference in behavior between autotrophic and glucose-based mixotrophic conditions, and that nitrate concentrations did not have a significant influence, probably due to endogenous nitrogen reserves. Furthermore, a dynamic metabolic model of <i>Synechocystis</i> photosynthesis was developed to gain insights on the underlying mechanism enabling this cyanobacterium to control the levels of external pH. The model showed a coupled effect between the increase of the pH and ATP production which in turn allows a higher carbon fixation rate.

Apa Reference Lopo, M., Montagud, A., Navarro, E., Cunha, I., Zille, A., de Córdoba, P. F., Moradas-Ferreira, P., Tamagnini, P., & Urchueguía, J. F. (2012). Experimental and Modeling Analysis of &lt;i&gt; Synechocystis &lt;/i&gt;sp. PCC 6803 Growth. Microbial Physiology, 22(2), 71–82. Portico. 10.1159/000336850
Doi 10.1159/000336850
Publication Date 2012
Publication Type Article
Researcher Arnau Montagud Aquino
Ontology Metabolic modelling
Research Groups Systems Biology Modeling
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