Quantitative insights into the cyanobacterial cell economy

0522763 - ÚVGZ 2020 US eng A - Abstract
Zavřel, Tomáš - Faizi, M. - Loureiro, C. - Poschmann, G. - Stühler, K. - Sinětova, Maria A. - Zorina, A. - Steuer, R. - Červený, Jan
Quantitative insights into the cyanobacterial cell economy.
Program and Abstracts 13th Workshop on Cyanobacteria. Boulder: Univesity of Colorado, Boulder, CO, USA, 2019 - (Jianping, .; Cameron, J.; Dawson, C.). s. 98-99
[13th Workshop on Cyanobacteria. 06.06.2019-09.06.2019, Boulder]
Keywords : cyanobacteria

Despite the importance of cyanobacteria as photosynthetic model organisms and as host organisms for green biotechnology, as yet only few studies have addressed quantitative growth properties and resource allocation even for well characterized model strains. Here, we provide a quantitative analysis of light-limited, light-saturated, and light-inhibited growth of the cyanobacterium Synechocystis sp. PCC 6803 using a reproducible cultivation setup. We focused on light as the only variable environmental parameter – and identified trends in key physiological parameters, including growth rate, cell size, photosynthetic activity as well as proteome allocation as a function of growth rate. The interpretation of data was facilitated by a coarse-grained computational model of cyanobacterial resource allocation. Overall, the resulting growth laws (decrease of proteome fraction associated with light harvesting and increase of proteome fraction associated with translation with increasing light intensity and growth rate) are in good agreement with previous theoretical and experimental studies, whereas the observed invariance of the proteome fraction associated with metabolic processes differed from model predictions. Light, however, is not the only factor that affects photoautotrophic growth. Further studies are required to identify growth limitation under different environmental conditions, in particular limitations induced by other biotechnologically or environmentally relevant macro- or micronutrients. The proposed reproducible cultivation setup and the coarse-grained computational model used in this study provide a suitable framework and reference to facilitate and to contribute to such studies.
Permanent Link: http://hdl.handle.net/11104/0307205