Séminaire
The potential offered by cyanobacteria will undoubtedly play a major role in mastering the challenges of the 21st century – from securing global food supply to the synthesis of renewable raw materials. As yet, however, fundamental questions regarding the metabolic principles of cyanobacterial phototrophic growth are not resolved: How are metabolic, photosynthetic, and ribosomal proteins optimally partitioned during phototrophic growth? What is the highest growth rate a cyanobacterium can attain?
The presentation will describe our recent efforts to answer these questions using experimental and constraint-based computational models: we describe phototrophic growth as a cellular resource allocation problem and estimate the costs and benefits of all metabolic constituents of a cyanobacterial cell. Of particular interest are the cellular organization that enables fast phototrophic growth and the corresponding intracellular limits on growth rates. The model-derived resource allocation is in good agreement with experimental findings. I will provide an outlook how such analyses has implications for ecology and models of global biogeochemical cycles.
References:
[1] Zavřel T(*), Faizi M, Loureiro C, Poschmann G, Stühler K, Sinetova M, Zorina A, Steuer R(*), Červený J (2019) Quantitative insights into the cyanobacterial cell economy. eLife [* corresponding authors]
[2] Faizi M, Zavrel T, Loureiro C, Cerveny J, Steuer R (2018) A model of optimal protein allocation during phototrophic growth. Biosystems 166, 26-36.
[3] Reimers AM, Knoop H, Bockmayr A, Steuer R (2017) Cellular trade-offs and optimal resource allocation during cyanobacterial diurnal growth. Proc Natl Acad Sci U S A. Pii: 201617508.
[4] Westermark S and Steuer R (2016) Toward multiscale models of cyanobacterial growth: a modular approach. Front. Bioeng. Biotechnol. 4:95.
[5] Knoop H, Gruendel M, Zilliges Y, Lehmann R, Hoffmann S, Lockau W, Steuer R (2013) Flux balance analysis of cyanobacterial metabolism: The metabolic network of Synechocystis sp. PCC 6803. PLoS Comput Biol 9(6): e1003081.