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groups:steuer:research [2016/12/09 16:49] – [Understanding Phototrophic Growth] steuergroups:steuer:research [2024/10/07 15:35] (current) – [Main Research Themes] steuer
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 ====== Main Research Themes ====== ====== Main Research Themes ======
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 +** This page is no longer maintained. Please visit: https://research.uni-leipzig.de/physics-of-evolution/ **
  
 ==== Understanding Phototrophic Growth ====  ==== Understanding Phototrophic Growth ==== 
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 We are interested in the organization and functioning of cyanobacterial metabolism. We are interested in the organization and functioning of cyanobacterial metabolism.
 Key research questions include the stoichiometric reconstruction of cyanobacterial metabolism, its comparison across different strains, the coordination of cyanobacterial metabolism in dynamic environments, in particular diurnal cycles, as well as resource allocation problems in dynamic metabolic networks.   Key research questions include the stoichiometric reconstruction of cyanobacterial metabolism, its comparison across different strains, the coordination of cyanobacterial metabolism in dynamic environments, in particular diurnal cycles, as well as resource allocation problems in dynamic metabolic networks.  
 +We are interested in fast growth of cyanobacteria and investigate the limits of phototrophic growth using computational methods. 
  
 **Further reading:**  **Further reading:** 
-  * Ruegen M, Bockmayr A, Steuer R.  (2015) **[[http://www.ncbi.nlm.nih.gov/pubmed/26496972|Elucidating temporal resource allocation and diurnal dynamics in phototrophic metabolism using conditional FBA]]**  +  * Westermark S and Steuer R (2016) **[[http://journal.frontiersin.org/article/10.3389/fbioe.2016.00095/|Toward Multiscale Models of Cyanobacterial Growth: A Modular Approach.]]** Front. Bioeng. Biotechnol. 4:95. doi: 10.3389/fbioe.2016.00095 
-Sci Rep. 2015 Oct 26;5:15247. doi: 10.1038/srep15247. +  * Reimers AM, Knoop H, Bockmayr A, Steuer R.​ (2017) **[[https://www.ncbi.nlm.nih.gov/pubmed/28720699|Cellular trade-offs and optimal resource allocation during cyanobacterial diurnal growth.]]** Proc Natl Acad Sci U S A. pii: 201617508. doi: 10.1073/pnas.1617508114. 
-  * H. Knoop, M. Gruendel, Y. Zilliges, R. Lehmann, S. Hoffmann, W. Lockau, R. Steuer. (2013) **[[http://www.ncbi.nlm.nih.gov/pubmed/23843751|Flux Balance Analysis of Cyanobacterial Metabolism: The metabolic network of Synechocystis sp. PCC 6803.]]** PLoS Comput Biol 9(6): e1003081. doi:10.1371/journal.pcbi.1003081 +  * H. Knoop, M. Gruendel, Y. Zilliges, R. Lehmann, S. Hoffmann, W. Lockau, R. Steuer. (2013) **[[http://www.ncbi.nlm.nih.gov/pubmed/23843751|Flux Balance Analysis of Cyanobacterial Metabolism: The metabolic network of Synechocystis sp. PCC 6803.]]** PLoS Comput Biol 9(6): e1003081. doi:10.1371/journal.pcbi.1003081 \\
-  * R. Steuer, H. Knoop, R. Machne (2012) **[[http://www.ncbi.nlm.nih.gov/pubmed/22450165|Modelling cyanobacteria: from metabolism to integrative models of phototrophic growth.]]** Journal of Experimental Botany 63(6):2259-74. doi:10.1093/jxb/ers018 \\+
  
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 Cyanobacteria have attracted growing attention as potential host organisms for the production of valuable organic products. We develop computational methods to facilitate and enhance production of renewable bulk products using cyanobacteria. The aim is to integrate photosynthetic solar energy conversion and product formation, including engine-ready fuels, in a single biological process.  Cyanobacteria have attracted growing attention as potential host organisms for the production of valuable organic products. We develop computational methods to facilitate and enhance production of renewable bulk products using cyanobacteria. The aim is to integrate photosynthetic solar energy conversion and product formation, including engine-ready fuels, in a single biological process. 
 Past target products are ethanol (in collaboration with several academic and industrial partners, including Algenol Deutschland GmbH), as well as short chain (propane) and medium chain alkanes.  Past target products are ethanol (in collaboration with several academic and industrial partners, including Algenol Deutschland GmbH), as well as short chain (propane) and medium chain alkanes. 
-High-quality reconstructions of cyanobacterial metabolism are used to guide and support experimental efforts to increase and sustain product yield in cyanobacteria. +High-quality reconstructions of cyanobacterial metabolism are used to guide and support experimental efforts to increase and sustain product yield in cyanobacteria. The group participated in launching a start-up company to commercialize cultivation of cyanobacteria and microalgae at ultra-high densities ([[http://www.celldeg.com|www.celldeg.com]]).
  
 **Further reading:**  **Further reading:** 
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-==== Dynamics in Large-Scale Metabolic Networks ====+==== The Nonlinear Dynamics of Metabolism ====
 {{groups/steuer/metabolism_control01.jpeg?nolink&150 }}  {{groups/steuer/metabolism_control01.jpeg?nolink&150 }} 
 One of the most challenging goals of computational systems biology is the development of large-scale kinetic models of cellular pathways. However, for most cellular networks, detailed kinetic modeling is not possible due to lack of knowledge kinetic parameters. To overcome some of these problems, we are interested in novel methods that allow the elucidation of large-scale metabolic networks in the face of uncertain and incomplete information. Recent work includes novel approaches that provide a bridge between stoichiometric analysis and explicit kinetic simulations. Without requiring knowledge about the explicit functional form of the kinetic rate equations and parameters, these methods seek to describe the possible dynamics of cellular networks. One of the most challenging goals of computational systems biology is the development of large-scale kinetic models of cellular pathways. However, for most cellular networks, detailed kinetic modeling is not possible due to lack of knowledge kinetic parameters. To overcome some of these problems, we are interested in novel methods that allow the elucidation of large-scale metabolic networks in the face of uncertain and incomplete information. Recent work includes novel approaches that provide a bridge between stoichiometric analysis and explicit kinetic simulations. Without requiring knowledge about the explicit functional form of the kinetic rate equations and parameters, these methods seek to describe the possible dynamics of cellular networks.