14:25 〜 14:45
[BBG01-03] Cyanobacteria overflow metabolism: shedding light on the diversification of an ancient clade throughout Earth’s history
★Invited Papers
キーワード：Cyanobacteria, Photosynthesis, Metabolomics, Metabolic Modeling
Cyanobacteria have played a pivotal role throughout Earth’s history, converting CO2 and water into organic matter and oxygen, which in turn have shaped the evolution of Earth’s geo- and biosphere.
Today, there is a wide morphological diversity across the almost 400 genera within the class Cyanobacteriia. Given oxygen generation is a common feature across all of them, there must be another, overlooked factor that drove the diversification of the clade from its emergence: we hypothesize that Cyanobacterias’ abilities to synthesize and secrete organic compounds vary among phylogenetic groups and that this metabolic diversification has been a key evolutionary trajectory in the clade’s species diversification, in turn leading to the biogeochemical alteration of Earth’s environments.
Here, we propose to use a combination of wet lab (cultivation & metabolomics) and computational (metabolic modeling & phylogenetics) tools to quantify extant Cyanobacteria’s metabolomic profiles and reconstruct the ancient exometabolome to uncover the relationship between species and metabolic diversification.
Our chemical analyses of the extracellular metabolomes of Cyanobacteria show that the organisms’ exometabolomes are different between strains, and that there are associations between morphologies (filamentous versus non-filamentous strains) and their metabolites, opening up questions about the importance of extracellular organics in the evolution of morphological diversity.
We then use this metabolite data to inform genome scale metabolic models of selected strains. The computational simulation of metabolism using genome scale models enables us to identify the intracellular pathways that are up- or downregulated with different substrate availability. Using this approach, we can compute the metabolic states of Cyanobacteria in ancient Earth environments and infer at which growth conditions and thus timepoints certain biosynthetic pathways may have become important for their ecological niche.
Metabolic models offer the opportunity to understand microbial growth under a variety of environmental conditions prior to or without cultivation. In the future, our experimentally constrained models may be used to simulate growth under a variety of environmental conditions mimicking both past and future environments, to further help us understand how Cyanobacteria contribute organic materials to their environment and trigger or respond to chemical changes of their environment.
Today, there is a wide morphological diversity across the almost 400 genera within the class Cyanobacteriia. Given oxygen generation is a common feature across all of them, there must be another, overlooked factor that drove the diversification of the clade from its emergence: we hypothesize that Cyanobacterias’ abilities to synthesize and secrete organic compounds vary among phylogenetic groups and that this metabolic diversification has been a key evolutionary trajectory in the clade’s species diversification, in turn leading to the biogeochemical alteration of Earth’s environments.
Here, we propose to use a combination of wet lab (cultivation & metabolomics) and computational (metabolic modeling & phylogenetics) tools to quantify extant Cyanobacteria’s metabolomic profiles and reconstruct the ancient exometabolome to uncover the relationship between species and metabolic diversification.
Our chemical analyses of the extracellular metabolomes of Cyanobacteria show that the organisms’ exometabolomes are different between strains, and that there are associations between morphologies (filamentous versus non-filamentous strains) and their metabolites, opening up questions about the importance of extracellular organics in the evolution of morphological diversity.
We then use this metabolite data to inform genome scale metabolic models of selected strains. The computational simulation of metabolism using genome scale models enables us to identify the intracellular pathways that are up- or downregulated with different substrate availability. Using this approach, we can compute the metabolic states of Cyanobacteria in ancient Earth environments and infer at which growth conditions and thus timepoints certain biosynthetic pathways may have become important for their ecological niche.
Metabolic models offer the opportunity to understand microbial growth under a variety of environmental conditions prior to or without cultivation. In the future, our experimentally constrained models may be used to simulate growth under a variety of environmental conditions mimicking both past and future environments, to further help us understand how Cyanobacteria contribute organic materials to their environment and trigger or respond to chemical changes of their environment.