TY - JOUR
T1 - Responses of Synechocystis sp. PCC 6803 to heterologous biosynthetic pathways
AU - Vavitsas, Konstantinos
AU - Rue, Emil Østergaard
AU - Stefánsdóttir, Lára Kristín
AU - Gnanasekaran, Thiyagarajan
AU - Blennow, Andreas
AU - Crocoll, Christoph
AU - Gudmundsson, Steinn
AU - Jensen, Poul Erik
PY - 2017
Y1 - 2017
N2 - BACKGROUND: There are an increasing number of studies regarding genetic manipulation of cyanobacteria to produce commercially interesting compounds. The majority of these works study the expression and optimization of a selected heterologous pathway, largely ignoring the wholeness and complexity of cellular metabolism. Regulation and response mechanisms are largely unknown, and even the metabolic pathways themselves are not fully elucidated. This poses a clear limitation in exploiting the rich biosynthetic potential of cyanobacteria.RESULTS: In this work, we focused on the production of two different compounds, the cyanogenic glucoside dhurrin and the diterpenoid 13R-manoyl oxide in Synechocystis PCC 6803. We used genome-scale metabolic modelling to study fluxes in individual reactions and pathways, and we determined the concentrations of key metabolites, such as amino acids, carotenoids, and chlorophylls. This allowed us to identify metabolic crosstalk between the native and the introduced metabolic pathways. Most results and simulations highlight the metabolic robustness of cyanobacteria, suggesting that the host organism tends to keep metabolic fluxes and metabolite concentrations steady, counteracting the effects of the heterologous pathway. However, the amino acid concentrations of the dhurrin-producing strain show an unexpected profile, where the perturbation levels were high in seemingly unrelated metabolites.CONCLUSIONS: There is a wealth of information that can be derived by combining targeted metabolite identification and computer modelling as a frame of understanding. Here we present an example of how strain engineering approaches can be coupled to 'traditional' metabolic engineering with systems biology, resulting in novel and more efficient manipulation strategies.
AB - BACKGROUND: There are an increasing number of studies regarding genetic manipulation of cyanobacteria to produce commercially interesting compounds. The majority of these works study the expression and optimization of a selected heterologous pathway, largely ignoring the wholeness and complexity of cellular metabolism. Regulation and response mechanisms are largely unknown, and even the metabolic pathways themselves are not fully elucidated. This poses a clear limitation in exploiting the rich biosynthetic potential of cyanobacteria.RESULTS: In this work, we focused on the production of two different compounds, the cyanogenic glucoside dhurrin and the diterpenoid 13R-manoyl oxide in Synechocystis PCC 6803. We used genome-scale metabolic modelling to study fluxes in individual reactions and pathways, and we determined the concentrations of key metabolites, such as amino acids, carotenoids, and chlorophylls. This allowed us to identify metabolic crosstalk between the native and the introduced metabolic pathways. Most results and simulations highlight the metabolic robustness of cyanobacteria, suggesting that the host organism tends to keep metabolic fluxes and metabolite concentrations steady, counteracting the effects of the heterologous pathway. However, the amino acid concentrations of the dhurrin-producing strain show an unexpected profile, where the perturbation levels were high in seemingly unrelated metabolites.CONCLUSIONS: There is a wealth of information that can be derived by combining targeted metabolite identification and computer modelling as a frame of understanding. Here we present an example of how strain engineering approaches can be coupled to 'traditional' metabolic engineering with systems biology, resulting in novel and more efficient manipulation strategies.
KW - Journal Article
U2 - 10.1186/s12934-017-0757-y
DO - 10.1186/s12934-017-0757-y
M3 - Journal article
C2 - 28806958
VL - 16
JO - Microbial Cell
JF - Microbial Cell
SN - 1475-2859
IS - 1
M1 - 140
ER -