Data from: Rerouting of carbon flux in a glycogen mutant of cyanobacteria assessed via isotopically non‐stationary 13C metabolic flux analysis
<p>Cyanobacteria, which constitute a quantitatively dominant phylum, have attracted attention in biofuel applications due to favorable physiological characteristics, high photosynthetic efficiency and amenability to genetic manipulations. However, quantitative aspects of cyanobacterial metabolism have received limited attention. In the present study, we have performed isotopically non‐stationary 13C metabolic flux analysis (INST‐13C‐MFA) to analyze rerouting of carbon in a glycogen synthase deficient mutant strain (glgA‐I glgA‐II) of the model cyanobacterium <em>Synechococcus</em> sp. PCC 7002. During balanced photoautotrophic growth, 10–20% of the fixed carbon is stored in the form of glycogen via a pathway that is conserved across the cyanobacterial phylum. Our results show that deletion of glycogen synthase gene orchestrates cascading effects on carbon distribution in various parts of the metabolic network. Carbon that was originally destined to be incorporated into glycogen gets partially diverted toward alternate storage molecules such as glucosylglycerol and sucrose. The rest is partitioned within the metabolic network, primarily via glycolysis and tricarboxylic acid cycle. A lowered flux toward carbohydrate synthesis and an altered distribution at the glucose‐1‐phosphate node indicate flexibility in the network. Further, reversibility of glycogen biosynthesis reactions points toward the presence of futile cycles. Similar redistribution of carbon was also predicted by Flux Balance Analysis. The results are significant to metabolic engineering efforts with cyanobacteria where fixed carbon needs to be re‐routed to products of interest. Biotechnol. Bioeng. 2017;114: 2298–2308. © 2017 Wiley Periodicals, Inc. </p><div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: Supporting Data S1: - Download docx.</p> <p>File Name: downloadSupplement, url: <a href="https://onlinelibrary.wiley.com/action/downloadSupplement?doi=10.1002/bit.26350&file=bit26350-sup-0001-SuppData-S1.docx">https://onlinelibrary.wiley.com/action/downloadSupplement?doi=10.1002/bit.26350&file=bit26350-sup-0001-SuppData-S1.docx</a> </p><p>SUPPLEMENTARY FIGURE 1. Dynamic labelling trajectories of measured metabolites in the wild type strain. Mass isotopomer distribution measure experimentally (data points) and the model fit using INCA (solid line). SUPPLEMENTARY FIGURE 2. Dynamic labelling trajectories of measured metabolites in the glgA-I glgA-II mutant strain. Mass isotopomer distribution measure experimentally (data points) and the model fit using INCA (solid line). SUPPLEMENTARY FIGURE 3. ATP consuming futile cycles. Selected ATP futile cycles that were observed in the flux map predicted by MOMA for the <em>glgA-I glgA-II</em> mutant. (A) Adenosine kinase (2.7.1.20) and 5’-Nucleotidase (ATP) (3.1.3.5) (B) CTP deaminase (3.5.4.13) and CTP synthase (63.4.2) (C) Diacylglycerol kinase (2.7.1.107) and Diacylglycerol pyrophosphate phosphatase (3.1.3.4) (D) 5-Formyltetrahydrofolate cyclo-ligase (6.3.3.2) and the spontaneous conversion of Methenyltetrahydrofolate to 5-Formyltetrahydrofolate. SUPPLEMENTARY TABLE 1. List of reactions and the corresponding atom transitions for the <em>Synechococcus</em> sp PCC 7002 metabolic network. SUPPLEMENTARY TABLE 2. Net fluxes estimated for the wild type strain. The flux values are normalized for a net CO2 uptake of 100mmol/gDW/hr. SUPPLEMENTARY TABLE 3. Net fluxes estimated for the <em>glgA-I glgA-II</em> mutant strain. The flux values are normalized for a net CO2 uptake of 100mmol/gDW/hr. SUPPLEMENTARY TABLE 4. Pool sizes (µmol/g-DW) estimated by INST-13C-MFA for the wild type strain. The identifiable pool sizes have finite upper bound and non-zero lower bound. The boundable pool sizes have finite upper bound and zero lower bound. SUPPLEMENTARY TABLE 5. Pool sizes (µmol/g-DW) estimated by INST-13C-MFA for the <em>glgA-I glgA-II</em> mutant strain. The identifiable pool sizes have finite upper bound and non-zero lower bound. The boundable pool sizes have finite upper bound and zero lower bound. SUPPLEMENTARY TABLE 6. The mass isotopomer distribution of measured metabolites at the experimental time points in the wild type <em>Synechococcus</em> sp PCC 7002. The metabolites marked with <em> were measured using GC-MS, while the rest were measured using LC-MS/MS. SUPPLEMENTARY TABLE 7. The mass isotopomer distribution of measured metabolites at the experimental time points in the </em>glgA-I glgA-II<em> mutant strain of Synechococcus sp PCC 7002. The metabolites marked with </em> were measured using GC-MS, while the rest were measured using LC-MS/MS</p> <p></p></li></ul><p></p>
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2018
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Subjects: | Genetics, Industrial biotechnology, carbon, stable isotopes, metabolic flux analysis, glycogen (starch) synthase, mutants, models, Cyanobacteria, Synechococcus, glycogen, biofuels, photosynthesis, genetic engineering, genes, sucrose, glycolysis, tricarboxylic acid cycle, carbohydrates, biosynthesis, metabolic engineering, metabolites, |
Online Access: | https://figshare.com/articles/dataset/Data_from_Rerouting_of_carbon_flux_in_a_glycogen_mutant_of_cyanobacteria_assessed_via_isotopically_non_stationary_13C_metabolic_flux_analysis/24852942 |
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Genetics Industrial biotechnology carbon stable isotopes metabolic flux analysis glycogen (starch) synthase mutants models Cyanobacteria Synechococcus glycogen biofuels photosynthesis genetic engineering genes sucrose glycolysis tricarboxylic acid cycle carbohydrates biosynthesis metabolic engineering metabolites |
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Genetics Industrial biotechnology carbon stable isotopes metabolic flux analysis glycogen (starch) synthase mutants models Cyanobacteria Synechococcus glycogen biofuels photosynthesis genetic engineering genes sucrose glycolysis tricarboxylic acid cycle carbohydrates biosynthesis metabolic engineering metabolites John I. Hendry (5201393) Charulata Prasannan (17480109) Fangfang Ma (1482463) K. Benedikt Möllers (17956658) Damini Jaiswa (17480115) Madhuri Digmurti (17480118) Doug K. Allen (17480121) Niels‐Ulrik Frigaard (17956661) Santanu Dasgupta (268790) Pramod P. Wangikar (7296398) Data from: Rerouting of carbon flux in a glycogen mutant of cyanobacteria assessed via isotopically non‐stationary 13C metabolic flux analysis |
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<p>Cyanobacteria, which constitute a quantitatively dominant phylum, have attracted attention in biofuel applications due to favorable physiological characteristics, high photosynthetic efficiency and amenability to genetic manipulations. However, quantitative aspects of cyanobacterial metabolism have received limited attention. In the present study, we have performed isotopically non‐stationary 13C metabolic flux analysis (INST‐13C‐MFA) to analyze rerouting of carbon in a glycogen synthase deficient mutant strain (glgA‐I glgA‐II) of the model cyanobacterium <em>Synechococcus</em> sp. PCC 7002. During balanced photoautotrophic growth, 10–20% of the fixed carbon is stored in the form of glycogen via a pathway that is conserved across the cyanobacterial phylum. Our results show that deletion of glycogen synthase gene orchestrates cascading effects on carbon distribution in various parts of the metabolic network. Carbon that was originally destined to be incorporated into glycogen gets partially diverted toward alternate storage molecules such as glucosylglycerol and sucrose. The rest is partitioned within the metabolic network, primarily via glycolysis and tricarboxylic acid cycle. A lowered flux toward carbohydrate synthesis and an altered distribution at the glucose‐1‐phosphate node indicate flexibility in the network. Further, reversibility of glycogen biosynthesis reactions points toward the presence of futile cycles. Similar redistribution of carbon was also predicted by Flux Balance Analysis. The results are significant to metabolic engineering efforts with cyanobacteria where fixed carbon needs to be re‐routed to products of interest. Biotechnol. Bioeng. 2017;114: 2298–2308. © 2017 Wiley Periodicals, Inc. </p><div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: Supporting Data S1: - Download docx.</p> <p>File Name: downloadSupplement, url: <a href="https://onlinelibrary.wiley.com/action/downloadSupplement?doi=10.1002/bit.26350&file=bit26350-sup-0001-SuppData-S1.docx">https://onlinelibrary.wiley.com/action/downloadSupplement?doi=10.1002/bit.26350&file=bit26350-sup-0001-SuppData-S1.docx</a> </p><p>SUPPLEMENTARY FIGURE 1. Dynamic labelling trajectories of measured metabolites in the wild type strain. Mass isotopomer distribution measure experimentally (data points) and the model fit using INCA (solid line).
SUPPLEMENTARY FIGURE 2. Dynamic labelling trajectories of measured metabolites in the glgA-I glgA-II mutant strain. Mass isotopomer distribution measure experimentally (data points) and the model fit using INCA (solid line).
SUPPLEMENTARY FIGURE 3. ATP consuming futile cycles. Selected ATP futile cycles that were observed in the flux map predicted by MOMA for the <em>glgA-I glgA-II</em> mutant. (A) Adenosine kinase (2.7.1.20) and 5’-Nucleotidase (ATP) (3.1.3.5) (B) CTP deaminase (3.5.4.13) and CTP synthase (63.4.2) (C) Diacylglycerol kinase (2.7.1.107) and Diacylglycerol pyrophosphate phosphatase (3.1.3.4) (D) 5-Formyltetrahydrofolate cyclo-ligase (6.3.3.2) and the spontaneous conversion of Methenyltetrahydrofolate to 5-Formyltetrahydrofolate.
SUPPLEMENTARY TABLE 1. List of reactions and the corresponding atom transitions for the <em>Synechococcus</em> sp PCC 7002 metabolic network.
SUPPLEMENTARY TABLE 2. Net fluxes estimated for the wild type strain. The flux values are normalized for a net CO2 uptake of 100mmol/gDW/hr.
SUPPLEMENTARY TABLE 3. Net fluxes estimated for the <em>glgA-I glgA-II</em> mutant strain. The flux values are normalized for a net CO2 uptake of 100mmol/gDW/hr.
SUPPLEMENTARY TABLE 4. Pool sizes (µmol/g-DW) estimated by INST-13C-MFA for the wild type strain. The identifiable pool sizes have finite upper bound and non-zero lower bound. The boundable pool sizes have finite upper bound and zero lower bound.
SUPPLEMENTARY TABLE 5. Pool sizes (µmol/g-DW) estimated by INST-13C-MFA for the <em>glgA-I glgA-II</em> mutant strain. The identifiable pool sizes have finite upper bound and non-zero lower bound. The boundable pool sizes have finite upper bound and zero lower bound.
SUPPLEMENTARY TABLE 6. The mass isotopomer distribution of measured metabolites at the experimental time points in the wild type <em>Synechococcus</em> sp PCC 7002. The metabolites marked with <em> were measured using GC-MS, while the rest were measured using LC-MS/MS.
SUPPLEMENTARY TABLE 7. The mass isotopomer distribution of measured metabolites at the experimental time points in the </em>glgA-I glgA-II<em> mutant strain of Synechococcus sp PCC 7002. The metabolites marked with </em> were measured using GC-MS, while the rest were measured using LC-MS/MS</p>
<p></p></li></ul><p></p> |
format |
Dataset |
author |
John I. Hendry (5201393) Charulata Prasannan (17480109) Fangfang Ma (1482463) K. Benedikt Möllers (17956658) Damini Jaiswa (17480115) Madhuri Digmurti (17480118) Doug K. Allen (17480121) Niels‐Ulrik Frigaard (17956661) Santanu Dasgupta (268790) Pramod P. Wangikar (7296398) |
author_facet |
John I. Hendry (5201393) Charulata Prasannan (17480109) Fangfang Ma (1482463) K. Benedikt Möllers (17956658) Damini Jaiswa (17480115) Madhuri Digmurti (17480118) Doug K. Allen (17480121) Niels‐Ulrik Frigaard (17956661) Santanu Dasgupta (268790) Pramod P. Wangikar (7296398) |
author_sort |
John I. Hendry (5201393) |
title |
Data from: Rerouting of carbon flux in a glycogen mutant of cyanobacteria assessed via isotopically non‐stationary 13C metabolic flux analysis |
title_short |
Data from: Rerouting of carbon flux in a glycogen mutant of cyanobacteria assessed via isotopically non‐stationary 13C metabolic flux analysis |
title_full |
Data from: Rerouting of carbon flux in a glycogen mutant of cyanobacteria assessed via isotopically non‐stationary 13C metabolic flux analysis |
title_fullStr |
Data from: Rerouting of carbon flux in a glycogen mutant of cyanobacteria assessed via isotopically non‐stationary 13C metabolic flux analysis |
title_full_unstemmed |
Data from: Rerouting of carbon flux in a glycogen mutant of cyanobacteria assessed via isotopically non‐stationary 13C metabolic flux analysis |
title_sort |
data from: rerouting of carbon flux in a glycogen mutant of cyanobacteria assessed via isotopically non‐stationary 13c metabolic flux analysis |
publishDate |
2018 |
url |
https://figshare.com/articles/dataset/Data_from_Rerouting_of_carbon_flux_in_a_glycogen_mutant_of_cyanobacteria_assessed_via_isotopically_non_stationary_13C_metabolic_flux_analysis/24852942 |
work_keys_str_mv |
AT johnihendry5201393 datafromreroutingofcarbonfluxinaglycogenmutantofcyanobacteriaassessedviaisotopicallynonstationary13cmetabolicfluxanalysis AT charulataprasannan17480109 datafromreroutingofcarbonfluxinaglycogenmutantofcyanobacteriaassessedviaisotopicallynonstationary13cmetabolicfluxanalysis AT fangfangma1482463 datafromreroutingofcarbonfluxinaglycogenmutantofcyanobacteriaassessedviaisotopicallynonstationary13cmetabolicfluxanalysis AT kbenediktmollers17956658 datafromreroutingofcarbonfluxinaglycogenmutantofcyanobacteriaassessedviaisotopicallynonstationary13cmetabolicfluxanalysis AT daminijaiswa17480115 datafromreroutingofcarbonfluxinaglycogenmutantofcyanobacteriaassessedviaisotopicallynonstationary13cmetabolicfluxanalysis AT madhuridigmurti17480118 datafromreroutingofcarbonfluxinaglycogenmutantofcyanobacteriaassessedviaisotopicallynonstationary13cmetabolicfluxanalysis AT dougkallen17480121 datafromreroutingofcarbonfluxinaglycogenmutantofcyanobacteriaassessedviaisotopicallynonstationary13cmetabolicfluxanalysis AT nielsulrikfrigaard17956661 datafromreroutingofcarbonfluxinaglycogenmutantofcyanobacteriaassessedviaisotopicallynonstationary13cmetabolicfluxanalysis AT santanudasgupta268790 datafromreroutingofcarbonfluxinaglycogenmutantofcyanobacteriaassessedviaisotopicallynonstationary13cmetabolicfluxanalysis AT pramodpwangikar7296398 datafromreroutingofcarbonfluxinaglycogenmutantofcyanobacteriaassessedviaisotopicallynonstationary13cmetabolicfluxanalysis |
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dat-usda-us-article248529422018-09-13T00:00:00Z Data from: Rerouting of carbon flux in a glycogen mutant of cyanobacteria assessed via isotopically non‐stationary 13C metabolic flux analysis John I. Hendry (5201393) Charulata Prasannan (17480109) Fangfang Ma (1482463) K. Benedikt Möllers (17956658) Damini Jaiswa (17480115) Madhuri Digmurti (17480118) Doug K. Allen (17480121) Niels‐Ulrik Frigaard (17956661) Santanu Dasgupta (268790) Pramod P. Wangikar (7296398) Genetics Industrial biotechnology carbon stable isotopes metabolic flux analysis glycogen (starch) synthase mutants models Cyanobacteria Synechococcus glycogen biofuels photosynthesis genetic engineering genes sucrose glycolysis tricarboxylic acid cycle carbohydrates biosynthesis metabolic engineering metabolites <p>Cyanobacteria, which constitute a quantitatively dominant phylum, have attracted attention in biofuel applications due to favorable physiological characteristics, high photosynthetic efficiency and amenability to genetic manipulations. However, quantitative aspects of cyanobacterial metabolism have received limited attention. In the present study, we have performed isotopically non‐stationary 13C metabolic flux analysis (INST‐13C‐MFA) to analyze rerouting of carbon in a glycogen synthase deficient mutant strain (glgA‐I glgA‐II) of the model cyanobacterium <em>Synechococcus</em> sp. PCC 7002. During balanced photoautotrophic growth, 10–20% of the fixed carbon is stored in the form of glycogen via a pathway that is conserved across the cyanobacterial phylum. Our results show that deletion of glycogen synthase gene orchestrates cascading effects on carbon distribution in various parts of the metabolic network. Carbon that was originally destined to be incorporated into glycogen gets partially diverted toward alternate storage molecules such as glucosylglycerol and sucrose. The rest is partitioned within the metabolic network, primarily via glycolysis and tricarboxylic acid cycle. A lowered flux toward carbohydrate synthesis and an altered distribution at the glucose‐1‐phosphate node indicate flexibility in the network. Further, reversibility of glycogen biosynthesis reactions points toward the presence of futile cycles. Similar redistribution of carbon was also predicted by Flux Balance Analysis. The results are significant to metabolic engineering efforts with cyanobacteria where fixed carbon needs to be re‐routed to products of interest. Biotechnol. Bioeng. 2017;114: 2298–2308. © 2017 Wiley Periodicals, Inc. </p><div><br>Resources in this dataset:</div><br><ul><li><p>Resource Title: Supporting Data S1: - Download docx.</p> <p>File Name: downloadSupplement, url: <a href="https://onlinelibrary.wiley.com/action/downloadSupplement?doi=10.1002/bit.26350&file=bit26350-sup-0001-SuppData-S1.docx">https://onlinelibrary.wiley.com/action/downloadSupplement?doi=10.1002/bit.26350&file=bit26350-sup-0001-SuppData-S1.docx</a> </p><p>SUPPLEMENTARY FIGURE 1. Dynamic labelling trajectories of measured metabolites in the wild type strain. Mass isotopomer distribution measure experimentally (data points) and the model fit using INCA (solid line). SUPPLEMENTARY FIGURE 2. Dynamic labelling trajectories of measured metabolites in the glgA-I glgA-II mutant strain. Mass isotopomer distribution measure experimentally (data points) and the model fit using INCA (solid line). SUPPLEMENTARY FIGURE 3. ATP consuming futile cycles. Selected ATP futile cycles that were observed in the flux map predicted by MOMA for the <em>glgA-I glgA-II</em> mutant. (A) Adenosine kinase (2.7.1.20) and 5’-Nucleotidase (ATP) (3.1.3.5) (B) CTP deaminase (3.5.4.13) and CTP synthase (63.4.2) (C) Diacylglycerol kinase (2.7.1.107) and Diacylglycerol pyrophosphate phosphatase (3.1.3.4) (D) 5-Formyltetrahydrofolate cyclo-ligase (6.3.3.2) and the spontaneous conversion of Methenyltetrahydrofolate to 5-Formyltetrahydrofolate. SUPPLEMENTARY TABLE 1. List of reactions and the corresponding atom transitions for the <em>Synechococcus</em> sp PCC 7002 metabolic network. SUPPLEMENTARY TABLE 2. Net fluxes estimated for the wild type strain. The flux values are normalized for a net CO2 uptake of 100mmol/gDW/hr. SUPPLEMENTARY TABLE 3. Net fluxes estimated for the <em>glgA-I glgA-II</em> mutant strain. The flux values are normalized for a net CO2 uptake of 100mmol/gDW/hr. SUPPLEMENTARY TABLE 4. Pool sizes (µmol/g-DW) estimated by INST-13C-MFA for the wild type strain. The identifiable pool sizes have finite upper bound and non-zero lower bound. The boundable pool sizes have finite upper bound and zero lower bound. SUPPLEMENTARY TABLE 5. Pool sizes (µmol/g-DW) estimated by INST-13C-MFA for the <em>glgA-I glgA-II</em> mutant strain. The identifiable pool sizes have finite upper bound and non-zero lower bound. The boundable pool sizes have finite upper bound and zero lower bound. SUPPLEMENTARY TABLE 6. The mass isotopomer distribution of measured metabolites at the experimental time points in the wild type <em>Synechococcus</em> sp PCC 7002. The metabolites marked with <em> were measured using GC-MS, while the rest were measured using LC-MS/MS. SUPPLEMENTARY TABLE 7. The mass isotopomer distribution of measured metabolites at the experimental time points in the </em>glgA-I glgA-II<em> mutant strain of Synechococcus sp PCC 7002. The metabolites marked with </em> were measured using GC-MS, while the rest were measured using LC-MS/MS</p> <p></p></li></ul><p></p> 2018-09-13T00:00:00Z Dataset Dataset 10.1002/bit.26350 https://figshare.com/articles/dataset/Data_from_Rerouting_of_carbon_flux_in_a_glycogen_mutant_of_cyanobacteria_assessed_via_isotopically_non_stationary_13C_metabolic_flux_analysis/24852942 CC BY 4.0 |