Literature DB >> 30552197

Genome-Scale Fluxome of Synechococcus elongatus UTEX 2973 Using Transient 13C-Labeling Data.

John I Hendry1, Saratram Gopalakrishnan1, Justin Ungerer2, Himadri B Pakrasi2, Yinjie J Tang3, Costas D Maranas4.   

Abstract

Synechococcus elongatus UTEX 2973 (Synechococcus 2973) has the shortest reported doubling time (2.1 h) among cyanobacteria, making it a promising platform for the solar-based production of biochemicals. In this meta-analysis, its intracellular flux distribution was recomputed using genome-scale isotopic nonstationary 13C-metabolic flux analysis given the labeling dynamics of 13 metabolites reported in an earlier study. To achieve this, a genome-scale mapping model, namely imSyu593, was constructed using the imSyn617 mapping model for Synechocystis sp. PCC 6803 (Synechocystis 6803) as the starting point encompassing 593 reactions. The flux elucidation revealed nearly complete conversion (greater than 96%) of the assimilated carbon into biomass in Synechococcus 2973. In contrast, Synechocystis 6803 achieves complete conversion of only 86% of the assimilated carbon. This high biomass yield was enabled by the reincorporation of the fixed carbons lost in anabolic and photorespiratory pathways in conjunction with flux rerouting through a nondecarboxylating reaction such as phosphoketolase. This reincorporation of lost CO2 sustains a higher flux through the photorespiratory C2 cycle that fully meets the glycine and serine demands for growth. In accordance with the high carbon efficiency drive, acetyl-coenzyme A was entirely produced using the carbon-efficient phosphoketolase pathway. Comparison of the Synechococcus 2973 flux map with that of Synechocystis 6803 revealed differences in the use of Calvin cycle and photorespiratory pathway reactions. The two species used different reactions for the synthesis of metabolites such as fructose-6-phosphate, glycine, sedoheptulose-7-phosphate, and Ser. These findings allude to a highly carbon-efficient metabolism alongside the fast carbon uptake rate in Synechococcus 2973, which explains its faster growth rate.
© 2019 American Society of Plant Biologists. All Rights Reserved.

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Year:  2018        PMID: 30552197      PMCID: PMC6367904          DOI: 10.1104/pp.18.01357

Source DB:  PubMed          Journal:  Plant Physiol        ISSN: 0032-0889            Impact factor:   8.340


  40 in total

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3.  Elementary metabolite units (EMU): a novel framework for modeling isotopic distributions.

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4.  Comparative genomics reveals the molecular determinants of rapid growth of the cyanobacterium Synechococcus elongatus UTEX 2973.

Authors:  Justin Ungerer; Kristen E Wendt; John I Hendry; Costas D Maranas; Himadri B Pakrasi
Journal:  Proc Natl Acad Sci U S A       Date:  2018-11-08       Impact factor: 11.205

5.  Isotopically nonstationary 13C flux analysis of cyanobacterial isobutyraldehyde production.

Authors:  Lara J Jazmin; Yao Xu; Yi Ern Cheah; Adeola O Adebiyi; Carl Hirschie Johnson; Jamey D Young
Journal:  Metab Eng       Date:  2017-05-04       Impact factor: 9.783

6.  Mapping photoautotrophic metabolism with isotopically nonstationary (13)C flux analysis.

Authors:  Jamey D Young; Avantika A Shastri; Gregory Stephanopoulos; John A Morgan
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7.  Stereochemically consistent reaction mapping and identification of multiple reaction mechanisms through integer linear optimization.

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8.  Genome-based metabolic mapping and 13C flux analysis reveal systematic properties of an oleaginous microalga Chlorella protothecoides.

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Authors:  Trang T Vu; Sergey M Stolyar; Grigoriy E Pinchuk; Eric A Hill; Leo A Kucek; Roslyn N Brown; Mary S Lipton; Andrei Osterman; Jim K Fredrickson; Allan E Konopka; Alexander S Beliaev; Jennifer L Reed
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10.  Adjustments to Photosystem Stoichiometry and Electron Transfer Proteins Are Key to the Remarkably Fast Growth of the Cyanobacterium Synechococcus elongatus UTEX 2973.

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3.  Parallel isotope differential modeling for instationary 13C fluxomics at the genome scale.

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4.  Expression and secretion of a lytic polysaccharide monooxygenase by a fast-growing cyanobacterium.

Authors:  D A Russo; J A Z Zedler; D N Wittmann; B Möllers; R K Singh; T S Batth; B van Oort; J V Olsen; M J Bjerrum; P E Jensen
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Review 5.  State-of-the-Art Genetic Modalities to Engineer Cyanobacteria for Sustainable Biosynthesis of Biofuel and Fine-Chemicals to Meet Bio-Economy Challenges.

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6.  Improved Salt Tolerance and Metabolomics Analysis of Synechococcus elongatus UTEX 2973 by Overexpressing Mrp Antiporters.

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8.  A Hybrid Flux Balance Analysis and Machine Learning Pipeline Elucidates Metabolic Adaptation in Cyanobacteria.

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9.  From Escherichia coli mutant 13C labeling data to a core kinetic model: A kinetic model parameterization pipeline.

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10.  Pooled CRISPRi screening of the cyanobacterium Synechocystis sp PCC 6803 for enhanced industrial phenotypes.

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