Metabolic flux analysis in biotechnology processes

Iwatani, Shintaro; Yamada, Yohei; Usuda, Yoshihiro

doi:10.1007/s10529-008-9633-5

Cited by 54 publications

(27 citation statements)

References 51 publications

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“…As a powerful tool for evaluating metabolic distribution within cells, intracellular flux analysis has been applied to many microbial cultures for the purpose of improvement of production processes (Vallino and Stephanopoulos 1993;Shi et al 1997;Melzer et al 2007;Iwatani et al 2008). Knowledge of intracellular flux distributions under different conditions makes it possible to understand the fundamental metabolism in detail and gives useful information which can be applied to bioreactor design and control strategies of culture systems.…”

Section: Introductionmentioning

confidence: 99%

Carbon metabolism and energy conversion of Synechococcus sp. PCC 7942 under mixotrophic conditions: comparison with photoautotrophic condition

et al. 2011

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To investigate the carbon metabolism and energy conversion efficiency of the cyanobacterium Synechococcus sp. PCC 7942 under mixotrophic conditions, we studied its growth characteristics in mixotrophic cultures with glucose and with acetate, respectively, and further discussed the carbon metabolism and energy utilization based on metabolic flux analysis. Results showed that both glucose and acetate could enhance the growth of Synechococcus sp. PCC 7942. The metabolic flux through the glycolytic pathway, tricarboxylic acid cycle, and mitochondrial oxidative phosphorylation was affected by the two organic substrates. Additionally, the cellular composition was also modulated by glucose and acetate. Under mixotrophic conditions, glucose exerts more significant impact on the diminishment of photochemical efficiency. Although the contribution of light energy was smaller, the cell yields based on total energy in mixotrophic cultures were higher compared with that of photoautotrophic one. On the basis of chlorophyll fluorescence analysis, the actual energy conversion efficiencies based on ATP synthesis in the photoautotrophic, glucose-mixotrophic, and acetatemixotrophic cultures were evaluated to be 4.59%, 5.86%, and 6.60%, respectively. Keywords Synechococcus sp. PCC 7942 . Mixotrophic cultivation . Carbon metabolism . Energy conversion . Metabolic flux analysis . Chlorophyll fluorescence analysis Nomenclature a ij Stoichiometric coefficient of metabolite i in the jth reaction (−) A m×nMatrix of stoichiometric coefficient (−) A 0 Side area of flask receiving incident light (m 2 ) E abLight energy absorbed by the biomass unit (kJ g −1 h −1 ) E P Actual light energy for photosynthesis (kJ g −1 h −1 ) E C Chemical energy received from organic carbon resources (kJ g −1 h −1 ) E C,ACE Chemical energy originated from acetate (kJ g −1 h −1 ) E C,GLC Chemical energy originated from glucoseThe total absorbed energy (kJ g −1 h −1 ) I 0 Incident light intensity (μmol m− 2 s −1 ) K a Effective absorption coefficient of light (m −1 ) rVector of m-dimensional metabolite accumulation rate (mmol g −1 h −1 ) r ATP Relative rate of ATP synthesized (mmol g −1 h −1 ) r ACE Relative rate of acetate consumption (mmol g −1 h −1 ) r ex Subvector of extracellular metabolite accumulation rate (mmol g −1 h −1 )Relative rate of glucose consumption (mmol g −1 h −1 ) r i Accumulation rate of metabolite i (mmol g −1 h −1 ) r in Subvector of intracellular metabolite accumulation rate (mmol gof cell mass based on ATP generation (g mol-ATP −1 ) Y E Cell yield based on total light energy (g kJ −1 ) ΔG o ACE Free energy change of acetate complete oxidation (kJ mol −1 ) ΔG o ATP Free energy change of ATP hydrolysis (kJ mol −1 ) ΔG o GLC Free energy change of glucose complete oxidation (kJ mol −1 ) μ Specific growth rate (h −1 ) 8 Vector of measurement noise variancecovariance (−) Φ PSII The efficiency of photosystem II photochemistry (−) Ψ ATP The efficiency of energy conversion on ATP synthesis (%)

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Section: Introductionmentioning

confidence: 99%

Carbon metabolism and energy conversion of Synechococcus sp. PCC 7942 under mixotrophic conditions: comparison with photoautotrophic condition

et al. 2011

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“…Among the achievements obtained from flux analysis are the identification of novel pathways, the elucidation of metabolic control, identification of targets for rational strain engineering in biotechnology, and first insights into design principles of metabolic networks in systems biology studies. Concerning C. glutamicum, metabolic flux analysis provided a fascinating view of its metabolic pathways and offered new possibilities for rational strain engineering as recently reviewed [34,87]. …”

Section: Analysis Of Metabolic Fluxesmentioning

confidence: 99%

Analysis and Engineering of Metabolic Pathway Fluxes in Corynebacterium glutamicum

Wittmann

2010

Biosystems Engineering I

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The Gram-positive soil bacterium Corynebacterium glutamicum was discovered as a natural overproducer of glutamate about 50 years ago. Linked to the steadily increasing economical importance of this microorganism for production of glutamate and other amino acids, the quest for efficient production strains has been an intense area of research during the past few decades. Efficient production strains were created by applying classical mutagenesis and selection and especially metabolic engineering strategies with the advent of recombinant DNA technology. Hereby experimental and computational approaches have provided fascinating insights into the metabolism of this microorganism and directed strain engineering. Today, C. glutamicum is applied to the industrial production of more than 2 million tons of amino acids per year. The huge achievements in recent years, including the sequencing of the complete genome and efficient post genomic approaches, now provide the basis for a new, fascinating era of research -analysis of metabolic and regulatory properties of C. glutamicum on a global scale towards novel and superior bioprocesses.

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“…For example, 13C-based metabolic-flux analysis provides information from inside the cell that can be used to identify rate-limiting steps [4]. Further, comparative genomics reveals phylogenetically conserved transcriptional regulation and provides important information about metabolic regulation [5].…”

Section: Introductionmentioning

confidence: 99%

Metabolic Control of the TCA cycle by the YdcI Transcriptional Regulator in Escherichia coli

Nishio¹,

Suzuki²,

Matsui³

et al. 2013

J Microb Biochem Technol

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Understanding the regulation and control of the expression of genes encoding metabolic enzymes is crucial for production using microbes. To overcome technical difficulties involved in identifying regulatory network systems, we designed a DNA motif finding procedure combining transcriptome and genome sequence data. Here, we used the ArcAB two-component system of Escherichia coli, which controls genes involved in the TCA cycle and energy metabolism, as a model to identify DNA motifs involved in gene-expression regulation. DNA-array data were used to extract up-regulated genes from ΔarcA and ΔarcB E. coli strains, and the upstream sequences were subjected to DNA-motif finding. Sequence similarity and conserved residues identified the known ArcA-binding motif and a novel DNA-motif candidate that was estimated to be related to YdcI, a putative LysR-type transcriptional regulator. A hypothetical YdcI-binding motif was found upstream of the gltA gene, suggesting that YdcI might control the carbon flux into the TCA cycle. To verify this, l-glutamic-acid production and citrate synthase activity in the ydcI gene-amplified strain were investigated. Our findings suggested that YdcI is a transcription factor that regulates the expression of gltA and other genes, and controls the carbon flux into the TCA cycle.

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Metabolic flux analysis in biotechnology processes

Cited by 54 publications

References 51 publications

Carbon metabolism and energy conversion of Synechococcus sp. PCC 7942 under mixotrophic conditions: comparison with photoautotrophic condition

Carbon metabolism and energy conversion of Synechococcus sp. PCC 7942 under mixotrophic conditions: comparison with photoautotrophic condition

Analysis and Engineering of Metabolic Pathway Fluxes in Corynebacterium glutamicum

Metabolic Control of the TCA cycle by the YdcI Transcriptional Regulator in Escherichia coli

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