Quantitative metabolic flux analysis revealed uneconomical utilization of ATP and NADPH in Acremonium chrysogenum fed with soybean oil

Li, Jianhua; Yang, Yiming; Chu, Ju; Huang, Mingzhi; Li, Liang; Zhang, Xiaochun; Wang, Yonghong; Zhuang, Yingping; Zhang, Siliang

doi:10.1007/s00449-010-0439-1

Cited by 11 publications

(2 citation statements)

References 24 publications

(22 reference statements)

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“…Another common application of MFA is to analyze the production of key cellular co-factors under different growth conditions. Li et al used MFA to analyze the uneconomical utilization of ATP in soybean oil feeding Acremonium chrysogenum , and they proposed strategies to improve cephalosporin C (CPC) based on controlling NADPH and ATP production and consumption [ 80 ]. In addition, MFA can predict changes in metabolic flux in metabolically engineered strains, which provides help when selecting appropriate metabolic engineering strategies [ 81 ].…”

Section: Methods and Applications Of Mechanistic Modelingmentioning

confidence: 99%

Optimization and Scale-Up of Fermentation Processes Driven by Models

Wang

Yang

et al. 2022

Bioengineering

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In the era of sustainable development, the use of cell factories to produce various compounds by fermentation has attracted extensive attention; however, industrial fermentation requires not only efficient production strains, but also suitable extracellular conditions and medium components, as well as scaling-up. In this regard, the use of biological models has received much attention, and this review will provide guidance for the rapid selection of biological models. This paper first introduces two mechanistic modeling methods, kinetic modeling and constraint-based modeling (CBM), and generalizes their applications in practice. Next, we review data-driven modeling based on machine learning (ML), and highlight the application scope of different learning algorithms. The combined use of ML and CBM for constructing hybrid models is further discussed. At the end, we also discuss the recent strategies for predicting bioreactor scale-up and culture behavior through a combination of biological models and computational fluid dynamics (CFD) models.

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Section: Methods and Applications Of Mechanistic Modelingmentioning

confidence: 99%

Optimization and Scale-Up of Fermentation Processes Driven by Models

Wang

Yang

et al. 2022

Bioengineering

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“…There are two main factors leading to the problems of oxygen supply; one is the extremely high oxygen consuming feature of the soybean oil metabolism pathway in A. chrysogenum , and the other is the high viscosity of soybean oil. Meanwhile, it was also found by Li et al that soybean oil is not a high efficiency substrate for CPC production as it generates a lot of wasted energy (more than 83% of total energy).…”

Section: Introductionmentioning

confidence: 99%

Enhanced cephalosporin C production with a novel DO‐Stat based carbon resources co‐feeding strategy

Duan

Gao³

et al. 2013

J of Chemical Tech & Biotech

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Background To solve the problems of high by‐product accumulations and low substrate utilization efficiencies in the traditional cephalosporin C (CPC) fermentation process, a novel DO‐Stat based substrates co‐feeding strategy for CPC production by Acremonium chrysogenum (A. chrysogenum) was conducted in a 7 L fermentor using the addition of glucose coupled with soybean oil. RESULTS Compared with the sole soybean oil feeding method, the final CPC concentration was enhanced from 25.3 g L‐1 to a higher level of 31.9 g L‐1 by the novel substrate co‐feeding strategy. The major by‐product of deacetoxycephalosporin C (DAOC) was reduced from 0.32 g L‐1 to a lower level of 0.092 g L‐1, and the final DAOC/CPC ratio (0.28%) reached the CPC fermentation quality standard (below 0.5%). Metabolic flux analysis revealed that the carbon fluxes in the CPC synthesis related route were increased about 2.2‐fold by applying the novel substrate co‐feeding strategy. Conclusion The results indicated that the co‐feeding of glucose and soybean oil in the main CPC production phase was desirable for CPC fermentation, and led to higher CPC production/yield and substrate utilization efficiencies but less DAOC accumulation. © 2013 Society of Chemical Industry

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Prelude to rational scale-up of penicillin production: a scale-down study

Wang

Chu

Noorman

et al. 2014

Appl Microbiol Biotechnol

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Penicillin is one of the best known pharmaceuticals and is also an important member of the β-lactam antibiotics. Over the years, ambitious yields, titers, productivities, and low costs in the production of the β-lactam antibiotics have been stepwise realized through successive rounds of strain improvement and process optimization. Penicillium chrysogenum was proven to be an ideal cell factory for the production of penicillin, and successful approaches were exploited to elevate the production titer. However, the industrial production of penicillin faces the serious challenge that environmental gradients, which are caused by insufficient mixing and mass transfer limitations, exert a considerably negative impact on the ultimate productivity and yield. Scale-down studies regarding diverse environmental gradients have been carried out on bacteria, yeasts, and filamentous fungi as well as animal cells. In accordance, a variety of scale-down devices combined with fast sampling and quenching protocols have been established to acquire the true snapshots of the perturbed cellular conditions. The perturbed metabolome information stemming from scale-down studies contributed to the comprehension of the production process and the identification of improvement approaches. However, little is known about the influence of the flow field and the mechanisms of intracellular metabolism. Consequently, it is still rather difficult to realize a fully rational scale-up. In the future, developing a computer framework to simulate the flow field of the large-scale fermenters is highly recommended. Furthermore, a metabolically structured kinetic model directly related to the production of penicillin will be further coupled to the fluid flow dynamics. A mathematical model including the information from both computational fluid dynamics and chemical reaction dynamics will then be established for the prediction of detailed information over the entire period of the fermentation process and thereby for the optimization of penicillin production, and subsequently also benefiting other fermentation products.

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Quantitative metabolic flux analysis revealed uneconomical utilization of ATP and NADPH in Acremonium chrysogenum fed with soybean oil

Cited by 11 publications

References 24 publications

Optimization and Scale-Up of Fermentation Processes Driven by Models

Optimization and Scale-Up of Fermentation Processes Driven by Models

Enhanced cephalosporin C production with a novel DO‐Stat based carbon resources co‐feeding strategy

Prelude to rational scale-up of penicillin production: a scale-down study

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