Dynamic response of Aspergillus niger to single pulses of glucose with high and low concentrations

Shuai Wang , Peng Liu , Wei Shu , Chao Li , Huan Li , Shanshan Liu , Jianye Xia , Henk Noorman

Bioresources and Bioprocessing ›› 2019, Vol. 6 ›› Issue (1) : 16

PDF
Bioresources and Bioprocessing ›› 2019, Vol. 6 ›› Issue (1) : 16 DOI: 10.1186/s40643-019-0251-y
Research

Dynamic response of Aspergillus niger to single pulses of glucose with high and low concentrations

Author information +
History +
PDF

Abstract

Microorganisms generally encounter a fluctuating environment in their natural habitat and similar conditions also happen in large-scale bioreactors. In this work, the dynamic response of intracellular and extracellular metabolites of Aspergillus niger was investigated after sudden exposure to high and low excess glucose concentrations in chemostats. It was found that the steady-state pathway turnover time of the carbon flux through the central carbon metabolism (CCM) was PP pathway 50 s, EMP pathway 20 s, and TCA cycle 189 s, and an upper limit for individual metabolite concentrations in the CCM was estimated. Regardless of the glucose pulse size, little changes of amino acids levels were observed except for aspartate, which showed a significant decrease. The ATP paradox, known from other organisms, was also observed in the studied A. niger strain. However, a different response of the NAD+/NADH ratio to the glucose pulses was found in A. niger compared to previously published observations on Penicillium chrysogenum and Saccharomyces cerevisiae. These findings are valuable for better understanding A. niger culture performance in large-scale bioreactors.

Keywords

Aspergillus niger / Substrate pulse / Glucose excess / Rapid sampling / Dynamic responses / Intracellular metabolites

Cite this article

Download citation ▾
Shuai Wang, Peng Liu, Wei Shu, Chao Li, Huan Li, Shanshan Liu, Jianye Xia, Henk Noorman. Dynamic response of Aspergillus niger to single pulses of glucose with high and low concentrations. Bioresources and Bioprocessing, 2019, 6(1): 16 DOI:10.1186/s40643-019-0251-y

登录浏览全文

4963

注册一个新账户 忘记密码

References

[1]

Aboka FO, . Identification of informative metabolic responses using a minibioreactor: a small step change in the glucose supply rate creates a large metabolic response in Saccharomyces cerevisiae. Yeast, 2012, 29(3–4): 95-110.

[2]

Bylund F, . Substrate gradient formation in the large-scale bioreactor lowers cell yield and increases by-product formation. Bioprocess Eng, 1998, 18(3): 171-180.

[3]

Carnicer M, . Development of quantitative metabolomics for Pichia pastoris. Metabolomics, 2012, 8(2): 284-298.

[4]

De Jonge LP, . Scale-down of penicillin production in Penicillium chrysogenum. Biotechnol J, 2011, 6(8): 944-958.

[5]

De Jonge L, . Flux response of glycolysis and storage metabolism during rapid feast/famine conditions in Penicillium chrysogenum using dynamic (13)C labeling. Biotechnol J, 2014, 9(3): 372-385.

[6]

Delvigne F, Goffin P. Microbial heterogeneity affects bioprocess robustness: dynamic single-cell analysis contributes to understanding of microbial populations. Biotechnol J, 2014, 9(1): 61-72.

[7]

Heijnen JJ. Impact of thermodynamic principles in systems biology. Adv Biochem Eng Biotechnol, 2010, 121: 139.

[8]

Junne S, . Scale down simulator for studying the impact of industrial scale inhomogeneities on Bacillus subtilis processes. J Biotechnol, 2010, 150(6): 420.

[9]

Junne S, . A two-compartment bioreactor system made of commercial parts for bioprocess scale-down studies: impact of oscillations on Bacillus subtilis fed-batch cultivations. Biotechnol J, 2011, 6(8): 1009-1017.

[10]

Lameiras F, Heijnen JJ, Gulik WMV. Development of tools for quantitative intracellular metabolomics of Aspergillus niger chemostat cultures. Metabolomics, 2015, 11(5): 1253-1264.

[11]

Liu P, . Combined 13C-assisted metabolomics and metabolic flux analysis reveals the impacts of glutamate on the central metabolism of high β-galactosidase-producing Pichia pastoris. Bioresour Bioprocess, 2016, 3(1): 47.

[12]

Lu H, . Integrated isotope-assisted metabolomics and 13C metabolic flux analysis reveals metabolic flux redistribution for high glucoamylase production by Aspergillus niger. Microb Cell Fact, 2015, 14(1): 147.

[13]

Mashego MR, . In vivo kinetics with rapid perturbation experiments in Saccharomyces cerevisiae using a second-generation BioScope. Metab Eng, 2006, 8(4): 370-383.

[14]

Nasution U, . Generating short-term kinetic responses of primary metabolism of Penicillium chrysogenum through glucose perturbation in the bioscope mini reactor. Metab Eng, 2006, 8(5): 395-405.

[15]

Nasution U, . Measurement of intracellular metabolites of primary metabolism and adenine nucleotides in chemostat cultivated Penicillium chrysogenum. Biotechnol Bioeng, 2010, 94(1): 159-166.

[16]

Neubauer P, Junne S. Scale-down simulators for metabolic analysis of large-scale bioprocesses. Curr Opin Biotechnol, 2010, 21(1): 114-121.

[17]

Ramaiah A, Hathaway JA, Atkinson DE. Adenylate as a metabolic regulator. Effect on Yeast phosphofructokinase kinetics. J Biol Chem, 1964, 239(239): 3619.

[18]

Sloothaak J, . Aspergillus niger membrane-associated proteome analysis for the identification of glucose transporters. Biotechnol Biofuels, 2015, 8: 150.

[19]

Smolke C. The metabolic pathway engineering handbook: fundamentals, 2010, Boca Raton: CRC Press/Taylor & Francis.

[20]

Suarez-Mendez CA, . Fast “feast/famine” cycles for studying microbial physiology under dynamic conditions: a case study with Saccharomyces cerevisiae. Metabolites, 2014, 4(2): 347.

[21]

Suarez-Mendez CA, Ras C, Wahl SA. Metabolic adjustment upon repetitive substrate perturbations using dynamic 13C-tracing in yeast. Microb Cell Fact, 2017, 16(1): 161.

[22]

Sui YF, . Global transcriptional response of Aspergillus niger in the process of glucoamylase fermentation. Bioresour Bioprocess, 2017, 4(1): 44.

[23]

Tang W, . A 9-pool metabolic structured kinetic model describing days to seconds dynamics of growth and product formation by Penicillium chrysogenum. Biotechnol Bioeng, 2017, 114(8): 1733.

[24]

Taymaz-Nikerel H, van Gulik WM, Heijnen JJ. Escherichia coli responds with a rapid and large change in growth rate upon a shift from glucose-limited to glucose-excess conditions. Metab Eng, 2011, 13(3): 307-318.

[25]

Theobald U, . In vivo analysis of metabolic dynamics in Saccharomyces cerevisiae: I. Experimental observations. Biotechnol Bioeng, 2015, 55(2): 305-316.

[26]

Torres NV, . Glucose transport by Aspergillus niger: the low-affinity carrier is only formed during growth on high glucose concentrations. Appl Microbiol Biotechnol, 1996, 44(6): 790-794.

[27]

Visser D, . Analysis of in vivo kinetics of glycolysis in aerobic Saccharomyces cerevisiae by application of glucose and ethanol pulses. Biotechnol Bioeng, 2010, 88(2): 157-167.

[28]

Walther T, . Control of ATP homeostasis during the respiro-fermentative transition in Yeast. Mol Syst Biol, 2010, 6(1): 344.

[29]

Wang G, . Integration of microbial kinetics and fluid dynamics toward model-driven scale-up of industrial bioprocesses. Eng Life Sci, 2015, 15(1): 20-29.

[30]

Wang G, . Power input effects on degeneration in prolonged penicillin chemostat cultures: a systems analysis at flux, residual glucose, metabolite and transcript levels. Biotechnol Bioeng, 2017, 115(1): 114-125.

[31]

Wang G, . Comparative performance of different scale-down simulators of substrate gradients in Penicillium chrysogenum cultures: the need of a biological systems response analysis. Microb Biotechnol, 2018, 11(3): 486-497.

[32]

Wu L, . Quantitative analysis of the microbial metabolome by isotope dilution mass spectrometry using uniformly 13C-labeled cell extracts as internal standards. Anal Biochem, 2005, 336(2): 164-171.

[33]

Wu L, . Short-term metabolome dynamics and carbon, electron, and ATP balances in chemostat-grown Saccharomyces cerevisiae CEN.PK 113-7D following a glucose pulse. Appl Environ Microbiol, 2006, 72(5): 3566.

[34]

Yu M, Shimizu K. Current status and future perspectives of kinetic modeling for the cell metabolism with incorporation of the metabolic regulation mechanism. Bioresour Bioprocess, 2015, 2(1): 1-19.

[35]

Zakhartsev M, . Fast sampling for quantitative microbial metabolomics: new aspects on cold methanol quenching: metabolite co-precipitation. Metabolomics, 2015, 11(2): 286-301.

Funding

The Fundamental Research Funds for the Central Universities(22221818014)

The National Natural Science Foundation of China(21506052)

The 111 Project(B18022)

AI Summary AI Mindmap
PDF

119

Accesses

0

Citation

Detail

Sections
Recommended

AI思维导图

/