Abstract
BackgroundAspergillus niger fermentation has provided the chief source of industrial citric acid for over 50 years. Traditional strain development of this organism was achieved through random mutagenesis, but advances in genomics have enabled the development of genome-scale metabolic modelling that can be used to make predictive improvements in fermentation performance. The parent citric acid-producing strain of A. niger, ATCC 1015, has been described previously by a genome-scale metabolic model that encapsulates its response to ambient pH. Here, we report the development of a novel double optimisation modelling approach that generates time-dependent citric acid fermentation using dynamic flux balance analysis.ResultsThe output from this model shows a good match with empirical fermentation data. Our studies suggest that citric acid production commences upon a switch to phosphate-limited growth and this is validated by fitting to empirical data, which confirms the diauxic growth behaviour and the role of phosphate storage as polyphosphate.ConclusionsThe calibrated time-course model reflects observed metabolic events and generates reliable in silico data for industrially relevant fermentative time series, and for the behaviour of engineered strains suggesting that our approach can be used as a powerful tool for predictive metabolic engineering.
Highlights
Aspergillus niger fermentation has provided the chief source of industrial citric acid for over 50 years
Citric acid fermentation occurs as part of a diauxic growth response To investigate citric acid production by the parent citric acid-producing ATCC 1015 strain, empirical timecourse data were obtained from fermentation performed in shake flasks
In order to better understand the basis of this growth behaviour, we developed a dynamic flux balance analysis model based on the previously published FBA model [13, 14]
Summary
Aspergillus niger fermentation has provided the chief source of industrial citric acid for over 50 years. The parent citric acid-producing strain of A. niger, ATCC 1015, has been described previously by a genome-scale metabolic model that encapsulates its response to ambient pH. A. niger is a saprotroph and its natural habitat is soil, it can be found in wide-ranging habitats, such as rotting fruit, plant debris, and indoor environments. This fast-growing fungus is both acid- and thermo-tolerant, able to grow in the pH range 1.4–9.8 and in the temperature range 6–47 °C [3]. This versatility and its ease of culture has helped it become an established industrial organism. Full genome sequences are currently available for 18 species of the Aspergilli group [5] and some of these have been subject to extensive systems biology studies [6]
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