Integration of Aspergillus niger transcriptomic profile with metabolic model identifies potential targets to optimise citric acid production from lignocellulosic hydrolysate

黑曲霉转录组谱与代谢模型的整合可确定优化木质纤维素水解物生产柠檬酸的潜在目标

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作者:Daniel J Upton, Mehak Kaushal, Caragh Whitehead, Laura Faas, Leonardo D Gomez, Simon J McQueen-Mason, Shireesh Srivastava, A Jamie Wood

Background

Citric acid is typically produced industrially by Aspergillus niger-mediated fermentation of a sucrose-based feedstock, such as molasses. The fungus Aspergillus niger has the potential to utilise lignocellulosic biomass, such as bagasse, for industrial-scale citric acid production, but realising this potential requires strain optimisation. Systems biology can accelerate strain engineering by systematic target identification, facilitated by

Conclusions

In this study, we demonstrate the production of citric acid from lignocellulosic hydrolysate and show how transcriptomic data across multiple timepoints can be coupled with evolutionary and metabolic modelling to identify potential targets for further engineering to maximise productivity from a chosen feedstock. The in silico strategies employed in this study can be applied to other biotechnological goals, assisting efforts to harness the potential of microorganisms for bio-based production of valuable chemicals.

Results

The novel integrated procedure matures our understanding of suboptimal citric acid production and reveals potential targets for strain engineering, including targets consistent with the literature such as the up-regulation of citrate export and pyruvate carboxylase as well as novel targets such as the down-regulation of inorganic diphosphatase. Conclusions: In this study, we demonstrate the production of citric acid from lignocellulosic hydrolysate and show how transcriptomic data across multiple timepoints can be coupled with evolutionary and metabolic modelling to identify potential targets for further engineering to maximise productivity from a chosen feedstock. The in silico strategies employed in this study can be applied to other biotechnological goals, assisting efforts to harness the potential of microorganisms for bio-based production of valuable chemicals.

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