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

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

doi:10.1186/s13068-021-02099-2

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

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

Research output: Contribution to journal › Article › peer-review

Abstract

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 methods for the integration of omics data into a high-quality metabolic model. In this work, we perform transcriptomic analysis to determine the temporal expression changes during fermentation of bagasse hydrolysate and develop an evolutionary algorithm to integrate the transcriptomic data with the available metabolic model to identify potential targets for strain engineering.

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.

Original language	English
Article number	4
Journal	Biotechnology for biofuels and bioproducts
Volume	15
DOIs	https://doi.org/10.1186/s13068-021-02099-2
Publication status	Published - 12 Jan 2022

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Upton, D. J., Kaushal, M., Whitehead, C., Faas, L., Gomez, L. D., McQueen-Mason, S. J., Srivastava, S., & Wood, A. J. (2022). Integration of Aspergillus niger transcriptomic profile with metabolic model identifies potential targets to optimise citric acid production from lignocellulosic hydrolysate. Biotechnology for biofuels and bioproducts, 15, Article 4. https://doi.org/10.1186/s13068-021-02099-2

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

abstract = "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 methods for the integration of omics data into a high-quality metabolic model. In this work, we perform transcriptomic analysis to determine the temporal expression changes during fermentation of bagasse hydrolysate and develop an evolutionary algorithm to integrate the transcriptomic data with the available metabolic model to identify potential targets for strain engineering.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.",

author = "Upton, {Daniel J} and Mehak Kaushal and Caragh Whitehead and Laura Faas and Gomez, {Leonardo D} and McQueen-Mason, {Simon J} and Shireesh Srivastava and Wood, {A Jamie}",

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doi = "10.1186/s13068-021-02099-2",

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Upton, DJ, Kaushal, M, Whitehead, C, Faas, L , Gomez, LD , McQueen-Mason, SJ, Srivastava, S & Wood, AJ 2022, 'Integration of Aspergillus niger transcriptomic profile with metabolic model identifies potential targets to optimise citric acid production from lignocellulosic hydrolysate', Biotechnology for biofuels and bioproducts, vol. 15, 4. https://doi.org/10.1186/s13068-021-02099-2

Integration of Aspergillus niger transcriptomic profile with metabolic model identifies potential targets to optimise citric acid production from lignocellulosic hydrolysate. / Upton, Daniel J; Kaushal, Mehak; Whitehead, Caragh et al.
In: Biotechnology for biofuels and bioproducts, Vol. 15, 4, 12.01.2022.

Research output: Contribution to journal › Article › peer-review

TY - JOUR

T1 - Integration of Aspergillus niger transcriptomic profile with metabolic model identifies potential targets to optimise citric acid production from lignocellulosic hydrolysate

AU - Upton, Daniel J

AU - Kaushal, Mehak

AU - Whitehead, Caragh

AU - Faas, Laura

AU - Gomez, Leonardo D

AU - McQueen-Mason, Simon J

AU - Srivastava, Shireesh

AU - Wood, A Jamie

PY - 2022/1/12

Y1 - 2022/1/12

N2 - 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 methods for the integration of omics data into a high-quality metabolic model. In this work, we perform transcriptomic analysis to determine the temporal expression changes during fermentation of bagasse hydrolysate and develop an evolutionary algorithm to integrate the transcriptomic data with the available metabolic model to identify potential targets for strain engineering.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.

AB - 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 methods for the integration of omics data into a high-quality metabolic model. In this work, we perform transcriptomic analysis to determine the temporal expression changes during fermentation of bagasse hydrolysate and develop an evolutionary algorithm to integrate the transcriptomic data with the available metabolic model to identify potential targets for strain engineering.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.

U2 - 10.1186/s13068-021-02099-2

DO - 10.1186/s13068-021-02099-2

M3 - Article

C2 - 35418297

SN - 2731-3654

VL - 15

JO - Biotechnology for biofuels and bioproducts

JF - Biotechnology for biofuels and bioproducts

M1 - 4

ER -