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Open AccessFeature PaperArticle

Uncovering Novel Pathways for Enhancing Hyaluronan Synthesis in Recombinant Lactococcus lactis: Genome-Scale Metabolic Modeling and Experimental Validation

1
Department of Biotechnology, Bhupat and Jyoti Mehta School of Biosciences, Indian Institute of Technology Madras, Chennai 600 036, India
2
Initiative for Biological Systems Engineering, IIT Madras, Chennai 600 036, India
3
Robert Bosch Centre for Data Science and Artificial Intelligence (RBC-DSAI), IIT Madras, Chennai 600 036, India
*
Authors to whom correspondence should be addressed.
Processes 2019, 7(6), 343; https://doi.org/10.3390/pr7060343
Received: 12 April 2019 / Revised: 25 May 2019 / Accepted: 30 May 2019 / Published: 5 June 2019
(This article belongs to the Special Issue In Silico Metabolic Modeling and Engineering)
Hyaluronan (HA), a glycosaminoglycan with important medical applications, is commercially produced from pathogenic microbial sources. The metabolism of HA-producing recombinant generally regarded as safe (GRAS) systems needs to be more strategically engineered to achieve yields higher than native producers. Here, we use a genome-scale model (GEM) to account for the entire metabolic network of the cell while predicting strategies to improve HA production. We analyze the metabolic network of Lactococcus lactis adapted to produce HA and identify non-conventional strategies to enhance HA flux. We also show experimental verification of one of the predicted strategies. We thus identified an alternate route for enhancement of HA synthesis, originating from the nucleoside inosine, that can function in parallel with the traditionally known route from glucose. Adopting this strategy resulted in a 2.8-fold increase in HA yield. The strategies identified and the experimental results show that the cell is capable of involving a larger subset of metabolic pathways in HA production. Apart from being the first report to use a nucleoside to improve HA production, we demonstrate the role of experimental validation in model refinement and strategy improvisation. Overall, we point out that well-constructed GEMs could be used to derive efficient strategies to improve the biosynthesis of high-value products. View Full-Text
Keywords: hyaluronic acid; genome-scale metabolic network model; Lactococcus lactis; metabolic engineering; inosine supplementation hyaluronic acid; genome-scale metabolic network model; Lactococcus lactis; metabolic engineering; inosine supplementation
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Badri, A.; Raman, K.; Jayaraman, G. Uncovering Novel Pathways for Enhancing Hyaluronan Synthesis in Recombinant Lactococcus lactis: Genome-Scale Metabolic Modeling and Experimental Validation. Processes 2019, 7, 343.

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