High‐quality genome‐scale metabolic model of Aurantiochytrium sp. T66

Abstract

The long‐chain, ω‐3 polyunsaturated fatty acids (PUFAs) (e.g., eicosapentaenoic acid [EPA] and docosahexaenoic acid [DHA]), are essential for humans and animals, including marine fish species. Presently, the primary source of these PUFAs is fish oils. As the global production of fish oils appears to be reaching its limits, alternative sources of high‐quality ω‐3 PUFAs is paramount to support the growing aquaculture industry. Thraustochytrids are a group of heterotrophic protists with the capability to synthesize and accrue large amounts of DHA. Thus, the thraustochytrids are prime candidates to solve the increasing demand for ω‐3 PUFAs using microbial cell factories. However, a systems‐level understanding of their metabolic shift from cellular growth into lipid accumulation is, to a large extent, unclear. Here, we reconstructed a high‐quality genome‐scale metabolic model of the thraustochytrid Aurantiochytrium sp. T66 termed iVS1191. Through iterative rounds of model refinement and extensive manual curation, we significantly enhanced the metabolic scope and coverage of the reconstruction from that of previously published models, making considerable improvements with stoichiometric consistency, metabolic connectivity, and model annotations. We show that iVS1191 is highly consistent with experimental growth data, reproducing in vivo growth phenotypes as well as specific growth rates on minimal carbon media. The availability of iVS1191 provides a solid framework for further developing our understanding of T66's metabolic properties, as well as exploring metabolic engineering and process‐optimization strategies in silico for increased ω‐3 PUFA production.

Experimental determination of Escherichia coli biomass composition for constraint-based metabolic modeling

“…While experimental data on the condition-dependent biomass compositions of some well-studied organisms are available [ 11 , 12 ], this is commonly lacking for most organisms. The usual strategy has therefore been to either adopt existing organism-specific biomass compositions from different conditions or employ parts or the whole composition from another organism entirely [ 13 , 14 ]. This, however, is a sub-optimal approach as the biomass composition depends on the particular organism and strain [ 15 , 16 ].…”

Production, Biosynthesis, and Commercial Applications of Fatty Acids From Oleaginous Fungi

“…In addition, lignocellulose hydrolysate may prove to be an inexpensive source of carbon for biomass production, which can efficiently metabolize xylose, and xylose metabolic engineering may help reduce fermentation costs ( 74 ). Metabolic engineering is also very important ( 75 , 76 ). Therefore, strains should be improved, complete metabolic flux analysis should be carried out, and the protein engineering field should be evaluated with the goal of metabolic engineering, etc., in order to maximize the fatty acid production in the biomass.…”

Recent Development of Advanced Biotechnology in the Oleaginous Fungi for Arachidonic Acid Production

“…Models for an ever increasing number of fungi such as Aspergillus niger , Myceliophthora thermophila , and the oleaginous yeast Papiliotrema laurentii have been published in recent years. Recently, various GEMs have been developed as process-optimization strategies for increasing the production of PUFAs, including iCY1170_DHA and iVS1191 (ω-3 PUFA) . The analysis of GEMs has also yielded potential targets for further improving PUFAs production.…”

“…78 Models for an ever increasing number of fungi such as Aspergillus niger, 79 Myceliophthora thermophila, 80 and the oleaginous yeast Papiliotrema laurentii 81 of PUFAs, including iCY1170_DHA 82 and iVS1191 (ω-3 PUFA). 83 The analysis of GEMs has also yielded potential targets for further improving PUFAs production. For example, it was demonstrated that GEMs have capability of predicting the growth rates of M.circinelloides on various nutrient sources and under different culture conditions using flux balance analysis (FBA).…”