Team:Evry Paris-Saclay/FBA
Flux Balance Analysis
In order to choose the best Yarrowia lipolytica strain to produce rare fatty acids such as jacaric acid and punicic acid, we have performed metabolic simulations, also called Flux Balance Analysis (FBA), on several known strains of Y. lipolytica.
First, we have got an improved version of iYali4 [1], a metabolic model of Yarrowia lipolytica W29, from GitHub.
We have used the Python package COBRApy [2] to add a simplified version of the reaction transforming linoleate into jacaric acid. By clicking below, you can download the original model and the code we have created to add the reaction.
Then, we have performed an FBA on this model, which corresponds to the JMY195 [3] strain, with the software OptFlux [4]. This simulation gave us a biomass value of 29.5 and a jacaric acid production of 226.54. These values are specific to the software and cannot be compared to the experimental yields directly. However, these values allow us to compare different strains. We have constructed models of the strains JMY1877 [5], JMY1233 [6], JMY2159 [7], JMY3325 [8] and JMY3820 [9] and performed FBA on them with the OptFlux tool “Gene Under-Over Expression Simulation”. In such models, the normal value for gene expression in set to 1. To knockout genes in the models, we have set this value to 0, and we have set it to 10 to simulate an over-expression. The FBA results are presented in Table 1.
| JMY195 (Po1d) | MATA ura3-302 leu2-270 xpr2-322 | 29.50 | 100.0% | 226.54 | 100.0% |
| JMY1233 | MATA ura3-302 leu2-270 xpr2-322 pox1-6Δ | 29.50 | 100.0% | 226.54 | 100.0% |
| JMY1877 | MATA ura3-302 leu2-270 xpr2-322 dga1Δ dga2Δ lro1Δ are1Δ | 0.00 | 0.0% | 0.00 | 0.0% |
| JMY2159 | MATA ura3-302 leu2-270 xpr2-322 pox1-6Δ dga1Δ dga2Δ lro1Δ fad2Δ | 0.00 | 0.0% | 0.00 | 0.0% |
| JMY3325 | MATA ura3-302 leu2-270 xpr2-322 pox1-6Δ dga1Δ dga2Δ lro1Δ fad2Δ pTEF-FAD2-LEU2 | 0.00 | 0.0% | 0.00 | 0.0% |
| JMY3820 | MATα ura3-302 leu2-270 xpr2-322 pox1-6Δ tgl4Δ + pTEF-DGA2 + pTEF-GPD1 | 29.50 | 100.0% | 386.41 | 170.6% |
For JMY1877, JMY2159 and JMY3325, the results are not relevant since their models were unable to show any growth. This is certainly due to a limitation in the original model, which treats as essential some genes that we have deleted. Indeed, when we have determined critical genes with OptFlux, are1 appeared to be essential, even if it is not in real life. About JMY2159 and JMY3325, it is likely that dga1, dga2 and lro1 are essential when deleted together, which again is not the case as seen experimentally.
For JMY1233, we see that both the biomass and the jacaric acid production have the same value than for the control JMY195.
Finally, the FBA indicates that JMY3820 is able to produce 70% more jacaric acid than JMY195, without changing the biomass production.
These results suggest that JMY3820 is the best strain to produce jacaric acid from linoleate. This would also suggest that it is the best strain to produce punicic acid with linoleate as the starting point, and we kept that in mind during the wet lab experiments. Happily, this has been confirmed by the experiments.
To go further, we have also tried to determine new genes that could be deleted to optimize the production of jacaric acid with Yarrowia lipolytica. To do so, we have used the evolutionary optimization tool of OtpFlux on JMY195 and set the minimum biomass production to 95% of the control. As results, this tool gave us genes or sets of genes the deletion of which increases the jacaric acid production to 1000, which is the maximum potential value of the reaction. These genes are presented in Table 2. The solutions proposed by this tool should always be manually verified since a model may not be refined enough to represent the exact reality and could propose absurd deletions as a result.
| YALI0D00583g | |
| YALI0F15631g | |
| YALI0E33517g | |
| YALI0F24475g | |
| YALI0E25740g | |
| YALI0F01210g | |
| YALI0F26323g | |
| YALI0E18568g | |
| YALI0A05379g | |
| YALI0B09647g | |
| YALI0B22682g | |
| YALI0E33099g | |
| YALI0C05258g | |
| YALI0D04741g | |
| YALI0D10131g | |
| YALI0E31009g | |
| YALI0F14025g | |
| YALI0E31471g | |
| YALI0D24750g | |
| YALI0E24013g | |
| YALI0C11407g |
YALI0D00583g, YALI0F15631g and YALI0F24475g are coding for a proton-transporting protein responsible for the vacuolar acidification; YALI0E33517g is coding for an oxoglutarate dehydrogenase involved in the Krebs cycle; YALI0E25740g is coding for a guanine deaminase involved in the reaction EC:3.5.4.3; YALI0F01210g is coding for a membrane water transporter; etc.
Interestingly, YALI0F14025g is the only gene that was not proposed in a set a gene. The only deletion of this gene is able to increase the production of jacaric acid to its maximum. This gene is coding for a kinase that is involved in the inositol-phosphate biosynthesis.
None of the deletions that have been performed in tested strains, including tgl4 which is deleted in JMY3820, was proposed by OptFlux.
This modelling part has implications well beyond its immediate scope and will definitely help future studies working on optimizing Yarrowia lipolytica for rare fatty acids production.
References
[1]Kerkhoven EJ, Pomraning KR, Baker SE, Nielsen J. Regulation of amino-acid metabolism controls flux to lipid accumulation in Yarrowia lipolytica. NPJ Syst Biol Appl (2016) 2, 16005.[2]Ebrahim A, Lerman JA, Palsson BO, Hyduke DR. COBRApy: COnstraints-Based Reconstruction and Analysis for Python. BMC Syst Biol (2013) 7, 74.
[3]Barth G, Gaillardin C. Yarrowia lipolytica. In: Wolf K (ed) Non conventional yeasts in biotechnology. Springer, Berlin (1996) 1, 314-388.
[4]Rocha I, Maia P, Evangelista P, Vilaça P, Soares S, Pinto JP, Nielsen J, Patil KR, Ferreira EC, Rocha M. OptFlux: an open-source software platform for in silico metabolic engineering. BMC Syst Biol (2010) 4, 45.
[5]Beopoulos A, Haddouche R, Kabran P, Dulermo T, Chardot T, Nicaud JM. Identification and characterization of DGA2, an acyltransferase of the DGAT1 acyl-CoA:diacylglycerol acyltransferase family in the oleaginous yeast Yarrowia lipolytica. New insights into the storage lipid metabolism of oleaginous yeasts. Appl Microbiol Biotechnol (2012) 93, 1523-1537.
[6]Beopoulos A, Mrozova Z, Thevenieau F, Le Dall MT, Hapala I, Papanikolaou S, Chardot T, Nicaud JM. Control of lipid accumulation in the yeast Yarrowia lipolytica. Appl Environ Microbiol (2008) 74, 7779-7789.
[7]Beopoulos A, Verbeke J, Bordes F, Guicherd M, Bressy M, Marty A, Nicaud JM. Metabolic engineering for ricinoleic acid production in the oleaginous yeast Yarrowia lipolytica. Appl Microbiol Biotechnol (2014) 98, 251-262.
[8]Imatoukene N, Verbeke J, Beopoulos A, Idrissi Taghki A, Thomasset B, Sarde CO, Nonus M, Nicaud JM. A metabolic engineering strategy for producing conjugated linoleic acids using the oleaginous yeast Yarrowia lipolytica. Appl Microbiol Biotechnol (2017) 101, 4605-4616.
[9]Lazar Z, Dulermo T, Neuvéglise C, Crutz-Le Coq AM, Nicaud JM. Hexokinase--A limiting factor in lipid production from fructose in Yarrowia lipolytica. Metab Eng (2014) 26, 89-99.
Our Sponsors
Contact Us
