- Research
- Open Access
Metabolic network analysis and experimental study of lipid production in Rhodosporidium toruloides grown on single and mixed substrates
- Rajesh Reddy Bommareddy†1,
- Wael Sabra†1,
- Garima Maheshwari1 and
- An-Ping Zeng1Email author
https://doi.org/10.1186/s12934-015-0217-5
© Bommareddy et al.; licensee BioMed Central. 2015
- Received: 24 December 2014
- Accepted: 24 February 2015
- Published: 18 March 2015
Abstract
Background
Microbial lipids (triacylglycerols, TAG) have received large attention for a sustainable production of oleochemicals and biofuels. Rhodosporidium toruloides can accumulate lipids up to 70% of its cell mass under certain conditions. However, our understanding of lipid production in this yeast is still much limited, especially for growth with mixed substrates at the level of metabolic network. In this work, the potentials of several important carbon sources for TAG production in R.toruloides are first comparatively studied in silico by means of elementary mode analysis followed by experimental validation.
Results
A simplified metabolic network of R.toruloides was reconstructed based on a combination of genome and proteome annotations. Optimal metabolic space was studied using elementary mode analysis for growth on glycerol, glucose, xylose and arabinose or in mixtures. The in silico model predictions of growth and lipid production are in agreement with experimental results. Both the in silico and experimental studies revealed that glycerol is an attractive substrate for lipid synthesis in R. toruloides either alone or in blend with sugars. A lipid yield as high as 0.53 (C-mol TAG/C-mol) has been experimentally obtained for growth on glycerol, compared to a theoretical maximum of 0.63 (C-mol TAG/C-mol). The lipid yield on glucose is much lower (0.29 (experimental) vs. 0.58 (predicted) C-mol TAG/C-mol). The blend of glucose with glycerol decreased the lipid yield on substrate but can significantly increase the overall volumetric productivity. Experimental studies revealed catabolite repression of glycerol by the presence of glucose for the first time. Significant influence of oxygen concentration on the yield and composition of lipids were observed which have not been quantitatively studied before.
Conclusions
This study provides for the first time a simplified metabolic model of R.toruloides and its detailed in silico analysis for growth on different carbon sources for their potential of TAG synthesis. Experimental studies revealed the phenomenon of catabolite repression of glycerol by glucose and the importance of oxygen supply on the yield and composition of lipids. More systematic studies are needed to understand the mechanisms which should help to further optimize the lipid production in this strain of industrial interest.
Keywords
- Metabolic network analysis
- Elementary mode analysis
- Lipids
- Glycerol
- Biomass
- Oleaginous yeast
Background
During the past years fuel production from biomass has gained enormous interest due to the escalating cost and scarcity of fossil fuels. Biodiesel industry has become important and the use of plant oils as raw materials is not ecologically sustainable because of the relatively high production costs and their competition with global supply of food. Despite the expected high production capacity of biodiesel the anticipated target has increased at a slower rate [1], mainly due to its relatively high production cost. However, utilization of glycerol, a co-product from biodiesel production, is one of the promising options for lowering its production cost [2,3]. In fact, biodiesel production generates about 10% (w/w) glycerol as the main byproduct. Therefore, many researchers have worked on valorization of glycerol and successfully produced value added chemicals which are industrially significant [4-8].
On the other hand, microbial lipids are being explored as raw materials for the production of biodiesel and functional oils with comparable properties of those produced from plant oils [9-11]. Moreover, microbial substitutes of industrially important products like cocoa butter from oils produced by microorganism has been previously reported [12]. An important advantage offered by the application of the oleaginous microorganisms is their ability to produce lipids from cheep substrates. Lignocellulosic biomass is considered as the only foreseeable, feasible and sustainable resource for renewable fuel, and large efforts have been implemented worldwide to replace the first generation of fuels based on high-value sugars and oils with 2nd generation biofuels based on cheaper and more abundant lignocellulosic biomass. In fact, several oleaginous microorganisms were reported for efficient lipid production using industrial wastes and biomass hydrolysate [2,13-18]. Since glycerol is the backbone of microbial lipids, it is of interest to examine if glycerol, especially glycerol from biodiesel production, can be effectively used together with biomass hydrolysate. Few studies have been reported on the use of mixed substrates for the synthesis of microbial lipids.
Several yeast strains are known for lipids production, which include Cryptococcus albidus, Lipomyces lipofera, Lipomyces starkeyi, Rhodosporidium toruloides, Rhodotorula glutinis, Trichosporon pullulan, and Yarrowia lipolytica [19]. Ageitos et al. [19] compared the different yeast strains in terms of productivity and yield, of which R. toruloides and R. glutinis were shown to be the most promising. Y. lipolytica was also proven to be a potential lipid producer, especially after improvement with genetic tools.
The red yeast Rhodosporidium toruloides has a high capability for growth and lipid synthesis on a range of carbon sources from glucose, fructose and xylose to glycerol [20-22]. Lipids can accumulate to a concentration of 60% (w/w) in cell mass of R. toruloides. Its ability to simultaneously assimilate sugars, especially glucose and glycerol has not been studied in detail. Studies on a closely related species R. glutinis showed that glucose and glycerol can be utilized simultaneously with preference toward glycerol which is similar to Y. lipolytica [23].
With substrate cost and availability being continually changing, the utilization of multiple feed stocks is crucial for process viability. Therefore the aim of this study was to analyze the metabolic network and fluxes of R. toruloides grown on different substrates and substrate mixtures, using detailed biochemical knowledge on genome scale. Elementary mode analysis was used to elucidate the optimal pathway and the various fluxes for lipid accumulation from different substrates. Validation experiments were then performed and the kinetics of growth, lipid production and substrate uptake were evaluated. Experiments with biomass hydrolysate as pure substrates or with glycerol were also compared. Since lipid production is a process requiring intensive reducing power and energy, the control of oxygen supply on lipid accumulation and composition is important and studied in a well-controlled bioreactor system. An understanding of these metabolic processes can open doors for metabolic engineering of this yeast and for process optimization.
Results and discussion
In silico analysis of triacylglycerol production on different substrates
Elementary modes (EMs) of the metabolic network of Rhodosporidium toruloides for growth on different substrates with corresponding maximum TAG and cell mass yields
Carbon source | EMs | Maximum yield of TAG [g.g −1 substrate] | Maximum yield of TAG [C-mol.C-mol −1 substrate] | Maximum cell mass yield [C-mol.C-mol −1 substrate] |
---|---|---|---|---|
Glucose | 14,164 | 0.30 | 0.58 | 0.67 |
Glycerol | 33,970 | 0.32 | 0.63 | 0.73 |
Xylose | 9,476 | 0.29 | 0.55 | 0.66 |
Arabinose | 15,231 | 0.27 | 0.53 | 0.63 |
Optimal flux distribution on glucose. All values are relative molar fluxes (mmol.g−1.h−1) normalized to the glucose uptake rate.
Optimal flux distribution on glycerol. All values are relative molar fluxes (mmol.g−1.h−1) normalized to the glycerol uptake rate.
Similarly, the optimal flux distributions with xylose and arabinose as substrates are shown in Additional file 1: Figures S2 and S3, respectively in the Supplement. Higher numbers of EMs were observed on arabinose compared to xylose. About 96% of the modes produced cell mass and 23% of the modes showed TAG production on both the pentoses. A very high PP pathway fluxes is observed on both pentoses, obviously due to the requirement of NADPH for uptake of these substrates [24]. Xylose showed slightly higher theoretical yields of TAG than arabinose. Most of the fluxes are channeled through the gluconeogenic glucose 6-phosphate isomerase reaction into the PP pathway on both the pentoses. Similar channeling of fluxes is observed towards the pyruvate dehydrogenase complex on both the substrates. Due to the high demand for NADPH on arabinose, the oxaloacetate transporter flux into the mitochondrion should be inactive whereas on all the other substrates it should be active for maximal TAG synthesis. This accumulation of oxaloacetate may drive a high flux through the malate dehydrogenase (MDH) in the cytosol towards malate which in turn also increases the flux through the cytolsolic malic enzyme on arabinose than on xylose.
Optimal flux distribution on glucose and glycerol. All values are relative molar fluxes (mmol.g−1 h−1) normalized to the glucose uptake rate.
Controlled bioreactor cultivations of R. toruloides and the utilization efficiency of different substrates
Batch cultivation of R. toruloides with either glycerol (a) or glucose (b) in pH controlled bioreactor: cell mass, lipid, substrate and pO 2 as a function of time.
Experimental lipid yields and productivity of different R. toruloides strains grown on different substrates
Carbon source | Lipid productivity | Condition | Lipid yield * (g/g substrate) | Lipid yield (C-mol.C-mol −1 substrate) | Reference |
---|---|---|---|---|---|
(g/L/h) | |||||
glucose | 0.15 | Batch- N limiting, pO2 controlled | 0.15 | 0.29 | This work |
glycerol | 0.06 | Batch- N limiting, pO2 controlled | 0.24 | 0.47 | |
glucose + glycerol | 0.12 | Batch- N limiting, pO2 controlled | 0.17 | 0.33 | |
glucose | 0.07 | Batch- N limiting, pO2 un-controlled | 0.12 | 0.23 | |
glycerol | 0.06 | Batch- N limiting, pO2 un-controlled | 0.27 | 0.53 | |
glucose + glycerol | 0.07 | Batch- N limiting, pO2 un-controlled | 0.2 | 0.38 | |
Glucose + glycerol + xylose | 0.08 | Batch- N limiting, pO2 controlled | 0.22 | 0.42 | |
(10:20:30) | |||||
Biomass hydrolysate + glycerol | 0.09 | Batch- N limiting, pO2 controlled | 0.17 | -- | |
(glucose- xylose -glycerol =10:20:30) | |||||
glucose | - | Batch, phosphorous limiting | 0.21 | -- | [17] |
glucose | - | Continuous- nitrogen limiting | 0.19 | -- | [38] |
ATP requirements for growth, lipid production and maintenance are supplied mainly through the TCA cycle in the mitochondria. In fact, our in silico analysis was all done with a fixed P:O ratio of 1.2. The effects of oxidative phosphorylation (with varied P:O ratio) on TAG yields using glucose as a substrate were analyzed using the proposed model. The change in P:O ratios (from 1.2 to 2) neither showed significant effect on the TAG yields (from 0.58 to 0.60 Cmol.Cmol −1 glucose), nor cell mass yield (0.67 to 0.71 Cmol.Cmol −1 glucose), respectively. Hence, it can be concluded that ATP generated by oxidative phosphorylation is not a major limiting factor for TAG synthesis. In agreement with the in silico analysis, controlling the oxygen concentration at 50% air saturation in the fermentation broth of R. toruloides grown either on glucose or glycerol throughout the cultivation process did not have any significant effect on the yield (Table 2). Similar to the cultivations without pO2 control (e.g. O2 limitation in phases 2 and 4, see Figure 4), the maximal growth rate with glucose was 0.23 h−1 compared to 0.13 h−1 with glycerol in pO2 controlled cultivations. The maximum lipid content on glycerol was 61% vs. 57% in pO2 uncontrolled culture, whereas it was 48% on glucose vs. 41% in pO2 uncontrolled culture. The lipid productivity increased significantly in the pO2 controlled experiments, mainly because of the increased growth rates.
pO 2 uncontrolled cultivation of R. toruloides and the diauxy growth behavior on a mixture of glucose and glycerol (10:90 g/g (a)), and a comparison of the different substrate and blend on the lipid yield on produced cell mass (b).
As shown in Figure 5a, a clear diauxic growth was observed in the mixed substrate cultivations: glycerol was consumed only after glucose consumption in this case. Despite of the observed catabolite repression, the addition of glycerol enhanced the lipid yield on glucose significantly (Figure 5b), confirming the predictions from the in silico analysis. In fact, the mixed substrate cultivation has the dual advantages of efficient cell mass production (normally maximized with glucose) with higher lipid content (obtained normally with glycerol). The lipid yields on the substrate consumed and the specific lipid productivities on cell mass are higher when glucose and glycerol are used in mixture rather than only glucose (Table 2).
Cell mass and lipid production by R. toruloides grown on mono-substrate and on different variation of dual substrate fermentation.
Fatty acid composition of lipid produced by R.toruloides grown on glucose or glycerol and on mixture. a. Fatty acid composition from a pO2 controlled cultivation, b. fatty acid composition on a pO2 un-controlled cultivation.
R. toruloides is a known lipogenic yeast and the results presented here confirm its ability to accumulate over 60% of its cell mass as lipid. However, lipid accumulation was strongly affected by the nature of the carbon source provided. The recently sequenced and annotated genome of R. toruloides, its proteomic analysis and the available protein annotation have opened doors to understand the underlying mechanism of this organism for lipid production [31-33]. In this work, elementary modes were used to decompose the complex metabolic network into its basic functioning units and to identify the potentials of triacyglyceride production on different substrates in R. toruloides. Maximum theoretical TAG yields on hexoses (glucose), pentose (xylose and arabionse), glycerol and on mixture of hexoses & glycerol, pentose & glycerol have been estimated (Table 1) and were in general agreement with previously reported theoretical maximum yields [34,35]. As shown from the computed solution span in Additional file 1: Figure S1, the production is still far from the theoretical optimum and the distance between the actual production state on glucose or glycerol and the theoretical optimum suggests an enormous potential for future optimization. In silico optimization, identification of limiting steps and finally suggestions for future genetic modification are discussed below.
One of the key processes for fatty acid biosynthesis is the provision of reducing power (e.g. NADPH) to reduce the acetyl group and channel it into the acyl chain of fatty acid. In Y. lipolytica, the PP pathway is assumed to be the sole supplier of NADPH for lipid synthesis, since it does not possess a cytosolic malic enzyme [36] and the deletion of mitochondrial malic enzyme did not show any effect on lipid production [37]. In R. toruloides, an alternative NADPH supplying reaction would be the cytosolic NADP-dependent isocitrate dehydrogenase (ICDH) which is inactive in the predicted optimal flux distribution of glucose (Figure 1). A single gene deletion study of our model was performed to remove the cytosolic malic enzyme from the reactions. A reduction in maximum theoretical yield of TAG was observed (from 0.30 g.g−1 to 0.27 g.g−1) on glucose and glycerol (0.32 g.g−1 to 0.27 g.g−1). However, the theoretical maximum yield retained to 0.30 g.g−1 on glucose and 0.32 g.g−1 on glycerol if a NADP-dependent acetaldehyde dehydrogenase (ALD6) is incorporated. This enzyme constitutively catalyzes the conversion of acetaldehyde to acetate, generating an NADPH in the cytoplasm. Another alternate route for supplying NADPH as proposed by Ratledge [34] can be a mitochondrial NAD-dependent ICDH acting in the reverse direction. EFM analysis and optimal flux distribution were done (Additional file 1: Figure S5) and the maximum theoretical yield of TAG on glucose is retained to 0.30 g.g−1 glucose. A third possible target could be a heterologous NADPH generating enzyme or an endogenous engineered NADPH generating enzyme, both in the glycolytic pathway [38] which could be a potential source for NADPH. By changing GAPDH, which is a NAD-dependent glyceraldehyde dehydrogenase in the glycolytic pathway, to an NADP-dependent enzyme can increase the theoretical TAG yields by 7% on glucose and 9% on glycerol.
Elementary modes (EMs) and theoretical TAG yields with heterologous genes/reactions
Carbon source | EMs | Characteristics | Maximum yield of TAG [C-mol.C-mol −1 substrate] | Maximum yield of TAG [g.g −1 substrate] |
---|---|---|---|---|
Glucose | 30,132 | Transhydrogenase | 0.64 | 0.33 |
Glycerol | 57,172 | Transhydrogenase | 0.68 | 0.35 |
Xylose | 21,323 | Transhydrogenase | 0.64 | 0.33 |
Arabinose | 27,264 | Transhydrogenase | 0.64 | 0.33 |
Glucose | 26,878 | Cytosolic NADP-dependent GAPDH | 0.62 | 0.32 |
Glycerol | 42,578 | Cytosolic NADP-dependent GAPDH | 0.67 | 0.35 |
Glucose | 6858 | Without cytosolic Malic enzyme | 0.51 | 0.27 |
Glucose | 12,487 | With NADP-dependent ALD6 | 0.58 | 0.30 |
Glycerol | 23,658 | With NADP-dependent ALD6 | 0.63 | .032 |
Glucose | 15,331 | Cytosolic NADH source | 0.68 | 0.36 |
Glycerol | 35,804 | Cytosolic NADH source | 0.68 | 0.35 |
Conclusions
The present work describes the successful application of reconstruction of metabolic network and it’s in silico analysis for determining and understanding the potential and metabolic pathways for lipid production in R. toruloides grown on different substrates, especially for substrate blends. Cultivations of R. toruloides were carried out with different substrates and in a well-controlled bioreactor system. The experimental results are in general agreement with model predictions in terms of lipid yield.
The constructed metabolic model can be used to guide further optimization of lipid synthesis in this strain. The maximal lipid yield experimentally achieved is still significantly below the theoretical maximum, especially for growth on glucose (0.29 vs. 0.58 C-Mol/C-Mol) and its blend with glycerol. Several strategies to increase the lipid yield are identified and discussed with the help of the metabolic model.
Methods
Microorganism and media
R. toruloides DSMZ 4444 was used for the current study. The strain was maintained at −80°C on potato dextrose medium with 20% glycerol (v/v). The medium for seed cultures and main cultures was a nitrogen limited medium which is similar to that reported previously [26]. Carbon sources (glucose, glycerol, xylose, arabinose or biomass hydrolysates) were autoclaved separately and added together with sterile FeCL3 and CaCl2 solutions and inoculated immediately. Spruce BH (Borregard, Norway) was also used in co-substrate fermentation with glycerol. An enzymatic hydrolysis of spruce was done without buffer. The hydrolysate was then heated at 80°C for 15–20 min to inactivate the enzymes. The supernatant was removed and filtered with a centrifuge with filter bag. The sample was then concentrated by vacuum evaporation at 60°C. The concentrated hydrolysate contained 550 g/L glucose and 35 g/L xylose.
Cultivations
Seed cultures and cultivations in flasks were performed in baffled shake flasks incubated at 30°C and 180 rpm for 24 h. Batch cultivations were performed in a 1.5 L well-equipped parallel bioreactor system (DASGIP parallel bioreactor system, Jülich, Germany) with 1 L initial working volume. Cultivations were started by inoculating 30 mL (3%) from the seed cultures grown for 24 h. pH was maintained at 6.0 using 5 N NaOH and 2 M HCL. Dissolved oxygen was maintained at 50% air saturation. Carbon dioxide evolution rates and oxygen uptake rates were automatically evaluated by the online DASGIP off gas analyzing system equipped with sensors from Bluesens.
Analytical methods
Cell growth was recorded as optical density at 600 nm. Cell mass was harvested during the cultivations after centrifugation (5000 rpm, 10 min at 4°C). Cell dry weight was determined gravimetrically after drying the harvested cells in an oven at 80°C to a constant weight. Extraction of lipids was performed with a modified method described previously using Folsch solution (Chloroform: Methanol = 2:1 vol.vol-1, [41]. Non-lipid cell mass was calculated after subtraction of intracellular lipids from the total cell mass. Quantification of glucose, glycerol and organic acids was carried out using high-performance liquid chromatography (HPLC; Kontron Instruments, United Kingdom) with separation on an Aminex HPX-87H column at 60°C with 0.005 M H2SO4 and detection via refractive index or by UV absorption at 210 nm. Ammonia concentration in the supernatant was determined by photometric measurements using a kit from Macherey Nagel, Germany. GC analysis of the fatty acid methyl esters was performed as reported [42] with a Varian 3900 gas chromatograph equipped with a flame ionization detector (FID) and a TR-FAME column (Thermo Scientific, Germany, 50 m X 0.22 mm X 0.25 μm).
Metabolic network and elementary mode analysis
Metabolic model of Triacylglycerol producing Rhodosporidium toruloides .
The metabolic network with D-glucose as a substrate comprises of 69 reactions, of which 27 are reversible with 61 internal metabolites and 8 external metabolites. With glycerol as a sole carbon source, the network is comprised of 71 reactions (28 reversible) of which 61 are internal and 8 external metabolites. The network with D-xylose and L-arabinose comprises 71 and 73 reactions respectively. Theoretical maximum yields were calculated based on the obtained fluxes. All fluxes are given in mmol.g−1.h−1 normalized to the substrate uptake rate.
Notes
Declarations
Acknowledgements
The financial support of this investigation from the BMBF under the project ‘Bio4Oil project number: 03SF0467’ is gratefully acknowledged. We thank the project partners Prof. Geoge Aggelis from the University of Patra und Prof. Seraphim Papanikoloau from Agricultural University of Athens for helpful discussion. We also thank Dr. Wei Wang for helping to set-up the GC method for lipid analysis.
Authors’ Affiliations
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Copyright
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