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Untargeted metabolomics analysis of Ralstonia eutropha during plant oil cultivations reveals the presence of a fucose salvage pathway

Process engineering of biotechnological productions can benefit greatly from comprehensive analysis of microbial physiology and metabolism. Ralstonia eutropha (syn. Cupriavidus necator) is one of the best studied organisms for the synthesis of biodegradable polyhydroxyalkanoate (PHA). A comprehensive metabolomic study during bioreactor cultivations with the wild-type (H16) and an engineered (Re2058/pCB113) R. eutropha strain for short- and or medium-chain-length PHA synthesis has been carried out. PHA production from plant oil was triggered through nitrogen limitation. Sample quenching allowed to conserve the metabolic states of the cells for subsequent untargeted metabolomic analysis, which consisted of GC–MS and LC–MS analysis. Multivariate data analysis resulted in identification of significant changes in concentrations of oxidative stress-related metabolites and a subsequent accumulation of antioxidative compounds. Moreover, metabolites involved in the de novo synthesis of GDP-l-fucose as well as the fucose salvage pathway were identified. The related formation of fucose-containing exopolysaccharides potentially supports the emulsion-based growth of R. eutropha on plant oils.


Scientific Reports
| (2021) 11:14267 | https://doi.org/10.1038/s41598-021-93720-9 www.nature.com/scientificreports/ which mediate the hydrolyzation of the triacylglycerols into free fatty acids, monoacylglycerols, diacylglycerols and glycerol and consequently allow the formation of a natural emulsion 39 . In this study, the metabolic characteristics of R. eutropha H16, a scl-PHA producer, and Re2058/pCB113, a scl-co-mcl-PHA producer, were examined during bioreactor cultivations under growth and nitrogen limitation (PHA synthesis) conditions using plant oil as the main carbon source. Both strains were evaluated by nontargeted metabolite profiling. Since the two strains produce different PHA polymer products, it was assumed that the metabolite profiles of the strains would exhibit significant differences, which were observed in this study. In addition, the metabolite profiling yielded the identification of the de novo and salvage pathway synthesis of GDP-l-fucose, a component of exopolysaccharide/lipopolysaccharide (EPS/LPS), as well as oxidative stressrelated metabolite changes.

Results
In this study, R. eutropha H16 and the engineered strain R. eutropha Re2058/pCB113 were grown in biological triplicate bioreactor cultivations to perform non-targeted metabolite analysis under controlled conditions for a further elucidation of the metabolic activities during growth and PHA formation under nitrogen limitation on plant oils.
Bioreactor cultivations. The cultivations were performed as batch cultivations with a NH 4 Cl and PO content as described previously 20,32 . Faster growth was observed for R. eutropha H16 with nitrogen being depleted after 30 h, compared to the nitrogen depletion after 36 h for R. eutropha Re2058/pCB113 (Fig. 1a). The cultivation of the wild-type strain yielded in a final cell dry weight (CDW) of 27.8 g L −1 with a polyhydroxybutyrate (PHB) content of 62 wt% (17.2 g PHB L −1 ). Thus, a CDW yield of 0.93 g CDW g PO −1 including a PHB yield of 0.57 g PHA g PO −1 was achieved. The maximal PHB space time yield (STY) was observed after 36 h (0.42 g PHB L −1 h −1 ). In contrast, the engineered strain grew to a lower final CDW of 21.6 g L −1 but accumulated 81 wt% P(HBco-19 mol%HHx) (17.5 g PHA L −1 ). A very similar PHA yield was achieved (0.58 g PHA g PO −1 ) but compared to the wild-type strain the total CDW yield and maximal STY for this strain were 23% and 21% lower, respectively (0.72 g CDW g PO −1 and 0.42 g PHA L −1 h −1 at 48 h) ( Exploratory multivariate data analysis. The cultivation samples mentioned above were analyzed by gas chromatography-mass spectrometry (GC-MS) and liquid chromatography-mass spectrometry (LC-MS) for non-targeted metabolite profiling in a range of 50-1700 g mol −1 . In total, 1,054 substances were identified and 656 of them could be annotated. Among the metabolites identified, 87 were shown to be di-, tri-and tetrapeptides. The substances found in the samples of each cultivation were analyzed by principal component analysis (PCA), which is an unsupervised multivariate data analysis method. After the projection of the high dimensional data into the 2D space by PCA, the samples were grouped by their sampling time point (Fig. S1). The first two principal components (PCs) of the R. eutropha H16 samples depict in total 56.6% of the variance (Fig. 1b). A clear separation of samples from the different time points can be seen along the first PC, whereas samples during the nitrogen limitation (30 and 36 h) are clustered closely together and cannot be completely distinguished. ANOVA analysis showed that the concentrations of 168 metabolites change significantly ( Fig. 1c; Table S2). In contrast, the metabolic profiles of the R. eutropha Re2058/pCB113 samples can only be differentiated between samples of the growth phase (24 and 30 h) and of the nitrogen limitation phase (36 and 48 h) along the first two PCs, which depict 54.7% of the variance in the sample set (Fig. 1d). ANOVA analysis showed that 88 metabolites change significantly ( Fig. 1e; Table S3). The clear separation of the metabolic profiles of the samples before and after nitrogen limitation for both strains led to the conclusion to investigate the two phases further by clustering the respective samples of each phase.
After clustering all samples into the corresponding nitrogen availability phase, the dataset was further analyzed (Fig. 1f). The first two PCs explain 45.2% of the variance and allow a good separation of the classes along both PCs. Using partial least square discriminant analysis (PLS-DA) the classes are clearly separated, but only 33.8% of the variance is explained (Fig. S1c). The t-test showed that the concentrations of 216 out of the 656 metabolites change significantly (Fig. 1g). In detail, 148 of the 216 metabolite concentrations changed more than two-fold: 54 concentrations increased after the nitrogen limitation, whereas 94 decreased (Table S4 & S5). Within those metabolites, the change of many different lipids, fatty acids and peptides was detected. In addition, methionine sulfoxide as a biomarker for oxidative stress decreased eightfold after N-limitation, whereas the concentration of multiple antioxidants, e.g. different tocopherols, increased. Moreover, the significant change of three metabolites (fucose, GDP-fucose, GDP-mannose), which are connected to the fucose sugar metabolism was identified (Table 1).
In order to identify general differences between the metabolite profiles of the two strains, all samples were grouped by the respective strain (Fig. 1h). In total 91 metabolite concentrations varied two-fold: 63 were higher in the wild-type strain and 28 higher in the engineered strain (Fig. 1i, Table S6 & S7). Especially, amino acids were higher in abundance in the wild-type strain.
Tricarboxylic acid cycle and glycerol pathway analysis. The tricarboxylic acid (TCA) cycle is the central pathway for aerobic growth in all organisms. During growth of R. eutropha on plant oil, TCA cycle precursors are supplied from the β-oxidation pathway in form of acetyl-CoA or through the catabolism of glycerol. The glycerol levels in both strains decreased during the cultivation to a minimum observed at the last time point (Fig. 2). In contrast, the levels of glycerol-3-phosphate, which is a direct product of glycerol phosphorylation did www.nature.com/scientificreports/ not decrease. Interestingly, the levels of acetyl-CoA in both strains clearly decreased after nitrogen limitation. Within the TCA cycle, overall higher levels of succinate and fumarate were detected, whereas citrate had similar levels in both strains not considering the 12 h timepoint of the wild-type strain. A decrease of cis-aconitate throughout the whole cultivation was detected. The 2-oxoglutarate concentration in both strains was the lowest at the first time point, the highest at the second time point and then decreased. Even though the trend was the same, higher 2-oxogluatarate levels were observed in the wild-type strain.
Polyhydroxyalkanoate pathway analysis. Our main purpose of cultivating R. eutropha is the production of PHA bioplastic. Whereas the wild-type strain can only synthesize scl-PHA, the engineered strain is able to produce the copolymer P(HB-co-HHx). A decrease of acetyl-CoA was observed for both strains after nitrogen limitation, whereas the acetoacetyl-CoA levels did not show a significant trend in either strain (Fig. 3). The metabolic profiling method did not differentiate between (R)-and (S)-hydroxyacyl-CoAs, which are either www.nature.com/scientificreports/ β-oxidation intermediates or PHA precursors. In this context, no alteration of the HHx-and HB-CoA levels were detected for the wild-type strain, but a slight decrease of HHx-CoA after the nitrogen limitation and overall low HB-CoA levels were detected in the engineered strain. The acyl-CoA levels (hexanoyl-and butanoyl-CoA) were in general higher in the engineered strain and a trend of concentration decrease towards the last time point for these metabolites can be seen.

Fucose pathway analysis. GDP-l-fucose is an important precursor for the synthesis of bacterial LPS
and EPS, which can be synthesized either de novo or via the fucose salvage pathway, which is rarely found in prokaryotes [40][41][42] . During analysis of metabolic changes induced by nitrogen depletion, l-fucose was identified as a significantly increasing metabolite in both strains (Table 1), whereas GDP-l-fucose and GDP-d-mannose were identified as significantly decreasing metabolites (Table 1). Additionally, further metabolites from both GDPl-fucose synthesis pathways were identified: d-mannose and l-fucose 1-phosphate (Fig. 4). In this context, neither the enzymes for the de novo synthesis from GDP-4-oxo-6-deoxy-mannose (EC 1.

Antioxidants and antioxidant-related metabolites.
Methionine sulfoxide is the oxidized form of methionine, which indicates oxidative stress 43 . High levels of methionine sulfoxide were detected in the beginning of both cultivations, which then significantly decreased towards the end, whereas a significant increase of different antioxidants was detected (Fig. 5, Table S2, Table S3). The oxidized form of glutathione decreased in concentration throughout the cultivations similar to methionine sulfoxide. In contrast, cysteine glutathione disulfide, which is also formed upon oxidative stress, did not exhibit any noticeable trends throughout the cultivations, but ethenodeoxyadenosine, a product derived from oxidative stress, increased and a significant increase of the amino acid derivate 5-methyltetrahydropteroyltri-L-glutamate was detected. The antioxidants δ-tocopherol, β-tocopherol, octyl gallate significantly increased, but other substances with antioxidative effects like epigallotechin sulfate and lipoic acid did not show any trends. Additionally, D-sedoheptulose 7-phosphate and thiamine pyrophosphate, which both play a role in stress response mechanisms, were identified, but did not show any significant trends.

Discussion
Fucose is a 6-deoxyhexose, which is found in LPS or EPS. Fucose-containing LPS or EPS are synthesized from guanosine diphosphate fucose (GDP-l-fucose), which can be synthesized via two pathways: The de novo pathway produces GDP-l-fucose from GDP-mannose or the salvage pathway, where GDP-l-fucose is synthesized from LPS or EPS 41 . The latter has been identified apart from the presence in eukaryotes in only one prokaryote so far, the gut commensal bacterium Bacterioides fragilis 9343 42 . A successful integration of the B. fragilis pathway into the Escherichia coli was recently described 44 . We identified for the first time the presence of GDP-l-fucose and metabolites in the GDP-l-fucose de novo synthesis and fucose salvage pathway in R. eutropha. Fucose-containing EPS have been reported to be surface active compounds, which have emulsion stabilizing characteristics [45][46][47] . Even though several studies have shown the efficient PHA production from lipids with R. eutropha 21,23,32,[36][37][38] , the presence of natural EPS emulsifiers was never described before. A large fraction of fucose in the EPS of R. eutropha IPT 027 was identified, but the emulsification behavior was not tested 48 . In this context, fucose-containing EPS potentially support the lipase-mediated emulsification process 39 , which would explain the excellent growth of R. eutropha on oleaginous substrates. A similar mechanism was described in Pseudomonas aeruginosa, which produces extracellular rhamnolipids from PO distillate with emulsifying properties 49 . The identification of this new metabolic pathway may facilitate the Table 1. Metabolites connected to oxidative stress and fucose sugar metabolism, which significantly change (FDR-adjusted p value ≤ 0.05) at least two-fold after the nitrogen limitation. Samples of both cultivations (strains H16 and Re2058/pCB113) were grouped according to nitrogen availability resulting in n = 12 samples in each phase. www.nature.com/scientificreports/ www.nature.com/scientificreports/ production of novel engineered strains with an increased fucose-EPS production for an enhanced emulsion formation. This could lead to strains with a reduced lag phase on plant oil or hard to emulsify solid waste animal fats, as it was shown for cultures with a chemical pre-emulsified PO or strains overexpressing an extracellular lipase 39,50 . The fucose-related metabolites in our study were identified by the annotation and subsequent statistical analysis of 656 metabolites, which are at least sixfold more annotated metabolites than in other comprehensive metabolomic studies with R. eutropha [13][14][15] . Genes for synthesis of GDP-l-fucose via both pathways have not been discovered or characterized in R. eutropha so far. The decrease of GDP-d-mannose and GDP-l-fucose throughout our cultivations suggests, that the de novo synthesis pathway is highly active in the beginning to build up EPS (Fig. 4). In contrast, the significant increase of l-fucose throughout the cultivations indicates, that the salvage pathway is more active during the later phase of the cultivation. The fucose salvage pathway was considered to be only present in eukaryotes until a bifunctional l-fucokinase/fucose-1-phosphate guanylyltransferase enzyme in the mammalian gut commensal bacterium B. fragilis was identified 42 . A BLAST search for a similar enzyme in R. eutropha did not result in a positive match (data not shown). High levels of methionine sulfoxide were detected in the beginning of the cultivations and these levels significantly decreased towards later time points (Fig. 5). Methionine sulfoxide is a product of methionine oxidation due to the presence of reactive oxidative intermediates, which are typically present in an aerobic bioprocess 43,51 . Although R. eutropha cells, which are exposed to oxidative stress, typically produce protective proteins, DNA www.nature.com/scientificreports/ damage occurs 10,11 . The increase in ethenodeoxyadenosine in our cultures can also be interpreted as an indication of such DNA damage (Fig. 5). Additionally, oxidative stress in R. eutropha is counteracted by antioxidative molecules 52 . In this study, we detected a significant increase of octyl gallate and two tocopherols throughout the cultivations (Fig. 5). The latter are hydrophobic antioxidants, which are present in high concentrations in PO 53 .
It is most likely that R. eutropha is able to absorb these compounds, from the PO containing media, to cope with oxidative stress. The analysis of metabolites in the PHA homeostasis pathway revealed for both strains that the main precursor metabolite acetyl-CoA is available at higher levels prior to nitrogen limitation and the concentrations drastically decrease after the onset of nitrogen limitation (Fig. 3). It is known that β-ketothiolases (PhaAs) are highly selective for acetyl-CoA and an enhanced expression of the phaA gene can yield in enhanced PHA accumulation [54][55][56] . However, phaA was found to be constitutively expressed in R. eutropha H16, which would not explain the lower levels of acetyl-CoA after the nitrogen depletion 8,57 . Multiple PHA mobilizing enzymes, namely PHA depolymerases PhaZ1-7 and oligomer hydrolases PhaY1-2, are responsible for the degradation of the intracellular PHA and finally supplying acetyl-CoA 58-60 . The high activity of the PHA mobilizing enzymes under growth conditions and downregulation under nutrient depleted conditions was previously shown, and can help to explain the acetyl-CoA pool size during growth in our experiments 61 . Another interesting finding about PHA metabolism is the absence of any HHx-CoA pools in the engineered strain Re2058/pCB113, but it is known that very high contents of HHx in the PHA are present during the growth phase 20,32 . Together with the fact that overall the HB-CoA levels are lower in the engineered strain compared to the wild-type strain, a very high activity of the PhaC Ra can be assumed. A further engineering of the pathways supplying the acyl-CoA precursors for the PhaC Ra could therefor potentially enhance the PHA productivity. The high polymerase activity could also explain why the engineered strain produces PHA with a significantly lower average molecular weight compared to the wild-type strain or a similar engineered strain harboring a low active PHA synthase, such as PhaC BP-M-CPF4 27 . The comparison of the two strains resulted in the detection of a shortage of many amino acids in the engineered strain (Table S6). Due to the constant expression of the complete PHA operon, which is located on the plasmid pCB113, the engineered strain produces quantitatively more enzymes compared to the wild-type strain, which results in a PHA accumulation in the growth phase and could be the reason for the overall lower amino acid levels in the engineered strain.
In conclusion, our comprehensive analysis of data from untargeted metabolomics of R. eutropha cultivations facilitated the identification of the fucose salvage pathway, which was previously identified in just one other www.nature.com/scientificreports/ bacterium. Even though R. eutropha is a well characterized organism, the presented approach allowed to add more understanding to the complexity of the microbial metabolic network. In detail, the findings presented here elucidate a potential additional emulsification mechanism for the efficient growth on oleaginous feedstocks. It can also be emphasized that diversity of fucose metabolism pathways in bacteria is poorly understood, suggesting that unknown enzymes involved in the fucose salvage pathway can be identified in future studies.

Experimental section
Bacterial strains. The experiments were performed with the R. eutropha wild-type strain H16 (DSM-428, Leibniz Institute DSMZ, Germany) or the engineered strain Re2058/pCB113 20 . In contrast to the wild-type strain, the engineered strain is able to synthesize P(HB-co-HHx) when grown on fatty acid containing substrates.
Growth media and preculture conditions. The cultures were grown either in dextrose-free tryptic soy broth (TSB) media (Becton Dickinson, USA) or in minimal salt media (MSM) as described previously 55   www.nature.com/scientificreports/ Initially, cultures were grown overnight in TSB media inoculated from a single colony until an optical density (OD 600 ) ≥ 5. The overnight cultures were harvested by centrifugation, resuspended in 0.85% (w v −1 ) NaCl and used to inoculate the second preculture to an initial OD 600 of 0.05. A second preculture was grown in 50 mL MSM containing 0.4% (w v −1 ) NH 4 Cl and 1% PO (w v −1 ) for 24 h in baffled glass flasks (250 mL, DURAN, Germany) at 200 rpm and 30 °C.
Bioreactor cultivations. Bioreactor cultivations were performed in 6.6-L bioreactors equipped with two six-blade Rushton impellers (BIOSTAT Aplus, Sartorius AG, Germany). The experiments were operated as batch cultivations with an initial working volume of 2.5 L MSM containing 3% (w v −1 ) PO and 0.4% (w v −1 ) NH 4 Cl. The temperature was maintained at 30 °C and the pH was controlled at 6.8 ± 0.1 by addition of 2 M NaOH and 1 M H 3 PO 4 . The aeration rate was set to 0.5 vvm and the dissolved oxygen concentration was kept above 40% through an automated stirrer cascade ranging from 300 to 1350 rpm. Two pairs of cable ties were mounted in the head space at the stirrer shift to mechanically break the foam.
Analytical methods. The CDW was determined by harvesting 5-15 mL of the culture suspension in preweighed test tubes by centrifugation (4000×g, 10-20 min, 4 °C). The pellets were washed with a mixture of 2 mL cold n-hexane and 5 mL cold water to remove residual lipids. The washed pellet was resuspended in 1-2 mL cold water, frozen at − 80 °C, dried for 24 h by lyophilization, and the CDW was determined by weighing the test tubes. The PHA content in the dried cells was determined using a methanolysis protocol described previously 20 . The nitrogen content was determined by clarifying the supernatant through a 0.2 µm cellulose acetate filter and subsequently using an ammonium test kit (Spectroquant, Merck KGaA, Germany) according to the manufacturer's instructions.
Metabolomic and statistical analysis. To conserve the metabolic state of the cells in each sample, all preparations were carried out as quickly as possible, the equipment was kept cool, and work was carried out over a dry ice/ethanol mixture. The quenching solution consisted of 60% (v v −1 ) methanol in water (Milli-Q). Prior to the sampling procedure, 15-mL tubes, the quenching solution and a centrifuge rotor were pre-cooled to − 40 °C. A 2 mL aliquot of the culture was removed from the bioreactor and added immediately to a tube containing 10 mL of the quenching solution. After mixing, the samples were centrifuged (1500×g, 5 min), the supernatant discarded, and the sample was washed with 10 mL quenching solution (− 40 °C). The supernatant was discarded, the pellet was immediately frozen in liquid nitrogen and stored at − 80 °C until shipping. The samples were shipped on dry ice to Metabolon GmbH (Munich, Germany), which carried out the metabolomic analysis and annotation. The protocol of GC-MS and LC-MS setup including sample preparation has been described in detail previously 62 . The LC separation was performed using hydrophilic interaction chromatography with a ZIC-HILIC column (3.5 μm, 200 Å, Merck Sequant, Umeå, Sweden), operated by an Agilent 1290 UPLC system (Agilent, Santa Clara, CA, USA). The LC mobile phase was a linear gradient from 90 to 70% acetonitrile over 15 min, followed by a linear gradient from 70 to 10% acetonitrile over 1 min, 3 min wash with 10% and 3 min reequilibration with 90% acetonitrile. The flow rate was 400 μL min −1 , the injection volume was 1 μL. The mass spectrometry was performed using a 6540 QTOF/MS Detector (Agilent, Santa Clara, CA, USA).
The metabolomic analysis consisted of 12 samples for each strain (4 time points, 3 biological triplicates). Nontargeted metabolite profiling comprising analysis by GC-MS and LC-MS was described previously 62 . Metabolites were analyzed in a range of 50-1700 g mol −1 with an accuracy up to 1 -2 ppm and a resolution of mass/∆mass of 40.000. The dimensionless metabolite concentration is shown through an internal standard normalization. Metabolites that were not annotated are listed according to their mass and retention time in minutes (e.g. 731.5113-1.55).
The generated data was explored by multivariate data analysis using the MetaboAnalyst 4.0 platform 63 . First, the data was normalized by autoscaling (mean centering and division by standard deviation) and a PCA was performed. PCA is used as a technique for dimensionality reduction and data visualization. It is an orthogonal projection of the high dimensional data onto a lower dimensional linear space, such that the variance of the projected data is maximized. In this lower dimensional space, the eigenvector having the largest eigenvalue is known as the first PC 64 . A one-way analysis of variance (ANOVA) was performed based on false discovery rate (FDR) adjusted p values ≤ 0.05. In addition, a Fisher's significant difference test was conducted. When differences of two sample classes were investigated, a t-test with FDR adjusted p values ≤ 0.05 was performed and a fold change analysis based on the ratio of mean concentrations with a threshold of ≥ 2 was conducted.

Data availability
The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation. www.nature.com/scientificreports/