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Environmental Microbiology (2015) 17(1), 156–170

doi:10.1111/1462-2920.12537

D-Xylose assimilation via the Weimberg pathway by solvent-tolerant Pseudomonas taiwanensis VLB120

Kirsten A. K. Köhler,1 Lars M. Blank,2 Oliver Frick1* and Andreas Schmid1 1 Laboratory of Chemical Biotechnology, TU Dortmund University, Emil-Figge-Str. 66, Dortmund D-44227, Germany. 2 iAMB – Institute of Applied Microbiology, RWTH Aachen University, Worringer Weg 1, Aachen 52074, Germany. Summary The natural ability of Pseudomonas taiwanensis VLB120 to use xylose as sole carbon and energy source offers a high potential for sustainable industrial biotechnology. In general, three xylose assimilation routes are reported for bacteria. To elaborate the metabolic capacity of P. taiwanensis VLB120 and to identify potential targets for metabolic engineering, an in silico/in vivo experiment was designed, allowing for discrimination between these pathways. Kinetics of glucose and xylose degradation in P. taiwanensis VLB120 was determined and the underlying stoichiometry was investigated by genome-based metabolic modelling and tracer studies using stable isotope labelling. Additionally, reverse transcription quantitative polymerase chain reaction experiments have been performed to link physiology to the genomic inventory. Based on in silico experiments, a labelling strategy was developed, ensuring a measurable and unique 13C-labelling distribution in proteinogenic amino acids for every possible distribution between the different xylose metabolization routes. A comparison with in vivo results allows the conclusion that xylose is metabolized by P. taiwanensis VLB120 via the Weimberg pathway. Transcriptomic and physiological studies point to the biotransformation of xylose to xylonate by glucose dehydrogenase. The kinetics of this enzyme is also responsible for the preference of glucose as carbon source by cells growing in the presence of glucose and xylose. Received 18 February, 2014; accepted 9 June, 2014. *For correspondence. E-mail [email protected]; Tel. +49 231 755 7180; Fax +49 231 755 7382.

© 2014 Society for Applied Microbiology and John Wiley & Sons Ltd

Introduction Lignocellulosic substrates gain increasing interest as alternative feedstock in industrial biotechnology, with bioethanol production as a front runner (Weber et al., 2010; Khattab et al., 2013; Svetlitchnyi et al., 2013). Lignocellulosic hydrolyzates contain a mixture of hexose (e.g. D-glucose) and pentose sugars (e.g. D-xylose, L-arabinose), as well as organic acids (e.g. acetate, formate) (Lee, 1997; Zheng et al., 2011). In most cases, these mixtures can only be metabolized partly or sequentially (Dien et al., 1999; Han et al., 2011; Yanase et al., 2012). Additionally, high acid and furfural concentrations require organisms that are tolerant to these by-products. Next to various approaches to introduce or enhance xylose metabolism in yeast (Bruinenberg et al., 1983; Walfridsson et al., 1995; Kuyper et al., 2003; Sonderegger and Sauer, 2003; Hahn-Hagerdal et al., 2007), Pseudomonas strains were engineered for xylose assimilation. Meijnen and colleagues integrated the orthologous xylose degradation pathways into Pseudomonas putida S12 by overexpressing the original xylose operon of Caulobacter crescentus (xylXABCD) coding for the Weimberg pathway (Meijnen et al., 2009) and an operon of Escherichia coli (xylAB) coding for the isomerase pathway (Meijnen et al., 2008; 2012). Integration of the xylXABCD operon enabled growth of P. putida S12 on xylose at a rate of 0.21 h−1 (Meijnen et al., 2009). The introduction of the xylAB operon from E. coli only led to poor growth of P. putida S12 on xylose (0.01 h−1), which could not be improved by the introduction of a xylose transporter (Meijnen et al., 2008). Le Meur and colleagues introduced the xylAB operon from E. coli into P. putida KT2440, which enabled the strain to grow on xylose as sole carbon source with a growth rate of 0.24 h−1. It was also shown that it was not necessary to integrate an additional xylose uptake system into P. putida KT2440, and it was hypothesized that xylose is either taken up by the glucose uptake system or by a phosphoenolpyruvate-dependent phosphotransferase system (Le Meur et al., 2012). The efforts made in the past to achieve xylose degradation in Pseudomonas underline the general interest of having industrial relevant strains in hand, which can efficiently

D-Xylose assimilation by P. taiwanensis VLB120 convert xylose into biomass or valuable products. However, the recent studies also demonstrate the challenge of utilizing xylose simultaneously with other sugars. Pseudomonas taiwanensis VLB120 is a solventtolerant, biofilm-forming strain with a high potential for applications in industrial biotransformation processes (Park et al., 2007; Gross et al., 2010; Halan et al., 2011). The strain was classified as belonging to the species of P. taiwanensis, after an extensive taxonomic revision, which will be published elsewhere (K. A. K. Köhler 2014, submitted). Pseudomonas taiwanensis VLB120, in contrast to other Pseudomonas strains with an industrial potential, like P. putida KT2440, P. putida DOT-T1E and P. putida S12, is able to assimilate xylose naturally and without any genetic modifications. To the best of our knowledge, this is the only described solvent-tolerant Pseudomonas strain with the ability to grow on xylose as single carbon and energy source. Xylose metabolism of P. taiwanensis has not yet been described. Three alternative degradation pathways are reported in literature. Xylose can be degraded via the pentose phosphate pathway (PPP) by an isomerase (isomerase pathway), present in numerous bacteria (Fossitt et al., 1964), or an oxo-reductive pathway described in fungi (Moret and Sperti, 1962; Wang and Schneider, 1980). Alternatively, xylose can fuel the TCA cycle via α-ketoglutarate by the Weimberg pathway, which has been described for bacteria and archaea (Weimberg, 1961). Another option of xylose metabolism in Pseudomonas is the conversion of 2-dehydro-3-deoxy-Dxylonate into pyruvate and glycoaldehyde via the Dahms pathway (Dahms, 1974). A schematic overview of the three pathway alternatives is provided in Fig. 1. In this study, a mixture of physiological, genomic and transcriptomic studies is used to investigate the mechanism of xylose metabolism of P. taiwanensis VLB120. The similarities and differences of xylose and glucose assimilation are investigated by determination of growth kinetics and stoichiometry. While these results provided a basic understanding of xylose catabolism, they could not be used to decipher directly between the three possible metabolization pathways. Thus, a hypothesis-driven mathematical model was established, mapping Pseudomonas central carbon metabolism including the three potential catabolization routes. This model was used for an in silico experimental design of a 13C-tracer study that allowed to distinguish experimentally between the three pathway alternatives. By applying this strategy, the xylose assimilation pathway of P. taiwanensis VLB120 could be identified, regardless of the lack of genetic information about pathway alternatives. Cell physiology was connected to the genome sequence using these experimental results and RT-qPCR.

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Fig. 1. Schematic overview of xylose assimilation pathways. F6P, D-Fructose-6-phosphate; G6P, D-Glucose-6-phosphate; GLYOX, Glyoxylate. MAL, malate; P5P, pentose-5-phosphate; PYR, pyruvate; T3P, triose-3-phosphate.

Results In silico characterization of D-xylose assimilation in P. taiwanensis VLB120 To investigate the genomic potential of P. taiwanensis VLB120 for the metabolization of xylose, a metabolic network based on the genome sequence of P. taiwanensis VLB120 (Köhler et al., 2013) was reconstructed using the genome-mapping software CARMEN (Schneider et al., 2010) (Supporting Information Fig. S7). The potential mechanisms of xylose assimilation in microorganisms, the isomerase pathway, the oxoreductive pathway, the Weimberg pathway and the Dahms pathway have been additionally checked by manually comparing the respective protein sequences with the protein sequences derived from genes of the genome and the megaplasmid of P. taiwanensis VLB120. While xylose is taken up directly for catabolism via the isomerase and oxo-reductive pathway, which are both fuelling the PPP, the Weimberg and Dahms pathway require an initial conversion of xylose to xylonate, which is then taken up by the cell. It is proposed that in P. taiwanensis VLB120 the conversion of xylose to xylonate via xylonolactone is performed by the same enzymes that are responsible for the conversion of glucose to gluconate, namely the glucose dehydrogenase (GCD) and gluconolactonase, as described for P. putida NCTC 10936 by Hardy and colleagues

© 2014 Society for Applied Microbiology and John Wiley & Sons Ltd, Environmental Microbiology, 17, 156–170

158 K. A. K. Köhler, L. M. Blank, O. Frick and A. Schmid Growth characteristics of P. taiwanensis VLB120 on xylose, glucose and their corresponding acids

(1993). The results from CARMEN and the manual amino acid BLASTS indicated that not all degradation pathways are present in the genome of P. taiwanensis VLB120 with high evidence (Supporting Information Fig. S7). We were able to identify all genes necessary for the Weimberg degradation pathway, the encoded proteins showed amino acid identities between 40% and 100%. The Dahms pathway only requires a single additional enzyme, the 3-deoxy-D-pentulosonic acid aldolase (Dahms, 1974); however, no amino acid sequence and no nucleotide sequence encoding this protein were reported yet. Hence, a sequence-based comparison for this pathway was only partially possible. In the isomerase and oxo-reductive pathways many proteins remain undetected, although a few genetic links could be detected (Supporting Information Fig. S7). From the genetic point of view, xylose utilization via the isomerase or oxo-reductive pathways seemed thus unlikely, but could not be excluded from further investigations.

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The physiology of P. taiwanensis VLB120 matches the basic requirements for growth on hydrolysed lignocellulose. Phenotype analysis (Biolog, Hayward CA, USA) has shown that the strain is able to grow at a pH in the range of 4.5–10. Furthermore, it can grow on acetic acid and tolerate up to 5% of sodium formate (K. A. K. Köhler 2014, submitted). Here, the stoichiometry and kinetics of growth, substrate consumption and product formation during cultivation of P. taiwanensis VLB120 on glucose and xylose, as well as on their corresponding acids were quantified (Fig. 2). The cultivations using xylose and glucose as carbon and energy sources revealed a diauxic growth profile in both cases consisting of the glucose/xylose conversion phase, followed by the gluconate/xylonate consumption phase respectively. In contrast to glucose, the two phases

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Fig. 2. Growth profiles of P. taiwanensis VLB120 in minimal media with (A) xylose, (B) glucose, (C) xylonate and (D) gluconate as carbon sources. Error bars give the deviation from the arithmetic mean of at least two independent cultures. CDW, cell dry weight.

© 2014 Society for Applied Microbiology and John Wiley & Sons Ltd, Environmental Microbiology, 17, 156–170

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Table 1. Rates and yields for P. taiwanensis VLB120 grown on different carbon sources.

Growth rate μ (h−1) Growth rate μ in second growth phase (h−1) Spec. substrate uptake/conversion rate (mmol g−1 h−1) Spec. xylonate formation rate (mmol g−1 h−1) Spec. gluconate formation rate (mmol g−1 h−1) Biomass yield for exp. growth phase (g g−1substrate) Biomass yield for overall fermentation (g g−1substrate)

Xylose

Xylonate

Glucose

Gluconate

0.18 ± 0.0 0.02 ± 0.0a −5.2 ± 0.2 0.7 ± 0.1 n/a 0.23 ± 0.0b 0.30 ± 0.0c

0.65 ± 0.0 n/a −5.8 ± 0.1 n/a n/a 0.68 ± 0.0b 0.74 ± 0.0c

0.54 ± 0.0 n/a −26.7 ± 3.7 n/a 23.8 ± 3.2 0.11 ± 0.0b 0.44 ± 0.0c

0.45 ± 0.0 n/a −10.2 ± 0.2 n/a n/a 0.22 ± 0.0b 0.22 ± 0.0c

a. Growth rate during second growth phase. b. Biomass yield calculated from growth rates and substrate uptake rates (for xylonate and gluconate) or substrate conversion rates (for xylose and glucose) during the exponential growth phase. c. Overall biomass yield calculated from highest observed cell dry weight and initial substrate concentrations. Substrate conversion rates were determined for xylose and glucose as the sum of uptake and acid accumulation from Fig. 1. Errors result from standard deviations of at least two independent cultures. n/a: not available.

Substrate (mM)

glucose depletion, simultaneous metabolism of xylose and gluconate could be observed (II, second phase). The following phases of xylose conversion (III, third phase) and xylonate consumption (IV, fourth phase) were sequential. The growth rates of the first and second phase with 0.58 ± 0.04 h−1 and 0.47 ± 0.15 h−1, respectively, were comparable with the growth rates on glucose and gluconate as single carbon sources (Table 1). The growth rates of the third and fourth phase were also in the same range with 0.10 ± 0.03 h−1 and 0.07 ± 0.01 h−1, respectively, but were significantly lower compared with the growth rates on xylose and xylonate as single carbon sources. The conversion rate for glucose (−36 ± 3 mmol g−1 h−1) was increased compared with the cultivation on glucose as sole carbon source. Notably, the uptake rate of gluconate (−5 ± 2 mmol g−1 h−1) was lower,

CDW (g l–1)

were reflected in the growth behaviour of P. taiwanensis VLB120 with xylose, as two different growth rates could be observed for the two phases. In comparison with xylose, glucose seemed to be the more favoured growth substrate since the gluconate production rate (24 mmol g−1 h−1) and the growth rate (0.54 h−1) were higher compared to the xylonate production rate (1 mmol g−1 h−1) and the growth rate on xylose (0.18 h−1) (Table 1). The biomass yield determined for the exponential growth phase on xylose (0.23 g g−1) was higher than that on glucose (0.11 g g−1) resulting from the lower xylonate production rate, while the biomass yield for the overall fermentation was higher on glucose (0.44 g g−1) than on xylose (0.3 g g−1). The growth rate and biomass yield on xylonate (0.65 h−1; 0.68 g g−1) as sole carbon source were higher than on gluconate (0.45 h−1; 0.22 g g−1) (Table 1), also exceeding the values observed for growth on xylose, while the substrate conversion and uptake rates for xylose and xylonate, respectively, were rather similar. However, the growth rate on gluconate was lower than on glucose, with a lower substrate uptake rate, but a higher biomass yield (Table 1). During cultivation of P. taiwanensis VLB120 on xylose, two different growth rates were observed, corresponding to the alternating growth phases. Based on this observation, it could not be excluded that xylose and xylonate are consumed by this strain via different metabolic pathways. Further, no other by-products were detected during cultivation on any of the tested substrates. It could be confirmed by subsequent inoculation with exponentially growing cells that the relatively long time period before the cells start to grow with xylose is a true lag phase and no adaptation process (data not shown). To characterize the growth of P. taiwanensis VLB120 on a mixture of glucose and xylose, cells were cultivated in a minimal medium containing 2.5 g l−1 glucose and 2.5 g l−1 xylose as substrates (Fig. 3). Glucose was the first substrate to be metabolized (I, first growth phase). After

Time (h) Fig. 3. Growth profile of P. taiwanensis VLB120 grown with a mixture of xylose and glucose. Error bars result from deviation from the arithmetic mean of at least two independent cultures. I) Consumption of glucose, II) co-consumption/conversion of gluconate and xylose, III) conversion of xylose, IV) consumption of xylonate. CDW, cell dry weight.

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160 K. A. K. Köhler, L. M. Blank, O. Frick and A. Schmid GCD is likely to catalyse the periplasmic conversion of xylose to xylonate. This would enable xylose metabolization via the Weimberg or the Dahms pathway. To investigate the influence of GCD on xylose assimilation and to examine the possibility of xylose catabolism via the PPP, the growth characteristics of P. taiwanensis VLB120-T7Δgcd, a GCD knock-out strain, which still grows on glucose as sole carbon source, (data not shown) were investigated on xylose as sole carbon source. Even after almost 130 h of cultivation, no growth or xylose consumption could be observed (Supporting Information Fig. S8). Thus, the conversion of xylose to xylonate and the following uptake and catabolism of xylonate seems to be degradation route used by the cells. In silico design of a 13C-labelling strategy for the identification of the xylose degradation pathway in P. taiwanensis VLB120

Fig. 4. Network of P. taiwanensis VLB120 xylose pathway alternatives used for isotopomer simulations. Corresponding reaction equations are given in Supporting Information Table S1. 3PG: 3-phospho-D-gylcerate, AcCoA: Acetyl coenzyme A, AKG: 2-Oxoglutarate, CIT: Citrate, DHAP: Dihydroxyacetonephosphate, E4P: D-Erythrose-4-phosphate, F6P: D-Fructose-6-phosphate, G3P: Glyceraldehyde-3-phosphate, G6P: D-Glucose-6-phosphate, GLYOX: Glyoxylate, MAL: Malate, OAA: Oxaloacetate, P5P: Pentose-5-phosphate, PEP: Phosphoenolpyruvate, PYR: Pyruvate, S7P: D-Sedoheptulose-7-phosphate, SUC: Succinate, XYL: Xylose, XYL_EX: extracellular Xylose, BM: Biomass.

which might be a result from the co-assimilation of gluconate and xylose during this growth phase. The conversion rate for xylose in phase III (−3 ± 1 mmol g−1 h−1) was in the range for the cultivation on xylose as sole carbon source, while the uptake rate for xylonate (−0.1 ± 0 mmol g−1 h−1) was significantly lower under these conditions. The biomass yield on glucose in phase I (0.09 ± 0.01 g g−1Glucose) was in the same range as for the cultivation on glucose as single carbon source, while the biomass yield on gluconate in phase II (0.48 ± 0.09 g g−1Gluconate) and on xylose in phase III (0.32 ± 0.16 g g−1Xylose) were increased, which could again be an effect of the co-assimilation.

The initial step in the design of an optimal 13C-tracer experiment is to find out whether the substrate labelling provides sufficient information to deduce specific flux parameters of interest from measurable 13C-labelling patterns in selected key metabolites (Wittmann and Heinzle, 2001). To identify the pathway responsible for xylose degradation in P. taiwanensis VLB120, an experimental strategy that allows discrimination between the three possible xylose assimilation routes (via TCA, via PPP and via Dahms pathway) was established. The information content of the chosen 13C-labelling strategy was evaluated by isotopomer simulations using OPENFLUX (Quek et al., 2009) for commercially available 1-13C xylose as tracer substrate. The basis for the simulations was a simplified network of P. taiwanensis VLB120 central carbon metabolism (Fig. 4, Supporting Information Table S1). For each of the three possible xylose degradation routes minimal and maximal activities of the PPP and Entner–Doudoroff (ED) pathway were determined to detect the boundaries of dependent flux parameters. Additionally, minimal and maximal activities for anaplerosis and gluconeogenesis were determined (see Supporting Information). Within the defined boundaries, the flux split ratio between the PPP and the ED pathway ΦPPP [ΦPPP = ν9/(ν9 + ν10)] was varied in order to follow the labelling distributions of the selected representative intracellular metabolites pyruvate (Pyr), 3-phosphoglycerate (3PG), oxaloacetate (OAA), 2-oxoglutarate (AKG), phophoenolpyruvate (PEP) and erythrose-4-phosphate (E4P). Those are precursor molecules for the synthesis of biomass components and can be detected experimentally by measuring the labelling patterns of the respective amino acids (Szyperski, 1998; Wittmann, 2007). Within the defined boundaries and

© 2014 Society for Applied Microbiology and John Wiley & Sons Ltd, Environmental Microbiology, 17, 156–170

D-Xylose assimilation by P. taiwanensis VLB120 13

using 1- C xylose as tracer substrate, for every possible catabolic degradation pathway and intracellular flux distribution, a specific labelling pattern could be obtained, reflecting the particular set of metabolic fluxes (see Supporting Information). In addition, the analysis showed that the discrimination between the three alternative xylose degradation routes requires labelling information of all five chosen metabolites (Supporting Information Figs S1 and S6). To investigate their participation in xylose degradation, the relative activity of each of the three potential pathways was varied gradually and the resulting labelling patterns in the chosen metabolites were calculated. In order to distinguish these observations from variations in the labelling patterns, which might result from a change in flux split ratios at constitutional branch points in the central metabolism, theoretically possible values for the flux split ratios have been determined for each branch point and kept constant upon shifting between the xylose degradation routes. The applied parameters were based on previous data published for glucose catabolism via PPP by P. putida (Blank et al., 2008). ΦPPP was set to 0.1 and the net flux between PEP/Pyr and OAA/Malate was set in the direction of anaplerosis. However, the literature-based value for ν8 had to be adjusted, in order to avoid the occurrence of negative values for the reactions ν11 and ν12 in case of xylose degradation via the PPP. To ensure data consistency, the same adjusted value was used for the investigation of the two other xylose degradation routes, because changes in the activity of ν8 do not affect the labelling pattern of metabolites when xylose is taken up via the Weimberg pathway. Also, the impact of ν8 on the labelling pattern of metabolites for the catabolization of xylose via the Dahms pathway is small, but has been determined before (see Supporting Information). Figure 5 shows the simulated labelling patterns of key metabolites during a shift of xylose catabolism completely via PPP [ν4/(ν2 + ν4) = 0] to xylose degradation completely via the Weimberg pathway [ν4/(ν2 + ν4) = 1 or ν4/(ν3 + ν4) = 0] to xylose degradation completely via the Dahms pathway [ν4/(ν3 + ν4) = 1]. Here, a specific change in the labelling patterns can be observed for every possible combination of catabolic pathways. The activity of xylose degradation via the Weimberg pathway (ν4) plays an important role. When ν4/(ν2 + ν4) is higher than 0.1, the net flux of ν24 and ν25 is changing from the direction of anaplerosis to gluconeogenesis. At a value for ν4/(ν2 + ν4) of 0.5, the net flux changes from the direction of ν15 to the direction of ν16, while the carbon flux from glyceraldehyde-3-phosphate still follows the direction of ν13. Above a value of 0.55 for ν4/(ν2 + ν4), ν13 is changing into the direction of ν14. This is reflected by the drastic change in the labelling pattern of 3PG. For the modelling and simulation presented here, the occurrence of natural

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carbon isotopes in the carbon backbone of each metabolite has been considered, which is reflected by a low residual labelling. These data show that through the utilization of 1-13C xylose, a unique labelling pattern for the selected representative metabolites can be observed for every possible xylose catabolic pathway independent of intracellular flux distributions and simultaneous use of the different xylose pathways. This makes the selected labelling strategy an adequate instrument to decipher a potential change in pathway utilization during xylose and xylonate metabolism by following the changes in the labelling patterns of the intracellular metabolites over the cultivation time. Experimental validation of xylose assimilation mechanisms using 13C labelling To investigate the labelling of the chosen intracellular metabolites and to be able to compare the experimental data with the data from the previous simulations, P. taiwanensis VLB120 was grown on 1-13C xylose as sole source of carbon and energy. In order to obtain higher biomass concentrations and thus higher intracellular amino acid concentrations required for 13C-labelling analysis, the cultivation on 1-13C xylose was performed with 10 g l−1 of substrate (Fig. 6). As a result, the growth rate on xylose (0.21 h−1) was slightly increased compared with growth in media containing 5 g l−1 xylose (Fig. 2, Table 1). The substrate uptake rate was calculated to be 8.3 mmol g−1 h−1 and the overall biomass yield was determined as 0.22 g g−1Xylose. The changes of the labelling patterns of key metabolites during the cultivation were monitored over the entire cultivation time to be able to distinguish between possible different xylose and xylonate degradation routes. From the raw data of mass spectrometry (MS), mass distribution vectors were calculated for the m-57 fragments and displayed as relative mass isotopomer distributions (MID) over time to enable comparability of experimental data and in silico results (Fig. 7). Only glutamate and proline, both resulting from the precursor AKG, show a significant labelling of the m-57 fragments and no change of the labellings over the time-course of the cultivation was detected. Slight changes were visible for the labelling patterns of amino acids resulting from OAA and AKG. The simulated labellings resulted in a relative MID for OAA m+1 of 0.21 for the flux being channelled completely through the Dahms pathway and 0.04, for the flux being completely channelled through the Weimberg pathway. Our experimental results showed that the m+1 labelling of threonine and aspartate started with a relative MID of 0.05 and reached a maximum of approximately 0.9 after 30 h. The

© 2014 Society for Applied Microbiology and John Wiley & Sons Ltd, Environmental Microbiology, 17, 156–170

162 K. A. K. Köhler, L. M. Blank, O. Frick and A. Schmid

Fig. 5. Simulated labelling distribution of key metabolites for variations of xylose catabolic pathways. ν4/(ν2 + ν4) = 0: xylose degradation only via PPP. ν4/(ν2 + ν4) = 1 or ν4/(ν3 + ν4) = 1: xylose degradation completely via Weimberg pathway. (ν4/(ν3 + ν4) = 0: xylose catabolism completely via Dahms pathway.

calculated MIDs for AKG m+1 are 0.29 if the flux is completely channelled through the Dahms pathway and 0.71, if the flux is completely channelled through the Weimberg pathway. In our experiments, a relative MID of 0.75 was measured at the beginning of the experiment, and it even increased to a maximum of approximately 0.9 after 22 h.

These results clearly confirm that the complete carbon flux is channelled through the Weimberg pathway as here the labelled carbon atom of 1-13C xylose is directly lost in the reaction of AKG to succinyl-CoA. Additionally, the introduction of the labelled CO2 can be observed in amino acids resulting from oxaloacetate as precursor.

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c Xylose / Xylonate (mM)

Discussion

Time (h) Fig. 6. Growth profile of P. taiwanensis VLB120 with 10 g l−1 1-13C xylose as sole source of carbon. Samples between 14 and 42 h were used for the measurement of intracellular metabolite labellings. Error bars result from deviation from the mean of analytes with two replicates for cell dry weight determinations and three replicates for xylose and xylonate determination. CDW, cell dry weight.

Transcription profile of putative D-xylose pathways To resolve the changes of the transcriptional profile of P. taiwanensis VLB120 grown on xylose and xylonate compared with glucose, RT-qPCR analyses of genes for the assimilation via the Weimberg and of representative genes for the Dahms pathways were performed (Fig. 8). The results clearly showed that the Weimberg pathway (operon PVLB_18550 – PVLB_18565) was highly upregulated during both, the metabolism of xylose and xylonate, as compared with glucose. Because no genetic information is available for the 3-deoxy-D-pentulosonic acid aldolase, two other representative genes were selected for investigating the Dahms pathway expression: the glycolate oxidase (PVLB_15130), which catalyses the reaction of glycolate to glyoxylate; and the malate synthase (PVLB_23460), which catalyses the formation of malate from glyoxylate and acetyl-CoA. Both genes were slightly upregulated on xylose, while the glycolate oxidase (PVLB_15130) was upregulated on xylonate and the malate synthase (PVLB_23460) was slightly downregulated. To investigate xylose and xylonate uptake, gcd (PVLB_05240) and the glucose and gluconate transporters (PVLB_20095 and PVLB_13665 respectively) were included. Transcription levels of gcd during metabolism on glucose and xylose were similar, while the transcription of the respective gene was lower during growth on xylonate (Fig. 8). The glucose and gluconate transporter genes were both less transcribed on xylose and xylonate, as compared with glucose. Thus, the transporters responsible for glucose and gluconate uptake were not induced on xylose and xylonate, respectively, suggesting the availability of an alternative uptake system for xylonate.

This study focused on the description of xylose metabolism in P. taiwanensis VLB120 cells, which had not been described before. We found that xylose is converted to xylonate by the periplasmic GCD. The xylonate is then converted via the Weimberg pathway to fuel the TCA cycle. A mutant deficient in GCD of P. taiwanensis VLB120 was not able to grow on xylose as sole carbon source, underlining that this strain does not possess a metabolic route or a transporter system for the direct uptake of xylose. The specific induction of the glucose transporter gene by glucose, as compared with xylose, has also been shown by RT-qPCR. Also, the gluconate transporter was not induced by xylonate. This implies that the strain must possess a different transport system for xylonate. The three times lower growth rate observed when P. taiwanensis VLB120 grew with xylose as carbon source in comparison to glucose might result from a kinetic preference of GCD for glucose as a substrate. These conclusions are supported by the observed increased growth rate on xylonate, which was even 44% higher than the growth rates on gluconate. Hence, growth on xylose is not limited by xylonate uptake but by xylose conversion. It was previously reported that the GCD of P. putida NCTC 10936 has a Km of 1–2 mM for glucose and a Km of 17–20 mM for xylose (Hardy et al., 1993). Also in engineered P. putida S12, the GCD showed a preference for glucose instead of xylose (Meijnen et al., 2009). These data are in agreement with the lower conversion rate of xylose to xylonate, and also with the observed growth kinetics when P. taiwanensis VLB120 is grown on a mixture of glucose and xylose. In this case, xylose conversion started after glucose was depleted, clearly showing a higher affinity of GCD for glucose as compared with xylose. The simultaneous uptake of gluconate and xylonate, however, implies that there is either no preference of the uptake system, or two uptake systems are acting in parallel. In recombinant P. putida KT2440 and P. putida S12, which were engineered to metabolize xylose via the PPP, no additional xylose uptake system was required, underlining the ability of these strains to take up xylose via the glucose transporter or an unspecific sugar transporter system, as no homology to a specific xylose transporter could be found in the described strains (Meijnen et al., 2008; Le Meur et al., 2012). The growth rate of P. taiwanensis VLB120 grown with glucose as carbon source was higher than with gluconate. These results are in contrast to the growth rates on xylose and xylonate, but reflect the ability of the strain to directly take up glucose, which is not possible for xylose. In the isotopomer simulations, not only different catabolic routes, but also different flux ratios resulting from the

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Time (h) Fig. 7. Experimentally determined labelling patterns during the cultivation of P. taiwanensis VLB120 on 10 g l−1 1-13C xylose. Labellings of amino acids were determined via GC-MS and corrected for naturally occurring isotopes of all atoms involved, apart from the carbon backbone. Error bars result from deviation from the mean of analysis by at least two different GC-MS analyses.

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Fig. 8. Transcription profile of representative pathway genes for xylose and xylonate catabolism of P. taiwanensis VLB120 compared to glucose. Cells were cultivated on the respective carbon source until mid-exponential phase. Transcription was analysed via RT-qPCR. Changes in the expression levels are given as relative quantification (RQ) normalized to the expression levels on glucose. Error bars were calculated based on three technical replicates.

degrees of freedom of our model (ΦPPP), have been investigated. The complexity of the simulation results underlines the importance of a thorough experimental design for 13C-tracer experiments. It could be shown that the information of all five key metabolites is crucial for the discrimination of the alternative degradation pathways. The 13C-tracer experiment showed that only amino acids resulting from AKG are significantly labelled, while the other amino acids selected as representatives for the other investigated pathways remained unlabelled. As a control, the low amount of labelled carbon in the amino acids resulting from naturally occurring carbon isotopes within the carbon backbone of the metabolite fits perfectly to the simulated labelling patterns. The loss of carbon labelling during conversion of AKG results from the decarboxylation reaction of AKG to succinyl-CoA, in which the first carbon atom of the substrate is specifically split off and released as 13CO2. These results strongly point to a xylose catabolism via the Weimberg pathway. The genes selected as representatives of the Dahms pathway were slightly upregulated when the cells were grown with xylose as a source of carbon and partly upregulated with xylonate. These findings suggest that a slight flux through the Dahms pathway cannot fully be excluded. However, if an activity of the Dahms pathway is really present, it is not high enough to be reflected in the labelling patterns of key metabolites. These findings also exclude the existence of any other potential xylose assimilation pathway that has not been regarded in this study. The slight changes in the labelling patterns of amino acids resulting from OAA and AKG are hypothesized to result from the protein history and, in the case of oxaloacetate, CO2 fixation via pyruvate carboxylase activity and not from a distribution between the two different

pathways. An assimilation of xylose via two different pathways should decrease the overall labelling of AKG. The CO2 labelling was not included in the in silico model, as no data about the gas exchange in the shake flasks were available. Additionally, it has been shown that glutamate has a high abundance in bacterial cells (Bennett et al., 2009) and has thus a high turnover, which might result in a more unstable labelling pattern, as observed in the tracer experiment. This is due to the high carbon exchange rates between the glutamate pool and the central carbon metabolism, which results from a high transaminase activity. To prove this theory, a direct measurement of intracellular metabolite labellings would be the preferred method. As an outlook to biotechnological applications, the potential of P. taiwanensis VLB120 to grow on lignocellulosic biomass might be engineered with simple genetic modifications. Meijnen and colleagues (2008) proposed that in an engineered P. putida S12, the consumption of xylose and L-arabinose can be catalysed in parallel by the xylAB operon of E. coli. But they also showed that the conversion of L-ribulose-5-phosphate to D-xylulose-5phosphate was missing in the genome of P. putida S12 (Meijnen et al., 2008). In P. taiwanensis VLB120, the enzyme catalysing this reaction was found. It is therefore hypothesized that the introduction of the XylAB operon and a xylose transporter system might enable P. taiwanensis VLB120 to grow on xylose, glucose and L-arabinose even simultaneously. With the GCD being the limiting step during xylose metabolism, enzyme engineering of the GCD toward enhanced xylose specificity or the introduction of an alternative dehydrogenase might be highly beneficial for xylose metabolism in P. taiwanensis VLB120. Additionally, this might possibly result in a

© 2014 Society for Applied Microbiology and John Wiley & Sons Ltd, Environmental Microbiology, 17, 156–170

166 K. A. K. Köhler, L. M. Blank, O. Frick and A. Schmid simultaneous consumption of glucose and xylose. Taking into account the data stored in Kyoto Encyclopedia of Genes and Genomes (KEGG), P. taiwanensis VLB120 is the only Pseudomonas strain possessing the Weimberg pathway for xylose degradation. Yet, the algorithm applied by CARMEN could also not identify the existence of this pathway from the genome sequence of P. taiwanensis VLB120. The possible existence of a Weimberg pathway could only be detected by manually comparing the protein sequences of known xylose degradation pathways with the genomic inventory of P. taiwanensis VLB120. These results suggest that there might be other Pseudomonas strains comprising a Weimberg pathway for xylose degradation, which slipped the current detection methods. Only two of the detected genes encoding the Weimberg pathway (PVLB_18560 and PVLB_18565) are adjacent, while PVLB_18550 is separated by a transcriptional regulator (PVLB_18555). In the future, a more detailed genetic characterization of the Weimberg pathway is planned by analysing the transcriptome of P. taiwanensis VLB120 growing on xylose and xylonate. The Weimberg pathway is offering high carbon efficiency, which characterizes P. taiwanensis VLB120 as a promising candidate for TCA cycle-based metabolic engineering. So far, P. taiwanensis VLB120 is the only known solvent-tolerant Pseudomonas strain, which is able to grow with xylose as sole source of carbon and energy. The direct assimilation via the TCA cycle thereby offers an interesting alternative to the assimilation of glucose via the ED and PPP. Even without further genetic modification, P. taiwanensis VLB120 is well suited for the production of valuable compounds from xylose or mixtures of glucose and xylose, by offering a co-metabolism of xylose and gluconate. With the background of various previous and significant efforts during the last 20 years to introduce an efficient metabolism of xylose into yeast and more recent developments to introduce xylose metabolism into other (solvent-tolerant) Pseudomonas strains, P. taiwanensis is thus a naturally highly versatile and interesting wild-type strain able to grow with xylose at high rates and yields. In addition, it possesses biotechnologically interesting physiological features like the degradation and synthesis of organic compounds, solvent-tolerance and biofilm formation (Park et al., 2007; Gross et al., 2010; Halan et al., 2011). Experimental procedures In silico metabolic network construction for possible xylose pathways in P. taiwanensis VLB120 The genomic information of P. taiwanensis VLB120 was plotted on available KEGG maps (Ogata et al., 1999) using CARMEN (Schneider et al., 2010), resulting in a metabolic network of P. taiwanensis VLB120. If no accordance was

found between the genome and the enzymes described in KEGG, relevant reactions were corrected manually by comparing the enzymatic information available for other strains with the genome sequence of P. taiwanensis VLB120 (CP003961) by BLAST comparison. Genomic data used for BLAST analysis are from P. putida KT2440 (NC_002947), Caulobacter crescentus CB15 (NC_002696), E. coli (K01996), Burkholderia pseudomallei 668 (NC_009074) and P. putida UW4 (NC_019670).

Cultivation conditions Pseudomonas taiwanensis VLB120 cells were grown in M9 minimal medium containing per litre 12.8 g of Na2HPO4 + 2 H2O, 3 g of KH2PO4, 0.5 g of NaCl, 1 g of NH4Cl, 2 mM MgSO4 supplemented with 0.2% (v/v) US* trace element solution (containing per litre 1 M HCl: 1.5 g of MnCl2 × 4 H2O, 1.05 g of ZnSO4, 0.3 g of H3BO3, 0.25 g of Na2MoO4 × 2 H2O, 0.15 CuCl2 × 2 H2O, 0.84 g of Na2EDTA × 2 H2O, 4.12 g of CaCl2 × H2O, 4.87 g of FeSO4 × 7 H2O) based on (Sambrook and Russel, 2001) and varying amounts of carbon sources (D-xylose, D-glucose, D-xylonate or D-gluconate). Before adding xylonate to the culture medium, the ions of D-xylonate calcium salt were exchanged by adding the equimolar amount of K2HPO4 and centrifuging for 15 min. The stability of the xylonate concentration was verified with the hydroxamate method. A droplet of Antifoam 204 (Sigma-Aldrich, Germany) was added to all cultures to prevent foam formation. All cultivations were performed in baffled shake flasks with a maximum volume of 500 ml containing 50 ml of medium in an Ecotron shaker (Infors HT, Switzerland). The reference cultivation on glucose, including a carbon balance (results not shown), was performed in 300 ml RALF Bioreactors (Bioengineering, Switzerland) containing 200 ml of medium. Growth was performed at 30°C and 200 r.p.m. in shake flasks or at 30°C, 1000 r.p.m. with an air supply of 12 NL h−1 and pH control at 7.1 using 25% NH4OH and 15% H3PO4 in the bioreactors. Pseudomonas taiwanensis VLB120-T7Δgcd is a gcd knock-out of a P. taiwanensis VLB120 strain that has a T7-polymerase integrated into the genome (Lang et al., 2014). The gcd knock-out mutant was constructed as described elsewhere (Martinez-Garcia and de Lorenzo, 2011). It was ensured that the T7 variant of the wild-type P. taiwanensis VLB120 without the gcd knock-out shows the same growth characteristics on xylose as the wild type (results not shown).

Analytical methods Bacterial growth was monitored by measuring the optical density at 450 nm (OD450), with a Libra S11 spectrophotometer (Biochrom, Germany). An OD of 1 corresponds to 0.186 gCDW l−1. Glucose and gluconate were measured with enzymatic D-glucose and D-gluconate test kits (Enzytec, Portugal) monitoring the increase of nicotinamide adenine dinucleotide phosphate at 340 nm in quartz microtitre plates in a Tecan reader (Tecan, Switzerland). Xylose was measured with an enzymatic D-xylose assay kit (Megazyme, Ireland), monitoring the increase of the reduced form of nicotinamide adenine dinucleotide phosphate at 340 nm in a Tecan reader. Xylonate and sometimes

© 2014 Society for Applied Microbiology and John Wiley & Sons Ltd, Environmental Microbiology, 17, 156–170

D-Xylose assimilation by P. taiwanensis VLB120 gluconate were measured with the hydroxamate method described by Lien (Lien, 1959). Two-hundred microlitre of culture supernatant were mixed with 100 μl of 0.7 M HCl to obtain a pH value of the sample between 1.5 and 2. Afterward, the samples were heated to 99°C for 15 min under constant shaking in an Eppendorf Thermomixer (Eppendorf, Germany). Fifty microlitre of the sample were added to 100 μl hydroxylamine reagent (2 M hydroxylamine-hydrochloride in 2 M NaOH) in microtitre plates. Additionally, 65 μl of 3.2 M HCl and 50 μl of FeCl3 (100 g l−1 in 0.1 M HCl) were added. The absorption was directly measured at 550 nm in a Tecan reader. Data from all assays in microtitre plates were compared with a standard curve. Sometimes sugars (xylose, glucose) and acids (xylonate, gluconate) were also determined by high-performance liquid chromatography applying a LaChrom Elite system (Merck Hitachi, Germany) equipped with a Trentec 308R-Gel.H ion exclusion column (300 × 8 mm, Trentec Analysentechnik, Germany) at 40°C and an elution of 1 ml of 5 mM H2SO4 min−1. Twenty microlitre of culture supernatant were injected and the detection of analyte concentrations was performed with an UV (λ = 210 nm) and refractive index detector.

Isotopomer simulation and in silico design of 13 C-tracer experiments For various sets of intracellular metabolic fluxes, the labelling distribution in the pools of branch point metabolites resulting from the conversion of 1-13C xylose via three different potential substrate degradation routes was calculated using the build-in mass isotopomer simulation function of OPENFLUX (Quek et al., 2009). Based on the reaction equations of the central carbon catabolism (Supporting Information Table S1) for all internal metabolites, mass balance equations have been formulated according to

d[ Xi ] = ∑ α ij ⋅ ν j = 0 dt j

(1)

where αij is the stoichiometric coefficient of the metabolite Xi in the reaction j with the flux νrj, which has a negative value if Xi is a substrate of the reaction and a positive value if Xi is a product. Based on the data for the biomass composition (Ebert et al., 2011), the biomass precursor demand in mol mol−1Xyl was calculated using the experimentally determined yield and inserted into the mass balance equation for each metabolite acting as a biomass precursor. Upon variation of the linearly independent flux parameters, hypothetical MIDs were generated for the metabolic intermediates pyruvate, 3-phosphoglycerate, oxaloacetate, 2-oxoglutarate, as well as the proteinogenic amino acids phenylalanine and tyrosine, which comprise a combination of the mass isotopomers of phosphoenolpyruvate and erythrose 4-phosphate (Wittmann, 2007). Based on the network reactions of P. taiwanensis VLB120, several flux spilt points were identified, and for a given set of fluxes the variations in the hypothetical MIDs were calculated for (i) changes in the net flux directions between anaplerosis and gluconeogenesis, (ii) changes in the flux split ratio between ED and PPP and (iii) changes in the contribution of the three potential catabolic routes to the assimilation of xylose. While the flux distribution

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between gluconeogenesis and anaplerosis was directly influenced by the relative fraction of each degradation mechanism, the flux split ration between the ED and the PPP has been set to ΦPPP = 0.1, based on literature data for different Pseudomonas strains growing on glucose (Blank et al., 2008). 13

C-tracer experiments

For 13C-tracer experiments, P. taiwanensis VLB120 was grown in 50 ml of M9 minimal medium containing 10 g l−1 99% labelled 1-13C D-xylose (Sigma-Aldrich, Germany) in baffled shake flasks at 30°C and 200 r.p.m. in an Ecotron shaker (Infors HT, Switzerland). The medium was inoculated from a pre-culture containing 10 g l−1 of unlabelled xylose that was washed once with a NaCl solution of equal osmolarity to the culture medium to remove access unlabelled substrate. The initial optical density was set to 0.07. And 0.5–1 mg of cells were harvested at various time points throughout the cultivation time, washed once with water to remove residual salts and stored at −20°C until analysis. For hydrolysis, the cell pellet was thawed and resuspended in 150 μl of 6 M HCl and hydrolysed at 105°C for 6 h in sealed tubes. The samples were dried over night at 85°C before 30 μl of acetonitrile and 30 μl of N-methyl-N-tert-butyldimethylsilyl-trifluoracetamid were added and the samples were derivatized at 85°C for 1 h. Gas chromatography–mass spectrometry (GC-MS) analysis was performed within 24 h, using a Varian CP-3800 GC in line with a Varian 1200 quadrupole MS (Varian, Germany) as described earlier (Heyland et al., 2009). The following amino acids were chosen as representatives for key metabolites according to Wittmann (2007): Alanine (precursor: PYR), Glycine (precursor: 3PG), Valine (precursor: PYR), Proline (precursor: AKG), Serine (precursor: 3PG), Threonine (precursor: OAA), Phenylalanine (precursors: PEP and E4P), Aspartate (precursor: OAA), Glutamate (precursor: AKG) and Tyrosine (precursors: PEP and E4P). For data analysis, m-57 fragments of the respective amino acids were used as they provide full information on the carbon backbone (Wittmann, 2007). To elaborate the labelling distribution of the measured analyte resulting from the conversion of the isotope-labelled carbon source, mass deviations originating from atoms outside the carbon backbone of the molecule have to be considered. The MIDs obtained from GC-MS measurements were corrected for the occurrence of natural stable isotopes in atoms of the analyte and of the derivatization residues like previously described (Wahl et al., 2004; Yang et al., 2008).

RT-qPCR analysis For RT-qPCR analysis, cells were cultivated in shake flasks and harvested in the mid-exponential growth phase. Cell pellets were stored at −80°C until further processing. mRNA was isolated using a NucleoSpin RNA II kit (Machery & Nagel, Germany) and final concentrations were quantified by NanoDrop (PeqLab, Germany). The samples were DNAse digested once with a Turbo DNA Free kit (Life Technologies, Germany), and the same mRNA concentrations were applied for RT-PCR using a GoScript Reverse Tran-

© 2014 Society for Applied Microbiology and John Wiley & Sons Ltd, Environmental Microbiology, 17, 156–170

168 K. A. K. Köhler, L. M. Blank, O. Frick and A. Schmid scription System (Promega, USA) with random primer supplied by the manufacturer. The resulting cDNA was stored at −20°C until analysis. cDNA levels for the genes of interest and two reference genes gyrB (PVLB_00020) and rpoB (PVLB_22956) were quantified in triplicates in a StepOne Plus Real-Time PCR System (Life Technologies, Germany) using a ROX FastStart universal SYBR Green master mix (Roche, USA). For detection of transcripts, qPCR primers (Supporting Information Table S2) were designed using the PRIMER EXPRESS software (Life Technologies, Germany). Primer annealing and elongation was performed at 65°C for 60 s with a total of 40 cycles. For quality analysis a melting curve was recorded at the end of the run. Raw data were processed using the STEPONE software (Life Technologies, Germany) to calculate –ΔΔCt values based on both endogenous controls. Physiological changes in the expression levels are given as relative quantification normalized to the expression levels on glucose.

Conflict of interest The authors declare no conflict of interest.

Acknowledgements The authors thank Jessica Schneider (CeBiTec Bielefeld) for mapping the genome sequence on KEGG maps with CARMEN (Schneider et al., 2010). We also thank Karsten Lang and Jan Volmer (TU Dortmund University) for providing P. taiwanensis VLB120Δgcd. We acknowledge financial support by the Ministry of Innovation, Science, Research and Technology of North Rhine-Westphalia (Bio.NRW, Technology Platforms: Biocatalysis-RedoxCell and PolyOmics). Kirsten A. K. Köhler was funded by a personal grant from the Ministry of Innovation, Science and Research of North Rhine-Westphalia in the frame of the CLIB-Graduate Cluster Industrial Biotechnology, Contract No: 314 - 108 001 08.

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Supporting information Additional Supporting Information may be found in the online version of this article at the publisher’s web-site: Modelling of key metabolite labelling patterns for varying pathway activities. Fig. S1. Simulated labelling distribution of key metabolites for xylose catabolism via the Weimberg pathway with varying distributions between PPP and ED pathway. Only mass distributions higher than 0 are displayed. Fig. S2. Simulated labelling distribution of key metabolites for xylose catabolism via the PPP with varying distributions between PPP and ED pathway. Only mass distributions higher than 0 are displayed. Fig. S3. Simulated labelling distribution of key metabolites for xylose catabolism via the Dahms pathway with varying distributions between PPP and ED pathway. Only mass distributions higher than 0 are displayed. Fig. S4. Simulated labelling distribution of key metabolites for xylose catabolism via the Weimberg pathway with varying distributions between anaplerosis and gluconeogenesis. Only mass distributions higher than 0 are displayed. Fig. S5. Simulated labelling distribution of key metabolites for xylose catabolism via the PPP with varying distributions between anaplerosis and gluconeogenesis. Only mass distributions higher than 0 are displayed. Fig. S6. Simulated labelling distribution of key metabolites for xylose catabolism via the Dahms pathway with varying distributions between gluconeogenesis and anaplerosis. Only mass distributions higher than 0 are displayed. Fig. S7. Possible xylose catabolic pathways identified by mapping the genome sequence of P. taiwanensis VLB120 onto KEGG maps. Numbers represent locus tags without ‘PVLB’ prefix. Green colours represent results from CARMEN (Schneider et al., 2010). Blue colours represent homologies

© 2014 Society for Applied Microbiology and John Wiley & Sons Ltd, Environmental Microbiology, 17, 156–170

170 K. A. K. Köhler, L. M. Blank, O. Frick and A. Schmid by manual BLAST comparison of genes undetected by CARMEN. Fig. S8. Cultivation of P. taiwanensis VLB120-T7Δgcd on minimal medium with xylose as sole carbon and energy source. The ability of this strain to grow on glucose has been

tested and will be published elsewhere (Volmer et al. 2014, in preparation). Table S1. Reactions and carbon transitions used for isotopomer simulations. Table S2. qRT-PCR primers used in this study.

© 2014 Society for Applied Microbiology and John Wiley & Sons Ltd, Environmental Microbiology, 17, 156–170

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