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Environmental Microbiology (2012) 14(4), 1049–1063

doi:10.1111/j.1462-2920.2011.02684.x

The polyhydroxyalkanoate metabolism controls carbon and energy spillage in Pseudomonas putida emi_2684

I. F. Escapa,1 J. L. García,1 B. Bühler,2 L. M. Blank2 and M. A. Prieto1* 1 Environmental Biology Department, Centro de Investigaciones Biológicas, CSIC, 28040 Madrid, Spain. 2 Laboratory of Chemical Biotechnology, Faculty of Biochemical and Chemical Engineering, TU Dortmund University, D44227 Dortmund, Germany. Summary The synthesis and degradation of polyhydroxyalkanoates (PHAs), the storage polymer of many bacteria, is linked to the operation of central carbon metabolism. To rationalize the impact of PHA accumulation on central carbon metabolism of the prototype bacterium Pseudomonas putida, we have revisited PHA production in quantitative physiology experiments in the wild-type strain vs. a PHA negative mutant growing under low nitrogen conditions. When octanoic acid was used as PHA precursor and as carbon and energy source, we have detected higher intracellular flux via acetyl-CoA in the mutant strain than in the wild type, which correlates with the stimulation of the TCA cycle and glyoxylate shunt observed on the transcriptional level. The mutant defective in carbon and energy storage spills the additional resources, releasing CO2 instead of generating biomass. Hence, P. putida operates the metabolic network to optimally exploit available resources and channels excess carbon and energy to storage via PHA, without compromising growth. These findings demonstrate that the PHA metabolism plays a critical role in synchronizing global metabolism to availability of resources in PHA-producing microorganisms. Introduction Environmental pollution caused by synthetic polymer wastes has been recognized as a large problem due to their resistance to biodegradability (Shah et al., 2008; Sivan, 2011). Polyhydroxyalkanoates (PHAs) are bacterial biopolyoxoesters accumulated in the cytoplasm as Received 2 July, 2011; revised 22 November, 2011; accepted 25 November, 2011. *For correspondence. E-mail [email protected]; Tel. (+34) 918 373 112; Fax (+34) 915 360 432.

© 2012 Society for Applied Microbiology and Blackwell Publishing Ltd

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reserve storage granules (Madison and Huisman, 1999; Luengo et al., 2003; Prieto et al., 2007). PHAs can be obtained from renewable resources, explaining why these biodegradable and recyclable thermoplastic polymers have been extensively studied for the past three decades (Witholt and Kessler, 1999; Luengo et al., 2003; Serafim et al., 2008). These biodegradable polymers have been broadly studied in terms of structural versatility, physicochemical properties and production optimization (Suriyamongkol et al., 2007; Chen, 2009; Rehm, 2010; Escapa et al., 2011). The PHA metabolic machinery in bacteria is not limited to the specific genes coding for the proteins involved directly in PHA synthesis, hydrolysis, granule formation and regulation (de Eugenio et al., 2010a; Galán et al., 2011), but also implicates its connection with other central and peripheral metabolic pathways. In most bacteria, such as the paradigmatic Ralstonia eutropha H16 strain, PHB is synthesized in a three-step reaction starting with acetyl-CoA (Peoples and Sinskey, 1989) (Fig. 1). In the first step two acetyl-CoA molecules are condensed in a reaction catalysed by a 3-ketothiolase. Then, the acetoacetyl-CoA generated is stereoselectively reduced to (R)-3-hydroxybutyryl-CoA by a NADPH-dependent acetoacetyl-CoA reductase. Finally, the (R)-3hydroxybutyryl-CoA monomers are polymerized by a PHB synthase, releasing PHB and free CoA as end-products. Pseudomonas species rely on the b-oxidation pathway and fatty acid de novo synthesis to convert fatty acid or carbohydrate intermediates, respectively, into different (R)-3-hydroxyacyl-CoAs (Fig. 1). These metabolites are used as substrates by the PHA synthases, which catalyse the committed step of medium-chain-length PHA (mclPHA) biosynthesis and finally end up in a biopolyester composed of (R)-3-hydroxy fatty acids of 6 to 12 carbon atoms (Prieto et al., 2007). Regulation of PHA metabolism is complex, since it is exerted first at the enzymatic level, by cofactor inhibition and availability of the metabolites, and second at the transcriptional level, by specific and global transcriptional regulatory factors (Kessler and Witholt, 2001; de Eugenio et al., 2010a). In PHB-producing bacteria such as R. eutropha, the intracellular concentrations of acetylCoA and free CoA play a central role in the regulation of polymer synthesis (Senior and Dawes, 1973; Budde et al., 2010). Furthermore, PHB synthesis is stimulated by

1050 I. F. Escapa et al.

Fig. 1. Metabolic pathways involved in PHA biosynthesis of Pseudomonads (left part of the scheme) and PHB in R. eutropha (right part of the scheme). In Pseudomonads synthesis and degradation of PHA were found to operate as a continuous cycle with 3-hydroxy-fatty acids released from PHA granules by PhaZ depolymerase and activated to 3-hydroxyacyl-CoAs by ACS1 acyl synthetase with the concomitant consumption of one ATP molecule. These activated monomers will be either metabolized via fatty acid degradation or re-incorporated into PHA by PHA synthase. The specific PHA/PHB metabolic pathways are interconnected with the main central pathways that converge in acetyl-CoA.

both high intracellular concentrations of NAD(P)H and high ratios of NAD(P)H/NAD(P) via inhibition of citrate synthase activity in the TCA cycle, facilitating the metabolic flux of acetyl-CoA to the PHB synthetic pathway (Haywood et al., 1988). The regulation of PHA biosynthesis in Pseudomonads has only been studied to a very limited extent. In particular, very little is known about the regulation of mcl-PHA production at enzymatic and physiological levels (Kessler and Witholt, 2001; Hoffmann and Rehm, 2005; de Eugenio et al., 2010a). Pseudomonas putida KT2440, a mcl-PHA producer, is a prototype microorganism for biotechnological purposes based on its GRAS (Generally Recognized As Safe) credentials, its metabolic versatility, its stress resistance, its amenability to genetic modifications and its vast potential for environmental and industrial applications (Nelson et al., 2002; Wu et al., 2011). The availability of its complete genome sequence (Nelson et al., 2002) and genome-scale metabolic models (Nogales et al., 2008; Puchalka et al., 2008) joined to the widespread use of the

new omics techniques provide the bases for understanding the physiology of processes such as the production of PHA. We have reported previously that the mutant P. putida KT42C1 defective in PHA the synthesis shows a considerably lower yield of total biomass (PHA plus the rest of cellular components) than the wild type (de Eugenio et al., 2010b). This difference was due to the higher PHA content in the parental strain since biomasses free of PHA were nearly identical. Moreover, it strongly influences the bacterial community architecture; cell number of P. putida KT42C1 was 10-fold higher, corresponding to a considerably smaller cell size (de Eugenio et al., 2010b). We have suggested that co-occurring PHA accumulation/mobilization (hereafter PHA-cycle) (Fig. 1) allows robust growth during transient nutrient conditions (de Eugenio et al., 2010b). How PHA-producing cells respond to an excess of carbon and energy fluxes in the absence of a functional PHA-cycle remains to be elucidated.

© 2012 Society for Applied Microbiology and Blackwell Publishing Ltd, Environmental Microbiology, 14, 1049–1063

PHA metabolism in Pseudomonas putida 04 0.4 KT2442 g l-1 PHA KT2442 g l-1 biomass free of PHA KT42C1 g l-1 biomass free of PHA

g l-1

03 0.3

0.2

0.1

0.0 4

5

6

7

8

9

Time (h)

Fig. 2. Comparison of the biomass free of PHA in P. putida KT2442 (black bars) and P. putida KT42C1 (white bars). PHA content is shown in grey bars (only for the wild-type strain). In P. putida KT2442 the total dry biomass correspond to the biomass free of PHA plus the PHA content (black bars plus grey ones).

To support the notion that PHA is not only a source of carbon during carbon starvation, but rather a key element in resource balancing that guarantees efficient growth, we revisited PHA metabolism using quantitative physiology experiments supported by transcriptomic and metabolic flux analyses. Our results revealed that under optimal PHA production conditions, this is elevated carbon/ nitrogen ratio, a higher intracellular flux via acetyl-CoA in the mutant strain correlated with the stimulation of the TCA cycle and glyoxylate shunt. Furthermore, the mutant defective in PHA storing spills the additional resources, increasing the release of CO2 instead of generating biomass. Results and discussion Effect of PHA synthase mutation on growth To investigate the role of the PHA-cycle during growth of P. putida, we performed quantitative physiology experiments on octanoic acid as optimal precursor favouring PHA accumulation (Lenz et al., 1992; de Eugenio et al., 2010a) (see Experimental procedures for growth condi-

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tion details). We compared growth kinetics of the PHAproducing wild-type P. putida KT2442 and its PHAdeficient mutant P. putida KT42C1, which carries a disrupted phaC1 gene encoding the PHA synthase (de Eugenio et al., 2010b) (Fig. 2 and Table 1). Growth parameters such as biomass free of PHA and PHA accumulation as well as ammonium and octanoic acid uptake rates were calculated during batch cultivation (from 0 h to 11 h) to define a pseudo steady-state period, in which consumption/production rates remained constant, as described previously to investigate the central carbon metabolism of Escherichia coli (Sauer et al., 1999; Fischer and Sauer, 2003). Although continuous cultivation is usually the method of choice to achieve steady-state conditions, a physiological pseudo steady-state is also attained in the exponential growth phase of batch cultures, allowing analyses under unrestricted growth conditions (Sauer et al., 1999). The pseudo steady-state period was established from fermentation hours 4 to 8.5 using an exponential growth model for multiregression analysis (see Experimental procedures for details) (Table 1 and Fig. S1). Considering the latter, both strains grew at similar rates (in terms of biomass free of PHA) of 0.29 ⫾ 0.03 h-1 and 0.27 ⫾ 0.02 h-1 for P. putida KT2442 and KT42C1 respectively (Table 1). Octanoic acid uptake was 1.2-fold higher for the wild type, which correlates with the additional requirements for PHA formation. Notably, octanoic acid is completely consumed by both strains with octanoic acid exhaustion in the late stationary phase (de Eugenio et al., 2010b). Estimation of reaction rates of pathways involved in PHA production Metabolic flux analysis using a stoichiometric model allows the quantification of intracellular reaction rates by balancing the fluxes of substrate consumption, product formation and synthesis of biomass free of PHA (Blank and Kuepfer, 2010). Using a flux model comprising all major pathways of P. putida central carbon metabolism (Blank et al., 2008) and extended as described in Experimental procedures (see also Table S1), intracellular net fluxes were estimated. As the carbon and energy metabo-

Table 1. Parameters of growth and PHA production of P. putida KT2442 and KT42C1. Parameters -1

mmax (h ) Octanoate uptake ratea Ammonium uptake ratea PHA (C6 monomer) production ratea PHA (C8 monomer) production ratea

P. putida KT2442

P. putida KT42C1

0.29 ⫾ 0.03 3.4 ⫾ 0.3 1.4 ⫾ 0.2 0.2 ⫾ 0.1 1.3 ⫾ 0.2

0.27 ⫾ 0.02 2.8 ⫾ 0.2 2.3 ⫾ 0.1

a. Average rate expressed as mmol (g biomass free of PHA)-1 h-1. Strains were cultivated in 0.1 N M63 minimal medium with 15 mM sodium octanoate as carbon source. The rates refer to the pseudo steady-state period between experimental hours 4 and 8.5. The rates were determined by simultaneous data fitting using an exponential growth model.


1052 I. F. Escapa et al. lism on fatty acids has few alternatives, the flux distribution can be estimated from high-quality physiological data with minimal assumptions at pseudo steady-state (Blank and Kuepfer, 2010). For this purpose, the flux from oxaloacetate to phosphoenolpyruvate was assumed to be negligible, so that the net flux towards gluconeogenesis is channelled through the malic enzyme. PHA synthesis and degradation operate as a continuous cycle involving PHA depolymerase-, acyl synthetase- and PHA synthasecatalysed reactions (Fig. 1) with the concomitant consumption of one ATP molecule per round. However, no kinetic data concerning the PHA turnover are currently available (de Eugenio et al., 2010b). Therefore, the PHA metabolism during pseudo steady-state growth was considered as a net synthesis flux, which is appropriate for the estimation of net global fluxes but does not allow an energy balance calculation (Ruth et al., 2008; de Eugenio et al., 2010b). Our results indicate that, in the wild-type strain, the flux in each round of b-oxidation decreases as the b-oxidation intermediates are partly redirected to PHA synthesis. In contrast, the mutant strain preferably catabolizes the fatty acid to acetyl-CoA. The model predicts an acetyl-CoA formation rate of 7.8 mmol (g of biomass free of PHA)-1 h-1 in the wild-type strain, while the mutant strain would produced up to 10.9 mmol (g of biomass free of PHA)-1 h-1 of acetyl-CoA. This higher acetyl-CoA formation rate in the PHA-deficient mutant subsequently leads to a higher flux through the TCA cycle (Fig. 3). The complete conversion of the fatty acid to acetyl-CoA during b-oxidation in the mutant strain together with the increased TCA cycle flux lead to the formation of additional reducing power resulting in a higher respiration rate. The calculated rate for oxygen consumption by the mutant strain was 1.6 ⫾ 0.2 times higher than for the wild-type strain. To gather independent evidence for these results, we determined the oxygen uptake rate (OUR) during pseudo steady-state growth of both strains. The ratio of respective rates in the mutant versus the wild-type strain was 1.6 ⫾ 0.1, which is in perfect agreement with the results obtained using the model. The calculated CO2 production rate of the mutant strain was 1.7 ⫾ 0.2 times higher than that of the wild-type strain, which is in agreement with the results obtained in vivo (1.4 ⫾ 0.05 times higher). These results indicate that, under optimal PHA production conditions (i.e. excess of carbon source and low nitrogen concentrations, see Experimental procedures for details), the lack of PHA synthesis leads P. putida to redirect the metabolism to the generation of surplus energy, which may either be spilt or flow into proliferative processes. The latter hypothesis would suggest an unbalance in the cellular maintenance energy; this is, an uncoupling of the energy invested on sustaining cellular functions as motility, turnover of macromolecules

and sensory molecules, and reestablishment of ion gradients across the cell membrane (Russell, 2007). This suggestion is in agreement with the increased rate of cell division observed in the mutant P. putida KT42C1 when compared with the wild-type strain, resulting in a higher number of viable cells with a considerably smaller cell size at an identical biomass free of PHA (see transmission electron microscopy images illustrating differences in cell size in de Eugenio et al., 2010b). Remarkably, our results indicate that PHA synthesis in P. putida obviously is required to maintain an efficient energy metabolism. However, we should also consider the hypothesis that the PHA-cycle might play a buffering role, balancing energy dissipation and carbon source availability. A continuous cycling through PHA synthesis and degradation would consume energy and therefore, when required, the cycle might also contribute to dissipate the energy excess as a futile cycle, balancing global biomass (including carbon/energy storage as PHA) and cell division. In this sense, the role of PHB metabolism as an energy- and reducing power-consuming or generating process as function of carbon source or metabolic route involved has been proposed by Babel (1992) in methylotrophic bacteria. Analysis of by-products generated by a defective PHA storage To investigate the accumulation of side metabolites originated from an unbalanced acetyl-CoA catabolism, the culture supernatant of both strains was analysed by HPLC for the presence of acetate, oxaloacetate, citrate, pyruvate, succinate and lactate. No significant amounts of these compounds were detected in the culture medium during pseudo steady-state growth (data not shown). Therefore, the pathways able to excrete those metabolites were not considered for flux analyses. Nevertheless, in the stationary phase after 24 h of cultivation, acetate was detected in the culture supernatant of the mutant strain at low but significant concentration (up to 8 mM), whereas its concentration in the supernatant of the wild-type culture remained below 1 mM. It might be interpreted as a direct consequence of the defective PHA metabolism in the KT42C1 strain, disabling a balanced carbon metabolism. Acetate excretion has been described in E. coli as a major by-product of its aerobic metabolism considered as an overflow metabolite when the respiration capacity is partially saturated (Galán et al., 2001; Wolfe, 2005). In this microorganism the conversion of acetyl-CoA to acetate is catalysed by the pta-ackA (phosphotransacetylaseacetate kinase pathway) or by the pyruvate oxidase (poxB). We could not identify homologous acetate kinase or pyruvate oxidase enzymes in the genome of P. putida what might explain why acetate excretion in this


Malate

6.4±0.2 6 4±0 2 9.5±0.2

NADH 1.5±0.2 1 4±0 2 1.4±0.2

Oxaloacetate

Pyruvate

Gluconeogenesis

6.0±0.3 9.2±0.3

12.6±0.7

19.6±0.7

3-ketoacyl-CoA

CoA

C4: 1.9±0.0 2.7±0.0

C6: 1.9±0.0 1 9±0 0 2.7±0.0 2 7±0 0

C8: 2.1±0.0 2.7±0.0

Acetyl-CoA

NADH

H2O FADH2

Enoyl-CoA

C6: 0.2±0.0 0.0±0.0

C8: 1.3±0.0 0.0±0.0

PHA

3rd round of β-oxidation (C4): 1.9±0.0 2.7±0.0

2nd round of β-oxidation (C6): 2.1±0.0 2.7±0.0

AMP + PPi

ATP

3.4±0.0 CoA 2 8±0 0 2.8±0.0 Octanoic Acyl-CoA acid FAD

CoA

1st round of β-oxidation (C8): 3.4±0.0 2.8±0.0

NAD+

3-hydroxyacyl-CoA

NADPH

NADP+

(R)-3-hydroxyacyl-CoA

C6 0.2±0.0 C6: 0 2 0 0 0.0±0.0 00 00

C8: 1.3±0.0 0.0±0.0

Fig. 3. Scheme of flux distribution in P. putida KT2442 vs. P. putida KT42C1 using 15 mM sodium octanoate as carbon source. Numbers enclosed in solid lines show the flux values for the wild-type strain, while numbers enclosed in dashed lines show fluxes calculated for the mutant strain. The flux values are expressed in mmol (g of biomass free of PHA)-1 h-1.

Respiration:

NADPH + CO2

4.5±0.5 7.7±0.5

Isocitrate

NADH Fumarate 2NADH + ATP α-Ketoglutarate + CO2 4.1±0.5 7.4±0.5

5.6±0.3 8.8±0.3

NADPH + CO2

0.8±0.2 0.7±0.3

Biomass

PHA metabolism in Pseudomonas putida


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I. F. Escapa et al.

microorganism was never reported (Sohn et al., 2010). In other Pseudomonas species such us P. aeruginosa, alginate biosynthesis seems to be an alternative to PHA production to avoid the unfruitful waste of carbon and energy (Hoffmann and Rehm, 2004). However, the lack of the transcriptional regulatory gene algM/mucC in the P. putida KT2440 genome accounts for its non-alginate production morphotype (Nelson et al., 2002). Transcriptional response to defective PHA storage To investigate in depth the basis for the observed changes in flux distribution, we used a genome-wide two-colour DNA array for performing transcriptome analyses of the wild type and mutant P. putida strains. Total mRNA was extracted from cells growing at pseudo steady-state in minimal medium with octanoic acid as the sole carbon and energy source. We considered changes in mRNA levels higher than 2.5-fold with a false discovery rate (FDR) P-value ⱕ 0.05 between wild type and mutant strains (Table 2). Using these cut-off values, we identified 28 genes with significantly differential expression levels. Notably, only seven genes were identified as downregulated in the mutant whereas the others were upregulated. As expected, the genes showing the lowest expression levels in the mutant (3.9–16.9 times lower) were the pha genes involved specifically in PHA metabolism (de Eugenio et al., 2010a) (Table 2). The analysis of the transcriptome profiles showed that the lack of PHA accumulation in the mutant strain modifies the expression of many genes coding for enzymes involved in central metabolic pathways including carbohydrate, fatty acid, amino acid, nucleotide, cofactor and prosthetic group synthesis pathways (Table 2 and Fig. 4). The transcription levels of the fad genes encoding the b-oxidation pathway were similar in both strains, suggesting that the expression of these genes do not depend on PHA accumulation. In agreement with this finding, the calculated growth rates indicate that both wild type and mutant strain synthesized biomass free of PHA at a highly similar rate. Although the expression levels of the boxidation genes do not differ significantly in both strains, the flux through this pathway is higher in the mutant strain. The transcriptome profiles suggest that the increased synthesis of acetyl-CoA resulted from a higher transcription (2.7-fold) of the PP_4636 gene encoding a putative acetyl-CoA acetyltransferase (according to KEGG Pathway Database: http://www.genome.jp/kegg/pathway. html) catalysing the last step of b-oxidation. This transcriptomic profile has been confirmed by quantitative reverse transcription PCR (qRT-PCR) showing a higher fold change (4.7 ⫾ 0.5) for this gene. Although the specific function of the encoded protein has not been experimentally demonstrated, it shares 70% and 60% amino acid

sequence identities with YqeF and AtoB respectively, the acetyl-CoA acetyltransferases of E. coli. These enzymes are required for growth on short-chain fatty acids (Jenkins and Nunn, 1987). The high rate of acetyl-CoA synthesis in the mutant correlates with increased transcription of genes encoding the TCA cycle and the glyoxylate shunt. In this sense, we have observed upregulation (threefold) of aceA (PP_4116) and sdhD (PP_4192) coding for the isocitrate lyase (ICL) and a succinate dehydrogenase component respectively (Table 2). We have validated aceA transcriptomic data using qRT-PCR; with this technique the fold change observed reaches a value of 3.5 ⫾ 0.4. In addition to the TCA cycle, the glyoxylate shunt appeared to be upregulated in the mutant strain. The replenishment of four-carbon intermediates of the TCA cycle is fulfilling anaplerosis, suggesting that intermediates might withdrawn for example for biomass synthesis. To have an indication of active enzymes in the two pathways, we determined the enzymatic activities of ICL, isocitrate dehydrogenase (ICDH) and pyruvate dehydrogenase (PDH) in crude extract of the PHA minus mutant and the wild-type strain during exponential growth (Table 3). The results indicate an increased activity of ICL in the mutant strain (threefold), confirming the results from the transcriptome analysis and an activation of the glyoxylate shunt in the mutant strain. However, we did not observe differences in ICDH between both strains neither at the enzymatic nor the transcriptomic level (qRT-PCR fold change of 1.3 ⫾ 0.2). These data confirm ICL as key factor connecting central metabolism to PHA accumulation yields (Klinke et al., 2000). In agreement with a high CoA demand by high acetyl-CoA synthesis, PP_4700 as part of the panBC putative operon responsible for pantothenate and CoA synthesis was also upregulated 2.7-fold. The expression of genes involved in other cofactor synthesis also was upregulated in the mutant strain. Examples are the lipA (qRT-PCR fold change of 4.1 ⫾ 0.2) and lipB (2.5-fold change from array data) genes (PP_4800 and PP_4801) responsible for the synthesis of lipoic acid. This cofactor is required for the transfer of acyl groups in enzymatic complexes such as the PDH or the a-ketoglutarate dehydrogenase, and the branched-chain oxo acid dehydrogenase complex. Furthermore, these genes are organized in the chromosome as part of a gene cluster related to cell division including PP_4804 and dacA (PP_4803) coding for an RlpA-like protein and D-alanyl-D-alanine carboxypeptidase, respectively, also upregulated in the mutant strain (Table 2). DacA is required for trimming the carboxy-terminal D-alanyl residues from peptidoglycan pentapeptides and RlpA is a lipoprotein which accumulates at cell division sites. Concordantly, other genes linked to peptidolgycan and lypopolysaccharide synthesis were higher expressed


PHA metabolism in Pseudomonas putida

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Table 2. Transcriptional response of phaC1 deletion. FC (DNA array)

FDR

Carbohydrates and central metabolism 2.8 0.0227 3.0 0.0064 3.0 0.0334 -2.5 0.0236 2.7 0.0070 Fatty acid metabolism 2.7 0.0366 2.3 0.0165 -6.8 0.0022 -3.9 0.0006 -8.7 0.0064 -6.5 0.0001 -16.9 0.0000 Nucleotides 2.5 0.0142 2.6 0.0142 Cofactors and prosthetic groups 2.7 0.0142 2.5 0.0085 3.2 0.0070 Cell envelope and cell division 3.2 0.0017 Transporters 3.1 0.0165 -6.7 0.0165 2.6 0.0064 3.7 0.0100 DNA/RNA metabolism 2.7 0.0185 Protein and peptide secretion and trafficking 2.7 0.0098 Stress 2.7 0.0241 Hypothetical proteins upregulated 2.5 0.0430 3.5 0.0142 2.6 0.0326

ID

Gen

Description

PP_3122 PP_4116 PP_4192 PP_4736 PP_4960

aceA sdhD lldD fda

CoA-transferase subunit A putative Isocitrate lyase Succinate dehydrogenase hydrophobic membrane anchor L-lactate dehydrogenase Fructose-1 6-bisphosphate aldolase

phaC1 phaZ phaC2 phaF phaI

Beta-ketothiolase Long-chain acyl-CoA thioester hydrolase family protein Poly(3-hydroxyalkanoate) polymerase 1 Poly(3-hydroxyalkanoate) depolymerase Poly(3-hydroxyalkanoate) polymerase 2 Polyhydroxyalkanoate granule-associated protein phaF Polyhydroxyalkanoate granule-associated protein phaI

PP_4636 PP_4975 PP_5003 PP_5004 PP_5005 PP_5007 PP_5008 PP_4708 PP_4919

pnp

Polyribonucleotide nucleotidyltransferase MutT/nudix family protein

PP_4700 PP_4801 PP_4869

panC lipB nadE

Pantoate-beta-alanine ligase Lipoate-protein ligase B NH(3)-dependent NAD(+) synthetase

PP_4803

dacA

D-alanyl-D-alanine

PP_4645 PP_4735 PP_4789 PP_5024

mscL lctP

Large conductance mechanosensitive channel protein L-lactate transporter Metal ion transporter putative Amino acid ABC transporter periplasmic

PP_4902

orn

Oligoribonuclease

carboxypeptidase

PP_4788

Putative metalloprotease

PP_4787

PhoH-like protein

PP_4087 PP_4115 PP_4958

FC (qRT-PCR)

SD

ID

Gen

Description

3.5 1.3 4.7 4.1 2.0

⫾ 0.4 ⫾ 0.2 ⫾ 0.5 ⫾ 0.5 ⫾ 0.5

PP_4116 PP_4011 PP_4636 PP_4800 PP_5046

aceA icd

Isocitrate lyase Isocitrate dehydrogenase Beta-ketothiolase Lipoic acid synthetase Glutamine synthetase type I

lipA glnA

Genes upregulated or downregulated upon inactivation of the phaC1 gene were grouped according to gene categories. The fold-change (FC) values indicate the mean fold upregulation (positive values) and downregulation (negative values shown in bold) of gene expression in P. putida KT42C1 vs. P. putida KT2442. The FDR values indicate the adjusted P-value for multiple testing to control the false discovery rate (see Experimental procedures). The table includes all significantly differentially expressed ORFs (FDR ⱕ 0.05) with an FC ⱖ 2.5 in the DNA array assays and the ORFs validated by qRT-PCR.

in the mutant (values very close to the cut-off value of 2.5). Although the elucidation of the molecular basis would need further experimental demonstration, the results from the transcriptome analysis suggest a simultaneous activation of the TCA cycle and the cell division machinery in the mutant. This is in good agreement with increased cell number and catabolic flux observed in the mutant cultured at optimal PHA production conditions (de Eugenio et al., 2010b) (Fig. 3). Studies on PHB leaky mutants of Rhizobium leguminosarum with increased secretion of glutamate were

mapped in genes encoding the TCA cycle enzymes succinyl-CoA synthetase (SucCD) and 2-oxoglutarate dehydrogenase (SucAB) or PhaC synthase indicating a link between amino acid metabolism, TCA and PHB formation (Walshaw et al., 1997). Furthermore, a direct connection between nitrogen assimilation machinery and PHA production has been demonstrated in P. putida CA-3 by proteomic analyses when cells were cultured with styrene as carbon source and PHA precursor (Nikodinovic-Runic et al., 2009). Table 1 shows an increase in the ammonia uptake in the mutant strain


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Fig. 4. Scheme of differential expression in P. putida KT2442 vs. P. putida KT42C1 central metabolic routes. Identification codes of the genes upregulated in the phaC1- mutant strain are shown in grey balloons while the ones in black correspond to genes with higher transcription levels in the wild-type strain. The correlation between the metabolic steps and the gene annotation is the one proposed in KEGG Pathway Database (http://www.genome.jp/kegg/pathway.html).

during the pseudo steady-state period. In Pseudomonas species, ammonia assimilation depends on the intracellular a-ketoglutarate pool, which is transformed into L-glutamate by the glutamate dehydrogenase (GDH), when ammonia supply is not limited (Ninfa and Jiang, 2005; Hervás et al., 2009; Hervás et al., 2010). NtrC is the master nitrogen transcriptional regulator driving the expression of several genes involved in the uptake and the metabolism of nitrogen including the glnA–ntrBC operon (Li and Lu, 2007; Hervás et al., 2008). The expression of the gene glnA coding for GS was upregulated 2.2-fold in the mutant strain, very close to the cut-off value of 2.5. However, glnA qRT-PCR analysis confirmed an increase of only 2.0 ⫾ 0.5 transcription rate of this gene,

which suggests that a coordinated assimilation of nitrogen and carbon sources implies a more complex regulation at enzymatic level. Several studies have analysed the link of PHA pathway to central carbon and nitrogen metabolism from a Systems Biology point of view (Yu and Si, 2004; Hervás et al., 2008; Nogales et al., 2008; Puchalka et al., 2008; Brigham et al., 2010; Peplinski et al., 2010; Rojo, 2010; Sohn et al., 2010; Raberg et al., 2011; Ramalingam et al., 2011). The effect of PHB accumulation on central metabolism of R. eutropha has been analysed using transcriptomic and proteomic approaches (Brigham et al., 2010; Peplinski et al., 2010; Raberg et al., 2011) supporting results from previous biochemical studies addressing

Table 3. Activities of some key enzymes of the central carbon metabolism. Enzymes a

Isocitrate lyase (ICL) Isocitrate dehydrogenase (ICDH)b Pyruvate dehydrogenase (PDH)b

P. putida KT2442

P. putida KT42C1

92 ⫾ 5 295 ⫾ 23 < 10

298 ⫾ 6 274 ⫾ 34 < 10

Specific activities values are shown in: a. nmol Glyoxylate mg-1 prot min-1. b. nmol NAD(P)H mg-1 prot min-1. Values are mean ⫾ SD from three independent determinations.


PHA metabolism in Pseudomonas putida PHB as storage compound of carbon and energy, but also as a sink for reducing equivalents (Schlegel and Gottschalk, 1962; Dawes, 1986; Schubert et al., 1988). Thus, inhibition of the TCA cycle during PHB production growth phase facilitates the metabolic flux of acetyl-CoA to the PHB synthetic pathway. Similar findings have been reported for E. coli recombinant strains expressing phb genes of R. eutropha demonstrating the effect of PHB accumulation in controlling the intracellular concentration of NADH/NADPH (Lee et al., 1996; Kabir and Shimizu, 2003; Sánchez et al., 2006; Li et al., 2009). To our knowledge, this is the first approach compiling metabolic flux analyses and transcriptomic data to study the role of PHA accumulation in bacteria. Our results revealed that the deletion of the PHA-cycle in P. putida KT2442 causes an increase of the acetyl-CoA synthesis in the mutant cells under low nitrogen growth conditions. The excess of acetyl-CoA is overflowed through the TCA cycle and the glyoxylate shunt increasing respiration and CO2 production instead of generating biomass but the spillage of energy. This suggests that the ability for PHA synthesis in P. putida is required to channel the energy excess to maintain the energy balance. Moreover, we hypothesize that the PHA-cycle might also contribute to dissipate energy excess, acting like a futile cycle, balancing global biomass (including carbon/energy storage as PHA) and cell division. This work provides new insights into the critical role of the PHA-cycle in the physiology of PHA producers.

Experimental procedures Bacterial strains, media and growth conditions Pseudomonas putida KT2442 is a derivative of KT2440 whose complete nucleotide sequence is accessible (Nelson et al., 2002). Pseudomonas putida KT42C1 (de Eugenio et al., 2010b) is a phaC1 mutant strain of P. putida KT2442 constructed via disruption of the phaC1 gene by insertion of a minitransposon containing a kanamycin resistance gene (de Lorenzo et al., 1990; Herrero et al., 1990). Pseudomonas putida strains were grown in lysogeny broth (LB) (Sambrook and Russell, 2001; Bertani, 2004) at 30°C for precultures and agar-plate growth. For optimal poly(hydroxyoctanoate-co-hydroxyhexanoate) (P(HO-co-HH)) production, P. putida strains were grown in 0.1 N M63 [13.6 g l-1 of KH2PO4, 0.2 g l-1 of (NH4)2SO4, 0.5 mg l-1 of FeSO4•7 H2O, adjusted to pH 7.0 with KOH], plus 2.5 g l-1 of sodium octanoate (15 mM), for 24 h at 30°C and 250 r.p.m. as previously described (Moldes et al., 2004). This medium was supplemented with 1 mM MgSO4 and a solution of trace elements (composition 1000¥: 2.78 g l-1 of FeSO4•7H2O, 1.98 g l-1 of MnCl2•4H2O, 2.81 g l-1 of CoSO4•7H2O, 1.47 g l-1 of CaCl2•2H2O, 0.17 g l-1 of CuCl2•2H2O, 0.29 g l-1 of ZnSO4•7H2O). The C/N ratio is 40 (mol/mol).

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Gas chromatography analysis for PHA content determinations Polyhydroxyalkanoate monomer composition and cellular PHA content were determined by gas chromatography (GC) of the methanolysed polyester. Methanolysis was carried out by suspending 5–10 mg of lyophilized cells in 2 ml of chloroform and 2 ml of methanol containing 15% sulfuric acid and 0.5 mg ml-1 of 3-methylbenzoic acid (internal standard), followed by an incubation at 100°C for 4 h. After cooling, 1 ml of demineralized water was added and the organic phase containing the methyl esters was analysed by GC (Lageveen et al., 1988; de Eugenio et al., 2010b). A standard curve from 0.5 to 2 mg of PHA (Biopolis S.L., Valencia, Spain) was used to interpolate sample data.

Biomass calculation It should be noticed that PHA content disturbs cells turbidimetry, so the optical density cannot be used to estimate growth rates in terms of viable cells or biomass. Biomass concentrations, expressed in grams per litre, were determined gravimetrically. Briefly, culture medium (35–100 ml) was centrifuged for 30 min at 3800 g and 4°C (centrifuge Sigma 3-18K, Osterode am Harz, Germany). Cell pellets were freeze-dried for 24 h in a VirTis Benchtop K Freeze Dryer of SP Industries (Gardiner, NY) and weighed. Biomass free of PHA, defined as total dry mass minus PHA mass, has been used for the analysis of growth kinetics and OUR determination.

Octanoic acid determination by GC analysis A GC determination assay was performed for the analysis of the octanoic acid concentration in the supernatants. The supernatants were diluted 1:2 in 0.1 N M63 medium without sodium octanoate. Forty microlitres of 10% HCl (v/v) were added to 1 ml of diluted supernatant to protonate the acid. The mixture was used for extraction with 1 ml of diethyl ether (with 0.2 mM decane as internal standard). The mixture was agitated on a vortex mixer for 1 min and then centrifuged for 10 min at 4°C and 14 000 g (centrifuge Sigma 1-15K, Osterode am Harz, Germany). The ether phase was dried adding NaSO4, which was removed by centrifugation (10 min at 4°C and 14 000 g). The clean supernatants were analysed in a gas chromatograph TRACE GC Ultra (ThermoFisher Scientific, Waltham, MA, USA) equipped with a FactorFour VF-5ms column (Varian, Palo Alto, CA, USA). Detection was achieved by a flame ionization detector (FID). A standard curve in 0.1 N M63 minimal medium from 0.5 to 8 mM of sodium octanoate (Sigma, St Luis, USA) was used to interpolate sample data.

Ammonium determination assay The quantification of the ammonium concentration was carried out using the Berthelot Method (Searle, 1984). Supernatants were diluted (100–400 times) with dH2O in a final volume of 100 ml. One millilitre of solution 1 (5 g phenol, 22.5 mg sodium-nitroprusside in a final volume of 500 ml of H2O) was added and gently agitated on a vortex mixer. Then,


1058 I. F. Escapa et al. 1 ml of solution 2 [2.75 ml sodium-hypochlorite (12%), 2.5 g NaOH in a final volume of 500 ml of H2O] was added and the mixture was gently agitated on a vortex mixer. After 30 min of incubation at 30°C the OD in the final mixture was measured at 633 nm. A standard curve in 0.1 N M63 minimal medium from 0.025 to 0.15 mM of (NH4)2SO4 (Sigma, St Luis, USA) was used to interpolate sample data.

Multiregression analysis of growth parameters Octanoic acid uptake, ammonium uptake, biomass free of PHA production, and PHA production (represented as the independent production of 3-hydroxyhexanoyl- and 3-hydroxyoctanoyl monomers; named in Fig. S1 as PHA6 and PHA8 respectively) rates and their respective errors were determined using a simultaneous non-linear fit of the concentration data represented over time. This analysis was performed using an exponential growth model described by Heyland and colleagues (2009) in Sigma Plot (Systat Software, V.10.0.0.54). The experimental data fitted to the model with an R 2 value of 0.9953 for the wild type and 0.9996 for the mutant strain.

In vivo determination of oxygen consumption For the OUR determination aliquots were harvested by centrifugation in the middle of the exponential phase (7 h) and concentrated 100 times in fresh culture medium. The OUR was measured by monitoring the substrate-dependent oxygen consumption rate at 30°C using an oxygen electrode (DW1 Hansa-Tech Oxygen Electrode, Hansa-Tech Oxygen Instrument Limited, Norfolk, UK) in 1 ml assay mixture (900 ml of medium plus 100 ml of concentrate sample).

In vivo determination of CO2 production In vivo determination of CO2 production was carried out by the microrespirometry system MicroResp™ (Macaulay Scientific Consulting, Aberdeen, UK). The protocol has been modified from Campbell and colleagues (2003) for measuring CO2 production in bacterial cultures. Aliquots of 900 ml of P. putida batch cultures grown for 7 h were placed in each well of a deep-well plate with a capacity of 1.2 ml. A second plate was used as a system for detecting the evolved carbon dioxide (Rowell, 1995). It was sealed to the first one with a silicone rubber gasket with interconnecting holes between the corresponding wells according to manufacturer instructions. The indicator dye used was Neutral Red. A solution of Neutral Red (0.025 mM), potassium chloride (100 mM) and sodium bicarbonate (2 mM) was set in 150 ml of noble agar (1%) in each well of the detection plate. The plates were stored at 4°C in the presence of soda lime to ensure desiccation or reaction with atmospheric CO2. For colorimetric analyses the detection plate was read immediately after 3 h of incubation at 30°C with a microtitre plate reader (Thermo Scientific Varioskan Flash) at 520 nm. A calibration curve of dye colour with CO2 concentration was performed using a CO2 incubator (MMM Medcenter CO2 Incubator 600 48 Liter) exposing several detection plates at CO2 concentrations ranging from 0.1% to 8%. The conversion

of absorbance to CO2 concentration is a non-linear relationship that fits (R 2 = 0.95) to a single rectangular hyperbola: y = c + ax/(b + x), where a is 0.177, b is 0.408, c is 0.014, y is A590 and x is the percentage of CO2.

Metabolic flux analysis Absolute values of intracellular fluxes were calculated with a flux model comprising all major pathways of P. putida central carbon metabolism (Blank et al., 2008) implemented in FiatFlux (Zamboni et al., 2005). This model was extended on the basis of previously annotated reactions (Nelson et al., 2002; Nogales et al., 2008; KEGG Pathway Database: http:// www.genome.jp/kegg/pathway.html) in order to incorporate the metabolic reactions of fatty acid b-oxidation and PHA metabolism. A complete set of the reactions used in the model is listed in supplemental data (Table S1). Serial reaction steps were combined in one equation (considered as lumped reactions). The biomass composition of P. putida was assumed to be highly similar to those published for E. coli (Emmerling et al., 2002), as previously stated (Fuhrer et al., 2005; Blank et al., 2008). The acetyl-CoA production rate estimation was based on the three rounds of b-oxidation required with sodium octanoate as carbon source, considering that two acetyl-CoA molecules are formed in the third b-oxidation round.

RNA purification All microarray analyses were performed with RNA samples obtained from three independent cultures grown under identical conditions. Precultures of the P. putida strains were cultivated overnight in LB medium, washed, inoculated at 0.3 OD600 in 0.1 N M63 medium and grown during 4 h. Aliquots of 50 ml were harvested by centrifugation at 4°C in tubes precooled on dry ice and quickly stored at -80°C. The cell pellet was resuspended in 1 ml of TriPure Isolation Reagent (Tri Reagent LS, Molecular Research Center, Cincinnati, USA) and incubated at room temperature for 5 min, after which cell lysis was complete. The solution was centrifuged in a microfuge (centrifuge Sigma 1-15K, Osterode am Harz, Germany) at 14 000 g for 10 min at 4°C and the pellet was discarded. Two hundred microlitres of chloroform was added to the supernatant and the mixture was vigorously shaken for 15 s. After 15 min at room temperature, the mixture was centrifuged (14 000 g, 15 min, 4°C) and the aqueous phase was recovered. Five hundred millilitres of isopropanol were added and, after 10 min at room temperature, the sample was centrifuged at 14 000 g for 10 min at 4°C. The pellet was washed with 70% (v/v) ethanol, dried and resuspended in 300 ml of H2O. DNase I (2 ml, 10 units ml-1) was added and the mixture incubated at 37°C for 2 h. After extracting the sample two to three times with acidic phenol, the nucleic acids were recovered by precipitation with sodium acetate and ethanol. The pellet was washed with 70% (v/v) ethanol, dried and resuspended in 100 ml of H2O. After proving the absence of contaminating DNA by PCR, the samples were purified by using RNeasy columns (Qiagen, Düsseldorf, Germany), which helped to eliminate the 5S rRNA. RNA integrity was checked with a capillary electrophoresis system (Agilent 2100 Bioanalyzer, California, USA).


PHA metabolism in Pseudomonas putida Hybridization and processing of microarrays cDNA was obtained from RNA preparations of the KT2442 wild type and KT42C1 mutant strain, fluorescently labelled with either Cy3 or Cy5, mixed and used to hybridize the two-colour DNA microarrays as reported (Yuste et al., 2006). Four microarrays corresponding to independent experiments (three arrays from three biological replicas and one array as technical replica with cDNAs from two, randomly chosen, of the biological experiments) were used and statistically analysed as described (Yuste et al., 2006) using the LIMMA software package (Smyth, 2004). The results for each replica (mean intensity for each spot) were normalized within each array using the lowest intensity-dependent normalization method (Yang et al., 2002) and between arrays using the scale method (Yang et al., 2002). Differential expression was calculated using linear models and empirical Bayes moderated t-statistics (Smyth and Speed, 2003; Smyth, 2004). The probability values obtained (P-values) were adjusted for multiple testing to control the FDR (Benjamini and Hochberg, 1995). Genes were considered differentially expressed when they fulfilled the filter parameters of expression ratio ⱖ 1.6 (LogRatio ⱖ 0.68) and FDR ⱕ 0.05. The replica with lowest adjusted P-value was chosen for each gene. Data have been deposited at http://www.ebi.ac.uk/arrayexpress/. The genes identified have been grouped as proposed previously (Riley, 1993; Domínguez-Cuevas et al., 2006) according to the metabolic function of the corresponding products (Table 2). These metabolic functions have been assigned using the available literature, the P. putida KT2440 genome annotation (Nelson et al., 2002), the KEGG Pathway Database (http:// www.genome.ad.jp/kegg/pathway.html), the Pseudomonas Genome Database (http://www.pseudomonas.com) and the iJN746 genome-scale metabolic network reconstruction of P. putida KT2440 (Nogales et al., 2008).

Real-time qRT-PCR assay Reverse transcription reactions for synthesis of total cDNA were carried out with 1 mg of RNA, 0.5 mM dNTPs, 200 U of SuperScript II Reverse Transcriptase (Invitrogen, Carlsbad, California, USA) and 2.5 mM of random hexamers as primers, in the buffer recommended by the manufacturer. Samples were initially heated at 65°C for 5 min and then incubated at 42°C for 2 h, terminated by incubation at 70°C for 15 min. The cDNA obtained was purified using Geneclean Turbo kit (MP Biomedicals, Santa Ana, CA, USA) and the concentration was measured using a NanoPhotometer™ Pearl (Implen, Munich, Germany). For the analysis of the transcripts levels target cDNAs (0.5 and 5 ng) and reference samples were amplified three times in separate PCR with 0.2 mM each of target primers and using iQ SYBR Green Supermix (Bio-Rad, Berkeley, California, USA) in a iQ5 Multicolor Real-Time PCR Detection System (Bio-Rad, Berkeley, California, USA). Target primers were: R-rpoNq (5′-TCCTGACGTTCGAGCATCG-3′) and F-rpoNq (5′-AAAATGGGCCAGCAACTGAC-3′) for rpoN; RT-5-PP_4116 (5′-AGTGGAAAGCCGGCAAGAAC-3′) and RT-3-PP_4116 (5′-TCTGCACGGCTTCCTGAGTC-3′) for the ORF PP_4116; RT-5-PP_4011 (5′-TCGACCAGGACTGCG GTATC-3′) and RT-3-PP_4011 (5′-CGCCATCAAGCAGTT CAGC-3′) for the ORF PP_4011; RT-5-PP_4636 (5′-

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GGTGGCCAGGAGAACATGAG-3′) and RT-3-PP_4636 (5′GCCTTGCGCTGCGATTC-3′) for the ORF PP_4636; RT-5PP_4800 (5′-CGACCTGCGCCTGAAGTATG-3′) and RT3-PP_4800 (5′-CGGTCTCGAGGTTGTGGTTG-3′) for the ORF PP_4800; RT-5-PP_5046 (5′-AGGCGCTGAAATAC GTCGTG-3′) and RT-3-PP_5046 (5′-GCTTGATG ATACCGCCGATG-3′) for the ORF PP_5046. Samples were initially denatured by heating at 95°C for 5 min, followed by 40 cycles of amplification (95°C, 30 s; test annealing temperature, 56°C, 30 s; elongation and signal acquisition, 72°C, 30 s). For quantification of the fluorescence values, a calibration curve was made using dilution series from 5 ¥ 10-7 to 5 ng of P. putida KT2442 genomic DNA sample. cDNAs from the experimental samples were amplified using amounts within the linear range of the standard curve. After the PCR a melting curve was generated to confirm the amplification of a single product. Results were normalized relative to those obtained for the rpoN gene, as its expression is known to remain relatively constant throughout growth phase in both E. coli and P. putida (Jishage et al., 1996; Morales et al., 2006; Yuste et al., 2006).

Enzymatic assays All the enzymatic assays were performed using crude extract of P. putida strains harvested by centrifugation in the middle of the exponential growth phase (7 h). Cells were resuspended in 50 mM Tris-HCl (pH 7.3), 1 mM phenylmethylsulfonyl fluoride (PMSF) and then disrupted by sonication. Cell debris was removed by 15 min centrifugation at 4°C and 14 000 g (centrifuge Sigma 1-15K, Osterode am Harz, Germany) and the clear supernatant was used as crude extract. The protein concentration was determined by the method of Bradford (Bradford, 1976), with bovine serum albumin as a standard. ICL activity was assayed in 25 mM Tris-HCl (pH 7.3) containing 5 mM MgCl2, 1 mM isocitrate and 15–30 mg of protein extract. Enzyme activity was determined spectrophotometrically by monitoring the production of glyoxylate with 2,4-dinitrophenylhydrazine (2,4-DNPH) at 450 nm and using glyoxylate as standard (standard curve from 0.05 to 0.5 mM) (Katsuki et al., 1971; Romanov et al., 1999). Briefly, the reaction mixture (600 ml) was incubated 15 min at room temperature. The reaction was stopped by adding 100 ml of 2,4-DNPH solution (5 mM in 2 N HCl, stable up to 2 weeks when stored in the darkness) followed by incubation at room temperature for 15 min. The samples were diluted to 1 ml with water and 1 ml of freshly prepared alkaline solution (1 M sodium phosphate adjusted to pH 12.5 with NaOH) was added. The absorbance at 450 nm arising from dinitrophenylhydrazone was measured after 15 min at room temperature. The ICDH and PDH activities were assayed at 30°C by following NAD(P)H formation spectrophotometrically at 340 nm. The assay mixture for the ICDH assay contained 25 mM Tris-HCl (pH 7.3), 5 mM MgCl2, 2 mM NADP, 1 mM isocitrate, 10 mM succinate (to inhibit interfering ICL activity) and 0.1 mg of protein extract (Goldberg and Ellis, 1983). PDH was assayed in 25 mM Tris-HCl (pH 7.3) containing 5 mM MgCl2, 2 mM NAD, 0.1 mM CoASH, 0.2 mM thiamine pyrophosphate, 2 mM cysteine, 1 mM pyruvate and 1 mg of protein extract (Shen and Atkinson, 1970).


1060 I. F. Escapa et al. High-performance liquid chromatography (HPLC) analysis Culture supernatants were analysed by HPLC using a Rezex ROA-Organic Acid H+ (8%) column at 60°C with a flow rate of 0.5 ml min-1 and an injection volume of 50 ml. The mobile phase was 2.5 mM H2SO4 applied in an isocratic regime and detection was performed with a refractive index detector. Oxalacetic acid, sodium citrate, sodium pyruvate, sodium succinate, glycerol, acetic acid and lactic acid were used as standards.

Acknowledgements We are greatly indebted to Dr. Eduardo Diaz and Prof. Dr. Andreas Schmid for helpful discussions and support. We thank the technical works of A. Valencia, F. de la Peña and V. Morales. The support of Marta Tortajada from Biopolis S.L., Spain, in OUR determination is very much appreciated. This work was supported by grants from the Comunidad Autónoma de Madrid (P-AMB-259-0505), the Comisión Interministerial de Ciencia y Tecnología (BIO2007-67304-C02, CSD2007-00005, BIO2010-21049) and by European Union Grants (GEN 2006-27750-C5-3-E and NMP2-CT-2007026515). Isabel F. Escapa is a recipient of CSIC-I3P predoctoral fellowship. This work was supported by the German Ministry of Science and Education (BMBF, Project ERA-NET SysMO, no. 0313980A) (VAPMdS).

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Supporting information Additional Supporting Information may be found in the online version of this article:


PHA metabolism in Pseudomonas putida Fig. S1. Comparison of growth parameters of P. putida KT2442 (A) and P. putida KT42C1 (B). Real values (spots) and fitting to a pseudo steady-state situation (lines), calculated according to the multiregression analysis (see Experimental procedures). Table S1. Reactions included in the flux model. The enzymatic steps taken into account to solve the model are indi-

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cated as well as the reaction direction that was considered in the prediction. Reactions in bold are shown in Fig. 3. Please note: Wiley-Blackwell are not responsible for the content or functionality of any supporting materials supplied by the authors. Any queries (other than missing material) should be directed to the corresponding author for the article.
