- Research article
- Open Access
Computational prediction of the Crc regulon identifies genus-wide and species-specific targets of catabolite repression control in Pseudomonas bacteria
© Browne et al; licensee BioMed Central Ltd. 2010
- Received: 15 July 2010
- Accepted: 25 November 2010
- Published: 25 November 2010
Catabolite repression control (CRC) is an important global control system in Pseudomonas that fine tunes metabolism in order optimise growth and metabolism in a range of different environments. The mechanism of CRC in Pseudomonas spp. centres on the binding of a protein, Crc, to an A-rich motif on the 5' end of an mRNA resulting in translational down-regulation of target genes. Despite the identification of several Crc targets in Pseudomonas spp. the Crc regulon has remained largely unexplored.
In order to predict direct targets of Crc, we used a bioinformatics approach based on detection of A-rich motifs near the initiation of translation of all protein-encoding genes in twelve fully sequenced Pseudomonas genomes. As expected, our data predict that genes related to the utilisation of less preferred nutrients, such as some carbohydrates, nitrogen sources and aromatic carbon compounds are targets of Crc. A general trend in this analysis is that the regulation of transporters is conserved across species whereas regulation of specific enzymatic steps or transcriptional activators are often conserved only within a species. Interestingly, some nucleoid associated proteins (NAPs) such as HU and IHF are predicted to be regulated by Crc. This finding indicates a possible role of Crc in indirect control over a subset of genes that depend on the DNA bending properties of NAPs for expression or repression. Finally, some virulence traits such as alginate and rhamnolipid production also appear to be regulated by Crc, which links nutritional status cues with the regulation of virulence traits.
Catabolite repression control regulates a broad spectrum of genes in Pseudomonas. Some targets are genus-wide and are typically related to central metabolism, whereas other targets are species-specific, or even unique to particular strains. Further study of these novel targets will enhance our understanding of how Pseudomonas bacteria integrate nutritional status cues with the regulation of traits that are of ecological, industrial and clinical importance.
- Carbon Catabolite Repression
- Rhamnolipid Production
- Toluene Degradation
- Alginate Production
- Integration Host Factor
The genus Pseudomonas is an important group of microorganisms that occupy a wide variety of habitats including soil , the rhizosphere , food  and mammalian hosts . Some species are important plant or human pathogens, whereas others are involved in processes such as bioremediation , biocontrol [6–8], nutrient cycling  or biotechnological processes . A key aspect of the lifestyle of Pseudomonads is their ability to adapt, grow and compete in a wide variety of habitats. Thus, Pseudomonads require great flexibility in controlling their diverse array of metabolic pathways and, like most microorganisms, have global regulatory systems that ensure that the best nutrient source is utilised and almost depleted before less favoured nutrient sources are exploited [11–13].
Pseudomonads favour the utilisation of organic acids, particularly tricarboxylic acid (TCA) cycle intermediates, and amino acids over various other carbon sources such as carbohydrates or hydrocarbons . This is in contrast to the majority of well-studied Enterobacteriaceae and Firmicutes, which favour glucose and use a system known as carbon catabolite repression (CCR) or catabolite repression control (CRC) to regulate carbon utilisation. The mechanism of CCR in Enterobacteriaceae and Firmicutes centres on a protein phosphorylation cascade and also involves transcriptional regulation mediated through cyclic AMP (cAMP) binding to the cAMP receptor protein (Crp) (for review see [11, 12]). Although Pseudomonads possess a Crp homolog, Vfr, this protein is not involved in carbon source regulation, at least in P. aeruginosa PAO1 . In fact, the CRC mechanism used by Pseudomonads to regulate carbon source utilisation is fundamentally different to CCR of Enterobacteriaceae and Firmicutes.
A central mediator of CRC is the Crc protein, which acts as a post-transcriptional regulator of target genes . The post-transcriptional action of Crc relies on the binding of Crc to an unpaired A-rich motif in the 5'-end of a target mRNA causing inhibition of the initiation of translation [17, 18]. It is still not fully understood how Crc activity is regulated in different Pseudomonas species, nor whether a common unified regulatory system is employed. In P. aeruginosa, activity is regulated by small RNA, CrcZ, which has five A-rich motifs, that binds to the Crc protein and sequesters it . Levels of the CrcZ sRNA, in turn, are regulated by a two-component system (CbrA/CbrB) and by RpoN. Interestingly, CbrAB and NtrBC form a network to control the C/N balance in both P. aeruginosa and P. fluorescens[19–21]. Furthermore, the presence of a readily available nitrogen source enhances the magnitude of CRC , two observations that are suggestive of a link between regulatory systems controlling C and N utilisation. Although the crcZ gene is present in other Pseudomonads, its role in regulating CRC outside of P. aeruginosa has not yet been demonstrated. Indeed, in P. putida, crc mRNA and Crc protein levels are higher under conditions where CRC is active, a phenomenon not observed in P. aeruginosa, suggesting that an alternative system of regulating CRC may be used in this species [23, 24].
Much of what is known about CRC comes from work on mutants lacking the Crc protein in P. aeruginosa and P. putida. Initially, the key work in identifying the CRC system came from the isolation and characterisation of a P. aeruginosa crc mutant . In this mutant, the succinate-mediated catabolite repression control (CRC) of glucose and mannitol transport and Entner-Doudoroff pathway enzymes was alleviated, thereby establishing the importance of Crc. More recently, the role of Crc has been examined on a global scale in P. putida and P. aeruginosa by carrying out transcriptome and proteome analyses of crc mutants. No less than 134 targets in P. putida and 65 targets in P. aeruginosa were differentially altered in expression in rich media as a result of a crc mutation. This indicates that crc is an important global regulator that superimposes an additional layer of regulation over many metabolic pathways that are otherwise regulated locally by specific regulatory elements that control only one or a few genes. The global analyses of the P. putida and P. aeruginosa crc mutants indicates that CRC is responsible for the hierarchical assimilation of amino acids from rich media, with pathways required for assimilation of valine, isoleucine, leucine, tyrosine, phenylalanine, threonine, glycine and serine inhibited by Crc [26, 27]. Additionally, the P. aeruginosa crc mutation was shown to alter the expression of targets with roles in anaerobic respiration, antibiotic resistance and virulence . Recent work on a crc mutant of P. putida DOT-T1E established that Crc is not involved in the induction of pathways for nutrient utilisation since the mutant grows on the same range of carbon and nitrogen sources as the wild type strain . This is in contrast to the E. coli CCR system where the cAMP-CRP complex is responsible for the induction of genes for utilisation of less favoured carbon sources such as lactose .
The role of CRC in regulating linear and aromatic hydrocarbon utilisation pathways in P. putida has received a lot of attention because of the potential implications of CRC on bioremediation processes. The utilisation of alkanes and a wide range of aromatic compounds including benzene and toluene are subject to CRC in P. putida[16, 30–34]. Indeed Crc mediated post-transcriptional control of the pheA and pheB toluene degradation genes , the benR activator of benzene degradation , the alkS activator of alkane degradation , the xylR activator of the TOL genes and xylB (benzyl alcohol dehydrogenase)  and the bkdR activator of branched-chain keto acid dehydrogenase  has been demonstrated. The Crc protein is known to bind in vitro to mRNAs of the PU, PM, PS1, PR1, promoters and mRNAs of the xylMABN (and weakly to xylL and xylQ) genes of the pWW0 toluene degradation plasmid in P. putida indicating that these targets may also be regulated by directly by Crc . Besides the role that CRC plays in the bioremediation activities of P. putida, little else is known about the control that CRC imposes on the ecological functions of Pseudomonads other than for virulence-associated functions in Pseudomonas aeruginosa. A crc mutant of P. aeruginosa PA14 was defective in biofilm formation and type IV pilus-mediated twitching motility . and a crc mutant of P. aeruginosa PAO1 displayed increased susceptibility to some antibiotics as well as defects in type III secretion, motility and expression of quorum sensing-regulated virulence factors . Given the range of ecological functions that Pseudomonas may perform there is great scope for Crc to be a significant regulator beyond the realm of primary metabolism. For instance, glucose metabolism is subject to CRC and gluconate is a product of glucose metabolism. Gluconate itself is linked to phosphate solubilisation  and biocontrol  and there is a link between the ability to produce gluconate and the levels of antimicrobial compounds produced such as 2,4-diacetylphloroglucinol and pyoluteorin . Additionally, recent evidence indicates that there is a link between primary metabolism and secondary metabolism controlled by the GacS/Rsm system . This suggests that there is great potential for CRC to interact with other regulatory networks, at least indirectly, and it is therefore a high priority to better understand the Crc regulon.
Based on the size of the Crc product and the proposed mechanism of action, it is thought that Crc binding must occur within -70 to +16 bp relative to the origin of translation . There remain, however, very few known direct targets of Crc: only benR, alkS, xylR and xylB mRNAs from P. putida and amiE mRNA  (product of the amidase gene amiE), in P. aeruginosa have been demonstrated to bind Crc. To extend the number of direct targets known, we carried out a bioinformatic analysis using genome information from sequenced Pseudomonas strains. By identifying the specific targets in pathways that are known to be regulated by CRC, it will be possible to determine precisely how different Pseudomonads control nutrient uptake and utilisation. Furthermore, the analysis is expected to identify new pathways and processes, not previously known to be CRC-regulated. A better understanding of how Pseudomonas species use CRC will enhance knowledge of the ecology of these bacteria and will facilitate efforts to exploit the metabolic capacity of these bacteria in industrial and environmental microbiology.
Crc binding site detection: estimation of the numbers of Crc regulated genes in Pseudomonas
Predicted core Crc regulon of Pseudomonas.
Amino acid transport and metabolism
Probable amino acid permease
Probable binding protein component of ABC transporter
Probable sodium/alanine symporter
Probable glutamine synthetase
Carbohydrate transport and metabolism
Probable binding protein component of ABC maltose/mannitol transporter
Glucose/carbohydrate outer membrane porin precursor
Probable binding protein component of ABC sugar transporter
PTS fructose IIC component
Glycerol uptake facilitator protein
Energy production and conservation
Cytochrome c oxidase, subunit II
Pyridine nucleotide transhydrogenase, beta subunit
Acetyl-coenzyme A synthetase
Putative glycerate 2-kinase
Probable D-beta-hydroxybutyrate permease
Putative acetate transporter
Probable carbon starvation protein
Poly(3-hydroxyalkanoic acid) synthase 1
polyhydroxyalkanoate synthesis protein PhaF
Alginate regulatory protein
Xenobiotic degradation and transport
DNA replication, recombination and repair
HU family DNA-binding protein
nucleotide transport and metabolism
50S ribosomal protein L18
Elongation factor Tu
Probable major facilitator superfamily (MFS) transporter
Probable ATP-binding component of ABC transporter
Phosphotransferase domain-containing protein
Comparison of predicted Crc-regulated candidates to experimental datasets
Comparison of predicted Crc regulon of P. putida with transcriptome and proteome data.
outer membrane ferric siderophore receptor
FruR transcriptional regulator
PTS fructose IIC component
glyceraldehyde-3-phosphate dehydrogenase, type I
probable binding protein component of ABC sugar transporter
Glucose/carbohydrate outer membrane porin OprB precursor
probable amino acid permease
probable binding protein component of ABC transporter
dicarboxylate MFS transporter
cold shock protein CspA
L-asparaginase, type II
3-oxoacid CoA-transferase subunit B
conserved hypothetical protein
amino acid ABC transporter, periplasmic amino acid-binding protein
aromatic amino acid transport protein AroP2
probable DNA-binding protein
acetyl-CoA carboxylase subunit A
Comparison of predicted Crc regulon of P. aeruginosa with proteome data.
conserved hypothetical protein
Basic amino acid, basic peptide and imipenem outer membrane porin OprD precursor
probable acyl-CoA thiolase
probable AMP-binding enzyme
conserved hypothetical protein
probable ATP-binding component of ABC transporter
probable binding protein component of ABC transporter
probable binding protein component of ABC transporter
probable ATP-binding component of ABC dipeptide transporter
D-amino acid dehydrogenase, small subunit
A proteomic analysis comparing the wild type strain P. aeruginosa PAO1 to an isogenic crc mutant in LB broth was also recently performed . Under these conditions, 46 proteins were present at higher levels in the crc mutant compared to the wild type strain, suggesting that these targets are negatively regulated by the CRC system. Comparing those 46 experimentally-identified targets with the 215 predicted Crc targets identified in our bioinformatic study, it is seen that 13 of the 46 targets overlap (Table 3). Of these, 9 common targets have a predicted Crc binding site in the gene itself and a further 4 targets are in operons downstream of predicted Crc targets (Table 3). When the comparison is expanded to include all 279 candidates identified in PAO1 no new matches were found. The authors of that study identified putative Crc-binding sites in the 5' region of 23 of the 46 genes, and suggested that these may be subject to direct Crc mediated regulation . The criteria applied for identifying putative Crc-binding sites was less strict than our study (with respect to consensus and distance from AUG codon), which explains the difference between the 13 binding sites we propose and the 23 postulated by these authors.
The fact that 18/23 overlaps are in the core P. putida regulon (and a further 2 are only excluded because orthologues are absent) and that no new overlaps with experimental data are introduced when the predicted Crc-regulon of P. aeruginosa is considered reinforces the validity of using the presence of the motif in orthologous genes within a species as a selection criterion in the global bioinformatic screen. Although the overlap between the experimental and bioinformatic datasets appears low for P. putida - 18(23)/267 genes - this should not be entirely unexpected. Genes predicted by the bioinformatics but not identified experimentally could simply be because they were below experimental detection limits, or more likely because the growth conditions used favoured some classes of genes. Of course, some hits may represent false positives, and our analysis predicted that there are rates of 18% and 26% false positive hits for P. aeruginosa and P. putida respectively. These are also possible explanations for differences between our data set and the PAO1 proteome data despite the higher level of overlap between our data with PAO1 (13/46) than between our data with KT2440. It is interesting that all three studies identify amino acid metabolism as an important component of the Crc-regulon. This reflects Crc metabolic adaptations in a nutrient rich environment (which was the experimental condition) where various amino acids are the major carbon sources. Performing the transcriptome/proteome experiments under different growth conditions, would be likely to yield a different set of genes. Conversely, there were also targets identified in the experimental studies that did not feature in the bioinformatic analysis. The most likely explanation for this is that these are indirect rather than direct targets of Crc as they lack the predicted Crc binding site. It is also possible, however, that the strict criteria used in the bioinformatic analysis excluded some genuine targets, or that Crc has alternative or additional binding sites, perhaps used only under certain conditions. From comparing all the data, we can already see that this was probably the case with the bkdA1 gene, which was identified as a target experimentally in both P. putida and P. aeruginosa, but bioinformatically only in P. putida (Table 2). The proposed Crc binding site in P. aeruginosa is AACAAGAGAAACAA , which differs in some positions to the consensus AAnAAnAA used in the bioinformatic analysis. Ultimately, protein-mRNA binding studies will be needed to resolve all these Crc-binding possibilities.
Crc regulates carbohydrate and amino acid utilisation
It is notable that another gene, cstA, with a predicted role in carbon starvation stress alleviation was also implicated as a Crc candidate. The CstA protein is involved in peptide transport that would assist the cell in escaping carbon starvation . In Escherichia coli, induction of the cstA gene depends on cAMP and Crp  indicating that this locus is subject to CCR in E. coli. It is intriguing that a locus is implicated as being subject to catabolite repression in both Escherichia and Pseudomonas, despite differences in preferred nutrient sources and mechanisms of catabolite repression.
Crc regulates transcriptional activators that are induced during stationary phase
Crc also seems to regulate proteins involved in transcriptional regulation, as previously described . Indeed the gene, hupA, encoding a bacterial histone like protein (HU-like protein), possesses a Crc motif in the P. aeruginosa, P. putida and P. fluorescens species. HU proteins are ubiquitous DNA binding factors that are involved in the structural maintenance of the bacterial chromosome and other events that require DNA binding . In contrast to the structurally related integration host factor (IHF), HU proteins bind DNA in a sequence-independent manner. Generally, Pseudomonas possesses five HU/IHF copies per genome . Two of these ORFs encode the two subunits of the IHF (integration host factor) protein (ihfA and ihfB), whereas hupA (or hupP), hupB and hupN encode HU-like proteins. Although the precise role of hupA is not known, HU-like proteins are required for transcription from the σ54-dependent Ps promoter of the toluene degradation pathway in P. putida, which is known to be subject to control by the CRC system. Identification of the Crc motif would be consistent with the idea that Crc impacts indirectly on the transcription level of a subset of genes through translational regulation of the regulatory genes hupA or ihfB. This may also explain some of the indirect targets of Crc identified in the transcriptome/proteome analysis discussed earlier . The expression of hupA, hupB and hupN has been monitored during P. putida KT2440 growth . Interestingly, whereas hupB and hupN transcript abundances are maximal in exponential phase, hupA expression seems to be activated during stationary phase. Remarkably, another Crc candidate of P. aeruginosa and P. syringae, ihfB, has increased expression during transition of cells from exponential growth to stationary phase . This observation is not an isolated phenomenon as other predicted Crc targets, for example cstA[47, 48] and polyhydroxyalkanoate biosynthesis (phaC1 or phaZ) , are also induced at the onset of stationary phase. CRC is depressed during stationary phase  so these observations on expression are consistent with a role for Crc in repressing expression of target genes during active growth.
Crc regulates virulence-related traits
It was shown previously that a crc mutant of P. aeruginosa PA14 was defective for biofilm formation and type IV pilus-mediated twitching motility  and a crc mutant of P. aeruginosa PAO1 is compromised in type III secretion, motility, expression of quorum sensing-regulated virulence factors and was less virulent in a Dictyostelium discoideum model . Therefore, we searched for bioinformatic evidence that Crc integrates nutritional status cues with the regulation of virulence-related traits. We postulate that Crc might regulate some steps in alginate biosynthesis in Pseudomonas. Alginate production is linked to the conversion of microcolonies from a non-mucoid to a mucoid phenotype. In P. aeruginosa this phenotype marks the transition to a more persistent state during pulmonary infection, characterised by antibiotic resistance and accelerated pulmonary decline . The regulation of alginate production in Pseudomonas is highly complex and involves the interaction of many regulatory systems . In this study, the transcriptional activator AlgP, involved in the transcription of a key alginate biosynthetic gene, algD encoding GDP-mannose 6-dehydrogenase, is predicted, to be directly regulated by Crc in P. aeruginosa, P. putida and P. syringae species. In this case, the interspecific Crc regulation blocks the synthesis of a transcriptional regulator which leads to indirect regulation of the biosynthetic pathway, reminiscent of the cases of alkS and benR in P. putida. Nevertheless, at the species level, Crc is also predicted to regulate some enzymes directly. In P. aeruginosa, Crc also is predicted to bind to alg8 and algF transcripts which encode a subunit of alginate polymerase [58, 59] and an alginate acetylation protein  respectively. The synthesis of the alginate precursor, mannose-6-phosphate, encoded by algA, is predicted to be under the control of Crc in P. fluorescens only (Figure 2). The additional levels of regulation of alginate in P. aeruginosa, could reflect the importance of this exopolysaccharide for persistence in specialised ecological niches, including inside the host.
Another interesting Crc target is estA encoding an autotransporter protein with esterase activity  that is indispensable for rhamnolipid production . Rhamnolipids are surface-active molecules that play a role in biofilm fluidity  and are toxic against a variety of microorganisms . Preliminary experiments confirm that rhamnolipid production is a Crc-regulated trait in P. aeruginosa (data not shown). Moreover, inactivation of the estA gene in P. aeruginosa also influenced other virulence-related functions like swimming, twitching and swarming in a rhamnolipid-independent fashion . Rhamnolipids have numerous features in common with polyhydroxyalkanoic acid (PHAs), a metabolic storage material involved in bacterial stress-resistance and biofilm formation . Firstly they are both synthesised in response to the presence of excess carbon where other nutrients, such as nitrogen or phosphorus, are growth limiting [54, 64, 66]. Secondly, both molecules are composed of 3-hydroxydecanoic acids connected by ester bonds. Interestingly, phaC1 and phaF encoding a PHA polymerase and PHA transcriptional regulator respectively are also predicted to be Crc regulated in P. aeruginosa, P. putida and P. syringae species. Notwithstanding the role of PHA in attachment of P. aeruginosa to surfaces , the implication of Crc in PHA production may also be interesting from an industrial point of view since it is hoped that PHA accumulating bacteria may be exploited in bioplastic production . Under high carbon:nitrogen ratios, PHA and rhamnolipids are produced and represent carbon sinks to accommodate an inability to metabolise an excess of carbon over nitrogen. One possible function of the CRC system is to integrate C/N metabolism by regulating the production of carbon sink compounds such as PHA and rhamnolipid. This could be mediated by the CbrAB/NtrBC links outlined earlier.
CRC is an important global control network employed by Pseudomonas to optimise growth with available nutrients in a variety of environments. This analysis aimed to predict the set of targets that are directly regulated by the Crc protein in four species of Pseudomonas. As expected, genes involved in the metabolism of less favoured nutrients were identified. An interesting feature, however, was that the regulation of transporters is a conserved feature of Crc regulation in Pseudomonas spp. while the regulation of particular enzymatic steps and transcriptional activators is generally present in a more species-dependent manner. This suggests that different Pseudomonas species have fine-tuned CRC to reflect the ecology of that particular species. In addition to anticipated effects on sugar metabolism, there are indications from the data that Crc may play a role in maintaining the carbon/nitrogen balance in Pseudomonas and this is worthy of further study. It was postulated that identifying Crc targets might enhance knowledge of some applied aspects of Pseudomonas and one example of this was the prediction that Crc regulates steps in polyhydroxyalkanoate (PHA) synthesis in P. putida, as this is of interest for the production of biodegradable bioplastics. In the case of P. aeruginosa, the analysis revealed that alginate production and other traits linked to virulence may be under CRC control. It was especially intriguing to discover that Crc may play a role in regulation of globally important DNA binding proteins such as HU and IHF and thus regulate, indirectly, many pathways that depend on the DNA bending properties of these proteins for transcription or repression. These novel aspects of Crc regulation therefore deserve further investigation given the potential that it may enhance our understanding of the integration of nutritional status cues with the regulation of important activities of the Pseudomonas.
Positions -70 to +16 relative to the origin of translation of all protein encoding genes of available Pseudomonas spp. were downloaded from the regulatory sequence analysis tool (RSAT)  using the retrieve sequence function. Genes containing an A-rich (AAnAAnAA) motif in the -70 to +16 region were identified using a script in Perl. Translated protein encoding sequences were downloaded from the Pseudomonas genome database  and used to create local blast databases with formatdb . Orthologous genes were identified as best hits using blastp analysis (blastall v2.2.22) [71, 72] against local databases. Cut-offs of 50% identity over at least 80% of the sequence length and an expected value (e-value) of 1e-10 were applied. Orthology was confirmed by reciprocating the blastp analysis. Since the A-rich motif is short and degenerate it is expected that occurrences of the A-rich motif that are unrelated to Crc binding will be detected in this analysis, giving rise to false positive hits. In order to estimate the rate of false positive hits in our analysis we searched for the A-rich motif in the reverse orientation of the upstream regions of orthologous loci . Since the A-rich motif in the reverse orientation is unrelated to Crc binding it is reasoned that this estimates the rate of occurrence of the A-rich motif in the sequence fragments tested. Predictably it was found that the use of more strains per species resulted in lower estimated rates of false positives (P. aeruginosa - 4 strains, 18% estimated false positives; P. fluorescens - 3 strains, 32% estimated false positives; P. putida - 3 strains, 26% estimated false positives; P. syringae - 2 strains, 41% estimated false positives). Thus, it is estimated, based on the weighted mean false discovery rate, that approximately 73% of the Crc candidates in additional file 1 are genuine targets for Crc binding. Functional information about the translated protein sequences was obtained from the sequence headers and by performing Blast2GO analysis .
This research was supported in part by grants awarded by the Science Foundation of Ireland (grants 04/BR/B0597, 07/IN.1/B948, 08/RFP/GEN1295, 08/RFP/GEN1319 and 09/RFP/BMT2350), the Department of Agriculture, Fisheries and Food (RSF grants 06-321 and 06-377; FIRM grants 06RDC459, 06RDC506 and 08RDC629), the European Commission (grant FP6#O36314 and Marie Currie TOK:TRAMWAYS), Irish Research Council for Science Engineering and Technology (grant 05/EDIV/FP107/INTERPAM), the Marine Institute (Beaufort award C&CRA2007/082), the Health Research Board (grants RP/2006/271 and RP/2007/290). P.B. is supported by a STRIVE Doctoral Scholarship from the Environmental Protection Agency, Ireland and the Department of Environment, Heritage and Local Government provided by the Irish Government under the National Development Plan 2007-2013 (EPA-2006-S-21). We thank Pat Higgins for ongoing techncial support and members of our groups for useful discussions.
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