Altering Toluene 4-Monooxygenase by Active-Site Engineering for the Synthesis of 3-Methoxycatechol, Methoxyhydroquinone, and Methylhydroquinone

Bacterial multicomponent monooxygenases (BMMs) are a heterogeneous family of di-iron monooxygenases which share the very interesting ability to hydroxylate aliphatic and/or aromatic hydrocarbons. Each BMM possesses defined substrate specificity and regioselectivity which match the metabolic requirements of the strain from which it has been isolated. Pseudomonas sp. strain OX1, a strain able to metabolize o-, m-, and p-cresols, produces the BMM toluene/o-xylene monooxygenase (ToMO), which converts toluene to a mixture of o-, m-, and p-cresol isomers. In order to investigate the molecular determinants of ToMO regioselectivity, we prepared and characterized 15 single-mutant and 3 double-mutant forms of the ToMO active site pocket. Using the Monte Carlo approach, we prepared models of ToMO-substrate and ToMO-reaction intermediate complexes which allowed us to provide a molecular explanation for the regioselectivities of wild-type and mutant ToMO enzymes. Furthermore, using binding energy values calculated by energy analyses of the complexes and a simple mathematical model of the hydroxylation reaction, we were able to predict quantitatively the regioselectivities of the majority of the variant proteins with good accuracy. The results show not only that the fine-tuning of ToMO regioselectivity can be achieved through a careful alteration of the shape of the active site but also that the effects of the mutations on regioselectivity can be quantitatively predicted a priori.Bacterial multicomponent monooxygenases (BMMs) are a large and heterogeneous family of nonheme di-iron enzymes which share the very interesting ability to activate dioxygen and transfer a single oxygen atom to a wide variety of substrates (13, 23). Aliphatic and aromatic hydrocarbons are converted, respectively, into alcohols and phenols (3,6,15,21,22,38), alkenes are converted into epoxides (8), and sulfur-containing compounds are oxidized into sulfoxides and sulfones (10).As BMMs allow bacteria to grow on hydrocarbons or xenobiotics as the sole source of carbon and energy, several members of this protein family, including the soluble methane monooxygenases (MMOs) (15, 21), alkene monooxygenases (8), phenol hydroxylases (PHs)/toluene 2-monooxygenases (T2MOs) (3,22), and toluene monooxygenases (TMOs) such as toluene 4-monooxygenase (T4MO) from Pseudomonas mendocina KR1 (38) and toluene/o-xylene monooxygenase (ToMO) from Pseudomonas sp. strain OX1 (6), have been characterized thoroughly.All these enzymes possess defined substrate specificity, regioselectivity, and enantioselectivity properties. For example, TMOs and PHs perform two consecutive hydroxylation reactions with aromatic rings, but usually TMOs are more efficient in the first hydroxylation step, whereas PHs are more efficient in the second (3, 5). Moreover, each TMO and PH shows its own characteristic regioselectivity. T4MO produces more than 96% p-cresol from toluene (25), whereas ToMO produces a mixture of the three isomers of cresol (5). PHs usually produce a large excess of o-cresol-70 a...

mentioning

confidence: 82%

Molecular Determinants of the Regioselectivity of Toluene/ o -Xylene Monooxygenase from Pseudomonas sp. Strain OX1

Notomista

Cafaro²,

Bozza³

et al. 2009

“…The ␤-galactosidase activities were calculated, based on a protein concentration of 0.24 mg protein/ml/OD 600 unit (53). Each experiment was repeated with a second independent culture.…”

Section: Methodsmentioning

confidence: 99%

YliH (BssR) and YceP (BssS) Regulate Escherichia coli K-12 Biofilm Formation by Influencing Cell Signaling

Domka

Lee

Wood

2006

Self Cite

215

224

We previously discovered that yliH and yceP are induced in Escherichia coli biofilms (D. Ren, L. A. Bedzyk, S. M. Thomas, R. W. Ye, and T. K. Wood, Appl. Microbiol. Biotechnol. 64:515-524, 2004). Here, it is shown that deletion of yceP (b1060) and yliH (b0836) increases biofilm formation in continuous-flow chambers with minimal glucose medium by increasing biofilm mass (240-to 290-fold), surface coverage (16-to 31-fold), and mean thickness (2,800-fold). To determine the genetic basis of the increase in biofilm formation, we examined the differential gene expression profile in biofilms for both the mutants relative to the wild-type strain in rich medium with glucose and found that 372 to 882 genes were induced and that 76 to 337 were repressed consistently >2-fold (P < 0.05). The increase in biofilm formation was related to differential expression of genes related to stress response (8 to 64 genes) for both mutants, including rpoS and sdiA. More importantly, 42 to 130 genes related to autoinducer 2 cell signaling were also differentially expressed, including gadAB and flgBCEGHIJLMN, as well as signaling through indole, since 17 to 26 indole-related genes were differentially expressed, including phoAER, gltBD, mtr (encodes protein for indole import), and acrEF (encodes proteins for indole export). Increased biofilm formation in the yliH and yceP mutants in LB supplemented with 0.2% glucose (LB glu) occurred through a reduction in extracellular and intracellular indole concentrations in both mutants (50-to 140-fold), and the addition of indole to the culture restored the wild-type biofilm phenotype; hence, indole represses biofilms. Additionally, both mutants regulate biofilms through quorum sensing, since deletion of either yliH or yceP increased extracellular autoinducer 2 concentrations 50-fold when grown in complex medium (most notably in the stationary phase). Both proteins are involved in motility regulation, since YliH (127 amino acids) and YceP (84 amino acids) repressed motility two to sevenfold (P < 0.05) in LB, and YceP repressed motility sevenfold (P < 0.05) in LB glu. Heightened motility in the yceP mutant occurred, due to increased transcription of the flagella and motility loci, including fliC, motA, and qseB (3-to 86-fold). We propose new names for these two loci: bssR for yliH and bssS for yceP, based on the phrase "regulator of biofilm through signal secretion."Bacteria spend the majority of their existence in biofilm communities (9) attached to a solid or a liquid (6, 33) in an extracellular matrix (10). The study of temporal biofilm development has shown that biofilm formation involves many regulatory mechanisms (15, 45), and DNA microarrays have been used to determine global gene expression patterns in Escherichia coli biofilms (4, 34, 42) and to determine how to control biofilms with plant-derived inhibitors (37). It has been discerned that sulfur metabolism impacts E. coli biofilm formation through CysB and CysE (37,49), that stress responses (e.g., RpoS, RpoE, SoxS, RecA, and DnaK) influence...

“…All vials were shaken at 30°C and 600 rpm (Vibramax 100; Heidolph, Nurenberg, Germany), and the reaction was stopped periodically (a vial was removed at each time period) by filtration of the cells. The progress of enzymatic hydroxylation of PEA was measured by reverse-phase high-performance liquid chromatography (HPLC), and the initial transformation rates (calculated as the amount of PEA decreased in the culture supernatant) were determined by sampling at 0.5-to 20-min intervals during the first 2 to 5 h. The specific activity (nmol/min/mg protein) was calculated as the ratio of the initial transformation rate and the total protein content (0.24 mg protein/ml/OD 600 for T4MO [30]). Activity data reported in this paper are based on at least two independent results.…”

Section: Methodsmentioning

confidence: 99%

Improving Biocatalyst Performance by Integrating Statistical Methods into Protein Engineering

Brouk

Nov

Fishman

2010

Self Cite

Directed evolution and rational design were used to generate active variants of toluene-4-monooxygenase (T4MO) on 2-phenylethanol (PEA), with the aim of producing hydroxytyrosol, a potent antioxidant. Due to the complexity of the enzymatic system-four proteins encoded by six genes-mutagenesis is labor-intensive and time-consuming. Therefore, the statistical model of Nov and Wein (J. Comput. Biol. 12:247-282) was used to reduce the number of variants produced and evaluated in a lab. From an initial data set of 24 variants, with mutations at nine positions, seven double or triple mutants were identified through statistical analysis. The average activity of these mutants was 4.6-fold higher than the average activity of the initial data set. In an attempt to further improve the enzyme activity to obtain PEA hydroxylation, a second round of statistical analysis was performed. Nine variants were considered, with 3, 4, and 5 point mutations. The average activity of the variants obtained in the second statistical round was 1.6-fold higher than in the first round and 7.3-fold higher than that of the initial data set. The best variant discovered, TmoA I100A E214G D285Q, exhibited an initial oxidation rate of 4.4 ؎ 0.3 nmol/min/mg protein, which is 190-fold higher than the rate obtained by the wild type. This rate was also 2.6-fold higher than the activity of the wild type on the natural substrate toluene. By considering only 16 preselected mutants (out of ϳ13,000 possible combinations), a highly active variant was discovered with minimum time and effort.