• Characterization of biphenyl dioxygenase sequences and activities encoded by the metagenomes of highly polychlorobiphenyl-contaminated soils.

      Standfuss-Gabisch, Christine; Al-Halbouni, Djamila; Hofer, Bernd; Helmholtz Centre for infection research, Inhoffenstr. 7, 38124 Braunschweig, Germany. (2012-04)
      Total extracted DNA from two heavily polychlorobiphenyl-contaminated soils was analyzed with respect to biphenyl dioxygenase sequences and activities. This was done by PCR amplification and cloning of a DNA segment encoding the active site of the enzyme. The translated sequences obtained fell into three similarity clusters (I to III). Sequence identities were high within but moderate or low between the clusters. Members of clusters I and II showed high sequence similarities with well-known biphenyl dioxygenases. Cluster III showed low (43%) sequence identity with a biphenyl dioxygenase from Rhodococcus jostii RHA1. Amplicons from the three clusters were used to reconstitute and express complete biphenyl dioxygenase operons. In most cases, the resulting hybrid dioxygenases were detected in cell extracts of the recombinant hosts. At least 83% of these enzymes were catalytically active. Several amino acid exchanges were identified that critically affected activity. Chlorobiphenyl turnover by the enzymes containing the prototype sequences of clusters I and II was characterized with 10 congeners that were major, minor, or not constituents of the contaminated soils. No direct correlations were observed between on-site concentrations and rates of productive dioxygenations of these chlorobiphenyls. The prototype enzymes displayed markedly different substrate and product ranges. The cluster II dioxygenase possessed a broader substrate spectrum toward the assayed congeners, whereas the cluster I enzyme was superior in the attack of ortho-chlorinated aromatic rings. These results demonstrate the feasibility of the applied approach to functionally characterize dioxygenase activities of soil metagenomes via amplification of incomplete genes.
    • Generation of novel-substrate-accepting biphenyl dioxygenases through segmental random mutagenesis and identification of residues involved in enzyme specificity.

      Zielinski, Marco; Kahl, Silke; Standfuss-Gabisch, Christine; Cámara, Beatriz; Seeger, Michael; Hofer, Bernd; Helmholtz Centre for infection research, Inhoffenstr. 7, 38124 Braunschweig, Germany. (2006-03)
      Aryl-hydroxylating dioxygenases are of interest for the degradation of persistant aromatic pollutants, such as polychlorobiphenyls (PCBs), or as catalysts for the functionalization of aromatic scaffolds. In order to achieve dioxygenation of technical mixtures of PCBs, enzymes with broadened or altered substrate ranges are essential. To alter the substrate specificity of the biphenyl dioxygenase (BphA) of Burkholderia xenovorans LB400, we applied a directed evolution approach that used structure-function relationship data to target random mutageneses to specific segments of the enzyme. The limitation of random amino acid (AA) substitutions to regions that are critical for substrate binding and the exclusion of AA exchanges from positions that are essential for catalytic activity yielded enzyme variants of interest at comparatively high frequencies. After only a single mutagenic cycle, 10 beneficial variants were detected in a library of fewer than 1,000 active enzymes. Compared to the parental BphA, they showed between 5- and 200-fold increased turnover of chlorinated biphenyls, with substituent patterns that rendered them largely recalcitrant to attack by BphA-LB400. Determination of their sequences identified AAs that prevent the acceptance of specific PCBs by the wild-type enzyme, such as Pro334 and Phe384. The results suggest prime targets for subsequent cycles of BphA modification. Correlations with a three-dimensional model of the enzyme indicated that most of the exchanges with major influence on substrate turnover do not involve pocket-lining residues and had not been predictable through structural modeling.