Dataset Information

Database Mining for Novel Bacterial ?-Etherases, Glutathione-Dependent Lignin-Degrading Enzymes.

ABSTRACT: Lignin is the most abundant aromatic polymer in nature and a promising renewable source for the provision of aromatic platform chemicals and biofuels. ?-Etherases are enzymes with a promising potential for application in lignin depolymerization due to their selectivity in the cleavage of ?-O-4 aryl ether bonds. However, only a very limited number of these enzymes have been described and characterized so far. Using peptide pattern recognition (PPR) as well as phylogenetic analyses, 96 putatively novel ?-etherases have been identified, some even originating from bacteria outside the order Sphingomonadales A set of 13 diverse enzymes was selected for biochemical characterization, and ?-etherase activity was confirmed for all of them. Some enzymes displayed up to 3-fold higher activity than previously known ?-etherases. Moreover, conserved sequence motifs specific for either LigE- or LigF-type enzymes were deduced from multiple-sequence alignments and the PPR-derived peptides. In combination with structural information available for the ?-etherases LigE and LigF, insight into the potential structural and/or functional role of conserved residues within these sequence motifs is provided. Phylogenetic analyses further suggest the presence of additional bacterial enzymes with potential ?-etherase activity outside the classical LigE- and LigF-type enzymes as well as the recently described heterodimeric ?-etherases.IMPORTANCE The use of biomass as a renewable source and replacement for crude oil for the provision of chemicals and fuels is of major importance for current and future societies. Lignin, the most abundant aromatic polymer in nature, holds promise as a renewable starting material for the generation of required aromatic structures. However, a controlled and selective lignin depolymerization to yield desired aromatic structures is a very challenging task. In this regard, bacterial ?-etherases are especially interesting, as they are able to cleave the most abundant bond type in lignin with high selectivity. With this study, we significantly expanded the toolbox of available ?-etherases for application in lignin depolymerization and discovered more active as well as diverse enzymes than previously known. Moreover, the identification of further ?-etherases by sequence database mining in the future will be facilitated considerably through our deduced etherase-specific sequence motifs.

SUBMITTER: Voß H

PROVIDER: S-EPMC6952239 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature

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Database Mining for Novel Bacterial β-Etherases, Glutathione-Dependent Lignin-Degrading Enzymes.

Voß Hauke H Heck Carina Amata CA Schallmey Marcus M Schallmey Anett A

Applied and environmental microbiology 20200107 2

Lignin is the most abundant aromatic polymer in nature and a promising renewable source for the provision of aromatic platform chemicals and biofuels. β-Etherases are enzymes with a promising potential for application in lignin depolymerization due to their selectivity in the cleavage of β-<i>O</i>-4 aryl ether bonds. However, only a very limited number of these enzymes have been described and characterized so far. Using peptide pattern recognition (PPR) as well as phylogenetic analyses, 96 puta ...[more]

PMID: 31676477

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Project description:Microarrays have become established tools for describing microbial systems, however the assessment of expression profiles for environmental microbial communities still presents unique challenges. Notably, the concentration of particular transcripts are likely very dilute relative to the pool of total RNA, and PCR-based amplification strategies are vulnerable to amplification biases and the appropriate primer selection. Thus, we apply a signal amplification approach, rather than template amplification, to analyze the expression of selected lignin-degrading enzymes in soil. Controls in the form of known amplicons and cDNA from Phanerochaete chrysosporium were included and mixed with the soil cDNA both before and after the signal amplification in order to assess the dynamic range of the microarray. We demonstrate that restored prairie soil expresses a diverse range of lignin-degrading enzymes following incubation with lignin substrate, while farmed agricultural soil does not. The mixed additions of control cDNA with soil cDNA indicate that the mixed biomass in the soil does interfere with low abundance transcript changes, nevertheless our microarray approach consistently reports the most robust signals. Keywords: comparative analysis, microbial ecology, soil microbial communities We used lignin degradation as a model process to demonstrate the use of an oligonucleotide microarray for directly detecting gene expression in soil communities using signal amplification instead of template amplification to avoid the introduction of PCR bias. In the current study, we analyzed mRNA isolated from two distinct soil microbial communities and demonstrate our ability to detect the expression of a small subset of lignin degrading genes following exposure to a lignitic substrate. We also included purified control amplicons and mixed target experiments with pure P. chrysosporium genomic cDNA to determine the level of interference from soil biomass on target hybridization.

Dataset Information

Database Mining for Novel Bacterial ?-Etherases, Glutathione-Dependent Lignin-Degrading Enzymes.

Publications

Database Mining for Novel Bacterial β-Etherases, Glutathione-Dependent Lignin-Degrading Enzymes.

Similar Datasets

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