Heterologous expression and structure prediction of a xylanase identified from a compost metagenomic library.

Xylanases are key biocatalysts in the degradation of the ß-1,4-glycosidic linkages in the xylan backbone of hemicellulose. These enzymes are potentially applied in a wide range of bioprocessing industries under harsh conditions. Metagenomics has emerged as powerful tools for the bioprospection and discovery of interesting bioactive molecules from extreme ecosystems with unique features, such as high temperatures. In this study, an innovative combination of function-driven screening of a compost metagenomic library and automatic extraction of halo areas with in-house MATLAB functions resulted in the identification of a promising clone with xylanase activity (LP4). The LP4 clone proved to be an effective xylanase producer under submerged fermentation conditions. Sequence and phylogenetic analyses revealed that the xylanase, Xyl4, corresponded to an endo-1,4-ß-xylanase belonging to glycosyl hydrolase family 10 (GH10). When xyl4 was expressed in Escherichia coli BL21(DE3), the enzyme activity increased about 2-fold compared to the LP4 clone. To get insight on the interaction of the enzyme with the substrate and establish possible strategies to improve its activity, the structure of Xyl4 was predicted, refined, and docked with xylohexaose. Our data unveiled, for the first time, the relevance of the amino acids Glu133 and Glu238 for catalysis, and a close inspection of the catalytic site suggested that the replacement of Phe316 by a bulkier Trp may improve Xyl4 activity. Our current findings contribute to enhancing the catalytic performance of Xyl4 towards industrial applications. KEY POINTS: • A GH10 endo-1,4-ß-xylanase (Xyl4) was isolated from a compost metagenomic library • MATLAB's in-house functions were developed to identify the xylanase-producing clones • Computational analysis showed that Glu133 and Glu238 are crucial residues for catalysis.

Functional and sequence-based metagenomics to uncover carbohydrate-degrading enzymes from composting samples.

The renewable, abundant , and low-cost nature of lignocellulosic biomass can play an important role in the sustainable production of bioenergy and several added-value bioproducts, thus providing alternative solutions to counteract the global energetic and industrial demands. The efficient conversion of lignocellulosic biomass greatly relies on the catalytic activity of carbohydrate-active enzymes (CAZymes). Finding novel and robust biocatalysts, capable of being active under harsh industrial conditions, is thus imperative to achieve an economically feasible process. In this study, thermophilic compost samples from three Portuguese companies were collected, and their metagenomic DNA was extracted and sequenced through shotgun sequencing. A novel multi-step bioinformatic pipeline was developed to find CAZymes and characterize the taxonomic and functional profiles of the microbial communities, using both reads and metagenome-assembled genomes (MAGs) as input. The samples' microbiome was dominated by bacteria, where the classes Gammaproteobacteria, Alphaproteobacteria, and Balneolia stood out for their higher abundance, indicating that the degradation of compost biomass is mainly driven by bacterial enzymatic activity. Furthermore, the functional studies revealed that our samples are a rich reservoir of glycoside hydrolases (GH), particularly of GH5 and GH9 cellulases, and GH3 oligosaccharide-degrading enzymes. We further constructed metagenomic fosmid libraries with the compost DNA and demonstrated that a great number of clones exhibited ß-glucosidase activity. The comparison of our samples with others from the literature showed that, independently of the composition and process conditions, composting is an excellent source of lignocellulose-degrading enzymes. To the best of our knowledge, this is the first comparative study on the CAZyme abundance and taxonomic/functional profiles of Portuguese compost samples. KEY POINTS: • Sequence- and function-based metagenomics were used to find CAZymes in compost samples. • Thermophilic composts proved to be rich in bacterial GH3, GH5, and GH9 enzymes. • Compost-derived fosmid libraries are enriched in clones with ß-glucosidase activity.

Improved method for the extraction of high-quality DNA from lignocellulosic compost samples for metagenomic studies.

The world economy is currently moving towards more sustainable approaches. Lignocellulosic biomass has been widely used as a substitute for fossil sources since it is considered a low-cost bio-renewable resource due to its abundance and continuous production. Compost habitats presenting high content of lignocellulosic biomass are considered a promising source of robust lignocellulose-degrading enzymes. Recently, several novel biocatalysts from different environments have been identified using metagenomic techniques. A key point of the metagenomics studies is the extraction and purification of nucleic acids. Nevertheless, the isolation of high molecular weight DNA from soil-like samples, such as compost, with the required quality for metagenomic approaches remains technically challenging, mainly due to the complex composition of the samples and the presence of contaminants like humic substances. In this work, a rapid and cost-effective protocol for metagenomic DNA extraction from compost samples composed of lignocellulosic residues and containing high content of humic substances was developed. The metagenomic DNA was considered as representative of the global environment and presented high quality (> 99% of humic acids effectively removed) and sufficient quantity (10.5-13.8 µg g-1 of compost) for downstream applications, namely functional metagenomic studies. The protocol takes about 4 h of bench work, and it can be performed using standard molecular biology equipment and reagents available in the laboratory. KEY POINTS/HIGHLIGHTS: • Metagenomic DNA was successfully extracted from compost samples rich in humic acids • The improved protocol was established by optimizing the cell lysis method and buffer • Complete removal of humic acids was achieved through the use of activated charcoal • The suitability of the DNA was proven by the construction of a metagenomic library.

Dataset on free amino acids contents of Serra da Estrela PDO cheeses determined by UPLC-DAD-MS/MS.

The composition of Serra da Estrela PDO cheeses (total fat, total protein, salt and free amino acids) was assessed using NIR spectrophotometry and UPLC-DAD-MS/MS. In total, 24 cheeses were acquired from 6 certified cheesemakers located in 5 different municipalities within the delimited PDO geographical region. Cheeses were produced from raw ewe milk of two autochthonous Portuguese sheep breeds, between November 2017 and March 2018, and were acquired after 45 days of maturation. The data include the mean (and respective standard deviations) levels of moisture (%), total fat (%), total protein (%) and salt (%), obtained by NIR spectrophotometry. As well the mean (and respective standard deviations) of free amino acids contents (mg/100 g of cheese, in wet basis) evaluated using a UPLC-DAD-MS/MS method are shown. The latter data include information regarding 8 essential free amino acids (histidine, leucine-isoleucine, lysine, methionine, phenylalanine, threonine, tryptophan and valine) and 9 non-essential free amino acids (arginine, asparagine, aspartic acid, cysteine, glutamine, glutamic acid, proline, tyrosine and serine). Leucine and isoleucine, being isomers, were quantified together. Leucine-isoleucine, phenylalanine and serine were the most abundant essential free amino acids and cysteine, proline and asparagine were the most abundant non-essential free amino acids. Free amino acids contents depended on the cheese producer as well as on the production time-period.

Serra da Estrela cheese's free amino acids profiles by UPLC-DAD-MS/MS and their application for cheese origin assessment.

Serra da Estrela cheese is a high-value Portuguese Protected Designation of Origin cheese, produced with raw ewe milk. Thus, information regarding its composition is of utmost relevance for both consumers and certified producers. In this work, the chromatographic profiles of free amino acids in cheeses (45 days of maturation, 6 producers located in 5 municipalities and produced from November 2017 to March 2018) were established by UPLC-DAD-MS/MS. The proposed method allowed detecting 19 free amino acids and cystine with overall limits of detection and quantification lower than 44 µmol/L (1.4 mg/100 g cheese, wet matter) and than 134 µmol/L (4.2 mg/100 g cheese, wet matter), respectively. In all cheeses, 17 free amino acids were quantified including 8 essential amino acids (histidine, leucine-isoleucine, lysine, methionine, phenylalanine, threonine, tryptophan and valine) and 9 non-essential amino acids (arginine, asparagine, aspartic acid, cysteine, glutamic acid, glutamine, proline, serine and tyrosine). The amounts of the free amino acids, essential free amino acids, branched chain free amino acids (leucine, isoleucine and valine) plus the free amino acids ratios (mg/g protein) were further used to identify the producer of Serra da Estrela cheeses. Linear discriminant analysis coupled with the simulated annealing variable selection algorithm was used allowing the correct classification of 96% and 90 ±â€¯8% of the samples, for leave-one-out and repeated K-fold cross-validation procedures, respectively. The satisfactory predictive performance pointed out the possibility of using cheeses' amino acids profiles as origin biomarkers for authenticity control, warranting the correctness identification of the cheese producer/brand, which is quite relevant for ensuring the consumer confidence and satisfaction when purchasing this high-value dairy food.