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

Abstract

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 β-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 β-glucosidase activity.

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

“…This company follows a well-established composting process, controlling and monitoring the initial residues’ composition and type, processing time, and temperature. The sample was collected at the thermophilic phase of the process (temperature of 50 °C) with 4 weeks of composting (Santos-Pereira et al 2023 ). Until DNA extraction, the sample was stored at 4 °C.…”

“…CopyControl™ Fosmid Library Production kit was used for the construction of the metagenomic library according to the manufacturer’s instructions. The high molecular weight DNA (≈ 40 kb) isolated from the compost sample (Santos-Pereira et al 2023 ) was end-repaired and ligated to the pCC1FOS™ vector. The ligation product was packaged into lambda phage and transformed into E. coli EPI300-T1 R cells (Epicentre Biotechnologies, Madison, Wisconsin, USA).…”

“…Mining of novel enzymes with efficient catalytic activities through metagenomics can be performed using two types of approaches, namely sequence- and function-based metagenomics. The sequence-based approach allows the characterization of microbial communities in terms of taxonomy and the prediction of functional diversity by applying complex sequencing methods and databases (e.g., CAZy database) (Kukkar et al 2022 ; Santos-Pereira et al 2023 ; Finore et al 2023 ). On the other hand, function-based metagenomics is focused on the discovery of new metabolic pathways and genes encoding functional enzymes or other bioactive molecules of biotechnological relevance (Pabbathi et al 2021 ; Kukkar et al 2022 ).…”

Exploring the presence of oral bacteria in non-oral sites of patients with cardiovascular diseases using whole metagenomic data

“…Taxonomic profiling of the entire metagenomic data sets was performed with Kaiju software v.1.9.0 64 using the nr_euk database, available in the kaiju web-server (71 GB; 2022-03-10), and standard parameters as described in Santos-Pereira et al . 65 . The Kaiju2table script was used to convert Kaiju’s output files into a summary table for taxonomic ranks.…”