Structural and functional characterization of a novel lipolytic enzyme from a Brazilian Cerrado soil metagenomic library

Precision enzyme discovery through targeted mining of metagenomic data

Metagenomics has opened new avenues for exploring the genetic potential of uncultured microorganisms, which may serve as promising sources of enzymes and natural products for industrial applications. Identifying enzymes with improved catalytic properties from the vast amount of available metagenomic data poses a significant challenge that demands the development of novel computational and functional screening tools. The catalytic properties of all enzymes are primarily dictated by their structures, which are predominantly determined by their amino acid sequences. However, this aspect has not been fully considered in the enzyme bioprospecting processes. With the accumulating number of available enzyme sequences and the increasing demand for discovering novel biocatalysts, structural and functional modeling can be employed to identify potential enzymes with novel catalytic properties. Recent efforts to discover new polysaccharide-degrading enzymes from rumen metagenome data using homology-based searches and machine learning-based models have shown significant promise. Here, we will explore various computational approaches that can be employed to screen and shortlist metagenome-derived enzymes as potential biocatalyst candidates, in conjunction with the wet lab analytical methods traditionally used for enzyme characterization.

Metagenomic Approaches as a Tool to Unravel Promising Biocatalysts from Natural Resources: Soil and Water

Natural resources are considered a promising source of microorganisms responsible for producing biocatalysts with great relevance in several industrial areas. However, a significant fraction of the environmental microorganisms remains unknown or unexploited due to the limitations associated with their cultivation in the laboratory through classical techniques. Metagenomics has emerged as an innovative and strategic approach to explore these unculturable microorganisms through the analysis of DNA extracted from environmental samples. In this review, a detailed discussion is presented on the application of metagenomics to unravel the biotechnological potential of natural resources for the discovery of promising biocatalysts. An extensive bibliographic survey was carried out between 2010 and 2021, covering diverse metagenomic studies using soil and/or water samples from different types and locations. The review comprises, for the first time, an overview of the worldwide metagenomic studies performed in soil and water and provides a complete and global vision of the enzyme diversity associated with each specific environment.

Short-Term Effect in Soil Microbial Community of Two Strategies of Recovering Degraded Area in Brazilian Savanna: A Pilot Case Study

The Brazilian Cerrado is a highland tropical savanna considered a biodiversity hotspot with many endemic species of plants and animals. Over the years, most of the native areas of this biome became arable areas, and with inadequate management, some are nowadays at varying levels of degradation stage. Crop-livestock integrated systems (CLIS) are one option for the recovery of areas in degradation, improving the physicochemical and biological characteristics of the soil while increasing income and mitigating risks due to product diversification. Little is known about the effect of CLIS on the soil microbial community. Therefore, we perform this pilot case study to support further research on recovering degraded areas. The bacterial and fungal soil communities in the area with CLIS were compared to an area under moderate recovery (low-input recovering - LI) and native savanna (NS) area. Bacterial and fungal communities were investigated by 16S and ITS rRNA gene sequencing (deep rRNA sequencing). Ktedonobacteraceae and AD3 families were found predominantly in LI, confirming the relationship of the members of the Chloroflexi phylum in challenging environmental conditions, which can be evidenced in LI. The CLIS soil presented 63 exclusive bacterial families that were not found in LI or NS and presented a higher bacterial richness, which can be related to good land management. The NS area shared 21 and 6 families with CLIS and LI, respectively, suggesting that the intervention method used in the analyzed period brings microbial diversity closer to the conditions of the native area, demonstrating a trend of approximation between NS and CLIS even in the short term. The most abundant fungal phylum in NS treatment was Basidiomycota and Mucoromycota, whereas Ascomycota predominated in CLIS and LI. The fungal community needs more time to recover and to approximate from the native area than the bacterial community. However, according to the analysis of bacteria, the CLIS area behaved differently from the LI area, showing that this treatment induces a faster response to the increase in species richness, tending to more accelerated recovery. Results obtained herein encourage CLIS as a sustainable alternative for recovery and production in degraded areas.