Outstanding impact of soil tillage on the abundance of soil hydrolases revealed by a metagenomic approach

ABSTRACT The soil represents the main source of novel biocatalysts and biomolecules of industrial relevance. We searched for hydrolases in silico in four shotgun metagenomes (4,079,223 sequences) obtained in a 13-year field trial carried out in southern Brazil, under the no-tillage (NT), or conventional tillage (CT) managements, with crop succession (CS, soybean/wheat), or crop rotation (CR, soybean/maize/wheat/lupine/oat). We identified 42,631 hydrolases belonging to five classes by comparing with the KEGG database, and 44,928 sequences by comparing with the NCBI-NR database. The abundance followed the order: lipases > laccases > cellulases > proteases > amylases > pectinases. Statistically significant differences were attributed to the tillage system, with the NT showing about five times more hydrolases than the CT system. The outstanding differences can be attributed to the management of crop residues, left on the soil surface in the NT, and mechanically broken and incorporated into the soil in the CT. Differences between the CS and the CR were slighter, 10% higher for the CS, but not statistically different. Most of the sequences belonged to fungi (Verticillium, and Colletotrichum for lipases and laccases, and Aspergillus for proteases), and to the archaea Sulfolobus acidocaldarius for amylases. Our results indicate that agricultural soils under conservative managements may represent a hotspot for bioprospection of hydrolases.

Comparative genomics using data mining tools.

We have analysed the genomes of representatives of three kingdoms of life, namely, archaea, eubacteria and eukaryota using data mining tools based on compositional analyses of the protein sequences. The representatives chosen in this analysis were Methanococcus jannaschii, Haemophilus influenzae and Saccharomyces cerevisiae. We have identified the common and different features between the three genomes in the protein evolution patterns. M. jannaschii has been seen to have a greater number of proteins with more charged amino acids whereas S. cerevisiae has been observed to have a greater number of hydrophilic proteins. Despite the differences in intrinsic compositional characteristics between the proteins from the different genomes we have also identified certain common characteristics. We have carried out exploratory Principal Component Analysis of the multivariate data on the proteins of each organism in an effort to classify the proteins into clusters. Interestingly, we found that most of the proteins in each organism cluster closely together, but there are a few 'outliers'. We focus on the outliers for the functional investigations, which may aid in revealing any unique features of the biology of the respective organisms