Metagenomic annotation and bioinformatics analysis applied to definition of microbial bioindicators for soil agricultural management effects in sugarcane production systems

Abstract

We present here a research internship abroad plan which main objective is to address one of two aims described in the ongoing principal research proposal (FAPESP 2012/13321-7). The main objective of this research internship abroad is to use computational method for annotation of metagenomes based on unique signature k-mers that represent members of a protein family. LEfSe algorithm will be applied to identify taxa characterizing the differences between two or more experimental treatments. This is important mainly when searching for potential taxonomic microbial bioindicators to assess agricultural soil management effects on soil. The use of bioindicators is not just restricted to a single species with a limited environmental tolerance, but biological processes or communities can also indicate the condition of the environment. Two different activities compose the work plan: (i) estimate relative abundances of bacterial community members using shotgun sequencing data obtained from soil under sugarcane production systems established at mesocosm scale in greenhouse experiment, and (ii) support the search for taxonomic microbial bioindicators using datasets obtained in the same mesocosm experiment for soil fertility and nutrients availability, soil microbial biomass, soil enzymatic activity, and CO2 and N2O emissions from soil. (AU)