Co-occurrence analysis of bacterial families using metagenomic data and network analysis

ORLOWSKI JF; CORREA OS; MONTECCHIA MS; SORIA MA

Rosario

Conferencia; 4to. Congreso Argentino de Bioinformática y Biología Computacional (4CAB2C) y 4ta. Conferencia Internacional de la Sociedad Iberoamericana de Bioinformática (SolBio); 2013

The massive sequencing of amplicons using next-generation technologies has had a deep impact in soil microbial ecology. A significant number of new taxa were discovered and many different environments and conditions were surveyed. A typical study begins by sampling soils under different agricultural management practices or from different locations and soil types. After DNA extraction, amplification of a target gene, sequencing and quality filtering, the resulting reads are aligned to a reference alignment and grouped in operating taxonomical units (OTUs) according to their genetic distances. The samples are characterized according to the frequency of OTUs present, their diversity and genetic distance. Also the OTUs are taxonomically classified. This information can be used, for example, to determine distributions, find core microbiomes or rare taxa. While the search of core microbiomes is useful to determine the composition of the shared communities, they are aggregated data that miss the fine structure of the patterns of taxa co-occurrence. The application of network analysis has been proposed as an alternative way to study patterns of co-occurrence at a higher level of detail [1]. In this work we extend the application of network analysis to a meta-analysis of several datasets, which requires an ad-hoc procedure for taxonomical data normalization, and analyze the fine structure of a connected microbiome applying network clustering techniques.