Comparative Metagenomic Analysis of Human Gut Microbiome Composition Using Two Different Bioinformatic Pipelines

Abstract EN

Technological advances in next-generation sequencing-based approaches have greatly impacted the analysis of microbial community composition.

In particular, 16S rRNA-based methods have been widely used to analyze the whole set of bacteria present in a target environment.

As a consequence, several specific bioinformatic pipelines have been developed to manage these data.

MetaGenome Rapid Annotation using Subsystem Technology (MG-RAST) and Quantitative Insights Into Microbial Ecology (QIIME) are two freely available tools for metagenomic analyses that have been used in a wide range of studies.

Here, we report the comparative analysis of the same dataset with both QIIME and MG-RAST in order to evaluate their accuracy in taxonomic assignment and in diversity analysis.

We found that taxonomic assignment was more accurate with QIIME which, at family level, assigned a significantly higher number of reads.

Thus, QIIME generated a more accurate BIOM file, which in turn improved the diversity analysis output.

Finally, although informatics skills are needed to install QIIME, it offers a wide range of metrics that are useful for downstream applications and, not less important, it is not dependent on server times.