Taxonomic and environmental annotation of bacterial 16S rRNA gene sequences via Shannon entropy and database metadata terms

Abstract

Microbial ecology seeks to describe the diversity and distribution of microorganisms in various habitats within the context of environmental variables. High throughput sequencing has greatly boosted the number and scope of projects aiming to study and analyse these organisms, with ever-increasing amounts of data being generated. Amplicon based taxonomic analysis, which determines the presence of microbial taxa in different environments on the basis of marker gene annotations, often uses percentage identity as the main metric to determine sequence similarity against databases. This data is then used to study the distribution of biodiversity as well as the response of microbial communities to stressors. However, the 16S rRNA gene displays varying degrees of sequence conservation along its length and is therefore prone to provide different results depending on the part of 16S rRNA gene used for sequencing and analysis. Furthermore, sequence alignment is primarily performed using the popular BLAST sequence alignment tool, which incurs a great computational performance penalty although newer, more efficient tools are being developed. A new approach that is fast and more accurate is critically needed to process the avalanche of data. Additionally, repositories of environmental metadata can provide contextual information to sequence annotations, potentially enhancing analysis if they can be incorporated into bioinformatics pipelines. The overarching aim of this work was to enhance the taxonomic annotation of bacterial sequences by developing a weighted scheme that utilizes inherent evolutionary conservation in the bacterial 16S rRNA gene sequences and by adding contextual, environmental information pertaining to these sequences in a systematic fashion.

Date of Award	2017
Original language	English