Circular Economy of Anaerobic Biofilm Microbiomes: A Meta-Analysis Framework for Re-exploration of Amplicon Sequencing Data

Abstract

AbstractUse of high-throughput sequencing is widespread in efforts to understand the microbial communities in natural and engineered systems. Many built ecosystems, in particular those used for engineered wastewater treatment, have harnessed the metabolic capacity of complex microbial communities for the effective removal and recovery of organic pollutants. Recent efforts to better understand and precisely engineer such systems have increasingly used high-throughput sequencing to map the structure and function of wastewater treatment microbiomes. An enormous amount of data is readily available on online repositories such as the National Center for Biotechnology Information Short Read Archive (NCBI SRA). Here, we describe and provide an optimised meta-analysis workflow to utilise this resource to collate heterogenous studies together for anaerobic digestion research. We analysed 16S rRNA gene Illumina Miseq amplicon sequencing data from 31 anaerobic digestion studies (from high-rate digesters), including >1,300 samples. Additionally, we compare several methodological choices: extraction method, v-region, taxonomical database, and the classifier. We demonstrate that collation of data from multiple v-regions can be achieved by using only the taxa for which sequences are available in the reference databases, without losses in diversity trends. This is made possible by focusing on alternative strategies for taxonomic assignments, namely, bayesian lowest common ancestor (BLCA) algorithm which offers increased resolution to the traditional naïve bayesian classifier (NBC). While we demonstrate this using an anaerobic digestion wastewater treatment dataset, this methodology can be translated to perform meta-analysis on amplicon sequences in any field. These findings not only provide a roadmap for meta-analysis in any field, but additionally provide an opportunity to reuse extensive data resources to ultimately advance knowledge of wastewater treatment systems.ImportanceIn this study, we have combined sequencing data from 31 individual studies with the purpose of identifying a meta-analysis workflow which can accurately collate data derived from sequencing different v-regions with minimal data loss and more accurate diversity patterns. While we have used Anaerobic Digestion (AD) communities for our proof-of-concept, our workflow (Fig 1) can be translated to any Illumina MiSeq meta-analysis study, in any field. Thereby, we provide the foundation for intensive data mining of existing amplicon sequencing resources. Such data-mining can provide a global perspective on complex microbial communities.Graphical Abstract