BackgroundThe rapid expansion of 16S rRNA gene sequencing in challenging clinical contexts has resulted in a growing body of literature of variable quality. To a large extent, this is due to a failure to address spurious signal that is characteristic of samples with low levels of bacteria and high levels of non-bacterial DNA. We have developed a workflow based on the paired-end read Illumina MiSeq-based approach, which enables significant improvement in data quality, post-sequencing. We demonstrate the efficacy of this methodology through its application to paediatric upper-respiratory samples from several anatomical sites.ResultsA workflow for processing sequence data was developed based on commonly available tools. Data generated from different sample types showed a marked variation in levels of non-bacterial signal and ‘contaminant’ bacterial reads. Significant differences in the ability of reference databases to accurately assign identity to operational taxonomic units (OTU) were observed. Three OTU-picking strategies were trialled as follows: de novo, open-reference and closed-reference, with open-reference performing substantially better. Relative abundance of OTUs identified as potential reagent contamination showed a strong inverse correlation with amplicon concentration allowing their objective removal. The removal of the spurious signal showed the greatest improvement in sample types typically containing low levels of bacteria and high levels of human DNA. A substantial impact of pre-filtering data and spurious signal removal was demonstrated by principal coordinate and co-occurrence analysis. For example, analysis of taxon co-occurrence in adenoid swab and middle ear fluid samples indicated that failure to remove the spurious signal resulted in the inclusion of six out of eleven bacterial genera that accounted for 80% of similarity between the sample types.ConclusionsThe application of the presented workflow to a set of challenging clinical samples demonstrates its utility in removing the spurious signal from the dataset, allowing clinical insight to be derived from what would otherwise be highly misleading output. While other approaches could potentially achieve similar improvements, the methodology employed here represents an accessible means to exclude the signal from contamination and other artefacts.Electronic supplementary materialThe online version of this article (doi:10.1186/s40168-015-0083-8) contains supplementary material, which is available to authorized users.

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A metagenomic analysis of two aquifer systems located under a dairy farming region was performed to examine to what extent the composition and function of microbial communities varies between confined and surface-influenced unconfined groundwater ecosystems. A fundamental shift in taxa was seen with an overrepresentation of Rhodospirillales, Rhodocyclales, Chlorobia and Circovirus in the unconfined aquifer, while Deltaproteobacteria and Clostridiales were overrepresented in the confined aquifer. A relative overrepresentation of metabolic processes including antibiotic resistance (β-lactamase genes), lactose and glucose utilization and DNA replication were observed in the unconfined aquifer, while flagella production, phosphate metabolism and starch uptake pathways were all overrepresented in the confined aquifer. These differences were likely driven by differences in the nutrient status and extent of exposure to contaminants of the two groundwater systems. However, when compared with freshwater, ocean, sediment and animal gut metagenomes, the unconfined and confined aquifers were taxonomically and metabolically more similar to each other than to any other environment. This suggests that intrinsic features of groundwater ecosystems, including low oxygen levels and a lack of sunlight, have provided specific niches for evolution to create unique microbial communities. Obtaining a broader understanding of the structure and function of microbial communities inhabiting different groundwater systems is particularly important given the increased need for managing groundwater reserves of potable water.

The composition and diversity of bacteria forming the microbiome of parasitic organisms have implications for differential host pathogenicity and host-parasite co-evolutionary interactions. The microbiome of pathogens can therefore have consequences that are relevant for managing disease prevalence and impact on affected hosts. Here, we investigate the microbiome of an invasive parasitic fly Philornis downsi, recently introduced to the Galápagos Islands, where it poses extinction threat to Darwin's finches and other land birds. Larvae infest nests of Darwin's finches and consume blood and tissue of developing nestlings, and have severe mortality impacts. Using 16s rRNA sequencing data, we characterize the bacterial microbiota associated with P. downsi adults and larvae sourced from four finch host species, inhabiting two islands and representing two ecologically distinct groups. We show that larval and adult microbiomes are dominated by the phyla Proteobacteria and Firmicutes, which significantly differ between life stages in their distributions. Additionally, bacterial community structure significantly differed between larvae retrieved from strictly insectivorous warbler finches (Certhidea olivacea) and those parasitizing hosts with broader dietary preferences (ground and tree finches, Geospiza and Camarhynchus spp., respectively). Finally, we found no spatial effects on the larval microbiome, as larvae feeding on the same host (ground finches) harboured similar microbiomes across islands. Our results suggest that the microbiome of P. downsi changes during its development, according to dietary composition or nutritional needs, and is significantly affected by host-related factors during the larval stage. Unravelling the ecological significance of bacteria for this parasite will contribute to the development of novel, effective control strategies.