Renee J. Smith

Deriving accurate microbiota profiles from human samples with low bacterial content through post-sequencing processing of Illumina MiSeq data

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.

Metagenomic comparison of microbial communities inhabiting confined and unconfined aquifer ecosystems

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.

Substrate Type Determines Metagenomic Profiles from Diverse Chemical Habitats

Environmental parameters drive phenotypic and genotypic frequency variations in microbial communities and thus control the extent and structure of microbial diversity. We tested the extent to which microbial community composition changes are controlled by shifting physiochemical properties within a hypersaline lagoon. We sequenced four sediment metagenomes from the Coorong, South Australia from samples which varied in salinity by 99 Practical Salinity Units (PSU), an order of magnitude in ammonia concentration and two orders of magnitude in microbial abundance. Despite the marked divergence in environmental parameters observed between samples, hierarchical clustering of taxonomic and metabolic profiles of these metagenomes showed striking similarity between the samples (>89%). Comparison of these profiles to those derived from a wide variety of publically available datasets demonstrated that the Coorong sediment metagenomes were similar to other sediment, soil, biofilm and microbial mat samples regardless of salinity (>85% similarity). Overall, clustering of solid substrate and water metagenomes into discrete similarity groups based on functional potential indicated that the dichotomy between water and solid matrices is a fundamental determinant of community microbial metabolism that is not masked by salinity, nutrient concentration or microbial abundance.

Random Whole Metagenomic Sequencing for Forensic Discrimination of Soils

Here we assess the ability of random whole metagenomic sequencing approaches to discriminate between similar soils from two geographically distinct urban sites for application in forensic science. Repeat samples from two parklands in residential areas separated by approximately 3 km were collected and the DNA was extracted. Shotgun, whole genome amplification (WGA) and single arbitrarily primed DNA amplification (AP-PCR) based sequencing techniques were then used to generate soil metagenomic profiles. Full and subsampled metagenomic datasets were then annotated against M5NR/M5RNA (taxonomic classification) and SEED Subsystems (metabolic classification) databases. Further comparative analyses were performed using a number of statistical tools including: hierarchical agglomerative clustering (CLUSTER); similarity profile analysis (SIMPROF); non-metric multidimensional scaling (NMDS); and canonical analysis of principal coordinates (CAP) at all major levels of taxonomic and metabolic classification. Our data showed that shotgun and WGA-based approaches generated highly similar metagenomic profiles for the soil samples such that the soil samples could not be distinguished accurately. An AP-PCR based approach was shown to be successful at obtaining reproducible site-specific metagenomic DNA profiles, which in turn were employed for successful discrimination of visually similar soil samples collected from two different locations.

The microbiome of otitis media with effusion in Indigenous Australian children

INTRODUCTION Indigenous Australian children have a high prevalence of otitis media with effusion (OME) and associated conductive hearing loss. Only three microbiological studies of middle ear fluid (MEF) from Indigenous Australian children with OME have been reported. All of these were reliant on culture or species-specific PCR assays. The aim of this study was to characterise the middle ear fluid (MEF), adenoid and nasopharyngeal (NP) microbiomes of Indigenous Australian children, using culture-independent 16S rRNA gene sequencing. METHODS MEF, NP swabs and adenoid specimens were collected from 11 children in the Alice Springs region of Central Australia. Bacterial communities in these specimens were characterised using 16S rRNA gene sequencing. RESULTS The microbiota in MEF samples were dominated (>50% relative abundance) by operational taxonomic units (OTUs) consistent with Alloiococcus otitidis (6/11), Haemophilus influenzae (3/11) or Streptococcus sp. (specifically, Mitis group streptococci which includes Streptococcus pneumoniae) (1/11). Anatomical site selectivity was indicated by the presence of a single conserved Haemophilus OTU in 7/11 MEF samples. In comparison, there were ten distinct Haemophilus OTUs observed across the NP and adenoid samples. Despite significant differences between the MEF and NP/adenoid microbiomes, Streptococcus sp., H. influenzae and Moraxella catarrhalis OTUs were common to all sample types. Co-occurrence of classical otopathogens in paired MEF and NP/Adenoid samples is consistent with earlier culture-based studies. CONCLUSION These data highlight the need to further assess H. influenzae traits important in otitis media and to understand the role of canal flora, especially A. otitidis, in populations with a high prevalence of tympanic membrane perforation.

A polyphasic approach for assessing the suitability of bioremediation for the treatment of hydrocarbon-impacted soil.

Bioremediation strategies, though widely used for treating hydrocarbon-contaminated soil, suffer from lack of biodegradation endpoint accountability. To address this limitation, molecular approaches of alkB gene analysis and pyrosequencing were combined with chemical approaches of bioaccessibility and nutrient assays to assess contaminant degrading capacity and develop a strategy for endpoint biodegradation predictions. In long-term hydrocarbon-contaminated soil containing 10.3 g C10-C36 hydrocarbons kg(-1), 454 pyrosequencing detected the overrepresentation of potential hydrocarbon degrading genera such as Pseudomonas, Burkholderia, Mycobacterium and Gordonia whilst amplicons for PCR-DGGE were detected only with alkB primers targeting Pseudomonas. This indicated the presence of potential microbial hydrocarbon degradation capacity in the soil. Using non-exhaustive extraction methods of 1-propanol and HP-β-CD for hydrocarbon bioaccessibility assessment combined with biodegradation endpoint predictions with linear regression models, we estimated 33.7% and 46.7% hydrocarbon removal respectively. These predictions were validated in pilot scale studies using an enhanced natural attenuation strategy which resulted in a 46.4% reduction in soil hydrocarbon content after 320 days. When predicted biodegradation endpoints were compared to measured values, there was no significant difference (P=0.80) when hydrocarbon bioaccessibility was assessed with HP-β-CD. These results indicate that a combination of molecular and chemical techniques that inform microbial diversity, functionality and chemical bioaccessibility can be valuable tools for assessing the suitability of bioremediation strategies for hydrocarbon-contaminated soil.

Confined aquifers as viral reservoirs

Knowledge about viral diversity and abundance in deep groundwater reserves is limited. We found that the viral community inhabiting a deep confined aquifer in South Australia was more similar to reclaimed water communities than to the viral communities in the overlying unconfined aquifer community. This similarity was driven by high relative occurrence of the single-stranded DNA viral groups Circoviridae, Geminiviridae and Microviridae, which include many known plant and animal pathogens. These groups were present in a 1500-year-old water situated 80 m below the surface, which suggests the potential for long-term survival and spread of potentially pathogenic viruses in deep, confined groundwater. Obtaining a broader understanding of potentially pathogenic viral communities within aquifers is particularly important given the ability of viruses to spread within groundwater ecosystems.

Determining the metabolic footprints of hydrocarbon degradation using multivariate analysis.

The functional dynamics of microbial communities are largely responsible for the clean-up of hydrocarbons in the environment. However, knowledge of the distinguishing functional genes, known as the metabolic footprint, present in hydrocarbon-impacted sites is still scarcely understood. Here, we conducted several multivariate analyses to characterise the metabolic footprints present in a variety of hydrocarbon-impacted and non-impacted sediments. Non-metric multi-dimensional scaling (NMDS) and canonical analysis of principal coordinates (CAP) showed a clear distinction between the two groups. A high relative abundance of genes associated with cofactors, virulence, phages and fatty acids were present in the non-impacted sediments, accounting for 45.7 % of the overall dissimilarity. In the hydrocarbon-impacted sites, a high relative abundance of genes associated with iron acquisition and metabolism, dormancy and sporulation, motility, metabolism of aromatic compounds and cell signalling were observed, accounting for 22.3 % of the overall dissimilarity. These results suggest a major shift in functionality has occurred with pathways essential to the degradation of hydrocarbons becoming overrepresented at the expense of other, less essential metabolisms.

Putative Effect of Aquifer Recharge on the Abundance and Taxonomic Composition of Endemic Microbial Communities

Drought events and the overexploitation of freshwater resources have led to the increased need to manage groundwater reserves. Aquifer storage and recovery (ASR), whereby artificial water is injected into aquifers for storage, is one of the proposed methods by which freshwater supplies can be increased. Microbial clogging following injection, however, is a major issue. Here, during laboratory simulations of ASR, we used flow cytometry and bar-coded pyrosequencing to investigate changes in microbial abundance and community dynamics. Bacterial abundance ranged from 5.0 × 104 to 1.4 × 107 cells ml-1 before the addition of synthetic wastewater. Following wastewater addition, a 25-fold decrease in abundance was observed, coinciding with a 12-fold increase in viral abundance. Taxa shifted from an overrepresentation of Sphingomonadales, Sphingobacteriales, Rhodospirillales, Caulobacterales, Legionellales, Bacillales, Fusobacteriales and Verrucomicrobiales prior to the addition of synthetic wastewater to Burkholderiales, Actinomycetales, Pseudomonadales, Xanthomonadales, Rhodobacterales, Thizobiales and Thiotrichales following the addition of synthetic wastewater. Furthermore, a significant difference in overall taxonomic composition between the groundwater samples before and after the addition of synthetic wastewater was observed, with water samples exhibiting more similarity to sediment samples after wastewater was added. Collectively, these results suggest that ASR may alter the taxonomic composition of endemic microbial communities and that complete profiles of groundwater properties, including microbial community abundance and composition need to be taken into consideration when selecting aquifers for ASR practices.

Stygofauna enhance prokaryotic transport in groundwater ecosystems

More than 97% of the world’s freshwater reserves are found in aquifers, making groundwater one of the most important resources on the planet. Prokaryotic communities in groundwater underpin the turnover of energy and matter while also maintaining groundwater purity. Thus, knowledge of microbial transport in the subsurface is crucial for maintaining groundwater health. Here, we describe for the first time the importance of stygofauna as vectors for prokaryotes. The “hitch-hiking” prokaryotes associated with stygofauna may be up to 5 orders of magnitude higher in abundance and transported up to 34× faster than bulk groundwater flow. We also demonstrate that prokaryotic diversity associated with stygofauna may be higher than that of the surrounding groundwater. Stygofauna are a newly recognized prokaryotic niche in groundwater ecosystems that have the potential to transport remediating, water purifying and pathogenic prokaryotes. Therefore, stygofauna may influence ecosystem dynamics and health at a microbial level, and at a larger scale could be a new source of prokaryotic diversity in groundwater ecosystems.