Quality-score refinement of SSU rRNA gene pyrosequencing differs across gene region for environmental samples

User-friendly bioinformatics pipeline gDAT (graphical downstream analysis tool) for analysing rDNA sequences

High-throughput sequencing (HTS) of multiple organisms in parallel (metabarcoding) has become a routine and cost-effective method for the analysis of microbial communities in environmental samples. However, careful data treatment is required to identify potential errors in HTS data, and the large volume of data generated by HTS requires in-house experience with command line tools for downstream analysis. This paper introduces a pipeline that incorporates the most common command line tools into an easy-to-use graphical interface-gDAT. By using the Python scripting language, the pipeline is compatible with the latest Windows, macOS and Linux operating systems. The pipeline supports analysis of Sanger, 454, IonTorrent, Illumina and PacBio sequences, allows custom modification of quality filtering steps, and implements both open and closed-reference operational taxonomic unit-picking for sequence identification. Predefined parameters are optimized for analysis of small subunit (SSU) rRNA gene amplicons from arbuscular mycorrhizal fungi, but the pipeline is widely applicable to metabarcoding studies targeting a broad range of organisms. The pipeline was additionally tested with data using general eukaryotic primers from the SSU gene region and fungal primers from the internal transcribed spacer (ITS) marker region. We describe the pipeline design and evaluate its performance and speed by conducting analysis of example data sets using different marker regions sequenced on Illumina platforms. The graphical interface, with the option to use the command line if needed, provides an accessible tool for rapid data analysis with repeatability and logging capabilities. Keeping the software open-source maximizes code accessibility, allowing scrutiny and bug fixes by the community.

Determining the Reliability of Measuring Mercury Cycling Gene Abundance with Correlations with Mercury and Methylmercury Concentrations

Methylmercury (MeHg) is a bioaccumulative toxic contaminant in many ecosystems, but factors governing its production are poorly understood. Recent work has shown that the anaerobic microbial conversion of mercury (Hg) to MeHg requires the Hg-methylation genes hgcAB and that these genes can be used as biomarkers in PCR-based estimators of Hg-methylator abundance. In an effort to determine reliable methods for assessing hgcA abundance and diversity and linking them to MeHg concentrations, multiple approaches were compared including metagenomic shotgun sequencing, 16S rRNA gene pyrosequencing and cloning/sequencing hgcAB gene products. Hg-methylator abundance was also determined by quantitative hgcA qPCR amplification and metaproteomics for comparison to the above measurements. Samples from eight sites were examined covering a range of total Hg (HgT; 0.03-14 mg kg^-1 dry wt. soil) and MeHg (0.05-27 μg kg^-1 dry wt. soil) concentrations. In the metagenome and amplicon sequencing of hgcAB diversity, the Deltaproteobacteria were the dominant Hg-methylators while Firmicutes and methanogenic Archaea were typically ∼50% less abundant. This was consistent with metaproteomics estimates where the Deltaproteobacteria were steadily higher. The 16S rRNA gene pyrosequencing did not have sufficient resolution to identify hgcAB⁺ species. Metagenomic and hgcAB results were similar for Hg-methylator diversity and clade-specific qPCR-based approaches for hgcA are only appropriate when comparing the abundance of a particular clade across various samples. Weak correlations between Hg-methylating bacteria and soil Hg concentrations were observed for similar environmental samples, but overall total Hg and MeHg concentrations poorly correlated with Hg-cycling genes.

Exploring Biodiversity and Arsenic Metabolism of Microbiota Inhabiting Arsenic-Rich Groundwaters in Northern Italy

Arsenic contamination of groundwater aquifers is an issue of global concern. Among the affected sites, in several Italian groundwater aquifers arsenic levels above the WHO limits for drinking water are present, with consequent issues of public concern. In this study, for the first time, the role of microbial communities in metalloid cycling in groundwater samples from Northern Italy lying on Pleistocene sediments deriving from Alps mountains has been investigated combining environmental genomics and cultivation approaches. 16S rRNA gene libraries revealed a high number of yet uncultured species, which in some of the study sites accounted for more of the 50% of the total community. Sequences related to arsenic-resistant bacteria (arsenate-reducing and arsenite-oxidizing) were abundant in most of the sites, while arsenate-respiring bacteria were negligible. In some of the sites, sulfur-oxidizing bacteria of the genus Sulfuricurvum accounted for more than 50% of the microbial community, whereas iron-cycling bacteria were less represented. In some aquifers, arsenotrophy, growth coupled to autotrophic arsenite oxidation, was suggested by detection of arsenite monooxygenase (aioA) and 1,5-ribulose bisphosphate carboxylase (RuBisCO) cbbL genes of microorganisms belonging to Rhizobiales and Burkholderiales. Enrichment cultures established from sampled groundwaters in laboratory conditions with 1.5 mmol L^-1 of arsenite as sole electron donor were able to oxidize up to 100% of arsenite, suggesting that this metabolism is active in groundwaters. The presence of heterotrophic arsenic resistant bacteria was confirmed by enrichment cultures in most of the sites. The overall results provided a first overview of the microorganisms inhabiting arsenic-contaminated aquifers in Northern Italy and suggested the importance of sulfur-cycling bacteria in the biogeochemistry of arsenic in these ecosystems. The presence of active arsenite-oxidizing bacteria indicates that biological oxidation of arsenite, in combination with arsenate-adsorbing materials, could be employed for metalloid removal.

Microbial community changes during a toxic cyanobacterial bloom in an alkaline Hungarian lake

The Carpathian Basin is a lowland plain located mainly in Hungary. Due to the nature of the bedrock, alluvial deposits, and a bowl shape, many lakes and ponds of the area are characterized by high alkalinity. In this study, we characterized temporal changes in eukaryal and bacterial community dynamics with high throughput sequencing and relate the changes to environmental conditions in Lake Velence located in Fejér county, Hungary. The sampled Lake Velence microbial populations (algal and bacterial) were analyzed to identify potential correlations with other community members and environmental parameters at six timepoints over 6 weeks in the Spring of 2012. Correlations between community members suggest a positive relationship between certain algal and bacterial populations (e.g. Chlamydomondaceae with Actinobacteria and Acidobacteria), while other correlations allude to changes in these relationships over time. During the study, high nitrogen availability may have favored non-nitrogen fixing cyanobacteria, such as the toxin-producing Microcystis aeruginosa, and the eutrophic effect may have been exacerbated by high phosphorus availability as well as the high calcium and magnesium content of the Carpathian Basin bedrock, potentially fostering exopolymer production and cell aggregation. Cyanobacterial bloom formation could have a negative environmental impact on other community members and potentially affect overall water quality as well as recreational activities. To our knowledge, this is the first prediction for relationships between photoautotrophic eukaryotes and bacteria from an alkaline, Hungarian lake.

Direct 16S rRNA-seq from bacterial communities: a PCR-independent approach to simultaneously assess microbial diversity and functional activity potential of each taxon

The analysis of environmental microbial communities has largely relied on a PCR-dependent amplification of genes entailing species identity as 16S rRNA. This approach is susceptible to biases depending on the level of primer matching in different species. Moreover, possible yet-to-discover taxa whose rRNA could differ enough from known ones would not be revealed. DNA-based methods moreover do not provide information on the actual physiological relevance of each taxon within an environment and are affected by the variable number of rRNA operons in different genomes. To overcome these drawbacks we propose an approach of direct sequencing of 16S ribosomal RNA without any primer- or PCR-dependent step. The method was tested on a microbial community developing in an anammox bioreactor sampled at different time-points. A conventional PCR-based amplicon pyrosequencing was run in parallel. The community resulting from direct rRNA sequencing was highly consistent with the known biochemical processes operative in the reactor. As direct rRNA-seq is based not only on taxon abundance but also on physiological activity, no comparison between its results and those from PCR-based approaches can be applied. The novel principle is in this respect proposed not as an alternative but rather as a complementary methodology in microbial community studies.

A Lipid-Accumulating Alga Maintains Growth in Outdoor, Alkaliphilic Raceway Pond with Mixed Microbial Communities

Algal biofuels and valuable co-products are being produced in both open and closed cultivation systems. Growing algae in open pond systems may be a more economical alternative, but this approach allows environmental microorganisms to colonize the pond and potentially infect or outcompete the algal "crop." In this study, we monitored the microbial community of an outdoor, open raceway pond inoculated with a high lipid-producing alkaliphilic alga, Chlorella vulgaris BA050. The strain C. vulgaris BA050 was previously isolated from Soap Lake, Washington, a system characterized by a high pH (∼9.8). An outdoor raceway pond (200 L) was inoculated with C. vulgaris and monitored for 10 days and then the culture was transferred to a 2,000 L raceway pond and cultivated for an additional 6 days. Community DNA samples were collected over the 16-day period in conjunction with water chemistry analyses and cell counts. Universal primers for the SSU rRNA gene sequences for Eukarya, Bacteria, and Archaea were used for barcoded pyrosequence determination. The environmental parameters that most closely correlated with C. vulgaris abundance were pH and phosphate. Community analyses indicated that the pond system remained dominated by the Chlorella population (93% of eukaryotic sequences), but was also colonized by other microorganisms. Bacterial sequence diversity increased over time while archaeal sequence diversity declined over the same time period. Using SparCC co-occurrence network analysis, a positive correlation was observed between C. vulgaris and Pseudomonas sp. throughout the experiment, which may suggest a symbiotic relationship between the two organisms. The putative relationship coupled with high pH may have contributed to the success of C. vulgaris. The characterization of the microbial community dynamics of an alkaliphilic open pond system provides significant insight into open pond systems that could be used to control photoautotrophic biomass productivity in an open, non-sterile environment.

Improved taxonomic assignment of human intestinal 16S rRNA sequences by a dedicated reference database

BACKGROUND

Current sequencing technology enables taxonomic profiling of microbial ecosystems at high resolution and depth by using the 16S rRNA gene as a phylogenetic marker. Taxonomic assignation of newly acquired data is based on sequence comparisons with comprehensive reference databases to find consensus taxonomy for representative sequences. Nevertheless, even with well-characterised ecosystems like the human intestinal microbiota it is challenging to assign genus and species level taxonomy to 16S rRNA amplicon reads. A part of the explanation may lie in the sheer size of the search space where competition from a multitude of highly similar sequences may not allow reliable assignation at low taxonomic levels. However, when studying a particular environment such as the human intestine, it can be argued that a reference database comprising only sequences that are native to the environment would be sufficient, effectively reducing the search space.

RESULTS

We constructed a 16S rRNA gene database based on high-quality sequences specific for human intestinal microbiota, resulting in curated data set consisting of 2473 unique prokaryotic species-like groups and their taxonomic lineages, and compared its performance against the Greengenes and Silva databases. The results showed that regardless of used assignment algorithm, our database improved taxonomic assignation of 16S rRNA sequencing data by enabling significantly higher species and genus level assignation rate while preserving taxonomic diversity and demanding less computational resources.

CONCLUSION

The curated human intestinal 16S rRNA gene taxonomic database of about 2500 species-like groups described here provides a practical solution for significantly improved taxonomic assignment for phylogenetic studies of the human intestinal microbiota.

Influence of artifact removal on rare species recovery in natural complex communities using high-throughput sequencing

Large-scale high-throughput sequencing techniques are rapidly becoming popular methods to profile complex communities and have generated deep insights into community biodiversity. However, several technical problems, especially sequencing artifacts such as nucleotide calling errors, could artificially inflate biodiversity estimates. Sequence filtering for artifact removal is a conventional method for deleting error-prone sequences from high-throughput sequencing data. As rare species represented by low-abundance sequences in datasets may be sensitive to artifact removal process, the influence of artifact removal on rare species recovery has not been well evaluated in natural complex communities. Here we employed both internal (reliable operational taxonomic units selected from communities themselves) and external (indicator species spiked into communities) references to evaluate the influence of artifact removal on rare species recovery using 454 pyrosequencing of complex plankton communities collected from both freshwater and marine habitats. Multiple analyses revealed three clear patterns: 1) rare species were eliminated during sequence filtering process at all tested filtering stringencies, 2) more rare taxa were eliminated as filtering stringencies increased, and 3) elimination of rare species intensified as biomass of a species in a community was reduced. Our results suggest that cautions be applied when processing high-throughput sequencing data, especially for rare taxa detection for conservation of species at risk and for rapid response programs targeting non-indigenous species. Establishment of both internal and external references proposed here provides a practical strategy to evaluate artifact removal process.

Correction of sequence-dependent ambiguous bases (Ns) from the 454 pyrosequencing system

Pyrosequencing of the 16S ribosomal RNA gene (16S) has become one of the most popular methods to assess microbial diversity. Pyrosequencing reads containing ambiguous bases (Ns) are generally discarded based on the assumptions of their non-sequence-dependent formation and high error rates. However, taxonomic composition differed by removal of reads with Ns. We determined whether Ns from pyrosequencing occur in a sequence-dependent manner. Our reads and the corresponding flow value data revealed occurrence of sequence-specific N errors with a common sequential pattern (a homopolymer + a few nucleotides with bases other than the homopolymer + N) and revealed that the nucleotide base of the homopolymer is the true base for the following N. Using an algorithm reflecting this sequence-dependent pattern, we corrected the Ns in the 16S (86.54%), bphD (81.37%) and nifH (81.55%) amplicon reads from a mock community with high precisions of 95.4, 96.9 and 100%, respectively. The new N correction method was applicable for determining most of Ns in amplicon reads from a soil sample, resulting in reducing taxonomic biases associated with N errors and in shotgun sequencing reads from public metagenome data. The method improves the accuracy and precision of microbial community analysis and genome sequencing using 454 pyrosequencing.

Archaeal and bacterial communities in three alkaline hot springs in Heart Lake Geyser Basin, Yellowstone National Park

The Heart Lake Geyser Basin (HLGB) is remotely located at the base of Mount Sheridan in southern Yellowstone National Park (YNP), Wyoming, USA and is situated along Witch Creek and the northwestern shore of Heart Lake. Likely because of its location, little is known about the microbial community structure of springs in the HLGB. Bacterial and archaeal populations were monitored via small subunit (SSU) rRNA gene pyrosequencing over 3 years in 3 alkaline (pH 8.5) hot springs with varying temperatures (44°C, 63°C, 75°C). The bacterial populations were generally stable over time, but varied by temperature. The dominant bacterial community changed from moderately thermophilic and photosynthetic members (Cyanobacteria and Chloroflexi) at 44°C to a mixed photosynthetic and thermophilic community (Deinococcus-Thermus) at 63°C and a non-photosynthetic thermophilic community at 75°C. The archaeal community was more variable across time and was predominantly a methanogenic community in the 44 and 63°C springs and a thermophilic community in the 75°C spring. The 75°C spring demonstrated large shifts in the archaeal populations and was predominantly Candidatus Nitrosocaldus, an ammonia-oxidizing crenarchaeote, in the 2007 sample, and almost exclusively Thermofilum or Candidatus Caldiarchaeum in the 2009 sample, depending on SSU rRNA gene region examined. The majority of sequences were dissimilar (≥10% different) to any known organisms suggesting that HLGB possesses numerous new phylogenetic groups that warrant cultivation efforts.

Phylogenetic affiliation of SSU rRNA genes generated by massively parallel sequencing: new insights into the freshwater protist diversity

Recent advances in next-generation sequencing (NGS) technologies spur progress in determining the microbial diversity in various ecosystems by highlighting, for example, the rare biosphere. Currently, high-throughput pyrotag sequencing of PCR-amplified SSU rRNA gene regions is mainly used to characterize bacterial and archaeal communities, and rarely to characterize protist communities. In addition, although taxonomic assessment through phylogeny is considered as the most robust approach, similarity and probabilistic approaches remain the most commonly used for taxonomic affiliation. In a first part of this work, a tree-based method was compared with different approaches of taxonomic affiliation (BLAST and RDP) of 18S rRNA gene sequences and was shown to be the most accurate for near full-length sequences and for 400 bp amplicons, with the exception of amplicons covering the V5-V6 region. Secondly, the applicability of this method was tested by running a full scale test using an original pyrosequencing dataset of 18S rRNA genes of small lacustrine protists (0.2-5 µm) from eight freshwater ecosystems. Our results revealed that i) fewer than 5% of the operational taxonomic units (OTUs) identified through clustering and phylogenetic affiliation had been previously detected in lakes, based on comparison to sequence in public databases; ii) the sequencing depth provided by the NGS coupled with a phylogenetic approach allowed to shed light on clades of freshwater protists rarely or never detected with classical molecular ecology approaches; and iii) phylogenetic methods are more robust in describing the structuring of under-studied or highly divergent populations. More precisely, new putative clades belonging to Mamiellophyceae, Foraminifera, Dictyochophyceae and Euglenida were detected. Beyond the study of protists, these results illustrate that the tree-based approach for NGS based diversity characterization allows an in-depth description of microbial communities including taxonomic profiling, community structuring and the description of clades of any microorganisms (protists, Bacteria and Archaea).