Inter-field variability in the microbial communities of hydrothermal vent deposits from a back-arc basin

Diverse microbial communities thrive on and in deep-sea hydrothermal vent mineral deposits. However, our understanding of the inter-field variability in these communities is poor, as limited sampling and sequencing efforts have hampered most previous studies. To explore the inter-field variability in these communities, we used barcoded pyrosequencing of the variable region 4 (V4) of the 16S rRNA gene to characterize the archaeal and bacterial communities of over 30 hydrothermal deposit samples from six vent fields located along the Eastern Lau Spreading Center. Overall, the bacterial and archaeal communities of the Eastern Lau Spreading Center are similar to other active vent deposits, with a high diversity of Epsilonproteobacteria and thermophilic Archaea. However, the archaeal and bacterial communities from the southernmost vent field, Mariner, were significantly different from the other vent fields. At Mariner, the epsilonproteobacterial genus Nautilia and the archaeal family Thermococcaceae were prevalent in most samples, while Lebetimonas and Thermofilaceae were more abundant at the other vent fields. These differences appear to be influenced in part by the unique geochemistry of the Mariner fluids resulting from active degassing of a subsurface magma chamber. These results show that microbial communities associated with hydrothermal vent deposits in back-arc basins are taxonomically similar to those from mid-ocean ridge systems, but differences in geologic processes between vent fields in a back-arc basin can influence microbial community structure.     

Effect of PCR amplicon size on assessments of clone library microbial diversity and community structure

PCR-based surveys of microbial communities commonly use regions of the small-subunit ribosomal RNA (SSU rRNA) gene to determine taxonomic membership and estimate total diversity. Here we show that the length of the target amplicon has a significant effect on assessments of microbial richness and community membership. Using operational taxonomic unit (OTU)- and taxonomy-based tools, we compared the V6 hypervariable region of the bacterial SSU rRNA gene of three amplicon libraries of c. 100, 400 and 1000 base pairs (bp) from each of two hydrothermal vent fluid samples. We found that the smallest amplicon libraries contained more unique sequences, higher diversity estimates and a different community structure than the other two libraries from each sample. We hypothesize that a combination of polymerase dissociation, cloning bias and mispriming due to secondary structure accounts for the differences. While this relationship is not linear, it is clear that the smallest amplicon libraries contained more different types of sequences, and accordingly, more diverse members of the community. Because divergent and lower abundant taxa can be more readily detected with smaller amplicons, they may provide better assessments of total community diversity and taxonomic membership than longer amplicons in molecular studies of microbial communities.     

Comparing Apples and Oranges?: Next Generation Sequencing and Its Impact on Microbiome Analysis

Rapid advancements in sequencing technologies along with falling costs present widespread opportunities for microbiome studies across a vast and diverse array of environments. These impressive technological developments have been accompanied by a considerable growth in the number of methodological variables, including sampling, storage, DNA extraction, primer pairs, sequencing technology, chemistry version, read length, insert size, and analysis pipelines, amongst others. This increase in variability threatens to compromise both the reproducibility and the comparability of studies conducted. Here we perform the first reported study comparing both amplicon and shotgun sequencing for the three leading next-generation sequencing technologies. These were applied to six human stool samples using Illumina HiSeq, MiSeq and Ion PGM shotgun sequencing, as well as amplicon sequencing across two variable 16S rRNA gene regions. Notably, we found that the factor responsible for the greatest variance in microbiota composition was the chosen methodology rather than the natural inter-individual variance, which is commonly one of the most significant drivers in microbiome studies. Amplicon sequencing suffered from this to a large extent, and this issue was particularly apparent when the 16S rRNA V1-V2 region amplicons were sequenced with MiSeq. Somewhat surprisingly, the choice of taxonomic binning software for shotgun sequences proved to be of crucial importance with even greater discriminatory power than sequencing technology and choice of amplicon. Optimal N50 assembly values for the HiSeq was obtained for 10 million reads per sample, whereas the applied MiSeq and PGM sequencing depths proved less sufficient for shotgun sequencing of stool samples. The latter technologies, on the other hand, provide a better basis for functional gene categorisation, possibly due to their longer read lengths. Hence, in addition to highlighting methodological biases, this study demonstrates the risks associated with comparing data generated using different strategies. We also recommend that laboratories with particular interests in certain microbes should optimise their protocols to accurately detect these taxa using different techniques.     

Dissecting the dominant hot spring microbial populations based on community-wide sampling at single-cell genomic resolution

With advances in DNA sequencing and miniaturized molecular biology workflows, rapid and affordable sequencing of single-cell genomes has become a reality. Compared to 16S rRNA gene surveys and shotgun metagenomics, large-scale application of single-cell genomics to whole microbial communities provides an integrated snapshot of community composition and function, directly links mobile elements to their hosts, and enables analysis of population heterogeneity of the dominant community members. To that end, we sequenced nearly 500 single-cell genomes from a low diversity hot spring sediment sample from Dewar Creek, British Columbia, and compared this approach to 16S rRNA gene amplicon and shotgun metagenomics applied to the same sample. We found that the broad taxonomic profiles were similar across the three sequencing approaches, though several lineages were missing from the 16S rRNA gene amplicon dataset, likely the result of primer mismatches. At the functional level, we detected a large array of mobile genetic elements present in the single-cell genomes but absent from the corresponding same species metagenome-assembled genomes. Moreover, we performed a single-cell population genomic analysis of the three most abundant community members, revealing differences in population structure based on mutation and recombination profiles. While the average pairwise nucleotide identities were similar across the dominant species-level lineages, we observed differences in the extent of recombination between these dominant populations. Most intriguingly, the creek’s Hydrogenobacter sp. population appeared to be so recombinogenic that it more closely resembled a sexual species than a clonally evolving microbe. Together, this work demonstrates that a randomized single-cell approach can be useful for the exploration of previously uncultivated microbes from community composition to population structure.Subject terms: Environmental microbiology, Microbial ecology, Population dynamics     

RiboFR-Seq: a novel approach to linking 16S rRNA amplicon profiles to metagenomes

16S rRNA amplicon analysis and shotgun metagenome sequencing are two main culture-independent strategies to explore the genetic landscape of various microbial communities. Recently, numerous studies have employed these two approaches together, but downstream data analyses were performed separately, which always generated incongruent or conflict signals on both taxonomic and functional classifications. Here we propose a novel approach, RiboFR-Seq (Ribosomal RNA gene flanking region sequencing), for capturing both ribosomal RNA variable regions and their flanking protein-coding genes simultaneously. Through extensive testing on clonal bacterial strain, salivary microbiome and bacterial epibionts of marine kelp, we demonstrated that RiboFR-Seq could detect the vast majority of bacteria not only in well-studied microbiomes but also in novel communities with limited reference genomes. Combined with classical amplicon sequencing and shotgun metagenome sequencing, RiboFR-Seq can link the annotations of 16S rRNA and metagenomic contigs to make a consensus classification. By recognizing almost all 16S rRNA copies, the RiboFR-seq approach can effectively reduce the taxonomic abundance bias resulted from 16S rRNA copy number variation. We believe that RiboFR-Seq, which provides an integrated view of 16S rRNA profiles and metagenomes, will help us better understand diverse microbial communities.     

Investigating the Impact of Storage Conditions on Microbial Community Composition in Soil Samples

Recent advances in DNA sequencing technologies have allowed scientists to probe increasingly complex biological systems, including the diversity of bacteria in the environment. However, despite a multitude of recent studies incorporating these methods, many questions regarding how environmental samples should be collected and stored still persist. Here, we assess the impact of different soil storage conditions on microbial community composition using Illumina-based 16S rRNA V4 amplicon sequencing. Both storage time and temperature affected bacterial community composition and structure. Frozen samples maintained the highest alpha diversity and differed least in beta diversity, suggesting the utility of cold storage for maintaining consistent communities. Samples stored for intermediate times (three and seven days) had both the highest alpha diversity and the largest differences in overall beta diversity, showing the degree of community change after sample collection. These divergences notwithstanding, differences in neither storage time nor storage temperature substantially altered overall communities relative to more than 500 previously examined soil samples. These results systematically support previous studies and stress the importance of methodological consistency for accurate characterization and comparison of soil microbiological assemblages.     

Comparing whole‐genome shotgun sequencing and DNA metabarcoding approaches for species identification and quantification of pollen species mixtures

Molecular identification of mixed‐species pollen samples has a range of applications in various fields of research. To date, such molecular identification has primarily been carried out via amplicon sequencing, but whole‐genome shotgun (WGS) sequencing of pollen DNA has potential advantages, including (1) more genetic information per sample and (2) the potential for better quantitative matching. In this study, we tested the performance of WGS sequencing methodology and publicly available reference sequences in identifying species and quantifying their relative abundance in pollen mock communities. Using mock communities previously analyzed with DNA metabarcoding, we sequenced approximately 200Mbp for each sample using Illumina HiSeq and MiSeq. Taxonomic identifications were based on the Kraken k‐mer identification method with reference libraries constructed from full‐genome and short read archive data from the NCBI database. We found WGS to be a reliable method for taxonomic identification of pollen with near 100% identification of species in mixtures but generating higher rates of false positives (reads not identified to the correct taxon at the required taxonomic level) relative to rbcL and ITS2 amplicon sequencing. For quantification of relative species abundance, WGS data provided a stronger correlation between pollen grain proportion and sequence read proportion, but diverged more from a 1:1 relationship, likely due to the higher rate of false positives. Currently, a limitation of WGS‐based pollen identification is the lack of representation of plant diversity in publicly available genome databases. As databases improve and costs drop, we expect that eventually genomics methods will become the methods of choice for species identification and quantification of mixed‐species pollen samples.     

Next-generation sequencing reveals significant bacterial diversity of botrytized wine

While wine fermentation has long been known to involve complex microbial communities, the composition and role of bacteria other than a select set of lactic acid bacteria (LAB) has often been assumed either negligible or detrimental. This study served as a pilot study for using barcoded amplicon next-generation sequencing to profile bacterial community structure in wines and grape musts, comparing the taxonomic depth achieved by sequencing two different domains of prokaryotic 16S rDNA (V4 and V5). This study was designed to serve two goals: 1) to empirically determine the most taxonomically informative 16S rDNA target region for barcoded amplicon sequencing of wine, comparing V4 and V5 domains of bacterial 16S rDNA to terminal restriction fragment length polymorphism (TRFLP) of LAB communities; and 2) to explore the bacterial communities of wine fermentation to better understand the biodiversity of wine at a depth previously unattainable using other techniques. Analysis of amplicons from the V4 and V5 provided similar views of the bacterial communities of botrytized wine fermentations, revealing a broad diversity of low-abundance taxa not traditionally associated with wine, as well as atypical LAB communities initially detected by TRFLP. The V4 domain was determined as the more suitable read for wine ecology studies, as it provided greater taxonomic depth for profiling LAB communities. In addition, targeted enrichment was used to isolate two species of Alphaproteobacteria from a finished fermentation. Significant differences in diversity between inoculated and uninoculated samples suggest that Saccharomyces inoculation exerts selective pressure on bacterial diversity in these fermentations, most notably suppressing abundance of acetic acid bacteria. These results determine the bacterial diversity of botrytized wines to be far higher than previously realized, providing further insight into the fermentation dynamics of these wines, and demonstrate the utility of next-generation sequencing for wine ecology studies.     

Performance of amplicon and shotgun sequencing for accurate biomass estimation in invertebrate community samples

New applications of DNA and RNA sequencing are expanding the field of biodiversity discovery and ecological monitoring, yet questions remain regarding precision and efficiency. Due to primer bias, the ability of metabarcoding to accurately depict biomass of different taxa from bulk communities remains unclear, while PCR‐free whole mitochondrial genome (mitogenome) sequencing may provide a more reliable alternative. Here, we used a set of documented mock communities comprising 13 species of freshwater macroinvertebrates of estimated individual biomass, to compare the detection efficiency of COI metabarcoding (three different amplicons) and shotgun mitogenome sequencing. Additionally, we used individual COI barcoding and de novo mitochondrial genome sequencing, to provide reference sequences for OTU assignment and metagenome mapping (mitogenome skimming), respectively. We found that, even though both methods occasionally failed to recover very low abundance species, metabarcoding was less consistent, by failing to recover some species with higher abundances, probably due to primer bias. Shotgun sequencing results provided highly significant correlations between read number and biomass in all but one species. Conversely, the read–biomass relationships obtained from metabarcoding varied across amplicons. Specifically, we found significant relationships for eight of 13 (amplicons B1FR‐450 bp, FF130R‐130 bp) or four of 13 (amplicon FFFR, 658 bp) species. Combining the results of all three COI amplicons (multiamplicon approach) improved the read–biomass correlations for some of the species. Overall, mitogenomic sequencing yielded more informative predictions of biomass content from bulk macroinvertebrate communities than metabarcoding. However, for large‐scale ecological studies, metabarcoding currently remains the most commonly used approach for diversity assessment.     

Improved Inference of Taxonomic Richness from Environmental DNA

Accurate estimation of biological diversity in environmental DNA samples using high-throughput amplicon pyrosequencing must account for errors generated by PCR and sequencing. We describe a novel approach to distinguish the underlying sequence diversity in environmental DNA samples from errors that uses information on the abundance distribution of similar sequences across independent samples, as well as the frequency and diversity of sequences within individual samples. We have further refined this approach into a bioinformatics pipeline, Amplicon Pyrosequence Denoising Program (APDP) that is able to process raw sequence datasets into a set of validated sequences in formats compatible with commonly used downstream analyses packages. We demonstrate, by sequencing complex environmental samples and mock communities, that APDP is effective for removing errors from deeply sequenced datasets comprising biological and technical replicates, and can efficiently denoise single-sample datasets. APDP provides more conservative diversity estimates for complex datasets than other approaches; however, for some applications this may provide a more accurate and appropriate level of resolution, and result in greater confidence that returned sequences reflect the diversity of the underlying sample.     

Shallow shotgun sequencing of the microbiome recapitulates 16S amplicon results and provides functional insights

Prevailing 16S rRNA gene-amplicon methods for characterizing the bacterial microbiome of wildlife are economical, but result in coarse taxonomic classifications, are subject to primer and 16S copy number biases, and do not allow for direct estimation of microbiome functional potential. While deep shotgun metagenomic sequencing can overcome many of these limitations, it is prohibitively expensive for large sample sets. Here we evaluated the ability of shallow shotgun metagenomic sequencing to characterize taxonomic and functional patterns in the faecal microbiome of a model population of feral horses (Sable Island, Canada). Since 2007, this unmanaged population has been the subject of an individual-based, long-term ecological study. Using deep shotgun metagenomic sequencing, we determined the sequencing depth required to accurately characterize the horse microbiome. In comparing conventional vs. high-throughput shotgun metagenomic library preparation techniques, we validate the use of more cost-effective laboratory methods. Finally, we characterize similarities between 16S amplicon and shallow shotgun characterization of the microbiome, and demonstrate that the latter recapitulates biological patterns first described in a published amplicon data set. Unlike for amplicon data, we further demonstrate how shallow shotgun metagenomic data provide useful insights regarding microbiome functional potential which support previously hypothesized diet effects in this study system.     

Two-stage microbial community experimental design

Microbial community samples can be efficiently surveyed in high throughput by sequencing markers such as the 16S ribosomal RNA gene. Often, a collection of samples is then selected for subsequent metagenomic, metabolomic or other follow-up. Two-stage study design has long been used in ecology but has not yet been studied in-depth for high-throughput microbial community investigations. To avoid ad hoc sample selection, we developed and validated several purposive sample selection methods for two-stage studies (that is, biological criteria) targeting differing types of microbial communities. These methods select follow-up samples from large community surveys, with criteria including samples typical of the initially surveyed population, targeting specific microbial clades or rare species, maximizing diversity, representing extreme or deviant communities, or identifying communities distinct or discriminating among environment or host phenotypes. The accuracies of each sampling technique and their influences on the characteristics of the resulting selected microbial community were evaluated using both simulated and experimental data. Specifically, all criteria were able to identify samples whose properties were accurately retained in 318 paired 16S amplicon and whole-community metagenomic (follow-up) samples from the Human Microbiome Project. Some selection criteria resulted in follow-up samples that were strongly non-representative of the original survey population; diversity maximization particularly undersampled community configurations. Only selection of intentionally representative samples minimized differences in the selected sample set from the original microbial survey. An implementation is provided as the microPITA (Microbiomes: Picking Interesting Taxa for Analysis) software for two-stage study design of microbial communities.     

Comparison of large-insert,small-insert and pyrosequencing libraries for metagenomic analysis

The development of DNA sequencing methods for characterizing microbial communities has evolved rapidly over the past decades. To evaluate more traditional, as well as newer methodologies for DNA library preparation and sequencing, we compared fosmid, short-insert shotgun and 454 pyrosequencing libraries prepared from the same metagenomic DNA samples. GC content was elevated in all fosmid libraries, compared with shotgun and 454 libraries. Taxonomic composition of the different libraries suggested that this was caused by a relative underrepresentation of dominant taxonomic groups with low GC content, notably Prochlorales and the SAR11 cluster, in fosmid libraries. While these abundant taxa had a large impact on library representation, we also observed a positive correlation between taxon GC content and fosmid library representation in other low-GC taxa, suggesting a general trend. Analysis of gene category representation in different libraries indicated that the functional composition of a library was largely a reflection of its taxonomic composition, and no additional systematic biases against particular functional categories were detected at the level of sequencing depth in our samples. Another important but less predictable factor influencing the apparent taxonomic and functional library composition was the read length afforded by the different sequencing technologies. Our comparisons and analyses provide a detailed perspective on the influence of library type on the recovery of microbial taxa in metagenomic libraries and underscore the different uses and utilities of more traditional, as well as contemporary ‘next-generation'' DNA library construction and sequencing technologies for exploring the genomics of the natural microbial world.     

RiboTagger: fast and unbiased 16S/18S profiling using whole community shotgun metagenomic or metatranscriptome surveys

Background

Taxonomic profiling of microbial communities is often performed using small subunit ribosomal RNA (SSU) amplicon sequencing (16S or 18S), while environmental shotgun sequencing is often focused on functional analysis. Large shotgun datasets contain a significant number of SSU sequences and these can be exploited to perform an unbiased SSU--based taxonomic analysis.

Results

Here we present a new program called RiboTagger that identifies and extracts taxonomically informative ribotags located in a specified variable region of the SSU gene in a high-throughput fashion.

Conclusions

RiboTagger permits fast recovery of SSU-RNA sequences from shotgun nucleic acid surveys of complex microbial communities. The program targets all three domains of life, exhibits high sensitivity and specificity and is substantially faster than comparable programs.

     

Bioinformatic Amplicon Read Processing Strategies Strongly Affect Eukaryotic Diversity and the Taxonomic Composition of Communities

Amplicon read sequencing has revolutionized the field of microbial diversity studies. The technique has been developed for bacterial assemblages and has undergone rigorous testing with mock communities. However, due to the great complexity of eukaryotes and the numbers of different rDNA copies, analyzing eukaryotic diversity is more demanding than analyzing bacterial or mock communities, so studies are needed that test the methods of analyses on taxonomically diverse natural communities. In this study, we used 20 samples collected from the Baltic Sea ice, slush and under-ice water to investigate three program packages (UPARSE, mothur and QIIME) and 18 different bioinformatic strategies implemented in them. Our aim was to assess the impact of the initial steps of bioinformatic strategies on the results when analyzing natural eukaryotic communities. We found significant differences among the strategies in resulting read length, number of OTUs and estimates of diversity as well as clear differences in the taxonomic composition of communities. The differences arose mainly because of the variable number of chimeric reads that passed the pre-processing steps. Singleton removal and denoising substantially lowered the number of errors. Our study showed that the initial steps of the bioinformatic amplicon read processing strategies require careful consideration before applying them to eukaryotic communities.     

Marine microbial community structure assessed from combined metagenomic analysis and ribosomal amplicon deep-sequencing

The microbial taxonomic composition of the three domains of life in two coastal plankton samples was assessed by random total community metagenomic sequencing and PCR-based rDNA amplicon deep-sequencing in order to compare the resulting diversity and investigate possible limitations and complementarities of each method. The various universal primer sets, used to amplify different hypervariable rDNA regions, revealed the same major high-level taxonomic groups in Bacteria and unicellular Eukaryota, and showed a scarce Archaea apparent richness. However, significant differences were found between the different primer sets (p-value < 0.05, with the Kolmogorov–Smirnov test), regarding both operational taxonomic unit (OTU) richness and relative abundance of the major high-level taxonomic groups detected. Based on the metagenomic approach, the phylum Bacteroidetes dominated the prokaryotic community, followed by Proteobacteria, while the detected eukaryotic unicellular taxa belonged to the groups of Alveolata, Fungi, Chlorophyta, Stramenopiles and Phaeophyceae. These groups were found to carry genes typically found in microbial communities, which are linked to DNA, RNA and protein metabolism and the synthesis of nucleotides, amino acids, carbohydrates and vitamins. Although our findings suggest that the total community metagenomic approach can provide a more comprehensive picture of the planktonic microbial community structure, a number of issues associated with this approach emerged. These issues include the still relatively high cost compared to amplicon sequencing, the possible low coverage of the full marine diversity, the insufficiency of databases for other gene markers than the small subunit gene, and the bias towards bacterial sequences because of their higher abundance relative to eukaryotes in marine environments.     

Metaxa2 Diversity Tools: Easing microbial community analysis with Metaxa2

DNA sequencing has become an integrated part of microbial ecology, and taxonomic marker genes such as the SSU and LSU rRNA are frequently used to assess community structure. One solution for taxonomic community analysis based on shotgun metagenomic data is the Metaxa2 software, which can extract and classify sequence fragments belonging to the rRNA genes. This paper describes the Metaxa2 Diversity Tools, a set of new open-source software programs that extends the capabilities of the Metaxa2 software. These tools allow for better handling of data from multiple samples, improved species classifications, rarefaction analysis accounting for unclassified entries, and determination of significant differences in community composition of different samples. We demonstrate the performance of the software tools on rRNA data extracted from different shotgun metagenomes, and find the tools to streamline and improve the assessments of community diversity, particularly for samples from environments for which few reference genomes are available. Finally, we establish that our resampling algorithm for determining community dissimilarity is robust to differences in coverage depth, suggesting that it forms a complement to multidimensional visualization approaches for finding differences between communities. The Metaxa2 Diversity Tools are included in recent versions (2.1 and later) of Metaxa2 (http://microbiology.se/software/metaxa2/) and facilitate implementation of Metaxa2 within software pipelines for taxonomic analysis of environmental communities.     

Endemic and cosmopolitan fungal taxa exhibit differential abundances in total and active communities of Antarctic soils

Our understanding of the diversity and community dynamics of soil fungi has increased greatly through the use of DNA-based identification. Community characterization of metabolically active communities via RNA sequencing has previously revealed differences between ‘active’ and ‘total’ fungal communities, which may be influenced by the persistence of DNA from nonactive components. However, it is not known how fungal traits influence their prevalence in these contrasting community profiles. In this study, we coextracted DNA and RNA from soil collected from three Antarctic islands to test for differences between total and active soil fungal communities. By matching these geographically isolated fungi against a global dataset of soil fungi, we show that widely dispersed taxa are often more abundant in the total community, whilst taxa restricted to Antarctica are more likely to have higher abundance in the active community. In addition, we find that active communities have lower richness, and show a reduction in the abundance of the most dominant fungi, whilst there are consistent differences in the abundances of certain taxonomic groups between the total and active communities. These results suggest that the views of soil fungal communities offered by DNA- and RNA-based characterization differ in predictable ways.