Benchmarking of 16S rRNA gene databases using known strain sequences

16S rRNA gene analysis is the most convenient and robust method for microbiome studies. Inaccurate taxonomic assignment of bacterial strains could have deleterious effects as all downstream analyses rely heavily on the accurate assessment of microbial taxonomy. The use of mock communities to check the reliability of the results has been suggested. However, often the mock communities used in most of the studies represent only a small fraction of taxa and are used mostly as validation of sequencing run to estimate sequencing artifacts. Moreover, a large number of databases and tools available for classification and taxonomic assignment of the 16S rRNA gene make it challenging to select the best-suited method for a particular dataset. In the present study, we used authentic and validly published 16S rRNA gene type strain sequences (full length, V3-V4 region) and analyzed them using a widely used QIIME pipeline along with different parameters of OTU clustering and QIIME compatible databases. Data Analysis Measures (DAM) revealed a high discrepancy in ratifying the taxonomy at different taxonomic hierarchies. Beta diversity analysis showed clear segregation of different DAMs. Limited differences were observed in reference data set analysis using partial (V3-V4) and full-length 16S rRNA gene sequences, which signify the reliability of partial 16S rRNA gene sequences in microbiome studies. Our analysis also highlights common discrepancies observed at various taxonomic levels using various methods and databases.     

A total crapshoot? Evaluating bioinformatic decisions in animal diet metabarcoding analyses

Metabarcoding studies provide a powerful approach to estimate the diversity and abundance of organisms in mixed communities in nature. While strategies exist for optimizing sample and sequence library preparation, best practices for bioinformatic processing of amplicon sequence data are lacking in animal diet studies. Here we evaluate how decisions made in core bioinformatic processes, including sequence filtering, database design, and classification, can influence animal metabarcoding results. We show that denoising methods have lower error rates compared to traditional clustering methods, although these differences are largely mitigated by removing low‐abundance sequence variants. We also found that available reference datasets from GenBank and BOLD for the animal marker gene cytochrome oxidase I (COI) can be complementary, and we discuss methods to improve existing databases to include versioned releases. Taxonomic classification methods can dramatically affect results. For example, the commonly used Barcode of Life Database (BOLD) Classification API assigned fewer names to samples from order through species levels using both a mock community and bat guano samples compared to all other classifiers (vsearch‐SINTAX and q2‐feature‐classifier's BLAST + LCA, VSEARCH + LCA, and Naive Bayes classifiers). The lack of consensus on bioinformatics best practices limits comparisons among studies and may introduce biases. Our work suggests that biological mock communities offer a useful standard to evaluate the myriad computational decisions impacting animal metabarcoding accuracy. Further, these comparisons highlight the need for continual evaluations as new tools are adopted to ensure that the inferences drawn reflect meaningful biology instead of digital artifacts.     

Whole-genome amplification (WGA) of marine photosynthetic eukaryote populations

Metagenomics approaches have been developing rapidly in marine sciences. However, the application of these approaches to marine eukaryotes, and in particular to the smallest ones, is challenging because marine microbial communities are dominated by prokaryotes. One way to circumvent this problem is to separate eukaryotic cells using techniques such as single-cell pipetting or flow cytometry sorting. However, the number of cells that can be recovered by such techniques remains low and genetic material needs to be amplified before metagenomic sequencing can be undertaken. In this methodological study, we tested the application of whole-genome amplification (WGA) to photosynthetic eukaryotes. We performed various optimization steps both on a mixture of known microalgal strains and on natural photosynthetic eukaryote populations sorted by flow cytometry. rRNA genes were used as markers for assessing the efficiency of different protocols. Our data indicate that WGA is suitable for the amplification of photosynthetic eukaryote genomes, but that biases are induced, reducing the diversity of the initial population. Nonetheless, this approach appears to be suitable for obtaining metagenomics data on microbial eukaryotic communities.     

Comparison of DNA extraction methods for microbial community profiling with an application to pediatric bronchoalveolar lavage samples

Barcoded amplicon sequencing is rapidly becoming a standard method for profiling microbial communities, including the human respiratory microbiome. While this approach has less bias than standard cultivation, several steps can introduce variation including the type of DNA extraction method used. Here we assessed five different extraction methods on pediatric bronchoalveolar lavage (BAL) samples and a mock community comprised of nine bacterial genera to determine method reproducibility and detection limits for these typically low complexity communities. Additionally, using the mock community, we were able to evaluate contamination and select a relative abundance cut-off threshold based on the geometric distribution that optimizes the trade off between detecting bona fide operational taxonomic units and filtering out spurious ones. Using this threshold, the majority of genera in the mock community were predictably detected by all extraction methods including the hard-to-lyse Gram-positive genus Staphylococcus. Differences between extraction methods were significantly greater than between technical replicates for both the mock community and BAL samples emphasizing the importance of using a standardized methodology for microbiome studies. However, regardless of method used, individual patients retained unique diagnostic profiles. Furthermore, despite being stored as raw frozen samples for over five years, community profiles from BAL samples were consistent with historical culturing results. The culture-independent profiling of these samples also identified a number of anaerobic genera that are gaining acceptance as being part of the respiratory microbiome. This study should help guide researchers to formulate sampling, extraction and analysis strategies for respiratory and other human microbiome samples.     

Water Content Differences Have Stronger Effects than Plant Functional Groups on Soil Bacteria in a Steppe Ecosystem

Many investigations across natural and artificial plant diversity gradients have reported that both soil physicochemical factors and plant community composition affect soil microbial communities. To test the effect of plant diversity loss on soil bacterial communities, we conducted a five-year plant functional group removal experiment in a steppe ecosystem in Inner Mongolia (China). We found that the number and composition type of plant functional groups had no effect on bacterial diversity and community composition, or on the relative abundance of major taxa. In contrast, bacterial community patterns were significantly structured by soil water content differences among plots. Our results support researches that suggest that water availability is the key factor structuring soil bacterial communities in this semi-arid ecosystem.     

Optimal extraction methods for the simultaneous analysis of DNA from diverse organisms and sample types

Using environmental DNA (eDNA) to assess the distribution of micro‐ and macroorganisms is becoming increasingly popular. However, the comparability and reliability of these studies is not well understood as we lack evidence on how different DNA extraction methods affect the detection of different organisms, and how this varies among sample types. Our aim was to quantify biases associated with six DNA extraction methods and identify one which is optimal for eDNA research targeting multiple organisms and sample types. We assessed each methods’ ability to simultaneously extract bacterial, fungal, plant, animal and fish DNA from soil, leaf litter, stream water, stream sediment, stream biofilm and kick‐net samples, as well as from mock communities. Method choice affected alpha‐diversity for several combinations of taxon and sample type, with the majority of the differences occurring in the bacterial communities. While a single method performed optimally for the extraction of DNA from bacterial, fungal and plant mock communities, different methods performed best for invertebrate and fish mock communities. The consistency of methods, as measured by the similarity of community compositions resulting from replicate extractions, varied and was lowest for the animal communities. Collectively, these data provide the first comprehensive assessment of the biases associated with DNA extraction for both different sample types and taxa types, allowing us to identify DNeasy PowerSoil as a universal DNA extraction method. The adoption of standardized approaches for eDNA extraction will ensure that results can be more reliably compared, and biases quantified, thereby advancing eDNA as an ecological research tool.     

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.     

Shotgun metagenomics of soil invertebrate communities reflects taxonomy,biomass, and reference genome properties

• Metagenomics – shotgun sequencing of all DNA fragments from a community DNA extract – is routinely used to describe the composition, structure, and function of microorganism communities. Advances in DNA sequencing and the availability of genome databases increasingly allow the use of shotgun metagenomics on eukaryotic communities. Metagenomics offers major advances in the recovery of biomass relationships in a sample, in comparison to taxonomic marker gene‐based approaches (metabarcoding). However, little is known about the factors which influence metagenomics data from eukaryotic communities, such as differences among organism groups, the properties of reference genomes, and genome assemblies.
• We evaluated how shotgun metagenomics records composition and biomass in artificial soil invertebrate communities at different sequencing efforts. We generated mock communities of controlled biomass ratios from 28 species from all major soil mesofauna groups: mites, springtails, nematodes, tardigrades, and potworms. We shotgun sequenced these communities and taxonomically assigned them with a database of over 270 soil invertebrate genomes.
• We recovered over 95% of the species, and observed relatively high false‐positive detection rates. We found strong differences in reads assigned to different taxa, with some groups (e.g., springtails) consistently attracting more hits than others (e.g., enchytraeids). Original biomass could be predicted from read counts after considering these taxon‐specific differences. Species with larger genomes, and with more complete assemblies, consistently attracted more reads than species with smaller genomes. The GC content of the genome assemblies had no effect on the biomass–read relationships. Results were similar among different sequencing efforts.
• The results show considerable differences in taxon recovery and taxon specificity of biomass recovery from metagenomic sequence data. The properties of reference genomes and genome assemblies also influence biomass recovery, and they should be considered in metagenomic studies of eukaryotes. We show that low‐ and high‐sequencing efforts yield similar results, suggesting high cost‐efficiency of metagenomics for eukaryotic communities. We provide a brief roadmap for investigating factors which influence metagenomics‐based eukaryotic community reconstructions. Understanding these factors is timely as accessibility of DNA sequencing and momentum for reference genomes projects show a future where the taxonomic assignment of DNA from any community sample becomes a reality.

     

Structure and diversity of bacterial, eukaryotic and archaeal communities in glacial cryoconite holes from the Arctic and the Antarctic

The cryosphere presents some of the most challenging conditions for life on earth. Nevertheless, (micro)biota survive in a range of niches in glacial systems, including water-filled depressions on glacial surfaces termed cryoconite holes (centimetre to metre in diameter and up to 0.5?m deep) that contain dark granular material (cryoconite). In this study, the structure of bacterial and eukaryotic cryoconite communities from ten different locations in the Arctic and Antarctica was compared using T-RFLP analysis of rRNA genes. Community structure varied with geography, with greatest differences seen between communities from the Arctic and the Antarctic. DNA sequencing of rRNA genes revealed considerable diversity, with individual cryoconite hole communities containing between six and eight bacterial phyla and five and eight eukaryotic 'first-rank' taxa and including both bacterial and eukaryotic photoautotrophs. Bacterial Firmicutes and Deltaproteobacteria and Epsilonproteobacteria, eukaryotic Rhizaria, Haptophyta, Choanomonada and Centroheliozoa, and archaea were identified for the first time in cryoconite ecosystems. Archaea were only found within Antarctic locations, with the majority of sequences (77%) related to members of the Thaumarchaeota. In conclusion, this research has revealed that Antarctic and Arctic cryoconite holes harbour geographically distinct highly diverse communities and has identified hitherto unknown bacterial, eukaryotic and archaeal taxa, therein.     

Disentangling the complex microbial community of coral reefs using standardized Autonomous Reef Monitoring Structures (ARMS)

Autonomous Reef Monitoring Structures (ARMS) have been applied worldwide to describe eukaryotic cryptic reef fauna. Conversely, bacterial communities, which are critical components of coral reef ecosystem functioning, remain largely overlooked. Here we deployed 56 ARMS across the 2,000‐km spread of the Red Sea to assay biodiversity, composition and inferred underlying functions of coral reef‐associated bacterial communities via 16S rRNA gene sequencing. We found that bacterial community structure and diversity aligned with environmental differences. Indeed, sea surface temperature and macroalgae cover were key in explaining bacterial relative abundance. Importantly, taxonomic and functional alpha diversity decreased under more extreme environmental conditions (e.g., higher temperatures) in the southern Red Sea. This may imply a link between bacterial community diversity and functional capabilities, with implications for conservation management. Our study demonstrates the utility of ARMS to investigate the response of coral reef‐associated bacterial communities to environmental change.     

转几丁质酶和葡聚糖酶双价基因棉花对土壤细菌种群多样性的影响

以转几丁质酶和葡聚糖酶双价基因棉花为研究对象,非转基因受体棉花为对照,通过比较可培养细菌数量和基于16S rRNA克隆文库细菌种群分析,评价外源双价基因的导入在苗期、蕾期、花铃期和吐絮期对棉花根际细菌群落多样性的影响。结果表明,可培养细菌的数量不受外源双价基因的影响,随着棉花生育期的交替而变化,以代谢旺盛的花铃期最多。构建的转基因和非转基因不同生育期根际土壤细菌16S rRNA文库容量为2400个克隆,涵盖了细菌的283个属。其中,Acidobacterium是最大优势类群,共包括624个克隆,其次为未知细菌种群和Flavisolibacter。比较转基因和非转基因棉花根际土壤细菌的种群结构,结果显示,同一生育期内前者种群的多样性显著低于后者,二者的共有类群随着生长发育的进行而增多。研究结果说明几丁质酶基因和葡聚糖酶基因对棉花根际细菌种群多样性有着不同程度的削减作用,但是随着种植时间的延长,该差异呈现逐渐缩小的趋势。     

Soil bacterial diversity in degraded and restored lands of Northeast Brazil

Land degradation deteriorates biological productivity and affects environmental, social, and economic sustainability, particularly so in the semi-arid region of Northeast Brazil. Although some studies exist reporting gross measures of soil microbial parameters and processes, limited information is available on how land degradation and restoration strategies influence the diversity and composition of soil microbial communities. In this study we compare the structure and diversity of bacterial communities in degraded and restored lands in Northeast Brazil and determine the soil biological and chemical properties influencing bacterial communities. We found that land degradation decreased the diversity of soil bacteria as indicated by both reduced operational taxonomic unit (OTU) richness and Shannon index. Soils under native vegetation and restoration had significantly higher bacterial richness and diversity than degraded soils. Redundancy analysis revealed that low soil bacterial diversity correlated with a high respiratory quotient, indicating stressed microbial communities. By contrast, soil bacterial communities in restored land positively correlated with high soil P levels. Importantly, however, we found significant differences in the soil bacterial community composition under native vegetation and in restored land, which may indicate differences in their functioning despite equal levels of bacterial diversity.     

Combined eukaryotic and bacterial community fingerprinting of natural freshwater biofilms using automated ribosomal intergenic spacer analysis

Biofilms are complex communities playing an important role in aquatic ecosystems. Automated ribosomal intergenic spacer analysis (ARISA) has been used successfully to explore biofilm bacterial diversity. However, a gap remains to be filled as regards its application to biofilm eukaryotic populations. The aim of this study is to use ARISA to detect eukaryotic population shifts in biofilm. We designed a new set of primers to focus specifically on the ITS1-5.8S-ITS2 region of diatoms and tested it on natural biofilms. Additionally, we tested universal primers, used previously to perform ARISA on fungal communities. Cloning and sequencing showed that the universal primer set amplified various eukaryotes, whereas the new set was diatom specific. The new set amplified a wider variety of diatoms. Therefore, the universal set is appropriate to study the general eukaryotic population shifts in biofilms, whereas the new set is more appropriate to study diatoms specifically. We used both primer sets, along with a bacterial set, to study the population shifts in natural river biofilms. Principal component analysis of the ARISA fingerprints revealed seasonal shifts that did not coincide for bacterial and eukaryotic communities. Therefore, the use of both eukaryotic and bacterial primers provides a useful insight to assess microbial succession in biofilms.     

Comparison of Bacterial and Fungal Communities Between Natural and Planted Pine Forests in Subtropical China

To improve our understanding of the changes in bacterial and fungal diversity in natural pine and planted forests in subtropical region of China, we examined bacterial and fungal communities from a native and a nearby planted pine forest of the Mt. Lushan by constructing clone libraries of 16S and 18S rRNA genes. For bacterial communities, Proteobacteria and Acidobacteria were dominant bacterial taxa in both two types of forest soils. The Shannon–Wiener diversity index, rarefaction curve analysis, and LibShuff analysis suggest that these two forests contained similar diversity of bacterial communities. Low soil acidity (pH ≈ 4) of our study forests might be one of the most important selection factors determining growth of acidophilic Acidobacteria and Proteobacteria. However, the natural forest harbored greater level of fungal diversity than the planted forest according to the Shannon–Wiener diversity index and rarefaction curve analysis. Basidiomycota and Ascomycota were dominant fungal taxa in the soils of natural and planted forests, respectively. Our results suggest that fungal community was more sensitive than the bacterial community in characterizing the differences in plant cover impacts on the microbial flora in the natural and planted forests. The natural and planted forests may function differently due to the differences in soil fungal diversity and relative abundance.     

Effects of above-ground plant species composition and diversity on the diversity of soil-borne microorganisms

A coupling of above-ground plant diversity and below-ground microbial diversity has been implied in studies dedicated to assessing the role of macrophyte diversity on the stability, resilience, and functioning of ecosystems. Indeed, above-ground plant communities have long been assumed to drive below-ground microbial diversity, but to date very little is known as to how plant species composition and diversity influence the community composition of micro-organisms in the soil. We examined this relationship in fields subjected to different above-ground biodiversity treatments and in field experiments designed to examine the influence of plant species on soil-borne microbial communities. Culture-independent strategies were applied to examine the role of wild or native plant species composition on bacterial diversity and community structure in bulk soil and in the rhizosphere. In comparing the influence of Cynoglossum officinale (hound's tongue) and Cirsium vulgare (spear thistle) on soil-borne bacterial communities, detectable differences in microbial community structure were confined to the rhizosphere. The colonisation of the rhizosphere of both plants was highly reproducible, and maintained throughout the growing season. In a separate experiment, effects of plant diversity on bacterial community profiles were also only observed for the rhizosphere. Rhizosphere soil from experimental plots with lower macrophyte diversity showed lower diversity, and bacterial diversity was generally lower in the rhizosphere than in bulk soil. These results demonstrate that the level of coupling between above-ground macrophyte communities and below-ground microbial communities is related to the tightness of the interactions involved. Although plant species composition and community structure appear to have little discernible effect on microbial communities inhabiting bulk soil, clear and reproducible changes in microbial community structure and diversity are observed in the rhizosphere. This revised version was published online in August 2006 with corrections to the Cover Date.     

Comprehensive single-PCR 16S and 18S rRNA community analysis validated with mock communities,and estimation of sequencing bias against 18S

Universal primers for SSU rRNA genes allow profiling of natural communities by simultaneously amplifying templates from Bacteria, Archaea, and Eukaryota in a single PCR reaction. Despite the potential to show relative abundance for all rRNA genes, universal primers are rarely used, due to various concerns including amplicon length variation and its effect on bioinformatic pipelines. We thus developed 16S and 18S rRNA mock communities and a bioinformatic pipeline to validate this approach. Using these mocks, we show that universal primers (515Y/926R) outperformed eukaryote-specific V4 primers in observed versus expected abundance correlations (slope = 0.88 vs. 0.67–0.79), and mock community members with single mismatches to the primer were strongly underestimated (threefold to eightfold). Using field samples, both primers yielded similar 18S beta-diversity patterns (Mantel test, p < 0.001) but differences in relative proportions of many rarer taxa. To test for length biases, we mixed mock communities (16S + 18S) before PCR and found a twofold underestimation of 18S sequences due to sequencing bias. Correcting for the twofold underestimation, we estimate that, in Southern California field samples (1.2–80 μm), there were averages of 35% 18S, 28% chloroplast 16S, and 37% prokaryote 16S rRNA genes. These data demonstrate the potential for universal primers to generate comprehensive microbiome profiles.     

Archaea, Bacteria, and Algal Plastids Associated with the Reef-Building Corals Siderastrea stellata and Mussismilia hispida from Búzios, South Atlantic Ocean, Brazil

Reef-building corals may be seen as holobiont organisms, presenting diverse associated microbial communities. Best known is the symbiotic relationship with zooxanthellae, but Archaea, Bacteria, fungi, viruses, and algal plastids are also abundant. Until now, there is little information concerning microbial communities associated with Brazilian corals. The present study aims to describe the diversity of Archaea, Bacteria, and eukaryotic algal plastid communities associated with two sympatric species, Siderastrea stellata and Mussismilia hispida, from Southeastern Brazil, using 16S rRNA gene libraries. Since corals present a high number of other associated invertebrates, coral barcoding (COI) was performed to confirm the exclusive occurrence of coral DNA in our samples. Our analysis yielded 354 distinct microbial OTUs, represented mainly by novel phylotypes. Richness (Chao1 and ACE) and diversity (H') estimations of the microbial communities associated with both species were high and comparable to other studies. Rarefaction analyses showed that microbial diversity of S. stellata is higher than that of M. hispida. Libshuff comparative analyses showed that the highest microbial community similarity between the two coral species occurred in the bacterial libraries, while archaeal and plastidial communities were significantly different. Crenarchaeota dominated archaeal communities, while Proteobacteria was the most abundant bacterial phylum, dominated by alpha-Proteobacteria. Plastids were also represented by novel phylotypes and did not match with any 16S rRNA sequences of Cyanobacteria and zooxanthellae from GenBank. Our data improves the pool of available information on Brazilian coral microbes and shows corals as sources of diverse prokaryotic and picoeukaryotic communities.     

Assessment of soil bacterial communities on Alexander Island (in the maritime and continental Antarctic transitional zone)

Despite an increasing number of Antarctic soil diversity assessments, understanding of the bacterial community composition in the arid soil environments of the maritime/continental Antarctic transitional zone remains lacking. Most documented microbiological studies had focused on either the wetter environments of the Antarctic Peninsula/Scotia arc or the exceptionally arid deserts of the Dry Valleys of continental Antarctica. In this study, soil bacterial diversity from three relatively arid sites on Alexander Island and the physicochemical parameters that might influence it were assessed. In general, the study sites exhibited levels of pH, hydration and metal content different from previous reports of maritime or continental Antarctic soil habitats. Although the soil from Alexander Island exhibited similar phylum-level bacterial taxonomic composition to those of other cold and arid environments, each study site was found to harbour significantly different bacterial assemblages. The latter finding was supported by three complementary molecular methods selected to address different elements of diversity. Our analyses of the measured parameters suggest that the differences in bacterial communities were best explained by soil pH and copper content. Using these data, we suggest that soil pH might play an important role in structuring bacterial assemblage patterns across polar soils.