Impact of sequence processing and taxonomic classification approaches on eukaryotic community structure from environmental samples with emphasis on diatoms

Next‐generation sequencing is a common method for analysing microbial community diversity and composition. Configuring an appropriate sequence processing strategy within the variety of tools and methods is a nontrivial task and can considerably influence the resulting community characteristics. We analysed the V4 region of 18S rRNA gene sequences of marine samples by 454‐pyrosequencing. Along this process, we generated several data sets with QIIME, mothur, and a custom‐made pipeline based on DNAStar and the phylogenetic tree‐based PhyloAssigner. For all processing strategies, default parameter settings and punctual variations were used. Our results revealed strong differences in total number of operational taxonomic units (OTUs), indicating that sequence preprocessing and clustering had a major impact on protist diversity estimates. However, diversity estimates of the abundant biosphere (abundance of ≥1%) were reproducible for all conducted processing pipeline versions. A qualitative comparison of diatom genera emphasized strong differences between the pipelines in which phylogenetic placement of sequences came closest to light microscopy‐based diatom identification. We conclude that diversity studies using different sequence processing strategies are comparable if the focus is on higher taxonomic levels, and if abundance thresholds are used to filter out OTUs of the rare biosphere.     

Investigating Microbial Eukaryotic Diversity from a Global Census: Insights from a Comparison of Pyrotag and Full-Length Sequences of 18S rRNA Genes

Next-generation DNA sequencing (NGS) approaches are rapidly surpassing Sanger sequencing for characterizing the diversity of natural microbial communities. Despite this rapid transition, few comparisons exist between Sanger sequences and the generally much shorter reads of NGS. Operational taxonomic units (OTUs) derived from full-length (Sanger sequencing) and pyrotag (454 sequencing of the V9 hypervariable region) sequences of 18S rRNA genes from 10 global samples were analyzed in order to compare the resulting protistan community structures and species richness. Pyrotag OTUs called at 98% sequence similarity yielded numbers of OTUs that were similar overall to those for full-length sequences when the latter were called at 97% similarity. Singleton OTUs strongly influenced estimates of species richness but not the higher-level taxonomic composition of the community. The pyrotag and full-length sequence data sets had slightly different taxonomic compositions of rhizarians, stramenopiles, cryptophytes, and haptophytes, but the two data sets had similarly high compositions of alveolates. Pyrotag-based OTUs were often derived from sequences that mapped to multiple full-length OTUs at 100% similarity. Thus, pyrotags sequenced from a single hypervariable region might not be appropriate for establishing protistan species-level OTUs. However, nonmetric multidimensional scaling plots constructed with the two data sets yielded similar clusters, indicating that beta diversity analysis results were similar for the Sanger and NGS sequences. Short pyrotag sequences can provide holistic assessments of protistan communities, although care must be taken in interpreting the results. The longer reads (>500 bp) that are now becoming available through NGS should provide powerful tools for assessing the diversity of microbial eukaryotic assemblages.     

Effects of OTU Clustering and PCR Artifacts on Microbial Diversity Estimates

Next-generation sequencing has increased the coverage of microbial diversity surveys by orders of magnitude, but differentiating artifacts from rare environmental sequences remains a challenge. Clustering 16S rRNA sequences into operational taxonomic units (OTUs) organizes sequence data into groups of 97 % identity, helping to reduce data volumes and avoid analyzing sequencing artifacts by grouping them with real sequences. Here, we analyze sequence abundance distributions across environmental samples and show that 16S rRNA sequences of >99 % identity can represent functionally distinct microorganisms, rendering OTU clustering problematic when the goal is an accurate analysis of organism distribution. Strict postsequencing quality control (QC) filters eliminated the most prevalent artifacts without clustering. Further experiments proved that DNA polymerase errors in polymerase chain reaction (PCR) generate a significant number of substitution errors, most of which pass QC filters. Based on our findings, we recommend minimizing the number of PCR cycles in DNA library preparation and applying strict postsequencing QC filters to reduce the most prevalent artifacts while maintaining a high level of accuracy in diversity estimates. We further recommend correlating rare and abundant sequences across environmental samples, rather than clustering into OTUs, to identify remaining sequence artifacts without losing the resolution afforded by high-throughput sequencing.     

Ironing out the wrinkles in the rare biosphere through improved OTU clustering

Deep sequencing of PCR amplicon libraries facilitates the detection of low‐abundance populations in environmental DNA surveys of complex microbial communities. At the same time, deep sequencing can lead to overestimates of microbial diversity through the generation of low‐frequency, error‐prone reads. Even with sequencing error rates below 0.005 per nucleotide position, the common method of generating operational taxonomic units (OTUs) by multiple sequence alignment and complete‐linkage clustering significantly increases the number of predicted OTUs and inflates richness estimates. We show that a 2% single‐linkage preclustering methodology followed by an average‐linkage clustering based on pairwise alignments more accurately predicts expected OTUs in both single and pooled template preparations of known taxonomic composition. This new clustering method can reduce the OTU richness in environmental samples by as much as 30–60% but does not reduce the fraction of OTUs in long‐tailed rank abundance curves that defines the rare biosphere.     

Comparing diversity levels in environmental samples: DNA sequence capture and metabarcoding approaches using 18S and COI genes

Environmental DNA studies targeting multiple taxa using metabarcoding provide remarkable insights into levels of species diversity in any habitat. The main drawbacks are the presence of primer bias and difficulty in identifying rare species. We tested a DNA sequence‐capture method in parallel with the metabarcoding approach to reveal possible advantages of one method over the other. Both approaches were performed using the same eDNA samples and the same 18S and COI regions, followed by high throughput sequencing. Metabarcoded eDNA libraries were PCR amplified with one primer pair from 18S and COI genes. DNA sequence‐capture libraries were enriched with 3,639 baits targeting the same gene regions. We tested amplicon sequence variants (ASVs) and operational taxonomic units (OTUs) in silico approaches for both markers and methods, using for this purpose the metabarcoding data set. ASVs methods uncovered more species for the COI gene, whereas the opposite occurred for the 18S gene, suggesting that clustering reads into OTUs could bias diversity richness especially using 18S with relaxed thresholds. Additionally, metabarcoding and DNA sequence‐capture recovered 80%–90% of the control sample species. DNA sequence‐capture was 8x more expensive, nonetheless it identified 1.5x more species for COI and 13x more genera for 18S than metabarcoding. Both approaches offer reliable results, sharing ca. 40% species and 72% families and retrieve more taxa when nuclear and mitochondrial markers are combined. eDNA metabarcoding is quite well established and low‐cost, whereas DNA‐sequence capture for biodiversity assessment is still in its infancy, is more time‐consuming but provides more taxonomic assignments.     

A novel conceptual approach to read-filtering in high-throughput amplicon sequencing studies

Adequate read filtering is critical when processing high-throughput data in marker-gene-based studies. Sequencing errors can cause the mis-clustering of otherwise similar reads, artificially increasing the number of retrieved Operational Taxonomic Units (OTUs) and therefore leading to the overestimation of microbial diversity. Sequencing errors will also result in OTUs that are not accurate reconstructions of the original biological sequences. Herein we present the Poisson binomial filtering algorithm (PBF), which minimizes both problems by calculating the error-probability distribution of a sequence from its quality scores. In order to validate our method, we quality-filtered 37 publicly available datasets obtained by sequencing mock and environmental microbial communities with the Roche 454, Illumina MiSeq and IonTorrent PGM platforms, and compared our results to those obtained with previous approaches such as the ones included in mothur, QIIME and USEARCH. Our algorithm retained substantially more reads than its predecessors, while resulting in fewer and more accurate OTUs. This improved sensitiveness produced more faithful representations, both quantitatively and qualitatively, of the true microbial diversity present in the studied samples. Furthermore, the method introduced in this work is computationally inexpensive and can be readily applied in conjunction with any existent analysis pipeline.     

不同抗、感水稻品种对褐飞虱肠道菌群的影响

本研究旨在探究取食不同抗性水稻品种对褐飞虱肠道菌群多样性及丰度的影响.将生长一致的3龄褐飞虱若虫分别置于高抗水稻品种RHT、高感水稻品种TN1以及中等抗性水稻品种ZH11,取食1d和3d后,分别对褐飞虱肠道进行取样,提取总DNA并通过HiSeq 2500平台对肠道细菌16S rRNA-V4区进行测序.对测序结果进行分析...     

PhylOTU: a high-throughput procedure quantifies microbial community diversity and resolves novel taxa from metagenomic data

Microbial diversity is typically characterized by clustering ribosomal RNA (SSU-rRNA) sequences into operational taxonomic units (OTUs). Targeted sequencing of environmental SSU-rRNA markers via PCR may fail to detect OTUs due to biases in priming and amplification. Analysis of shotgun sequenced environmental DNA, known as metagenomics, avoids amplification bias but generates fragmentary, non-overlapping sequence reads that cannot be clustered by existing OTU-finding methods. To circumvent these limitations, we developed PhylOTU, a computational workflow that identifies OTUs from metagenomic SSU-rRNA sequence data through the use of phylogenetic principles and probabilistic sequence profiles. Using simulated metagenomic data, we quantified the accuracy with which PhylOTU clusters reads into OTUs. Comparisons of PCR and shotgun sequenced SSU-rRNA markers derived from the global open ocean revealed that while PCR libraries identify more OTUs per sequenced residue, metagenomic libraries recover a greater taxonomic diversity of OTUs. In addition, we discover novel species, genera and families in the metagenomic libraries, including OTUs from phyla missed by analysis of PCR sequences. Taken together, these results suggest that PhylOTU enables characterization of part of the biosphere currently hidden from PCR-based surveys of diversity?     

Molecular diversity and distribution of marine fungi across 130 European environmental samples

Environmental DNA and culture-based analyses have suggested that fungi are present in low diversity and in low abundance in many marine environments, especially in the upper water column. Here, we use a dual approach involving high-throughput diversity tag sequencing from both DNA and RNA templates and fluorescent cell counts to evaluate the diversity and relative abundance of fungi across marine samples taken from six European near-shore sites. We removed very rare fungal operational taxonomic units (OTUs) selecting only OTUs recovered from multiple samples for a detailed analysis. This approach identified a set of 71 fungal ‘OTU clusters'' that account for 66% of all the sequences assigned to the Fungi. Phylogenetic analyses demonstrated that this diversity includes a significant number of chytrid-like lineages that had not been previously described, indicating that the marine environment encompasses a number of zoosporic fungi that are new to taxonomic inventories. Using the sequence datasets, we identified cases where fungal OTUs were sampled across multiple geographical sites and between different sampling depths. This was especially clear in one relatively abundant and diverse phylogroup tentatively named Novel Chytrid-Like-Clade 1 (NCLC1). For comparison, a subset of the water column samples was also investigated using fluorescent microscopy to examine the abundance of eukaryotes with chitin cell walls. Comparisons of relative abundance of RNA-derived fungal tag sequences and chitin cell-wall counts demonstrate that fungi constitute a low fraction of the eukaryotic community in these water column samples. Taken together, these results demonstrate the phylogenetic position and environmental distribution of 71 lineages, improving our understanding of the diversity and abundance of fungi in marine environments.     

A Comparison of Methods for Clustering 16S rRNA Sequences into OTUs

Recent studies of 16S rRNA sequences through next-generation sequencing have revolutionized our understanding of the microbial community composition and structure. One common approach in using these data to explore the genetic diversity in a microbial community is to cluster the 16S rRNA sequences into Operational Taxonomic Units (OTUs) based on sequence similarities. The inferred OTUs can then be used to estimate species, diversity, composition, and richness. Although a number of methods have been developed and commonly used to cluster the sequences into OTUs, relatively little guidance is available on their relative performance and the choice of key parameters for each method. In this study, we conducted a comprehensive evaluation of ten existing OTU inference methods. We found that the appropriate dissimilarity value for defining distinct OTUs is not only related with a specific method but also related with the sample complexity. For data sets with low complexity, all the algorithms need a higher dissimilarity threshold to define OTUs. Some methods, such as, CROP and SLP, are more robust to the specific choice of the threshold than other methods, especially for shorter reads. For high-complexity data sets, hierarchical cluster methods need a more strict dissimilarity threshold to define OTUs because the commonly used dissimilarity threshold of 3% often leads to an under-estimation of the number of OTUs. In general, hierarchical clustering methods perform better at lower dissimilarity thresholds. Our results show that sequence abundance plays an important role in OTU inference. We conclude that care is needed to choose both a threshold for dissimilarity and abundance for OTU inference.     

高通量测序分析环保肥料增效剂对马铃薯根际土壤真菌多样性变化影响

【目的】高通量测序技术对研究环境样品中微生物群落组成具有很大的应用价值。土壤微生物群落结构和多样性及其变化在一定程度上反映了土壤的质量。旨在从微生物群落结构的角度阐述环保肥料增效剂对马铃薯根际土壤主要真菌类群结构的影响。【方法】通过高通量测序结果对比分析应用增效剂前后马铃薯根际真菌宏基因组ITS1区,并依据RDP中设置的分类阈值对序列进行物种分类。【结果】测序结果经过质量控制,共获得有效条带437 375条,依据97%的序列相似性做聚类分析,获得全部样品的可分类操作单元(OTUs)共633个。子囊菌的总体数量在所有样品中最多(相对丰度在56.95%-97.23%之间),且处理后呈增加趋势(HY除外),而担子菌门数量在处理后呈下降的趋势。基于真菌ITS1高通量测序结果获得的α指数显示,样品内部处理和对照之间真菌物种多样性有差别。基于真菌ITS1高通量测序获得的β指数显示,处理组与对照组的真菌多样性之间没有差别,这表明真菌多样性之间的差异更多地取决于样品采集地点。【结论】土壤特性是影响真菌种群的重要因素之一,环保肥料增效剂显著改善了土壤真菌的种群结构。     

Genetic barcoding of dark‐spored myxomycetes (Amoebozoa)—Identification,evaluation and application of a sequence similarity threshold for species differentiation in NGS studies

Unicellular, eukaryotic organisms (protists) play a key role in soil food webs as major predators of microorganisms. However, due to the polyphyletic nature of protists, no single universal barcode can be established for this group, and the structure of many protistean communities remains unresolved. Plasmodial slime moulds (Myxogastria or Myxomycetes) stand out among protists by their formation of fruit bodies, which allow for a morphological species concept. By Sanger sequencing of a large collection of morphospecies, this study presents the largest database to date of dark‐spored myxomycetes and evaluate a partial 18S SSU gene marker for species annotation. We identify and discuss the use of an intraspecific sequence similarity threshold of 99.1% for species differentiation (OTU picking) in environmental PCR studies (ePCR) and estimate a hidden diversity of putative species, exceeding those of described morphospecies by 99%. When applying the identified threshold to an ePCR data set (including sequences from both NGS and cloning), we find 64 OTUs of which 21.9% had a direct match (>99.1% similarity) to the database and the remaining had on average 90.2 ± 0.8% similarity to their best match, thus thought to represent undiscovered diversity of dark‐spored myxomycetes.     

Fungal Community Analyses of Endophytic Fungi from Two Oak Species,Quercus mongolica and Quercus serrata,in Korea

Fungal endophytes have been recorded in various plant species with a richness of diversity, and their presence plays an essential role in host plant protection against biotic and abiotic stresses. This study applied the Illumina MiSeq sequencing platform based on the amplification of fungal ribosomal ITS2 region to analyze fungal endophytic communities of two oak species (Quercus mongolica and Q. serrata) with different oak wilt disease susceptibilities in Korea. The results showed a total of 230,768 sequencing reads were obtained and clustered at a 97% similarity threshold into 709 operational taxonomic units (OTUs). The OTUs of Q. serrata were higher than that of Q. mongolica with the number of 617 OTUs and 512 OTUs, respectively. Shannon index also showed that Q. serrata had a significantly higher level of fungal diversity than Q. mongolica. Total of OTUs were assigned into 5 fungal phyla, 17 classes, 60 orders, 133 families, 195 genera, and 280 species. Ascomycota was the dominant phylum with 75.11% relative abundance, followed by Basidiomycota with 5.28%. Leptosillia, Aureobasidium and Acanthostigma were the most abundant genera detected in Q. serrata with the average relative abundance of 2.85, 2.76, and 2.19%, respectively. On the other hand, Peltaster, Cladosporium and Monochaetia were the most common genera detected in Q. mongolica with the average relative abundance of 4.83, 3.03, and 2.87%, respectively. Our results indicated that fungal endophytic communities were significantly different between two oak species and these differences could influence responses of host trees to oak wilt disease caused by Raffaelea quercus-mongolicae.     

Glyphosate has a negligible impact on bacterial diversity and dynamics during composting

The herbicide glyphosate has several potential entry points into composting sites and its impact on composting processes has not yet been evaluated. To assess its impact on bacterial diversity and abundance as well as on community composition and dynamics, we conducted a mesocosm experiment at the Montreal Botanical Garden. Glyphosate had no effect on physicochemical property evolution during composting, while it was completely dissipated by the end of the experiment. Sampling at Days 0, 2, 28 and 112 of the process followed by 16S rRNA amplicon sequencing also found no effect of glyphosate on species richness and community composition. Differential abundance analyses revealed an increase of a few taxa in the presence of glyphosate, namely TRA3-20 (order Polyangiales), Pedosphaeraceae and BIrii41 (order Burkholderiales) after 28 days. In addition, five amplicon sequence variants (ASVs) had lower relative abundance in the glyphosate treatment compared to the control on Day 2, namely Comamonadaceae, Pseudomonas sp., Streptomyces sp., Thermoclostridium sp. and Actinomadura keratinilytica, while two ASVs were less abundant on Day 112, namely Pedomicrobium sp. and Pseudorhodoplanes sp. Most differences in abundance were measured between the different sampling points within each treatment. These results present glyphosate as a poor determinant of species recruitment during composting.     

Reducing the effects of PCR amplification and sequencing artifacts on 16S rRNA-based studies

The advent of next generation sequencing has coincided with a growth in interest in using these approaches to better understand the role of the structure and function of the microbial communities in human, animal, and environmental health. Yet, use of next generation sequencing to perform 16S rRNA gene sequence surveys has resulted in considerable controversy surrounding the effects of sequencing errors on downstream analyses. We analyzed 2.7×10(6) reads distributed among 90 identical mock community samples, which were collections of genomic DNA from 21 different species with known 16S rRNA gene sequences; we observed an average error rate of 0.0060. To improve this error rate, we evaluated numerous methods of identifying bad sequence reads, identifying regions within reads of poor quality, and correcting base calls and were able to reduce the overall error rate to 0.0002. Implementation of the PyroNoise algorithm provided the best combination of error rate, sequence length, and number of sequences. Perhaps more problematic than sequencing errors was the presence of chimeras generated during PCR. Because we knew the true sequences within the mock community and the chimeras they could form, we identified 8% of the raw sequence reads as chimeric. After quality filtering the raw sequences and using the Uchime chimera detection program, the overall chimera rate decreased to 1%. The chimeras that could not be detected were largely responsible for the identification of spurious operational taxonomic units (OTUs) and genus-level phylotypes. The number of spurious OTUs and phylotypes increased with sequencing effort indicating that comparison of communities should be made using an equal number of sequences. Finally, we applied our improved quality-filtering pipeline to several benchmarking studies and observed that even with our stringent data curation pipeline, biases in the data generation pipeline and batch effects were observed that could potentially confound the interpretation of microbial community data.     

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.     

基于高通量测序的褐飞虱肠道微生物多样性分析

【目的】探明褐飞虱Nilaparvata lugens成虫肠道微生物群落结构和多样性。【方法】分离褐飞虱成虫完整肠道并提取总DNA,利用Illumina MiSeq(PE300)技术对其肠道细菌16S rRNA的V3-V4变异区和真菌ITS2序列进行测序,统计肠道微生物的操作分类单元(operational taxonomic unit, OTU)数量,分析其物种组成、丰度及Alpha多样性。并通过qPCR技术验证随机挑选注释到的4种肠道菌的高通量测序数据的有效性。【结果】分别获得褐飞虱成虫肠道细菌16S rRNA和真菌ITS2优质序列32 395和24 986条,根据序列相似性进行聚类分析分别获得235和128个OTUs。其中,细菌共注释到7个门, 15个纲, 26个目, 45个科和73个属;真菌共鉴定到3个门, 9个纲, 12个目, 15个科和18个属。在门分类水平上,细菌以变形菌门(Proteobacteria)、拟杆菌门(Bacteroidetes)和厚壁菌门(Firmicutes)为优势门类;真菌以子囊菌门(Ascomycota)为绝对优势菌门。在属分类水平上,细菌的优势属为不动杆菌属Acinetobacter以及紫单胞菌科(Porphyromonadaceae)未确定属和毛螺菌科(Lachnospiraceae)未确定属,其丰度分别为36.37%, 17.22%和15.01%;真菌的优势属为粪壳菌纲(Sordariomycetes)未确定属,丰度为95.77%。Alpha多样性分析结果显示,褐飞虱肠道细菌(真菌)的观测物种数、Chao1指数、Shannon指数和Simpson 指数分别为235(128), 262.64(165.40), 3.90(0.91)和0.62(0.75)。4种肠道菌的qPCR结果显示高通量测序数据具有较高的有效性。【结论】褐飞虱成虫肠道细菌和真菌群落整体多样性比较丰富。研究结果为从共生微生物角度解析褐飞虱的环境适应性以及开发基于微生物防治的新技术等方面提供了依据。     

Intracellular Diversity of the V4 and V9 Regions of the 18S rRNA in Marine Protists (Radiolarians) Assessed by High-Throughput Sequencing

Metabarcoding is a powerful tool for exploring microbial diversity in the environment, but its accurate interpretation is impeded by diverse technical (e.g. PCR and sequencing errors) and biological biases (e.g. intra-individual polymorphism) that remain poorly understood. To help interpret environmental metabarcoding datasets, we investigated the intracellular diversity of the V4 and V9 regions of the 18S rRNA gene from Acantharia and Nassellaria (radiolarians) using 454 pyrosequencing. Individual cells of radiolarians were isolated, and PCRs were performed with generalist primers to amplify the V4 and V9 regions. Different denoising procedures were employed to filter the pyrosequenced raw amplicons (Acacia, AmpliconNoise, Linkage method). For each of the six isolated cells, an average of 541 V4 and 562 V9 amplicons assigned to radiolarians were obtained, from which one numerically dominant sequence and several minor variants were found. At the 97% identity, a diversity metrics commonly used in environmental surveys, up to 5 distinct OTUs were detected in a single cell. However, most amplicons grouped within a single OTU whereas other OTUs contained very few amplicons. Different analytical methods provided evidence that most minor variants forming different OTUs correspond to PCR and sequencing artifacts. Duplicate PCR and sequencing from the same DNA extract of a single cell had only 9 to 16% of unique amplicons in common, and alignment visualization of V4 and V9 amplicons showed that most minor variants contained substitutions in highly-conserved regions. We conclude that intracellular variability of the 18S rRNA in radiolarians is very limited despite its multi-copy nature and the existence of multiple nuclei in these protists. Our study recommends some technical guidelines to conservatively discard artificial amplicons from metabarcoding datasets, and thus properly assess the diversity and richness of protists in the environment.