ITS all right mama: investigating the formation of chimeric sequences in the ITS2 region by DNA metabarcoding analyses of fungal mock communities of different complexities

The formation of chimeric sequences can create significant methodological bias in PCR‐based DNA metabarcoding analyses. During mixed‐template amplification of barcoding regions, chimera formation is frequent and well documented. However, profiling of fungal communities typically uses the more variable rDNA region ITS. Due to a larger research community, tools for chimera detection have been developed mainly for the 16S/18S markers. However, these tools are widely applied to the ITS region without verification of their performance. We examined the rate of chimera formation during amplification and 454 sequencing of the ITS2 region from fungal mock communities of different complexities. We evaluated the chimera detecting ability of two common chimera‐checking algorithms: perseus and uchime . Large proportions of the chimeras reported were false positives. No false negatives were found in the data set. Verified chimeras accounted for only 0.2% of the total ITS2 reads, which is considerably less than what is typically reported in 16S and 18S metabarcoding analyses. Verified chimeric ‘parent sequences’ had significantly higher per cent identity to one another than to random members of the mock communities. Community complexity increased the rate of chimera formation. GC content was higher around the verified chimeric break points, potentially facilitating chimera formation through base pair mismatching in the neighbouring regions of high similarity in the chimeric region. We conclude that the hypervariable nature of the ITS region seems to buffer the rate of chimera formation in comparison with other, less variable barcoding regions, due to shorter regions of high sequence similarity.     

Does peptide-nucleic acid (PNA) clamping of host plant DNA benefit ITS1 amplicon-based characterization of the fungal endophyte community?

Fungal endophyte community amplicon sequencing can lose a significant number of informative reads due to host-plant co-amplification. Blocking of plant-specific sequences with peptide nucleic acid (PNA) clamps has been shown to improve metrics of detected microbial diversity in studies targeting 16S and 18S regions of rRNA genes. However, PNA clamping has not been applied to the plant ITS region of rRNA gene – a widely accepted fungal marker. By applying PNA clamping technique to ITS amplicon sequencing of the endophytic fungal community of elderberry this study shows that PNA clamping significantly reduces host-plant co-amplification with the universal ITS1/ITS4 primer set. However, PNA clamping in combination with the discriminatory ITS1F/ITS2 primer set did not improve the metrics of fungal endophyte community ITS amplicon Illumina sequencing. This study shows that PNA clamping does not add practical benefit to taxonomic profiling of plant-associated fungal communities if the primers are already specific enough to exclude amplification of host DNA.     

两种混合样品策略对揭示杜鹃花根部真菌多样性的影响

由于土壤微生物群落物种组成的高度空间异质性,混合样品(sample pooling)被广泛应用于微生物多样性与群落结构研究。在根部真菌的分子检测中,样品混合策略以及测序的克隆数或序列数均对揭示真菌群落结构的准确性有影响。【目的】为建立一套能快速准确地反映杜鹃花属植物根部真菌的物种组成与群落结构的分子检测技术平台,【方法】本研究采集锈红杜鹃和亮鳞杜鹃多份根系样品分别提取DNA,比较PCR扩增前和扩增后混合策略构建的克隆文库中真菌物种组成的差异。【结果】在2种宿主植物根系中,多份样品在PCR扩增后混合构建的克隆文库检测到的根部真菌物种丰富度、真菌群落的Shannon-Wiener多样性指数均高于扩增前混合的克隆文库。高频度的根部真菌在2种克隆文库中均检测到,但低频度的真菌物种组成在2种克隆文库中完全不同。更重要的是,当采用广泛应用的真菌通用引物ITS1f和ITS4扩增根部真菌ITS序列时,PCR扩增后混合的方法能有效地减轻杜鹃花属植物ITS序列被优先扩增的现象。真菌物种累积曲线显示,当测序的真菌ITS片段克隆数达到50个左右,即能较全面地反映2种杜鹃花根部真菌物种组成。【结论】独立扩增多份根系样品DNA,再将PCR产物混合构建克隆文库的方法能更全面地揭示杜鹃花属植物根部真菌物种丰富度与物种组成。     

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.     

Groundtruthing next-gen sequencing for microbial ecology-biases and errors in community structure estimates from PCR amplicon pyrosequencing

Analysis of microbial communities by high-throughput pyrosequencing of SSU rRNA gene PCR amplicons has transformed microbial ecology research and led to the observation that many communities contain a diverse assortment of rare taxa-a phenomenon termed the Rare Biosphere. Multiple studies have investigated the effect of pyrosequencing read quality on operational taxonomic unit (OTU) richness for contrived communities, yet there is limited information on the fidelity of community structure estimates obtained through this approach. Given that PCR biases are widely recognized, and further unknown biases may arise from the sequencing process itself, a priori assumptions about the neutrality of the data generation process are at best unvalidated. Furthermore, post-sequencing quality control algorithms have not been explicitly evaluated for the accuracy of recovered representative sequences and its impact on downstream analyses, reducing useful discussion on pyrosequencing reads to their diversity and abundances. Here we report on community structures and sequences recovered for in vitro-simulated communities consisting of twenty 16S rRNA gene clones tiered at known proportions. PCR amplicon libraries of the V3-V4 and V6 hypervariable regions from the in vitro-simulated communities were sequenced using the Roche 454 GS FLX Titanium platform. Commonly used quality control protocols resulted in the formation of OTUs with >1% abundance composed entirely of erroneous sequences, while over-aggressive clustering approaches obfuscated real, expected OTUs. The pyrosequencing process itself did not appear to impose significant biases on overall community structure estimates, although the detection limit for rare taxa may be affected by PCR amplicon size and quality control approach employed. Meanwhile, PCR biases associated with the initial amplicon generation may impose greater distortions in the observed community structure.     

High-coverage ITS primers for the DNA-based identification of ascomycetes and basidiomycetes in environmental samples

The kingdom Fungi is estimated to include 1.5 million or more species, playing key roles as decomposers, mutualists, and parasites in every biome on the earth. To comprehensively understand the diversity and ecology of this huge kingdom, DNA barcoding targeting the internal transcribed spacer (ITS) region of the nuclear ribosomal repeat has been regarded as a prerequisite procedure. By extensively surveying ITS sequences in public databases, we designed new ITS primers with improved coverage across diverse taxonomic groups of fungi compared to existing primers. An in silico analysis based on public sequence databases indicated that the newly designed primers matched 99% of ascomycete and basidiomycete ITS taxa (species, subspecies or varieties), causing little taxonomic bias toward either fungal group. Two of the newly designed primers could inhibit the amplification of plant sequences and would enable the selective investigation of fungal communities in mycorrhizal associations, soil, and other types of environmental samples. Optimal PCR conditions for the primers were explored in an in vitro investigation. The new primers developed in this study will provide a basis for ecological studies on the diversity and community structures of fungi in the era of massive DNA sequencing.     

What Goes in Must Come out: Testing for Biases in Molecular Analysis of Arbuscular Mycorrhizal Fungal Communities

Arbuscular mycorrhizal (AM) fungi are widely distributed microbes that form obligate symbioses with the majority of terrestrial plants, altering nutrient transfers between soils and plants, thereby profoundly affecting plant growth and ecosystem properties. Molecular methods are commonly used in the study of AM fungal communities. However, the biases associated with PCR amplification of these organisms and their ability to be utilized quantitatively has never been fully tested. We used Terminal Restriction Fragment Length Polymorphism (TRFLP) analysis to characterise artificial community templates containing known quantities of defined AM fungal genotypes. This was compared to a parallel in silico analysis that predicted the results of this experiment in the absence of bias. The data suggest that when used quantitatively the TRFLP protocol tested is a powerful, repeatable method for AM fungal community analysis. However, we suggest some limitations to its use for population-level analyses. We found no evidence of PCR bias, supporting the quantitative use of other PCR-based methods for the study of AM fungi such as next generation amplicon sequencing. This finding greatly improves our confidence in methods that quantitatively examine AM fungal communities, providing a greater understanding of the ecology of these important fungi.     

Performance Comparison of Illumina and Ion Torrent Next-Generation Sequencing Platforms for 16S rRNA-Based Bacterial Community Profiling

High-throughput sequencing of the taxonomically informative 16S rRNA gene provides a powerful approach for exploring microbial diversity. Here we compare the performances of two common “benchtop” sequencing platforms, Illumina MiSeq and Ion Torrent Personal Genome Machine (PGM), for bacterial community profiling by 16S rRNA (V1-V2) amplicon sequencing. We benchmarked performance by using a 20-organism mock bacterial community and a collection of primary human specimens. We observed comparatively higher error rates with the Ion Torrent platform and report a pattern of premature sequence truncation specific to semiconductor sequencing. Read truncation was dependent on both the directionality of sequencing and the target species, resulting in organism-specific biases in community profiles. We found that these sequencing artifacts could be minimized by using bidirectional amplicon sequencing and an optimized flow order on the Ion Torrent platform. Results of bacterial community profiling performed on the mock community and a collection of 18 human-derived microbiological specimens were generally in good agreement for both platforms; however, in some cases, results differed significantly. Disparities could be attributed to the failure to generate full-length reads for particular organisms on the Ion Torrent platform, organism-dependent differences in sequence error rates affecting classification of certain species, or some combination of these factors. This study demonstrates the potential for differential bias in bacterial community profiles resulting from the choice of sequencing platform alone.     

Insight into biases and sequencing errors for amplicon sequencing with the Illumina MiSeq platform

With read lengths of currently up to 2 × 300 bp, high throughput and low sequencing costs Illumina''s MiSeq is becoming one of the most utilized sequencing platforms worldwide. The platform is manageable and affordable even for smaller labs. This enables quick turnaround on a broad range of applications such as targeted gene sequencing, metagenomics, small genome sequencing and clinical molecular diagnostics. However, Illumina error profiles are still poorly understood and programs are therefore not designed for the idiosyncrasies of Illumina data. A better knowledge of the error patterns is essential for sequence analysis and vital if we are to draw valid conclusions. Studying true genetic variation in a population sample is fundamental for understanding diseases, evolution and origin. We conducted a large study on the error patterns for the MiSeq based on 16S rRNA amplicon sequencing data. We tested state-of-the-art library preparation methods for amplicon sequencing and showed that the library preparation method and the choice of primers are the most significant sources of bias and cause distinct error patterns. Furthermore we tested the efficiency of various error correction strategies and identified quality trimming (Sickle) combined with error correction (BayesHammer) followed by read overlapping (PANDAseq) as the most successful approach, reducing substitution error rates on average by 93%.     

Relationships among wood‐boring beetles,fungi, and the decomposition of forest biomass

A prevailing paradigm in forest ecology is that wood‐boring beetles facilitate wood decay and carbon cycling, but empirical tests have yielded mixed results. We experimentally determined the effects of wood borers on fungal community assembly and wood decay within pine trunks in the southeastern United States. Pine trunks were made either beetle‐accessible or inaccessible. Fungal communities were compared using culturing and high‐throughput amplicon sequencing (HTAS) of DNA and RNA. Prior to beetle infestation, living pines had diverse fungal endophyte communities. Endophytes were displaced by beetle‐associated fungi in beetle‐accessible trees, whereas some endophytes persisted as saprotrophs in beetle‐excluded trees. Beetles increased fungal diversity several fold. Over forty taxa of Ascomycota were significantly associated with beetles, but beetles were not consistently associated with any known wood‐decaying fungi. Instead, increasing ambrosia beetle infestations caused reduced decay, consistent with previous in vitro experiments that showed beetle‐associated fungi reduce decay rates by competing with decay fungi. No effect of bark‐inhabiting beetles on decay was detected. Platypodines carried significantly more fungal taxa than scolytines. Molecular results were validated by synthetic and biological mock communities and were consistent across methodologies. RNA sequencing confirmed that beetle‐associated fungi were biologically active in the wood. Metabarcode sequencing of the LSU/28S marker recovered important fungal symbionts that were missed by ITS2, though community‐level effects were similar between markers. In contrast to the current paradigm, our results indicate ambrosia beetles introduce diverse fungal communities that do not extensively decay wood, but instead reduce decay rates by competing with wood decay fungi.     

Fungal diversity in sheep (Ovis aries) and cattle (Bos taurus) feces assessed by comparison of 18S, 28S and ITS ribosomal regions

To explore the fungal diversity in ruminant feces for bioenergy, libraries based on internal transcribed spacer (ITS), 18S rRNA, and 28S rRNA regions were constructed, respectively. Although the libraries were constructed from the same DNA extracts, the fungal taxa analyses based on these libraries are different. The ITS and 28S libraries comprised higher proportions of fungal clones than 18S libraries, and the ITS libraries converged into the lower diversities. The ITS libraries could be used to analyze the fungal community. The 18S libraries were suitable for the fungi and protozoa community. However, the 28S are suitable for analysis of Ascomycota fungi. The major fungal taxa in cattle feces analyzed by ITS, 18S, and 28S libraries are similar to those of sheep feces, respectively. The fungal taxa detected by the ITS library comprised only 20 % fungal taxa detected by the three libraries. The 18S library comprised 30 % fungal taxa; the 28S library comprised about 50 % fungal taxa. The results indicated that primer sets toward different DNA regions lead to the difference in structures of fungal community. So the selection of primer sets may influence the fungal communities, and libraries based on single primer sets may underestimate the fungal diversity. The comparison of ITS, 18S, and 28S libraries could fid more diverse fungi than that based on only one library.     

Comparison of ITS1 and ITS2 rDNA in 454 sequencing of hyperdiverse fungal communities

Next-generation amplicon sequencing is a powerful tool in ecological studies of fungi. Technological development suggests that short fragment high-throughput techniques, e.g. Illumina, will gain importance in fungal community analyses. Thus there is a need for short (250 bp) and informative molecular identifiers. Here we compared ITS1 vs. ITS2 rDNA using empirical data from a study of hyperdiverse leaf-associated fungal communities. Our results suggest that ITS2 may be more variable and recovers more of the molecular diversity. We confirm an earlier in silico study showing that ITS1 and ITS2 yielded somewhat different taxonomic community compositions when blasted against public databases. However, we demonstrate that both ITS1 and ITS2 reveal similar patterns in community structure when analyzed in a community ecology context.     

Amphibian skin fungal communities vary across host species and do not correlate with infection by a pathogenic fungus

Amphibian population declines caused by the fungus Batrachochytrium dendrobatidis (Bd) have prompted studies on the bacterial community that resides on amphibian skin. However, studies addressing the fungal portion of these symbiont communities have lagged behind. Using ITS1 amplicon sequencing, we examined the fungal portion of the skin microbiome of temperate and tropical amphibian species currently coexisting with Bd in nature. We assessed cooccurrence patterns between bacterial and fungal OTUs using a subset of samples for which bacterial 16S rRNA gene amplicon data were also available. We determined that fungal communities were dominated by members of the phyla Ascomycota and Basidiomycota, and also by Chytridiomycota in the most aquatic amphibian species. Alpha diversity of the fungal communities differed across host species, and fungal community structure differed across species and regions. However, we did not find a correlation between fungal diversity/community structure and Bd infection, though we did identify significant correlations between Bd and specific OTUs. Moreover, positive bacterial–fungal cooccurrences suggest that positive interactions between these organisms occur in the skin microbiome. Understanding the ecology of amphibian skin fungi, and their interactions with bacteria will complement our knowledge of the factors influencing community assembly and the overall function of these symbiont communities.     

Exploring the accuracy of amplicon‐based internal transcribed spacer markers for a fungal community

With the continual improvement in high‐throughput sequencing technology and constant updates to fungal reference databases, the use of amplicon‐based DNA markers as a tool to reveal fungal diversity and composition in various ecosystems has become feasible. However, both primer selection and the experimental procedure require meticulous verification. Here, we computationally and experimentally evaluated the accuracy and specificity of three widely used or newly designed internal transcribed spacer (ITS) primer sets (ITS1F/ITS2, gITS7/ITS4 and 5.8S‐Fun/ITS4‐Fun). In silico evaluation revealed that primer coverage varied at different taxonomic levels due to differences in degeneracy and the location of primer sets. Using even and staggered mock community standards, we identified different proportions of chimeric and mismatch reads generated by different primer sets, as well as great variation in species abundances, suggesting that primer selection would affect the results of amplicon‐based metabarcoding studies. Choosing proofreading and high‐fidelity polymerase (KAPA HiFi) could significantly reduce the percentage of chimeric and mismatch sequences, further reducing inflation of operational taxonomic units. Moreover, for two types of environmental fungal communities, plant endophytic and soil fungi, it was demonstrated that the three primer sets could not reach a consensus on fungal community composition or diversity, and that primer selection, not experimental treatment, determines observed soil fungal community diversity and composition. Future DNA marker surveys should pay greater attention to potential primer effects and improve the experimental scheme to increase credibility and accuracy.     

Reliability for detecting composition and changes of microbial communities by T-RFLP genetic profiling

Terminal restriction fragment length polymorphism (T-RFLP) analysis is commonly used for profiling microbial communities in various environments. However, it may suffer from biases during the analytic process. This study addressed the potential of T-RFLP profiles (1) to reflect real community structures and diversities, as well as (2) to reliably detect changing components of microbial community structures. For this purpose, defined artificial communities of 30 SSU rRNA gene clones, derived from nine bacterial phyla, were used. PCR amplification efficiency was one primary bias with a maximum variability factor of 3.5 among clones. PCR downstream analyses such as enzymatic restriction and capillary electrophoresis introduced a maximum bias factor of 4 to terminal restriction fragment (T-RF) signal intensities, resulting in a total maximum bias factor of 14 in the final T-RFLP profiles. In addition, the quotient between amplification efficiency and T-RF size allowed predicting T-RF abundances in the profiles with high accuracy. Although these biases impaired detection of real community structures, the relative changes in structures and diversities were reliably reflected in the T-RFLP profiles. These data support the suitability of T-RFLP profiling for monitoring effects on microbial communities.     

ITS-1 versus ITS-2 pyrosequencing: a comparison of fungal populations in truffle grounds

In a recent study pyrosequencing of the ribosomal internal transcribed spacer-1 (ITS-1) has validated the effectiveness of such technology in the survey of soil fungal diversity. Here we compare the two ITS regions, ITS-1 and ITS-2, of the fungal populations occurring in Tuber melanosporum/Quercus pubescens truffle grounds and sampled in two areas, one devoid of vegetation ("burned", brulé in French) where T. melanosporum fruiting bodies are usually collected, and outside the brulé. TS1F/ITS2 and ITS3/ITS4 were used respectively for the amplification of the ITS-1 and ITS-2 regions. Two amplicon libraries were built, one for inside and the other for outside. A set of 15.788 reads was obtained. After the removal of low quality sequences, 3568 and 3156 sequences were obtained from inside the brulé with the ITS-1 and ITS-2 primers respectively. The sequences obtained from outside the brulé were 4490 with the ITS-1 primers and 2432 with the ITS-2 primers. Most of the sequences obtained for both ITS fragments could be attributed to fungal organisms. The pair of primers, ITS1-F/ITS2, was more selective, producing fewer non-fungal sequences (1% inside, 3% outside), in addition to a higher number of sequences, than the pair ITS3/ITS4 (6% inside, 11% outside). Although differences are present in the taxa percentages between ITS-1 and ITS-2, both reveal that Ascomycota were the dominant fungal phylum and that their number decreased moving from inside the brulé to outside, while the number of Basidiomycota increased. Taken together, both the short ITS-1 and ITS-2 reads obtained by the high throughput 454 sequencing provide adequate information for taxon assignment and are suitable to correlate the dynamics of the fungal populations to specific environments.     

Sample richness and genetic diversity as drivers of chimera formation in nSSU metagenetic analyses

Eukaryotic diversity in environmental samples is often assessed via PCR-based amplification of nSSU genes. However, estimates of diversity derived from pyrosequencing environmental data sets are often inflated, mainly because of the formation of chimeric sequences during PCR amplification. Chimeras are hybrid products composed of distinct parental sequences that can lead to the misinterpretation of diversity estimates. We have analyzed the effect of sample richness, evenness and phylogenetic diversity on the formation of chimeras using a nSSU data set derived from 454 Roche pyrosequencing of replicated, large control pools of closely and distantly related nematode mock communities, of known intragenomic identity and richness. To further investigate how chimeric molecules are formed, the nSSU gene secondary structure was analyzed in several individuals. For the first time in eukaryotes, chimera formation proved to be higher in both richer and more genetically diverse samples, thus providing a novel perspective of chimera formation in pyrosequenced environmental data sets. Findings contribute to a better understanding of the nature and mechanisms involved in chimera formation during PCR amplification of environmentally derived DNA. Moreover, given the similarities between biodiversity analyses using amplicon sequencing and those used to assess genomic variation, our findings have potential broad application for identifying genetic variation in homologous loci or multigene families in general.     

The Quantification of Representative Sequences pipeline for amplicon sequencing: case study on within‐population ITS1 sequence variation in a microparasite infecting Daphnia

Next generation sequencing (NGS) platforms are replacing traditional molecular biology protocols like cloning and Sanger sequencing. However, accuracy of NGS platforms has rarely been measured when quantifying relative frequencies of genotypes or taxa within populations. Here we developed a new bioinformatic pipeline (QRS) that pools similar sequence variants and estimates their frequencies in NGS data sets from populations or communities. We tested whether the estimated frequency of representative sequences, generated by 454 amplicon sequencing, differs significantly from that obtained by Sanger sequencing of cloned PCR products. This was performed by analysing sequence variation of the highly variable first internal transcribed spacer (ITS1) of the ichthyosporean Caullerya mesnili, a microparasite of cladocerans of the genus Daphnia. This analysis also serves as a case example of the usage of this pipeline to study within‐population variation. Additionally, a public Illumina data set was used to validate the pipeline on community‐level data. Overall, there was a good correspondence in absolute frequencies of C. mesnili ITS1 sequences obtained from Sanger and 454 platforms. Furthermore, analyses of molecular variance (amova ) revealed that population structure of C. mesnili differs across lakes and years independently of the sequencing platform. Our results support not only the usefulness of amplicon sequencing data for studies of within‐population structure but also the successful application of the QRS pipeline on Illumina‐generated data. The QRS pipeline is freely available together with its documentation under GNU Public Licence version 3 at http://code.google.com/p/quantification-representative-sequences .