Factors that affect large subunit ribosomal DNA amplicon sequencing studies of fungal communities: classification method, primer choice, and error

Niche-dependent sponge hologenome expression profiles and the host-microbes interplay: a case of the hawaiian demosponge Mycale Grandis

BACKGROUND

Most researches on sponge holobionts focus primarily on symbiotic microbes, yet data at the level of the sponge hologenome are still relatively scarce. Understanding of the sponge host and its microbial gene expression profiles and the host-microbes interplay in different niches represents a key aspect of sponge hologenome. Using the Hawaiian demosponge Mycale grandis in different niches as a model, i.e. on rocks, on the surface of coral Porites compressa, under alga Gracilaria salicornia, we compared the bacterial and fungal community structure, functional gene diversity, expression pattern and the host transcriptome by integrating open-format (deep sequencing) and closed-format (GeoChip microarray) high-throughput techniques.

RESULTS

Little inter-niche variation in bacterial and fungal phylogenetic diversity was detected for M. grandis in different niches, but a clear niche-dependent variability in the functional gene diversity and expression pattern of M. grandis host and its symbiotic microbiota was uncovered by GeoChip microarray and transcriptome analyses. Particularly, sponge host genes related to innate immunity and microbial recognition showed a strong correlation with the microbial symbionts' functional gene diversity and transcriptional richness in different niches. The cross-niche variability with respect to the symbiont functional gene diversity and the transcriptional richness of M. grandis holobiont putatively reflects the interplay of niche-specific selective pressure and the symbiont functional diversity.

CONCLUSIONS

Niche-dependent gene expression profiles of M. grandis hologenome and the host-microbes interplay were suggested though little inter-niche variation in bacterial and fungal diversity was detected, particularly the sponge innate immunity was found to be closely related to the symbiotic microbes. Altogether, these findings provide novel insights into the black box of one sponge holobiont in different niches at the hologenome level.

Understudied, underrepresented, and unknown: Methodological biases that limit detection of early diverging fungi from environmental samples

Metabarcoding is an important tool for understanding fungal communities. The internal transcribed spacer (ITS) rDNA is the accepted fungal barcode but has known problems. The large subunit (LSU) rDNA has also been used to investigate fungal communities but available LSU metabarcoding primers were mostly designed to target Dikarya (Ascomycota + Basidiomycota) with little attention to early diverging fungi (EDF). However, evidence from multiple studies suggests that EDF comprise a large portion of unknown diversity in community sampling. Here, we investigate how DNA marker choice and methodological biases impact recovery of EDF from environmental samples. We focused on one EDF lineage, Zoopagomycota, as an example. We evaluated three primer sets (ITS1F/ITS2, LROR/LR3, and LR3 paired with new primer LR22F) to amplify and sequence a Zoopagomycota mock community and a set of 146 environmental samples with Illumina MiSeq. We compared two taxonomy assignment methods and created an LSU reference database compatible with AMPtk software. The two taxonomy assignment methods recovered strikingly different communities of fungi and EDF. Target fragment length variation exacerbated PCR amplification biases and influenced downstream taxonomic assignments, but this effect was greater for EDF than Dikarya. To improve identification of LSU amplicons we performed phylogenetic reconstruction and illustrate the advantages of this critical tool for investigating identified and unidentified sequences. Our results suggest much of the EDF community may be missed or misidentified with "standard" metabarcoding approaches and modified techniques are needed to understand the role of these taxa in a broader ecological context.

Mushroom DNA barcoding project: Sequencing a segment of the 28S rRNA gene

DNA barcoding is an important molecular methodology for species identification that was developed over the last two decades and it should be covered in the biology bachelor curriculum. Here, we present an example of DNA barcoding by sequencing a segment of the 28S nuclear ribosomal large subunit rRNA gene of wild mushrooms and framing the education in a project form for undergraduate students in biology. Students perform this project in 6-8 weeks, which also includes preparing a poster, writing a report and presenting a paper related to the work in a journal club format. First, fieldwork in the Netherlands was carried out, during which students collected mushrooms under supervision of a professional mycologist with the goal to (a) verify morphologically based identifications with a molecular method and (b) assess phylogenetic relationships of the different species collected. Next, DNA extractions and quantitation were performed, PCR amplification was done, and samples were sent out for Sanger sequencing. Students aligned and analyzed the sequences using BLAST and Geneious and subsequently created a phylogenetic tree. In case of collecting DNA barcodes of an earlier sequenced species, students could upload the data to a repository established for facilitation of future research projects. The method described is very robust, reagents and equipment are readily available, and costs are relatively low. In addition, the results can be compared to published fungal phylogenetic trees.

Mollisiaceae: An overlooked lineage of diverse endophytes

Mollisia is a taxonomically neglected discomycete genus (Helotiales, Leotiomycetes) of commonly encountered saprotrophs on decaying plant tissues throughout temperate regions. The combination of indistinct morphological characters, more than 700 names in the literature, and lack of reference DNA sequences presents a major challenge when working with Mollisia. Unidentified endophytes, including strains that produced antifungal or antiinsectan secondary metabolites, were isolated from conifer needles in New Brunswick and placed with uncertainty in Phialocephala and Mollisia, necessitating a more comprehensive treatment of these genera. In this study, morphology and multigene phylogenetic analyses were used to explore the taxonomy of Mollisiaceae, including Mollisia, Phialocephala, and related genera, using new field collections, herbarium specimens, and accessioned cultures and sequences. The phylogeny of Mollisiaceae was reconstructed and compared using the nuc internal transcribed spacer rDNA (ITS) barcode and partial sequences of the 28S nuc rDNA (LSU) gene, largest subunit of RNA polymerase II (RPB1), DNA topoisomerase I (TOP1), and the hypothetical protein Lipin/Ned1/Smp2 (LNS2). The results show that endophytism is common throughout the Mollisiaceae lineage in a diverse range of hosts but is infrequently attributed to Mollisia because of a paucity of reference sequences. Generic boundaries within Mollisiaceae are poorly resolved and based on phylogenetic evidence the family included species placed in Acephala, Acidomelania, Barrenia, Bispora, Cheirospora, Cystodendron, Fuscosclera, Hysteronaevia, Loramyces, Mollisia, Neopyrenopeziza, Obtectodiscus, Ombrophila, Patellariopsis, Phialocephala, Pulvinata, Tapesia (=Mollisia), and Trimmatostroma. Taxonomic novelties included the description of five novel Mollisia species and five novel Phialocephala species and the synonymy of Fuscosclera with Phialocephala, Acidomelania with Mollisia, and Loramycetaceae with Mollisiaceae.

Anthropogenic N deposition alters soil organic matter biochemistry and microbial communities on decaying fine roots

Fine root litter is a primary source of soil organic matter (SOM), which is a globally important pool of C that is responsive to climate change. We previously established that ~20 years of experimental nitrogen (N) deposition has slowed fine root decay and increased the storage of soil carbon (C; +18%) across a widespread northern hardwood forest ecosystem. However, the microbial mechanisms that have directly slowed fine root decay are unknown. Here, we show that experimental N deposition has decreased the relative abundance of Agaricales fungi (-31%) and increased that of partially ligninolytic Actinobacteria (+24%) on decaying fine roots. Moreover, experimental N deposition has increased the relative abundance of lignin-derived compounds residing in SOM (+53%), and this biochemical response is significantly related to shifts in both fungal and bacterial community composition. Specifically, the accumulation of lignin-derived compounds in SOM is negatively related to the relative abundance of ligninolytic Mycena and Kuehneromyces fungi, and positively related to Microbacteriaceae. Our findings suggest that by altering the composition of microbial communities on decaying fine roots such that their capacity for lignin degradation is reduced, experimental N deposition has slowed fine root litter decay, and increased the contribution of lignin-derived compounds from fine roots to SOM. The microbial responses we observed may explain widespread findings that anthropogenic N deposition increases soil C storage in terrestrial ecosystems. More broadly, our findings directly link composition to function in soil microbial communities, and implicate compositional shifts in mediating biogeochemical processes of global significance.

Different response of bacteria, archaea and fungi to process parameters in nine full-scale anaerobic digesters

Biogas production is a biotechnological process realized by complex bacterial, archaeal and likely fungal communities. Their composition was assessed in nine full-scale biogas plants with distinctly differing feedstock input and process parameters. This study investigated the actually active microbial community members by using a comprehensive sequencing approach based on ribosomal 16S and 28S rRNA fragments. The prevailing taxonomical units of each respective community were subsequently linked to process parameters. Ribosomal rRNA of bacteria, archaea and fungi, respectively, showed different compositions with respect to process parameters and supplied feedstocks: (i) bacterial communities were affected by the key factors temperature and ammonium concentration; (ii) composition of archaea was mainly related to process temperature; and (iii) relative abundance of fungi was linked to feedstocks supplied to the digesters. Anaerobic digesters with a high methane yield showed remarkably similar bacterial communities regarding identified taxonomic families. Although archaeal communities differed strongly on genus level from each other, the respective digesters still showed high methane yields. Functional redundancy of the archaeal communities may explain this effect. 28S rRNA sequences of fungi in all nine full-scale anaerobic digesters were primarily classified as facultative anaerobic Ascomycota and Basidiomycota. Since the presence of ribosomal 28S rRNA indicates that fungi may be active in the biogas digesters, further research should be carried out to examine to which extent they are important players in anaerobic digestion processes.

Effects of agricultural management on phyllosphere fungal diversity in vineyards and the association with adjacent native forests

Agriculture is one of the main drivers of land conversion, and agriculture practices can impact on microbial diversity. Here we characterized the phyllosphere fungal diversity associated with Carménère grapevines under conventional and organic agricultural management. We also explored the fungal diversity present in the adjacent sclerophyllous forests to explore the potential role of native forest on vineyard phyllosphere. After conducting D2 and ITS2 amplicon sequencing, we found that fungal diversity indices did not change between conventional and organic vineyards, but community structure was sensitive to the agricultural management. On the other hand, we found a high proportion of shared fungal OTUs between vineyards and native forests. In addition, both habitats had similar levels of fungal diversity despite forest samples were derived from multiple plant species. In contrast, the community structure was different in both habitats. Interestingly, the native forest had more unidentified species and unique OTUs than vineyards. Forest dominant species were Aureobasidium pullulans and Endoconidioma populi, whereas Davidiella tassiana, Didymella sp., and Alternaria eichhorniae were more abundant in vineyards. Overall, this study argues that a better understanding of the relationship native forests and agroecosystems is needed for maintaining and enhancing ecosystem services provided by natural ecosystems. Finally, knowledge of microbial communities living in the Chilean Mediterranean biome is needed for appropriate conservation management of these biomes and their classification as biodiversity hotspots.

A reference cytochrome c oxidase subunit I database curated for hierarchical classification of arthropod metabarcoding data

Metabarcoding is a popular application which warrants continued methods optimization. To maximize barcoding inferences, hierarchy-based sequence classification methods are increasingly common. We present methods for the construction and curation of a database designed for hierarchical classification of a 157 bp barcoding region of the arthropod cytochrome c oxidase subunit I (COI) locus. We produced a comprehensive arthropod COI amplicon dataset including annotated arthropod COI sequences and COI sequences extracted from arthropod whole mitochondrion genomes, the latter of which provided the only source of representation for Zoraptera, Callipodida and Holothyrida. The database contains extracted sequences of the target amplicon from all major arthropod clades, including all insect orders, all arthropod classes and Onychophora, Tardigrada and Mollusca outgroups. During curation, we extracted the COI region of interest from approximately 81 percent of the input sequences, corresponding to 73 percent of the genus-level diversity found in the input data. Further, our analysis revealed a high degree of sequence redundancy within the NCBI nucleotide database, with a mean of approximately 11 sequence entries per species in the input data. The curated, low-redundancy database is included in the Metaxa2 sequence classification software (http://microbiology.se/software/metaxa2/). Using this database with the Metaxa2 classifier, we performed a cross-validation analysis to characterize the relationship between the Metaxa2 reliability score, an estimate of classification confidence, and classification error probability. We used this analysis to select a reliability score threshold which minimized error. We then estimated classification sensitivity, false discovery rate and overclassification, the propensity to classify sequences from taxa not represented in the reference database. Our work will help researchers design and evaluate classification databases and conduct metabarcoding on arthropods and alternate taxa.

Scaling up: A guide to high-throughput genomic approaches for biodiversity analysis

The purpose of this review is to present the most common and emerging DNA-based methods used to generate data for biodiversity and biomonitoring studies. As environmental assessment and monitoring programmes may require biodiversity information at multiple levels, we pay particular attention to the DNA metabarcoding method and discuss a number of bioinformatic tools and considerations for producing DNA-based indicators using operational taxonomic units (OTUs), taxa at a variety of ranks and community composition. By developing the capacity to harness the advantages provided by the newest technologies, investigators can "scale up" by increasing the number of samples and replicates processed, the frequency of sampling over time and space, and even the depth of sampling such as by sequencing more reads per sample or more markers per sample. The ability to scale up is made possible by the reduced hands-on time and cost per sample provided by the newest kits, platforms and software tools. Results gleaned from broad-scale monitoring will provide opportunities to address key scientific questions linked to biodiversity and its dynamics across time and space as well as being more relevant for policymakers, enabling science-based decision-making, and provide a greater socio-economic impact. As genomic approaches are continually evolving, we provide this guide to methods used in biodiversity genomics.

Effect of Simulated Climate Warming on the Ectomycorrhizal Fungal Community of Boreal and Temperate Host Species Growing Near Their Shared Ecotonal Range Limits

Ectomycorrhizal (ECM) fungi can influence the establishment and performance of host species by increasing nutrient and water absorption. Therefore, understanding the response of ECM fungi to expected changes in the global climate is crucial for predicting potential changes in the composition and productivity of forests. While anthropogenic activity has, and will continue to, cause global temperature increases, few studies have investigated how increases in temperature will affect the community composition of ectomycorrhizal fungi. The effects of global warming are expected to be particularly strong at biome boundaries and in the northern latitudes. In the present study, we analyzed the effects of experimental manipulations of temperature and canopy structure (open vs. closed) on ectomycorrhizal fungi identified from roots of host seedlings through 454 pyrosequencing. The ecotonal boundary site selected for the study was between the southern boreal and temperate forests in northern Minnesota, USA, which is the southern limit range for Picea glauca and Betula papyrifera and the northern one for Pinus strobus and Quercus rubra. Manipulations that increased air and soil temperature by 1.7 and 3.4 °C above ambient temperatures, respectively, did not change ECM richness but did alter the composition of the ECM community in a manner dependent on host and canopy structure. The prediction that colonization of boreal tree species with ECM symbionts characteristic of temperate species would occur was not substantiated. Overall, only a small proportion of the ECM community appears to be strongly sensitive to warming.

Metabarcoding analysis of eukaryotic microbiota in the gut of HIV-infected patients

Research on the relationship between changes in the gut microbiota and human disease, including AIDS, is a growing field. However, studies on the eukaryotic component of the intestinal microbiota have just begun and have not yet been conducted in HIV-infected patients. Moreover, eukaryotic community profiling is influenced by the use of different methodologies at each step of culture-independent techniques. Herein, initially, four DNA extraction protocols were compared to test the efficiency of each method in recovering eukaryotic DNA from fecal samples. Our results revealed that recovering eukaryotic components from fecal samples differs significantly among DNA extraction methods. Subsequently, the composition of the intestinal eukaryotic microbiota was evaluated in HIV-infected patients and healthy volunteers through clone sequencing, high-throughput sequencing of nuclear ribosomal internal transcribed spacers 1 (ITS1) and 2 (ITS2) amplicons and real-time PCRs. Our results revealed that not only richness (Chao-1 index) and alpha diversity (Shannon diversity) differ between HIV-infected patients and healthy volunteers, depending on the molecular strategy used, but also the global eukaryotic community composition, with little overlapping taxa found between techniques. Moreover, our results based on cloning libraries and ITS1/ITS2 metabarcoding sequencing showed significant differences in fungal composition between HIV-infected patients and healthy volunteers, but without distinct clusters separating the two groups. Malassezia restricta was significantly more prevalent in fecal samples of HIV-infected patients, according to cloning libraries, whereas operational taxonomic units (OTUs) belonging to Candida albicans and Candida tropicalis were significantly more abundant in fecal samples of HIV-infected patients compared to healthy subjects in both ITS subregions. Finally, real-time PCR showed the presence of Microsporidia, Giardia lamblia, Blastocystis and Hymenolepis diminuta in different proportions in fecal samples from HIV patients as compared to healthy individuals. Our work revealed that the use of different sequencing approaches can impact the perceived eukaryotic diversity results of the human gut. We also provide a more comprehensive view of the eukaryotic community in the gut of HIV-infected patients through the complementarity of the different molecular techniques used. Combining these various methodologies may provide a gold standard for a more complete characterization of the eukaryotic microbiome in future studies.

Evaluating and optimizing the performance of software commonly used for the taxonomic classification of DNA metabarcoding sequence data

The taxonomic classification of DNA sequences has become a critical component of numerous ecological research applications; however, few studies have evaluated the strengths and weaknesses of commonly used sequence classification approaches. Further, the methods and software available for sequence classification are diverse, creating an environment in which it may be difficult to determine the best course of action and the trade-offs made using different classification approaches. Here, we provide an in silico evaluation of three DNA sequence classifiers, the rdp Naïve Bayesian Classifier, rtax and utax. Further, we discuss the results, merits and limitations of both the classifiers and our method of classifier evaluation. Our methods of comparison are simple, yet robust, and will provide researchers a methodological and conceptual foundation for making such evaluations in a variety of research situations. Generally, we found a considerable trade-off between accuracy and sensitivity for the classifiers tested, indicating a need for further improvement of sequence classification tools.

Ribosomal DNA and Plastid Markers Used to Sample Fungal and Plant Communities from Wetland Soils Reveals Complementary Biotas

Though the use of metagenomic methods to sample below-ground fungal communities is common, the use of similar methods to sample plants from their underground structures is not. In this study we use high throughput sequencing of the ribulose-bisphosphate carboxylase large subunit (rbcL) plastid marker to study the plant community as well as the internal transcribed spacer and large subunit ribosomal DNA (rDNA) markers to investigate the fungal community from two wetland sites. Observed community richness and composition varied by marker. The two rDNA markers detected complementary sets of fungal taxa and total fungal composition clustered according to primer rather than by site. The composition of the most abundant plants, however, clustered according to sites as expected. We suggest that future studies consider using multiple genetic markers, ideally generated from different primer sets, to detect a more taxonomically diverse suite of taxa compared with what can be detected by any single marker alone. Conclusions drawn from the presence of even the most frequently observed taxa should be made with caution without corroborating lines of evidence.

Microbial Community Analysis with Ribosomal Gene Fragments from Shotgun Metagenomes

Shotgun metagenomic sequencing does not depend on gene-targeted primers or PCR amplification; thus, it is not affected by primer bias or chimeras. However, searching rRNA genes from large shotgun Illumina data sets is computationally expensive, and no approach exists for unsupervised community analysis of small-subunit (SSU) rRNA gene fragments retrieved from shotgun data. We present a pipeline, SSUsearch, to achieve the faster identification of short-subunit rRNA gene fragments and enabled unsupervised community analysis with shotgun data. It also includes classification and copy number correction, and the output can be used by traditional amplicon analysis platforms. Shotgun metagenome data using this pipeline yielded higher diversity estimates than amplicon data but retained the grouping of samples in ordination analyses. We applied this pipeline to soil samples with paired shotgun and amplicon data and confirmed bias against Verrucomicrobia in a commonly used V6-V8 primer set, as well as discovering likely bias against Actinobacteria and for Verrucomicrobia in a commonly used V4 primer set. This pipeline can utilize all variable regions in SSU rRNA and also can be applied to large-subunit (LSU) rRNA genes for confirmation of community structure. The pipeline can scale to handle large amounts of soil metagenomic data (5 Gb memory and 5 central processing unit hours to process 38 Gb [1 lane] of trimmed Illumina HiSeq2500 data) and is freely available at https://github.com/dib-lab/SSUsearch under a BSD license.

Molecular evidence on the occurrence of co-infection with Pichia guilliermondii and Wuchereria bancrofti in two filarial endemic districts of India

Background

Lymphatic filariasis (LF), a vector-borne parasitic disease, is endemic in several parts of India and mostly affects the poor or those with a low-income. The disease results in huge numbers of morbidities, disabilities, and deaths every year. Association of co-infection with other pathogens makes the condition more severe. Although co-infection is becoming a growing area of research, it is yet to emerge as a frontier research topic in filarial research specifically. This study reports the occurrence of a fungal infection in a large number of patients suffering from bancroftian filariasis in two districts of West Bengal, India.

Methods

Nocturnal blood samples from filarial patients containing parasites and fungus were initially co-cultured, and further the fungus was isolated and characterized. Molecular identification of the isolate was carried out by PCR-based selective amplification and sequencing of highly-conserved D1/D2 region of 26S rDNA, whereas pathogenicity was determined by amplification of the RPS0 gene. A phylogenetic tree was constructed to study the relationship between the isolate and common pathogenic yeasts. The isolate was studied for antibiotic sensitivity, whereas morphological characterization was performed by microscopic techniques.

Results

The isolate was identified as Pichia guilliermondii and this fungus was found to exist in co-infection with Wuchereria bancrofti in filarial patients. The fungus showed resistance to azole antifungals, griseofulvin, and, amphotericin B, whereas significant susceptibility was evident in cases of nystatin and cycloheximide. A total of 197 out of 222 patients showed this co-infection.

Conclusion

This study revealed, for the first time, that P. guilliermondii exists as a co-infection in microfilaraemic individuals living in a filarial endemic zone. The findings are important and have relevance to human health, especially for filarial patients.

Fungal community structure in disease suppressive soils assessed by 28S LSU gene sequencing

Natural biological suppression of soil-borne diseases is a function of the activity and composition of soil microbial communities. Soil microbe and phytopathogen interactions can occur prior to crop sowing and/or in the rhizosphere, subsequently influencing both plant growth and productivity. Research on suppressive microbial communities has concentrated on bacteria although fungi can also influence soil-borne disease. Fungi were analyzed in co-located soils 'suppressive' or 'non-suppressive' for disease caused by Rhizoctonia solani AG 8 at two sites in South Australia using 454 pyrosequencing targeting the fungal 28S LSU rRNA gene. DNA was extracted from a minimum of 125 g of soil per replicate to reduce the micro-scale community variability, and from soil samples taken at sowing and from the rhizosphere at 7 weeks to cover the peak Rhizoctonia infection period. A total of ∼ 994,000 reads were classified into 917 genera covering 54% of the RDP Fungal Classifier database, a high diversity for an alkaline, low organic matter soil. Statistical analyses and community ordinations revealed significant differences in fungal community composition between suppressive and non-suppressive soil and between soil type/location. The majority of differences associated with suppressive soils were attributed to less than 40 genera including a number of endophytic species with plant pathogen suppression potentials and mycoparasites such as Xylaria spp. Non-suppressive soils were dominated by Alternaria, Gibberella and Penicillum. Pyrosequencing generated a detailed description of fungal community structure and identified candidate taxa that may influence pathogen-plant interactions in stable disease suppression.

Rapid and accurate taxonomic classification of insect (class Insecta) cytochrome c oxidase subunit 1 ( COI ) DNA barcode sequences using a naïve Bayesian classifier

Current methods to identify unknown insect (class Insecta) cytochrome c oxidase (COI barcode) sequences often rely on thresholds of distances that can be difficult to define, sequence similarity cut-offs, or monophyly. Some of the most commonly used metagenomic classification methods do not provide a measure of confidence for the taxonomic assignments they provide. The aim of this study was to use a naïve Bayesian classifier (Wang et al.Applied and Environmental Microbiology, 2007; 73: 5261) to automate taxonomic assignments for large batches of insect COI sequences such as data obtained from high-throughput environmental sequencing. This method provides rank-flexible taxonomic assignments with an associated bootstrap support value, and it is faster than the blast-based methods commonly used in environmental sequence surveys. We have developed and rigorously tested the performance of three different training sets using leave-one-out cross-validation, two field data sets, and targeted testing of Lepidoptera, Diptera and Mantodea sequences obtained from the Barcode of Life Data system. We found that type I error rates, incorrect taxonomic assignments with a high bootstrap support, were already relatively low but could be lowered further by ensuring that all query taxa are actually present in the reference database. Choosing bootstrap support cut-offs according to query length and summarizing taxonomic assignments to more inclusive ranks can also help to reduce error while retaining the maximum number of assignments. Additionally, we highlight gaps in the taxonomic and geographic representation of insects in public sequence databases that will require further work by taxonomists to improve the quality of assignments generated using any method.

From genus to phylum: large-subunit and internal transcribed spacer rRNA operon regions show similar classification accuracies influenced by database composition

We compared the classification accuracy of two sections of the fungal internal transcribed spacer (ITS) region, individually and combined, and the 5' section (about 600 bp) of the large-subunit rRNA (LSU), using a naive Bayesian classifier and BLASTN. A hand-curated ITS-LSU training set of 1,091 sequences and a larger training set of 8,967 ITS region sequences were used. Of the factors evaluated, database composition and quality had the largest effect on classification accuracy, followed by fragment size and use of a bootstrap cutoff to improve classification confidence. The naive Bayesian classifier and BLASTN gave similar results at higher taxonomic levels, but the classifier was faster and more accurate at the genus level when a bootstrap cutoff was used. All of the ITS and LSU sections performed well (>97.7% accuracy) at higher taxonomic ranks from kingdom to family, and differences between them were small at the genus level (within 0.66 to 1.23%). When full-length sequence sections were used, the LSU outperformed the ITS1 and ITS2 fragments at the genus level, but the ITS1 and ITS2 showed higher accuracy when smaller fragment sizes of the same length and a 50% bootstrap cutoff were used. In a comparison using the larger ITS training set, ITS1 and ITS2 had very similar accuracy classification for fragments between 100 and 200 bp. Collectively, the results show that any of the ITS or LSU sections we tested provided comparable classification accuracy to the genus level and underscore the need for larger and more diverse classification training sets.

Fungal diversity in permafrost and tallgrass prairie soils under experimental warming conditions

Soil fungi play a major role in terrestrial ecosystem functioning through interactions with soil structure, plants, micro- and mesofauna, and nutrient cycling through predation, pathogenesis, mutualistic, and saprotrophic roles. The diversity of soil fungi was assessed by sequencing their 28S rRNA gene in Alaskan permafrost and Oklahoma tallgrass prairie soils at experimental sites where the effect of climate warming is under investigation. A total of 226,695 reads were classified into 1,063 genera, covering 62% of the reference data set. Using the Bayesian Classifier offered by the Ribosomal Database Project (RDP) with 50% bootstrapping classification confidence, approximately 70% of sequences were returned as "unclassified" at the genus level, although the majority (∼65%) were classified at the class level, which provided insight into these lesser-known fungal lineages. Those unclassified at the genus level were subjected to BLAST analysis against the ARB-SILVA database, where ∼50% most closely matched nonfungal taxa. Compared to the more abundant sequences, a higher proportion of rare operational taxonomic units (OTU) were successfully classified to genera at 50% bootstrap confidence, indicating that the fungal rare biosphere in these sites is not composed of sequencing artifacts. There was no significant effect after 1 year of warming on the fungal community structure at both sites, except perhaps for a few minor members, but there was a significant effect of sample depth in the permafrost soils. Despite overall significant community structure differences driven by variations in OTU dominance, the prairie and permafrost soils shared 90% and 63% of all fungal sequences, respectively, indicating a fungal "seed bank" common between both sites.

Fungal community analysis by high-throughput sequencing of amplified markers--a user's guide

Novel high-throughput sequencing methods outperform earlier approaches in terms of resolution and magnitude. They enable identification and relative quantification of community members and offer new insights into fungal community ecology. These methods are currently taking over as the primary tool to assess fungal communities of plant-associated endophytes, pathogens, and mycorrhizal symbionts, as well as free-living saprotrophs. Taking advantage of the collective experience of six research groups, we here review the different stages involved in fungal community analysis, from field sampling via laboratory procedures to bioinformatics and data interpretation. We discuss potential pitfalls, alternatives, and solutions. Highlighted topics are challenges involved in: obtaining representative DNA/RNA samples and replicates that encompass the targeted variation in community composition, selection of marker regions and primers, options for amplification and multiplexing, handling of sequencing errors, and taxonomic identification. Without awareness of methodological biases, limitations of markers, and bioinformatics challenges, large-scale sequencing projects risk yielding artificial results and misleading conclusions.

Improved selection of internal transcribed spacer-specific primers enables quantitative, ultra-high-throughput profiling of fungal communities

Ultra-high-throughput sequencing (HTS) of fungal communities has been restricted by short read lengths and primer amplification bias, slowing the adoption of newer sequencing technologies to fungal community profiling. To address these issues, we evaluated the performance of several common internal transcribed spacer (ITS) primers and designed a novel primer set and work flow for simultaneous quantification and species-level interrogation of fungal consortia. Primer comparison and validation were predicted in silico and by sequencing a "mock community" of mixed yeast species to explore the challenges of amplicon length and amplification bias for reconstructing defined yeast community structures. The amplicon size and distribution of this primer set are smaller than for all preexisting ITS primer sets, maximizing sequencing coverage of hypervariable ITS domains by very-short-amplicon, high-throughput sequencing platforms. This feature also enables the optional integration of quantitative PCR (qPCR) directly into the HTS preparatory work flow by substituting qPCR with these primers for standard PCR, yielding quantification of individual community members. The complete work flow described here, utilizing any of the qualified primer sets evaluated, can rapidly profile mixed fungal communities and capably reconstructed well-characterized beer and wine fermentation fungal communities.

CREST--classification resources for environmental sequence tags

Sequencing of taxonomic or phylogenetic markers is becoming a fast and efficient method for studying environmental microbial communities. This has resulted in a steadily growing collection of marker sequences, most notably of the small-subunit (SSU) ribosomal RNA gene, and an increased understanding of microbial phylogeny, diversity and community composition patterns. However, to utilize these large datasets together with new sequencing technologies, a reliable and flexible system for taxonomic classification is critical. We developed CREST (Classification Resources for Environmental Sequence Tags), a set of resources and tools for generating and utilizing custom taxonomies and reference datasets for classification of environmental sequences. CREST uses an alignment-based classification method with the lowest common ancestor algorithm. It also uses explicit rank similarity criteria to reduce false positives and identify novel taxa. We implemented this method in a web server, a command line tool and the graphical user interfaced program MEGAN. Further, we provide the SSU rRNA reference database and taxonomy SilvaMod, derived from the publicly available SILVA SSURef, for classification of sequences from bacteria, archaea and eukaryotes. Using cross-validation and environmental datasets, we compared the performance of CREST and SilvaMod to the RDP Classifier. We also utilized Greengenes as a reference database, both with CREST and the RDP Classifier. These analyses indicate that CREST performs better than alignment-free methods with higher recall rate (sensitivity) as well as precision, and with the ability to accurately identify most sequences from novel taxa. Classification using SilvaMod performed better than with Greengenes, particularly when applied to environmental sequences. CREST is freely available under a GNU General Public License (v3) from http://apps.cbu.uib.no/crest and http://lcaclassifier.googlecode.com.

Potential benefits of the application of yeast starters in table olive processing

Yeasts play an important role in the food and beverage industry, especially in products such as bread, wine, and beer, among many others. However, their use as a starter in table olive processing has not yet been studied in detail. The candidate yeast strains should be able to dominate fermentation, together with lactic acid bacteria, but should also provide a number of beneficial advantages. Technologically, yeasts should resist low pH and high salt concentrations, produce desirable aromas, improve lactic acid bacteria growth, and inhibit spoilage microorganisms. Nowadays, they are being considered as probiotic agents because many species are able to resist the passage through the gastrointestinal tract and show favorable effects on the host. In this way, yeasts may improve the health of consumers by means of the degradation of non-assimilated compounds (such as phytate complexes), a decrease in cholesterol levels, the production of vitamins and antioxidants, the inhibition of pathogens, an adhesion to intestinal cell line Caco-2, and the maintenance of epithelial barrier integrity. Many yeast species, usually found in table olive processing (Wickerhamomyces anomalus, Saccharomyces cerevisiae, Pichia membranifaciens, and Kluyveromyces lactis, among others), have exhibited some of these properties. Thus, the selection of the most appropriate strains to be used as starters in this fermented vegetable, alone or in combination with lactic acid bacteria, is a promising research line to develop in the near future.

Potential benefits of the application of yeast starters in table olive processing

The classification of high-throughput sequencing data of protein-encoding genes is not as well established as for 16S rRNA. The objective of this work was to develop a simple and accurate method of classifying large datasets of pmoA sequences, a common marker for methanotrophic bacteria. A taxonomic system for pmoA was developed based on a phylogenetic analysis of available sequences. The taxonomy incorporates the known diversity of pmoA present in public databases, including both sequences from cultivated and uncultivated organisms. Representative sequences from closely related genes, such as those encoding the bacterial ammonia monooxygenase, were also included in the pmoA taxonomy. In total, 53 low-level taxa (genus-level) are included. Using previously published datasets of high-throughput pmoA amplicon sequence data, we tested two approaches for classifying pmoA: a naïve Bayesian classifier and BLAST. Classification of pmoA sequences based on BLAST analyses was performed using the lowest common ancestor (LCA) algorithm in MEGAN, a software program commonly used for the analysis of metagenomic data. Both the naïve Bayesian and BLAST methods were able to classify pmoA sequences and provided similar classifications; however, the naïve Bayesian classifier was prone to misclassifying contaminant sequences present in the datasets. Another advantage of the BLAST/LCA method was that it provided a user-interpretable output and enabled novelty detection at various levels, from highly divergent pmoA sequences to genus-level novelty.