A laboratory information management system for DNA barcoding workflows

dnabarcoder: an open-source software package for analyzing and predicting DNA sequence similarity cut-offs for fungal sequence identification

The accuracy and precision of fungal molecular identification and classification are challenging, particularly in environmental metabarcoding approaches as these often trade accuracy for efficiency given the large data volumes at hand. In most ecological studies, only a single similarity cutoff value is used for sequence identification. This is not sufficient since the most commonly used DNA markers are known to vary widely in terms of inter‐ and intraspecific variability. We address this problem by presenting a new tool, dnabarcoder, to predict local similarity cutoffs and measure the resolving powers of a biomarker for sequence identification for different clades of fungi. It was shown that the predicted similarity cutoffs varied significantly between the clades of a recently released ITS DNA barcode data set from the CBS culture collection of the Westerdijk Fungal Biodiversity Institute. When classifying a large public fungal ITS data set—the UNITE database—against the barcode data set, the local similarity cutoffs assigned fewer sequences than the traditional cutoffs used in metabarcoding studies. However, the obtained accuracy and precision were significantly improved. Our study showed that it might be better to extract the ITS region from the ITS barcodes to optimize taxonomic assignment accuracy. Furthermore, 15.3, 25.6, and 26.3% of the fungal species of the barcode data set were indistinguishable by full‐length ITS, ITS1, and ITS2, respectively. Except for these indistinguishable species, the resolving powers of full‐length ITS, ITS1, and ITS2 sequences were similar at the species level. Nevertheless, the complete ITS region had a better resolving power at higher taxonomic levels.

Molecular and Phenotypic Characterization of Nannizzia (Arthrodermataceae)

Phylogenetic studies of the family Arthrodermataceae have revealed seven monophyletic dermatophyte clades representing the genera Trichophyton, Epidermophyton, Nannizzia, Lophophyton, Paraphyton, Microsporum, and Arthroderma. Members of the genus Nannizzia are geo- or zoophiles that occasionally infect humans. With the newly proposed taxonomy, the genus Nannizzia comprises thirteen species, i.e., Nannizzia aenigmatica, N. corniculata, N. duboisii, N. fulva, N. graeserae, N. gypsea, N. nana, N. incurvata, N. perplicata, N. persicolor, N. praecox, and two novel species. Nannizzia polymorpha sp. nov. was isolated from a skin lesion of a patient from French Guiana. For the strain originally described as Microsporum racemosum by Borelli in 1965, we proposed Nannizzia lorica nom. nov. The species are fully characterized with five sequenced loci (ITS, LSU, TUB2, RP 60S L1 and TEF3), combined with morphology of the asexual form and physiological features. A key to the species based on phenotypic and physiological characters is provided.

Convolutional neural networks improve fungal classification

Sequence classification plays an important role in metagenomics studies. We assess the deep neural network approach for fungal sequence classification as it has emerged as a successful paradigm for big data classification and clustering. Two deep learning-based classifiers, a convolutional neural network (CNN) and a deep belief network (DBN) were trained using our recently released barcode datasets. Experimental results show that CNN outperformed the traditional BLAST classification and the most accurate machine learning based Ribosomal Database Project (RDP) classifier on datasets that had many of the labels present in the training datasets. When classifying an independent dataset namely the "Top 50 Most Wanted Fungi", CNN and DBN assigned less sequences than BLAST. However, they could assign much more sequences than the RDP classifier. In terms of efficiency, it took the machine learning classifiers up to two seconds to classify a test dataset while it was 53 s for BLAST. The result of the current study will enable us to speed up the taxonomic assignments for the fungal barcode sequences generated at our institute as ~ 70% of them still need to be validated for public release. In addition, it will help to quickly provide a taxonomic profile for metagenomics samples.

Polyphasic Discrimination of Trichophyton tonsurans and T. equinum from Humans and Horses

The anthropophilic dermatophyte Trichophyton tonsurans and its zoophilic counterpart T. equinum are phylogenetically closely related. The barcoding marker rDNA internal transcribed spacer (ITS) shows limited variation between these two species. In the current study, we combined molecular approaches with phenotypic data to determine the species boundaries between T. tonsurans (n = 52) and T. equinum (n = 15) strains originating from humans (n = 40), horses (n = 26), and a mouse (n = 1). Culture characteristics and physiology on Trichophyton agar media 1 and 5 were evaluated. Multi-locus sequencing involving ITS, partial large rDNA subunit (LSU), β-tubulin (TUB), 60S ribosomal protein (RPB), and translation elongation factor-3 (TEF3) genes, and the mating-type (MAT) locus was performed. Amplified fragment length polymorphism data were added. None of the test results showed complete mutual correspondence. With the exception of strains from New Zealand, strains of equine origin required niacin for growth, whereas most strains from human origin did not show this dependence. It is concluded that T. tonsurans and T. equinum incompletely diverged from a common lineage relatively recently. MAT1-1 and MAT1-2 are the main distinguishing genes between the two species.

Large-scale generation and analysis of filamentous fungal DNA barcodes boosts coverage for kingdom fungi and reveals thresholds for fungal species and higher taxon delimitation

Species identification lies at the heart of biodiversity studies that has in recent years favoured DNA-based approaches. Microbial Biological Resource Centres are a rich source for diverse and high-quality reference materials in microbiology, and yet the strains preserved in these biobanks have been exploited only on a limited scale to generate DNA barcodes. As part of a project funded in the Netherlands to barcode specimens of major national biobanks, sequences of two nuclear ribosomal genetic markers, the Internal Transcribed Spaces and 5.8S gene (ITS) and the D1/D2 domain of the 26S Large Subunit (LSU), were generated as DNA barcode data for ca. 100 000 fungal strains originally assigned to ca. 17 000 species in the CBS fungal biobank maintained at the Westerdijk Fungal Biodiversity Institute, Utrecht. Using more than 24 000 DNA barcode sequences of 12 000 ex-type and manually validated filamentous fungal strains of 7 300 accepted species, the optimal identity thresholds to discriminate filamentous fungal species were predicted as 99.6 % for ITS and 99.8 % for LSU. We showed that 17 % and 18 % of the species could not be discriminated by the ITS and LSU genetic markers, respectively. Among them, ∼8 % were indistinguishable using both genetic markers. ITS has been shown to outperform LSU in filamentous fungal species discrimination with a probability of correct identification of 82 % vs. 77.6 %, and a clustering quality value of 84 % vs. 77.7 %. At higher taxonomic classifications, LSU has been shown to have a better discriminatory power than ITS. With a clustering quality value of 80 %, LSU outperformed ITS in identifying filamentous fungi at the ordinal level. At the generic level, the clustering quality values produced by both genetic markers were low, indicating the necessity for taxonomic revisions at genus level and, likely, for applying more conserved genetic markers or even whole genomes. The taxonomic thresholds predicted for filamentous fungal identification at the genus, family, order and class levels were 94.3 %, 88.5 %, 81.2 % and 80.9 % based on ITS barcodes, and 98.2 %, 96.2 %, 94.7 % and 92.7 % based on LSU barcodes. The DNA barcodes used in this study have been deposited to GenBank and will also be publicly available at the Westerdijk Institute's website as reference sequences for fungal identification, marking an unprecedented data release event in global fungal barcoding efforts to date.

Phylogeny of dermatophytes with genomic character evaluation of clinically distinct Trichophyton rubrum and T. violaceum

Trichophyton rubrum and T. violaceum are prevalent agents of human dermatophyte infections, the former being found on glabrous skin and nail, while the latter is confined to the scalp. The two species are phenotypically different but are highly similar phylogenetically. The taxonomy of dermatophytes is currently being reconsidered on the basis of molecular phylogeny. Molecular species definitions do not always coincide with existing concepts which are guided by ecological and clinical principles. In this article, we aim to bring phylogenetic and ecological data together in an attempt to develop new species concepts for anthropophilic dermatophytes. Focus is on the T. rubrum complex with analysis of rDNA ITS supplemented with LSU, TUB2, TEF3 and ribosomal protein L10 gene sequences. In order to explore genomic differences between T. rubrum and T. violaceum, one representative for both species was whole genome sequenced. Draft sequences were compared with currently available dermatophyte genomes. Potential virulence factors of adhesins and secreted proteases were predicted and compared phylogenetically. General phylogeny showed clear gaps between geophilic species of Arthroderma, but multilocus distances between species were often very small in the derived anthropophilic and zoophilic genus Trichophyton. Significant genome conservation between T. rubrum and T. violaceum was observed, with a high similarity at the nucleic acid level of 99.38 % identity. Trichophyton violaceum contains more paralogs than T. rubrum. About 30 adhesion genes were predicted among dermatophytes. Seventeen adhesins were common between T. rubrum and T. violaceum, while four were specific for the former and eight for the latter. Phylogenetic analysis of secreted proteases reveals considerable expansion and conservation among the analyzed species. Multilocus phylogeny and genome comparison of T. rubrum and T. violaceum underlined their close affinity. The possibility that they represent a single species exhibiting different phenotypes due to different localizations on the human body is discussed.

Novel taxa of thermally dimorphic systemic pathogens in the Ajellomycetaceae (Onygenales)

Recent discoveries of novel systemic fungal pathogens with thermally dimorphic yeast-like phases have challenged the current taxonomy of the Ajellomycetaceae, a family currently comprising the genera Blastomyces, Emmonsia, Emmonsiellopsis, Helicocarpus, Histoplasma, Lacazia and Paracoccidioides. Our morphological, phylogenetic and phylogenomic analyses demonstrated species relationships and their specific phenotypes, clarified generic boundaries and provided the first annotated genome assemblies to support the description of two new species. A new genus, Emergomyces, accommodates Emmonsia pasteuriana as type species, and the new species Emergomyces africanus, the aetiological agent of case series of disseminated infections in South Africa. Both species produce small yeast cells that bud at a narrow base at 37°C and lack adiaspores, classically associated with the genus Emmonsia. Another novel dimorphic pathogen, producing broad-based budding cells at 37°C and occurring outside North America, proved to belong to the genus Blastomyces, and is described as Blastomyces percursus.

DNA barcoding analysis of more than 9 000 yeast isolates contributes to quantitative thresholds for yeast species and genera delimitation

DNA barcoding is a global initiative for species identification through sequencing of short DNA sequence markers. Sequences of two loci, ITS and LSU, were generated as barcode data for all (ca. 9k) yeast strains included in the CBS collection, originally assigned to ca. 2 000 species. Taxonomic sequence validation turned out to be the most severe bottleneck due to the large volume of generated trace files and lack of reference sequences. We have analysed and validated CBS strains and barcode sequences automatically. Our analysis shows that there were 6 and 9.5 % of CBS yeast species that could not be distinguished by ITS and LSU, respectively. Among them, ∼3 % were indistinguishable by both loci. Except for those species, both loci were successfully resolving yeast species as the grouping of yeast DNA barcodes with the predicted taxonomic thresholds was more than 90 % similar to the grouping with respect to the expected taxon names. The taxonomic thresholds predicted to discriminate yeast species were 98.41 % for ITS and 99.51 % for LSU. To discriminate current yeast genera, thresholds were 96.31 % for ITS and 97.11 % for LSU. Using ITS and LSU barcodes, we were also able to show that the recent reclassifications of basidiomycetous yeasts in 2015 have made a significant improvement for the generic taxonomy of those organisms. The barcodes of 4 730 (51 %) CBS yeast strains of 1 351 (80 %) accepted yeast species that were manually validated have been released to GenBank and the CBS-KNAW website as reference sequences for yeast identification.

Toward a Novel Multilocus Phylogenetic Taxonomy for the Dermatophytes

Type and reference strains of members of the onygenalean family Arthrodermataceae have been sequenced for rDNA ITS and partial LSU, the ribosomal 60S protein, and fragments of β-tubulin and translation elongation factor 3. The resulting phylogenetic trees showed a large degree of correspondence, and topologies matched those of earlier published phylogenies demonstrating that the phylogenetic representation of dermatophytes and dermatophyte-like fungi has reached an acceptable level of stability. All trees showed Trichophyton to be polyphyletic. In the present paper, Trichophyton is restricted to mainly the derived clade, resulting in classification of nearly all anthropophilic dermatophytes in Trichophyton and Epidermophyton, along with some zoophilic species that regularly infect humans. Microsporum is restricted to some species around M. canis, while the geophilic species and zoophilic species that are more remote from the human sphere are divided over Arthroderma, Lophophyton and Nannizzia. A new genus Guarromyces is proposed for Keratinomyces ceretanicus. Thirteen new combinations are proposed; in an overview of all described species it is noted that the largest number of novelties was introduced during the decades 1920–1940, when morphological characters were used in addition to clinical features. Species are neo- or epi-typified where necessary, which was the case in Arthroderma curreyi, Epidermophyton floccosum, Lophophyton gallinae, Trichophyton equinum, T. mentagrophytes, T. quinckeanum, T. schoenleinii, T. soudanense, and T. verrucosum. In the newly proposed taxonomy, Trichophyton contains 16 species, Epidermophyton one species, Nannizzia 9 species, Microsporum 3 species, Lophophyton 1 species, Arthroderma 21 species and Ctenomyces 1 species, but more detailed studies remain needed to establish species borderlines. Each species now has a single valid name. Two new genera are introduced: Guarromyces and Paraphyton. The number of genera has increased, but species that are relevant to routine diagnostics now belong to smaller groups, which enhances their identification.

One fungus, which genes? Development and assessment of universal primers for potential secondary fungal DNA barcodes

The aim of this study was to assess potential candidate gene regions and corresponding universal primer pairs as secondary DNA barcodes for the fungal kingdom, additional to ITS rDNA as primary barcode. Amplification efficiencies of 14 (partially) universal primer pairs targeting eight genetic markers were tested across > 1 500 species (1 931 strains or specimens) and the outcomes of almost twenty thousand (19 577) polymerase chain reactions were evaluated. We tested several well-known primer pairs that amplify: i) sections of the nuclear ribosomal RNA gene large subunit (D1–D2 domains of 26/28S); ii) the complete internal transcribed spacer region (ITS1/2); iii) partial β -tubulin II (TUB2); iv) γ-actin (ACT); v) translation elongation factor 1-α (TEF1α); and vi) the second largest subunit of RNA-polymerase II (partial RPB2, section 5–6). Their PCR efficiencies were compared with novel candidate primers corresponding to: i) the fungal-specific translation elongation factor 3 (TEF3); ii) a small ribosomal protein necessary for t-RNA docking; iii) the 60S L10 (L1) RP; iv) DNA topoisomerase I (TOPI); v) phosphoglycerate kinase (PGK); vi) hypothetical protein LNS2; and vii) alternative sections of TEF1α. Results showed that several gene sections are accessible to universal primers (or primers universal for phyla) yielding a single PCR-product. Barcode gap and multi-dimensional scaling analyses revealed that some of the tested candidate markers have universal properties providing adequate infra- and inter-specific variation that make them attractive barcodes for species identification. Among these gene sections, a novel high fidelity primer pair for TEF1α, already widely used as a phylogenetic marker in mycology, has potential as a supplementary DNA barcode with superior resolution to ITS. Both TOPI and PGK show promise for the Ascomycota, while TOPI and LNS2 are attractive for the Pucciniomycotina, for which universal primers for ribosomal subunits often fail.

Massive fungal biodiversity data re-annotation with multi-level clustering

With the availability of newer and cheaper sequencing methods, genomic data are being generated at an increasingly fast pace. In spite of the high degree of complexity of currently available search routines, the massive number of sequences available virtually prohibits quick and correct identification of large groups of sequences sharing common traits. Hence, there is a need for clustering tools for automatic knowledge extraction enabling the curation of large-scale databases. Current sophisticated approaches on sequence clustering are based on pairwise similarity matrices. This is impractical for databases of hundreds of thousands of sequences as such a similarity matrix alone would exceed the available memory. In this paper, a new approach called MultiLevel Clustering (MLC) is proposed which avoids a majority of sequence comparisons, and therefore, significantly reduces the total runtime for clustering. An implementation of the algorithm allowed clustering of all 344,239 ITS (Internal Transcribed Spacer) fungal sequences from GenBank utilizing only a normal desktop computer within 22 CPU-hours whereas the greedy clustering method took up to 242 CPU-hours.

Novel genera and species of coniothyrium-like fungi in Montagnulaceae (Ascomycota)

Based on analyses of concatenated internal transcribed spacer regions of the nrDNA operon (ITS), large subunit rDNA (LSU), γ-actin and β-tubulin gene sequences the taxonomy of coniothyrium-like fungi belonging in the family Montagnulaceae, order Pleosporales, was re-assessed. Two new genera are proposed, Alloconiothyrium, to accommodate A. aptrootii sp. nov., and Dendrothyrium for D. longisporum sp. nov. and D. variisporum sp. nov. One new species is described in Paraconiothyrium, viz. Parac. archidendri sp. nov., while two species so far classified in Paraconiothyrium are transferred to Paraphaeosphaeria, viz. Paraph. minitans comb. nov. and Paraph. sporulosa comb. nov. In Paraphaeosphaeria five new species are described based on asexual morphs, viz. Paraph. arecacearum sp. nov., Paraph. neglecta sp. nov., Paraph. sardoa sp. nov., Paraph. verruculosa sp. nov., and Paraph. viridescens sp. nov. Macro- and micromorphological characteristics are fully described.

A comprehensive molecular phylogeny of the Mortierellales (Mortierellomycotina) based on nuclear ribosomal DNA

The basal fungal order Mortierellales constitutes one of the largest orders in the basal lineages. This group consists of one family and six genera. Most species are saprobic soil inhabiting fungi with the ability of diverse biotransformations or the accumulation of unsaturated fatty acids, making them attractive for biotechnological applications. Only few studies exist aiming at the revelation of the evolutionary relationships of this interesting fungal group. This study includes the largest dataset of LSU and ITS sequences for more than 400 specimens containing 63 type or reference strains. Based on a LSU phylogram, fungal groups were defined and evaluated using ITS sequences and morphological features. Traditional morphology-based classification schemes were rejected, because the morphology of the Mortierellales seems to depend on culture conditions, a fact, which makes the identification of synapomorphic characters tedious. This study belongs to the most comprehensive molecular phylogenetic analyses for the Mortierellales up to date and reveals unresolved species and species complexes.

Transforming microbial genotyping: a robotic pipeline for genotyping bacterial strains

Microbial genotyping increasingly deals with large numbers of samples, and data are commonly evaluated by unstructured approaches, such as spread-sheets. The efficiency, reliability and throughput of genotyping would benefit from the automation of manual manipulations within the context of sophisticated data storage. We developed a medium- throughput genotyping pipeline for MultiLocus Sequence Typing (MLST) of bacterial pathogens. This pipeline was implemented through a combination of four automated liquid handling systems, a Laboratory Information Management System (LIMS) consisting of a variety of dedicated commercial operating systems and programs, including a Sample Management System, plus numerous Python scripts. All tubes and microwell racks were bar-coded and their locations and status were recorded in the LIMS. We also created a hierarchical set of items that could be used to represent bacterial species, their products and experiments. The LIMS allowed reliable, semi-automated, traceable bacterial genotyping from initial single colony isolation and sub-cultivation through DNA extraction and normalization to PCRs, sequencing and MLST sequence trace evaluation. We also describe robotic sequencing to facilitate cherrypicking of sequence dropouts. This pipeline is user-friendly, with a throughput of 96 strains within 10 working days at a total cost of < €25 per strain. Since developing this pipeline, >200,000 items were processed by two to three people. Our sophisticated automated pipeline can be implemented by a small microbiology group without extensive external support, and provides a general framework for semi-automated bacterial genotyping of large numbers of samples at low cost.