Fungal Internal Transcribed Spacer Research Articles

MycoAI: Fast and accurate taxonomic classification for fungal ITS sequences.

Efficient and accurate classification of DNA barcode data is crucial for large-scale fungal biodiversity studies. However, existing methods are either computationally expensive or lack accuracy. Previous research has demonstrated the potential of deep learning in this domain, successfully training neural networks for biological sequence classification. We introduce the MycoAI Python package, featuring various deep learning models such as BERT and CNN tailored for fungal Internal Transcribed Spacer (ITS) sequences. We explore different neural architecture designs and encoding methods to identify optimal models. By employing a multi-head output architecture and multi-level hierarchical label smoothing, MycoAI effectively generalizes across the taxonomic hierarchy. Using over 5 million labelled sequences from the UNITE database, we develop two models: MycoAI-BERT and MycoAI-CNN. While we emphasize the necessity of verifying classification results by AI models due to insufficient reference data, MycoAI still exhibits substantial potential. When benchmarked against existing classifiers such as DNABarcoder and RDP on two independent test sets with labels present in the training dataset, MycoAI models demonstrate high accuracy at the genus and higher taxonomic levels, with MycoAI-CNN being the fastest and most accurate. In terms of efficiency, MycoAI models can classify over 300,000 sequences within 5 min. We publicly release the MycoAI models, enabling mycologists to classify their ITS barcode data efficiently. Additionally, MycoAI serves as a platform for developing further deep learning-based classification methods. The source code for MycoAI is available under the MIT Licence at https://github.com/MycoAI/MycoAI.

Hitac: a hierarchical taxonomic classifier for fungal ITS sequences compatible with QIIME2

BackgroundFungi play a key role in several important ecological functions, ranging from organic matter decomposition to symbiotic associations with plants. Moreover, fungi naturally inhabit the human body and can be beneficial when administered as probiotics. In mycology, the internal transcribed spacer (ITS) region was adopted as the universal marker for classifying fungi. Hence, an accurate and robust method for ITS classification is not only desired for the purpose of better diversity estimation, but it can also help us gain a deeper insight into the dynamics of environmental communities and ultimately comprehend whether the abundance of certain species correlate with health and disease. Although many methods have been proposed for taxonomic classification, to the best of our knowledge, none of them fully explore the taxonomic tree hierarchy when building their models. This in turn, leads to lower generalization power and higher risk of committing classification errors.ResultsHere we introduce HiTaC, a robust hierarchical machine learning model for accurate ITS classification, which requires a small amount of data for training and can handle imbalanced datasets. HiTaC was thoroughly evaluated with the established TAXXI benchmark and could correctly classify fungal ITS sequences of varying lengths and a range of identity differences between the training and test data. HiTaC outperforms state-of-the-art methods when trained over noisy data, consistently achieving higher F1-score and sensitivity across different taxonomic ranks, improving sensitivity by 6.9 percentage points over top methods in the most noisy dataset available on TAXXI.ConclusionsHiTaC is publicly available at the Python package index, BIOCONDA and Docker Hub. It is released under the new BSD license, allowing free use in academia and industry. Source code and documentation, which includes installation and usage instructions, are available at https://gitlab.com/dacs-hpi/hitac.

Loop-Mediated Isothermal Amplification (LAMP): Potential Point-of-Care Testing for Vulvovaginal Candidiasis.

The aim of this study is to establish a loop-mediated isothermal amplification (LAMP) method for the rapid detection of vulvovaginal candidiasis (VVC). We developed and validated a loop-mediated isothermal amplification (LAMP) method for detecting the most common Candida species associated with VVC, including C. albicans, N. glabratus, C. tropicalis, and C. parapsilosis. We evaluated the specificity, sensitivity, positive predictive value (PPV), negative predictive value (NPV), and Kappa value of the LAMP method to detect different Candida species, using the conventional culture method and internal transcribed spacer (ITS) sequencing as gold standards and smear Gram staining and real-time Rolymerase Chain Reaction (PCR) as controls. A total of 202 cases were enrolled, of which 88 were VVC-positive and 114 were negative. Among the 88 positive patients, the fungal culture and ITS sequencing results showed that 67 cases (76.14%) were associated with C. albicans, 13 (14.77%) with N. glabratus, 5 (5.68%) with C. tropicalis, and 3 (3.41%) with other species. Regarding the overall detection rate, the LAMP method presented sensitivity, specificity, PPV, NPV, and Kappa values of 90.91%, 100%, 100%, 93.4%, and 0.919, respectively. Moreover, the LAMP had a specificity of 100% for C. albicans, N. glabratus, and C. tropicalis, with a sensitivity of 94.03%, 100%, and 80%, respectively. Moreover, the microscopy evaluation had the highest sensitivity, while the real-time PCR was less specific for C. albicans than LAMP. In addition, CHROMagar Candida was inferior to LAMP in detecting non-albicans Candida (NAC) species. Based on the cost-effective, rapid, and inexpensive characteristics of LAMP, coupled with the high sensitivity and specificity of our VVC-associated Candida detection method, we provided a possibility for the point-of-care testing (POCT) of VVC, especially in developing countries and some laboratories with limited resources.

Effects of multiple N, P, and K fertilizer combinations on strawberry growth and the microbial community.

Nitrogen (N), phosphorus (P), and potassium (K) exert various effects on strawberry (Fragaria ananassa Duchesne) yields. In this study, we employed an orthogonal experimental design (T1-T9) with three fertilization treatments (N, P, and K) at three levels to identify an optimal fertilization scheme for strawberry cultivation. The effects of fertilizer combinations the rhizosphere soil microbial community were also explored by using bacterial full-length 16S rRNA and fungal ITS (internal transcribed spacer) sequencing (30 samples for each analysis). The results showed that the average plant height and leaf area of the fertilized groups were 24.6% and 41.6% higher than those of the non-fertilized group (T0). After 60 d of planting, the sucrase activity in the T6 group increased by 76.67% compared to the T0 group, with phosphate fertilizer exerting a more significant impact on sucrase activity. The T6 treatment group had the highest alpha diversity index among bacterial and fungal microorganisms, and had a different microbial community structure compared with the control group. The most abundant bacterial taxa in the strawberry rhizosphere soil were Proteobacteria, Bacteroidota, and Acidobacteriota, and the most abundant fungal phyla were Monoblepharomycota, Glomeromycota, and Mucoromycota. Application of the optimal combined fertilizer treatment (T6) significantly increased the abundance of Proteobacteria and altered the abundance of Gemmatimonas compared to other treatment groups. Notably, Gemmatimonas abundance positively correlated with strawberry plant height and soil N, P, and K levels. These findings indicated that the relative abundance of beneficial bacteria could be enhanced by the application of an optimal fertilizer ratio, ultimately improving strawberry agronomic traits.

Skin Microbiome Composition is Associated with Radiation Dermatitis in Breast Cancer Patients Undergoing Radiation after Reconstructive Surgery: A Prospective, Longitudinal Study

Approximately 95% of breast cancer (BC) patients receiving radiotherapy (RT) develop varying degrees of radiation dermatitis (RD), which can greatly affect the patient's quality of life and aesthetics. Severe acute RD can lead to interruption or delay of RT. Currently, there is no consensus on the prevention and management of RD. The skin microbiota (SM), which are mainly composed of bacteria and fungi, are essential for skin homeostasis and microbial dysbiosis is correlated with the onset and progression of many common skin diseases. However, to date, research on the role of the SM in RD remains scarce. This prospective, longitudinal study aims to analyze the association of SM with RD. We collected 200 SM samples both before and after RT from the region in the irradiated chest wall of 100 BC patients receiving RT after reconstructive surgery and samples from the corresponding region in the contralateral breast for bacterial 16S and fungal ITS (internal transcribed spacer) rRNA sequencing. Acute RD was graded according to the Toxicity Criteria of the Radiation Therapy Oncology Group (RTOG). Patients were divided into no or mild dermatitis (N/MD, RTOG grade 0 or 1) and severe dermatitis (SD, RTOG grade 2 and above). The compositional differences across groups were compared using STAMP and high-dimensional class comparisons by linear discriminant analysis of effect size (LEfSe). Differences in metabolic function between groups were predicted by the Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt) method. Significant differences were observed in the diversity and composition of the SM between N/MD and SD both before and after RT. Analysis of bacterial 16S sequencing (n = 89, 63 N/MD, 26 SD) showed significantly higher relative abundance of particular taxa such as Ralstonia, Truepera, Methyloversatilis genera and lower abundance of particular taxa including Staphylococcus, Corynebacterium genera in N/MD patients. Besides, analysis of fungal ITS sequencing (n = 71, 53 N/MD, 18 SD) showed significantly higher relative abundance of particular taxa such as Hypocreaceae family and lower abundance of particular taxa such as Sporidiobolus genus in N/MD patients. Pathways including fatty acid synthesis were predicted to be enriched in N/MD patients. The SM and pathway markers were identified in this study to be associated with the severity of acute RD in BC patients undergoing RT after reconstructive surgery. More patient data is needed to verify the current findings and the results of metagenomic, metatranscriptomic, and metabolomic analyses will further mine key biomarkers at the compositional and functional level.

DNA‐based fungal diversity in Madagascar and arrival of the ectomycorrhizal fungi to the island

AbstractMadagascar is known for its high diversity and endemism of fauna and flora. Fungi, however, have been largely overlooked in diversity and evolution studies on the island, and whether fungi exhibit the same patterns as animals and plants has yet to be further examined. We collected fungal sporocarps and ectomycorrhizal (EcM) roots during three opportunistic surveys in five forests in Madagascar and generated a dataset of fungal Internal Transcribed Spacer (ITS) DNA sequences. We analyzed them together with all publicly available fungal ITS DNA sequences and identified 620 Operational Taxonomic Units (OTUs) from Madagascar, 10% of which contained only sequences from our surveys. Two hundred and ninety‐two OTUs belonged to EcM species with /russula‐lactarius, /boletus, /tomentella‐telephora, /cortinarius, and /amanita being the most abundant EcM lineages. Overall, 60% of all fungi and 81% of the EcM species from Madagascar appear to be endemic. We conducted a phylogenetic analysis using all the OTUs in Amanitaceae, Boletaceae, and Russulaceae families to elucidate their relative timing of arrival in Madagascar. We found that most EcM species from Madagascar in the three families diverged less than 22 million years ago (mya), long after the separation of India and Madagascar (88 mya), which is consistent with a dispersal mediated process of arrival to the island. Our study provides the first comprehensive view of the overall DNA‐based fungal diversity in Madagascar and the current state of knowledge of EcM fungi based on DNA sequences, useful for further ecological and evolutionary studies.Abstract in Malagasy is available with online material.

No Evidence of an Elevation Effect Caused by Temperature Differences on Soil Microbial Properties in a Walnut Fruit Forest in Kyrgyzstan

This study is to investigate the effect of differences in annual average temperature on soil microbial communities as caused by elevation in walnut-fruit forests in Kyrgyzstan with similar vegetation. Soil samples (n = 10 per site) were collected from top- and subsoil at three elevation levels (1000, 1300 and 1600 m above sea level) with an average temperature difference of 1.3 °C between sites and analysed for soil chemical and biological properties. All soil properties showed high variability within, but most revealed no differences between elevation levels. Microbial biomass, activity and community composition were largely similar at all sites with slightly higher fungal contribution based on internal transcribed spacer (ITS) sequence counts at high elevation, which, however was not reflected by ergosterol. Total soil organic carbon and nitrogen levels did not show elevation effects either. Mehlich-extractable elements revealed positive relationship with soil microbial properties, which was in particular pronounced for copper, manganese and zinc, highlighting the relevance of trace elements for soil microorganisms. The subsoil showed lower levels for all microbial properties even though they were on a comparably high level; it contained smaller sized bacteria and fungi, as revealed by MBC/dsDNA ratios, and fungal ITS counts/ergosterol ratios illustrating growth limitations for microorganisms in subsoils. Elevation with long-term average temperature differences did not yield pronounced differences in soil microbial properties, which were more potentially stronger affected by similar C input quantity and substrate quality from the similar vegetation. Consequently, climate change effects will more likely affect microbial properties indirectly via changes in vegetation.

Alfalfa Cover Crops Influence the Soil Fungal Community and Function in Apple Orchards in Arid Desert Oases in Northwest China

The present study investigated the effects of alfalfa cover crops on soil fungal communities and function in apple orchards in arid desert oases. A five-year apple orchard was subjected to two treatments: Intercropping with an alfalfa cover crop (A) and clean tillage (QG). The soil fungal ITS (internal transcribed spacer) region was analyzed using Illumina MiSeq high-throughput sequencing technology, and fungal function was determined using FUNGuild. Changes in the fungal community structure, diversity, and metabolic function in the 0–60 cm soil layer of the apple orchard were compared. The results showed that the alfalfa cover crops enhanced fungal richness but reduced diversity. The alfalfa cover crops improved fungal copy numbers but reduced the relative abundance of the dominant phylum, Ascomycota. Correlations between soil fungi and soil factors revealed that total nitrogen and total carbon were the most important nutrient factors in positively regulating the fungal community. The main negative factors were soil total salts and pH. The FUNGuild functional prediction showed that Ectomycorrhizal-Wood Saprotroph and Endophyte-Undefined Saprotroph only appeared in the alfalfa cover crops. The abundance of endophytes was enhanced (p < 0.05), but the abundance of plant pathogens and wood saprotrophs decreased (p < 0.01). Alfalfa cover crops could increase the copy numbers and richness in arid oasis apple orchards.

Human Gut Mycobiome and Fungal Community Interaction: The Unknown Musketeer in the Chemotherapy Response Status in Bladder Cancer

BackgroundUntil recently, the properties of microbiome and mycobiome in humans and its relevance to disease have largely been unexplored. While the interest of microbiome and malignancy over the past few years have burgeoned with advent of new technologies, no research describing the composition of mycobiome in bladder cancer has been done. Deciphering of the metagenome and its aggregate genetic information can be used to understand the functional properties and relationships between the bacteria, fungi, and cancer. ObjectiveThe aim of this project is to characterize the compositional range of the normal versus bladder cancer mycobiome of the gut. Design, setting, and participantsAn internal transcribed spacer (ITS) survey of 52 fecal samples was performed to evaluate the gut mycobiome differences between noncancer controls and bladder cancer patients. Outcome measurements and statistical analysisOur study evaluated the differences in mycobiome among patients with bladder cancer, versus matched controls. Our secondary analysis evaluated compositional differences in the gut as a function of response status with neoadjuvant chemotherapy. Data demultiplexing and classification were performed using the QIIME v.1.1.1.1 platform. The Ion Torrent–generated fungal ITS sequence data were processed using QIIME (v.1.9.1), and the reads were demultiplexed, quality filtered, and clustered into operation taxonomic units using default parameters. Alpha and beta diversity were computed and plotted in Phyloseq, principal coordinate analysis was performed on Bray-Curtis dissimilarity indices, and a one-way permutational multivariate analysis of variance was used to test for significant differences between cohorts. Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt) was applied to infer functional categories associated with taxonomic composition. Results and limitationsWe found distinctive mycobiome differences between control group (n = 32) and bladder cancer (n = 29) gut flora, and identified an increasing abundance of Tremellales, Hypocreales, and Dothideales. Significant differences in alpha and beta diversity were present between the groups (control vs bladder; p = 0.002), noting distinct compositions within each cohort. A subgroup analysis by sex and neoadjuvant chemotherapy status did not show any further differences in mycobiome composition and diversity. Our results indicate that the gut mycobiome may modulate tumor response to preoperative chemotherapy in bladder cancer patients. We propose that patients with a “favorable” mycobiome composition (eg, high diversity, and low abundance of Agaricomycetes and Saccharomycetes) may have enhanced systemic immune response to chemotherapy through antigen presentation. ConclusionsOur study is the first to characterize the enteric mycobiome in patients with bladder cancer and describe complex ecological network alterations, indicating complex bacteria-fungi interactions, particularly highlighted among patients with complete neoadjuvant chemotherapy response. Patient summaryOur study has demonstrated that the composition of stool mycobiome (fungal inhabitants of the gastrointestinal tract) in patients with bladder cancer is different from that in noncancer individuals. Furthermore, when evaluating how patients respond to chemotherapy given prior to their surgery, our study noted significant differences between patients who responded and those who did not.

Soil Microbial Community Composition and Tolerance to Contaminants in an Urban Brownfield Site

Brownfields are unused sites that contain hazardous substances due to previous commercial or industrial use. The sites are inhospitable for many organisms, but some fungi and microbes can tolerate and thrive in the nutrient-depleted and contaminated soils. However, few studies have characterized the impacts of long-term contamination on soil microbiome composition and diversity at brownfields. This study focuses on an urban brownfield—a former rail yard in Los Angeles that is contaminated with heavy metals, volatile organic compounds, and petroleum-derived pollutants. We anticipate that heavy metals and organic pollutants will shape soil microbiome diversity and that several candidate fungi and bacteria will be tolerant to the contaminants. We sequence three gene markers (16S ribosomal RNA, 18S ribosomal RNA, and the fungal internal transcribed spacer (FITS)) in 55 soil samples collected at five depths to (1) profile the composition of the soil microbiome across depths; (2) determine the extent to which hazardous chemicals predict microbiome variation; and (3) identify microbial taxonomic groups that may metabolize these contaminants. Detected contaminants in the samples included heavy metals, petroleum hydrocarbons, polycyclic aromatic hydrocarbons, and volatile organic compounds. Bacterial, eukaryotic, and fungal communities all varied with depth and with concentrations of arsenic, chromium, cobalt, and lead. 18S rRNA microbiome richness and fungal richness were positively correlated with lead and cobalt levels, respectively. Furthermore, bacterial Paenibacillus and Iamia, eukaryotic Actinochloris, and fungal Alternaria were enriched in contaminated soils compared to uncontaminated soils and represent taxa of interest for future bioremediation research. Based on our results, we recommend incorporating DNA-based multi-marker microbial community profiling at multiple sites and depths in brownfield site assessment standard methods and restoration.

DNA barcoding of fungal specimens using PacBio long-read high-throughput sequencing.

Molecular methods are increasingly used to identify species that lack conspicuous macro- or micromorphological characters. Taxonomic and ecological research teams barcode large numbers of collected voucher specimens annually. In this study we assessed the efficiency of long-read high throughput sequencing (HTS) as opposed to the traditionally used Sanger method for taxonomic identification of multiple vouchered fungal specimens. We also evaluated whether this method can provide reference information about intraindividual gene polymorphism. We developed a workflow based on a test set of 423 basidiomycete specimens (representing 195 species), the PacBio HTS method, and ribosomal rRNA operon internal transcribed spacer (ITS) and 28S rRNA gene (LSU) markers. The PacBio HTS had a higher success rate than Sanger sequencing at a comparable cost. Species identification based on PacBio reads was usually straightforward, because the dominant operational taxonomic unit (OTU) typically represented the targeted organism. The PacBio HTS also enabled us to detect widespread polymorphism within the ITS marker. We conclude that multiplex DNA barcoding of the fungal ITS and LSU markers using PacBio HTS is a useful tool for taxonomic identification of large amounts of collected voucher specimens at a competitive price. Furthermore, PacBio HTS accurately recovers various alleles and paralogues, which can provide crucial information for species delimitation and population-level studies.

Comparison of Fungal Fluorescent Staining and ITS rDNA PCR-based Sequencing with Conventional Methods for Diagnosis of Onychomycosis

Accurate identification of fungal causes for onychomycosis is essential for proper treatment. Presently available laboratory methods show unreliable sensitivity; so there is a requirement for innovative detection techniques. The aim for this work was to assess the efficiencies of fluorescent staining and internal transcribed spacer (ITS) ribosomal DNA (rDNA) polymerase chain reaction (PCR)-based sequencing in comparison to conventional techniques for diagnosis of onychomycosis. Nail specimens obtained from 100 patients with clinically- diagnosed onychomycosis were analyzed. Nail scrapings or clippings were subjected to direct microscopic examination by KOH mount, culture by using Sabouraud’s dextrose agar and histopathological examination with periodic-acid Schiff (PAS). Collected specimens were subsequently examined by fluorescent staining and PCR-based sequencing (30 specimens only) to compare the feasibility, sensitivity and diagnostic accuracy for these two methods. The most frequently isolated fungi were yeasts (39/76: 51.3%), dermatophytes (24/76; 31.6%) and non-dermatophyte molds (NDMs) (13/76; 17.1%). Mixed mycotic infections were recovered from 6% of the collected nail specimens. The positive detection rates were significantly different between KOH examinations (52%), nail plate histology (55%), fungal culture (70%) and fluorescent staining (80%). Considering fungal culture as the gold standard, the most sensitive technique was PCR (100%) followed by fluorescent staining (89%), PAS staining (69%) while the least sensitive technique was KOH mount (53%). Fluorescence staining can be used as a rapid and high-yield technique for identification of fungi in the specimens. PCR-based sequencing was highly sensitive and faster compared to culture. Whenever possible, it enables species identification with higher adequacy.

Rhizosphere analysis of field-grown Panax ginseng with different degrees of red skin provides the basis for preventing red skin syndrome

BackgroundGinseng red skin root syndrome (GRS) is one of the most common ginseng (Panax ginseng Meyer) diseases. It leads to a severe decline in P. ginseng quality and seriously affects the P. ginseng industry in China. However, as a root disease, the characteristics of the GRS rhizosphere microbiome are still unclear.MethodsThe amplicon bacterial 16 S rRNA genes and fungal ITS (Internal Transcribed Spacer) regions Illumina sequencing technology, combined with microbial diversity and composition analysis based on R software, was used to explore the relationship between soil ecological environment and GRS.ResultsThere were significant differences in the diversity and richness of soil microorganisms between the rhizosphere with different degrees of disease, especially between healthy P. ginseng (HG) and heavily diseased groups. The variation characteristics of microbial abundance in different taxa levels were analyzed. The interaction network of rhizosphere microorganisms of P. ginseng under GRS background was established. We also found that different P. ginseng rhizosphere microbial communities have multiple changes in stability and complexity through the established interaction network. Microbes closely related to potential pathogenic fungi were also identified according to the interaction network, which provided clues for looking for biological control agents. Finally, the Distance-based redundancy analysis (dbRDA) results indicated that total phosphorus (TP), available potassium (AK), available phosphorus (AP), catalase (CAT), invertase (INV) are the key factors that influence the microbial communities. Moreover, the content of these key factors in the rhizosphere was negatively correlated with disease degrees.ConclusionsIn this study, we comprehensively analyzed the rhizosphere characteristics of P. ginseng with different levels of disease, and explored the interaction relationship among microorganisms. These results provide a basis for soil improvement and biological control of field-grown in the future.

Dadaist2: A Toolkit to Automate and Simplify Statistical Analysis and Plotting of Metabarcoding Experiments.

The taxonomic composition of microbial communities can be assessed using universal marker amplicon sequencing. The most common taxonomic markers are the 16S rDNA for bacterial communities and the internal transcribed spacer (ITS) region for fungal communities, but various other markers are used for barcoding eukaryotes. A crucial step in the bioinformatic analysis of amplicon sequences is the identification of representative sequences. This can be achieved using a clustering approach or by denoising raw sequencing reads. DADA2 is a widely adopted algorithm, released as an R library, that denoises marker-specific amplicons from next-generation sequencing and produces a set of representative sequences referred to as ‘Amplicon Sequence Variants’ (ASV). Here, we present Dadaist2, a modular pipeline, providing a complete suite for the analysis that ranges from raw sequencing reads to the statistics of numerical ecology. Dadaist2 implements a new approach that is specifically optimised for amplicons with variable lengths, such as the fungal ITS. The pipeline focuses on streamlining the data flow from the command line to R, with multiple options for statistical analysis and plotting, both interactive and automatic.

Caveats of fungal barcoding: a case study in Trametes s.lat. (Basidiomycota: Polyporales) in Vietnam reveals multiple issues with mislabelled reference sequences and calls for third-party annotations

DNA barcoding using the nuclear internal transcribed spacer (ITS) has become prevalent in surveys of fungal diversity. This approach is, however, associated with numerous caveats, including the desire for speed, rather than accuracy, through the use of automated analytical pipelines, and the shortcomings of reference sequence repositories. Here we use the case of a specimen of the bracket fungus Trametes s.lat. (which includes the common and widespread turkey tail, T. versicolor) to illustrate these problems. The material was collected in Vietnam as part of a biodiversity inventory including DNA barcoding approaches for arthropods, plants and fungi. The ITS barcoding sequence of the query taxon was compared against reference sequences in GenBank and the curated fungal ITS database UNITE, using BLASTn and MegaBLAST, and was subsequently analysed in a multiple alignment-based phylogenetic context through a maximum likelihood tree including related sequences. Our results initially indicated issues with BLAST searches, including the use of pairwise local alignments and sorting through Total score and E value, rather than Percentage identity, as major shortcomings of the DNA barcoding approach. However, after thorough analysis of the results, we concluded that the single most important problem of this approach was incorrect sequence labelling, calling for the implementation of third-party annotations or analogous approaches in primary sequence repositories. In addition, this particular example revealed problems of improper fungal nomenclature, which required reinstatement of the genus name Cubamyces (= Leiotrametes), with three new combinations: C. flavidus, C. lactineus and C. menziesii. The latter was revealed as the correct identification of the query taxon, although the name did not appear among the best BLAST hits. While the best BLAST hits did correspond to the target taxon in terms of sequence data, their label names were misleading or unresolved, including [Fungal endophyte], [Uncultured fungus], Basidiomycota, Trametes cf. cubensis, Lenzites elegans and Geotrichum candidum (an unrelated ascomycetous contaminant). Our study demonstrates that accurate identification of fungi through molecular barcoding is currently not a fast-track approach that can be achieved through automated pipelines.Citation: Lucking R., Truong B. V., Huong D. T. T., Le N. H., Nguyen Q. D., Nguyen V. D., Raab-Straube E. von, Bollendorff S., Govers K. & Di Vincenzo V. 2020: Caveats of fungal barcoding: a case study in Trametes s.lat. (Basidiomycota: Polyporales) in Vietnam reveals multiple issues with mislabelled reference sequences and calls for third-party annotations. – Willdenowia 50: 383–403. doi: https://doi.org/10.3372/wi.50.50302Version of record first published online on 15 September 2020 ahead of inclusion in December 2020 issue.

Its2vec: Fungal Species Identification Using Sequence Embedding and Random Forest Classification.

Fungi play essential roles in many ecological processes, and taxonomic classification is fundamental for microbial community characterization and vital for the study and preservation of fungal biodiversity. To cope with massive fungal barcode data, tools that can implement extensive volumes of barcode sequences, especially the internal transcribed spacer (ITS) region, are necessary. However, high variation in the ITS region and computational requirements for processing high-dimensional features remain challenging for existing predictors. In this study, we developed Its2vec, a bioinformatics tool for the classification of fungal ITS barcodes to the species level. An ITS database covering more than 25,000 species in a broad range of fungal taxa was assembled. For dimensionality reduction, a word embedding algorithm was used to represent an ITS sequence as a dense low-dimensional vector. A random forest-based classifier was built for species identification. Benchmarking results showed that our model achieved an accuracy comparable to that of several state-of-the-art predictors, and more importantly, it could implement large datasets and greatly reduce dimensionality. We expect the Its2vec model to be helpful for fungal species identification and, thus, for revealing microbial community structures and in deepening our understanding of their functional mechanisms.

A 28 Day Clinical Assessment of a Lactic Acid-containing Antimicrobial Intimate Gel Wash Formulation on Skin Tolerance and Impact on the Vulvar Microbiome.

While intimate feminine hygiene products are widely used as part of daily cleansing routines, little is known about how these products impact the vulvovaginal area and its microbiome stability. This 4 week clinical study assessed tolerance of a novel gel wash containing lactic acid (pH 4.2) for external daily use when used on the external genital area and its effects on skin moisturization, vulvar skin pH, and the vulvar microbiome. After a 7 day pre-study conditioning period, 36 healthy females in three balanced age groups (18–29, 30–44, and 45–55 years) used the gel wash to cleanse their external genital area (mons pubis and vulva) and entire body at least once per day for 28 days. Skin tolerance of the gel wash was assessed by the gynecologist. Effects of the gel wash on vulvar skin microbiota were studied by performing bacterial 16S rRNA and fungal internal transcribed spacer (ITS) microbial richness and diversity analysis. Based on gynecologic assessment after 28 days of use, the gel wash showed acceptable tolerance, with no signs of increased dryness, redness, edema, itching, stinging, or burning. Use of the gel wash was associated with a significant increase in both short-term (single application) and longer-term (daily use for 28 days) skin moisturization. There was no significant change in vulvar skin pH over time with daily product use, and the gel wash did not significantly affect the natural vulvar microbiome species richness or diversity for bacteria or fungi. Results showed that this gel wash is a mild, moisturizing cleanser that maintains the natural pH and microbial diversity of vulvar skin. To our knowledge, this was the first study to assess the effect of an antimicrobial feminine gel wash on the natural pH and vulvar microbiome habitat of the skin using bacterial 16S rRNA and fungal ITS genetic sequencing techniques.

Step-by-Step Pipeline for the Ecological Analysis of Endophytic Fungi using ITS nrDNA Data.

The nuclear ribosomal DNA internal transcribed spacer (ITS) is accepted as the genetic marker or barcode of choice for the identification of fungal samples. Here, we present a protocol to analyze fungal ITS data, from quality preprocessing of raw sequences to identification of operational taxonomic units (OTUs), taxonomic classification, and assignment of functional traits. The pipeline relies on well-established and manually curated data collections, namely the UNITE database and the FUNGuild script. As an example, real ITS data from culturable endophytic fungi were analyzed, providing detailed descriptions for every step, parameter, and downstream analysis, and finishing with a phylogenetic analysis of the sequences and assigned ecological roles. This article constitutes a comprehensive guide for researchers that have little familiarity with bioinformatic analysis of essential steps required in further ecological studies of fungal communities. © 2020 by John Wiley & Sons, Inc. Basic Protocol 1: Raw sequencing data processing Support Protocol: Building a BLAST database Basic Protocol 2: Obtaining information from databases Basic Protocol 3: Phylogenetic analysis.

Patterns of PCR Amplification Artifacts of the Fungal Barcode Marker in a Hybrid Mushroom.

The polymerase chain reaction (PCR) is widely used in modern biology and medicine. However, PCR artifacts can complicate the interpretation of PCR-based results. The internal transcribed spacer (ITS) region of the ribosomal RNA gene cluster is the consensus fungal barcode marker and suspected PCR artifacts have been reported in many studies, especially for the analyses of environmental fungal samples. At present, the patterns of PCR artifacts in the whole fungal ITS region (ITS1+5.8S+ITS2) are not known. In this study, we analyzed the error rates of PCR at three template complexity levels using the divergent copies of ITS from the mushroom Agaricus subrufescens. Our results showed that PCR using the Phusion® High-Fidelity DNA Polymerase has a per nucleotide error rate of about 4 × 10–6 per replication. Among the detected mutations, transitions were much more frequent than transversions, insertions, and deletions. When divergent alleles were mixed as templates in the same reaction, a significant proportion (∼30%) of recombinant molecules were detected. The in vitro mixed-template results were comparable to those obtained from using the genomic DNA of the original mushroom specimen as template. Our results indicate that caution should be in place when interpreting ITS sequences from individual fungal specimens, especially those containing divergent ITS copies. Similar results could also happen to PCR-based analyses of other multicopy DNA fragments as well as single-copy DNA sequences with divergent alleles in diploid organisms.

The UNITE Database for Molecular Identification and for Communicating Fungal Species

UNITE (https://unite.ut.ee; Nilsson et al. 2018) is an international community of scientists and citizen scientists established in 2001. The ambition of UNITE is to develop: 1) datasets and tools for robust and reproducible molecular identification; 2) Persistent Identifiers based system for the communicating fungal species. Datasets of the nuclear ribosomal internal transcribed spacer (ITS) region, form the basis for UNITE. The current version includes nearly 1 million public fungal ITS sequences. Datasets are curated and annotated by community members. During the past 15 years, they made more than 275 000 improvements. In the complete absence of Latin names for species, UNITE offers a unique system where species hypotheses (SH) are provided with Digital Object Identifiers (DOIs). The current version 8 of UNITE offers more than 800 000 DOI-based SHs. One such SH DOI page is shown in Fig. 1. These DOI identifiers are also incorporated into the taxonomic backbone, making communication of taxa seamless in both directions. DOI identifiers of species hypotheses are also used by GBIF (Global Biodiversity Information Facility) in order to publish high-throughput sequencing taxon occurrence data in their data portal. UNITE serves as a data provider for a range of metabarcoding software pipelines and regularly exchanges data with all major fungal sequence databases and other community resources. Recent improvements include ITS-based species hypotheses for all eukaryotes and aggregation of full-length, high-quality ITS sequences generated by the PacBio Sequel system (https://www.pacb.com/products-and-services/sequel-system) from diverse material samples.