Fungal Internal Transcribed Spacer Sequences 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.

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.

Nutrient availability is a dominant predictor of soil bacterial and fungal community composition after nitrogen addition in subtropical acidic forests.

Nutrient addition to forest ecosystems significantly influences belowground microbial diversity, community structure, and ecosystem functioning. Nitrogen (N) addition in forests is common in China, especially in the southeast region. However, the influence of N addition on belowground soil microbial community diversity in subtropical forests remains unclear. In May 2018, we randomly selected 12 experimental plots in a Pinus taiwanensis forest within the Daiyun Mountain Nature Reserve, Fujian Province, China, and subjected them to N addition treatments for one year. We investigated the responses of the soil microbial communities and identified the major elements that influenced microbial community composition in the experimental plots. The present study included three N treatments, i.e., the control (CT), low N addition (LN, 40 kg N ha-1 yr-1), and high N addition (HN, 80 kg N ha-1 yr-1), and two depths, 0-10 cm (topsoil) and 10-20 cm (subsoil), which were all sampled in the growing season (May) of 2019. Soil microbial diversity and community composition in the topsoil and subsoil were investigated using high-throughput sequencing of bacterial 16S rDNA genes and fungal internal transcribed spacer sequences. According to our results, 1) soil dissolved organic carbon (DOC) significantly decreased after HN addition, and available nitrogen (AN) significantly declined after LN addition, 2) bacterial α-diversity in the subsoil significantly decreased with HN addition, which was affected significantly by the interaction between N addition and soil layer, and 3) soil DOC, rather than pH, was the dominant environmental factor influencing soil bacterial community composition, while AN and MBN were the best predictors of soil fungal community structure dynamics. Moreover, N addition influence both diversity and community composition of soil bacteria more than those of fungi in the subtropical forests. The results of the present study provide further evidence to support shifts in soil microbial community structure in acidic subtropical forests in response to increasing N deposition.

Diversity and composition of microbiota during fermentation of traditional Nuodeng ham.

The microbial community is one of the most important factors in shaping the characteristics of fermented food. Nuodeng ham, traditionally produced and subjected to 1-4 years of fermentation, is a dry fermented food product with cultural and economic significance to locals in southwestern China. In this study, we aimed to characterize the microbiota and physicochemical profiles of Nuodeng ham across different stages of fermentation. Ham samples from each of the four years were analyzed by sequencing bacterial 16S rRNA gene and fungal internal transcribed spacer sequence, in order to characterize the diversity and composition of their microflora. A total of 2,679,483 bacterial and 2,983,234 fungal sequences of high quality were obtained and assigned to 514 and 57 genera, respectively. Among these microbes, Staphylococcus and Candida were the most abundant genera observed in the ham samples, though samples from different years showed differences in their microbial abundance. Results of physicochemical properties (pH, water, amino acid, NaCl, nitrate and nitrite contents, and the composition of volatile compounds) revealed differences among the ham samples in the composition of volatile compounds, especially in the third year samples, in which no nitrite was detected. These results suggest that the structure and diversity of microbial communities significantly differed across different stages of fermentation. Moreover, the third year hams exhibits a unique and balanced microbial community, which might contribute to the special flavor in the green and safe food products. Thus, our study lends insights into the production of high quality Nuodeng ham.

The proportions of ectomycorrhizal roots are varied depending on the different host plant compositions in Scottish arctic/alpine coastal relict vegetation

The relative abundance of ectomycorrhizal (ECM) roots in pure and mixed stand compositions of Dryas octopetala, Salix repens and Arctostaphylos uva-ursi grown in Scottish coastal arctic/alpine relict habitat was described through ECM morphotyping and comparisons of fungal internal transcribed spacer sequences. Neither specific ECM morphotypes nor the morphotype communities were found in association with any stand compositions. The proportions of the ECM roots on S. repens , however, were significantly less in pure stand and were further decreased in mixed with A. uva-ursi . Possible factors contributing the reduction, including the effects by other host species grown in proximity, are discussed. • ECM morphotype abundance was described in three arctic/alpine host species. • Neither specific ECM morphotypes nor their communities were found. • The proportions of ECM root tips on S. repens were less compared with other two. • The ECM root tips on S. repens grown with A. uva-ursi were further reduced.

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.

A leafless epiphytic orchid, Taeniophyllum glandulosum Blume (Orchidaceae), is specifically associated with the Ceratobasidiaceae family of basidiomycetous fungi.

Leafless epiphytes in the Orchidaceae undergo a morphological metamorphosis in which the root has chloroplast-containing cortical cells and is the sole photosynthetic organ for carbon gain. All orchids are entirely dependent on mycorrhizal fungi for their carbon supply during seed germination, and this mycorrhizal association generally persists in adult plants. However, our knowledge of the mycorrhizal association of leafless epiphytic orchids remains limited, and the contribution of the mycorrhizal association to nutrient acquisition in these orchid species is largely unknown. In this study, the mycorrhizal fungi of a leafless epiphytic orchid, Taeniophyllum glandulosum, were identified molecularly using 68 mature plants and 17 seedlings. In total, 187 fungal internal transcribed spacer sequences were obtained, of which 99% were identified as Ceratobasidiaceae. These sequences were classified into five operational taxonomic units (OTUs) based on 97% sequence similarity. The most frequent sequence was OTU1, which accounted for 91% of all Ceratobasidiaceae sequences, although other phylogenetically distinct Ceratobasidiaceae fungi were detected. These results show that T. glandulosum is specifically associated with a particular group of Ceratobasidiaceae. All mycorrhizal fungi found in T. glandulosum seedlings belonged to OTU1, which was also found in adult plants on the same host tree. The mycorrhizal fungi from 13 host tree species were compared, and T. glandulosum was preferentially associated with OTU1 on 11 tree species. In conclusion, T. glandulosum is specifically associated with Ceratobasidiaceae fungi and this specific association remains throughout the orchid life cycle and is found on divergent host tree species.

The UNITE database for molecular identification of fungi: handling dark taxa and parallel taxonomic classifications.

UNITE (https://unite.ut.ee/) is a web-based database and sequence management environment for the molecular identification of fungi. It targets the formal fungal barcode—the nuclear ribosomal internal transcribed spacer (ITS) region—and offers all ∼1 000 000 public fungal ITS sequences for reference. These are clustered into ∼459 000 species hypotheses and assigned digital object identifiers (DOIs) to promote unambiguous reference across studies. In-house and web-based third-party sequence curation and annotation have resulted in more than 275 000 improvements to the data over the past 15 years. 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 redesigned handling of unclassifiable species hypotheses, integration with the taxonomic backbone of the Global Biodiversity Information Facility, and support for an unlimited number of parallel taxonomic classification systems.

Protax-fungi: a web-based tool for probabilistic taxonomic placement of fungal internal transcribed spacer sequences.

Incompleteness of reference sequence databases and unresolved taxonomic relationships complicates taxonomic placement of fungal sequences. We developed Protax-fungi, a general tool for taxonomic placement of fungal internal transcribed spacer (ITS) sequences, and implemented it into the PlutoF platform of the UNITE database for molecular identification of fungi. With empirical data on root- and wood-associated fungi, Protax-fungi reliably identified (with at least 90% identification probability) the majority of sequences to the order level but only around one-fifth of them to the species level, reflecting the current limited coverage of the databases. Protax-fungi outperformed the Sintax and Rdb classifiers in terms of increased accuracy and decreased calibration error when applied to data on mock communities representing species groups with poor sequence database coverage. We applied Protax-fungi to examine the internal consistencies of the Index Fungorum and UNITE databases. This revealed inconsistencies in the taxonomy database as well as mislabelling and sequence quality problems in the reference database. The according improvements were implemented in both databases. Protax-fungi provides a robust tool for performing statistically reliable identifications of fungi in spite of the incompleteness of extant reference sequence databases and unresolved taxonomic relationships.

Fungi as Endophytes in Artemisia thuscula: Juxtaposed Elements of Diversity and Phylogeny.

Artemisia is a plant genus highly studied for its medicinal applications. The studies on the associated fungal endophytes are scarce. Ten plants specimens of Artemisia thuscula from Tenerife and La Palma were sampled to isolate the endophytic fungi. Identification of the endophytic fungi was based on morphology, Internal Transcribed Spacer (ITS) and Large Subunit (LSU) regions sequencing and indicates 37 fungal species affiliated to 25 fungal genera. Colonization rate varied among plants (CR = 25% to 92.11%). The most dominant colonizers found were Alternaria alternata (CF = 18.71%), Neofusicoccum sp. (CF = 8.39%) and Preussia sp. (CF = 3.23). Tendency for host specificity of most endophytic fungal species was observed. Sorensen–Dice index revealed that of 45 cases in the matrix, 27 of them were of zero similarity. Further, only one case was found to have 57% similarity (TF2 and TF7) and one case with 50% similarity (TF1 and TF4). The rest of the cases had values ranging between 11% and 40% similarity. Diversity indices like Brillouin, Margalef species richness, Simpson index of diversity and Fisher’s alpha, revealed plants from La Palma with higher values than plants from Tenerife. Three nutrient media (i.e., potato dextrose agar―PDA, lignocellulose agar―LCA, and tomato juice agar―V8) were used in a case study and revealed no differences in terms of colonization rate when data was averaged. Colonization frequency showed several species with preference for nutrient medium (63% of the species were isolated from only one nutrient medium). For the phylogenetic reconstruction using the Bayesian method, 54 endophytic fungal ITS sequences and associated GenBank sequences were analyzed. Ten orders (Diaporthales, Dothideales, Botryosphaeriales, Hypocreales, Trichosphaeriales, Amphisphaeriales, Xylariales, Capnodiales, Pleosporales and Eurotiales) were recognized. Several arrangements of genera draw the attention, like Aureobasidium (Dothideales) and Aplosporella (Botryosphaeriales) which are clustered with a recent ancestor (BS = 0.97).

CONSTAX: a tool for improved taxonomic resolution of environmental fungal ITS sequences

BackgroundOne of the most crucial steps in high-throughput sequence-based microbiome studies is the taxonomic assignment of sequences belonging to operational taxonomic units (OTUs). Without taxonomic classification, functional and biological information of microbial communities cannot be inferred or interpreted. The internal transcribed spacer (ITS) region of the ribosomal DNA is the conventional marker region for fungal community studies. While bioinformatics pipelines that cluster reads into OTUs have received much attention in the literature, less attention has been given to the taxonomic classification of these sequences, upon which biological inference is dependent.ResultsHere we compare how three common fungal OTU taxonomic assignment tools (RDP Classifier, UTAX, and SINTAX) handle ITS fungal sequence data. The classification power, defined as the proportion of assigned OTUs at a given taxonomic rank, varied among the classifiers. Classifiers were generally consistent (assignment of the same taxonomy to a given OTU) across datasets and ranks; a small number of OTUs were assigned unique classifications across programs. We developed CONSTAX (CONSensus TAXonomy), a Python tool that compares taxonomic classifications of the three programs and merges them into an improved consensus taxonomy. This tool also produces summary classification outputs that are useful for downstream analyses.ConclusionsOur results demonstrate that independent taxonomy assignment tools classify unique members of the fungal community, and greater classification power is realized by generating consensus taxonomy of available classifiers with CONSTAX.

Read quality-based trimming of the distal ends of public fungal DNA sequences is nowhere near satisfactory

DNA sequences are increasingly used for taxonomic and functional assessment of environmental communities. In mycology, the nuclear ribosomal internal transcribed spacer (ITS) region is the most commonly chosen marker for such pursuits. Molecular identification is associated with many challenges, one of which is low read quality of the reference sequences used for inference of taxonomic and functional properties of the newly sequenced community (or single taxon). This study investigates whether public fungal ITS sequences are subjected to sufficient trimming in their distal (5’ and 3’) ends prior to deposition in the public repositories. We examined 86 species (and 10,584 sequences) across the fungal tree of life, and we found that on average 13.1% of the sequences were poorly trimmed in one or both of their 5’ and 3’ ends. Deposition of poorly trimmed entries was found to continue through 2016. Poorly trimmed reference sequences add noise and mask biological signal in sequence similarity searches and phylogenetic analyses, and we provide a set of recommendations on how to manage the sequence trimming problem.

Assessment of fungal diversity in a water-damaged office building

ABSTRACTRecent studies have described fungal communities in indoor environments using gene sequencing-based approaches. In this study, dust-borne fungal communities were elucidated from a water-damaged office building located in the northeastern region of the United States using internal transcribed spacer (ITS) rRNA gene sequencing. Genomic DNA was extracted from 5 mg of floor dust derived from 22 samples collected from either the lower floors (n = 8) or a top floor (n = 14) of the office building. ITS gene sequencing resolved a total of 933 ITS sequences and was clustered into 216 fungal operational taxonomic units (OTUs). Analysis of fungal OTUs at the 97% similarity threshold showed a difference between the lower and top floors that was marginally significant (p = 0.049). Species richness and diversity indices were reduced in the lower floor samples compared to the top floor samples and there was a high degree of compositional dissimilarity within and between the two different areas within the building. Fungal OTUs were placed in the phyla Ascomycota (55%), Basidiomycota (41%), Zygomycota (3%), Glomeromycota (0.4%), Chytridiomycota (0.3%), and unassigned fungi (0.5%). The Ascomycota classes with the highest relative abundances included the Dothideomycetes (30%) and Eurotiomycetes (16%). The Basidiomycota consisted of the classes Ustilaginomycetes (14%), Tremellomycetes (11%), and Agaricomycetes (8%). Sequence reads derived from the plant pathogen Ustilago syntherismae were the most abundant in the analysis as were obligate Basidiomycota yeast species that accounted for 12% and 11% of fungal ITS sequences, respectively. ITS gene sequencing provides additional insight into the diversity of fungal OTUs. These data further highlight the contribution of fungi placed in the phylum Basidiomycota, obligate yeasts, as well as xerophilic species that are typically not resolved using traditional culture methods.

Investigation of the fungal community structures of imported wheat using high-throughput sequencing technology.

This study introduced the application of high-throughput sequencing techniques to the investigation of microbial diversity in the field of plant quarantine. It examined the microbial diversity of wheat imported into China, and established a bioinformatics database of wheat pathogens based on high-throughput sequencing results. This study analyzed the nuclear ribosomal internal transcribed spacer (ITS) region of fungi through Illumina Miseq sequencing to investigate the fungal communities of both seeds and sieve-through. A total of 758,129 fungal ITS sequences were obtained from ten samples collected from five batches of wheat imported from the USA. These sequences were classified into 2 different phyla, 15 classes, 33 orders, 41 families, or 78 genera, suggesting a high fungal diversity across samples. Apairwise analysis revealed that the diversity of the fungal community in the sieve-through is significantly higher than those in the seeds. Taxonomic analysis showed that at the class level, Dothideomycetes dominated in the seeds and Sordariomycetes dominated in the sieve-through. In all, this study revealed the fungal community composition in the seeds and sieve-through of the wheat, and identified key differences in the fungal community between the seeds and sieve-through.

PIPITS: an automated pipeline for analyses of fungal internal transcribed spacer sequences from the Illumina sequencing platform.

Summary Studying fungal biodiversity using data generated from Illumina MiSeq sequencing platforms poses a number of bioinformatic challenges with the analysis typically involving a large number of tools for each analytical step from quality filtering to generating identified operational taxonomic unit (OTU) abundance tables.Here, we introduce PIPITS, an open‐source stand‐alone suite of software for automated processing of Illumina MiSeq sequences for fungal community analysis. PIPITS exploits a number of state of the art applications to process paired‐end reads from quality filtering to producing OTU abundance tables.We provide detailed descriptions of the pipeline and show its utility in the analysis of 9 396 092 sequences generated on the MiSeq platform from Illumina MiSeq. PIPITS is the first automated bioinformatics pipeline dedicated for fungal ITS sequences which incorporates ITSx to extract subregions of ITS and exploits the latest RDP Classifier to classify sequences against the curated UNITE fungal data set.

Rhizosphere microbial community manipulated by 2 years of consecutive biofertilizer application associated with banana Fusarium wilt disease suppression

In our previous work, applying biofertilizer containing Bacillus amyloliquefaciens strain NJN-6 to a banana orchard infected by a serious Fusarium wilt disease over two consecutive years effectively controlled this soil-borne disease. In this study, deep pyrosequencing of 16S ribosomal RNA (rRNA) genes and internal transcribed spacer (ITS) sequences was performed to investigate how the composition of rhizosphere microbial community responded to the application of biofertilizer (BIO), pig manure compost (PM), and chemical fertilizer (CF) and to explore the potential correlation between the microbial community composition and the Fusarium wilt disease. A total of 104,201 bacterial 16S rRNA genes and 154,953 fungal ITS sequence reads were obtained after basic quality control, and Acidobacteria, Actinobacteria, Bacteroidetes, Firmicutes, Proteobacteria, and Ascomycota were the most abundant bacterial and fungal phyla across all samples. Compared with the PM and CF control, the alpha diversity of bacteria significantly (P < 0.05) increased, whereas the value of the fungi was significantly (P < 0.05) reduced following two consecutive years of biofertilizer application. Moreover, the abundance of Acidobacteria (Gp1 and Gp3), Firmicutes, Leptosphaeria, and Phaeosphaeriopsis was significantly (P < 0.05) increased, while the abundance of Proteobacteria and Ascomycota was significantly (P < 0.05) decreased in the BIO treatment. Furthermore, the abundance of Fusarium, a causal pathogen for Fusarium wilt disease, was significantly (P < 0.05) reduced in the BIO treatment compared with the CF control and was slightly reduced (not significant) compared with the PM control. Interestingly, the disease incidence was negatively correlated with the enriched taxa of Acidobacteria (Gp1 and Gp3) and Firmicutes, Leptosphaeria, and Phaeosphaeriopsis but positively correlated with abundance of Proteobacteria, Ascomycota, Fusarium, Cylindrocarpon, Gymnascella, Monographella, Pochonia, and Sakaguchia taxa. The results from this study suggest that 2 years of biofertilizer application manipulated the composition of rhizosphere microbial community and induced the Fusarium suppression by increasing bacterial diversity and potentially stimulating microbial consortia taxa, such as Acidobacteria (Gp1 and Gp3), Firmicutes, Leptosphaeria, and Phaeosphaeriopsis.

Soil carbon content drives the biogeographical distribution of fungal communities in the black soil zone of northeast China

Black soils (Mollisols) are one of the most important soil resources for maintaining food security in China, and they are mainly distributed in northeast China. A previous comprehensive study revealed the biogeographical distribution patterns of bacterial communities in the black soil zone. In this study, we used the same soil samples and analyzed the 454 pyrosequencing data for the nuclear ribosomal internal transcribed spacer (ITS) region to examine the fungal communities in these black soils. A total of 220,812 fungal ITS sequences were obtained from 26 soil samples that were collected across the black soil zone. These sequences were classified into at least 5 phyla, 20 classes, greater than 70 orders and over 350 genera, suggesting a high fungal diversity across the black soils. The diversity of fungal communities and distribution of several abundant fungal taxa were significantly related to the soil carbon content. Non-metric multidimensional scaling and canonical correspondence analysis plots indicated that the fungal community composition was most strongly affected by the soil carbon content followed by soil pH. This finding differs from the bacterial community results, which indicated that soil pH was the most important edaphic factor in determining the bacterial community composition of these black soils. A variance partitioning analysis indicated that the geographic distance contributed 20% of the fungal community variation and soil environmental factors that were characterized explained approximately 35%. A pairwise analysis revealed that the diversity of the fungal community was relatively higher at lower latitudes, which is similar to the findings for the bacterial communities in the same region and suggests that a latitudinal gradient of microbial community diversity might occur in the black soil zone. By incorporating our previous findings on the bacterial communities, we can conclude that contemporary factors of soil characteristics are more important than historical factor of geographic distance in shaping the microbial community in the black soil zone of northeast China.

A Comprehensive, Automatically Updated Fungal ITS Sequence Dataset for Reference-Based Chimera Control in Environmental Sequencing Efforts.

The nuclear ribosomal internal transcribed spacer (ITS) region is the most commonly chosen genetic marker for the molecular identification of fungi in environmental sequencing and molecular ecology studies. Several analytical issues complicate such efforts, one of which is the formation of chimeric—artificially joined—DNA sequences during PCR amplification or sequence assembly. Several software tools are currently available for chimera detection, but rely to various degrees on the presence of a chimera-free reference dataset for optimal performance. However, no such dataset is available for use with the fungal ITS region. This study introduces a comprehensive, automatically updated reference dataset for fungal ITS sequences based on the UNITE database for the molecular identification of fungi. This dataset supports chimera detection throughout the fungal kingdom and for full-length ITS sequences as well as partial (ITS1 or ITS2 only) datasets. The performance of the dataset on a large set of artificial chimeras was above 99.5%, and we subsequently used the dataset to remove nearly 1,000 compromised fungal ITS sequences from public circulation. The dataset is available at http://unite.ut.ee/repository.php and is subject to web-based third-party curation.

A cultured endophyte community is associated with the plant Clerodendrum inerme and antifungal activity.

Fungal endophytes live in the inner tissues of Clerodendrum inerme and may be significant resources for new chemicals in drug discovery. A total of 242 endophytic fungi were recovered from 602 sample segments of C. inerme; 66 were purified. The 66 fungi belonging to 16 taxa and 11 genera (Alternaria, Nigrospora, Bartalinia, Pestalotiopsis, Fusarium, Mycoleptodiscus, Trichoderma, Phomopsis, Diaporthe, Lasiodiplodia, and Curvularia) were identified by morphological characteristics and fungal internal transcribed spacer sequences. The most abundant genera were Alternaria and Lasiodiplodia. Some of the endophytes exhibited tissue specificity. The colonization frequencies of endophytes in the stems were evidently higher than those in the roots and leaves. The crude ethyl acetate extracts were tested against 6 endophytes isolated from C. inerme. Three of 10 (33.3%) endophytes, which were identified as Phomopsis sp, Curvularia sp, and Mycoleptodiscus sp, displayed distinct antifungal activity against ≥3 tested fungi. To our knowledge, this is the first report of an endophytic community associated with C. inerme in China and its antifungal activity in vitro.