Multi-locus sequencing typing reveals geographically related intraspecies variability of Sporothrix brasiliensis.

Sporotrichosis is a subcutaneous mycosis caused by pathogenic Sporothrix species. Among them, Sporothrix brasiliensis is the main species associated with endemic regions in South America, especially Brazil. It is highly virulent and can be spread through zoonotic transmission. Molecular epidemiological surveys are needed to determine the extent of genetic variation, to investigate outbreaks, and to identify genotypes associated with antifungal resistance and susceptibility. This study investigated the sequence variation of different constitutive genes and established a novel multilocus sequence typing (MLST) scheme for S. brasiliensis. Specific primers were designed for 16 genes using Primer-BLAST software based on the genome sequences of three S. brasiliensis strains (ATCC MYA-4823, A001 and A005). Ninety-one human, animal, and environmental S. brasiliensis isolates from different Brazilian geographic regions (South, Southeast, Midwest and Northeast) andtwo isolates from Paraguay were sequenced. The loci that presented the highest nucleotide diversity (π) were selected for the MLST scheme. Among the 16 studied genetic loci, four presented increased π value and were able to distinguish all S. brasiliensis isolates into seven distinct haplotypes. The PCR conditions were standardized for four loci. Some of the obtained haplotypes were associated with the geographic origin of the strains. This study presents an important advance in the understanding of this important agent of sporotrichosis in Brazil. It significantly increased the discriminatory power for genotyping of S. brasiliensis isolates, and enabled new contributions to the epidemiological studies of this human and animal pathogen in Brazil and in other countries.

In depth search of the Sequence Read Archive database reveals global distribution of the emerging pathogenic fungus Scedosporium aurantiacum.

Scedosporium species are emerging opportunistic fungal pathogens causing various infections mainly in immunocompromised patients, but also in immunocompetent individuals, following traumatic injuries. Clinical manifestations range from local infections, such as subcutaneous mycetoma or bone and joint infections, to pulmonary colonization and severe disseminated diseases. They are commonly found in soil and other environmental sources. To date S. aurantiacum has been reported only from a handful of countries. To identify the worldwide distribution of this species we screened publicly available sequencing data from fungal metabarcoding studies in the Sequence Read Archive (SRA) of The National Centre for Biotechnology Information (NCBI) by multiple BLAST searches. S. aurantiacum was found in 26 countries and two islands, throughout every climatic region. This distribution is like that of other Scedosporium species. Several new environmental sources of S. aurantiacum including human and bovine milk, chicken and canine gut, freshwater, and feces of the giant white-tailed rat (Uromys caudimaculatus) were identified. This study demonstrated that raw sequence data stored in the SRA database can be repurposed using a big data analysis approach to answer biological questions of interest. LAY SUMMARY: To understand the distribution and natural habitat of S. aurantiacum, species-specific DNA sequences were searched in the SRA database. Our large-scale data analysis illustrates that S. aurantiacum is more widely distributed than previously thought and new environmental sources were identified.

Long-read sequencing based clinical metagenomics for the detection and confirmation of Pneumocystis jirovecii directly from clinical specimens: A paradigm shift in mycological diagnostics.

The advent of next generation sequencing technologies has enabled the characterization of the genetic content of entire communities of organisms, including those in clinical specimens, without prior culturing. The MinION from Oxford Nanopore Technologies offers real-time, direct sequencing of long DNA fragments directly from clinical samples. The aim of this study was to assess the ability of unbiased, genome-wide, long-read, shotgun sequencing using MinION to identify Pneumocystis jirovecii directly from respiratory tract specimens and to characterize the associated mycobiome. Pneumocystis pneumonia (PCP) is a life-threatening fungal disease caused by P. jirovecii. Currently, the diagnosis of PCP relies on direct microscopic or real-time quantitative polymerase chain reaction (PCR) examination of respiratory tract specimens, as P. jirovecii cannot be cultured readily in vitro. P. jirovecii DNA was detected in bronchoalveolar lavage (BAL) and induced sputum (IS) samples from three patients with confirmed PCP. Other fungi present in the associated mycobiome included known human pathogens (Aspergillus, Cryptococcus, Pichia) as well as commensal species (Candida, Malassezia, Bipolaris). We have established optimized sample preparation conditions for the generation of high-quality data, curated databases, and data analysis tools, which are key to the application of long-read MinION sequencing leading to a fundamental new approach in fungal diagnostics.

Database establishment for the secondary fungal DNA barcode translational elongation factor 1α (TEF1α) 1.

With new or emerging fungal infections, human and animal fungal pathogens are a growing threat worldwide. Current diagnostic tools are slow, non-specific at the species and subspecies levels, and require specific morphological expertise to accurately identify pathogens from pure cultures. DNA barcodes are easily amplified, universal, short species-specific DNA sequences, which enable rapid identification by comparison with a well-curated reference sequence collection. The primary fungal DNA barcode, ITS region, was introduced in 2012 and is now routinely used in diagnostic laboratories. However, the ITS region only accurately identifies around 75% of all medically relevant fungal species, which has prompted the development of a secondary barcode to increase the resolution power and suitability of DNA barcoding for fungal disease diagnostics. The translational elongation factor 1α (TEF1α) was selected in 2015 as a secondary fungal DNA barcode, but it has not been implemented into practice, due to the absence of a reference database. Here, we have established a quality-controlled reference database for the secondary barcode that together with the ISHAM-ITS database, forms the ISHAM barcode database, available online at http://its.mycologylab.org/ . We encourage the mycology community for active contributions.

Scedosporium and Lomentospora: an updated overview of underrated opportunists.

Species of Scedosporium and Lomentospora are considered as emerging opportunists, affecting immunosuppressed and otherwise debilitated patients, although classically they are known from causing trauma-associated infections in healthy individuals. Clinical manifestations range from local infection to pulmonary colonization and severe invasive disease, in which mortality rates may be over 80%. These unacceptably high rates are due to the clinical status of patients, diagnostic difficulties, and to intrinsic antifungal resistance of these fungi. In consequence, several consortia have been founded to increase research efforts on these orphan fungi. The current review presents recent findings and summarizes the most relevant points, including the Scedosporium/Lomentospora taxonomy, environmental distribution, epidemiology, pathology, virulence factors, immunology, diagnostic methods, and therapeutic strategies.

Online Databases for Taxonomy and Identification of Pathogenic Fungi and Proposal for a Cloud-Based Dynamic Data Network Platform.

The increase in public online databases dedicated to fungal identification is noteworthy. This can be attributed to improved access to molecular approaches to characterize fungi, as well as to delineate species within specific fungal groups in the last 2 decades, leading to an ever-increasing complexity of taxonomic assortments and nomenclatural reassignments. Thus, well-curated fungal databases with substantial accurate sequence data play a pivotal role for further research and diagnostics in the field of mycology. This minireview aims to provide an overview of currently available online databases for the taxonomy and identification of human and animal-pathogenic fungi and calls for the establishment of a cloud-based dynamic data network platform.

International Society of Human and Animal Mycology (ISHAM)-ITS reference DNA barcoding database--the quality controlled standard tool for routine identification of human and animal pathogenic fungi.

Human and animal fungal pathogens are a growing threat worldwide leading to emerging infections and creating new risks for established ones. There is a growing need for a rapid and accurate identification of pathogens to enable early diagnosis and targeted antifungal therapy. Morphological and biochemical identification methods are time-consuming and require trained experts. Alternatively, molecular methods, such as DNA barcoding, a powerful and easy tool for rapid monophasic identification, offer a practical approach for species identification and less demanding in terms of taxonomical expertise. However, its wide-spread use is still limited by a lack of quality-controlled reference databases and the evolving recognition and definition of new fungal species/complexes. An international consortium of medical mycology laboratories was formed aiming to establish a quality controlled ITS database under the umbrella of the ISHAM working group on "DNA barcoding of human and animal pathogenic fungi." A new database, containing 2800 ITS sequences representing 421 fungal species, providing the medical community with a freely accessible tool at http://www.isham.org/ and http://its.mycologylab.org/ to rapidly and reliably identify most agents of mycoses, was established. The generated sequences included in the new database were used to evaluate the variation and overall utility of the ITS region for the identification of pathogenic fungi at intra-and interspecies level. The average intraspecies variation ranged from 0 to 2.25%. This highlighted selected pathogenic fungal species, such as the dermatophytes and emerging yeast, for which additional molecular methods/genetic markers are required for their reliable identification from clinical and veterinary specimens.

Phoma-like fungi on soybeans.

Numerous coelomycetous fungi classified in Ascochyta, Phoma and Phyllosticta, and lately established and/or re-classified genera and species, namely Boeremia and Peyronellaea have been recorded from spots on leaves and pods of soybeans. These rarely observed pathogens are cosmopolitan, ubiquitous species on diseased and dead plant materials, and define frequently as weak or opportunistic parasites. Based on the Genealogical Concordance Phylogenetic Species Recognition, the authors summarize the re-evaluation of the taxonomic status of Phoma sojicola (syn. Ascochyta sojicola) and Phyllosticta sojicola. Inspite of the former delimitation of Ph. sojicola based on small differences in morphological features, it has proved to be identical to Peyronellaea pinodella (syn. Phoma pinodella). Similarly, it was also confirmed that Ph. sojicola was identical to Boeremia exigua var. exigua (syn. Phoma exigua var. exigua). The authors and co-workers contributed to the identification of Phoma-like fungi by combined conventional and molecular methods. Protein-encoding genes (TEF1 and ß-tubulin) were successfully applied within the Phoma genus to infer phylogenetic relationships.

Advances in taxonomy of genus phoma: polyphyletic nature and role of phenotypic traits and molecular systematics.

Phoma is a highly polyphyletic genus with its unclear species boundaries. The conventional system of identification is functional but it has its limitations. Besides morphological studies, chemotaxonomy, secondary metabolite and protein profiling have been assessed for the classification and identification of these fungi. Molecular datasets have provided a better outlook towards the phylogenetic and evolutionary trends of Phoma. Molecular markers such as ITS-rDNA, tubulin, actin, translation elongation factor have been widely used by the taxonomists to demarcate species. However, outcomes gained up till now represent preliminary step towards the study of Phoma systematics and a combined approach would be beneficial in the understanding of this polyphyletic group members. Lately, on the base of molecular phylogeny of the type species of the seven Phoma sections a new teleomorph family, Didymellaceae has been established, besides the Phaeosphaeriaceae related to sect. Paraphoma anamorphs, and the Leptosphaeriaceae to sect. Heterospora anamorphs. The estimated ratio is about 70 % of the recognized Phoma-like species can be associated with the Didymellaceae ascomycetous family.

Targeted sequencing analysis pipeline for species identification of human pathogenic fungi using long-read nanopore sequencing.

Among molecular-based techniques for fungal identification, Sanger sequencing of the primary universal fungal DNA barcode, the internal transcribed spacer (ITS) region (ITS1, 5.8S, ITS2), is commonly used in clinical routine laboratories due to its simplicity, universality, efficacy, and affordability for fungal species identification. However, Sanger sequencing fails to identify mixed ITS sequences in the case of mixed infections. To overcome this limitation, different high-throughput sequencing technologies have been explored. The nanopore-based technology is now one of the most promising long-read sequencing technologies on the market as it has the potential to sequence the full-length ITS region in a single read. In this study, we established a workflow for species identification using the sequences of the entire ITS region generated by nanopore sequencing of both pure yeast isolates and mocked mixed species reads generated with different scenarios. The species used in this study included Candida albicans (n = 2), Candida tropicalis (n = 1), Nakaseomyces glabratus (formerly Candida glabrata) (n = 1), Trichosporon asahii (n = 2), Pichia kudriavzevii (formerly Candida krusei) (n = 1), and Cryptococcus neoformans (n = 1). Comparing various methods to generate the consensus sequence for fungal species identification, the results from this study indicate that read clustering using a modified version of the NanoCLUST pipeline is more sensitive than Canu or VSEARCH, as it classified species accurately with a lower abundance cluster of reads (3% abundance compared to 10% with VSEARCH). The modified NanoCLUST also reduced the number of classified clusters compared to VSEARCH, making the subsequent BLAST+ analysis faster. Subsampling of the datasets, which reduces the size of the datasets by approximately tenfold, did not significantly affect the identification results in terms of the identified species name, percent identity, query coverage, percentage of reads in the classified cluster, and the number of clusters. The ability of the method to distinguish mixed species within sub-populations of large datasets has the potential to aid computer analysis by reducing the required processing power. The herein presented new sequence analysis pipeline will facilitate better interpretation of fungal sequence data for species identification.

Finding a Needle in a Haystack - In Silico Search for Environmental Traces of Candida auris.

Candida auris, first described from an ear infection in Japan, is an important emerging multidrug-resistant pathogenic fungal species. Its environmental niche remained a mystery until its isolation from the wetlands of the Andaman Islands, India, in 2020. We screened a subset of the world's largest sequence repository, the Sequence Read Archive at National Center for Biotechnology Information, using a DNA metabarcoding approach based on either the internal transcribed spacer (ITS)1 or ITS2 region of the official primary fungal DNA barcode, to identify potential environmental sources of C. auris. Our search identified 34 matches with partial C. auris ITS sequences from seven metabarcoding studies, providing wider evidence for the presence of C. auris outside human-maintained facilities.

Inferring Species Compositions of Complex Fungal Communities from Long- and Short-Read Sequence Data.

The kingdom Fungi is highly diverse in morphology and ecosystem function. Yet fungi are challenging to characterize as they can be difficult to culture and morphologically indistinct. Overall, their description and analysis lag far behind other microbes such as bacteria. Classification of species via high-throughput sequencing is increasingly becoming the norm for pathogen detection, microbiome studies, and environmental monitoring. With the rapid development of sequencing technologies, however, standardized procedures for taxonomic assignment of long sequence reads have not yet been well established. Focusing on nanopore sequencing technology, we compared classification and community composition analysis pipelines using shotgun and amplicon sequencing data generated from mock communities comprising 43 fungal species. We show that regardless of the sequencing methodology used, the highest accuracy of species identification was achieved by sequence alignment against a fungal-specific database. During the assessment of classification algorithms, we found that applying cutoffs to the query coverage of each read or contig significantly improved the classification accuracy and community composition analysis without major data loss. We also generated draft genome assemblies for three fungal species from nanopore data which were absent from genome databases. Our study improves sequence-based classification and estimation of relative sequence abundance using real fungal community data and provides a practical guide for the design of metagenomics analyses focusing on fungi. IMPORTANCE Our study is unique in that it provides an in-depth comparative study of a real-life complex fungal community analyzed with multiple long- and short-read sequencing approaches. These technologies and their application are currently of great interest to diverse biologists as they seek to characterize the community compositions of microbiomes. Although great progress has been made on bacterial community compositions, microbial eukaryotes such as fungi clearly lag behind. Our study provides a detailed breakdown of strategies to improve species identification with immediate relevance to real-world studies. We find that real-life data sets do not always behave as expected, distinct from reports based on simulated data sets.

Environmental Isolation of Sporothrix brasiliensis in an Area With Recurrent Feline Sporotrichosis Cases.

Sporotrichosis has been expanding throughout the Brazilian territory in recent years. New outbreaks have emerged, and consequently, the sporotrichosis agents, mainly Sporothrix brasiliensis, should remain in the environment somehow. Therefore, the aim of this study was to investigate the presence of Sporothrix spp. in the environment from an area of ​​the Rio de Janeiro state, Brazil, with recurrent cases of human and animal sporotrichosis. Abandoned demolition timber wood samples were collected in the garden of a house where the cases of human and feline sporotrichosis have occurred in the last 10 years. The environmental survey revealed a Sporothrix spp. colony from the serial dilution cultures of one abandoned demolition wood sample. In addition, a fungal strain isolated from a cat with skin lesions that lived in the house was also included in the study. The species-specific PCR, and calmodulin partial sequencing identified the environmental and cat isolates as S. brasiliensis. Furthermore, the phylogenetic analysis performed with the partial sequences of internal transcribed spacer region and constitutive genes (calmodulin, ß-tubulin, and chitin synthase) showed high similarity between environmental and cat isolates from the same geographic region. Moreover, the antifungal susceptibility test revealed that the minimal inhibitory concentration of itraconazole from the environment isolate was lower than the cat isolate, while amphotericin B and terbinafine were similar. Our results show that S. brasiliensis is able to maintain itself in the environmental material for years. With this, we corroborate that the eco-epidemiology of sporotrichosis is not well understood, and despite the major occurrence of S. brasiliensis in Brazil, it is rarely isolated from the environment.

Long-Reads-Based Metagenomics in Clinical Diagnosis With a Special Focus on Fungal Infections.

Identification of the causative infectious agent is essential in the management of infectious diseases, with the ideal diagnostic method being rapid, accurate, and informative, while remaining cost-effective. Traditional diagnostic techniques rely on culturing and cell propagation to isolate and identify the causative pathogen. These techniques are limited by the ability and the time required to grow or propagate an agent in vitro and the facts that identification based on morphological traits are non-specific, insensitive, and reliant on technical expertise. The evolution of next-generation sequencing has revolutionized genomic studies to generate more data at a cheaper cost. These are divided into short- and long-read sequencing technologies, depending on the length of reads generated during sequencing runs. Long-read sequencing also called third-generation sequencing emerged commercially through the instruments released by Pacific Biosciences and Oxford Nanopore Technologies, although relying on different sequencing chemistries, with the first one being more accurate both platforms can generate ultra-long sequence reads. Long-read sequencing is capable of entirely spanning previously established genomic identification regions or potentially small whole genomes, drastically improving the accuracy of the identification of pathogens directly from clinical samples. Long-read sequencing may also provide additional important clinical information, such as antimicrobial resistance profiles and epidemiological data from a single sequencing run. While initial applications of long-read sequencing in clinical diagnosis showed that it could be a promising diagnostic technique, it also has highlighted the need for further optimization. In this review, we show the potential long-read sequencing has in clinical diagnosis of fungal infections and discuss the pros and cons of its implementation.

Fungal taxonomy and sequence-based nomenclature.

The identification and proper naming of microfungi, in particular plant, animal and human pathogens, remains challenging. Molecular identification is becoming the default approach for many fungal groups, and environmental metabarcoding is contributing an increasing amount of sequence data documenting fungal diversity on a global scale. This includes lineages represented only by sequence data. At present, these taxa cannot be formally described under the current nomenclature rules. By considering approaches used in bacterial taxonomy, we propose solutions for the nomenclature of taxa known only from sequences to facilitate consistent reporting and communication in the literature and public sequence repositories.

Consensus Multilocus Sequence Typing Scheme for Pneumocystis jirovecii.

Pneumocystis jirovecii is an opportunistic human pathogenic fungus causing severe pneumonia mainly in immunocompromised hosts. Multilocus sequence typing (MLST) remains the gold standard for genotyping of this unculturable fungus. However, the lack of a consensus scheme impedes a global comparison, large scale population studies and the development of a global MLST database. To overcome this problem this study compared all genetic regions (19 loci) currently used in 31 different published Pneumocystis MLST schemes. The most diverse/commonly used eight loci, ß-TUB, CYB, DHPS, ITS1, ITS1/2, mt26S and SOD, were further assess for their ability to be successfully amplified and sequenced, and for their discriminatory power. The most successful loci were tested to identify genetically related and unrelated cases. A new consensus MLST scheme consisting of four genetically independent loci: ß-TUB, CYB, mt26S and SOD, is herein proposed for standardised P. jirovecii typing, successfully amplifying low and high fungal burden specimens, showing adequate discriminatory power, and correctly identifying suspected related and unrelated isolates. The new consensus MLST scheme, if accepted, will for the first time provide a powerful tool to investigate outbreak settings and undertake global epidemiological studies shedding light on the spread of this important human fungal pathogen.

Genetic Heterogeneity of Australian Candida auris Isolates: Insights From a Nonoutbreak Setting Using Whole-Genome Sequencing.

Whole-genome sequencing clustered Australian Candida auris isolates from sporadic cases within clade III. Case isolates were genomically distinct; however, unexpectedly, those from 1 case comprised 2 groups separated by >60 single nucleotide polymorphisms (SNPs) with no isolate being identical, in contrast to outbreaks where isolates from any 1 individual have differed by <3 SNPs. Multidrug resistance was absent. High within-host genetic heterogeneity should be considered when investigating C. auris infections.

Unambiguous identification of fungi: where do we stand and how accurate and precise is fungal DNA barcoding?

True fungi (Fungi) and fungus-like organisms (e.g. Mycetozoa, Oomycota) constitute the second largest group of organisms based on global richness estimates, with around 3 million predicted species. Compared to plants and animals, fungi have simple body plans with often morphologically and ecologically obscure structures. This poses challenges for accurate and precise identifications. Here we provide a conceptual framework for the identification of fungi, encouraging the approach of integrative (polyphasic) taxonomy for species delimitation, i.e. the combination of genealogy (phylogeny), phenotype (including autecology), and reproductive biology (when feasible). This allows objective evaluation of diagnostic characters, either phenotypic or molecular or both. Verification of identifications is crucial but often neglected. Because of clade-specific evolutionary histories, there is currently no single tool for the identification of fungi, although DNA barcoding using the internal transcribed spacer (ITS) remains a first diagnosis, particularly in metabarcoding studies. Secondary DNA barcodes are increasingly implemented for groups where ITS does not provide sufficient precision. Issues of pairwise sequence similarity-based identifications and OTU clustering are discussed, and multiple sequence alignment-based phylogenetic approaches with subsequent verification are recommended as more accurate alternatives. In metabarcoding approaches, the trade-off between speed and accuracy and precision of molecular identifications must be carefully considered. Intragenomic variation of the ITS and other barcoding markers should be properly documented, as phylotype diversity is not necessarily a proxy of species richness. Important strategies to improve molecular identification of fungi are: (1) broadly document intraspecific and intragenomic variation of barcoding markers; (2) substantially expand sequence repositories, focusing on undersampled clades and missing taxa; (3) improve curation of sequence labels in primary repositories and substantially increase the number of sequences based on verified material; (4) link sequence data to digital information of voucher specimens including imagery. In parallel, technological improvements to genome sequencing offer promising alternatives to DNA barcoding in the future. Despite the prevalence of DNA-based fungal taxonomy, phenotype-based approaches remain an important strategy to catalog the global diversity of fungi and establish initial species hypotheses.

Phoma Saccardo: distribution, secondary metabolite production and biotechnological applications.

Phoma Sacc. is an ubiquitous fungus, which has been reported from plants, soil, human beings, animals, and air. Some species of Phoma like P. sorghina, P. herbarum, P. exigua var. exigua, P. macrostoma, P. glomerata, Phoma macdonaldii, Phoma tracheiphila, Phoma proboscis, P. multirostrata, and Phoma foveata secrete phytotoxin and anthraquinone pigments as secondary metabolites, which have great potential for the biological control of weeds, and can be exploited for the production of mycopesticides, agrophytochemicals, and dyes. Some other species produce pharmaceutically active metabolites, viz., Sirodesmins, Phomenoic acid, Phomenolactone, Phomadecalins, Phomactin A, Phomasetin, Squalestatin-1 (S1), and Squalestatin-2 (S2). The secondary metabolites secreted by some species of Phoma are antitumor, antimicrobial, and anti-HIV. Equisetin and Phomasetin obtained from species of Phoma are useful against AIDS. The main goal of the present review is to discuss secondary metabolite production by species of Phoma and their utilization as antibiotics and as biocontrol agents.

The mycobiome of Australian tree hollows in relation to the Cryptococcus gattii and C. neoformans species complexes.

Cryptococcosis is a fungal infection caused by members of the Cryptococcus gattii and C. neoformans species complexes. The C. gattii species complex has a strong environmental association with eucalypt hollows (particularly Eucalyptus camaldulensis), which may present a source of infection. It remains unclear whether a specific mycobiome is required to support its environmental survival and growth. Conventional detection of environmental Cryptococcus spp. involves culture on differential media, such as Guizotia abyssinica seed agar. Next-generation sequencing (NGS)-based culture-independent identification aids in contextualising these species in the environmental mycobiome. Samples from 23 Australian tree hollows were subjected to both culture- and amplicon-based metagenomic analysis to characterize the mycobiome and assess relationships between Cryptococcus spp. and other fungal taxa. The most abundant genera detected were Coniochaeta, Aspergillus, and Penicillium, all being commonly isolated from decaying wood. There was no correlation between the presence of Cryptococcus spp. in a tree hollow and the presence of any other fungal genus. Some differences in the abundance of numerous taxa were noted in a differential heat tree comparing samples with or without Cryptococcus-NGS reads. The study expanded the known environmental niche of the C. gattii and C. neoformans species complexes in Australia with detections from a further five tree species. Discrepancies between the detection of Cryptococcus spp. using culture or NGS suggest that neither is superior per se and that, rather, these methodologies are complementary. The inherent biases of amplicon-based metagenomics require cautious interpretation of data through consideration of its biological relevance.