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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

Dual DNA Barcoding for the Molecular Identification of the Agents of Invasive Fungal Infections.

Invasive fungal infections, such as aspergillosis, candidiasis, and cryptococcosis, have significantly increased among immunocompromised people. To tackle these infections the first and most decisive step is the accurate identification of the causal pathogen. Routine identification of invasive fungal infections has progressed away from culture-dependent methods toward molecular techniques, including DNA barcoding, a highly efficient and widely used diagnostic technique. Fungal DNA barcoding previously relied on a single barcoding region, the internal transcribed spacer (ITS) region. However, this allowed only for 75% of all fungi to be correctly identified. As such, the translational elongation factor 1α (TEF1α) was recently introduced as the secondary barcode region to close the gap. Both loci together form the dual fungal DNA barcoding scheme. As a result, the ISHAM Barcoding Database has been expanded to include sequences for both barcoding regions to enable practical implementation of the dual barcoding scheme into clinical practice. The present study investigates the impact of the secondary barcode on the identification of clinically important fungal taxa, that have been demonstrated to cause severe invasive disease. Analysis of the barcoding regions was performed using barcoding gap analysis based on the genetic distances generated with the Kimura 2-parameter model. The secondary barcode demonstrated an improvement in identification for all taxa that were unidentifiable with the primary barcode, and when combined with the primary barcode ensured accurate identification for all taxa analyzed, making DNA barcoding an important, efficient and reliable addition to the diagnostic toolset of invasive fungal infections.

Genetic differences in Chlamydia pecorum between neighbouring sub-populations of koalas (Phascolarctos cinereus).

Chlamydiosis, caused by Chlamydia pecorum, is regarded as an important threat to koala populations. Across the koala's geographical range, disease severity associated with C. pecorum infection varies, with pathogen diversity and strain pathogenicity being likely important factors. To examine C. pecorum diversity on a sub-population level a Multi-Locus Sequence Typing (MLST) scheme, containing the housekeeping genes; gatA, oppA_3, hflX, gidA, enoA, hemN and fumC, was used to type strains from two sub-populations of koalas from the Liverpool Plains, NSW, Australia, with different disease expressions. Typing of samples from 2015 to 2017, revealed a significant association between sequence type ST 69 and clinical disease and a significant difference in sequence type frequencies between sub-populations. Sequence type ST 69 has previously been identified in both subclinical and clinically diseased koalas indicating that these markers alone are not illustrative of pathogenicity. However, recent emergence of this sequence type in a naïve population may explain the differing disease expressions. Sequence types ST 73 and ST 69 have been described in koalas across a broad geographic range, indicating multiple introduction events and/or a limited veracity of the MLST loci to explore fine scale epidemiological investigations, particularly those examining the interface between pathogenic strain and disease outcome.

Preliminary study of the oral mycobiome of children with and without dental caries.

Children's oral health is in a dire state, with dental decay (caries) being one of the most common chronic diseases. While the role of bacteria in the oral microbiome and dental caries is established, the contribution of fungi is relatively unknown. We assessed the oral mycobiome in childhood (n = 17), to determine if the composition of fungi varies between children with and without caries. Oral mycobiome composition was assessed by using Illumina MiSeq to sequence the ITS2 region, which was amplified from dental plaque. This revealed that the oral mycobiome in the investigated children contained 46 fungal species. Candida albicans was the most abundant species and was ubiquitous in all samples, indicating this species may not be involved in caries development as previously suggested. While the overall diversity of fungi was similar, independent of caries status (p > 0.05), we found caries influenced the abundance of specific fungi. Children without caries had a significantly higher abundance of 17 species compared to children with caries, which had three enriched species (p < 0.001). While the differentially abundant species between health and caries may be specific to an Australian population, our findings indicate the mycobiome plays a role in oral health.

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.

Metatranscriptomics as a tool to identify fungal species and subspecies in mixed communities - a proof of concept under laboratory conditions.

High-throughput sequencing (HTS) enables the generation of large amounts of genome sequence data at a reasonable cost. Organisms in mixed microbial communities can now be sequenced and identified in a culture-independent way, usually using amplicon sequencing of a DNA barcode. Bulk RNA-seq (metatranscriptomics) has several advantages over DNA-based amplicon sequencing: it is less susceptible to amplification biases, it captures only living organisms, and it enables a larger set of genes to be used for taxonomic identification. Using a model mock community comprising 17 fungal isolates, we evaluated whether metatranscriptomics can accurately identify fungal species and subspecies in mixed communities. Overall, 72.9% of the RNA transcripts were classified, from which the vast majority (99.5%) were correctly identified at the species level. Of the 15 species sequenced, 13 were retrieved and identified correctly. We also detected strain-level variation within the Cryptococcus species complexes: 99.3% of transcripts assigned to Cryptococcus were classified as one of the four strains used in the mock community. Laboratory contaminants and/or misclassifications were diverse, but represented only 0.44% of the transcripts. Hence, these results show that it is possible to obtain accurate species- and strain-level fungal identification from metatranscriptome data as long as taxa identified at low abundance are discarded to avoid false-positives derived from contamination or misclassifications. This study highlights both the advantages and current challenges in the application of metatranscriptomics in clinical mycology and ecological studies.

Taxonomic annotation of public fungal ITS sequences from the built environment - a report from an April 10-11, 2017 workshop (Aberdeen, UK).

Recent DNA-based studies have shown that the built environment is surprisingly rich in fungi. These indoor fungi - whether transient visitors or more persistent residents - may hold clues to the rising levels of human allergies and other medical and building-related health problems observed globally. The taxonomic identity of these fungi is crucial in such pursuits. Molecular identification of the built mycobiome is no trivial undertaking, however, given the large number of unidentified, misidentified, and technically compromised fungal sequences in public sequence databases. In addition, the sequence metadata required to make informed taxonomic decisions - such as country and host/substrate of collection - are often lacking even from reference and ex-type sequences. Here we report on a taxonomic annotation workshop (April 10-11, 2017) organized at the James Hutton Institute/University of Aberdeen (UK) to facilitate reproducible studies of the built mycobiome. The 32 participants went through public fungal ITS barcode sequences related to the built mycobiome for taxonomic and nomenclatural correctness, technical quality, and metadata availability. A total of 19,508 changes - including 4,783 name changes, 14,121 metadata annotations, and the removal of 99 technically compromised sequences - were implemented in the UNITE database for molecular identification of fungi (https://unite.ut.ee/) and shared with a range of other databases and downstream resources. Among the genera that saw the largest number of changes were Penicillium, Talaromyces, Cladosporium, Acremonium, and Alternaria, all of them of significant importance in both culture-based and culture-independent surveys of the built environment.