Search
Close
Search
Advanced Search
Search Menu

Abstract

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.

fungal identification, DNA barcoding, ITS region, reference ITS database, intraspecies/interspecies genetic diversity

Introduction

The number of human and animal fungal infections, ranging from superficial infections of the nails and skin, through mucocutaneous candidiasis to invasive fungal infections, have significantly increased over the last three decades, causing serious public health burdens and increased risk of biodiversity loss among animal species [1,2]. In humans, superficial infections affect an estimated 25% ( = 1.7 billion) individuals world-wide. Oropharyngeal or genital mucosal infections are also common and can be disabling. For example, an estimated 75% of women of childbearing age suffering from vulvovaginitis, mainly caused by Candida species [3], which are the third most common opportunistic fungal disease agents after Aspergillus spp. worldwide [1]. Invasive fungal diseases are of great concern, due to their high mortality that can exceed 50%. More than 90% of fungal-related deaths are caused by four fungal genera: Aspergillus, Candida, Cryptococcus, and Pneumocystis [1,4,5]. Delays in diagnosis are not only associated with high mortality but also severe organ dysfunction, for example, respiratory failure (endemic fungal infections and chronic pulmonary aspergillosis), neurologic deficits (endemic fungal infections and cryptococcosis) [6], blindness and visual impairment (fungal keratitis) [7]. To better understand, control, and treat these diseases, more rapid and accurate identification of the causal agents is essential.

DNA barcoding, first proposed by Hebert et al. [8], utilizes DNA sequences to standardize the identification of organisms from all kingdoms to the species level by comparison to a reference collection of well-identified species. The principle behind barcoding is that species identification must be accurate, fast, cost-effective, culture independent, universally accessible, and feasible for nonexperts [9]. As a consequence, its popularity as a species identification tool has drastically increased. Barcodes are short diverse genetic sequences (500–800 bp) that are flanked by conserved regions allowing for the design of universal primers. From a pragmatic perspective, a universal sequence suitable for all kingdoms would be ideal, but the identification of a universal genetic region for a wide range of taxa remains elusive. The key concepts underlying barcoding are that the interspecies distances should exceed intraspecies distances, creating a barcoding gap [10], and that identification is straightforward when a sequence is unique to a single species and constant within each species [8,11,12]. The most important question in barcoding is: How accurate and reliable are the delineation and identification of a species using a single gene?

The correct identification of fungi is essential for many biological purposes, such as the assessment of biodiversity, taxonomy and species conservation [9,13]. It is mandatory for clinical diagnosis and early initiation of appropriate antifungal therapy. Traditional identification based on morphology and biochemistry of pathogenic fungi is time-consuming and requires a certain level of morphological and taxonomical expertise. To overcome these limitations, DNA barcoding was evaluated in fungi, targeting numerous genetic loci, including COX1 [14], protein-coding genes like RNA polymerase I and II [15–19], partial translation elongation factor 1-α [20–22], β-tubulin [23], and the internal transcribed spacer (ITS) regions [24,25]. The protein coding genes have proven to be a powerful tool for species delimitation, providing a high level of phylogenetic resolution and information [21,26,27]. However, the primers used to amplify these regions are usually restricted to specific taxa and amplification can often be problematic [16]. In contrast, the ITS regions are easily amplified with universal primers that are compatible among most fungal species. It has shown sufficient genetic variability for identification at interspecies level, and has been adopted as the official standard barcoding region for fungi [28]. However, use of the ITS region as a barcode has been criticized by Kiss [29] because of its inability to distinguish many closely related fungal species. In addition, for some fungi, the ITS regions alone do not provide accurate identification to species level [30]. In some groups of fungi (Aspergillus, Colletotrichum) the interspecies variation is insignificant [31,32] and in other groups (Glomeromycota, Chytridiomycota) the diversity within species is too high [33,34] Fungal genomes may contain more than 200 copies of the ribosomal region [35,36] dispersed over one or more chromosomal locations [37]. This results in polymorphism within a genome of one individual [38,39]. Intragenomic diversity is mainly explained by concerted evolutionary processes, for example, unequal crossing over between repeat units, gene conversion or gene amplification [39,40].

Despite these limitations the ITS region has been used in molecular identification and phylogenetic studies of human pathogenic fungi [41–48] long before its selection as the official fungal DNA barcode. The ITS sequences in publicly accessible databases are used routinely by the medical community to identify fungi at the species level on the basis of matching sequences. However, its widespread application has been compromised by the deposition of incorrectly identified or incomplete sequences in the commonly used public databases of the International Nucleotide Sequence Database Collaboration (INSDC) [49]. This includes GenBank [50], at the National Center for Biotechnology Information (NCBI), which is the major nucleotide sequence depository and is widely utilised by clinical microbiologists and the scientific community [51,52]. Because GenBank acts primarily as an archive, many sequences submitted have been annotated with incorrect or poorly defined species names. It has also been shown that more than 10% of the publicly available fungal ITS sequences were annotated incorrectly at species level [53]. As a consequence, a number of curated ITS databases have been created to ensure the correct identification of fungal species, for example, within the Barcode of Life Data System (BOLD) [54] and UNITE [55]. Partially in response to requests to allow third party annotation of GenBank records NCBI has also initiated a curated database RefSeq Targeted Loci (RTL) [56] that will provide a limited set of curated sequences obtained from type and verified material [57]. In a second, broader approach NCBI is currently annotating the type material associated with taxonomic names. This will allow type related searches to be conducted across multiple sequence markers or whole genomes [58]. Other reference databases are available for specific taxonomic groups, for example, Fusarium [59] and Aspergillus [60]. The deficiency of these reference databases with respect to human pathogenic fungi is the limited number of medically important fungal species contained within them. The demand for curated, reliable reference databases has increased significantly due to diminishing expertise in fungal morphology and its increasing replacement by the use of sequencing in fungal diagnostic laboratories.

To address these issues, a working group of the International Society for Human and Animal Mycology (ISHAM) on “Barcoding of Medical Fungi” was established in 2011 [61]. The working group identified the need to: (a) generate a medical barcode database by incorporating existing fungal group-specific databases; (b) extend the number of quality-controlled ITS sequences to cover all medically important fungal species; (c) evaluate the value of ITS as a barcode at intra-and interspecies level; (d) eventually incorporate these sequences into the BOLD database; (e) UNITE; and (f) achieve a species status as “quality controlled reference sequences” for those sequences within RTL at NCBI.

The main objective of this study was to generate a publicly available, quality-controlled, ITS reference database for human and animal pathogenic fungal species and to evaluate the applicability of ITS sequences (the official barcode for fungi) as a genetic marker for species identification. The secondary aim was to highlight fungal taxa where additional genetic sequence information is recommended beyond the ITS for a more accurate identification.

Materials and methods

Generating the database

The ISHAM-ITS reference database is a result of an international collaboration between 14 medical mycology laboratories representing three continents (Table 1). The contributors provided a total of 2945 ITS sequences. Species were identified based on polyphasic identification including morphology, biochemical and physiological tests when appropriate and sequencing. After collecting all the data, the overall identity of sequences obtained from more than two strains per species was determined, including available type strains. In the case of species with less than two strains, trace files were checked for the quality and integrity of sequences. A total of 145 sequences that did not meet the inclusion criteria were discarded, as well as sequences that were misidentified or not identified to species level. Each taxon was provided with the taxonomic name, taking into account the “One Name = One Fungus” concept of the International Code of Nomenclature for algae, fungi and plants (ICN) [62]. The current taxonomical names were provided by using online nomenclature data resources such as MycoBank [63,64], Index Fungorum [65], the latest edition of The Yeasts [66], as well as the latest publications and consulting taxonomical experts of specific taxa. Where possible, former anamorph or teleomorph names and the most-used synonyms were also listed to facilitate reading for clinicians.

Table 1.

Institutions, number of quality controlled ITS sequences, and represented number of species contributed to the ISHAM-ITS reference database.

Number ofNumber of
Institutionsstrainsspecies
Molecular Mycology Research Laboratory, CIDM, Sydney Medical School-Westmead Hospital, The University of Sydney, WMI, Australia663173
Mycology Research Laboratory, Department of Microbiology, Medical School, the University of Athens Hellenic Collection of Pathogenic Fungi (UOA/HCPF), National and Kapodistrian University of Athens, Athens, Greece417117
Unitat de Microbiologia, Facultat de Medicina i Ciències de la Salut, IISPV, Universitat Rovira i Virgili, Reus, Spain36052
CBS-KNAW, Fungal Biodiversity Centre, Utrecht, The Netherlands35233
BCCM/IHEM, Biomedical fungi and yeasts collection, Scientific Institute of Public Health, Brussels, Belgium28992
Institut Pasteur, National Reference Center of Invasive Mycosis and Antifungals, Molecular Mycology Unit, CNRS URA 3012, Paris, France223106
Parasitology - Mycology, APHM, CHU Timone-Adultes, Marseille, France; Aix-Marseille University, UMR MD3 IP-TPT, Marseille, France14655
Mycology Laboratory, Department of Microbiology and Infectious Diseases, PathWest Laboratory Medicine WA, QEII Medical Centre, Nedlands, Western Australia, Australia9931
BDEEP-EA4547, CIIL, Institut Pasteur de Lille, CHU de Lille, Université de Lille2, Lille, France7318
Laboratório Especial de Micologia, Escola Paulista de Medicina, Universidade Federal de São Paulo, São Paulo, Brazil5818
Instituto de Pesquisa Clínica Evandro Chagas (IPEC) - Fundação Oswaldo Cruz (Fiocruz), Rio de Janeiro, Brazil501
Facultad de Medicina, Departamento de Microbiología y Parasitología (Unidad de Micología), Universidad Nacional Autónoma de México, Ciudad de México, México393
Centre of Molecular and Environmental Biology (CBMA), Biology Department, School of Sciences, University of Minho, Braga, Portugal2210
Universidade Federal de Goiás, Instituto de Ciências Biológicas, Laboratório de Biologia Molecular, Goiânia, Goiás, Brazil92
Number ofNumber of
Institutionsstrainsspecies
Molecular Mycology Research Laboratory, CIDM, Sydney Medical School-Westmead Hospital, The University of Sydney, WMI, Australia663173
Mycology Research Laboratory, Department of Microbiology, Medical School, the University of Athens Hellenic Collection of Pathogenic Fungi (UOA/HCPF), National and Kapodistrian University of Athens, Athens, Greece417117
Unitat de Microbiologia, Facultat de Medicina i Ciències de la Salut, IISPV, Universitat Rovira i Virgili, Reus, Spain36052
CBS-KNAW, Fungal Biodiversity Centre, Utrecht, The Netherlands35233
BCCM/IHEM, Biomedical fungi and yeasts collection, Scientific Institute of Public Health, Brussels, Belgium28992
Institut Pasteur, National Reference Center of Invasive Mycosis and Antifungals, Molecular Mycology Unit, CNRS URA 3012, Paris, France223106
Parasitology - Mycology, APHM, CHU Timone-Adultes, Marseille, France; Aix-Marseille University, UMR MD3 IP-TPT, Marseille, France14655
Mycology Laboratory, Department of Microbiology and Infectious Diseases, PathWest Laboratory Medicine WA, QEII Medical Centre, Nedlands, Western Australia, Australia9931
BDEEP-EA4547, CIIL, Institut Pasteur de Lille, CHU de Lille, Université de Lille2, Lille, France7318
Laboratório Especial de Micologia, Escola Paulista de Medicina, Universidade Federal de São Paulo, São Paulo, Brazil5818
Instituto de Pesquisa Clínica Evandro Chagas (IPEC) - Fundação Oswaldo Cruz (Fiocruz), Rio de Janeiro, Brazil501
Facultad de Medicina, Departamento de Microbiología y Parasitología (Unidad de Micología), Universidad Nacional Autónoma de México, Ciudad de México, México393
Centre of Molecular and Environmental Biology (CBMA), Biology Department, School of Sciences, University of Minho, Braga, Portugal2210
Universidade Federal de Goiás, Instituto de Ciências Biológicas, Laboratório de Biologia Molecular, Goiânia, Goiás, Brazil92
Open in new tab
Table 1.

Institutions, number of quality controlled ITS sequences, and represented number of species contributed to the ISHAM-ITS reference database.

Number ofNumber of
Institutionsstrainsspecies
Molecular Mycology Research Laboratory, CIDM, Sydney Medical School-Westmead Hospital, The University of Sydney, WMI, Australia663173
Mycology Research Laboratory, Department of Microbiology, Medical School, the University of Athens Hellenic Collection of Pathogenic Fungi (UOA/HCPF), National and Kapodistrian University of Athens, Athens, Greece417117
Unitat de Microbiologia, Facultat de Medicina i Ciències de la Salut, IISPV, Universitat Rovira i Virgili, Reus, Spain36052
CBS-KNAW, Fungal Biodiversity Centre, Utrecht, The Netherlands35233
BCCM/IHEM, Biomedical fungi and yeasts collection, Scientific Institute of Public Health, Brussels, Belgium28992
Institut Pasteur, National Reference Center of Invasive Mycosis and Antifungals, Molecular Mycology Unit, CNRS URA 3012, Paris, France223106
Parasitology - Mycology, APHM, CHU Timone-Adultes, Marseille, France; Aix-Marseille University, UMR MD3 IP-TPT, Marseille, France14655
Mycology Laboratory, Department of Microbiology and Infectious Diseases, PathWest Laboratory Medicine WA, QEII Medical Centre, Nedlands, Western Australia, Australia9931
BDEEP-EA4547, CIIL, Institut Pasteur de Lille, CHU de Lille, Université de Lille2, Lille, France7318
Laboratório Especial de Micologia, Escola Paulista de Medicina, Universidade Federal de São Paulo, São Paulo, Brazil5818
Instituto de Pesquisa Clínica Evandro Chagas (IPEC) - Fundação Oswaldo Cruz (Fiocruz), Rio de Janeiro, Brazil501
Facultad de Medicina, Departamento de Microbiología y Parasitología (Unidad de Micología), Universidad Nacional Autónoma de México, Ciudad de México, México393
Centre of Molecular and Environmental Biology (CBMA), Biology Department, School of Sciences, University of Minho, Braga, Portugal2210
Universidade Federal de Goiás, Instituto de Ciências Biológicas, Laboratório de Biologia Molecular, Goiânia, Goiás, Brazil92
Number ofNumber of
Institutionsstrainsspecies
Molecular Mycology Research Laboratory, CIDM, Sydney Medical School-Westmead Hospital, The University of Sydney, WMI, Australia663173
Mycology Research Laboratory, Department of Microbiology, Medical School, the University of Athens Hellenic Collection of Pathogenic Fungi (UOA/HCPF), National and Kapodistrian University of Athens, Athens, Greece417117
Unitat de Microbiologia, Facultat de Medicina i Ciències de la Salut, IISPV, Universitat Rovira i Virgili, Reus, Spain36052
CBS-KNAW, Fungal Biodiversity Centre, Utrecht, The Netherlands35233
BCCM/IHEM, Biomedical fungi and yeasts collection, Scientific Institute of Public Health, Brussels, Belgium28992
Institut Pasteur, National Reference Center of Invasive Mycosis and Antifungals, Molecular Mycology Unit, CNRS URA 3012, Paris, France223106
Parasitology - Mycology, APHM, CHU Timone-Adultes, Marseille, France; Aix-Marseille University, UMR MD3 IP-TPT, Marseille, France14655
Mycology Laboratory, Department of Microbiology and Infectious Diseases, PathWest Laboratory Medicine WA, QEII Medical Centre, Nedlands, Western Australia, Australia9931
BDEEP-EA4547, CIIL, Institut Pasteur de Lille, CHU de Lille, Université de Lille2, Lille, France7318
Laboratório Especial de Micologia, Escola Paulista de Medicina, Universidade Federal de São Paulo, São Paulo, Brazil5818
Instituto de Pesquisa Clínica Evandro Chagas (IPEC) - Fundação Oswaldo Cruz (Fiocruz), Rio de Janeiro, Brazil501
Facultad de Medicina, Departamento de Microbiología y Parasitología (Unidad de Micología), Universidad Nacional Autónoma de México, Ciudad de México, México393
Centre of Molecular and Environmental Biology (CBMA), Biology Department, School of Sciences, University of Minho, Braga, Portugal2210
Universidade Federal de Goiás, Instituto de Ciências Biológicas, Laboratório de Biologia Molecular, Goiânia, Goiás, Brazil92
Open in new tab

DNA isolation, amplification and sequencing

DNA was isolated and purified from cultures using the methods routinely used in the contributing laboratories. A number of fungal-specific universal primers (Table 2) were used to amplify the ITS region, polymerase chain reaction (PCR), and sequencing protocols varied from laboratory to laboratory according to the primers, chemical reagents, and thermocyclers used. Primers used differed depending on the fungal species investigated or starting material used. In general ITS1, ITS3, ITS4 and ITS5 [67] are universal ribosomal primers, which are recommended being used if the amplification is based on pure fungal cultures. The primers SR6R and LR1 [68], V9D, V9G and LS266 [69] and ITS1F [70] have subsequently been designed to be fungal specific, they can be used for amplification based on pure culture as well as directly form clinical specimens, as they will avoid co-amplification of human DNA. The general PCR amplification conditions are given for each of the primer pairs in Table 2 [67–72]. All PCR products were sequenced in both the forward and reverse directions. Bidirectional sequences were assembled and edited using Sequencher® [73]. Trace files were manually checked and ambiguous bases were corrected based on the forward and reverse sequences taking into account the PHRED scores received with the sequence trace files.

Table 2.

Primers and amplification conditions used to amplify ITS sequences maintained in the ISHAM-ITS reference database.

PrimersAmplification conditions
SR6R (5′ AAGTATAAGTCGTAACAAGG 3′) and LR1 (5′ GGTTGGTTTCTTTTCCT 3′)(68)97ºC for 3 min; 30 cycles of denaturation (94ºC for 35 s), annealing (50ºC for 45 s), and extension (72ºC for 45 s); and a final extension step at 72ºC for 7 min
ITS1 (5′ TCCGTAGGTGAACCTGCGG 3′) and ITS4 (5′ TCCTCCGCTTATTGATATGC 3′)(67)94ºC for 3 min; 35 cycles of denaturation (94ºC for 60 s), annealing (56ºC for 60 s), and extension (72ºC for 2 min); and a final extension step at 72ºC for 7 min
ITS5 (5′ GGAAGTAAAAGTCGTAACAAGG 3′) and ITS4 (5′ TCCTCCGCTTATTGATATGC 3′)(67)94ºC for 5 min.; 35 cycles of denaturation (94ºC for 30 s), annealing (55ºC for 1 min), and extension (72ºC 1 min and 20 s); and a final extension step at 72ºC for 7 min
ITS5 (5′ GGAAGTAAAAGTCGTAACAAGG 3′) and NL4b (5′ GGATTCTCACCCTCTATGAC 3′)(67,71)94ºC for 5 min.; 35 cycles of denaturation (94ºC for 30 s), annealing (53ºC for 1 min), and extension (72ºC 1 min and 30 s); and a final extension step at 72ºC for 7 min
V9D (5′ TTAAGTCCCTGCCCTTTGTA 3′) and LS266 (5′ GCATTCCCAAACAACTCGACTC 3′)(69)95ºC for 10 min; 30 cycles of denaturation (94ºC for 30 s), annealing (58ºC for 30 s), and extension (72ºC for 30 s); and a final extension step at 72ºC for 10 min
V9G (5′ TTACGTCCCTGCCCTTTGTA 3′) and LS266 (5′ GCATTCCCAAACAACTCGACTC 3′)(69)94ºC for 5 min; 35 cycles of denaturation (94ºC for 60 min), annealing (56ºC for 30 s), and extension (72ºC for 2 min); and a final extension step at 72ºC for 10 min
ITS1F (5′ CTTGGTCATTTAGAGGAAGTAA 3′) and ITS4 (5′ TCCTCCGCTTATTGATATGC 3′)(67,70)95ºC for 5 min; 30 cycles of denaturation (95ºC for 30 s), annealing (58ºC for 30 s), and extension (72ºC for 1 min); and a final extension (72ºC for 10 min).
ITS1 (5′ TCCGTAGGTGAACCTGCGG 3′) and IT2 (5′ CCTCCGCTTATTGATATGCTTAGG 3′)(67,72)94ºC for 3 min; 35 cycles of denaturation (94ºC for 45 s), annealing (52ºC for 45 s), and extension (72ºC for 60 s); and a final extension at 72ºC for 7 min
ITS3 (5′ GCATCGATGAAGAACGCAGC 3′) and LS266 (5′ GCATTCCCAAACAACTCGACTC 3′)(67,69)95ºC for 10 min; 30 cycles of denaturation (94ºC for 30 s), annealing (58ºC for 30 s), and extension (72ºC for 30 s); and a final extension step at 72ºC for 10 min
PrimersAmplification conditions
SR6R (5′ AAGTATAAGTCGTAACAAGG 3′) and LR1 (5′ GGTTGGTTTCTTTTCCT 3′)(68)97ºC for 3 min; 30 cycles of denaturation (94ºC for 35 s), annealing (50ºC for 45 s), and extension (72ºC for 45 s); and a final extension step at 72ºC for 7 min
ITS1 (5′ TCCGTAGGTGAACCTGCGG 3′) and ITS4 (5′ TCCTCCGCTTATTGATATGC 3′)(67)94ºC for 3 min; 35 cycles of denaturation (94ºC for 60 s), annealing (56ºC for 60 s), and extension (72ºC for 2 min); and a final extension step at 72ºC for 7 min
ITS5 (5′ GGAAGTAAAAGTCGTAACAAGG 3′) and ITS4 (5′ TCCTCCGCTTATTGATATGC 3′)(67)94ºC for 5 min.; 35 cycles of denaturation (94ºC for 30 s), annealing (55ºC for 1 min), and extension (72ºC 1 min and 20 s); and a final extension step at 72ºC for 7 min
ITS5 (5′ GGAAGTAAAAGTCGTAACAAGG 3′) and NL4b (5′ GGATTCTCACCCTCTATGAC 3′)(67,71)94ºC for 5 min.; 35 cycles of denaturation (94ºC for 30 s), annealing (53ºC for 1 min), and extension (72ºC 1 min and 30 s); and a final extension step at 72ºC for 7 min
V9D (5′ TTAAGTCCCTGCCCTTTGTA 3′) and LS266 (5′ GCATTCCCAAACAACTCGACTC 3′)(69)95ºC for 10 min; 30 cycles of denaturation (94ºC for 30 s), annealing (58ºC for 30 s), and extension (72ºC for 30 s); and a final extension step at 72ºC for 10 min
V9G (5′ TTACGTCCCTGCCCTTTGTA 3′) and LS266 (5′ GCATTCCCAAACAACTCGACTC 3′)(69)94ºC for 5 min; 35 cycles of denaturation (94ºC for 60 min), annealing (56ºC for 30 s), and extension (72ºC for 2 min); and a final extension step at 72ºC for 10 min
ITS1F (5′ CTTGGTCATTTAGAGGAAGTAA 3′) and ITS4 (5′ TCCTCCGCTTATTGATATGC 3′)(67,70)95ºC for 5 min; 30 cycles of denaturation (95ºC for 30 s), annealing (58ºC for 30 s), and extension (72ºC for 1 min); and a final extension (72ºC for 10 min).
ITS1 (5′ TCCGTAGGTGAACCTGCGG 3′) and IT2 (5′ CCTCCGCTTATTGATATGCTTAGG 3′)(67,72)94ºC for 3 min; 35 cycles of denaturation (94ºC for 45 s), annealing (52ºC for 45 s), and extension (72ºC for 60 s); and a final extension at 72ºC for 7 min
ITS3 (5′ GCATCGATGAAGAACGCAGC 3′) and LS266 (5′ GCATTCCCAAACAACTCGACTC 3′)(67,69)95ºC for 10 min; 30 cycles of denaturation (94ºC for 30 s), annealing (58ºC for 30 s), and extension (72ºC for 30 s); and a final extension step at 72ºC for 10 min
Open in new tab
Table 2.

Primers and amplification conditions used to amplify ITS sequences maintained in the ISHAM-ITS reference database.

PrimersAmplification conditions
SR6R (5′ AAGTATAAGTCGTAACAAGG 3′) and LR1 (5′ GGTTGGTTTCTTTTCCT 3′)(68)97ºC for 3 min; 30 cycles of denaturation (94ºC for 35 s), annealing (50ºC for 45 s), and extension (72ºC for 45 s); and a final extension step at 72ºC for 7 min
ITS1 (5′ TCCGTAGGTGAACCTGCGG 3′) and ITS4 (5′ TCCTCCGCTTATTGATATGC 3′)(67)94ºC for 3 min; 35 cycles of denaturation (94ºC for 60 s), annealing (56ºC for 60 s), and extension (72ºC for 2 min); and a final extension step at 72ºC for 7 min
ITS5 (5′ GGAAGTAAAAGTCGTAACAAGG 3′) and ITS4 (5′ TCCTCCGCTTATTGATATGC 3′)(67)94ºC for 5 min.; 35 cycles of denaturation (94ºC for 30 s), annealing (55ºC for 1 min), and extension (72ºC 1 min and 20 s); and a final extension step at 72ºC for 7 min
ITS5 (5′ GGAAGTAAAAGTCGTAACAAGG 3′) and NL4b (5′ GGATTCTCACCCTCTATGAC 3′)(67,71)94ºC for 5 min.; 35 cycles of denaturation (94ºC for 30 s), annealing (53ºC for 1 min), and extension (72ºC 1 min and 30 s); and a final extension step at 72ºC for 7 min
V9D (5′ TTAAGTCCCTGCCCTTTGTA 3′) and LS266 (5′ GCATTCCCAAACAACTCGACTC 3′)(69)95ºC for 10 min; 30 cycles of denaturation (94ºC for 30 s), annealing (58ºC for 30 s), and extension (72ºC for 30 s); and a final extension step at 72ºC for 10 min
V9G (5′ TTACGTCCCTGCCCTTTGTA 3′) and LS266 (5′ GCATTCCCAAACAACTCGACTC 3′)(69)94ºC for 5 min; 35 cycles of denaturation (94ºC for 60 min), annealing (56ºC for 30 s), and extension (72ºC for 2 min); and a final extension step at 72ºC for 10 min
ITS1F (5′ CTTGGTCATTTAGAGGAAGTAA 3′) and ITS4 (5′ TCCTCCGCTTATTGATATGC 3′)(67,70)95ºC for 5 min; 30 cycles of denaturation (95ºC for 30 s), annealing (58ºC for 30 s), and extension (72ºC for 1 min); and a final extension (72ºC for 10 min).
ITS1 (5′ TCCGTAGGTGAACCTGCGG 3′) and IT2 (5′ CCTCCGCTTATTGATATGCTTAGG 3′)(67,72)94ºC for 3 min; 35 cycles of denaturation (94ºC for 45 s), annealing (52ºC for 45 s), and extension (72ºC for 60 s); and a final extension at 72ºC for 7 min
ITS3 (5′ GCATCGATGAAGAACGCAGC 3′) and LS266 (5′ GCATTCCCAAACAACTCGACTC 3′)(67,69)95ºC for 10 min; 30 cycles of denaturation (94ºC for 30 s), annealing (58ºC for 30 s), and extension (72ºC for 30 s); and a final extension step at 72ºC for 10 min
PrimersAmplification conditions
SR6R (5′ AAGTATAAGTCGTAACAAGG 3′) and LR1 (5′ GGTTGGTTTCTTTTCCT 3′)(68)97ºC for 3 min; 30 cycles of denaturation (94ºC for 35 s), annealing (50ºC for 45 s), and extension (72ºC for 45 s); and a final extension step at 72ºC for 7 min
ITS1 (5′ TCCGTAGGTGAACCTGCGG 3′) and ITS4 (5′ TCCTCCGCTTATTGATATGC 3′)(67)94ºC for 3 min; 35 cycles of denaturation (94ºC for 60 s), annealing (56ºC for 60 s), and extension (72ºC for 2 min); and a final extension step at 72ºC for 7 min
ITS5 (5′ GGAAGTAAAAGTCGTAACAAGG 3′) and ITS4 (5′ TCCTCCGCTTATTGATATGC 3′)(67)94ºC for 5 min.; 35 cycles of denaturation (94ºC for 30 s), annealing (55ºC for 1 min), and extension (72ºC 1 min and 20 s); and a final extension step at 72ºC for 7 min
ITS5 (5′ GGAAGTAAAAGTCGTAACAAGG 3′) and NL4b (5′ GGATTCTCACCCTCTATGAC 3′)(67,71)94ºC for 5 min.; 35 cycles of denaturation (94ºC for 30 s), annealing (53ºC for 1 min), and extension (72ºC 1 min and 30 s); and a final extension step at 72ºC for 7 min
V9D (5′ TTAAGTCCCTGCCCTTTGTA 3′) and LS266 (5′ GCATTCCCAAACAACTCGACTC 3′)(69)95ºC for 10 min; 30 cycles of denaturation (94ºC for 30 s), annealing (58ºC for 30 s), and extension (72ºC for 30 s); and a final extension step at 72ºC for 10 min
V9G (5′ TTACGTCCCTGCCCTTTGTA 3′) and LS266 (5′ GCATTCCCAAACAACTCGACTC 3′)(69)94ºC for 5 min; 35 cycles of denaturation (94ºC for 60 min), annealing (56ºC for 30 s), and extension (72ºC for 2 min); and a final extension step at 72ºC for 10 min
ITS1F (5′ CTTGGTCATTTAGAGGAAGTAA 3′) and ITS4 (5′ TCCTCCGCTTATTGATATGC 3′)(67,70)95ºC for 5 min; 30 cycles of denaturation (95ºC for 30 s), annealing (58ºC for 30 s), and extension (72ºC for 1 min); and a final extension (72ºC for 10 min).
ITS1 (5′ TCCGTAGGTGAACCTGCGG 3′) and IT2 (5′ CCTCCGCTTATTGATATGCTTAGG 3′)(67,72)94ºC for 3 min; 35 cycles of denaturation (94ºC for 45 s), annealing (52ºC for 45 s), and extension (72ºC for 60 s); and a final extension at 72ºC for 7 min
ITS3 (5′ GCATCGATGAAGAACGCAGC 3′) and LS266 (5′ GCATTCCCAAACAACTCGACTC 3′)(67,69)95ºC for 10 min; 30 cycles of denaturation (94ºC for 30 s), annealing (58ºC for 30 s), and extension (72ºC for 30 s); and a final extension step at 72ºC for 10 min
Open in new tab

Data analysis

The length, continuity and annotation of the ITS sequences were checked using ITSx 1.0.7. [74] and membership in one species was verified by centrality analysis [75] using the software BioloMICS ver. 7.5.44 [76]. Briefly, sequences of each species were aligned to find the “central sequence”, which is the one having the highest average similarity to other members of the group. Questionable sequences that were very divergent from their central sequence, therefore doubtful as clear members of a species, were removed from further analyses. The sequences for each taxon were aligned using the program CLUSTALW [77] that is part of the software MEGA ver. 5.2.2 [78]. Resulting multiple alignments were then checked visually and edited when needed. For further analyses, the sequences were truncated at conserved sites to obtain equal 3′- and 5′-endings.

The intraspecies diversity was estimated by calculating the average nucleotide diversity (π), which gives the proportion of nucleotide differences in all haplotypes in the studied sample, the number of segregating polymorphic sites (S), and the proportion of polymorphic sites on base pair basis in a sample (Theta, Θ) of each species with sequences from more than two strains, using the software DnaSP ver. 5.10.01 [79].

For interspecies analyses, all taxa were subjected to pairwise sequence divergence calculations using the Kimura 2-parameter distance model (K2P) [80] using MEGA ver. 5.2.2. [78]. This model provides the best metric when genetic distances are low [81].

Barcoding gaps were evaluated by comparing the distribution of interspecies to intraspecies divergence within taxa sharing the same phylogenetic lineage [10]. In total, 17 barcoding gap analyses (of genera and phylogenetic clades), including two variants of the analysis for Cryptococcus neoformans/Cryptococcus gattii and Arthrodermataceae/Trichophyton, were performed (Table 3).

Table 3.

Intraspecies diversity of the 176 fungal species with more than two strains in the ISHAM-ITS reference database.

Number ofNumber ofProportion of
NumbernucleotideNucleotidepolymorphicpolymorphic sitesITS is sufficient
Speciesof strainssitesdiversity (π)sites (S)in a sample (Θ)for identification
Acremonium fusidioides35200.0064150.00641yes
Acremonium implicatum64980.0037550.000887yes
Acremonium persicinum64940.0006710.000887yes
Alternaria alternata7475000yes
Alternaria infectoria7475000yes
Arthrographis kalrae214800.0009120.001158yes
Arthropsis hispanica45980.0025130.002736yes
Aspergillus calidoustus5482000yes
Aspergillus flavus364990.0007110.000483yes
Aspergillus fumigatiaffinis4505000yes
Aspergillus fumigatus834630.0009460.002597yes
Aspergillus hiratsukae35020.0053140.005312yes
Aspergillus nidulans174730.0004710.000625yes
Aspergillus niger19392000yes
Aspergillus ochraceus34910.0027220.002716yes
Aspergillus sydowii34800.0041730.004167yes
Aspergillus terreus274640.0006120.001118yes
Aspergillus tubingensis18425000yes
Aspergillus versicolor64330.0063150.005057yes
Aureobasidium pullulans204590.00764150.009083yes
Bipolaris cynodontis93760.0005910.000981yes
Bipolaris micropus34550.0014710.001465yes
Blastobotrys adeninivorans45470.0014620.001755yes
Blastobotrys raffinosifermentans35170.0038730.003868yes
Candida albicans444400.00298100.005225yes
Candida blankii7459000yes
Candida carpophila36020.0033740.003681yes
Candida catenulata133780.0012210.000853yes
Candida deformans143200.007770.008244yes
Candida diddensiae3541000yes
Candida dubliniensis164510.0011140.002673yes
Candida duobushaemulonis4295000yes
Candida glabrata297910.00485220.007304yes
Candida haemulonis6285000yes
Candida inconspicua74130.006370.007423yes
Candida intermedia62990.01672120.017577yes
Candida mesorugosa133140.0044950.005131yes
Candida metapsilosis144100.0039740.003068yes
Candida orthopsilosis284130.0025550.005907yes
Candida palmioleophila36320.0042240.004219yes
Candida parapsilosis1094080.0001420.000933yes
Candida pararugosa74120.01133110.010898yes
Candida tropicalis274320.00352130.007807yes
Candida zeylanoides4579000yes
Cladophialophora bantiana3626000yes
Cladophialophora boppii45430.0018420.002009yes
Cladophialophora carrionii65380.0037260.004884yes
Clavispora lusitaniae452930.02248220.018258no
Cryptococcus albidus185830.00577210.010472yes
Cryptococcus carnescens6485000yes
Cryptococcus diffluens36120.0010910.001089yes
Cryptococcus gattii VGI334630.0010810.000536yes
Cryptococcus gattii VGII41463000yes
Cryptococcus gattii VGIII24463000yes
Cryptococcus gattii VGIV13463000yes
Cryptococcus laurentii64440.0049540.003946yes
Cryptococcus magnus6522000yes
Cryptococcus neoformans var. grubii VNI22452000no
Cryptococcus neoformans var. grubii VNII13460000no
Cryptococcus neoformans var. neoformans VNIV17463000yes
Curvularia aeria274420.00311110.006457yes
Curvularia borreriae45720.0032230.002861yes
Curvularia geniculata155030.0010120.00125yes
Curvularia hawaiiensis203790.0013610.000755yes
Curvularia inaequalis65180.0012920.001691yes
Curvularia lunata104670.0010710.000788yes
Curvularia protuberata3562000yes
Curvularia sorghina44900.0010210.001113yes
Curvularia spicifera373670.0004430.001958yes
Curvularia verruculosa6524000yes
Cyberlindnera jadinii75200.00769100.007849yes
Debaryomyces hansenii155400.0018730.001709yes
Epidermophyton floccosum56920.0005810.000694yes
Exophiala bergeri94950.01016120.00892yes
Exophiala dermatitidis225390.0034790.004777yes
Exophiala exophialae35380.0012410.001239yes
Exophiala jeanselmei264700.00349100.005576yes
Exophiala oligosperma624600.0016530.001389yes
Exophiala spinifera235010.00841160.008653yes
Exophiala xenobiotica394760.00458180.008838yes
Exserohilum rostratum374110.00197100.00532yes
Filobasidium uniguttulatum46160.0008110.000885yes
Fonsecaea monophora225280.00634170.008832yes
Fonsecaea nubica35120.0058660.006392yes
Fonsecaea pedrosoi324830.0013250.00257yes
Fusarium delphinoides3526000yes
Fusarium falciforme7458000no
Fusarium keratoplasticum84690.0021360.004236no
Fusarium oxysporum144550.0012820.001382yes
Fusarium petroliphilum64810.0009110.00071no
Fusarium proliferatum114510.0007310.000757yes
Fusarium solani94660.01788210.016581no
Fusarium verticillioides17455000yes
Galactomyces candidus63330.01782100.013152yes
Hanseniaspora uvarum36330.0031630.00316yes
Histoplasma capsulatum834160.01126380.018351yes
Hormographiella aspergillata45660.0008810.000964yes
Hyphopichia burtonii53590.0050140.005348yes
Hypocrea orientalis74380.0006510.000932yes
Kazachstania pintolopesii36500.0051350.005128yes
Kluyveromyces lactis var. lactis11618000yes
Kluyveromyces marxianus266030.0016550.002173yes
Kodamaea ohmeri233410.01954230.018275no
Leptosphaeria senegalensis35730.0011610.001163yes
Lichtheimia corymbifera56500.00677110.008123yes
Lichtheimia ramosa107700.02214550.025054yes
Lomentospora prolificans354750.0002420.001022yes
Magnusiomyces capitatus4365000yes
Medicopsis romeroi34670.0071450.007138yes
Meyerozyma caribbica175160.0015530.001985yes
Meyerozyma guilliermondii345160.0013430.001444yes
Microascus cirrosus3502000yes
Microsporum audouinii7666000yes
Microsporum canis8632000yes
Microsporum fulvum66170.00648100.007098yes
Microsporum gypseum5619000yes
Microsporum racemosum35560.0095980.009592yes
Millerozyma farinosa36260.01065100.01065yes
Mucor circinelloides95470.00792110.007399yes
Neoscytalidium dimidiatum94640.0004810.000793yes
Paracoccidioides brasiliensis84680.0148170.01401yes
Penicillium brevicompactum3539000yes
Phialemonium atrogriseum35240.0050940.005089yes
Pichia kudriavzevii224040.0020640.002716yes
Pichia manshurica3434000yes
Pichia norvegensis143980.0030340.003239yes
Pithomyces chartarum75680.0046980.006168yes
Pithomyces sacchari65490.0023130.002393yes
Purpureocillium lilacinum55010.000810.000958yes
Rasamsonia aegroticola104670.001940.003151yes
Rhinocladiella similis184970.00285110.006435yes
Rhizomucor pusillus35860.0034130.003413yes
Rhizopus microsporus65870.0069380.005969yes
Rhizopus oryzae45380.0021720.002028yes
Rhodotorula mucilaginosa165270.00120.001144yes
Saccharomyces cerevisiae276640.0009870.002735yes
Sarocladium kiliense234830.00546160.009208yes
Sarocladium strictum84840.0022120.001594yes
Scedosporium angustum35230.0038230.003824yes
Scedosporium apiospermum464970.00442110.004587yes
Scedosporium aurantiacum454970.0005240.001841yes
Scedosporium boydii234800.0028790.005021yes
Scedosporium dehoogii275180.003760.003005yes
Scedosporium ellipsoideum55230.0019120.001836yes
Scedosporium minutisporum75200.0027550.003925yes
Scopulariopsis brevicaulis174590.0034340.002578yes
Scopulariopsis brumptii74160.0034340.003925yes
Scopulariopsis cinerea55020.0015920.001912yes
Scopulariopsis gracilis125330.0003410.000621yes
Scytalidium cuboideum45160.0012910.001057yes
Sporothrix schenckii114840.0025540.002822yes
Torulaspora delbrueckii47110.0056380.006137yes
Trichoderma atroviride55670.0021230.00254yes
Trichoderma citrinoviride114930.0007420.001385yes
Trichoderma harzianum125260.0059990.005666yes
Trichoderma koningiopsis3549000yes
Trichoderma longibrachiatum205210.0021360.003246yes
Trichophyton ajelloi65940.0011220.001475yes
Trichophyton erinacei255790.00541160.007318yes
Trichophyton interdigitale685250.0018940.001591yes
Trichophyton mentagrophytes = T. quinckeanum5603000yes
Trichophyton persicolor36010.0011110.001109yes
Trichophyton rubrum305400.0022840.00187yes
Trichophyton schoenleinii4623000yes
Trichophyton simii76080.0015720.001343yes
Trichophyton terrestre4615000yes
Trichophyton tonsurans65970.0011220.001467yes
Trichophyton verrucosum4534000yes
Trichosporon asahii74470.0010710.000913yes
Trichosporon dermatis4440000yes
Trichosporon inkin45390.0037140.004048yes
Trichosporon montevideense4528000yes
Wickerhamomyces anomalus375220.0013170.003212yes
Yamadazyma mexicana35610.0011910.001188yes
Yamadazyma scolyti36220.0053650.005359yes
Yarrowia lipolytica243470.0062150.011576yes
Number ofNumber ofProportion of
NumbernucleotideNucleotidepolymorphicpolymorphic sitesITS is sufficient
Speciesof strainssitesdiversity (π)sites (S)in a sample (Θ)for identification
Acremonium fusidioides35200.0064150.00641yes
Acremonium implicatum64980.0037550.000887yes
Acremonium persicinum64940.0006710.000887yes
Alternaria alternata7475000yes
Alternaria infectoria7475000yes
Arthrographis kalrae214800.0009120.001158yes
Arthropsis hispanica45980.0025130.002736yes
Aspergillus calidoustus5482000yes
Aspergillus flavus364990.0007110.000483yes
Aspergillus fumigatiaffinis4505000yes
Aspergillus fumigatus834630.0009460.002597yes
Aspergillus hiratsukae35020.0053140.005312yes
Aspergillus nidulans174730.0004710.000625yes
Aspergillus niger19392000yes
Aspergillus ochraceus34910.0027220.002716yes
Aspergillus sydowii34800.0041730.004167yes
Aspergillus terreus274640.0006120.001118yes
Aspergillus tubingensis18425000yes
Aspergillus versicolor64330.0063150.005057yes
Aureobasidium pullulans204590.00764150.009083yes
Bipolaris cynodontis93760.0005910.000981yes
Bipolaris micropus34550.0014710.001465yes
Blastobotrys adeninivorans45470.0014620.001755yes
Blastobotrys raffinosifermentans35170.0038730.003868yes
Candida albicans444400.00298100.005225yes
Candida blankii7459000yes
Candida carpophila36020.0033740.003681yes
Candida catenulata133780.0012210.000853yes
Candida deformans143200.007770.008244yes
Candida diddensiae3541000yes
Candida dubliniensis164510.0011140.002673yes
Candida duobushaemulonis4295000yes
Candida glabrata297910.00485220.007304yes
Candida haemulonis6285000yes
Candida inconspicua74130.006370.007423yes
Candida intermedia62990.01672120.017577yes
Candida mesorugosa133140.0044950.005131yes
Candida metapsilosis144100.0039740.003068yes
Candida orthopsilosis284130.0025550.005907yes
Candida palmioleophila36320.0042240.004219yes
Candida parapsilosis1094080.0001420.000933yes
Candida pararugosa74120.01133110.010898yes
Candida tropicalis274320.00352130.007807yes
Candida zeylanoides4579000yes
Cladophialophora bantiana3626000yes
Cladophialophora boppii45430.0018420.002009yes
Cladophialophora carrionii65380.0037260.004884yes
Clavispora lusitaniae452930.02248220.018258no
Cryptococcus albidus185830.00577210.010472yes
Cryptococcus carnescens6485000yes
Cryptococcus diffluens36120.0010910.001089yes
Cryptococcus gattii VGI334630.0010810.000536yes
Cryptococcus gattii VGII41463000yes
Cryptococcus gattii VGIII24463000yes
Cryptococcus gattii VGIV13463000yes
Cryptococcus laurentii64440.0049540.003946yes
Cryptococcus magnus6522000yes
Cryptococcus neoformans var. grubii VNI22452000no
Cryptococcus neoformans var. grubii VNII13460000no
Cryptococcus neoformans var. neoformans VNIV17463000yes
Curvularia aeria274420.00311110.006457yes
Curvularia borreriae45720.0032230.002861yes
Curvularia geniculata155030.0010120.00125yes
Curvularia hawaiiensis203790.0013610.000755yes
Curvularia inaequalis65180.0012920.001691yes
Curvularia lunata104670.0010710.000788yes
Curvularia protuberata3562000yes
Curvularia sorghina44900.0010210.001113yes
Curvularia spicifera373670.0004430.001958yes
Curvularia verruculosa6524000yes
Cyberlindnera jadinii75200.00769100.007849yes
Debaryomyces hansenii155400.0018730.001709yes
Epidermophyton floccosum56920.0005810.000694yes
Exophiala bergeri94950.01016120.00892yes
Exophiala dermatitidis225390.0034790.004777yes
Exophiala exophialae35380.0012410.001239yes
Exophiala jeanselmei264700.00349100.005576yes
Exophiala oligosperma624600.0016530.001389yes
Exophiala spinifera235010.00841160.008653yes
Exophiala xenobiotica394760.00458180.008838yes
Exserohilum rostratum374110.00197100.00532yes
Filobasidium uniguttulatum46160.0008110.000885yes
Fonsecaea monophora225280.00634170.008832yes
Fonsecaea nubica35120.0058660.006392yes
Fonsecaea pedrosoi324830.0013250.00257yes
Fusarium delphinoides3526000yes
Fusarium falciforme7458000no
Fusarium keratoplasticum84690.0021360.004236no
Fusarium oxysporum144550.0012820.001382yes
Fusarium petroliphilum64810.0009110.00071no
Fusarium proliferatum114510.0007310.000757yes
Fusarium solani94660.01788210.016581no
Fusarium verticillioides17455000yes
Galactomyces candidus63330.01782100.013152yes
Hanseniaspora uvarum36330.0031630.00316yes
Histoplasma capsulatum834160.01126380.018351yes
Hormographiella aspergillata45660.0008810.000964yes
Hyphopichia burtonii53590.0050140.005348yes
Hypocrea orientalis74380.0006510.000932yes
Kazachstania pintolopesii36500.0051350.005128yes
Kluyveromyces lactis var. lactis11618000yes
Kluyveromyces marxianus266030.0016550.002173yes
Kodamaea ohmeri233410.01954230.018275no
Leptosphaeria senegalensis35730.0011610.001163yes
Lichtheimia corymbifera56500.00677110.008123yes
Lichtheimia ramosa107700.02214550.025054yes
Lomentospora prolificans354750.0002420.001022yes
Magnusiomyces capitatus4365000yes
Medicopsis romeroi34670.0071450.007138yes
Meyerozyma caribbica175160.0015530.001985yes
Meyerozyma guilliermondii345160.0013430.001444yes
Microascus cirrosus3502000yes
Microsporum audouinii7666000yes
Microsporum canis8632000yes
Microsporum fulvum66170.00648100.007098yes
Microsporum gypseum5619000yes
Microsporum racemosum35560.0095980.009592yes
Millerozyma farinosa36260.01065100.01065yes
Mucor circinelloides95470.00792110.007399yes
Neoscytalidium dimidiatum94640.0004810.000793yes
Paracoccidioides brasiliensis84680.0148170.01401yes
Penicillium brevicompactum3539000yes
Phialemonium atrogriseum35240.0050940.005089yes
Pichia kudriavzevii224040.0020640.002716yes
Pichia manshurica3434000yes
Pichia norvegensis143980.0030340.003239yes
Pithomyces chartarum75680.0046980.006168yes
Pithomyces sacchari65490.0023130.002393yes
Purpureocillium lilacinum55010.000810.000958yes
Rasamsonia aegroticola104670.001940.003151yes
Rhinocladiella similis184970.00285110.006435yes
Rhizomucor pusillus35860.0034130.003413yes
Rhizopus microsporus65870.0069380.005969yes
Rhizopus oryzae45380.0021720.002028yes
Rhodotorula mucilaginosa165270.00120.001144yes
Saccharomyces cerevisiae276640.0009870.002735yes
Sarocladium kiliense234830.00546160.009208yes
Sarocladium strictum84840.0022120.001594yes
Scedosporium angustum35230.0038230.003824yes
Scedosporium apiospermum464970.00442110.004587yes
Scedosporium aurantiacum454970.0005240.001841yes
Scedosporium boydii234800.0028790.005021yes
Scedosporium dehoogii275180.003760.003005yes
Scedosporium ellipsoideum55230.0019120.001836yes
Scedosporium minutisporum75200.0027550.003925yes
Scopulariopsis brevicaulis174590.0034340.002578yes
Scopulariopsis brumptii74160.0034340.003925yes
Scopulariopsis cinerea55020.0015920.001912yes
Scopulariopsis gracilis125330.0003410.000621yes
Scytalidium cuboideum45160.0012910.001057yes
Sporothrix schenckii114840.0025540.002822yes
Torulaspora delbrueckii47110.0056380.006137yes
Trichoderma atroviride55670.0021230.00254yes
Trichoderma citrinoviride114930.0007420.001385yes
Trichoderma harzianum125260.0059990.005666yes
Trichoderma koningiopsis3549000yes
Trichoderma longibrachiatum205210.0021360.003246yes
Trichophyton ajelloi65940.0011220.001475yes
Trichophyton erinacei255790.00541160.007318yes
Trichophyton interdigitale685250.0018940.001591yes
Trichophyton mentagrophytes = T. quinckeanum5603000yes
Trichophyton persicolor36010.0011110.001109yes
Trichophyton rubrum305400.0022840.00187yes
Trichophyton schoenleinii4623000yes
Trichophyton simii76080.0015720.001343yes
Trichophyton terrestre4615000yes
Trichophyton tonsurans65970.0011220.001467yes
Trichophyton verrucosum4534000yes
Trichosporon asahii74470.0010710.000913yes
Trichosporon dermatis4440000yes
Trichosporon inkin45390.0037140.004048yes
Trichosporon montevideense4528000yes
Wickerhamomyces anomalus375220.0013170.003212yes
Yamadazyma mexicana35610.0011910.001188yes
Yamadazyma scolyti36220.0053650.005359yes
Yarrowia lipolytica243470.0062150.011576yes
Open in new tab
Table 3.

Intraspecies diversity of the 176 fungal species with more than two strains in the ISHAM-ITS reference database.

Number ofNumber ofProportion of
NumbernucleotideNucleotidepolymorphicpolymorphic sitesITS is sufficient
Speciesof strainssitesdiversity (π)sites (S)in a sample (Θ)for identification
Acremonium fusidioides35200.0064150.00641yes
Acremonium implicatum64980.0037550.000887yes
Acremonium persicinum64940.0006710.000887yes
Alternaria alternata7475000yes
Alternaria infectoria7475000yes
Arthrographis kalrae214800.0009120.001158yes
Arthropsis hispanica45980.0025130.002736yes
Aspergillus calidoustus5482000yes
Aspergillus flavus364990.0007110.000483yes
Aspergillus fumigatiaffinis4505000yes
Aspergillus fumigatus834630.0009460.002597yes
Aspergillus hiratsukae35020.0053140.005312yes
Aspergillus nidulans174730.0004710.000625yes
Aspergillus niger19392000yes
Aspergillus ochraceus34910.0027220.002716yes
Aspergillus sydowii34800.0041730.004167yes
Aspergillus terreus274640.0006120.001118yes
Aspergillus tubingensis18425000yes
Aspergillus versicolor64330.0063150.005057yes
Aureobasidium pullulans204590.00764150.009083yes
Bipolaris cynodontis93760.0005910.000981yes
Bipolaris micropus34550.0014710.001465yes
Blastobotrys adeninivorans45470.0014620.001755yes
Blastobotrys raffinosifermentans35170.0038730.003868yes
Candida albicans444400.00298100.005225yes
Candida blankii7459000yes
Candida carpophila36020.0033740.003681yes
Candida catenulata133780.0012210.000853yes
Candida deformans143200.007770.008244yes
Candida diddensiae3541000yes
Candida dubliniensis164510.0011140.002673yes
Candida duobushaemulonis4295000yes
Candida glabrata297910.00485220.007304yes
Candida haemulonis6285000yes
Candida inconspicua74130.006370.007423yes
Candida intermedia62990.01672120.017577yes
Candida mesorugosa133140.0044950.005131yes
Candida metapsilosis144100.0039740.003068yes
Candida orthopsilosis284130.0025550.005907yes
Candida palmioleophila36320.0042240.004219yes
Candida parapsilosis1094080.0001420.000933yes
Candida pararugosa74120.01133110.010898yes
Candida tropicalis274320.00352130.007807yes
Candida zeylanoides4579000yes
Cladophialophora bantiana3626000yes
Cladophialophora boppii45430.0018420.002009yes
Cladophialophora carrionii65380.0037260.004884yes
Clavispora lusitaniae452930.02248220.018258no
Cryptococcus albidus185830.00577210.010472yes
Cryptococcus carnescens6485000yes
Cryptococcus diffluens36120.0010910.001089yes
Cryptococcus gattii VGI334630.0010810.000536yes
Cryptococcus gattii VGII41463000yes
Cryptococcus gattii VGIII24463000yes
Cryptococcus gattii VGIV13463000yes
Cryptococcus laurentii64440.0049540.003946yes
Cryptococcus magnus6522000yes
Cryptococcus neoformans var. grubii VNI22452000no
Cryptococcus neoformans var. grubii VNII13460000no
Cryptococcus neoformans var. neoformans VNIV17463000yes
Curvularia aeria274420.00311110.006457yes
Curvularia borreriae45720.0032230.002861yes
Curvularia geniculata155030.0010120.00125yes
Curvularia hawaiiensis203790.0013610.000755yes
Curvularia inaequalis65180.0012920.001691yes
Curvularia lunata104670.0010710.000788yes
Curvularia protuberata3562000yes
Curvularia sorghina44900.0010210.001113yes
Curvularia spicifera373670.0004430.001958yes
Curvularia verruculosa6524000yes
Cyberlindnera jadinii75200.00769100.007849yes
Debaryomyces hansenii155400.0018730.001709yes
Epidermophyton floccosum56920.0005810.000694yes
Exophiala bergeri94950.01016120.00892yes
Exophiala dermatitidis225390.0034790.004777yes
Exophiala exophialae35380.0012410.001239yes
Exophiala jeanselmei264700.00349100.005576yes
Exophiala oligosperma624600.0016530.001389yes
Exophiala spinifera235010.00841160.008653yes
Exophiala xenobiotica394760.00458180.008838yes
Exserohilum rostratum374110.00197100.00532yes
Filobasidium uniguttulatum46160.0008110.000885yes
Fonsecaea monophora225280.00634170.008832yes
Fonsecaea nubica35120.0058660.006392yes
Fonsecaea pedrosoi324830.0013250.00257yes
Fusarium delphinoides3526000yes
Fusarium falciforme7458000no
Fusarium keratoplasticum84690.0021360.004236no
Fusarium oxysporum144550.0012820.001382yes
Fusarium petroliphilum64810.0009110.00071no
Fusarium proliferatum114510.0007310.000757yes
Fusarium solani94660.01788210.016581no
Fusarium verticillioides17455000yes
Galactomyces candidus63330.01782100.013152yes
Hanseniaspora uvarum36330.0031630.00316yes
Histoplasma capsulatum834160.01126380.018351yes
Hormographiella aspergillata45660.0008810.000964yes
Hyphopichia burtonii53590.0050140.005348yes
Hypocrea orientalis74380.0006510.000932yes
Kazachstania pintolopesii36500.0051350.005128yes
Kluyveromyces lactis var. lactis11618000yes
Kluyveromyces marxianus266030.0016550.002173yes
Kodamaea ohmeri233410.01954230.018275no
Leptosphaeria senegalensis35730.0011610.001163yes
Lichtheimia corymbifera56500.00677110.008123yes
Lichtheimia ramosa107700.02214550.025054yes
Lomentospora prolificans354750.0002420.001022yes
Magnusiomyces capitatus4365000yes
Medicopsis romeroi34670.0071450.007138yes
Meyerozyma caribbica175160.0015530.001985yes
Meyerozyma guilliermondii345160.0013430.001444yes
Microascus cirrosus3502000yes
Microsporum audouinii7666000yes
Microsporum canis8632000yes
Microsporum fulvum66170.00648100.007098yes
Microsporum gypseum5619000yes
Microsporum racemosum35560.0095980.009592yes
Millerozyma farinosa36260.01065100.01065yes
Mucor circinelloides95470.00792110.007399yes
Neoscytalidium dimidiatum94640.0004810.000793yes
Paracoccidioides brasiliensis84680.0148170.01401yes
Penicillium brevicompactum3539000yes
Phialemonium atrogriseum35240.0050940.005089yes
Pichia kudriavzevii224040.0020640.002716yes
Pichia manshurica3434000yes
Pichia norvegensis143980.0030340.003239yes
Pithomyces chartarum75680.0046980.006168yes
Pithomyces sacchari65490.0023130.002393yes
Purpureocillium lilacinum55010.000810.000958yes
Rasamsonia aegroticola104670.001940.003151yes
Rhinocladiella similis184970.00285110.006435yes
Rhizomucor pusillus35860.0034130.003413yes
Rhizopus microsporus65870.0069380.005969yes
Rhizopus oryzae45380.0021720.002028yes
Rhodotorula mucilaginosa165270.00120.001144yes
Saccharomyces cerevisiae276640.0009870.002735yes
Sarocladium kiliense234830.00546160.009208yes
Sarocladium strictum84840.0022120.001594yes
Scedosporium angustum35230.0038230.003824yes
Scedosporium apiospermum464970.00442110.004587yes
Scedosporium aurantiacum454970.0005240.001841yes
Scedosporium boydii234800.0028790.005021yes
Scedosporium dehoogii275180.003760.003005yes
Scedosporium ellipsoideum55230.0019120.001836yes
Scedosporium minutisporum75200.0027550.003925yes
Scopulariopsis brevicaulis174590.0034340.002578yes
Scopulariopsis brumptii74160.0034340.003925yes
Scopulariopsis cinerea55020.0015920.001912yes
Scopulariopsis gracilis125330.0003410.000621yes
Scytalidium cuboideum45160.0012910.001057yes
Sporothrix schenckii114840.0025540.002822yes
Torulaspora delbrueckii47110.0056380.006137yes
Trichoderma atroviride55670.0021230.00254yes
Trichoderma citrinoviride114930.0007420.001385yes
Trichoderma harzianum125260.0059990.005666yes
Trichoderma koningiopsis3549000yes
Trichoderma longibrachiatum205210.0021360.003246yes
Trichophyton ajelloi65940.0011220.001475yes
Trichophyton erinacei255790.00541160.007318yes
Trichophyton interdigitale685250.0018940.001591yes
Trichophyton mentagrophytes = T. quinckeanum5603000yes
Trichophyton persicolor36010.0011110.001109yes
Trichophyton rubrum305400.0022840.00187yes
Trichophyton schoenleinii4623000yes
Trichophyton simii76080.0015720.001343yes
Trichophyton terrestre4615000yes
Trichophyton tonsurans65970.0011220.001467yes
Trichophyton verrucosum4534000yes
Trichosporon asahii74470.0010710.000913yes
Trichosporon dermatis4440000yes
Trichosporon inkin45390.0037140.004048yes
Trichosporon montevideense4528000yes
Wickerhamomyces anomalus375220.0013170.003212yes
Yamadazyma mexicana35610.0011910.001188yes
Yamadazyma scolyti36220.0053650.005359yes
Yarrowia lipolytica243470.0062150.011576yes
Number ofNumber ofProportion of
NumbernucleotideNucleotidepolymorphicpolymorphic sitesITS is sufficient
Speciesof strainssitesdiversity (π)sites (S)in a sample (Θ)for identification
Acremonium fusidioides35200.0064150.00641yes
Acremonium implicatum64980.0037550.000887yes
Acremonium persicinum64940.0006710.000887yes
Alternaria alternata7475000yes
Alternaria infectoria7475000yes
Arthrographis kalrae214800.0009120.001158yes
Arthropsis hispanica45980.0025130.002736yes
Aspergillus calidoustus5482000yes
Aspergillus flavus364990.0007110.000483yes
Aspergillus fumigatiaffinis4505000yes
Aspergillus fumigatus834630.0009460.002597yes
Aspergillus hiratsukae35020.0053140.005312yes
Aspergillus nidulans174730.0004710.000625yes
Aspergillus niger19392000yes
Aspergillus ochraceus34910.0027220.002716yes
Aspergillus sydowii34800.0041730.004167yes
Aspergillus terreus274640.0006120.001118yes
Aspergillus tubingensis18425000yes
Aspergillus versicolor64330.0063150.005057yes
Aureobasidium pullulans204590.00764150.009083yes
Bipolaris cynodontis93760.0005910.000981yes
Bipolaris micropus34550.0014710.001465yes
Blastobotrys adeninivorans45470.0014620.001755yes
Blastobotrys raffinosifermentans35170.0038730.003868yes
Candida albicans444400.00298100.005225yes
Candida blankii7459000yes
Candida carpophila36020.0033740.003681yes
Candida catenulata133780.0012210.000853yes
Candida deformans143200.007770.008244yes
Candida diddensiae3541000yes
Candida dubliniensis164510.0011140.002673yes
Candida duobushaemulonis4295000yes
Candida glabrata297910.00485220.007304yes
Candida haemulonis6285000yes
Candida inconspicua74130.006370.007423yes
Candida intermedia62990.01672120.017577yes
Candida mesorugosa133140.0044950.005131yes
Candida metapsilosis144100.0039740.003068yes
Candida orthopsilosis284130.0025550.005907yes
Candida palmioleophila36320.0042240.004219yes
Candida parapsilosis1094080.0001420.000933yes
Candida pararugosa74120.01133110.010898yes
Candida tropicalis274320.00352130.007807yes
Candida zeylanoides4579000yes
Cladophialophora bantiana3626000yes
Cladophialophora boppii45430.0018420.002009yes
Cladophialophora carrionii65380.0037260.004884yes
Clavispora lusitaniae452930.02248220.018258no
Cryptococcus albidus185830.00577210.010472yes
Cryptococcus carnescens6485000yes
Cryptococcus diffluens36120.0010910.001089yes
Cryptococcus gattii VGI334630.0010810.000536yes
Cryptococcus gattii VGII41463000yes
Cryptococcus gattii VGIII24463000yes
Cryptococcus gattii VGIV13463000yes
Cryptococcus laurentii64440.0049540.003946yes
Cryptococcus magnus6522000yes
Cryptococcus neoformans var. grubii VNI22452000no
Cryptococcus neoformans var. grubii VNII13460000no
Cryptococcus neoformans var. neoformans VNIV17463000yes
Curvularia aeria274420.00311110.006457yes
Curvularia borreriae45720.0032230.002861yes
Curvularia geniculata155030.0010120.00125yes
Curvularia hawaiiensis203790.0013610.000755yes
Curvularia inaequalis65180.0012920.001691yes
Curvularia lunata104670.0010710.000788yes
Curvularia protuberata3562000yes
Curvularia sorghina44900.0010210.001113yes
Curvularia spicifera373670.0004430.001958yes
Curvularia verruculosa6524000yes
Cyberlindnera jadinii75200.00769100.007849yes
Debaryomyces hansenii155400.0018730.001709yes
Epidermophyton floccosum56920.0005810.000694yes
Exophiala bergeri94950.01016120.00892yes
Exophiala dermatitidis225390.0034790.004777yes
Exophiala exophialae35380.0012410.001239yes
Exophiala jeanselmei264700.00349100.005576yes
Exophiala oligosperma624600.0016530.001389yes
Exophiala spinifera235010.00841160.008653yes
Exophiala xenobiotica394760.00458180.008838yes
Exserohilum rostratum374110.00197100.00532yes
Filobasidium uniguttulatum46160.0008110.000885yes
Fonsecaea monophora225280.00634170.008832yes
Fonsecaea nubica35120.0058660.006392yes
Fonsecaea pedrosoi324830.0013250.00257yes
Fusarium delphinoides3526000yes
Fusarium falciforme7458000no
Fusarium keratoplasticum84690.0021360.004236no
Fusarium oxysporum144550.0012820.001382yes
Fusarium petroliphilum64810.0009110.00071no
Fusarium proliferatum114510.0007310.000757yes
Fusarium solani94660.01788210.016581no
Fusarium verticillioides17455000yes
Galactomyces candidus63330.01782100.013152yes
Hanseniaspora uvarum36330.0031630.00316yes
Histoplasma capsulatum834160.01126380.018351yes
Hormographiella aspergillata45660.0008810.000964yes
Hyphopichia burtonii53590.0050140.005348yes
Hypocrea orientalis74380.0006510.000932yes
Kazachstania pintolopesii36500.0051350.005128yes
Kluyveromyces lactis var. lactis11618000yes
Kluyveromyces marxianus266030.0016550.002173yes
Kodamaea ohmeri233410.01954230.018275no
Leptosphaeria senegalensis35730.0011610.001163yes
Lichtheimia corymbifera56500.00677110.008123yes
Lichtheimia ramosa107700.02214550.025054yes
Lomentospora prolificans354750.0002420.001022yes
Magnusiomyces capitatus4365000yes
Medicopsis romeroi34670.0071450.007138yes
Meyerozyma caribbica175160.0015530.001985yes
Meyerozyma guilliermondii345160.0013430.001444yes
Microascus cirrosus3502000yes
Microsporum audouinii7666000yes
Microsporum canis8632000yes
Microsporum fulvum66170.00648100.007098yes
Microsporum gypseum5619000yes
Microsporum racemosum35560.0095980.009592yes
Millerozyma farinosa36260.01065100.01065yes
Mucor circinelloides95470.00792110.007399yes
Neoscytalidium dimidiatum94640.0004810.000793yes
Paracoccidioides brasiliensis84680.0148170.01401yes
Penicillium brevicompactum3539000yes
Phialemonium atrogriseum35240.0050940.005089yes
Pichia kudriavzevii224040.0020640.002716yes
Pichia manshurica3434000yes
Pichia norvegensis143980.0030340.003239yes
Pithomyces chartarum75680.0046980.006168yes
Pithomyces sacchari65490.0023130.002393yes
Purpureocillium lilacinum55010.000810.000958yes
Rasamsonia aegroticola104670.001940.003151yes
Rhinocladiella similis184970.00285110.006435yes
Rhizomucor pusillus35860.0034130.003413yes
Rhizopus microsporus65870.0069380.005969yes
Rhizopus oryzae45380.0021720.002028yes
Rhodotorula mucilaginosa165270.00120.001144yes
Saccharomyces cerevisiae276640.0009870.002735yes
Sarocladium kiliense234830.00546160.009208yes
Sarocladium strictum84840.0022120.001594yes
Scedosporium angustum35230.0038230.003824yes
Scedosporium apiospermum464970.00442110.004587yes
Scedosporium aurantiacum454970.0005240.001841yes
Scedosporium boydii234800.0028790.005021yes
Scedosporium dehoogii275180.003760.003005yes
Scedosporium ellipsoideum55230.0019120.001836yes
Scedosporium minutisporum75200.0027550.003925yes
Scopulariopsis brevicaulis174590.0034340.002578yes
Scopulariopsis brumptii74160.0034340.003925yes
Scopulariopsis cinerea55020.0015920.001912yes
Scopulariopsis gracilis125330.0003410.000621yes
Scytalidium cuboideum45160.0012910.001057yes
Sporothrix schenckii114840.0025540.002822yes
Torulaspora delbrueckii47110.0056380.006137yes
Trichoderma atroviride55670.0021230.00254yes
Trichoderma citrinoviride114930.0007420.001385yes
Trichoderma harzianum125260.0059990.005666yes
Trichoderma koningiopsis3549000yes
Trichoderma longibrachiatum205210.0021360.003246yes
Trichophyton ajelloi65940.0011220.001475yes
Trichophyton erinacei255790.00541160.007318yes
Trichophyton interdigitale685250.0018940.001591yes
Trichophyton mentagrophytes = T. quinckeanum5603000yes
Trichophyton persicolor36010.0011110.001109yes
Trichophyton rubrum305400.0022840.00187yes
Trichophyton schoenleinii4623000yes
Trichophyton simii76080.0015720.001343yes
Trichophyton terrestre4615000yes
Trichophyton tonsurans65970.0011220.001467yes
Trichophyton verrucosum4534000yes
Trichosporon asahii74470.0010710.000913yes
Trichosporon dermatis4440000yes
Trichosporon inkin45390.0037140.004048yes
Trichosporon montevideense4528000yes
Wickerhamomyces anomalus375220.0013170.003212yes
Yamadazyma mexicana35610.0011910.001188yes
Yamadazyma scolyti36220.0053650.005359yes
Yarrowia lipolytica243470.0062150.011576yes
Open in new tab

Sequence data were stored in BioloMICS ver. 7.5.44 [76] and statistical analyses were carried out in the statistical environment R [82].

Definitions

Species = a well-defined organism with a proven clinical relevance. Species complex = are organisms which form a cryptic species for which currently no proven evidence of individual medical relevance is known [83].

Results

Establishment of the quality controlled ISHAM-ITS reference database

A quality-controlled ITS reference database for human and animal pathogenic fungi was established as the result of the collaboration between 14 mycology laboratories from three continents. Altogether, the participating laboratories generated complete ITS (ITS1-5.8S-ITS2) sequences representing most of the pathogenic fungi. The number of ITS sequences and species contributed are shown in Table 1. According to the most recent taxonomic nomenclature, many species with different synonyms proved to be identical. Each sequence was associated with the current taxonomic species name, as well as with the most commonly used scientific names, used in a clinical setting. The sequences are freely accessible at http://www.isham.org/, directly from http://its.mycologylab.org/ or as specifically labelled ISHAM-ITS sequences in GenBank and UNITE. Of the 421 fungal species contained in the ISHAM-ITS sequences 71 representing the type culture of the species have also been submitted RTL at NCBI, following the principles laid out in Schoch et al. [57].

Number of sequences

At present, the quality-controlled ISHAM-ITS reference database contains 2800 complete ITS sequences representing 421 human/animal pathogenic fungal species. It contains 176 species represented by one strain, 69 species by two strains, and 176 species by a minimum of three to a maximum of 109 sequences. The distribution of strains per species was hyperbolic, meaning that the species with few strains were more frequent than those with many (Fig. 1).

Figure 1.
Distribution of the number of strains per species in the ISHAM-ITS reference database.
Open in new tabDownload slide

Distribution of the number of strains per species in the ISHAM-ITS reference database.

Lengths of the ITS

The lengths of complete ITS sequences in the ISHAM-ITS reference database varied between 285 and 791 bp. The distribution of the number of nucleotides per sequence is given in Figure 2. The shortest complete ITS sequences were assigned to Candida haemulonis (285 bp), Clavispora lusitaniae (293 bp), and the longest ones to Candida glabrata (791 bp) and Lichtheimia ramosa (770 bp). The mean nucleotide length of ITS sequences in the database was 503 bp, while the median was 500 bp, indicating that the distribution of the sequence lengths was almost normal, with 0.08 skewness and 0.71 kurtosis (Fig. 2). These two metrics indicate that the population of sequences is centered around the average (skewness close to 0) and displays a more acute peak (kurtosis >0) than expected in a normal distribution. Altogether these metrics indicate that the sequences can be described rather well by a normal distribution very dense around the mean.

Figure 2.
Length distribution of ITS sequences in the ISHAM-ITS reference database.
Open in new tabDownload slide

Length distribution of ITS sequences in the ISHAM-ITS reference database.

Quality of the database

There were 206 species, including 69 represented by only two strains, whose sequences showed diversity from the “central sequence” of the species. Figure 3 shows the average and the minimum similarity of the sequences to their central sequence as well as the number of the sequences within these species. The minimum similarity to the central sequence was less than 0.95% in the case of seven species, between 0.95–0.98% in 32 species and 0.98–0.998% in 167 species.

Figure 3.
Average and the minimum similarity of the sequences to their central sequence as well as the number of the sequences within these species.
Open in new tabDownload slide

Average and the minimum similarity of the sequences to their central sequence as well as the number of the sequences within these species.

The average nucleotide diversity (π) was compared with the number of strains to test the hypothesis that the number of strain influences the variability. The nucleotide diversity and the number of strains did not show significant correlation, indicating that it is unlikely that the number of strains influences the variability. According to these two parameters, 160 out of the 176 species with more than two strains, were placed within a region spanning from 0 to 40 strains per species and from 0 to 1.1% variability within the species (Fig. 4). Six species (Lichtheimia ramosa, Fusarium solani, Kodamaea ohmeri, Galactomyces candidus, Candida intermedia, and Clavispora lusitaniae) showed a high intraspecies variability of up to 2.25% based on the value of π. Nine species (Histoplasma capsulatum, Scedosporium apiospermum, Scedosporium aurantiacum, Cryptococcus gattii VGII, Exophiala oligosperma, Trichophyton interdigitale, Aspergillus fumigatus, Candida parapsilosis, and Candida albicans) were in a region with less than 1.1% intraspecies variability, although the number of strains per species ranged from 40 to 109. Interestingly, this group of taxa with relatively low variability includes some of the more important pathogenic fungi namely A. fumigatus, C. parapsilosis, and C. albicans.

Figure 4.
Nucleotide diversity (π) compared to the number of sequences by species in the ISHAM-ITS reference database.
Open in new tabDownload slide

Nucleotide diversity (π) compared to the number of sequences by species in the ISHAM-ITS reference database.

Intraspecies genetic diversity of pathogenic fungal species in the ISHAM-ITS reference database

The two metrics of nucleotide diversity (π and Θ) generated very similar values (Table 3). The nucleotide diversity (π) estimated the proportion of nucleotide differences in all haplotypes and Θ measured the proportion of all segregating sites in a sample, thus being strongly influenced by rare haplotypes. The average nucleotide diversity per species was expressed as a percentage based on the value of π (Fig. 5).

Figure 5.
Average nucleotide diversity per species expressed as a percentage based on the value of π of the 176 fungal species with more than three strains in the ISHAM-ITS reference database. The error bars indicate the standard deviation of nucleotide differences.
Open in new tabDownload slide

Average nucleotide diversity per species expressed as a percentage based on the value of π of the 176 fungal species with more than three strains in the ISHAM-ITS reference database. The error bars indicate the standard deviation of nucleotide differences.

In the ISHAM-ITS reference database, the average nucleotide diversity was less than 0.5% for 138 species, between 0.5–1.0% in 27 species, 1.01–1.5% in five species (Exophiala bergeri, Millerozyma farinosa, H. capsulatum, Candida pararugosa, and Paracoccidioides brasiliensis), 1.5–2.0% in four species (C. intermedia, G. candidus, F. solani, and K. ohmeri), and more than 2% in two species (Lichtheimia ramosa and C. lusitaniae) (Table 3, Fig. 5).

The distribution of the distances from the “central sequence” of a species was hyperbolic, with the most frequent class, containing 63 species, representing more than one third of the species with more than two strains in the database, showing intraspecies variability ranging from 0 to 0.1%. More than half of the species with more than two strains in the database (97 species) were represented by species with less than 0.4% distance (Fig. 6).

Figure 6.
Distribution of average distance of s within species compared to the number of species in the ISHAM-ITS reference database.
Open in new tabDownload slide

Distribution of average distance of s within species compared to the number of species in the ISHAM-ITS reference database.

The polymorphic site distribution showed a similar result. In 117 species, the number of polymorphic sites was less than five, in 35 species it was between five and ten, in 11 species between 11 and 15, in six species between 16 and 20 and finally more than 20 in seven species. The species with the highest number of segregating sites were Cryptococcus albidus (21 sites), the complex of F. solani (21 sites), C. lusitaniae (22 sites), C. glabrata (22 sites), K. ohmeri (23 sites), H. capsulatum (38 sites), and L. ramosa (55 sites) (Table 3). The value of Θ showed a strong correlation with the average nucleotide diversity and the number of segregating sites. The proportion of rare haplotypes in a given sample was the highest in F. solani, C. lusitaniae, K. ohmeri, H. capsulatum, and L. ramosa (Table 3).

The intraspecies genetic analyses showed that the majority of medically important species had a low variability in ITS regions. Thus ITS sequencing can be used for the identification of most medical relevant fungal species (Table 3). The species with high intraspecies diversity within the ITS region require analysis of additional molecular markers to be reliably identified (see Table 4).

Table 4.

Taxa with high ITS diversity and alternative methods to be used for their reliable identification.

TaxaProposed alternatives
Clavispora lusitaniaeMorphological identification by mating unknowns with a strain of known mating type(89,90)
Fusarium solani species complex (FSSC)MLST(116); translation elongation factor 1-α (TEF-1α), RNA polymerase II gene (RPB2), secondary metabolite profiles(94)
Kodamaea ohmeriFurther taxonomic studies needed
Lichtheimia spp.D1/D2 region, translation elongation factor 1-α (TEF-1α)(102); MALDI-TOF(105)
CryptococcusAFLP(110); PCR fingerprinting, RFLP of orotidine monophosphate pyrophosphorylase gene (URA5)(111); MLST(114)
Scedosporiumβ -tubulin (BT2)(122), AFLP(121); LSU(124)
ArthrodermataceaeRAPD, PCR fingerprinting, AFLP, microsatellite markers(102)
TaxaProposed alternatives
Clavispora lusitaniaeMorphological identification by mating unknowns with a strain of known mating type(89,90)
Fusarium solani species complex (FSSC)MLST(116); translation elongation factor 1-α (TEF-1α), RNA polymerase II gene (RPB2), secondary metabolite profiles(94)
Kodamaea ohmeriFurther taxonomic studies needed
Lichtheimia spp.D1/D2 region, translation elongation factor 1-α (TEF-1α)(102); MALDI-TOF(105)
CryptococcusAFLP(110); PCR fingerprinting, RFLP of orotidine monophosphate pyrophosphorylase gene (URA5)(111); MLST(114)
Scedosporiumβ -tubulin (BT2)(122), AFLP(121); LSU(124)
ArthrodermataceaeRAPD, PCR fingerprinting, AFLP, microsatellite markers(102)
Open in new tab
Table 4.

Taxa with high ITS diversity and alternative methods to be used for their reliable identification.

TaxaProposed alternatives
Clavispora lusitaniaeMorphological identification by mating unknowns with a strain of known mating type(89,90)
Fusarium solani species complex (FSSC)MLST(116); translation elongation factor 1-α (TEF-1α), RNA polymerase II gene (RPB2), secondary metabolite profiles(94)
Kodamaea ohmeriFurther taxonomic studies needed
Lichtheimia spp.D1/D2 region, translation elongation factor 1-α (TEF-1α)(102); MALDI-TOF(105)
CryptococcusAFLP(110); PCR fingerprinting, RFLP of orotidine monophosphate pyrophosphorylase gene (URA5)(111); MLST(114)
Scedosporiumβ -tubulin (BT2)(122), AFLP(121); LSU(124)
ArthrodermataceaeRAPD, PCR fingerprinting, AFLP, microsatellite markers(102)
TaxaProposed alternatives
Clavispora lusitaniaeMorphological identification by mating unknowns with a strain of known mating type(89,90)
Fusarium solani species complex (FSSC)MLST(116); translation elongation factor 1-α (TEF-1α), RNA polymerase II gene (RPB2), secondary metabolite profiles(94)
Kodamaea ohmeriFurther taxonomic studies needed
Lichtheimia spp.D1/D2 region, translation elongation factor 1-α (TEF-1α)(102); MALDI-TOF(105)
CryptococcusAFLP(110); PCR fingerprinting, RFLP of orotidine monophosphate pyrophosphorylase gene (URA5)(111); MLST(114)
Scedosporiumβ -tubulin (BT2)(122), AFLP(121); LSU(124)
ArthrodermataceaeRAPD, PCR fingerprinting, AFLP, microsatellite markers(102)
Open in new tab

Barcoding gap analysis of the species represented in the ISHAM-ITS reference database

For the estimation of the barcoding gap the distribution of the Kimura 2-parameter (K2P) genetic distances within species and between species was calculated. In the ISHAM-ITS reference database, 17 taxonomical groups with more than two species sharing the same phylogenetic clade were identified based on previous data in MycoBank [63,64], Index Fungorum [65], and The Yeasts [66] (Table 5). The barcoding gap analysis was performed in all 17 taxa, including two versions of analysis for C. neoformans/C. gattii and Arthrodermataceae/Trichophyton (see Table 5). The distribution of genetic distances (intra- and interspecies) in each taxon is shown in Figures 7–10 and Supplementary Figures S1–S13. In 13 taxa (phylogenetic clades), a clear barcoding gap (K2P distance) was found (Table 5). The smallest barcoding gap (0.0002) was found in the Microsporum spp., while the largest one was found in the Cladophialophora spp. (0.09). In these cases, the highest intraspecies distances were smaller than the lowest genetic distances between species, creating a barcoding gap. For the remaining four taxa Cryptococcus (Fig. 7), Fusarium (Fig. 8), Scedosporium (Fig. 9), and Trichophyton (Fig. 10), it was not possible to define a clear barcoding gap, meaning that the distributions of genetic distances within and between species overlapped.

Figure 7.
A) Distribution of interspecies (broken line) and intraspecies (solid line) pairwise Kimura 2-parameter genetic distances in Cryptococcus (Filobasidiella clade diveded into three taxa) including C. gattii; C. neoformans var. grubii; C. neoformans var. neoformans.B) Distribution of interspecies (broken line) and intraspecies (solid line) pairwise Kimura 2-parameter genetic distances in Cryptococcus (Filobasidiella clade diveded into seven taxa) including C. gattii VGI; C. gattii VGII; C. gattii VGIII; C. gattii VGIV; C. neoformans var. grubii VNI; C. neoformans var. grubii VNII; C. neoformans var. neoformans VNIV.
Open in new tabDownload slide

A) Distribution of interspecies (broken line) and intraspecies (solid line) pairwise Kimura 2-parameter genetic distances in Cryptococcus (Filobasidiella clade diveded into three taxa) including C. gattii; C. neoformans var. grubii; C. neoformans var. neoformans.B) Distribution of interspecies (broken line) and intraspecies (solid line) pairwise Kimura 2-parameter genetic distances in Cryptococcus (Filobasidiella clade diveded into seven taxa) including C. gattii VGI; C. gattii VGII; C. gattii VGIII; C. gattii VGIV; C. neoformans var. grubii VNI; C. neoformans var. grubii VNII; C. neoformans var. neoformans VNIV.

Figure 8.
Distribution of interspecies (broken line) and intraspecies (solid line) pairwise Kimura 2-parameter genetic distances in Fusarium including F. delphinoides; F. falciforme; F. oxysporum; F. proliferatum; F. solani; F. keratoplasticum; F. petroliphilum; F. verticillioides.
Open in new tabDownload slide

Distribution of interspecies (broken line) and intraspecies (solid line) pairwise Kimura 2-parameter genetic distances in Fusarium including F. delphinoides; F. falciforme; F. oxysporum; F. proliferatum; F. solani; F. keratoplasticum; F. petroliphilum; F. verticillioides.

Figure 9.
Distribution of interspecies (broken line) and intraspecies (solid line) pairwise Kimura 2-parameter genetic distances in Scedosporium including S. angustum; S. apiospermum; S. aurantiacum; S. boydii; S. dehoogii; S. ellipsoideum; S. minutisporum.
Open in new tabDownload slide

Distribution of interspecies (broken line) and intraspecies (solid line) pairwise Kimura 2-parameter genetic distances in Scedosporium including S. angustum; S. apiospermum; S. aurantiacum; S. boydii; S. dehoogii; S. ellipsoideum; S. minutisporum.

Figure 10.
Distribution of interspecies (broken line) and intraspecies (solid line) pairwise Kimura 2-parameter genetic distances in Trichophyton including T. ajelloi; T. erinacei; T. interdigitale; T. mentagrophytes (=T. quinckeanum); T. rubrum; T. schoenleinii; T. simii; T. terrestre; T. verrucosum.
Open in new tabDownload slide

Distribution of interspecies (broken line) and intraspecies (solid line) pairwise Kimura 2-parameter genetic distances in Trichophyton including T. ajelloi; T. erinacei; T. interdigitale; T. mentagrophytes (=T. quinckeanum); T. rubrum; T. schoenleinii; T. simii; T. terrestre; T. verrucosum.

Table 5.

Barcoding gap based on Kimura 2-parameter genetic distances in 17 studied phylogenetic clades represented by more than two species, with two variants of analysis for Cryptococcus neoformans/Cryptococcus gattii, and Arthrodermataceae/Trichophyton in the ISHAM-ITS reference database.

TaxaBarcoding gapSpecies included in the analyses represented with more than two strains by species
Acremonium0.055Acremonium fusidioides; A. implicatum; A. persicinum; Phialemonium atrogriseum; Sarocladium kiliense; S. strictum;
Arthrodermataceae0.002Arthroderma benhamiae; A. fulvum; A. gypseum; A. insingulare; A. otae; A. persicolor; A. simii; A. uncinatum; A. vanbreuseghemii
Aspergillus0.002Aspergillus calidoustus; A. flavus; A. fumigatiaffinis; A. fumigatus; A. hiratsukae; A. nidulans; A. niger; A. ochraceus; A. sydowii; A. terreus; A. tubingensis
Cladophialophora0.09Cladophialophora bantiana; C. boppii; C. carrionii
Cryptococcus (Filobasidiella clade divided into three taxa)–Cryptococcus gattii; C. neoformans var. grubii; C. neoformans var. neoformans
Cryptococcus (Filobasidiella clade divided into seven taxa)–Cryptococcus gattii VGI; C. gattii VGII; C. gattii VGIII; C. gattii VGIV; C. neoformans var. grubii VNI; C. neoformans var. grubii VNII; C. neoformans var. neoformans VNIV
Curvularia0.001Curvularia aeria; C. borreriae; C. inaequalis; C. geniculata; C. hawaiiensis; C. inaequalis; C. lunata; C. protuberata; C. spicifera; C. sorghina; C. verruculosa
Debaryomycetaceae (Lodderomyces clade)0.001Candida albicans; C. dubliniensis; C. metapsilosis; C. orthopsilosis; C. parapsilosis; C. tropicalis; Debaryomyces hansenii
Exophiala0.015Exophiala bergeri; E. dermatitidis; E. exophialae; E. jeanselmei; E. oligosperma; E. spinifera; E. xenobiotica
Fusarium–Fusarium delphinoides; F. falciforme; F. oxysporum; F. proliferatum; F. solani; F. keratoplasticum; F. petroliphilum; F. verticillioides
Metschnikowiaceae0.0603Candida duobushaemulonis; C. haemulonis; C. intermedia; C. lusitaniae; Kodamaea ohmeri
Microsporum0.0002Microsporum audouinii; M. canis; M. fulvum; M. gypseum
Pichiaceae0.005Pichia kudriavzevii; P. norvegensis; P. manshurica
Saccharomycetaceae0.009Kluyveromyces marxianus; K. lactis var. lactis; Saccharomyces cerevisiae; Torulaspora delbrueckii
Scedosporium–Scedosporium angustum; S. apiospermum; S. aurantiacum; S. boydii; S. dehoogii; S. ellipsoideum; S. minutisporum
Scopulariopsis0.0034Scopulariopsis brevicaulis; S. brumptii; S. cinerea; S. gracilis
Trichophyton–Trichophyton ajelloi; T. erinacei; T. interdigitale; T. mentagrophytes ( = T. quinckeanum); T. rubrum; T. schoenleinii; T. simii; T. terrestre; T. verrucosum
Trichosporon0.004Trichosporon asahii; T. dermatis; T. inkin; T. montevideense
TaxaBarcoding gapSpecies included in the analyses represented with more than two strains by species
Acremonium0.055Acremonium fusidioides; A. implicatum; A. persicinum; Phialemonium atrogriseum; Sarocladium kiliense; S. strictum;
Arthrodermataceae0.002Arthroderma benhamiae; A. fulvum; A. gypseum; A. insingulare; A. otae; A. persicolor; A. simii; A. uncinatum; A. vanbreuseghemii
Aspergillus0.002Aspergillus calidoustus; A. flavus; A. fumigatiaffinis; A. fumigatus; A. hiratsukae; A. nidulans; A. niger; A. ochraceus; A. sydowii; A. terreus; A. tubingensis
Cladophialophora0.09Cladophialophora bantiana; C. boppii; C. carrionii
Cryptococcus (Filobasidiella clade divided into three taxa)–Cryptococcus gattii; C. neoformans var. grubii; C. neoformans var. neoformans
Cryptococcus (Filobasidiella clade divided into seven taxa)–Cryptococcus gattii VGI; C. gattii VGII; C. gattii VGIII; C. gattii VGIV; C. neoformans var. grubii VNI; C. neoformans var. grubii VNII; C. neoformans var. neoformans VNIV
Curvularia0.001Curvularia aeria; C. borreriae; C. inaequalis; C. geniculata; C. hawaiiensis; C. inaequalis; C. lunata; C. protuberata; C. spicifera; C. sorghina; C. verruculosa
Debaryomycetaceae (Lodderomyces clade)0.001Candida albicans; C. dubliniensis; C. metapsilosis; C. orthopsilosis; C. parapsilosis; C. tropicalis; Debaryomyces hansenii
Exophiala0.015Exophiala bergeri; E. dermatitidis; E. exophialae; E. jeanselmei; E. oligosperma; E. spinifera; E. xenobiotica
Fusarium–Fusarium delphinoides; F. falciforme; F. oxysporum; F. proliferatum; F. solani; F. keratoplasticum; F. petroliphilum; F. verticillioides
Metschnikowiaceae0.0603Candida duobushaemulonis; C. haemulonis; C. intermedia; C. lusitaniae; Kodamaea ohmeri
Microsporum0.0002Microsporum audouinii; M. canis; M. fulvum; M. gypseum
Pichiaceae0.005Pichia kudriavzevii; P. norvegensis; P. manshurica
Saccharomycetaceae0.009Kluyveromyces marxianus; K. lactis var. lactis; Saccharomyces cerevisiae; Torulaspora delbrueckii
Scedosporium–Scedosporium angustum; S. apiospermum; S. aurantiacum; S. boydii; S. dehoogii; S. ellipsoideum; S. minutisporum
Scopulariopsis0.0034Scopulariopsis brevicaulis; S. brumptii; S. cinerea; S. gracilis
Trichophyton–Trichophyton ajelloi; T. erinacei; T. interdigitale; T. mentagrophytes ( = T. quinckeanum); T. rubrum; T. schoenleinii; T. simii; T. terrestre; T. verrucosum
Trichosporon0.004Trichosporon asahii; T. dermatis; T. inkin; T. montevideense
Open in new tab
Table 5.

Barcoding gap based on Kimura 2-parameter genetic distances in 17 studied phylogenetic clades represented by more than two species, with two variants of analysis for Cryptococcus neoformans/Cryptococcus gattii, and Arthrodermataceae/Trichophyton in the ISHAM-ITS reference database.

TaxaBarcoding gapSpecies included in the analyses represented with more than two strains by species
Acremonium0.055Acremonium fusidioides; A. implicatum; A. persicinum; Phialemonium atrogriseum; Sarocladium kiliense; S. strictum;
Arthrodermataceae0.002Arthroderma benhamiae; A. fulvum; A. gypseum; A. insingulare; A. otae; A. persicolor; A. simii; A. uncinatum; A. vanbreuseghemii
Aspergillus0.002Aspergillus calidoustus; A. flavus; A. fumigatiaffinis; A. fumigatus; A. hiratsukae; A. nidulans; A. niger; A. ochraceus; A. sydowii; A. terreus; A. tubingensis
Cladophialophora0.09Cladophialophora bantiana; C. boppii; C. carrionii
Cryptococcus (Filobasidiella clade divided into three taxa)–Cryptococcus gattii; C. neoformans var. grubii; C. neoformans var. neoformans
Cryptococcus (Filobasidiella clade divided into seven taxa)–Cryptococcus gattii VGI; C. gattii VGII; C. gattii VGIII; C. gattii VGIV; C. neoformans var. grubii VNI; C. neoformans var. grubii VNII; C. neoformans var. neoformans VNIV
Curvularia0.001Curvularia aeria; C. borreriae; C. inaequalis; C. geniculata; C. hawaiiensis; C. inaequalis; C. lunata; C. protuberata; C. spicifera; C. sorghina; C. verruculosa
Debaryomycetaceae (Lodderomyces clade)0.001Candida albicans; C. dubliniensis; C. metapsilosis; C. orthopsilosis; C. parapsilosis; C. tropicalis; Debaryomyces hansenii
Exophiala0.015Exophiala bergeri; E. dermatitidis; E. exophialae; E. jeanselmei; E. oligosperma; E. spinifera; E. xenobiotica
Fusarium–Fusarium delphinoides; F. falciforme; F. oxysporum; F. proliferatum; F. solani; F. keratoplasticum; F. petroliphilum; F. verticillioides
Metschnikowiaceae0.0603Candida duobushaemulonis; C. haemulonis; C. intermedia; C. lusitaniae; Kodamaea ohmeri
Microsporum0.0002Microsporum audouinii; M. canis; M. fulvum; M. gypseum
Pichiaceae0.005Pichia kudriavzevii; P. norvegensis; P. manshurica
Saccharomycetaceae0.009Kluyveromyces marxianus; K. lactis var. lactis; Saccharomyces cerevisiae; Torulaspora delbrueckii
Scedosporium–Scedosporium angustum; S. apiospermum; S. aurantiacum; S. boydii; S. dehoogii; S. ellipsoideum; S. minutisporum
Scopulariopsis0.0034Scopulariopsis brevicaulis; S. brumptii; S. cinerea; S. gracilis
Trichophyton–Trichophyton ajelloi; T. erinacei; T. interdigitale; T. mentagrophytes ( = T. quinckeanum); T. rubrum; T. schoenleinii; T. simii; T. terrestre; T. verrucosum
Trichosporon0.004Trichosporon asahii; T. dermatis; T. inkin; T. montevideense
TaxaBarcoding gapSpecies included in the analyses represented with more than two strains by species
Acremonium0.055Acremonium fusidioides; A. implicatum; A. persicinum; Phialemonium atrogriseum; Sarocladium kiliense; S. strictum;
Arthrodermataceae0.002Arthroderma benhamiae; A. fulvum; A. gypseum; A. insingulare; A. otae; A. persicolor; A. simii; A. uncinatum; A. vanbreuseghemii
Aspergillus0.002Aspergillus calidoustus; A. flavus; A. fumigatiaffinis; A. fumigatus; A. hiratsukae; A. nidulans; A. niger; A. ochraceus; A. sydowii; A. terreus; A. tubingensis
Cladophialophora0.09Cladophialophora bantiana; C. boppii; C. carrionii
Cryptococcus (Filobasidiella clade divided into three taxa)–Cryptococcus gattii; C. neoformans var. grubii; C. neoformans var. neoformans
Cryptococcus (Filobasidiella clade divided into seven taxa)–Cryptococcus gattii VGI; C. gattii VGII; C. gattii VGIII; C. gattii VGIV; C. neoformans var. grubii VNI; C. neoformans var. grubii VNII; C. neoformans var. neoformans VNIV
Curvularia0.001Curvularia aeria; C. borreriae; C. inaequalis; C. geniculata; C. hawaiiensis; C. inaequalis; C. lunata; C. protuberata; C. spicifera; C. sorghina; C. verruculosa
Debaryomycetaceae (Lodderomyces clade)0.001Candida albicans; C. dubliniensis; C. metapsilosis; C. orthopsilosis; C. parapsilosis; C. tropicalis; Debaryomyces hansenii
Exophiala0.015Exophiala bergeri; E. dermatitidis; E. exophialae; E. jeanselmei; E. oligosperma; E. spinifera; E. xenobiotica
Fusarium–Fusarium delphinoides; F. falciforme; F. oxysporum; F. proliferatum; F. solani; F. keratoplasticum; F. petroliphilum; F. verticillioides
Metschnikowiaceae0.0603Candida duobushaemulonis; C. haemulonis; C. intermedia; C. lusitaniae; Kodamaea ohmeri
Microsporum0.0002Microsporum audouinii; M. canis; M. fulvum; M. gypseum
Pichiaceae0.005Pichia kudriavzevii; P. norvegensis; P. manshurica
Saccharomycetaceae0.009Kluyveromyces marxianus; K. lactis var. lactis; Saccharomyces cerevisiae; Torulaspora delbrueckii
Scedosporium–Scedosporium angustum; S. apiospermum; S. aurantiacum; S. boydii; S. dehoogii; S. ellipsoideum; S. minutisporum
Scopulariopsis0.0034Scopulariopsis brevicaulis; S. brumptii; S. cinerea; S. gracilis
Trichophyton–Trichophyton ajelloi; T. erinacei; T. interdigitale; T. mentagrophytes ( = T. quinckeanum); T. rubrum; T. schoenleinii; T. simii; T. terrestre; T. verrucosum
Trichosporon0.004Trichosporon asahii; T. dermatis; T. inkin; T. montevideense
Open in new tab

Most of the studied taxa could be identified with the ITS barcode, although in some cases a clear discrimination could not be observed. There are two possible reasons for this: either the taxa is insufficiently studied or the ITS region is simply an inappropriate marker for discrimination between biologically consistent groups. Alternative loci and/or molecular methods are required for correct identification of these species (Table 5).

Discussion

ISHAM-ITS reference database

With a significant rise in the diversity of etiological agents of fungal infections in human and animal populations [1,2], rapid and accurate identification of pathogenic fungal species is one of the most important requirements for early and successful clinical treatment. As such, molecular information is expected to become a reliable tool for the identification of fungal species in medical diagnostic laboratories.

DNA barcoding represents a recent attempt to obtain rapid and accurate species identification based on comparative analysis of short but taxonomically significant sequences that has already found broad application in biology. However, the widespread application of fungal barcoding is hindered by a lack of reference databases. We herein report the establishment of the ISHAM-ITS reference database, containing 2800 quality controlled sequences, covering 421 human/animal pathogenic fungal species, which is publicly accessible at http://its.mycologylab.org/ and http://www.isham.org/. The principal roles of this reference database are to provide a reliable source for diagnostic medical and veterinary mycology laboratories, to enable correct identification of the causal agents of fungal infections, rapid diagnosis of mycoses, and early initiation of appropriate antifungal therapy (Fig. 11).

Figure 11.
Proposed working flow to identify human and animal pathogenic fungi.
Open in new tabDownload slide

Proposed working flow to identify human and animal pathogenic fungi.

Intraspecies variation

The intraspecies genetic diversity of the ITS region varied between 0 and 2.25% but in 170 species it was less than 1.5%. The data generated in the present study are in agreement with previous studies stating that the genetic diversity of the ITS regions in fungi varies between taxa and that a single cut-off value cannot be established [33,84]. One could hypothesize that highly invasive fungal species show little variability because they are fully adapted to the host environment. However, further analyses are necessary to determine whether or not the variability calculated within the ITS regions is representative of the general genotypic and phenotypic variability within these species. Notably, the intraspecies diversity is more complex, with intragenomic polymorphism of rDNA repeats documented in a number of fungal species [36,85]. Observed intraspecies diversity in medical fungi may partly be due to the intragenomic polymorphism. Although we were not able to address this issue, its impact on the functionality of the database is mitigated because the ITS sequences contained in the ISHAM-ITS reference database are the result of direct sequencing which leads to the amplification of the most abundant sequence in the sample.

Taxa with high intraspecies variation for which identification based solely on the ITS region could be problematic

In the ISHAM-ITS reference database, only six fungal species (C. intermedia, C. lusitaniae, F. solani, G. candidus, K. ohmeri, and L. ramosa) revealed an intraspecies diversity of more than 1.5%.

Clavispora lusitaniae

Among these six species, C. lusitaniae (the teleomorph of Candida lusitaniae) causes approximately 1–2% of episodes of candidemia, including nosocomial outbreaks [86]. The species is exceptionally polymorphic in the ITS region and the D2 domain of the large-subunit rDNA gene, containing more than 30 substitutions [87,88]. In the ISHAM-ITS reference database, the average nucleotide diversity for this species was 2.19%, with 22 polymorphic sites, which may be a problem for identification of strains with sequences that are currently not represented in the database. In this case, correct species identification, may be determined by mating type for sexual reproduction [89,90] (see Table 4). The polyphyletic nature of the genus Clavispora was recently confirmed by multigene sequence analysis [91]. Further taxonomic studies are required for a better delimitation of this species.

Fusarium solani species complex (FSSC)

The second highest intraspecies variation was found amongst Fusarium species, which are primarily saprobes, plant pathogens, often linked with pathological infections, mainly keratitis, in both humans and animals. The F. solani species complex is the most common group of fusaria responsible for human infections, primarily in immunocompromised individuals [92,93]. Before taxonomical reanalysis the ISHAM-ITS database contained ten different Fusarium species including the highly polyphyletic FSSC. Seven of these species showed below 0.5% intraspecies variability suggesting a good taxonomic delimitation which can in turn allow easy identification with the ITS. However, within the FSSC the average nucleotide diversity was 3.76%, indicating that this complex has remained unresolved and contains multiple other cryptic species. According to the latest taxonomic studies [94], F. keratoplasticum, F. petroliphilum, and F. falciforme have been separated from the FSSC as new taxa, reducing the average nucleotide diversity to 1.65% in the ISHAM-ITS reference database. This variation still represents a significantly high degree of sequence diversity, making it necessary to employ different markers for correct identification at the species level (Table 4 and see below).

Galactomyces candidus

G. candidus (anamorph Geotrichum candidum) is a ubiquitous and dimorphic yeast, which occurs commonly on moist substrates rich in nutrients. Occasionally it is found as an opportunistic pathogen in the human respiratory and gastro-intestinal tracts [92,95]. The taxonomic classification of the species was revised in 2004 by de Hoog and Smith [96]. A standardized protocol was proposed for the identification of G. candidus at species and strain level in 2006 [97]. According to a recent study [38], the ITS region, especially the ITS1 region of G. candidus, proved to be highly polymorphic at intraspecies and intragenomic levels. In the ISHAM-ITS database, the species was represented by five strains with 1.78% genetic diversity, mainly in the ITS1 region. Although the 18S-ITS1-5.8S-ITS2-26S as a whole provides an improved phylogenetic resolution for the different phylotypes, use of the ITS region alone is not suitable for rapid identification of the species [38].

Kodamaea ohmeri

Using the ISHAM-ITS reference database, K. ohmeri (syn.: Pichia ohmeri, the teleomorph of Candida guilliermondii var. membranifaciens) has been found to contain high intraspecies diversity. This is an ascosporogenic yeast, mainly used in the food industry for fermentation, but has recently emerged as a fungal pathogen, particularly in immunocompromised patients [98,99]. However, few studies on this species have been done. Recently a number of species have been found with characteristics similar to those of K. ohmeri raising the possibility of cryptic species and the potential misidentification of previously described isolates [100]. Phylogenetic analyses of the ITS sequences contained in the ISHAM-ITS reference database supported two clades not previously identified. Further studies are needed to taxonomically resolve possible cryptic species.

Lichtheimia spp

The next group of fungi with marked ITS intraspecies variation was Lichtheimia species, which causes life-threating rhinocerebral and bronchorespiratory mucormycoses [101]. Multigene sequence analysis (ITS, 28S, EF-1α) of 38 isolates identified morphologically as L. corymbifera revealed a new species, named L. ramosa, which differed in morphology and nucleotide sequences from L. corymbifera [102]. To date, from the five recognized species of the genus Lichtheimia, only three L. corymbifera, L. ornata, and L. ramosa are of clinical relevance [103]. L. ramosa proved to be more polymorphic than L. corymbifera, with more than 2% diversity in the ITS sequences. Similar values for the ITS region of L. ramosa have been reported by Walther et al. in 2013 [104], suggesting that different groups among L. ramosa should be considered as a separate species. If so, the ITS region would be an appropriate marker for identification of these species. In view of the high diversity observed among ITS sequences within Lichtheimia, currently it is recommended to use either a multiple gene approach [102] or MALDI-TOF [105] for a reliable identification (see Table 4).

Barcoding gap analysis

At interspecies level, clear barcoding gaps, ranging from 0.0002 to 0.09, were found in 13 of 17 taxonomical clades, containing at least three species with more than two strains. These included the taxa Acremonium, Arthrodermataceae, Aspergillus, Cladophialophora, Curvularia, Debaryomycetaceae (Lodderomyces clade), Exophiala, Metschnikowiaceae, Microsporum, Pichiaceae, Saccharomycetaceae, Scopulariopsis, and Trichosporon. Thus, the identification of these species based on ITS sequences is reliable, the taxonomy of the groups is well defined and all the species in the current dataset are well delimited. However, four taxa showed no clear barcoding gap: Cryptococcus, Fusarium, Scedosporium, and Trichophyton. The species of these four clades require more insight to fully understand if and why the ITS barcoding fails to dissect this specific group or if these species are not yet well isolated from a taxonomic point of view. Additional molecular methods or genetic markers are required to accurately identify the species in this group (Table 4). The barcoding gap analyses presented herein are based on the current dataset in the ISHAM-ITS database, which may not reflect all known cryptic species of all studied taxa, for example, it is well known that A. fumigatus is species complex, and ITS will only enable an identification to the species complex, with additional sequencing of either β-tubulin [106] and calmodulin [107] being needed to identify the actual species.

Overall, ITS barcoding can be used as a screening system to evaluate and indicate to specialists which species require more attention at the taxonomic level.

Cryptococcus neoformans/C. gattii species complex

The C. neoformans/C. gattii species complex is a good example of how the delimitation of a species can be improved by molecular characterization. Cryptococcosis is a life-threatening systemic mycosis in a broad range of animals and humans. Most cases are due two species belonging to the family Tremellaceae. The causal agent of cryptococcosis was originally considered as one species until four serotypes were identified based on antigenic properties of the polysaccharide capsule [108]. Currently, the etiologic agents of cryptococcosis are divided into two species, C. neoformans (serotypes A, D, and AD) and C. gattii (serotypes B and C) [109]. Molecular genotyping methods have more recently revealed seven major haplotypes among the two species [110–113]. These include three lineages in C. neoformans (VNI/AFLP1, VNII/AFLP1A/1B, and VNIV/AFLP3) and four in C. gattii (VGI/AFLP4, VGII/AFLP6, VGIII/AFLP5 and VGIV/AFLP7) [114]. As with other species complexes, the C. neoformans/C. gattii species complex is a controversial topic and there is no agreement amongst taxonomists regarding the delimitation of the species. This is likely due to the absence of a consensus species definition for fungi. It has been suggested that every molecular type should be considered as a different variety or even as separate species [113]. The ISHAM-ITS reference database contains a large set of ITS sequences representing all seven major haploid molecular types of the C. neoformans/C. gattii species complex. In order to determine the effect of accurate taxonomic recognition, the genetic diversity within and between species was calculated in two different ways: (a) considering only C. neoformans and C. gattii as species and (b) considering the seven major haplotypes as “species.” In the first case, the average intraspecies diversity was 0.35% for C. gattii and 0.19% for C. neoformans. These values are consistent with genetic diversity within species. However, in the barcoding gap analyses the K2P genetic distances overlapped significantly (Table 5, Fig. 7A). In the second analysis based on the seven species assumption, the average genetic diversity among molecular types was 0–0.1%, which was significantly less variation than in the analysis based on the two-species assumption (Table 5, Fig. 7B). However, a clear barcoding gap was still absent, but the overlap was considerably less than in the first set. The only reason for the absence of a barcoding gap was that the VNI and VNII molecular types of C. neoformans could not be separated by ITS sequencing, which confirmed previous findings (43). Alternative methods are therefore needed to fully resolve this species complex. Currently AFLP analysis [110], URA5-RFLP analysis [111], MLMT/SCAR analysis [115] and MLST analysis using the ISHAM consensus MLST scheme for the C. neoformans/C. gattii species complex, which includes the following genetic loci: CAP59, GPD1, LAC1, PLB1, SOD1, URA5, and IGS1 [114] are recommended to separate all major molecular types/potential species in this species complex.

Fusarium solani species complex (FSSC)

The second group of fungi lacking a clear barcoding gap comprised the FSSC. No clear barcoding gap was identified amongst Fusarium species in the ISHAM-ITS database (Fig. 8). The overlap of the K2P genetic distance within and between species was undeniably due to the poorly resolved F. solani species complex. For correct species identification, the following additional genetic loci are recommended: translation elongation factor 1-α (TEF-1α) and the RNA polymerase II gene (RPB2) [94]. An MLST method, including eight protein-coding genes was also developed to identify species in FSSC [116] (Table 4).

Scedosporium

The third group that lacked a barcoding gap was the ascomycetous fungal species of the genus Scedosporium (Microascaceae) (Fig. 9). They are well known emerging pathogens, which are associated with important human diseases [117–119] and animal infections [120]. In this group, important taxonomic changes have been made in recent years using different molecular methodologies [121]. Based on several genetic markers including the ITS region, S. apiospermum and S. boydii have been re-evaluated, resulting in the definition of S. apiospermum (heterothallic teleomorph Pseudallescheria apiosperma), S. boydii (homothallic teleomorph Pseudallescheria boydii), S. dehoogii, S. minutisporum and S. aurantiacum [122,123]. The routine identification of species within the genus Scedosporium is complicated due to a high intraspecies but little constant interspecies variability in morphological characters mixed within the various synanamorphs and teleomorphs [123]. The ITS regions are a widely used molecular marker for the identification of these species, possibly in association with other markers. According to a new molecular study, these species can be reliably identified by ITS sequencing, although the distances between certain species (S. boydii and S. apiospermum) remain very small [121]. The identification of newly described species within the genus, S. ellipsoideum, S. fusoideum, and S. angustum is also questionable if only ITS sequences are used, as they cluster within S. boydii, with limited statistical support [121]. In the ISHAM-ITS reference database, the intraspecies diversity of Scedosporium species was low, indicating that they are all well-delineated taxa. The highest divergence was observed in S. apiospermum, S. boydii, and S. dehoogii. However, at interspecies level, no clear barcoding gap has been found since the smallest interspecies distances (S. boydii – S. apiospermum and S. boydii – S. ellipsoideum) were smaller than the biggest intraspecies distances found in S. apiospermum, S. boydii, and S. dehoogii. As such, to obtain a clear differentiation among all Scedosporium species, the amplification of the large subunit rRNA (LSU) [124], β-tubulin (BT2) [122], or AFLP [121] are recommended (Table 4).

Dermatophytes

The last group of species, which did not show a defined barcoding gap was the dermatophytes (Fig. 10). They comprise a highly polyphyletic group of fungi that attack keratinized tissue of humans and animals, causing dermatophytoses [125]. The anamorphic stages of dermatophyte species belong mainly to the genera Microsporum, Trichophyton, and Epidermophyton, while their teleomorphic stages belonged to Arthroderma [125]. The taxonomy of dermatophyte species has been changed and revised several times [126,127]. The nomenclature has recently become more unsettled because separate names are no longer used for the anamorph/teleomorph stages of fungi [62]. The application of different molecular and biochemical methods has largely contributed to the description, delineation and taxonomical re-evaluation of these species. However, many taxonomic questions still remain unresolved in these taxa. According to a recent phylogenetic study using four genetic markers, including the ITS region, many anamorph species in Trichophyton share the same teleomorph genus Arthroderma [128]. The most recent taxonomy, nomenclature and phylogeny of the family are summarized in a review by Cafarchia et al. [127].

Currently, two opposing concepts exist for the medically well-known species Trichophyton mentagrophytes. In a phylogenetic study of the T. mentagrophytes complex by Gräser et al. [129], three clades containing T. mentagrophytes varieties were recovered. Based on clinical and morphological data, most varieties were reduced to synonym species, whereas two were elevated to species level [126,130,131]. This resulted in three clades assigned to T. erinacei, T. interdigitale and to T. mentagrophytes. The third clade was composed of two strains: CBS 318.56, originally identified as T. mentagrophytes var. mentagrophytes, and CBS 106.67, originally identified as T. mentagrophytes var. quinckeanum. The latter strain was considered incorrectly identified, and CBS 318.56 was designated by Gräser et al. [129] as the neotype for T. mentagrophytes. The choice of this neotype has been under debate ever since, as T. mentagrophytes in this sense are now encountered rarely in clinical surveys that use DNA sequencing for identification. At the same time, an unnamed zoophilic species closely related to T. interdigitale was detected which appeared to be quite common and seemed to fit the original concept of T. mentagrophytes [132,133]. In an article verifying the new dermatophyte taxonomy using mating results and phylogenetic analyses, Kawasaki [128] states that the selected neotype only corresponds to strains of T. mentagrophytes var. quinckeanum, a rather rare dermatophyte causing favus predominantly in rodents. Beguin et al. [72] found that the neotype strain CBS 318.56 was included in a clade consisting exclusively of strains originally identified as T. (mentagrophytes var.) quinckeanum. They also provided arguments on why this epithet should not be disposed of as a nomen nudum. Although part of the medical mycological community disagrees with the current neotype for T. mentagrophytes, no alternative neotype for T. mentagrophytes has been proposed so far.

In the ISHAM-ITS reference database, the three major genera of the dermatophytes are present with a number of species, including six Microsporum, 15 Trichophyton, four Arthroderma and one Epidermophyton species. These species showed a high similarity at the intraspecies level, except T. erinacei, which had still less than 1% ITS sequence variation. To evaluate the interspecies diversity and estimate the existence of a barcoding gap, the distribution of interspecies/intraspecies divergence in the genera Trichophyton and Microsporum was compared. The results indicated that there was a clear, though very small barcoding gap in the genus Microsporum but not in the genus Trichophyton, where the two overlapped. There were species, for example, T. erinacei, where the intraspecies K2P genetic distance exceeded the interspecies K2P distances between two species. The difference in the ITS region was only a few nucleotides, e.g., between T. mentagrophytes (= T. quinckeanum strains) and T. schoenleinii or between T. tonsurans and T. interdigitale. However, evaluation of the former teleomorph stages of the species revealed that there was a clear barcoding gap (Supplementary Fig. S2) in the family Arthrodermataceae, since the different former anamorph species have a common former teleomorph genus. Based on the results of this study and the complex taxonomy of the dermatophytes it is strongly recommended that other molecular or biochemical features, for example, BT2, AFLP, PCR fingerprinting, or microsatellite analysis, be used to accurately identify the closely related species (T. schoenleinii – T. mentagrophytes ( = T. quinckeanum), T. tonsurans – T. interdigitale and T. verrucosum – T. erinacei) of this group [72,134] (Table 4).

Algorithm consideration

The occurrence of taxa without a barcoding gap can be explained by the fact that the algorithms which have long been used by the barcoding community to calculate the genetic distances (K2P) [80] or the algorithm used in BLAST [135] for sequence matching between the query sequence and reference sequences represent different approaches from those commonly used for phylogenetic analyses. Both K2P and BLAST approaches are based on simple sequence similarities. The most commonly applied method for species delimitation using phylogenetic approaches in mycology is the genealogical concordance phylogenetic species recognition (GCPSR), first proposed by Taylor et al. [136]. This relies on the concordant discrimination of characters from three or more unlinked loci. Phylogenetic analysis can be performed using a variety of algorithms relying on complex, computationally intensive evolutionary models based on “phylogenetic signals.” These methods are more robust and require more computational power and expertise. In exchange they give a more reliable summary of the evolutionary relatedness of the members of a specific taxonomic group. A common question often arises in the barcoding community whether a phylogenetic model is necessary for DNA barcode sequence analyses. In this study, we tested the discriminatory power of the official fungal barcode, the ITS regions [28], to identify human and animal pathogenic fungi and showed that it is efficient, using a simple sequence similarity based algorithm, for the identification of an unknown fungal disease agent in the majority of species. However, in sibling/cryptic species with only 1–2 bp differences, identification based only on ITS sequencing may be unreliable. Many articles have been published discriminating species by only one or two polymorphic sites in the ITS region [43,47,121]. However, the majority of these studies used phylogenetic approaches, e.g., maximum likelihood, parsimony or Bayesian analysis [137–139]. It should be noted that, in contrast to phylogenetic methods, the DNA barcoding approach focuses on the use of a universal marker that maximises the number of specimens to be examined, whilst lowering the time spent on processing and analysis. This approach can be simplified in two major indications, namely specimen identification and species discovery [140,141]. The method popularly used in DNA barcoding approaches, K2P genetic distances, does not capture the same level of species distinctiveness with limited genetic variation. [142]. This is especially true when only one marker is used in the barcoding analyses. Specimen identification works best in concert with a well-annotated reference database that incorporates species boundaries delimited with phylogenetic multi-gene analyses. However, due to the paucity of sequence data in many fungi DNA databases barcoding will provide a first sweep of species discovery that should eventually be verified with more robust phylogenetic methods.

A basic step in phylogenetic analysis is the global alignment of all sequences. Beyond causing excessive gap opening and extension when divergent sequences are compared, this approach requires all sequences to be of the same length. It is questionable whether in the hectic practice of diagnostic labs this level of sequence quality and analytical care can be obtained, when the presence of life threatening pathogens has to be determined. Distance based algorithms seem to better fit these situations, maybe with upgrades in terms of taxonomic and bioinformatics conception [75,143,144], and with flexible distance algorithms [76].

The lack of interspecies gaps paves the way to three basic questions: (i) Is this relevant in the diagnostic practice? (ii) Is it due to unresolved taxonomy or to the intrinsic low power of the ITS barcode? and (iii) Are there taxonomic approaches and bioinformatics pipelines to reduce or resolve this problem?

The first question is a trivial one, but as long as the therapies for the unresolved species are similar, the lack of specific gaps is more a biological than a clinical problem. An attentive analysis from this point of view should accompany the purely taxonomic search, in order to pay particular attention to unresolved groups requiring different drug treatments. The second question is more complex. Many fungal species are not easily resolved for an exceeding number of taxonomic questions no matter of the single marker used. More insight on this point is necessary, maybe to develop easy to read indexes describing the ratio between the single marker vs. multiparameter species delimitation. This type of analysis seems to be necessary for further development of molecular markers in order to define their effective “taxonomic resolution power”. The evidence that many species presented a large variability does not impair the validity of ITS as a barcoding gene but suggest that particular attention must be paid in delimiting large species at the taxonomic level. Finally, the third question calls for a more attentive analysis of the species structure and of the algorithms necessary to discriminate them in fungi.

As a result of this study a quality–controlled reference ITS database, containing 2800 strains covering 421 species has been established and is publically accessible at http://its.mycologylab.org/ and http://www.isham.org/. The sequences selected in this study expand the number of medical species represented in the RTL ITS reference database at NCBI. There are several sequences with type information shared between the ISHAM-ITS database and RTL. Curators at NCBI will continuously verify additional single ITS accessions representing species where type information is currently unavailable. After a series of verifications these will serve as “verified” reference sequences [57] until a sequence obtained from type material is available. ISHAM-ITS database records are linked with their appropriate records at NCBI, similarly to the existing link between GenBank records and the UNITE and BOLD databases using Linkout (http://www.ncbi.nlm.nih.gov/projects/linkout/) and db_xref (http://www.ncbi.nlm.nih.gov/genbank/collab/db_xref) links. The results of the analysis of the sequences maintained in the database showed that ITS works well as a barcode for the majority of species. However, it has limitations in resolving species within species complexes and in sibling species delineation, where the difference of only one or a few nucleotide positions exist at the ITS locus. This study does not intend to challenge the current taxonomy of any fungal taxon. The goal was to highlight those taxa for the scientific community where additional genetic markers or molecular algorithms should be used for the reliable species identification.

Call for participation

The database is intended to cover all clinically relevant fungal species. It is open for further sequence submission to cover all medially relevant species with a sufficient number of strains, either via direct submission through the database (http://its.mycologylab.org/) or contacting the curators of the database (Prof. Wieland Meyer, wieland.meyer@sydney.edu.au or Laszlo Irinyi, laszlo.irinyi@sydney.edu.au).

This study was supported by an National Health and Medical Research Council of Australia (NH&MRC) grant [#APP1031952] to W Meyer, S Chen, V Robert, and D Ellis; CNPq [350338/2000-0] and FAPERJ [E-26/103.157/2011] grants to RM Zancopé-Oliveira; CNPq [308011/2010-4] and FAPESP [2007/08575-1] Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP) grants to AL Colombo; PEst-OE/BIA/UI4050/2014 from Fundação para a Ciência e Tecnologia (FCT) to C Pais; the Belgian Science Policy Office (Belspo) to BCCM/IHEM; the MEXBOL program of CONACyT-Mexico, [ref. number: 122896] to ML Taylor and [122481] to C Toriello; the Institut Pasteur and Institut de Veille Sanitaire to F Dromer and D Garcia-Hermoso; and the grants from the Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) and the Fundação de Amparo a Pesquisa do Estado de Goiás (FAPEG) to CM de Almeida Soares and JA Parente Rocha. I Arthur would like to thank G Cherian, A Higgins and the staff of the Molecular Diagnostics Laboratory, Division of Microbiology and Infectious Diseases, PathWest, QEII Medical Centre. F Dromer would like to thank for the technical help of the sequencing facility and specifically that of L Diancourt, A-S Delannoy-Vieillard, J-M Thiberge (Genotyping of Pathogens and Public Health, Institut Pasteur). RM Zancopé-Oliveira would like to thank the Genomic/DNA Sequencing Platform at Fundação Oswaldo Cruz—PDTIS/FIOCRUZ [RPT01A], Brazil for the sequencing. B Robbertse and CL Schoch acknowledge support from the Intramural Research Program of the NIH, National Library of Medicine. T Sorrell's work is funded by the NH&MRC of Australia; she is a Sydney Medical School Foundation Fellow.

Declaration of interest

The authors report no conflicts of interest. The authors alone are responsible for the content and the writing of the paper.

Supplementary material

Supplementary material is available at Medical Mycology online (http://www.mmy.oxfordjournals.org/).

References

1.
Brown
GD
, 
Denning
DW
, 
Gow
NA
, et al. 
Hidden killers: human fungal infections
, 
Sci Transl Med
, 
2012
, vol. 
4
 
165
pg. 
165rv113
 

Google Scholar

Crossref
Search ADS

 
2.
Fisher
MC
, 
Henk
DA
, 
Briggs
CJ
, et al. 
Emerging fungal threats to animal, plant and ecosystem health
, 
Nature
, 
2012
, vol. 
484
 
7393
(pg. 
186
-
194
)

Google Scholar

Crossref
Search ADS
PubMed

 
3.
Sobel
JD
. 
Vulvovaginal candidosis
, 
Lancet
, 
2007
, vol. 
369
 
9577
(pg. 
1961
-
1971
)

Google Scholar

Crossref
Search ADS
PubMed

 
4.
Bitar
D
, 
Lortholary
O
, 
Le Strat
Y
, et al. 
Population-based analysis of invasive fungal infections, France, 2001–2010
, 
Emerg Infect Dis
, 
2014
, vol. 
20
 
7
(pg. 
1149
-
1155
)

Google Scholar

Crossref
Search ADS
PubMed

 
5.
Nucci
M
, 
Queiroz-Telles
F
, 
Alvarado-Matute
T
, et al. 
Epidemiology of candidemia in Latin America: a laboratory-based survey
, 
PLoS One
, 
2013
, vol. 
8
 
3
pg. 
e59373
 

Google Scholar

Crossref
Search ADS
PubMed

 
6.
Chen
SC
, 
Slavin
MA
, 
Heath
CH
, et al. 
Clinical manifestations of Cryptococcus gattii infection: determinants of neurological sequelae and death
, 
Clin Infect Dis
, 
2012
, vol. 
55
 
6
(pg. 
789
-
798
)

Google Scholar

Crossref
Search ADS
PubMed

 
7.
Keay
LJ
, 
Gower
EW
, 
Iovieno
A
, et al. 
Clinical and microbiological characteristics of fungal keratitis in the United States, 2001-2007: a multicenter study
, 
Ophthalmology
, 
2011
, vol. 
118
 
5
(pg. 
920
-
926
)

Google Scholar

Crossref
Search ADS
PubMed

 
8.
Hebert
PD
, 
Cywinska
A
, 
Ball
SL
, et al. 
Biological identifications through DNA barcodes
, 
Proc Biol Sci
, 
2003
, vol. 
270
 (pg. 
1512
(pg. 
313
-
321
)

Google Scholar

Crossref
Search ADS

 
9.
Frezal
L
, 
Leblois
R
. 
Four years of DNA barcoding: current advances and prospects
, 
Infect Genet Evol
, 
2008
, vol. 
8
 
5
(pg. 
727
-
736
)

Google Scholar

Crossref
Search ADS
PubMed

 
10.
Meyer
CP
, 
Paulay
G
. 
DNA barcoding: error rates based on comprehensive sampling
, 
PLoS Biol
, 
2005
, vol. 
3
 
12
pg. 
e422
 

Google Scholar

Crossref
Search ADS
PubMed

 
11.
Hebert
PD
, 
Ratnasingham
S
, 
deWaard
JR
. 
Barcoding animal life: cytochrome c oxidase subunit 1 divergences among closely related species
, 
Proc Biol Sci
, 
2003
, vol. 
270
 
Suppl 1
(pg. 
S96
-
99
)

Google Scholar

Crossref
Search ADS
PubMed

 
12.
Letourneau
A
, 
Seena
S
, 
Marvanová
L
, et al. 
Potential use of barcoding to identify aquatic hyphomycetes
, 
Fungal Divers
, 
2010
, vol. 
40
 
1
(pg. 
51
-
64
)

Google Scholar

Crossref
Search ADS

 
13.
Dayrat
B
. 
Towards integrative taxonomy
, 
Biol J Linn Soc
, 
2005
, vol. 
85
 
3
(pg. 
407
-
415
)

Google Scholar

Crossref
Search ADS

 
14.
Seifert
KA
, 
Samson
RA
, 
Dewaard
JR
, et al. 
Prospects for fungus identification using CO1 DNA barcodes, with Penicillium as a test case
, 
Proc Natl Acad Sci U S A
, 
2007
, vol. 
104
 
10
(pg. 
3901
-
3906
)

Google Scholar

Crossref
Search ADS
PubMed

 
15.
Tanabe
Y
, 
Watanabe
MM
, 
Sugiyama
J
. 
Evolutionary relationships among basal fungi (Chytridiomycota and Zygomycota): Insights from molecular phylogenetics
, 
J Gen Appl Microbiol
, 
2005
, vol. 
51
 
5
(pg. 
267
-
276
)

Google Scholar

Crossref
Search ADS
PubMed

 
16.
Hofstetter
V
, 
Miadlikowska
J
, 
Kauff
F
, et al. 
Phylogenetic comparison of protein-coding versus ribosomal RNA-coding sequence data: a case study of the Lecanoromycetes (Ascomycota)
, 
Mol Phylogenet Evol
, 
2007
, vol. 
44
 
1
(pg. 
412
-
426
)

Google Scholar

Crossref
Search ADS
PubMed

 
17.
Crespo
A
, 
Lumbsch
HT
, 
Mattsson
JE
, et al. 
Testing morphology-based hypotheses of phylogenetic relationships in Parmeliaceae (Ascomycota) using three ribosomal markers and the nuclear RPB1 gene
, 
Mol Phylogenet Evol
, 
2007
, vol. 
44
 
2
(pg. 
812
-
824
)

Google Scholar

Crossref
Search ADS
PubMed

 
18.
McLaughlin
DJ
, 
Hibbett
DS
, 
Lutzoni
F
, et al. 
The search for the fungal tree of life
, 
Trends Microbiol
, 
2009
, vol. 
17
 
11
(pg. 
488
-
497
)

Google Scholar

Crossref
Search ADS
PubMed

 
19.
O'Donnell
K
, 
Rooney
AP
, 
Proctor
RH
, et al. 
Phylogenetic analyses of RPB1 and RPB2 support a middle Cretaceous origin for a clade comprising all agriculturally and medically important fusaria
, 
Fungal Genet Biol
, 
2013
, vol. 
52
 (pg. 
20
-
31
)

Google Scholar

Crossref
Search ADS
PubMed

 
20.
James
TY
, 
Kauff
F
, 
Schoch
CL
, et al. 
Reconstructing the early evolution of Fungi using a six-gene phylogeny
, 
Nature
, 
2006
, vol. 
443
 
7113
(pg. 
818
-
822
)

Google Scholar

Crossref
Search ADS
PubMed

 
21.
Schoch
CL
, 
Sung
GH
, 
Lopez-Giráldez
F
, et al. 
The Ascomycota tree of life: a phylum-wide phylogeny clarifies the origin and evolution of fundamental reproductive and ecological traits
, 
Syst Biol
, 
2009
, vol. 
58
 
2
(pg. 
224
-
239
)

Google Scholar

Crossref
Search ADS
PubMed

 
22.
O'Donnell
K
, 
Sutton
DA
, 
Rinaldi
MG
, et al. 
Internet-accessible DNA sequence database for identifying fusaria from human and animal infections
, 
J Clin Microbiol
, 
2010
, vol. 
48
 
10
(pg. 
3708
-
3718
)

Google Scholar

Crossref
Search ADS
PubMed

 
23.
Frisvad
JC
, 
Samson
RA
. 
Polyphasic taxonomy of Penicillium subgenus Penicillium—a guide to identification of food and air-borne terverticillate penicillia and their mycotoxins
, 
Stud Mycol
, 
2004
, vol. 
49
 (pg. 
1
-
174
)

Google Scholar

OpenURL Placeholder Text

 
24.
Hibbett
DS
, 
Binder
M
, 
Bischoff
JF
, et al. 
A higher-level phylogenetic classification of the Fungi
, 
Mycol Res
, 
2007
, vol. 
111
 
5
(pg. 
509
-
547
)

Google Scholar

Crossref
Search ADS
PubMed

 
25.
Hibbett
DS
, 
Ohman
A
, 
Glotzer
D
, et al. 
Progress in molecular and morphological taxon discovery in Fungi and options for formal classification of environmental sequences
, 
Fungal Biol Rev
, 
2011
, vol. 
25
 
1
(pg. 
38
-
47
)

Google Scholar

Crossref
Search ADS

 
26.
Geiser
DM
, 
Gueidan
C
, 
Miadlikowska
J
, et al. 
Eurotiomycetes: Eurotiomycetidae and Chaetothyriomycetidae
, 
Mycologia
, 
2006
, vol. 
98
 
6
(pg. 
1053
-
1064
)

Google Scholar

Crossref
Search ADS
PubMed

 
27.
Spatafora
JW
, 
Sung
GH
, 
Johnson
D
, et al. 
A five-gene phylogeny of Pezizomycotina
, 
Mycologia
, 
2006
, vol. 
98
 
6
(pg. 
1018
-
1028
)

Google Scholar

Crossref
Search ADS
PubMed

 
28.
Schoch
CL
, 
Seifert
KA
, 
Huhndorf
S
, et al. 
Nuclear ribosomal internal transcribed spacer (ITS) region as a universal DNA barcode marker for Fungi
, 
Proc Natl Acad Sci U S A
, 
2012
, vol. 
109
 
16
(pg. 
6241
-
6246
)

Google Scholar

Crossref
Search ADS
PubMed

 
29.
Kiss
L
. 
Limits of nuclear ribosomal DNA internal transcribed spacer (ITS) sequences as species barcodes for Fungi
, 
Proc Natl Acad Sci U S A
, 
2012
, vol. 
109
 
27
pg. 
E1811
 

Google Scholar

Crossref
Search ADS
PubMed

 
30.
Rakeman
JL
, 
Bui
U
, 
Lafe
K
, et al. 
Multilocus DNA sequence comparisons rapidly identify pathogenic molds
, 
J Clin Microbiol
, 
2005
, vol. 
43
 
7
(pg. 
3324
-
3333
)

Google Scholar

Crossref
Search ADS
PubMed

 
31.
Balajee
SA
, 
Houbraken
J
, 
Verweij
PE
, et al. 
Aspergillus species identification in the clinical setting
, 
Stud Mycol
, 
2007
, vol. 
59
 (pg. 
39
-
46
)

Google Scholar

Crossref
Search ADS
PubMed

 
32.
Rojas
EI
, 
Rehner
SA
, 
Samuels
GJ
, et al. 
Colletotrichum gloeosporioides s.l. associated with Theobroma cacao and other plants in Panama: multilocus phylogenies distinguish host-associated pathogens from asymptomatic endophytes
, 
Mycologia
, 
2010
, vol. 
102
 
6
(pg. 
1318
-
1338
)

Google Scholar

Crossref
Search ADS
PubMed

 
33.
Nilsson
RH
, 
Kristiansson
E
, 
Ryberg
M
, et al. 
Intraspecific ITS variability in the kingdom Fungi as expressed in the international sequence databases and its implications for molecular species identification
, 
Evol Bioinform Online
, 
2008
, vol. 
4
 (pg. 
193
-
201
)

Google Scholar

PubMed
OpenURL Placeholder Text

 
34.
Blaalid
R
, 
Kumar
S
, 
Nilsson
RH
, et al. 
ITS1 versus ITS2 as DNA metabarcodes for fungi
, 
Mol Ecol Resour
, 
2013
, vol. 
13
 
2
(pg. 
218
-
224
)

Google Scholar

Crossref
Search ADS
PubMed

 
35.
Maleszka
R
, 
Clark-Walker
GD
. 
Magnification of the rDNA cluster in Kluyveromyces lactis
, 
Mol Gen Genet
, 
1990
, vol. 
223
 
2
(pg. 
342
-
344
)

Google Scholar

Crossref
Search ADS
PubMed

 
36.
Ganley
AR
, 
Kobayashi
T
. 
Highly efficient concerted evolution in the ribosomal DNA repeats: total rDNA repeat variation revealed by whole-genome shotgun sequence data
, 
Genome Res
, 
2007
, vol. 
17
 
2
(pg. 
184
-
191
)

Google Scholar

Crossref
Search ADS
PubMed

 
37.
Pasero
P
, 
Marilley
M
. 
Size variation of rDNA clusters in the yeasts Saccharomyces cerevisiae and Schizosaccharomyces pombe
, 
Mol Gen Genet
, 
1993
, vol. 
236
 (pg. 
2
-
3
)(pg. 
448
-
452
)

Google Scholar

OpenURL Placeholder Text

 
38.
Alper
I
, 
Frenette
M
, 
Labrie
S
. 
Ribosomal DNA polymorphisms in the yeast Geotrichum candidum
, 
Fungal Biol
, 
2011
, vol. 
115
 
12
(pg. 
1259
-
1269
)

Google Scholar

Crossref
Search ADS
PubMed

 
39.
Lindner
DL
, 
Carlsen
T
, 
Henrik Nilsson
R
, et al. 
Employing 454 amplicon pyrosequencing to reveal intragenomic divergence in the internal transcribed spacer rDNA region in Fungi
, 
Ecology and Evolution
, 
2013
, vol. 
3
 
6
(pg. 
1751
-
1764
)

Google Scholar

Crossref
Search ADS
PubMed

 
40.
Hughes
KW
, 
Petersen
RH
, 
Lodge
DJ
, et al. 
Evolutionary consequences of putative intra-and interspecific hybridization in agaric fungi
, 
Mycologia
, 
2013
, vol. 
105
 
6
(pg. 
1577
-
1594
)

Google Scholar

Crossref
Search ADS
PubMed

 
41.
Gräser
Y
, 
Kuijpers
AF
, 
Presber
W
, et al. 
Molecular taxonomy of the Trichophyton rubrum complex
, 
J Clin Microbiol
, 
2000
, vol. 
38
 
9
(pg. 
3329
-
3336
)

Google Scholar

PubMed
OpenURL Placeholder Text

 
42.
Meyer
W
, 
Gams
W
. 
Delimitation of Umbelopsis (Mucorales, Umbelopsidaceae fam. nov.) based on ITS sequence and RFLP data
, 
Mycol Res
, 
2003
, vol. 
107
 
Pt 3
(pg. 
339
-
350
)

Google Scholar

Crossref
Search ADS
PubMed

 
43.
Katsu
M
, 
Kidd
S
, 
Ando
A
, et al. 
The internal transcribed spacers and 5.8S rRNA gene show extensive diversity among isolates of the Cryptococcus neoformans species complex
, 
FEMS Yeast Res
, 
2004
, vol. 
4
 
4–5
(pg. 
377
-
388
)

Google Scholar

Crossref
Search ADS
PubMed

 
44.
Leaw
SN
, 
Chang
HC
, 
Sun
HF
, et al. 
Identification of medically important yeast species by sequence analysis of the internal transcribed spacer regions
, 
J Clin Microbiol
, 
2006
, vol. 
44
 
3
(pg. 
693
-
699
)

Google Scholar

Crossref
Search ADS
PubMed

 
45.
Begerow
D
, 
Nilsson
H
, 
Unterseher
M
, et al. 
Current state and perspectives of fungal DNA barcoding and rapid identification procedures
, 
Appl Microbiol Biotechnol
, 
2010
, vol. 
87
 
1
(pg. 
99
-
108
)

Google Scholar

Crossref
Search ADS
PubMed

 
46.
Romanelli
AM
, 
Sutton
DA
, 
Thompson
EH
, et al. 
Sequence-based identification of filamentous basidiomycetous fungi from clinical specimens: a cautionary note
, 
J Clin Microbiol
, 
2010
, vol. 
48
 
3
(pg. 
741
-
752
)

Google Scholar

Crossref
Search ADS
PubMed

 
47.
Symoens
F
, 
Jousson
O
, 
Planard
C
, et al. 
Molecular analysis and mating behaviour of the Trichophyton mentagrophytes species complex
, 
Int J Med Microbiol
, 
2011
, vol. 
301
 
3
(pg. 
260
-
266
)

Google Scholar

Crossref
Search ADS
PubMed

 
48.
Estrada-Bárcenas
DA
, 
Vite-Garín
T
, 
Navarro-Barranco
H
, et al. 
Genetic diversity of Histoplasma and Sporothrix complexes based on sequences of their ITS1-5.8S-ITS2 regions from the BOLD System
, 
Rev Iberoam Micol
, 
2014
, vol. 
31
 
1
(pg. 
90
-
94
)

Google Scholar

Crossref
Search ADS
PubMed

 
49.
Nakamura
Y
, 
Cochrane
G
, 
Karsch-Mizrachi
I
. 
The international nucleotide sequence database collaboration
, 
Nucleic Acids Res
, 
2013
, vol. 
41
 
Database issue
(pg. 
D21
-
24
)

Google Scholar

Crossref
Search ADS
PubMed

 
50.
Benson
DA
, 
Clark
K
, 
Karsch-Mizrachi
I
, et al. 
GenBank
, 
Nucleic Acids Res
, 
2014
, vol. 
42
 
D1
(pg. 
D32
-
D37
)

Google Scholar

Crossref
Search ADS
PubMed

 
51.
Bridge
PD
, 
Roberts
PJ
, 
Spooner
BM
, et al. 
On the unreliability of published DNA sequences
, 
New Phytologist
, 
2003
, vol. 
160
 
1
(pg. 
43
-
48
)

Google Scholar

Crossref
Search ADS

 
52.
Bidartondo
MI
. 
Preserving accuracy in GenBank
, 
Science
, 
2008
, vol. 
319
 
5870
pg. 
1616
 

Google Scholar

Crossref
Search ADS
PubMed

 
53.
Nilsson
RH
, 
Ryberg
M
, 
Kristiansson
E
, et al. 
Taxonomic reliability of DNA sequences in public sequence databases: a fungal perspective
, 
PLoS ONE
, 
2006
, vol. 
1
 
1
pg. 
e59
 

Google Scholar

Crossref
Search ADS
PubMed

 
54.
Ratnasingham
S
, 
Hebert
PD
. 
BOLD: The Barcode of Life Data System (http://www.barcodinglife.org)
, 
Mol Ecol Notes
, 
2007
, vol. 
7
 
3
(pg. 
355
-
364
)

Google Scholar

Crossref
Search ADS
PubMed

 
55.
Kõljalg
U
, 
Nilsson
RH
, 
Abarenkov
K
, et al. 
Towards a unified paradigm for sequence-based identification of Fungi
, 
Mol Ecol
, 
2013
, vol. 
22
 
21
(pg. 
5271
-
5277
)

Google Scholar

Crossref
Search ADS
PubMed

 
56.
RefSeq Targeted Loci Project
 
http://www.ncbi.nlm.nih.gov/genomes/static/refseqtarget.html
57.
Schoch
CL
, 
Robbertse
B
, 
Robert
V
, et al. 
Finding needles in haystacks: linking scientific names, reference specimens and molecular data for Fungi
, 
Database (Oxford)
, 
2014
, vol. 
2014
 

Google Scholar

OpenURL Placeholder Text

 
58.
Federhen
S
. 
Type material in the NCBI Taxonomy Database
, 
Nucleic Acids Research
, 
2014
59.
Park
B
, 
Park
J
, 
Cheong
KC
, et al. 
Cyber infrastructure for Fusarium: three integrated platforms supporting strain identification, phylogenetics, comparative genomics and knowledge sharing
, 
Nucleic Acids Res
, 
2011
, vol. 
39
 
Database issue
(pg. 
D640
-
646
)

Google Scholar

Crossref
Search ADS
PubMed

 
60.
Cerqueira
GC
, 
Arnaud
MB
, 
Inglis
DO
, et al. 
The Aspergillus genome database: multispecies curation and incorporation of RNA-Seq data to improve structural gene annotations
, 
Nucleic Acids Res
, 
2014
, vol. 
42
 
Database issue
(pg. 
D705
-
710
)

Google Scholar

Crossref
Search ADS
PubMed

 
61.
Barcoding of Medical Fungi
 
http://www.isham.org/WorkingGroups/barcoding/index.html
62.
McNeill
J
, 
Barrie
FR
, 
Buck
WR
, et al. , 
International Code of Nomenclature for Algae, Fungi, and Plants (Melbourne code)
, 
2012
Königstein
Koeltz Scientific Books

Google Scholar

OpenURL Placeholder Text

 
63.
Robert
V
, 
Stegehuis
G
, 
Stalpers
D
. 
The MycoBank engine and related databases
, 
2005
 
http://www.mycobank.org/
64.
Crous
PW
, 
Gams
W
, 
Stalpers
D
, et al. 
MycoBank: an online initiative to launch mycology into the 21st century
, 
Stud Mycol
, 
2004
, vol. 
50
 (pg. 
19
-
22
)

Google Scholar

OpenURL Placeholder Text

 
65.
Index Fungorum Partnership
, 
2014
 
http://www.indexfungorum.org/
66.
Kurtzman
CP
, 
Fell
JW
, 
Boekhout
T
. , 
The Yeasts: a Taxonomic Study
, 
2011
5th ed
Amsterdam, The Netherlands
Elsevier

Google Scholar

OpenURL Placeholder Text

 
67.
White
TJ
, 
Bruns
T
, 
Lee
S
. 
Innis
MA
, 
Gelfandm
DH
, 
Sninsky
JJ
, et al. 
Amplification and direct sequencing of fungal ribosomal RNA genes for phylogenetics
, 
PCR Protocols: a Guide to Methods and Applications
, 
1990
1st ed
New York
Academic Press
(pg. 
315
-
322
)

Google Scholar

OpenURL Placeholder Text

 
68.
Vilgalys
R
, 
Hester
M
. 
Rapid genetic identification and mapping of enzymatically amplified ribosomal DNA from several Cryptococcus species
, 
J Bacteriol
, 
1990
, vol. 
172
 
8
(pg. 
4238
-
4246
)

Google Scholar

Crossref
Search ADS
PubMed

 
69.
Gerrits van den Ende
AHG
, 
de Hoog
GS
. 
Variability and molecular diagnostics of the neurotropic species Cladophialophora bantiana
, 
Stud Mycol
, 
1999
, vol. 
43
 (pg. 
151
-
162
)

Google Scholar

OpenURL Placeholder Text

 
70.
Gardes
M
, 
Bruns
TD
. 
ITS primers with enhanced specificity for Basidiomycetes - application to the identification of mycorrhizae and rusts
, 
Mol Ecol
, 
1993
, vol. 
2
 
2
(pg. 
113
-
118
)

Google Scholar

Crossref
Search ADS
PubMed

 
71.
O'Donnell
K
. 
Reynolds
DR
, 
Taylor
JW
. 
Fusarium and its near relatives
, 
The Fungal Holomorph: Mitotic, Meiotic and Pleomorphic Speciation in Fungal Systematics
, 
1993
Wallingford, United Kingdom
CAB International
(pg. 
225
-
233
)

Google Scholar

OpenURL Placeholder Text

 
72.
Beguin
H
, 
Pyck
N
, 
Hendrickx
M
, et al. 
The taxonomic status of Trichophyton quinckeanum and T. interdigitale revisited: a multigene phylogenetic approach
, 
Med Mycol
, 
2012
, vol. 
50
 
8
(pg. 
871
-
882
)

Google Scholar

Crossref
Search ADS
PubMed

 
73.
Sequencher® version 4.9 sequence analysis software, Gene Codes Corporation, Ann Arbor, MI USA
 
http://www.genecodes.com/
74.
Bengtsson-Palme
J
, 
Ryberg
M
, 
Hartmann
M
, et al. 
Improved software detection and extraction of ITS1 and ITS2 from ribosomal ITS sequences of fungi and other eukaryotes for analysis of environmental sequencing data
, 
Methods Ecol Evol
, 
2013
, vol. 
4
 
10
(pg. 
914
-
919
)

Google Scholar

OpenURL Placeholder Text

 
75.
Antonielli
L
, 
Robert
V
, 
Corte
L
, et al. 
Centrality of objects in a multidimensional space and its effects on distance-based biological classifications
, 
Open Appl Inform J
, 
2011
, vol. 
5
 
Suppl 1-M3
(pg. 
11
-
19
)

Google Scholar

Crossref
Search ADS

 
76.
Robert
V
, 
Szöke
S
, 
Jabas
B
, et al. 
BioloMICS Software: Biological Data Management, Identification, Classification and Statistics
, 
Open Appl Inform J
, 
2011
, vol. 
5
 
Suppl 1-M10
(pg. 
87
-
98
)

Google Scholar

Crossref
Search ADS

 
77.
Thompson
JD
, 
Higgins
DG
, 
Gibson
TJ
. 
CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice
, 
Nucleic Acids Res
, 
1994
, vol. 
22
 
22
(pg. 
4673
-
4680
)

Google Scholar

Crossref
Search ADS
PubMed

 
78.
Tamura
K
, 
Peterson
D
, 
Peterson
N
, et al. 
MEGA5: molecular evolutionary genetics analysis using maximum likelihood, evolutionary distance, and maximum parsimony methods
, 
Mol Biol Evol
, 
2011
, vol. 
28
 
10
(pg. 
2731
-
2739
)

Google Scholar

Crossref
Search ADS
PubMed

 
79.
Librado
P
, 
Rozas
J
. 
DnaSP v5: a software for comprehensive analysis of DNA polymorphism data
, 
Bioinformatics
, 
2009
, vol. 
25
 
11
(pg. 
1451
-
1452
)

Google Scholar

Crossref
Search ADS
PubMed

 
80.
Kimura
M
. 
A simple method for estimating evolutionary rates of base substitutions through comparative studies of nucleotide sequences
, 
J Mol Evol
, 
1980
, vol. 
16
 
2
(pg. 
111
-
120
)

Google Scholar

Crossref
Search ADS
PubMed

 
81.
Nei
M
, 
Kumar
S
. , 
Molecular Evolution and Phylogenetics
, 
2000
Oxford
Oxford University Press

Google Scholar

OpenURL Placeholder Text

 
82.
R Core Team
R: A language and environment for statistical computing
, 
2013
Vienna, Austria
R Foundation for Statistical Computing
 
http://www.R-project.org/

Google Scholar

83.
de Hoog
GS
, 
Haase
G
, 
Chaturvedi
V
, et al. 
Taxonomy of medically important fungi in the molecular era
, 
Lancet Infect Dis
, 
2013
, vol. 
13
 
5
(pg. 
385
-
386
)

Google Scholar

Crossref
Search ADS
PubMed

 
84.
Smith
ME
, 
Douhan
GW
, 
Rizzo
DM
. 
Intra-specific and intra-sporocarp ITS variation of ectomycorrhizal fungi as assessed by rDNA sequencing of sporocarps and pooled ectomycorrhizal roots from a Quercus woodland
, 
Mycorrhiza
, 
2007
, vol. 
18
 
1
(pg. 
15
-
22
)

Google Scholar

Crossref
Search ADS
PubMed

 
85.
Simon
UK
, 
Weiß
M
. 
Intragenomic variation of fungal ribosomal genes is higher than previously thought
, 
Mol Biol Evol
, 
2008
, vol. 
25
 
11
(pg. 
2251
-
2254
)

Google Scholar

Crossref
Search ADS
PubMed

 
86.
Atkinson
BJ
, 
Lewis
RE
, 
Kontoyiannis
DP
. 
Candida lusitaniae fungemia in cancer patients: risk factors for amphotericin B failure and outcome
, 
Med Mycol
, 
2008
, vol. 
46
 
6
(pg. 
541
-
546
)

Google Scholar

Crossref
Search ADS
PubMed

 
87.
Lachance
MA
, 
Daniel
HM
, 
Meyer
W
, et al. 
The D1/D2 domain of the large-subunit rDNA of the yeast species Clavispora lusitaniae is unusually polymorphic
, 
FEMS Yeast Res
, 
2003
, vol. 
4
 
3
(pg. 
253
-
258
)

Google Scholar

Crossref
Search ADS
PubMed

 
88.
Taverna
CG
, 
Bosco-Borgeat
ME
, 
Murisengo
OA
, et al. 
Comparative analyses of classical phenotypic method and ribosomal RNA gene sequencing for identification of medically relevant Candida species
, 
Mem Inst Oswaldo Cruz
, 
2013
, vol. 
108
 
2
(pg. 
178
-
185
)

Google Scholar

Crossref
Search ADS
PubMed

 
89.
François
F
, 
Noël
T
, 
Pépin
R
, et al. 
Alternative identification test relying upon sexual reproductive abilities of Candida lusitaniae strains isolated from hospitalized patients
, 
J Clin Microbiol
, 
2001
, vol. 
39
 
11
(pg. 
3906
-
3914
)

Google Scholar

Crossref
Search ADS
PubMed

 
90.
Noël
T
, 
Favel
A
, 
Michel-Nguyen
A
, et al. 
Differentiation between atypical isolates of Candida lusitaniae and Candida pulcherrima by determination of mating type
, 
J Clin Microbiol
, 
2005
, vol. 
43
 
3
(pg. 
1430
-
1432
)

Google Scholar

Crossref
Search ADS
PubMed

 
91.
Guzmán
B
, 
Lachance
MA
, 
Herrera
CM
. 
Phylogenetic analysis of the angiosperm-floricolous insect-yeast association: have yeast and angiosperm lineages co-diversified?
, 
Mol Phylogenet Evol
, 
2013
, vol. 
68
 
2
(pg. 
161
-
175
)

Google Scholar

Crossref
Search ADS
PubMed

 
92.
de Hoog
GS
, 
Guarro
J
, 
Gené
J
, et al. , 
Atlas of Clinical Fungi
, 
2000
2nd ed
The Netherlands
Centraalbureau voor Schimmelcultures, Utrecht, The Netherlands and Facultat de Medicina, Universitat Rovira i Virgili, Reus, Spain

Google Scholar

OpenURL Placeholder Text

 
93.
Dignani
MC
, 
Anaissie
E
. 
Human fusariosis
, 
Clin Microbiol Infect
, 
2004
, vol. 
10
 
Suppl 1
(pg. 
67
-
75
)

Google Scholar

Crossref
Search ADS
PubMed

 
94.
Short
DP
, 
O'Donnell
K
, 
Thrane
U
, et al. 
Phylogenetic relationships among members of the Fusarium solani species complex in human infections and the descriptions of F. keratoplasticum sp. nov. and F. petroliphilum stat. nov
, 
Fungal Genet Biol
, 
2013
, vol. 
53
 (pg. 
59
-
70
)

Google Scholar

Crossref
Search ADS
PubMed

 
95.
Carmichael
JW
. 
Geotrichum candidum
, 
Mycologia
, 
1957
, vol. 
49
 (pg. 
820
-
830
)

Google Scholar

Crossref
Search ADS

 
96.
de Hoog
GS
, 
Smith
MT
. 
Ribosomal gene phylogeny and species delimitation in Geotrichum and its teleomorphs
, 
Stud Mycol
, 
2004
, vol. 
50
 (pg. 
489
-
516
)

Google Scholar

OpenURL Placeholder Text

 
97.
Gente
S
, 
Sohier
D
, 
Coton
E
, et al. 
Identification of Geotrichum candidum at the species and strain level: proposal for a standardized protocol
, 
J Ind Microbiol Biotechnol
, 
2006
, vol. 
33
 
12
(pg. 
1019
-
1031
)

Google Scholar

Crossref
Search ADS
PubMed

 
98.
Han
XY
, 
Tarrand
JJ
, 
Escudero
E
. 
Infections by the yeast Kodamaea (Pichia) ohmeri: two cases and literature review
, 
Eur J Clin Microbiol Infect Dis
, 
2004
, vol. 
23
 
2
(pg. 
127
-
130
)

Google Scholar

Crossref
Search ADS
PubMed

 
99.
Otag
F
, 
Kuyucu
N
, 
Erturan
Z
, et al. 
An outbreak of Pichia ohmeri infection in the paediatric intensive care unit: case reports and review of the literature
, 
Mycoses
, 
2005
, vol. 
48
 
4
(pg. 
265
-
269
)

Google Scholar

Crossref
Search ADS
PubMed

 
100.
Lachance
MA
, 
Kurtzman
CP
. 
Kurtzman
CP
, 
Fell
JW
, 
Boekhout
T
. 
Kodamaea Y. Yamada, T. Suzuki, Matsuda & Mikata emend. Rosa, Lachance, Starmer, Barker, Bowles & Schlag-Edler (1999)
, 
The Yeasts: a taxonomic study
, 
2011
, vol. 
2
 Fifth ed
Amsterdam, The Netherlands
Elsevier
(pg. 
483
-
490
)

Google Scholar

OpenURL Placeholder Text

 
101.
Roden
MM
, 
Zaoutis
TE
, 
Buchanan
WL
, et al. 
Epidemiology and outcome of zygomycosis: a review of 929 reported cases
, 
Clin Infect Dis
, 
2005
, vol. 
41
 
5
(pg. 
634
-
653
)

Google Scholar

Crossref
Search ADS
PubMed

 
102.
Garcia-Hermoso
D
, 
Hoinard
D
, 
Gantier
JC
, et al. 
Molecular and phenotypic evaluation of Lichtheimia corymbifera (formerly Absidia corymbifera) complex isolates associated with human mucormycosis: rehabilitation of L. ramosa
, 
J Clin Microbiol
, 
2009
, vol. 
47
 
12
(pg. 
3862
-
3870
)

Google Scholar

Crossref
Search ADS
PubMed

 
103.
Alastruey-Izquierdo
A
, 
Hoffmann
K
, 
de Hoog
GS
, et al. 
Species recognition and clinical relevance of the zygomycetous genus Lichtheimia (syn. Absidia pro parte, Mycocladus)
, 
J Clin Microbiol
, 
2010
, vol. 
48
 
6
(pg. 
2154
-
2170
)

Google Scholar

Crossref
Search ADS
PubMed

 
104.
Walther
G
, 
Pawlowska
J
, 
Alastruey-Izquierdo
A
, et al. 
DNA barcoding in Mucorales: an inventory of biodiversity
, 
Persoonia
, 
2013
, vol. 
30
 (pg. 
11
-
47
)

Google Scholar

Crossref
Search ADS
PubMed

 
105.
Schrödl
W
, 
Heydel
T
, 
Schwartze
VU
, et al. 
Direct analysis and identification of pathogenic Lichtheimia species by matrix-sssisted laser desorption ionization–time of flight analyzer-mediated mass spectrometry
, 
J Clin Microbiol
, 
2012
, vol. 
50
 
2
(pg. 
419
-
427
)

Google Scholar

Crossref
Search ADS
PubMed

 
106.
Balajee
SA
, 
Borman
AM
, 
Brandt
ME
, et al. 
Sequence-based identification of Aspergillus, Fusarium, and Mucorales species in the clinical mycology laboratory: where are we and where should we go from here?
, 
J Clin Microbiol
, 
2009
, vol. 
47
 
4
(pg. 
877
-
884
)

Google Scholar

Crossref
Search ADS
PubMed

 
107.
Samson
RA
, 
Visagie
CM
, 
Houbraken
J
, et al. 
Phylogeny, identification and nomenclature of the genus Aspergillus
, 
Studies in Mycology
, 
2014
, vol. 
78
 (pg. 
141
-
173
)

Google Scholar

Crossref
Search ADS
PubMed

 
108.
Wilson
DE
, 
Bennett
JE
, 
Bailey
JW
. 
Serologic grouping of Cryptococcus neoformans
, 
Proc Soc Exp Biol Med
, 
1968
, vol. 
127
 
3
(pg. 
820
-
823
)

Google Scholar

Crossref
Search ADS
PubMed

 
109.
Kwon-Chung
KJ
, 
Boekhout
T
, 
Fell
JW
, et al. 
Proposal to conserve the name Cryptococcus gattii against C. hondurianus and C. bacillisporus (Basidiomycota, Hymenomycetes, Tremellomycetidae)
, 
Taxon
, 
2002
, vol. 
51
 (pg. 
804
-
806
)

Google Scholar

Crossref
Search ADS

 
110.
Boekhout
T
, 
Theelen
B
, 
Diaz
M
, et al. 
Hybrid genotypes in the pathogenic yeast Cryptococcus neoformans
, 
Microbiology
, 
2001
, vol. 
147
 
4
(pg. 
891
-
907
)

Google Scholar

Crossref
Search ADS
PubMed

 
111.
Meyer
W
, 
Castañeda
A
, 
Jackson
S
, et al. 
Molecular typing of IberoAmerican Cryptococcus neoformans isolates
, 
Emerg Infect Dis
, 
2003
, vol. 
9
 
2
(pg. 
189
-
195
)

Google Scholar

Crossref
Search ADS
PubMed

 
112.
Bovers
M
, 
Hagen
F
, 
Kuramae
EE
, et al. 
Six monophyletic lineages identified within Cryptococcus neoformans and Cryptococcus gattii by multi-locus sequence typing
, 
Fungal Genet Biol
, 
2008
, vol. 
45
 
4
(pg. 
400
-
421
)

Google Scholar

Crossref
Search ADS
PubMed

 
113.
Ngamskulrungroj
P
, 
Gilgado
F
, 
Faganello
J
, et al. 
Genetic diversity of the Cryptococcus species complex suggests that Cryptococcus gattii deserves to have varieties
, 
PLoS ONE
, 
2009
, vol. 
4
 
6
pg. 
e5862
 

Google Scholar

Crossref
Search ADS
PubMed

 
114.
Meyer
W
, 
Aanensen
DM
, 
Boekhout
T
, et al. 
Consensus multi-locus sequence typing scheme for Cryptococcus neoformans and Cryptococcus gattii
, 
Med Mycol
, 
2009
, vol. 
47
 
6
(pg. 
561
-
570
)

Google Scholar

Crossref
Search ADS
PubMed

 
115.
Hagen
F
, 
Illnait-Zaragozi
MT
, 
Meis
JF
, et al. 
Extensive genetic diversity within the Dutch clinical Cryptococcus neoformans population
, 
J Clin Microbiol
, 
2012
, vol. 
50
 
6
(pg. 
1918
-
1926
)

Google Scholar

Crossref
Search ADS
PubMed

 
116.
Debourgogne
A
, 
Gueidan
C
, 
Hennequin
C
, et al. 
Development of a new MLST scheme for differentiation of Fusarium solani Species Complex (FSSC) isolates
, 
J Microbiol Methods
, 
2010
, vol. 
82
 
3
(pg. 
319
-
323
)

Google Scholar

Crossref
Search ADS
PubMed

 
117.
Defontaine
A
, 
Zouhair
R
, 
Cimon
B
, et al. 
Genotyping study of Scedosporium apiospermum isolates from patients with cystic fibrosis
, 
J Clin Microbiol
, 
2002
, vol. 
40
 
6
(pg. 
2108
-
2114
)

Google Scholar

Crossref
Search ADS
PubMed

 
118.
Horre
R
, 
Marklein
G
, 
Siekmeier
R
, et al. 
Selective isolation of Pseudallescheria and Scedosporium species from respiratory tract specimens of cystic fibrosis patients
, 
Respiration
, 
2009
, vol. 
77
 
3
(pg. 
320
-
324
)

Google Scholar

Crossref
Search ADS
PubMed

 
119.
Matsumoto
Y
, 
Oh
IT
, 
Nagai
A
, et al. 
Case of cutaneous Scedosporium apiospermum infection successfully treated with voriconazole
, 
J Dermatol
, 
2009
, vol. 
36
 
2
(pg. 
98
-
102
)

Google Scholar

Crossref
Search ADS
PubMed

 
120.
Elad
D
. 
Infections caused by fungi of the Scedosporium/Pseudallescheria complex in veterinary species
, 
Vet J
, 
2011
, vol. 
187
 
1
(pg. 
33
-
41
)

Google Scholar

Crossref
Search ADS
PubMed

 
121.
Lackner
M
, 
Klaassen
CH
, 
Meis
JF
, et al. 
Molecular identification tools for sibling species of Scedosporium and Pseudallescheria
, 
Med Mycol
, 
2012
, vol. 
50
 
5
(pg. 
497
-
508
)

Google Scholar

Crossref
Search ADS
PubMed

 
122.
Gilgado
F
, 
Cano
J
, 
Gené
J
, et al. 
Molecular phylogeny of the Pseudallescheria boydii species complex: proposal of two new species
, 
J Clin Microbiol
, 
2005
, vol. 
43
 
10
(pg. 
4930
-
4942
)

Google Scholar

Crossref
Search ADS
PubMed

 
123.
Gilgado
F
, 
Gené
J
, 
Cano
J
, et al. 
Heterothallism in Scedosporium apiospermum and description of its teleomorph Pseudallescheria apiosperma sp. nov
, 
Med Mycol
, 
2010
, vol. 
48
 
1
(pg. 
122
-
128
)

Google Scholar

Crossref
Search ADS
PubMed

 
124.
Rainer
J
, 
de Hoog
GS
. 
Molecular taxonomy and ecology of Pseudallescheria, Petriella and Scedosporium prolificans (Microascaceae) containing opportunistic agents on humans
, 
Mycol Res
, 
2006
, vol. 
110
 
Pt 2
(pg. 
151
-
160
)

Google Scholar

Crossref
Search ADS
PubMed

 
125.
Weitzman
I
, 
Summerbell
RC
. 
The dermatophytes
, 
Clin Microbiol Rev
, 
1995
, vol. 
8
 
2
(pg. 
240
-
259
)

Google Scholar

PubMed
OpenURL Placeholder Text

 
126.
Gräser
Y
, 
El Fari
M
, 
Vilgalys
R
, et al. 
Phylogeny and taxonomy of the family Arthrodermataceae (dermatophytes) using sequence analysis of the ribosomal ITS region
, 
Med Mycol
, 
1999
, vol. 
37
 
2
(pg. 
105
-
114
)

Google Scholar

Crossref
Search ADS
PubMed

 
127.
Cafarchia
C
, 
Iatta
R
, 
Latrofa
MS
, et al. 
Molecular epidemiology, phylogeny and evolution of dermatophytes
, 
Infect Genet Evol
, 
2013
, vol. 
20
 (pg. 
336
-
351
)

Google Scholar

Crossref
Search ADS
PubMed

 
128.
Kawasaki
M
. 
Verification of a taxonomy of dermatophytes based on mating results and phylogenetic analyses
, 
Med Mycol
, 
2011
, vol. 
52
 
4
(pg. 
291
-
295
)

Google Scholar

Crossref
Search ADS

 
129.
Gräser
Y
, 
Kuijpers
AFA
, 
Presber
W
, et al. 
Molecular taxonomy of Trichophyton mentagrophytes and T. tonsurans
, 
Med Mycol
, 
1999
, vol. 
37
 
5
(pg. 
315
-
330
)

Google Scholar

Crossref
Search ADS
PubMed

 
130.
Kaszubiak
A
, 
Klein
S
, 
de Hoog
GS
, et al. 
Population structure and evolutionary origins of Microsporum canis, M. ferrugineum and M. audouinii
, 
Infect Genet Evol
, 
2004
, vol. 
4
 
3
(pg. 
179
-
186
)

Google Scholar

Crossref
Search ADS
PubMed

 
131.
Summerbell
RC
, 
Haugland
RA
, 
Li
A
, et al. 
rRNA gene internal transcribed spacer 1 and 2 sequences of asexual, anthropophilic dermatophytes related to Trichophyton rubrum
, 
J Clin Microbiol
, 
1999
, vol. 
37
 
12
(pg. 
4005
-
4011
)

Google Scholar

PubMed
OpenURL Placeholder Text

 
132.
Ninet
B
, 
Jan
I
, 
Bontems
O
, et al. 
Identification of dermatophyte species by 28S ribosomal DNA sequencing with a commercial kit
, 
J Clin Microbiol
, 
2003
, vol. 
41
 
2
(pg. 
826
-
830
)

Google Scholar

Crossref
Search ADS
PubMed

 
133.
Sun
PL
, 
Hsieh
HM
, 
Ju
YM
, et al. 
Molecular characterization of dermatophytes of the Trichophyton mentagrophytes complex found in Taiwan with emphasis on their correlation with clinical observations
, 
Br J Dermatol
, 
2010
, vol. 
163
 
6
(pg. 
1312
-
1318
)

Google Scholar

Crossref
Search ADS
PubMed

 
134.
Cafarchia
C
, 
Otranto
D
, 
Weigl
S
, et al. 
Molecular characterization of selected dermatophytes and their identification by electrophoretic mutation scanning
, 
Electrophoresis
, 
2009
, vol. 
30
 
20
(pg. 
3555
-
3564
)

Google Scholar

Crossref
Search ADS
PubMed

 
135.
Altschul
SF
, 
Gish
W
, 
Miller
W
, et al. 
Basic local alignment search tool
, 
J Mol Biol
, 
1990
, vol. 
215
 
3
(pg. 
403
-
410
)

Google Scholar

Crossref
Search ADS
PubMed

 
136.
Taylor
JW
, 
Jacobson
DJ
, 
Kroken
S
, et al. 
Phylogenetic species recognition and species concepts in Fungi
, 
Fungal Genet Biol
, 
2000
, vol. 
31
 
1
(pg. 
21
-
32
)

Google Scholar

Crossref
Search ADS
PubMed

 
137.
Fitch
WM
. 
Toward defining the course of evolution: minimum change for a specific tree topology
, 
Syst Zool
, 
1971
, vol. 
20
 
4
(pg. 
406
-
416
)

Google Scholar

Crossref
Search ADS

 
138.
Farris
JS
. 
Estimating phylogenetic trees from distance matrices
, 
Am Nat
, 
1972
, vol. 
106
 
951
(pg. 
645
-
668
)

Google Scholar

Crossref
Search ADS

 
139.
Yang
Z
, 
Rannala
B
. 
Bayesian phylogenetic inference using DNA sequences: a Markov Chain Monte Carlo Method
, 
Mol Biol Evol
, 
1997
, vol. 
14
 
7
(pg. 
717
-
724
)

Google Scholar

Crossref
Search ADS
PubMed

 
140.
Schindel
DE
, 
Miller
SE
. 
DNA barcoding a useful tool for taxonomists
, 
Nature
, 
2005
, vol. 
435
 
7038
pg. 
17
 

Google Scholar

Crossref
Search ADS
PubMed

 
141.
Collins
RA
, 
Cruickshank
RH
. 
The seven deadly sins of DNA barcoding
, 
Mol Ecol Resour
, 
2013
, vol. 
13
 
6
(pg. 
969
-
975
)

Google Scholar

PubMed
OpenURL Placeholder Text

 
142.
Boykin
LM
, 
Armstrong
KF
, 
Kubatko
L
, et al. 
Species delimitation and global biosecurity
, 
Evol Bioinform Online
, 
2012
, vol. 
8
 (pg. 
1
-
37
)

Google Scholar

PubMed
OpenURL Placeholder Text

 
143.
Antonielli
L
, 
Corte
L
, 
Roscini
L
, et al. 
A multidisciplinary approach to the microbial species concept: the role of bioinformatics in the search of detectable discontinuities
, 
Open Appl Inform J
, 
2011
, vol. 
5
 
Suppl 1-M2
(pg. 
3
-
10
)

Google Scholar

Crossref
Search ADS

 
144.
Robert
V
, 
Szöke
S
, 
Eberhardt
U
, et al. 
The quest for a general and reliable fungal DNA barcode
, 
Open Appl Inform J
, 
2011
, vol. 
5
 
Suppl 1-M6
(pg. 
45
-
61
)

Google Scholar

Crossref
Search ADS

 
© The Author 2015. Published by Oxford University Press on behalf of The International Society for Human and Animal Mycology. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com
Topic:
Issue Section:
Review Article
Download all slides
  • Supplementary data

    • Supplementary data

    Supplementary Data - zip file