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Official Journal of the Japan Wood Research Society

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Identification and species-typing of wood rotting fungi using melting curve analysis

Journal of Wood Science volume 59, pages 432–441 (2013)Cite this article

Abstract

A method for identification and typing of wood rotting fungi using the melting temperature [T(m)] of DNA fragments coding rRNA (rDNA) was examined. The T(m)s of four DNA fragments, inter transcribed spacer (ITS) I, ITS II, and two partial fragments of 28S rDNA from each of 20 species of wood rotting fungi, were measured by melting curve analysis. The T(m) variation was large enough between species to enable identification based on the T(m) values. A pair of T(m)s of the ITS I region (between the primers ITS1 and ITS2) and the ITS II region (between the primers ITS3 and ITS4) had the highest resolution for identifying wood rotting fungi. To assess about the diversity of the T(m), intraspecific diversity of these DNA fragment sequences was evaluated using test strain sequences and data from the GenBank/EMBL/DDBJ biological database. The intraspecific diversity of T(m) was considered to be small because the nucleotide diversity of each fragment was small within the species.

Introduction

Identification of fungal species, including wood rotting fungi, based on the morphology of fruiting bodies is difficult because time and environmental conditions change their morphology. Moreover, hyphal morphology and physiological features did not provide sufficient information to allow identification of fungal species. Tubes or dishes with fungal strains in them can be confused in the daily laboratory work. Identification of wood rotting fungi is important in the research of wood degradation and in the ongoing development of wood preservation. A correct, rapid, and convenient method to identify fungi is needed.

Recently, certain methods based on the information of biomolecules have been become popular for the identification of wood rotting fungi [1–8]. In particular, methods based on DNA nucleotide sequences are attractive because of their simplicity and accuracy [9–14]. The sequences used for fungal species identification and typing are ribosomal RNA genes (rDNAs), which contain three rDNA, the 18S, 28S, and 5.8S rDNA; inter transcribed spacer (ITS) regions; and a large intergenic spacer (IGS) region [15]. Sometimes another rDNA, the 5S, may be present within the IGS. The rDNA copy number varies widely; in most eukaryotes, it is between 30 and 30,000 copies [16] and the repeats are organized tandemly at one or more sites per haploid genome. The ITS region is located between the 18S and the 28S rDNA and consists of two spacers, the ITS I and the ITS II, and the 5.8S rDNA (Fig. 1). The spacers allow mutations and accumulate diversities of nucleotide sequences and length. Thus, the ITS region was employed for the detection and identification of environmental fungi because of its high sensitivity and resolution [17–19]. The D1/D2 region, a part of the 28S rDNA has sufficient diversity to allow for characterizing species and was adopted for that purpose [20–22].

Fig. 1
figure 1

Schematic diagram of the structure of fungal rDNA and the sites of the universal primers. a rDNA genes consisting of four genes, 18s rDNA, 5.8s rDNA, 28s rDNA, and 5s rDNA, are repeated. The open wide bar shows a coding region, and the solid thin bar shows a non-coding region. b The ITS region and the D1/D2 region. The ITS region consisted of the ITS I region, the ITS II region, and the 5.8s rDNA. Short arrows show the universal primers. Bars show the DNA fragments that are amplified by PCR using the universal primers

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DNA sequencing has been the main method used to identify microbial species including fungi, but the process requires an enormous amount of time, cost, and effort in some cases, such as for the stock management of numerous fungal strains in a laboratory or for handling a huge group of samples in an environmental analysis. Therefore, a simpler and higher throughput method is needed. Species-specific primers are convenient for detecting and identifying species [19, 23–25], but the development of these primers take a long time because the primers should be designed for each species. The melting temperature [T(m)] of a DNA fragment represents a characteristic of its sequence, because it is affected by its length and nucleotide sequence. The T(m) is obtained by melting curve analysis, which is conducted after polymerase chain reaction (PCR) amplification by means of a real-time PCR. The melting curve allows the analysis of differences in the T(m) to <0.1 °C and detection of a single nucleotide polymorphism, and is applied to the genotyping of pathogenic microbes [26–29]. The use of SYBR® green-based T(m) analysis lowers the cost of the procedure [30]. However, there have been no reports on the use of T(m)s representing character of long nucleotide sequences to identify fungal species.

In the present study, we determined the T(m)s of each of four types of DNA fragments to identify 20 species of wood rotting fungi that often appear in buildings and wood exteriors. The nucleotide variety of the sequences encountered in this study was investigated using not only the sequence information of the tested fungi, but also gene information obtained from the GenBank/EMBL/DDBJ database to examine the intraspecies variety of T(m).

Materials and methods

Fungal strains and DNA extraction

Fifty-seven strains of the 20-fungal species used in this study are listed in Table 1. The DNA of each fungal strain was extracted by the modified benzyl chloride method [31] using the ISOPLANT II DNA extraction kit (Nippon Gene, Tokyo, Japan). The mycelia of the test strains were collected from their growing mycelial mat on potato dextrose agar (PDA) plates. Approximately, 0.1 g of mycelia was placed in a 2.0-ml microtube, to which 500 μl of TE buffer (10 mM Tris–HCl, 0.1 mM EDTA, pH 8.0) and 10 μl of mercaptoethanol was added. Sample mycelia were ground for 2 min with a 7-mm zirconia bead at a frequency of 25 Hz, using a TissueLyser mixer mill grinder (Qiagen, Inc., CA, USA). Then, the DNA was extracted from ground tissue using the ISOPLANT II. The extracted DNA was dissolved in TE buffer, and its concentration was measured using a Nano drop ND-1000 (Thermo Scientific, DE, USA).

Table 1 Tested fungi
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Real-time PCR amplification and T(m) estimation by melting curve analysis

Four types of DNA fragments, the ITS I, the ITS II, and two parts of the D1/D2 region, were amplified using universal primers. The gene structure of rDNA including the ITS region, the D1/D2 region, and priming sites are shown in Fig. 1. Nucleotide sequences of the primers are shown in Table 2. In the present study, a DNA fragment between the primers is represented using the names of the two primers; for example, a fragment between primers ITS1 and ITS2, the ITS I, is presented as “ITS1–ITS2” and another fragment between the primers NL1 and NL2 is presented as “NL1–NL2”. Real-time PCR was performed in a 20-μl reaction containing 1 ng template DNA, SYBR® Premix Ex Taq™ Perfect Real Time (Takara Bio, Inc., Shiga, Japan) and 200 μM of each forward and reverse primer. The following program was performed on the Applied Biosystems 7000 real-time PCR system (Applied Biosystems, CA, USA): an initial denaturization step at 95 °C for 5 min followed by 40 cycles of denaturization at 95 °C for 5 s, followed by annealing and extension at 60 °C for 41 s [19]. After that, a dissociation stage was added with a slow ramp to 95 °C. The real-time PCR and melting curve analyses were carried out in triple-replication using three reaction wells for each template DNA.

Table 2 List of universal primers used
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Sequence analysis

Four types of DNA fragment were amplified by PCR using the Takara Ex Taq™ (Takara Bio, Inc., Shiga, Japan). The mixture contained 10 ng of template DNA; each primer at a concentration of 0.5 pM; each dNTP at a concentration of 200 nM, 1.2 U/100 μl of DNA polymerase; and expand reaction buffer with 1.5 mM MgCl2. PCR was performed with a GeneAmp 2720 thermal cycler (ABi, CA, USA) with the following parameters: an initial denaturization of 5 min at 95 °C, 25 cycles of 30 s at 95 °C for denaturization, 30 s at 56 °C for annealing, 60 s at 72 °C for extension, and a final extension of 7 min at 72 °C. All PCR products were stored at 4 °C until use. Aliquots of PCR products were checked by running them on 1.0 % agarose gel. The PCR products were cloned into a sequence vector using the pGEM T-vector system (Promega, WI, USA). A BigDye Terminator Cycle Sequencing Ready Reaction Kit (Applied Biosystems) was used to sequence the re-amplified fragments. The sequenced reactions were performed with a Prism 3100 genetic analyzer (Applied Biosystems). Sequences were compared with the compilation of 16S rDNA genes available in the GenBank/EMBL/DDBJ database. A BLAST search identified the first sequences retrieved.

Calculation of nucleotide diversity (π)

Nucleotide sequences for the species tested were obtained from the GenBank/DDBJ/EMBL database to estimate intraspecific diversity (Table 1). The sequences that were analyzed and downloaded were aligned using ClustalX 2.0. [32] and then optimized manually. The DnaSP ver. 5.10. [33] was used to estimate the average nucleotide diversity π [34], which was computed from an aligned dataset for each kind of DNA fragments for each species.

Results

The T(m) of the rDNA fragments for fungal identification

T(m)s of the rDNA fragments for fungal identification were determined by melting curve analysis and intraspecific average, and standard diversities of the T(m)s were calculated (Table 3). The T(m) was measured at least thrice for each strain, and the results within each strain were in good agreement. The intraspecific diversity of T(m) varied according to species. The average of the T(m)s for each fragment of all species were 85.1, 85.0, 85.4, and 87.2 °C at ITS1–ITS2, ITS3–ITS4, NL1–NL2, and NL3–NL4, respectively. Concerning Serpula lacrymans, the standard deviations (SDs) of 13 strains, which were 0.09, 0.13, 0.11, and 0.06 in fragments ITS1–ITS2, ITS3–ITS4, NL1–NL2, and NL3–NL4, respectively, were very small; while the SDs of 9 Trametes versicolor strains, which were 0.42, 0.23, 0.09, and 0.08, respectively, were a little larger. The larger SDs were observed in Bjerkandera adusta. The measured T(m) of the strain of B. adusta NBRC 4983 differed from that of the other strains of B. adusta. The new average T(m)s from the other strains of B. adusta were 86.5 °C (± 0.17), 85.5 °C (± 0.12), 85.6 °C (± 0.25), and 86.3 °C (± 0.12) in fragments ITS1–ITS2, ITS3–ITS4, NL1–NL2, and NL3–NL4, respectively. A single strain was used in Fomitopsis palustris, Ganoderma gibbosum, Pleurotus cystidiosus, Pycnoporus cinnabarinus, Stereum hirsutum, and Trametes pubescens, and the SDs of these species were not obtained.

Table 3 Melting temperature [T(m)] of DNA fragments to identify species of wood rot fungi, ITS1–ITS2, ITS3–ITS4, NL1–NL2, and NL3–NL4
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T(m) determination by the melting curve analysis in the present study had high reproducibility because it was almost not affected by quality and quantity of the template DNA solution. Multipeaks that indicate cross-contamination were not detected.

Species identification from the T(m) of the rDNA fragments

Fungal species discrimination using T(m) was examined for the 20 test species. Two types of T(m) were selected arbitrarily from the four, and one was plotted on the X-axis and the other on the Y-axis (Fig. 2A–C). The fact that the plots do not overlap implies that the combination of T(m)s has the ability to discriminate species. Sufficient diversity of T(m) to allow discrimination of the species was observed in fragments ITS1–ITS2, ITS3–ITS4, and NL3-NL4. The combination of ITS1–ITS2 and ITS3–ITS4 had higher resolution in most cases. The T(m)s of Fomitopsis palustris and Daedalea dickinsii were similar in this combination (Fig. 2A, a), as were those of T. pubescens and T. versicolor (Fig. 2A, b). For higher resolution, we examined the combination of three T(m)s for fragments ITS1–ITS2, ITS3–ITS4, and NL3–NL4 (Fig. 2D). The three-dimensional analysis was sufficient to discriminate those species.

Fig. 2
figure 2

Species identification by the combination of T(m)s from the four DNA fragments, ITS1–ITS2, ITS3–ITS4, NL1–NL2, and NL3–NL4. A–C The combination of two types of T(m). D The combination of three types of DNA fragments, ITS1–ITS2, ITS3–ITS4, and NL3–NL4. Dotted circles show examples of crowded plots; a Fomitopsis palstris and Daedalea dickinsii, b Trametes pubescens and Trametes versicolor

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Intraspecific diversity of nucleotide sequences

The four types of DNA fragments for each strain used in this study were determined and submitted to the DDBJ database. The accession numbers of the sequences determined in this study are AB592333–AB592336, AB733118–AB733170, AB733173–AB733301, AB733420–AB733431, and AB733644–AB733646 for the ITS region and AB592333, AB733172, AB733299–AB733348, and AB733411–AB733419 for the D1/D2 region. The average nucleotide diversity (π) of each DNA fragment for every species was calculated using the determined and downloaded sequences (Table 4). The π value exhibits the average number of nucleotide differences per site from two randomly selected sequences. The π values were small, <0.05 in all the ITS fragments except for the ITS of B. adusta, and close to 0.02 or less. The π of B. adusta in fragment ITS1–ITS2 was high, 0.121. To examine the cause, we checked the sequence data very carefully. The alignment data of fragment ITS1–ITS2 from the 17 sequences of B. adusta showed that only one sequence, AB733156 from B. adusta NBRC 4983, was very different from the others. The new alignment data eliminated the sequence of B. adusta NBRC 4983, which had a π value of 0.005, which was low compared to that of other species. Blast search showed that the whole region of ITS of B. adusta NBRC 4983 had a level of homology at 95 % with other ITS sequences of B. adusta, which was on a borderline between identification and error, and 99 % homology with Bjerkandera fumosa (AJ006673 and FJ903376). However, there was insufficient data on B. fumosa to evaluate whether NBRC 4983 was misidentified.

Table 4 Nucleotide diversity (π) of DNA fragments to identify species of wood rot fungi, ITS1–ITS2, ITS3–ITS4, NL1–NL2, and NL3–NL4
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Discussion

The results showed that the T(m)s of fragments ITS1–ITS2, ITS3–ITS4, and NL3–NL4 have almost enough diversity to identify species. The length of the ITS and D1/D2 regions that can be used as probes for species identification is 650 bp each. If a DNA fragment becomes long, the T(m) will become high and the difference in diversity of the nucleotide sequences will become hard to be reflected. Therefore, these probes were divided into two fragments, respectively. The average length of the fragments ITS1–ITS2, ITS3–ITS4, NL1–NL2, and NL3–NL4 in all tested species were 278.7 (±21.8 SD) bp, 388.9 (±19.4) bp, 353.9 (±10.3) bp, and 307.1 (±15.7) bp, respectively. To identify species using the PCR-based fungal identification, the DNA fragment must be amplifiable using the universal primers that are applied to most organisms, even when no genetic information can be obtained. For these reasons, the four fragments used in this study are considered to be appropriate for the analysis using T(m).

The results showed that the combination of T(m)s of two types of fragment was sufficient to identify species and that the melting curve analysis is a simple but effective, low cost tool for identifying fungal species. As many strains of each species as possible need to be tested to obtain a more accurate diagnosis. However, it is difficult to both collect a large number of strains and precisely identify the species. We calculated the data of the nucleotide diversity using the data of nucleotide sequence in the gene database and estimated the accuracy and intraspecific diversity of T(m) based on that calculation. The nucleotide diversities of the four types of DNA fragment were small in most of the species tested, and the diversity of the ITS region was larger than that of the D1/D2 region. It is easy to understand results because the ITS region is a non-coding spacer and the D1/D2 codes for the rRNA fragment. The intraspecies diversity of B. adusta is notable, because it reveals a problem of species diagnosis based on the nucleotide sequences. The case of B. adusta suggests that misidentification of species or the multi-genetic type included in the species leads to the estimation of a large T(m) and nucleotide diversity. In particular, having fewer samples may result in larger diversity. Therefore, the accumulation of accurate nucleotide information about fungi is required for improvement of the species identification method based on the DNA sequences. The 20 species in the present study were mainly selected as the fungi that often attack wooden house and construction. For utilizing T(m) of DNA as one of identification tools, a T(m) database also from many other species has to be established. Incorrect identification will be avoided using T(m) in conjunction with information on the fungal growing environment, decay type, mycelial morphology, etc. For example, F. palustris and D. dickinsii, those were not discriminated by two-dimensional T(m)s, could be distinguished using T(m)s together with their decay type (Table 1). However, it was impossible to discriminate of Trametes hirsuta and T. pubescens even using decay type. A dendrogram based on the ITS sequences of T. hirsuta and T. pubescens showed that some sequences of both species fell into the same cluster (data not shown). Therefore, re-examining classification of DNA sequences referenced is required to enhance the reliability of this typing method. The T(m)s will be a useful laboratory tool for the stock management of fungal strains because T(m) measurement is simpler and less cost with sequencing which is a conventional practice.

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Acknowledgments

We would like to thank Mr. Kensuke Hanata of the Akita Wood Technology Transfer Foundation for useful suggestions and Mr. Masato Maeda and Mr. Kodai Hamaguchi of Kochi University of Technology for their technical assistance.

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Authors and Affiliations

  1. Department of Environmental Systems Engineering, Faculty of Engineering, Kochi University of Technology, Kami-gun, Kochi, 782-8502, Japan

    Sakae Horisawa

  2. Graduate School of Science and Engineering, Ehime University, Matsuyama, Ehime, 790-8577, Japan

    Yoh Sakuma

  3. Graduate School of Life and Environmental Sciences, University of Tsukuba, Tsukuba, Ibaraki, 305−8572, Japan

    Shuichi Doi

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Horisawa, S., Sakuma, Y. & Doi, S. Identification and species-typing of wood rotting fungi using melting curve analysis. J Wood Sci 59, 432–441 (2013). https://doi.org/10.1007/s10086-013-1349-z

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