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. 2020 Sep 1;86(18):e01532-20. doi: 10.1128/AEM.01532-20

MIST: a Multilocus Identification System for Trichoderma

Kai Dou a,b,c, Zhixiang Lu a,b,c, Qiong Wu a,d,h, Mi Ni d,h, Chuanjin Yu e, Meng Wang a,b,c, Yaqian Li a,b,c, Xinhua Wang a,b,c, Huilan Xie f, Jie Chen a,b,c,✉, Chulong Zhang g,✉
Editor: Irina S Druzhininai
PMCID: PMC7480375  PMID: 32680870

The genus Trichoderma is important to humankind, with a wide range of applications in industry, agriculture, and bioremediation. Thus, quick and accurate identification of Trichoderma species is paramount, since it is usually the first step in Trichoderma-based research. However, it frequently becomes a limitation, especially for researchers who lack taxonomic knowledge of fungi. Moreover, as the number of Trichoderma-based studies has increased, a growing number of unidentified sequences have been stored in public databases, which has made the species identification more ambiguous. In this study, we provide an easy-to-use tool, MIST, for automated species identification, a list of Trichoderma species, and corresponding sequences of reference DNA barcodes. Therefore, this study will facilitate the research on the biodiversity and applications of the genus Trichoderma.

KEYWORDS: Trichoderma, barcoding, species identification

ABSTRACT

Due to the rapid expansion in microbial taxonomy, precise identification of common industrially and agriculturally relevant fungi such as Trichoderma species is challenging. In this study, we introduce the online multilocus identification system (MIST) for automated detection of 349 Trichoderma species based on a set of three DNA barcodes. MIST is based on the reference databases of validated sequences of three commonly used phylogenetic markers collected from public databases. The databases consist of 414 complete sequences of the nuclear rRNA internal transcribed spacers (ITS) 1 and 2, 583 sequence fragments of the gene encoding translation elongation factor 1-alpha (tef1), and 534 sequence fragments of the gene encoding RNA polymerase subunit 2 (rpb2). Through MIST, information from different DNA barcodes can be combined and the identification of Trichoderma species can be achieved based on the integrated parametric sequence similarity search (blastn) performed in the manner of a decision tree classifier. In the verification process, MIST provided correct identification for 44 Trichoderma species based on DNA barcodes consisting of tef1 and rpb2 markers. Thus, MIST can be used to obtain an automated species identification as well as to retrieve sequences required for manual identification by means of phylogenetic analysis.

IMPORTANCE The genus Trichoderma is important to humankind, with a wide range of applications in industry, agriculture, and bioremediation. Thus, quick and accurate identification of Trichoderma species is paramount, since it is usually the first step in Trichoderma-based research. However, it frequently becomes a limitation, especially for researchers who lack taxonomic knowledge of fungi. Moreover, as the number of Trichoderma-based studies has increased, a growing number of unidentified sequences have been stored in public databases, which has made the species identification more ambiguous. In this study, we provide an easy-to-use tool, MIST, for automated species identification, a list of Trichoderma species, and corresponding sequences of reference DNA barcodes. Therefore, this study will facilitate the research on the biodiversity and applications of the genus Trichoderma.

INTRODUCTION

The genus Trichoderma (Hypocreales) is a taxonomically expanding group of fungi found worldwide. It contains numerous environmentally opportunistic species with economic importance to humankind (1–3). Trichoderma spp. have been used as bioeffectors in biofertilizers and biopesticides (4, 5) or as agents for bioremediation of heavy metal and/or other xenobiotic contamination (6, 7). In addition, Trichoderma species have also been employed as a microbial cell factory system for the heterologous production of enzymes (8–10) that are used for biofuel production in industry (11, 12), and in numerous other industries, including production of animal feed (13). As the scientific and practical value has continuously been explored, studies involving Trichoderma species have emerged in a variety of research fields and have shown sustained growth.

To make Trichoderma-based studies more accessible to researchers without training in fungal nomenclature, Trichoderma taxonomists have developed a series of identification tools. First, Samuels and colleagues at the United States Department of Agriculture (USDA) compiled and cataloged the phenotypic characteristics of Trichoderma species to create an interactive web-based key (TrichodermaIndex, Samuels et al., 2009, not currently available) for species identification. Although the interactive key made the comparison of different phenotypic characteristics convenient by avoiding referencing the protologues of each species, phenotype-based identification had inherent defects as the number of morphological traits is limited. Therefore, the phenotype-based identification is prone to error. Moreover, the recognition of new Trichoderma species relies heavily on DNA-based methods (14–27). The requirement for molecular characterization exists not only in Trichoderma taxonomy but is also commonly present in fungal diversity studies.

To make improvements, DNA barcoding, originally developed for species identification in animals (28, 29), was introduced to Trichoderma identification by Druzhinina et al. and integrated in a program named TrichOKey (30). The original version of TrichOKey made use of several species-, clade-, and genus-specific oligonucleotide sequences (named hallmarks) derived from the nuclear rRNA internal transcribed spacer (ITS) region for a quick identification of 75 single species, 5 species pairs, and 1 species triplet, representing the diversity of Trichoderma recognized by the year 2005. An updated second version allowed simultaneous identification of multiple ITS rRNA sequences (31). However, the ITS rRNA region is currently considered to be insufficient for Trichoderma species identification in this genus (32). Another identification tool box, TrichoBLAST, for Trichoderma species has been developed by the same group; this tool box is a combination of multilocus databases of phylogenetic markers, a diagnostic program for phylogenetic markers (TrichoMARK), and a local BLAST server (33). TrichOKey and TrichoBLAST are Trichoderma-specific identification tools. These tools promoted Trichoderma-related studies (34, 35) at a time when the taxonomic system for the genus Trichoderma contained around 100 species (33). However, the taxonomy of Trichoderma has changed drastically, and a report in 2015 listed already 256 accepted Trichoderma names (36) that have not been updated in the databases of TrichOKey and TrichoBLAST. Thus, there are no Trichoderma-specific identification tools that are applicable to the currently recognized diversity of Trichoderma.

In addition to the above-mentioned identification databases, there are numerous public databases with a broad scope of organisms, including fungi (37, 38). Among them, the shared pool of such databases as NCBI GenBank, DDBJ, and EMBL contains the largest number of nucleotide sequences, including phylogenetic markers useful for DNA barcoding of fungi. However, identification of Trichoderma species via the parametric sequence similarity search algorithms such as BLAST programs against public databases was advised to be handled with caution due to the noncurated association of sequences with taxonomic names (30, 39). Given this problem, a curated sequence database was created especially for Trichoderma, referred to as the RefSeq Targeted Loci database (RTL), via a joint effort between the NCBI and fungal taxonomy experts (40). In addition, among the numerous curated databases involving fungal DNA barcoding sequences, the User-friendly Nordic ITS Ectomycorrhiza (UNITE) database (41) could also be adopted to identify Trichoderma species, but within a limited number of species names. For comprehensive information regarding the identification tools and databases, please refer to the published reviews (32, 42).

Overall, the most suitable identification system currently available for Trichoderma is the RTL-based blastn search, due to its consistency with the up-to-date taxonomy of Trichoderma. Nevertheless, the RTL is mainly focused on the ITS rRNA region (40), which is not enough for identification at the species level within Trichoderma. Currently, new Trichoderma species are defined based mainly on three phylogenetic markers: ITS rRNA, translation elongation factor 1-alpha (tef1), and RNA polymerase subunit 2 (rpb2). To the best of our knowledge, there is currently no tool that makes full use of these phylogenetic markers for species identification. In this study, a multilocus identification system for Trichoderma (MIST) was constructed based on the latest Trichoderma taxonomy. The MIST consists of three phylogenetic marker databases (ITS rRNA, tef1, and rpb2) and a retrieval program that could utilize comprehensive information on phylogenetic markers for species identification.

RESULTS

Outline of the web interface.

The MIST (Multilocus Identification System for Trichoderma) is available through a web interface (http://mmit.china-cctc.org/). There are six zones designed in the web interface for species identification, as shown in Fig. 1. The user manual is provided in the supplemental material.

FIG 1.

FIG 1

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Outline of the MIST web interface. There are six zones designed in the current version of MIST (Z1 to Z6). Z1 is associated with a hyperlink, and functions to initialize a new retrieval by a single click. Z2 is a drop-down list used to select one of the phylogenetic marker databases (ITS rRNA, tef1, or rpb2). Z3 is a textbox for users to insert a phylogenetic sequence corresponding to Z2. The inserted sequences are required to contain only characters (i.e., letters) representing nucleic acids without any annotations and titles. Z4 includes three textboxes for users to change retrieval parameters of the BLAST program. The parameter of “identity” allows an input of a number from 0 to 100 (e.g., 98) representing the sequence similarity score from 0% to 100%. The parameter of “expect value” allows an input of a number in decimal form (e.g., 0.00001), and the parameter of “coverage” allows an input of a number from 0.0 to 1.0, representing the sequence coverage score from 0% to 100%. Z6 provides a submission function and works by a single click at the “submit” button. Subsequently, candidate Trichoderma species that meet the users’ retrieval requirements are exhibited in Z5.

The operation and underlying principles of MIST are similar to NCBI BLAST (32, 43, 44). MIST performs the sequence similarity searches of several (up to three) DNA barcode markers available for Trichoderma and results in a sequential automatic retrieval of the correct species name from the pool of all available taxa for the genus. A retrieval process consists of several actions. For each retrieval step, only one phylogenetic marker is allowed for retrieval against the corresponding database. More details regarding the operations are described in the legend of Fig. 1.

Construction and characteristic analysis of the databases.

There are 349 Trichoderma names included in the databases of MIST (Table S1 in the supplemental material). Most of these names were assigned representative strains and sequences (i.e., ex-type, ex-epitype) while some newly identified species (e.g., T. acremonioides [45], T. adaptatum [46], T. angustum [47]) were not assigned. After the phylogenetic analyses of the rpb2 and tef1 sequences in the databases (Fig. S1), T. aggressivum CBS 433.95 was corrected as T. aggressivum f. sp. europaeum. The sequences of unidentified T. cremeum G.J.S. 02-52, T. lixii G.J.S. 90-22, T. neocrassum G.J.S. 95-157, T. pyramidale 9155, T. tawa G.J.S. 02-79, T. pezizoides G.J.S. 01-231, and T. crystalligenum 8880 were removed from the databases.

After the correction of the data sets, a total of 416 ITS rRNA, 583 tef1, and 534 rpb2 sequences were included in the databases. The sequence length within the ITS rRNA database ranges from 200 bp to 1,609 bp. Most of the ITS rRNA sequences contain the ITS1, 5.8S, and ITS2 fragments, while the ITS rRNA (AY665701) from T. flaviconidium G.J.S. 99-57 lacks the ITS1 and 5.8S fragments, and the ITS rRNA (AF400751) from T. atrogelatinosum CBS 237.63 lacks the ITS2 fragment. The sequence length in the rpb2 database ranges from 314 bp to 1,403 bp, and that in the tef1 database ranges from 208 bp to 2,279 bp. The differences in sequence length within a phylogenetic marker database are probably caused by the inconsistency of primer pairs used for amplifying the corresponding phylogenetic markers (48–50) and may generate a series of uncertain or incorrect results in the species identification process. It is apparent that the retrieval process within MIST will fail if the ITS2 fragment of a Trichoderma strain is used for retrieval in a database containing only the ITS1 and 5.8S fragments.

Relative to that in the ITS rRNA database, the inconsistency of phylogenetic fragments among different Trichoderma species is greater in the rpb2 and tef1 databases. For instance, tef1 of T. longibrachiatum DAOM 166989 (EU338335) contains fragments of introns 4 and 5, tef1 of T. longibrachiatum CBS 816.68 (EU401591) contains fragments of intron 5 and exon 6, and tef1 of T. americanum G.J.S. 92-93 (DQ835489) mainly contains a fragment of exon 6. This will lead to incorrect species identification if improper primer pairs are used for amplification of phylogenetic markers (33). For example, if the intron region of tef1 is used for retrieval within MIST, no Trichoderma strains will be identified as T. chlorosporum, due to the lack of tef1 intron sequences from the T. chlorosporum reference strain G.J.S. 88-33.

The lowest intraspecies similarity scores of ITS rRNA, tef1, and rpb2 are 91% (KJ783296 and KJ783283 from T. oligosporum), 87% (EU280055 and KJ871125 from T. helicum), and 96% (KJ842161 and FJ442772 from T. austrokoningii), respectively. Except for the few cases mentioned above, the intraspecies similarity score of ITS rRNA, tef1, and rpb2 within the databases is greater than 95% for almost all the species. Infrequently, there are few cases in which the similarity score is higher between species than within species. For instance, the similarity score of the tef1 sequences HQ342223 (T. barbatum G.J.S. 04-308) and HQ342224 (T. barbatum DAOM 230008) is 95%, while that of AY937441 (T. rossicum DAOM 230011) and HQ342224 (T. barbatum DAOM 230008) is 99%.

Identification process using MIST.

According to the characteristic analysis of the databases, a corresponding identification process was provided for MIST. A series of primer pairs were suggested for the amplification of corresponding phylogenetic markers: ITS4 (TCCTCCGCTTATTGATATGC) and ITS5 (GGAAGTAAAAGTCGTAACAAGG) were suggested for ITS rRNA (51), EF1-728F (CATCGAGAAGTTCGAGAAGG) and TEF1LLErev (AACTTGCAGGCAATGTGG) for tef1 (52, 53), and fRPB2-5f (GA[T/C]GA[T/C][A/C]G[A/T]GATCA[T/C]TT[T/C]GG) and fRPB2-7cr (CCCAT[A/G]GCTTG[T/C]TT[A/G]CCCAT) for rpb2 (49). The amplicons derived from the suggested primer pairs should cover all kinds of fragments existing in the databases. In addition, considering that the amplicon generated from the suggested tef1 primer pair contains only the partial exon 6 fragment, and because in the given example the interspecies similarity score was higher than the intraspecies score, the default retrieval parameters of MIST were set to 0.5 for “coverage” and 95 for “identity.” A general identification process was suggested, as shown in Fig. 2. There are six steps for species identification within MIST. Step one involves amplifying and sequencing the phylogenetic markers using the suggested primer pairs and previously published PCR protocols (51, 54). Then, the ambiguous bases are removed from the sequenced ITS rRNA, tef1, and rpb2. Step two involves initializing a new retrieval process by clicking Z1 (Fig. 1). Step three involves choosing a database from Z2 and inserting the corresponding sequence into Z3. Step four involves clicking the “submit” button for retrieval and obtaining the retrieved candidate species. Step five involves repeating steps three and four using more phylogenetic markers. For steps one to five, currently, tef1 and rpb2 are recommended for retrieval since there are at least 82 Trichoderma species lacking ITS rRNA sequences. In step six, if any candidate species remain, additional phylogenetic analyses of different phylogenetic markers are necessary (e.g., maximum parsimony tree analysis). For phylogenetic analyses, the reference sequences of the candidate species are available in Table S1. For some infrequent conditions, if one phylogenetic marker shows no retrieval results after a retrieval action, the identification process should be restarted from step two. Meanwhile, the parameter of “identity” should be turned down, since the lowest intraspecies similarity scores of ITS rRNA and tef1 were observed to be 91% and 87%, respectively. The provided identification process was made to accommodate the current databases. When the absent phylogenetic fragments are supplemented (e.g., ITS rRNA of T. flavipes and T. sempervirentis, tef1 introns 4 and 5 of T. melanomagnum, rpb2 of T. matsushimae), the ITS rRNA and customized retrieval parameters should be used within MIST (see the user manual in the supplemental material).

FIG 2.

FIG 2

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Identification process of MIST. The blue lines represent the main process currently used for species identification. The blue dotted lines represent the optional operation. The red dotted lines represent the extensible modules of databases.

Effectiveness testing of MIST.

Forty-four reliably identified Trichoderma strains (15) distributed in different phylogenetic clusters were used for effectiveness testing. Of the 44 tested Trichoderma strains, 43 could be identified through MIST with the species name assigned in GenBank listed in the retrieval results. In most cases, a single retrieval action (tef1 or rpb2) could help to reduce the number of candidate species to less than 40 (Table 1). In sequential retrieval processes, tef1 and rpb2 are complementary in species discrimination. For instance, the Trichoderma strain HMAS 248837 could be identified as T. hainanense, and strain S27 could be identified as T. citrinoviride through the sequential retrieval of tef1 and rpb2. The Trichoderma strain C.P.K. 1934, assigned as T. lixii in GenBank, was retrieved for 10 candidate species, and these did not include T. lixii. Therefore, phylogenetic analyses of tef1 and rpb2 from the retrieved 10 species, the reference strain CBS 110080 of T. lixii, and the strain C.P.K. 1934 were conducted. The phylogenetic analyses showed that the Trichoderma strain C.P.K. 1934 was incorrectly assigned as T. lixii in GenBank and should be identified as T. atrobrunneum (Fig. S2).

TABLE 1.

Effectiveness testing of MIST

Species Strain Clade No. of entries:
Retrieved by tef1a Retrieved by rpb2a Retrieved by tef1 and rpb2
T. rodmanii C.P.K. 2852 Brevicompactum 16 (FJ860688) 2 (FJ860581) 2
T. deliquescens ATCC 208838 Deliquescens More than 40 (AF543781) 2 (DQ522446) 2
T. ceramicum S366 Green 23 (KJ665446) 22 (KJ665249) 5
T. christiani S43 Green More than 40 (KJ665438) More than 40 (KJ665243) 20
T. guizhouense S278 Green 28 (KF134799) More than 40 (KF134791) 10
T. harzianum T1 Green 32 (KX632590) 35 (MG917684) 11
T. harzianum HZA11 Green 34 (MK850833) More than 40 (MH647801) 14
T. lixii C.P.K. 1934 Green 27 (FJ179573)b More than 30 (FJ179608) 10b
T. longipile S40 Green 21 (KJ665556) 14 (KJ665292) 5
T. tomentosum S23 Green 22 (KJ665759) 32 (KJ665351) 5
T. hainanense HMAS 248837 Helicum 22 (KY688033) 2 (KY687976) 1
T. citrinum C.P.K. 960 Hypocreanum 9 (FJ860631) 5 (FJ179603) 4
T. taxi ZJUF 0870 Lone lineage 1 (DQ859028) 3 (DQ859031) 1
T. taxi ZJUF 0869 Lone lineage 1 (DQ859027) 3 (DQ859030) 1
T. britdaniae K89878 Longibrachiatum 6 (JQ685865) 1 (JQ685881) 1
T. citrinoviride S27 Longibrachiatum 26 (KJ665450) 3 (KJ665251) 1
T. leguminosarum S391 Longibrachiatum 2 (KJ665548) 2 (KJ665287) 2
T. europaeum Hypo 183 Polysporum 8 (KJ665474) 6 (KJ665261) 4
T. europaeum S37 Polysporum 7 (KJ665484) 8 (KJ665266) 4
T. europaeum S611 Polysporum 8 (KJ665489) 8 (KJ665268) 4
T. europaeum Hypo 300 Polysporum 8 (KJ665475) 8 (KJ665262) 4
T. mediterraneum S29 Polysporum 11 (KJ665578) 9 (KJ665298) 4
T. mediterraneum S184 Polysporum 11 (KJ665567) 8 (KJ665295) 4
T. mediterraneum S292 Polysporum 15 (KJ665579) 9 (KJ665299) 5
T. mediterraneum S594 Polysporum 14 (KJ665607) 9 (KJ665311) 4
T. minutisporum CBS 112253 Polysporum 9 (KJ665617) 8 (KJ665315) 4
T. polysporum S103 Polysporum 9 (KJ665673) 7 (KJ665328) 2
T. oligosporum 7720 Psychrophilum 8 (KJ634752) 2 (KJ634719) 1
T. psychrophilum C.P.K. 2435 Psychrophilum 2 (FJ860682) 1 (FJ860576) 1
T. rossicum T52 Stromaticum 24 (KX632642) 14 (KX632585) 7
T. acremonioides 11585 Viride 11 (MH612374) 6 (MH612368) 3
T. caerulescens S232 Viride 8 (JN715631) 4 (JN715606) 3
T. dorotheae S444 Viride 26 (KJ665469) 25 (KJ665259) 13
T. gamsii S488 Viride 11 (JN715613) 31 (KJ665270) 5
T. hamatum Hypo 647 Viride 10 (KJ665513) 14 (KJ665274) 3
T. koningii S227 Viride 14 (KC285596) 18 (JN715609) 2
T. koningii S22 Viride 14 (KC285595) 17 (KC285749) 2
T. koningiopsis S359 Viride 14 (KJ665546) 18 (KJ665285) 6
T. olivascens CBS 119322 Viride 20 (DQ672609) 31 (KC285750) 17
T. paraviridescens S122 Viride 28 (KC285671) 32 (KC285764) 22
T. petersenii CBS 136466 Viride 17 (KJ665632) 18 (KJ665326) 7
T. petersenii S200 Viride 22 (KJ665636) 18 (KJ665327) 7
T. stilbohypoxyli S24 Viride 1 (KJ665742) 35 (KJ665350) 1
T. tawa DAOM 232841 Green 1 (EU279972) More than 40 (KJ842187) 1
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a

An entry such as “16 (FJ860688)” indicates there were 16 species retrieved by the sequence FJ860688.

b

Results in boldface indicate that the species names assigned by the GenBank database were not retrieved by the corresponding sequences within MIST.

DISCUSSION

Trichoderma species identification has been a challenging task (48, 55). The abundant homoplasy in phenetic characteristics is likely the underlying reason (56). Therefore, the methods used for identification of Trichoderma have evolved from phenotypic characteristic-based methods to DNA-based methods supplemented by phenotypic observation. For Trichoderma, there are three common questions regarding DNA-based species identification. First, which kind of phylogenetic markers are appropriate for species identification? Second, for one phylogenetic marker, which strains and sequences are precise species references? Third, with the reference sequences, how can precise species identification be performed? These questions are simple for Trichoderma taxonomists but can lead to confusion for researchers focusing on the Trichoderma-based practical activities and lacking taxonomic knowledge. Furthermore, DNA-based species identification is highly dependent on databases and is error prone if not conducted properly.

The purpose of this study was to develop an identification system for the genus Trichoderma in line with the development of the Trichoderma taxonomy system and thereby facilitate Trichoderma-based research. Moreover, the common questions are discussed below in an effort to explain the species identification process.

Which kind of phylogenetic markers is appropriate for species identification?

The ITS rRNA region was employed for fungal identification in almost all fungal databases (37, 57, 58) and nominated as the official fungal barcode (59). For Trichoderma, as reviewed by Druzhinina and Kubicek (48), at least eight phylogenetic markers were used for molecular phylogenetic analyses. ITS1 and ITS2 were used for revision of section Longibrachiatum (60), which was defined by Bissett using morphological characteristics (61, 62). 18S rRNA was used to assess the evolution of the genus Trichoderma within the ascomycetes. The analysis of 28S rRNA showed that Trichoderma is a paraphyletic group within the Hypocreaceae. A combination of ITS rRNA, the small subunit of the mitochondrial rRNA (mitSSU), the D1 and D2 regions of 28S rRNA, the fifth and partial sixth exons of tef1, and the exon of endochitinase 42 (ech42) showed four clades of 47 Trichoderma species (63). ITS rRNA, tef1, calmodulin (cal1), and actin (act1) were used for the analysis of T. harzianum and Hypocrea lixii (64). Recently, 100 neutrally evolving genes derived from genome data were used for phylogenetic analysis of 9 Trichoderma species and 12 reference taxa from the Hypocreales (65). Zhu et al. (66) compared ITS rRNA, tef1, and rpb2 for the selection of a supplementary DNA barcode for Trichoderma. Through the analysis of 231 sequences from 35 Trichoderma species, it was found that for rpb2 the minimum interspecies variation (2.48%) was greater than the maximum intraspecies variation (1.8%). For ITS rRNA and tef1, overlap occurred between the intra- and interspecies variations, indicating that rpb2 was appropriate as a supplementary barcode for Trichoderma. Regarding species identification, there are additional requirements for phylogenetic markers (67). First, the marker should be easily amplified and sequenced. In addition, there should be accumulation of sequences of the marker throughout the genus, and these sequences should be available from public databases. Based on the public databases, only the ITS rRNA, tef1, and rpb2 markers are suitable.

Which of the three phylogenetic markers (ITS rRNA, tef1, and rpb2) is appropriate for species identification?

Previous work has shown that the ITS rRNA is identical within some related Trichoderma species (48). However, in some cases, the interspecies variability of ITS rRNA is higher than that of rpb2. For instance, the similarity score of the ITS rRNA sequences NR_154570 (T. bannaense HMAS 248840) and JX089584 (T. guizhouense HGUP 0039) is 95.7%, while that of the rpb2 sequences KY687979 and JQ901401 is 97.3%. From the MIST testing process, the two phylogenetic markers (tef1 and rpb2) are complementary for species identification (Table 1). These cases suggest that each of the three markers is unique in species identification and cannot be replaced by any of the other markers. The uniqueness of phylogenetic markers in species identification has also been suggested in recent analyses of ITS rRNA and the D1/D2 domain of the 26S rRNA gene cluster (LSU) from 24,000 sequences of 7,300 filamentous fungal species. The results of the study showed that although ITS rRNA outperforms LSU in species identification, combining ITS rRNA and LSU could further improve the performance (68). Actually, no single phylogenetic marker can provide phylogenetic resolution within the entire genus of Trichoderma. It was pointed out that the simultaneous use of the tef1 large intron and last large exon, rpb2, the ech42 last large exon, and ITS rRNA may lead to the most reliable phylogeny within Trichoderma (48). Therefore, a combination of the three phylogenetic markers (ITS rRNA, tef1, and rpb2) was selected for use in MIST for Trichoderma species identification.

Which strains and sequences are precise species references?

A curated data set of sequences from representative Trichoderma strains is the basis for correct species identification. For taxonomists, the accumulation and updating of curated sequences is routine work. However, for other researchers, the only way to obtain reference sequences is by retrieval from public databases (mainly from NCBI GenBank) or publications. Currently, hundreds of strains and thousands of sequences from Trichoderma species are stored in publicly available databases. However, for some cases, the correct association of sequences with species is distributed among different studies rather than in public databases (15, 33, 36, 69, 70). Therefore, the safest approach for species identification is to retrieve sequences from public databases based on the literature information. In 2005, a database of curated sequences of Trichoderma was constructed in the identification tool TrichoBLAST (33), and made available from the website of the International Subcommission on Trichoderma and Hypocrea Taxonomy (ISTH; no longer online but formerly at http://www.isth.info). Nevertheless, the database covers only 88 species and has not been updated since 2005. Accordingly, we made an effort to collect Trichoderma sequences from the literature published before 2020 (Table S1). Consequently, the MIST is supported by the databases of ITS rRNA, tef1, and rpb2 covering 349 Trichoderma species.

It is noteworthy that not all of the Trichoderma strains contain a complete set of the three phylogenetic markers within the MIST sequence database. The genes tef1 and rpb2 were sequenced from more Trichoderma species than ITS rRNA. Moreover, in recent years, new Trichoderma species are often being described using tef1 and rpb2, and do not provide ITS rRNA information (15, 17, 46, 47, 71–73). Therefore, in the current stage, only tef1 and rpb2 are recommended for retrieval within MIST.

Comparison of different identification methods.

Phenotypic characteristics are traditionally employed to form a fungal taxonomic system and to identify fungal species by a phenotype-based species key. Since the genealogical concordance phylogenetic species recognition (GCPSR) concept (48, 74) was introduced to Trichoderma, species identification has mainly relied on nucleotide sequences. Currently, the most precise species identification method should be phylogenetic analyses. However, the execution of phylogenetic analyses is inconvenient due to the computational complexity. With more sequences being added for phylogenetic analyses, the process will become time consuming even for a high-performance computer.

The DNA barcode is an effective tool for species identification. To meet the requirements for quick and accurate identification of Trichoderma species, an ITS-based barcode method, named TrichOKey, was developed; this method is able to discriminate 75 individual species (30). The barcode in TrichOKey refers to a series of oligonucleotides (hallmarks) within ITS rRNA, exhibiting conservation at the genus, clade, or species level within Trichoderma. The conservation of hallmarks is of statistical significance, as it was derived from more than one thousand sequences from different Trichoderma species. However, the hallmark-based strategy was not adopted in MIST for the following reasons: currently, given the large number of Trichoderma species, it is difficult to develop hallmarks from the inconsistent phylogenetic fragments with species specificity. Even in 2005, with a total Trichoderma species number of 88, there was still a lack of hallmarks in TrichOKey for distinguishing five species pairs and one species triplet (30). Moreover, as new Trichoderma strains or species are being identified, the species specificities of the existing hallmarks will be easily abolished. For example, through TrichOKey, T. pubescens (NR_077179) was identified as T. hamatum, and T. scalesiae (NR_144876.1) was identified as T. atroviride. In fact, MIST is an improvement over the TrichoBLAST program (33) and/or the GenBank-based BLAST search. Specifically, MIST works by a decision tree classifier using multiple phylogenetic markers, while TrichoBLAST or GenBank-based BLAST employs one marker for a single retrieval process.

Before MIST, a series of polyphasic identification systems were developed for Aspergillus, Penicillium, Fusarium (http://www.westerdijkinstitute.nl/Collections/), Ceratocystis, Colletotrichum, and Phytophthora (http://www.q-bank.eu/fungi/). The polyphasic identification systems mentioned above were derived from BioloMICS software (57) and allow the simultaneous submission of several different characteristics. Unlike the listed polyphasic identification systems, MIST provides a relatively flexible method for sequential retrieval. This means that for different phylogenetic markers, the retrieval parameters can be changed during the retrieval processes. This is important because, generally, noncoding sequences show more polymorphisms than coding sequences. With a large-scale analysis of filamentous fungal DNA barcodes, the optimal similarity thresholds to assign filamentous fungal species were predicted as 99.6% for ITS rRNA and 99.8% for the 26S LSU (68). For Trichoderma, sequence similarity search using blastn showed that the similarity score of ITS rRNA was below 98% between clades, and identical or very close to being identical within clades (40). In fact, there is no finalized similarity score that can be applied throughout the genus. According to the inconsistent fragments of phylogenetic markers and, given that the interspecies sequence similarity score was higher than the intraspecies score, as mentioned in the Results section, a loose retrieval parameter setting (95% similarity score and 0.5 coverage score) was adopted within MIST to obtain high generalization performance. With the loose parameter setting in MIST, nine Trichoderma strains could be identified in certain species, while the precision of identification for other strains requires further phylogenetic analyses (Table 1). Nonetheless, for the latter conditions, the MIST could be considered an assistive tool for the phylogenetic analysis. The MIST could narrow down the candidate species to a small range (i.e., less than 20 candidate species, Table 1) and make the subsequent phylogenetic analyses efficient. In the future, the MIST has the potential for unambiguous species identification when more phylogenetic markers are developed and added to the system.

In conclusion, supplementation and improvement of the databases will essentially enhance the performance of MIST. There are at least 82 Trichoderma species lacking ITS rRNA sequences, and 12 Trichoderma species lacking rpb2 sequences in the current databases of MIST. Moreover, the inconsistent fragments of phylogenetic markers make it challenging to obtain precise retrieval results within MIST. It is obvious that uniform databases are important for precise identification. However, the sequence length of rpb2 ranges from 314 bp to 1,403 bp in the current rpb2 database. If all the rpb2 sequences are trimmed to a unified length, the species discrimination power of the discarded fragments will be lost. On the other hand, if long fragments were to be retained, the Trichoderma species with short length fragments would not be retrieved. For tef1, different fragments were amplified for different species (e.g., the tef1 from the representative strains of T. sulawesense and T. melanomagnum contained only the exon 6 fragment, while that of T. albocorneum mainly contained the intron fragment). To construct a unified tef1 database, it is difficult to decide which kind of fragment should be retained. Considering that generalization performance is important in the current stage, the databases of MIST were constructed to include different fragments that located in the phylogenetic markers of ITS rRNA, tef1, and rpb2. Correspondingly, several rules were made to adapt to the current databases (e.g., loose retrieval parameters and unified primer pairs for amplifying phylogenetic markers). The precision of the MIST could be improved by sequential retrieval of multilocus phylogenetic markers. However, the supplementation with phylogenetic markers or fragments within phylogenetic markers for the representative strains of each Trichoderma species will further improve the MIST and facilitate the phylogenetic analyses of the entire Trichoderma genus. It is also important for researchers to reach a consensus on the primer pairs used for amplifying phylogenetic markers. Ideally, the phylogenetic markers from geographically representative strains of each Trichoderma species could be sequenced, and in that case, a precision retrieval parameter for similarity score could be provided.

The construction of MIST is based on the following assumptions: (i) for each phylogenetic marker, it is possible that in some cases, the interspecies sequence similarity is higher than the intraspecies sequence similarity; and (ii) with the whole genome considered (i.e., including every phylogenetic markers), the intraspecies sequence similarity is higher than the interspecies sequence similarity. In other words, the species barcode gap becomes more obvious as more phylogenetic markers are involved. Therefore, with the accumulation of genomic data from Trichoderma species, new phylogenetic markers could be developed to help define a Trichoderma species within the MIST.

MATERIALS AND METHODS

Web programming.

The MIST is running on an Ubuntu Linux 16.04 server maintained by the Center for Culture Collection of Trichoderma at Shanghai Jiao Tong University. The operating environment is supported by Apache2, PHP 5.3.3, the BLAST program (75), Perl, and Bioperl. The interactive function between users and the web interface was achieved using PHP language. Sequence databases were formatted by BLAST program (43, 44) and stored separately. The core cross-referencing program was written in Perl language with the Bioperl package, and following functions were performed: (i) initializing for a new retrieval; (ii) adjusting the retrieval parameters (e.g., identity, coverage) according to the input from the users; (iii) retrieving corresponding databases (i.e., calling the BLAST program) according to the submission and returning species names as results; (iv) based on the latest retrieval results, adjusting the databases and preparing the adjusted databases for the next retrieval unless initializing the MIST.

The default identity parameter was set to 95 and the default coverage parameter was set to 0.5.

Data collection and verification.

The Trichoderma names and representative sequences were collected according to Bissett et al. (36), the NCBI RTL project (40), and the newly identified species published during the period from 2015 to 2019 (16, 18, 22, 45, 47, 76–80). The sequences of ITS rRNA, tef1, and rpb2 were retrieved from NCBI GenBank. Detailed information regarding species, strains and corresponding sequences is provided in Table S1 in the supplemental material, in which the type, ex-type, and other kinds of representative strains of Trichoderma species are exhibited in bold text. The validity of nonrepresentative strains was verified by phylogenetic analyses of rpb2. The phylogenetic analyses were conducted separately according to the Trichoderma clades (e.g., Longibrachiatum, Basel, Green and Viride) divided by Jaklitsch and Voglmayr (15), and the results are shown in Fig. S1. The detailed steps of phylogenetic analysis are described below. The association of nonrepresentative strains with species names was considered to be correct when the strains were clustered with the corresponding representative strains with bootstrap support values greater than 80%. Those strains with a bootstrap support value less than 80% in the rpb2 phylogenetic analysis were used for further phylogenetic analysis based on tef1.

MIST effectiveness testing.

In total, 44 Trichoderma strains distributed in different phylogenetic clades (15) were used for testing the effectiveness of the MIST (Table 1). The selection criteria for the tested Trichoderma strains were as follows: (i) the sequences of the strains were not included in the databases of MIST; (ii) both the tef1 and rpb2 were sequenced for the strains; and (iii) the sequenced length of tef1 and rpb2 was long enough to cover most fragments within the tef1 and rpb2 databases (i.e., usually longer than 1,000 bp). The testing process was conducted using the default parameter of MIST. To be concise, the testing results were exhibited as the number of retrieved Trichoderma species instead of detailed species names. The testing results were marked in bold when the species names assigned in GenBank database were not retrieved by the corresponding sequences. The problematic associations of species names and sequences detected by MIST were subjected to phylogenetic analyses based on rpb2 and tef1 (Fig. S2).

Phylogenetic analysis.

The phylogenetic analyses were conducted using MEGA-X (81). Sequences were aligned by MUSCLE (82), and all the alignments were manually adjusted by trimming the leading and trailing gap regions. Then, the cured sequences were used for maximum parsimony analysis with 1,000 bootstrap replicates. The loci of the phylogenetic markers were determined by TrichoMARK (33).

Data availability.

All the sequences used in this research have been stored in NCBI GenBank database, and the accession numbers and partial sequences are accessible in Table S1 and “sequences unavailable in public databases.”

Supplementary Material

Supplemental file 1
AEM.01532-20-s0001.pdf (1.9MB, pdf)

ACKNOWLEDGMENTS

This work was supported by the National Key Research and Development Program of China (2017YFD0201108, 2017YFD0200403), the National Key Research and Development Program of China—Key International Intergovernmental Scientific and Technological Innovation Cooperation Projects (2017YFE0104900), and the National Natural Science Foundation of China (31872015).

He Meng and Weixing Ye (Shanghai Personal Biotechnology Co., Ltd.) are thanked for the support of software development.

We declare no competing interests.

Footnotes

Supplemental material is available online only.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplemental file 1
AEM.01532-20-s0001.pdf (1.9MB, pdf)

Data Availability Statement

All the sequences used in this research have been stored in NCBI GenBank database, and the accession numbers and partial sequences are accessible in Table S1 and “sequences unavailable in public databases.”

Articles from Applied and Environmental Microbiology are provided here courtesy of American Society for Microbiology (ASM)

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