- Open Access
ITS1, 5.8S and ITS2 secondary structure modelling for intra-specific differentiation among species of the Colletotrichum gloeosporioides sensu lato species complex
© Rampersad; licensee Springer. 2014
- Received: 19 August 2014
- Accepted: 12 November 2014
- Published: 23 November 2014
The Colletotrichum gloeosporioides species complex is among the most destructive fungal plant pathogens in the world, however, identification of member species which are of quarantine importance is impacted by a number of factors that negatively affect species identification. Structural information of the rRNA marker may be considered to be a conserved marker which can be used as supplementary information for possible species identification. The difficulty in using ITS rDNA sequences for identification lies in the low level of sequence variation at the intra-specific level and the generation of artificially-induced sequence variation due to errors in polymerization of the ITS array during DNA replication. Type and query ITS sequences were subjected to sequence analyses prior to generation of predicted consensus secondary structures, including the pattern of nucleotide polymorphisms and number of indel haplotypes, GC content, and detection of artificially-induced sequence variation. Data pertaining to structure stability, the presence of conserved motifs in secondary structures and mapping of all sequences onto the consensus C. gloeosporioides sensu stricto secondary structure for ITS1, 5.8S and ITS2 markers was then carried out. Motifs that are evolutionarily conserved among eukaryotes were found for all ITS1, 5.8S and ITS2 sequences. The sequences exhibited conserved features typical of functional rRNAs. Generally, polymorphisms occurred within less conserved regions and were seen as bulges, internal and terminal loops or non-canonical G–U base-pairs within regions of the double stranded helices. Importantly, there were also taxonomic motifs and base changes that were unique to specific taxa and which may be used to support intra-specific identification of members of the C. gloeosporioides sensu lato species complex.
- Colletotrichum spp
- Internally transcribed spacer region
- Secondary structure prediction
Colletotrichum gloeosporioides is one of the most ubiquitous fungal plant pathogens in the world (Sutton 1992; Cannon et al., 2008) and has been associated with at least 1,972 different fungus-host combinations in the fungal databases (http://nt.ars-grin.gov/fungaldatabases/) including many tropical fruit crops (See Phoulivong et al. 2010 for a review of Colletotrichum species infecting tropical fruits). It has also been established that C. gloeosporioides is a species complex (Colletotrichum gloeosporioides sensu lato; Weir et al. 2012). Non-molecular traits commonly used to assign intra-specific ranking to these segregate taxa do not demonstrate adequate variability (e.g. using morphological characters), and/or are homoplasious (e.g. morphology and host range criteria). In view of this difficulty, there is a preference among many practitioners to refer to the broad, group-species concept rather than referring to names at the intra-specific level. However, correct identification is important for biosecurity and quarantine reasons, and for development of more targeted integrated disease management schemes.
To date, multi-locus phylogeny must be used for correct identification of Colletotrichum species (Weir et al. 2012). There are several genetic markers that are currently used for member species assignment including partial Actin (ACT), Calmodulin (CAL), Glutamine synthetase (GS), Glyceraldehyde 3-phosphate dehydrogenase (GAPDH), β-Tubulin (TUB2), Apn2/Mat and the nuclear rDNA internally transcribed spacer (ITS) region (Silva et al. 2012; Weir et al. 2012). However, some of the problems encountered with this approach include (i) some isolates still had ambiguous phylogenetic placement based on separate gene tree assessment or when a concatenated data set was used (Weir et al. 2012, (ii) other isolates are recalcitrant to amplification (e.g. CAL primers) and/or multiple bands are produced after PCR amplification which requires gel extraction and purification prior to sequencing (Weir et al. 2012), and (iii) there is information bias among the different genes used to identify member species of this complex (Rampersad et al. 2014).
The nuclear internal transcribed spacer (ITS) regions have been used as molecular markers because of their relative variability and ease of PCR amplification (Nilsson et al. 2012). The ITS array consists of the entire ITS1, 5.8S and ITS2 regions of the nuclear rDNA cistron. It is a multigene family with the potential for variation among tandem repeats. Polymorphisms are not uniformly distributed across the ITS array. The 5.8S gene sequence is highly conserved but the ITS1 and ITS2 sequences are more variable and are highly polymorphic depending on the fungal species (Hillis and Dixon 1991; Coleman 2007; Nilsson et al. 2008). Evidence suggests that significant variation among ITS sequences is found only within organisms that are diploid or polyploid hybrids, and of disparate parents (Buckler 1997). It is believed that concerted evolution allows homogenization of the many copies of this array and it is proposed that the ITS can be analyzed as a single gene (Coleman 2003). ITS sequences are typically found to be more similar within species and more divergent between species (Alvarez and Wendel 2003). In addition to being widely used for phylogenetic inference and in systematics, the ITS region is the formal fungal barcode and is the primary choice for molecular identification of fungi from a number of sources (Schoch et al. 2012). The difficulty in using ITS sequences for phylogenetic inference, however, is appropriate ITS sequence alignment which must be carried out in the absence of a translated protein product (Coleman 2009). Further, many intergenic spacers may exist as a mosaic of functional elements and inactivated pseudogenes at different stages of decay (Degnan et al. 2011). In addition, it is important that the presence of chimeric sequences be ascertained prior to sequence alignment.
Immediately post-transcription, the initial ITS transcript folds and forms helices that provide recognition and docking signals that enable processing of the transcript into mature rRNAs (van Nues et al. 1995; Joseph et al. 1999; Venema and Tolervey 1999). Schlötterer et al. (1994) found that the more variable portions of ITS2 appear to be slow evolving, at a rate close to neutral which suggests no selection. The relatively conserved regions of the ITS2 sequence are stabilized by selective forces which ensure correct rRNA processing (Coleman 2009). Less information about the function and the secondary structure of ITS1 is available, however, the region may play a role in the maturation of the 18S rRNA (van Nues et al. 1994, 1995; Coleman 2003, 2007). Although the ITS1 and ITS2 sequences can vary significantly at the sequence level, the sequences still display high levels of conservation at the structural level (Hausner and Wang 2005).
Secondary structure prediction is advantageous for species identification because it allows for the detection of sequencing errors, pseudogenes and genetic footprints indicative of past hybridization events (Coleman 2009). Accordingly, structural information can offer supplementary information for species identification (Coleman 2003, 2007). Non-functional pseudogenes are readily recognizable by their irregular 5.8S sequences and by the absence of some or all of the relatively conserved regions of ITS2, can be determined through the use of secondary structure data (Freire et al. 2012). In structure modelling, however, sequence read errors can give rise to artificial structures involving several-to-many base-pairs, whereas they only give rise to single-base-pair alignment mismatches in similarity searches.
Conservation of certain domains and nucleotide motifs are apparent across the eukaryotic kingdom (Coleman 2007). By analyzing the predicted secondary structure of an rRNA sequence and detecting conserved domains and motifs, it is possible to estimate whether the sequence is likely to code for functional rRNA and as such, validate the authenticity of rDNA gene copies (Harpke and Peterson 2008). Therefore, invalid ITS sequences that would otherwise negatively affect phylogenetic reconstruction can be removed from the data set. Additionally, given the number of ITS sequences that are misidentified and mislabelled in International Nucleotide Sequence Databases (INSD: GenBank, ENA, and DDBJ; Nilsson et al. 2012; Crouch et al. 2009) it is important that sequences be validated prior to use in subsequent analyses (Nilsson et al. 2012; Schoch et al. 2014).
This is the first study to systematically investigate the potential use of ITS1, 5.8S and ITS2 consensus secondary structure prediction towards species identification within the C. gloeosporioides sensu lato species complex based on type and query sequences. The main objectives of this study were: (i) to assess the nature of polymorphisms (the number and type) that may accumulate in the ITS1 and ITS2 rDNA sequences; (ii) to detect whether sequences under study are pseudogenes or represent PCR artifacts as a result of replication or sequencing errors; (iii) to examine the predicted consensus secondary structures for all epitypes and query isolates for separate ITS1, 5.8S and ITS2 markers and identify ITS structural features, including conserved motifs and variable regions; (iv) to determine whether predicted ITS secondary structures can be used to identify species within the C. gloeosporioides sensu lato species complex and to discuss the usefulness of secondary structure analyses to validate ITS sequence data for use in phylogenetic reconstruction.
ITS sequence analysis and predicted secondary structures
The trimmed and edited sequences of each marker were as follows: ITS1, 140 nucleotides; 5.8S, 117 nucleotides and ITS2, 164 nucleotides. MAFFT analysis (http://mafft.cbrc.jp/alignment/server/ (Katoh 2005, 2008) revealed no evidence of chimeric sequences present in the ITS data set and indicated good quality ITS sequences with no stochastic or artifactual nucleotide data.
ITS1 structure modelling
The consensus secondary structure of ITS1 marker of C. gloeosporioides sensu stricto consisted of a long, double helix; at its central part, the double helix contained one large, internal loop in addition to other asymmetrical internal loops. There were three non-canonical G-U base pairings and a number of base substitutions. Non-canonical G–U pairing presents certain degeneracy in base-pairing which may provide structural flexibility and can be allowed within rRNA secondary structures without resulting in significant structural changes (Mullineux and Hausner 2009). Comparisons of consensus structures suggest that insertions/deletions that impact upon helix length or base changes that occur in loops or bulges do not necessarily affect the formation of mature functional rRNA and these regions may be susceptible to such changes (Bridge et al., 2008).
There is no consensus structure for this marker across all eukaryotes, however, the GGCRY-RYGYC motif was found in the ITS1 sequence alignment and has been identified as similar to the inverted repeats found in ascomycetes and to the stem of helix 1C in some angiosperms (Liu and Schardl 1994).
As a result of the number of polymorphisms in sequences of PAW-Cg110, PAW-Cg122, PAW-Cg6 and PAW-Cg7, the predicted consensus secondary structure was distinct from all other taxa and a fifth ribotype was proposed. Among eukaryotes, there is an apparent variability in the number of helices and structural details that occur in the ITS1 transcript, for example, four helices were identified in Chlorobionta (Coleman et al. 1998; Gottschling et al. 2001) and Saccharomyces cerevisiae (van Nues et al., 1994), but seven helices were proposed for Digenea (von der Schulenburg et al., 1999). Since there is no consensus structure for this ITS marker as there is for the ITS2 marker, it is difficult to determine whether these variants are normally distributed or may be representative of a separate species within the C. gloeosporioides sensu lato complex but which was not considered in this study.
5.8S structure modelling
There were no polymorphic sites within the aligned 5.8S sequences and the entire 117 nt region was conserved with 0.0000 entropy (Hx) value. The delta G required for formation of the secondary structure of the 5.8S gene was -15.2 kcal/mol, and the GC content was 39.3%.
ITS2 structure modelling
Homology modelling provided high quality models and recovered a consensus secondary structure for the two ribotypes (Figure 5) which consisted of four helices radiating from a central loop. Four helices were identified and were designated I, II, III and IV. The consensus secondary structure of this region has been described as having four helices of which helix III may be the longest, and contains an “UGGU” motif 5’ to the apex. Sequence variations of this helix, such as “UGGGU”, “UGG”, or “GGU”, have been described in addition to the existence of a U-U mismatch in the second helix which is conserved in the vast majority of eukaryotes (Schultz et al. 2005; Coleman 2007). For each ribotype, percentages of helix transfer were 100% for any of the four helices. C. asianum and C. siamense had 87.14% similarity match for helix IV when ribotypes 1 and 2 (a) and (b) were compared. The ITS2 database motif description was a “U-U” mismatch (helix II, left, at 395–409 nt) “U-U” mismatch (helix II, right) with AAA between helices II and III (at 429–443 nt), “UGGU” on helix III at the 5′ end. The GC content of the ITS2 was 56.19% which was similar to that of the ITS1 marker and indicated that no pseudogenes were present in the data set.
In this study, the observed variability of the ITS1 marker was higher than that of ITS2 which is in-keeping with the findings of Freire et al. (2012) and Nilsson et al. (2008). Although several conserved nucleotide sequence motifs have been identified in 5.8S and ITS2 sequences (Liu and Schardl 1994; Mai and Coleman 1997), it is the retention of functionally conserved secondary structures that enable the ITS array to play a critical role in the production of mature rRNA molecules (van Nues et al. 1994, 1995; Joseph et al. 1999; Michot et al. 1999; Venema and Tollervey 1999). It is apparent from the level of variation in the nucleotide sequence and predicted secondary structures of the ITS1 and ITS2 markers that different selective pressures may be acting at each markers. Within the ITS array, some regions are under evolutionary constraints at the level of the nucleotide sequence (Liu and Schardl 1994; Mai and Coleman 1997), while others are under positive selection at the level of the secondary structure with the emergence of concomitant compensatory base changes to preserve this structure (van Nues et al. 1994, 1995; Joseph et al. 1999).
Studies have shown that within the C. gloeosporioides sensu lato species complex, ITS sequences are capable of resolving approximately 50% of the accepted species (Weir et al. 2012). This reflects the low number of base changes in the ITS region across the C. gloeosporioides sensu lato species complex. Member species are often distinguished by only one or two base changes. In some cases, the variation in the ITS sequence is insufficient to distinguish among certain members of this species complex. There was only one other study by Bridge et al. (2008) in which the structure types of the ITS1 marker for C. gloeosporioides were compared. At the time of that study, many of the now-known epitype member species of this complex were not used and it is, therefore, difficult to determine the reliability of the predicted structures and precisely to which intra-specific level the identified structures belonged.
This is the first study to systematically evaluate the predicted secondary structures for the rRNA sequences of member species belonging to C. gloeosporioides sensu lato species complex that infect papaya in Trinidad. The ITS sequences of fungal species of this complex have been considered to be insufficiently variable to reliably distinguish between member species. In this study, taxon-specific secondary structures have been predicted for certain member species of the C. gloeosporioides sensu lato species complex which may provide supplementary data to improve the identification of species belonging to this species complex.
Type sequences of C. gloeosporioides sensu stricto, C. asianum, C. fructicola, C. siamense and C. tropicale (Additional file 1: Table S1) were mined from GenBank. These species within the C. gloeosporioides species complex have been commonly identified as the causal agents of anthracnose of tropical fruit (Phoulivong et al. 2010). In selecting the sequences from holotype and epitype specimens for analyses, there were three important considerations, (i) the type sequences were selected based on the study by Cannon et al. (2012), and were included to provide sufficient range of sequence diversity, (ii) the species used are well- characterized and recognized at the phylogenetic and morphological levels, and (iii) the selected species have been analyzed in previous independent studies.
To obtain test sequences, papaya fruit displaying symptoms of anthracnose were collected during the period 2011 to 2013 (Additional file 1: Table S2). DNA was extracted from pure single spore cultures of Colletotrichum sp. using the E.Z.N.A. fungal DNA extraction kit® according to the manufacturer’s instructions (Omega bio-tek Ltd., USA). The entire ITS region (496 bp) was amplified using the universal primer pair ITS4/5 (White et al. 1990) and sequenced with independent base call verification (Amplicon Express, WA, USA). Representative sequences were submitted to GenBank (KM117226 to KM117228). A total of 56 sequences were used in the final data set for generating consensus secondary structures for ITS1, 5.8S and ITS2 markers: 30 type sequences obtained from holotype and epitype specimens and 26 query sequences belonging to the C. gloeosporioides sensu lato complex. Other fungal sequences were also mined from GenBank (HQ238968, JF780523, EU480703, HQ238962, EF543854) and were used as out-groups to assist in defining of helical domains of the three markers based on mfold alignments in the UNAFold webserver (http://mfold.rna.albany.edu/) (Zuker 2003; Markham and Zuker 2008).
ITS sequence analysis and alignment
Errors can occur during PCR amplification when two different DNA templates may be present. The resulting amplicon may be chimeric, that is, a mosaic of these original sequences (Jumpponen 2011). Such chimeric sequences may be misinterpreted as novel which can artificially inflate estimates of diversity and interfere with phylogenetic inference and species discrimination if undetected (Hugenholtz and Huber 2003). ITS sequences were checked for possible chimeras using the UNITE PlutoF Chimera checker (Nilsson et al. 2010; Edgar et al. 2011) and the Chimera Test developed in the Fungal Metagenomics Project at the University of Alaska (https://biotech.inbre.alaska.edu/fungal_portal/?program=chimera_test).
Verifying ITS sequence validity
Alignments were carried out using the online version of the sequence alignment program MAFFT version 6 ((http://mafft.cbrc.jp/alignment/server/ (Katoh et al. 2005; Katoh and Toh 2008). This sequence analysis will also aid in determining if the ITS sequences were composed of stochastic, artifactual nucleotide data. The start and end point of each marker were first defined for each species using the pipeline available on the ITS2 database website (http://its2.bioapps.biozentrum.uni-wuerzburg.de/). Ultimately, three sets of sequence alignments were generated: ITS1, 5.8S and ITS2 as separate data sets.
Comparison of GC content and nucleotide diversity of the ITS sequences
The sequence length of the ITS1 and ITS2 region for a given species can be variable, however, the two markers should have similar GC content if they are authentic sequences under functional and selective constraints and not pseudogenes (Harpke and Peterson 2008; Mullineaux and Hausner 2009). The GC content of the ITS1, 5.8S and ITS2 sequences was determined using BioEdit version 7.2.0 software. DNASP version 5.10 (Rozas et al. 2003; Librado and Rozas 2009) was used to determine the nucleotide diversity (Pi), polymorphic and singleton sites, indel sites and indel haplotypes among the ITS1, 5.8S and ITS2 sequences.
Secondary structure prediction
Ribosomal secondary structure and motif detection was determined for the ITS2 marker. Secondary structure predictions of rRNA sequences are sensitive to single base changes which in turn, can affect hydrogen base-pairing especially along the stem aspect of a stem-loop secondary structure (Matthews et al. 2005). Consequently for this study, the ITS sequences and their electropherograms were manually reviewed and evaluated for signal quality and accurate nucleotide assignment in order to prevent user-induced errors in structural predictions. Because the core folding pattern of the ITS2 sequence is already known, this presents an external criterion or reference to check for the correctness of the predicted structures (Schultz and Wolf 2009). For the ITS2 consensus secondary structure prediction, the ITS2 database pipeline (http://its2.bioapps.biozentrum.uni-wuerzburg.de/) (Koetschan et al. 2010; Merget et al. 2012; Koetschan et al. 2012) was used. Consensus secondary structures for the ITS1 and 5.8S markers were determined using LocaRNA-P simultaneous RNA alignment and folding option of the Freiburg RNA Tools pipeline (http://rna.informatik.uni-freiburg.de:8080/LocARNA/Input.jsp) (Will et al. 2007, Will et al. 2012 and Smith et al. 2010), and the RNA folding form option of the mfold webserver using default conditions for temperature (37°C) and ionic conditions (http://mfold.rna.albany.edu/) (Zuker 2003; Markham and Zuker 2008). Consensus secondary structures for ITS1, 5.8S and ITS2 markers as radial view structures were re-drawn and annotated for publication purposes using VARNA 3.9 (Darty et al. 2009).
Funding for this work was provided by The University of the West Indies, St. Augustine, Campus Research and Publications Grant (Grant No. CRP.3.NOV11.8). This funding source had no role in the study design; in the collection, analysis and interpretation of data; in the writing of the report; and in the decision to submit the article for publication. The author is indebted to Prof. Annette Coleman at Brown University for her review of the predicted secondary structures and for her helpful suggestions regarding punctuations and annotations and to Dr. Sebastian Will at MIT for his review of the LocaRNA-P-generated RNA sequence alignments and MFE consensus structures.
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