Ribosomal protein coding genes SSU12p and LSU36p as molecular markers for phytoplasma detection and differentiation

Abstract

Summary. Detection and classification of phytoplasmas mainly rely on amplification of the 16S rRNA gene followed by RFLP analysis and/or sequencing, because these organisms lack complete phenotypic characterization. Other conserved genomic loci have been exploited as additional molecular markers for phytoplasma differentiation. Two loci, SSU12p and LSU36p, selected by whole-genome comparison of 12 phytoplasma strains, were used for primer design, and were successfully tested on DNA samples from plants infected by phytoplasmas belonging to ten 16S ribosomal groups. The phylogenetic trees inferred from SSU12p and LSU36p loci were highly congruent to the trees derived from 16S rRNA and tuf genes of the same phytoplasma strains. Virtual RFLP analysis of the amplified SSU12p gene showed distinct patterns for most of the phytoplasma ribosomal subgroups tested. These results show that SSU12p and LSU36p genes are reliable additional markers for phytoplasma detection and differentiation.

Headnote

Summary. Detection and classification of phytoplasmas mainly rely on amplification of the 16S rRNA gene followed by RFLP analysis and/or sequencing, because these organisms lack complete phenotypic characterization. Other conserved genomic loci have been exploited as additional molecular markers for phytoplasma differentiation. Two loci, SSU12p and LSU36p, selected by whole-genome comparison of 12 phytoplasma strains, were used for primer design, and were successfully tested on DNA samples from plants infected by phytoplasmas belonging to ten 16S ribosomal groups. The phylogenetic trees inferred from SSU12p and LSU36p loci were highly congruent to the trees derived from 16S rRNA and tuf genes of the same phytoplasma strains. Virtual RFLP analysis of the amplified SSU12p gene showed distinct patterns for most of the phytoplasma ribosomal subgroups tested. These results show that SSU12p and LSU36p genes are reliable additional markers for phytoplasma detection and differentiation.

Keywords. PCR, 16S rRNA gene, tuf gene, RFLP.

INTRODUCTION

Phytoplasmas are obligate intracellular pathogens that reside and multiply in the phloem tissues of plants and in insect hosts. They are associated with severe diseases of economically important plants, including aster yellows, coconut lethal yellowing, apple proliferation, pear decline, peach X disease and ash yellows. Australian grapevine yellows, which is associated with three phytoplasmas, causes up to 54% yield losses (Glenn, 2000). In Brazil, yield losses caused by maize bushy stunt are estimated to be worth $US 16.5 million (Oliveira et al., 2003). Due to the difficulty to culture phytoplasmas (Contaldo and Bertaccini, 2019) and the lack of a complete phenotypic characterization of these organisms, phytoplasmas classification is based on their 16S rRNA gene sequences, that are conserved and widely used for prokary ote identification (Lee et al., 1993; Ludwig and Schleifer, 1994; Seemüller et al., 1994; Schneider et al, 1995; Jenkins et al., 2012). A provisional naming system (IRPCM, 2004) assigned 'Candidatus Phytoplasma' species to strains whose 16S rRNA gene sequence has less than 97.5% identity to any previously described 'Ca. Phytoplasma' species. A set of 17 restriction enzymes was selected to generate the restriction fragment length polymorphism (RFLP) profile of the R16F2n/R2 fragment of the 16S rRNA gene. By this approach, 16Sr groups and subgroups have been identified (Lee et al., 1998; Wei et al., 2008). The 'Ca. Phytoplasma' species and the RFLPgenerated ribosomal groups and subgroups are therefore the two approaches used to classify these prokaryotes. However, one 16S ribosomal group may contain one or more 'Ca. Phytoplasma' species, whereas all the strains within one ribosomal subgroup belong to the same 'Ca. Phytoplasma' species (Bertaccini and Lee, 2018).

Considering the stringency of the 16S rRNA gene in assigning 'Ca. Phytoplasma' species, there are limitations in differentiating closely related strains, so other loci have been described and utilized as additional molecular markers for phytoplasma strain differentiation. Other markers have been used in phytoplasma phylogenetic studies, including the 16S-23S intergenic spacer, the 23S rRNA gene, the ribosomal protein operon (rp19-rpl22rps3), the elongation factor Tu (tuf), protein translocase units (secA and secY), the chaperonin 60 (cpnóü), and the subunit ß of RNA polymerase (rpoB) (Marcone et al., 2000; Martini et al., 2002, 2007; Hodgetts et al., 2008; Lee et al., 2010; Makarova et al., 2012; Valiunas et al., 2013). The methionine aminopeptidase gene (map)-uvrBdegV, nusA and vmp1 was also used for differentiation of strains within, respectively, the 16SrV, 16SrI and 16SrXII-A groups and subgroups (Shao et al., 2006; Arnaud et al., 2007; Cimerman et al., 2009). All these markers except vmp1 have also been used for differentiation of other bacteria (Pérez-López et al., 2016), confirming the suitability of a gene-based strategy also for phytoplasma strain differentiation.

Besides providing classification, the 16S rRNA gene also serves as the most important detection marker for phytoplasmas. Several sets of primers have been designed to amplify different fragments from this gene. The combination of P1/P7 and R16F2n/R2 is the most employed for phytoplasma detection, but other primer sets as well as ribosomal group-specific primers are useful for detection of multiple phytoplasma infections and/ or heterogeneous phytoplasma populations (Duduk et al., 2013). Other loci are also used as detection markers, including tuf, rpoB, cpn60, nusA and vmp1 (Shao et al., 2006; Cimerman et al., 2009; Makarova et al., 2012; Valiunas et al., 2013; Dumonceaux et al., 2014). However, the lack of universal primers (rpoB, secY, rp), the narrow detection range (nusA, vmp1, map-uvrB-degV) and the high rate of false positives (cpn60) severely reduce their detection efficiency.

In the present study, new molecular markers for phytoplasma detection and differentiation were designed and tested. Using whole genome comparisons, the phytoplasma genome conserved regions SSU12p and LSU36p were selected for primer design, and tested to verify their usefulness as molecular markers for a range of phytoplasma strains.

MATERIALS AND METHODS

Phytoplasma strains and nucleic acid preparation

Thirty-three phytoplasma strains collected from various host plant species from different geographic regions worldwide were used. The strains were identified on their 16S ribosomal DNA (Cui et al., 2019; EPPO-Q-bank, 2020), and belong to the 16Sr groups: -I, -II, -III, -V, -VI, -VII, -IX, -X, -XII and -XIII. The strain names, acronyms, 16Sr groups/subgroups, and providers are listed in Table 1. The DNAs from strawberry plants infected by the StrPh-CL strains were extracted as described by Cui et al. (2019). DNA samples provided by EPPO-Q-bank were extracted as described by Makarova et al. (2012).

Primer design

Direct and nested PCR primers were designed by comparing the conserved genomic regions of 12 phytoplasma strains available from the GenBank, including those associated with the diseases aster yellows witches' broom (AYWB) (CP000061), onion yellows mild strain (OYM) (NC_005303), peanut witches' broom (PnWB) strain NTU2011 (AMWZ00000000), Echinacea purpurea witches' broom (E. purpurea WB) strain NCHU2014 (LKAC00000000), Italian clover phyllody (ItClPh) strain MA1 (AKIM00000000), Vaccinium witches' broom (VacWB) strain VAC (AKIN00000000), milkweed yellows (MWY) strain MW1 (AKIL00000000), poinsettia branch-inducing phytoplasma (PoiBI) strain JR1 (AKIK00000000), 'Ca. P. mali' strain AT (CU469464), 'Ca. P. australiense' (AUSGY) (AM422018), strawberry lethal yellows phytoplasma (CPA) strain NZSb11 (CP002548), and phytoplasma Vc33 (LLKK00000000). Whole-genome comparison was performed with the "Sequence-based comparison" tool on the Rapid Annotation using the Subsystem Technology (RAST) server (http://rast.nmpdr.org/rast.cgi). The annotated genes were sorted based on similarity, and four genes with the greatest similarities, except for the 16S rRNA, were selected for primer design. These were: the small subunit ribosomal protein S12p (SSU12p), and the large subunit ribosomal proteins L2p, L27p and L36p (LSU2p, LSU27p and LSU36p). For each gene, a region containing the gene and 500 bp flanking the region upstream and downstream was used for the alignment. Direct and nested primers were selected within the most conserved regions (Table 2).

Cloning and sequencing

PCRs were carried out using the Invitrogen™ Platinum™ Taq DNA Polymerase system. Each reaction was performed in a 30 pL volume containing 1x reaction buffer, 2.5 mM MgCl2 and 2 U Taq polymerase, supplied with 0.3 mM dNTP, 0.8 pM of each primer and sterile double distilled water. One pL (20 ng) of nucleic acid was used as template, and 0.2 pL of the amplicon was used as template for the nested assays. A sample devoid of DNA template was enclosed as negative control. PCR was initiated by a 5 min denaturation at 94°C, followed by 35 cycles of 30 s denaturation at 94°C, 45 s annealing at respective temperatures (Table 2) and 1 min extension at 72°C, and a final extension at 72°C for 7 min. A three step annealing strategy was used, with each step of 15 s, for all the primer sets (Table 2).

The PCR products were resolved in 1.2% agarose gels with ethidium bromide. Amplicons, corresponding to approx. 820 bp for the SSU12p gene and 420 to 530 bp for the LSU36p gene from nested PCR, were recovered and cloned into the vector pGEM·-T Easy (Promega). The plasmids were transformed into E. coli TOP10 chemically competent cells (Life Technologies), and the clones were sequenced using the T7/SP6 primers in both directions. Each pair of sequences was aligned and assembled using BioEdit. Three individual clones for each amplicon from each sample were analyzed. Each PCR, cloning and sequencing was repeated at least three times.

Phylogenetic analyses

The consensus sequence of each amplicon was submitted to the NCBI GenBank database (Table 1). Sequence information of the 12 phytoplasma strains used for the primer design was obtained from the same database. Sequence information of four other strains, including maize bushy stunt phytoplasma (MBS) strain M3 (CP015149), 'Ca. P. pruni' strain CX (LHCF00000000), 'Ca. P. phoenicium strain SA213 (JPSQ00000000), and 'Ca. P. solani' (STOL) strain SA-1 (MPBG00000000), was also retrieved from the database for constructing phylogenetic trees. The sequence alignment was performed using ClustalW. Acholeplasma laidlawii (CP000896) served as outgroup. The phylogenetic trees were constructed using the Molecular Evolutionary Genetics Analysis program (MEGA7) (Kumar et al., 2016). Diversity indices, represented by the distances within and between groups, were also calculated using MEGA7. Virtual RFLP was performed using Vector NTI.

RESULTS

PCR amplification

In all the PCR reactions, several annealing temperatures were tested to select the best combinations. Since one reaction may include more than two primers and each primer may contain several degenerate nucleotides, a range of melting temperatures was calculated using the online tool (IDT OligoAnalyzer). This range could exceed the suggested melting temperature difference (5°C) for primer design, and when a single annealing temperature was utilized, not all the primers would anneal as efficiently, and nonspecific amplicons might be produced. Therefore, a three-step annealing strategy was used to optimize the reactions. Three annealing temperatures were selected at the maximum, mean and minimum points in the melting temperature range, each step lasting 15 sec. For each primer set, several adjustments were made before establishing the optimal combination (Table 2).

For all the samples used in this study, the PCR assay using the ItSSU12pF/ItSSU12pR primer pair produced clear bands approximately ranging from 750 bp to 820 bp (Figure 1A, Table 1). Subsequent nested PCR also generated clear bands (data not shown). These PCR amplicons were cloned and sequenced.

The PCR assay using the ItLSU36pF1/2/ItLSU36pR primers generated multiple bands or smears, and, in several cases, the expected products were not visible (Figure 1B). However, the subsequent nested PCR using the ItLSU36pFn/ItLSU36pRn primers always generated a strong and clear amplicon, and, in some cases, longer but significantly weaker bands (Figure 1C, Table 1). The strongest bands from each sample were recovered from the gels, cloned and sequenced.

The direct and nested PCR assays targeting LSU2p and LSU27p genes failed to produce satisfactory results. In each trial, less than half of the tested samples showed amplification, and the results were not repeatable (data not shown). Optimization of the annealing temperatures failed to achieve consistent results and these primers were therefore discarded.

The specificity of the remaining primers was tested for detection of Xylella fastidiosa, Agrobacterium tumefaciens, Pantoea agglomerans, Clavibacter michiganensis subsp. michiganesis, Pseudomonas syringae pv. tomato, P. syringae pv. syringae, Ralstonia solanacearum, Curtobacterium flaccumfaciens pv. flaccumfaciens, Xanthomonas arboricola pv. juglandis, 'Candidatus Liberibacter solanacearum', and Ca. L. asiaticus', with no amplification (data not shown).

Loci structures

The amplicons generated by ItSSU12pF/ItSSU12pR covered the full length of the SSU12p gene, the partial sequence of SSU7p gene, and the intergenic region between the two genes. In the following text, this amplicon and its corresponding genomic locus are referred to as SSU12p. Sequence alignment of all the amplified samples and selected strains retrieved from the GenBank showed that SSU12p presented greater variation among ribosomal groups and subgroups compared with 16S rRNA (Supplementary Figure S1). The most relevant variation lay between 396 to 431 nt in strain AYWB (16SrIA) corresponding to the intergenic region, which was less conserved than the coding genes, where the phytoplasma strains of the same ribosomal group and/or subgroup were featured by specific insertions and deletions.

The amplicon generated by ItLSU36pFn/ItLSU36pRn covered approximately 80% of the LSU36p gene, the full length of the gene encoding bacterial protein translation initiation factor 1 (IF-1), approx. 5% of the map gene, and the two intergenic regions. This amplicon and its corresponding genomic locus is referred to as LSU36p in the following text. Sequence alignment showed that the most conserved region was that encompassing the first 102 nt in the sequence of the strain AYWB, corresponding to the LSU36p gene (Supplementary Figure S2). The rest of the amplicon was highly variable among ribosomal groups and/or subgroups, with especially low similarity between the three tested strains in the 16SrIX group and the rest of the strains. However, by comparing this region in AYWB and 'Ca. P. phoenicium' strain SA213 (16SrIX-B) it was observed that the low similarity was mainly located in the two intergenic regions, which also resulted in differences in length among the tested strains (Supplementary Figures S2 and S3).

Phylogenetic analyses

Phylogenetic trees were constructed with the SSU12p and LSU36p sequences separately as well as with the concatenated sequences (Figures 2A, 2B and 2C). The three trees showed clear separation of the phytoplasmas classified in the different 16Sr groups, the only exception being the 16SrXII-A subgroup (Ca. P. solani'), which was more closely related to the 16SrI group than to the other 16SrXII subgroups in the SSU12p tree (Figure 2A). A number of subgroups and their corresponding Ca. Phytoplasma' species were also clearly separated, e.g. 16SrIB B P. asteris'), 16SrXII-A ('Ca. P. solani'), 16SrXIIIF, 16SrXIII-K, 16SrX-A ('Ca. P. mali'), 16SrX-B ('Ca. P. prunorum') and 16SrX-C ('Ca. P. pyri'). The three trees showed significant consistency with those inferred from the 16S rRNA and tuf genes (Figure 2D and 2E).

To further evaluate the efficiency of the SSU12p and LSU36p for phytoplasma strain differentiation, the diversity indices within each 16Sr group and between any two groups were calculated, and paired t-Tests were performed to compare the set of "between group mean distance" indices from each marker (Supplementary Table S1). Both sets of indices from SSU12p and LSU36p were significantly higher than that of 16S rRNA (P < 0.01), suggesting that these two markers could efficiently separate the strains in different ribosomal groups. The indi- ces from LSU36p are also significantly higher than that of the tuf gene, suggesting that using LSU36p would improve the differentiation of phytoplasma strains.

RFLP analyses

The SSU12p sequences were further examined using by virtual RFLP with 18 restriction enzymes including: AluI, BamHI, BfaI, BatUI, DraI, EcoRI, HaeIII, HhaI, HinfI, HpaI, HpaII, KpnI, MseI, RsaI, Sau3AI, SspI, TaqI and ThaI (Supplementary Figure S4). EcoRI had no restriction site in any of the 49 samples examined, BamHI, HpaI and KpnI each recognized only a single restriction site in one subgroup, HaeIII recognized only one restriction site in two subgroups, and MseI recognized up to 17 restriction sites in some subgroups. These enzymes were therefore not suitable for RFLP analyses. Another seven enzymes, AluI, BstUI, DraI, HhaI, RsaI, TaqI and ThaI generated two patterns within only one subgroup, and were therefore not suitable for the general phytoplasma differentiation. A set of five enzymes, BfaI, HinfI, HpaII, Sau3AI and SspI clearly separated all the 16Sr groups (Figure 3). However, subgroups 16SrIIA A 16SrIII-A and -E, 16SrIII-D and -F, 16SrXIIB B and 16SrXIII-F and-K still showed the same restriction patterns. Some of these pairs could be distinguished by additional enzymes, including: 16SrIII-D and -F distinguished by AluI, 16SrXII-B and -C by HhaI, and 16SrXIII-F and -K by AluI, BstUI, HhaI, RsaI and ThaI. The 16SrII-A and -D and 16SrIII-A and -E remained unresolved.

Several 16S ribosomal groups and subgroups were featured with specific SNP sites, some of which contributed to their distinct RFLP patterns. For example, all the sample strains from the 16SrI group shared the specific sites of 11T, 183C, 362G, 375T, 376T, 471C, 519C, 630C and 633C, whereas those belonging to the 16SrIII group were marked with the sites of 30T, 48G, 58A, 275G and 320G (Supplementary Figure S1). The 578A site of the strains from the 16SrXIII-F subgroup, and the 576A site of the strains from the 16SrXIII-K subgroup, also resulted in a specific SspI restriction site, producing a triple-band pattern for these two subgroups on the virtual RFLP. The 218G site unique to the strains from the 16SrIX-C subgroup resulted in a specific HpaII restriction site, generating double bands on the virtual RFLP for this subgroup (Figure 3, Supplementary Figures S1 and S4).

DISCUSSION

Using 33 DNA samples and 16 sequences retrieved from the GenBank belonging to ten 16Sr groups and 27 subgroups, this study has shown that both SSU12p and LSU36p are suitable loci for phytoplasma detection and differentiation. In the RFLP analyses using amplicons generated by SSU12p, a set of seven enzymes, including BfaI, HinfI, HpaII, Sau3AI, SspI, AluI and HhaI, were able to identify all the phytoplasmas in the 16Sr groups, and in all but four subgroups (16SrII-A/-D and 16SrIIIA/-E) examined.

The primers for SSU12p and LSU36p amplified phytoplasma sequences from all the samples tested, proving that they are amplifying conserved regions in a robust manner. The SSU12p primers generated in direct PCR clear, single-band products. According to the literature, SSU12p is to date peerless for phytoplasma PCR detection, considering its ability to generate a unique specific band in direct PCR using a single pair of primers from a wide range of phytoplasmas. The high consistency of SSU12p for phytoplasma identification with 16S rRNA and tuf genes confirms its reliability, suggesting that the application of this pair of primers is appropriate for rapid and efficient phytoplasma detection and identification. The LSU36p primers, on the other hand, requires nested amplification, and the resulting products may vary significantly in size. However, the relatively high value of between-group mean distance indices suggests that LSU36p has potential for resolving closely related strains. Further study focused on other strains belonging to different subgroups from the same ribosomal group is required for confirmation.

Due to different evolutionary processes, phylogenetic trees derived from different genome loci may show conflicting structures. One way to interpret the conflicting information is to concatenate the loci for phylogenetic analyses. Although concatenation is a controversial method because of potential misspecification of models, it provides longer sequences to overcome sampling errors (Holland et al, 2004). In the present study, the phylogenetic trees inferred from SSU12p, LSU36p and SSU12p plus LSU36p showed clear and unambiguous consistency of ramification of phytoplasma subgroups within most of the 16Sr groups, confirming the robustness of the concatenation methods.

The only exception was the 16SrIII group, which showed unclear relationships among several subgroups. For example, in the SSU12p tree, the strain SBB from the 16SrIII-F subgroup formed a clade with the Vc33 from the 16SrIII-J subgroup, while the other two strains from the 16SrIII-F group, MWY and MW1, were grouped with strains from the 16SrIII-B and 16SrIII-D subgroups. This was probably due to the intrinsic structure of the 16SrIII group, since the trees from both tuf and 16S rRNA also showed unclear structures within this phytoplasma group. A similar conflict occurred within the 16SrIII group in independent studies analyzing 16S rRNA and secY phylogenies (Lee et al., 2010; Fernández et al., 2017). The two copies of the 16S rRNA gene of phytoplasmas in this group very often present interoperon heterogeneity. Data from secY and tuf genes, both present in the genome in single copy, indicated that the confusing tree structures were not incidental. These results suggest that the subgroup classification within the 16SrIII group may not reflect phylogenetic interrelationship and the RFLP-based classification may be biased, because this classification solely depends on the restriction sites of a selected set of enzymes while the SNPs in sequences other than these sites are neglected.

The reliability of SSU12p and LSU36p as phytoplasma markers confirms that genome comparison is an approach that could also be used for selecting genes to differentiate these bacteria. A larger number of samples than used in the present study, containing strains from untested groups and subgroups, will help to confirm the wide reliability of this detection system. The development of next-generation sequencing and long-read sequencing has built an expanding genomic database of microbial pathogens. Comparative genomics has been used to study the mechanisms of pathogenicity, molecular epidemiology, molecular diagnostics, multi-locus sequence typing, and transmission prediction (Avarre et al., 2011; Bastardo et al., 2012; Walker et al., 2014; Bayliss et al., 2017; Aly et al., 2019). As more phytoplasma genomes are being sequenced, comparative genomics has also become the trend for analyses in genome reports (Sparks et al., 2018; Wang et al., 2018; Music et al., 2019; Cho et al., 2019). Approaches on the genome level will likely be increasingly applied to phytoplasmas for understanding their adaptations to diverse host species. However, the identification of new markers for detection and differentiation of phytoplasmas strains is still a necessary tool for developing knowledge of epidemiology and management of phytoplasma-associated diseases that aim to avoid their pandemic distribution.

ACKNOWLED GEMENTS

This study was supported by the National Fund for Scientific and Technological Development (FONDECYT) of Chile, project Nos. 1140883 and 11160719, and Postdoctoral Project 2017, No. 3170120.

Sidebar

Citation: W. Cui, A. Zamorano, N. Quiroga,A. Bertaccini, N. Fiore (2021) Ribosomal protein coding genes SSU12p and LSU36p as molecular markers for phytoplasma detection and differentiation. Phytopathologia Mediterranea 60(2): 281-292. doi: 10.36253/phyto-11993

Accepted: July 7, 2021

Published: September 13, 2021

Copyright: © 2021 W. Cui, A. Zamorano, N. Quiroga, A. Bertaccini, N. Fiore. This is an open access, peer-reviewed article published by Firenze University Press (http://www.fupress.com/pm) and distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability Statement: All relevant data are within the paper and its Supporting Information files.

Competing Interests: The Author(s) declare(s) no conflict of interest.

Editor: Nihal Buzkan, Kahramanmaraş Sütçü Imam University, Turkey.

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