Molecular diagnostic tools for detection and differentiation of phytoplasmas based on chaperonin-60 reveal differences in host plant infection patterns

Development of a Specific Nested PCR Assay for the Detection of 16SrI Group Phytoplasmas Associated with Sisal Purple Leafroll Disease in Sisal Plants and Mealybugs

Sisal purple leafroll disease (SPLD) is currently the most destructive disease affecting sisal in China, yet its aetiology remains unclear. In our previous research, it was verified to be associated with phytoplasmas, and nested PCR based on the 16S rRNA gene using universal primers R16mF2/R16mR1 followed by R16F2n/R16R2 was confirmed as the most effective molecular method for the detection of phytoplasmas associated with SPLD (SPLDaP). However, the method has a shortcoming of inaccuracy, for it could produce false positive results. To further manage the disease, accurate detection is needed. In this study, we developed a specific nested PCR assay using universal primers R16F2n/R16R2, followed by a set of primers designed on 16Sr gene sequences amplified from SPLDaP, nontarget bacteria from sisal plants, and other phytoplasma subgroups or groups. This established method is accurate, specific, and effective for detection of 16SrI group phytoplasma in sisal, and its sensitivity is up to 10 fg/μL of total DNA. It also minimized the false positive problem of nested PCR using universal primers R16mF2/R16mR1 followed by R16F2n/R16R2. This method was further used to verify the presence of phytoplasma in Dysmicoccusneobrevipes, and the results showed that D. neobrevipes could be infected by SPLDaP and thus could be a candidate for vector transmission assays.

Multilocus sequence typing of diverse phytoplasmas using hybridization probe-based sequence capture provides high resolution strain differentiation

Phytoplasmas are insect-vectored, difficult-to-culture bacterial pathogens that infect a wide variety of crop and non-crop plants, and are associated with diseases that can lead to significant yield losses in agricultural production worldwide. Phytoplasmas are currently grouped in the provisional genus ‘Candidatus Phytoplasma’, which includes 49 ‘Candidatus’ species. Further differentiation of phytoplasmas into ribosomal groups is based on the restriction fragment length polymorphism (RFLP) pattern of the 16S rRNA-encoding operon, with more than 36 ribosomal groups (16Sr) and over 100 subgroups reported. Since disease symptoms on plants are not associated with phytoplasma identity, accurate diagnostics is of critical importance to manage disease associated with these microorganisms. Phytoplasmas are typically detected from plant and insect tissue using PCR-based methods targeting universal taxonomic markers. Although these methods are relatively sensitive, specific and are widely used, they have limitations, since they provide limited resolution of phytoplasma strains, thus necessitating further assessment of biological properties and delaying implementation of mitigation measures. Moreover, the design of PCR primers that can target multiple loci from phytoplasmas that differ at the sequence level can be a significant challenge. To overcome these limitations, a PCR-independent, multilocus sequence typing (MLST) assay to characterize an array of phytoplasmas was developed. Hybridization probe s targeting cpn60, tuf, secA, secY, and nusA genes, as well as 16S and rp operons, were designed and used to enrich DNA extracts from phytoplasma-infected samples for DNA fragments corresponding to these markers prior to Illumina sequencing. This method was tested using different phytoplasmas including ‘Ca. P. asteris’ (16SrI-B), ‘Ca. P. pruni’ (16SrIII-A),‘Ca. P. prunorum’ (16SrX-B), ‘Ca. P. pyri’ (16SrX-C), ‘Ca. P. mali’ (16SrX-A), and ‘Ca. P. solani’ (16SrXII-A). Thousands of reads were obtained for each gene with multiple overlapping fragments, which were assembled to generate full-length (typically >2 kb), high-quality sequences. Phytoplasma groups and subgroups were accurately determined based on 16S ribosomal RNA and cpn60 gene sequences. Hybridization-based MLST facilitates the enrichment of target genes of phytoplasmas and allows the simultaneous determination of sequences corresponding to seven different markers. In this proof-of-concept study, hybridization-based MLST was demonstrated to be an efficient way to generate data regarding ‘Ca. Phytoplasma’ species/strain differentiation.

Detection of blueberry stunt phytoplasma in Eastern Canada using cpn60-based molecular diagnostic assays

Blueberry stunt phytoplasma (BBSP; ‘Candidatus Phytoplasma asteris’) is an insect-vectored plant pathogen that causes severe yield losses in blueberry (Vaccinium corymbosum), which is the most valuable fruit crop in Canada. Rapid, field-based diagnostic assays are desirable tools for the control of BBSP, as part of an integrated, proactive approach to production management termed biovigilance. We designed and validated a chaperonin-60 (cpn60)-targeted LAMP assay for detection of BBSP, providing a rapid, low cost, field-deployable diagnostic option. Our validation demonstrates that the assay is reproducible, with high analytical specificity and improved sensitivity when compared with 16S rRNA nested PCR. We applied the validated LAMP assay to nearly 2000 blueberry samples from Québec and Nova Scotia over three growing seasons (2016–2018). Our surveys revealed that BBSP is present in most sites across both provinces, though detection of the pathogen in individual plants varied in different tissues across sampling dates and across years, and evidence of spread between plants was limited. To quantify pathogen load in select plants, we designed additional qPCR and ddPCR assays, also based on cpn60. We found that pathogen load fluctuates in individual plants, both within and between growing seasons. Finally, we designed an interactive map to visualize the results of our surveys. These results provide a validated diagnostic assay that can be used as part of a biovigilance strategy for detecting and controlling infections caused by BBSP.

Species Boundaries and Molecular Markers for the Classification of 16SrI Phytoplasmas Inferred by Genome Analysis

Phytoplasmas are plant-pathogenic bacteria that impact agriculture worldwide. The commonly adopted classification system for phytoplasmas is based on the restriction fragment length polymorphism (RFLP) analysis of their 16S rRNA genes. With the increased availability of phytoplasma genome sequences, the classification system can now be refined. This work examined 11 strains in the 16SrI group within the genus ‘Candidatus Phytoplasma’ and investigated the possible species boundaries. We confirmed that the RFLP classification method is problematic due to intragenomic variation of the 16S rRNA genes and uneven weighing of different nucleotide positions. Importantly, our results based on the molecular phylogeny, differentiations in chromosomal segments and gene content, and divergence in homologous sequences, all supported that these strains may be classified into multiple operational taxonomic units (OTUs) equivalent to species. Strains assigned to the same OTU share >97% genome-wide average nucleotide identity (ANI) and >78% of their protein-coding genes. In comparison, strains assigned to different OTUs share < 94% ANI and < 75% of their genes. Reduction in homologous recombination between OTUs is one possible explanation for the discontinuity in genome similarities, and these findings supported the proposal that 95% ANI could serve as a cutoff for distinguishing species in bacteria. Additionally, critical examination of these results and the raw sequencing reads led to the identification of one genome that was presumably mis-assembled by combining two sequencing libraries built from phytoplasmas belonging to different OTUs. This finding provided a cautionary tale for working on uncultivated bacteria. Based on the new understanding of phytoplasma divergence and the current genome availability, we developed five molecular markers that could be used for multilocus sequence analysis (MLSA). By selecting markers that are short yet highly informative, and are distributed evenly across the chromosome, these markers provided a cost-effective system that is robust against recombination. Finally, examination of the effector gene distribution further confirmed the rapid gains and losses of these genes, as well as the involvement of potential mobile units (PMUs) in their molecular evolution. Future improvements on the taxon sampling of phytoplasma genomes will allow further expansions of similar analysis, and thus contribute to phytoplasma taxonomy and diagnostics.

The CpnClassiPhyR Is a Resource for cpn60 Universal Target-Based Classification of Phytoplasmas

Phytoplasmas are plant-pathogenic bacteria that are associated with yield losses in many crop plants worldwide. Phytoplasma strain differentiation is accomplished using in silico restriction fragment length polymorphism (RFLP) analysis of 16S ribosomal RNA-encoding gene sequences, which has resulted in the definition of ribosomal groups and subgroups of phytoplasmas. Due to limitations associated with this approach, a complementary classification scheme was recently developed based on RFLP analysis of the single-copy, protein-encoding gene chaperonin-60 (cpn60). We present the CpnClassiPhyR, software that facilitates phytoplasma strain classification using both RFLP and automated phylogenetic analysis of cpn60 sequences. This software is available through a web interface at http://cpnclassiphyr.ca.

A novel 'Candidatus Phytoplasma asteris' subgroup 16SrI-(E/AI)AI associated with blueberry stunt disease in eastern Canada

Phytoplasmas ('Candidatus Phytoplasma' species) are phytopathogenic bacteria vectored by insects and are associated with crop diseases that cause severe yield losses by affecting reproductive tissue development. Infection of northern highbush blueberry plants (Vaccinium corymbosum; Ericaceae) with phytoplasma leads to yield losses by altering plant development resulting in stunting and subsequent plant death. Samples collected from symptomatic blueberry plants in two important blueberry-producing areas in Canada, in the provinces of Québec and Nova Scotia, were analysed for the presence of DNA sequences associated with phytoplasma. Analysis of the 16S rRNA gene sequences demonstrated that the plants were infected with a strain of 'Candidatus Phytoplasma asteris', which was previously identified as blueberry stunt phytoplasma (BBS; 16SrI-E). Examination of further bacterial sequences revealed that two distinct 16S rRNA-encoding gene sequences were present in each sample in combination with a single chaperonin-60 (cpn60) sequence and a single rpoperon sequence, suggesting that this strain displays 16S rRNA-encoding gene sequence heterogeneity. Two distinct rrnoperons, rrnE and the newly described rrnAI, were identified in samples analysed from all geographic locations. We propose, based on the sequences obtained, delineating the new subgroup 16SrI-(E/AI)AI, following the nomenclature proposed for heterogeneous subgroups. To our knowledge, this is the first report of a heterogeneous phytoplasma strain affecting blueberry plants and associated with blueberry stunt disease.

Genome Sequence of a Plant-Pathogenic Bacterium, "Candidatus Phytoplasma asteris" Strain TW1

A draft genome sequence is presented for a strain of "Candidatus Phytoplasma asteris" affecting canola plants in Saskatoon, Canada. This phytopathogenic bacterium was determined to be a 16SrI strain and features 16S rRNA-encoding gene sequence heterogeneity.

Detection and Typing of "Candidatus Phytoplasma " spp. in Host DNA Extracts Using Oligonucleotide-Coupled Fluorescent Microspheres

The use of oligonucleotide-coupled fluorescent microspheres is a rapid, sequencing-independent, and reliable way to diagnose bacterial diseases. Previously described applications of oligonucleotide-coupled fluorescent microspheres for the detection and identification of bacteria in human clinical samples have been successfully adapted to detect and differentiate "Ca. Phytoplasma" species using as a target the chaperonin 60-encoding gene. In this chapter, we describe in detail the design and validation of oligonucleotide capture probes, and their application in the assay aiming to differentiate phytoplasma strains infecting Brassica napus and Camelina sativa plants grown in the same geographic location at the same time.

Molecular identification and characterization of the new 16SrIX-J and cpn60 UT IX-J phytoplasma subgroup associated with chicory bushy stunt disease in Saudi Arabia

Chicory (Cichorium intybus) is a perennial plant (Asteraceae) that grows wild in pasture fields in Saudi Arabia. Chicory plants displaying symptoms typically induced by phytoplasmas, such as bushy phenotype and stunt, were observed in the Mulayda region, Qassim governorate, Saudi Arabia. In this study we examined samples taken from three symptomatic chicory plants and confirmed the presence of phytoplasma DNA. Analysis of the 16S rRNA-encoding sequences showed that the plants were infected with a phytoplasma from the pigeon pea witches'-broom group (16SrIX). Sequencing of the 16S rRNA-encoding gene and the partial cpn60 sequence, computer-simulated RFLP analysis, and phylogenetic analysis of both markers revealed that the phytoplasma identified was representative of a new 16SrIX-J and cpn60 UT IX-IJ subgroup. The present study identified chicory plants as a novel host for phytoplasma strains within the pigeon pea witches'-broom phytoplasma group, and expanded the known diversity of this group.

Molecular diagnostic assays based on cpn60 UT sequences reveal the geographic distribution of subgroup 16SrXIII-(A/I)I phytoplasma in Mexico

Geographically diverse samples from strawberry exhibiting symptoms of Strawberry Green Petal (SbGP), periwinkle plants with virescence, and blackberry, blueberry, and raspberry plants displaying yellowing and inedible fruits, were assayed for the presence of phytoplasma DNA. PCR targeting the 16S rRNA-encoding gene and chaperonin-60 (cpn60) showed that the plants were infected with phytoplasma subgroup16SrXIII-(A/I)I (SbGP/MPV). To examine the geographic distribution of this pathogen in Mexico, we designed an array of cpn60-targeted molecular diagnostic assays for SbGP/MPV phytoplasma. A fluorescent microsphere hybridization assay was designed that was capable of detecting SbGP/MPV phytoplasma in infected plant tissues, successfully differentiating it from other known phytoplasma cpn60 UT sequences, while identifying a double infection with SbGP/MPV and aster yellows (16SrI) phytoplasma. Two quantitative assays, quantitative real-time PCR (qRT-PCR) and droplet digital PCR (ddPCR), gave similar results in infected samples. Finally, a loop-mediated isothermal amplification (LAMP) assay provided rapid detection of SbGP/MPV phytoplasma DNA. Application of these assays revealed that SbGP/MPV phytoplasma is widely distributed in Central Mexico, with positive samples identified from eleven localities within three states separated by hundreds of kilometres. These results also provide tools for determining the presence and geographic distribution of this pathogen in plant and insect samples in other localities.

Phytoplasma classification and phylogeny based on in silico and in vitro RFLP analysis of cpn60 universal target sequences

Phytoplasmas are unculturable, phytopathogenic bacteria that cause economic losses worldwide. As unculturable micro-organisms, phytoplasma taxonomy has been based on the use of the 16S rRNA-encoding gene to establish 16Sr groups and subgroups based on the restriction fragment length polymorphism (RFLP) pattern resulting from the digestion of amplicon (in vitro) or sequence (in silico) with seventeen restriction enzymes. Problems such as heterogeneity of the ribosomal operon and the inability to differentiate closely related phytoplasma strains has motivated the search for additional markers capable of providing finer differentiation of phytoplasma strains. In this study we developed and validated a scheme to classify phytoplasmas based on the use of cpn60 universal target (cpn60 UT) sequences. Ninety-six cpn60 UT sequences from strains belonging to 19 16Sr subgroups were subjected to in silico RFLP using pDRAW32 software, resulting in 25 distinctive RFLP profiles. Based on these results we delineated cpn60 UT groups and subgroups, and established a threshold similarity coefficient for groups and subgroups classifying all the strains analysed in this study. The nucleotide identity among the reference strains, the correspondence between in vitro and in silico RFLP, and the phylogenetic relationships of phytoplasma strains based on cpn60 UT sequences are also discussed.

Development and Validation of a Fluorescent Multiplexed Immunoassay for Measurement of Transgenic Proteins in Cotton (Gossypium hirsutum)

In order to provide farmers with better and more customized alternatives to improve yields, combining multiple genetically modified (GM) traits into a single product (called stacked trait crops) is becoming prevalent. Trait protein expression levels are used to characterize new GM products and establish exposure limits, two important components of safety assessment. Developing a multiplexed immunoassay capable of measuring all trait proteins in the same sample allows for higher sample throughput and savings in both time and expense. Fluorescent (bead-based) multiplexed immunoassays (FMI) have gained wide acceptance in mammalian research and in clinical applications. In order to facilitate the measurement of stacked GM traits, we have developed and validated an FMI assay that can measure five different proteins (β-glucuronidase, neomycin phosphotransferase II, Cry1Ac, Cry2Ab2, and CP4 5-enolpyruvyl-shikimate-3-phosphate synthase) present in cotton leaf from a stacked trait product. Expression levels of the five proteins determined by FMI in cotton leaf tissues have been evaluated relative to expression levels determined by enzyme-linked immunosorbent assays (ELISAs) of the individual proteins and shown to be comparable. The FMI met characterization requirements similar to those used for ELISA. Therefore, it is reasonable to conclude that FMI results are equivalent to those determined by conventional individual ELISAs to measure GM protein expression levels in stacked trait products but with significantly higher throughput, reduced time, and more efficient use of resources.