A New Multiplex TaqMan qPCR for Precise Detection and Quantification of Clavibacter michiganensis in Seeds and Plant Tissue.

Bacterial canker of tomato caused by Clavibacter michiganensis (Cm) is one of the most devastating bacterial diseases affecting the tomato industry worldwide. As the result of Cm colonization of the xylem, the susceptible host shows typical symptoms of wilt, marginal leaf necrosis, stem cankers, and ultimately plant death. However, what makes Cm an even more dangerous pathogen is its ability to infect seeds and plants without causing symptoms. Unfortunately, there are no resistant cultivars or effective chemical or biological control methods available to growers against Cm. Its control relies heavily on prevention. The implementation of a rapid and accurate detection tool is imperative to monitor the presence of Cm and prevent its spread. In this study, we developed a specific and sensitive multiplex TaqMan qPCR assay to detect Cm and distinguish it from related bacterial species that affect tomato plants. Two Cm chromosomal virulence-related genes, rhuM and tomA, were used as specific targets. The plant internal control tubulin alpha-3 was included in each of the multiplexes to improve the reliability of the assay. Specificity was evaluated with 37 bacterial strains including other Clavibacter spp. and related and unrelated bacterial pathogens from different geographic locations affecting a wide variety of hosts. Results showed that the assay is able to discriminate Cm strains from other related bacteria. The assay was validated on tissue and seed samples following artificial infection, and all tested samples accurately detected the presence of Cm. The tool described here is highly specific, sensitive, and reliable for the detection of Cm and allows the quantification of Cm in seeds, roots, stems, and leaves. The diagnostic assay can also be adapted for multiple purposes such as seed certification programs, surveillance, biosafety, the effectiveness of control methods, border protection, and epidemiological studies.[Formula: see text] Copyright © 2024 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.

Quantification of Plasmodiophora brassicae Resting Spores in Soils Using Droplet Digital PCR (ddPCR).

Plasmodiophora brassicae, an obligate soilborne pathogen that causes clubroot on Brassica crops, is spreading rapidly in western Canada, threatening canola production in the region. Bioassays and molecular assays have been used to estimate the concentration of P. brassicae resting spores in soil, which can affect clubroot incidence and severity on crops. Droplet digital PCR (ddPCR) is a promising new approach for quantification of pathogen inoculum owing to its low sensitivity to inhibitors and consistency at low target concentrations. The objective of this study was to assess ddPCR against existing quantitative PCR (qPCR) for potential advantage and/or improvement in quantifying P. brassicae resting spores in soil. The new protocol enumerated resting spores accurately in spiked potting mix or soil samples ranging from 102 to 107 spores per gram. At a spore concentration ≥107 spores per gram, however, ddPCR became less accurate, with a tendency of overestimation. The protocol was validated by quantifying the resting spores in spiked brown, dark brown, and black soils using both ddPCR and qPCR simultaneously. These soil types are found commonly on the Canadian Prairies, and they vary in texture, pH, and organic content. ddPCR showed similar results among the different soil types, whereas qPCR often displayed lower counts for the same spore concentration, with the amplification of DNA inhibited completely in black soil samples. The inhibition can be removed by a 10-fold dilution of DNA samples. The results show that ddPCR can be a more versatile tool than qPCR for detection and quantification of P. brassicae resting spores in soil samples.

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.

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.

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.

Detection and identification of the heterogeneous novel subgroup 16SrXIII-(A/I)I phytoplasma associated with strawberry green petal disease and Mexican periwinkle virescence.

Phytoplasmas (species of the genus 'CandidatusPhytoplasma') are insect-vectored phytopathogenic bacteria associated with economically and ecologically important crop diseases. Strawberry production represents an important part of agricultural activity in Mexico and elsewhere, and infection of plants with phytoplasma renders the fruit inedible by altering plant development, resulting in virescence and phyllody. In this study we examined samples taken from four strawberry plants showing symptoms associated with strawberry green petal disease and from two periwinkle plants showing virescence, sampled in different areas of Mexico. Analysis of the 16S rRNA-encoding sequences showed that the plants were infected with a phytoplasma previously identified as Mexican periwinkle virescence (MPV; 16SrXIII). Examination of bacterial sequences from these samples revealed that two distinct 16S rRNA gene sequences were present in each sample along with a single chaperonin-60 (cpn60) sequence and a single rpoB sequence, suggesting that this strain displays 16S rRNA gene sequence heterogeneity. Two distinct rrn operons, identified with subgroup 16SrXIII-A and the newly described subgroup 16SrXIII-I, were identified from the six samples analyzed, delineating the novel subgroup 16SrXIII-(A/I)I, following the nomenclature proposed for heterogeneous subgroups.

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.

The underestimated diversity of phytoplasmas in Latin America.

Phytoplasmas ('Candidatus Phytoplasma') are insect-transmitted, cell-wall-less, plant-pathogenic bacteria that cause economically important crop diseases. Because phytoplasmas are difficult or impossible to culture in vitro, they are classified taxonomically according to the convention used for unculturable micro-organisms. The first coherent scheme of classification of phytoplasmas, based on the RFLP pattern of the 16S rRNA-encoding gene generated with 17 restriction endonucleases, was updated several times until the development of the iPhyClassifier. iPhyClassifier is an interactive online tool capable of determining the species, group and subgroup of 'Candidatus Phytoplasma' of unknown samples using the 16S F2nR2 sequence. Latin America, an important geographical area in relation to food production, has a high incidence of plant diseases caused by phytoplasmas. However, many phytoplasmas associated with these diseases have not been properly classified. An extensive literature review and the use of iPhyClassifier allowed us to identify two new tentative groups (16SrXXXIII-A and 16SrXXXIV-A) and the following tentative new subgroups among Latin American strains that were either previously unclassified or misclassified: six in 16SrI, six in 16SrII, one in 16SrIII, one in 16SrVII, one in 16SrIX, one in 16SrXII and two in 16SrXIII.

Laboratory-scale bioaugmentation relieves acetate accumulation and stimulates methane production in stalled anaerobic digesters.

An imbalance between acidogenic and methanogenic organisms during anaerobic digestion can result in increased accumulation of volatile fatty acids, decreased reactor pH, and inhibition of methane-producing Archaea. Most commonly the result of organic input overload or poor inoculum selection, these microbiological and biochemical changes severely hamper reactor performance, and there are a few tools available to facilitate reactor recovery. A small, stable consortium capable of catabolizing acetate and producing methane was propagated in vitro and evaluated as a potential bioaugmentation tool for stimulating methanogenesis in acidified reactors. Replicate laboratory-scale batch digesters were seeded with a combination of bioethanol stillage waste and a dairy manure inoculum previously observed to result in high volatile fatty acid accumulation and reactor failure. Experimental reactors were then amended with the acetoclastic consortium, and control reactors were amended with sterile culture media. Within 7 days, bioaugmented reactors had significantly reduced acetate accumulation and the proportion of methane in the biogas increased from 0.2 ± 0 to 74.4 ± 9.9 % while control reactors showed no significant reduction in acetate accumulation or increase in methane production. Organisms from the consortium were enumerated using specific quantitative PCR assays to evaluate their growth in the experimental reactors. While the abundance of hydrogenotrophic microorganisms remained stable during the recovery period, an acetoclastic methanogen phylogenetically similar to Methanosarcina sp. increased more than 100-fold and is hypothesized to be the primary contributor to reactor recovery. Genomic sequencing of this organism revealed genes related to the production of methane from acetate, hydrogen, and methanol.

Simultaneous profiling of seed-associated bacteria and fungi reveals antagonistic interactions between microorganisms within a shared epiphytic microbiome on Triticum and Brassica seeds.

In order to address the hypothesis that seeds from ecologically and geographically diverse plants harbor characteristic epiphytic microbiota, we characterized the bacterial and fungal microbiota associated with Triticum and Brassica seed surfaces. The total microbial complement was determined by amplification and sequencing of a fragment of chaperonin 60 (cpn60). Specific microorganisms were quantified by qPCR. Bacteria and fungi corresponding to operational taxonomic units (OTU) that were identified in the sequencing study were isolated and their interactions examined. A total of 5477 OTU were observed from seed washes. Neither total epiphytic bacterial load nor community richness/evenness was significantly different between the seed types; 578 OTU were shared among all samples at a variety of abundances. Hierarchical clustering revealed that 203 were significantly different in abundance on Triticum seeds compared with Brassica. Microorganisms isolated from seeds showed 99-100% identity between the cpn60 sequences of the isolates and the OTU sequences from this shared microbiome. Bacterial strains identified as Pantoea agglomerans had antagonistic properties toward one of the fungal isolates (Alternaria sp.), providing a possible explanation for their reciprocal abundances on both Triticum and Brassica seeds. cpn60 enabled the simultaneous profiling of bacterial and fungal microbiota and revealed a core seed-associated microbiota shared between diverse plant genera.

Composition and Dynamics of Plant- and Soil-Associated Microbial Communities in Forest and Agricultural Ecosystems.

Peter Kropotkin (1842-1921) is well known as an anarchist intellectual, an amiable mass of contradictions who loved humanity and was highly regarded in academic and intellectual circles, yet also penned "fiery peans to violence" in Le Révolté, the anarchist journal he established with Elisée Reclus in the 1870s [...].

Modeling the microbial pretreatment of camelina straw and switchgrass by Trametes versicolor and Phanerochaete chrysosporium via solid-state fermentation process: A growth kinetic sub-model in the context of biomass-based biorefineries.

Advancing microbial pretreatment of lignocellulose has the potential not only to reduce the carbon footprint and environmental impacts of the pretreatment processes from cradle-to-grave, but also increase biomass valorization, support agricultural growers, and boost the bioeconomy. Mathematical modeling of microbial pretreatment of lignocellulose provides insights into the metabolic activities of the microorganisms as responses to substrate and environment and provides baseline targets for the design, development, and optimization of solid-state-fermentation (SSF) bioreactors, including substrate concentrations, heat and mass transfer. In this study, the growth of Trametes versicolor 52J (TV52J), Trametes versicolor m4D (TVm4D), and Phanerochaete chrysosporium (PC) on camelina straw (CS) and switchgrass (SG) during an SSF process was examined. While TV52J illustrated the highest specific growth rate and maximum cell concentration, a mutant strain deficient in cellulose catabolism, TVm4D, performed best in terms of holocellulose preservation and delignification. The hybrid logistic-Monod equation along with holocellulose consumption and delignification models described well the growth kinetics. The oxygen uptake rate and carbon dioxide production rate were directly correlated to the fungal biomass concentration; however, a more sophisticated non-linear relationship might explain those correlations better than a linear model. This study provides an informative baseline for developing SSF systems to integrate fungal pretreatment into a large-scale, on-farm, wet-storage process for the utilization of agricultural residues as feedstocks for biofuel production.

Crop rotation significantly influences the composition of soil, rhizosphere, and root microbiota in canola (Brassica napus L.).

BACKGROUND: Crop rotation is an agronomic practice that is known to enhance productivity and yield, and decrease pest and disease pressure. Economic and other factors have increased the frequency of certain crops, including canola, with unknown effects on the below ground microbial communities that impact plant health and performance. This study investigated the effect of 12 years of crop rotation including canola-wheat; canola-pea-barley; and unrotated canola across three geographic sites in Western Canada with diverse soil types and environmental conditions. To provide data on mature, established crop rotation strategies, root exudate profiles, soil nutrient fluxes, and bacterial and fungal microbial community profiles were determined at the flowering stage in the final two (canola) years of the 12-year rotations. RESULTS: After 12 years of rotation, nutrient fluxes were affected in the soil in an inconsistent manner, with K, NO3, Mg, Ca, P, and Fe fluxes variably impacted by rotation depending on the year and site of sampling. As expected, rotation positively influenced yield and oil content, and decreased disease pressure from Leptosphaeria and Alternaria. In two of the three sites, root exudate profiles were significantly influenced by crop rotation. Bacterial soil, root, and rhizosphere communities were less impacted by crop rotation than the fungal communities. Fungal sequences that were associated with specific rotation strategies were identified in the bulk soil, and included known fungal pathogens in the canola-only strategy. Two closely related fungal sequences identified as Olpidium brassicae were extremely abundant at all sites in both years. One of these sequences was observed uniquely at a single site and was significantly associated with monocropped canola; moreover, its abundance correlated negatively with yield in both years. CONCLUSIONS: Long-term canola monoculture affected root exudate profiles and soil nutrient fluxes differently in the three geographic locations. Bacterial communities were less impacted by rotation compared to the fungal communities, which consistently exhibited changes in composition in all ecological niches at all sites, in both years. Fungal sequences identified as O. brassicae were highly abundant at all sites, one of which was strongly associated with canola monoculture. Soil management decisions should include consideration of the effects on the microbial ecosystems associated with the plants in order to inform best management practices.

Maternal vaginal microbiome composition does not affect development of the infant gut microbiome in early life.

Birth mode has been implicated as a major factor influencing neonatal gut microbiome development, and it has been assumed that lack of exposure to the maternal vaginal microbiome is responsible for gut dysbiosis among caesarean-delivered infants. Consequently, practices to correct dysbiotic gut microbiomes, such as vaginal seeding, have arisen while the effect of the maternal vaginal microbiome on that of the infant gut remains unknown. We conducted a longitudinal, prospective cohort study of 621 Canadian pregnant women and their newborn infants and collected pre-delivery maternal vaginal swabs and infant stool samples at 10-days and 3-months of life. Using cpn60-based amplicon sequencing, we defined vaginal and stool microbiome profiles and evaluated the effect of maternal vaginal microbiome composition and various clinical variables on the development of the infant stool microbiome. Infant stool microbiomes showed significant differences in composition by delivery mode at 10-days postpartum; however, this effect could not be explained by maternal vaginal microbiome composition and was vastly reduced by 3 months. Vaginal microbiome clusters were distributed across infant stool clusters in proportion to their frequency in the overall maternal population, indicating independence of the two communities. Intrapartum antibiotic administration was identified as a confounder of infant stool microbiome differences and was associated with lower abundances of Escherichia coli, Bacteroides vulgatus, Bifidobacterium longum and Parabacteroides distasonis. Our findings demonstrate that maternal vaginal microbiome composition at delivery does not affect infant stool microbiome composition and development, suggesting that practices to amend infant stool microbiome composition focus factors other than maternal vaginal microbes.

Combining Desirable Traits for a Good Biocontrol Strategy against Sclerotinia sclerotiorum.

The fungal pathogen Sclerotinia sclerotiorum (Helotiales: Sclerotiniaceae) causes white mold, a disease that leads to substantial losses on a wide variety of hosts throughout the world. This economically important fungus affects yield and seed quality, and its control mostly relies on the use of environmentally damaging fungicides. This review aimed to present the latest discoveries on microorganisms and the biocontrol mechanisms used against white mold. A special focus is put on the identification of biocontrol desirable traits required for efficient disease control. A better understanding of the mechanisms involved and the conditions required for their action is also essential to ensure a successful implementation of biocontrol under commercial field conditions. In this review, a brief introduction on the pathogen, its disease cycle, and its main pathogenicity factors is presented, followed by a thorough description of the microorganisms that have so far demonstrated biocontrol potential against white mold and the mechanisms they use to achieve control. Antibiosis, induced systemic resistance, mycoparasitism, and hypovirulence are discussed. Finally, based on our actual knowledge, the best control strategies against S. sclerotiorum that are likely to succeed commercially are discussed, including combining biocontrol desirable traits of particular interest.

Rapid Molecular Diagnostics in the Field and Laboratory to Detect Plant Pathogen DNA in Potential Insect Vectors.

A variety of sensitive and specific molecular diagnostic assays has been described for detecting nucleic acids in biological samples that may harbor pathogens of interest. These methods include very rapid, isothermal nucleic acid amplification methods that can be deployed outside of the laboratory environment, such as loop-mediated isothermal DNA amplification (LAMP) and recombinase-polymerase amplification (RPA). However, all molecular diagnostic assays must be preceded by nucleic acid extraction from the biological samples of interest, which provides suitable template molecules for the assays. To exploit the features of the amplification assays and be utilized outside of the lab, these methods must be rapid and avoid the need for typical laboratory chemicals and equipment. We describe a protocol for the extraction of DNA from field-collected insects that can be implemented at the point of collection and used to detect the presence of DNA sequences from potential plant pathogens that may be vectored by the insects. This protocol provides template DNA that is suitable for PCR, LAMP, and RPA. The FTA PlantSaver card-based DNA extraction product was also confirmed to amplify the mitochondrial cytochrome oxidase 1 (CO1) universal barcode that could later be sequenced to identify any insect. Lastly, we provide an example using field-collected insects, Neokolla (Graphocephala) heiroglyphica, and demonstrate the detection of the plant pathogen Xylella fastidiosa in carrier insects using PCR, RPA, and LAMP.

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.

Molecular definition of vaginal microbiota in East African commercial sex workers.

Resistance to HIV infection in a cohort of commercial sex workers living in Nairobi, Kenya, is linked to mucosal and antiinflammatory factors that may be influenced by the vaginal microbiota. Since bacterial vaginosis (BV), a polymicrobial dysbiosis characterized by low levels of protective Lactobacillus organisms, is an established risk factor for HIV infection, we investigated whether vaginal microbiology was associated with HIV-exposed seronegative (HESN) or HIV-seropositive (HIV(+)) status in this cohort. A subset of 44 individuals was selected for deep-sequencing analysis based on the chaperonin 60 (cpn60) universal target (UT), including HESN individuals (n = 16), other HIV-seronegative controls (HIV-N, n = 16), and HIV(+) individuals (n = 12). Our findings indicate exceptionally high phylogenetic resolution of the cpn60 UT using reads as short as 200 bp, with 54 species in 29 genera detected in this group. Contrary to our initial hypothesis, few differences between HESN and HIV-N women were observed. Several HIV(+) women had distinct profiles dominated by Escherichia coli. The deep-sequencing phylogenetic profile of the vaginal microbiota corresponds closely to BV(+) and BV(-) diagnoses by microscopy, elucidating BV at the molecular level. A cluster of samples with intermediate abundance of Lactobacillus and dominant Gardnerella was identified, defining a distinct BV phenotype that may represent a transitional stage between BV(+) and BV(-). Several alpha- and betaproteobacteria, including the recently described species Variovorax paradoxus, were found to correlate positively with increased Lactobacillus levels that define the BV(-) ("normal") phenotype. We conclude that cpn60 UT is ideally suited to next-generation sequencing technologies for further investigation of microbial community dynamics and mucosal immunity underlying HIV resistance in this cohort.

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.

CaptureSeq: Hybridization-Based Enrichment of cpn60 Gene Fragments Reveals the Community Structures of Synthetic and Natural Microbial Ecosystems.

BACKGROUND: The molecular profiling of complex microbial communities has become the basis for examining the relationship between the microbiome composition, structure and metabolic functions of those communities. Microbial community structure can be partially assessed with "universal" PCR targeting taxonomic or functional gene markers. Increasingly, shotgun metagenomic DNA sequencing is providing more quantitative insight into microbiomes. However, both amplicon-based and shotgun sequencing approaches have shortcomings that limit the ability to study microbiome dynamics. METHODS: We present a novel, amplicon-free, hybridization-based method (CaptureSeq) for profiling complex microbial communities using probes based on the chaperonin-60 gene. Molecular profiles of a commercially available synthetic microbial community standard were compared using CaptureSeq, whole metagenome sequencing, and 16S universal target amplification. Profiles were also generated for natural ecosystems including antibiotic-amended soils, manure storage tanks, and an agricultural reservoir. RESULTS: The CaptureSeq method generated a microbial profile that encompassed all of the bacteria and eukaryotes in the panel with greater reproducibility and more accurate representation of high G/C content microorganisms compared to 16S amplification. In the natural ecosystems, CaptureSeq provided a much greater depth of coverage and sensitivity of detection compared to shotgun sequencing without prior selection. The resulting community profiles provided quantitatively reliable information about all three domains of life (Bacteria, Archaea, and Eukarya) in the different ecosystems. The applications of CaptureSeq will facilitate accurate studies of host-microbiome interactions for environmental, crop, animal and human health. CONCLUSIONS: cpn60-based hybridization enriched for taxonomically informative DNA sequences from complex mixtures. In synthetic and natural microbial ecosystems, CaptureSeq provided sequences from prokaryotes and eukaryotes simultaneously, with quantitatively reliable read abundances. CaptureSeq provides an alternative to PCR amplification of taxonomic markers with deep community coverage while minimizing amplification biases.