Integrated approaches for detection of plant pathogenic bacteria and diagnosis of bacterial diseases

Use of the 23S rRNA gene as a target template in the universal loop-mediated isothermal amplification (LAMP) of genomic DNA from phytoplasmas

Plant-pathogenic bacteria cause numerous diseases in host plants and can result in serious damage. Timely and accurate diagnostic techniques are, therefore, crucial. While advances in molecular techniques have led to diagnostic systems able to distinguish known plant pathogens at the species or strain level, systems covering larger categories are mostly lacking. In this study, a specific and universal LAMP-based diagnostic system was developed for phytoplasmas, a large group of insect-borne plant-pathogenic bacteria that cause significant agricultural losses worldwide. Targeting the 23S rRNA gene of phytoplasma, the newly designed primer set CaPU23S-4 detected 31 'Candidatus Phytoplasma' tested within 30 min. This primer set also showed high specificity, without false-positive results for other bacteria (including close relatives of phytoplasmas) or healthy plants. The detection sensitivity was ~10,000 times higher than that of PCR methods for phytoplasma detection. A simple, rapid method of DNA extraction, by boiling phytoplasma-infected tissues, was developed as well. When used together with the universal LAMP assay, it enabled the prompt and accurate detection of phytoplasmas from plants and insects. The results demonstrate the potential of the 23S rRNA gene as a versatile target for the LAMP-based universal detection of bacteria at the genus level and provide a novel avenue for exploring this gene as molecular marker for phytoplasma presence detection.IMPORTANCEPhytoplasmas are associated with economically important diseases in crops worldwide, including lethal yellowing of coconut palm, "flavescence dorée" and "bois noir" of grapevine, X-disease in stone fruits, and white leaf and grassy shoot in sugarcane. Numerous LAMP-based diagnostic assays, mostly targeting the 16S rRNA gene, have been reported for phytoplasmas. However, these assays can only detect a limited number of 'Candidatus Phytoplasma' species, whereas the genus includes at least 50 of these species. In this study, a universal, specific, and rapid diagnostic system was developed that can detect all provisionally classified phytoplasmas within 1 h by combining the LAMP technique targeting the 23S rRNA gene with a simple method for DNA extraction. This diagnostic system will facilitate the on-site detection of phytoplasmas and may aid in the discovery of new phytoplasma-associated diseases and putative insect vectors, irrespective of the availability of infrastructure and experimental resources.

An Inhibitor-Monitorable Single-Tube Duplex Quantitative Real-Time PCR Assay for the Detection of 'Candidatus Liberibacter asiaticus'

Huanglongbing (HLB) is a citrus infectious disease caused by 'Candidatus Liberibacter' spp. Recently, it has begun to spread rapidly worldwide, causing significant losses to the citrus industry. Early diagnosis of HLB relies on quantitative real-time PCR assays. However, the PCR inhibitors found in the nucleic acid extracted from plant materials pose challenges for PCR assays because they may result in false-negative results. Internal standard (IS) can be introduced to establish a single-tube duplex PCR for monitoring the influence of the PCR inhibitor, but it also brings the risk of false-negative results because the amplification of IS may compete with the target. To solve this problem, we proposed a mutation-enhanced single-tube duplex PCR (mSTD-PCR) containing IS with mutant-type primers. By introducing the 3'-terminal mutation in the primer of IS to weaken its amplification reaction and its inhibition of 'Candidatus Liberibacter asiaticus' (CLas) detection, the sensitivity and quantitative accuracy of CLas detection will not be affected by IS. In evaluating the sensitivity of CLas detection using simulation samples, the mSTD-PCR showed consistent sensitivity at 25 copies per test compared with the single-plex CLas assay. The detection result of 30 leaves and 30 root samples showed that the mSTD-PCR could recognize false-negative results caused by the PCR inhibitors and reduce workload by 48% compared with the single-plex CLas assay. Generally, the proposed mSTD-PCR provides a reliable, efficient, inhibitor-monitorable, quantitative screening method for accurately controlling HLB and a universal method for establishing a PCR assay for various pathogens.

Rapid and accurate identification of bacteria utilizing laser-induced breakdown spectroscopy

Timely and accurate identification of harmful bacterial species in the environment is paramount for preventing the spread of diseases and ensuring food safety. In this study, laser-induced breakdown spectroscopy technology was utilized, combined with four machine learning methods - KNN, PCA-KNN, RF, and SVM, to conduct classification and identification research on 7 different types of bacteria, adhering to various substrate materials. The experimental results showed that despite the nearly identical elemental composition of these bacteria, differences in the intensity of elemental spectral lines provide crucial information for identification of bacteria. Under conditions of high-purity aluminum substrate, the identification rates of the four modeling methods reached 74.91%, 84.05%, 85.36%, and 96.07%, respectively. In contrast, under graphite substrate conditions, the corresponding identification rates reached 96.87%, 98.11%, 98.93%, and 100%. Graphite is found to be more suitable as a substrate material for bacterial classification, attributed to the fact that more characteristic spectral lines are excited in bacteria under graphite substrate conditions. Additionally, the emission spectral lines of graphite itself are relatively scarce, resulting in less interference with other elemental spectral lines of bacteria. Meanwhile, SVM exhibited the highest precision rate and recall rate, reaching up to 1, making it the most effective classification method in this experiment. This study provides a valuable approach for the rapid and accurate identification of bacterial species based on LIBS, as well as substrate selection, enhancing efficient microbial identification capabilities in fields related to social security and military applications.

Novel plant disease detection techniques-a brief review

Plant pathogens cause severe losses to agricultural yield worldwide. Tracking plant health and early disease detection is important to reduce the disease spread and thus economic loss. Though visual scouting has been practiced from former times, detection of asymptomatic disease conditions is difficult. So, DNA-based and serological methods gained importance in plant disease detection. The progress in advanced technologies challenges the development of rapid, non-invasive, and on-field detection techniques such as spectroscopy. This review highlights various direct and indirect ways of detecting plant diseases like Enzyme-linked immunosorbent assay, Lateral flow assays, Polymerase chain reaction, spectroscopic techniques and biosensors. Although these techniques are sensitive and pathogen-specific, they are more laborious and time-intensive. As a consequence, a lot of interest is gained in in-field adaptable point-of-care devices with artificial intelligence-assisted pathogen detection at an early stage. More recently computer-aided techniques like neural networks are gaining significance in plant disease detection by image processing. In addition, a concise report on the latest progress achieved in plant disease detection techniques is provided.

Root microbiota alters response to root rot in Rhododendron delavayi Franch

Root microbiota have a significant effect on plant health. However, the role of root microbiota in the resistance of Rhododendron against root rot is not known. In this study, we employed amplicon 16S and ITS sequencing to investigate the bacterial and fungal communities associated with four distinct niches (bulk soil, rhizosphere, rhizoplane, and endosphere) of both healthy and diseased Rhododendron plants in the Baili Rhododendron nature reserve in China. The amplicon data analysis identified 182 bacterial genera and 141 fungal genera that were impacted by root rot across all niches. Specifically, the rhizoplane appeared to exert a selective gating effect, resulting in a reduction in the complexity of bacterial communities, but not fungal communities, in wild Rhododendron delavayi Franch roots. Nevertheless, the stress induced by root rot led to alterations in the root microbiota and compromised the gating function of the rhizoplane, thereby significantly increasing the complexity of the bacterial community within the plant root. In the root tissue following root rot outbreak, the relative abundance of the pathogenic species Pezicula brunnea and Diaporthe helianthi was enriched by as much as 6.13% and 1.71%, respectively. These findings provide novel insights into the contribution of enrichment of root-associated microbiota to wild plant hosts under the disease stress of root rot. The root rot-causing pathogenic fungi may interact with beneficial bacteria and induce plants to send out "cry for help" signals, which may encourage the specific assembly of microbiota. In the Rhododendron delavayi Franch root microbiota, we found 23 potentially beneficial microbes. Notably, certain beneficial bacteria, such as Sporolactobacillus and Stenotrophomonas, were found to accumulate in the rhizoplane and endosphere under root rot disease stress. Overall, our results lend support to our hypothesis that Rhododendron recruits protective microbes as a strategy to suppress root rot outbreaks. Future endeavors in isolating beneficial microbes capable of mitigating root rot have the potential to enhance plant resilience against root diseases.

The type-III effectors-based multiplex PCR for detection of Xanthomonas campestris pv. campestris causing black rot disease in crucifer crops

The black rot disease in crucifer crops is caused by Xanthomonas campestris pv. campestris (Xcc) which drastically reduces the productivity of crops. Three Xcc races, such as races 1, 4, and 6, have been identified from India that possess nine avr genes, or type-III effectors (T3Es). Here, we used three T3Es-avrXccC, avrBs1, and avrGf1 to identify Xcc from bacterial DNA, bacterial suspensions, Xcc-infected seeds, and the sap of the infected leaves using multiplex PCR. The T3Es were amplified using gene-specific primers with gDNA of Xcc. Then, the multiplex PCR was optimized and amplified T3Es using the sap of black rot-infected cauliflower leaves. Further, this method amplified T3Es from artificially infected seeds (1-100%) of cauliflower and from Xcc colonies (0.1-100%) grown on nutrient agar medium. The primer specificity of T3E genes elucidates that these are specifically detected in all Indian Xcc strains and races, while no bands were observed with other unrelated bacteria, such as X. euvesicatoria, X. oryzae pv. oryzae, Pseudomonas fluorescens, Ralstonia solanacearum, Bacillus subtilis, and B. amyloliquefaciens. Further, this PCR possesses high sensitivity and amplifies T3E genes using up to 0.01 ng Xcc DNA. The high specificity and sensitivity of T3Es-based multiplex PCR make it a potential method and can be used to amplify Xcc from various templates, such as purified DNA, Xcc-infected seeds and leaves, crude extracts, etc., without the need to extract plant or bacterial DNA.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13205-023-03691-z.

Strain-Level Discrimination of Bacteria by Liquid Chromatography and Paper Spray Ion Mobility Mass Spectrometry

Determining bacterial identity at the strain level is critical for public health to enable proper medical treatments and reduce antibiotic resistance. Herein, we used liquid chromatography, ion mobility, and tandem MS (LC-IM-MS/MS) to distinguish Escherichia coli (E. coli) strains. Numerical multivariate statistics (principal component analysis, followed by linear discriminant analysis) showed the capability of this method to perform strain-level discrimination with prediction rates of 96.1% and 100% utilizing the negative and positive ion information, respectively. The tandem MS and LC separation proved effective in discriminating diagnostic lipid isomers in the negative mode, while IM separation was more effective in resolving lipid conformational biomarkers in the positive ion mode. Because of the clinical importance of early detection for rapid medical intervention, a faster technique, paper spray (PS)-IM-MS/MS, was used to discriminate the E. coli strains. The achieved prediction rates of the analysis of E. coli strains by PS-IM-MS/MS were 62.5% and 73.5% in the negative and positive ion modes, respectively. The strategy of numerical data fusion of negative and positive ion data increased the classification rates of PS-IM-MS/MS to 80.5%. Lipid isomers and conformers were detected, which served as strain-indicating biomarkers. The two complementary multidimensional techniques revealed biochemical differences between the E. coli strains confirming the results obtained from comparative genomic analysis. Moreover, the results suggest that PS-IM-MS/MS is a rapid, highly selective, and sensitive method for discriminating bacterial strains in environmental and food samples.

Current and emerging trends in techniques for plant pathogen detection

Plant pathogenic microorganisms cause substantial yield losses in several economically important crops, resulting in economic and social adversity. The spread of such plant pathogens and the emergence of new diseases is facilitated by human practices such as monoculture farming and global trade. Therefore, the early detection and identification of pathogens is of utmost importance to reduce the associated agricultural losses. In this review, techniques that are currently available to detect plant pathogens are discussed, including culture-based, PCR-based, sequencing-based, and immunology-based techniques. Their working principles are explained, followed by an overview of the main advantages and disadvantages, and examples of their use in plant pathogen detection. In addition to the more conventional and commonly used techniques, we also point to some recent evolutions in the field of plant pathogen detection. The potential use of point-of-care devices, including biosensors, have gained in popularity. These devices can provide fast analysis, are easy to use, and most importantly can be used for on-site diagnosis, allowing the farmers to take rapid disease management decisions.

DIANA: A deep learning-based paprika plant disease and pest phenotyping system with disease severity analysis

The emergence of deep neural networks has allowed the development of fully automated and efficient diagnostic systems for plant disease and pest phenotyping. Although previous approaches have proven to be promising, they are limited, especially in real-life scenarios, to properly diagnose and characterize the problem. In this work, we propose a framework which besides recognizing and localizing various plant abnormalities also informs the user about the severity of the diseases infecting the plant. By taking a single image as input, our algorithm is able to generate detailed descriptive phrases (user-defined) that display the location, severity stage, and visual attributes of all the abnormalities that are present in the image. Our framework is composed of three main components. One of them is a detector that accurately and efficiently recognizes and localizes the abnormalities in plants by extracting region-based anomaly features using a deep neural network-based feature extractor. The second one is an encoder-decoder network that performs pixel-level analysis to generate abnormality-specific severity levels. Lastly is an integration unit which aggregates the information of these units and assigns unique IDs to all the detected anomaly instances, thus generating descriptive sentences describing the location, severity, and class of anomalies infecting plants. We discuss two possible ways of utilizing the abovementioned units in a single framework. We evaluate and analyze the efficacy of both approaches on newly constructed diverse paprika disease and pest recognition datasets, comprising six anomaly categories along with 11 different severity levels. Our algorithm achieves mean average precision of 91.7% for the abnormality detection task and a mean panoptic quality score of 70.78% for severity level prediction. Our algorithm provides a practical and cost-efficient solution to farmers that facilitates proper handling of crops.

Point-of-Care DNA Amplification for Disease Diagnosis and Management

Early detection of pests and pathogens is of paramount importance in reducing agricultural losses. One approach to early detection is point-of-care (POC) diagnostics, which can provide early warning and therefore allow fast deployment of preventive measures to slow down the establishment of crop diseases. Among the available diagnostic technologies, nucleic acid amplification-based diagnostics provide the highest sensitivity and specificity, and those technologies that forego the requirement for thermocycling show the most potential for use at POC. In this review, I discuss the progress, advantages, and disadvantages of the established and most promising POC amplification technologies. The success and usefulness of POC amplification are ultimately dependent on the availability of POC-friendly nucleic acid extraction methods and amplification readouts, which are also briefly discussed in the review.

Real-time monitoring of Ralstonia solanacearum infection progress in tomato and Arabidopsis using bioluminescence imaging technology

BACKGROUND

Ralstonia solanacearum, one of the most devastating bacterial plant pathogens, is the causal agent of bacterial wilt. Recently, several studies on resistance to bacterial wilt have been conducted using the Arabidopsis-R. solanacearum system. However, the progress of R. solanacearum infection in Arabidopsis is still unclear.

RESULTS

We generated a bioluminescent R. solanacearum by expressing plasmid-based luxCDABE. Expression of luxCDABE did not alter the bacterial growth and pathogenicity. The light intensity of bioluminescent R. solanacearum was linearly related to bacterial concentrations from 104 to 108 CFU·mL-1. After root inoculation with bioluminescent R. solanacearum strain, light signals in tomato and Arabidopsis were found to be transported from roots to stems via the vasculature. Quantification of light intensity from the bioluminescent strain accurately reported the difference in disease resistance between Arabidopsis wild type and resistant mutants.

CONCLUSIONS

Bioluminescent R. solanacearum strain spatially and quantitatively measured bacterial growth in tomato and Arabidopsis, and offered a tool for the high-throughput study of R. solanacearum-Arabidopsis interaction in the future.

Xanthomonas arboricola pv. juglandis and pv. corylina: Brothers or distant relatives? Genetic clues, epidemiology, and insights for disease management

BACKGROUND

The species Xanthomonas arboricola comprises up to nine pathovars, two of which affect nut crops: pv. juglandis, the causal agent of walnut bacterial blight, brown apical necrosis, and the vertical oozing canker of Persian (English) walnut; and pv. corylina, the causal agent of the bacterial blight of hazelnut. Both pathovars share a complex population structure, represented by different clusters and several clades. Here we describe our current understanding of symptomatology, population dynamics, epidemiology, and disease control.

TAXONOMIC STATUS

Bacteria; Phylum Proteobacteria; Class Gammaproteobacteria; Order Lysobacterales (earlier synonym of Xanthomonadales); Family Lysobacteraceae (earlier synonym of Xanthomonadaceae); Genus Xanthomonas; Species X. arboricola; Pathovars: pv. juglandis and pv. corylina.

HOST RANGE AND SYMPTOMS

The host range of each pathovar is not limited to a single species, but each infects mainly one plant species: Juglans regia (X. arboricola pv. juglandis) and Corylus avellana (X. arboricola. pv. corylina). Walnut bacterial blight is characterized by lesions on leaves and fruits, and cankers on twigs, branches, and trunks; brown apical necrosis symptoms consist of apical necrosis originating at the stigmatic end of the fruit. A peculiar symptom, the vertical oozing canker developing along the trunk, is elicited by a particular genetic lineage of the bacterium. Symptoms of hazelnut bacterial blight are visible on leaves and fruits as necrotic lesions, and on woody parts as cankers. A remarkable difference is that affected walnuts drop abundantly, whereas hazelnuts with symptoms do not.

DISTRIBUTION

Bacterial blight of walnut has a worldwide distribution, wherever Persian (English) walnut is cultivated; the bacterial blight of hazelnut has a more limited distribution, although disease outbreaks are currently more frequently reported. X. arboricola pv. juglandis is regulated almost nowhere, whereas X. arboricola pv. corylina is regulated in most European and Mediterranean Plant Protection Organization (EPPO) countries.

EPIDEMIOLOGY AND CONTROL

For both pathogens infected nursery material is the main pathway for their introduction and spread into newly cultivated areas; additionally, infected nursery material is the source of primary inoculum. X. arboricola pv. juglandis is also disseminated through pollen. Disease control is achieved through the phytosanitary certification of nursery material (hazelnut), although approved certification schemes are not currently available. Once the disease is present in walnut/hazelnut groves, copper compounds are widely used, mostly in association with dithiocarbamates; where allowed, antibiotics (preferably kasugamycin) are sprayed. The emergence of strains highly resistant to copper currently represents the major threat for effective management of the bacterial blight of walnut. USEFUL WEBSITES: https://gd.eppo.int/taxon/XANTJU, https://gd.eppo.int/taxon/XANTCY, https://www.euroxanth.eu, http://www.xanthomonas.org.

Advances in Plant Disease Detection and Monitoring: From Traditional Assays to In-Field Diagnostics

Human activities significantly contribute to worldwide spread of phytopathological adversities. Pathogen-related food losses are today responsible for a reduction in quantity and quality of yield and decrease value and financial returns. As a result, “early detection” in combination with “fast, accurate, and cheap” diagnostics have also become the new mantra in plant pathology, especially for emerging diseases or challenging pathogens that spread thanks to asymptomatic individuals with subtle initial symptoms but are then difficult to face. Furthermore, in a globalized market sensitive to epidemics, innovative tools suitable for field-use represent the new frontier with respect to diagnostic laboratories, ensuring that the instruments and techniques used are suitable for the operational contexts. In this framework, portable systems and interconnection with Internet of Things (IoT) play a pivotal role. Here we review innovative diagnostic methods based on nanotechnologies and new perspectives concerning information and communication technology (ICT) in agriculture, resulting in an improvement in agricultural and rural development and in the ability to revolutionize the concept of “preventive actions”, making the difference in fighting against phytopathogens, all over the world.

Inoculum Dynamics and Infection of Citrus Fruit by Phyllosticta citricarpa

Citrus black spot, caused by Phyllosticta citricarpa, is characterized by fruit blemishes and premature fruit drop, resulting in significant economic losses in summer rainfall areas. The pathogen forms both conidia and ascospores during its life cycle. However, the occurrence of these spores and their contributions to infection of fruit in field conditions are not well understood. Our research using direct leaf litter monitoring and volumetric spore trapping in Queensland orchards revealed that pseudothecia and ascospores in leaf litter as well as trapped ascospores had low abundance, while pycnidia and conidia were highly abundant. Both P. citricarpa and endophytic Phyllosticta spp. were identified, with P. citricarpa being dominant. In replicated field trials, we determined that infection of Imperial mandarin fruit by P. citricarpa occurred from fruit set until week 20 of fruit development, with the key infection events taking place between weeks 4 and 16 in Queensland subtropical conditions. These results demonstrate that protecting fruit during weeks 4 to 16 significantly reduced P. citricarpa infection. We found no significant correlation between the disease incidence in fruit and P. citricarpa conidial abundance in leaf litter or ascospore abundance measured by volumetric spore trapping. Therefore, it is suggested that inoculum sources in the tree canopy other than those detected by spore trapping and direct leaf litter monitoring may play a major role in the epidemiology of citrus black spot. Improved knowledge regarding epidemiology of P. citricarpa and an understanding of propagules causing infection may aid in development of more effective disease management strategies.

Pectobacterium atrosepticum Biosensor for Monitoring Blackleg and Soft Rot Disease of Potato

Pectobacterium atrosepticum (Pba) is a quarantine and threatening phytopathogen known as the causal agent of blackleg and soft rot disease of potatoes in many areas. Its early detection is then important to have healthy potato tubers and reduce economic losses. Today, conventional methods such as enzyme-linked immunosorbent-assay (ELISA) and polymerase chain reaction (PCR) are typically used for Pba detection, but they are expensive and time-consuming. Here we report on the optimization of an alternative approach based on an electrochemical impedance immunosensor combining a microfluidic module and a microelectrodes array, and having advantages in terms of low cost, ease of use and portability. For validation and for assessing its performance, the lab-on-chip platform has been compared with two standard methods (ELISA and PCR).

Development of PCR-Based Detection System for Soft Rot Pectobacteriaceae Pathogens Using Molecular Signatures

Pectobacterium and Dickeya species, usually referred to as soft rot Enterobacteriaceae, are phytopathogenic genera of bacteria that cause soft rot and blackleg diseases and are responsible for significant yield losses in many crops across the globe. Diagnosis of soft rot disease is difficult through visual disease symptoms. Pathogen detection and identification methods based on cultural and morphological identification are time-consuming and not always reliable. A polymerase chain reaction (PCR)-based detection method with the species-specific primers is fast and reliable for detecting soft rot pathogens. We have developed a specific and sensitive detection system for some species of soft rot Pectobacteriaceae pathogens in the Pectobacterium and Dickeya genera based on the use of species-specific primers to amplify unique genomic segments. The specificities of primers were verified by PCR analysis of genomic DNA from 14 strains of Pectobacterium, 8 strains of Dickeya, and 6 strains of non-soft rot bacteria. This PCR assay provides a quick, simple, powerful, and reliable method for detection of soft rot bacteria.

Resistance and virulence determinants of faecal Salmonella spp. isolated from slaughter animals in Benin

OBJECTIVE

Salmonella spp. are one of the leading foodborne pathogens worldwide naturally found in the intestines of many animals. People that are in direct contact with the infected animals or their cages may become ill. The aim of this study was to determine the prevalence, antibiogram and virulence genes associated with Salmonella serovars from fecal samples of animals intended for consumption in Southern Benin.

RESULTS

Out of a total of 406 samples, 2.46% were positive. The isolates identified were multidrug-resistant Salmonella spp. to penicillins, first generation cephalosporins and some aminoglycosides. All Salmonella isolates produced invA gene of 284 bp, fimA of 85 bp and stn of 260 bp. The spvC gene (571 bp) was present in 10% of the isolates whereas the spvR gene (310 bp) was found in 20% of the isolates. The control strain possessed all the tested genes. The invA gene implies that strains are able to invade epithelial cells. The fimA and stn genes present in all isolates show that they are capable of causing gastrointestinal illness in humans. The presence of spvC and spvR genes suggests the possibility of these strains to produce toxins.

In Situ Plant Virus Nucleic Acid Isothermal Amplification Detection on Gold Nanoparticle-Modified Electrodes

Solid-phase isothermal recombinase polymerase amplification (RPA) offers many benefits over the standard RPA in homogeneous phase in terms of sensitivity, portability, and versatility. However, RPA devices reported to date are limited by the need for heating sources to reach sensitive detection. With the aim of overcoming such limitation, we propose here a label-free highly integrated in situ RPA amplification/detection approach at room temperature that takes advantage of the high sensitivity offered by gold nanoparticle (AuNP)-modified sensing substrates and electrochemical impedance spectroscopic (EIS) detection. Plant disease ( Citrus tristeza virus (CTV)) diagnostics was selected as a relevant target for demonstration of the proof-of-concept. RPA assay for amplification of the P20 gene (387-bp) characteristic of CTV was first designed/optimized and tested by standard gel electrophoresis analysis. The optimized RPA conditions were then transferred to the AuNP-modified electrode surface, previously modified with a thiolated forward primer. The in situ-amplified CTV target was investigated by EIS in a Fe(CN₆)^4-/Fe(CN₆)^3- red-ox system, being able to quantitatively detect 1000 fg μL^-1 of nucleic acid. High selectivity against nonspecific gene sequences characteristic of potential interfering species such as Citrus psorosis virus (CPsV) and Citrus caxicia viroid (CCaV) was demonstrated. Good reproducibility (RSD of 8%) and long-term stability (up to 3 weeks) of the system were also obtained. Overall, with regard to sensitivity, cost, and portability, our approach exhibits better performance than RPA in homogeneous phase, also without the need of heating sources required in other solid-phase approaches.

Importance evaluation of spectral lines in Laser-induced breakdown spectroscopy for classification of pathogenic bacteria

The correct classification of pathogenic bacteria is significant for clinical diagnosis and treatment. Compared with the use of whole spectral data, using feature lines as the inputs of the classification model can improve the correct classification rate (CCR) and reduce the analyzing time. In order to select feature lines, we need to investigate the contribution to the CCR of each spectral line. In this paper, two algorithms, important weights based on principal component analysis (IW-PCA) and random forests (RF), were proposed to evaluate the importance of spectra lines. The laser-induced plasma spectra (LIBS) of six common clinical pathogenic bacteria species were measured and a support vector machine (SVM) classifier was used to classify the LIBS of bacteria species. In the proposed IW-PCA algorithm, the product of the loading of each line and the variance of the corresponding principal component were calculated. The maximum product of each line calculated from the first three PCs was used to represent the line's importance weight. In the RF algorithm, the Gini index reduction value of each line was considered as the line's importance weight. The experimental results demonstrated that the lines with high importance were more suitable for classification and can be chosen as feature lines. The optimal number of feature lines used in the SVM classifier can be determined by comparing the CCRs with a different number of feature lines. Importance weights evaluated by RF are more suitable for extracting feature lines using LIBS combined with an SVM classification mechanism than those evaluated by IW-PCA. Furthermore, the two methods mutually verified the importance of selected lines and the lines evaluated important by both IW-PCA and RF contributed more to the CCR.

Where are we going with genomics in plant pathogenic bacteria?

Genome sequencing is commonly used in research laboratories right now thanks to the rise of high-throughput sequencing with higher speed and output-to-cost ratios. Here, we summarized the application of genomics in different aspects of plant bacterial pathosystems. Genomics has been used in studying the mechanisms of plant-bacteria interactions, and host specificity. It also helps with taxonomy, study of non-cultured bacteria, identification of causal agent, single cell sequencing, population genetics, and meta-transcriptomic. Overall, genomics has significantly improved our understanding of plant-microbe interaction.

Bacterial Endophytes in Plant Tissue Culture: Mode of Action, Detection, and Control

Endophytic bacteria have been increasingly in the focus of research projects during the last decade. This has changed the view on bacteria in plant tissue culture and led to the differentiation between artificially introduced contaminations and naturally occurring endophytes with neutral, negative, or positive impact on the plant propagation process. This review chapter gives an overview on recent findings about the impact that bacteria have on the plant physiology in general and during micropropagation. Additionally, methods for the detection and identification of bacteria in plant tissue are described and, finally, suggestions of how to deal with bacterial endophytes in in vitro culture are given.

Advanced DNA-Based Point-of-Care Diagnostic Methods for Plant Diseases Detection

Diagnostic technologies for the detection of plant pathogens with point-of-care capability and high multiplexing ability are an essential tool in the fight to reduce the large agricultural production losses caused by plant diseases. The main desirable characteristics for such diagnostic assays are high specificity, sensitivity, reproducibility, quickness, cost efficiency and high-throughput multiplex detection capability. This article describes and discusses various DNA-based point-of care diagnostic methods for applications in plant disease detection. Polymerase chain reaction (PCR) is the most common DNA amplification technology used for detecting various plant and animal pathogens. However, subsequent to PCR based assays, several types of nucleic acid amplification technologies have been developed to achieve higher sensitivity, rapid detection as well as suitable for field applications such as loop-mediated isothermal amplification, helicase-dependent amplification, rolling circle amplification, recombinase polymerase amplification, and molecular inversion probe. The principle behind these technologies has been thoroughly discussed in several review papers; herein we emphasize the application of these technologies to detect plant pathogens by outlining the advantages and disadvantages of each technology in detail.

A Robust Deep-Learning-Based Detector for Real-Time Tomato Plant Diseases and Pests Recognition

Plant Diseases and Pests are a major challenge in the agriculture sector. An accurate and a faster detection of diseases and pests in plants could help to develop an early treatment technique while substantially reducing economic losses. Recent developments in Deep Neural Networks have allowed researchers to drastically improve the accuracy of object detection and recognition systems. In this paper, we present a deep-learning-based approach to detect diseases and pests in tomato plants using images captured in-place by camera devices with various resolutions. Our goal is to find the more suitable deep-learning architecture for our task. Therefore, we consider three main families of detectors: Faster Region-based Convolutional Neural Network (Faster R-CNN), Region-based Fully Convolutional Network (R-FCN), and Single Shot Multibox Detector (SSD), which for the purpose of this work are called "deep learning meta-architectures". We combine each of these meta-architectures with "deep feature extractors" such as VGG net and Residual Network (ResNet). We demonstrate the performance of deep meta-architectures and feature extractors, and additionally propose a method for local and global class annotation and data augmentation to increase the accuracy and reduce the number of false positives during training. We train and test our systems end-to-end on our large Tomato Diseases and Pests Dataset, which contains challenging images with diseases and pests, including several inter- and extra-class variations, such as infection status and location in the plant. Experimental results show that our proposed system can effectively recognize nine different types of diseases and pests, with the ability to deal with complex scenarios from a plant's surrounding area.

Simultaneous Detection of Brown Rot- and Soft Rot-Causing Bacterial Pathogens from Potato Tubers Through Multiplex PCR

Ralstonia solanacearum (Smith) Yabuuchi et al. and Erwinia carotovora subsp. carotovora (Jones) Bergey et al. (Pectobacterium carotovorum subsp. carotovorum) are the two major bacterial pathogens of potato causing brown rot (wilt) and soft rot diseases, respectively, in the field and during storage. Reliable and early detection of these pathogens are keys to avoid occurrence of these diseases in potato crops and reduce yield loss. In the present study, multiplex polymerase chain reaction (PCR) protocol was developed for simultaneous detection of R. solanacearum and E. carotovora subsp. carotovora from potato tubers. A set of oligos targeting the pectatelyase (pel) gene of E. carotovora subsp. carotovora and the universal primers based on 16S r RNA gene of R. solanacearum were used. The standardized multiplex PCR protocol could detect R. solanacearum and E. carotovora subsp. carotovora up to 0.01 and 1.0 ng of genomic DNA, respectively. The protocol was further validated on 96 stored potato tuber samples, collected from different potato-growing states of India, viz. Uttarakhand, Odisha, Meghalaya and Delhi. 53.1 % tuber samples were positive for R. solanacearum, and 15.1 % of samples were positive for E. carotovora subsp. carotovora, and both the pathogens were positive in 26.0 % samples when BIO-PCR was used. This method offers sensitive, specific, reliable and fast detection of two major bacterial pathogens from potato tubers simultaneously, particularly pathogen-free seed certification in large scale.

Gall-ID: tools for genotyping gall-causing phytopathogenic bacteria

Understanding the population structure and genetic diversity of plant pathogens, as well as the effect of agricultural practices on pathogen evolution, is important for disease management. Developments in molecular methods have contributed to increase the resolution for accurate pathogen identification, but those based on analysis of DNA sequences can be less straightforward to use. To address this, we developed Gall-ID, a web-based platform that uses DNA sequence information from 16S rDNA, multilocus sequence analysis and whole genome sequences to group disease-associated bacteria to their taxonomic units. Gall-ID was developed with a particular focus on gall-forming bacteria belonging to Agrobacterium, Pseudomonas savastanoi, Pantoea agglomerans, and Rhodococcus. Members of these groups of bacteria cause growth deformation of plants, and some are capable of infecting many species of field, orchard, and nursery crops. Gall-ID also enables the use of high-throughput sequencing reads to search for evidence for homologs of characterized virulence genes, and provides downloadable software pipelines for automating multilocus sequence analysis, analyzing genome sequences for average nucleotide identity, and constructing core genome phylogenies. Lastly, additional databases were included in Gall-ID to help determine the identity of other plant pathogenic bacteria that may be in microbial communities associated with galls or causative agents in other diseased tissues of plants. The URL for Gall-ID is http://gall-id.cgrb.oregonstate.edu/.

Characterization of Xanthomonas hortorum pv. pelargonii Isolated from Geranium in Serbia

Geranium leaves and stems with symptoms of bacterial blight were collected from commercial greenhouses during the last decade in Serbia. In total, 17 isolates with colony morphology typical for the genus Xanthomonas were characterized with pathogenicity, biochemical, serological, and molecular assays. All 17 isolates reacted positive in a polymerase chain reaction (PCR) using XcpM1 and XcpM2 primers specific for Xanthomonas hortorum pv. pelargonii. In pathogenicity tests on Pelargonium zonale (leaf and stem inoculation), all isolates caused typical symptoms on leaves starting 2 days after inoculation as sunken, water-soaked, irregular lesions, and 6 to 8 days after inoculation on stems as necrotic lesions also showing yellow exudate. Symptoms resulted in general wilting of inoculated plants 20 days after inoculation. Selected phenotypic tests indicated that all isolates showed the same results as described for the bacterium X. hortorum pv. pelargonii. Repetitive sequence-based PCR typing using BOX and ERIC revealed that all isolates showed two fingerprinting profiles but (GTG)₅ and REP did not reveal differences. Multilocus sequence typing of partial sequences of rpoD, dnaK, fyuA, and gyrB genes of tested isolates and sequences obtained from GenBank of Xanthomonas pathovar pathotype strains did not reveal genetic variability among the isolates, showing the same gene sequence pattern.

Biochemical and molecular tools reveal two diverse Xanthomonas groups in bananas

Xanthomonas campestris pv. musacearum (Xcm) causing the banana Xanthomonas wilt (BXW) disease has been the main xanthomonad associated with bananas in East and Central Africa based on phenotypic and biochemical characteristics. However, biochemical methods cannot effectively distinguish between pathogenic and non-pathogenic xanthomonads. In this study, gram-negative and yellow-pigmented mucoid bacteria were isolated from BXW symptomatic and symptomless bananas collected from different parts of Uganda. Biolog, Xcm-specific (GspDm), Xanthomonas vasicola species-specific (NZ085) and Xanthomonas genus-specific (X1623) primers in PCR, and sequencing of ITS region were used to identify and characterize the isolates. Biolog tests revealed several isolates as xanthomonads. The GspDm and NZ085 primers accurately identified three isolates from diseased bananas as Xcm and these were pathogenic when re-inoculated into bananas. DNA from more isolates than those amplified by GspDm and NZ085 primers were amplified by the X1623 primers implying they are xanthomonads, these were however non-pathogenic on bananas. In the 16-23 ITS sequence based phylogeny, the pathogenic bacteria clustered together with the Xcm reference strain, while the non-pathogenic xanthomonads isolated from both BXW symptomatic and symptomless bananas clustered with group I xanthomonads. The findings reveal dynamic Xanthomonas populations in bananas, which can easily be misrepresented by only using phenotyping and biochemical tests. A combination of tools provides the most accurate identity and characterization of these plant associated bacteria. The interactions between the pathogenic and non-pathogenic xanthomonads in bananas may pave way to understanding effect of microbial interactions on BXW disease development and offer clues to biocontrol of Xcm.

Seasonal Variation in Populations of 'Candidatus Liberibacter asiaticus' in Citrus Trees in Paraná State, Brazil

Huanglongbing (HLB) is considered one of the most destructive diseases of citrus because the plants rapidly become unproductive, enter a decline, and eventually die. HLB is caused by the phloem-limited bacterium 'Candidatus Liberibacter' spp. The objective of this study was to evaluate seasonal variation of the in planta population of 'Ca. Liberibacter asiaticus' in the foliage of citrus trees in Brazil using real-time polymerase chain reaction (qPCR). Eleven plants (naturally infected, then screened) in the field with very mild and localized symptoms of HLB were confirmed to be 'Ca. L. asiaticus' infected by conventional PCR, and the canopies were divided into four quadrants. The bacterial population in the trees was tested on a monthly basis for up to 20 months by quantifying 'Ca. L. asiaticus' DNA using qPCR 'Ca. L. asiaticus'-specific primers (As84F/As180R). The average cycle threshold (C_t) values, which relate to 'Ca. L. asiaticus' titer, were analyzed using a mixed model. Significant differences were observed in C_t values between seasons (F = 8.77, P = 0.0004), and abrupt changes were observed in C_t values in different quadrants of the trees. Autumn had the lowest C_t values, indicating the highest 'Ca. L. asiaticus' titer, and, thus, is considered the best period to detect 'Ca. L. asiaticus' infection in foliage of citrus trees in southern Brazil. In addition to the seasonal changes in C_t values, there was an initial decline in the C_t value in the months following initial detection, the rate of decline slowing with time. Concomitant with the increase of the bacterial population in the host, there was an increase in severity of HLB symptoms in the trees over time (Spearman's rank correlation, r = -0.4083, P < 0.0001). The results identify the optimal season to sample foliage for 'Ca. L. asiaticus' in southern Brazil (autumn) and confirm the importance of sample timing to maximize detection of 'Ca. L. asiaticus' and, thus, contribute to the search for effective measures to manage HLB.

Practical benefits of knowing the enemy: modern molecular tools for diagnosing the etiology of bacterial diseases and understanding the taxonomy and diversity of plant-pathogenic bacteria

Knowing the identity of bacterial plant pathogens is essential to strategic and sustainable disease management in agricultural systems. This knowledge is critical for growers, diagnosticians, extension agents, and others dealing with crops. However, such identifications are linked to bacterial taxonomy, a complicated and changing discipline that depends on methods and information that are often not used by those who are diagnosing field problems. Modern molecular tools for fingerprinting and sequencing allow for pathogen identification in the absence of distinguishing or conveniently tested phenotypic characteristics. These methods are also useful in studying the etiology and epidemiology of phytopathogenic bacteria from epidemics, as was done in numerous studies conducted in California's Salinas Valley. Multilocus and whole-genome sequence analyses are becoming the cornerstones of studies of microbial diversity and bacterial taxonomy. Whole-genome sequence analysis needs to become adequately accessible, automated, and affordable in order to be used routinely for identification and epidemiology. The power of molecular tools in accurately identifying bacterial pathogenesis is therefore of value to the farmer, diagnostician, phytobacteriologist, and taxonomist.

Differentiation in MALDI-TOF MS and FTIR spectra between two pathovars of Xanthomonas oryzae

Xanthomonas oryzae pv. oryzae (Xoo) and Xanthomonas oryzae pv. oryzicola (Xoc) strains are closely related phenotypically and genetically, which make it difficult to differentiate between the two pathovars based on phenotypic and DNA-based methods. In this study, a fast and accurate method was developed based on the differences in MALDI-TOF MS and FTIR spectra between the two pathovars. MALDI-TOF MS analysis revealed that 9 and 10 peaks are specific to Xoo and Xoc, respectively, which can be used as biomarkers to identify and differentiate the two closely related pathovars. Furthermore, FTIR analysis showed that there is a significant difference in both the band frequencies and absorption intensity of various functional groups between the two pathovars. In particular, the 6 peaks at 3433, 2867, 1273, 1065, 983 and 951cm(-1) were specific to the Xoo strains, while one peak at 1572cm(-1) was specific to the Xoc strains. Overall, this study gives the first attempt to identify and differentiate the two pathovars of X. oryzae based on mass and FTIR spectra, which will be helpful for the early detection and prevention of the two rice diseases caused by both X. oryzae pathovars.

Future of portable devices for plant pathogen diagnosis

The demand for rapid and accurate diagnosis of plant diseases has risen in the last decade. On-site diagnosis of single or multiple pathogens using portable devices is the first step in this endeavour. Despite extensive attempts to develop portable devices for pathogen detection, current technologies are still restricted to detecting known pathogens with limited detection accuracy. Developing new detection techniques for rapid and accurate detection of multiple plant pathogens and their associated variants is essential. Recent single DNA sequencing technologies are a promising new avenue for developing future portable devices for plant pathogen detection. In this review, we detail the current progress in portable devices and technologies used for detecting plant pathogens, the current position of emerging sequencing technologies for analysis of plant genomics, and the future of portable devices for rapid pathogen diagnosis.

Rapid detection of shrimp white spot syndrome virus by real time, isothermal recombinase polymerase amplification assay

White spot syndrome virus (WSSV) causes large economic losses to the shrimp aquaculture industry, and thus far there are no efficient therapeutic treatments available against this lethal virus. In this study, we present the development of a novel real time isothermal recombinase polymerase amplification (RPA) assay for WSSV detection on a small ESEQuant Tube Scanner device. The RPA sensitivity, specificity and rapidity were evaluated by using a plasmid standard as well as viral and shrimp genomic DNAs. Compared with qPCR, the RPA assay revealed more satisfactory performance. It reached a detection limit up to 10 molecules in 95% of cases as determined by probit analysis of 8 independent experiments within 6.41 ± 0.17 min at 39 °C. Consequently, this rapid RPA method has great application potential for field use or point of care diagnostics.

A multi-target, non-infectious and clonable artificial positive control for routine PCR-based assays

Positive controls are essential for PCR reliability and are challenging to obtain for rare, exotic and/or emerging pathogens and pose biosafety risks if manufactured using infectious pathogens. Custom synthetic DNA inserts can be designed de novo in tandems of forward and reverse complement priming sequences to be inserted in circular plasmid vectors. To test this concept, artificial positive controls (APCs) for use in PCR were synthesized to contain primer sequences targeting four viruses (Barley yellow dwarf virus, Soilborne wheat mosaic virus, Triticum mosaic virus and Wheat streak mosaic virus) pathogenic to wheat and, as internal control, the plant mitochondrial nad5 gene. Thermodynamics and folding parameters of twenty-four APC inserts were assessed in silico. Two thermodynamically different APCs, designated optimal and sub-optimal, were cloned and tested using end point PCR. The optimal APC had a 100% amplification rate, while only 92% of virus-infected plant tissues, commonly used as reference positive controls, amplified. An array of APC priming sequences from different organisms and/or previously tested primers can be accommodated in a large and flexible number of positive control targets. APCs will streamline and standardize routine PCR, improve reliability and biosafety, and create opportunities for development and commercialization of new synthetic positive control sequences.

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Controls are essential for PCR reliability in diagnostics and microbial forensics.

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Controls are challenging to obtain for rare, exotic and/or emerging pathogens.

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Positive controls pose biosafety risks if manufactured using infectious pathogens.

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Tandems of forward and reverse primers were engineered as synthetic DNA inserts.

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Synthetic controls were demonstrated in silico and subsequently in vitro by PCR.

Quantification of Live 'Candidatus Liberibacter asiaticus' Populations Using Real-Time PCR and Propidium Monoazide

Huanglongbing (HLB) is a devastating citrus disease. It is associated with a phloem-restricted bacterium, 'Candidatus Liberibacter asiaticus', and primarily transmitted by Asian citrus psyllid in Florida. Because Liberibacter cannot be cultured, early diagnosis of HLB relies on DNA-based polymerase chain reaction (PCR), including real-time quantitative (q)PCR. Although estimating genomes from live bacteria (GLB) is critical for HLB research, PCR does not distinguish between live and dead cells and, thus, does not estimate GLB in hosts. Propidium monoazide (PMA), a novel DNA-binding dye, has been successfully used on many bacterial pathogens to effectively remove DNA from dead cells but there is no report of its use on uncultured bacteria. In this study, PMA-qPCR protocols were first optimized to work with plant and psyllid samples, respectively. Both TissueLyser treatment and plant tissue were demonstrated to have an insignificant impact on the GLB detected by PMA-qPCR. Finally, a standard curve for GLB determination was successfully established between PMA-qPCR results and microscopic counts and then applied in two studies with different greenhouse plant samples. This rapid qPCR method provides a more accurate way to determine GLB in HLB hosts which, in turn, should benefit disease epidemiology studies and serve as a crucial component in HLB management.

Genome characterization of a novel Burkholderia cepacia complex genomovar isolated from dieback affected mango orchards

We characterized the genome of the antibiotic resistant, caseinolytic and non-hemolytic Burkholderia sp. strain TJI49, isolated from mango trees (Mangifera indica L.) with dieback disease. This isolate produced severe disease symptoms on the indicator plants. Next generation DNA sequencing and short-read assembly generated the 60X deep 7,631,934 nucleotide draft genome of Burkholderia sp. TJI49 which comprised three chromosomes and at least one mega plasmid. Genome annotation studies revealed a total 8,992 genes, out of which 8,940 were protein coding genes. Comparative genomics and phylogenetics identified Burkholderia sp. TJI49 as a distinct species of Burkholderia cepacia complex (BCC), closely related to B. multivorans ATCC17616. Genome-wide sequence alignment of this isolate with replicons of BCC members showed conservation of core function genes but considerable variations in accessory genes. Subsystem-based gene annotation identified the active presence of wide spread colonization island and type VI secretion system in Burkholderia sp. TJI49. Sequence comparisons revealed (a) 28 novel ORFs that have no database matches and (b) 23 ORFs with orthologues in species other than Burkholderia, indicating horizontal gene transfer events. Fold recognition of novel ORFs identified genes encoding pertactin autotransporter-like proteins (a constituent of type V secretion system) and Hap adhesion-like proteins (involved in cell-cell adhesion) in the genome of Burkholderia sp. TJI49. The genomic characterization of this isolate provided additional information related to the 'pan-genome' of Burkholderia species.

Development of TaqMan probe-based insulated isothermal PCR (iiPCR) for sensitive and specific on-site pathogen detection

Insulated isothermal PCR (iiPCR), established on the basis of Ralyeigh-Bénard convection, is a rapid and low-cost platform for nucleic acid amplification. However, the method used for signal detection, namely gel electrophoresis, has limited the application of iiPCR. In this study, TaqMan probe-based iiPCR system was developed to obviate the need of post-amplification processing. This system includes an optical detection module, which was designed and integrated into the iiPCR device to detect fluorescent signals generated by the probe. TaqMan probe-iiPCR assays targeting white spot syndrome virus (WSSV) and infectious myonecrosis virus were developed for preliminary evaluation of this system. Significant elevation of fluorescent signals was detected consistently among positive iiPCR reactions in both assays, correlating with amplicon detection by gel electrophoresis analysis. After condition optimization, a threshold value of S/N (fluorescent intensity_after/fluorescent intensity_before) for positive reactions was defined for WSSV TaqMan probe-iiPCR on the basis of 20 blank reactions. WSSV TaqMan probe-iiPCR generated positive S/Ns from as low as 10¹ copies of standard DNA and lightly infected Litopenaeus vannamei. Compared with an OIE-certified nested PCR, WSSV TaqMan probe-iiPCR showed a sensitivity of 100% and a specificity of 96.67% in 120 WSSV-free or lightly infected shrimp samples. Generating positive signals specifically and sensitively, TaqMan probe-iiPCR system has a potential as a low-cost and rapid on-site diagnostics method.

Novel techniques and findings in the study of plant microbiota: search for plant probiotics

Plants live in intimate relationships with numerous microorganisms present inside or outside plant tissues. The plant exterior provides two distinct ecosystems, the rhizosphere (below ground) and the phyllosphere (above ground), both populated by microbial communities. Most studies on plant microbiota deal with pathogens or mutualists. This review focuses on plant commensal bacteria, which could represent a rich source of bacteria beneficial to plants, alternatively termed plant probiotics. Plant commensal bacteria have been addressed only recently with culture-independent studies. These use next-generation sequencing, DNA microarray technologies and proteomics to decipher microbial community composition and function. Diverse bacterial populations are described in both rhizosphere and phyllosphere of different plants. The microorganisms can emerge from neighboring environmental ecosystems at random; however their survival is regulated by the plant. Influences from the environment, such as pesticides, farming practice and atmosphere, also affect the composition of microbial communities. Apart from community composition studies, some functional studies have also been performed. These include identification of broad-substrate surface receptors and methanol utilization enzymes by the proteomic approach, as well as identification of bacterial species that are important mediators of disease-suppressive soil phenomenon. Experience from more advanced human microbial studies could provide useful information and is discussed in the context of methodology and common trends. Administration of microbial mixtures of whole communities, rather than individual species, is highlighted and should be considered in future agricultural applications.

Evolutionary and experimental assessment of novel markers for detection of Xanthomonas euvesicatoria in plant samples

BACKGROUND

Bacterial spot-causing xanthomonads (BSX) are quarantine phytopathogenic bacteria responsible for heavy losses in tomato and pepper production. Despite the research on improved plant spraying methods and resistant cultivars, the use of healthy plant material is still considered as the most effective bacterial spot control measure. Therefore, rapid and efficient detection methods are crucial for an early detection of these phytopathogens.

METHODOLOGY

In this work, we selected and validated novel DNA markers for reliable detection of the BSX Xanthomonas euvesicatoria (Xeu). Xeu-specific DNA regions were selected using two online applications, CUPID and Insignia. Furthermore, to facilitate the selection of putative DNA markers, a customized C program was designed to retrieve the regions outputted by both databases. The in silico validation was further extended in order to provide an insight on the origin of these Xeu-specific regions by assessing chromosomal location, GC content, codon usage and synteny analyses. Primer-pairs were designed for amplification of those regions and the PCR validation assays showed that most primers allowed for positive amplification with different Xeu strains. The obtained amplicons were labeled and used as probes in dot blot assays, which allowed testing the probes against a collection of 12 non-BSX Xanthomonas and 23 other phytopathogenic bacteria. These assays confirmed the specificity of the selected DNA markers. Finally, we designed and tested a duplex PCR assay and an inverted dot blot platform for culture-independent detection of Xeu in infected plants.

SIGNIFICANCE

This study details a selection strategy able to provide a large number of Xeu-specific DNA markers. As demonstrated, the selected markers can detect Xeu in infected plants both by PCR and by hybridization-based assays coupled with automatic data analysis. Furthermore, this work is a contribution to implement more efficient DNA-based methods of bacterial diagnostics.

New grower-friendly methods for plant pathogen monitoring

Accurate plant disease diagnoses and rapid detection and identification of plant pathogens are of utmost importance for controlling plant diseases and mitigating the economic losses they incur. Technological advances have increasingly simplified the tools available for the identification of pathogens to the extent that, in some cases, this can be done directly by growers and producers themselves. Commercially available immunoprinting kits and lateral flow devices (LFDs) for detection of selected plant pathogens are among the first tools of what can be considered grower-friendly pathogen monitoring methods. Research efforts, spurned on by point-of-care needs in the medical field, are paving the way for the further development of on-the-spot diagnostics and multiplex technologies in plant pathology. Grower-friendly methods need to be practical, robust, readily available, and cost-effective. Such methods are not restricted to on-the-spot testing but extend to laboratory services, which are sometimes more practicable for growers, extension agents, regulators, and other users of diagnostic tests.

A Comparison of Standard and High-Fidelity PCR: Evaluating Quantification and Detection of Pathogen DNA in the Presence of Orchid Host Tissue

The polymerase chain reaction (PCR) has been used with increasing frequency for detecting and identifying plant pathogens. Although PCR is sensitive, research has shown that amplification of target microbial DNA from within another organism, such as an arthropod or plant, can be inhibited by the presence of host DNA. In this study, the sensitivity of standard and high-fidelity PCR, which incorporates a second DNA polymerase with proofreading ability, to detect and amplify DNA from the fungal pathogen Pseudocercospora odontoglossi while in the presence of Cattleya orchid DNA, was compared. Different dilutions of plasmids containing internal transcribed spacer (ITS)1, 5.8S, and ITS2 rDNA from P. odontoglossi were spiked with Cattleya orchid plant DNA. The high-fidelity PCR could detect and amplify as few as 207 plasmids containing the fungal DNA, whereas the standard PCR required over 200 million copies. The high-fidelity PCR was more efficient than conventional PCR in detecting Sclerotium rolfsii and a Dickeya sp. from freshly inoculated orchid plants, demonstrating its increased sensitivity in early detection of fungal and bacterial pathogens that are difficult to discriminate early in disease development.

A thermally baffled device for highly stabilized convective PCR

Rayleigh-Bénard convective PCR is a simple and effective design for amplification of DNA. Convective PCR is, however, extremely sensitive to environmental temperature fluctuations, especially when using small- diameter test tubes. Therefore, this method is inherently unstable with limited applications. Here, we present a convective PCR device that has been modified by adding thermal baffles. With this thermally baffled device the influence from fluctuations in environmental temperature were significantly reduced, even in a wind tunnel (1 m/s). The thermally baffled PCR instrument described here has the potential to be used as a low-cost, point-of-care device for PCR-based molecular diagnostics in the field.

Novel and Highly Specific Monoclonal Antibody to Acidovorax citrulli and Development of ELISA-Based Detection in Cucurbit Leaves and Seed

A novel monoclonal antibody (MAb) specific to the seedborne bacterium Acidovorax citrulli was produced. MAb 11E5 reacted specifically with 19 strains of A. citrulli but not with three closely related bacteria in the family Comamonadaceae (i.e., A. facilis, Comamonas acidovorans, and C. testosteroni) and another seven phytopathogenic bacteria. Moreover, this MAb detected a strain of A. citrulli that was not detected by a commercial enzyme-linked immunosorbent assay (ELISA)-based kit and a commercial immunochromatographic strip test. In Western blot analysis, MAb 11E5 reacted with an A. citrulli protein of a molecular mass >170 kDa. MAb 11E5 was employed to develop two sandwich ELISA systems: MAb captured-sandwich ELISA (MC-sELISA) and polyclonal antibody captured-sandwich ELISA (PC-sELISA). MC-sELISA was 10 times more sensitive than PC-sELISA for detection of A. citrulli in cucurbit leaf and seed extracts. The detection limit of the MC-sELISA was 5 × 10⁴ CFU/ml. Detection of A. citrulli in naturally infected cucurbit leaves, fruit, and seed was also feasible using MC-sELISA. The newly established MCsELISA provides another alternative for specific detection of A. citrulli in cucurbits and can be applied for routine field inspection.