Current and emerging trends in techniques for plant pathogen detection

Electrochemical molecularly imprinted polymer sensors in viral diagnostics: Innovations, challenges and case studies

Molecularly imprinted polymers (MIPs) are synthetic equivalent of antibodies and have been widely used in electrochemical sensing as recognition elements. They offer advantages over traditional recognition elements such as antibodies, nucleic acids and aptamers due to their simple synthesis, lower production costs, greater chemical and physical stability, and robust performance in diverse environments. Improved detection techniques and combining MIPs with materials like metal nanoparticles, carbon nanotubes, aptamers, metal organic frameworks, quantum dots, and electrochemically active internal probes show increasing potential. These combinations could become a reliable method for detecting viruses quickly, with performance similar or better than standard techniques. In this review article we provide detailed case studies covering ten different viruses (Bean pod mottle virus, Dengue virus, Zika virus, Foot-and-mouth disease virus, Human papillomavirus, Hepatitis C virus, Human immunodeficiency virus, Influenza A virus, Norovirus, Severe acute respiratory syndrome coronavirus 2) and over forty specific examples. We summarize the recent advances in the development of electrochemical MIP-based sensors for the diagnostics of viral diseases and compare their performance. Additionally, challenges and future perspectives of MIPs as promising recognition elements are discussed.

Early Detection of Plant Diseases and their Management Using Quantum Dots: Status and Strategies

Quantum dots (QDs) are nanoscale semiconductor structures, typically measuring below 10 nm, that exhibit unique electro-optical properties, making them highly suitable for diverse applications in chemistry, pharmacy, and microbiology. Their semiconducting nature allows precise control over optical and electronic behaviours, leading to significant advancements in fluorescence-based studies. Over the past few decades, rapid developments in QD technology have resulted in luminescent materials that emit in the near-infrared region, further enhancing their utility in imaging and sensing applications. QDs possess several desirable characteristics, including high quantum efficiency, excellent biocompatibility, solubility, chemical inertness, stability, and resistance to photobleaching. These properties have expanded their potential in plant pathology, where they facilitate pathogen detection through bioimaging and biosensors. Additionally, QDs are instrumental in studying plant-pathogen interactions, enabling researchers to track the movement and behaviour of various organisms such as fungi, bacteria, and viruses. Their application in disease diagnosis and management continues to grow, promising improved strategies for monitoring and mitigating plant infections. This review provides an in-depth discussion on the fundamental properties of QDs, their synthesis techniques, and their evolving role in enhancing plant disease detection and management through innovative imaging and sensing technologies.

Bioluminescent imaging of an oomycete pathogen empowers chemical selections and rational fungicide applications

Fungicides play an indispensable role in ensuring food security. However, rational chemical selection and fungicide precision application guidance remain constrained by the limitations in real-time monitoring of tracking pathogens within plant tissues. In the current study, we generated a genetically stable Phytophthora infestans strain (PiLuc) expressing luciferase gene, which serves as a dual-mode quantification platform for both in vitro and in vivo throughput screening. Consequently, we designed a 96-well plate high-throughput screening system to assess compounds inhibitory efficacy using PiLuc. Crucially, bioluminescence imaging enabled visualization of PiLuc in potato leaves and tubers during early infection stage, which is invisible to the naked eye. Capitalizing on the semi non-destructive and visual advantages, we developed a system for fungicide bioavailability evaluation and dosage-response assessment in tuber tissues, integrating real-time dynamic monitoring of pathogen. The development of bioluminescent imaging of late blight pathogen establishes an enabling platform for high-throughput fungicide screening while improving the precision bioavailability assessments.

Molecular virulotyping and advancing the detection of Magnaporthe oryzae using a CRISPR-Cas12a-based diagnostic tool

Rice blast, caused by Magnaporthe oryzae, is a major threat to global rice production. The disease affects various growth stages of rice including leaves, nodes, and panicles leading to significant yield loss. Understanding the genetic diversity and early detection of M. oryzae is essential for developing effective intervention and disease management. In current study, 30 isolates of M. oryzae were collected from major rice-growing areas in Karnataka, Tamil Nadu, Andhra Pradesh, and Telangana, revealing considerable morphological and genetic diversity. Molecular characterization using ITS, LSU, and actin primers confirmed all isolates as M. oryzae, showing 100% sequence homology to reference strains. Phylogenetic analysis revealed regional clustering of isolates, with notable diversity observed in populations from Tamil Nadu and Karnataka. Pathogenicity assays identified significant variability in disease severity, with isolates MOK1, MOTN4, and MOK10 being highly virulent. Virulotyping revealed the widespread presence of critical pathogenicity genes, with Avr-Pik, Avr-Pita, MPS1, SLP1 and TYR1 as prominent contributors. Disease severity is highly correlated with the presence of EXO 70. The tyrosinase gene remains well conserved among all the isolates and was used as a target for CRISPR cas12a based detection. A novel CRISPR-Cas12a detection system, coupled with recombinase polymerase amplification (RPA), demonstrated high sensitivity and specificity for M. oryzae DNA, detecting concentrations as low as 10⁻¹/µL of DNA copies. Field testing successfully identified the pathogen in leaf, neck, and seed samples with visual confirmation via fluorescence and lateral flow assays. This integrated approach provides valuable insights into M. oryzae diversity, pathogenicity, and a robust diagnostic tool for early pathogen detection, paving the way for targeted management strategies to mitigate rice blast disease.

A qPCR assay for the detection of Phytophthora abietivora, an emerging pathogen on fir species cultivated as Christmas trees

Emerging species of the Phytophthora genus are among the most important threats to global plant biodiversity, horticulture and trade. For instance, Phytophthora root rot (PRR) of Christmas trees, mainly Fraser (Abies fraseri) and balsam (Abies balsamea) firs, is responsible for an average of 10% of the observed diseased trees in plantations. Diagnosing PRR involves isolation followed by morphological and molecular identification of the causal agents. However, these methods are rarely adapted to larger scale monitoring such as in situ detection. For these applications, molecular detection of environmental DNA (eDNA) provides the fast and high-throughput results needed. Phytophthora abietivora was associated with PRR in firs (Abies spp.) cultivated as Christmas trees in the province of Québec (Canada). This study focused on developing a sensitive and specific qPCR assay targeting P. abietivora and validating its efficiency on DNA extracted from soil and roots. A set of primers and probe was designed for this assay, and parameters such as the limit of detection (LOD95%) and limit of quantification (LOQ) were measured. The assay was tested on DNA obtained from healthy-looking and PRR symptomatic Fraser and balsam firs. The assay was shown to be semi-specific because it cross-reacted with P. europaea and three other phylogenetically close species, but deemed specific in the context of PRR of firs. The LOD95% was estimated at 10 copies per reaction (Cq of 35.7) and the LOQ to 33 P. abietivora oospores per gram of soil. Out of 488 DNA samples from soil, 68 were positive for P. abietivora from which 42 (61.7%) were from PRR symptomatic trees. Only a slight overlap (3 out of 7 samples) was observed with previously obtained baiting results. This assay will be useful for rapid diagnostics of P. abietivora infected trees and as a prospecting tool to better characterize the natural distribution and dissemination of the disease.

Development and Application of a Multiplex PCR Assay for Simultaneous Detection of Tomato Yellow Leaf Curl Virus and Tomato Leaf Curl New Delhi Virus

Tomato leaf curl New Delhi virus (ToLCNDV) and tomato yellow leaf curl virus (TYLCV) are two important viral pathogens that severely affect Solanaceae and Cucurbitaceae plants. In order to reduce the further spread of these viruses, it is crucial to establish an efficient and reliable method to accurately detect the viruses. In this study, a multiplex PCR assay for the simultaneous detection of TYLCV and ToLCNDV was established. Three primer pairs designed from conserved regions within the coat protein or movement protein-encoding regions of the respective viruses were employed in the assay. The optimization of parameters such as primer concentration was set at 0.15 μM/0.15 μM, 0.25 μM/0.25 μM, and 0.50 μM/0.50 μM for ToLCNDV-DNA-A-F/R, TYLCV-F/R, and ToLCNDV-DNA-B-F/R primer pairs. At optimal primer concentrations, the multiplex PCR method demonstrates effective performance with an annealing temperature ranging from 51 °C to 66 °C. The specificity of the assay evaluated by testing against other begomoviruses showed no evidence of cross-amplification. Further sensitivity analysis performed using a serially diluted plasmid containing viral targets as templates demonstrated high sensitivity with a detection limit of 103 copies/μL. Field surveys utilizing the multiplex PCR assay successfully identified the infection of TYLCV and ToLCNDV in field-collected samples.

Advanced rDNA-Based Detection of Wheat Pathogens in Grain Samples Using Next-Generation Sequencing (NGS)

High-throughput sequencing (HTS) has revolutionized phytopathology by overcoming many limitations of traditional diagnostic methods, as it permits precise pathogen monitoring, identification, and control, with ribosomal DNA (rDNA) regions serving as reliable markers for fungal classification. In this study, next-generation sequencing (NGS) was used, targeting the ITS1 and ITS2 regions to explore fungal diversity and pathogen presence in winter wheat grain samples and identifying 183 OTU sequences across 115 taxa. The ITS1 analysis yielded 249,743 reads, with Fusarium sp. (61%) as the dominant pathogenic taxon, followed by Sporobolomyces sp. (14%), Cladosporium sp. (3%), and other yeast-like or saprotrophic fungi, such as Cryptoccocus spp., F. wieringae, and B. alba. Sequencing of ITS1 also permitted the detection of F. acuminatum and the quarantine-regulated pathogens T. caries and T. triticoides. The ITS2 analysis produced 179,675 reads, with F. culmorum (47%) as the most abundant taxon, confirming significant grain contamination with this pathogen. Other frequently detected taxa included yeast-like fungi such as C. tephrensis (21%) and V. victoriae (13%), along with saprotrophic species like S. roseus and Davidella sp. ITS2 provided better resolution for the identification of Fusarium species by the detection of more pathogenic taxa associated with cereal diseases, including F. culmorum, as well as F. cerealis, F. poae, and F. tricinctum. The analysis revealed a diverse fungal community, including other pathogens such as A. porri, B. cinerea, and C. herbarum, as well as various non-pathogenic and saprotrophic fungal taxa. These findings underscore the complementary utility of ITS1 and ITS2 in profiling fungal diversity and detecting critical pathogens using HTS, highlighting the potential of these DNA regions for monitoring and managing cereal crop health.

Portable solutions for plant pathogen diagnostics: development, usage, and future potential

The increasing prevalence of plant pathogens presents a critical challenge to global food security and agricultural sustainability. While accurate, traditional diagnostic methods are often time-consuming, resource-intensive, and unsuitable for real-time field applications. The emergence of portable diagnostic tools represents a paradigm shift in plant disease management, offering rapid, on-site detection of pathogens with high accuracy and minimal technical expertise. This review explores portable diagnostic technologies' development, deployment, and future potential, including handheld analyzers, smartphone-integrated systems, microfluidics, and lab-on-a-chip platforms. We examine the core technologies underlying these devices, such as biosensors, nucleic acid amplification techniques, and immunoassays, highlighting their applicability to detect bacterial, viral, and fungal pathogens in diverse agricultural settings. Furthermore, the integration of these devices with digital technologies, including the Internet of Things (IoT), artificial intelligence (AI), and machine learning (ML), is transforming disease surveillance and management. While portable diagnostics have clear advantages in speed, cost-effectiveness, and user accessibility, challenges related to sensitivity, durability, and regulatory standards remain. Innovations in nanotechnology, multiplex detection platforms, and personalized agriculture promise to further enhance the efficacy of portable diagnostics. By providing a comprehensive overview of current technologies and exploring future directions, this review underscores the critical role of portable diagnostics in advancing precision agriculture and mitigating the impact of plant pathogens on global food production.

AutoPVPrimer: A comprehensive AI-Enhanced pipeline for efficient plant virus primer design and assessment

Plant viruses pose a significant threat to global agriculture and require efficient tools for their timely detection. We present AutoPVPrimer, an innovative pipeline that integrates artificial intelligence (AI) and machine learning to accelerate the development of plant virus primers. The pipeline uses Biopython to automatically retrieve different genomic sequences from the NCBI database to increase the robustness of the subsequent primer design. The design_primers_with_tuning module uses a random forest classifier that optimizes parameters and provides flexibility for different experimental conditions. Quality control measures, including the evaluation of poly-X content and melting temperature, increase primer reliability. Unique to AutoPVPrimer is the visualize_primer_dimer module, which supports the visual evaluation of primer dimers-a feature missing in other tools. Primer specificity is validated via primer BLAST, which contributes to the overall efficiency of the pipeline. AutoPVPrimer has been successfully applied to the tomato mosaic virus, proving its adaptability and efficiency. The modular design allows customization by the user and extends the applicability to different plant viruses and experimental scenarios. The pipeline represents a significant advance in primer design and provides researchers with an effective tool to accelerate molecular biology experiments. Future developments aim to extend compatibility and incorporate user feedback to consolidate AutoPVPrimer as an innovative contribution to the bioinformatics toolbox and a promising resource for the advancement of plant virology research.

Quantitative detection of the maize phytocytokine Zip1 utilizing ELISA

Plant signaling peptides, also known as phytocytokines, play a crucial role in cell-to-cell communication during plant development and immunity. The detection of small peptides in plant tissues is challenging and often relies on time-consuming and cost-intensive approaches. Here, we present an ELISA-based assay as a rapid and cost-effective method for the detection of naturally released peptides in plant tissues. Our ELISA-based method was developed to detect Zip1, a 17-amino-acid phytocytokine derived from Zea mays that elicits salicylic acid signaling in maize leaves. Using a custom peptide-antibody, we designed an experimental pipeline to achieve peptide specificity, selectivity, and sensitivity allowing the detection of the Zip1 peptide in complex biological samples. As a proof of concept, we first overexpressed the precursor molecule PROZIP1 in Nicotiana benthamiana and in transfected maize protoplasts and monitored the release of Zip1-containing peptides. In a second approach we treated maize leaves with salicylic acid to induce native PROZIP1 expression and processing. Using ELISA, we were able to quantify native Zip1 signals with a detection limit in the nanogram range, which allowed us to detect different Zip1-containing peptides in plant material. This method can be adapted for the detection and quantification of a variety of plant signaling peptides.

Feels Like Home: A Biobased and Biodegradable Plastic Offers a Novel Habitat for Diverse Plant Pathogenic Fungi in Temperate Forest Ecosystems

Poly(butylene succinate-co-adipate) (PBSA), a biodegradable plastic, is significantly colonized and degraded by soil microbes under natural field conditions, especially by fungal plant pathogens, raising concerns about potential economic losses. This study hypothesizes that the degradation of biodegradable plastics may increase the presence and abundance of plant pathogens by serving as an additional carbon source, ultimately posing a risk to forest ecosystems. We investigated (i) fungal plant pathogens during the exposure of PBSA in European broadleaved and coniferous forests (two forest types), with a specific focus on potential risk to tree health, and (ii) the response of such fungi to environmental factors, including tree species, soil pH, nutrient availability, moisture content, and the physicochemical properties of leaf litter layer. Next-generation sequencing (NGS) revealed that PBSA harbored a total of 318 fungal plant pathogenic amplicon sequence variants (ASVs) belonging to 108 genera. Among the identified genera (Alternaria, Nectria, Phoma, Lophodermium, and Phacidium), some species have been reported as causative agents of tree diseases. Plenodomus was present in high relative abundances on PBSA, which have not previously been associated with disease in broadleaved and coniferous forests. Furthermore, the highest number of fungal plant pathogens were detected at 200 days of PBSA exposure (112 and 99 fungal plant pathogenic ASV on PBSA degraded under Q. robur and F. sylvatic-dominated forest, respectively), which was double compared mature leaves and needles from the same forest sites. These findings suggest that PBSA attracts fungal plant pathogens in forests as an additional carbon source, potentially leading to increased disease outbreaks and disrupting the stability of forest ecosystems. The fungal plant pathogenic community compositions were mainly shaped by forest type, PBSA exposure time, site locations, leaf litter layer water content, and N:P ratio from leaf litter layer in both forest types. This study provides valuable insights into the potential risks posed by biodegradable plastic degradation in forests after 200 and 400 days of exposure, respectively. Further comprehensive evaluations of their effects on tree health and ecosystems, ideally on a long-term basis, are needed. These evaluations should include integrating microbial investigation, soil health monitoring, and ecosystem interaction assessments. Nevertheless, it should be noted that our interpretation of plant pathogens is solely based on high-throughput sequencing, bioinformatics, and annotation tools.

Isothermal Detection Methods for Fungal Pathogens in Closed Environment Agriculture

Closed environment agriculture (CEA) is rapidly gaining traction as a sustainable option to meet global food demands while mitigating the impacts of climate change. Fungal pathogens represent a significant threat to crop productivity in CEA, where the controlled conditions can inadvertently foster their growth. Historically, the detection of pathogens has largely relied on the manual observation of signs and symptoms of disease in the crops. These approaches are challenging at large scale, time consuming, and often too late to limit crop loss. The emergence of fungicide resistance further complicates management strategies, necessitating the development of more effective diagnostic tools. Recent advancements in technology, particularly in molecular and isothermal diagnostics, offer promising tools for the early detection and management of fungal pathogens. Innovative detection methods have the potential to provide real-time results and enhance pathogen management in CEA systems. This review explores isothermal amplification and other new technologies in detection of fungal pathogens that occur in CEA.

Impact of Metabolites from Foodborne Pathogens on Cancer

Foodborne pathogens are microorganisms that cause illness through contamination, presenting significant risks to public health and food safety. This review explores the metabolites produced by these pathogens, including toxins and secondary metabolites, and their implications for human health, particularly concerning cancer risk. We examine various pathogens such as Salmonella sp., Campylobacter sp., Escherichia coli, and Listeria monocytogenes, detailing the specific metabolites of concern and their carcinogenic mechanisms. This study discusses analytical techniques for detecting these metabolites, such as chromatography, spectrometry, and immunoassays, along with the challenges associated with their detection. This study covers effective control strategies, including food processing techniques, sanitation practices, regulatory measures, and emerging technologies in pathogen control. This manuscript considers the broader public health implications of pathogen metabolites, highlighting the importance of robust health policies, public awareness, and education. This review identifies research gaps and innovative approaches, recommending advancements in detection methods, preventive strategies, and policy improvements to better manage the risks associated with foodborne pathogens and their metabolites.

Highly Targeted Detection of Priority Phytopathogen Pectobacterium brasiliense: From Obtaining Polyclonal Antibodies to Development and Approbation of Enzyme-Linked Immunoassay and Lateral Flow Immunoassay

Pectobacterium brasiliense is a bacterial phytopathogen that causes soft and black rot and actively spreads worldwide. Our study is the first development of immunoassays for detecting P. brasiliense. We immunized rabbits and obtained serum with an extremely high titer (1:108). Isolated polyclonal antibodies were tested by enzyme-linked immunosorbent assay (ELISA) using 18 closely related strains and 5 non-related bacterial pathogens. No cross-reactivity was found concerning the tested pathogens. The ELISA of P. brasiliense was developed in a double-antibody sandwich format with a detection limit of 1.5 × 104 cells/mL. A lateral flow immunoassay (LFIA) for P. brasiliense was also developed in a double-antibody sandwich format with a detection limit of 1 × 105 cells/mL. The results of P. brasiliense cells testing with LFIA in plant matrix showed a high correlation (R2 = 0.932) between concentrations of added and revealed cells. When testing potato seed material, ELISA and LFIA confirmed 75 and 66% of positive samples according to real-time PCR, respectively. For negative samples, ELISA showed 84% coincidence, and LFIA coincided with PCR for 89% of samples. Thus, the developed immunoassays can be used to evaluate plant material in poorly equipped conditions or under field testing.

Droplet Digital PCR: A New Molecular Method to Detect G1105S/V Mutations in Plasmopara viticola CesA3 Gene

Plasmopara viticola is the causal agent of Grapevine Downy Mildew (GDM), which is a devastating disease of grapevines in humid temperate regions. The most employed method for protecting grapevines against GDM is the application of chemical fungicides. In Spain, Carboxylic Acid Amides (CAAs) are a fungicide group currently utilized in GDM control. In P. viticola, resistance to CAAs is conferred by G1105S and G1105V mutations in the CesA3 gene. Droplet digital polymerase chain reaction (ddPCR) is an innovative technique that combines PCR and droplet microfluidics to disperse the sample into thousands of water-in-oil droplets in which an amplification reaction is individually performed. In this study, we set up a ddPCR protocol to quantify S1105 and V1105 mutations conferring resistance to CAAs in P. viticola. The optimal PCR conditions were established, and the sensitivity and precision of the protocol were assessed. Four P. viticola populations coming from commercial vineyards in northern Spain were analyzed, and different allele frequencies were found in the analyzed samples corresponding to the different fungicide management strategies, ranging from 7.72% to 100%. Knowing the level of mutated alleles allows for designing resistance management strategies suited for each location. This suggests that similar ddPCR assays could be developed for studying mutations implicated in fungicide resistance in other fungicide groups and plant pathogens.

Early Detection of Both Pyrenophora teres f. teres and f. maculata in Asymptomatic Barley Leaves Using Digital Droplet PCR (ddPCR)

Efficient early pathogen detection, before symptom apparition, is crucial for optimizing disease management. In barley, the fungal pathogen Pyrenophora teres is the causative agent of net blotch disease, which exists in two forms: P. teres f. sp. teres (Ptt), causing net-form of net blotch (NTNB), and P. teres f. sp. maculata (Ptm), responsible for spot-form of net blotch (STNB). In this study, we developed primers and a TaqMan probe to detect both Ptt and Ptm. A comprehensive k-mer based analysis was performed across a collection of P. teres genomes to identify the conserved regions that had potential as universal genetic markers. These regions were then analyzed for their prevalence and copy number across diverse Moroccan P. teres strains, using both a k-mer analysis for sequence identification and a phylogenetic assessment to establish genetic relatedness. The designed primer-probe set was successfully validated through qPCR, and early disease detection, prior to symptom development, was achieved using ddPCR. The k-mer analysis performed across the available P. teres genomes suggests the potential for these sequences to serve as universal markers for P. teres, transcending environmental variations.

Triplex real-time qPCR for the simultaneous detection of Botryosphaeriaceae species in woody crops and environmental samples

Introduction

Species of Botryosphaeriaceae fungi are relevant pathogens of almond causing trunk cankers, extensive gumming, necrosis of internal tissues and plant dieback and dead, threatening almond productivity. A novel triplex quantitative real-time PCR (qPCR) assay was designed for the simultaneous detection and quantification of Neofusicoccum parvum, Botryosphaeria dothidea and the Botryosphaeriaceae family.

Material and methods

The method was validated in symptomatic and asymptomatic almond, avocado, blueberry and grapevine plants and in environmental samples, such as cropping soil and rainwater and in artificially inoculated trapped spores, demonstrating the same performance on several matrices.

Results and discussion

The limit of detection of the triplex qPCR was 10 fg of genomic DNA for the three fungal targets, with high correlation coefficients (R2) and amplification efficiencies between 90 and 120%. Although the triplex qPCR demonstrated to be more sensitive and accurate than the traditional plate culturing and further sequencing method, a substantial agreement (kappa index = 0.8052 ± 0.0512) was found between the two detection methods. The highly sensitive qPCR assay allows for accurate diagnosis of symptomatic plants and early detection of Botryosphaeriaceae fungi in asymptomatic plants (rootstocks and grafting scions from almond nurseries). Furthermore, the triplex qPCR successfully detected Botryosphaeriaceae fungi in environmental samples, such as cropping soils and rainwater. It was also capable of detecting as few as 10 conidia in artificially inoculated tapes. Therefore, the triplex qPCR is a valuable tool for accurate diagnosis, aiding in the implementation of suitable control measures. It enables preventive detection in asymptomatic samples, helping to avoid the introduction and spread of these pathogens in production fields. Moreover, it assists in identifying inoculum sources and quantifying inoculum levels in crop environments, contributing to a precise phytosanitary application schedule, thereby reducing production costs and preserving the environment.

Kinetic and catalytic mechanisms of the methionine-derived glucosinolate biosynthesis enzyme methylthioalkylmalate synthase

In Brassica plants, methionine-derived aliphatic glucosinolates are chemically diverse natural products that serve as plant defense compounds, as well as molecules with dietary health-promoting effects. During their biosynthesis, methylthioalkylmalate synthase (MAMS) catalyzes the elongation reaction of the aliphatic chain. The MAMS-catalyzed condensation of 4-methylthio-2-oxobutanoic acid and acetyl-CoA generates a 2-malate derivative that either enters the pathway for the synthesis of C3-glucosinolates or undergoes additional extension reactions, which lead to C4- to C9-glucosinolates. Recent determination of the x-ray crystal structure of MAMS from Brassica juncea (Indian mustard) provided insight on the molecular evolution of MAMS, especially substrate specificity changes, from the leucine biosynthesis enzyme α-isopropylmalate synthase but left details of the reaction mechanism unanswered. Here we use the B. juncea MAMS2A (BjMAMS2A) isoform to analyze the kinetic and catalytic mechanisms of this enzyme. Initial velocity studies indicate that MAMS follows an ordered bi bi kinetic mechanism, which based on the x-ray crystal structure, involves binding of 4-methylthio-2-oxobutanoic acid followed by acetyl-CoA. Examination of the pH-dependence of kcat and kcat/Km are consistent with acid/base catalysis. Site-directed mutagenesis of three residues originally proposed to function in the reaction mechanism-Arg89 (R89A, R89K, R89Q), Glu227 (E227A, E227D, E227Q), and His388 (H388A, H388N, H388Q, H388D, and H388E)-showed that only two mutants (E227Q and H388N) retained activity. Based on available structural and biochemical data, a revised reaction mechanism for MAMS-catalyzed elongation of methionine-derived aliphatic glucosinolates is proposed, which is likely also conserved in α-isopropylmalate synthase from leucine biosynthesis in plants and microbes.

Rapid real-time quantitative colorimetric LAMP methodology for field detection of Verticillium dahliae in crude olive-plant samples

BACKGROUND

Verticilium dahliae is the most important wilt pathogen of olive trees with a broad host range causing devastating diseases currently without any effective chemical control. Traditional detection methodologies are based on symptoms-observation or lab-detection using time consuming culturing or molecular techniques. Therefore, there is an increasing need for portable tools that can detect rapidly V. dahliae in the field.

RESULTS

In this work, we report the development of a novel method for the rapid, reliable and on-site detection of V. dahliae using a newly designed isothermal LAMP assay and crude extracts of olive wood. For the detection of the fungus, LAMP primers were designed targeting the internal transcribed spacer (ITS) region of the rRNA gene. The above assay was combined with a purpose-built prototype portable device which allowed real time quantitative colorimetric detection of V. dahliae in 35 min. The limit of detection of our assay was found to be 0.8 fg/μl reaction and the specificity 100% as indicated by zero cross-reactivity to common pathogens found in olive trees. Moreover, detection of V. dahliae in purified DNA gave a sensitivity of 100% (Ct < 30) and 80% (Ct > 30) while the detection of the fungus in unpurified crude wood extracts showed a sensitivity of 80% when multisampling was implemented. The superiority of the LAMP methodology regarding robustness and sensitivity was demonstrated when only LAMP was able to detect V. dahliae in crude samples from naturally infected trees with very low infection levels, while nested PCR and SYBR qPCR failed to detect the pathogen in an unpurified form.

CONCLUSIONS

This study describes the development of a new real time LAMP assay, targeting the ITS region of the rRNA gene of V. dahliae in olive trees combined with a 3D-printed portable device for field testing using a tablet. The assay is characterized by high sensitivity and specificity as well as ability to operate using directly crude samples such as woody tissue or petioles. The reported methodology is setting the basis for the development of an on-site detection methodology for V. dahliae in olive trees, but also for other plant pathogens.

New Approaches to Plant Pathogen Detection and Disease Diagnosis

Detecting plant pathogens and diagnosing diseases are critical components of successful pest management. These key areas have undergone significant advancements driven by breakthroughs in molecular biology and remote sensing technologies within the realm of precision agriculture. Notably, nucleic acid amplification techniques, with recent emphasis on sequencing procedures, particularly next-generation sequencing, have enabled improved DNA or RNA amplification detection protocols that now enable previously unthinkable strategies aimed at dissecting plant microbiota, including the disease-causing components. Simultaneously, the domain of remote sensing has seen the emergence of cutting-edge imaging sensor technologies and the integration of powerful computational tools, such as machine learning. These innovations enable spectral analysis of foliar symptoms and specific pathogen-induced alterations, making imaging spectroscopy and thermal imaging fundamental tools for large-scale disease surveillance and monitoring. These technologies contribute significantly to understanding the temporal and spatial dynamics of plant diseases.

Recent advances and challenges in plant viral diagnostics

Accurate and timely diagnosis of plant viral infections plays a key role in effective disease control and maintaining agricultural productivity. Recent advances in the diagnosis of plant viruses have significantly expanded our ability to detect and monitor viral pathogens in agricultural crops. This review discusses the latest advances in diagnostic technologies, including both traditional methods and the latest innovations. Conventional methods such as enzyme-linked immunosorbent assay and DNA amplification-based assays remain widely used due to their reliability and accuracy. However, diagnostics such as next-generation sequencing and CRISPR-based detection offer faster, more sensitive and specific virus detection. The review highlights the main advantages and limitations of detection systems used in plant viral diagnostics including conventional methods, biosensor technologies and advanced sequence-based techniques. In addition, it also discusses the effectiveness of commercially available diagnostic tools and challenges facing modern diagnostic techniques as well as future directions for improving informed disease management strategies. Understanding the main features of available diagnostic methodologies would enable stakeholders to choose optimal management strategies against viral threats and ensure global food security.

Serological and Molecular Detection of Citrus Tristeza Virus: A Review

Citrus tristeza virus (CTV) is a globally pervasive and economically significant virus that negatively impacts citrus trees, leading to substantial reductions in fruit yield. CTV occurs within the phloem of infected plants, causing a range of disease phenotypes, such as stem pitting (SP), quick decline (QD), and other detrimental diseases. Research on CTV is challenging due to the large size of its RNA genome and the diversity of CTV populations. Comparative genomic analyses have uncovered genetic diversity in multiple regions of CTV isolates' genomes, facilitating the classification of the virus into distinct genotypes. Despite these challenges, notable advancements have been made in identifying and controlling CTV strains through serological and molecular methods. The following review concentrates on the techniques of nucleic acid identification and serological analysis for various CTV isolates, assisting in the comparison and evaluation of various detection methods, which are crucial for the effective management of CTV diseases, and so contributes to the innovation and development of CTV detection methods.

Recent advances in biosensors for screening plant pathogens

Worldwide, plant pathogens have been a considerably important cause of economic loss in agriculture especially in the decades of agricultural intensification. The increasing losses in agriculture due to biotic plant diseases have drawn attention towards the development of plant disease analyzing methods. In this context, biosensors have emerged as significantly important tools which help farmers in on-field diagnosis of plant diseases. Compared to traditional methods, biosensors have outstanding features such as being highly sensitive and selective, cost-effective, portable, fast and user-friendly operation, and so on. There are three common types of biosensors including electrochemical, fluorescent, and colorimetric biosensors. In this review, some common biotic plant diseases caused by fungi, bacteria, and viruses are first summarized. Then, current advances in developing biosensors are discussed.

A simple graphene oxide-based DNA purification strategy for plant pathogen detection

BACKGROUND

The on-site molecular detection of plant pathogens is particularly important for the development of sustainable agriculture. Extracting DNA from plant tissues, microbes or coexisting environments is complex, labor-intensive and time-consuming. To facilitate this process, we propose a DNA purification strategy based on graphene oxide (GO).

RESULTS

The excellent adsorption ability of GO was verified by visualizing changes in its microscopic surface and macroscopic mixture. To further optimize the DNA purification, we determined the optimal GO concentration and treatment time at 95 °C (2 mg mL-1 and 2 min, respectively). We confirmed that our strategy is effective on plant tissues and various microorganisms, and that the obtained DNA can be directly used for polymerase chain reaction amplification. Combining the proposed GO-based DNA purification method with the loop-mediated isothermal amplification method is superior, in terms of the required steps, time, cost and detection effect, to the cetyltrimethylammonium bromide method and a commercial kit for detecting plant pathogens.

CONCLUSION

We present a feasible, rapid, simple and low-cost DNA purification method with high practical value for scientific applications in plant pathogen detection. This strategy can also provide important technical support for future research on plant-microbial microenvironments. © 2024 Society of Chemical Industry.

Metagenome-enabled models improve genomic predictive ability and identification of herbivory-limiting genes in sweetpotato

Plant-insect interactions are often influenced by host- or insect-associated metagenomic community members. The relative abundance of insects and the microbes that modulate their interactions were obtained from sweetpotato (Ipomoea batatas) leaf-associated metagenomes using quantitative reduced representation sequencing and strain/species-level profiling with the Qmatey software. Positive correlations were found between whitefly (Bemisia tabaci) and its endosymbionts (Candidatus Hamiltonella defensa, Candidatus Portiera aleyrodidarum, and Rickettsia spp.) and negative correlations with nitrogen-fixing bacteria that implicate nitric oxide in sweetpotato-whitefly interaction. Genome-wide associations using 252 975 dosage-based markers, and metagenomes as a covariate to reduce false positive rates, implicated ethylene and cell wall modification in sweetpotato-whitefly interaction. The predictive abilities (PA) for whitefly and Ocypus olens abundance were high in both populations (68%-69% and 33.3%-35.8%, respectively) and 69.9% for Frankliniella occidentalis. The metagBLUP (gBLUP) prediction model, which fits the background metagenome-based Cao dissimilarity matrix instead of the marker-based relationship matrix (G-matrix), revealed moderate PA (35.3%-49.1%) except for O. olens (3%-10.1%). A significant gain in PA after modeling the metagenome as a covariate (gGBLUP, ≤11%) confirms quantification accuracy and that the metagenome modulates phenotypic expression and might account for the missing heritability problem. Significant gains in PA were also revealed after fitting allele dosage (≤17.4%) and dominance effects (≤4.6%). Pseudo-diploidized genotype data underperformed for dominance models. Including segregation-distorted loci (SDL) increased PA by 6%-17.1%, suggesting that traits associated with fitness cost might benefit from the inclusion of SDL. Our findings confirm the holobiont theory of host-metagenome co-evolution and underscore its potential for breeding within the context of G × G × E interactions.

It's a Trap! Part I: Exploring the Applications of Rotating-Arm Impaction Samplers in Plant Pathology

Although improved knowledge on the movement of airborne plant pathogens is likely to benefit plant health management, generating this knowledge is often far more complicated than anticipated. This complexity is driven by the dynamic nature of environmental variables, diversity among pathosystems that are targeted, and the unique needs of each research group. When using a rotating-arm impaction sampler, particle collection is dependent on the pathogen, environment, research objectives, and limitations (monetary, environmental, or labor). Consequently, no design will result in 100% collection efficiency. Fortunately, it is likely that multiple approaches can succeed despite these constraints. Choices made during design and implementation of samplers can influence the results, and recognizing this influence is crucial for researchers. This article is for beginners in the art and science of using rotating-arm impaction samplers; it provides a foundation for designing a project, from planning the experiment to processing samples. We present a relatively nontechnical discussion of the factors influencing pathogen dispersal and how placement of the rotating-arm air samplers alters propagule capture. We include a discussion of applications of rotating-arm air samplers to demonstrate their versatility and potential in plant pathology research as well as their limitations.

Towards Pathogen-Free Coconut Germplasm Exchange

Coconut (Cocos nucifera L.) is an important palm species that serves as the mainstay of several industries and contributes to the livelihoods of millions of smallholder farmers. International exchange of coconut germplasm has been undertaken for several decades to facilitate the conservation of selected varieties within global genebanks and for the distribution to farmers and scientists. In vitro systems are a convenient and an efficient method for the exchange of coconut germplasm. However, it is possible that these tissue culture systems can transfer lethal pathogens causing a threat to the importing countries. In this review, the following topics are discussed: the major disease-causing agents of concern, the various tissues that could be used for coconut germplasm exchange, and the techniques available for the detection and elimination of disease-causing agents from various transmission systems. Additionally, the lack of clear, science-backed guidelines to facilitate the exchange of in vitro coconut materials is raised, along with recommendations for future studies to ensure the safe movement of coconut germplasm without biosecurity risks.

Soil Microbial Communities in Lemon Orchards Affected by Citrus Mal Secco Disease

Mal secco is a vascular disease of citrus caused by the mitosporic fungus Plenodomus tracheiphilus. Soil containing infected plant material constitutes an inoculum source for root infections. In this study, the soil bacterial and fungal communities of five lemon orchards located in Syracuse Province (Sicily, Italy) affected by mal secco were analyzed. Soil samples were collected under lemon tree canopies and subjected to total genomic DNA extraction. The fungal DNA was detected through qPCR in all orchards, with variable concentrations. Bacterial and fungal communities were profiled using 16S and ITS amplicon-based high-throughput sequencing, respectively. According to our results, the relative abundances of the most represented bacterial phyla (e.g., Proteobacteria, Actinobacteriota, Acidobacteriota) changed across the orchards, while in the fungal community, the phylum Ascomycota was dominant, with Basidiomycota and Mortierellomycota abundances fluctuating. On the whole, β diversity analysis showed significant variation in the composition of the soil microbial communities across the orchards. This result was confirmed by the analysis of the core community (taxa present at ≥ 75% of total samples), where putative beneficial bacteria resulted in significantly enriched fungus-infected soil samples, suggesting complex microbial interactions. Our findings shed light on the composition and diversity of the soil microbiome in lemon orchards with the occurrence of mal secco infections.

Current and emerging nanotechnology for sustainable development of agriculture: Implementation design strategy and application

Recently, agriculture systems have faced numerous challenges involving sustainable nutrient use efficiency and feeding, environmental pollution especially heavy metals (HMs), infection of harmful microorganisms, and maintenance of crop production quality during postharvesting and packaging. Nanotechnology and nanomaterials have emerged as powerful tools in agriculture applications that provide alternatives or support traditional methods. This review aims to address and highlight the current overarching issue and various implementation strategies of nanotechnology for sustainable agriculture development. In particular, the current progress of different nano-fertilizers (NFs) systems was analyzed to show their advances in enhancing the uptake and translocations in plants and improving nutrient bioavailability in soil. Also, the design strategy and application of nanotechnology for rapid detection of HMs and pathogenic diseases in plant crops were emphasized. The engineered nanomaterials have great potential for biosensors with high sensitivity and selectivity, high signal throughput, and reproducibility through various detection approaches such as Raman, colorimetric, biological, chemical, and electrical sensors. We obtain that the development of microfluidic and lab-on-a-chip (LoC) technologies offers the opportunity to create on-site portable and smart biodevices and chips for real-time monitoring of plant diseases. The last part of this work is a brief introduction to trends in nanotechnology for harvesting and packaging to provide insights into the overall applications of nanotechnology for crop production quality. This review provides the current advent of nanotechnology in agriculture, which is essential for further studies examining novel applications for sustainable agriculture.

Pathogen Discovery in the Post-COVID Era

Pathogen discovery plays a crucial role in the fields of infectious diseases, clinical microbiology, and public health. During the past four years, the global response to the COVID-19 pandemic highlighted the importance of early and accurate identification of novel pathogens for effective management and prevention of outbreaks. The post-COVID era has ushered in a new phase of infectious disease research, marked by accelerated advancements in pathogen discovery. This review encapsulates the recent innovations and paradigm shifts that have reshaped the landscape of pathogen discovery in response to the COVID-19 pandemic. Primarily, we summarize the latest technology innovations, applications, and causation proving strategies that enable rapid and accurate pathogen discovery for both acute and historical infections. We also explored the significance and the latest trends and approaches being employed for effective implementation of pathogen discovery from various clinical and environmental samples. Furthermore, we emphasize the collaborative nature of the pandemic response, which has led to the establishment of global networks for pathogen discovery.

Recent advances of microneedles biosensors for plants

As the lack of plants can affect the energy operation of the entire ecosystem, monitoring and improving the health status of plants is crucial. However, ordinary biosensing platforms lack accuracy and timeliness in monitoring plant growth status. In addition, the prevention and control of plant diseases often involve spraying and administering drugs, which is inefficient and prone to pollution. Microneedles have unique dimensions and shapes, and they have significant advantages as biosensors in the fields of sensing, detection, and drug delivery. Recent evidence suggests that microneedle biosensors can become effective tools for plant diagnosis and treatment. In this review, the comprehensive development of the application of microneedle biosensors in the field of plants is introduced, as well as their manufacturing processes and sensing and detection functions. Furthermore, the application of microneedle biosensors in this field is discussed, and future development directions are proposed.

Aptamer-based technology for detecting Bacillus subtilis in soil

The uncertainty associated with the impact of a bioinoculant on soil microbial community and, as a consequence, on soil quality, as well as the need to define its persistence, has prompted the demand for an accurate detection and tracking of the presence and the quantification of a target microbial inoculant in soil. Although DNA or RNA-based molecular detection are well established and commonly applied in this regard, alternative ligands such as DNA-aptamers have several advantages over them, such as low cost, ease of modification, ease of immobilisation on lab-on-chip or nanosensors, high stability and not thermolability. In this study, we used a toggle-cell SELEX method to isolate, select and characterise ssDNA (single-strand DNA) aptamers to detect a Bacillus subtilis strain which is being tested as a plant growth promoting rhizobacteria (PGPR) formulation. Two ssDNA aptamers (patenting application n.102022000022590) showed strong affinity and specificity for B. subtilis strains, with values of the kinetic parameters Kd (dissociation constant) in the nanomolar range and Bmax (maximum intensity of binding) around 1. Validation of the suitability of the aptamers was validated on three inoculated soils characterised by different chemical-physical features and in soil from a field trial with the formulated B. subtilis PCM/B 00105 strain. These are considered significant features to monitor B. subtilis strains in soil, practical to optimise bioinoculant application methods, support regulatory processes and foster the shift of agricultural production toward more sustainable cropping systems. KEY POINTS: • First DNA aptamers binding a B. subtilis strain included in a bioinoculum formulation. • First DNA aptamer binding B. subtilis in soil. • Aptamer may be a method for microbial inoculant detection in soil.

The Imperative Use of Bacillus Consortium and Quercetin Contributes to Suppress Fusarium Wilt Disease by Direct Antagonism and Induced Resistance

Fusarium wilt diseases severely influence the growth and productivity of numerous crop plants. The consortium of antagonistic rhizospheric Bacillus strains and quercetin were evaluated imperatively as a possible remedy to effectively manage the Fusarium wilt disease of tomato plants. The selection of Bacillus strains was made based on in-vitro antagonistic bioassays against Fusarium oxysporum f.sp. lycoprsici (FOL). Quercetin was selected after screening a library of phytochemicals during in-silico molecular docking analysis using tomato LysM receptor kinases "SILKY12" based on its dual role in symbiosis and plant defense responses. After the selection of test materials, pot trials were conducted where tomato plants were provided consortium of Bacillus strains as soil drenching and quercetin as a foliar spray in different concentrations. The combined application of consortium (Bacillus velezensis strain BS6, Bacillus thuringiensis strain BS7, Bacillus fortis strain BS9) and quercetin (1.0 mM) reduced the Fusarium wilt disease index up to 69%, also resulting in increased plant growth attributes. Likewise, the imperative application of the Bacillus consortium and quercetin (1.0 mM) significantly increased total phenolic contents and activities of the enzymes of the phenylpropanoid pathway. Non-targeted metabolomics analysis was performed to investigate the perturbation in metabolites. FOL pathogen negatively affected a range of metabolites including carbohydrates, amino acids, phenylpropanoids, and organic acids. Thereinto, combined treatment of Bacillus consortium and quercetin (1.0 mM) ameliorated the production of different metabolites in tomato plants. These findings prove the imperative use of Bacillus consortium and quercetin as an effective and sustainable remedy to manage Fusarium wilt disease of tomato plants and to promote the growth of tomato plants under pathogen stress conditions.

Quadruplex and q-PCR based diagnostic assay to delineate the major quarantine and other seed-borne fungal pathogens of soybean

Soybean is one of the most important crops grown worldwide and accounting for significant global trade including transgenic soybean. The crop is attacked by several seed-borne fungal pathogens and some of them are of quarantine concern for India. Keeping in view of the risks associated with movement of soybean seeds, sensitive and reliable molecular diagnostics have been developed for precise and simultaneous detection of three pathogens of quarantine concern for India namely, Diaporthe phaseolorum (stem blight), D. longicolla (seed decay), Peronospora manshurica (downy mildew), along with Macrophomina phaseolina causing dry root rot. The targeted pathogens after isolation from imported transgenic and non-transgenic soybean seeds were identified. Quadruplex and qPCR assays were developed targeting the sequences of different genes such as Histone-3 for detection of D. longicolla and M. phaseolina. The markers DlHisF2&R2 and MpHisF1&R1 produced 265 and 309 bp amplicons for D. longicolla and M. phaseolina, respectively. Actin gene based marker DpActF1&R2 was developed for D. phaseolorum which provided 113 bp amplicon whereas, COX2 based marker PmCoxF2&R2 was developed for P. manshurica with amplified product of 152 bp. During qPCR analysis, these markers proved highly specific and sensitive for detection of these pathogens up to 0.1 pg of template DNA. Quadruplex PCR protocol was also developed by combining these specific markers which could distinguish all the targeted pathogens simultaneously in a single reaction. The developed diagnostic protocols are extremely valuable for quarantine clearance and to ensure the safe transboundary exchange and healthy conservation of germplasm in the National Genebank.