Produced by the International Association for the Plant Protection Sciences (IAPPS). To join IAPPS and receive the Crop Protection journal online go to: www.plantprotection.org
The 2024 Fungal Pathogen Genomics workshop will take place 2-7 June 2024 in Hinxton, UK. This immersive week-long training is sponsored by the Wellcome Trust Advanced Courses Program, offering experimental biologists and geneticists working with fungal and oomycete species practical training in genomic-scale data analysis using web-based data-mining resources including FungiDB, Ensembl Fungi, SGD/CGD and MycoCosm.
Training includes lectures, hands-on exercises, group projects, and seminars featuring distinguished guest speakers. Throughout the course, attendees will acquire expertise in data mining and analysis using tools provided by various fungal informatics resources. Highlights include:
– learning to access, assess, and integrate information on gene structure, epigenetics, expression, function, population diversity, comparative genomics, etc, carrying out in silico experiments on hundreds of supported fungal/oomycete taxa
– conducting RNA-Seq and SNP analysis and visualization of your own (or any publicly available) data using the VEuPathDB Galaxy workspace
– identifying secondary metabolite clusters in MycoCosm
– discovering virulence genes and annotations in Ensembl Fungi/PHI-Base
– accessing genetic interactions in CGD/SGD
– contributing your insights on specific genes (or lists of genes) via User Comments or manual genome curation in Apollo
– identifying gene (sets) of interest for analysis of GO term or pathway enrichment, further analysis using other informatics resources, or experimental analysis in the lab/field
Don’t miss this opportunity to enhance your skills in pathogen genomics! If you – or others in your group are interested – further information and application materials are available at:
Note that the application deadline of 29 February 2024 is fast approaching. Applications are accepted from anywhere in the world; the Trust covers all local expenses, and limited bursary support for travel may be available for selected applicants who would not otherwise be able to attend the workshop.
Yours in science — Eve Basenko, Nishadi de Silva & David S Roos … on behalf of all workshop organizers and instructors
John Leslie
For more information contact: John Leslie <jfl@KSU.EDU>
A novel pathogenic fungus causing leaf spot disease in Arctic plants was reported on Ellesmere Island. Although there are a few reports on plant pathogens in Arctic ecosystems, this study showed that even in the Arctic, the regional location and the host species-level differences drive pathogenic diversity. Credit: University of Tsukuba
Ellesmere Island (76°N–83°N) is one of the northernmost islands in the world, along with Greenland and Spitsbergen Island. More than 100 species of vascular plants are distributed across this island in the ice-free areas in summer. However, there has been little research on fungal diseases in these plants.
In this new study published in Forest Pathology, a researcher at the University of Tsukuba discovered a pathogenic fungus that forms a unique black stroma (reproductive organs of fungi, such as mushrooms) on the leaves of the Arctic willow, which is a dominant plant on the island.
The morphological characteristics of fungus were different from those of any related species discovered as yet in terms of the key points for species identification, namely, the size of the spores and shape of stroma. Molecular phylogenetic analysis also supports the uniqueness of this specimen, and it has been described as a novel species of fungus of the genus Rhytisma.
This study has shown that even in the Arctic, the regional location and the host species–level differences drive the diversity of the pathogens. Further data on Rhytisma spp. from other regions in the Arctic will help researchers understand how they spread across the Arctic region with their hosts and how they survived in the tundra ecosystem.
More information: Shota Masumoto, The northernmost plant pathogenic fungus, Rhytisma arcticum sp. nov.: Morphological and molecular characterization of a novel species from Ellesmere Island, Canada, Forest Pathology (2023). DOI: 10.1111/efp.12818
Fusarium head blight, commonly called scab disease, is a highly destructive wheat disease that leads to substantial yield loss and contamination of wheat grain with deoxynivalenol.
Jessica Rutkoksi, pictured, is part of a University of Illinois team using cell phone images and AI to detect fungal toxins in wheat kernels. The goal is to quickly identify wheat lines with lower susceptibility to the fungus, making it easier to breed for disease resistance in the crop. Image Credit: University of Illinois College of ACES
Deoxynivalenol (DON) is a mycotoxin that can cause adverse health effects in humans and animals. Phenotyping for Fusarium-damaged kernels (FDKs) provides an accurate assessment of resistance to accumulation of DON; however, it is a time-consuming and subjective process.
A study published in The Plant Phenome Journal implemented sophisticated object recognition technology for filtering out DON-contaminated wheat kernels from the food supply chain and to assist scientists in developing wheat that has stronger resistance to FHB.
Fusarium Head Blight – A Significant Threat to Wheat
Fusarium head blight (FHB) is a serious disease for wheat, causing billions of dollars of losses in crops to date. FHB causes deoxynivalenol buildup in wheat grains. DON is a mycotoxin belonging to the trichothecene family of vomitoxins. FHB is of great concern since DON ingestion in people and animals from infected wheat end products has detrimental effects on health.
In humans, DON consumption may cause nausea, headaches, vomiting, and diarrhea. The adverse health consequences of DON consumption differ amongst animals, but most typically result in weight loss, nutritional deficiencies, and immunological deficiencies.
Detecting Fusarium-Damaged Kernels Using AI
FDK is a well-established visual grain damage caused by Fusarium, which is observed post-harvest. It is used as a ‘proxy’ phenotype to indirectly select for resistance to DON accumulation within the grain.
Robotics & Automation eBook
Compilation of the top interviews, articles, and news in the last year.
The team developed a simple and user-friendly method to identify FDKs by training a convolutional neural network (CNN) model on images of healthy and infected wheat kernels.
The images were taken with a smartphone and uploaded to the app, which then used the trained CNN model to determine the percentage of infected kernels. The model achieved an accuracy of around 90% in detecting FDKs in wheat, which was comparable to manual FDK counting.
While alternative techniques for quantifying DON levels in wheat grain samples exist, they entail lab-intensive tests like mass spectrometry (MS) and enzyme-linked immunosorbent tests, which can be costly and time-consuming.
The CNN model used in the study was trained on numerous images of wheat kernels taken with a smartphone, half of which were healthy, and the other half were infected with Fusarium graminearum.
The model was then used to classify new images of kernels as healthy or infected. The researchers tested the model on additional images of wheat kernels, achieving a high accuracy in detecting FDKs in wheat.
Girish Chowdhary, an author of the study, remarked on the novelty of their research, “One of the unique things about this advance is that we trained our network to detect minutely damaged kernels with good enough accuracy using just a few images. We made this possible through meticulous pre-processing of data, transfer learning, and bootstrapping of labeling activities.”
Potential Applications
According to the researchers, the mobile app has the potential to make the process of phenotyping for FDKs more accessible and affordable, especially in developing countries where laboratory assays are not readily available.
It can also be used in the field to identify infected wheat kernels, enabling farmers to monitor FHB in real time and take necessary measures to minimize yield loss and mycotoxin contamination.
The app can also help researchers and industries to screen large numbers of wheat varieties for resistance to FHB and DON accumulation.
The CNN model can be fine-tuned to identify specific resistance mechanisms and to develop wheat varieties that are resistant to FHB and have low DON levels, thus contributing to global food safety and security.
Fusarium head blight remains one of the most destructive diseases in wheat, resulting in significant yield losses and the contamination of wheat grain with deoxynivalenol.
Phenotyping for Fusarium-damaged kernels is a critical component of identifying resistance to DON accumulation in wheat, but manual phenotyping can be time-consuming.
This study has developed and tested an open-access and easy-to-use method for the phenotyping of FDKs using a convolutional neural network trained on cell phone images.
The method achieved an accuracy of around 90% when tested on a separate dataset, demonstrating its potential to greatly improve the efficiency and accuracy of FDK phenotyping.
Future research in this area could focus on further refining the CNN model, as well as combining this method with other technologies to develop a more comprehensive system for monitoring crop health and identifying disease outbreaks.
Reference
Wu, J., Ackerman, A., Gaire, R., Chowdhary, G., & Rutkoski, J. (2023). A neural network for phenotyping Fusarium-damaged kernels (FDKs) in wheat and its impact on genomic selection accuracy. The Plant Phenome Journal, 6(1). https://doi.org/10.1002/ppj2.20065
Source:
Disclaimer: The views expressed here are those of the author expressed in their private capacity and do not necessarily represent the views of AZoM.com Limited T/A AZoNetwork the owner and operator of this website. This disclaimer forms part of the Terms and conditions of use of this website.
Shaheer is a graduate of Aerospace Engineering from the Institute of Space Technology, Islamabad. He has carried out research on a wide range of subjects including Aerospace Instruments and Sensors, Computational Dynamics, Aerospace Structures and Materials, Optimization Techniques, Robotics, and Clean Energy. He has been working as a freelance consultant in Aerospace Engineering for the past year. Technical Writing has always been a strong suit of Shaheer’s. He has excelled at whatever he has attempted, from winning accolades on the international stage in match competitions to winning local writing competitions. Shaheer loves cars. From following Formula 1 and reading up on automotive journalism to racing in go-karts himself, his life revolves around cars. He is passionate about his sports and makes sure to always spare time for them. Squash, football, cricket, tennis, and racing are the hobbies he loves to spend his time in.
How do plants defend themselves against pathogenic micro-organisms? This is a complex puzzle, of which a team of biologists from the University of Amsterdam has solved a new piece. The team, led by Harrold van den Burg, discovered that while the water pores (hydathodes) in leaves provide an entry point for bacteria, they are also an active part of the defence against these invaders. Their research has now been published in the journal Current Biology.
Anyone who is used to giving plants plenty of water might know the phenomenon: small droplets of plant sap that sometimes appear at the edge of the leaves. Especially at night times. When plants take up more water via their roots than they lose through evaporation, they can use their water pores on the leaf margins to release excess water. The pores literally prevent root water pressure from becoming too high. An important mechanism – but at the same time, risky. Pathogenic microorganisms can enter the plant’s veins through these sap droplets to colonize the water pores.
Biologists have therefore been asking themselves for a long time: how do plants defend themselves against this wide-open entry point? Are those water pores—the scientific name is hydathodes— defenceless glands that allow ample entry of harmful pests? Or have they evolved in such a way that they are part of the plant’s line of defence against pathogens?
Line of defence
A team of researchers from the Swammerdam Institute for Life Sciences at the University of Amsterdam has found evidence that the latter is the case. In the journal Current Biology they describe their experiments with the model plant Arabidopsis and two types of harmful bacteria. Arabidopsis, or thale cress, is related to all types of cabbage and other edible plants in the Brassicaceae family. The biologists discovered that the water pores are part of both the plant’s first and second line of defence against bacteria. In other words, they are involved in both the rapid initial response and the follow-up actions against the invaders.
Harrold van den Burg, who led the team of researchers, explains: ‘For this study, we used Arabidopsis mutants with deficits in their immune system that made them more susceptible to infection with the bacteria Xanthomonas campestris and Pseudomonas syringae. We selected these bacteria because they cause notorious problems in agriculture. Here they were used to help unravel the plant immune system. We were able to establish that two protein complexes (for those interested: BAK1 and EDS1-PAD4-ADR1) prevent the bacteria from multiplying in the water pores. The same immune responses also prevent these bacteria from advancing further into the plant interior. In addition, we discovered that when this first line of defence occurs, the water pores produce a signal that causes the plant to produce hormones that suppress further spread of the invading bacteria along the vascular system.’
Make agricultural crops more resilient
The team thus provides an important fundamental insight into how these natural entry points for bacteria have evolved and are protected by the plant’s immune system. In the long term, this may help to make agricultural crops more resistant to bacterial diseases.
Van den Burg: For now we will continue with this line of research. For example, we now know which protein complexes are involved in preventing bacteria from multiplying in the water pores, but not how this happens. Do they for instance regulate the production of antimicrobial substances in hydathodes that inhibit bacterial growth? That would be interesting to know. The better we understand this, the closer we get to a practical application for better protection of agricultural crops.’
Details of the publication:
Misha Paauw, Marieke van Hulten, Sayantani Chatterjee, Jeroen A. Berg, Nanne W. Taks, Marcel Giesbers, Manon M. S. Richard, and Harrold A. van den Burg: Hydathode immunity protects the Arabidopsis leaf vasculature against colonization by bacterial pathogens, in: Current Biology, 1 February 2023.
INSIGHTS INTO PATHOGEN-HOST INTERACTION OFFER A CLUE TO PROTECTING CROPS FROM BLAST
Insights into pathogen-host interaction offer a clue to protecting crops from blast
20th October 2022
A mechanism used by a fungal pathogen to promote spread of the devastating cereal crop disease, blast, has been revealed in fine detail.
The Banfield group at the John Innes Centre, in collaboration with the Iwate Biotechnology Research Centre in Japan and The Sainsbury Laboratory in Norwich describes how an effector protein (AVR-Pii) used by the blast fungus Maganaporthe oryzae binds with the rice host receptor protein Exo70.
Using protein structure analysis, the study reveals a tight binding mechanism in which a significant proportion of the effector surface is involved in the interaction with the host target.
In revealing the structure of AVR-Pii, the research group have also shown that this effector belongs to a new protein family in the blast pathogen, termed “Zifs”, as they are based on a Zinc-finger motif.
“We have identified a new family of Zif effectors, a finding which has implications for understanding the molecular mechanisms of blast disease. These proteins could be useful in our quest to engineer new disease resistance properties against blast,” said Professor Mark Banfield a group leader at the John Innes and corresponding author of the study.
Previously, all effector structures in the blast pathogen were from a family known as the MAX fold. The team hypothesised that AVR-Pii would not be a MAX effector, and speculated the research could discover a novel protein family.
This AVR-Pii – Exo70 interaction was already known to support disease resistance in rice plants expressing the NLR immune receptor protein pair Pii. But how the interaction underpinned resistance was unknown.
Future research will explore how the association between AVR-Pii and Exo70 leads to immune recognition by the NLR receptor. NLR receptors belong to a family of proteins that enable plants to sense the presence of pathogen effector molecules and mount an immune response to resist disease.
Plant diseases destroy up to 30% of annual crop production, contributing to global food insecurity, and blast is a major disease of cereal crops.
Discovering how pathogens target plant hosts to promote virulence is essential if we are to understand how diseases develop, in addition to engineering immunity.
“A blast fungus zinc-finger fold effector binds to a hydrophobic pocket in host Exo70 proteins to modulate immune recognition in rice”, appears in PNAS (Proceedings of the National Academy of Sciences).
Global Plant Protection News 