Biocontrol Potential of Aspergillus Species Producing Antimicrobial Metabolites

Microbial metabolites have been recognized as an important source for the discovery of new antifungal agents because of their diverse chemical structures with novel modes of action. In the course of our screening for new antifungal agents from microbes, we found that culture filtrates of two fungal species Aspergillus candidus SFC20200425-M11 and Aspergillus montenegroi SFC20200425-M27 have the potentials to reduce the development of fungal plant diseases such as tomato late blight and wheat leaf rust. From these two Aspergillus spp., we isolated a total of seven active compounds, including two new compounds (4 and 6), and identified their chemical structures based on the NMR spectral analyses: sphaeropsidin A (1), (R)-formosusin A (2), (R)-variotin (3), candidusin (4), asperlin (5), montenegrol (6), and protulactone A (7). Based on the results of the in vitro bioassays of 11 plant pathogenic fungi and bacteria, sphaeropsidin A (1), (R)-formosusin A (2), (R)-variotin (3), and asperlin (5) exhibited a wide range of antimicrobial activity. Furthermore, when plants were treated with sphaeropsidin A (1) and (R)-formosusin A (2) at a concentration of 500 μg/ml, sphaeropsidin A (1) exhibited an efficacy disease control value of 96 and 90% compared to non-treated control against tomato late blight and wheat leaf rust, and (R)-formosusin A (2) strongly reduced the development of tomato gray mold by 82%. Asperlin (5) at a concentration of 500 μg/ml effectively controlled the development of tomato late blight and wheat leaf rust with a disease control value of 95%. Given that culture filtrates and active compounds derived from two Aspergillus spp. exhibited disease control efficacies, our results suggest that the Aspergillus-produced antifungal compounds could be useful for the development of new natural fungicides.

A Chromosome-Scale Assembly of the Wheat Leaf Rust Pathogen Puccinia triticina Provides Insights Into Structural Variations and Genetic Relationships With Haplotype Resolution

Despite the global economic importance of the wheat leaf rust pathogen Puccinia triticina (Pt), genomic resources for Pt are limited and chromosome-level assemblies of Pt are lacking. Here, we present a complete haplotype-resolved genome assembly at a chromosome-scale for Pt using the Australian pathotype 64-(6),(7),(10),11 (Pt64; North American race LBBQB) built upon the newly developed technologies of PacBio and Hi-C sequencing. PacBio reads with ∼200-fold coverage (29.8 Gb data) were assembled by Falcon and Falcon-unzip and subsequently scaffolded with Hi-C data using Falcon-phase and Proximo. This approach allowed us to construct 18 chromosome pseudomolecules ranging from 3.5 to 12.3 Mb in size for each haplotype of the dikaryotic genome of Pt64. Each haplotype had a total length of ∼147 Mb, scaffold N50 of ∼9.4 Mb, and was ∼93% complete for BUSCOs. Each haplotype had ∼29,800 predicted genes, of which ∼2,000 were predicted as secreted proteins (SPs). The investigation of structural variants (SVs) between haplotypes A and B revealed that 10% of the total genome was spanned by SVs, highlighting variations previously undetected by short-read based assemblies. For the first time, the mating type (MAT) genes on each haplotype of Pt64 were identified, which showed that MAT loci a and b are located on two chromosomes (chromosomes 7 and 14), representing a tetrapolar type. Furthermore, the Pt64 assembly enabled haplotype-based evolutionary analyses for 21 Australian Pt isolates, which highlighted the importance of a haplotype resolved reference when inferring genetic relationships using whole genome SNPs. This Pt64 assembly at chromosome-scale with full phase information provides an invaluable resource for genomic and evolutionary research, which will accelerate the understanding of molecular mechanisms underlying Pt-wheat interactions and facilitate the development of durable resistance to leaf rust in wheat and sustainable control of rust disease.

A Probabilistic Bio-Economic Assessment of the Global Consequences of Wheat Leaf Rust

This study provides a bio-economic assessment of the global climate suitability and probabilistic crop-loss estimates attributable to wheat leaf rust. We draw on a purpose-built, spatially explicit, ecoclimatic suitability model for wheat leaf rust to estimate that 94.4% of global wheat production is vulnerable to the disease. To reflect the spatiotemporal variation in leaf rust losses, we used a probabilistic approach to estimate a representative rust loss distribution based on long-term, state-level annual U.S. loss estimates. Applying variants of this representative loss distribution to selected wheat production areas in 15 epidemiological zones throughout the world, we project global annual average losses of 8.6 million metric tons of grain for the period 2000 to 2050 based on a conservative, baseline scenario, and 18.3 million metric tons based on a high-loss scenario; equivalent to economic losses ranging from $1.5 to $3.3 billion per year (2016 U.S. prices). Even the more conservative baseline estimate implies that a sustained, worldwide investment of $50.5 million per year in leaf rust research is economically justified.

Monitoring Wheat Leaf Rust and Stripe Rust in Winter Wheat Using High-Resolution UAV-Based Red-Green-Blue Imagery

During the past decade, imagery data acquired from unmanned aerial vehicles (UAVs), thanks to their high spatial, spectral, and temporal resolutions, have attracted increasing attention for discriminating healthy from diseased plants and monitoring the progress of such plant diseases in fields. Despite the well-documented usage of UAV-based hyperspectral remote sensing for discriminating healthy and diseased plant areas, employing red-green-blue (RGB) imagery for a similar purpose has yet to be fully investigated. This study aims at evaluating UAV-based RGB imagery to discriminate healthy plants from those infected by stripe and wheat leaf rusts in winter wheat (Triticum aestivum L.), with a focus on implementing an expert system to assist growers in improved disease management. RGB images were acquired at four representative wheat-producing sites in the Grand Duchy of Luxembourg. Diseased leaf areas were determined based on the digital numbers (DNs) of green and red spectral bands for wheat stripe rust (WSR), and the combination of DNs of green, red, and blue spectral bands for wheat leaf rust (WLR). WSR and WLR caused alterations in the typical reflectance spectra of wheat plants between the green and red spectral channels. Overall, good agreements between UAV-based estimates and observations were found for canopy cover, WSR, and WLR severities, with statistically significant correlations (p-value (Kendall) < 0.0001). Correlation coefficients were 0.92, 0.96, and 0.86 for WSR severity, WLR severity, and canopy cover, respectively. While the estimation of canopy cover was most often less accurate (correlation coefficients < 0.20), WSR and WLR infected leaf areas were identified satisfactorily using the RGB imagery-derived indices during the critical period (i.e., stem elongation and booting stages) for efficacious fungicide application, while disease severities were also quantified accurately over the same period. Using such a UAV-based RGB imagery method for monitoring fungal foliar diseases throughout the cropping season can help to identify any new disease outbreak and efficaciously control its spread.

Transcriptome Analysis Based on Lr19-Virulent Mutants Strain Provides Clues for the Pathogenicity-Related Genes and Effectors of Puccinia Triticina

Background: Wheat leaf rust caused by Puccinia triticina (Pt) remains one of the most destructive diseases of common wheat worldwide. Cultivating resistant cultivars is an effective way to control this disease, but race-specific resistance can be overcome quickly due to the rapid evolution of Pt populations. The critical to control wheat leaf rust is to understand the pathogenicity mechanisms of Pt. Results: In this study, the spores of the Pt race PHNT (wheat leaf rust resistance gene Lr19-avirulent isolate) were mutagenized with ethyl methanesulfonate (EMS) and two Pt Lr19-virulent mutants named M1 and M2 were isolated, suggesting that they carry mutations affecting the Lr19-specific avirulent factor. RNA sequencing was performed on samples collected from the wheat cultivars Chinese Spring and TcLr19 that were infected by wild-type (WT) PHNT and the two Lr19-virulent mutant isolates at 14 days post-inoculation (dpi). The assembled transcriptome data were compared to the reference genome “Pt 1-1 BBBD Race 1.” A total of 216 differentially expressed genes (DEGs) were found from three different sample comparisons including M1-vs-WT, M2-vs-WT, and M1-vs-M2. Of these DEGs, 29 common DEGs were shared between M1-vs-WT and M2-vs-WT comparisons. Among the 216 DEGs encoding proteins, 30 were predicted to be effector candidates. Then 6 effector candidates (PTTG_27844, PTTG_05290, PTTG_27401, PTTG_27224, PTTG_26282, PTTG_25521) were verified that these genes were differentially expressed during Pt infection by quantitative real-time PCR (qRT-PCR) and were validated on tobacco, and the results showed that PTTG_27401 could inhibit progress of cell death (PCD) induced by BAX.Conclusions: Our results showed that a large number of genes participate in the interaction between Pt and TcLr19, which will provide valuable resources for the identification and targeting of AvrLr19 effector candidates and pathogenesis-related genes. Furthermore, our analyses are of great significance to reveal the pathogenesis of Pt.