The genome assembly of the fungal pathogen Pyrenochaeta lycopersici from Single-Molecule Real-Time sequencing sheds new light on its biological complexity

How do emerging long-read sequencing technologies function in transforming the plant pathology research landscape?

Long-read sequencing technologies are revolutionizing the sequencing and analysis of plant and pathogen genomes and transcriptomes, as well as contributing to emerging areas of interest in plant-pathogen interactions, disease management techniques, and the introduction of new plant varieties or cultivars. Long-read sequencing (LRS) technologies are progressively being implemented to study plants and pathogens of agricultural importance, which have substantial economic effects. The variability and complexity of the genome and transcriptome affect plant growth, development and pathogen responses. Overcoming the limitations of second-generation sequencing, LRS technology has significantly increased the length of a single contiguous read from a few hundred to millions of base pairs. Because of the longer read lengths, new analysis methods and tools have been developed for plant and pathogen genomics and transcriptomics. LRS technologies enable faster, more efficient, and high-throughput ultralong reads, allowing direct sequencing of genomes that would be impossible or difficult to investigate using short-read sequencing approaches. These benefits include genome assembly in repetitive areas, creating more comprehensive and exact genome determinations, assembling full-length transcripts, and detecting DNA and RNA alterations. Furthermore, these technologies allow for the identification of transcriptome diversity, significant structural variation analysis, and direct epigenetic mark detection in plant and pathogen genomic regions. LRS in plant pathology is found efficient for identifying and characterization of effectors in plants as well as known and unknown plant pathogens. In this review, we investigate how these technologies are transforming the landscape of determination and characterization of plant and pathogen genomes and transcriptomes efficiently and accurately. Moreover, we highlight potential areas of interest offered by LRS technologies for future study into plant-pathogen interactions, disease control strategies, and the development of new plant varieties or cultivars.

New-Generation Sequencing Technology in Diagnosis of Fungal Plant Pathogens: A Dream Comes True?

The fast and continued progress of high-throughput sequencing (HTS) and the drastic reduction of its costs have boosted new and unpredictable developments in the field of plant pathology. The cost of whole-genome sequencing, which, until few years ago, was prohibitive for many projects, is now so affordable that a new branch, phylogenomics, is being developed. Fungal taxonomy is being deeply influenced by genome comparison, too. It is now easier to discover new genes as potential targets for an accurate diagnosis of new or emerging pathogens, notably those of quarantine concern. Similarly, with the development of metabarcoding and metagenomics techniques, it is now possible to unravel complex diseases or answer crucial questions, such as "What's in my soil?", to a good approximation, including fungi, bacteria, nematodes, etc. The new technologies allow to redraw the approach for disease control strategies considering the pathogens within their environment and deciphering the complex interactions between microorganisms and the cultivated crops. This kind of analysis usually generates big data that need sophisticated bioinformatic tools (machine learning, artificial intelligence) for their management. Herein, examples of the use of new technologies for research in fungal diversity and diagnosis of some fungal pathogens are reported.

Structured Framework and Genome Analysis of Magnaporthe grisea Inciting Pearl Millet Blast Disease Reveals Versatile Metabolic Pathways, Protein Families, and Virulence Factors

Magnaporthe grisea (T.T. Herbert) M.E. Barr is a major fungal phytopathogen that causes blast disease in cereals, resulting in economic losses worldwide. An in-depth understanding of the basis of virulence and ecological adaptation of M. grisea is vital for devising effective disease management strategies. Here, we aimed to determine the genomic basis of the pathogenicity and underlying biochemical pathways in Magnaporthe using the genome sequence of a pearl millet-infecting M. grisea PMg_Dl generated by dual NGS techniques, Illumina NextSeq 500 and PacBio RS II. The short and long nucleotide reads could be draft assembled in 341 contigs and showed a genome size of 47.89 Mb with the N50 value of 765.4 Kb. Magnaporthe grisea PMg_Dl showed an average nucleotide identity (ANI) of 86% and 98% with M. oryzae and Pyricularia pennisetigena, respectively. The gene-calling method revealed a total of 10,218 genes and 10,184 protein-coding sequences in the genome of PMg_Dl. InterProScan of predicted protein showed a distinct 3637 protein families and 695 superfamilies in the PMg_Dl genome. In silico virulence analysis revealed the presence of 51VFs and 539 CAZymes in the genome. The genomic regions for the biosynthesis of cellulolytic endo-glucanase and beta-glucosidase, as well as pectinolytic endo-polygalacturonase, pectin-esterase, and pectate-lyases (pectinolytic) were detected. Signaling pathways modulated by MAPK, PI3K-Akt, AMPK, and mTOR were also deciphered. Multicopy sequences suggestive of transposable elements such as Type LTR, LTR/Copia, LTR/Gypsy, DNA/TcMar-Fot1, and Type LINE were recorded. The genomic resource presented here will be of use in the development of molecular marker and diagnosis, population genetics, disease management, and molecular taxonomy, and also provide a genomic reference for ascomycetous genome investigations in the future.

Genomic Variations and Mutational Events Associated with Plant-Pathogen Interactions

Simple Summary

Plants, unlike animals, do not have defender cells or an adaptive immune system. Instead, plants rely on each cell’s innate immunity and systemic signals emitted from infection sites. On the other hand, not all plants, even within the same species, are genetically identical, and their genetic backgrounds determine how well they respond to stress factors. Through evolution, plants have acquired various defense mechanisms that play important roles in the never-ending fight between plants and pathogens. Genetic variation in relation to plant disease resistance can thus be contextualized to provide new insights into these defense mechanisms and evolutionary processes that lead to resistance to pathogens. By focusing on genetic variations and mutational events linked with plant–pathogen interactions, the paper explores how genome compartments facilitate plant and pathogen evolutionary processes.

Abstract

Phytopathologists are actively researching the molecular basis of plant–pathogen interactions. The mechanisms of responses to pathogens have been studied extensively in model crop plant species and natural populations. Today, with the rapid expansion of genomic technologies such as DNA sequencing, transcriptomics, proteomics, and metabolomics, as well as the development of new methods and protocols, data analysis, and bioinformatics, it is now possible to assess the role of genetic variation in plant–microbe interactions and to understand the underlying molecular mechanisms of plant defense and microbe pathogenicity with ever-greater resolution and accuracy. Genetic variation is an important force in evolution that enables organisms to survive in stressful environments. Moreover, understanding the role of genetic variation and mutational events is essential for crop breeders to produce improved cultivars. This review focuses on genetic variations and mutational events associated with plant–pathogen interactions and discusses how these genome compartments enhance plants’ and pathogens’ evolutionary processes.

Genome Analysis of the Broad Host Range Necrotroph Nalanthamala psidii Highlights Genes Associated With Virulence

Guava wilt disease is caused by the fungus Nalanthamala psidii. The wilt disease results in large-scale destruction of orchards in South Africa, Taiwan, and several Southeast Asian countries. De novo assembly, annotation, and in-depth analysis of the N. psidii genome were carried out to facilitate the identification of characteristics associated with pathogenicity and pathogen evolution. The predicted secretome revealed a range of CAZymes, proteases, lipases and peroxidases associated with plant cell wall degradation, nutrient acquisition, and disease development. Further analysis of the N. psidii carbohydrate-active enzyme profile exposed the broad-spectrum necrotrophic lifestyle of the pathogen, which was corroborated by the identification of putative effectors and secondary metabolites with the potential to induce tissue necrosis and cell surface-dependent immune responses. Putative regulatory proteins including transcription factors and kinases were identified in addition to transporters potentially involved in the secretion of secondary metabolites. Transporters identified included important ABC and MFS transporters involved in the efflux of fungicides. Analysis of the repetitive landscape and the detection of mechanisms linked to reproduction such as het and mating genes rendered insights into the biological complexity and evolutionary potential of N. psidii as guava pathogen. Hence, the assembly and annotation of the N. psidii genome provided a valuable platform to explore the pathogenic potential and necrotrophic lifestyle of the guava wilt pathogen.

Fungal Genomics in Respiratory Medicine: What, How and When?

Respiratory infections caused by fungal pathogens present a growing global health concern and are a major cause of death in immunocompromised patients. Worryingly, coronavirus disease-19 (COVID-19) resulting in acute respiratory distress syndrome has been shown to predispose some patients to airborne fungal co-infections. These include secondary pulmonary aspergillosis and mucormycosis. Aspergillosis is most commonly caused by the fungal pathogen Aspergillus fumigatus and primarily treated using the triazole drug group, however in recent years, this fungus has been rapidly gaining resistance against these antifungals. This is of serious clinical concern as multi-azole resistant forms of aspergillosis have a higher risk of mortality when compared against azole-susceptible infections. With the increasing numbers of COVID-19 and other classes of immunocompromised patients, early diagnosis of fungal infections is critical to ensuring patient survival. However, time-limited diagnosis is difficult to achieve with current culture-based methods. Advances within fungal genomics have enabled molecular diagnostic methods to become a fast, reproducible, and cost-effective alternative for diagnosis of respiratory fungal pathogens and detection of antifungal resistance. Here, we describe what techniques are currently available within molecular diagnostics, how they work and when they have been used.

Application of an optimized annotation pipeline to the Cryptococcus deuterogattii genome reveals dynamic primary metabolic gene clusters and genomic impact of RNAi loss

Evaluating the quality of a de novo annotation of a complex fungal genome based on RNA-seq data remains a challenge. In this study, we sequentially optimized a Cufflinks-CodingQuary-based bioinformatics pipeline fed with RNA-seq data using the manually annotated model pathogenic yeasts Cryptococcus neoformans and Cryptococcus deneoformans as test cases. Our results show that the quality of the annotation is sensitive to the quantity of RNA-seq data used and that the best quality is obtained with 5–10 million reads per RNA-seq replicate. We also showed that the number of introns predicted is an excellent a priori indicator of the quality of the final de novo annotation. We then used this pipeline to annotate the genome of the RNAi-deficient species Cryptococcus deuterogattii strain R265 using RNA-seq data. Dynamic transcriptome analysis revealed that intron retention is more prominent in C. deuterogattii than in the other RNAi-proficient species C. neoformans and C. deneoformans. In contrast, we observed that antisense transcription was not higher in C. deuterogattii than in the two other Cryptococcus species. Comparative gene content analysis identified 21 clusters enriched in transcription factors and transporters that have been lost. Interestingly, analysis of the subtelomeric regions in these three annotated species identified a similar gene enrichment, reminiscent of the structure of primary metabolic clusters. Our data suggest that there is active exchange between subtelomeric regions, and that other chromosomal regions might participate in adaptive diversification of Cryptococcus metabolite assimilation potential.

Trichoderma-Based Biopreparation with Prebiotics Supplementation for the Naturalization of Raspberry Plant Rhizosphere

The number of raspberry plants dying from a sudden outbreak of gray mold, verticillium wilt, anthracnosis, and phytophthora infection has increased in recent times, leading to crop failure. The plants suffer tissue collapse and black roots, symptoms similar to a Botrytis-Verticillium-Colletotrichum-Phytophthora disease complex. A sizeable number of fungal isolates were acquired from the root and rhizosphere samples of wild raspberries from different locations. Subsequent in vitro tests revealed that a core consortium of 11 isolates of selected Trichoderma spp. was the most essential element for reducing in phytopathogen expansion. For this purpose, isolates were characterized by the efficiency of their antagonistic properties against Botrytis, Verticillium, Colletotrichum and Phytophthora isolates and with hydrolytic properties accelerating the decomposition of organic matter in the soil and thus making nutrients available to plants. Prebiotic additive supplementation with a mixture of adonitol, arabitol, erythritol, mannitol, sorbitol, and adenosine was proven in a laboratory experiment to be efficient in stimulating the growth of Trichoderma isolates. Through an in vivo pathosystem experiment, different raspberry naturalization-protection strategies (root inoculations and watering with native Trichoderma isolates, applied separately or simultaneously) were tested under controlled phytotron conditions. The experimental application of phytopathogens attenuated raspberry plant and soil properties, while Trichoderma consortium incorporation exhibited a certain trend of improving these features in terms of a short-term response, depending on the pathosystem and naturalization strategy. What is more, a laboratory-scale development of a biopreparation for the naturalization of the raspberry rhizosphere based on the Trichoderma consortium was proposed in the context of two application scenarios. The first was a ready-to-use formulation to be introduced while planting (pellets, gel). The second was a variant to be applied with naturalizing watering (soluble powder).

Maize (Zea mays L. Sp.) varieties significantly influence bacterial and fungal community in bulk soil, rhizosphere soil and phyllosphere

The plant-microbe interaction can affect ecosystem function, and many studies have demonstrated that plant species influence relevant microorganisms. In this study, microbial communities in bulk soil, rhizosphere soil and phyllosphere from different maize varieties were investigated using high-throughput sequencing method. Results demonstrated that cultivar Gaoneng 1 (G1) showed higher bacterial diversity in soil (both bulk and rhizosphere soils) and lower bacterial diversity in the phyllosphere, while cultivar Gaoneng 2 (G2) had lower fungal diversity in both the soil and phyllosphere compare to the other cultivars. The bacterial community structure of soils among the three varieties was significantly different; however, no significant differences were found in the soil fungal community and phyllosphere bacterial and fungal community. The soil networks from cultivar G1 and phyllosphere networks from cultivar Zhengdan (ZD) have the highest complexity in contrast to the other two cultivars. In conclusion, the bacterial community structure in bulk soil of different cultivars was significantly different, so do the co-occurrence ecological networks of phyllosphere bacterial community. This study comprehensively analyzed the microbial community among different maize cultivars and could be useful for guiding practices, such as evaluation of new plant cultivars and quality predictions of these varieties at the microbial level.

Long-read only assembly of Drechmeria coniospora genomes reveals widespread chromosome plasticity and illustrates the limitations of current nanopore methods

BACKGROUND

Long-read sequencing is increasingly being used to determine eukaryotic genomes. We used nanopore technology to generate chromosome-level assemblies for 3 different strains of Drechmeria coniospora, a nematophagous fungus used extensively in the study of innate immunity in Caenorhabditis elegans.

RESULTS

One natural geographical isolate demonstrated high stability over decades, whereas a second isolate not only had a profoundly altered genome structure but exhibited extensive instability. We conducted an in-depth analysis of sequence errors within the 3 genomes and established that even with state-of-the-art tools, nanopore methods alone are insufficient to generate eukaryotic genome sequences of sufficient accuracy to merit inclusion in public databases.

CONCLUSIONS

Although nanopore long-read sequencing is not accurate enough to produce publishable eukaryotic genomes, in our case, it has revealed new information about genome plasticity in D. coniospora and provided a backbone that will permit future detailed study to characterize gene evolution in this important model fungal pathogen.

Comparative transcriptome profiling of the response to Pyrenochaeta lycopersici in resistant tomato cultivar Mogeor and its background genotype-susceptible Moneymaker

Breeding for resistance is the most effective tool for controlling the corky root disease of tomato caused by Pyrenochaeta lycopersici. A comparative RNA-Seq-based transcriptomic analysis was conducted at 96 hpi (hours post infection) on two tomato cultivars: resistant Mogeor and its genetic background, and susceptible Moneymaker to investigate the differences in their transcriptomic response and identify the molecular bases of this plant-pathogen interaction. The number of differentially expressed genes (DEGs) identified was much higher in the susceptible than in the resistant genotype; however, the proportion of upregulated genes was higher in Mogeor (70.81%) than in Moneymaker (52.95%). Gene Ontology (GO) analysis enabled identification of 24 terms shared by the two cultivars that were consistent with responses to external stimulus, such as fungal infection. On the other hand, as many as 54 GO were enriched solely in Moneymaker, including terms related to defense response and cell wall metabolism. Our results could support the previous observations in other pathosystems, that susceptibility and resistance have overlapping signaling pathways and responses, suggesting that the P. lycopersici resistance gene pyl might be a recessive allele at a susceptibility locus, for which different candidate genes were identified based on the differences in induction or expression levels, observed between the resistant and susceptible genotype. MapMan analysis highlighted a complex hormone and transcription factors interplay where SA- and JA-induced pathways are modulated in a similar way in both genotypes and thus take part in a common response while the ethylene signaling pathways, induced mainly in susceptible Moneymaker, seem putatively contribute to its susceptibility.