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The plant-associated microbiota confers beneficial traits to the plant host that promote growth and prevents disease. It is, however, not fully understood how the host, and pathogens, modulate the assembly of the associated microbiota. In this work, we investigated the effects of inoculation with bacterial consortia (BCs) that had been primed with either the host plant Arabidopsis thaliana alone or by a combination of the host and the pathogen Fusarium oxysporum f. sp. mathioli (FOM), on the root-associated microbiota and FOM. We used 16S rRNA and ITS amplicon sequencing for profiling root bacterial and fungal communities, respectively. qPCR was employed for the assessment of FOM quantities in the shoots of Arabidopsis. Our results showed distinct effects of host or pathogen primed BCs on microbial community structures and networks. Both host and pathogen primed BCs inhibited FOM proliferation in shoots, distinctively affected rhizo-microbial communities, and network structuring. Beneficial bacterial genera including Flavobacterium, Azospirillum, Massilia and Pedobacter were significant biomarkers in the samples inoculated with host-primed BCs and could potentially be involved in FOM antagonism. Bacterial taxa Bacteriodetes, Flavobacterium and Chthoniabacteraceae and the fungal, Exophiala and Phaeosphaeriaceae were the most enriched biomarker taxa in the samples treated with FOM-primed BCs. Moreover, the host genotype effect was significant in overall microbial community network structuring and could contribute to resistance to FOM pathogens. Altogether, these findings deepen our understanding of both host- and pathogen-priming on plant-associated microbiomes, thus, revealing pivotal engineering routes in exploring microbiomes to manage plant diseases. Keywords: rhizosphere engineering, microbiome inoculation, disease suppression, fungal pathogens, invasion networks.

Supplementary files (Tables and Figures) for Kudjordjie et al., Fusarium oxysporum disrupts microbiome-metabolome networks in Arabidopsis thaliana roots Supplementary files Supplementary Figures Figure S1. Structure and pathways of quantified metabolites and hormones. A) Chemical structure of glucosinolates and their degradation products quantified in this study B) A schematic view of the biosynthetic pathways of phenylpropanoids and representative intermediates and chemical structures. For simplicity, only the enzymes involved in the formation of 4-coumaryl CoA from phenylalanine are shown. Solid arrows represent single enzymatic steps. Dashed arrows indicate multiple consecutive enzymatic steps. The colors are representative of following chemical classes: coumarins (green), cinnamic acid derivatives (black), benzoic acids (dark red), lignin precursors (monolignols) (blue), and lignans (light red). Figure S2. (A) FOM quantities in shoots of inoculated and non-inoculated Arabidopsis. Distribution of (B) bacterial and (C) fungal sequence reads and OTUs in samples used in this study. Rarefaction curves showing the coverage of (D) bacterial and (E) fungal OTU richness (species richness in number of OTUs) as a function of sequencing depth (sample size in number of reads). Figure S3. Bacterial and fungal community analysis. A) Bacterial and B) fungal communities in inoculated and non-inoculated Col-0 and Ler-0. C) Relative abundance of fOTUs assigned to the Fusarium genus in Col-0 control and inoculated samples. D) Relative abundance of fOTUs assigned to the Fusarium genus in Ler-0 non-inoculated and inoculated samples at different DAI. Red colour shades represented inoculated samples while green colour shades represent non-inoculated samples at different DAI. Bacterial alpha diversity E) and F) fungal beta diversity visualized using Principal coordinates analysis (PCoA) in inoculated and control Col-0 and Ler-0. ANOVA was used to determine statistically significant differences between sample means, followed by the Tukey post hoc test using R statistical package “agricolae”. Significance of test indicated as *** for p < 0.001, ** p > 0.01, *p < 0.05. Figure S4. Analysis of differential OTUs in inoculated and non-inoculated samples. Heatmap showing top50 bacterial (A) and B) fungal OTU relative abundances in inoculated and non-inoculated samples across different 5 DAI. (C) Global analysis revealed two bacterial OTUs; bOTU6 (Rhizobium) and bOTU10 (Pseudomonas protegens) to be significantly abundant in inoculated and non-inoculated samples of Col-0 and Ler-0. (D) bOTU4 (Streptomyces) abundance in inoculated and non-inoculated samples of Col-0 and Ler-0. One-way ANOVA was used to determine statistically significant differences between sample means, followed by the Tukey post hoc test using R statistical package. Significance of test indicated as *** for p < 0.001, ** p < 0.01, *p < 0.05. Figure S5. Differentially abundant bacterial (A) and fungal (B) taxa between samples of Col-0 and Ler-0. Log2fold changes greater than and less than zero indicate enrichment OTUs in Ler-0 and Col-0, respectively. C) Heatmap showing differentially abundant bacteria taxa in inoculated and non-inoculated samples of Col-0 and Ler-0. D) Heatmap showing differentially abundant fungal taxa in inoculated and non-inoculated samples of Col-0 and Ler-0. OTU1 (FOM) was significantly enriched in the inoculated samples. In C and D, taxa enrichment in non-inoculated are indicated in blue while enrichment in inoculated samples are indicated in red. Log2fold changes greater than and less than zero indicated an enrichment of the relevant genera in Ler-0 and Col-0 respectively. The analysis was performed using DESeq2 with phyloseq. Globally enriched OTUS; bOTU6 and bOTU10 are indicated in astericks. Differences were considered significant with the p-value (adjusted for false discovery rate using Benjamini–Hochberg correction) cut-off of 0.01, except for fOTUs differential abundance estimation in Col-0 and Ler-0 comparison where a cut-off of 0.05 was used. Figure S6. Abundance of indicator (A) bacterial and (B) fungal taxa identified in inoculated and non-inoculated root samples of Col-0 and Ler-0. Bars correspond to summed abundances for taxonomic divisions at phylum level, with individual classes (and lower-level taxa) denoted by stacked boxes. C) Fungal indicator OTU enrichment in non-inoculated and inoculated samples of Col-0 and Ler-0 at different days after inoculation (DAI). Number of indicator microbial OTUs identified in inoculated and non-inoculated Col-0 and Ler-0 samples are shown in the table. Highly significant OTUs (p Figure S7: The missense variants in Ler-0 Fusarium resistance proteins as compared with Col-0. Supplementary tables Table S1: MRM transitions and compound-dependent parameters for LC-MS/MS analysis of the target analytes in both negative and positive ESI modes. Each analyte has two MRM transitions. Q1= quadrupole 1, protonated or deprotonated molecule (m/z ratio); Q3 (1) = quadrupole 3 (quantifier); Q3 (2) = quadrupole 3 (qualifier); DP= declustering potential; EP= entrance potential; CE = collision energy. Aliphatic glucosinolates (AG); Indole glucosinolates (IG); Hydroxybenzyl glucosinolates (OH-benzyl-G); Benzoic acid (BZ); Cinnamic acids (CA); ISTD (internal standard). Table S2: Sequence read statistics for bacterial and fungal reads. Table S3: Permutational analysis of variance (PERMANOVA) using ‘adonis’ test on Bray-Curtis distance matrices for bacterial and fungal community dissimilarity assessment using 1000 permutations. Table S4: Differentially affected taxa in genotypes and inoculated and non-inoculated samples. Differences were considered significant with the p-value (adjusted for false discovery rate using Benjamini–Hochberg correction) cut-off of 0.01, except for fOTUs differential abundance estimation in Col-0 and Ler-0 comparison where a cut-off of 0.05 was used. Table S5: Bacterial and fungal indicator OTUs identified in inoculated and non-inoculated Col-0 and Ler-0 lines. Indicator value and relative abundance of each indicator taxa is provided. Table S6: Summary of co-occurrence network properties including keystone OTUs, and their relative abundances identified in inoculated and non-inoculated Arabidopsis lines. Table S7: Summary of bOTU_fOTU1 correlations identified in inoculated and non-inoculated Arabidopsis lines. Table S8: Absolute concentrations (μg/g) of glucosinolates, glucosinolates hydrolysis products, camalexin, C) coumarins, lignin precursors, lignans, phenolic acids, and hormones in the root of Arabidopsis accessions after root was challenged with the FOM spores (inoculated) or water (non-inoculated). Values represent the mean of five biological replicates + standard error. At each time‐point, significant differences between the root of non­-inoculated samples and those exposed to FOM are indicated by asterisks (*: pTable S9: Pathway enrichment analysis highlights different pathogen response mechanisms in which the co-expressed genes are involved Table S10: Summary of OTU-metabolite correlation analysis using all dataset obtained and partitions of inoculated and non-inoculated Arabidopsis samples. Table S11: Summary of metabolite-fOTU1 correlations identified in inoculated and non-inoculated Arabidopsis lines. Table S12: Summary of indicator hubOTU metabolite-correlations identified in inoculated and non-inoculated Arabidopsis lines.

Source at https://vkm.no/risikovurderinger/allevurderinger/konsekvenseravaimporteregrovfor.4.372fcd091727089bb664ab15.html. Det er stor usikkerhet om import av grovfôr til Norge kan føre med seg planteskadegjørere, invaderende planter og smittestoff som kan forårsake sykdom hos dyr og mennesker.

Slide of the Euphresco project 2020-A-335 ' Survey of pathotypes of Globodera pallida occurring in Europe', Project funded through the Euphresco network

Epitrix Foudras 1860, is a genus of flea beetles (Coleoptera: Chrysomelidae: Alticinae) with nearly 180 species worldwide. Most species occur in South and Central America (neotropics), and only 12 and 10 species are known from North America and Europe, respectively. A few species of Epitrix are reported to feed on potato plants, the adults feeding on the leaves and the larvae on the roots and tubers. In the European Union (EU) emergency measures have been introduced to prevent the introduction of the EPPO A1 listed species Epitrix tuberis and E. subcrinita and the spread of the EPPO A2 species E. cucumeris and E. papa, accidentally introduced in Portugal and Spain. The three former species are native from North America and are known to cause damage to tubers, with E. tuberis being the most damaging one. E. papa is a newly described species with unknown geographic origin and known distribution limited to some regions of Portugal and Spain and causes damage to tubers. Other neotropical Epitrix species could also be of concern for European phytosanitary authorities, such as E. yanazara, which are known to feed on potato. Further research into the taxonomy and pest status of other potential Epitrix species of concern within the neotropics is required to understand these lesser-known species better and the impacts they may pose to other regions. This project utilises the expertise of a network of scientists developed during Euphresco Epitrix I project to increase knowledge, understanding and preparedness for potential new outbreaks of Epitrix spp. affecting potato crops. Epitrix species are uniform in their external morphology and difficult to distinguish in the field or in the laboratory even by specialists. Taxonomic experts from affected areas in Europe and North America prepared samples of accurately identified Epitrix beetles to help validate molecular detection methods for the benefit of the plant inspection services, particularly for regions where this expertise does not exist. Validated methods are now ready for interlaboratory comparative tests, which will be carried out in autumn 2021. Many new potential pest Epitrix spp. were collected on solanaceous plants during a field expedition to Peru in 2020. This material will be used to help to bridge the knowledge gap of lesser-known Epitrix species within the neotropics. Plant volatile organic compounds (VOCs) were investigated in EPITRIX I in the laboratory and in field experiments as potential attractants for detecting and monitoring Epitrix. Further research into the attractiveness of the VOC substances were studied, and although the results were encouraging, the attractiveness of the substances tested in the field was insufficient for reliable insect detection and monitoring. An additional study for testing new attractants (plant and insect volatiles) was therefore proposed but unfortunately not funded. Available licensed insecticides and cultural management practices were reviewed to ensure that chemical control measures are still feasible, as several widely used pesticides have recently been removed from the market or are under review in the EU and the United Kingdom. The study showed that cultural practices (such as crop rotation, dates of planting, plantation of a trap crop, destruction of crop residues, and control of solanaceous weeds) may be used for efficiently disrupting the insect���s biology and target control., Report of the Euphresco project 2016-F-218 'Epitrix (flea beetle) species, life cycles and detection methods (Epitrix II)'

High-throughput sequencing (HTS, formerly also known as next-generation sequencing or pyrosequecing) technologies have seen a tremendous evolution in terms of technical developments. These technologies are more and more used for plant virus discovery, metagenomic and ecological studies but are also increasingly being used in plant virus diagnostic settings, post-entry quarantine investigations or pre-export diagnostics. Conventional virus detection methods based on serology (i.e., enzyme-linked immunosorbent assays) or nucleic acids (polymerase chain reaction (PCR), real-time PCR), requires in depth knowledge for the target pathogen to develop antisera or primers limiting these methods to the detection of mostly known viruses. The use of HTS for virus detection is not dependent on a priori knowledge about the viruses to be detected which is a major advance in diagnostic testing. This project aimed to harmonise sample enrichment strategies and HTS workflows for plant virus and viroid detection within a diagnostic framework. Existing bioinformatics approaches were investigated during a proficiency test and a test performance study which demonstrated the power of HTS for diagnostics but also the limitations if diagnosticians are not experienced with the analyses of HTS data. HTS and newly developed sequencing technologies such as Oxford Nanopore Sequencing have a great potential for diagnostics but further work is required to set up guidelines for validation of HTS workflows., Report of the Euphresco project 2015-F-172 'The application of Next-Generation Sequencing technology for the detection and diagnosis of non-culturable organisms: viruses and viroids (NGSdetect)'

Baggrund: I dag dominerer de store monokulturer det danske landskab, og det sætter biodiversiteten under pres, fordi skadedyr og sygdomme får optimale betingelser og dermed udfordrer jordens frugtbarhed. Derfor har vi brug for nye dyrkningsmetoder, der øger biodiversiteten i landskabet og samtidig fastholder høstudbytterne. Stribedyrkning med 3-5 forskellige afgrøder i striber på 3-12 meters bredde har vist sig at have positive effekter i flere udenlandske forsøg. Typisk resulterer stribedyrkning i højere biodiversitet, mere modstandsdygtige afgrøder, mere frugtbar jord, færre angreb fra skadedyr, færre sygdomme og mindre jorderosion. Formål: Resultaterne fra projektets forsøg skal gøre det muligt for økologiske landbrugere at træffe kvalificerede beslutninger med henblik på at øge biodiversiteten og samtidig øge afgrødernes robusthed samt fastholde udbytterne.

Indenfor de seneste årtier har der været en stigende interesse for samtidig dyrkning af flere afgrøder stribevis i en mark (stribedyrkning). StripCrop er et nyt dansk projekt, som beskæftiger sig med emnet. I artiklen introduceres projektet.