Impact of a resistance gene against a fungal pathogen on the plant host residue microbiome: The case of the Leptosphaeria maculans-Brassica napus pathosystem

Abstract

Oilseed rape residues are a crucial determinant of stem canker epidemiology as they support the sexual reproduction of the fungal pathogen Leptosphaeria maculans. The aim of this study was to characterize the impact of a resistance gene against L. maculans infection on residue microbial communities and to identify microorganisms interacting with this pathogen during residue degradation. We used near-isogenic lines to obtain healthy and infected host plants. The microbiome associated with the two types of plant residues was characterized by metabarcoding. A combination of linear discriminant analysis and ecological network analysis was used to compare the microbial communities and to identify microorganisms interacting with L. maculans. Fungal community structure differed between the two lines at harvest, but not subsequently, suggesting that the presence/absence of the resistance gene influences the microbiome at the base of the stem whilst the plant is alive, but that this does not necessarily lead to differential colonization of the residues by fungi. Direct interactions with other members of the community involved many fungal and bacterial amplicon sequence variants (ASVs). L. maculans appeared to play a minor role in networks, whereas one ASV affiliated to Plenodomus biglobosus (synonym Leptosphaeria biglobosa) from the Leptosphaeria species complex may be considered a keystone taxon in the networks at harvest. This approach could be used to identify and promote microorganisms with beneficial effects against residue-borne pathogens and, more broadly, to decipher the complex interactions between multispecies pathosystems and other microbial components in crop residues.

Keywords: ecological network analysis; metabarcoding; microbial communities; microbiome; oilseed rape residues; pathobiome; stem canker.

FIGURE 1

Effect of the presence of the Rlm11 resistance gene and of sampling date (July, October, December, and February) on fungal (a, c) and bacterial (b, d) communities originating from 120 samples of oilseed rape residues. (a) and (b) Visualization of compositional distances between samples through multidimensional scaling (MDS) based on the Bray–Curtis dissimilarity matrix. MDS analysis was performed on all samples together and was faceted according to the sampling date. Each data point corresponds to one sample of oilseed rape residues. The colours of the points distinguish between sampling dates (July, green; October, red; December, blue; February, grey) and cultivar (Darmor, light hues; Darmor‐Rlm11, dark hues). (c) and (d) Diversity and predominance of the 25 most abundant (25/62, excluding unclassified genera) fungal genera (a) and the 35 most abundant (35/134, excluding unclassified genera) bacterial genera (b) distributed in all samples, distinguishing between the different experimental conditions. The colours used to distinguish samples are as in (a) and (b)

FIGURE 2

Influence of the presence of the Rlm11 resistance gene and sampling date (July, October, December, and February) on (a) the stem canker G2 score (proxy for disease severity, estimated for 60 plants of Darmor and Darmor‐Rlm11) and (b) the percentage of reads corresponding to Leptosphaeria maculans. (a) Percentage of plants with each G2 score for the two cultivars. The dashed lines correspond to the G2 score for each of the two cultivars (Darmor, yellow; Darmor‐Rlm11, blue). (b) Percentage of reads affiliated to L. maculans in the 15 samples for each condition. The dashed lines correspond to the mean read percentage for each of the two cultivars at each sampling date (Darmor, yellow; Darmor‐Rlm11, blue)

FIGURE 3

Impact of the presence of the Rlm11 resistance gene on microbial communities in oilseed rape residues. (a) and (b) Significant differences in the predominance of bacterial (a) and fungal (b) amplicon sequence variants (ASVs) between the Darmor samples (orange) and the Darmor‐Rlm11 samples (blue) obtained in linear discriminant analysis (LDA). Only ASVs with p < .05 for the Kruskal–Wallis test and LDA scores >2 were retained for the plot. (c) Relative abundances of Leptosphaeria, Plenodomus, Alternaria, and Hydropisphaera by host cultivar (Darmor and Darmor‐Rlm11) and sampling date (July, October, December, and February). All ASVs were grouped by genus (Alternaria 8 ASVs, Hydropisphaera 8 ASVs, Leptosphaeria 13 ASVs, Plenodomus 81 ASVs)

FIGURE 4

Temporal dynamics of co‐occurrence networks. (a) Networks based on bacterial and fungal amplicon sequence variants (ASVs) combined. In all networks, circles and squares correspond to bacterial and fungal ASVs, respectively, with colours representing the class. Isolated nodes are not indicated. Edges represent positive (grey) or negative (red) interactions. (b) Betweenness centrality and degree of each ASV in the networks. The place of Leptosphaeria maculans in the networks is indicated. Colour and shape are as in (a). The genera of the fungal and bacterial ASVs with the highest degree and centrality have been added: Agrom(yces), Alter(naria), Clado(sporium), Lepto(sphaeria), Monog(raphella), Pedob(acter), Pleno(domus), Polar(omonas), Pseud(omonas), Sphin(gopyxis), Torul(a). (c) Percentage of reads associated with fungal and bacterial classes for each network. Isolated nodes are indicated. Colours are as in (a)

FIGURE 5

Subnetworks combining linear discriminant analysis (LDA; see Figure 3) and ecological interaction networks (see Figure 4), focusing on bacterial and fungal amplicon sequence variants (ASVs) identified as differential in LDA and their first adjacent nodes. Node colour indicates the results of LefSe differential analysis (Segataet al., 2011) between Darmor (yellow) and Darmor‐Rlm11 (blue) treatments. Only genera with p < .05 for the Kruskal–Wallis test and LDA scores >2 were retained for the plot. Edges represent positive (grey) or negative (red) interactions. Differential ASVs are plotted with genus name abbreviations: Acido(vorax), Adven(ella), Aerom(icrobium), Agari(cicola), Agrom(yces), Alter(naria), Alter(erythrobacter), Arthr(obacter), Astic(cacaulis), Aurei(monas), Brevu(ndimonas), Chond(romyces), Chrys(eobacterium), Clado(sporium), Cryob(acterium), Crypt(ococcus), Dacty(lella), Devos(ia), Dyado(bacter), Flavo(bacterium), Gemmo(bacter), Hydro(pisphaera), Lepto(sphaeria), Lutei(monas), Massi(lia), Methy(lobacterium), Monog(raphella), Nitro(lancea), Nocar(dioides), Panto(ea), Param(icrothyrium), Pedob(acter), Phial(ophora), Phyll(obacterium), Pleno(domus), Polar(omonas), Promi(cromonospora), Pseud(omonas), PseuR(=Pseudorhodoferax), Pyren(opeziza), Rhizo(bium), Skerm(anella), SphiB(=Sphingobacterium), Sphin(gomonas), Steno(trophomonas), Thele(bolus), Torul(a), Uligi(nosibacterium), Uncl.(assified), Vario(vorax), Verti(cillium)