Contrasting glucosinolate profiles in rapeseed genotypes shape the rhizosphere-insect continuum and microbial detoxification potential in a root herbivore

Abstract

Plant secondary metabolites are key mediators of plant-insect-microbiome interactions, yet their role in structuring functionally relevant insect-associated microbial communities remains poorly understood. Here, we combined a factorial experiment using Brassica napus genotypes differing in glucosinolate (GLS) content with distinct succession to investigate the eco-evolutionary dynamics of the microbiota of the root herbivore Delia radicum. Amplicon sequencing and microbial culturing revealed that both rhizospheric and gut microbial communities are shaped by plant genotype and soil legacy, with a subset of bacterial taxa shared across compartments. Notably, Pseudomonas brassicacearum, harboring the isothiocyanates (ITC) detoxifying gene saxA, was consistently recovered from both plant and insect habitats. Functional assays confirmed its capacity to degrade 2-phenylethyl isothiocyanate (PEITC), a major toxic GLS hydrolysis product. Other gut-derived microbial isolates exhibited heterogeneous responses to PEITC, ranging from growth inhibition, promotion, or growth recovery after a prolonged lag phase. Despite the toxicity of ITC, insect fitness proxies were enhanced on GLS +plants, suggesting microbiota-mediated adaptation to host chemical defenses. Our findings reveal a plant genotype-specific filtering of environmentally acquired microbes and highlight the role of detoxifying symbionts in Delia radicum performance.IMPORTANCEUnderstanding how herbivorous insects adapt to plant chemical defenses is important in the context of new agricultural practices. This study highlights that the host plant genotype shapes not only rhizospheric and gut microbial communities but also promotes the acquisition of symbiotic bacteria capable of detoxifying harmful isothiocyanates. These findings reveal a functional microbial pathway for insect adaptation to plant defenses, with potential implications for pest management strategies. By uncovering the role of plant-associated microbiota, the acquisition of beneficial microbes, and their functional contributions to host fitness, this work provides a foundation for innovative agroecological approaches that leverage plant-microbe-insect interactions.

Keywords: Brassica napus; Delia radicum; Pseudomonas brassicacearum; glucosinolates; horizontal transmission; isothiocyanates; plant-insect-microbiome interactions.

Fig 1

Observed ASVs and Shannon index of bacterial communities in soil (A and B) and roots (C and D). The four modalities were derived from combining two rapeseed genotypes (GLS+ and GLS−) with three soil legacy conditions (GLS−, GLS+, and Wheat), resulting in the following four modalities: GLS−/Wheat, GLS−/GLS−, GLS+/Wheat, and GLS+/GLS+. Data were analyzed using the Kruskal-Wallis test. Different letters indicate a significant difference where P < 0.05.

Fig 2

Observed ASVs and Shannon index of fungal communities in soil (A and B) and roots (C and D). The four modalities were derived from combining two rapeseed genotypes (GLS+ and GLS−) with three soil legacy conditions (GLS−, GLS+, and Wheat), resulting in the following four modalities: GLS−/Wheat, GLS−/GLS−, GLS+/Wheat, and GLS+/GLS+. Data were analyzed using the Kruskal-Wallis test. Different letters indicate a significant difference, where P < 0.05.

Fig 3

Beta diversity analyzed using db-RDA on Bray-Curtis distance on the bacterial communities of (A) the rhizosphere soil (B) the roots and the fungal communities of (C) the rhizospheric soil and (D) the roots. The four modalities tested correspond to the two rapeseed genotypes (GLS+ and GLS−) combined with soil legacy conditions (GLS−, GLS+, and Wheat) to obtain: GLS−/Wheat, GLS−/GLS−, GLS+/Wheat, and GLS+/GLS+.

Fig 4

Beta diversity analyzed using db-RDA on Bray-Curtis distance on (A) the bacterial communities of larvae; (B) the fungal communities of larvae (B) and (C) the fungal communities of adults of Delia radicum developing on Brassica napus growing in different soils. The four modalities tested correspond to the two rapeseed genotypes (GLS+ and GLS−) combined with soil legacy conditions (GLS−, GLS+, and Wheat) to obtain: GLS−/Wheat, GLS−/GLS−, GLS+/Wheat, and GLS+/GLS+.

Fig 5

Number of bacterial (A) and fungal (B) ASVs according to the genus and shared between the rhizospheric soil, the roots, and the larvae of Delia radicum developing on Brassica napus growing in different soils. The four modalities tested correspond to the two rapeseed genotypes (GLS+ and GLS−) combined with soil legacy conditions (GLS−, GLS+, and Wheat) to obtain: GLS−/Wheat, GLS−/GLS−, GLS+/Wheat, and GLS+/GLS+. Each column on the x axis represents a plant.

Fig 6

Relative growth (area under the curve, AUC) of 20 bacterial isolates at 125 µM of PEITC compared to PEITC-free control. The red line corresponds to the similar growth in both control and PEITC treatments (i.e., ratio = 1). Values above 1 indicate a higher AUC than the control mean, while values below 1 indicate a reduced AUC. Mann-Whitney symbols indicate paired Whitney tests performed between the control treatment (PEITC concentration = 0 µM) and the PEITC treatment (ns = not significant, * =P < 0.05, ** =P < 0.01, *** =P < 0.001).

Fig 7

Maximum-likelihood tree of saxA homologs from the RefSeq database. DNA sequences were aligned with MAFFT, and phylogenetic trees were calculated with RAxML using 1,000 bootstraps. Only bootstrap values above 60 are indicated.

Fig 8

Proportion of PEITC remaining in the media with (dark gray) and without (light gray) Pseudomonas brassicacearum at 0 h, 1 h, 3 h, 6 h, 12 h, and 24 h after its addition to the medium. ANOVA, ns: P > 0.05, *: P < 0.05, ***: P < 0.001.

Fig 9

Survival and morphometric parameters of Delia radicum developing on Brassica napus growing in different soils. The four modalities tested correspond to the two rapeseed genotypes (GLS+ and GLS−) combined with soil legacy conditions (GLS−, GLS+, and Wheat) to obtain GLS−/Wheat, GLS−/GLS−, GLS+/Wheat, and GLS+/GLS+. (A) Number of larvae per plant; (B) number of adults emerging from each plant; (C) surface of collected larvae; (D) tibial length of emerging flies. ANOVA, Different letters indicate a significant difference, P < 0.05.