
Figure: The rosettes of A. thaliana accessions IP-Hue-3 and Hadd-3 did not differ in size compared between BX- and BX+ growth conditions. F1.2 plants developed significantly larger rosettes in BX+ growth conditions. (A) shows photographs of all A. thaliana plants included in the experiment (n = 120), five weeks after germination, sorted by their genotype. Plants that died during the experiment (n = 2) are also included in the photograph. (B) Plant region area measurements in pixel counts of A. thaliana accessions IP-Hue-3 and Hadd-3 and their reciprocal F1 plants Hadd-3 x IP-Hue-3 (F1.1) and IP-Hue-3 x Hadd-3 (F1.2), measured 3, 4, and 5 weeks after germination. For each measured time point and genotype, plants grown in BX- conditions (green) are compared to plants grown in BX+ conditions (yellow). Points represent individual replicates (n = 14-15 per group). The centre line of each boxplot represents the median, boxes represent the interquartile range, and whiskers extend to the most extreme values within 1.5 times the interquartile range. P-values of the Student’s t-test are shown above the boxplots. Results of the three-way ANOVA testing the effects of genotype (gen), conditioning (con), and time on plant region area are shown in the upper right with asterisks indicating the level of significance: ns = not significant, * = p < 0.05, ** = p < 0.01, *** = p < 0.001, **** = p < 0.0001.
MSc Lewis Di Gallo
08/2026
Supervision: Prof. Klaus Schlaeppi and Dr. Pascale Flury
Abstract:
Plants are closely connected to the soil microbiome through their roots and actively shape the composition through root exudates. Interactions between plants and soil microorganisms can have both, beneficial and detrimental effects on plant performance. Whilst beneficial plant microbe interactions offer promising applications in sustainable agriculture, their outcomes are often highly context dependent. Understanding the factors that determine these outcomes and identifying the organisms involved are therefore of great importance. In this thesis we investigated the context dependency of plant feedback responses to the soil microbiome by focusing on the effects of plant genotype and soil origin. To assess the role of plant genotype in feedback responses, we focused on two Arabidopsis thaliana accessions displaying contrasting responses to soils conditioned with the plant exudate benzoxazinoid (BX). The accessions were cross-pollinated to obtain first filial generation (F1) plants. In a subsequent BX feedback experiment including parental and F1 lines, the F1 lines displayed positive growth feedback response to BX+ conditioned soils, whereas no significant feedback responses were observed in the parental lines.
To investigate the influence of soil origin on context dependency, a greenhouse arbuscular mycorrhizal fungi inoculation experiment was conducted using soils collected from five Swiss field sites that previously showed contrasting mycorrhizal growth responses (MGRs). In contrast to the previously reported strong and site-dependent variation in MGR observed under field conditions, only weak MGRs were observed under greenhouse conditions. To further expand our understanding of the maize root microbiome, we complemented the previously established maize root bacteria collection from BX+ and BX- conditioned Changins field soils with fungal community data obtained through long-read ITS amplicon sequencing and cultivation approaches. Within the established maize root fungal collection, we could identify Setophoma terrestris as the most abundant amplicon sequence variant (ASV) and Fusarium oxysporum as the most frequently cultivated fungus. Furthermore, four ASVs showed differences in abundance between wild-type (WT) and benzoxazinoid-deficient mutant (bx1) maize roots, suggesting a potential influence of BXs on fungal root colonization. Together, these findings further highlight the context dependency of the interaction between plants and microbiome and provide further insights into the fungal maize root microbiome. To ultimately apply microbiome-based approaches in agriculture, a better understanding of the mechanisms underlying the context dependency is pivotal and requires further research.
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