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Hanemann, A.

Publications and source records attributed to Hanemann, A..

2 recordsLinked to original sources

Glycosylated diterpenes associate with early containment of Fusarium culmorum infection across wheat (Triticum aestivum L.) genotypes under field conditions

Wheat (Triticum aestivum L.) is severely affected by head blight, a destructive disease caused primarily by Fusarium species, which reduces yield and contaminates grains with trichothecene mycotoxins that compromise food and feed safety worldwide. Mechanistic insights into host-pathogen interactions have largely emerged from controlled experimental settings, providing conceptual foundations under conditions of constrained genetic and environmental complexity. Resolving consistent, generalizable molecular patterns across diverse wheat genotypes within a large-scale, heterogeneous field study remains technically and methodologically challenging. Addressing this gap, we integrated quantitative mycotoxin profiling with untargeted metabolomics in a field experiment comprising 105 wheat genotypes deliberately inoculated with F. culmorum, with the goal of identifying molecular signatures of infection and containment under realistic agronomic conditions. Quantified deoxynivalenol (DON) concentrations provided a robust, continuous measure of infection intensity, enabling metabolite profiles to be related directly to pathogen activity beyond the limitations of symptom-based visual scoring. Consistent with established Fusarium trichothecene biosynthesis, sesquiterpene-derived metabolites closely tracked toxin accumulation, thereby recapitulating infection-associated metabolic patterns across the large-scale field study. Conversely, glycosylated diterpene conjugates were elevated under low toxin accumulation, linking their abundance to contained Fusarium pathogen activity and highlighting a largely underexplored aspect of wheat metabolism in host-pathogen interactions. Elucidating their biosynthetic origin, enzymatic interconversion, and regulatory context will be key to defining potential diterpene-associated defense processes across wheat genotypes.

plant biology↗

An atlas of robust microbiome associations with phenotypic traits based on large-scale cohorts from two continents

Numerous human conditions are associated with the microbiome, yet studies are inconsistent as to the magnitude of the associations and the bacteria involved, likely reflecting insufficiently employed sample sizes. Here, we collected diverse phenotypes and gut microbiota from 34,057 individuals from Israel and the U.S.. Analyzing these data using a much-expanded microbial genomes set, we derive an atlas of robust and numerous unreported associations between bacteria and physiological human traits, which we show to replicate in cohorts from both continents. Using machine learning models trained on microbiome data, we predict human traits with high accuracy across continents. Subsampling our cohort to smaller cohort sizes yielded highly variable models and thus sensitivity to the selected cohort, underscoring the utility of large cohorts and possibly explaining the source of discrepancies across studies. Finally, many of our prediction models saturate at these numbers of individuals, suggesting that similar analyses on larger cohorts may not further improve these predictions.

genomics↗