Project description:Genetic and molecular evidence to support the hypothesis that fungal secondary metabolites play a significant role in protecting the fungi against fungivory is scarce. We investigated the impact of fungal secondary metabolites on transcript regulation of stress related expressed sequence tags (ESTs) of the Collembola Folsomia candida feeding on mixed vs. single diets. Aspergillus nidulans wildtype (WT; Ascomycota) able to produce secondary metabolites including sterigmatocystin (ST) and a knockout mutant with reduced secondary metabolism (A. nidulans ΔLaeA) were combined with the high quality fungus Cladosporium cladosporioides as mixed diets or offered as single diets. We hypothesized that (i) A. nidulans WT triggers more genes associated with stress responses compared to the A. nidulans ΔlaeA strain with suppressed secondary metabolism, (ii) C. cladosporioides causes significantly different transcript regulation than the A. nidulans strains ΔlaeA and WT, and (iii) mixed diets will cause significantly different transcript expression levels than single diets. All three hypotheses are generally supported despite the fact that many functions of the affected ESTs are unknown. The results bring molecular evidence for the existence of a link between fungal secondary metabolites and responses in springtails supporting the hypothesis that fungal secondary metabolites act as a shield against fungivory.
Project description:Genetic and molecular evidence to support the hypothesis that fungal secondary metabolites play a significant role in protecting the fungi against fungivory is scarce. We investigated the impact of fungal secondary metabolites on transcript regulation of stress related expressed sequence tags (ESTs) of the Collembola Folsomia candida feeding on mixed vs. single diets. Aspergillus nidulans wildtype (WT; Ascomycota) able to produce secondary metabolites including sterigmatocystin (ST) and a knockout mutant with reduced secondary metabolism (A. nidulans ?LaeA) were combined with the high quality fungus Cladosporium cladosporioides as mixed diets or offered as single diets. We hypothesized that (i) A. nidulans WT triggers more genes associated with stress responses compared to the A. nidulans ?laeA strain with suppressed secondary metabolism, (ii) C. cladosporioides causes significantly different transcript regulation than the A. nidulans strains ?laeA and WT, and (iii) mixed diets will cause significantly different transcript expression levels than single diets. All three hypotheses are generally supported despite the fact that many functions of the affected ESTs are unknown. The results bring molecular evidence for the existence of a link between fungal secondary metabolites and responses in springtails supporting the hypothesis that fungal secondary metabolites act as a shield against fungivory. Twenty-three day old Folsomia candida were fed ad libitum for five days to fungal cuts respectively Cladosporium cladosporoides, Aspergillus nidulans WT, Aspergillus nidulans ?LaeA and two mixed diets of C.cladosporoides/A. nidulans WT (mix 1) and C. cladosporoides/A. nudlans ?LaeA (mix2) respectively. Four biological replicates were used for every treatment and a dye swap was used with the Cy3/Cy5 labels. This resulted in 20 samples which were analysed in 10 hybridisations executed in an interwoven loop design. The C. cladosporoides diet was used as the reference in the data analysis.
Project description:This study utilized comparative global gene expression microarray analysis to evaluate the effects of a compound including garlic-derived secondary metabolites on intestinal immunity of chicken. Two-condition experiment, Garlic metabolites-fed chickens vs. Non-treated control chickens. Biological replicates: 2 control replicates, 2 Garlic metabolites-fed replicates with dye-switching.
Project description:The collection of metabolites circulating in the human blood, termed the serum metabolome, contains a plethora of biomarkers and causative agents. Although the origin of specific compounds is known, we have a poor understanding of the key determinants of most metabolites. Here, we measured the levels of 1251 circulating metabolites in serum samples from a healthy human cohort of 491 individuals, and devised machine learning algorithms to predict their levels in held-out subjects based on a comprehensive profile consisting of host genetics, gut microbiome, clinical parameters, diet, lifestyle, anthropometric measurements and medication data. Notably, we obtained statistically significant predictions for over 76% of the profiled metabolites. Despite using the strict out-of-sample prediction metric, which is a lower bound for the explained variance, diet and microbiome each explained hundreds of metabolites, with over 50% of the variance explained in some metabolites. We further validated the robustness of the microbiome related associations by showing a high replication rate in two geographically independent cohorts that were not available to us when developing the algorithms. We also demonstrate that some of these interactions are causal, as some metabolites we predicted to be positively associated with bread increased in level following a randomized clinical trial of bread intervention. Microbiome-explained metabolites were enriched with unnamed metabolites, and we devised an algorithm that accurately predicts their biological pathway, finding that they mainly include food components, aromatic amino acids and secondary bile acid derivatives. Overall, our results unravel potential determinants of over 800 metabolites, paving the way towards mechanistic understanding of alterations in metabolites under different conditions and to designing interventions for manipulating circulating metabolite levels.
Project description:Genomic and transcriptomic analysis and prediction of genes involved in polysaccharide and bioactive secondary metabolites in wild Flammulina filiformis