Browsing by Subject "Metabolites"

Now showing 1 - 2 of 2
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    Multi-omics reveals different strategies in the immune and metabolic systems of high-yielding strains of laying hens
    (2022) Iqbal, Muhammad Arsalan; Reyer, Henry; Oster, Michael; Hadlich, Frieder; Trakooljul, Nares; Perdomo-Sabogal, Alvaro; Schmucker, Sonja; Stefanski, Volker; Roth, Christoph; Camarinha Silva, Amélia; Huber, Korinna; Sommerfeld, Vera; Rodehutscord, Markus; Wimmers, Klaus; Ponsuksili, Siriluck
    Lohmann Brown (LB) and Lohmann Selected Leghorn (LSL) are two commercially important laying hen strains due to their high egg production and excellent commercial suitability. The present study integrated multiple data sets along the genotype-phenotype map to better understand how the genetic background of the two strains influences their molecular pathways. In total, 71 individuals were analyzed (LB, n = 36; LSL, n = 35). Data sets include gut miRNA and mRNA transcriptome data, microbiota composition, immune cells, inositol phosphate metabolites, minerals, and hormones from different organs of the two hen strains. All complex data sets were pre-processed, normalized, and compatible with the mixOmics platform. The most discriminant features between two laying strains included 20 miRNAs, 20 mRNAs, 16 immune cells, 10 microbes, 11 phenotypic traits, and 16 metabolites. The expression of specific miRNAs and the abundance of immune cell types were related to the enrichment of immune pathways in the LSL strain. In contrast, more microbial taxa specific to the LB strain were identified, and the abundance of certain microbes strongly correlated with host gut transcripts enriched in immunological and metabolic pathways. Our findings indicate that both strains employ distinct inherent strategies to acquire and maintain their immune and metabolic systems under high-performance conditions. In addition, the study provides a new perspective on a view of the functional biodiversity that emerges during strain selection and contributes to the understanding of the role of host–gut interaction, including immune phenotype, microbiota, gut transcriptome, and metabolome.
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    Regulatory modules of metabolites and protein phosphorylation in arabidopsis genotypes with altered sucrose allocation
    (2022) Stefan, Thorsten; Wu, Xu Na; Zhang, Youjun; Fernie, Alisdair; Schulze, Waltraud X.
    Multi-omics data sets are increasingly being used for the interpretation of cellular processes in response to environmental cues. Especially, the posttranslational modification of proteins by phosphorylation is an important regulatory process affecting protein activity and/or localization, which, in turn, can have effects on metabolic processes and metabolite levels. Despite this importance, relationships between protein phosphorylation status and metabolite abundance remain largely underexplored. Here, we used a phosphoproteomics–metabolomics data set collected at the end of day and night in shoots and roots of Arabidopsis to propose regulatory relationships between protein phosphorylation and accumulation or allocation of metabolites. For this purpose, we introduced a novel, robust co-expression measure suited to the structure of our data sets, and we used this measure to construct metabolite-phosphopeptide networks. These networks were compared between wild type and plants with perturbations in key processes of sugar metabolism, namely, sucrose export (sweet11/12 mutant) and starch synthesis (pgm mutant). The phosphopeptide–metabolite network turned out to be highly sensitive to perturbations in sugar metabolism. Specifically, KING1, the regulatory subunit of SnRK1, was identified as a primary candidate connecting protein phosphorylation status with metabolism. We additionally identified strong changes in the fatty acid network of the sweet11/12 mutant, potentially resulting from a combination of fatty acid signaling and metabolic overflow reactions in response to high internal sucrose concentrations. Our results further suggest novel protein-metabolite relationships as candidates for future targeted research.