Project description:Diet-microbe interactions play a crucial role in infant development and modulation of the early-life microbiota. The genus Bifidobacterium dominates the breast-fed infant gut, with strains of B. longum subsp. longum (B. longum) and B. longum subsp. infantis (B. infantis) particularly prevalent within the early-life microbiota. Although, transition from milk to a more diversified diet later in infancy initiates a shift to a more complex microbiome, with concurrent reductions in Bifidobacterium abundance, specific strains of B. longum may persist in individual hosts for prolonged periods of time. Here, we sought to investigate the adaptation of B. longum to the changing infant diet during the early-life developmental window. Genomic characterisation of 75 strains isolated from nine either exclusively breast- or formula-fed infants in the first 18 months of their lives revealed subspecies- and strain-specific intra-individual genomic diversity with respect to glycosyl hydrolase families and enzymes, which corresponded to different dietary stages. Complementary phenotypic growth studies indicated strain-specific differences in human milk oligosaccharide and plant carbohydrate utilisation profiles between and within individual infants, while proteomic profiling identified proteins involved in metabolism of selected carbohydrates. Our results indicate a strong link between infant diet and B. longum subspecies/strain genomic and carbohydrate utilisation diversity, which aligns with a changing nutritional environment i.e. moving from breast milk to a solid food diet. These data provide additional insights into possible mechanisms responsible for the competitive advantage of this bifidobacterial species and their long-term persistence in a single host and may contribute to rational development of new dietary therapies for this important development window.

2020-07-15 | PXD017277 | Pride

Nassar2022 - Microbiome engineered environment NER model

Project description:Microbiome engineered environment model is a Named Entity Recognition (NER) model that identifies and annotates the man-made environment of microbiome samples in texts. This is the final model version used to annotate metagenomics publications in Europe PMC and enrich metagenomics studies in MGnify with engineered metadata from literature. For more information, please refer to the following blogs: http://blog.europepmc.org/2020/11/europe-pmc-publications-metagenomics-annotations.html https://www.ebi.ac.uk/about/news/service-news/enriched-metadata-fields-mgnify-based-text-mining-associated-publications

2022-02-21 | MODEL2202170004 | BioModels

Wheat associated microbiome in a semiarid environment

Project description:Wheat associated microbiome in a semiarid environment Raw sequence reads

| PRJNA1073986 | ENA

Soil and plant associated microbiome

Project description:Soil and plant associated microbiome Raw sequence reads

| PRJNA421086 | ENA

Expression data from Arabidopsis seedlings heat-stressed in dark environment

Project description:Plants transcriptome react to environment temperature changes profoundly. In Arabidopsis seedlings, genes respond to temperature fluctuations to adopt the ever-changing ambient environment. We used microarrays to detail the global programme of gene expression underlying heat stress response progress in Arabidopsis. Ten-day-old Arabidopsis seedlings were selected for RNA extraction and hybridization on Affymetrix microarrays. We sought to explore the heat stress response in transcriptome, thus we treat the plants with heat stress. While in order to identify the interaction between light and temperature signaling pathways in plant , we treat Arabidopsis with heat stress under both light and dark conditions. To that end, our plant tissues are grouped as: HS-LIGHT, HS-DARK,CONTROL-LIGHT,CONTROL-DARK.

2014-06-19 | E-GEOD-58620 | biostudies-arrayexpress

Plant root associated microbiome

Project description:Plant root associated microbiome Metagenome

| PRJNA495431 | ENA

Biogas plant reactors microbiome

Project description:Biogas plant reactors microbiome metagenome

| PRJNA1101514 | ENA