Ontology highlight
ABSTRACT:
PROVIDER: PRJNA1309869 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:In this study we investigated whether gut microbiota profile of Italian healthy volunteers could differ based on their geaographical origin. To this purpose, fecal samples were collected from 31 healthy individuals living in 3 different italian regions (Lombardy, North; Lazio, Center; Apulia, South) and their respective microbiota profiles were analyzed employing 16S metagenomic sequencing method. This study identifies differences in the gut microbiota content and richness among individuals with the same ethnicity coming from three different Italian regions.
2026-01-08 | E-MTAB-8136 | biostudies-arrayexpress
Project description:We have previously demonstrated that the gut microbiota can play a role in the pathogenesis of conditions associated with exposure to environmental pollutants. It is well accepted that diets high in fermentable fibers such as inulin can beneficially modulate the gut microbiota and lessen the severity of pro-inflammatory diseases. Therefore, we aimed to test the hypothesis that hyperlipidemic mice fed a diet enriched with inulin would be protected from the pro-inflammatory toxic effects of PCB 126.
2020-02-27 | E-MTAB-8798 | biostudies-arrayexpress
Project description:Early life gut microbiota plays a critical role in gut development, maturation of the immune response and protection against enteric pathogens such as Salmonella. In this study, we investigated how different gut microbiota compositions influence the host transcriptomic signatures and susceptibility to Salmonella infection in chicks.
2025-11-30 | E-MTAB-16061 | biostudies-arrayexpress
Project description:Analysis of breast cancer survivors' gut microbiota after lifestyle intervention, during the COVID-19 lockdown, by 16S sequencing of fecal samples.
2023-01-13 | E-MTAB-12486 | biostudies-arrayexpress
Project description:Sequence-based deep learning models have become the state of the art for the analysis of the genomic regulatory code. Particularly for transcriptional enhancers, deep learning models excel at deciphering sequence features and grammar that underlie their spatiotemporal activity. To enable end-to-end enhancer modeling and design, we developed a software and modeling package, called CREsted. It combines preprocessing starting from single-cell ATAC-seq data; modeling with a choice of several architectures for training classification and regression models on either topics or pseudobulk peak heights; sequence design using multiple strategies; and downstream analysis through a collection of tools to locate transcription factor (TF) binding sites, infer the effect of a TF (activating or repressing) on enhancer accessibility, decipher enhancer grammar, and score gene loci. We demonstrate CREsted using a mouse cortex model that we validate using the BICCN collection of in vivo validated mouse brain enhancers. Classical enhancers in immune cells, including the IFN-β enhanceosome are revisited using a PBMC model, and we assess the accuracy of TF binding site predictions with ChIP-seq. Additionally, we use CREsted to compare mesenchymal-like cancer cell states between tumor types; and we investigate different fine-tuning strategies of Borzoi within CREsted, comparing their performance and explainability with CREsted models trained from scratch. Finally, we train a CREsted model on a scATAC-seq atlas of zebrafish development, and use this to design and in vivo validate cell type-specific synthetic enhancers in 3 tissues. For varying datasets we demonstrate that CREsted facilitates efficient training and analyses, enabling scrutinization of the enhancer logic and design of synthetic enhancers across tissues and species. CREsted is available at https://crested.readthedocs.io.
2025-03-28 | GSE292617 | GEO
Project description:Intracerebral hemorrhage (ICH) induces alterations in the gut microbiota composition, significantly impacting neuroinflammation post-ICH. However, the impact of gut microbiota absence on neuroinflammation following ICH-induced brain injury remain unexplored. Here, we observed that the gut microbiota absence was associated with reduced neuroinflammation, alleviated neurological dysfunction, and mitigated gut barrier dysfunction post-ICH. In contrast, recolonization of microbiota from ICH-induced SPF mice by transplantation of fecal microbiota (FMT) exacerbated brain injury and gut impairment post-ICH. Additionally, microglia with transcriptional changes mediated the protective effects of gut microbiota absence on brain injury, with Apoe emerging as a hub gene. Subsequently, Apoe deficiency in peri-hematomal microglia was associated with improved brain injury. Finally, we revealed that gut microbiota influence brain injury and gut impairment via gut-derived short-chain fatty acids (SCFA).
2024-05-13 | GSE266602 | GEO