Ontology highlight
ABSTRACT:
PROVIDER: PRJNA1184419 | ENA |
REPOSITORIES: ENA
Similar Datasets
Project description:16s rRNA sequencing data of broiler cecum contents
| PRJNA1064438 | ENA
Project description:Background- Resistant starch is a prebiotic metabolized by the gut bacteria. It has been shown to attenuate chronic kidney disease (CKD) progression in rats. Previous studies employed taxonomic analysis using 16S rRNA sequencing and untargeted metabolomics profiling. Here we expand these studies by metaproteomics, gaining new insight into the host-microbiome interaction. Methods- Differences between cecum contents in CKD rats fed a diet containing resistant starch with those fed a diet containing digestible starch were examined by comparative metaproteomics analysis. Taxonomic information was obtained using unique protein sequences. Our methodology results in quantitative data covering both host and bacterial proteins. Results - 5,834 proteins were quantified, with 947 proteins originating from the host organism. Taxonomic information derived from metaproteomics data surpassed previous 16S RNA analysis, and reached species resolutions for moderately abundant taxonomic groups. In particular, the Ruminococcaceae family becomes well resolved – with butyrate producers and amylolytic species such as R. bromii clearly visible and significantly higher while fibrolytic species such as R. flavefaciens are significantly lower with resistant starch feeding. The observed changes in protein patterns are consistent with fiber-associated improvement in CKD phenotype. Several known host CKD-associated proteins and biomarkers of impaired kidney function were significantly reduced with resistant starch supplementation. Conclusions- Metaproteomics analysis of cecum contents of CKD rats with and without resistant starch supplementation reveals changes within gut microbiota at unprecedented resolution, providing both functional and taxonomic information. Proteins and organisms differentially abundant with RS supplementation point toward a shift from mucin degraders to butyrate producers.
2018-12-18 | PXD008845 | Pride
Project description:It is well known that host-microbes and immunity interactions are influenced by dietary patterns, as well as daily environmental light-dark (LD) cycles that entrain circadian rhythms in the host. Emerging data has highlighted the importance of diet patterns and timing on the interaction among circadian rhythms, gut microbiome, and immunity, however, their impacts on LD cycles are less reported. Therefore, we aim to study how LD cycles regulate the homeostatic crosstalk between gut microbiome, hypothalamic and hepatic circadian clock oscillations and immunity. We hypothesized that different environmental LD cycles: (1) constant darkness, LD0/24; (2) short light, LD8/16; (3) normal LD cycle, LD12/12; (4) long light, LD16/8; and (5) constant light, LD24/0, may affect immunity and metabolism to varying degrees. Therefore, 240 mice were managed with chow diets (CD) and antibiotics treatments (ABX) under five different LD cycles for 42 days. The colonic (co) and cecum (ce) contents were obtained for studying their impacts on gut microbiome using 16S rRNA sequencing.
2023-03-10 | GSE226852 | GEO
Project description:Gut microbiota were assessed in 540 colonoscopy-screened adults by 16S rRNA gene sequencing of stool samples. Investigators compared gut microbiota diversity, overall composition, and normalized taxon abundance among these groups.
| 2255499 | ecrin-mdr-crc
Project description:We report the use of high-throughput sequencing technology to detect the microbial composition and abundance of mice grastic contents before and after Helicobacter pylori infection or Lactobacillus paracasei ZFM54 pretreatment/treatment. The genomic DNA was obtained by the QIAamp PowerFecal DNA Kit. Then, the DNA samples were sent to BGI Genomics Co., Ltd. (Shenzhen, China) for V3-V4 region of the 16S rRNA gene high-throughput sequencing with an Illumina MiSeq platform. DNA samples were sequenced using primers 338F (forward primer sequence ACTCCTACGGGAGGCAGCAG)-806R (reverse primer sequence GGACTACHVGGGTWTCTAAT). The sequencing analyses were carried out using silva138/16s database as a reference for the assignation of Amplicon Sequence Variant (ASV) at 100% similarity.
2022-07-27 | GSE208665 | GEO