Project description:Microbial RNAseq analysis of cecal and fecal samples collected from mice colonized with the microbiota of human twins discordant for obesity. Samples were colleted at the time of sacrifice, or 15 days after colonization from mice gavaged with uncultured or cultured fecal microbiota from the lean twins or their obese co-twins. Samples were sequenced using Illumina HiSeq technology, with 101 paired end chemistry. Comparisson of microbial gene expression between the microbiota of lean and obese twins fed a Low fat, rich in plant polysaccharide diet.
Project description:We found that low protein diet consumption resulted in decrease in the percentage of normal Paneth cell population in wild type mice, indicating that low protein diet could negatively affect Paneth cell function. We performed fecal microbiota composition profiling. Male mice were used at 4-5 weeks of age. Fecal samples were collected for microbiome analysis.
Project description:We found that western diet consumption resulted in decrease in the percentage of normal Paneth cell population in wild type mice, indicating that western diet could negatively affect Paneth cell function. Subsequent generations of western diet consumption further reduced percentages of normal Paneth cell population. We performed fecal microbiota composition profiling. Male mice were used at 4-5 weeks of age. Fecal samples were collected for microbiome analysis.
Project description:A metaproteomics analysis was conducted on the infant fecal microbiome to characterize global protein expression in 8 samples obtained from infants with a range of early-life experiences. Samples included breast-, formula- or mixed-fed, mode of delivery, and antibiotic treatment and one set of monozygotic twins. Although label-free mass spectrometry-based proteomics is routinely used for the identification and quantification of thousands of proteins in complex samples, the metaproteomic analysis of the gut microbiome presents particular technical challenges. Among them: the extreme complexity and dynamic range of member taxa/species, the need for matched, well-annotated metagenomics databases, and the high inter-protein sequence redundancy/similarity between related members. In this study, a metaproteomic approach was developed for assessment of the biological phenotype and functioning, as a complement to 16S rRNA sequencing analysis to identify constituent taxa. A sample preparation method was developed for recovery and lysis of bacterial cells, followed by trypsin digestion, and pre-fractionation using Strong Cation Exchange chromatography. Samples were then subjected to high performance LC-MS/MS. Data was searched against the Human Microbiome Project database, and a homology-based meta-clustering strategy was used to combine peptides from multiple species into representative proteins. Bacterial taxonomies were also identified, based on species-specific protein sequences, and protein metaclusters were assigned to pathways and functional groups. The results obtained demonstrate the applicability of this approach for performing qualitative comparisons of human fecal microbiome composition, physiology and metabolism, and also provided a more detailed assessment of microbial composition in comparison to 16S rRNA.
