Project description:To address the role of gut microbiota in the development of paclitaxel-induced peripheral neuropathy (PIPN), we performed 16S rRNA sequencing analysis of feces samples at 14 days and 28 days after the initiation of paclitaxel or vehicle injections.
Project description:This study aimed to analyze changes in gut microbiota composition in mice after transplantation of fecal microbiota (FMT, N = 6) from the feces of NSCLC patients by analyzing fecal content using 16S rRNA sequencing, 10 days after transplantation. Specific-pathogen-free (SPF) mice were used for each experiments (N=4) as controls.
Project description:Nitrate-reducing iron(II)-oxidizing bacteria are widespread in the environment contribute to nitrate removal and influence the fate of the greenhouse gases nitrous oxide and carbon dioxide. The autotrophic growth of nitrate-reducing iron(II)-oxidizing bacteria is rarely investigated and poorly understood. The most prominent model system for this type of studies is enrichment culture KS, which originates from a freshwater sediment in Bremen, Germany. To gain insights in the metabolism of nitrate reduction coupled to iron(II) oxidation under in the absence of organic carbon and oxygen limited conditions, we performed metagenomic, metatranscriptomic and metaproteomic analyses of culture KS. Raw sequencing data of 16S rRNA amplicon sequencing, shotgun metagenomics (short reads: Illumina; long reads: Oxford Nanopore Technologies), metagenome assembly, raw sequencing data of shotgun metatranscriptomes (2 conditions, triplicates) can be found at SRA in https://www.ncbi.nlm.nih.gov/bioproject/PRJNA682552. This dataset contains proteomics data for 2 conditions (heterotrophic and autotrophic growth conditions) in triplicates.
Project description:To explore the effects of gut microbiota of young (8 weeks) or old mice (18～20 months) on stroke, feces of young (Y1-Y9) and old mice (O6-O16) were collected and analyzed by 16s rRNA sequencing. Then stroke model was established on young mouse receive feces from old mouse (DOT1-15) and young mouse receive feces from young mouse (DYT1-15). 16s rRNA sequencing were also performed for those young mice received feces from young and old mice.
Project description:<p><strong>BACKGROUND:</strong> The human intestinal microbiome plays a central role in overall health status, especially in early life stages. 16S rRNA amplicon sequencing is used to profile its taxonomic composition; however, multiomic approaches have been proposed as the most accurate methods for study of the complexity of the gut microbiota. In this study, we propose an optimized method for bacterial diversity analysis that we validated and complemented with metabolomics by analyzing fecal samples.</p><p><strong>METHODS:</strong> Forty-eight different analytical combinations regarding (1) 16S rRNA variable region sequencing, (2) a feature selection approach, and (3) taxonomy assignment methods were tested. A total of 18 infant fecal samples grouped depending on the type of feeding were analyzed by the proposed 16S rRNA workflow and by metabolomic analysis.</p><p><strong>RESULTS:</strong> The results showed that the sole use of V4 region sequencing with ASV identification and VSEARCH for taxonomy assignment produced the most accurate results. The application of this workflow showed clear differences between fecal samples according to the type of feeding, which correlated with changes in the fecal metabolic profile.</p><p><strong>CONCLUSION:</strong> A multiomic approach using real fecal samples from 18 infants with different types of feeding demonstrated the effectiveness of the proposed 16S rRNA-amplicon sequencing workflow.</p>
