2026-10-14T15:43:28Z https://www.scidb.cn/oai

10.57760/sciencedb.32968 2026-08-18T10:20:39Z

2026-08-18 Fecal microbiota 16S rRNA sequencing of aged donors and FMT recipients in a neonatal overfeeding mouse model doi:10.57760/sciencedb.32968 en This dataset comprises raw 16S rRNA gene sequencing reads from a study on Fecal Microbiota Transplantation (FMT) in an aging mouse model. We first employed an established neonatal overfeeding model by reducing litter size, assigning litters to either 4 pups per dam (Overfed group) or 8 pups per dam (Normal-fed control group). For the FMT experiment, donor fecal material was collected from 24-month-old normal-fed or overfed mice and transplanted into 12-month-old recipients maintained strictly on a standard chow diet (rNormal-Chow and rOver-Chow), fecal samples were prospectively collected at the end of the intervention. Microbial genomic DNA was extracted from fecal samples using the DNA Stool Mini Kit (TIANGEN). The V3-V4 hypervariable regions of the 16S rRNA gene were amplified using universal primers (515F/806R). Sequencing libraries were constructed with the NEB Next® Ultra™ II FS DNA PCR-free Library Prep Kit (New England Biolabs, E7430L) to ensure high-quality, bias-free amplicons. High-throughput paired-end sequencing was performed on the Illumina NovaSeq 6000 platform (Illumina, San Diego, CA, USA) through Novogene Co., Ltd (Novogene, Beijing, China). The dataset includes raw sequencing reads which were subsequently processed by merging with FLASH and quality-filtering via Fastp. Subsequently, operational taxonomic units (OTUs) were generated using UPARSE pipeline within QIIME1 framework, with sequences of ≥ 97% similarity assigned to the same OTUs. The data is presented in FASTQ format, representing 32 biological samples with consistent sequencing depth and high taxonomic resolution. donor; recipient; normal-fed; overfed Yeyu Song Jingyi Xu Jingjie Zhao Yameng Liu Zhuo-Xian Meng Jian-Gao Fan Cen Xie EMBARGO https://creativecommons.org/licenses/by-nc-sa/4.0/ dataset Science Data Bank