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.
Project description:We conducted 16S rRNA sequencing analyse on colonic contents to evaluate whether forced loss led to alterations in gut microbiota composition and function.
Project description:Metagenomic sequencing of mice with different treatments: Mice were randomly divided into donor control group (Donor + MRS), constipation model group (STC + MRS), or a Lactobacillus acidophilus treated group (STC + La): A humanized mouse model was established by intragastric administration of fecal bacterial liquid from healthy donors or STC patients on alternate days, followed by continuous administration of Lactobacillus acidophilus in treatment group. Finally, the feces of each group of mice were collected, and the intestinal microbial communities of the mice were analyzed through metagenomic sequencing. 16S rRNA sequencing of mice before and after the use antibiotics: Before and after treating the mice with antibiotics, the mice's feces were collected for 16s rRNA sequencing respectively.
Project description:What are the effects of Microcystis aeruginosa and cyanotoxin on the grass carp intestine? 16S rRNA sequencing is needed to analyze the gut microbiota.
Project description:16s RNA gene sequencing data from seawater, bed sediment and steel corrosion samples from Shoreham Harbour, UK, collected to allow bacterial species comparisons between microbially influenced corrosion, the surrounding seawater, and the sea bed sediment at the seafloor and 50cm depth below seafloor.
Project description:We found that mainstream cigarette smoking (4 cigarettes/day, 5 days/week for 2 weeks using Kentucky Research Cigarettes 3R4F) resulted in >20% decrease in the percentage of normal Paneth cell population in Atg16l1 T300A mice but showed minimal effect in wildtype littermate control mice, indicating that Atg16l1 T300A polymorphism confers sensitivity to cigarette smoking-induced Paneth cell damage. We performed 16S rRNA sequencing to identify potential microbiota changes associated with Paneth cell defect in Atg16l1 T300A mice exposed to cigarette smoking. Female mice were used at 4-5 weeks of age. Cigarette smoking was performed using smoking chamber with the dosage and schedule as described above. The fecal samples from the mice were collected for 16S rRNA sequencing analysis after completing 6 weeks of smoking.
Project description:Purpose: This study aims to compare and analyze the differences in bacterial community composition in fecal samples from mice treated with Control(DW), Vancomycin (VAN), Ampicillin (AMP), Neomycin (NEO), Metronidazole (MET), and a combination of all antibiotics (ALL, VANM) using 16S rRNA sequencing. Methods: Each antibiotics treated mice's fecal samples were collected and stored -80'c until analyzation. DNA was extracted using the NucleoSpin DNA Stool Kit (MACHEREY-NAGEL) following the manufacturer’s protocol. Metagenomic sequencing was performed on an Illumina MiSeq platform (Illumina), targeting the V3 and V4 regions of the 16S rRNA gene according to the manufacturer's instructions. PCR products were purified using AMPure XP beads, and sequencing adapters were added using the Nextera XT Index Kit (Illumina). The library was further purified with AMPure XP beads and quantified using automated electrophoresis with the TapeStation System (Agilent). Sequencing was performed using the MiSeq v3 reagent kit (Illumina), following the manufacturer’s protocol. Results: QIIME2 (v2023.02) was used to process and analyze 16S rRNA gene amplicon sequencing data, from sequence preprocessing to taxonomic classification. Paired-end sequences were merged and quality-filtered using Deblur. The resulting amplicon sequence variants (ASVs) were used for downstream analyses. Conclusions: Our study presents a comparative analysis of bacterial community composition in fecal samples from antibiotic-treated mice. We observed that microbiota composition varied distinctly depending on the type of antibiotic administered.
Project description:We aim to determine if mice in our mouse colony had similar of different microbiomes. To do this, we perfromed 16S sequencing of stool from unifected mice of the gentotypes listed below. We also looked at how infection causes dysbiosis of the mircobiome, measuring 16S sequencing over a C.rodentium infection timecourse.