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.
Project description:The impact of mono-chronic S. stercoralis infection on the gut microbiome and microbial activities in infected participants was explored. The 16S rRNA gene sequencing of a longitudinal study with 2 sets of human fecal was investigated. Set A, 42 samples were matched, and divided equally into positive (Pos) and negative (Neg) for S. stercoralis diagnoses. Set B, 20 samples of the same participant in before (Ss+PreT) and after (Ss+PostT) treatment was subjected for 16S rRNA sequences and LC-MS/MS to explore the effect of anti-helminthic treatment on microbiome proteomes.
Project description:Primary outcome(s): Analysis of the diversity and composition of the gut microbiome by 16S rRNA sequencing
Study Design: Observational Study Model : Others, Time Perspective : Prospective, Enrollment : 60, Biospecimen Retention : Collect & Archive- Sample with DNA, Biospecimen Description : Blood, Stool
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:Controlling the progression of chronic kidney disease (CKD) at an early stage is critical for reducing disease severity. A cross-sectional study of chronic kidney disease (CKD) patients at all stages with S. stercoralis infection found that helminth infection caused gut dysbiosis, which may be involved in CKD progression. Because of the variation of gut microbiome results with helminth infection, the cross-sectional study of 16S rRNA sequencing, therefore, is insufficient to draw valid conclusions and correct the effects of S. stercoralis on the early stages of CKD. Combination with other omics approach is warrant to be better understand the disease.
Project description:IL22 induces antimicrobial peptides which influnce microbiota. We used 16s rRNA gene sequencing (16s DNA-seq) to analyze the microbiota with Fc or IL-22Fc treatment.
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:Iron-rich pelagic aggregates (iron snow) were collected directly onto silicate glass filters using an electronic water pump installed below the redoxcline. RNA was extracted and library preparation was done using the NEBNext Ultra II directional RNA library prep kit for Illumina. Data was demultiplied by GATC sequencing company and adaptor was trimmed by Trimgalore. After trimming, data was processed quality control by sickle and mRNA/rRNA sequences were sorted by SortmeRNA. mRNA sequences were blast against NCBI-non redundant protein database and the outputs were meganized in MEGAN to do functional analysis. rRNA sequences were further sorted against bacterial/archeal 16S rRNA, eukaryotic 18S rRNA and 10,000 rRNA sequences of bacterial 16S rRNA, eukaryotic 18S rRNA were subset to do taxonomy analysis.
