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.
Project description:Villin-Cre+ Lsd1fl/fl (cKO) mice display an immature intestinal epithelium characterized by an incomplete differentiation of enterocytes and secretory lineages, reduced number of goblet cells and a complete loss of Paneth cells. This experiment aims to elucidate the differences in stool microbial composition derived from WT (Villin-Cre- Lsd1fl/fl) and cKO mice both in adult (2-month-old) and neonatal (14 days postpartum P14) stages. Different timepoints are crucial to understand the role of intestinal maturation in microbiome composition since said maturation is dependent on time-dependent external cues happening at P14-21 (weaning and transition from milk to solid foods).
Project description:Small RNA-Seq analysis of on stool samples from an Italian cohort of 120 healthy individuals with three dietary habits. The cohort includes 72 women and 48 men included an equal proportion of vegetarians, vegans and omnivores.
Project description:Background and Aims: RNA biomarkers derived from sloughed enterocytes would provide an ideal, non-invasive method for early detection of colorectal cancer (CRC) and precancerous adenomas. To realize this goal, a highly reliable method to isolate preserved human RNA from stool samples is needed. Here we develop a protocol to identify RNA biomarkers associated with CRC to assess the use of these biomarkers for noninvasive screening of disease. Methods: Stool samples were collected from 454 patients prior to a colonoscopy. A nucleic acid extraction protocol was developed to isolate human RNA from 330 stool samples and transcript abundances were estimated by microarray analysis. This 330-patient cohort was split into a training set of 265 individuals to develop a machine learning model and a testing set of 65 individuals to determine the model’s ability to detect colorectal neoplasms. Results: Analysis of the transcriptome from 265 individuals identified 200 transcript clusters as differentially expressed (p<0.03). These transcripts were used to build a Support Vector Machine (SVM) based model to classify 65 individuals within the testing set. This SVM algorithm attained a 95% sensitivity for precancerous adenomas and a 65% sensitivity for CRC (stage I-IV). The machine learning algorithm attained a specificity of 59% for healthy individuals and an overall accuracy of 72.3%. Conclusions: We developed an RNA-based neoplasm detection model that is sensitive for CRC and precancerous adenomas. The model allows for non-invasive assessment of tumors and could potentially be used to provide clinical guidance for individuals within the screening population for colorectal cancer.
Project description:Longitudinal analysis of Salmonella typhimurium mRNA from superspeader mouse cecal content and stool compared to in vitro Salmonella typhimurium mRNA.
Project description:The aim of study is to evaluate whether salidroside (S), tyrosol (T) and hydroxytyrosol (H) which are dietary phenylethanoids of natural origins have an influence on reversing gut dysbiosis induced by metabolic syndrome (MetS) mice. C57 BL/6J female mice induced by high fructose diet were established. All mice were adapted to the environment for 7 days with normal diet and sterile drinking water (DW), and randomly divided into 6 groups. Mice in the ND group are fed with ND and treated with normal saline. Other groups were fed with high fructose (HFru) by administration of normal saline, salidroside (S), tyrosol (T) or hydroxytyrosol (H) for 12 weeks by intragastric gavage. Fresh feces from each mouse were collected one days before the end of the experiment and temporarily placed in sterile tubules, and then snap-frozen in liquid nitrogen. Total DNA from stool bacteria was extracted using QIAamp DNA stool mini kit from Qiagen (Germantown, MD, USA) according to the manufacturer’s instructions. Illumina HiSeq sequencing analysis of the DNA samples.16S rRNA gene sequence data further revealed that S, T and H could enhance the diversity of gut microbiota. In general, the abundance of Shigella, Acinetobacter, Lactobacillus, Staphylococcus and Sporosarcina had changed significantly. These findings suggest that S, T and H probably suppress lipid accumulation and to hepatoprotective effect and improve intestinal microflora disorders to attenuate metabolic syndromes.