Intestinal microbiota in health and disease

Intestinal microbiota is constantly changing depending on various conditions. It is a well known fact that in different diseases shifts in intestinal microbiota are observed. But treatment of such dysbiotic states remains a big challenge.

The aim of this research is to find the most efficient autoprobiotic for the treatment of patients with Irritable Bowel Syndrome (IBS). It can be achieved by the analysis of changes in microbiota towards its normalization during treatment.

First of all experiments were performed on a rat dysbiosis model. Combination of ampicillin and metronidazole were used for 3 days to cause dysbiosis. The first control group was getting saline solution for 5 days after antibiotics treatment and the second group for the duration of the experiment (8 days). After that rats were receiving different autoprobiotics for 5 days. Fecal samples were taken for sequencing at the 0, 3’rd and the 8’th days of the experiment. Bacterial DNA extracted from feces was sequenced with Illumina MiSeq platform. Paired-end reads were obtained using primers to V3-V4 region of the 16S gene. Then reads were merged with PEAR, classified and clustered into OTUs using RDP Classifier. This pipeline was chosen after benchmarking other tools. Visualisation of the microbiota composition in rat samples and as well as the consequent analysis was performed in R using phyloseq package.

Eventually we have tried different tools for metagenomic analysis and optimized our analysis pipeline. But more experimental data is needed to make conclusions about the most effective autoprobiotic in animal to proceed to experiments with people.