Project description:Hypericum perforatum extracts have been used as dietary supplements to treat conditions including mild-moderate depression and inflammation. A group of four bioactive constituents were identified from an active fraction of the extract. In order to identify the mechanism for the potential anti-inflammatory activity of the identified compounds, we used Affymatrix microarray to study the gene expression profile impacteded by these compounds, as well as the active fraction in LPS-stimulated mouse macrophages. We treated RAW264.7 mouse macrophages with DMSO control, active fraction from Hypericum perforaum extract, and a combination of the 4 putative bioactive compounds, called the 4-component system, all with and without LPS induction. A total of six treatment combinations were included in the final gene expression analysis using microarray.
Project description:Analyses of new genomic, transcriptomic or proteomic data commonly result in trashing many unidentified data escaping the ‘canonical’ DNA-RNA-protein scheme. Testing systematic exchanges of nucleotides over long stretches produces inversed RNA pieces (here named “swinger” RNA) differing from their template DNA. These may explain some trashed data. Here analyses of genomic, transcriptomic and proteomic data of the pathogenic Tropheryma whipplei according to canonical genomic, transcriptomic and translational 'rules' resulted in trashing 58.9% of DNA, 37.7% RNA and about 85% of mass spectra (corresponding to peptides). In the trash, we found numerous DNA/RNA fragments compatible with “swinger” polymerization. Genomic sequences covered by «swinger» DNA and RNA are 3X more frequent than expected by chance and explained 12.4 and 20.8% of the rejected DNA and RNA sequences, respectively. As for peptides, several match with “swinger” RNAs, including some chimera, translated from both regular, and «swinger» transcripts, notably for ribosomal RNAs. Congruence of DNA, RNA and peptides resulting from the same swinging process suggest that systematic nucleotide exchanges increase coding potential, and may add to evolutionary diversification of bacterial populations.
