Project description:The Aloe vera transcriptome was analysed by hybridising triplicate samples of root and leaf tissue to the Affymetrix Arabidopsis ATH1 array. In total, 7 samples were hybridised to the array. Samples consisted of 1 genomic DNA, and triplicate samples of leaf and root RNA.
Project description:The Aloe vera transcriptome was analysed by hybridising triplicate samples of root and leaf tissue to the Affymetrix Arabidopsis ATH1 array.
Project description:Aloe plant species have been used for centuries in traditional medicine and reported to be an important source of natural products. However, despite the large number of species within the Aloe genus, only a few of them have been investigated chemotaxonomically. A Molecular Network approach was used to highlight the different chemical classes characterizing the leaves of five Aloe species: Aloe macra, Aloe vera, Aloe tormentorii, Aloe ferox and Aloe purpurea. Aloe macra, A. tormentorii and A. purpurea are endemic from the Mascarene Islands comprising Reunion, Mauritius and Rodrigues. UHPLC-MS/MS analysis followed by a dereplication process allowed the characterization of 93 metabolites. The newly developed MolNotator algorithm was used as a tool for molecular networking and allowed a better exploration of the Aloe metabolome chemodiversity. The five species appeared to be rich in polyphenols (anthracene derivatives, flavonoids, phenolic acids). Therefore, total phenolic content and antioxidant activity of the five species were evaluated, and a DPPH-On-Line-HPLC assay was used to determine the metabolites responsible for the radical scavenging activity. The use of computational tools allowed a better description of the chemotaxonomy of five Aloe species, which showed differences in their metabolite composition, both qualitative and quantitative. Moreover, the molecular network approach allowed the identification of metabolites responsible for the antioxidant activity.
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.
