Oriane Matte-Tailliez

Molecular diversity of new Thermococcales isolates from a single area of hydrothermal deep-sea vents as revealed by randomly amplified polymorphic DNA fingerprinting and 16S rRNA gene sequence analysis

ABSTRACT Members of the Thermococcales are anaerobic Archaea belonging to the kingdom Euryarchaea that are studied in many laboratories as model organisms for hyperthermophiles. We describe here a molecular analysis of 86 new Thermococcales isolates collected from six different chimneys of a single hydrothermal field located in the 13°N 104°W segment of the East Pacific ridge at a depth of 2,330 m. These isolates were sorted by randomly amplified polymorphic DNA (RAPD) fingerprinting into nine groups, and nine unique RAPD profiles were obtained. One RAPD group corresponds to new isolates of Thermococcus hydrothermalis, whereas all other groups and isolates with unique profiles are different from the 22 reference strains included in this study. Analysis of 16S rRNA gene sequences of representatives of each RAPD group and unique profiles showed that one group corresponds to Pyrococcus strains, whereas all the other isolates are Thermococcus strains. We estimated that our collection may contain at least 11 new species. These putative species, isolated from a single area of hydrothermal deep-sea vents, are dispersed in the 16S rRNA tree among the reference strains previously isolated from diverse hot environments (terrestrial, shallow water, hydrothermal vents) located around the world, suggesting that there is a high degree of dispersal of Thermococcales. About one-half of our isolates contain extrachromosomal elements that could be used to search for novel replication proteins and to develop genetic tools for hyperthermophiles.

Mining texts by association rules discovery in a technical corpus

The text mining tools proposed in this paper extract association rules from a set of specialized and homogeneous texts (corpus). This tool is built in several steps and, at each of them, the expert plays a fundamental role. The first step extracts the terms from the corpus, and clusters them in classes by semantic similarity, associating each class to a concept meaningful to a field expert. Using the knowledge thus obtained, the corpus generates a table of concept frequencies in the texts. Next, we discretize the values of this table, and finally we are able to extract association rules among the concept occurrences.

Immersive Visualization for Genome Exploration and Analysis

Genomic and post-genomic data processing comprising genome sequencing, annotation and large scale genome technology produce increasing amounts of data which need to be analyzed. Visualization is a powerful analytical technique that uses the ability of the human brain to process complex data. Biological data were already explored by virtual-reality. Whereas the proteins are the subject of many works of modeling and visualization, still very little work has been done on the DNA. 3D graphical representation of DNA primary sequences allows complexity reduction while transforming 3D spatial representation into a numerical matrix to facilitate comparative studies of DNA. Two biological application were addressed in this paper that show the use of immersive visualization to help the users at genomic analysis phases. The first application is particularly concerned with the visualization of genes sharing similar expression factors within groups. The second one is focused on 3D shape modeling of exonintron elements within genes organization.