Ralstonia solanacearum is a devastating, soil-borne plant pathogen with a global distribution and an unusually wide host range. It is a model system for the dissection of molecular determinants governing pathogenicity. We present here the complete genome sequence and its analysis of strain GMI1000. The 5.8-megabase (Mb) genome is organized into two replicons: a 3.7-Mb chromosome and a 2.1-Mb megaplasmid. Both replicons have a mosaic structure providing evidence for the acquisition of genes through horizontal gene transfer. Regions containing genetically mobile elements associated with the percentage of G+C bias may have an important function in genome evolution. The genome encodes many proteins potentially associated with a role in pathogenicity. In particular, many putative attachment factors were identified. The complete repertoire of type III secreted effector proteins can be studied. Over 40 candidates were identified. Comparison with other genomes suggests that bacterial plant pathogens and animal pathogens harbour distinct arrays of specialized type III-dependent effectors.

As part of the goal to generate a detailed transcript map for Arabidopsis thaliana, 1152 single run sequences (expressed sequence tags or ESTs) have been determined from cDNA clones taken at random in libraries prepared from different sources of plant material: developing siliques, etiolated seedlings, flower buds, and cultured cells. Eight hundred and ninety-five different genes could be identified, 32% of which showed significant similarity to existing sequences in Arabidopsis and an array of other organisms. These sequences in combination with their positioning on the Arabidopsis genetic map will not only constitute a new set of molecular markers for genome analysis in Arabidopsis but also provide a direct route for the in vivo analysis of their gene products. The sequences have been made available to the public databases.

The aim of this study was to evaluate the diagnostic value of technetium-99m hexamethylpropylene amine oxime leucocyte scintigraphy (HMPAO-LS) by means of a retrospective review of 116 patients divided into three groups of bone and joint infection. One hundred and thirty-one LS examinations were performed, and 143 sites analysed. The final diagnosis of infection was based on surgical, histological and bacteriological data and follow-up. Ninety-four suspected localizations were examined in group 1, which included 74 patients with an infection suspected to involve orthopaedic implants. In this group, there were 38 true-positives, 1 false-negative, 49 true-negatives and 6 false-positives. Surgical confirmation was obtained in 34 cases. In group 2 (24 patients with suspected osteomyelitis), there were 27 localizations of which 14 were true-positives and 13 were true-negatives (including seven surgical confirmations). In group 3 (18 patients suspected of septic arthritis) there were eight true-positives, two false-negatives, ten true-negatives and two false-positives. Overall sensitivity of 99mTc-HMPAO-LS for the detection of bone and joint infection was 95%, with a specificity of 90% (group 1: sensitivity 97%, specificity 89%; group 2: 100% and 100%; group 3: 80% and 83%). It may be concluded that HMPAO-LS is an effective tool for the diagnosis of both bone infection involving implants and chronic osteomyelitis.

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We describe FrameD, a program that predicts coding regions in prokaryotic and matured eukaryotic sequences. Initially targeted at gene prediction in bacterial GC rich genomes, the gene model used in FrameD also allows to predict genes in the presence of frameshifts and partially undetermined sequences which makes it also very suitable for gene prediction and frameshift correction in unfinished sequences such as EST and EST cluster sequences. Like recent eukaryotic gene prediction programs, FrameD also includes the ability to take into account protein similarity information both in its prediction and its graphical output. Its performances are evaluated on different bacterial genomes. The web site (http://genopole.toulouse.inra.fr/bioinfo/FrameD/FD) allows direct prediction, sequence correction and translation and the ability to learn new models for new organisms.