Phylogenetic analyses are central to many research areas in biology and typically involve the identification of homologous sequences, their multiple alignment, the phylogenetic reconstruction and the graphical representation of the inferred tree. The Phylogeny.fr platform transparently chains programs to automatically perform these tasks. It is primarily designed for biologists with no experience in phylogeny, but can also meet the needs of specialists; the first ones will find up-to-date tools chained in a phylogeny pipeline to analyze their data in a simple and robust way, while the specialists will be able to easily build and run sophisticated analyses. Phylogeny.fr offers three main modes. The ‘One Click’ mode targets non-specialists and provides a ready-to-use pipeline chaining programs with recognized accuracy and speed: MUSCLE for multiple alignment, PhyML for tree building, and TreeDyn for tree rendering. All parameters are set up to suit most studies, and users only have to provide their input sequences to obtain a ready-to-print tree. The ‘Advanced’ mode uses the same pipeline but allows the parameters of each program to be customized by users. The ‘A la Carte’ mode offers more flexibility and sophistication, as users can build their own pipeline by selecting and setting up the required steps from a large choice of tools to suit their specific needs. Prior to phylogenetic analysis, users can also collect neighbors of a query sequence by running BLAST on general or specialized databases. A guide tree then helps to select neighbor sequences to be used as input for the phylogeny pipeline. Phylogeny.fr is available at: http://www.phylogeny.fr/

Genes differentially expressed in different tissues, during development, or during specific pathologies are of foremost interest to both basic and pharmaceutical research. “Transcript profiles” or “digital Northerns” are generated routinely by partially sequencing thousands of randomly selected clones from relevant cDNA libraries. Differentially expressed genes can then be detected from variations in the counts of their cognate sequence tags. Here we present the first systematic study on the influence of random fluctuations and sampling size on the reliability of this kind of data. We establish a rigorous significance test and demonstrate its use on publicly available transcript profiles. The theory links the threshold of selection of putatively regulated genes (e.g., the number of pharmaceutical leads) to the fraction of false positive clones one is willing to risk. Our results delineate more precisely and extend the limits within which digital Northern data can be used.

We recently reported the discovery and preliminary characterization of Mimivirus, the largest known virus, with a 400-nanometer particle size comparable to mycoplasma. Mimivirus is a double-stranded DNA virus growing in amoebae. We now present its 1,181,404–base pair genome sequence, consisting of 1262 putative open reading frames, 10% of which exhibit a similarity to proteins of known functions. In addition to exceptional genome size, Mimivirus exhibits many features that distinguish it from other nucleocytoplasmic large DNA viruses. The most unexpected is the presence of numerous genes encoding central protein-translation components, including four amino-acyl transfer RNA synthetases, peptide release factor 1, translation elongation factor EF-TU, and translation initiation factor 1. The genome also exhibits six tRNAs. Other notable features include the presence of both type I and type II topoisomerases, components of all DNA repair pathways, many polysaccharide synthesis enzymes, and one intein-containing gene. The size and complexity of the Mimivirus genome challenge the established frontier between viruses and parasitic cellular organisms. This new sequence data might help shed a new light on the origin of DNA viruses and their role in the early evolution of eukaryotes.

Acinetobacter baumannii is a species of nonfermentative gram-negative bacteria commonly found in water and soil. This organism was susceptible to most antibiotics in the 1970s. It has now become a major cause of hospital-acquired infections worldwide due to its remarkable propensity to rapidly acquire resistance determinants to a wide range of antibacterial agents. Here we use a comparative genomic approach to identify the complete repertoire of resistance genes exhibited by the multidrug-resistant A. baumannii strain AYE, which is epidemic in France, as well as to investigate the mechanisms of their acquisition by comparison with the fully susceptible A. baumannii strain SDF, which is associated with human body lice. The assembly of the whole shotgun genome sequences of the strains AYE and SDF gave an estimated size of 3.9 and 3.2 Mb, respectively. A. baumannii strain AYE exhibits an 86-kb genomic region termed a resistance island—the largest identified to date—in which 45 resistance genes are clustered. At the homologous location, the SDF strain exhibits a 20 kb-genomic island flanked by transposases but devoid of resistance markers. Such a switching genomic structure might be a hotspot that could explain the rapid acquisition of resistance markers under antimicrobial pressure. Sequence similarity and phylogenetic analyses confirm that most of the resistance genes found in the A. baumannii strain AYE have been recently acquired from bacteria of the genera Pseudomonas, Salmonella, or Escherichia. This study also resulted in the discovery of 19 new putative resistance genes. Whole-genome sequencing appears to be a fast and efficient approach to the exhaustive identification of resistance genes in epidemic infectious agents of clinical significance. The bacterial species Acinetobacter baumannii is a major cause of hospital-acquired infection throughout the world, and it is an increasing public health concern due to its increasing resistance to antibiotic treatment. Coincidently, a high incidence of multidrug-resistant A. baumannii bloodstream infections was recently reported in US Army service members injured during Afghanistan and Iraq/Kuwait military operations. A. baumannii exhibits a remarkable ability to rapidly develop antibiotic resistance, which led from fully susceptible to multidrug-resistant strains within three decades. The authors used whole-genome sequencing and bioinformatic analyses to identify the complete repertoire of resistance genes exhibited by the multidrug-resistant A. baumannii strain AYE, which is epidemic in France, and to investigate the mechanisms of their acquisition by comparison with the fully susceptible A. baumannii strain SDF, which is associated with human body lice. This study led to the discovery in the AYE genome of an 86-kb region called a resistance “island”—the largest identified to date—that contains a cluster of 45 resistance genes. The homologous location in the susceptible strain, curiously, exhibited a 20-kb genomic island that is devoid of resistance markers. This ability to “switch” its genomic structure probably explains the unmatched speed at which A. baumannii captures resistance markers when under antibacterial pressure, such as is found in hospital intensive care units.