Draft genome sequence of an environmental multidrug-resistant Klebsiella pneumoniae ST340/CC258 harbouring blaCTX-M-15 and blaKPC-2 genes

Anthropogenic activities, including the release of wastewater and sewage from hospitals, have contributed to the contamination of aquatic environments, raising a concern to public health. In this study, we present the first draft genome sequence of a Klebsiella pneumoniae strain (Kp171, TIET-4200) belonging to the high-risk hospital-associated clonal lineage ST340/CC258, which was recovered from a water sample collected in an urban river in Brazil.

High-virulence CMY-2- and CTX-M-2-producing avian pathogenic Escherichia coli strains isolated from commercial turkeys

This study reports the high-virulence phylogenetic backgrounds of CMY-2- and CTX-M-2-producing avian pathogenic Escherichia coli strains isolated from turkeys sent to slaughter and condemned by airsacculitis in Brazil. Among 300 air sac samples, seven E. coli strains produced plasmid-mediated CMY-2-type AmpC, of which three carried also the bla_CTX-M-2 Extended Spectrum Beta-Lactamase encoding gene. Interestingly, the transfer of the bla_CMY-2 gene was positive for three E. coli strains, being associated with the presence of IncI1 plasmids. The complete sequence of the representative pJB10 plasmid revealed that the bla_CMY-2 gene was within a transposon-like element in the classical genetic environment consisting of tnpA-bla_CMY-2-blc-sugE structure. This plasmid with 94-kb belonged to the sequence type (ST) 12 among IncI1 plasmids, which has been associated with the worldwide spread of bla_CMY-2 among Salmonella enterica and E. coli. Furthermore, to the best of our knowledge, this is the first complete sequence of a CMY-2-encoding plasmid derived from an Escherichia coli isolated from food-producing animals in Latin America.

The genome of Anopheles darlingi, the main neotropical malaria vector

Anopheles darlingi is the principal neotropical malaria vector, responsible for more than a million cases of malaria per year on the American continent. Anopheles darlingi diverged from the African and Asian malaria vectors ∼100 million years ago (mya) and successfully adapted to the New World environment. Here we present an annotated reference A. darlingi genome, sequenced from a wild population of males and females collected in the Brazilian Amazon. A total of 10 481 predicted protein-coding genes were annotated, 72% of which have their closest counterpart in Anopheles gambiae and 21% have highest similarity with other mosquito species. In spite of a long period of divergent evolution, conserved gene synteny was observed between A. darlingi and A. gambiae. More than 10 million single nucleotide polymorphisms and short indels with potential use as genetic markers were identified. Transposable elements correspond to 2.3% of the A. darlingi genome. Genes associated with hematophagy, immunity and insecticide resistance, directly involved in vector–human and vector–parasite interactions, were identified and discussed. This study represents the first effort to sequence the genome of a neotropical malaria vector, and opens a new window through which we can contemplate the evolutionary history of anopheline mosquitoes. It also provides valuable information that may lead to novel strategies to reduce malaria transmission on the South American continent. The A. darlingi genome is accessible at www.labinfo.lncc.br/index.php/anopheles-darlingi.

PIPS: pathogenicity island prediction software

The adaptability of pathogenic bacteria to hosts is influenced by the genomic plasticity of the bacteria, which can be increased by such mechanisms as horizontal gene transfer. Pathogenicity islands play a major role in this type of gene transfer because they are large, horizontally acquired regions that harbor clusters of virulence genes that mediate the adhesion, colonization, invasion, immune system evasion, and toxigenic properties of the acceptor organism. Currently, pathogenicity islands are mainly identified in silico based on various characteristic features: (1) deviations in codon usage, G+C content or dinucleotide frequency and (2) insertion sequences and/or tRNA genetic flanking regions together with transposase coding genes. Several computational techniques for identifying pathogenicity islands exist. However, most of these techniques are only directed at the detection of horizontally transferred genes and/or the absence of certain genomic regions of the pathogenic bacterium in closely related non-pathogenic species. Here, we present a novel software suite designed for the prediction of pathogenicity islands (pathogenicity island prediction software, or PIPS). In contrast to other existing tools, our approach is capable of utilizing multiple features for pathogenicity island detection in an integrative manner. We show that PIPS provides better accuracy than other available software packages. As an example, we used PIPS to study the veterinary pathogen Corynebacterium pseudotuberculosis, in which we identified seven putative pathogenicity islands.