Raoul J. P. Bonnal

Whole-Genome Pyrosequencing of an Epidemic Multidrug-Resistant Acinetobacter baumannii Strain Belonging to the European Clone II Group

ABSTRACT The whole-genome sequence of an epidemic, multidrug-resistant Acinetobacter baumannii strain (strain ACICU) belonging to the European clone II group and carrying the plasmid-mediated blaOXA-58 carbapenem resistance gene was determined. The A. baumannii ACICU genome was compared with the genomes of A. baumannii ATCC 17978 and Acinetobacter baylyi ADP1, with the aim of identifying novel genes related to virulence and drug resistance. A. baumannii ACICU has a single chromosome of 3,904,116 bp (which is predicted to contain 3,758 genes) and two plasmids, pACICU1 and pACICU2, of 28,279 and 64,366 bp, respectively. Genome comparison showed 86.4% synteny with A. baumannii ATCC 17978 and 14.8% synteny with A. baylyi ADP1. A conspicuous number of transporters belonging to different superfamilies was predicted for A. baumannii ACICU. The relative number of transporters was much higher in ACICU than in ATCC 17978 and ADP1 (76.2, 57.2, and 62.5 transporters per Mb of genome, respectively). An antibiotic resistance island, AbaR2, was identified in ACICU and had plausibly evolved by reductive evolution from the AbaR1 island previously described in multiresistant strain A. baumannii AYE. Moreover, 36 putative alien islands (pAs) were detected in the ACICU genome; 24 of these had previously been described in the ATCC 17978 genome, 4 are proposed here for the first time and are present in both ATCC 17978 and ACICU, and 8 are unique to the ACICU genome. Fifteen of the pAs in the ACICU genome encode genes related to drug resistance, including membrane transporters and ex novo acquired resistance genes. These findings provide novel insight into the genetic basis of A. baumannii resistance.

BioRuby: bioinformatics software for the Ruby programming language

Summary: The BioRuby software toolkit contains a comprehensive set of free development tools and libraries for bioinformatics and molecular biology, written in the Ruby programming language. BioRuby has components for sequence analysis, pathway analysis, protein modelling and phylogenetic analysis; it supports many widely used data formats and provides easy access to databases, external programs and public web services, including BLAST, KEGG, GenBank, MEDLINE and GO. BioRuby comes with a tutorial, documentation and an interactive environment, which can be used in the shell, and in the web browser. Availability: BioRuby is free and open source software, made available under the Ruby license. BioRuby runs on all platforms that support Ruby, including Linux, Mac OS X and Windows. And, with JRuby, BioRuby runs on the Java Virtual Machine. The source code is available from http://www.bioruby.org/. Contact: katayama@bioruby.org

The long intergenic noncoding RNA landscape of human lymphocytes highlights the regulation of T cell differentiation by linc-MAF-4

Long noncoding RNAs are emerging as important regulators of cellular functions, but little is known of their role in the human immune system. Here we investigated long intergenic noncoding RNAs (lincRNAs) in 13 subsets of T lymphocytes and B lymphocytes by next-generation sequencing–based RNA sequencing (RNA-seq analysis) and de novo transcriptome reconstruction. We identified over 500 previously unknown lincRNAs and described lincRNA signatures. Expression of linc-MAF-4, a chromatin-associated lincRNA specific to the TH1 subset of helper T cells, was inversely correlated with expression of MAF, a TH2-associated transcription factor. Downregulation of linc-MAF-4 skewed T cell differentiation toward the TH2 phenotype. We identified a long-distance interaction between the genomic regions of the gene encoding linc-MAF-4 and MAF, where linc-MAF-4 associated with the chromatin modifiers LSD1 and EZH2; this suggested that linc-MAF-4 regulated MAF transcription through the recruitment of chromatin modifiers. Our results demonstrate a key role for lincRNA in T lymphocyte differentiation.

Complete Mitochondrial Genome Sequence of the Tyrolean Iceman

The Tyrolean Iceman was a witness to the Neolithic-Copper Age transition in Central Europe 5350-5100 years ago, and his mummified corpse was recovered from an Alpine glacier on the Austro-Italian border in 1991 [1]. Using a mixed sequencing procedure based on PCR amplification and 454 sequencing of pooled amplification products, we have retrieved the first complete mitochondrial-genome sequence of a prehistoric European. We have then compared it with 115 related extant lineages from mitochondrial haplogroup K. We found that the Iceman belonged to a branch of mitochondrial haplogroup K1 that has not yet been identified in modern European populations. This is the oldest complete Homo sapiens mtDNA genome generated to date. The results point to the potential significance of complete-ancient-mtDNA studies in addressing questions concerning the genetic history of human populations that the phylogeography of modern lineages is unable to tackle.

Transcriptional Landscape of Human Tissue Lymphocytes Unveils Uniqueness of Tumor-Infiltrating T Regulatory Cells

Summary Tumor-infiltrating regulatory T lymphocytes (Treg) can suppress effector T cells specific for tumor antigens. Deeper molecular definitions of tumor-infiltrating-lymphocytes could thus offer therapeutic opportunities. Transcriptomes of T helper 1 (Th1), Th17, and Treg cells infiltrating colorectal or non-small-cell lung cancers were compared to transcriptomes of the same subsets from normal tissues and validated at the single-cell level. We found that tumor-infiltrating Treg cells were highly suppressive, upregulated several immune-checkpoints, and expressed on the cell surfaces specific signature molecules such as interleukin-1 receptor 2 (IL1R2), programmed death (PD)-1 Ligand1, PD-1 Ligand2, and CCR8 chemokine, which were not previously described on Treg cells. Remarkably, high expression in whole-tumor samples of Treg cell signature genes, such as LAYN, MAGEH1, or CCR8, correlated with poor prognosis. Our findings provide insights into the molecular identity and functions of human tumor-infiltrating Treg cells and define potential targets for tumor immunotherapy.

Role of microRNAs and long‐non‐coding RNAs in CD4+ T‐cell differentiation

CD4+ T lymphocytes orchestrate adaptive immune responses by differentiating into various subsets of effector T cells such as T‐helper 1 (Th1), Th2, Th17, and regulatory T cells. These subsets have been generally described by master transcription factors that dictate the expression of cytokines and receptors, which ultimately define lymphocyte effector functions. However, the view of T‐lymphocyte subsets as stable and terminally differentiated lineages has been challenged by increasing evidence of functional plasticity within CD4+ T‐cell subsets, which implies flexible programming of effector functions depending on time and space of T‐cell activation. An outstanding question with broad basic and traslational implications relates to the mechanisms, besides transcriptional regulation, which define the plasticity of effector functions. In this study, we discuss the emerging role of regulatory non‐coding RNAs in T‐cell differentiation and plasticity. Not only microRNAs have been proven to be important for CD4+ T‐cell differentiation, but it is also likely that the overall T‐cell functioning is the result of a multilayered network composed by coding RNAs as well as by short and long non‐coding RNAs. The integrated study of all the nodes of this network will provide a comprehensive view of the molecular mechanisms underlying T‐cell functions in health and disease.

BioHackathon series in 2011 and 2012: penetration of ontology and linked data in life science domains

The application of semantic technologies to the integration of biological data and the interoperability of bioinformatics analysis and visualization tools has been the common theme of a series of annual BioHackathons hosted in Japan for the past five years. Here we provide a review of the activities and outcomes from the BioHackathons held in 2011 in Kyoto and 2012 in Toyama. In order to efficiently implement semantic technologies in the life sciences, participants formed various sub-groups and worked on the following topics: Resource Description Framework (RDF) models for specific domains, text mining of the literature, ontology development, essential metadata for biological databases, platforms to enable efficient Semantic Web technology development and interoperability, and the development of applications for Semantic Web data. In this review, we briefly introduce the themes covered by these sub-groups. The observations made, conclusions drawn, and software development projects that emerged from these activities are discussed.

RSSsite: a reference database and prediction tool for the identification of cryptic Recombination Signal Sequences in human and murine genomes

Recombination signal sequences (RSSs) flanking V, D and J gene segments are recognized and cut by the VDJ recombinase during development of B and T lymphocytes. All RSSs are composed of seven conserved nucleotides, followed by a spacer (containing either 12 ± 1 or 23 ± 1 poorly conserved nucleotides) and a conserved nonamer. Errors in V(D)J recombination, including cleavage of cryptic RSS outside the immunoglobulin and T cell receptor loci, are associated with oncogenic translocations observed in some lymphoid malignancies. We present in this paper the RSSsite web server, which is available from the address http://www.itb.cnr.it/rss. RSSsite consists of a web-accessible database, RSSdb, for the identification of pre-computed potential RSSs, and of the related search tool, DnaGrab, which allows the scoring of potential RSSs in user-supplied sequences. This latter algorithm makes use of probability models, which can be recasted to Bayesian network, taking into account correlations between groups of positions of a sequence, developed starting from specific reference sets of RSSs. In validation laboratory experiments, we selected 33 predicted cryptic RSSs (cRSSs) from 11 chromosomal regions outside the immunoglobulin and TCR loci for functional testing.

Biogem : an effective tool-based approach for scaling up open source software development in bioinformatics

Summary: Biogem provides a software development environment for the Ruby programming language, which encourages community-based software development for bioinformatics while lowering the barrier to entry and encouraging best practices. Biogem, with its targeted modular and decentralized approach, software generator, tools and tight web integration, is an improved general model for scaling up collaborative open source software development in bioinformatics. Availability: Biogem and modules are free and are OSS. Biogem runs on all systems that support recent versions of Ruby, including Linux, Mac OS X and Windows. Further information at http://www.biogems.info. A tutorial is available at http://www.biogems.info/howto.html Contact: bonnal@ingm.org

Bio-samtools: Ruby bindings for SAMtools, a library for accessing BAM files containing high-throughput sequence alignments

BackgroundThe SAMtools utilities comprise a very useful and widely used suite of software for manipulating files and alignments in the SAM and BAM format, used in a wide range of genetic analyses. The SAMtools utilities are implemented in C and provide an API for programmatic access, to help make this functionality available to programmers wishing to develop in the high level Ruby language we have developed bio-samtools, a Ruby binding to the SAMtools library.ResultsThe utility of SAMtools is encapsulated in 3 main classes, Bio::DB::Sam, representing the alignment files and providing access to the data in them, Bio::DB::Alignment, representing the individual read alignments inside the files and Bio::DB::Pileup, representing the summarised nucleotides of reads over a single point in the nucleotide sequence to which the reads are aligned.ConclusionsBio-samtools is a flexible and easy to use interface that programmers of many levels of experience can use to access information in the popular and common SAM/BAM format.