Organics in comet 67P – a first comparative analysis of mass spectra from ROSINA–DFMS, COSAC and Ptolemy

The ESA Rosetta spacecraft followed comet 67P at a close distance for more than 2 yr. In addition, it deployed the lander Philae on to the surface of the comet. The (surface) composition of the comet is of great interest to understand the origin and evolution of comets. By combining measurements made on the comet itself and in the coma, we probe the nature of this surface material and compare it to remote sensing observations. We compare data from the double focusing mass spectrometer (DFMS) of the ROSINA experiment on ESA's Rosetta mission and previously published data from the two mass spectrometers COSAC (COmetary Sampling And Composition) and Ptolemy on the lander. The mass spectra of all three instruments show very similar patterns of mainly CHO-bearing molecules that sublimate at temperatures of 275 K. The DFMS data also show a great variety of CH-, CHN-, CHS-, CHO2- and CHNO-bearing saturated and unsaturated species. Methyl isocyanate, propanal and glycol aldehyde suggested by the earlier analysis of the measured COSAC spectrum could not be confirmed. The presence of polyoxymethylene in the Ptolemy spectrum was found to be unlikely. However, the signature of the aromatic compound toluene was identified in DFMS and Ptolemy data. Comparison with remote sensing instruments confirms the complex nature of the organics on the surface of 67P, which is much more diverse than anticipated

EDGAR 2.0: an enhanced software platform for comparative gene content analyses.

The rapidly increasing availability of microbial genome sequences has led to a growing demand for bioinformatics software tools that support the functional analysis based on the comparison of closely related genomes. By utilizing comparative approaches on gene level it is possible to gain insights into the core genes which represent the set of shared features for a set of organisms under study. Vice versa singleton genes can be identified to elucidate the specific properties of an individual genome. Since initial publication, the EDGAR platform has become one of the most established software tools in the field of comparative genomics. Over the last years, the software has been continuously improved and a large number of new analysis features have been added. For the new version, EDGAR 2.0, the gene orthology estimation approach was newly designed and completely re-implemented. Among other new features, EDGAR 2.0 provides extended phylogenetic analysis features like AAI (Average Amino Acid Identity) and ANI (Average Nucleotide Identity) matrices, genome set size statistics and modernized visualizations like interactive synteny plots or Venn diagrams. Thereby, the software supports a quick and user-friendly survey of evolutionary relationships between microbial genomes and simplifies the process of obtaining new biological insights into their differential gene content. All features are offered to the scientific community via a web-based and therefore platform-independent user interface, which allows easy browsing of precomputed datasets. The web server is accessible at http://edgar.computational.bio

Next-generation sequencing analysis of the Tineola bisselliella larval gut transcriptome reveals candidate enzymes for keratin digestion

The clothes moth Tineola bisselliella is one of a few insects that can digest keratin, leading to the destruction of clothing, textiles and artwork. The mechanism of keratin digestion is not yet fully understood, partly reflecting the lack of publicly available genomic and transcriptomic data. Here we present a high-quality gut transcriptome of T. bisselliella generated from larvae reared on keratin-rich and keratin-free diets. The overall transcriptome consists of 428,221 contigs that were functionally annotated and screened for candidate enzymes involved in keratin utilization. As a mechanism for keratin digestion, we identified cysteine synthases, cystathionine β-synthases and cystathionine γ-lyases. These enzymes release hydrogen sulfite, which may reduce the disulfide bonds in keratin. The dataset also included 27 differentially expressed contigs with trypsin domains, among which 20 were associated with keratin feeding. Finally, we identified seven collagenases that were upregulated on the keratin-rich diet. In addition to this enzymatic repertoire potentially involved in breaking down keratin, our analysis of poly(A)-enriched and poly(A)-depleted transcripts suggested that T. bisselliella larvae possess an unstable intestinal microbiome that may nevertheless contribute to keratin digestion

BRIGEP—the BRIDGE-based genome–transcriptome–proteome browser

The growing amount of information resulting from the increasing number of publicly available genomes and experimental results thereof necessitates the development of comprehensive systems for data processing and analysis. In this paper, we describe the current state and latest developments of our BRIGEP bioinformatics software system consisting of three web-based applications: GenDB, EMMA and ProDB. These applications facilitate the processing and analysis of bacterial genome, transcriptome and proteome data and are actively used by numerous international groups. We are currently in the process of extensively interconnecting these applications. BRIGEP was developed in the Bioinformatics Resource Facility of the Center for Biotechnology at Bielefeld University and is freely available. A demo project with sample data and access to all three tools is available at . Code bundles for these and other tools developed in our group are accessible on our FTP server at

Multi-membership gene regulation in pathway based microarray analysis

This article is available through the Brunel Open Access Publishing Fund. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Background: Gene expression analysis has been intensively researched for more than a decade. Recently, there has been elevated interest in the integration of microarray data analysis with other types of biological knowledge in a holistic analytical approach. We propose a methodology that can be facilitated for pathway based microarray data analysis, based on the observation that a substantial proportion of genes present in biochemical pathway databases are members of a number of distinct pathways. Our methodology aims towards establishing the state of individual pathways, by identifying those truly affected by the experimental conditions based on the behaviour of such genes. For that purpose it considers all the pathways in which a gene participates and the general census of gene expression per pathway. Results: We utilise hill climbing, simulated annealing and a genetic algorithm to analyse the consistency of the produced results, through the application of fuzzy adjusted rand indexes and hamming distance. All algorithms produce highly consistent genes to pathways allocations, revealing the contribution of genes to pathway functionality, in agreement with current pathway state visualisation techniques, with the simulated annealing search proving slightly superior in terms of efficiency. Conclusions: We show that the expression values of genes, which are members of a number of biochemical pathways or modules, are the net effect of the contribution of each gene to these biochemical processes. We show that by manipulating the pathway and module contribution of such genes to follow underlying trends we can interpret microarray results centred on the behaviour of these genes.The work was sponsored by the studentship scheme of the School of Information Systems, Computing and Mathematics, Brunel Universit

Evolutionarily stable gene clusters shed light on the common grounds of pathogenicity in the Acinetobacter calcoaceticus-baumannii complex

Nosocomial pathogens of the Acinetobacter calcoaceticus-baumannii (ACB) complex are a cautionary example for the world-wide spread of multi- and pan-drug resistant bacteria. Aiding the urgent demand for novel therapeutic targets, comparative genomics studies between pathogens and their apathogenic relatives shed light on the genetic basis of human-pathogen interaction. Yet, existing studies are limited in taxonomic scope, sensing of the phylogenetic signal, and resolution by largely analyzing genes independent of their organization in functional gene clusters. Here, we explored more than 3,000 Acinetobacter genomes in a phylogenomic framework integrating orthology-based phylogenetic profiling and microsynteny conservation analyses. We delineate gene clusters in the type strain A. baumannii ATCC 19606 whose evolutionary conservation indicates a functional integration of the subsumed genes. These evolutionarily stable gene clusters (ESGCs) reveal metabolic pathways, transcriptional regulators residing next to their targets but also tie together sub-clusters with distinct functions to form higher-order functional modules. We shortlisted 150 ESGCs that either co-emerged with the pathogenic ACB clade or are preferentially found therein. They provide a high-resolution picture of genetic and functional changes that coincide with the manifestation of the pathogenic phenotype in the ACB clade. Key innovations are the remodeling of the regulatory-effector cascade connecting LuxR/LuxI quorum sensing via an intermediate messenger to biofilm formation, the extension of micronutrient scavenging systems, and the increase of metabolic flexibility by exploiting carbon sources that are provided by the human host. We could show experimentally that only members of the ACB clade use kynurenine as a sole carbon and energy source, a substance produced by humans to fine-tune the antimicrobial innate immune response. In summary, this study provides a rich and unbiased set of novel testable hypotheses on how pathogenic Acinetobacter interact with and ultimately infect their human host. It is a comprehensive resource for future research into novel therapeutic strategies.Peer Reviewe

Evolutionarily stable gene clusters shed light on the common grounds of pathogenicity in the Acinetobacter calcoaceticus-baumannii complex

Nosocomial pathogens of the Acinetobacter calcoaceticus-baumannii (ACB) complex are a cautionary example for the world-wide spread of multi- and pan-drug resistant bacteria. Aiding the urgent demand for novel therapeutic targets, comparative genomics studies between pathogens and their apathogenic relatives shed light on the genetic basis of human-pathogen interaction. Yet, existing studies are limited in taxonomic scope, sensing of the phylogenetic signal, and resolution by largely analyzing genes independent of their organization in functional gene clusters. Here, we explored more than 3,000 Acinetobacter genomes in a phylogenomic framework integrating orthology-based phylogenetic profiling and microsynteny conservation analyses. We delineate gene clusters in the type strain A. baumannii ATCC 19606 whose evolutionary conservation indicates a functional integration of the subsumed genes. These evolutionarily stable gene clusters (ESGCs) reveal metabolic pathways, transcriptional regulators residing next to their targets but also tie together sub-clusters with distinct functions to form higher-order functional modules. We shortlisted 150 ESGCs that either co-emerged with the pathogenic ACB clade or are preferentially found therein. They provide a high-resolution picture of genetic and functional changes that coincide with the manifestation of the pathogenic phenotype in the ACB clade. Key innovations are the remodeling of the regulatory-effector cascade connecting LuxR/LuxI quorum sensing via an intermediate messenger to biofilm formation, the extension of micronutrient scavenging systems, and the increase of metabolic flexibility by exploiting carbon sources that are provided by the human host. We could show experimentally that only members of the ACB clade use kynurenine as a sole carbon and energy source, a substance produced by humans to fine-tune the antimicrobial innate immune response. In summary, this study provides a rich and unbiased set of novel testable hypotheses on how pathogenic Acinetobacter interact with and ultimately infect their human host. It is a comprehensive resource for future research into novel therapeutic strategies

It's a Trap! A Review of MOMA and Other Ion Traps in Space or Under Development

Since the Viking Program, quadrupole mass spectrometer (QMS) instruments have been used to explore a wide survey of planetary targets in our solar system, including (from the inner to outer reaches): Venus (Pioneer); our moon (LADEE); Mars (Viking, Phoenix, and Mars Science Laboratory); and, Saturns largest moon Titan (Cassini-Huygens). More recently, however, ion trap mass spectrometer (ITMS) instruments have found a niche as smaller, versatile alternatives to traditional quadrupole mass analyzers, capable of in situ characterization of planetary environments and the search for organic matter. For example, whereas typical QMS systems are limited to a mass range up to 500 Da and normally require multiple RF frequencies and pressures of less than 10(exp -6) mbar for optimal operation, ITMS instruments commonly reach upwards of 1000 Da or more on a single RF frequency, and function in higher pressure environments up to 10(exp -3) mbar