75 research outputs found
Alvira : comparative genomics of viral strains
The Alvira tool is a general purpose multiple sequence alignment viewer with a special emphasis on the comparative analysis of viral genomes. This new tool has been devised specifically to address the problem of the simultaneous analysis of a large number of viral strains. The multiple alignment is embedded in a graph that can be explored at different levels of resolution
Different Dose-Dependent Modes of Action of C-Type Natriuretic Peptide on Pseudomonas aeruginosa Biofilm Formation.
We have previously shown that the C-type Natriuretic Peptide (CNP), a peptide produced by lungs, is able to impact Pseudomonasaeruginosa physiology. In the present work, the effect of CNP at different concentrations on P. aeruginosa biofilm formation was studied and the mechanisms of action of this human hormone on P. aeruginosa were deciphered. CNP was shown to inhibit dynamic biofilm formation in a dose-dependent manner without affecting the bacterial growth at any tested concentrations. The most effective concentrations were 1 and 0.1 µM. At 0.1 µM, the biofilm formation inhibition was fully dependent on the CNP sensor protein AmiC, whereas it was only partially AmiC-dependent at 1 µM, revealing the existence of a second AmiC-independent mode of action of CNP on P. aeruginosa. At 1 µM, CNP reduced both P. aeruginosa adhesion on glass and di-rhamnolipid production and also increased the bacterial membrane fluidity. The various effects of CNP at 1 µM and 0.1 µM on P. aeruginosa shown here should have major consequences to design drugs for biofilm treatment or prevention
A fragile metabolic network adapted for cooperation in the symbiotic bacterium Buchnera aphidicola
<p>Abstract</p> <p>Background</p> <p><it>In silico </it>analyses provide valuable insight into the biology of obligately intracellular pathogens and symbionts with small genomes. There is a particular opportunity to apply systems-level tools developed for the model bacterium <it>Escherichia coli </it>to study the evolution and function of symbiotic bacteria which are metabolically specialised to overproduce specific nutrients for their host and, remarkably, have a gene complement that is a subset of the <it>E. coli </it>genome.</p> <p>Results</p> <p>We have reconstructed and analysed the metabolic network of the γ-proteobacterium <it>Buchnera aphidicola </it>(symbiont of the pea aphid) as a model for using systems-level approaches to discover key traits of symbionts with small genomes. The metabolic network is extremely fragile with > 90% of the reactions essential for viability <it>in silico</it>; and it is structured so that the bacterium cannot grow without producing the essential amino acid, histidine, which is released to the insect host. Further, the amount of essential amino acid produced by the bacterium <it>in silico </it>can be controlled by host supply of carbon and nitrogen substrates.</p> <p>Conclusion</p> <p>This systems-level analysis predicts that the fragility of the bacterial metabolic network renders the symbiotic bacterium intolerant of drastic environmental fluctuations, whilst the coupling of histidine production to growth prevents the bacterium from exploiting host nutrients without reciprocating. These metabolic traits underpin the sustained nutritional contribution of <it>B. aphidicola </it>to the host and, together with the impact of host-derived substrates on the profile of nutrients released from the bacteria, point to a dominant role of the host in controlling the symbiosis.</p
Minimum information about an uncultivated virus genome (MIUVIG)
This is the final version. Available on open access from Nature Research via the DOI in this recordNOTE: the full list of funders and grants is in the acknowledgements section of the articleWe present an extension of the Minimum Information about any (x) Sequence (MIxS) standard for reporting sequences of uncultivated virus genomes. Minimum Information about an Uncultivated Virus Genome (MIUViG) standards were developed within the Genomic Standards Consortium framework and include virus origin, genome quality, genome annotation, taxonomic classification, biogeographic distribution and in silico host prediction. Community-wide adoption of MIUViG standards, which complement the Minimum Information about a Single Amplified Genome (MISAG) and Metagenome-Assembled Genome (MIMAG) standards for uncultivated bacteria and archaea, will improve the reporting of uncultivated virus genomes in public databases. In turn, this should enable more robust comparative studies and a systematic exploration of the global virosphere.Simons Foundation InternationalNatural Environment Research Council (NERC
ProPhylo: partial phylogenetic profiling to guide protein family construction and assignment of biological process
Assessing the Diversity and Specificity of Two Freshwater Viral Communities through Metagenomics
Transitions between saline and fresh waters have been shown to be infrequent for microorganisms. Based on host-specific interactions, the presence of specific clades among hosts suggests the existence of freshwater-specific viral clades. Yet, little is known about the composition and diversity of the temperate freshwater viral communities, and even if freshwater lakes and marine waters harbor distinct clades for particular viral sub-families, this distinction remains to be demonstrated on a community scale
The evolutionary signal in metagenome phyletic profiles predicts many gene functions
Background. The function of many genes is still not known even in model organisms. An increasing availability of microbiome DNA sequencing data provides an opportunity to infer gene function in a systematic manner. Results. We evaluated if the evolutionary signal contained in metagenome phyletic profiles (MPP) is predictive of a broad array of gene functions. The MPPs are an encoding of environmental DNA sequencing data that consists of relative abundances of gene families across metagenomes. We find that such MPPs can accurately predict 826 Gene Ontology functional categories, while drawing on human gut microbiomes, ocean metagenomes, and DNA sequences from various other engineered and natural environments. Overall, in this task, the MPPs are highly accurate, and moreover they provide coverage for a set of Gene Ontology terms largely complementary to standard phylogenetic profiles, derived from fully sequenced genomes. We also find that metagenomes approximated from taxon relative abundance obtained via 16S rRNA gene sequencing may provide surprisingly useful predictive models. Crucially, the MPPs derived from different types of environments can infer distinct, non-overlapping sets of gene functions and therefore complement each other. Consistently, simulations on > 5000 metagenomes indicate that the amount of data is not in itself critical for maximizing predictive accuracy, while the diversity of sampled environments appears to be the critical factor for obtaining robust models. Conclusions. In past work, metagenomics has provided invaluable insight into ecology of various habitats, into diversity of microbial life and also into human health and disease mechanisms. We propose that environmental DNA sequencing additionally constitutes a useful tool to predict biological roles of genes, yielding inferences out of reach for existing comparative genomics approaches
Understanding Communication Signals during Mycobacterial Latency through Predicted Genome-Wide Protein Interactions and Boolean Modeling
About 90% of the people infected with Mycobacterium tuberculosis carry latent bacteria that are believed to get activated upon immune suppression. One of the fundamental challenges in the control of tuberculosis is therefore to understand molecular mechanisms involved in the onset of latency and/or reactivation. We have attempted to address this problem at the systems level by a combination of predicted functional protein∶protein interactions, integration of functional interactions with large scale gene expression studies, predicted transcription regulatory network and finally simulations with a Boolean model of the network. Initially a prediction for genome-wide protein functional linkages was obtained based on genome-context methods using a Support Vector Machine. This set of protein functional linkages along with gene expression data of the available models of latency was employed to identify proteins involved in mediating switch signals during dormancy. We show that genes that are up and down regulated during dormancy are not only coordinately regulated under dormancy-like conditions but also under a variety of other experimental conditions. Their synchronized regulation indicates that they form a tightly regulated gene cluster and might form a latency-regulon. Conservation of these genes across bacterial species suggests a unique evolutionary history that might be associated with M. tuberculosis dormancy. Finally, simulations with a Boolean model based on the regulatory network with logical relationships derived from gene expression data reveals a bistable switch suggesting alternating latent and actively growing states. Our analysis based on the interaction network therefore reveals a potential model of M. tuberculosis latency
Phydbac (phylogenomic display of bacterial genes): an interactive resource for the annotation of bacterial genomes
Metagenomic and metatranscriptomic analysis for the study of clouds and aerosols.
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