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Montbonnot-Saint-Martin, France

Zago M.,Italian Agricultural Research Council | Scaltriti E.,University of Parma | Rossetti L.,Italian Agricultural Research Council | Guffanti A.,Genomnia Srl | And 13 more authors.
Applied and Environmental Microbiology | Year: 2013

The complete genomic sequence of the dairy Lactobacillus helveticus bacteriophage φAQ113 was determined. Phage φAQ113 is a Myoviridae bacteriophage with an isometric capsid and a contractile tail. The final assembled consensus sequence revealed a linear, circularly permuted, double-stranded DNA genome with a size of 36,566 bp and a G_C content of 37%. Fifty-six open reading frames (ORFs) were predicted, and a putative function was assigned to approximately 90% of them. The φAQ113 genome shows functionally related genes clustered together in a genome structure composed of modules for DNA replication/regulation, DNA packaging, head and tail morphogenesis, cell lysis, and lysogeny. The identification of genes involved in the establishment of lysogeny indicates that it may have originated as a temperate phage, even if it was isolated from natural cheese whey starters as a virulent phage, because it is able to propagate in a sensitive host strain. Additionally, we discovered that the φAQ113 phage genome is closely related to Lactobacillus gasseri phage KC5a and Lactobacillus johnsonii phage Lj771 genomes. The phylogenetic similarities between L. helveticus phage_AQ113 and two phages that belong to gut species confirm a possible common ancestral origin and support the increasing consideration of L. helveticus as a health-promoting organism. © 2013, American Society for Microbiology. All Rights Reserved. Source

Cruaud P.,CNRS Lab for Microbiology of Extreme Environments | Vigneron A.,CNRS Lab for Microbiology of Extreme Environments | Lucchetti-Miganeh C.,Genostar | Ciron P.E.,Genostar | And 2 more authors.
Applied and Environmental Microbiology | Year: 2014

Next-generation sequencing (NGS) opens up exciting possibilities for improving our knowledge of environmental microbial diversity, allowing rapid and cost-effective identification of both cultivated and uncultivated microorganisms. However, library preparation, sequencing, and analysis of the results can provide inaccurate representations of the studied community compositions. Therefore, all these steps need to be taken into account carefully. Here we evaluated the effects of DNA extraction methods, targeted 16S rRNA hypervariable regions, and sample origins on the diverse microbes detected by 454 pyrosequencing in marine cold seep and hydrothermal vent sediments. To assign the reads with enough taxonomic precision, we built a database with about 2,500 sequences from Archaea and Bacteria from deep-sea marine sediments, affiliated according to reference publications in the field. Thanks to statistical and diversity analyses as well as inference of operational taxonomic unit (OTU) networks, we show that (i) while DNA extraction methods do not seem to affect the results for some samples, they can lead to dramatic changes for others; and (ii) the choice of amplification and sequencing primers also considerably affects the microbial community detected in the samples. Thereby, very different proportions of pyrosequencing reads were obtained for some microbial lineages, such as the archaeal ANME-1, ANME-2c, and MBG-D and deltaproteobacterial subgroups. This work clearly indicates that the results from sequencing-based analyses, such as pyrosequencing, should be interpreted very carefully. Therefore, the combination of NGS with complementary approaches, such as fluorescence in situ hybridization (FISH)/catalyzed reporter deposition (CARD)-FISH or quantitative PCR (Q-PCR), would be desirable to gain a more comprehensive picture of environmental microbial communities. © 2014, American Society for Microbiology. Source

Batt G.,French Institute for Research in Computer Science and Automation | Besson B.,Genostar | Ciron P.-E.,Genostar | De Jong H.,French Institute for Research in Computer Science and Automation | And 7 more authors.
Methods in Molecular Biology | Year: 2012

Genetic Network Analyzer (GNA) is a tool for the qualitative modeling and simulation of gene regulatory networks, based on so-called piecewise-linear differential equation models. We describe the use of this tool in the context of the modeling of bacterial regulatory networks, notably the network of global regulators controlling the adaptation of Escherichia coli to carbon starvation conditions. We show how the modeler, by means of GNA, can define a regulatory network, build a model of the network, determine the steady states of the system, perform a qualitative simulation of the network dynamics, and analyze the simulation results using model-checking tools. The example illustrates the interest of qualitative approaches for the analysis of the dynamics of bacterial regulatory networks. © 2012 Springer Science+Business Media, LLC. Source

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