Études des relations entre activités solaire et géomagnétique

The quality of the information provided by navigation systems such as GPS / EGNOS depends on many factors. We are specifically interested in the ionospheric events which cause the most relevant losses of these services. This study focuses on the previous state of these events, studing the relationship that may exist between the solar activity and geomagnetic one. Ionospheric events are directly dependent on geomagnetism, but we do not have a clear idea of the relation between them and the sun. By using signal processing tools and optimization modelling, we show that the geomagnetic and solar activities are simply related by a linear relationship. This relationship evolves over time but remains of the same nature. We have also studied the different cycles in solar and geomagnetic signals and we have founded that the two activities share some cycles. Finally we have studied the case of geomagnetic storms being considered rare events ; however, it is possible to assign a probability according to their power.Keywords : Navigation - signal processing - relation - solar activity - geomagnetic activity.La qualité des informations produites par les Systèmes de Navigation tel que GPS / EGNOS dépendent de beaucoup de facteurs. Nous nous intéressons plus précisément aux évènements ionosphériques qui sont les plus importants dans la déficience de ces services. Cette étude nous place en amont de ces évènements, nous étudions la relation qui peut exister entre l'activité solaire et géomagnétique. Les évènements ionosphériques dépendent directement du géomagnétisme mais nous n'avons pas encore une idée précise de la relation avec le soleil. Par l'utilisation d'outils de traitement de signal ainsi que par optimisation de modèle, nous prouvons que les activités géomagnétique et solaire sont simplement liées par une relation linéaire. Cette relation évolue dans le temps mais reste de la même nature. Nous avons également procédé à une étude des différents cycles que contiennent les données solaires et géomagnétiques et il s'avère que certains soient communs entre les deux activités. Enfin nous faisons l'étude des occurrences des orages géomagnétique que nous considérons comme des évènements rares cependant il est possible de leur attribuer une probabilité selon leur puissance. Mots-clés : Navigation – traitement du signal – relation – activité solaire – activité géoma-gnétique

UTOPIA: an automatically UpdaTed, cOmPlete and consistent ITS reference dAtabase

Taxonomic assignment in metabarcoding analysis is a critical and challenging step. As more organisms being sequenced, taxonomy is evolving fast with multiple taxa rearrangement and thousand of new sequences uploaded each year. The internal transcribed spacer (ITS) is an ubiquitous sequence used as a barcode to identify fungi species in complex environmental samples.Currently used databases like UNITE, offer a good and reliable reference, but update frequency is generally low, and new strain sequences can take several years to be integrated. UTOPIA provides a workflow that produce an updated ITS reference database directly from the NCBI genbank and taxonomy database.Our workflow downloads all complete fungi ITS sequences from NCBI thanks to a formatted esearch query. Then homemade scripts extract sequences with their corresponding seven ranks taxonomy string. Post treatment consists on sequence quality filtering, dereplication and clustering. Taxonomy of each cluster are checked for consistency and incongruity are resolved by an homemade customizable script. Finally UTOPIA workflow generates two simple file, one fasta file containing sequences and a two columns tabulated file containing corresponding taxonomy that can be formatted for current assignment tools.On our real dataset of 11000 ITS sequences, UTOPIA performs best in term of resolution and confidence on about 60% of sequences compared to UNITE. When UNITE fails to assign sequences, UTOPIA gives annotation up to 25% of these. But more interestingly, UTOPIA taxonomy is an exact copy of NCBI’s, given the possibility to integrate latest sequenced fungal genomes

ANOMALY: AmplicoN wOrkflow for Microbial community AnaLYsis

Bioinformatic tools for amplicon sequencing data analysis are continuously and rapidly evolving, thus integrating We present an R workflow for 16S and ITS amplicons based sequencing. It is mainly based on the Dada2 and Phyloseq R packages. This workflow is based on several scripts in order to perform an analysis from fastq sequence files to final statistical analysis. The objective was to automate bioinformatic analyses to ensure reproducibility between projects trying to be versatile and simple to integrate new bioinformatic tools or statistical techniques.ANOMALY use Amplicon Sequence Variant (ASV from Dada2 package) as taxonomic unit, allowing an easy and relevant sequence tracking between different environments and/or projects. Decontam package is included for an accurate and consistent detection of contaminant ASV and taxonomic assignment step relies on IDTAXA method. Our workflow is able to merge and check annotations from two taxonomic databases to unravel misannotation, discordance or inconsistency. The well known Phyloseq package provides the most common graphical representation, with additional statistics to assess significant impact of tested factors on microbial communities. The workflow incorporate multiple differential analyses (DESeq2 etc...) to reveal thin community contrast between conditions. Finally we are able to combine those results for cross-validation and thinner interpretation.ANOMALY is a simple and customizable R workflow, that uses ASVs level for community characterization and integrates all assets of the up-to-date methods such as better sequence tracking, decontamination, merged taxonomic annotation, statistical tests, and cross-validated differential analysis

rANOMALY: AmplicoN wOrkflow for Microbial community AnaLYsis

International audienceBioinformatic tools for marker gene sequencing data analysis are continuously and rapidly evolving, thus integrating most recent techniques and tools is challenging. We present an R package for data analysis of 16S and ITS amplicons based sequencing. This workflow is based on several R functions and performs automatic treatments from fastq sequence files to diversity and differential analysis with statistical validation. The main purpose of this package is to automate bioinformatic analysis, ensure reproducibility between projects, and to be flexible enough to quickly integrate new bioinformatic tools or statistical methods. rANOMALY is an easy to install and customizable R package, that uses amplicon sequence variants (ASV) level for microbial community characterization. It integrates all assets of the latest bioinformatics methods, such as better sequence tracking, decontamination from control samples, use of multiple reference databases for taxonomic annotation, all main ecological analysis for which we propose advanced statistical tests, and a cross-validated differential analysis by four different methods. Our package produces ready to publish figures, and all of its outputs are made to be integrated in Rmarkdown code to produce automated reports.Les outils bioinformatiques pour l'analyse des données de séquençage des gènes marqueurs évoluent continuellement et rapidement, ce qui rend difficile l'intégration des techniques et des outils les plus récents. Nous présentons un package R pour l'analyse des données du séquençage basé sur les amplicons 16S et ITS. Ce workflow est basé sur plusieurs fonctions R et effectue des traitements automatiques depuis les fichiers de séquence fastq jusqu'à la diversité et l'analyse différentielle avec validation statistique. L'objectif principal de ce package est d'automatiser l'analyse bioinformatique, d'assurer la reproductibilité entre les projets et d'être suffisamment flexible pour intégrer rapidement de nouveaux outils bioinformatiques ou méthodes statistiques. rANOMALY est un package R facile à installer et personnalisable, qui utilise le niveau des variants de séquence d'amplicon (ASV) pour la caractérisation de la communauté microbienne. Il intègre tous les atouts des dernières méthodes bioinformatiques, comme un meilleur suivi des séquences, la décontamination à partir d'échantillons de contrôle, l'utilisation de plusieurs bases de données de référence pour l'annotation taxonomique, toutes les principales analyses écologiques pour lesquelles nous proposons des tests statistiques avancés, et une analyse différentielle à validation croisée par quatre méthodes différentes. Notre package produit des chiffres prêts à publier, et toutes ses sorties sont conçues pour être intégrées dans le code Rmarkdown afin de produire des rapports automatisés

ANOMALY: AmplicoN wOrkflow for Microbial community AnaLYsis

Bioinformatic tools for amplicon sequencing data analysis are continuously and rapidly evolving, thus integrating We present an R workflow for 16S and ITS amplicons based sequencing. It is mainly based on the Dada2 and Phyloseq R packages. This workflow is based on several scripts in order to perform an analysis from fastq sequence files to final statistical analysis. The objective was to automate bioinformatic analyses to ensure reproducibility between projects trying to be versatile and simple to integrate new bioinformatic tools or statistical techniques.ANOMALY use Amplicon Sequence Variant (ASV from Dada2 package) as taxonomic unit, allowing an easy and relevant sequence tracking between different environments and/or projects. Decontam package is included for an accurate and consistent detection of contaminant ASV and taxonomic assignment step relies on IDTAXA method. Our workflow is able to merge and check annotations from two taxonomic databases to unravel misannotation, discordance or inconsistency. The well known Phyloseq package provides the most common graphical representation, with additional statistics to assess significant impact of tested factors on microbial communities. The workflow incorporate multiple differential analyses (DESeq2 etc...) to reveal thin community contrast between conditions. Finally we are able to combine those results for cross-validation and thinner interpretation.ANOMALY is a simple and customizable R workflow, that uses ASVs level for community characterization and integrates all assets of the up-to-date methods such as better sequence tracking, decontamination, merged taxonomic annotation, statistical tests, and cross-validated differential analysis

UTOPIA: an automatically UpdaTed, cOmPlete and consistent ITS reference dAtabase

Taxonomic assignment in metabarcoding analysis is a critical and challenging step. As more organisms being sequenced, taxonomy is evolving fast with multiple taxa rearrangement and thousand of new sequences uploaded each year. The internal transcribed spacer (ITS) is an ubiquitous sequence used as a barcode to identify fungi species in complex environmental samples. Currently used databases like UNITE, offer a good and reliable reference, but update frequency is generally low, and new strain sequences can take several years to be integrated. UTOPIA provides a workflow that produce an updated ITS reference database directly from the NCBI genbank and taxonomy database. Our workflow downloads all complete fungi ITS sequences from NCBI thanks to a formatted esearch query. Then homemade scripts extract sequences with their corresponding seven ranks taxonomy string. Post treatment consists on sequence quality filtering, dereplication and clustering. Taxonomy of each cluster are checked for consistency and incongruity are resolved by an homemade customizable script. Finally UTOPIA workflow generates two simple file, one fasta file containing sequences and a two columns tabulated file containing corresponding taxonomy that can be formatted for current assignment tools. On our real dataset of 11000 ITS sequences, UTOPIA performs best in term of resolution and confidence on about 60% of sequences compared to UNITE. When UNITE fails to assign sequences, UTOPIA gives annotation up to 25% of these. But more interestingly, UTOPIA taxonomy is an exact copy of NCBI’s, given the possibility to integrate latest sequenced fungal genomes

DAIRYdb: Une base de données de références pour une meilleure assignation taxonomique des ARNr 16S issus des produits laitiers

International audienc

Identification of Loci Enabling Stable and High-Level Heterologous Gene Expression

International audienceEfficient and reliable genome engineering technologies have yet to be developed for diatoms. The delivery of DNA in diatoms results in the random integration of multiple copies, quite often leading to heterogeneous gene activity, as well as host instability. Transgenic diatoms are generally selected on the basis of transgene expression or high enzyme activity, without consideration of the copy number or the integration locus. Here, we propose an integrated pipeline for the diatom, Phaeodactylum tricornutum , that accurately quantifies transgene activity using a β-glucuronidase assay and the number of transgene copies integrated into the genome through Droplet Digital PCR (ddPCR). An exhaustive and systematic analysis performed on 93 strains indicated that 42% of them exhibited high β-glucuronidase activity. Though most were attributed to high transgene copy numbers, we succeeded in isolating single-copy clones, as well as sequencing the integration loci. In addition to demonstrating the impact of the genomic integration site on gene activity, this study identifies integration sites for stable transgene expression in Phaeodactylum tricornutum

DAIRYdb: a manually curated reference database for improved taxonomy annotation of 16S rRNA gene sequences from dairy products

Reads assignment to taxonomic units is a key step in microbiome analysis pipelines. To date, accurate taxonomy annotation of 16S reads, particularly at species rank, is still challenging due to the short size of read sequences and differently curated classification databases. The close phylogenetic relationship between species encountered in dairy products, however, makes it crucial to annotate species accurately to achieve sufficient phylogenetic resolution for further downstream ecological studies or for food diagnostics. Curated databases dedicated to the environment of interest are expected to improve the accuracy and resolution of taxonomy annotation

Lactic Starter Dose Shapes S. aureus and STEC O26:H11 Growth, and Bacterial Community Patterns in Raw Milk Uncooked Pressed Cheeses

International audienceAdding massive amounts of lactic starters to raw milk to manage the sanitary risk in the cheese-making process could be detrimental to microbial diversity. Adjusting the amount of the lactic starter used could be a key to manage these adverse impacts. In uncooked pressed cheeses, we investigated the impacts of varying the doses of a lactic starter (the recommended one, 1×, a 0.1× lower and a 2× higher) on acidification, growth of Staphylococcus aureus SA15 and Shiga-toxin-producing Escherichia coli (STEC) O26:H11 F43368, as well as on the bacterial community patterns. We observed a delayed acidification and an increase in the levels of pathogens with the 0.1× dose. This dose was associated with increased richness and evenness of cheese bacterial community and higher relative abundance of potential opportunistic bacteria or desirable species involved in cheese production. No effect of the increased lactic starter dose was observed. Given that sanitary criteria were paramount to our study, the increase in the pathogen levels observed at the 0.1× dose justified proscribing such a reduction in the tested cheese-making process. Despite this, the effects of adjusting the lactic starter dose on the balance of microbial populations of potential interest for cheese production deserve an in-depth evaluation