Interaction between Medicago truncatula and Pseudomonas fluorescens: evaluation of costs and benefits across an elevated atmospheric CO2.

10 pagesInternational audienceSoil microorganisms play a key role in both plants nutrition and health. Their relation with plant varies from mutualism to parasitism, according to the balance of costs and benefits for the two partners of the interaction. These interactions involved the liberation of plant organic compounds via rhizodeposition. Modification of atmospheric CO2 concentration may affect rhizodeposition and as a consequence trophic interactions that bind plants and microorganisms. Positive effect of elevated CO2 on plants are rather well known but consequences for micoorganisms and their interactions with plants are still poorly understood. A gnotobiotic system has been developed to study the interaction between Medicago truncatula Jemalong J5 and the mutualistic bacteria Pseudomonas fluorescens strain C7R12 under two atmospheric CO2 concentrations: ambient (365 ppm) versus enriched (750 ppm). Costs and benefits for each partner have been determined over time by measuring plant development and growth, the C and N contents of the various plant parts and the density of the bacteria in rhizosphere compartments. Following the increase in CO2, there was a beneficial effect of P. fluorescens C7R12 on development, vegetative growth, and C/N content of M. truncatula. Concerning plant reproduction, an early seed production was noticed in presence of the bacterial strain combined with increased atmospheric CO2 conditions. Paradoxically, this transient increase in seed production was correlated with a decrease in bacterial density in the rhizosphere soil, revealing a cost of increased CO2 for the bacterial strain. This shift of costs-benefits ratio disappeared later during the plant growth. In conclusion, the increase in CO2 concentration modifies transiently the cost-benefit balance in favor of the plant. These results may be explained either by a competition between the two partners or a change in bacterial physiology. The ecosystem functioning depends on the stability of many plant-microbe associations that abiotic factors can disrupt

Extraction sous Contraintes d'Ensembles de Cliques Homogènes

Document sur site LIRIS : http://liris.cnrs.fr/Documents/Liris-4915.pdfNational audienceNous proposons une méthode de fouille de données sur des graphes ayant un ensemble d'étiquettes associé à chaque sommet. Une application est, par exemple, d'analyser un réseau social de chercheurs co-auteurs lorsque des étiquettes précisent les conférences dans lesquelles ils publient.Nous définissons l'extraction sous contraintes d'ensembles de cliques tel que chaque sommet des cliques impliquées partage suffisamment d'étiquettes. Nous proposons une méthode pour calculer tous les Ensembles Maximaux de Cliques dits Homogènes qui satisfont une conjonction de contraintes fixée par l'analyste et concernant le nombre de cliques séparées, la taille des cliques ainsi que le nombre d'étiquettes partagées. Les expérimentations montrent que l'approche fonctionne sur de grands graphes construits à partir de données réelles et permet la mise en évidence de structures intéressantes

Multi-scale characterization of symbiont diversity in the pea aphid complex through metagenomic approaches

International audienceMost metazoans are involved in durable symbiotic relationships with microbes which can take several forms, from mutualism to parasitism. The advances of NGS technologies and bioinformatics tools have opened new opportunities to shed light on this hidden but very influential diversity.The pea aphid is a model insect system for symbiont studies. It harbors both an obligatory symbiont supplying key nutrients and several facultative symbionts bringing some novel functions to the host, such as protection against natural enemies and thermal stress. The pea aphid is organized in a complex of biotypes, each adapted to a specific host plant of the legume family and having its own symbiont composition. Yet, the metagenomic diversity of the biotype-associated symbiotic community is still largely unknown. In particular, little is known on how the symbiotic genomic diversity is structured at different scales: across host biotypes, amongst individuals of the same biotype, or within individual aphids.We used high throughput whole genome metagenomic sequencing to characterize with a fine resolution the metagenomic diversity of both individual resequenced aphids and biotype specific pooled aphids. By a reference genome mapping approach, we first assessed the taxonomic diversity of the samples and built symbiont specific read sets. We then performed a genome-wide SNP-calling, to examine the differences in bacterial strains between samples. Our results revealed different diversity patterns at the three considered scales for the pea aphid symbionts. At the inter-biotype and intra-biotype scales, the primary symbiont Buchnera and some secondary symbionts such as Serratia showed a biotype specific diversity. We showed evidence for horizontal transfer of a Hamiltonella strain between biotypes, and found two distinct strains of Regiella symbionts within some biotypes. At the finest intra-host diversity scale, we also showed that these two strains of Regiella may coexist inside the same aphid host. This study highlights the huge potential of bioinformatics analyses of metagenomic dataset in exploring microbiote diversity in relation with host variation

Apport des nouvelles générations de séquençage pour accéder à la diversité des communautés microbiennes du sol : nécessité d’un ‘pipeline’ bio-informatique pour les biologistes

Communication orale, résuméLa diversité microbienne d’un sol est difficile à caractériser. Ceci s’explique par une accessibilité plus ou moins importante des populations au sein d’une matrice hétérogène et structurée, mais aussi par l’incapacité à résoudre une information constituée de 100 000 à 1 000 000 d’espèces différentes par gramme de sol. Toutefois, récemment, d’importantes avancées en biologie moléculaire ont permis de mieux caractériser la diversité des communautés microbiennes du sol in situ et ce sans a priori. Ainsi, la puissance des nouvelles générations de séquençage comme le pyroséquençage permettent de travailler en haut-débit afin d’obtenir plusieurs dizaines, voire plusieurs centaines de milliers de séquences à partir d’un ADN méta-génomique. De premières études ont déjà été réalisées avec cette technique afin d’aborder la diversité bactérienne des sols. Ces études ont, pour la première fois, permis de quantifier de façon exhaustive la diversité microbienne de sols en termes de richesse spécifique et de démontrer la pertinence, la faisabilité et la robustesse de cette approche. Cette approche est maintenant unanimement reconnue pour sa pertinence et ses potentialités très importantes, et ce afin de déterminer la diversité des microorganismes telluriques. Notre approche consiste en la caractérisation de la diversité taxonomique (bactérienne et fongique) de sols sur des échantillonnages de grande ampleur dans le temps et dans l’espace, avec comme objectifs : (i) de faire un inventaire exhaustif de la diversité microbienne tellurique, (ii) d’évaluer sa distribution spatiale, (iii) de mieux comprendre sa régulation et, (iv) in fine, de pouvoir relier cette diversité en fonctionnement biologique du sol et en services écosystémiques [1-3]. Cependant, l’étude d’un aussi grand nombre d’échantillons va entraîner la production massive de séquences. Ce caractère massif, ainsi que les caractéristiques inhérentes aux séquences obtenues par cette technique requièrent le développement d’outils bioinformatiques adaptés, optimisés et évalués, afin d’analyser rapidement et efficacement ce type de données. Ce nouveau pipeline d’analyse doit tout d’abord être facile d’utilisation et répondre aux attentes des différents utilisateurs, qu’ils soient compétents en bio-informatique, ou novices dans l’analyse de tels jeux de données. Il doit également permettre de gérer un grand nombre de séquences et d’automatiser les grandes étapes d’analyse (prétraitement, filtration, clustérisation, assignation taxonomique, calculs d’indices d’abondance et de diversité, taux de couverture,…). L’ensemble du système devra enfin être transféré sur un serveur de calcul et accessible au travers d’un serveur Web pour être accessible à la collectivité des écologistes microbiens. L’objectif étant de coupler, sur un grand nombre d’échantillons, cette approche avec des mesures d’activités et de faire le lien entre la diversité microbienne et l’aptitude des sols à rendre des services

Validation and Application of a PCR Primer Set to Quantify Fungal Communities in the Soil Environment by Real-Time Quantitative PCR

Fungi constitute an important group in soil biological diversity and functioning. However, characterization and knowledge of fungal communities is hampered because few primer sets are available to quantify fungal abundance by real-time quantitative PCR (real-time Q-PCR). The aim in this study was to quantify fungal abundance in soils by incorporating, into a real-time Q-PCR using the SYBRGreen® method, a primer set already used to study the genetic structure of soil fungal communities. To satisfy the real-time Q-PCR requirements to enhance the accuracy and reproducibility of the detection technique, this study focused on the 18S rRNA gene conserved regions. These regions are little affected by length polymorphism and may provide sufficiently small targets, a crucial criterion for enhancing accuracy and reproducibility of the detection technique. An in silico analysis of 33 primer sets targeting the 18S rRNA gene was performed to select the primer set with the best potential for real-time Q-PCR: short amplicon length; good fungal specificity and coverage. The best consensus between specificity, coverage and amplicon length among the 33 sets tested was the primer set FR1 / FF390. This in silico analysis of the specificity of FR1 / FF390 also provided additional information to the previously published analysis on this primer set. The specificity of the primer set FR1 / FF390 for Fungi was validated in vitro by cloning - sequencing the amplicons obtained from a real time Q-PCR assay performed on five independent soil samples. This assay was also used to evaluate the sensitivity and reproducibility of the method. Finally, fungal abundance in samples from 24 soils with contrasting physico-chemical and environmental characteristics was examined and ranked to determine the importance of soil texture, organic carbon content, C∶N ratio and land use in determining fungal abundance in soils

HIV controls the selective packaging of genomic, spliced viral and cellular RNAs into virions through different mechanisms

In addition to genomic RNA, HIV-1 particles package cellular and spliced viral RNAs. In order to determine the encapsidation mechanisms of these RNAs, we determined the packaging efficiencies and specificities of genomic RNA, singly and fully spliced HIV mRNAs and different host RNAs species: 7SL RNA, U6 snRNA and GAPDH mRNA using RT-QPCR. Except GAPDH mRNA, all RNAs are selectively encapsidated. Singly spliced RNAs, harboring the Rev-responsible element, and fully spliced viral RNAs, which do not contain this motif, are enriched in virions to similar levels, even though they are exported from the nucleus by different routes. Deletions of key motifs (SL1 and/or SL3) of the packaging signal of genomic RNA indicate that HIV and host RNAs are encapsidated through independent mechanisms, while genomic and spliced viral RNA compete for the same trans-acting factor due to the presence of the 5′ common exon containing the TAR, poly(A) and U5-PBS hairpins. Surprisingly, the RNA dimerization initiation site (DIS/SL1) appears to be the main packaging determinant of genomic RNA, but is not involved in packaging of spliced viral RNAs, suggesting a functional interaction with intronic sequences. Active and selective packaging of host and spliced viral RNAs provide new potential functions to these RNAs in the early stages of the virus life cycle

Métagénomique et métatranscriptome

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