Showing papers by "Mahendra Mariadassou published in 2016"

Beneficial metabolic effects of selected probiotics on diet-induced obesity and insulin resistance in mice are associated with improvement of dysbiotic gut microbiota

Abstract: Alterations in gut microbiota composition and diversity were suggested to play a role in the development of obesity, a chronic subclinical inflammatory condition. We here evaluated the impact of oral consumption of a monostrain or multi-strain probiotic preparation in high-fat diet-induced obese mice. We observed a strain-specific effect and reported dissociation between the capacity of probiotics to dampen adipose tissue inflammation and to limit body weight gain. A multi-strain mixture was able to improve adiposity, insulin resistance and dyslipidemia through adipose tissue immune cell-remodelling, mainly affecting macrophages. At the gut level, the mixture modified the uptake of fatty acids and restored the expression level of the short-chain fatty acid receptor GPR43. These beneficial effects were associated with changes in the microbiota composition, such as the restoration of the abundance of Akkermansia muciniphila and Rikenellaceae and the decrease of other taxa like Lactobacillaceae. Using an in vitro gut model, we further showed that the probiotic mixture favours the production of butyrate and propionate. Our findings provide crucial clues for the design and use of more efficient probiotic preparations in obesity management and may bring new insights into the mechanisms by which host-microbe interactions govern such protective effects.

Multiple Comparative Metagenomics using Multiset k-mer Counting

Abstract: Background Large scale metagenomic projects aim to extract biodiversity knowledge between different environmental conditions. Current methods for comparing microbial communities face important limitations. Those based on taxonomical or functional assignation rely on a small subset of the sequences that can be associated to known organisms. On the other hand, de novo methods, that compare the whole sets of sequences, either do not scale up on ambitious metagenomic projects or do not provide precise and exhaustive results. Methods These limitations motivated the development of a new de novo metagenomic comparative method, called Simka. This method computes a large collection of standard ecological distances by replacing species counts by k-mer counts. Simka scales-up today’s metagenomic projects thanks to a new parallel k-mer counting strategy on multiple datasets. Results Experiments on public Human Microbiome Project datasets demonstrate that Simka captures the essential underlying biological structure. Simka was able to compute in a few hours both qualitative and quantitative ecological distances on hundreds of metagenomic samples (690 samples, 32 billions of reads). We also demonstrate that analyzing metagenomes at the k-mer level is highly correlated with extremely precise de novo comparison techniques which rely on all-versus-all sequences alignment strategy or which are based on taxonomic profiling.

Multiple Comparative Metagenomics using Multiset k-mer Counting

Abstract: Background. Large scale metagenomic projects aim to extract biodiversity knowledge between different environmental conditions. Current methods for comparing microbial communities face important limitations. Those based on taxonomical or functional assignation rely on a small subset of the sequences that can be associated to known organisms. On the other hand, de novo methods, that compare the whole sets of sequences, either do not scale up on ambitious metagenomic projects or do not provide precise and exhaustive results. Methods. These limitations motivated the development of a new de novo metagenomic comparative method, called Simka. This method computes a large collection of standard ecological distances by replacing species counts by k-mer counts. Simka scales-up today's metagenomic projects thanks to a new parallel k-mer counting strategy on multiple datasets. Results. Experiments on public Human Microbiome Project datasets demonstrate that Simka captures the essential underlying biological structure. Simka was able to compute in a few hours both qualitative and quantitative ecological distances on hundreds of metagenomic samples (690 samples, 32 billions of reads). We also demonstrate that analyzing metagenomes at the k-mer level is highly correlated with extremely precise de novo comparison techniques which rely on all-versus-all sequences alignment strategy or which are based on taxonomic profiling.

Olfactory epithelium changes in germfree mice.

Abstract: Intestinal epithelium development is dramatically impaired in germfree rodents, but the consequences of the absence of microbiota have been overlooked in other epithelia. In the present study, we present the first description of the bacterial communities associated with the olfactory epithelium and explored differences in olfactory epithelium characteristics between germfree and conventional, specific pathogen-free, mice. While the anatomy of the olfactory epithelium was not significantly different, we observed a thinner olfactory cilia layer along with a decreased cellular turn-over in germfree mice. Using electro-olfactogram, we recorded the responses of olfactory sensitive neuronal populations to various odorant stimulations. We observed a global increase in the amplitude of responses to odorants in germfree mice as well as altered responses kinetics. These changes were associated with a decreased transcription of most olfactory transduction actors and of olfactory xenobiotic metabolising enzymes. Overall, we present here the first evidence that the microbiota modulates the physiology of olfactory epithelium. As olfaction is a major sensory modality for most animal species, the microbiota may have an important impact on animal physiology and behaviour through olfaction alteration.

The red queen lives: Epistasis between linked resistance loci

Abstract: A popular theory explaining the maintenance of genetic recombination (sex) is the Red Queen Theory. This theory revolves around the idea that time-lagged negative frequency-dependent selection by parasites favors rare host genotypes generated through recombination. Although the Red Queen has been studied for decades, one of its key assumptions has remained unsupported. The signature host-parasite specificity underlying the Red Queen, where infection depends on a match between host and parasite genotypes, relies on epistasis between linked resistance loci for which no empirical evidence exists. We performed 13 genetic crosses and tested over 7000 Daphnia magna genotypes for resistance to two strains of the bacterial pathogen Pasteuria ramosa. Results reveal the presence of strong epistasis between three closely linked resistance loci. One locus masks the expression of the other two, while these two interact to produce a single resistance phenotype. Changing a single allele on one of these interacting loci can reverse resistance against the tested parasites. Such a genetic mechanism is consistent with host and parasite specificity assumed by the Red Queen Theory. These results thus provide evidence for a fundamental assumption of this theory and provide a genetic basis for understanding the Red Queen dynamics in the Daphnia-Pasteuria system.

FROGS : Find Rapidly OTU with Galaxy Solution

Abstract: High-throughput sequencing of 16S/18S RNA amplicons has opened new horizons in the study of microbe communities. With the sequencing at great depth the current processing pipelines struggle to run rapidly and the most effective solutions are often designed for specialists. These tools are designed to give both the abundance table of operational taxonomic units (OTUs) and their taxonomic affiliation. In this context we developed the pipeline FROGS: « Find Rapidly OTU with Galaxy Solution ». Developed for the Galaxy platform [1-3], FROGS was designed to be run in two modes: with or without demultiplexed sequences. A preprocessing tool merges paired sequences into contigs with flash [4], cleans the data with cutadapt [5], deletes the chimeras with VSEARCH [6] and dereplicates sequences with a home-made python script. The clusterisation tool runs with SWARM [7] that uses a local clustering threshold, not a global clustering threshold like other software do. This tool generate the OTU’s abundance table. The affiliation tool returns taxonomic affiliation for each OTU using both RDPClassifier [8] and NCBI Blast+ [9] on Silva SSU 119 and 123 [10]. And finally, the post processing tool allows users to process this table with the user-specified filters and provides statistical results and numerous graphical illustrations of these data. FROGS has been developed to be very fast even on large amounts of MiSeq data in using cutting-edge tools and an optimized design, also it is portable on all Galaxy platforms with a minimum of informatics and architecture dependencies. FROGS was tested on several simulated data sets. The tool has been extremely rapid, robust and highly sensitive for the detection of OTU with very few false positives compared to other pipelines widely used by the community. 1. Blankenberg, D., et al., Galaxy: a web-based genome analysis tool for experimentalists. Curr Protoc Mol Biol, 2010. Chapter 19: p. Unit 19 10 1-21. 2. Giardine, B., et al., Galaxy: a platform for interactive large-scale genome analysis. Genome Res, 2005. 15(10): p. 1451-5. 3. Goecks, J., et al., Galaxy: a comprehensive approach for supporting accessible, reproducible, and transparent computational research in the life sciences. Genome Biol, 2010. 11(8): p. R86. 4. Magoc, T. and S.L. Salzberg, FLASH: fast length adjustment of short reads to improve genome assemblies. Bioinformatics, 2011. 27(21): p. 2957-63. 5. Martin, M., Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet.journal, 2011. 17(1): p. 10-12. 6. Flouri, T., et al., the VSEARCH GitHub repository, release 1.0.16, doi 10.5281/zenodo.15524. 7. Mahé, F., et al., Swarm: robust and fast clustering method for amplicon-based studies. PeerJ, 2014(2:e593). 8. Wang, Q., G. M. Garrity, J. M. Tiedje, and J. R. Cole, Naïve Bayesian Classifier for Rapid Assignment of rRNA Sequences into the New Bacterial Taxonomy. Appl Environ Appl Environ Microbiol. , 2007. 73(16): p. 5261-7. 9. Camacho, C., et al., BLAST+: architecture and applications. BMC Bioinformatics, 2009. 10: p. 421. 10. Quast, C., et al., The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. Nucleic Acids Res, 2013. 41(Database issue): p. D590-6.

Normalité asymptotique de l’estimateur du maximum de vraisemblance dans le modèle de blocs latents

Abstract: Le modele de blocs latents est une methode non supervisee de classification simultanee des n lignes et d colonnes d’une matrice basee sur un modele probabiliste de melange. Si les methodes d’estimation sont maintenant bien maitrisees, les resultats concernant l’asymptotique de l’estimateur du maximum de vraisemblance restent encore parcellaires. Sous certaines conditions de bornes sur les parametres, et pour un regime asymptotique tel que log(d)/n et log(n)/d tendent vers 0 avec n et d, nous montrons l’equivalence asymptotique du rapport de vraisemblance observee avec celui de la vraisemblance complete. Cette equivalence permet de transferer les proprietes de normalite asymptotique de l’estimateur du maximum de vraisemblance du modele complet a l’estimateur du maximum de vraisemblance.

Detection of adaptive shifts on phylogenies using shifted stochastic processes on a tree

Abstract: Comparative and evolutive ecologists are interested in the distribution of quantitative traits among related species. The classical framework for these distributions consists of a random process running along the branches of a phylogenetic tree relating the species. We consider shifts in the process parameters, which reveal fast adaptation to changes of ecological niches. We show that models with shifts are not identifiable in general. Constraining the models to be parsimonious in the number of shifts partially alleviates the problem but several evolutionary scenarios can still provide the same joint distribution for the extant species. We provide a recursive algorithm to enumerate all the equivalent scenarios and to count the effectively different scenarios. We introduce an incomplete-data framework and develop a maximum likelihood estimation procedure based on the EM algorithm. Finally, we propose a model selection procedure, based on the cardinal of effective scenarios, to estimate the number of shifts and prove an oracle inequality.