Pyrosequencing identification of Mycobacterium tuberculosis W-Beijing

<p>Abstract</p> <p>Background</p> <p>The worldwide expanding <it>Mycobacterium tuberculosis </it>W-Beijing family is associated with treatment failure and relapse. Its identification currently relies on spoligotyping and conventional sequencing. We developed pyrosequencing as an alternative method for its identification.</p> <p>Findings</p> <p>Pyrosequencing found a G/A substitution in the Rv0927c-pstS3 intergenic spacer and a RD105 deletion, identifying 8/104 <it>M. tuberculosis </it>isolates as W-Beijing isolates. In addition, pyrosequencing found a previously unreported TGC deletion in the Rv0927c gene of W-Beijing isolates. Total concordance was found between the pyrosequencing data and conventional sequencing, as well as reference molecular identification. Multispacer Sequence Typing assigned the W-Beijing isolates to the Asian lineage and the 96 non-W-Beijing isolates to the Euro-American lineage (P < 10^-5). The W-Beijing isolates were all susceptible to streptomycin, rifampin, isoniazid, ethambutol, and pyrazinamide; no resistance-associated mutations were detected in these eight W-Beijing isolates. There were no statistically significant differences in the antibiotic susceptibility of W-Beijing and non-W-Beijing isolates (<it>p </it>= 0.2, X²test). Pyrosequencing correctly identified <it>M. tuberculosis </it>organisms in 26/26 sputum specimens exhibiting acid-fast bacilli. Pyrosequencing results were obtained within four hours, incurring an estimated cost of 1.86 €/test.</p> <p>Conclusion</p> <p>Pyrosequencing of the Rv0927c gene and adjacent intergenic spacer is an efficient, low-cost technique for the rapid identification of W-Beijing isolates.</p

Sensitivity analysis and uncertainty in CFD simulations of multiphase flow

International audienceWe present recent developments that have been made within the framework of the VIMMP EU project (Virtual Materials Market Place). Our objective is to set up a methodology to analyse the sensitivityand then quantify uncertainty in numerical simulations of multiphase flows to a number of input variables. In this talk, we start by introducing the workflow used for the multiphase flow simulations. The physical case studied here consists in the point-source dispersion of particles by a turbulent pipe flow. Numerical simulations are performed by coupling a CFD simulation of the turbulent pipe flow (using standard turbulence models) to a particle-tracking simulation (using a stochastic Lagrangian model). The simulations are performed in Code_Saturne CFD [1]. The workflow is launched using tools from the Salome Platform, which allows to handle the coupling of the fluid phase simulation and the particle-phase simulation. The results obtained are then analysed using existing tools within OpenTurns [2]. For that purpose, a dataset is obtained by running the workflow with a range of input variables (e.g. the fluid velocity, number of particles injected, size of particles) and accounting for the intrinsic stochasticity of each run. Then, we use sensitivity analysis techniques (especially Sobol sensitivity index [3] through meta-model) to identify the key parameters affecting the observed results. By considering several observables, we also highlight the need to define a clear observable before running such analysis

ANALYSE DE SENSIBILITÉ DE LA DISPERSION DE GOUTTELETTES AUX CONDITIONS D'ÉMISSION ET A L'AIR AMBIENT

National audienceThis work presents a methodology to analyse the sensitivity of numerical simulations related to the dispersion of droplets in the air. The methodology is based on existing tools for sensitivity analysis (e.g. Sobol sensitivity index). This methodology is illustrated by analysing a large number of numerical results obtained in two situations: first a simple toy model (without underlying flow) and then a more realistic case (with underlying flow). The preliminary results allow to identify the parameters affecting the results but show a significant impact of the observable chosen for the analysis.Nous présentons une méthodologie pour analyser la sensibilité et quantifier l'incertitude des résultats de simulation numérique obtenus dans le contexte de la dispersion de gouttelettes dans l'air. La méthodologie se fonde sur les outils existants d'analyse de sensibilité (notamment la méthode de Sobol). L'intérêt de recourir à ces outils d'analyse de grands nombres de résultats est illustré à travers deux situations: un cas simplifié sans écoulement fluide environnant et un cas réaliste avec écoulement fluide. Les résultats préliminaires permettent d'identifier les paramètres influençant les résultats numériques mais montrent une forte sensibilité à l'observable choisie pour l'analyse

High Prevalence of Methanobrevibacter smithii and Methanosphaera stadtmanae Detected in the Human Gut Using an Improved DNA Detection Protocol

Background: The low and variable prevalence of Methanobrevibacter smithii and Methanosphaera stadtmanae DNA in human stool contrasts with the paramount role of these methanogenic Archaea in digestion processes. We hypothesized that this contrast is a consequence of the inefficiencies of current protocols for archaeon DNA extraction. We developed a new protocol for the extraction and PCR-based detection of M. smithii and M. stadtmanae DNA in human stool. Methodology/Principal Findings: Stool specimens collected from 700 individuals were filtered, mechanically lysed twice, and incubated overnight with proteinase K prior to DNA extraction using a commercial DNA extraction kit. Total DNA was used as a template for quantitative real-time PCR targeting M. smithii and M. stadtmanae 16S rRNA and rpoB genes. Amplification of 16S rRNA and rpoB yielded positive detection of M. smithii in 95.7% and M. stadtmanae in 29.4% of specimens. Sequencing of 16S rRNA gene PCR products from 30 randomly selected specimens ( 15 for M. smithii and 15 for M. stadtmanae) yielded a sequence similarity of 99-100% using the reference M. smithii ATCC 35061 and M. stadtmanae DSM 3091 sequences. Conclusions/Significance: In contrast to previous reports, these data indicate a high prevalence of the methanogens M. smithii and M. stadtmanae in the human gut, with the former being an almost ubiquitous inhabitant of the intestinal microbiome

Monitoring Bacterial Community of Human Gut Microbiota Reveals an Increase in Lactobacillus in Obese Patients and Methanogens in Anorexic Patients

Background: Studies of the bacterial communities of the gut microbiota have revealed a shift in the ratio of Firmicutes and Bacteroidetes in obese patients. Determining the variations of microbial communities in feces may be beneficial for the identification of specific profiles in patients with abnormal weights. The roles of the archaeon Methanobrevibacter smithii and Lactobacillus species have not been described in these studies. Methods and Findings: We developed an efficient and robust real-time PCR tool that includes a plasmid-based internal control and allows for quantification of the bacterial divisions Bacteroidetes, Firmicutes, and Lactobacillus as well as the methanogen M. smithii. We applied this technique to the feces of 20 obese subjects, 9 patients with anorexia nervosa, and 20 normal-weight healthy controls. Our results confirmed a reduction in the Bacteroidetes community in obese patients (p<0.01). We found a significantly higher Lactobacillus species concentration in obese patients than in lean controls (p = 0.0197) or anorexic patients (p = 0.0332). The M. smithii concentration was much higher in anorexic patients than in the lean population (p = 0.0171). Conclusions: Lactobacillus species are widely used as growth promoters in the farm industry and are now linked to obesity in humans. The study of the bacterial flora in anorexic patients revealed an increase in M. smithii. This increase might represent an adaptive use of nutrients in this population

Annual cycles are the most common reproductive strategy in African tropical tree communities

We present the first cross continental comparison of the flowering and fruiting phenology of tropical forests across Africa. Flowering events of 5,446 trees from 196 species across 12 sites, and fruiting events of 4,595 trees from 191 species, across 11 sites were monitored over periods of 6 to 29 years, and analysed to describe phenology at the continental level. To study phenology we used Fourier analysis to identify the dominant cycles of flowering and fruiting for each individual tree and we identified the time of year African trees bloom and bear fruit and their relationship to local seasonality. Reproductive strategies were diverse and no single regular cycle was found in >50% of individuals across all 12 sites. Additionally, we found annual flowering and fruiting cycles to be the most common. Sub-annual cycles were the next most common for flowering whereas supra-annual patterns were the next most common for fruiting. We also identify variation in different subsets of species, with species exhibiting mainly annual cycles most common in West and West-Central African tropical forests, while more species at sites in East-Central and Eastern African forests showed cycles ranging from sub-annual to supra-annual. Despite many trees showing strong seasonality, at most sites some flowering and fruiting occurred all year round. Environmental factors with annual cycles are likely to be important drivers of seasonal periodicity in trees across Africa, but proximate triggers are unlikely to be constant across the continen

Socializing One Health: an innovative strategy to investigate social and behavioral risks of emerging viral threats

In an effort to strengthen global capacity to prevent, detect, and control infectious diseases in animals and people, the United States Agency for International Development’s (USAID) Emerging Pandemic Threats (EPT) PREDICT project funded development of regional, national, and local One Health capacities for early disease detection, rapid response, disease control, and risk reduction. From the outset, the EPT approach was inclusive of social science research methods designed to understand the contexts and behaviors of communities living and working at human-animal-environment interfaces considered high-risk for virus emergence. Using qualitative and quantitative approaches, PREDICT behavioral research aimed to identify and assess a range of socio-cultural behaviors that could be influential in zoonotic disease emergence, amplification, and transmission. This broad approach to behavioral risk characterization enabled us to identify and characterize human activities that could be linked to the transmission dynamics of new and emerging viruses. This paper provides a discussion of implementation of a social science approach within a zoonotic surveillance framework. We conducted in-depth ethnographic interviews and focus groups to better understand the individual- and community-level knowledge, attitudes, and practices that potentially put participants at risk for zoonotic disease transmission from the animals they live and work with, across 6 interface domains. When we asked highly-exposed individuals (ie. bushmeat hunters, wildlife or guano farmers) about the risk they perceived in their occupational activities, most did not perceive it to be risky, whether because it was normalized by years (or generations) of doing such an activity, or due to lack of information about potential risks. Integrating the social sciences allows investigations of the specific human activities that are hypothesized to drive disease emergence, amplification, and transmission, in order to better substantiate behavioral disease drivers, along with the social dimensions of infection and transmission dynamics. Understanding these dynamics is critical to achieving health security--the protection from threats to health-- which requires investments in both collective and individual health security. Involving behavioral sciences into zoonotic disease surveillance allowed us to push toward fuller community integration and engagement and toward dialogue and implementation of recommendations for disease prevention and improved health security