Caracterização da comunidade bacteriana endofítica de citros por isolamento, PCR específico e DGGE

O objetivo deste trabalho foi caracterizar a comunidade bacteriana endofítica de plantas assintomáticas (escapes) e afetadas pela clorose variegada dos citros (CVC) por meio de isolamento em meio de cultura, técnica de gradiente desnaturante em gel de eletroforese (DGGE) e detecção de Methylobacterium mesophilicum e Xyllela fastidiosa por meio de PCR específico, para estudar esta comunidade e sua relação com a ocorrência da CVC. A análise da comunidade bacteriana via DGGE permitiu a detecção de X. fastidiosa, bem como Klebsiella sp. e Acinetobacter sp. como endófitos de citros. Foram observados também Curtobacterium sp., Pseudomonas sp., Enterobacter sp. e Bacillus spp. Utilizando primers específicos, Methylobacterium mesophilicum e X. fastidiosa também foram observadas, reforçando hipóteses de que estas bactérias podem estar interagindo no interior da planta hospedeira.

Improved diagnosis of periprosthetic joint infection by multiplex PCR of sonication fluid from removed implants.

The microbiological diagnosis of periprosthetic joint infection (PJI) is crucial for successful antimicrobial treatment. Cultures have limited sensitivity, especially in patients receiving antibiotics. We evaluated the value of multiplex PCR for detection of microbial DNA in sonication fluid from removed orthopedic prostheses. Cases of PJI in which the prosthesis (or part of it) was removed were prospectively included. The removed implant was sonicated, and the resulting sonication fluid was cultured and subjected to multiplex PCR. Of 37 PJI cases (17 hip prostheses, 14 knee prostheses, 4 shoulder prostheses, 1 elbow prosthesis, and 1 ankle prosthesis), pathogens were identified in periprosthetic tissue in 24 (65%) cases, in sonication fluid in 23 (62%) cases, and by multiplex PCR in 29 (78%) cases. The pathogen was detected in 5 cases in sonication fluid only (Propionibacterium acnes in all cases; none of these patients had previously received antibiotics) and in 11 cases by multiplex PCR only (all of these patients had previously received antibiotics). After exclusion of 8 cases caused by P. acnes or Corynebacterium species, which cannot be detected due to the absence of specific primers in the PCR kit, sonication cultures were positive in 17 cases and multiplex PCR sonication cultures were positive in 29 cases (59% versus 100%, respectively; P < 0.01). Among 19 cases (51%) receiving antibiotics, multiplex PCR was positive in all 19 (100%), whereas sonication cultures grew the organism in 8 (42%) (P < 0.01). Multiplex PCR of sonication fluid is a promising test for diagnosis of PJI, particularly in patients who previously received antibiotics. With modified primer sets, multiplex PCR has the potential for further improvement of the diagnosis of PJI.

Combining RT-PCR-seq and RNA-seq to catalog all genic elements encoded in the human genome.

Within the ENCODE Consortium, GENCODE aimed to accurately annotate all protein-coding genes, pseudogenes, and noncoding transcribed loci in the human genome through manual curation and computational methods. Annotated transcript structures were assessed, and less well-supported loci were systematically, experimentally validated. Predicted exon-exon junctions were evaluated by RT-PCR amplification followed by highly multiplexed sequencing readout, a method we called RT-PCR-seq. Seventy-nine percent of all assessed junctions are confirmed by this evaluation procedure, demonstrating the high quality of the GENCODE gene set. RT-PCR-seq was also efficient to screen gene models predicted using the Human Body Map (HBM) RNA-seq data. We validated 73% of these predictions, thus confirming 1168 novel genes, mostly noncoding, which will further complement the GENCODE annotation. Our novel experimental validation pipeline is extremely sensitive, far more than unbiased transcriptome profiling through RNA sequencing, which is becoming the norm. For example, exon-exon junctions unique to GENCODE annotated transcripts are five times more likely to be corroborated with our targeted approach than with extensive large human transcriptome profiling. Data sets such as the HBM and ENCODE RNA-seq data fail sampling of low-expressed transcripts. Our RT-PCR-seq targeted approach also has the advantage of identifying novel exons of known genes, as we discovered unannotated exons in ~11% of assessed introns. We thus estimate that at least 18% of known loci have yet-unannotated exons. Our work demonstrates that the cataloging of all of the genic elements encoded in the human genome will necessitate a coordinated effort between unbiased and targeted approaches, like RNA-seq and RT-PCR-seq.

Rhizosphere bacterial communities of potato cultivars evaluated through PCR-DGGE profiles

The objective of this work was to determine the shifts on the PCR-DGGE profiles of bacterial communities associated to the rhizosphere of potato cultivars, in order to generate baseline information for further studies of environmental risk assessment of genetically modified potato plants. A greenhouse experiment was carried out with five potato cultivars (Achat, Bintje, Agata, Monalisa and Asterix), cultivated in pots containing soil from an integrated system for agroecological production. The experiment was conducted in a split plot randomized block design with five cultivars, three sampling periods and five replicates. Rhizosphere samples were collected in three sampling dates during plant development. DNA of rhizosphere microorganisms was extracted, amplified by PCR using bacterial universal primers, and analyzed through DGGE. Shifts on the rhizosphere bacterial communities associated to rhizosphere of different cultivars were related to both cultivar and plant age. Differences among rhizosphere bacterial communities were clearest at the earliest plant age, tending to decrease in later stages. This variation was detected among bacterial communities of the five tested cultivars. The characterization of soil microbial communities can be part of plant breeding programs to be used on studies of environmental risk assessment of genetically modified potatoes.

Childhood epilepsy with neuropsychological regression and continuous spike waves during sleep: epilepsy surgery in a young adult.

We describe the case of a man with a history of complex partial seizures and severe language, cognitive and behavioural regression during early childhood (3.5 years), who underwent epilepsy surgery at the age of 25 years. His early epilepsy had clinical and electroencephalogram features of the syndromes of epilepsy with continuous spike waves during sleep and acquired epileptic aphasia (Landau-Kleffner syndrome), which we considered initially to be of idiopathic origin. Seizures recurred at 19 years and presurgical investigations at 25 years showed a lateral frontal epileptic focus with spread to Broca's area and the frontal orbital regions. Histopathology revealed a focal cortical dysplasia, not visible on magnetic resonance imaging. The prolonged but reversible early regression and the residual neuropsychological disorders during adulthood were probably the result of an active left frontal epilepsy, which interfered with language and behaviour during development. Our findings raise the question of the role of focal cortical dysplasia as an aetiology in the syndromes of epilepsy with continuous spike waves during sleep and acquired epileptic aphasia.

Exposure to bioaerosols in poultry houses at different stages of fattening: use of real-time PCR for airborne bacterial quantification

Previous studies have demonstrated that poultry-house workers are exposed to very high levels of organic dust and consequently have an increased prevalence of adverse respiratory symptoms. However, the influence of the age of broilers, on bioaerosol concentrations has not been investigated. To evaluate the evolution of bioaerosol concentration during the fattening period, bioaerosol parameters (inhalable dust, endotoxin and bacteria) were measured in 12 poultry confinement buildings in Switzerland, at 3 different stages of the birds' growth; Samples of air taken from within the breathing zones of individual poultry-house employees as they caught the chickens ready to be transported for slaughter, were also analysed. Quantitative PCR (Q-PCR) was used to assess the quantity of total airborne bacteria and total airborne Staphylococcus species. Bioaerosol levels increased significantly during the fattening period of the chickens. During the task of catching mature birds, the mean inhalable dust concentration for a worker was 31 ± 4.7 mg/m3, and endotoxin concentration was 11'080 ± 3436 UE/m3 air, more than ten-fold higher than the Swiss occupational recommended value (1000 UE/m3). The mean exposure level of bird catchers to total bacteria and Staphylococcus species measured by Q-PCR is also very high, respectively reaching values of 72 (± 11) x107 cells/m3 air and 70 (± 16) x106/m3 air. It was concluded that in the absence of wearing protective breathing apparatus, chicken catchers in Switzerland risk exposure beyond recommended limits for all measured bioaerosol parameters. Moreover, the use of Q-PCR to estimate total and specific numbers of airborne bacteria is a promising tool for evaluating any modifications intended to improve the safety of current working practices.

Statistical significance of quantitative PCR.

BACKGROUND: PCR has the potential to detect and precisely quantify specific DNA sequences, but it is not yet often used as a fully quantitative method. A number of data collection and processing strategies have been described for the implementation of quantitative PCR. However, they can be experimentally cumbersome, their relative performances have not been evaluated systematically, and they often remain poorly validated statistically and/or experimentally. In this study, we evaluated the performance of known methods, and compared them with newly developed data processing strategies in terms of resolution, precision and robustness. RESULTS: Our results indicate that simple methods that do not rely on the estimation of the efficiency of the PCR amplification may provide reproducible and sensitive data, but that they do not quantify DNA with precision. Other evaluated methods based on sigmoidal or exponential curve fitting were generally of both poor resolution and precision. A statistical analysis of the parameters that influence efficiency indicated that it depends mostly on the selected amplicon and to a lesser extent on the particular biological sample analyzed. Thus, we devised various strategies based on individual or averaged efficiency values, which were used to assess the regulated expression of several genes in response to a growth factor. CONCLUSION: Overall, qPCR data analysis methods differ significantly in their performance, and this analysis identifies methods that provide DNA quantification estimates of high precision, robustness and reliability. These methods allow reliable estimations of relative expression ratio of two-fold or higher, and our analysis provides an estimation of the number of biological samples that have to be analyzed to achieve a given precision.

Improved detection of Rhodococcus coprophilus with a new quantitative PCR assay.

Agricultural practices, such as spreading liquid manure or the utilisation of land as animal pastures, can result in faecal contamination of water resources. Rhodococcus coprophilus is used in microbial source tracking to indicate animal faecal contamination in water. Methods previously described for detecting of R. coprophilus in water were neither sensitive nor specific. Therefore, the aim of this study was to design and validate a new quantitative polymerase chain reaction (qPCR) to improve the detection of R. coprophilus in water. The new PCR assay was based on the R. coprophilus 16S rRNA gene. The validation showed that the new approach was specific and sensitive for deoxyribunucleic acid from target host species. Compared with other PCR assays tested in this study, the detection limit of the new qPCR was between 1 and 3 log lower. The method, including a filtration step, was further validated and successfully used in a field investigation in Switzerland. Our work demonstrated that the new detection method is sensitive and robust to detect R. coprophilus in surface and spring water. Compared with PCR assays that are available in the literature or to the culture-dependent method, the new molecular approach improves the detection of R. coprophilus.

Robust Nonlinear Mapping of Soil Contamination Using Support Regression

Spatial data analysis mapping and visualization is of great importance in various fields: environment, pollution, natural hazards and risks, epidemiology, spatial econometrics, etc. A basic task of spatial mapping is to make predictions based on some empirical data (measurements). A number of state-of-the-art methods can be used for the task: deterministic interpolations, methods of geostatistics: the family of kriging estimators (Deutsch and Journel, 1997), machine learning algorithms such as artificial neural networks (ANN) of different architectures, hybrid ANN-geostatistics models (Kanevski and Maignan, 2004; Kanevski et al., 1996), etc. All the methods mentioned above can be used for solving the problem of spatial data mapping. Environmental empirical data are always contaminated/corrupted by noise, and often with noise of unknown nature. That's one of the reasons why deterministic models can be inconsistent, since they treat the measurements as values of some unknown function that should be interpolated. Kriging estimators treat the measurements as the realization of some spatial randomn process. To obtain the estimation with kriging one has to model the spatial structure of the data: spatial correlation function or (semi-)variogram. This task can be complicated if there is not sufficient number of measurements and variogram is sensitive to outliers and extremes. ANN is a powerful tool, but it also suffers from the number of reasons. of a special type ? multiplayer perceptrons ? are often used as a detrending tool in hybrid (ANN+geostatistics) models (Kanevski and Maignank, 2004). Therefore, development and adaptation of the method that would be nonlinear and robust to noise in measurements, would deal with the small empirical datasets and which has solid mathematical background is of great importance. The present paper deals with such model, based on Statistical Learning Theory (SLT) - Support Vector Regression. SLT is a general mathematical framework devoted to the problem of estimation of the dependencies from empirical data (Hastie et al, 2004; Vapnik, 1998). SLT models for classification - Support Vector Machines - have shown good results on different machine learning tasks. The results of SVM classification of spatial data are also promising (Kanevski et al, 2002). The properties of SVM for regression - Support Vector Regression (SVR) are less studied. First results of the application of SVR for spatial mapping of physical quantities were obtained by the authorsin for mapping of medium porosity (Kanevski et al, 1999), and for mapping of radioactively contaminated territories (Kanevski and Canu, 2000). The present paper is devoted to further understanding of the properties of SVR model for spatial data analysis and mapping. Detailed description of the SVR theory can be found in (Cristianini and Shawe-Taylor, 2000; Smola, 1996) and basic equations for the nonlinear modeling are given in section 2. Section 3 discusses the application of SVR for spatial data mapping on the real case study - soil pollution by Cs137 radionuclide. Section 4 discusses the properties of the modelapplied to noised data or data with outliers.

Identification des dermatophytes causant des teignes de la peau glabre (Tinea glabra) et du cuir chevelu (Tinea capitis) par PCR

Contexte: Le nombre de teignes du cuir chevelu et de la peau glabre étant en nette augmentation, l'identification du pathogène qui est indispensable pour un traitement ciblé, a, par conséquence, un grand intérêt pour la santé publique. Dans divers cas, un animal de compagnie peut être identifié en tant que source du pathogène. La fréquence de cultures restant stériles est particulièrement élevée en cas de prétraitement antifongique. Objectif: Le but de ce travail est de mettre au point une méthode rapide d'identification du dermatophyte pathogène in situ par PCR/séquençage dans les cas de teignes du cuir chevelu et/ou de la peau glabre. Matériel et méthodes : De l'ADN a été extrait de squames (N=5) et cheveux (N=21) dont l'examen direct démontrait une infection fongique (N=26) ou se révèlait négatif (N=1). Ensuite, une première PCR du segment 28s de l'ADN ribosomale fongique a été effectuée, suivie par une PCR nichée intérieure à ce segment. L'amplicon a été séquencé et le champignon est identifié par alignement. Résultats : Seule la PCR enchainée a permis d'obtenir une quantité suffisante d'amplicon pour permettre le séquençage. Dans 4 cas sur 5 de tinea pedis, 10 sur 12 de tinea glabra, respectivement 4 sur 4 de tinea capitis, dans lesquels un dermato- phyte a été identifié en culture, le même dermatophyte a été identifié par PCR/séquençage. Une fois sur 27 prélèvements, un autre dermatophyte a été identifié par PCR/séquençage. Ce résultat pourrait être dû à une fausse identification du champignon en culture. Dans un cas de tinea pedis et un cas de tinea corporis, la culture est restée stérile, mais un dermatophyte a pu être identifié par PCR et séquençage. Conclusions : La méthode décrite est à la fois rapide (24 h au lieu de deux semaines pour la culture), sensible et très spécifique. Elle est particulièrement utile dans les cas de teigne du cuir chevelu, dans lesquels le traitement est différent selon l'espèce de dermatophyte et où il s'agit d'un traitement systémique lourd, souvent chez l'enfant.

Identification of reference genes for expression analysis by real-time quantitative PCR in drought-stressed soybean

The objective of this work was to validate, by quantitative PCR in real time (RT-qPCR), genes to be used as reference in studies of gene expression in soybean in drought-stressed trials. Four genes commonly used in soybean were evaluated: Gmβ-actin, GmGAPDH, GmLectin and GmRNAr18S. Total RNA was extracted from six samples: three from roots in a hydroponic system with different drought intensities (0, 25, 50, 75 and 100 minutes of water stress), and three from leaves of plants grown in sand with different soil moistures (15, 5 and 2.5% gravimetric humidity). The raw cycle threshold (Ct) data were analyzed, and the efficiency of each primer was calculated for an overall analysis of the Ct range among the different samples. The GeNorm application was used to evaluate the best reference gene, according to its stability. The GmGAPDH was the least stable gene, with the highest mean values of expression stability (M), and the most stable genes, with the lowest M values, were the Gmβ-actin and GmRNAr18S, when both root and leaves samples were tested. These genes can be used in RT-qPCR as reference gene for expression analysis.

Development of a duplex real-time PCR for the detection of Rickettsia spp. and typhus group rickettsia in clinical samples.

Molecular diagnosis using real-time polymerase chain reaction (PCR) may allow earlier diagnosis of rickettsiosis. We developed a duplex real-time PCR that amplifies (1) DNA of any rickettsial species and (2) DNA of both typhus group rickettsia, that is, Rickettsia prowazekii and Rickettsia typhi. Primers and probes were selected to amplify a segment of the 16S rRNA gene of Rickettsia spp. for the pan-rickettsial PCR and the citrate synthase gene (gltA) for the typhus group rickettsia PCR. Analytical sensitivity was 10 copies of control plasmid DNA per reaction. No cross-amplification was observed when testing human DNA and 22 pathogens or skin commensals. Real-time PCR was applied to 16 clinical samples. Rickettsial DNA was detected in the skin biopsies of three patients. In one patient with severe murine typhus, the typhus group PCR was positive in a skin biopsy from a petechial lesion and seroconversion was later documented. The two other patients with negative typhus group PCR suffered from Mediterranean and African spotted fever, respectively; in both cases, skin biopsy was performed on the eschar. Our duplex real-time PCR showed a good analytical sensitivity and specificity, allowing early diagnosis of rickettsiosis among three patients, and recognition of typhus in one of them.

Stability and adaptability of runner peanut genotypes based on nonlinear regression and AMMI analysis

The objective of this work was to estimate the stability and adaptability of pod and seed yield in runner peanut genotypes based on the nonlinear regression and AMMI analysis. Yield data from 11 trials, distributed in six environments and three harvests, carried out in the Northeast region of Brazil during the rainy season were used. Significant effects of genotypes (G), environments (E), and GE interactions were detected in the analysis, indicating different behaviors among genotypes in favorable and unfavorable environmental conditions. The genotypes BRS Pérola Branca and LViPE‑06 are more stable and adapted to the semiarid environment, whereas LGoPE‑06 is a promising material for pod production, despite being highly dependent on favorable environments.

Spatial prediction of monthly wind speeds in complex terrain with adaptive general regression neural networks

This paper presents the general regression neural networks (GRNN) as a nonlinear regression method for the interpolation of monthly wind speeds in complex Alpine orography. GRNN is trained using data coming from Swiss meteorological networks to learn the statistical relationship between topographic features and wind speed. The terrain convexity, slope and exposure are considered by extracting features from the digital elevation model at different spatial scales using specialised convolution filters. A database of gridded monthly wind speeds is then constructed by applying GRNN in prediction mode during the period 1968-2008. This study demonstrates that using topographic features as inputs in GRNN significantly reduces cross-validation errors with respect to low-dimensional models integrating only geographical coordinates and terrain height for the interpolation of wind speed. The spatial predictability of wind speed is found to be lower in summer than in winter due to more complex and weaker wind-topography relationships. The relevance of these relationships is studied using an adaptive version of the GRNN algorithm which allows to select the useful terrain features by eliminating the noisy ones. This research provides a framework for extending the low-dimensional interpolation models to high-dimensional spaces by integrating additional features accounting for the topographic conditions at multiple spatial scales. Copyright (c) 2012 Royal Meteorological Society.