Machine learning for geospatial data : algorithms, software tools and case studies

Résumé Cette thèse est consacrée à l'analyse, la modélisation et la visualisation de données environnementales à référence spatiale à l'aide d'algorithmes d'apprentissage automatique (Machine Learning). L'apprentissage automatique peut être considéré au sens large comme une sous-catégorie de l'intelligence artificielle qui concerne particulièrement le développement de techniques et d'algorithmes permettant à une machine d'apprendre à partir de données. Dans cette thèse, les algorithmes d'apprentissage automatique sont adaptés pour être appliqués à des données environnementales et à la prédiction spatiale. Pourquoi l'apprentissage automatique ? Parce que la majorité des algorithmes d'apprentissage automatiques sont universels, adaptatifs, non-linéaires, robustes et efficaces pour la modélisation. Ils peuvent résoudre des problèmes de classification, de régression et de modélisation de densité de probabilités dans des espaces à haute dimension, composés de variables informatives spatialisées (« géo-features ») en plus des coordonnées géographiques. De plus, ils sont idéaux pour être implémentés en tant qu'outils d'aide à la décision pour des questions environnementales allant de la reconnaissance de pattern à la modélisation et la prédiction en passant par la cartographie automatique. Leur efficacité est comparable au modèles géostatistiques dans l'espace des coordonnées géographiques, mais ils sont indispensables pour des données à hautes dimensions incluant des géo-features. Les algorithmes d'apprentissage automatique les plus importants et les plus populaires sont présentés théoriquement et implémentés sous forme de logiciels pour les sciences environnementales. Les principaux algorithmes décrits sont le Perceptron multicouches (MultiLayer Perceptron, MLP) - l'algorithme le plus connu dans l'intelligence artificielle, le réseau de neurones de régression généralisée (General Regression Neural Networks, GRNN), le réseau de neurones probabiliste (Probabilistic Neural Networks, PNN), les cartes auto-organisées (SelfOrganized Maps, SOM), les modèles à mixture Gaussiennes (Gaussian Mixture Models, GMM), les réseaux à fonctions de base radiales (Radial Basis Functions Networks, RBF) et les réseaux à mixture de densité (Mixture Density Networks, MDN). Cette gamme d'algorithmes permet de couvrir des tâches variées telle que la classification, la régression ou l'estimation de densité de probabilité. L'analyse exploratoire des données (Exploratory Data Analysis, EDA) est le premier pas de toute analyse de données. Dans cette thèse les concepts d'analyse exploratoire de données spatiales (Exploratory Spatial Data Analysis, ESDA) sont traités selon l'approche traditionnelle de la géostatistique avec la variographie expérimentale et selon les principes de l'apprentissage automatique. La variographie expérimentale, qui étudie les relations entre pairs de points, est un outil de base pour l'analyse géostatistique de corrélations spatiales anisotropiques qui permet de détecter la présence de patterns spatiaux descriptible par une statistique. L'approche de l'apprentissage automatique pour l'ESDA est présentée à travers l'application de la méthode des k plus proches voisins qui est très simple et possède d'excellentes qualités d'interprétation et de visualisation. Une part importante de la thèse traite de sujets d'actualité comme la cartographie automatique de données spatiales. Le réseau de neurones de régression généralisée est proposé pour résoudre cette tâche efficacement. Les performances du GRNN sont démontrées par des données de Comparaison d'Interpolation Spatiale (SIC) de 2004 pour lesquelles le GRNN bat significativement toutes les autres méthodes, particulièrement lors de situations d'urgence. La thèse est composée de quatre chapitres : théorie, applications, outils logiciels et des exemples guidés. Une partie importante du travail consiste en une collection de logiciels : Machine Learning Office. Cette collection de logiciels a été développée durant les 15 dernières années et a été utilisée pour l'enseignement de nombreux cours, dont des workshops internationaux en Chine, France, Italie, Irlande et Suisse ainsi que dans des projets de recherche fondamentaux et appliqués. Les cas d'études considérés couvrent un vaste spectre de problèmes géoenvironnementaux réels à basse et haute dimensionnalité, tels que la pollution de l'air, du sol et de l'eau par des produits radioactifs et des métaux lourds, la classification de types de sols et d'unités hydrogéologiques, la cartographie des incertitudes pour l'aide à la décision et l'estimation de risques naturels (glissements de terrain, avalanches). Des outils complémentaires pour l'analyse exploratoire des données et la visualisation ont également été développés en prenant soin de créer une interface conviviale et facile à l'utilisation. Machine Learning for geospatial data: algorithms, software tools and case studies Abstract The thesis is devoted to the analysis, modeling and visualisation of spatial environmental data using machine learning algorithms. In a broad sense machine learning can be considered as a subfield of artificial intelligence. It mainly concerns with the development of techniques and algorithms that allow computers to learn from data. In this thesis machine learning algorithms are adapted to learn from spatial environmental data and to make spatial predictions. Why machine learning? In few words most of machine learning algorithms are universal, adaptive, nonlinear, robust and efficient modeling tools. They can find solutions for the classification, regression, and probability density modeling problems in high-dimensional geo-feature spaces, composed of geographical space and additional relevant spatially referenced features. They are well-suited to be implemented as predictive engines in decision support systems, for the purposes of environmental data mining including pattern recognition, modeling and predictions as well as automatic data mapping. They have competitive efficiency to the geostatistical models in low dimensional geographical spaces but are indispensable in high-dimensional geo-feature spaces. The most important and popular machine learning algorithms and models interesting for geo- and environmental sciences are presented in details: from theoretical description of the concepts to the software implementation. The main algorithms and models considered are the following: multi-layer perceptron (a workhorse of machine learning), general regression neural networks, probabilistic neural networks, self-organising (Kohonen) maps, Gaussian mixture models, radial basis functions networks, mixture density networks. This set of models covers machine learning tasks such as classification, regression, and density estimation. Exploratory data analysis (EDA) is initial and very important part of data analysis. In this thesis the concepts of exploratory spatial data analysis (ESDA) is considered using both traditional geostatistical approach such as_experimental variography and machine learning. Experimental variography is a basic tool for geostatistical analysis of anisotropic spatial correlations which helps to understand the presence of spatial patterns, at least described by two-point statistics. A machine learning approach for ESDA is presented by applying the k-nearest neighbors (k-NN) method which is simple and has very good interpretation and visualization properties. Important part of the thesis deals with a hot topic of nowadays, namely, an automatic mapping of geospatial data. General regression neural networks (GRNN) is proposed as efficient model to solve this task. Performance of the GRNN model is demonstrated on Spatial Interpolation Comparison (SIC) 2004 data where GRNN model significantly outperformed all other approaches, especially in case of emergency conditions. The thesis consists of four chapters and has the following structure: theory, applications, software tools, and how-to-do-it examples. An important part of the work is a collection of software tools - Machine Learning Office. Machine Learning Office tools were developed during last 15 years and was used both for many teaching courses, including international workshops in China, France, Italy, Ireland, Switzerland and for realizing fundamental and applied research projects. Case studies considered cover wide spectrum of the real-life low and high-dimensional geo- and environmental problems, such as air, soil and water pollution by radionuclides and heavy metals, soil types and hydro-geological units classification, decision-oriented mapping with uncertainties, natural hazards (landslides, avalanches) assessments and susceptibility mapping. Complementary tools useful for the exploratory data analysis and visualisation were developed as well. The software is user friendly and easy to use.

Magnetic resonance-guided, real-time targeted delivery and imaging of magnetocapsules immunoprotecting pancreatic islet cells.

In type I diabetes mellitus, islet transplantation provides a moment-to-moment fine regulation of insulin. Success rates vary widely, however, necessitating suitable methods to monitor islet delivery, engraftment and survival. Here magnetic resonance-trackable magnetocapsules have been used simultaneously to immunoprotect pancreatic beta-cells and to monitor, non-invasively in real-time, hepatic delivery and engraftment by magnetic resonance imaging (MRI). Magnetocapsules were detected as single capsules with an altered magnetic resonance appearance on capsule rupture. Magnetocapsules were functional in vivo because mouse beta-cells restored normal glycemia in streptozotocin-induced diabetic mice and human islets induced sustained C-peptide levels in swine. In this large-animal model, magnetocapsules could be precisely targeted for infusion by using magnetic resonance fluoroscopy, whereas MRI facilitated monitoring of liver engraftment over time. These findings are directly applicable to ongoing improvements in islet cell transplantation for human diabetes, particularly because our magnetocapsules comprise clinically applicable materials.

Navigator-gated and real-time motion corrected free-breathing MR Imaging of myocardial late enhancement.

PURPOSE: A new magnetic resonance imaging approach for detection of myocardial late enhancement during free-breathing was developed. METHODS AND RESULTS: For suppression of respiratory motion artifacts, a prospective navigator technology including real-time motion correction and a local navigator restore was implemented. Subject specific inversion times were defined from images with incrementally increased inversion times acquired during a single dynamic scout navigator-gated and real-time motion corrected free-breathing scan. Subsequently, MR-imaging of myocardial late enhancement was performed with navigator-gated and real-time motion corrected adjacent short axis and long axis (two, three and four chamber) views. This alternative approach was investigated in 7 patients with history of myocardial infarction 12 min after i. v. administration of 0.2 mmol/kg body weight gadolinium-DTPA. CONCLUSION: With the presented navigator-gated and real-time motion corrected sequence for MR-imaging of myocardial late enhancement data can be completely acquired during free-breathing. Time constraints of a breath-hold technique are abolished and optimized patient specific inversion time is ensured.

Impact of the introduction of real-time therapeutic drug monitoring on empirical doses of carbapenems in critically ill burn patients.

PURPOSE: Adequate empirical antibiotic dose selection for critically ill burn patients is difficult due to extreme variability in drug pharmacokinetics. Therapeutic drug monitoring (TDM) may aid antibiotic prescription and implementation of initial empirical antimicrobial dosage recommendations. This study evaluated how gradual TDM introduction altered empirical dosages of meropenem and imipenem/cilastatin in our burn ICU. METHODS: Imipenem/cilastatin and meropenem use and daily empirical dosage at a five-bed burn ICU were analyzed retrospectively. Data for all burn admissions between 2001 and 2011 were extracted from the hospital's computerized information system. For each patient receiving a carbapenem, episodes of infection were reviewed and scored according to predefined criteria. Carbapenem trough serum levels were characterized. Prior to May 2007, TDM was available only by special request. Real-time carbapenem TDM was introduced in June 2007; it was initially available weekly and has been available 4 days a week since 2010. RESULTS: Of 365 patients, 229 (63%) received antibiotics (109 received carbapenems). Of 23 TDM determinations for imipenem/cilastatin, none exceeded the predefined upper limit and 11 (47.8%) were insufficient; the number of TDM requests was correlated with daily dose (r=0.7). Similar numbers of inappropriate meropenem trough levels (30.4%) were below and above the upper limit. Real-time TDM introduction increased the empirical dose of imipenem/cilastatin, but not meropenem. CONCLUSIONS: Real-time carbapenem TDM availability significantly altered the empirical daily dosage of imipenem/cilastatin at our burn ICU. Further studies are needed to evaluate the individual impact of TDM-based antibiotic adjustment on infection outcomes in these patients.

Early detection of microcirculatory perfusion changes with a high resolution, real time laser Doppler imaging camera--frostbite case study.

A 41-year-old male presented with severe frostbite that was monitored clinically and with a new laser Doppler imaging (LDI) camera that records arbitrary microcirculatory perfusion units (1-256 arbitrary perfusion units (APU's)). LDI monitoring detected perfusion differences in hand and foot not seen visually. On day 4-5 after injury, LDI showed that while fingers did not experience any significant perfusion change (average of 31±25 APUs on day 5), the patient's left big toe did (from 17±29 APUs day 4 to 103±55 APUs day 5). These changes in regional perfusion were not detectable by visual examination. On day 53 postinjury, all fingers with reduced perfusion by LDI were amputated, while the toe could be salvaged. This case clearly demonstrates that insufficient microcirculatory perfusion can be identified using LDI in ways which visual examination alone does not permit, allowing prognosis of clinical outcomes. Such information may also be used to develop improved treatment approaches.

Discovery of a 29-gene panel in peripheral blood mononuclear cells for the detection of colorectal cancer and adenomas using high throughput real-time PCR.

Colorectal cancer (CRC) is the second leading cause of cancer-related death in developed countries. Early detection of CRC leads to decreased CRC mortality. A blood-based CRC screening test is highly desirable due to limited invasiveness and high acceptance rate among patients compared to currently used fecal occult blood testing and colonoscopy. Here we describe the discovery and validation of a 29-gene panel in peripheral blood mononuclear cells (PBMC) for the detection of CRC and adenomatous polyps (AP). Blood samples were prospectively collected from a multicenter, case-control clinical study. First, we profiled 93 samples with 667 candidate and 3 reference genes by high throughput real-time PCR (OpenArray system). After analysis, 160 genes were retained and tested again on 51 additional samples. Low expressed and unstable genes were discarded resulting in a final dataset of 144 samples profiled with 140 genes. To define which genes, alone or in combinations had the highest potential to discriminate AP and/or CRC from controls, data were analyzed by a combination of univariate and multivariate methods. A list of 29 potentially discriminant genes was compiled and evaluated for its predictive accuracy by penalized logistic regression and bootstrap. This method discriminated AP >1cm and CRC from controls with a sensitivity of 59% and 75%, respectively, with 91% specificity. The behavior of the 29-gene panel was validated with a LightCycler 480 real-time PCR platform, commonly adopted by clinical laboratories. In this work we identified a 29-gene panel expressed in PBMC that can be used for developing a novel minimally-invasive test for accurate detection of AP and CRC using a standard real-time PCR platform.

Reverse transcription quantitative real-time polymerase chain reaction reference genes in the spared nerve injury model of neuropathic pain : validation and literature search

La douleur neuropathique est définie comme une douleur causée par une lésion du système nerveux somato-sensoriel. Elle se caractérise par des douleurs exagérées, spontanées, ou déclenchées par des stimuli normalement non douloureux (allodynie) ou douloureux (hyperalgésie). Bien qu'elle concerne 7% de la population, ses mécanismes biologiques ne sont pas encore élucidés. L'étude des variations d'expressions géniques dans les tissus-clés des voies sensorielles (notamment le ganglion spinal et la corne dorsale de la moelle épinière) à différents moments après une lésion nerveuse périphérique permettrait de mettre en évidence de nouvelles cibles thérapeutiques. Elles se détectent de manière sensible par reverse transcription quantitative real-time polymerase chain reaction (RT- qPCR). Pour garantir des résultats fiables, des guidelines ont récemment recommandé la validation des gènes de référence utilisés pour la normalisation des données ("Minimum information for publication of quantitative real-time PCR experiments", Bustin et al 2009). Après recherche dans la littérature des gènes de référence fréquemment utilisés dans notre modèle de douleur neuropathique périphérique SNI (spared nerve injury) et dans le tissu nerveux en général, nous avons établi une liste de potentiels bons candidats: Actin beta (Actb), Glyceraldehyde-3-phosphate dehydrogenase (GAPDH), ribosomal proteins 18S (18S), L13a (RPL13a) et L29 (RPL29), hypoxanthine phosphoribosyltransferase 1 (HPRT1) et hydroxymethyl-bilane synthase (HMBS). Nous avons évalué la stabilité d'expression de ces gènes dans le ganglion spinal et dans la corne dorsale à différents moments après la lésion nerveuse (SNI) en calculant des coefficients de variation et utilisant l'algorithme geNorm qui compare les niveaux d'expression entre les différents candidats et détermine la paire de gènes restante la plus stable. Il a aussi été possible de classer les gènes selon leur stabilité et d'identifier le nombre de gènes nécessaires pour une normalisation la plus précise. Les gènes les plus cités comme référence dans le modèle SNI ont été GAPDH, HMBS, Actb, HPRT1 et 18S. Seuls HPRT1 and 18S ont été précédemment validés dans des arrays de RT-qPCR. Dans notre étude, tous les gènes testés dans le ganglion spinal et dans la corne dorsale satisfont au critère de stabilité exprimé par une M-value inférieure à 1. Par contre avec un coefficient de variation (CV) supérieur à 50% dans le ganglion spinal, 18S ne peut être retenu. La paire de gènes la plus stable dans le ganglion spinal est HPRT1 et Actb et dans la corne dorsale il s'agit de RPL29 et RPL13a. L'utilisation de 2 gènes de référence stables suffit pour une normalisation fiable. Nous avons donc classé et validé Actb, RPL29, RPL13a, HMBS, GAPDH, HPRT1 et 18S comme gènes de référence utilisables dans la corne dorsale pour le modèle SNI chez le rat. Dans le ganglion spinal 18S n'a pas rempli nos critères. Nous avons aussi déterminé que la combinaison de deux gènes de référence stables suffit pour une normalisation précise. Les variations d'expression génique de potentiels gènes d'intérêts dans des conditions expérimentales identiques (SNI, tissu et timepoints post SNI) vont pouvoir se mesurer sur la base d'une normalisation fiable. Non seulement il sera possible d'identifier des régulations potentiellement importantes dans la genèse de la douleur neuropathique mais aussi d'observer les différents phénotypes évoluant au cours du temps après lésion nerveuse.

Real-time antifungal susceptibility testing of Mucor spp., Fusarium spp. and Scedosporium spp. by isothermal microcalorimetry

Objective: Aspergillus species are the main pathogens causing invasive fungal infections but the prevalence of other mould species is rising. Resistance to antifungals among these new emerging pathogens presents a challenge for managing of infections. Conventional susceptibility testing of non-Aspergillus species is laborious and often difficult to interpret. We evaluated a new method for real-time susceptibility testing of moulds based on their of growth-related heat production.Methods: Laboratory and clinical strains of Mucor spp. (n = 4), Scedoporium spp. (n = 4) and Fusarium spp. (n = 5) were used. Conventional MIC was determined by microbroth dilution. Isothermal microcalorimetry was performed at 37 C using Sabouraud dextrose broth (SDB) inoculated with 104 spores/ml (determined by microscopical enumeration). SDB without antifungals was used for evaluation of growth characteristics. Detection time was defined as heat flow exceeding 10 lW. For susceptibility testing serial dilutions of amphotericin B, voriconazole, posaconazole and caspofungin were used. The minimal heat inhibitory concentration (MHIC) was defined as the lowest antifungal concentration, inhbiting 50% of the heat produced by the growth control at 48 h or at 24 h for Mucor spp. Susceptibility tests were performed in duplicate.Results: Tested mould genera had distinctive heat flow profiles with a median detection time (range) of 3.4 h (1.9-4.1 h) for Mucor spp, 11.0 h (7.1-13.7 h) for Fusarium spp and 29.3 h (27.4-33.0 h) for Scedosporium spp. Graph shows heat flow (in duplicate) of one representative strain from each genus (dashed line marks detection limit). Species belonging to the same genus showed similar heat production profiles. Table shows MHIC and MIC ranges for tested moulds and antifungals.Conclusions: Microcalorimetry allowed rapid detection of growth of slow-growing species, such as Fusarium spp. and Scedosporium spp. Moreover, microcalorimetry offers a new approach for antifungal susceptibility testing of moulds, correlating with conventional MIC values. Interpretation of calorimetric susceptibility data is easy and real-time data on the effect of different antifungals on the growth of the moulds is additionally obtained. This method may be used for investigation of different mechanisms of action of antifungals, new substances and drug-drug combinations.

Analytical validation of a lymphocytic choriomeningitis virus real-time RT-PCR assay.

Lymphocytic choriomeningitis virus (LCMV) is a rare cause of central nervous system disease in humans. Screening by real-time RT-PCR assay is of interest in the case of aseptic meningitis of unknown etiology. A specific LCMV real-time RT-PCR assay, based on the detection of genomic sequences of the viral nucleoprotein (NP), was developed to assess the presence of LCMV in cerebrospinal fluids (CSF) sent for viral screening to a Swiss university hospital laboratory. A 10-fold dilution series assay using a plasmid containing the cDNA of the viral NP of the LCMV isolate Armstrong (Arm) 53b demonstrated the high sensitivity of the assay with a lowest detection limit of ≤50 copies per reaction. High sensitivity was confirmed by dilution series assays in a pool of human CSF using four different LCMV isolates (Arm53b, WE54, Traub and E350) with observed detection limits of ≤10PFU/ml (Arm53b and WE54) and 1PFU/ml (Traub and E350). Analysis of 130 CSF showed no cases of acute infection. The absence of positive cases was confirmed by a published PCR assay detecting all Old World arenaviruses. This study validates a specific and sensitive real-time RT-PCR assay for the diagnosis of LCMV infections. Results showed that LCMV infections are extremely rare in hospitalized patients western in Switzerland.

Detection of live and antibiotic-killed bacteria by quantitative real-time PCR of specific fragments of ribosomal RNA

RÉSUMÉ Le but d'un traitement antimicrobien est d'éradiquer une infection bactérienne. Cependant, il est souvent difficile d'en évaluer rapidement l'efficacité en utilisant les techniques standard. L'estimation de la viabilité bactérienne par marqueurs moléculaires permettrait d'accélérer le processus. Ce travail étudie donc la possibilité d'utiliser le RNA ribosomal (rRNA) à cet effet. Des cultures de Streptococcus gordonii sensibles (parent Wt) et tolérants (mutant Tol 1) à l'action bactéricide de la pénicilline ont été exposées à différents antibiotiques. La survie bactérienne au cours du temps a été déterminée en comparant deux méthodes. La méthode de référence par compte viable a été comparée à une méthode moléculaire consistant à amplifier par PCR quantitative en temps réel une partie du génome bactérien. La cible choisie devait refléter la viabilité cellulaire et par conséquent être synthétisée de manière constitutive lors de la vie de la bactérie et être détruite rapidement lors de la mort cellulaire. Le choix s'est porté sur un fragment du gène 16S-rRNA. Ce travail a permis de valider ce choix en corrélant ce marqueur moléculaire à la viabilité bactérienne au cours d'un traitement antibiotique bactéricide. De manière attendue, les S. gordonii sensibles à la pénicilline ont perdu ≥ 4 log10 CFU/ml après 48 heures de traitement par pénicilline alors que le mutant tolérant Tol1 en a perdu ≥ 1 log10 CFU/ml. De manière intéressant, la quantité de marqueur a augmenté proportionnellement au compte viable durant la phase de croissance bactérienne. Après administration du traitement antibiotique, l'évolution du marqueur dépendait de la capacité de la bactérie à survivre à l'action de l'antibiotique. Stable lors du traitement des souches tolérantes, la quantité de marqueur détectée diminuait de manière proportionnelle au compte viable lors du traitement des souches sensibles. Cette corrélation s'est confirmée lors de l'utilisation d'autres antibiotiques bactéricides. En conclusion, l'amplification par PCR du RNA ribosomal 16S permet d'évaluer rapidement la viabilité bactérienne au cours d'un traitement antibiotique en évitant le recours à la mise en culture dont les résultats ne sont obtenus qu'après plus de 24 heures. Cette méthode offre donc au clinicien une évaluation rapide de l'efficacité du traitement, particulièrement dans les situations, comme le choc septique, où l'initiation sans délai d'un traitement efficace est une des conditions essentielles du succès thérapeutique. ABSTRACT Assessing bacterial viability by molecular markers might help accelerate the measurement of antibiotic-induced killing. This study investigated whether ribosomal RNA (rRNA) could be suitable for this purpose. Cultures of penicillin-susceptible and penicillin-tolerant (Tol1 mutant) Streptococcus gordonii were exposed to mechanistically different penicillin and levofloxacin. Bacterial survival was assessed by viable counts, and compared to quantitative real-time PCR amplification of either the 16S-rRNA genes (rDNA) or the 16S rRNA, following reverse transcription. Penicillin-susceptible S. gordonii lost ≥ 4 log10 CFU/ml of viability over 48 h of penicillin treatment. In comparison, the Toll mutant lost ≤ 1 log10 CFU/ml. Amplification of a 427-base fragment of 16S rDNA yielded amplicons that increased proportionally to viable counts during bacterial growth, but did not decrease during drug-induced killing. In contrast, the same 427-base fragment amplified from 16S rDNA paralleled both bacterial growth and drug-induced killing. It also differentiated between penicillin-induced killing of the parent and the Toll mutant (≥4 log10 CFU/ml and ≤1 lo10 CFU/ml, respectively), and detected killing by mechanistically unrelated levofloxacin. Since large fragments of polynucleotides might be degraded faster than smaller fragments the experiments were repeated by amplifying a 119-base region internal to the origina1 427-base fragment. The amount of 119-base amplicons increased proportionally to viability during growth, but remained stable during drug treatment. Thus, 16S rRNA was a marker of antibiotic-induced killing, but the size of the amplified fragment was critical to differentiate between live and dead bacteria.

Assessment of airborne microorganisms by real-time PCR: optimistic findings and research challenges

Most airborne microorganisms are natural components of our ecosystem. Soil, vegetation and animals, including humans, are sources for aerial release of these living or dead cells. In the past, assessment of airborne microorganisms was mainly restricted to occupational health concerns. Indeed, in several occupations, exposure to very high concentrations of non-infectious airborne bacteria and fungi, result in allergenic, toxic or irritant reactions. Recently, the threat of bioterrorism and pandemics have highlighted the urgent need to increase knowledge of bioaerosol ecology. More fundamentally, airborne bacterial and fungal communities begin to draw much more consideration from environmental microbiologists, who have neglected this area for a long time. This increased interest of scientists is to a great part due to the development and use of real-time PCR techniques to identify and quantify airborne microorganisms. Even if the advantages of the PCR technology are obvious, researchers are confronted with new problems. This review describes the methodological state of the art in bioaerosols field and emphasizes the future challenges and perspectives of the real-time PCR-based methods for airborne microorganism studies.

Development of a new chlamydiales-specific real-time PCR and its application to respiratory clinical samples.

Originally composed of the single family Chlamydiaceae, the Chlamydiales order has extended considerably over the last several decades. Chlamydia-related bacteria were added and classified into six different families and family-level lineages: the Criblamydiaceae, Parachlamydiaceae, Piscichlamydiaceae, Rhabdochlamydiaceae, Simkaniaceae, and Waddliaceae. While several members of the Chlamydiaceae family are known pathogens, recent studies showed diverse associations of Chlamydia-related bacteria with human and animal infections. Some of these latter bacteria might be of medical importance since, given their ability to replicate in free-living amoebae, they may also replicate efficiently in other phagocytic cells, including cells of the innate immune system. Thus, a new Chlamydiales-specific real-time PCR targeting the conserved 16S rRNA gene was developed. This new molecular tool can detect at least five DNA copies and show very high specificity without cross-amplification from other bacterial clade DNA. The new PCR was validated with 128 clinical samples positive or negative for Chlamydia trachomatis or C. pneumoniae. Of 65 positive samples, 61 (93.8%) were found to be positive with the new PCR. The four discordant samples, retested with the original test, were determined to be negative or below detection limits. Then, the new PCR was applied to 422 nasopharyngeal swabs taken from children with or without pneumonia; a total of 48 (11.4%) samples were determined to be positive, and 45 of these were successfully sequenced. The majority of the sequences corresponded to Chlamydia-related bacteria and especially to members of the Parachlamydiaceae family.

Detection of four Plasmodium species in blood from humans by 18S rRNA gene subunit-based and specific real-time PCR assays

Résumé : Un nombre croissant de cas de malaria chez les voyageurs et migrants a été rapporté. Bien que l'analyse microscopique des frottis sanguins reste traditionnellement l'outil diagnostic de référence, sa fiabilité dépend considérablement de l'expertise de l'examinateur, pouvant elle-même faire défaut sous nos latitudes. Une PCR multiplex en temps réel a donc été développée en vue d'une standardisation du diagnostic. Un ensemble d'amorces génériques ciblant une région hautement conservée du gène d'ARN ribosomial 18S du genre Plasmodium a tout d'abord été conçu, dont le polymorphisme du produit d'amplification semblait suffisant pour créer quatre sondes spécifiques à l'espèce P. falciparum, P. malariae, P. vivax et P. ovale. Ces sondes utilisées en PCR en temps réel se sont révélées capables de détecter une seule copie de plasmide de P. falciparum, P. malariae, P. vivax et P. ovale spécifiquement. La même sensibilité a été obtenue avec une sonde de screening pouvant détecter les quatre espèces. Quatre-vingt-dix-sept échantillons de sang ont ensuite été testés, dont on a comparé la microscopie et la PCR en temps réel pour 66 (60 patients) d'entre eux. Ces deux méthodes ont montré une concordance globale de 86% pour la détection de plasmodia. Les résultats discordants ont été réévalués grâce à des données cliniques, une deuxième expertise microscopique et moléculaire (laboratoire de Genève et de l'Institut Suisse Tropical de Bâle), ainsi qu'à l'aide du séquençage. Cette nouvelle analyse s'est prononcé en faveur de la méthode moléculaire pour tous les neuf résultats discordants. Sur les 31 résultats positifs par les deux méthodes, la même réévaluation a pu donner raison 8 fois sur 9 à la PCR en temps réel sur le plan de l'identification de l'espèce plasmodiale. Les 31 autres échantillons ont été analysés pour le suivi de sept patients sous traitement antimalarique. Il a été observé une baisse rapide du nombre de parasites mesurée par la PCR en temps réel chez six des sept patients, baisse correspondant à la parasitémie déterminée microscopiquement. Ceci suggère ainsi le rôle potentiel de la PCR en temps réel dans le suivi thérapeutique des patients traités par antipaludéens. Abstract : There have been reports of increasing numbers of cases of malaria among migrants and travelers. Although microscopic examination of blood smears remains the "gold standard" in diagnosis, this method suffers from insufficient sensitivity and requires considerable expertise. To improve diagnosis, a multiplex real-time PCR was developed. One set of generic primers targeting a highly conserved region of the 18S rRNA gene of the genus Plasmodium was designed; the primer set was polymorphic enough internally to design four species-specific probes for P. falciparum, P. vivax, P. malarie, and P. ovale. Real-time PCR with species-specific probes detected one plasmid copy of P. falciparum, P. vivax, P. malariae, and P. ovale specifically. The same sensitivity was achieved for all species with real-time PCR with the 18S screening probe. Ninety-seven blood samples were investigated. For 66 of them (60 patients), microscopy and real-time PCR results were compared and had a crude agreement of 86% for the detection of plasmodia. Discordant results were reevaluated with clinical, molecular, and sequencing data to resolve them. All nine discordances between 18S screening PCR and microscopy were resolved in favor of the molecular method, as were eight of nine discordances at the species level for the species-specific PCR among the 31 samples positive by both methods. The other 31 blood samples were tested to monitor the antimalaria treatment in seven patients. The number of parasites measured by real-time PCR fell rapidly for six out of seven patients in parallel to parasitemia determined microscopically. This suggests a role of quantitative PCR for the monitoring of patients receiving antimalaria therapy.

Reverse transcription quantitative real-time polymerase chain reaction reference genes in the spared nerve injury model of neuropathic pain: validation and literature search.

BACKGROUND: The reverse transcription quantitative real-time polymerase chain reaction (RT-qPCR) is a widely used, highly sensitive laboratory technique to rapidly and easily detect, identify and quantify gene expression. Reliable RT-qPCR data necessitates accurate normalization with validated control genes (reference genes) whose expression is constant in all studied conditions. This stability has to be demonstrated.We performed a literature search for studies using quantitative or semi-quantitative PCR in the rat spared nerve injury (SNI) model of neuropathic pain to verify whether any reference genes had previously been validated. We then analyzed the stability over time of 7 commonly used reference genes in the nervous system - specifically in the spinal cord dorsal horn and the dorsal root ganglion (DRG). These were: Actin beta (Actb), Glyceraldehyde-3-phosphate dehydrogenase (GAPDH), ribosomal proteins 18S (18S), L13a (RPL13a) and L29 (RPL29), hypoxanthine phosphoribosyltransferase 1 (HPRT1) and hydroxymethylbilane synthase (HMBS). We compared the candidate genes and established a stability ranking using the geNorm algorithm. Finally, we assessed the number of reference genes necessary for accurate normalization in this neuropathic pain model. RESULTS: We found GAPDH, HMBS, Actb, HPRT1 and 18S cited as reference genes in literature on studies using the SNI model. Only HPRT1 and 18S had been once previously demonstrated as stable in RT-qPCR arrays. All the genes tested in this study, using the geNorm algorithm, presented gene stability values (M-value) acceptable enough for them to qualify as potential reference genes in both DRG and spinal cord. Using the coefficient of variation, 18S failed the 50% cut-off with a value of 61% in the DRG. The two most stable genes in the dorsal horn were RPL29 and RPL13a; in the DRG they were HPRT1 and Actb. Using a 0.15 cut-off for pairwise variations we found that any pair of stable reference gene was sufficient for the normalization process. CONCLUSIONS: In the rat SNI model, we validated and ranked Actb, RPL29, RPL13a, HMBS, GAPDH, HPRT1 and 18S as good reference genes in the spinal cord. In the DRG, 18S did not fulfill stability criteria. The combination of any two stable reference genes was sufficient to provide an accurate normalization.

Application of real-time PCR for total airborne bacterial assessment : comparison with epifluorescence microscopy and culture-dependent methods

Traditional culture-dependent methods to quantify and identify airborne microorganisms are limited by factors such as short-duration sampling times and inability to count nonculturableor non-viable bacteria. Consequently, the quantitative assessment of bioaerosols is often underestimated. Use of the real-time quantitative polymerase chain reaction (Q-PCR) to quantify bacteria in environmental samples presents an alternative method, which should overcome this problem. The aim of this study was to evaluate the performance of a real-time Q-PCR assay as a simple and reliable way to quantify the airborne bacterial load within poultry houses and sewage treatment plants, in comparison with epifluorescencemicroscopy and culture-dependent methods. The estimates of bacterial load that we obtained from real-time PCR and epifluorescence methods, are comparable, however, our analysis of sewage treatment plants indicate these methods give values 270-290 fold greater than those obtained by the ''impaction on nutrient agar'' method. The culture-dependent method of air impaction on nutrient agar was also inadequate in poultry houses, as was the impinger-culture method, which gave a bacterial load estimate 32-fold lower than obtained by Q-PCR. Real-time quantitative PCR thus proves to be a reliable, discerning, and simple method that could be used to estimate airborne bacterial load in a broad variety of other environments expected to carry high numbers of airborne bacteria. [Authors]