Molecular analysis of a novel gene cluster encoding an insect toxin in plant-associated strains of Pseudomonas fluorescens

Pseudomonas fluorescens CHA0 and the related strain Pf-5 are well-characterized representatives of rhizosphere bacteria that have the capacity to protect crop plants from fungal root diseases, mainly by releasing a variety of exoproducts that are toxic to plant pathogenic fungi. Here, we report that the two plant-beneficial pseudomonads also exhibit potent insecticidal activity. Anti-insect activity is linked to a novel genomic locus encoding a large protein toxin termed Fit (for P. fluorescensinsecticidal toxin) that is related to the insect toxin Mcf (Makes caterpillars floppy) of the entomopathogen Photorhabdus luminescens, a mutualist of insect-invading nematodes. When injected into the haemocoel, even low doses of P. fluorescens CHA0 or Pf-5 killed larvae of the tobacco hornworm Manduca sexta and the greater wax moth Galleria mellonella. In contrast, mutants of CHA0 or Pf-5 with deletions in the Fit toxin gene were significantly less virulent to the larvae. When expressed from an inducible promoter in a non-toxic Escherichia coli host, the Fit toxin gene was sufficient to render the bacterium toxic to both insect hosts. Our findings establish the Fit gene products of P. fluorescens CHA0 and Pf-5 as potent insect toxins that define previously unappreciated anti-insect properties of these plant-colonizing bacteria

Cluster-based active learning for compact image classification

In this paper, we consider active sampling to label pixels grouped with hierarchical clustering. The objective of the method is to match the data relationships discovered by the clustering algorithm with the user's desired class semantics. The first is represented as a complete tree to be pruned and the second is iteratively provided by the user. The active learning algorithm proposed searches the pruning of the tree that best matches the labels of the sampled points. By choosing the part of the tree to sample from according to current pruning's uncertainty, sampling is focused on most uncertain clusters. This way, large clusters for which the class membership is already fixed are no longer queried and sampling is focused on division of clusters showing mixed labels. The model is tested on a VHR image in a multiclass classification setting. The method clearly outperforms random sampling in a transductive setting, but cannot generalize to unseen data, since it aims at optimizing the classification of a given cluster structure.

Simulation of stromatolite growth using diffusion-limited aggregation and a discrete model of biogeochemical exchanges in microbial mat

Resume : Mieux comprendre les stromatolithes et les tapis microbiens est un sujet important en biogéosciences puisque cela aide à l'étude des premières formes de vie sur Terre, a mieux cerner l'écologie des communautés microbiennes et la contribution des microorganismes a la biominéralisation, et même à poser certains fondements dans les recherches en exobiologie. D'autre part, la modélisation est un outil puissant utilisé dans les sciences naturelles pour appréhender différents phénomènes de façon théorique. Les modèles sont généralement construits sur un système d'équations différentielles et les résultats sont obtenus en résolvant ce système. Les logiciels disponibles pour implémenter les modèles incluent les logiciels mathématiques et les logiciels généraux de simulation. L'objectif principal de cette thèse est de développer des modèles et des logiciels pour aider a comprendre, via la simulation, le fonctionnement des stromatolithes et des tapis microbiens. Ces logiciels ont été développés en C++ en ne partant d'aucun pré-requis de façon a privilégier performance et flexibilité maximales. Cette démarche permet de construire des modèles bien plus spécifiques et plus appropriés aux phénomènes a modéliser. Premièrement, nous avons étudié la croissance et la morphologie des stromatolithes. Nous avons construit un modèle tridimensionnel fondé sur l'agrégation par diffusion limitée. Le modèle a été implémenté en deux applications C++: un moteur de simulation capable d'exécuter un batch de simulations et de produire des fichiers de résultats, et un outil de visualisation qui permet d'analyser les résultats en trois dimensions. Après avoir vérifié que ce modèle peut en effet reproduire la croissance et la morphologie de plusieurs types de stromatolithes, nous avons introduit un processus de sédimentation comme facteur externe. Ceci nous a mené a des résultats intéressants, et permis de soutenir l'hypothèse que la morphologie des stromatolithes pourrait être le résultat de facteurs externes autant que de facteurs internes. Ceci est important car la classification des stromatolithes est généralement fondée sur leur morphologie, imposant que la forme d'un stromatolithe est dépendante de facteurs internes uniquement (c'est-à-dire les tapis microbiens). Les résultats avancés dans ce mémoire contredisent donc ces assertions communément admises. Ensuite, nous avons décidé de mener des recherches plus en profondeur sur les aspects fonctionnels des tapis microbiens. Nous avons construit un modèle bidimensionnel de réaction-diffusion fondé sur la simulation discrète. Ce modèle a été implémenté dans une application C++ qui permet de paramétrer et exécuter des simulations. Nous avons ensuite pu comparer les résultats de simulation avec des données du monde réel et vérifier que le modèle peut en effet imiter le comportement de certains tapis microbiens. Ainsi, nous avons pu émettre et vérifier des hypothèses sur le fonctionnement de certains tapis microbiens pour nous aider à mieux en comprendre certains aspects, comme la dynamique des éléments, en particulier le soufre et l'oxygène. En conclusion, ce travail a abouti à l'écriture de logiciels dédiés à la simulation de tapis microbiens d'un point de vue tant morphologique que fonctionnel, suivant deux approches différentes, l'une holistique, l'autre plus analytique. Ces logiciels sont gratuits et diffusés sous licence GPL (General Public License). Abstract : Better understanding of stromatolites and microbial mats is an important topic in biogeosciences as it helps studying the early forms of life on Earth, provides clues re- garding the ecology of microbial ecosystems and their contribution to biomineralization, and gives basis to a new science, exobiology. On the other hand, modelling is a powerful tool used in natural sciences for the theoretical approach of various phenomena. Models are usually built on a system of differential equations and results are obtained by solving that system. Available software to implement models includes mathematical solvers and general simulation software. The main objective of this thesis is to develop models and software able to help to understand the functioning of stromatolites and microbial mats. Software was developed in C++ from scratch for maximum performance and flexibility. This allows to build models much more specific to a phenomenon rather than general software. First, we studied stromatolite growth and morphology. We built a three-dimensional model based on diffusion-limited aggregation. The model was implemented in two C++ applications: a simulator engine, which can run a batch of simulations and produce result files, and a Visualization tool, which allows results to be analysed in three dimensions. After verifying that our model can indeed reproduce the growth and morphology of several types of stromatolites, we introduced a sedimentation process as an external factor. This lead to interesting results, and allowed to emit the hypothesis that stromatolite morphology may be the result of external factors as much as internal factors. This is important as stromatolite classification is usually based on their morphology, imposing that a stromatolite shape is dependant on internal factors only (i.e. the microbial mat). This statement is contradicted by our findings, Second, we decided to investigate deeper the functioning of microbial mats, We built a two-dimensional reaction-diffusion model based on discrete simulation, The model was implemented in a C++ application that allows setting and running simulations. We could then compare simulation results with real world data and verify that our model can indeed mimic the behaviour of some microbial mats. Thus, we have proposed and verified hypotheses regarding microbial mats functioning in order to help to better understand them, e.g. the cycle of some elements such as oxygen or sulfur. ln conclusion, this PhD provides a simulation software, dealing with two different approaches. This software is free and available under a GPL licence.

Characterization of Fas (Apo-1, CD95)-Fas ligand interaction.

The death-inducing receptor Fas is activated when cross-linked by the type II membrane protein Fas ligand (FasL). When human soluble FasL (sFasL, containing the extracellular portion) was expressed in human embryo kidney 293 cells, the three N-linked glycans of each FasL monomer were found to be essential for efficient secretion. Based on the structure of the closely related lymphotoxin alpha-tumor necrosis factor receptor I complex, a molecular model of the FasL homotrimer bound to three Fas molecules was generated using knowledge-based protein modeling methods. Point mutations of amino acid residues predicted to affect the receptor-ligand interaction were introduced at three sites. The F275L mutant, mimicking the loss of function murine gld mutation, exhibited a high propensity for aggregation and was unable to bind to Fas. Mutants P206R, P206D, and P206F displayed reduced cytotoxicity toward Fas-positive cells with a concomitant decrease in the binding affinity for the recombinant Fas-immunoglobulin Fc fusion proteins. Although the cytotoxic activity of mutant Y218D was unaltered, mutant Y218R was inactive, correlating with the prediction that Tyr-218 of FasL interacts with a cluster of three basic amino acid side chains of Fas. Interestingly, mutant Y218F could induce apoptosis in murine, but not human cells.

The Hydrophobic interaction: modeling hydrophobic interactions and aggregation of non-polar particles in aqueous solutions

Malgré son importance dans notre vie de tous les jours, certaines propriétés de l?eau restent inexpliquées. L'étude des interactions entre l'eau et les particules organiques occupe des groupes de recherche dans le monde entier et est loin d'être finie. Dans mon travail j'ai essayé de comprendre, au niveau moléculaire, ces interactions importantes pour la vie. J'ai utilisé pour cela un modèle simple de l'eau pour décrire des solutions aqueuses de différentes particules. Récemment, l?eau liquide a été décrite comme une structure formée d?un réseau aléatoire de liaisons hydrogènes. En introduisant une particule hydrophobe dans cette structure à basse température, certaines liaisons hydrogènes sont détruites ce qui est énergétiquement défavorable. Les molécules d?eau s?arrangent alors autour de cette particule en formant une cage qui permet de récupérer des liaisons hydrogènes (entre molécules d?eau) encore plus fortes : les particules sont alors solubles dans l?eau. A des températures plus élevées, l?agitation thermique des molécules devient importante et brise les liaisons hydrogènes. Maintenant, la dissolution des particules devient énergétiquement défavorable, et les particules se séparent de l?eau en formant des agrégats qui minimisent leur surface exposée à l?eau. Pourtant, à très haute température, les effets entropiques deviennent tellement forts que les particules se mélangent de nouveau avec les molécules d?eau. En utilisant un modèle basé sur ces changements de structure formée par des liaisons hydrogènes j?ai pu reproduire les phénomènes principaux liés à l?hydrophobicité. J?ai trouvé une région de coexistence de deux phases entre les températures critiques inférieure et supérieure de solubilité, dans laquelle les particules hydrophobes s?agrègent. En dehors de cette région, les particules sont dissoutes dans l?eau. J?ai démontré que l?interaction hydrophobe est décrite par un modèle qui prend uniquement en compte les changements de structure de l?eau liquide en présence d?une particule hydrophobe, plutôt que les interactions directes entre les particules. Encouragée par ces résultats prometteurs, j?ai étudié des solutions aqueuses de particules hydrophobes en présence de co-solvants cosmotropiques et chaotropiques. Ce sont des substances qui stabilisent ou déstabilisent les agrégats de particules hydrophobes. La présence de ces substances peut être incluse dans le modèle en décrivant leur effet sur la structure de l?eau. J?ai pu reproduire la concentration élevée de co-solvants chaotropiques dans le voisinage immédiat de la particule, et l?effet inverse dans le cas de co-solvants cosmotropiques. Ce changement de concentration du co-solvant à proximité de particules hydrophobes est la cause principale de son effet sur la solubilité des particules hydrophobes. J?ai démontré que le modèle adapté prédit correctement les effets implicites des co-solvants sur les interactions de plusieurs corps entre les particules hydrophobes. En outre, j?ai étendu le modèle à la description de particules amphiphiles comme des lipides. J?ai trouvé la formation de différents types de micelles en fonction de la distribution des regions hydrophobes à la surface des particules. L?hydrophobicité reste également un sujet controversé en science des protéines. J?ai défini une nouvelle échelle d?hydrophobicité pour les acides aminés qui forment des protéines, basée sur leurs surfaces exposées à l?eau dans des protéines natives. Cette échelle permet une comparaison meilleure entre les expériences et les résultats théoriques. Ainsi, le modèle développé dans mon travail contribue à mieux comprendre les solutions aqueuses de particules hydrophobes. Je pense que les résultats analytiques et numériques obtenus éclaircissent en partie les processus physiques qui sont à la base de l?interaction hydrophobe.<br/><br/>Despite the importance of water in our daily lives, some of its properties remain unexplained. Indeed, the interactions of water with organic particles are investigated in research groups all over the world, but controversy still surrounds many aspects of their description. In my work I have tried to understand these interactions on a molecular level using both analytical and numerical methods. Recent investigations describe liquid water as random network formed by hydrogen bonds. The insertion of a hydrophobic particle at low temperature breaks some of the hydrogen bonds, which is energetically unfavorable. The water molecules, however, rearrange in a cage-like structure around the solute particle. Even stronger hydrogen bonds are formed between water molecules, and thus the solute particles are soluble. At higher temperatures, this strict ordering is disrupted by thermal movements, and the solution of particles becomes unfavorable. They minimize their exposed surface to water by aggregating. At even higher temperatures, entropy effects become dominant and water and solute particles mix again. Using a model based on these changes in water structure I have reproduced the essential phenomena connected to hydrophobicity. These include an upper and a lower critical solution temperature, which define temperature and density ranges in which aggregation occurs. Outside of this region the solute particles are soluble in water. Because I was able to demonstrate that the simple mixture model contains implicitly many-body interactions between the solute molecules, I feel that the study contributes to an important advance in the qualitative understanding of the hydrophobic effect. I have also studied the aggregation of hydrophobic particles in aqueous solutions in the presence of cosolvents. Here I have demonstrated that the important features of the destabilizing effect of chaotropic cosolvents on hydrophobic aggregates may be described within the same two-state model, with adaptations to focus on the ability of such substances to alter the structure of water. The relevant phenomena include a significant enhancement of the solubility of non-polar solute particles and preferential binding of chaotropic substances to solute molecules. In a similar fashion, I have analyzed the stabilizing effect of kosmotropic cosolvents in these solutions. Including the ability of kosmotropic substances to enhance the structure of liquid water, leads to reduced solubility, larger aggregation regime and the preferential exclusion of the cosolvent from the hydration shell of hydrophobic solute particles. I have further adapted the MLG model to include the solvation of amphiphilic solute particles in water, by allowing different distributions of hydrophobic regions at the molecular surface, I have found aggregation of the amphiphiles, and formation of various types of micelle as a function of the hydrophobicity pattern. I have demonstrated that certain features of micelle formation may be reproduced by the adapted model to describe alterations of water structure near different surface regions of the dissolved amphiphiles. Hydrophobicity remains a controversial quantity also in protein science. Based on the surface exposure of the 20 amino-acids in native proteins I have defined the a new hydrophobicity scale, which may lead to an improvement in the comparison of experimental data with the results from theoretical HP models. Overall, I have shown that the primary features of the hydrophobic interaction in aqueous solutions may be captured within a model which focuses on alterations in water structure around non-polar solute particles. The results obtained within this model may illuminate the processes underlying the hydrophobic interaction.<br/><br/>La vie sur notre planète a commencé dans l'eau et ne pourrait pas exister en son absence : les cellules des animaux et des plantes contiennent jusqu'à 95% d'eau. Malgré son importance dans notre vie de tous les jours, certaines propriétés de l?eau restent inexpliquées. En particulier, l'étude des interactions entre l'eau et les particules organiques occupe des groupes de recherche dans le monde entier et est loin d'être finie. Dans mon travail j'ai essayé de comprendre, au niveau moléculaire, ces interactions importantes pour la vie. J'ai utilisé pour cela un modèle simple de l'eau pour décrire des solutions aqueuses de différentes particules. Bien que l?eau soit généralement un bon solvant, un grand groupe de molécules, appelées molécules hydrophobes (du grecque "hydro"="eau" et "phobia"="peur"), n'est pas facilement soluble dans l'eau. Ces particules hydrophobes essayent d'éviter le contact avec l'eau, et forment donc un agrégat pour minimiser leur surface exposée à l'eau. Cette force entre les particules est appelée interaction hydrophobe, et les mécanismes physiques qui conduisent à ces interactions ne sont pas bien compris à l'heure actuelle. Dans mon étude j'ai décrit l'effet des particules hydrophobes sur l'eau liquide. L'objectif était d'éclaircir le mécanisme de l'interaction hydrophobe qui est fondamentale pour la formation des membranes et le fonctionnement des processus biologiques dans notre corps. Récemment, l'eau liquide a été décrite comme un réseau aléatoire formé par des liaisons hydrogènes. En introduisant une particule hydrophobe dans cette structure, certaines liaisons hydrogènes sont détruites tandis que les molécules d'eau s'arrangent autour de cette particule en formant une cage qui permet de récupérer des liaisons hydrogènes (entre molécules d?eau) encore plus fortes : les particules sont alors solubles dans l'eau. A des températures plus élevées, l?agitation thermique des molécules devient importante et brise la structure de cage autour des particules hydrophobes. Maintenant, la dissolution des particules devient défavorable, et les particules se séparent de l'eau en formant deux phases. A très haute température, les mouvements thermiques dans le système deviennent tellement forts que les particules se mélangent de nouveau avec les molécules d'eau. A l'aide d'un modèle qui décrit le système en termes de restructuration dans l'eau liquide, j'ai réussi à reproduire les phénomènes physiques liés à l?hydrophobicité. J'ai démontré que les interactions hydrophobes entre plusieurs particules peuvent être exprimées dans un modèle qui prend uniquement en compte les liaisons hydrogènes entre les molécules d'eau. Encouragée par ces résultats prometteurs, j'ai inclus dans mon modèle des substances fréquemment utilisées pour stabiliser ou déstabiliser des solutions aqueuses de particules hydrophobes. J'ai réussi à reproduire les effets dûs à la présence de ces substances. De plus, j'ai pu décrire la formation de micelles par des particules amphiphiles comme des lipides dont la surface est partiellement hydrophobe et partiellement hydrophile ("hydro-phile"="aime l'eau"), ainsi que le repliement des protéines dû à l'hydrophobicité, qui garantit le fonctionnement correct des processus biologiques de notre corps. Dans mes études futures je poursuivrai l'étude des solutions aqueuses de différentes particules en utilisant les techniques acquises pendant mon travail de thèse, et en essayant de comprendre les propriétés physiques du liquide le plus important pour notre vie : l'eau.

Acute schistosomiasis: a risk underestimated by travelers and a diagnosis frequently missed by general practitioners-a cluster analysis of 42 travelers.

BACKGROUND: In 2011, a patient was admitted to our hospital with acute schistosomiasis after having returned from Madagascar and having bathed at the Lily waterfalls. On the basis of this patient's indication, infection was suspected in 41 other subjects. This study investigated (1) the knowledge of the travelers about the risks of schistosomiasis and their related behavior to evaluate the appropriateness of prevention messages and (2) the diagnostic workup of symptomatic travelers by general practitioners to evaluate medical care of travelers with a history of freshwater exposure in tropical areas. METHODS: A questionnaire was sent to the 42 travelers with potential exposure to schistosomiasis. It focused on pre-travel knowledge of the disease, bathing conditions, clinical presentation, first suspected diagnosis, and treatment. RESULTS: Of the 42 questionnaires, 40 (95%) were returned, among which 37 travelers (92%) reported an exposure to freshwater, and 18 (45%) were aware of the risk of schistosomiasis. Among these latter subjects, 16 (89%) still reported an exposure to freshwater. Serology was positive in 28 (78%) of 36 exposed subjects at least 3 months after exposure. Of the 28 infected travelers, 23 (82%) exhibited symptoms and 16 (70%) consulted their general practitioner before the information about the outbreak had spread, but none of these patients had a serology for schistosomiasis done during the first consultation. CONCLUSIONS: The usual prevention message of avoiding freshwater contact when traveling in tropical regions had no impact on the behavior of these travelers, who still went swimming at the Lily waterfalls. This prevention message should, therefore, be either modified or abandoned. The clinical presentation of acute schistosomiasis is often misleading. General practitioners should at least request an eosinophil count, when confronted with a returning traveler with fever. If eosinophilia is detected, it should prompt the search for a parasitic disease.

Soft tissue artifact distribution on lower limbs during treadmill gait: Influence of skin markers' location on cluster design.

Segment poses and joint kinematics estimated from skin markers are highly affected by soft tissue artifact (STA) and its rigid motion component (STARM). While four marker-clusters could decrease the STA non-rigid motion during gait activity, other data, such as marker location or STARM patterns, would be crucial to compensate for STA in clinical gait analysis. The present study proposed 1) to devise a comprehensive average map illustrating the spatial distribution of STA for the lower limb during treadmill gait and 2) to analyze STARM from four marker-clusters assigned to areas extracted from spatial distribution. All experiments were realized using a stereophotogrammetric system to track the skin markers and a bi-plane fluoroscopic system to track the knee prosthesis. Computation of the spatial distribution of STA was realized on 19 subjects using 80 markers apposed on the lower limb. Three different areas were extracted from the distribution map of the thigh. The marker displacement reached a maximum of 24.9mm and 15.3mm in the proximal areas of thigh and shank, respectively. STARM was larger on thigh than the shank with RMS error in cluster orientations between 1.2° and 8.1°. The translation RMS errors were also large (3.0mm to 16.2mm). No marker-cluster correctly compensated for STARM. However, the coefficient of multiple correlations exhibited excellent scores between skin and bone kinematics, as well as for STARM between subjects. These correlations highlight dependencies between STARM and the kinematic components. This study provides new insights for modeling STARM for gait activity.

The specificity of the familial aggregation of early-onset bipolar disorder: A controlled 10-year follow-up study of offspring of parents with mood disorders.

BACKGROUND: Two major sources of heterogeneity of mood disorders that have been demonstrated in clinical, family and genetic studies are the mood disorder subtype (i.e. bipolar (BPD) and major depressive disorder (MDD)) and age of onset of mood episodes. Using a prospective high-risk study design, our aims were to test the specificity of the parent-child transmission of BPD and MDD and to establish the risk of psychopathology in offspring in function of the age of onset of the parental disorder. METHODS: Clinical information was collected on 208 probands (n=81 with BPD, n=64 with MDD, n=63 medical controls) as well as their 202 spouses and 372 children aged 6-17 years at study entry. Parents and children were directly interviewed every 3 years (mean duration of follow-up=10.6 years). Parental age of onset was dichotomized at age 21. RESULTS: Offspring of parents with early onset BPD entailed a higher risk of BPD HR=7.9(1.8-34.6) and substance use disorders HR=5.0(1.1-21.9) than those with later onset and controls. Depressive disorders were not significantly increased in offspring regardless of parental mood disorder subtype or age of onset. LIMITATIONS: Limited sample size, age of onset in probands was obtained retrospectively, age of onset in co-parents was not adequately documented, and a quarter of the children had no direct interview. CONCLUSIONS: Our results provide support for the independence of familial aggregation of BPD from MDD and the heterogeneity of BPD based on patterns of onset. Future studies should further investigate correlates of early versus later onset BPD.

Responding to Young People's Health Risks in Primary Care: A Cluster Randomised Trial of Training Clinicians in Screening and Motivational Interviewing.

OBJECTIVE: To evaluate the effectiveness of a complex intervention implementing best practice guidelines recommending clinicians screen and counsel young people across multiple psychosocial risk factors, on clinicians' detection of health risks and patients' risk taking behaviour, compared to a didactic seminar on young people's health. DESIGN: Pragmatic cluster randomised trial where volunteer general practices were stratified by postcode advantage or disadvantage score and billing type (private, free national health, community health centre), then randomised into either intervention or comparison arms using a computer generated random sequence. Three months post-intervention, patients were recruited from all practices post-consultation for a Computer Assisted Telephone Interview and followed up three and 12 months later. Researchers recruiting, consenting and interviewing patients and patients themselves were masked to allocation status; clinicians were not. SETTING: General practices in metropolitan and rural Victoria, Australia. PARTICIPANTS: General practices with at least one interested clinician (general practitioner or nurse) and their 14-24 year old patients. INTERVENTION: This complex intervention was designed using evidence based practice in learning and change in clinician behaviour and general practice systems, and included best practice approaches to motivating change in adolescent risk taking behaviours. The intervention involved training clinicians (nine hours) in health risk screening, use of a screening tool and motivational interviewing; training all practice staff (receptionists and clinicians) in engaging youth; provision of feedback to clinicians of patients' risk data; and two practice visits to support new screening and referral resources. Comparison clinicians received one didactic educational seminar (three hours) on engaging youth and health risk screening. OUTCOME MEASURES: Primary outcomes were patient report of (1) clinician detection of at least one of six health risk behaviours (tobacco, alcohol and illicit drug use, risks for sexually transmitted infection, STI, unplanned pregnancy, and road risks); and (2) change in one or more of the six health risk behaviours, at three months or at 12 months. Secondary outcomes were likelihood of future visits, trust in the clinician after exit interview, clinician detection of emotional distress and fear and abuse in relationships, and emotional distress at three and 12 months. Patient acceptability of the screening tool was also described for the intervention arm. Analyses were adjusted for practice location and billing type, patients' sex, age, and recruitment method, and past health risks, where appropriate. An intention to treat analysis approach was used, which included multilevel multiple imputation for missing outcome data. RESULTS: 42 practices were randomly allocated to intervention or comparison arms. Two intervention practices withdrew post allocation, prior to training, leaving 19 intervention (53 clinicians, 377 patients) and 21 comparison (79 clinicians, 524 patients) practices. 69% of patients in both intervention (260) and comparison (360) arms completed the 12 month follow-up. Intervention clinicians discussed more health risks per patient (59.7%) than comparison clinicians (52.7%) and thus were more likely to detect a higher proportion of young people with at least one of the six health risk behaviours (38.4% vs 26.7%, risk difference [RD] 11.6%, Confidence Interval [CI] 2.93% to 20.3%; adjusted odds ratio [OR] 1.7, CI 1.1 to 2.5). Patients reported less illicit drug use (RD -6.0, CI -11 to -1.2; OR 0·52, CI 0·28 to 0·96), and less risk for STI (RD -5.4, CI -11 to 0.2; OR 0·66, CI 0·46 to 0·96) at three months in the intervention relative to the comparison arm, and for unplanned pregnancy at 12 months (RD -4.4; CI -8.7 to -0.1; OR 0·40, CI 0·20 to 0·80). No differences were detected between arms on other health risks. There were no differences on secondary outcomes, apart from a greater detection of abuse (OR 13.8, CI 1.71 to 111). There were no reports of harmful events and intervention arm youth had high acceptance of the screening tool. CONCLUSIONS: A complex intervention, compared to a simple educational seminar for practices, improved detection of health risk behaviours in young people. Impact on health outcomes was inconclusive. Technology enabling more efficient, systematic health-risk screening may allow providers to target counselling toward higher risk individuals. Further trials require more power to confirm health benefits. TRIAL REGISTRATION: ISRCTN.com ISRCTN16059206.