Reverse-translational biomarker validation of Abnormal Repetitive Behaviors in mice: an illustration of the 4P's modeling approach

The NIMH's new strategic plan, with its emphasis on the "4P's" (Prediction, Pre-emption, Personalization, and Populations) and biomarker-based medicine requires a radical shift in animal modeling methodology. In particular 4P's models will be non-determinant (i.e. disease severity will depend on secondary environmental and genetic factors); and validated by reverse-translation of animal homologues to human biomarkers. A powerful consequence of the biomarker approach is that different closely related disorders have a unique fingerprint of biomarkers. Animals can be validated as a highly specific model of a single disorder by matching this 'fingerprint'; or as a model of a symptom seen in multiple disorders by matching common biomarkers. Here we illustrate this approach with two Abnormal Repetitive Behaviors (ARBs) in mice: stereotypies and barbering (hair pulling). We developed animal versions of the neuropsychological biomarkers that distinguish human ARBs, and tested the fingerprint of the different mouse ARBs. As predicted, the two mouse ARBs were associated with different biomarkers. Both barbering and stereotypy could be discounted as models of OCD (even though they are widely used as such), due to the absence of limbic biomarkers which are characteristic of OCD and hence are necessary for a valid model. Conversely barbering matched the fingerprint of trichotillomania (i.e. selective deficits in set-shifting), suggesting it may be a highly specific model of this disorder. In contrast stereotypies were correlated only with a biomarker (deficits in response shifting) correlated with stereotypies in multiple disorders, suggesting that animal stereotypies model stereotypies in multiple disorders.

Modeling nitrous oxide emissions in grass and grass-legume pastures in the western Brazilian Amazon.

Mineral nitrogen (N) dynamics in soil and the exchange of N gaseous in the interface soil-atmosphere are intimately associated with animal manure in pastures. According to soil inorganic-N pools and the site studied, forest or pasture, and pastures age the soil inorganic-N pools of ammonium and nitrate can be similar in the forest or ammonium dominated in the pasture. Also annual average net nitrification rates at soil surface in forest can be higher than in pasture suggesting a higher potential for nitrate-N losses either through leaching or gaseous emissions from intact forests compared with established pastures (NEILL et al., 1995).

Mécanismes de plasticité synaptique dans l’amygdale lors de la réactivation de la mémoire de peur auditive chez le rat : interaction dynamique des récepteurs NMDA et AMPA

La plasticité synaptique est une propriété indispensable à l’acquisition de la mémoire chez toutes les espèces étudiées, des invertébrés aux primates. La formation d’une mémoire débute par une phase de plasticité qui inclut une restructuration synaptique ; ensuite elle se poursuit par la consolidation de ces modifications, contribuant à la mémoire à long terme. Certaines mémoires redeviennent malléables lorsqu’elles sont rappelées. La trace mnésique entre alors dans une nouvelle de phase de plasticité, au cours de laquelle certaines composantes de la mémoire peuvent être mises à jour, puis reconsolidées. L’objectif de la présente thèse est d’étudier les mécanismes cellulaires et moléculaires qui sont activés lors du rappel d’une mémoire. Nous avons utilisé un modèle de conditionnement Pavlovien, combiné à l’administration d’agents pharmacologiques et à l’analyse quantitative de marqueurs de plasticité synaptique, afin d’étudier la dynamique de la mémoire de peur auditive chez des rats Sprague Dawley. La circuiterie neuronale et les mécanismes associatifs impliqués dans la neurobiologie de cette mémoire sont bien caractérisés, en particulier le rôle des récepteurs glutamatergiques de type NMDA et AMPA dans la plasticité synaptique et la consolidation. Nos résultats démontrent que le retour de la trace mnésique à un état de labilité nécessite l’activation des récepteurs NMDA dans l’amygdale baso-latérale à l’instant même du rappel, alors que les récepteurs AMPA sont requis pour l’expression comportementale de la réponse de peur conditionnée. D’autre part, les résultats identifient le rappel comme une phase bien plus dynamique que présumée, et suggèrent que l’expression de la peur conditionnée mette en jeu la régulation du trafic des récepteurs AMPA par les récepteurs NMDA. Le présent travail espère contribuer à la compréhension de la neurobiologie fondamentale de la mémoire. De plus, il propose une intégration des résultats aux modèles animaux d’étude des troubles psychologiques conséquents aux mémoires traumatiques chez l’humain, tels que les phobies et les syndromes de stress post-traumatiques.

Études des rôles physiopathologiques de PTEN dans le tractus reproducteur femelle

La tumeur des cellules de la granulosa (GCT) représente 5% des cas de cancers ovariens chez la femme. Bien que considérées comme peu malignes, la mort survient dans 80% des cas suite à une recrudescence de la maladie. En dépit de ces statistiques sinistres, peu d’études ont été portées sur ce type de cancer. Le premier objectif de cette étude consistait à élucider les mécanismes moléculaires causant les GCT en démontrant l’implication de la voie de signalisation PI3K/AKT dans leur étiologie. Pour ce faire, nous avons employé la technologie Cre-Lox afin de cibler le gène Pten (antagoniste de cette voie) spécifiquement dans les cellules de la granulosa chez la souris. Ces souris (Ptenflox/flox;Amhr2cre/+) ont occasionnellement développé des GCT, soutenant notre hypothèse de l’importance de la voie PI3K/AKT dans leur étiologie. La voie WNT/CTNNB1 est une autre voie de signalisation qui a récemment été impliquée dans le développement des GCT. Dans le cadre de ce projet, nous avons également testé l’existence possible d’une synergie fonctionnelle entre les voies WNT/CTNNB1 et PI3K/AKT dans le développement de la maladie. Pour ce faire, nous avons créé le modèle transgénique Ptenflox/flox;Ctnnb1flox(ex3)/+;Amhr2cre/+, chez lequel les cellules de la granulosa présentant non seulement une désinhibition de la voie PI3K/AKT, mais aussi une suractivation de la voie WNT/CTNNB1. Tel que prédit, les souris Ptenflox/flox;Ctnnb1flox(ex3)/+;Amhr2cre/+ ont développé une forme de GCT beaucoup plus agressive que celle observée chez les femelles Ptenflox/flox;Amhr2cre/+. Spécifiquement, le développement des tumeurs se déclenchait plus tôt, leur croissance était beaucoup plus rapide, nous avons pu observer des métastases pulmonaires et la dissémination des cellules tumorales dans la cavité péritonéale, et la maladie était invariablement fatale avant l’âge de 8 semaines. Le modèle Ptenflox/flox;Ctnnb1flox (ex3)/+;Amhr2cre/+ a donc servi à démontrer l'existence d'une synergie entre les voies WNT/CTNNB1 et PI3K/AKT dans le développement de la GCT. De façon inattendue, les souris Ptenflox/flox;Amhr2cre/+ ont aussi présenté un phénotype de sous-fertilité qui n’était pas d’origine ovarienne. Il a récemment été démontré que la souche Amhr2cre dirige l’expression de Cre non seulement aux cellules de la granulosa, mais aussi au stroma utérin et au myomètre. Le second objectif de ce travail était donc de démontrer si et comment le phénotype d’infertilité chez les souris Ptenflox/flox;Amhr2cre/+ pouvait découler d’un défaut utérin. Lors de l'implantation, les cellules du stroma utérin se différencient en cellules déciduelles pour former la décidua maternelle (DM), qui se régresse ensuite par apoptose afin de faciliter l’invasion des cellules trophoblastiques. De plus, la DM, en collaboration avec le tissu foetal, recrute des uNKs dont le rôle est de remodeler les artères spiralées pour augmenter l’apport sanguin maternel vers le foetus en développement. Nous avons pu démontrer que l'utérus des femelles gestantes Ptenflox/flox;Amhr2cre/+ présentait une DM anormalement résistante à l'apoptose, moins de uNKs et des artères spiralées non-remodelées. Par conséquent, l’invasion des cellules du trophoblaste était restreinte, compromettant le développement et la survie de l'embryon. Nous avons donc établi pour la première fois l’importance de Pten lors de la décidualisation et de l’invasion du trophoblaste.

A frailty modeling approach for parental effects in animal breeding

Survival models involving frailties are commonly applied in studies where correlated event time data arise due to natural or artificial clustering. In this paper we present an application of such models in the animal breeding field. Specifically, a mixed survival model with a multivariate correlated frailty term is proposed for the analysis of data from over 3611 Brazilian Nellore cattle. The primary aim is to evaluate parental genetic effects on the trait length in days that their progeny need to gain a commercially specified standard weight gain. This trait is not measured directly but can be estimated from growth data. Results point to the importance of genetic effects and suggest that these models constitute a valuable data analysis tool for beef cattle breeding.

Structured modeling of recombinant protein production in batch and fed-batch culture of baculovirus-infected insect cells

The infection of insect cells with baculovirus was described in a mathematical model as a part of the structured dynamic model describing whole animal cell metabolism. The model presented here is capable of simulating cell population dynamics, the concentrations of extracellular and intracellular viral components, and the heterologous product titers. The model describes the whole processes of viral infection and the effect of the infection on the host cell metabolism. Dynamic simulation of the model in batch and fed-batch mode gave good agreement between model predictions and experimental data. Optimum conditions for insect cell culture and viral infection in batch and fed-batch culture were studied using the model.

Effect of the immunosuppressants on hepatocyte proliferation and apoptosis in a young animal model of liver regeneration: An immunohistochemical study using tissue microarrays

Hepatocyte proliferation and apoptosis (programmed cell death) occur during the liver parenchyma regeneration and the liver size modeling is mainly controlled by hepatocyte apoptosis. The purpose of the present study was to verify the influence of immunosuppressant drugs on these phenomena by utilizing tissue microarray techniques. Thirty-six weaning rats (age 21-23 days, weight 30-50 g) were divided into six groups: control, sham, hepatectomy, hepatectomy plus solumedrol, hepatectomy plus CsA, and hepatectomy plus Tac. The animals were killed one day after hepatectomy, and the remnant livers were weighed and harvested for tissue microarray sections. Liver cell proliferation was evaluated by staining for PCNA and apoptosis was detected by the TUNEL method. It was verified that CsA promoted a decrease in the liver weight, Tac and CsA decreased the proliferation index of hepatocytes, and glucocorticoid had no significant effects. The apoptosis index was not altered by hepatectomy or immunosuppressants. Our data indicate that, in the growing rat, CsA and Tac have negative effects on hepatocyte proliferation and have no effect on the hepatocyte apoptosis.

Evaluation of the respiratory motion effect in small animal PET images with GATE Monte Carlo simulations

The rapid growth in genetics and molecular biology combined with the development of techniques for genetically engineering small animals has led to increased interest in in vivo small animal imaging. Small animal imaging has been applied frequently to the imaging of small animals (mice and rats), which are ubiquitous in modeling human diseases and testing treatments. The use of PET in small animals allows the use of subjects as their own control, reducing the interanimal variability. This allows performing longitudinal studies on the same animal and improves the accuracy of biological models. However, small animal PET still suffers from several limitations. The amounts of radiotracers needed, limited scanner sensitivity, image resolution and image quantification issues, all could clearly benefit from additional research. Because nuclear medicine imaging deals with radioactive decay, the emission of radiation energy through photons and particles alongside with the detection of these quanta and particles in different materials make Monte Carlo method an important simulation tool in both nuclear medicine research and clinical practice. In order to optimize the quantitative use of PET in clinical practice, data- and image-processing methods are also a field of intense interest and development. The evaluation of such methods often relies on the use of simulated data and images since these offer control of the ground truth. Monte Carlo simulations are widely used for PET simulation since they take into account all the random processes involved in PET imaging, from the emission of the positron to the detection of the photons by the detectors. Simulation techniques have become an importance and indispensable complement to a wide range of problems that could not be addressed by experimental or analytical approaches.

Modeling and optimization of extracellular polysaccharides production by Enterobacter A47

Polysaccharides are gaining increasing attention as potential environmental friendly and sustainable building blocks in many fields of the (bio)chemical industry. The microbial production of polysaccharides is envisioned as a promising path, since higher biomass growth rates are possible and therefore higher productivities may be achieved compared to vegetable or animal polysaccharides sources. This Ph.D. thesis focuses on the modeling and optimization of a particular microbial polysaccharide, namely the production of extracellular polysaccharides (EPS) by the bacterial strain Enterobacter A47. Enterobacter A47 was found to be a metabolically versatile organism in terms of its adaptability to complex media, notably capable of achieving high growth rates in media containing glycerol byproduct from the biodiesel industry. However, the industrial implementation of this production process is still hampered due to a largely unoptimized process. Kinetic rates from the bioreactor operation are heavily dependent on operational parameters such as temperature, pH, stirring and aeration rate. The increase of culture broth viscosity is a common feature of this culture and has a major impact on the overall performance. This fact complicates the mathematical modeling of the process, limiting the possibility to understand, control and optimize productivity. In order to tackle this difficulty, data-driven mathematical methodologies such as Artificial Neural Networks can be employed to incorporate additional process data to complement the known mathematical description of the fermentation kinetics. In this Ph.D. thesis, we have adopted such an hybrid modeling framework that enabled the incorporation of temperature, pH and viscosity effects on the fermentation kinetics in order to improve the dynamical modeling and optimization of the process. A model-based optimization method was implemented that enabled to design bioreactor optimal control strategies in the sense of EPS productivity maximization. It is also critical to understand EPS synthesis at the level of the bacterial metabolism, since the production of EPS is a tightly regulated process. Methods of pathway analysis provide a means to unravel the fundamental pathways and their controls in bioprocesses. In the present Ph.D. thesis, a novel methodology called Principal Elementary Mode Analysis (PEMA) was developed and implemented that enabled to identify which cellular fluxes are activated under different conditions of temperature and pH. It is shown that differences in these two parameters affect the chemical composition of EPS, hence they are critical for the regulation of the product synthesis. In future studies, the knowledge provided by PEMA could foster the development of metabolically meaningful control strategies that target the EPS sugar content and oder product quality parameters.

Climate change effects on animal and plant phylogenetic diversity in southern Africa

Much attention has been paid to the effects of climate change on species' range reductions and extinctions. There is however surprisingly little information on how climate change driven threat may impact the tree of life and result in loss of phylogenetic diversity (PD). Some plant families and mammalian orders reveal nonrandom extinction patterns, but many other plant families do not. Do these discrepancies reflect different speciation histories and does climate induced extinction result in the same discrepancies among different groups? Answers to these questions require representative taxon sampling. Here, we combine phylogenetic analyses, species distribution modeling, and climate change projections on two of the largest plant families in the Cape Floristic Region (Proteaceae and Restionaceae), as well as the second most diverse mammalian order in Southern Africa (Chiroptera), and an herbivorous insect genus (Platypleura) in the family Cicadidae to answer this question. We model current and future species distributions to assess species threat levels over the next 70years, and then compare projected with random PD survival. Results for these animal and plant clades reveal congruence. PD losses are not significantly higher under predicted extinction than under random extinction simulations. So far the evidence suggests that focusing resources on climate threatened species alone may not result in disproportionate benefits for the preservation of evolutionary history.

Quantitative genetic modeling and inference in the presence of nonignorable missing data.

Natural selection is typically exerted at some specific life stages. If natural selection takes place before a trait can be measured, using conventional models can cause wrong inference about population parameters. When the missing data process relates to the trait of interest, a valid inference requires explicit modeling of the missing process. We propose a joint modeling approach, a shared parameter model, to account for nonrandom missing data. It consists of an animal model for the phenotypic data and a logistic model for the missing process, linked by the additive genetic effects. A Bayesian approach is taken and inference is made using integrated nested Laplace approximations. From a simulation study we find that wrongly assuming that missing data are missing at random can result in severely biased estimates of additive genetic variance. Using real data from a wild population of Swiss barn owls Tyto alba, our model indicates that the missing individuals would display large black spots; and we conclude that genes affecting this trait are already under selection before it is expressed. Our model is a tool to correctly estimate the magnitude of both natural selection and additive genetic variance.

Using environmental niche modeling to understand biological invasions in a changing world

L'activité humaine affecte particulièrement la biodiversité, qui décline à une vitesse préoccupante. Parmi les facteurs réduisant la biodiversité, on trouve les espèces envahissantes. Symptomatiques d'un monde globalisé où l'échange se fait à l'échelle de la planète, certaines espèces, animales ou végétales, sont introduites, volontairement ou accidentellement par l'activité humaine (par exemple lors des échanges commerciaux ou par les voyageurs). Ainsi, ces espèces atteignent des régions qu'elles n'auraient jamais pu coloniser naturellement. Une fois introduites, l'absence de compétiteur peut les rendre particulièrement nuisibles. Ces nuisances sont plus ou moins directes, allant de problèmes sanitaires (p. ex. les piqûres très aigües des fourmis de feu, originaires d'Amérique du Sud et colonisant à une vitesse fulgurante les USA, l'Australie ou la Chine) à des nuisances sur la biodiversité (p. ex. les ravages de la perche du Nil sur la diversité unique des poissons Cichlidés du Lac Victoria). Il est donc important de pouvoir prévenir de telles introductions. De plus, pour le biologiste, ces espèces représentent une rare occasion de pouvoir comprendre les mécanismes évolutifs et écologiques qui expliquent le succès des envahissantes dans un monde où les équilibres sont bouleversés. Les modèles de niche environnementale sont un outil particulièrement utile dans le cadre de cette problématique. En reliant des observations d'espèces aux conditions environnementales où elles se trouvent, ils peuvent prédire la distribution potentielle des envahissantes, permettant d'anticiper et de mieux limiter leur impact. Toutefois, ils reposent sur des hypothèses pas évidentes à démontrer. L'une d'entre elle étant que la niche d'une espèce reste constante dans le temps, et dans l'espace. Le premier objectif de mon travail est de comparer si la niche d'une espèce envahissante diffère entre sa distribution d'origine native et celle d'origine introduite. En étudiant 50 espèces de plantes et 168 espèces de Mammifères, je démontre que c'est le cas et que par corolaire, il est possible de prédire leurs distributions. La deuxième partie de mon travail consiste à comprendre quelles seront les interactions entre le changement climatiques et les envahissantes, afin d'estimer leur impact sous un climat réchauffé. En étudiant la distribution de 49 espèces de plantes envahissantes, je démontre que les montagnes, régions relativement préservée par ce problème, deviendront bien plus exposées aux risques d'invasions biologiques. J'expose aussi comment les interactions entre l'activité humaine, le réchauffement climatique et les espèces envahissantes menacent la vigne sauvage en Europe et propose des zones géographiques particulièrement adaptée pour sa conservation. Enfin, à une échelle beaucoup plus locale, je montre qu'il est possible d'utiliser ces modèles de niches le long d'une rivière à une échelle extrêmement fine (1 mètre), potentiellement utile pour rationnaliser des mesures de conservations sur le terrain. - Biodiversity is significantly negatively affected by human activity. Invasive species are one of the most important factors causing biodiversity's decline. Intimately linked to the era of global trade, some plant or animal species can be accidentally or casually introduced with human activity (e.g. trade or travel). In this way, these species reach areas they could never reach through natural dispersal. Once naturalized, the lack of competitors can make these species highly noxious. Their effect is more or less direct, from sanitary problems (e.g. the harmful sting of Fire Ants, originating from South America and now spreading throughout USA, China and Australia) or can affect biodiversity (e.g. the Nile perch, devastating the one of the richest hotspot of Cichlid fishes diversity in Lake Victoria). It is thus important to prevent such harmful introductions. Moreover, invasive species represent for biologists one of the rare occasions to understand the evolutionary and ecological mechanisms behind the success of invaders in a world where natural equilibrium is already disturbed. Environmental niche models are particularly useful to tackle this problematic. By relating species observation to the environmental conditions where they occur, they can predict the potential distribution of invasive species, allowing a better anticipation and thus limiting their impact. However, they rely on strong assumption, one of the most important being that the modeled niche remains constant through space and time. The first aim of my thesis is to quantify the difference between the native and the invaded niche. By investigating 50 plant and 168 mammal species, I show that the niche is at least partially conserved, supporting for reliable predictions of invasive' s potential distributions. The second aim of my thesis is to understand the possible interactions between climate change and invasive species, such as to assess their impact under a warmer climate. By studying 49 invasive plant species, I show that mountain areas, which were relatively preserved, will become more suitable for biological invasions. Additionally, I show how interactions between human activity, global warming and invasive species are threatening the wild grapevine in Europe and propose geographical areas particularly adapted for conservation measures. Finally, at a much finer scale where conservation plannings ultimately take place, I show that it is possible to model the niche at very high resolution (1 meter) in an alluvial area allowing better prioritizations for conservation.

Physiologically based pharmacokinetic modeling of arsenic in the mouse

A remarkable feature of the carcinogenicity of inorganic arsenic is that while human exposures to high concentrations of inorganic arsenic in drinking water are associated with increases in skin, lung, and bladder cancer, inorganic arsenic has not typically caused tumors in standard laboratory animal test protocols. Inorganic arsenic administered for periods of up to 2 yr to various strains of laboratory mice, including the Swiss CD-1, Swiss CR:NIH(S), C57Bl/6p53(+/-), and C57Bl/6p53(+/+), has not resulted in significant increases in tumor incidence. However, Ng et al. (1999) have reported a 40% tumor incidence in C57Bl/6J mice exposed to arsenic in their drinking water throughout their lifetime, with no tumors reported in controls. In order to investigate the potential role of tissue dosimetry in differential susceptibility to arsenic carcinogenicity, a physiologically based pharmacokinetic (PBPK) model for inorganic arsenic in the rat, hamster, monkey, and human (Mann et al., 1996a, 1996b) was extended to describe the kinetics in the mouse. The PBPK model was parameterized in the mouse using published data from acute exposures of B6C3F1 mice to arsenate, arsenite, monomethylarsonic acid (MMA), and dimethylarsinic acid (DMA) and validated using data from acute exposures of C57Black mice. Predictions of the acute model were then compared with data from chronic exposures. There was no evidence of changes in the apparent volume of distribution or in the tissue-plasma concentration ratios between acute and chronic exposure that might support the possibility of inducible arsenite efflux. The PBPK model was also used to project tissue dosimetry in the C57Bl/6J study, in comparison with tissue levels in studies having shorter duration but higher arsenic treatment concentrations. The model evaluation indicates that pharmacokinetic factors do not provide an explanation for the difference in outcomes across the various mouse bioassays. Other possible explanations may relate to strain-specific differences, or to the different durations of dosing in each of the mouse studies, given the evidence that inorganic arsenic is likely to be active in the later stages of the carcinogenic process. [Authors]

The Role of the Delay Time in the Modeling of Biological Range Expansions

The time interval between successive migrations of biological species causes a delay time in the reaction-diffusion equations describing their space-time dynamics. This lowers the predicted speed of the waves of advance, as compared to classical models. It has been shown that this delay-time effect improves the modeling of human range expansions. Here, we demonstrate that it can also be important for other species. We present two new examples where the predictions of the time-delayed and the classical (Fisher) approaches are compared to experimental data. No free or adjustable parameters are used. We show that the importance of the delay effect depends on the dimensionless product of the initial growth rate and the delay time. We argue that the delay effect should be taken into account in the modeling of range expansions for biological species

Fuzzy modeling of broiler performance, raised from 1 to 21 days, subject to heat stress

ABSTRACT Given the need to obtain systems to better control broiler production environment, we performed an experiment with broilers from 1 to 21 days, which were submitted to different intensities and air temperature durations in conditioned wind tunnels and the results were used for validation of afuzzy model. The model was developed using as input variables: duration of heat stress (days), dry bulb air temperature (°C) and as output variable: feed intake (g) weight gain (g) and feed conversion (g.g-1). The inference method used was Mamdani, 20 rules have been prepared and the defuzzification technique used was the Center of Gravity. A satisfactory efficiency in determining productive responses is evidenced in the results obtained in the model simulation, when compared with the experimental data, where R2 values ​​calculated for feed intake, weight gain and feed conversion were 0.998, 0.981 and 0.980, respectively.