Evolution of decision-making and learning under fluctuating social environments

The capacity to learn to associate sensory perceptions with appropriate motor actions underlies the success of many animal species, from insects to humans. The evolutionary significance of learning has long been a subject of interest for evolutionary biologists who emphasize the bene¬fit yielded by learning under changing environmental conditions, where it is required to flexibly switch from one behavior to another. However, two unsolved questions are particularly impor¬tant for improving our knowledge of the evolutionary advantages provided by learning, and are addressed in the present work. First, because it is possible to learn the wrong behavior when a task is too complex, the learning rules and their underlying psychological characteristics that generate truly adaptive behavior must be identified with greater precision, and must be linked to the specific ecological problems faced by each species. A framework for predicting behavior from the definition of a learning rule is developed here. Learning rules capture cognitive features such as the tendency to explore, or the ability to infer rewards associated to unchosen actions. It is shown that these features interact in a non-intuitive way to generate adaptive behavior in social interactions where individuals affect each other's fitness. Such behavioral predictions are used in an evolutionary model to demonstrate that, surprisingly, simple trial-and-error learn¬ing is not always outcompeted by more computationally demanding inference-based learning, when population members interact in pairwise social interactions. A second question in the evolution of learning is its link with and relative advantage compared to other simpler forms of phenotypic plasticity. After providing a conceptual clarification on the distinction between genetically determined vs. learned responses to environmental stimuli, a new factor in the evo¬lution of learning is proposed: environmental complexity. A simple mathematical model shows that a measure of environmental complexity, the number of possible stimuli in one's environ¬ment, is critical for the evolution of learning. In conclusion, this work opens roads for modeling interactions between evolving species and their environment in order to predict how natural se¬lection shapes animals' cognitive abilities. - La capacité d'apprendre à associer des sensations perceptives à des actions motrices appropriées est sous-jacente au succès évolutif de nombreuses espèces, depuis les insectes jusqu'aux êtres hu¬mains. L'importance évolutive de l'apprentissage est depuis longtemps un sujet d'intérêt pour les biologistes de l'évolution, et ces derniers mettent l'accent sur le bénéfice de l'apprentissage lorsque les conditions environnementales sont changeantes, car dans ce cas il est nécessaire de passer de manière flexible d'un comportement à l'autre. Cependant, deux questions non résolues sont importantes afin d'améliorer notre savoir quant aux avantages évolutifs procurés par l'apprentissage. Premièrement, puisqu'il est possible d'apprendre un comportement incorrect quand une tâche est trop complexe, les règles d'apprentissage qui permettent d'atteindre un com¬portement réellement adaptatif doivent être identifiées avec une plus grande précision, et doivent être mises en relation avec les problèmes écologiques spécifiques rencontrés par chaque espèce. Un cadre théorique ayant pour but de prédire le comportement à partir de la définition d'une règle d'apprentissage est développé ici. Il est démontré que les caractéristiques cognitives, telles que la tendance à explorer ou la capacité d'inférer les récompenses liées à des actions non ex¬périmentées, interagissent de manière non-intuitive dans les interactions sociales pour produire des comportements adaptatifs. Ces prédictions comportementales sont utilisées dans un modèle évolutif afin de démontrer que, de manière surprenante, l'apprentissage simple par essai-et-erreur n'est pas toujours battu par l'apprentissage basé sur l'inférence qui est pourtant plus exigeant en puissance de calcul, lorsque les membres d'une population interagissent socialement par pair. Une deuxième question quant à l'évolution de l'apprentissage concerne son lien et son avantage relatif vis-à-vis d'autres formes plus simples de plasticité phénotypique. Après avoir clarifié la distinction entre réponses aux stimuli génétiquement déterminées ou apprises, un nouveau fac¬teur favorisant l'évolution de l'apprentissage est proposé : la complexité environnementale. Un modèle mathématique permet de montrer qu'une mesure de la complexité environnementale - le nombre de stimuli rencontrés dans l'environnement - a un rôle fondamental pour l'évolution de l'apprentissage. En conclusion, ce travail ouvre de nombreuses perspectives quant à la mo¬délisation des interactions entre les espèces en évolution et leur environnement, dans le but de comprendre comment la sélection naturelle façonne les capacités cognitives des animaux.

Verbal labels selectively bias brain responses to high-energy foods.

The influence of external factors on food preferences and choices is poorly understood. Knowing which and how food-external cues impact the sensory processing and cognitive valuation of food would provide a strong benefit toward a more integrative understanding of food intake behavior and potential means of interfering with deviant eating patterns to avoid detrimental health consequences for individuals in the long run. We investigated whether written labels with positive and negative (as opposed to 'neutral') valence differentially modulate the spatio-temporal brain dynamics in response to the subsequent viewing of high- and low-energetic food images. Electrical neuroimaging analyses were applied to visual evoked potentials (VEPs) from 20 normal-weight participants. VEPs and source estimations in response to high- and low- energy foods were differentially affected by the valence of preceding word labels over the ~260-300 ms post-stimulus period. These effects were only observed when high-energy foods were preceded by labels with positive valence. Neural sources in occipital as well as posterior, frontal, insular and cingulate regions were down-regulated. These findings favor cognitive-affective influences especially on the visual responses to high-energetic food cues, potentially indicating decreases in cognitive control and goal-adaptive behavior. Inverse correlations between insular activity and effectiveness in food classification further indicate that this down-regulation directly impacts food-related behavior.

Brain dynamics of meal size selection in humans.

Although neuroimaging research has evidenced specific responses to visual food stimuli based on their nutritional quality (e.g., energy density, fat content), brain processes underlying portion size selection remain largely unexplored. We identified spatio-temporal brain dynamics in response to meal images varying in portion size during a task of ideal portion selection for prospective lunch intake and expected satiety. Brain responses to meal portions judged by the participants as 'too small', 'ideal' and 'too big' were measured by means of electro-encephalographic (EEG) recordings in 21 normal-weight women. During an early stage of meal viewing (105-145ms), data showed an incremental increase of the head-surface global electric field strength (quantified via global field power; GFP) as portion judgments ranged from 'too small' to 'too big'. Estimations of neural source activity revealed that brain regions underlying this effect were located in the insula, middle frontal gyrus and middle temporal gyrus, and are similar to those reported in previous studies investigating responses to changes in food nutritional content. In contrast, during a later stage (230-270ms), GFP was maximal for the 'ideal' relative to the 'non-ideal' portion sizes. Greater neural source activity to 'ideal' vs. 'non-ideal' portion sizes was observed in the inferior parietal lobule, superior temporal gyrus and mid-posterior cingulate gyrus. Collectively, our results provide evidence that several brain regions involved in attention and adaptive behavior track 'ideal' meal portion sizes as early as 230ms during visual encounter. That is, responses do not show an increase paralleling the amount of food viewed (and, in extension, the amount of reward), but are shaped by regulatory mechanisms.

Regulation of adaptive behaviour during fasting by hypothalamic Foxa2.

The lateral hypothalamic area is considered the classic 'feeding centre', regulating food intake, arousal and motivated behaviour through the actions of orexin and melanin-concentrating hormone (MCH). These neuropeptides are inhibited in response to feeding-related signals and are released during fasting. However, the molecular mechanisms that regulate and integrate these signals remain poorly understood. Here we show that the forkhead box transcription factor Foxa2, a downstream target of insulin signalling, regulates the expression of orexin and MCH. During fasting, Foxa2 binds to MCH and orexin promoters and stimulates their expression. In fed and in hyperinsulinemic obese mice, insulin signalling leads to nuclear exclusion of Foxa2 and reduced expression of MCH and orexin. Constitutive activation of Foxa2 in the brain (Nes-Cre/+;Foxa2T156A(flox/flox) genotype) results in increased neuronal MCH and orexin expression and increased food consumption, metabolism and insulin sensitivity. Spontaneous physical activity of these animals in the fed state is significantly increased and is similar to that in fasted mice. Conditional activation of Foxa2 through the T156A mutation expression in the brain of obese mice also resulted in improved glucose homeostasis, decreased fat and increased lean body mass. Our results demonstrate that Foxa2 can act as a metabolic sensor in neurons of the lateral hypothalamic area to integrate metabolic signals, adaptive behaviour and physiological responses.

Adaptive search and information updating in sequential mate choice

Classical treatments of problems of sequential mate choice assume that the distribution of the quality of potential mates is known a priori. This assumption, made for analytical purposes, may seem unrealistic, opposing empirical data as well as evolutionary arguments. Using stochastic dynamic programming, we develop a model that includes the possibility for searching individuals to learn about the distribution and in particular to update mean and variance during the search. In a constant environment, a priori knowledge of the parameter values brings strong benefits in both time needed to make a decision and average value of mate obtained. Knowing the variance yields more benefits than knowing the mean, and benefits increase with variance. However, the costs of learning become progressively lower as more time is available for choice. When parameter values differ between demes and/or searching periods, a strategy relying on fixed a priori information might lead to erroneous decisions, which confers advantages on the learning strategy. However, time for choice plays an important role as well: if a decision must be made rapidly, a fixed strategy may do better even when the fixed image does not coincide with the local parameter values. These results help in delineating the ecological-behavior context in which learning strategies may spread.

Verification at the protein level of the PIF4-mediated external coincidence model for the temperature-adaptive photoperiodic control of plant growth in Arabidopsis thaliana.

Plant circadian clock controls a wide variety of physiological and developmental events, which include the short-days (SDs)-specific promotion of the elongation of hypocotyls during de-etiolation and also the elongation of petioles during vegetative growth. In A. thaliana, the PIF4 gene encoding a phytochrome-interacting basic helix-loop-helix (bHLH) transcription factor plays crucial roles in this photoperiodic control of plant growth. According to the proposed external coincidence model, the PIF4 gene is transcribed precociously at the end of night specifically in SDs, under which conditions the protein product is stably accumulated, while PIF4 is expressed exclusively during the daytime in long days (LDs), under which conditions the protein product is degraded by the light-activated phyB and also the residual proteins are inactivated by the DELLA family of proteins. A number of previous reports provided solid evidence to support this coincidence model mainly at the transcriptional level of the PIF 4 and PIF4-traget genes. Nevertheless, the diurnal oscillation profiles of PIF4 proteins, which were postulated to be dependent on photoperiod and ambient temperature, have not yet been demonstrated. Here we present such crucial evidence on PIF4 protein level to further support the external coincidence model underlying the temperature-adaptive photoperiodic control of plant growth in A. thaliana.

Geometric morphometric analyses provide evidence for the adaptive character of the Tanganyikan cichlid fish radiations.

The cichlids of East Africa are renowned as one of the most spectacular examples of adaptive radiation. They provide a unique opportunity to investigate the relationships between ecology, morphological diversity, and phylogeny in producing such remarkable diversity. Nevertheless, the parameters of the adaptive radiations of these fish have not been satisfactorily quantified yet. Lake Tanganyika possesses all of the major lineages of East African cichlid fish, so by using geometric morphometrics and comparative analyses of ecology and morphology, in an explicitly phylogenetic context, we quantify the role of ecology in driving adaptive speciation. We used geometric morphometric methods to describe the body shape of over 1000 specimens of East African cichlid fish, with a focus on the Lake Tanganyika species assemblage, which is composed of more than 200 endemic species. The main differences in shape concern the length of the whole body and the relative sizes of the head and caudal peduncle. We investigated the influence of phylogeny on similarity of shape using both distance-based and variance partitioning methods, finding that phylogenetic inertia exerts little influence on overall body shape. Therefore, we quantified the relative effect of major ecological traits on shape using phylogenetic generalized least squares and disparity analyses. These analyses conclude that body shape is most strongly predicted by feeding preferences (i.e., trophic niches) and the water depths at which species occur. Furthermore, the morphological disparity within tribes indicates that even though the morphological diversification associated with explosive speciation has happened in only a few tribes of the Tanganyikan assemblage, the potential to evolve diverse morphologies exists in all tribes. Quantitative data support the existence of extensive parallelism in several independent adaptive radiations in Lake Tanganyika. Notably, Tanganyikan mouthbrooders belonging to the C-lineage and the substrate spawning Lamprologini have evolved a multitude of different shapes from elongated and Lamprologus-like hypothetical ancestors. Together, these data demonstrate strong support for the adaptive character of East African cichlid radiations.

Adaptive tracking of EEG oscillations.

Neuronal oscillations are an important aspect of EEG recordings. These oscillations are supposed to be involved in several cognitive mechanisms. For instance, oscillatory activity is considered a key component for the top-down control of perception. However, measuring this activity and its influence requires precise extraction of frequency components. This processing is not straightforward. Particularly, difficulties with extracting oscillations arise due to their time-varying characteristics. Moreover, when phase information is needed, it is of the utmost importance to extract narrow-band signals. This paper presents a novel method using adaptive filters for tracking and extracting these time-varying oscillations. This scheme is designed to maximize the oscillatory behavior at the output of the adaptive filter. It is then capable of tracking an oscillation and describing its temporal evolution even during low amplitude time segments. Moreover, this method can be extended in order to track several oscillations simultaneously and to use multiple signals. These two extensions are particularly relevant in the framework of EEG data processing, where oscillations are active at the same time in different frequency bands and signals are recorded with multiple sensors. The presented tracking scheme is first tested with synthetic signals in order to highlight its capabilities. Then it is applied to data recorded during a visual shape discrimination experiment for assessing its usefulness during EEG processing and in detecting functionally relevant changes. This method is an interesting additional processing step for providing alternative information compared to classical time-frequency analyses and for improving the detection and analysis of cross-frequency couplings.

Spatiotemporal adaptive multiscale multiphysics simulations of two-phase flow

We present a spatiotemporal adaptive multiscale algorithm, which is based on the Multiscale Finite Volume method. The algorithm offers a very efficient framework to deal with multiphysics problems and to couple regions with different spatial resolution. We employ the method to simulate two-phase flow through porous media. At the fine scale, we consider a pore-scale description of the flow based on the Volume Of Fluid method. In order to construct a global problem that describes the coarse-scale behavior, the equations are averaged numerically with respect to auxiliary control volumes, and a Darcy-like coarse-scale model is obtained. The space adaptivity is based on the idea that a fine-scale description is only required in the front region, whereas the resolution can be coarsened elsewhere. Temporal adaptivity relies on the fact that the fine-scale and the coarse-scale problems can be solved with different temporal resolution (longer time steps can be used at the coarse scale). By simulating drainage under unstable flow conditions, we show that the method is able to capture the coarse-scale behavior outside the front region and to reproduce complex fluid patterns in the front region.

Adaptive changes in a radial maze task: Efficient selection of baited arms with reduced foraging in senescent hooded rats

Qualitative differences in strategy selection during foraging in a partially baited maze were assessed in young and old rats. The baited and non-baited arms were at a fixed position in space and marked by a specific olfactory cue. The senescent rats did more re-entries during the first four-trial block but were more rapid than the young rats in selecting the reinforced arms during the first visits. Dissociation between the olfactory spatial cue reference by rotating the maze revealed that only few old subjects relied on olfactory cues to select the baited arms and the remainder relied mainly on the visuo-spatial cues.

The effect of learning on the evolution of new courtship behavior: a simulation model

The fact that individuals learn can change the relationship between genotype and phenotype in the population, and thus affect the evolutionary response to selection. Here we ask how male ability to learn from female response affects the evolution of a novel male behavioral courtship trait under pre-existing female preference (sensory drive). We assume a courtship trait which has both a genetic and a learned component, and a two-level female response to males. With individual-based simulations we show that, under this scenario, learning generally increases the strength of selection on the genetic component of the courtship trait, at least when the population genetic mean is still low. As a consequence, learning not only accelerates the evolution of the courtship trait, but also enables it when the trait is costly, which in the absence of learning results in an adaptive valley. Furthermore, learning can enable the evolution of the novel trait in the face of gene flow mediated by immigration of males that show superior attractiveness to females based on another, non-heritable trait. However, rather than increasing monotonically with the speed of learning, the effect of learning on evolution is maximized at intermediate learning rates. This model shows that, at least under some scenarios, the ability to learn can drive the evolution of mating behaviors through a process equivalent to Waddington's genetic assimilation.

La dépendance à l'égard de l'environnement lors de lésions cérébrales: conduites d'imitation, de préhension et d'utilisation [Environmental dependence in brain lesions: imitative behavior, prehension and utilization].

This paper reviews the literature on clinical signs such as imitation behavior, grasp reaction, manipulation of tools, utilization behavior, environmental dependency, hyperlexia, hypergraphia and echolalia. Some aspects of this semiology are of special interest because they refer to essential notions such as free-will and autonomy.

Molecular variation at a candidate gene implicated in the regulation of fire ant social behavior

The fire ant Solenopsis invicta and its close relatives display an important social polymorphism involving differences in colony queen number. Colonies are headed by either a single reproductive queen (monogyne form) or multiple queens (polygyne form). This variation in social organization is associated with variation at the gene Gp-9, with monogyne colonies harboring only B-like allelic variants and polygyne colonies always containing b-like variants as well. We describe naturally occurring variation at Gp-9 in fire ants based on 185 full-length sequences, 136 of which were obtained from S. invicta collected over much of its native range. While there is little overall differentiation between most of the numerous alleles observed, a surprising amount is found in the coding regions of the gene, with such substitutions usually causing amino acid replacements. This elevated coding-region variation may result from a lack of negative selection acting to constrain amino acid replacements over much of the protein, different mutation rates or biases in coding and non-coding sequences, negative selection acting with greater strength on non-coding than coding regions, and/or positive selection acting on the protein. Formal selection analyses provide evidence that the latter force played an important role in the basal b-like lineages coincident with the emergence of polygyny. While our data set reveals considerable paraphyly and polyphyly of S. invicta sequences with respect to those of other fire ant species, the b-like alleles of the socially polymorphic species are monophyletic. An expanded analysis of colonies containing alleles of this clade confirmed the invariant link between their presence and expression of polygyny. Finally, our discovery of several unique alleles bearing various combinations of b-like and B-like codons allows us to conclude that no single b-like residue is completely predictive of polygyne behavior and, thus, potentially causally involved in its expression. Rather, all three typical b-like residues appear to be necessary.

HARNESSING iNKT CELLS WITH RECOMBINANT CD1d FUSION PROTEINS TO REDIRECT INNATE AND ADAPTIVE IMMUNITY TO THE TUMOR

Les thérapies du cancer, comme la radiothérapie et la chimiothérapie, sont couramment utilisées mais ont de nombreux effets secondaires. Ces thérapies invasives pour le patient nécessitent d'être améliorées et de nombreuses avancées ont été faites afin d'adapter et de personnaliser le traitement du cancer. L'immunothérapie a pour but de renforcer le système immunitaire du patient et de le rediriger de manière spécifique contre la tumeur. Dans notre projet, nous activons les lymphocytes Invariant Natural Killer T (iNKT) afin de mettre en place une immunothérapie innovatrice contre le cancer. Les cellules iNKT sont une unique sous-population de lymphocytes T qui ont la particularité de réunir les propriétés de l'immunité innée ainsi qu'adaptative. En effet, les cellules iNKT expriment à leur surface des molécules présentes aussi sur les cellules tueuses NK, caractéristique de l'immunité innée, ainsi qu'un récepteur de cellules T (TCR) qui représente l'immunité adaptative. Les cellules iNKT reconnaissent avec leur TCR des antigènes présentés par la molécule CD1d. Les antigènes sont des protéines, des polysaccharides ou des lipides reconnus par les cellules du système immunitaire ou les anticorps pour engendrer une réponse immunitaire. Dans le cas des cellules iNKT, l'alpha-galactosylceramide (αGC) est un antigène lipidique fréquemment utilisé dans les études cliniques comme puissant activateur. Après l'activation des cellules iNKT avec l'αGC, celles-ci produisent abondamment et rapidement des cytokines. Ces cytokines sont des molécules agissant comme des signaux activateurs d'autres cellules du système immunitaire telles que les cellules NK et les lymphocytes T. Cependant, les cellules iNKT deviennent anergiques après un seul traitement avec l'αGC c'est à dire qu'elles ne peuvent plus être réactivées, ce qui limite leur utilisation dans l'immunothérapie du cancer. Dans notre groupe, Stirnemann et al ont publié une molécule recombinante innovante, composée de la molécule CD1d soluble et chargée avec le ligand αGC (αGC/sCD1d). Cette protéine est capable d'activer les cellules iNKT tout en évitant l'anergie. Dans le système immunitaire, les anticorps sont indispensables pour combattre une infection bactérienne ou virale. En effet, les anticorps ont la capacité de reconnaître et lier spécifiquement un antigène et permettent l'élimination de la cellule qui exprime cet antigène. Dans le domaine de l'immunothérapie, les anticorps sont utilisés afin de cibler des antigènes présentés seulement par la tumeur. Ce procédé permet de réduire efficacement les effets secondaires lors du traitement du cancer. Nous avons donc fusionné la protéine recombinante αGC/CD1d à un fragment d'anticorps qui reconnaît un antigène spécifique des cellules tumorales. Dans une étude préclinique, nous avons démontré que la protéine αGC/sCD1d avec un fragment d'anticorps dirigé contre la tumeur engendre une meilleure activation des cellules iNKT et entraîne un effet anti-tumeur prolongé. Cet effet anti-tumeur est augmenté comparé à une protéine αGC/CD1d qui ne cible pas la tumeur. Nous avons aussi montré que l'activation des cellules iNKT avec la protéine αGC/sCD1d-anti-tumeur améliore l'effet anti- tumoral d'un vaccin pour le cancer. Lors d'expériences in vitro, la protéine αGC/sCD1d-anti- tumeur permet aussi d'activer les cellules humaines iNKT et ainsi tuer spécifiquement les cellules tumorales humaines. La protéine αGC/sCD1d-anti-tumeur représente une alternative thérapeutique prometteuse dans l'immunothérapie du cancer. - Les cellules Invariant Natural Killer T (iNKT), dont les effets anti-tumoraux ont été démontrés, sont de puissants activateurs des cellules Natural Killer (NK), des cellules dendritiques (DC) et des lymphocytes T. Cependant, une seule injection du ligand de haute affinité alpha-galactosylceramide (αGC) n'induit une forte activation des cellules iNKT que durant une courte période. Celle-ci est alors suivie d'une longue phase d'anergie, limitant ainsi leur utilisation pour la thérapie. Comme alternative prometteuse, nous avons montré que des injections répétées d'αGC chargé sur une protéine recombinante de CD1d soluble (αGC/sCD1d) chez la souris entraînent une activation prolongée des cellules iNKT, associée à une production continue de cytokine. De plus, le maintien de la réactivité des cellules iNKT permet de prolonger l'activité anti-tumorale lorsque la protéine αGC/sCD1d est fusionnée à un fragment d'anticorps (scFv) dirigé contre la tumeur. L'inhibition de la croissance tumorale n'est optimale que lorsque les souris sont traitées avec la protéine αGC/sCD1d-scFv ciblant la tumeur, la protéine αGC/sCD1d-scFv non-appropriée étant moins efficace. Dans le système humain, les protéines recombinantes αGC/sCD1d-anti-HER2 et anti-CEA sont capables d'activer et de faire proliférer des cellules iNKT à partir de PBMCs issues de donneurs sains. De plus, la protéine αGC/sCD1d-scFv a la capacité d'activer directement des clones iNKT humains en l'absence de cellules présentatrices d'antigènes (CPA), contrairement au ligand αGC libre. Mais surtout, la lyse des cellules tumorales par les iNKT humaines n'est obtenue que lorsqu'elles sont incubées avec la protéine αGC/sCD1d-scFv anti- tumeur. En outre, la redirection de la cytotoxicité des cellules iNKT vers la tumeur est supérieure à celle obtenue avec une stimulation par des CPA chargées avec l'αGC. Afin d'augmenter les effets anti-tumoraux, nous avons exploité la capacité des cellules iNKT à activer l'immunité adaptive. Pour ce faire, nous avons combiné l'immunothérapie NKT/CD1d avec un vaccin anti-tumoral composé d'un peptide OVA. Des effets synergiques ont été obtenus lorsque les traitements avec la protéine αGC/sCD1d-anti-HER2 étaient associés avec le CpG ODN comme adjuvant pour la vaccination avec le peptide OVA. Ces effets ont été observés à travers l'activation de nombreux lymphocytes T CD8+ spécifique de la tumeur, ainsi que par la forte expansion des cellules NK. Les réponses, innée et adaptive, élevées après le traitement avec la protéine αGC/sCD1d-anti-HER2 combinée au vaccin OVA/CpG ODN étaient associées à un fort ralentissement de la croissance des tumeurs B16- OVA-HER2. Cet effet anti-tumoral corrèle avec l'enrichissement des lymphocytes T CD8+ spécifiques observé à la tumeur. Afin d'étendre l'application des protéines αGC/sCD1d et d'améliorer leur efficacité, nous avons développé des fusions CD1d alternatives. Premièrement, une protéine αGC/sCD1d dimérique, qui permet d'augmenter l'avidité de la molécule CD1d pour les cellules iNKT. Dans un deuxième temps, nous avons fusionné la protéine αGC/sCD1d avec un scFv dirigé contre le récepteur 3 du facteur de croissance pour l'endothélium vasculaire (VEGFR-3), afin de cibler l'environnement de la tumeur. Dans l'ensemble, ces résultats démontrent que la thérapie médiée par la protéine recombinante αGC/sCD1d-scFv est une approche prometteuse pour rediriger l'immunité innée et adaptive vers le site tumoral. - Invariant Natural Killer T cells (iNKT) are potent activators of Natural Killer (NK), dendritic cells (DC) and T lymphocytes, and their anti-tumor activities have been well demonstrated. However, a single injection of the high affinity CD1d ligand alpha-galactosylceramide (αGC) leads to a strong but short-lived iNKT cell activation followed by a phase of long-term anergy, limiting the therapeutic use of this ligand. As a promising alternative, we have demonstrated that when αGC is loaded on recombinant soluble CD1d molecules (αGC/sCD1d), repeated injections in mice led to the sustained iNKT cell activation associated with continued cytokine secretion. Importantly, the retained reactivity of iNKT cell led to prolonged antitumor activity when the αGC/sCD1d was fused to an anti-tumor scFv fragments. Optimal inhibition of tumor growth was obtained only when mice were treated with the tumor-targeted αGC/CD1d-scFv fusion, whereas the irrelevant αGC/CD1d-scFv fusion was less efficient. When tested in a human system, the recombinant αGC/sCD1d-anti-HER2 and -anti-CEA fusion proteins were able to expand iNKT cells from PBMCs of healthy donors. Furthermore, the αGC/sCD1d-scFv fusion had the capacity to directly activate human iNKT cells clones without the presence of antigen-presenting cells (APCs), in contrast to the free αGC ligand. Most importantly, tumor cell killing by human iNKT cells was obtained only when co- incubated with the tumor targeted sCD1d-antitumor scFv, and their direct tumor cytotoxicity was superior to the bystander killing obtained with αGC-loaded APCs stimulation. To further enhance the anti-tumor effects, we exploited the ability of iNKT cells to transactivate the adaptive immunity, by combining the NKT/CD1d immunotherapy with a peptide cancer vaccine. Interestingly, synergistic effects were obtained when the αGC/sCD1d- anti-HER2 fusion treatment was combined with CpG ODN as adjuvant for the OVA peptide vaccine, as seen by higher numbers of activated antigen-specific CD8 T cells and NK cells, as compared to each regimen alone. The increased innate and adaptive immune responses upon combined tumor targeted sCD1d-scFv treatment and OVA/CpG vaccine were associated with a strong delay in B16-OVA-HER2 melanoma tumor growth, which correlated with an enrichment of antigen-specific CD8 cells at the tumor site. In order to extend the application of the CD1d fusion, we designed alternative CD1d fusion proteins. First, a dimeric αGC/sCD1d-Fc fusion, which permits to augment the avidity of the CD1d for iNKT cells and second, an αGC/sCD1d fused to an anti vascular endothelial growth factor receptor-3 (VEGFR-3) scFv, in order to target tumor stroma environment. Altogether, these results demonstrate that the iNKT-mediated immunotherapy via recombinant αGC/sCD1d-scFv fusion is a promising approach to redirect the innate and adaptive antitumor immune response to the tumor site.

How the gut links innate and adaptive immunity.

Mucosal surfaces represent the main sites in which environmental microorganisms and antigens interact with the host. Sentinel cells, including epithelial cells, lumenal macrophages, and intraepithelial dendritic cells, continuously sense the environment and coordinate defenses for the protection of mucosal tissues. The mucosal epithelial cells are crucial actors in coordinating defenses. They sense the outside world and respond to environmental signals by releasing chemokines and cytokines that recruit inflammatory and immune cells to control potential infectious agents and to attract cells able to trigger immune responses. Among immune cells, dendritic cells (DC) play a key role in controlling adaptive immune responses, due to their capacity to internalize foreign materials and to present antigens to naive T and B lymphocytes, locally or in draining organized lymphoid tissues. Immune cells recruited in epithelial tissues can, in turn, act upon the epithelial cells and change their phenotype in a process referred to as epithelial metaplasia.