The effect of mutations in the DRY motif on the constitutive activity and structural instability of the histamine H(2) receptor.

In previous studies we showed that the wild-type histamine H(2) receptor stably expressed in Chinese hamster ovary cells is constitutively active. Because constitutive activity of the H(2) receptor is already found at low expression levels (300 fmol/mg protein) this receptor is a relatively unique member of the G-protein-coupled receptor (GPCR) family and a useful tool for studying GPCR activation. In this study the role of the highly conserved DRY motif in activation of the H(2) receptor was investigated. Mutation of the aspartate 115 residue in this motif resulted in H(2) receptors with high constitutive activity, increased agonist affinity, and increased signaling properties. In addition, the mutant receptors were shown to be highly structurally instable. Mutation of the arginine 116 residue in the DRY motif resulted also in a highly structurally instable receptor; expression of the receptor could only be detected after stabilization with either an agonist or inverse agonist. Moreover, the agonist affinity at the Arg-116 mutant receptors was increased, whereas the signal transduction properties of these receptors were decreased. We conclude that the Arg-116 mutant receptors can adopt an active conformation but have a decreased ability to couple to or activate the G(s)-protein. This study examines the pivotal role of the aspartate and arginine residues of the DRY motif in GPCR function. Disruption of receptor stabilizing constraints by mutation in the DRY motif leads to the formation of active GPCR conformations, but concomitantly to GPCR instability.

Structural variation and its effect on expression.

Structural variation, whether it is caused by copy number variants or present in a balanced form, such as reciprocal translocations and inversions, can have a profound and dramatic effect on the expression of genes mapping within and close to the rearrangement, as well as affecting others genome wide. These effects can be caused by altering the copy number of one or more genes or regulatory elements (dosage effect) or from physical disruption of links between regulatory elements and their associated gene or genes, resulting in perturbation of expression. Similarly, large-scale structural variants can result in genome-wide expression changes by altering the positions that chromosomes occupy within the nucleus, potentially disrupting not only local cis interactions, but also trans interactions that occur throughout the genome. Structural variation is, therefore, a significant factor in the study of gene expression and is discussed here in more detail.

Multiscale assessment of plant diversity in wooded pastures of the Jura mountains

Résumé La diminution de la biodiversité, à toutes les échelles spatiales et sur l'ensemble de la planète, compte parmi les problèmes les plus préoccupants de notre époque. En terme de conservation, il est aujourd'hui primordial de mieux comprendre les mécanismes qui créent et maintiennent la biodiversité dans les écosystèmes naturels ou anthropiques. La présente étude a pour principal objectif d'améliorer notre compréhension des patrons de biodiversité végétale et des mécanismes sous jacents, dans un écosystème complexe, riche en espèces et à forte valeur patrimoniale, les pâturages boisés jurassiens. Structure et échelle spatiales sont progressivement reconnues comme des dimensions incontournables dans l'étude des patrons de biodiversité. De plus, ces deux éléments jouent un rôle central dans plusieurs théories écologiques. Toutefois, peu d'hypothèses issues de simulations ou d'études théoriques concernant le lien entre structure spatiale du paysage et biodiversité ont été testées de façon empirique. De même, l'influence des différentes composantes de l'échelle spatiale sur les patrons de biodiversité est méconnue. Cette étude vise donc à tester quelques-unes de ces hypothèses et à explorer les patrons spatiaux de biodiversité dans un contexte multi-échelle, pour différentes mesures de biodiversité (richesse et composition en espèces) à l'aide de données de terrain. Ces données ont été collectées selon un plan d'échantillonnage hiérarchique. Dans un premier temps, nous avons testé l'hypothèse élémentaire selon laquelle la richesse spécifique (le nombre d'espèces sur une surface donnée) est liée à l'hétérogénéité environnementale quelque soit l'échelle. Nous avons décomposé l'hétérogénéité environnementale en deux parties, la variabilité des conditions environnementales et sa configuration spatiale. Nous avons montré que, en général, la richesse spécifique augmentait avec l'hétérogénéité de l'environnement : elle augmentait avec le nombre de types d'habitats et diminuait avec l'agrégation spatiale de ces habitats. Ces effets ont été observés à toutes les échelles mais leur nature variait en fonction de l'échelle, suggérant une modification des mécanismes. Dans un deuxième temps, la structure spatiale de la composition en espèces a été décomposée en relation avec 20 variables environnementales et 11 traits d'espèces. Nous avons utilisé la technique de partition de la variation et un descripteur spatial, récemment développé, donnant accès à une large gamme d'échelles spatiales. Nos résultats ont montré que la structure spatiale de la composition en espèces végétales était principalement liée à la topographie, aux échelles les plus grossières, et à la disponibilité en lumière, aux échelles les plus fines. La fraction non-environnementale de la variation spatiale de la composition spécifique avait une relation complexe avec plusieurs traits d'espèces suggérant un lien avec des processus biologiques tels que la dispersion, dépendant de l'échelle spatiale. Dans un dernier temps, nous avons testé, à plusieurs échelles spatiales, les relations entre trois composantes de la biodiversité : la richesse spécifique totale d'un échantillon (diversité gamma), la richesse spécifique moyenne (diversité alpha), mesurée sur des sous-échantillons, et les différences de composition spécifique entre les sous-échantillons (diversité beta). Les relations deux à deux entre les diversités alpha, beta et gamma ne suivaient pas les relations attendues, tout du moins à certaines échelles spatiales. Plusieurs de ces relations étaient fortement dépendantes de l'échelle. Nos résultats ont mis en évidence l'importance du rapport d'échelle (rapport entre la taille de l'échantillon et du sous-échantillon) lors de l'étude des patrons spatiaux de biodiversité. Ainsi, cette étude offre un nouvel aperçu des patrons spatiaux de biodiversité végétale et des mécanismes potentiels permettant la coexistence des espèces. Nos résultats suggèrent que les patrons de biodiversité ne peuvent être expliqués par une seule théorie, mais plutôt par une combinaison de théories. Ils ont également mis en évidence le rôle essentiel joué par la structure spatiale dans la détermination de la biodiversité, quelque soit le composant de la biodiversité considéré. Enfin, cette étude souligne l'importance de prendre en compte plusieurs échelles spatiales et différents constituants de l'échelle spatiale pour toute étude relative à la diversité spécifique. Abstract The world-wide loss of biodiversity at all scales has become a matter of urgent concern, and improving our understanding of local drivers of biodiversity in natural and anthropogenic ecosystems is now crucial for conservation. The main objective of this study was to further our comprehension of the driving forces controlling biodiversity patterns in a complex and diverse ecosystem of high conservation value, wooded pastures. Spatial pattern and scale are central to several ecological theories, and it is increasingly recognized that they must be taken -into consideration when studying biodiversity patterns. However, few hypotheses developed from simulations or theoretical studies have been tested using field data, and the evolution of biodiversity patterns with different scale components remains largely unknown. We test several such hypotheses and explore spatial patterns of biodiversity in a multi-scale context and using different measures of biodiversity (species richness and composition), with field data. Data were collected using a hierarchical sampling design. We first tested the simple hypothesis that species richness, the number of species in a given area, is related to environmental heterogeneity at all scales. We decomposed environmental heterogeneity into two parts: the variability of environmental conditions and its spatial configuration. We showed that species richness generally increased with environmental heterogeneity: species richness increased with increasing number of habitat types and with decreasing spatial aggregation of those habitats. Effects occurred at all scales but the nature of the effect changed with scale, suggesting a change in underlying mechanisms. We then decomposed the spatial structure of species composition in relation to environmental variables and species traits using variation partitioning and a recently developed spatial descriptor, allowing us to capture a wide range of spatial scales. We showed that the spatial structure of plant species composition was related to topography at the coarsest scales and insolation at finer scales. The non-environmental fraction of the spatial variation in species composition had a complex relationship with several species traits, suggesting a scale-dependent link to biological processes, particularly dispersal. Finally, we tested, at different spatial scales, the relationships between different components of biodiversity: total sample species richness (gamma diversity), mean species .richness (alpha diversity), measured in nested subsamples, and differences in species composition between subsamples (beta diversity). The pairwise relationships between alpha, beta and gamma diversity did not follow the expected patterns, at least at certain scales. Our result indicated a strong scale-dependency of several relationships, and highlighted the importance of the scale ratio when studying biodiversity patterns. Thus, our results bring new insights on the spatial patterns of biodiversity and the possible mechanisms allowing species coexistence. They suggest that biodiversity patterns cannot be explained by any single theory proposed in the literature, but a combination of theories is sufficient. Spatial structure plays a crucial role for all components of biodiversity. Results emphasize the importance of considering multiple spatial scales and multiple scale components when studying species diversity.

Holism and structural realism

We first introduce structural realism as a position in the metaphysics of science, pointing out the way in which this position replaces intrinsic properties with relations so that it amounts to a holistic in contrast to an atomistic metaphysics. We argue in favour of a moderate version of structural realism that puts objects and relations on the same ontological footing and assess the general philosophical arguments for this position. The second section shows how structural realism gains support from quantum physics. The third section explains how structural realism can be applied to the metaphysics of space-time.

Holism and structural realism

We first introduce structural realism as a position in the metaphysics of science, pointing out the way in which this position replaces intrinsic properties with relations so that it amounts to a holistic in contrast to an atomistic metaphysics. We argue in favour of a moderate version of structural realism that puts objects and relations on the same ontological footing and assess the general philosophical arguments for this position. The second section shows how structural realism gains support from quantum physics. The third section explains how structural realism can be applied to the metaphysics of space-time.

Contribution of electrostatic interactions, compactness and quaternary structure to protein thermostability: lessons from structural genomics of Thermotoga maritima.

Studies of the structural basis of protein thermostability have produced a confusing picture. Small sets of proteins have been analyzed from a variety of thermophilic species, suggesting different structural features as responsible for protein thermostability. Taking advantage of the recent advances in structural genomics, we have compiled a relatively large protein structure dataset, which was constructed very carefully and selectively; that is, the dataset contains only experimentally determined structures of proteins from one specific organism, the hyperthermophilic bacterium Thermotoga maritima, and those of close homologs from mesophilic bacteria. In contrast to the conclusions of previous studies, our analyses show that oligomerization order, hydrogen bonds, and secondary structure play minor roles in adaptation to hyperthermophily in bacteria. On the other hand, the data exhibit very significant increases in the density of salt-bridges and in compactness for proteins from T.maritima. The latter effect can be measured by contact order or solvent accessibility, and network analysis shows a specific increase in highly connected residues in this thermophile. These features account for changes in 96% of the protein pairs studied. Our results provide a clear picture of protein thermostability in one species, and a framework for future studies of thermal adaptation.

Structural abnormalities in the thalamus of migraineurs with aura: a multiparametric study at 3 T.

BACKGROUND AND OBJECTIVES: The thalamus exerts a pivotal role in pain processing and cortical excitability control, and migraine is characterized by repeated pain attacks and abnormal cortical habituation to excitatory stimuli. This work aimed at studying the microstructure of the thalamus in migraine patients using an innovative multiparametric approach at high-field magnetic resonance imaging (MRI). DESIGN: We examined 37 migraineurs (22 without aura, MWoA, and 15 with aura, MWA) as well as 20 healthy controls (HC) in a 3-T MRI equipped with a 32-channel coil. We acquired whole-brain T1 relaxation maps and computed magnetization transfer ratio (MTR), generalized fractional anisotropy, and T2* maps to probe microstructural and connectivity integrity and to assess iron deposition. We also correlated the obtained parametric values with the average monthly frequency of migraine attacks and disease duration. RESULTS: T1 relaxation time was significantly shorter in the thalamus of MWA patients compared with MWoA (P < 0.001) and HC (P ≤ 0.01); in addition, MTR was higher and T2* relaxation time was shorter in MWA than in MWoA patients (P < 0.05, respectively). These data reveal broad microstructural alterations in the thalamus of MWA patients compared with MWoA and HC, suggesting increased iron deposition and myelin content/cellularity. However, MWA and MWoA patients did not show any differences in the thalamic nucleus involved in pain processing in migraine. CONCLUSIONS: There are broad microstructural alterations in the thalamus of MWA patients that may underlie abnormal cortical excitability control leading to cortical spreading depression and visual aura.