On the success of generalized food deception in orchids : the role of sympatric rewarding species and pollinators

Résumé : La production de nectar assure aux plantes entomophiles un important succès reproducteur. Malgré cela, de nombreuses espèces d'orchidées ne produisent pas de nectar. La majorité de ces orchidées dites trompeuses exploitent simplement l'instinct des pollinisateurs généralistes, qui les pousse à chercher du nectar dans les fleurs. Afin d'optimiser la récolte de nectar, les pollinisateurs apprennent à différencier les fleurs trompeuses des nectarifères, et à concentrer leurs visites sur ces dernières, au détriment des plantes trompeuses. Chez les orchidées non autogames, la reproduction est assurée uniquement par les pollinisateurs. L'apprentissage des pollinisateurs a donc un impact négatif sur la reproduction des orchidées trompeuses. Cependant, les caractéristiques d'une espèce trompeuse et des espèces nectarifères au sein d'une communauté végétale peuvent affecter l'apprentissage et le taux de visite des pollinisateurs aux plantes trompeuses. J'ai réalisé des expériences en milieu naturel et en milieu contrôlé, pour déterminer si les caractéristiques florales, spatiales et temporelles des communautés affectent le taux de visite et le succès reproducteur de plantes trompeuses. Une agrégation spatiale élevée des plantes trompeuses et des plantes nectarifères diminue le succès reproducteur des plantes trompeuses. De plus, les pollinisateurs visitent plus souvent l'espèce trompeuse Iorsque ses fleurs sont de couleur similaire à celles de l'espèce nectarifère. Cet effet bénéfique de la similarité pour la couleur des fleurs s'accentue si les deux espèces sont mélangées et proches spatialement, ou si l'espèce trompeuse fleurit après l'espèce nectarifère. Enfin, le comportement des pollinisateurs n'est pas tout de suite affecté lorsque les caractéristiques de la communauté changent. Les caractéristiques des communautés végétales affectent donc la reproduction des espèces trompeuses. Bien que L'absence de coûts associés à la production de nectar, l'exportation efficace de pollen et la production de graines de qualité dont bénéficient les orchidées trompeuses favorisent Ieur maintien, les caractéristiques de la communauté peuvent aussi y contribuer. Mon étude fournit donc une explication alternative et complémentaire au maintien des orchidées trompeuses. Je conclus par une discussion des implications possibles de ces résultats sur le maintien et l'évolution des orchidées trompeuses, en tenant compte de la dynamique des caractéristiques des communautés végétales naturelles. Abstract : Despite the importance of producing food to ensure a high reproductive success, many orchid species lack such rewards. The majority of deceptive orchids simply exploit the instinctive food-foraging behaviour of generalist pollinators. This strategy is termed generalized food deception. To optimize their foraging efficiency, pollinators can learn to discriminate deceptive from rewarding flowers and to focus their visits to the rewarding plants, to the disadvantage of the deceptive plants. Because the reproductive success of non-autogamous orchids entirely relies on pollinator visitation rate, pollinator learning decreases the reproductive success of deceptive orchids. However, the characteristics of deceptive and rewarding plants within a community may affect pollinator learning and visitation rate to a deceptive orchid. Therefore, the biological characteristics of natural plant communities may be crucial to the maintenance of generalized food deceptive orchids. My study focused on the floral, spatial and temporal characteristics of plant communities. I used both in and ex sitar experiments to investigate whether these characteristics influence pollinator visitation rates and the reproductive success of deceptive orchids. A high spatial aggregation of both deceptive and rewarding species decreased the reproductive success of the deceptive species. Also, being of similar flower colour to rewarding sympatric species increased pollinator visitation rates to a deceptive species. The beneficial effect of flower colour similarity was even more pronounced when both species were spatially closely mingled or when the deceptive species flowered after the rewarding species. Finally, pollinator behaviour was unaffected in the short term by a change in the characteristics of plant communities, indicating that pollinators need time to learn under new conditions. Thus, the characteristics of plant communities may crucially affect the reproductive success of deceptive orchids. Although the absence of costs associated with nectar production, the efficient pollen export and the high seed quality of deceptive orchids may favour their maintenance, the characteristics of plant communities may also contribute to it. Therefore, my study provides an alternative yet complementary explanation to the maintenance of generalized food deceptive orchids in natural populations. I discuss the possible implications for the maintenance and the evolution of generalized food deceptive orchids with regards to the floral and temporal dynamics of natural plant communities.

Fourier transform convolution integrals applied to generalized Born molecular volume.

Generalized Born methods are currently among the solvation models most commonly used for biological applications. We reformulate the generalized Born molecular volume method initially described by (Lee et al, 2003, J Phys Chem, 116, 10606; Lee et al, 2003, J Comp Chem, 24, 1348) using fast Fourier transform convolution integrals. Changes in the initial method are discussed and analyzed. Finally, the method is extensively checked with snapshots from common molecular modeling applications: binding free energy computations and docking. Biologically relevant test systems are chosen, including 855-36091 atoms. It is clearly demonstrated that, precision-wise, the proposed method performs as good as the original, and could better benefit from hardware accelerated boards.

Estimating parameters for generalized mass action models using constraint propagation.

As modern molecular biology moves towards the analysis of biological systems as opposed to their individual components, the need for appropriate mathematical and computational techniques for understanding the dynamics and structure of such systems is becoming more pressing. For example, the modeling of biochemical systems using ordinary differential equations (ODEs) based on high-throughput, time-dense profiles is becoming more common-place, which is necessitating the development of improved techniques to estimate model parameters from such data. Due to the high dimensionality of this estimation problem, straight-forward optimization strategies rarely produce correct parameter values, and hence current methods tend to utilize genetic/evolutionary algorithms to perform non-linear parameter fitting. Here, we describe a completely deterministic approach, which is based on interval analysis. This allows us to examine entire sets of parameters, and thus to exhaust the global search within a finite number of steps. In particular, we show how our method may be applied to a generic class of ODEs used for modeling biochemical systems called Generalized Mass Action Models (GMAs). In addition, we show that for GMAs our method is amenable to the technique in interval arithmetic called constraint propagation, which allows great improvement of its efficiency. To illustrate the applicability of our method we apply it to some networks of biochemical reactions appearing in the literature, showing in particular that, in addition to estimating system parameters in the absence of noise, our method may also be used to recover the topology of these networks.

Robust Estimators of the Generalized Log-Gamma Distribution

We propose robust estimators of the generalized log-gamma distribution and, more generally, of location-shape-scale families of distributions. A (weighted) Q tau estimator minimizes a tau scale of the differences between empirical and theoretical quantiles. It is n(1/2) consistent; unfortunately, it is not asymptotically normal and, therefore, inconvenient for inference. However, it is a convenient starting point for a one-step weighted likelihood estimator, where the weights are based on a disparity measure between the model density and a kernel density estimate. The one-step weighted likelihood estimator is asymptotically normal and fully efficient under the model. It is also highly robust under outlier contamination. Supplementary materials are available online.

PRPF mutations are associated with generalized defects in spliceosome formation and pre-mRNA splicing in patients with retinitis pigmentosa.

Proteins PRPF31, PRPF3 and PRPF8 (RP-PRPFs) are ubiquitously expressed components of the spliceosome, a macromolecular complex that processes nearly all pre-mRNAs. Although these spliceosomal proteins are conserved in eukaryotes and are essential for survival, heterozygous mutations in human RP-PRPF genes lead to retinitis pigmentosa, a hereditary disease restricted to the eye. Using cells from patients with 10 different mutations, we show that all clinically relevant RP-PRPF defects affect the stoichiometry of spliceosomal small nuclear RNAs (snRNAs), the protein composition of tri-small nuclear ribonucleoproteins and the kinetics of spliceosome assembly. These mutations cause inefficient splicing in vitro and affect constitutive splicing ex-vivo by impairing the removal of at least 9% of endogenously expressed introns. Alternative splicing choices are also affected when RP-PRPF defects are present. Furthermore, we show that the steady-state levels of snRNAs and processed pre-mRNAs are highest in the retina, indicating a particularly elevated splicing activity. Our results suggest a role for PRPFs defects in the etiology of PRPF-linked retinitis pigmentosa, which appears to be a truly systemic splicing disease. Although these mutations cause widespread and important splicing defects, they are likely tolerated by the majority of human tissues but are critical for retinal cell survival.

Risk factors of postictal generalized EEG suppression in generalized convulsive seizures.

OBJECTIVE: To identify the clinical determinants of occurrence of postictal generalized EEG suppression (PGES) after generalized convulsive seizures (GCS). METHODS: We reviewed the video-EEG recordings of 417 patients included in the REPO2MSE study, a multicenter prospective cohort study of patients with drug-resistant focal epilepsy. According to ictal semiology, we classified GCS into 3 types: tonic-clonic GCS with bilateral and symmetric tonic arm extension (type 1), clonic GCS without tonic arm extension or flexion (type 2), and GCS with unilateral or asymmetric tonic arm extension or flexion (type 3). Association between PGES and person-specific or seizure-specific variables was analyzed after correction for individual effects and the varying number of seizures. RESULTS: A total of 99 GCS in 69 patients were included. Occurrence of PGES was independently associated with GCS type (p < 0.001) and lack of early administration of oxygen (p < 0.001). Odds ratio (OR) for GCS type 1 in comparison with GCS type 2 was 66.0 (95% confidence interval [CI 5.4-801.6]). In GCS type 1, risk of PGES was significantly increased when the seizure occurred during sleep (OR 5.0, 95% CI 1.2-20.9) and when oxygen was not administered early (OR 13.4, 95% CI 3.2-55.9). CONCLUSION: The risk of PGES dramatically varied as a function of GCS semiologic characteristics. Whatever the type of GCS, occurrence of PGES was prevented by early administration of oxygen.