Variable responses of hawkmoths to nectar-depleted plants in two native Petunia axillaris (Solanaceae) populations

Pollination success of deceptive orchids is affected by the density and distribution of nectar providing plant species and overall plant density. Here we extended the framework of how plant density can affect pollination to examine how it may promote the success of plant intraspecific cheaters. We compared hawkmoth behaviour in two native populations of Petunia axillaris, where we simultaneously offered rewarding and manually depleted P. axillaris. We asked whether pollinator foraging strategies change as a function of plant density and whether such changes may differentially affect nectarless plants. We observed the first choice and number of flowers visited by pollinators and found that in the dense population, pollinators visited more flowers on rewarding plants than on nectar-depleted plants. In the sparse population, such discrimination was absent. As we found no differences in nectar volume between plants of the two populations, the observed differences in plant density may be temporal. We reason that if differences were more permanent, an equivalent of the remote habitat hypothesis prevails: in a sparse population, cheating plants benefit from the absence of inter- and intraspecific competitors because pollinators tend to visit all potential resources. In a denser population, a pollinator's optimal foraging strategy involves more selectivity. This would cause between-plant competition for pollinators in a pollinator-limited context, which applies to most hawkmoth-pollinated systems. We propose that nectar-provisioning of plants can be density-dependant, with cheaters able to persist in low density area

Variable responses of hawkmoths to nectar-depleted plants in two native Petunia axillaris (Solanaceae) populations

Abstract Pollination success of deceptive orchids is affected by the density and distribution of nectar providing plant species and overall plant density. Here we extended the framework of how plant density can affect pollination to examine how it may promote the success of plant intraspecific cheaters. We compared hawkmoth behaviour in two native populations of Petunia axillaris, where we simultaneously offered rewarding and manually depleted P. axillaris. We asked whether pollinator foraging strategies change as a function of plant density and whether such changes may differentially affect nectarless plants. We observed the first choice and number of flowers visited by pollinators and found that in the dense population, pollinators visited more flowers on rewarding plants than on nectar-depleted plants. In the sparse population, such discrimination was absent. As we found no differences in nectar volume between plants of the two populations, the observed differences in plant density may be temporal. We reason that if differences were more permanent, an equivalent of the remote habitat hypothesis prevails: in a sparse population, cheating plants benefit from the absence of inter-and intraspecific competitors because pollinators tend to visit all potential resources. In a denser population, a pollinator's optimal foraging strategy involves more selectivity. This would cause between-plant competition for pollinators in a pollinator-limited context, which applies to most hawkmoth-pollinated systems. We propose that nectar-provisioning of plants can be density-dependant, with cheaters able to persist in low density areas

RNF12 X-linked intellectual disability mutations disrupt E3 ligase activity and neural differentiation

Summary: X-linked intellectual disability (XLID) is a heterogeneous syndrome affecting mainly males. Human genetics has identified >100 XLID genes, although the molecular and developmental mechanisms underpinning this disorder remain unclear. Here, we employ an embryonic stem cell model to explore developmental functions of a recently identified XLID gene, the RNF12/RLIM E3 ubiquitin ligase. We show that RNF12 catalytic activity is required for proper stem cell maintenance and neural differentiation, and this is disrupted by patient-associated XLID mutation. We further demonstrate that RNF12 XLID mutations specifically impair ubiquitylation of developmentally relevant substrates. XLID mutants disrupt distinct RNF12 functional modules by either inactivating the catalytic RING domain or interfering with a distal regulatory region required for efficient ubiquitin transfer. Our data thereby uncover a key function for RNF12 E3 ubiquitin ligase activity in stem cell and neural development and identify mechanisms by which this is disrupted in intellectual disability. : Bustos et al. show that the RNF12 E3 ubiquitin ligase regulates stem cell maintenance and neuronal differentiation. They demonstrate that RNF12/RLIM mutations identified in X-linked intellectual disability patients disrupt regions required for catalytic activity, which leads to compromised stem cell maintenance and abnormal neural differentiation. Keywords: ubiquitin, protein ubiquitylation, E3 ubiquitin ligase, proteasomal degradation, RNF12/RLIM, intellectual disability, X-linked intellectual disability, embryonic stem cells, neural differentiatio

Host taxon-derived Sarcoptes mite in European wild animals revealed by microsatellite markers

Ten markers specific to Sarcoptes mites were used in applying microsatellite genotyping to individual Sarcoptes mites collected in three European countries from 15 wild mammal populations belonging to 10 host species. The results showed that geographical separation had real biological significance for the definition of mite sub-populations, and that the degree of genetic exchange occurring between mites from different localities was apparently related to the geographical distance between locations. Wild host-derived mite populations were found to be clustered into three main groups: herbivore-, carnivore- and omnivore-derived Sarcoptes populations, with the omnivore-derived group located halfway between the herbivore- and carnivore-derived Sarcoptes populations. The separation between these three mite groups was better supported than the geographical separations; nevertheless, a kind of sub-clustering was detected within each of these three groups that separates mite populations into their geographical localities (countries). The lack of gene flow between Sarcoptes populations may have improved parasitic adaptations and led to what we refer to as a host-taxon-derived (carnivore host-, herbivore host- and omnivore host-derived) Sarcoptes mite found on European wild animals. Our results demonstrate that Sarcoptes is not a single panmictic population, even within each geographical location. This finding will have important ramifications for the study of the genetic structure of populations, life cycles, diagnosis and the monitoring protocols of the ubiquitous Sarcoptes mite, and could thus contribute to a better understanding of its associated epidemiology, which is of pivotal interest for wildlife biological conservation. © 2010 Elsevier Ltd. All rights reserved.Peer Reviewe

Synthesis and crystal structure of 1,4,10,13-tetraoxa-7,16-diazoniumcyclo-octadecane bis(4-chloro-2-methyl-phenoxyacetate)

The title compound was prepared by the reaction of 1,4,10,13-tetraoxa-7,16-diazacyclo-octadecane with 4-chloro-2-methyl-phenoxyacetic acid in a ratio of 1:2. The structure has been proved by the data of elemental analysis, IR spectroscopy, NMR (1H, 13C) technique and by X-ray diffraction analysis. Intermolecular hydrogen bonds between the azonium protons and oxygen atoms of the carboxylate groups were found. Immunoactive properties of the title compound have been screened. The compound has the ability to suppress spontaneous and Con A-stimulated cell proliferation in vitro and therefore can be considered as immunodepressant

The Lipopolysaccharide Core of Brucella abortus Acts as a Shield Against Innate Immunity Recognition

Innate immunity recognizes bacterial molecules bearing pathogen-associated molecular patterns to launch inflammatory responses leading to the activation of adaptive immunity. However, the lipopolysaccharide (LPS) of the gram-negative bacterium Brucella lacks a marked pathogen-associated molecular pattern, and it has been postulated that this delays the development of immunity, creating a gap that is critical for the bacterium to reach the intracellular replicative niche. We found that a B. abortus mutant in the wadC gene displayed a disrupted LPS core while keeping both the LPS O-polysaccharide and lipid A. In mice, the wadC mutant induced proinflammatory responses and was attenuated. In addition, it was sensitive to killing by non-immune serum and bactericidal peptides and did not multiply in dendritic cells being targeted to lysosomal compartments. In contrast to wild type B. abortus, the wadC mutant induced dendritic cell maturation and secretion of pro-inflammatory cytokines. All these properties were reproduced by the wadC mutant purified LPS in a TLR4-dependent manner. Moreover, the core-mutated LPS displayed an increased binding to MD-2, the TLR4 co-receptor leading to subsequent increase in intracellular signaling. Here we show that Brucella escapes recognition in early stages of infection by expressing a shield against recognition by innate immunity in its LPS core and identify a novel virulence mechanism in intracellular pathogenic gram-negative bacteria. These results also encourage for an improvement in the generation of novel bacterial vaccines

Report on the sixth blind test of organic crystal structure prediction methods.

The sixth blind test of organic crystal structure prediction (CSP) methods has been held, with five target systems: a small nearly rigid molecule, a polymorphic former drug candidate, a chloride salt hydrate, a co-crystal and a bulky flexible molecule. This blind test has seen substantial growth in the number of participants, with the broad range of prediction methods giving a unique insight into the state of the art in the field. Significant progress has been seen in treating flexible molecules, usage of hierarchical approaches to ranking structures, the application of density-functional approximations, and the establishment of new workflows and `best practices' for performing CSP calculations. All of the targets, apart from a single potentially disordered Z' = 2 polymorph of the drug candidate, were predicted by at least one submission. Despite many remaining challenges, it is clear that CSP methods are becoming more applicable to a wider range of real systems, including salts, hydrates and larger flexible molecules. The results also highlight the potential for CSP calculations to complement and augment experimental studies of organic solid forms.The organisers and participants are very grateful to the crystallographers who supplied the candidate structures: Dr. Peter Horton (XXII), Dr. Brian Samas (XXIII), Prof. Bruce Foxman (XXIV), and Prof. Kraig Wheeler (XXV and XXVI). We are also grateful to Dr. Emma Sharp and colleagues at Johnson Matthey (Pharmorphix) for the polymorph screening of XXVI, as well as numerous colleagues at the CCDC for assistance in organising the blind test. Submission 2: We acknowledge Dr. Oliver Korb for numerous useful discussions. Submission 3: The Day group acknowledge the use of the IRIDIS High Performance Computing Facility, and associated support services at the University of Southampton, in the completion of this work. We acknowledge funding from the EPSRC (grants EP/J01110X/1 and EP/K018132/1) and the European Research Council under the European Union’s Seventh Framework Programme (FP/2007-2013)/ERC through grant agreements n. 307358 (ERC-stG- 2012-ANGLE) and n. 321156 (ERC-AG-PE5-ROBOT). Submission 4: I am grateful to Mikhail Kuzminskii for calculations of molecular structures on Gaussian 98 program in the Institute of Organic Chemistry RAS. The Russian Foundation for Basic Research is acknowledged for financial support (14-03-01091). Submission 5: Toine Schreurs provided computer facilities and assistance. I am grateful to Matthew Habgood at AWE company for providing a travel grant. Submission 6: We would like to acknowledge support of this work by GlaxoSmithKline, Merck, and Vertex. Submission 7: The research was financially supported by the VIDI Research Program 700.10.427, which is financed by The Netherlands Organisation for Scientific Research (NWO), and the European Research Council (ERC-2010-StG, grant agreement n. 259510-KISMOL). We acknowledge the support of the Foundation for Fundamental Research on Matter (FOM). Supercomputer facilities were provided by the National Computing Facilities Foundation (NCF). Submission 8: Computer resources were provided by the Center for High Performance Computing at the University of Utah and the Extreme Science and Engineering Discovery Environment (XSEDE), supported by NSF grant number ACI-1053575. MBF and GIP acknowledge the support from the University of Buenos Aires and the Argentinian Research Council. Submission 9: We thank Dr. Bouke van Eijck for his valuable advice on our predicted structure of XXV. We thank the promotion office for TUT programs on advanced simulation engineering (ADSIM), the leading program for training brain information architects (BRAIN), and the information and media center (IMC) at Toyohashi University of Technology for the use of the TUT supercomputer systems and application software. We also thank the ACCMS at Kyoto University for the use of their supercomputer. In addition, we wish to thank financial supports from Conflex Corp. and Ministry of Education, Culture, Sports, Science and Technology. Submission 12: We thank Leslie Leiserowitz from the Weizmann Institute of Science and Geoffrey Hutchinson from the University of Pittsburgh for helpful discussions. We thank Adam Scovel at the Argonne Leadership Computing Facility (ALCF) for technical support. Work at Tulane University was funded by the Louisiana Board of Regents Award # LEQSF(2014-17)-RD-A-10 “Toward Crystal Engineering from First Principles”, by the NSF award # EPS-1003897 “The Louisiana Alliance for Simulation-Guided Materials Applications (LA-SiGMA)”, and by the Tulane Committee on Research Summer Fellowship. Work at the Technical University of Munich was supported by the Solar Technologies Go Hybrid initiative of the State of Bavaria, Germany. Computer time was provided by the Argonne Leadership Computing Facility (ALCF), which is supported by the Office of Science of the U.S. Department of Energy under contract DE-AC02-06CH11357. Submission 13: This work would not have been possible without funding from Khalifa University’s College of Engineering. I would like to acknowledge Prof. Robert Bennell and Prof. Bayan Sharif for supporting me in acquiring the resources needed to carry out this research. Dr. Louise Price is thanked for her guidance on the use of DMACRYS and NEIGHCRYS during the course of this research. She is also thanked for useful discussions and numerous e-mail exchanges concerning the blind test. Prof. Sarah Price is acknowledged for her support and guidance over many years and for providing access to DMACRYS and NEIGHCRYS. Submission 15: The work was supported by the United Kingdom’s Engineering and Physical Sciences Research Council (EPSRC) (EP/J003840/1, EP/J014958/1) and was made possible through access to computational resources and support from the High Performance Computing Cluster at Imperial College London. We are grateful to Professor Sarah L. Price for supplying the DMACRYS code for use within CrystalOptimizer, and to her and her research group for support with DMACRYS and feedback on CrystalPredictor and CrystalOptimizer. Submission 16: R. J. N. acknowledges financial support from the Engineering and Physical Sciences Research Council (EPSRC) of the U.K. [EP/J017639/1]. R. J. N. and C. J. P. acknowledge use of the Archer facilities of the U.K.’s national high-performance computing service (for which access was obtained via the UKCP consortium [EP/K014560/1]). C. J. P. also acknowledges a Leadership Fellowship Grant [EP/K013688/1]. B. M. acknowledges Robinson College, Cambridge, and the Cambridge Philosophical Society for a Henslow Research Fellowship. Submission 17: The work at the University of Delaware was supported by the Army Research Office under Grant W911NF-13-1- 0387 and by the National Science Foundation Grant CHE-1152899. The work at the University of Silesia was supported by the Polish National Science Centre Grant No. DEC-2012/05/B/ST4/00086. Submission 18: We would like to thank Constantinos Pantelides, Claire Adjiman and Isaac Sugden of Imperial College for their support of our use of CrystalPredictor and CrystalOptimizer in this and Submission 19. The CSP work of the group is supported by EPSRC, though grant ESPRC EP/K039229/1, and Eli Lilly. The PhD students support: RKH by a joint UCL Max-Planck Society Magdeburg Impact studentship, REW by a UCL Impact studentship; LI by the Cambridge Crystallographic Data Centre and the M3S Centre for Doctoral Training (EPSRC EP/G036675/1). Submission 19: The potential generation work at the University of Delaware was supported by the Army Research Office under Grant W911NF-13-1-0387 and by the National Science Foundation Grant CHE-1152899. Submission 20: The work at New York University was supported, in part, by the U.S. Army Research Laboratory and the U.S. Army Research Office under contract/grant number W911NF-13-1-0387 (MET and LV) and, in part, by the Materials Research Science and Engineering Center (MRSEC) program of the National Science Foundation under Award Number DMR-1420073 (MET and ES). The work at the University of Delaware was supported by the U.S. Army Research Laboratory and the U.S. Army Research Office under contract/grant number W911NF-13-1- 0387 and by the National Science Foundation Grant CHE-1152899. Submission 21: We thank the National Science Foundation (DMR-1231586), the Government of Russian Federation (Grant No. 14.A12.31.0003), the Foreign Talents Introduction and Academic Exchange Program (No. B08040) and the Russian Science Foundation, project no. 14-43-00052, base organization Photochemistry Center of the Russian Academy of Sciences. Calculations were performed on the Rurik supercomputer at Moscow Institute of Physics and Technology. Submission 22: The computational results presented have been achieved in part using the Vienna Scientific Cluster (VSC). Submission 24: The potential generation work at the University of Delaware was supported by the Army Research Office under Grant W911NF-13-1-0387 and by the National Science Foundation Grant CHE-1152899. Submission 25: J.H. and A.T. acknowledge the support from the Deutsche Forschungsgemeinschaft under the program DFG-SPP 1807. H-Y.K., R.A.D., and R.C. acknowledge support from the Department of Energy (DOE) under Grant Nos. DE-SC0008626. This research used resources of the Argonne Leadership Computing Facility at Argonne National Laboratory, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC02-06CH11357. This research used resources of the National Energy Research Scientific Computing Center, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DEAC02-05CH11231. Additional computational resources were provided by the Terascale Infrastructure for Groundbreaking Research in Science and Engineering (TIGRESS) High Performance Computing Center and Visualization Laboratory at Princeton University.This is the final version of the article. It first appeared from Wiley via http://dx.doi.org/10.1107/S2052520616007447