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      Insights into the Evolution of the CSP Gene Family through the Integration of Evolutionary Analysis and Comparative Protein Modeling

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      1 , 2 , * , 2 , 3 , 4
      PLoS ONE
      Public Library of Science

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          Abstract

          Insect chemical communication and chemosensory systems rely on proteins coded by several gene families. Here, we have combined protein modeling with evolutionary analysis in order to study the evolution and structure of chemosensory proteins (CSPs) within arthropods and, more specifically, in ants by using the data available from sequenced genomes. Ants and other social insects are especially interesting model systems for the study of chemosensation, as they communicate in a highly complex social context and much of their communication relies on chemicals. Our ant protein models show how this complexity has shaped CSP evolution; the proteins are highly modifiable by their size, surface charge and binding pocket. Based on these findings, we divide ant CSPs into three groups: typical insect CSPs, an ancient 5-helical CSP and hymenopteran CSPs with a small binding pocket, and suggest that these groups likely serve different functions. The hymenopteran CSPs have duplicated repeatedly in individual ant lineages. In these CSPs, positive selection has driven surface charge changes, an observation which has possible implications for the interaction between CSPs and ligands or odorant receptors. Our phylogenetic analysis shows that within the Arthropoda the only highly conserved gene is the ancient 5-helical CSP, which is likely involved in an essential ubiquitous function rather than chemosensation. During insect evolution, the 6-helical CSPs have diverged and perform chemosensory functions among others. Our results contribute to the general knowledge of the structural differences between proteins underlying chemosensation and highlight those protein properties which have been affected by adaptive evolution.

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          Most cited references36

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          Structure validation by Calpha geometry: phi,psi and Cbeta deviation.

          Geometrical validation around the Calpha is described, with a new Cbeta measure and updated Ramachandran plot. Deviation of the observed Cbeta atom from ideal position provides a single measure encapsulating the major structure-validation information contained in bond angle distortions. Cbeta deviation is sensitive to incompatibilities between sidechain and backbone caused by misfit conformations or inappropriate refinement restraints. A new phi,psi plot using density-dependent smoothing for 81,234 non-Gly, non-Pro, and non-prePro residues with B < 30 from 500 high-resolution proteins shows sharp boundaries at critical edges and clear delineation between large empty areas and regions that are allowed but disfavored. One such region is the gamma-turn conformation near +75 degrees,-60 degrees, counted as forbidden by common structure-validation programs; however, it occurs in well-ordered parts of good structures, it is overrepresented near functional sites, and strain is partly compensated by the gamma-turn H-bond. Favored and allowed phi,psi regions are also defined for Pro, pre-Pro, and Gly (important because Gly phi,psi angles are more permissive but less accurately determined). Details of these accurate empirical distributions are poorly predicted by previous theoretical calculations, including a region left of alpha-helix, which rates as favorable in energy yet rarely occurs. A proposed factor explaining this discrepancy is that crowding of the two-peptide NHs permits donating only a single H-bond. New calculations by Hu et al. [Proteins 2002 (this issue)] for Ala and Gly dipeptides, using mixed quantum mechanics and molecular mechanics, fit our nonrepetitive data in excellent detail. To run our geometrical evaluations on a user-uploaded file, see MOLPROBITY (http://kinemage.biochem.duke.edu) or RAMPAGE (http://www-cryst.bioc.cam.ac.uk/rampage). Copyright 2003 Wiley-Liss, Inc.
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            Molecular evolution of the major chemosensory gene families in insects.

            Chemoreception is a crucial biological process that is essential for the survival of animals. In insects, olfaction allows the organism to recognise volatile cues that allow the detection of food, predators and mates, whereas the sense of taste commonly allows the discrimination of soluble stimulants that elicit feeding behaviours and can also initiate innate sexual and reproductive responses. The most important proteins involved in the recognition of chemical cues comprise moderately sized multigene families. These families include odorant-binding proteins (OBPs) and chemosensory proteins (CSPs), which are involved in peripheral olfactory processing, and the chemoreceptor superfamily formed by the olfactory receptor (OR) and gustatory receptor (GR) families. Here, we review some recent evolutionary genomic studies of chemosensory gene families using the data from fully sequenced insect genomes, especially from the 12 newly available Drosophila genomes. Overall, the results clearly support the birth-and-death model as the major mechanism of evolution in these gene families. Namely, new members arise by tandem gene duplication, progressively diverge in sequence and function, and can eventually be lost from the genome by a deletion or pseudogenisation event. Adaptive changes fostered by environmental shifts are also observed in the evolution of chemosensory families in insects and likely involve reproductive, ecological or behavioural traits. Consequently, the current size of these gene families is mainly a result of random gene gain and loss events. This dynamic process may represent a major source of genetic variation, providing opportunities for FUTURE specific adaptations.
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              Function and evolution of a gene family encoding odorant binding-like proteins in a social insect, the honey bee (Apis mellifera).

              The remarkable olfactory power of insect species is thought to be generated by a combinatorial action of two large protein families, G protein-coupled olfactory receptors (ORs) and odorant binding proteins (OBPs). In olfactory sensilla, OBPs deliver hydrophobic airborne molecules to ORs, but their expression in nonolfactory tissues suggests that they also may function as general carriers in other developmental and physiological processes. Here we used bioinformatic and experimental approaches to characterize the OBP-like gene family in a highly social insect, the Western honey bee. Comparison with other insects shows that the honey bee has the smallest set of these genes, consisting of only 21 OBPs. This number stands in stark contrast to the more than 70 OBPs in Anopheles gambiae and 51 in Drosophila melanogaster. In the honey bee as in the two dipterans, these genes are organized in clusters. We show that the evolution of their structure involved frequent intron losses. We describe a monophyletic subfamily of OBPs where the diversification of some amino acids appears to have been accelerated by positive selection. Expression profiling under a wide range of conditions shows that in the honey bee only nine OBPs are antenna-specific. The remaining genes are expressed either ubiquitously or are tightly regulated in specialized tissues or during development. These findings support the view that OBPs are not restricted to olfaction and are likely to be involved in broader physiological functions.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2013
                28 May 2013
                : 8
                : 5
                : e63688
                Affiliations
                [1 ]Department of Biology and Biocenter Oulu, University of Oulu, Oulu, Finland
                [2 ]Department of Biosciences, Centre of Excellence in Biological Interactions, University of Helsinki, Helsinki, Finland
                [3 ]Department of Chemistry, Biotechnology and Food Science, Norwegian University of Life Sciences, Aas, Norway
                [4 ]School of Life Sciences, Arizona State University, Tempe, Arizona, United States of America
                University of Georgia, United States of America
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Conceived and designed the experiments: JK HH. Performed the experiments: JK HH. Analyzed the data: JK HH. Wrote the paper: JK HH.

                Article
                PONE-D-12-39191
                10.1371/journal.pone.0063688
                3665776
                23723994
                c1d4fda1-d3d3-42b7-9570-e374702aaf27
                Copyright @ 2013

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 10 December 2012
                : 5 April 2013
                Page count
                Pages: 11
                Funding
                This work was supported by the Biocenter Oulu Graduate School (J.K.), the Centre of Excellence in Biological Interactions (J.K.) and the Research Council of Norway (#180504 and 191699) (H.H.). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology
                Biochemistry
                Proteins
                Protein Structure
                Computational Biology
                Macromolecular Structure Analysis
                Protein Structure
                Sequence Analysis
                Evolutionary Biology
                Evolutionary Processes
                Adaptation
                Natural Selection
                Comparative Genomics
                Evolutionary Genetics

                Uncategorized
                Uncategorized

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