Phylogeny of the Infraorder Pentatomomorpha Based on Fossil and Extant Morphology, with Description of a New Fossil Family from China

<div><h3>Background</h3><p>An extinct new family of Pentatomomorpha, Venicoridae Yao, Ren & Cai <b>fam. nov.</b>, with 2 new genera and 2 new species (<em>Venicoris solaris</em> Yao, Ren & Rider <b>gen. & sp. nov.</b> and <em>Clavaticoris zhengi</em> Yao, Ren & Cai <b>gen. & sp. nov.</b>) are described from the Early Cretaceous Yixian Formation in Northeast China.</p> <h3>Methodology/Principal Findings</h3><p>A cladistic analysis based on a combination of fossil and extant morphological characters clarified the phylogenetic status of the new family and has allowed the reconstruction of intersuperfamily and interfamily relationships within the Infraorder Pentatomomorpha. The fossil record and diversity of Pentatomomorpha during the Mesozoic is discussed.</p> <h3>Conclusions/Significance</h3><p>Pentatomomorpha is a monophyletic group; Aradoidea and the Trichophora are sister groups; these fossils belong to new family, treated as the sister group of remainder of Trichophora; Pentatomoidea is a monophyletic group; Piesmatidae should be separated as a superfamily, Piesmatoidea. Origin time of Pentatomomorpha should be tracked back to the Middle or Early Triassic.</p> </div

'Unite and conquer': enhanced prediction of protein subcellular localization by integrating multiple specialized tools

<p>Abstract</p> <p>Background</p> <p>Knowing the subcellular location of proteins provides clues to their function as well as the interconnectivity of biological processes. Dozens of tools are available for predicting protein location in the eukaryotic cell. Each tool performs well on certain data sets, but their predictions often disagree for a given protein. Since the individual tools each have particular strengths, we set out to integrate them in a way that optimally exploits their potential. The method we present here is applicable to various subcellular locations, but tailored for predicting whether or not a protein is localized in mitochondria. Knowledge of the mitochondrial proteome is relevant to understanding the role of this organelle in global cellular processes.</p> <p>Results</p> <p>In order to develop a method for enhanced prediction of subcellular localization, we integrated the outputs of available localization prediction tools by several strategies, and tested the performance of each strategy with known mitochondrial proteins. The accuracy obtained (up to 92%) surpasses by far the individual tools. The method of integration proved crucial to the performance. For the prediction of mitochondrion-located proteins, integration via a two-layer decision tree clearly outperforms simpler methods, as it allows emphasis of biologically relevant features such as the mitochondrial targeting peptide and transmembrane domains.</p> <p>Conclusion</p> <p>We developed an approach that enhances the prediction accuracy of mitochondrial proteins by uniting the strength of specialized tools. The combination of machine-learning based integration with biological expert knowledge leads to improved performance. This approach also alleviates the conundrum of how to choose between conflicting predictions. Our approach is easy to implement, and applicable to predicting subcellular locations other than mitochondria, as well as other biological features. For a trial of our approach, we provide a webservice for mitochondrial protein prediction (named YimLOC), which can be accessed through the AnaBench suite at http://anabench.bcm.umontreal.ca/anabench/. The source code is provided in the Additional File <supplr sid="S2">2</supplr>.</p> <suppl id="S2"> <title> <p>Additional file 2</p> </title> <text> <p>This file contains scripts for the online server YimLOC. Please note that there scripts only codes for the ready-to-use STACK-mem-DT described in the main text. The scripts do not provide the training process.</p> </text> <file name="1471-2105-8-420-S2.pdf"> <p>Click here for file</p> </file> </suppl

Transcriptional responses underlying the hormetic and detrimental effects of the plant secondary metabolite gossypol on the generalist herbivore Helicoverpa armigera

<p>Abstract</p> <p>Background</p> <p>Hormesis is a biphasic biological response characterized by the stimulatory effect at relatively low amounts of chemical compounds which are otherwise detrimental at higher concentrations. A hormetic response in larval growth rates has been observed in cotton-feeding insects in response to increasing concentrations of gossypol, a toxic metabolite found in the pigment glands of some plants in the family Malvaceae. We investigated the developmental effect of gossypol in the cotton bollworm, <it>Helicoverpa armigera</it>, an important heliothine pest species, by exposing larvae to different doses of this metabolite in their diet. In addition, we sought to determine the underlying transcriptional responses to different gossypol doses.</p> <p>Results</p> <p>Larval weight gain, pupal weight and larval development time were measured in feeding experiments and a hormetic response was seen for the first two characters. On the basis of net larval weight gain responses to gossypol, three concentrations (0%, 0.016% and 0.16%) were selected for transcript profiling in the gut and the rest of the body in a two-color double reference design microarray experiment. Hormesis could be observed at the transcript level, since at the low gossypol dose, genes involved in energy acquisition such as β-fructofuranosidases were up-regulated in the gut, and genes involved in cell adhesion were down-regulated in the body. Genes with products predicted to be integral to the membrane or associated with the proteasome core complex were significantly affected by the detrimental dose treatment in the body. Oxidoreductase activity-related genes were observed to be significantly altered in both tissues at the highest gossypol dose.</p> <p>Conclusions</p> <p>This study represents the first transcriptional profiling approach investigating the effects of different concentrations of gossypol in a lepidopteran species. <it>H. armigera</it>'s transcriptional response to gossypol feeding is tissue- and dose-dependent and involves diverse detoxifying mechanisms not only to alleviate direct effects of gossypol but also indirect damage such as pH disturbance and oxygen radical formation. Genes discovered through this transcriptional approach may be additional candidates for understanding gossypol detoxification and coping with gossypol-induced stress. In a generalist herbivore that has evolved transcriptionally-regulated responses to a variety of different plant compounds, hormesis may be due to a lower induction threshold of growth-promoting, stress-coping responses and a higher induction threshold of detoxification pathways that are costly and cause collateral damage to the cell.</p