61 research outputs found

    Logistic regression models to predict solvent accessible residues using sequence- and homology-based qualitative and quantitative descriptors applied to a domain-complete X-ray structure learning set

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    A working example of relative solvent accessibility (RSA) prediction for proteins is presented. Novel logistic regression models with various qualitative descriptors that include amino acid type and quantitative descriptors that include 20- and six-term sequence entropy have been built and validated. A domain-complete learning set of over 1300 proteins is used to fit initial models with various sequence homology descriptors as well as query residue qualitative descriptors. Homology descriptors are derived from BLASTp sequence alignments, whereas the RSA values are determined directly from the crystal structure. The logistic regression models are fitted using dichotomous responses indicating buried or accessible solvent, with binary classifications obtained from the RSA values. The fitted models determine binary predictions of residue solvent accessibility with accuracies comparable to other less computationally intensive methods using the standard RSA threshold criteria 20 and 25% as solvent accessible. When an additional non-homology descriptor describing Lobanov–Galzitskaya residue disorder propensity is included, incremental improvements in accuracy are achieved with 25% threshold accuracies of 76.12 and 74.45% for the Manesh-215 and CASP(8+9) test sets, respectively. Moreover, the described software and the accompanying learning and validation sets allow students and researchers to explore the utility of RSA prediction with simple, physically intuitive models in any number of related applications

    Interstellar deuteroammonia. Tracing physical conditions in dense, cold interstellar medium

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    International audienceClose to 30 deuterated molecules have now been detected in the ISM, including doubly-deuterated species D2H+, ND2H, D2CO, CHD2OH, D2S, and D2CS, as well as triply-deuterated ammonia and methanol. We review the current understanding of depletion and deuteration processes in cold, dense interstellar medium (ISM) and discuss the utility of deuteroammonia as a tracer of the physical conditions and kinematics of cold, dense gas

    Leaf metabolic signatures induced by real and simulated herbivory in black mustard (Brassica nigra)

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    Introduction The oxylipin methyl jasmonate (MeJA) is a plant hormone active in response signalling and defence against herbivores. Although MeJA is applied experimentally to mimic herbivory and induce plant defences, its downstream effects on the plant metabolome are largely uncharacterized, especially in the context of primary growth and tissue-specificity of the response. Objectives We investigated the effects of MeJA-simulated and real caterpillar herbivory on the foliar metabolome of the wild plant Brassica nigra and monitored the herbivore-induced responses in relation to leaf ontogeny. Methods As single or multiple herbivory treatments, MeJA- and mock-sprayed plants were consecutively exposed to caterpillars or left untreated. Gas chromatography (GC) and liquid chromatography (LC) time-of-flight mass-spectrometry (TOF-MS) were combined to analyse foliar compounds, including central primary and specialized defensive plant metabolites. Results Plant responses were stronger in young leaves, which simultaneously induced higher chlorophyll levels. Both MeJA and caterpillar herbivory induced similar, but not identical, accumulation of tricarboxylic acids (TCAs), glucosinolates (GSLs) and phenylpropanoids (PPs), but only caterpillar feeding led to depletion of amino acids. MeJA followed by caterpillars caused higher induction of defence compounds, including a three-fold increase in the major defence compound allyl-GSL (sinigrin). When feeding on MeJA-treated plants, caterpillars gained less weight indicative of the reduced host-plant quality and enhanced resistance. Conclusions The metabolomics approach showed that plant responses induced by herbivory extend beyond the regulation of defence metabolism and are tightly modulated throughout leaf development. This leads to a new understanding of the plant metabolic potential that can be exploited for future plant protection strategies

    Leaf metabolic signatures induced by real and simulated herbivory in black mustard (Brassica nigra)

    Get PDF
    Introduction The oxylipin methyl jasmonate (MeJA) is a plant hormone active in response signalling and defence against herbivores. Although MeJA is applied experimentally to mimic herbivory and induce plant defences, its downstream effects on the plant metabolome are largely uncharacterized, especially in the context of primary growth and tissue-specificity of the response. Objectives We investigated the effects of MeJA-simulated and real caterpillar herbivory on the foliar metabolome of the wild plant Brassica nigra and monitored the herbivore-induced responses in relation to leaf ontogeny. Methods As single or multiple herbivory treatments, MeJA- and mock-sprayed plants were consecutively exposed to caterpillars or left untreated. Gas chromatography (GC) and liquid chromatography (LC) time-of-flight mass-spectrometry (TOF-MS) were combined to analyse foliar compounds, including central primary and specialized defensive plant metabolites. Results Plant responses were stronger in young leaves, which simultaneously induced higher chlorophyll levels. Both MeJA and caterpillar herbivory induced similar, but not identical, accumulation of tricarboxylic acids (TCAs), glucosinolates (GSLs) and phenylpropanoids (PPs), but only caterpillar feeding led to depletion of amino acids. MeJA followed by caterpillars caused higher induction of defence compounds, including a three-fold increase in the major defence compound allyl-GSL (sinigrin). When feeding on MeJA-treated plants, caterpillars gained less weight indicative of the reduced host-plant quality and enhanced resistance. Conclusions The metabolomics approach showed that plant responses induced by herbivory extend beyond the regulation of defence metabolism and are tightly modulated throughout leaf development. This leads to a new understanding of the plant metabolic potential that can be exploited for future plant protection strategies
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