Publications by authors named "Melisande Blein-Nicolas"

Introduction: A better understanding of the physiological response of silage maize to a mild reduction in nitrogen (N) fertilization and the identification of predictive biochemical markers of N utilization efficiency could contribute to limit the detrimental effect of the overuse of N inputs.

Objectives: We integrated phenotypic and biochemical data to interpret the physiology of maize in response to a mild reduction in N fertilization under agronomic conditions and identify predictive leaf metabolic and proteic markers that could be used to pilot and rationalize N fertilization.

Methods: Eco-physiological, developmental and yield-related traits were measured and complemented with metabolomic and proteomic approaches performed on young leaves of a core panel of 29 European genetically diverse dent hybrids cultivated in the field under non-limiting and reduced N fertilization conditions.

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Water deficit is a major cause of yield loss for maize (), leading to ovary abortion when applied at flowering time. To help understand the mechanisms involved in this phenomenon, the proteome response to water deficit has been analysed in developing ovaries at the silk emergence stage and five days later. Differential analysis, abundance pattern clustering and co-expression networks were performed in order to draw a general picture of the proteome changes all along ovary development and under the effect of water deficit.

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Ion mobility mass spectrometry has become popular in proteomics lately, in particular because the Bruker timsTOF instruments have found significant adoption in proteomics facilities. The Bruker's implementation of the ion mobility dimension generates massive amounts of mass spectrometric data that require carefully designed software both to extract meaningful information and to perform processing tasks at reasonable speed. In a historical move, the Bruker company decided to harness the skills of the scientific software development community by releasing to the public the timsTOF data file format specification.

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Nitrogen is the most limiting nutrient for plants, and it is preferentially absorbed in the form of nitrate by roots, which adapt to nitrate fluctuations by remodelling their architecture. Although core mechanisms of the response to nitrate availability are relatively well-known, signalling events controlling root growth and architecture have not all been identified, in particular in Legumes. However, the developmental effect of nitrate in Legumes is critical since external nitrate not only regulates root architecture but also N-fixing nodule development.

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Background: In proteomics, the interpretation of mass spectra representing peptides carrying multiple complex modifications remains challenging, as it is difficult to strike a balance between reasonable execution time, a limited number of false positives, and a huge search space allowing any number of modifications without a priori. The scientific community needs new developments in this area to aid in the discovery of novel post-translational modifications that may play important roles in disease.

Results: To make progress on this issue, we implemented SpecGlobX (SpecGlob eXTended to eXperimental spectra), a standalone Java application that quickly determines the best spectral alignments of a (possibly very large) list of Peptide-to-Spectrum Matches (PSMs) provided by any open modification search method, or generated by the user.

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Multi-trial genome wide association study of plasticity indices allow to detect QTLs specifically involved in the genotype x water availability interaction. Concerns regarding high maize yield losses due to increasing occurrences of drought events are growing, and breeders are still looking for molecular markers for drought tolerance. However, the genetic determinism of traits in response to drought is highly complex and identification of causal regions is a tremendous task.

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Sunflower is a hybrid crop that is considered moderately drought-tolerant and adapted to new cropping systems required for the agro-ecological transition. Here, we studied the impact of hybridity status (hybrids vs. inbred lines) on the responses to drought at the molecular and eco-physiological level exploiting publicly available datasets.

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Article Synopsis
  • The study investigates how seed germination in Arabidopsis is controlled by environmental factors and phosphoprotein signaling networks.
  • Researchers analyzed the phosphoproteome during the process of imbibition (soaking seeds) under different light conditions, identifying over 10,000 phosphopeptides associated with seed germination.
  • Findings suggest that phosphosignaling plays a crucial role in regulating germination, with significant changes observed in both dormant and non-dormant seeds during early imbibition.
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One of the difficulties encountered in the statistical analysis of metaproteomics data is the high proportion of missing values, which are usually treated by imputation. Nevertheless, imputation methods are based on restrictive assumptions regarding missingness mechanisms, namely "at random" or "not at random". To circumvent these limitations in the context of feature selection in a multi-class comparison, we propose a univariate selection method that combines a test of association between missingness and classes, and a test for difference of observed intensities between classes.

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In proteomics, it is essential to quantify proteins in absolute terms if we wish to compare results among studies and integrate high-throughput biological data into genome-scale metabolic models. While labeling target peptides with stable isotopes allow protein abundance to be accurately quantified, the utility of this technique is constrained by the low number of quantifiable proteins that it yields. Recently, label-free shotgun proteomics has become the "gold standard" for carrying out global assessments of biological samples containing thousands of proteins.

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The gut microbiota are increasingly considered as a main partner of human health. Metaproteomics enables us to move from the functional potential revealed by metagenomics to the functions actually operating in the microbiome. However, metaproteome deciphering remains challenging.

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In Northern Europe, sowing maize one-month earlier than current agricultural practices may lead to moderate chilling damage. However, studies of the metabolic responses to low, non-freezing, temperatures remain scarce. Here, genetically-diverse maize hybrids (Zea mays, dent inbred lines crossed with a flint inbred line) were cultivated in a growth chamber at optimal temperature and then three decreasing temperatures for 2 days each, as well as in the field.

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The effect of drought on maize yield is of particular concern in the context of climate change and human population growth. However, the complexity of drought-response mechanisms makes the design of new drought-tolerant varieties a difficult task that would greatly benefit from a better understanding of the genotype-phenotype relationship. To provide novel insight into this relationship, we applied a systems genetics approach integrating high-throughput phenotypic, proteomic, and genomic data acquired from 254 maize hybrids grown under two watering conditions.

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Transcriptomic and proteomic analyses were performed on three replicates of tomato fruit pericarp samples collected at nine developmental stages, each replicate resulting from the pooling of at least 15 fruits. For transcriptome analysis, Illumina-sequenced libraries were mapped on the tomato genome with the aim to obtain absolute quantification of mRNA abundance. To achieve this, spikes were added at the beginning of the RNA extraction procedure.

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Protein phosphorylation especially on serine/threonine/tyrosine residues are frequent in many bacteria. This post-translational modification has been associated with pathogenicity and virulence in various species. However, only few data have been produced so far on generally recognized as safe bacteria used in food fermentations.

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Protein synthesis and degradation are essential processes that regulate cell status. Because labeling in bulky organs, such as fruits, is difficult, we developed a modeling approach to study protein turnover at the global scale in developing tomato () fruit. Quantitative data were collected for transcripts and proteins during fruit development.

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In bottom-up proteomics, data are acquired on peptides resulting from proteolysis. In XIC-based quantification, the quality of the estimation of protein abundance depends on how peptide data are filtered and on which quantification method is used to express peptide intensity as protein abundance. So far, these two questions have been addressed independently.

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The so-called tube-gel method is a sample preparation protocol allowing for management of SDS for protein solubilization through in-gel protein trapping. Because of its simplicity, we assumed that once miniaturized, this method could become a standard for large scale experiments. We evaluated the performances of two variants of the miniaturized version of the tube-gel method based on different solubilization buffers (Tris-SDS or urea-SDS).

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X!TandemPipeline is a software designed to perform protein inference and to manage redundancy in the results of phosphosite identification by database search. It provides the minimal list of proteins or phosphosites that are present in a set of samples using grouping algorithms based on the principle of parsimony. Regarding proteins, a two-level classification is performed, where groups gather proteins sharing at least one peptide and subgroups gather proteins that are not distinguishable according to the identified peptides.

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How to process and analyze MS data to quantify and statistically compare protein abundances in bottom-up proteomics has been an open debate for nearly fifteen years. Two main approaches are generally used: the first is based on spectral data generated during the process of identification (e.g.

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Heterosis is a universal phenomenon that has major implications in evolution and is of tremendous agro-economic value. To study the molecular manifestations of heterosis and to find factors that maximize its strength, we implemented a large-scale proteomic experiment in yeast. We analyzed the inheritance of 1,396 proteins in 55 inter- and intraspecific hybrids obtained from Saccharomyces cerevisiae and S.

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Article Synopsis
  • S. cerevisiae and S. uvarum are domesticated yeast species that diverged around 100 million years ago and have distinct evolutionary paths, despite both being capable of fermenting grape must.
  • A study using quantitative mass spectrometry quantified 445 proteins, revealing significant differences in protein abundances that correlate with the phenotypic traits of each species.
  • The findings suggest that although S. cerevisiae and S. uvarum have similar fermentation capabilities, they evolved through different metabolic pathways and gene duplications, highlighting their unique evolutionary histories.
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Inferring protein abundances from peptide intensities is the key step in quantitative proteomics. The inference is necessarily more accurate when many peptides are taken into account for a given protein. Yet, the information brought by the peptides shared by different proteins is commonly discarded.

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