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1. Genomic Signatures of a Major Adaptive Event in the Pathogenic Fungus Melampsora larici-populina

Author

Antoine Persoons, Agathe Maupetit, Clémentine Louet, Axelle Andrieux, Anna Lipzen, Kerrie W Barry, Hyunsoo Na, Catherine Adam, Igor V Grigoriev, Vincent Segura, Sébastien Duplessis, Pascal Frey, Fabien Halkett, Stéphane De Mita, Alba, Mar, Interactions Arbres-Microorganismes (IAM), Université de Lorraine (UL)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Department of Energy / Joint Genome Institute (DOE), Los Alamos National Laboratory (LANL), University of California [Berkeley] (UC Berkeley), University of California (UC), Biologie intégrée pour la valorisation de la diversité des Arbres et de la Forêt (BioForA), Office national des forêts (ONF)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Amélioration génétique et adaptation des plantes méditerranéennes et tropicales (UMR AGAP), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro Montpellier, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Université de Montpellier (UM), Plant Health Institute of Montpellier (UMR PHIM), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut de Recherche pour le Développement (IRD)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro Montpellier, The work within the framework of the poplar rust genome project (CSP 1416) conducted by the U.S. Department of Energy Joint Genome Institute, a DOE Office of Science User Facility, is supported by the Office of Science of the U.S. Department of Energy under Contract No.DE-AC02-05CH11231., A.P. was supported by a PhD fellowship from the Region Lorraine and INRAE and a partial post doc fellowship from the Region Grand-Est., A.M. was supported by a PhD fellowship from the Region Lorraine and INRAE., C.L. was supported by a PhD fellowship from the Region Lorraine, ANR-12-ADAP-0009,GANDALF,Génomique et adaptation des traits de vie des champignons impliqués dans les interactions plante-pathogène(2012), ANR-11-LABX-0002,ARBRE,Recherches Avancées sur l'Arbre et les Ecosytèmes Forestiers(2011), and ANR-18-CE32-0001,Clonix2D,Les conséquences génétiques de reproduction partiellement clonale dans les populations colonisant de nouveaux territoires(2018)

Subjects
AcademicSubjects/SCI01140, 0106 biological sciences, population genomics, [SDV]Life Sciences [q-bio], genome scan, 01 natural sciences, 03 medical and health sciences, Genetics, plant–pathogen interactions, Ecology, Evolution, Behavior and Systematics, Plant Diseases, 030304 developmental biology, Evolutionary Biology, 0303 health sciences, Basidiomycota, plant-pathogen interactions, Human Genome, AcademicSubjects/SCI01130, Genomics, Populus, coevolution, genome-wide association studies, Biochemistry and Cell Biology, Research Article, Biotechnology, Developmental Biology, 010606 plant biology & botany
Abstract

The recent availability of genome-wide sequencing techniques has allowed systematic screening for molecular signatures of adaptation, including in nonmodel organisms. Host–pathogen interactions constitute good models due to the strong selective pressures that they entail. We focused on an adaptive event which affected the poplar rust fungus Melampsora larici-populina when it overcame a resistance gene borne by its host, cultivated poplar. Based on 76 virulent and avirulent isolates framing narrowly the estimated date of the adaptive event, we examined the molecular signatures of selection. Using an array of genome scan methods based on different features of nucleotide diversity, we detected a single locus exhibiting a consistent pattern suggestive of a selective sweep in virulent individuals (excess of differentiation between virulent and avirulent samples, linkage disequilibrium, genotype–phenotype statistical association, and long-range haplotypes). Our study pinpoints a single gene and further a single amino acid replacement which may have allowed the adaptive event. Although our samples are nearly contemporary to the selective sweep, it does not seem to have affected genome diversity further than the immediate vicinity of the causal locus, which can be explained by a soft selective sweep (where selection acts on standing variation) and by the impact of recombination in mitigating the impact of selection. Therefore, it seems that properties of the life cycle of M. larici-populina, which entails both high genetic diversity and outbreeding, has facilitated its adaptation.

Published
2021
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2. Causes and consequences of impaired methionine synthase activity in acquired and inherited disorders of vitamin B 12 metabolism

Author

David Coelho, Jean-Louis Guéant, Viola J Kosgei, Rosa-Maria Guéant-Rodriguez, Nutrition-Génétique et Exposition aux Risques Environnementaux (NGERE), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Lorraine (UL), Service de Biochimie et Biologie Moléculaire, Nutrition et Métabolisme [CHRU Nancy], Centre Hospitalier Régional Universitaire de Nancy (CHRU Nancy), The present work was financially supported by FHU ARRIMAGE and the French PIA GEENAGE project of Lorraine Université d’Excellence, reference: ANR-15-IDEX-04-LUE and the OMAGE project granted by Region Grand-Est of France and FEDER., IMPACT GEENAGE, and ANR-15-IDEX-0004,LUE,Isite LUE(2015)

Subjects
Homocysteine, [SDV]Life Sciences [q-bio], peroxisome proliferator-activated receptor-γ coactivator-1α, inborn errors of metabolism, Biochemistry, sirtuin 1, 03 medical and health sciences, chemistry.chemical_compound, 0302 clinical medicine, Methionine synthase, vitamin B12 deficiency, cobalamin, Molecular Biology, 030304 developmental biology, Methionine synthase activity, 2. Zero hunger, 0303 health sciences, Methionine, biology, Chemistry, Methylation, (Methionine synthase) reductase, MMACHC, 3. Good health, fetal programming, biology.protein, Transmethylation, 030217 neurology & neurosurgery
Abstract

International audience; Methyl-Cobalamin (Cbl) derives from dietary vitamin B12 and acts as a cofactor of methionine synthase (MS) in mammals. MS encoded by MTR catalyzes the remethylation of homocysteine to generate methionine and tetrahydrofolate, which fuel methionine and cytoplasmic folate cycles, respectively. Methionine is the precursor of S-adenosyl methionine (SAM), the universal methyl donor of transmethylation reactions. Impaired MS activity results from inadequate dietary intake or malabsorption of B12 and inborn errors of Cbl metabolism (IECM). The mechanisms at the origin of the high variability of clinical presentation of impaired MS activity are classically considered as the consequence of the disruption of the folate cycle and related synthesis of purines and pyrimidines and the decreased synthesis of endogenous methionine and SAM. For one decade, data on cellular and animal models of B12 deficiency and IECM have highlighted other key pathomechanisms, including altered interactome of MS with methionine synthase reductase, MMACHC, and MMADHC, endoplasmic reticulum stress, altered cell signaling, and genomic/epigenomic dysregulations. Decreased MS activity increases catalytic protein phosphatase 2A (PP2A) and produces imbalanced phosphorylation/methylation of nucleocytoplasmic RNA binding proteins, including ELAVL1/HuR protein, with subsequent nuclear sequestration of mRNAs and dramatic alteration of gene expression, including SIRT1. Decreased SAM and SIRT1 activity induce ER stress through impaired SIRT1-deacetylation of HSF1 and hypomethylation/hyperacetylation of peroxisome proliferator-activated receptor-γ coactivator-1α (PGC1α), which deactivate nuclear receptors and lead to impaired energy metabolism and neuroplasticity. The reversibility of these pathomechanisms by SIRT1 agonists opens promising perspectives in the treatment of IECM outcomes resistant to conventional supplementation therapies.

Published
2021
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3. Speech Frame Selection for Spoofing Detection with an Application to Partially Spoofed Audio-Data

Author

Goutam Saha, Sahidullah, A Kishore Kumar, Monisankha Pal, Dipjyoti Paul, Indian Institute of Technology Kharagpur (IIT Kharagpur), University of Crete [Heraklion] (UOC), University of Southern California (USC), Speech Modeling for Facilitating Oral-Based Communication (MULTISPEECH), Inria Nancy - Grand Est, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Department of Natural Language Processing & Knowledge Discovery (LORIA - NLPKD), Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS), We would like acknowledge the funding agencies. Dipjyoti Paul’s work is funded by the EUs H2020 research and innovation programme under theMSCA GA 67532 (the ENRICH network: www.enrich-etn.eu). The work of Md Sahidullah is supported by Region Grand Est., Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), and Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)

Subjects
Linguistics and Language, Spoofing attack, Computer science, Speech recognition, Feature extraction, Selection strategy, Anti-spoofing, Frame selection, Language and Linguistics, Synthetic speech detection, [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI], 030507 speech-language pathology & audiology, 03 medical and health sciences, Countermeasures, [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG], ASVspoof, [INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV], Mixture model, Human-Computer Interaction, Partially spoofed speech, Speaker verification, Computer Vision and Pattern Recognition, Mel-frequency cepstrum, Performance improvement, 0305 other medical science, Classifier (UML), [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, Software, Utterance, Voice conversion
Abstract

International audience; In this paper, we introduce a frame selection strategy for improved detection of spoofed speech. A countermeasure (CM) system typically uses a Gaussian mixture model (GMM) based classifier for computing the log-likelihood scores. The average log-likelihood ratio for all speech frames of a test utterance is calculated as the score for the decision making. As opposed to this standard approach, we propose to use selected speech frames of the test utterance for scoring. We present two simple and computationally efficient frame selection strategies based on the log-likelihood ratios of the individual frames. The performance is evaluated with constant-Q cepstral coefficients as front-end feature extraction and two-class GMM as a back-end classifier. We conduct the experiments using the speech corpora from ASVspoof 2015, 2017, and 2019 challenges. The experimental results show that the proposed scoring techniques substantially outperform the conventional scoring technique for both the development and evaluation data set of ASVspoof 2015 corpus. We did not observe noticeable performance gain in ASVspoof 2017 and ASVspoof 2019 corpus. We further conducted experiments with partially spoofed data where spoofed data is created by augmenting natural and spoofed speech. In this scenario, the proposed methods demonstrate considerable performance improvement over baseline.

Published
2021
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4. Visualizing Classifier Adjacency Relations: A Case Study in Speaker Verification and Voice Anti-Spoofing

Author

Xin Wang, Kong Aik Lee, Massimiliano Todisco, Junichi Yamagishi, Andreas Nautsch, Md. Sahidullah, Héctor Delgado, Tomi Kinnunen, Nicholas Evans, University of Eastern Finland, Eurecom [Sophia Antipolis], Speech Modeling for Facilitating Oral-Based Communication (MULTISPEECH), Inria Nancy - Grand Est, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Department of Natural Language Processing & Knowledge Discovery (LORIA - NLPKD), Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL), National Institute of Informatics (NII), Nuance Communications [Spain], Institute for Infocomm Research (I2R), This work was supported by a number of projects and funding sources: VoicePersonae, supported by the French Agence Nationale de la Recherche (ANR) and the Japan Science and Technology Agency (JST) with grant No. JPMJCR18A6, Academy of Finland (proj. 309629), Region Grand Est, France., Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), and Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)

Subjects
FOS: Computer and information sciences, Computer Science - Machine Learning, Sound (cs.SD), Computer science, multi-dimensional scaling, 02 engineering and technology, Classifier, Statistics - Applications, Computer Science - Sound, Machine Learning (cs.LG), Set (abstract data type), 030507 speech-language pathology & audiology, 03 medical and health sciences, [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG], [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, Audio and Speech Processing (eess.AS), Classifier (linguistics), 0202 electrical engineering, electronic engineering, information engineering, FOS: Electrical engineering, electronic engineering, information engineering, Applications (stat.AP), Representation (mathematics), [STAT.AP]Statistics [stat]/Applications [stat.AP], Receiver operating characteristic, business.industry, Visual comparison, 020206 networking & telecommunications, Pattern recognition, Mixture model, Automatic summarization, Adjacency list, Artificial intelligence, 0305 other medical science, business, Electrical Engineering and Systems Science - Audio and Speech Processing
Abstract

Whether it be for results summarization, or the analysis of classifier fusion, some means to compare different classifiers can often provide illuminating insight into their behaviour, (dis)similarity or complementarity. We propose a simple method to derive 2D representation from detection scores produced by an arbitrary set of binary classifiers in response to a common dataset. Based upon rank correlations, our method facilitates a visual comparison of classifiers with arbitrary scores and with close relation to receiver operating characteristic (ROC) and detection error trade-off (DET) analyses. While the approach is fully versatile and can be applied to any detection task, we demonstrate the method using scores produced by automatic speaker verification and voice anti-spoofing systems. The former are produced by a Gaussian mixture model system trained with VoxCeleb data whereas the latter stem from submissions to the ASVspoof 2019 challenge., Comment: Accepted to Interspeech 2021. Example code available at https://github.com/asvspoof-challenge/classifier-adjacency

Published
2021
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5. Unsupervised Extra Trees: a stochastic approach to compute similarities in heterogeneous data

Author

Kevin Dalleau, Miguel Couceiro, Malika Smaïl-Tabbone, Computational Algorithms for Protein Structures and Interactions (CAPSID), Inria Nancy - Grand Est, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Department of Complex Systems, Artificial Intelligence & Robotics (LORIA - AIS), Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL), Knowledge representation, reasonning (ORPAILLEUR), Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Department of Natural Language Processing & Knowledge Discovery (LORIA - NLPKD), Kevin Dalleau’s PhD is funded by the RHU FIGHTHF (ANR-15-RHUS-0004) and the Region Grand Est (France)., ANR-15-RHUS-0004,FIGHT-HF,Combattre l'insuffisance cardiaque(2015), Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Laboratoire Lorrain de Recherche en Informatique et ses Applications (LORIA), and Institut National de Recherche en Informatique et en Automatique (Inria)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS)

Subjects
0301 basic medicine, Hierarchical agglomerative clustering, Unsupervised classification, Computer science, Decision tree, Monotonic function, Similarity measure, Clustering, 03 medical and health sciences, 0302 clinical medicine, [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG], Robustness (computer science), Cluster (physics), Preprocessor, Cluster analysis, business.industry, Applied Mathematics, Pattern recognition, Computer Science Applications, 030104 developmental biology, Computational Theory and Mathematics, 030220 oncology & carcinogenesis, Modeling and Simulation, Artificial intelligence, Extremely randomized trees, business, Information Systems
Abstract

International audience; In this paper we present a method to compute similarities on unlabeled data, based on extremely randomized trees. The main idea of our method, Unsu-pervised Extremely Randomized Trees (UET) is to randomly split the data in an iterative fashion until a stopping criterion is met, and to compute a similarity based on the co-occurrence of samples in the leaves of each generated tree. Using a tree-based approach to compute similarities is interesting, as the inherent We evaluate our method on synthetic and real-world datasets by comparing the mean similarities between samples with the same label and the mean similarities between samples with different labels. These metrics are similar to intracluster and intercluster similarities, and are used to assess the computed similarities instead of a clustering algorithm's results. Our empirical study shows that the method effectively gives distinct similarity values between samples belonging to different clusters, and gives indiscernible values when there is no cluster structure. We also assess some interesting properties such as in-variance under monotone transformations of variables and robustness to correlated variables and noise. Finally , we performed hierarchical agglomerative clustering on synthetic and real-world homogeneous and heterogeneous datasets using UET versus standard similarity measures. Our experiments show that the algorithm outperforms existing methods in some cases, and can reduce the amount of preprocessing needed with many real-world datasets.

Published
2020
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6. Element content and expression of genes of interest in guard cells are connected to spatiotemporal variations in stomatal conductance

Author

Cyril Buré, Irène Hummel, Oliver Brendel, Nathalie Aubry, Ivana Tomášková, David Cohen, Didier Le Thiec, Maxime Durand, SILVA (SILVA), Institut National de la Recherche Agronomique (INRA)-AgroParisTech-Université de Lorraine (UL), University of Life Sciences Prague, FP7 Food, Agriculture and Fisheries, Biotechnology Watbio/311929, Institut National de la Recherche Agronomique (INRA), Region Grand-Est, French National Research Agency (ANR) ANR-12-LABXARBRE-01 European Union (EU), Le Thiec, Didier, Institut National de la Recherche Agronomique (INRA)-Université de Lorraine (UL)-AgroParisTech, and Czech University of Life Sciences Prague (CZU)

Subjects
0106 biological sciences, 0301 basic medicine, Physiology, [SDV]Life Sciences [q-bio], Plant Science, 01 natural sciences, Trees, chemistry.chemical_compound, DROUGHT TOLERANCE, HYBRID POPLAR, Gene Expression Regulation, Plant, Guard cell, Arabidopsis thaliana, Abscisic acid, plant stomata, Plant Proteins, biology, droughts, populus euramericana, food and beverages, ABSCISIC-ACID, ANION CHANNEL SLAC1, Proton-Translocating ATPases, elements, Populus, RNA, Plant, LIGHT-INTENSITY, expression des gènes, variabilité spatio temporelle, Stomatal conductance, DNA, Complementary, Genotype, Plant Development, Aquaporin, WATER TRANSPORT, Black poplar, 03 medical and health sciences, ADAXIAL STOMATA, Botany, black poplar, conductance stomatique, Water transport, fungi, HYDRAULIC CONDUCTIVITY, Water, Plant Transpiration, PLASMA-MEMBRANE AQUAPORINS, biology.organism_classification, abaxial and adaxial surfaces, gene expression, stomatal conductance, ARABIDOPSIS-THALIANA, Plant Leaves, Light intensity, 030104 developmental biology, chemistry, populus nigra, Electron Probe Microanalysis, 010606 plant biology & botany
Abstract

Element content and expression of genes of interest on single cell types, such as stomata, provide valuable insights into their specific physiology, improving our understanding of leaf gas exchange regulation. We investigated how far differences in stomatal conductance (g(s)) can be ascribed to changes in guard cells functioning in amphistomateous leaves. g(s) was measured during the day on both leaf sides, on well-watered and drought-stressed trees (two Populus euramericana Moench and two Populus nigra L. genotypes). In parallel, guard cells were dissected for element content and gene expressions analyses. Both were strongly arranged according to genotype, and drought had the lowest impact overall. Normalizing the data by genotype highlighted a structure on the basis of leaf sides and time of day both for element content and gene expression. Guard cells magnesium, phosphorus, and chlorine were the most abundant on the abaxial side in the morning, where g(s) was at the highest. In contrast, genes encoding H+-ATPase and aquaporins were usually more abundant in the afternoon, whereas genes encoding Ca2+-vacuolar antiporters, K+ channels, and ABA-related genes were in general more abundant on the adaxial side. Our work highlights the unique physiology of each leaf side and their analogous rhythmicity through the day.

Published
2019
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7. The structure of Trametes versicolor glutathione transferase Omega 3S bound to its conjugation product glutathionyl-phenethylthiocarbamate reveals plasticity of its active site

Author

Thomas Perrot, Mélanie Morel-Rouhier, Mathieu Schwartz, Claude Didierjean, Eric Gelhaye, Frédérique Favier, Guillermo Mulliert, Cristallographie, Résonance Magnétique et Modélisations (CRM2), Université de Lorraine (UL)-Centre National de la Recherche Scientifique (CNRS), Interactions Arbres-Microorganismes (IAM), Université de Lorraine (UL)-Institut National de la Recherche Agronomique (INRA), Region Grand Est CPER 2014-2020, University of Lorraine, Centre National de la Recherche Scientifique (CNRS), French National Research Agency (ANR) ANR-11-LAS-0002-01, Universite de Lorraine, PEPS-Mirabelle 2016, Institut National de la Recherche Agronomique (INRA)-Université de Lorraine (UL), and Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL)

Subjects
Models, Molecular, Conformational change, Phenethyl isothiocyanate, Stereochemistry, liaison hydrophobe, [SDV]Life Sciences [q-bio], Context (language use), champignon lignivore, Biochemistry, 03 medical and health sciences, chemistry.chemical_compound, trametes versicolor, Isothiocyanates, glutathione transferase, Transferase, Binding site, glutathion, Molecular Biology, polyphenols, 030304 developmental biology, X-ray crystallography, Trametes, 0303 health sciences, Binding Sites, Molecular Structure, biology, wood destroying fungi, 030302 biochemistry & molecular biology, Active site, Glutathione, chemistry, Isothiocyanate, Biocatalysis, biology.protein, Protein Structure Reports, isothiocyanate
Abstract

Trametes versicolor glutathione transferase Omega 3S (TvGSTO3S) catalyzes the conjugation of isothiocyanates (ITC) with glutathione (GSH).Previously, this isoform was investigated in depth both biochemically and structurally. Structural analysis of complexes revealed the presence of a GSH binding site (G site) and a deep hydrophobic binding site (H site) able to bind plant polyphenols. In the present study, crystals of apo TvGSTO3S were soaked with glutathionyl-phenethylthiocarbamate, the product of the reaction between GSH and phenethyl isothiocyanate (PEITC).On the basis of this crystal structure, we show that the phenethyl moiety binds in a new site at loop beta(2)-alpha(2) while the glutathionyl part exhibits a particular conformation that occupies both the G site and the entrance to the H site. This binding mode is allowed by a conformational change of the loop beta(2)-alpha(2) at the enzyme active site. It forms a hydrophobic slit that stabilizes the phenethyl group at a distinct site from the previously described H site.Structural comparison of TvGSTO3S with drosophila DmGSTD2 suggests that this flexible loop could be the region that binds PEITC for both isoforms. These structural features are discussed in a catalytic context.

Published
2019
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8. A secreted WY-domain-containing protein present in European isolates of the oomycete Plasmopara viticola induces cell death in grapevine and tobacco species

Author

Liron Shenhav, Maud Combier, Edouard Evangelisti, Marie-Christine Piron, David Rengel, Ludovic Legrand, Sebastian Schornack, Pere Mestre, Olivier Bouchez, Santé de la vigne et qualité du vin (SVQV), Institut National de la Recherche Agronomique (INRA)-Université de Strasbourg (UNISTRA), University of Cambridge [UK] (CAM), Laboratoire des interactions plantes micro-organismes (LIPM), Institut National de la Recherche Agronomique (INRA)-Centre National de la Recherche Scientifique (CNRS), Génome et Transcriptome - Plateforme Génomique (GeT-PlaGe), Institut National de la Recherche Agronomique (INRA)-Plateforme Génome & Transcriptome (GET), Génopole Toulouse Midi-Pyrénées [Auzeville] (GENOTOUL), Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Ecole Nationale Vétérinaire de Toulouse (ENVT), Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Génopole Toulouse Midi-Pyrénées [Auzeville] (GENOTOUL), Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), French National Research Agency (ANR) : ANR-13-ADAP-0003 INRA BAP Department, Region Grand-Est, Gatsby Charitable Foundation, Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Toulouse III - Paul Sabatier (UT3), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Ecole Nationale Vétérinaire de Toulouse (ENVT), Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM)-Institut National des Sciences Appliquées - Toulouse (INSA Toulouse), Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM)-Génopole Toulouse Midi-Pyrénées [Auzeville] (GENOTOUL), and Université Fédérale Toulouse Midi-Pyrénées-Institut National de la Santé et de la Recherche Médicale (INSERM)

Subjects
0106 biological sciences, 0301 basic medicine, Leaves, Plant Science, 01 natural sciences, Biochemistry, Database and Informatics Methods, Sequence Analysis, Protein, Vitis, Cloning, Molecular, Post-Translational Modification, Phylogeny, Flowering Plants, Oomycete, Peronospora, Multidisciplinary, Vegetal Biology, biology, Cell Death, Effector, Plant Anatomy, Eukaryota, Plants, Europe, Oomycetes, Cell Processes, Plasmopara viticola, Host-Pathogen Interactions, Medicine, Grapevine, Sequence Analysis, Signal Peptides, Research Article, Signal peptide, Bioinformatics, Science, Protein domain, Plant Pathogens, Sequence alignment, Research and Analysis Methods, Microbiology, Evolution, Molecular, Fungal Proteins, 03 medical and health sciences, Protein Domains, Species Specificity, Sequence Motif Analysis, Tobacco, [SDV.BV]Life Sciences [q-bio]/Vegetal Biology, Nicotiana, Plant Diseases, Cell Nucleus, Organisms, Fungi, Biology and Life Sciences, Proteins, Cell Biology, Plant Pathology, biology.organism_classification, United States, 030104 developmental biology, Downy Mildew, Downy mildew, Sequence Alignment, Biologie végétale, 010606 plant biology & botany
Abstract

International audience; Plasmopara viticola is a biotrophic oomycete pathogen causing grapevine downy mildew. We characterized the repertoire of P. viticola effector proteins which may be translocated into plants to support the disease. We found several secreted proteins that contain canonical dEER motifs and conserved WY-domains but lack the characteristic RXLR motif reported previously from oomycete effectors. We cloned four candidates and showed that one of them, Pv33, induces plant cell death in grapevine and Nicotiana species. This activity is dependent on the nuclear localization of the protein. Sequence similar effectors were present in seven European, but in none of the tested American isolates. Together our work contributes a new type of conserved P. viticola effector candidates.

Published
2019
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9. Facing global change: The millennium challenge for plant scientists

Author

Clémence Bonnot, Feng Zhang, Veronica Basso, Julieta Mallerman, Maíra de Freitas Pereira, Lauralie Mangeot-Peter, François Maillard, Interactions Arbres-Microorganismes (IAM), Institut National de la Recherche Agronomique (INRA)-Université de Lorraine (UL), LabEx ARBRE : Advanced Research on the Biology of Tree and Forest Ecosystems ([LabEx ARBRE]), Office National des Forêts (ONF)-AgroParisTech-Institut National de la Recherche Agronomique (INRA)-Centre National de la Propriété Forestière-CRITT Bois-European Forest Institute = Institut Européen de la Forêt = Euroopan metsäinstituutti (EFI)-Université de Lorraine (UL), SILVA (SILVA), Institut National de la Recherche Agronomique (INRA)-Université de Lorraine (UL)-AgroParisTech, Instituto de Investigaciones Fisiologicas y Ecologicas Vinculadas a la Agricultura (IFEVA), Facultad de Agronomía [Buenos Aires], Universidad de Buenos Aires [Buenos Aires] (UBA)-Universidad de Buenos Aires [Buenos Aires] (UBA)-Consejo Nacional de Investigaciones Científicas y Técnicas [Buenos Aires] (CONICET), New Phytologist Trust, LabEx ARBRE ANR-11-LABX-0002-01, Region Grand-Est, University of Lorraine, Genomic Science Programme of the US Department of Energy as part of the Plant-Microbe Interfaces Scientific Focus Area, ANPCyT PICT 2015-1231 PICT 2016-1780 University of Buenos Aires (UBACyT), CONICET of Argentina, ANR-11-LABX-0002,ARBRE,Recherches Avancées sur l'Arbre et les Ecosytèmes Forestiers(2011), Bonnot, Clémence, Université de Lorraine (UL)-Institut National de la Recherche Agronomique (INRA), Institut National de la Recherche Agronomique (INRA)-AgroParisTech-Office National des Forêts (ONF)-Université de Lorraine (UL)-Centre National de la Propriété Forestière-CRITT Bois-European Forest Institute = Institut Européen de la Forêt = Euroopan metsäinstituutti (EFI), and Institut National de la Recherche Agronomique (INRA)-AgroParisTech-Université de Lorraine (UL)

Subjects
0301 basic medicine, IMPACTS, anthropocene, Physiology, Natural resource economics, [SDV]Life Sciences [q-bio], CLIMATE CHANGE, Climate change, Plant Science, 7. Clean energy, 12. Responsible consumption, Ciencias Biológicas, 03 medical and health sciences, ACCLIMATION, 11. Sustainability, PHENOTYPIC PLASTICITY, changement global, PLANT ADAPTIVE STRATEGIES, BIOCHEMICAL CYCLES, Ciencias de las Plantas, Botánica, DROUGHT, 2. Zero hunger, SECURITY, Phenotypic plasticity, Food security, CLIMATE-CHANGE, PESTS, production agricole, FOOD SECURITY, HOLOBIONT, durabilité, Global change, 15. Life on land, sustainability, Holobiont, PLANT SCIENCES, 030104 developmental biology, Geography, 13. Climate action, Plant productivity, agricultural production, GROWTH, RESISTANCE, CIENCIAS NATURALES Y EXACTAS, PLANT PRODUCTIVITY
Abstract

We entered the Anthropocene with the industrial revolution. This geological era is defined by the unprecedented impact of human activities on the planet's geochemical cycles, making us the main driving force of Earth environmental changes (Crutzen, 2002; Steffen et al., 2011). Since the middle of the twentieth century the human population has tripled, reaching seven billion today and probably 10 billion by 2050 (United Nations, 2015). This dramatic increase, associated with the improvement in the welfare of the population, has led to the overexploitation of natural resources. Intensive agriculture and industrialization has resulted in global warming, modification of nutrient cycles, pollution and reduction of wilderness; and endangering the preservation of eco‐ and agro‐systems (Tilman et al., 2002; Steffen et al., 2011; Ehrlich & Harte, 2015). Today, the challenge is not only to intensify agro‐productions to feed, fuel and shelter the growing population; but to do so in spite of the consequences of climate change while lessening our impact on the supporting ecosystems (Godfray et al., 2010; Ehrlich & Harte, 2015; Byrne et al., 2018). Plant sciences can play an important part in mitigating both the causes and consequences of the pressure population growth imposes on the environment. As the primary producer of eco‐ and agro‐systems, plants are essential to assess and understand human‐driven environmental changes (Loreau et al., 2001; Lin et al., 2008). They are also central tools to develop sustainable production methods (Godfray et al., 2010; Ehrlich & Harte, 2015; Byrne et al., 2018). In this context, the 41st New Phytologist Symposium ‘Plant sciences for the future’ was set as an experimental interdisciplinary platform. Bringing together early career and leader scientists from different fields of plant sciences, it aimed to promote the development of transdisciplinary research projects to build a better understanding of the multiple aspects of the upcoming environmental challenges; and to produce robust solutions for society. A special debate chaired by Marc‐André Selosse (Natural History Museum of Paris, France) and Richard Norby (Oak Ridge National Laboratory, TN, USA) highlighted the critical topics and knowledge gaps the scientific community needs to fill in order to harness plant sciences to solve these societal issues. This event, held in Nancy, France on 11–13 April 2018, hosted researchers from 70 universities, research institutes and companies representing 29 countries in the fields of Developmental biology, Evolutionary biology, Ecology, Plant–microorganism interactions, Physiology and Genetic engineering (Fig. 1). In this article we outline how all plant science fields contribute to understand the effects of global change and to developing innovative solutions to maintain agro‐productions, promote sustainability and counteract climate change. Fil: Basso, Veronica. Institut National de la Recherche Agronomique; Francia Fil: De Freitas Pereira, Maíra. Institut National de la Recherche Agronomique; Francia Fil: Maillard, François. Institut National de la Recherche Agronomique; Francia Fil: Mallerman, Julieta. Consejo Nacional de Investigaciones Científicas y Técnicas. Oficina de Coordinación Administrativa Parque Centenario. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura. Universidad de Buenos Aires. Facultad de Agronomía. Instituto de Investigaciones Fisiológicas y Ecológicas Vinculadas a la Agricultura; Argentina Fil: Mangeot Peter, Lauralie. Institut National de la Recherche Agronomique; Francia Fil: Zhang, Feng. Institut National de la Recherche Agronomique; Francia Fil: Bonnot, Clémence. Institut National de la Recherche Agronomique; Francia

Published
2018
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10. Bacterial weathering and its contribution to nutrient cycling in temperate forest ecosystems

Author

Philippe Oger, Stéphane Uroz, Pascale Frey-Klett, Cendrella Lepleux, Marie-Pierre Turpault, Christelle Collignon, Interactions Arbres-Microorganismes (IAM), Université de Lorraine (UL)-Institut National de la Recherche Agronomique (INRA), Unité de recherche Biogéochimie des Ecosystèmes Forestiers (BEF), Institut National de la Recherche Agronomique (INRA), Laboratoire de Géologie de Lyon - Terre, Planètes, Environnement [Lyon] (LGL-TPE), Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-École normale supérieure - Lyon (ENS Lyon), Programme national Ecosphere Continentale et Cotiere EC2CORegion Grand-Est INRA Region Grand-Est ONF (Office Nationale des Forets), Programme national Ecosphere Continentale et Cotiere : EC2CO, Bureau des Ressources genetiques (BRG), Region Lorraine, INRA, Lorraine Région, ONF (Office Nationale des Forêts), Institut National de la Recherche Agronomique (INRA)-Université de Lorraine (UL), École normale supérieure - Lyon (ENS Lyon)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS), Laboratoire de Géologie de Lyon - Terre, Planètes, Environnement (LGL-TPE), École normale supérieure de Lyon (ENS de Lyon)-Université Claude Bernard Lyon 1 (UCBL), and Université de Lyon-Université de Lyon-Institut national des sciences de l'Univers (INSU - CNRS)-Université Jean Monnet - Saint-Étienne (UJM)-Centre National de la Recherche Scientifique (CNRS)

Subjects
Nutrient cycle, Mineral-weathering, Forest management, Biology, Plant Roots, Microbiology, Nutrient cycling, Carbon Cycle, Trees, 03 medical and health sciences, Soil, Mycorrhizae, Forest ecology, Ecosystem, Forest, Symbiosis, Weather, Molecular Biology, Phylogeny, Soil Microbiology, 030304 developmental biology, Forest floor, Minerals, 0303 health sciences, geography, geography.geographical_feature_category, Bacteria, Ecology, Temperate forest, Pyrosequencing, 04 agricultural and veterinary sciences, General Medicine, Nitrogen Cycle, 15. Life on land, Old-growth forest, Bacterial communities, [SDV.MP]Life Sciences [q-bio]/Microbiology and Parasitology, Microscopy, Electron, Scanning, 040103 agronomy & agriculture, 0401 agriculture, forestry, and fisheries, Terrestrial ecosystem, [SDE.BE]Environmental Sciences/Biodiversity and Ecology
Abstract

International audience; Unlike farmland, forests growing on acidic soils are among the terrestrial ecosystems that are the least influenced or amended by man. Forests which developed on acidic soils are characterized by an important stock of inorganic nutrients entrapped in poorly weatherable soil minerals. In this context, the mineral-weathering process is of great importance, since such minerals are not easily accessible to tree roots. To date, several bacterial genera have been noted for their ability to weather minerals and, in the case of some of them, to improve tree nutrition. Nevertheless, few studies have focused their analyses on mineral-weathering bacterial communities in relation to geochemical cycles and soil characteristics, their ecological origin, associated tree species and forest management practices. Here we discuss the heterogeneity of the mineral-weathering process in forest soils and present what is known concerning the taxonomic and functional characteristics of mineral-weathering bacteria, as well as the different locations where they have been isolated in forest soils. We also discuss the biotic and abiotic factors that may influence the distribution of these bacteria, such as the effect of tree species or forest management practices.

Published
2011
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