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5. Phylogenetically diverse wild plant species use common biochemical strategies to thrive in the Atacama Desert.

Author

Dussarrat, Thomas, Nilo-Poyanco, Ricardo, Moyano, Tomás C, Prigent, Sylvain, Jeffers, Tim L, Díaz, Francisca P, Decros, Guillaume, Audi, Lauren, Sondervan, Veronica M, Shen, Bingran, Araus, Viviana, Rolin, Dominique, Shasha, Dennis, Coruzzi, Gloria M, Gibon, Yves, Latorre, Claudio, Pétriacq, Pierre, and Gutiérrez, Rodrigo A

Subjects
PLANT species, WILD plants, GENE expression, DESERTS, ABIOTIC stress, STRICT parenting
Abstract

The best ideotypes are under mounting pressure due to increased aridity. Understanding the conserved molecular mechanisms that evolve in wild plants adapted to harsh environments is crucial in developing new strategies for agriculture. Yet our knowledge of such mechanisms in wild species is scant. We performed metabolic pathway reconstruction using transcriptome information from 32 Atacama and phylogenetically related species that do not live in Atacama (sister species). We analyzed reaction enrichment to understand the commonalities and differences of Atacama plants. To gain insights into the mechanisms that ensure survival, we compared expressed gene isoform numbers and gene expression patterns between the annotated biochemical reactions from 32 Atacama and sister species. We found biochemical convergences characterized by reactions enriched in at least 50% of the Atacama species, pointing to potential advantages against drought and nitrogen starvation, for instance. These findings suggest that the adaptation in the Atacama Desert may result in part from shared genetic legacies governing the expression of key metabolic pathways to face harsh conditions. Enriched reactions corresponded to ubiquitous compounds common to extreme and agronomic species and were congruent with our previous metabolomic analyses. Convergent adaptive traits offer promising candidates for improving abiotic stress resilience in crop species. [ABSTRACT FROM AUTHOR]

Published
2024
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6. Ecological and metabolic implications of the nurse effect of Maihueniopsis camachoi in the Atacama Desert

Author

Díaz, Francisca P., primary, Dussarrat, Thomas, additional, Carrasco‐Puga, Gabriela, additional, Colombié, Sophie, additional, Prigent, Sylvain, additional, Decros, Guillaume, additional, Bernillon, Stéphane, additional, Cassan, Cédric, additional, Flandin, Amélie, additional, Guerrero, Pablo C., additional, Gibon, Yves, additional, Rolin, Dominique, additional, Cavieres, Lohengrin A., additional, Pétriacq, Pierre, additional, Latorre, Claudio, additional, and Gutiérrez, Rodrigo A., additional

Published
2023
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7. Convergent and divergent responses of the rhizosphere chemistry and bacterial communities to a stress gradient in the Atacama Desert

Author

Dussarrat, Thomas, primary, Latorre, Claudio, additional, Barros Santos, Millena C., additional, Aguado-Norese, Constanza, additional, Prigent, Sylvain, additional, Díaz, Francisca P., additional, Rolin, Dominique, additional, González, Mauricio, additional, Müller, Caroline, additional, Gutiérrez, Rodrigo A, additional, and Pétriacq, Pierre, additional

Published
2023
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8. Plant metabolomics and breeding

Author

Fernandez, Olivier, primary, Millet, Emilie J., additional, Rincent, Renaud, additional, Prigent, Sylvain, additional, Pétriacq, Pierre, additional, and Gibon, Yves, additional

Published
2021
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10. Ecological and metabolic implications of the nurse effect of Maihueniopsis camachoi in the Atacama Desert.

Author

Díaz, Francisca P., Dussarrat, Thomas, Carrasco‐Puga, Gabriela, Colombié, Sophie, Prigent, Sylvain, Decros, Guillaume, Bernillon, Stéphane, Cassan, Cédric, Flandin, Amélie, Guerrero, Pablo C., Gibon, Yves, Rolin, Dominique, Cavieres, Lohengrin A., Pétriacq, Pierre, Latorre, Claudio, and Gutiérrez, Rodrigo A.

Subjects
DESERTS, PHYTOGEOGRAPHY, TEMPERATURE distribution, BIOMARKERS, MACHINE learning
Abstract

Summary: Plant–plant positive interactions are key drivers of community structure. Yet, the underlying molecular mechanisms of facilitation processes remain unexplored. We investigated the 'nursing' effect of Maihueniopsis camachoi, a cactus that thrives in the Atacama Desert between c. 2800 and 3800 m above sea level. We hypothesised that an important protective factor is thermal amelioration of less cold‐tolerant species with a corresponding impact on molecular phenotypes.To test this hypothesis, we compared plant cover and temperatures within the cactus foliage with open areas and modelled the effect of temperatures on plant distribution. We combined eco‐metabolomics and machine learning to test the molecular consequences of this association.Multiple species benefited from the interaction with M. camachoi. A conspicuous example was the extended distribution of Atriplex imbricata to colder elevations in association with M. camachoi (400 m higher as compared to plants in open areas). Metabolomics identified 93 biochemical markers predicting the interaction status of A. imbricata with 79% accuracy, independently of year.These findings place M. camachoi as a key species in Atacama plant communities, driving local biodiversity with an impact on molecular phenotypes of nursed species. Our results support the stress‐gradient hypothesis and provide pioneer insights into the metabolic consequences of facilitation. [ABSTRACT FROM AUTHOR]

Published
2024
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11. Enzyme‐based kinetic modelling of ASC–GSH cycle during tomato fruit development reveals the importance of reducing power and ROS availability

Author

Decros, Guillaume, primary, Dussarrat, Thomas, additional, Baldet, Pierre, additional, Cassan, Cédric, additional, Cabasson, Cécile, additional, Dieuaide‐Noubhani, Martine, additional, Destailleur, Alice, additional, Flandin, Amélie, additional, Prigent, Sylvain, additional, Mori, Kentaro, additional, Colombié, Sophie, additional, Jorly, Joana, additional, Gibon, Yves, additional, Beauvoit, Bertrand, additional, and Pétriacq, Pierre, additional

Published
2023
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12. Comparative constraint‐based modelling of fruit development across species highlights nitrogen metabolism in the growth‐defence trade‐off

Author

Colombié, Sophie, primary, Prigent, Sylvain, additional, Cassan, Cédric, additional, Hilbert‐Masson, Ghislaine, additional, Renaud, Christel, additional, Dell'Aversana, Emilia, additional, Carillo, Petronia, additional, Moing, Annick, additional, Beaumont, Chloé, additional, Beauvoit, Bertrand, additional, McCubbin, Tim, additional, Nielsen, Lars Keld, additional, and Gibon, Yves, additional

Published
2023
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13. Identification of metabolic and protein markers representative of the impact of mild nitrogen deficit on agronomic performance of maize hybrids

Author

Urrutia, Maria, primary, Blein-Nicolas, Mélisande, additional, Fernandez, Ollivier, additional, Bernillon, Stéphane, additional, Maucourt, Mickaël, additional, Deborde, Catherine, additional, Balliau, Thierry, additional, Rabier, Dominique, additional, Bénard, Camille, additional, Prigent, Sylvain, additional, Quillere, Isabelle, additional, Jacob, Daniel, additional, Gibon, Yves, additional, Zivy, Michel, additional, Giauffret, Catherine, additional, Hirel, Bertrand, additional, and Moing, Annick, additional

Published
2023
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16. Extending the Metabolic Network of Ectocarpus Siliculosus Using Answer Set Programming

Author

Collet, Guillaume, Eveillard, Damien, Gebser, Martin, Prigent, Sylvain, Schaub, Torsten, Siegel, Anne, Thiele, Sven, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Goebel, Randy, editor, Siekmann, Jörg, editor, Wahlster, Wolfgang, editor, Cabalar, Pedro, editor, and Son, Tran Cao, editor

Published
2013
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17. A project-scale map of metadata to improve future data management

Author

Pétéra, Mélanie, Cabasson, Cecile, Comte, Blandine, Duperier, Christophe, Filangi, Olivier, Prigent, Sylvain, Pujos-Guillot, Estelle, Giacomoni, Franck, Plateforme Exploration du Métabolisme (PFEM), Institut National de la Recherche Agronomique (INRA)-Université Blaise Pascal - Clermont-Ferrand 2 (UBP)-MetaboHUB-Clermont, MetaboHUB-MetaboHUB, Biologie du fruit et pathologie (BFP), Université de Bordeaux (UB)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Plateforme Bordeaux Metabolome, Université de Bordeaux (UB)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-MetaboHUB-Bordeaux, Institut de Génétique, Environnement et Protection des Plantes (IGEPP), Université de Rennes (UR)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro Rennes Angers, 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), ANR-11-INBS-0010,METABOHUB,Développement d'une infrastructure française distribuée pour la métabolomique dédiée à l'innovation(2011), Petera, Mélanie, and Développement d'une infrastructure française distribuée pour la métabolomique dédiée à l'innovation - - METABOHUB2011 - ANR-11-INBS-0010 - INBS - VALID

Subjects
[CHIM.OTHE] Chemical Sciences/Other, Gestion de données de la recheche, [CHIM.OTHE]Chemical Sciences/Other, Métabolomique, FAIR, Méta-données
Abstract

International audience; Today, the intra-lab application of best practices in the metabolomics field usually guarantees an adequate data exploitation within a single lab. However, the growing interest in multi-analyses designs (e.g. complementary analytical platforms, variety of matrices, multi-omics), as well as the need of data sharing and reuse, increase the difficulty of data management. Indeed, managing the multiplicity and the heterogeneity of information involved is required to achieve relevant knowledge extraction from metabolomics data. Within the MetaboHUB national infrastructure, one objective is to optimize data handling, especially metadata, to facilitate large-scale analyses, multi-platforms studies, and data FAIRisation (Findability, Accessibility, Interoperability, Reusability). In particular, this fits in the MetaboHUB scientific roadmap that promotes the open science development in the field of metabolomics.In the context of metabolomic and lipidomic studies, data production and analysis come along with a large diversity of metadata (data of the data). To identify clearly-defined bottlenecks and targets for future improvement in data management, the objective of this work was to build a metadata map at the scale of a scientific project. Aiming for completeness, this map was constructed in a collaborative and multidisciplinary way involving chemists, biologists, data stewards as well as computer scientists, combining their respective experience and knowledge. Based on the resulting metadata map, targets (areas and topics) to be further investigated were identified, enabling the construction of transversal working groups at the consortium scale. In particular, this work enables to focus efforts on clearly defined issues to improve standardisation of practices regarding data management and metadata documentation. In conclusion, this collaborative map construction has been shown to be an efficient tool to draw a clear « where do we stand / where do we go » picture inside a national infrastructure like MetaboHUB regarding project-scale metadata. This facilitates the definition of a precise data management. Such an approach could be translated within other infrastructures, consortia and/or communities.

Published
2022

20. Predictive metabolomics of multiple Atacama plant species unveils a core set of generic metabolites for extreme climate resilience

Author

Dussarrat, Thomas, primary, Prigent, Sylvain, additional, Latorre, Claudio, additional, Bernillon, Stéphane, additional, Flandin, Amélie, additional, Díaz, Francisca P., additional, Cassan, Cédric, additional, Van Delft, Pierre, additional, Jacob, Daniel, additional, Varala, Kranthi, additional, Joubes, Jérôme, additional, Gibon, Yves, additional, Rolin, Dominique, additional, Gutiérrez, Rodrigo A., additional, and Pétriacq, Pierre, additional

Published
2022
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21. Combining phenotypic, metabolome and proteome data to study maize response to a mild nitrogen deficit

Author

Urrutia, Maria, Blein-Nicolas, Melisande, Fernandez, Olivier, Bernillon, Stéphane, Maucourt, Mickael, Deborde, Catherine, Balliau, Thierry, Bénard, Camille, Prigent, Sylvain, Quilleré, Isabelle, Jacob, Daniel, Gibon, Yves, Zivy, Michel, Giauffret, Catherine, Hirel, Bertrand, Moing, Annick, and Blein-Nicolas, Mélisande

Subjects
[SDV] Life Sciences [q-bio], [SDV.BBM.GTP] Life Sciences [q-bio]/Biochemistry, Molecular Biology/Genomics [q-bio.GN], [SDV.BV.AP] Life Sciences [q-bio]/Vegetal Biology/Plant breeding
Abstract

To decipher the biochemical bases of nitrogen (N) utilization and metabolism of silage maize inrelation to growth and productivity, an untargeted metabolomic (proton NMR- and LC-QTOF-MSbased) and proteomic approach was conducted on leaves of 29 hybrids cultivated in the field underoptimal and reduced N fertilization. The corresponding biochemical data were analyzed eitherindividually (PCA, ANOVA), or integrated with that of eco-physiological, developmental and yield-related traits (multi-block sparse PLS-DA). Such integrated analysis was conducted to interpret theunderlying physiology concerning the plant response to a mild N deficit often occurring underagronomic conditions. The genetic diversity of the core panel of 29 European dent hybrids crossed toa flint tester was exploited to highlight common N-responsive metabolites and proteins in order toidentify putative biological markers that could be used to pilot and rationalize N fertilization. Theresponses of metabolites, proteins, and yield-related traits to the reduced N treatment were alsoexploited to identify biochemical markers representative of a maize ideotype exhibiting betteragronomic performances when N fertilization is limited. These markers could be used to select high-yielding commercial maize hybrids used for silage production requiring less N fertilizer inputs.

Published
2022

22. Presence/absence variations and SNPs equally contribute to the variations of protein and metabolite abundance

Author

Djabali, Yacine, Blein-Nicolas, Melisande, Moing, Annick, Duarte, Jorge, Bernillon, Stéphane, Prigent, Sylvain, Mabire, Clément, Madur, Delphine, Cabrera-Bosquet, Llorenç, Welcker, Claude, Tardieu, Francois, Gibon, Yves, Zivy, Michel, Charcosset, Alain, Nicolas, Stephane, and Blein-Nicolas, Mélisande

Subjects
[SDV] Life Sciences [q-bio], [SDV.BIBS] Life Sciences [q-bio]/Quantitative Methods [q-bio.QM], [SDV.BBM.MN] Life Sciences [q-bio]/Biochemistry, Molecular Biology/Molecular Networks [q-bio.MN], [SDV.GEN.GPL] Life Sciences [q-bio]/Genetics/Plants genetics, [SDV.BBM.GTP] Life Sciences [q-bio]/Biochemistry, Molecular Biology/Genomics [q-bio.GN], [SDV.BV.AP] Life Sciences [q-bio]/Vegetal Biology/Plant breeding
Abstract

Understanding the mechanisms of adaptation to the environment in cultivated plants is a promising way to meet the challenge of maintaining food security in the context of global warming. In the case of maize, high-throughput sequencing has revealed that structural variations represent a large part of the genome and could have huge phenotypic effects. Among these, Presence Absence Variants (PAVs, which include insertion/deletion of large DNA sequences) may be involved in adaptation of maize to its environment, but their contribution to the genetic determinism of traits and genotype by environment interactions remains largely unknown. To address this issue, we performed a genome-wide association study between two types of polymorphisms, SNPs and InDels, and molecular traits obtained from proteomics and metabolomics analyses to detect quantitative trait loci (QTLs). The genetic panel used for this study was composed of 254 dent inbred lines genotyped with 978,134 SNPs and 72,041 InDels. The latter encompassed from 37 to 129,700 pb, including thousands of PAVs that are not present in the B73 reference genome. Proteins and metabolites were quantified by mass spectrometry in leaf samples from F1 hybrids obtained by crossing the inbred lines with one flint tester line. Hybrid plants were grown under two watering conditions (well-watered and water deficit) in greenhouse. In total, we detected 61,225 QTLs associated with proteome or metabolome variations. Among these, 4,766 QTLs were exclusively detected by InDels. To take into account the difference of marker density between InDels and SNPs, we used a re-sampling approach which showed that there was no difference between InDels and SNPs regarding the number and effect of the QTLs detected . Additionally, the QTLs detected by the two types of polymorphism were equally distributed in the two watering conditions. These preliminary results show that InDels are worse considering to detect new genetic regions of interest. They also suggest that InDels and SNPs equally contribute to molecular trait variation and response to drought stress.

Published
2022

25. SPITFIR(e): a supermaneuverable image restoration algorithm for 2D, 3D and 3D+Time microscopy images

Author

Prigent, Sylvain, Valades-Cruz, Cesar Augusto, Leconte, Ludovic, Salamero, Jean, Kervrann, Charles, Space-timE RePresentation, Imaging and cellular dynamics of molecular COmplexes (SERPICO), Inria Rennes – Bretagne Atlantique, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Biologie Cellulaire et Cancer, Institut Curie [Paris]-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), and Kervrann, Charles

Subjects
[INFO.INFO-TI] Computer Science [cs]/Image Processing [eess.IV], [INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV], [INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM], ComputingMilieux_MISCELLANEOUS, [INFO.INFO-BI] Computer Science [cs]/Bioinformatics [q-bio.QM]
Abstract

International audience

Published
2021

26. High-resolution reconstruction and deconvolution of array detector images

Author

Prigent, Sylvain, Dutertre, Stéphanie, Bidaud-Meynard, Aurélien, Bertolin, Giulia, Michaux, Grégoire, Kervrann, Charles, Institut de Génétique et Développement de Rennes (IGDR), Structure Fédérative de Recherche en Biologie et Santé de Rennes ( Biosit : Biologie - Santé - Innovation Technologique )-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES), Centre National de la Recherche Scientifique (CNRS), Université de Rennes 1 (UR1), and Université de Rennes (UNIV-RENNES)

Subjects
ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION, [INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM]
Abstract

Array detector allows a resolution gain for confocal microscopy by combining several images acquired by 32 sub-detectors. A single high resolution image is generally obtained by spatially re-assigning the signal from the 32 sub-detectors and applying a deconvolution procedure. Alternative methods have been proposed to produce high resolution images by linearly combining the signals of sub-detectors. We propose here a novel method that deconvolves directly the stack constituted of 32 spatially re-assigned detectors signals. We demonstrate on both calibration slides and real data that the proposed method allows to produce more homogeneous, well-contrasted, high-resolution images than those obtained with previous methods. All the tested methods have been implemented in an open source software which can be be downloaded for free.

Published
2021

29. Presence/absence variations and SNPs equally contribute to the variations of protein and metabolite abundance

Author

Djabali, Yacine, Blein, Mélisande, Moing, Annick, Duarte, Jorge, Berton, Thierry, Bernillon, Stéphane, Prigent, Sylvain, Fernandez, Olivier, Pétriacq, Pierre, Mabire, Clément, Madur, Delphine, Cabrera-Bosquet, Llorenç, Welcker, Claude, Tardieu, Francois, Gibon, Yves, Zivy, Michel, Charcosset, Alain, Nicolas, Stephane, Génétique Quantitative et Evolution - Le Moulon (Génétique Végétale) (GQE-Le Moulon), AgroParisTech-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Plateforme Metabolome Bordeaux, INRAE, 2018, MetaboHUB, Centre INRAE Nouvelle Aquitaine Bordeaux, doi: 10.15454/1.5572412770331912E12 (PMB), Institut National de la Recherche Agronomique (INRA), Groupe Limagrain, Biologie du fruit et pathologie (BFP), Université de Bordeaux (UB)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Laboratoire des Interactions Plantes Microbes Environnement (LIPME), Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Centre National de la Recherche Scientifique (CNRS)-AgroParisTech-Université Paris-Sud - Paris 11 (UP11)-Institut National de la Recherche Agronomique (INRA), Écophysiologie des Plantes sous Stress environnementaux (LEPSE), Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), 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)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), and ANR-10-BTBR-0001,AMAIZING,Développer de nouvelles variétés de maïs pour une agriculture durable: une approche intégrée de la génomique à la sélection(2010)

Subjects
[SDV.GEN.GPL]Life Sciences [q-bio]/Genetics/Plants genetics, [SDV.BV.AP]Life Sciences [q-bio]/Vegetal Biology/Plant breeding, [SDV.BBM.GTP]Life Sciences [q-bio]/Biochemistry, Molecular Biology/Genomics [q-bio.GN], food and beverages
Abstract

International audience; Understanding the mechanisms of adaptation to the environment in cultivated plants is a promising way to meet the challenge of maintaining food security in the context of global warming. In the case of maize, high-throughput sequencing has revealed that structural variations represent a large part of the genome and could have huge phenotypic effects. Among these, Presence Absence Variants (PAVs) may be involved in adaptation of maize to its environment, but their contribution to the genetic determinism of traits and genotype by environment interactions remains largely unknown. To address this issue, we performed a genome-wide association study between two types of polymorphisms, SNPs and Insetions/Deletions (InDels), and molecular traits obtained from proteomics and metabolomics analyses. The genetic panel used for this study was composed of 254 dent inbred lines genotyped with 978,134 SNPs and 72,041 InDels. The latter encompassed from 37 to 129,700 pb, including thousands of PAVs that are not present in the B73 reference genome. Proteins and metabolites were quantified by mass spectrometry in leaf samples from F1 hybrids obtained by crossing the inbred lines with one flint tester line. Hybrid plants were grown under two watering conditions (well-watered and water deficit) in greenhouse. In total, we detected 61,225 QTLs associated with proteome or metabolome variations. Among these, 4,766 QTLs were exclusively detected by InDels. To take into account the difference of marker density between InDels and SNPs, we used a re-sampling approach which showed that there is no difference for effect size distribution of QTLs between InDels and SNPs and for the number of QTLs detected by InDels or SNPs. Additionally, the QTLs detected by the two types of polymorphism were equally distributed in the two watering conditions. Our results suggest that InDels and SNPs equally contributed to molecular trait variation and response to drought stress.

Published
2021

30. Chapter Eight - Plant genome-scale metabolic networks

Author

Gerlin, Léo, Frainay, Clément, Jourdan, Fabien, Baroukh, Caroline, Prigent, Sylvain, Science Direct, Laboratoire des Interactions Plantes Microbes Environnement (LIPME), Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Métabolisme et Xénobiotiques (ToxAlim-MeX), ToxAlim (ToxAlim), 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-Ecole d'Ingénieurs de Purpan (INPT - EI Purpan), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-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), Biologie du fruit et pathologie (BFP), Université de Bordeaux (UB)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), and Pierre Pétriacq, Alain Bouchereau

Subjects
Metabolic network, [SDV.BV]Life Sciences [q-bio]/Vegetal Biology, metabolic models, [SDV.BBM.BM]Life Sciences [q-bio]/Biochemistry, Molecular Biology/Molecular biology, [INFO]Computer Science [cs], Plant genome-scale, Plant-microorganism interaction, visualization
Abstract

International audience; With the development of plant metabolomics, projects like the 10,000 plants genome sequencing project and the growth of other omics, the amount of data describing plant metabolism has never been so big. Genome-scale metabolic models (GEMs) are widely used to integrate and study the available information, and to better understand global responses to metabolic changes.In the first part of this chapter, we will focus on the existing plant GEMs, their history, and the biological questions associated with their reconstruction. Those GEMs were initially reconstructed based on cell suspension systems, but current reconstructions are widely focused on multiorgans and multitissues models, requiring some model integration.Model integration is the focus of the second part of this chapter, with the study of biotic interactions with the integration of GEMs coming from plant-interacting microorganisms and their host plants, modeling either pathogenic and symbiotic interactions. Emphasis will be placed on modeling quantitative interaction between plants and microorganisms.Finally, the third part of this chapter describes how the visualization of networks could be used to improve the understanding of the models and the integration of different omics data, and how good representation of metabolic networks can help the user to perform diverse tasks and put knowledge in context.

Published
2021

31. BioImageIT: Integration of image data-management with analysis

Author

Leconte, Ludovic, Prigent, Sylvain, Maury, Léo, Valades Cruz, Cesar Augusto, Salamero, Jean, Kervrann, Charles, Kervrann, Charles, Space-timE RePresentation, Imaging and cellular dynamics of molecular COmplexes (SERPICO), Inria Rennes – Bretagne Atlantique, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Biologie Cellulaire et Cancer, and Institut Curie [Paris]-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)

Subjects
[INFO.INFO-TI] Computer Science [cs]/Image Processing [eess.IV], [INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV], [INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM], [INFO.INFO-BI] Computer Science [cs]/Bioinformatics [q-bio.QM]
Abstract

International audience; Open science and FAIR principles are major topics in the field of modern microscopy for biology. This is due to both new data acquisition technologies like super-resolution and light sheet microscopy that generate large datasets but also to the new data analysis methodologies such as deep learning that automated data mining with high accuracy. Nevertheless data are still rarely shared and annotated because this implies a lot of manual and tedious work and software packaging. We present BioImageIT an open source framework that integrates automation of image datamanagement with data processing. Scientists then only need to import their data once in BioImageIT, which automatically generates and manages the metadata every time an operation is performed on the data. This accelerates the data mining process with no need anymore to deal with IT integration and manual analysis and annotations. BioImageIT then automatically implements FAIR principles. The interest of bioImageIT is thus twice. Wewill illustrate this through diverse application workflows, including preprocessing of raw data, complex images reconstructions (i.e Lattice Light Sheet or Multi-Angle TIRF micrscopy), deconvolution/denoising (including DL approaches) and analysis (tracking).

Published
2021

33. Loss of light colour preference after chronic embryonic stress in rainbow trout fry: A novel and potential indicator of fish welfare?

Author

Colson, Violaine, primary, Ferreira, Vitor Hugo Bessa, additional, Luchiari, Ana Carolina, additional, Valotaire, Claudiane, additional, Borel, Frédéric, additional, Bugeon, Jérôme, additional, Prigent, Sylvain, additional, Dickel, Ludovic, additional, Calandreau, Ludovic, additional, and Guesdon, Vanessa, additional

Published
2021
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34. Overproduction of ascorbic acid impairs pollen fertility in tomato

Author

Deslous, Paul, primary, Bournonville, Céline, additional, Decros, Guillaume, additional, Okabe, Yoshihiro, additional, Mauxion, Jean-Philippe, additional, Jorly, Joana, additional, Gadin, Stéphanie, additional, Brès, Cécile, additional, Mori, Kentaro, additional, Ferrand, Carine, additional, Prigent, Sylvain, additional, Ariizumi, Tohru, additional, Ezura, Hiroshi, additional, Hernould, Michel, additional, Rothan, Christophe, additional, Pétriacq, Pierre, additional, Gibon, Yves, additional, and Baldet, Pierre, additional

Published
2021
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35. Maize metabolome and proteome responses to controlled cold stress partly mimic early‐sowing effects in the field and differ from those of Arabidopsis

Author

Urrutia, Maria, primary, Blein‐Nicolas, Mélisande, additional, Prigent, Sylvain, additional, Bernillon, Stéphane, additional, Deborde, Catherine, additional, Balliau, Thierry, additional, Maucourt, Mickaël, additional, Jacob, Daniel, additional, Ballias, Patricia, additional, Bénard, Camille, additional, Sellier, Hélène, additional, Gibon, Yves, additional, Giauffret, Catherine, additional, Zivy, Michel, additional, and Moing, Annick, additional

Published
2021
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36. BioImage-IT: Design data analysis workflows using tools from different languages and keep track of the metadata

Author

Prigent, Sylvain, Kervrann, Charles, Salamero, Jean, Space-timE RePresentation, Imaging and cellular dynamics of molecular COmplexes (SERPICO), Inria Rennes – Bretagne Atlantique, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), France-BioImaging, and Kervrann, Charles

Subjects
[SDV.IB] Life Sciences [q-bio]/Bioengineering, [INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB], [INFO.INFO-TI] Computer Science [cs]/Image Processing [eess.IV], [INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV], [INFO.INFO-DS]Computer Science [cs]/Data Structures and Algorithms [cs.DS], [INFO.INFO-DB] Computer Science [cs]/Databases [cs.DB], [INFO.INFO-DS] Computer Science [cs]/Data Structures and Algorithms [cs.DS], [SDV.IB]Life Sciences [q-bio]/Bioengineering, [INFO.INFO-IA]Computer Science [cs]/Computer Aided Engineering, [INFO.INFO-IA] Computer Science [cs]/Computer Aided Engineering, ComputingMilieux_MISCELLANEOUS
Abstract

International audience

Published
2020

37. BioImage-IT

Author

Prigent, Sylvain, Kervrann, Charles, Salamero, Jean, Space-timE RePresentation, Imaging and cellular dynamics of molecular COmplexes (SERPICO), Inria Rennes – Bretagne Atlantique, and Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)

Subjects
[INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV], [SDV.BC]Life Sciences [q-bio]/Cellular Biology, [INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM], ComputingMilieux_MISCELLANEOUS
Abstract

International audience

Published
2020

38. Biomass composition explains fruit relative growth rate and discriminates climacteric from non-climacteric species

Author

Roch, Léa, Prigent, Sylvain, Klose, Holger, Cakpo, Coffi-Belmys, Beauvoit, Bertrand, Deborde, Catherine, Fouillen, Laetitia, van Delft, Pierre, Jacob, Daniel, Usadel, Björn, Dai, Zhanwu, Génard, Michel, Vercambre, Gilles, Colombié, Sophie, Moing, Annick, Gibon, Yves, Biologie du fruit et pathologie (BFP), Université de Bordeaux (UB)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), RWTH Aachen University, Unité de recherche Plantes et Systèmes de Culture Horticoles (PSH), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Platetorme Métabolome Bordeaux, Institut National de la Recherche Agronomique (INRA), Laboratoire de biogenèse membranaire (LBM), Université Bordeaux Segalen - Bordeaux 2-Centre National de la Recherche Scientifique (CNRS), Ecophysiologie et Génomique Fonctionnelle de la Vigne (UMR EGFV), Université de Bordeaux (UB)-Institut des Sciences de la Vigne et du Vin (ISVV)-Ecole Nationale Supérieure des Sciences Agronomiques de Bordeaux-Aquitaine (Bordeaux Sciences Agro)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), ANR-11-INBS-0012,PHENOME,Centre français de phénomique végétale(2011), ANR-11-INBS-0010,METABOHUB,Développement d'une infrastructure française distribuée pour la métabolomique dédiée à l'innovation(2011), and ANR-15-CE20-0009,FRIMOUSS,Modélisation intégrative du fruit pour un système de sélection unifié(2015)

Subjects
AcademicSubjects/SCI01210, [SDV]Life Sciences [q-bio], Actinidia, Biomass composition, food and beverages, fruit, Ethylenes, Research Papers, climacteric, modelling, Plant Breeding, ddc:580, relative growth rate, [SDV.BV]Life Sciences [q-bio]/Vegetal Biology, Growth and Development, Biomass, metaphenomics, metabolism
Abstract

A comparison of eight fruit species (herbaceous, vines, and trees) throughout their development shows that biomass composition and fruit relative growth rate are closely linked., Fleshy fruits are very varied, whether in terms of their composition, physiology, or rate and duration of growth. To understand the mechanisms that link metabolism to phenotypes, which would help the targeting of breeding strategies, we compared eight fleshy fruit species during development and ripening. Three herbaceous (eggplant, pepper, and cucumber), three tree (apple, peach, and clementine) and two vine (kiwifruit and grape) species were selected for their diversity. Fruit fresh weight and biomass composition, including the major soluble and insoluble components, were determined throughout fruit development and ripening. Best-fitting models of fruit weight were used to estimate relative growth rate (RGR), which was significantly correlated with several biomass components, especially protein content (R=84), stearate (R=0.72), palmitate (R=0.72), and lignocerate (R=0.68). The strong link between biomass composition and RGR was further evidenced by generalized linear models that predicted RGR with R-values exceeding 0.9. Comparison of the fruit also showed that climacteric fruit (apple, peach, kiwifruit) contained more non-cellulosic cell-wall glucose and fucose, and more starch, than non-climacteric fruit. The rate of starch net accumulation was also higher in climacteric fruit. These results suggest that the way biomass is constructed has a major influence on performance, especially growth rate.

Published
2020

40. Proton-NMR Metabolomics of Rainbow Trout Fed a Plant-Based Diet Supplemented with Graded Levels of a Protein-Rich Yeast Fraction Reveal Several Metabolic Processes Involved in Growth

Author

Roques, Simon, primary, Deborde, Catherine, additional, Richard, Nadège, additional, Marchand, Yann, additional, Larroquet, Laurence, additional, Prigent, Sylvain, additional, Skiba-Cassy, Sandrine, additional, Moing, Annick, additional, and Fauconneau, Benoit, additional

Published
2020
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44. Regulation of Pyridine Nucleotide Metabolism During Tomato Fruit Development Through Transcript and Protein Profiling

Author

Decros, Guillaume, primary, Beauvoit, Bertrand, additional, Colombié, Sophie, additional, Cabasson, Cécile, additional, Bernillon, Stéphane, additional, Arrivault, Stéphanie, additional, Guenther, Manuela, additional, Belouah, Isma, additional, Prigent, Sylvain, additional, Baldet, Pierre, additional, Gibon, Yves, additional, and Pétriacq, Pierre, additional

Published
2019
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45. MetaboHUB-Bordeaux

Author

Bernillon, Stéphane, Cabasson, Cecile, CASSAN, Cédric, Da Costa, Grégory, Deborde, Catherine, Flandin, Amélie, Fouillen, Laetitia, Gibon, Yves, Jacob, Daniel, Moing, Annick, Mongrand, Sebastien, Pedrot, Eric, Pétriacq, Pierre, Prigent, Sylvain, Renouf, Elodie, Richard, Tristan, Rolin, Dominique, Rouger, Caroline, Valls, Josep, Van Delft, Pierre, Biologie du fruit et pathologie (BFP), Université de Bordeaux (UB)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Plateforme Metabolome Bordeaux, INRAE, 2018, MetaboHUB, Centre INRAE Nouvelle Aquitaine Bordeaux, doi: 10.15454/1.5572412770331912E12 (PMB), Institut National de la Recherche Agronomique (INRA), Unité de Recherche Oenologie [Villenave d'Ornon], Université de Bordeaux (UB)-Institut des Sciences de la Vigne et du Vin (ISVV)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Laboratoire de biogenèse membranaire (LBM), Université Bordeaux Segalen - Bordeaux 2-Centre National de la Recherche Scientifique (CNRS), Polyphénols Biotech (EA 3675), and Université Bordeaux Segalen - Bordeaux 2

Subjects
[INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB], Métabolisme, [CHIM.ANAL]Chemical Sciences/Analytical chemistry, [SDV.BV]Life Sciences [q-bio]/Vegetal Biology, [SDV.BBM]Life Sciences [q-bio]/Biochemistry, Molecular Biology, Metabohub, [INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM], ComputingMilieux_MISCELLANEOUS, Métabolomique, [SDV.BV.PEP]Life Sciences [q-bio]/Vegetal Biology/Phytopathology and phytopharmacy
Abstract

International audience

Published
2019

46. Using metabolomic data to predict Maize yield

Author

Prigent, Sylvain, Fernandez, Olivier, Bernillon, Stéphane, Pétriacq, Pierre, Moing, Annick, Berton, Thierry, Cabrera-Bosquet, Llorenç, Millet, Émilie, Welcker, Claude, Tardieu, François, Gibon, Yves, Biologie du fruit et pathologie (BFP), Université de Bordeaux (UB)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Plateforme Metabolome MetaboHUB INRA Nouvelle Aquitaine, Institut National de la Recherche Agronomique (INRA), Écophysiologie des Plantes sous Stress environnementaux (LEPSE), Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), 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)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), and Gauthier, Muriel

Subjects
[SDV] Life Sciences [q-bio], Métabolome, Plante céréalière, Métabolisme, [SDV]Life Sciences [q-bio], Métabolite, Maïs, [SDV.BV]Life Sciences [q-bio]/Vegetal Biology, [SDV.BV] Life Sciences [q-bio]/Vegetal Biology, rendement, ComputingMilieux_MISCELLANEOUS, Métabolomique
Abstract

International audience

Published
2019

47. Leaf metabolite profiling reveals biochemical diversities within wheat genetic resources

Author

Petriacq, Pierre, Flandin, Amélie, Prigent, Sylvain, Bernillon, Stéphane, CASSAN, Cédric, Rolin, Dominique, Rincent, Renaud, Salon, Christophe, Le Gouis, Jacques, Gibon, Yves, Moing, Annick, Bernard, Nathalie, Développement d'une infrastructure française distribuée pour la métabolomique dédiée à l'innovation - - METABOHUB2011 - ANR-11-INBS-0010 - INBS - VALID, Infrastructures - Centre français de phénomique végétale - - PHENOME2011 - ANR-11-INBS-0012 - INBS - VALID, Biotech - Bioressources - Développer de nouvelles variétés de blé pour une agriculture durable - - BREEDWHEAT2010 - ANR-10-BTBR-0003 - BTBR - VALID, University of Sheffield [Sheffield], Biologie du fruit et pathologie (BFP), Université Bordeaux Segalen - Bordeaux 2-Institut National de la Recherche Agronomique (INRA)-Université Sciences et Technologies - Bordeaux 1 (UB), Génétique Diversité et Ecophysiologie des Céréales (GDEC), Institut National de la Recherche Agronomique (INRA)-Université Clermont Auvergne [2017-2020] (UCA [2017-2020]), Agroécologie [Dijon], Institut National de la Recherche Agronomique (INRA)-Université de Bourgogne (UB)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement-Université Bourgogne Franche-Comté [COMUE] (UBFC), Plateforme Bordeaux Metabolome, Université de Bordeaux (UB)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-MetaboHUB-Bordeaux, MetaboHUB-MetaboHUB, FSOV {2016K], Metabolomics Society, ANR-11-INBS-0010,METABOHUB,Développement d'une infrastructure française distribuée pour la métabolomique dédiée à l'innovation(2011), ANR-11-INBS-0012,PHENOME,Centre français de phénomique végétale(2011), ANR-10-BTBR-0003,BREEDWHEAT,Développer de nouvelles variétés de blé pour une agriculture durable(2010), Université Sciences et Technologies - Bordeaux 1-Université Bordeaux Segalen - Bordeaux 2-Institut National de la Recherche Agronomique (INRA), Université de Bourgogne (UB)-Institut National de la Recherche Agronomique (INRA)-Université Bourgogne Franche-Comté [COMUE] (UBFC)-AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement, Plateforme Métabolome [Bordeaux] (PMB), and Institut National de la Recherche Agronomique (INRA)

Subjects
[SDV] Life Sciences [q-bio], [SDV]Life Sciences [q-bio], [SDV.BV]Life Sciences [q-bio]/Vegetal Biology, [SDV.BV] Life Sciences [q-bio]/Vegetal Biology, ComputingMilieux_MISCELLANEOUS
Abstract

Session : Plant, food, enviromenal and microbial, Poster P-422; International audience

Published
2019

48. Comparative Transcriptome Analysis Shows Conserved Metabolic Regulation during Production of Secondary Metabolites in Filamentous Fungi

Author

Nielsen, Jens, Prigent, Sylvain, Grijseels, Sietske, Workman, Mhairi, Ji, Boyang, Nielsen, Jens, Prigent, Sylvain, Grijseels, Sietske, Workman, Mhairi, and Ji, Boyang

Abstract

Filamentous fungi possess great potential as sources of medicinal bioactive compounds, such as antibiotics, but efficient production is hampered by a limited understanding of how their metabolism is regulated. We investigated the metabolism of six secondary metabolite-producing fungi of the Penicillium genus during nutrient depletion in the stationary phase of batch fermentations and assessed conserved metabolic responses across species using genome-wide transcriptional profiling. A coexpression analysis revealed that expression of biosynthetic genes correlates with expression of genes associated with pathways responsible for the generation of precursor metabolites for secondary metabolism. Our results highlight the main metabolic routes for the supply of precursors for secondary metabolism and suggest that the regulation of fungal metabolism is tailored to meet the demands for secondary metabolite production. These findings can aid in identifying fungal species that are optimized for the production of specific secondary metabolites and in designing metabolic engineering strategies to develop high-yielding fungal cell factories for production of secondary metabolites. IMPORTANCE Secondary metabolites are a major source of pharmaceuticals, especially antibiotics. However, the development of efficient processes of production of secondary metabolites has proved troublesome due to a limited understanding of the metabolic regulations governing secondary metabolism. By analyzing the conservation in gene expression across secondary metabolite-producing fungal species, we identified a metabolic signature that links primary and secondary metabolism and that demonstrates that fungal metabolism is tailored for the efficient production of secondary metabolites. The insight that we provide can be used to develop high-yielding fungal cell factories that are optimized for the production of specific secondary metabolites of pharmaceutical interest.

Published
2019

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