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1. Genome-scale community modelling reveals conserved metabolic cross-feedings in epipelagic bacterioplankton communities

Author

Nils Giordano, Marinna Gaudin, Camille Trottier, Erwan Delage, Charlotte Nef, Chris Bowler, and Samuel Chaffron

Subjects
Science
Abstract

Abstract Marine microorganisms form complex communities of interacting organisms that influence central ecosystem functions in the ocean such as primary production and nutrient cycling. Identifying the mechanisms controlling their assembly and activities is a major challenge in microbial ecology. Here, we integrated Tara Oceans meta-omics data to predict genome-scale community interactions within prokaryotic assemblages in the euphotic ocean. A global genome-resolved co-activity network revealed a significant number of inter-lineage associations across diverse phylogenetic distances. Identified co-active communities include species displaying smaller genomes but encoding a higher potential for quorum sensing, biofilm formation, and secondary metabolism. Community metabolic modelling reveals a higher potential for interaction within co-active communities and points towards conserved metabolic cross-feedings, in particular of specific amino acids and group B vitamins. Our integrated ecological and metabolic modelling approach suggests that genome streamlining and metabolic auxotrophies may act as joint mechanisms shaping bacterioplankton community assembly in the global ocean surface.

Published
2024
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2. Gut Microbiota Remodeling and Intestinal Adaptation to Lipid Malabsorption After Enteroendocrine Cell Loss in Adult MiceSummary

Author

Florence Blot, Justine Marchix, Miriam Ejarque, Sara Jimenez, Aline Meunier, Céline Keime, Camille Trottier, Mikaël Croyal, Céline Lapp, Maxime M. Mahe, Adèle De Arcangelis, and Gérard Gradwohl

Subjects
Enteroendocrine Cells, Food Efficiency, Lipid Absorption, Microbiota, Diseases of the digestive system. Gastroenterology, RC799-869
Abstract

Background & Aims: Enteroendocrine cells (EECs) and their hormones are essential regulators of whole-body energy homeostasis. EECs sense luminal nutrients and microbial metabolites and subsequently secrete various hormones acting locally or at a distance. Impaired development of EECs during embryogenesis is life-threatening in newborn mice and humans due to compromised nutrient absorption. However, the physiological importance of the EEC system in adult mice has yet to be directedly studied. Herein, we aimed to determine the long-term consequences of a total loss of EECs in healthy adults on energy metabolism, intestinal transcriptome, and microbiota. Methods: We depleted intestinal EECs by tamoxifen treatment of adult Neurog3fl/fl; Villin-CreERT2 male mice. We studied intestinal cell differentiation, food efficiency, lipid absorption, microbiota composition, fecal metabolites, and transcriptomic responses in the proximal and distal small intestines of mice lacking EECs. We also determined the high-fat diet-induced transcriptomic changes in sorted Neurog3eYFP/+ EECs. Results: Induction of EEC deficiency in adults is not life-threatening unless fed with a high-fat diet. Under a standard chow diet, mice lose 10% of weight due to impaired food efficiency. Blood concentrations of cholesterol, triglycerides, and free fatty acids are reduced, and lipid absorption is impaired and delayed in the distal small intestine. Genes controlling lipogenesis, carbohydrate metabolism, and neoglucogenesis are upregulated. Microbiota composition is rapidly altered after EECs depletion and is characterized by decreased α-diversity. Bacteroides and Lactobacillus were progressively enriched, whereas Lachnospiraceae declined without impacting fecal short-chain fatty acid concentrations. Conclusions: EECs are dispensable for survival in adult male mice under a standard chow diet. The absence of EECs impairs intestinal lipid absorption, leading to transcriptomic and metabolic adaptations and remodeling of the gut microbiota.

Published
2023
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3. Damage Localization on Composite Structures Based on the Delay-and-Sum Algorithm Using Simulation and Experimental Methods

Author

Cedric Bertolt Nzouatchoua, Mourad Bentahar, Silvio Montresor, Nicolas Colin, Vincent Le Cam, Camille Trottier, and Nicolas Terrien

Subjects
structural health monitoring, PZT network, Lamb waves, anisotropic composite structures, impact damage, delay-and-sum, Chemical technology, TP1-1185
Abstract

Damage detection and localization based on ultrasonic guided waves revealed to be promising for structural health monitoring and nondestructive testing. However, the use of a piezoelectric sensor’s network to locate and image damaged areas in composite structures requires a number of precautions including the consideration of anisotropy and baseline signals. The lack of information related to these two parameters drastically deteriorates the imaging performance of numerous signal processing methods. To avoid such deterioration, the present contribution proposes different methods to build baseline signals in different types of composites. Baseline signals are first constructed from a numerical simulation model using the previously determined elasticity tensor of the structure. Since the latter tensor is not always easy to obtain especially in the case of anisotropic materials, a second PZT network is used in order to obtain signals related to Lamb waves propagating in different directions. Waveforms are then translated according to a simplified theoretical propagation model of Lamb waves in homogeneous structures. The application of the different methods on transversely isotropic, unidirectional and quasi-transversely isotropic composites allows to have satisfactory images that well represent the damaged areas with the help of the delay-and-sum algorithm.

Published
2023
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4. Inferring Biochemical Reactions and Metabolite Structures to Understand Metabolic Pathway Drift

Author

Arnaud Belcour, Jean Girard, Méziane Aite, Ludovic Delage, Camille Trottier, Charlotte Marteau, Cédric Leroux, Simon M. Dittami, Pierre Sauleau, Erwan Corre, Jacques Nicolas, Catherine Boyen, Catherine Leblanc, Jonas Collén, Anne Siegel, and Gabriel V. Markov

Subjects
Science
Abstract

Summary: Inferring genome-scale metabolic networks in emerging model organisms is challenged by incomplete biochemical knowledge and partial conservation of biochemical pathways during evolution. Therefore, specific bioinformatic tools are necessary to infer biochemical reactions and metabolic structures that can be checked experimentally. Using an integrative approach combining genomic and metabolomic data in the red algal model Chondrus crispus, we show that, even metabolic pathways considered as conserved, like sterols or mycosporine-like amino acid synthesis pathways, undergo substantial turnover. This phenomenon, here formally defined as “metabolic pathway drift,” is consistent with findings from other areas of evolutionary biology, indicating that a given phenotype can be conserved even if the underlying molecular mechanisms are changing. We present a proof of concept with a methodological approach to formalize the logical reasoning necessary to infer reactions and molecular structures, abstracting molecular transformations based on previous biochemical knowledge. : Bioinformatics; Genomics; Metabolomics Subject Areas: Bioinformatics, Genomics, Metabolomics

Published
2020
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5. Traceability, reproducibility and wiki-exploration for 'à-la-carte' reconstructions of genome-scale metabolic models.

Author

Méziane Aite, Marie Chevallier, Clémence Frioux, Camille Trottier, Jeanne Got, María Paz Cortés, Sebastián N Mendoza, Grégory Carrier, Olivier Dameron, Nicolas Guillaudeux, Mauricio Latorre, Nicolás Loira, Gabriel V Markov, Alejandro Maass, and Anne Siegel

Subjects
Biology (General), QH301-705.5
Abstract

Genome-scale metabolic models have become the tool of choice for the global analysis of microorganism metabolism, and their reconstruction has attained high standards of quality and reliability. Improvements in this area have been accompanied by the development of some major platforms and databases, and an explosion of individual bioinformatics methods. Consequently, many recent models result from "à la carte" pipelines, combining the use of platforms, individual tools and biological expertise to enhance the quality of the reconstruction. Although very useful, introducing heterogeneous tools, that hardly interact with each other, causes loss of traceability and reproducibility in the reconstruction process. This represents a real obstacle, especially when considering less studied species whose metabolic reconstruction can greatly benefit from the comparison to good quality models of related organisms. This work proposes an adaptable workspace, AuReMe, for sustainable reconstructions or improvements of genome-scale metabolic models involving personalized pipelines. At each step, relevant information related to the modifications brought to the model by a method is stored. This ensures that the process is reproducible and documented regardless of the combination of tools used. Additionally, the workspace establishes a way to browse metabolic models and their metadata through the automatic generation of ad-hoc local wikis dedicated to monitoring and facilitating the process of reconstruction. AuReMe supports exploration and semantic query based on RDF databases. We illustrate how this workspace allowed handling, in an integrated way, the metabolic reconstructions of non-model organisms such as an extremophile bacterium or eukaryote algae. Among relevant applications, the latter reconstruction led to putative evolutionary insights of a metabolic pathway.

Published
2018
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6. Combining graph and flux-based structures to decipher phenotypic essential metabolites within metabolic networks

Author

Julie Laniau, Clémence Frioux, Jacques Nicolas, Caroline Baroukh, Maria-Paz Cortes, Jeanne Got, Camille Trottier, Damien Eveillard, and Anne Siegel

Subjects
Graph-based analysis, Constraint-based analysis, Metabolic networks, Answer Set Programming, Essential metabolite, Medicine, Biology (General), QH301-705.5
Abstract

Background The emergence of functions in biological systems is a long-standing issue that can now be addressed at the cell level with the emergence of high throughput technologies for genome sequencing and phenotyping. The reconstruction of complete metabolic networks for various organisms is a key outcome of the analysis of these data, giving access to a global view of cell functioning. The analysis of metabolic networks may be carried out by simply considering the architecture of the reaction network or by taking into account the stoichiometry of reactions. In both approaches, this analysis is generally centered on the outcome of the network and considers all metabolic compounds to be equivalent in this respect. As in the case of genes and reactions, about which the concept of essentiality has been developed, it seems, however, that some metabolites play crucial roles in system responses, due to the cell structure or the internal wiring of the metabolic network. Results We propose a classification of metabolic compounds according to their capacity to influence the activation of targeted functions (generally the growth phenotype) in a cell. We generalize the concept of essentiality to metabolites and introduce the concept of the phenotypic essential metabolite (PEM) which influences the growth phenotype according to sustainability, producibility or optimal-efficiency criteria. We have developed and made available a tool, Conquests, which implements a method combining graph-based and flux-based analysis, two approaches that are usually considered separately. The identification of PEMs is made effective by using a logical programming approach. Conclusion The exhaustive study of phenotypic essential metabolites in six genome-scale metabolic models suggests that the combination and the comparison of graph, stoichiometry and optimal flux-based criteria allows some features of the metabolic network functionality to be deciphered by focusing on a small number of compounds. By considering the best combination of both graph-based and flux-based techniques, the Conquests python package advocates for a broader use of these compounds both to facilitate network curation and to promote a precise understanding of metabolic phenotype.

Published
2017
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8. Combined in vivo and in situ genome-resolved metagenomics reveals novel symbiotic nitrogen fixing interactions between non-cyanobacterial diazotrophs and microalgae

Author

UDITA CHANDOLA, CAMILLE TROTTIER, MARINNA GAUDIN, ERIC MANIRAKIZA, SAMUEL MENICOT, ISABELLE LOUVET, THOMAS LACOUR, TIMOTHEE CHAUMIER, ATSUKO TANAKA, Samuel Chaffron, Leila Tirichine, Unité en Sciences Biologiques et Biotechnologies de Nantes (US2B), Centre National de la Recherche Scientifique (CNRS)-Nantes Université - UFR de Médecine et des Techniques Médicales (Nantes Univ - UFR MEDECINE), Nantes Université - pôle Santé, Nantes Université (Nantes Univ)-Nantes Université (Nantes Univ)-Nantes Université - pôle Santé, Nantes Université (Nantes Univ)-Nantes Université (Nantes Univ), Laboratoire des Sciences du Numérique de Nantes (LS2N), Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-École Centrale de Nantes (Nantes Univ - ECN), Nantes Université (Nantes Univ)-Nantes Université (Nantes Univ)-Nantes université - UFR des Sciences et des Techniques (Nantes univ - UFR ST), Nantes Université - pôle Sciences et technologie, Nantes Université (Nantes Univ)-Nantes Université (Nantes Univ)-Nantes Université - pôle Sciences et technologie, Nantes Université (Nantes Univ), Global Oceans Systems Ecology & Evolution - Tara Oceans (GOSEE), Université de Perpignan Via Domitia (UPVD)-École Pratique des Hautes Études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Aix Marseille Université (AMU)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université d'Évry-Val-d'Essonne (UEVE)-Université de Toulon (UTLN)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes [2016-2019] (UGA [2016-2019])-Institut de Recherche pour le Développement (IRD [France-Nord])-Ecole Normale Supérieure Paris-Saclay (ENS Paris Saclay)-European Molecular Biology Laboratory (EMBL)-École Centrale de Nantes (Nantes Univ - ECN), Nantes Université (Nantes Univ)-Nantes Université (Nantes Univ)-Université australe du Chili, Chimie Et Interdisciplinarité : Synthèse, Analyse, Modélisation (CEISAM), Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS)-Nantes université - UFR des Sciences et des Techniques (Nantes univ - UFR ST), Laboratoire Physiologie des Microalgues (PHYSALG), Physiologie et Toxines des Microalgues Toxiques et Nuisibles (PHYTOX), Institut Français de Recherche pour l'Exploitation de la Mer (IFREMER)-Institut Français de Recherche pour l'Exploitation de la Mer (IFREMER), Department of Chemistry, Biology and Marine Science, University of the Ryukyus [Okinawa], Unité en Sciences Biologiques et Biotechnologies de Nantes - UMR CNRS 6286 (US2B), Nantes Université - UFR de Médecine et des Techniques Médicales (Nantes Univ - UFR MEDECINE), unité de recherche de l'institut du thorax UMR1087 UMR6291 (ITX), Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS)-Université de Nantes - UFR de Médecine et des Techniques Médicales (UFR MEDECINE), Université de Nantes (UN)-Université de Nantes (UN), Nutrition, Métabolismes et Cancer (NuMeCan), Institut National de la Recherche Agronomique (INRA)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National de la Santé et de la Recherche Médicale (INSERM), Université de Nantes - UFR des Sciences et des Techniques (UN UFR ST), Université de Nantes (UN)-Université de Nantes (UN)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS), Unité de Recherche Génomique Info (URGI), Institut National de la Recherche Agronomique (INRA), National Cardiovascular Center, Université de Nantes (UN)-Université de Nantes (UN)-École Centrale de Nantes (ECN)-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), Tara Oceans-GOSEE (FR2022), and Faculty of Science - University of Nantes

Subjects
[SDV.EE.ECO]Life Sciences [q-bio]/Ecology, environment/Ecosystems, [SDV.BBM.GTP]Life Sciences [q-bio]/Biochemistry, Molecular Biology/Genomics [q-bio.GN], [SDV.BBM.MN]Life Sciences [q-bio]/Biochemistry, Molecular Biology/Molecular Networks [q-bio.MN], [SDE.BE]Environmental Sciences/Biodiversity and Ecology, [SDV.BIBS]Life Sciences [q-bio]/Quantitative Methods [q-bio.QM], [SDV.EE.IEO]Life Sciences [q-bio]/Ecology, environment/Symbiosis
Abstract

Non-cyanobacteria diazotrophs (NCDs) were shown to dominate in surface waters shifting the long-held paradigm of cyanobacteria dominance and raising fundamental questions on how these putative heterotrophic bacteria thrive in sunlit oceans. Here, we report an unprecedented finding in the widely used model diatom Phaeodactylum tricornutum (Pt) of NCDs sustaining diatom cells in the absence of bioavailable nitrogen. We identified PtNCDs using metagenomics sequencing and detected nitrogenase gene in silico and/or by PCR. We demonstrated nitrogen fixation in PtNCDs and their close genetic affiliation with NCDs from the environment. We showed the wide occurrence of this type of symbiosis with the isolation of NCDs from other microalgae, their identification in the environment, and predicted their associations with photosynthetic microalgae. Overall, this study provides evidence for a previously overlooked symbiosis using a multidisciplinary model-based approach, which will help understand the different players driving global marine nitrogen fixation.

Published
2023
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9. Inferring Biochemical Reactions and Metabolite Structures to Understand Metabolic Pathway Drift

Author

Pierre Sauleau, Camille Trottier, Catherine Boyen, Arnaud Belcour, Simon M. Dittami, Gabriel V. Markov, Jean Girard, Charlotte Marteau, Anne Siegel, Jonas Collén, Cédric Leroux, Méziane Aite, Ludovic Delage, Jacques Nicolas, Catherine Leblanc, Erwan Corre, Dynamics, Logics and Inference for biological Systems and Sequences (Dyliss), Inria Rennes – Bretagne Atlantique, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-GESTION DES DONNÉES ET DE LA CONNAISSANCE (IRISA-D7), Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), Laboratoire de Biologie Intégrative des Modèles Marins (LBI2M), Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Station biologique de Roscoff (SBR), Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), Laboratoire de Biotechnologie et Chimie Marines (LBCM), Université de Bretagne Sud (UBS)-Université de Brest (UBO)-Institut Universitaire Européen de la Mer (IUEM), Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Brest (UBO)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS), Station biologique de Roscoff (SBR), Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Fédération de recherche de Roscoff (FR2424), Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), ABiMS - Informatique et bioinformatique = Analysis and Bioinformatics for Marine Science (ABIMS), Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Station biologique de Roscoff (SBR), Scalable, Optimized and Parallel Algorithms for Genomics (GenScale), ANR-10-BTBR-04, Agence Nationale de la Recherche, 9673, Région Bretagne, Université de Bretagne Sud (UBS)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National de Recherche en Informatique et en Automatique (Inria)-École normale supérieure - Rennes (ENS Rennes)-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-CentraleSupélec-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Université de Bretagne Sud (UBS)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-École normale supérieure - Rennes (ENS Rennes)-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes 1 (UR1), ABiMS - Informatique et bioinformatique = Analysis and Bioinformatics for Marine Science (FR2424), Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Université de Rennes 1 (UR1), and Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique)

Subjects
0301 basic medicine, Bioinformatics, Metabolite, ved/biology.organism_classification_rank.species, Genomics, 02 engineering and technology, Computational biology, Biology, Article, 03 medical and health sciences, chemistry.chemical_compound, Metabolomics, Chondrus crispus, Genome-scale metabolic network, Model organism, lcsh:Science, Gene, Amino acid synthesis, chemistry.chemical_classification, Metabolic pathway drift, Multidisciplinary, ved/biology, food and beverages, Mycosporine-like amino acid, 021001 nanoscience & nanotechnology, Phenotype, 3. Good health, Metabolic pathway, Sterols, 030104 developmental biology, chemistry, lcsh:Q, [INFO.INFO-BI]Computer Science [cs]/Bioinformatics [q-bio.QM], 0210 nano-technology
Abstract

Summary Inferring genome-scale metabolic networks in emerging model organisms is challenged by incomplete biochemical knowledge and partial conservation of biochemical pathways during evolution. Therefore, specific bioinformatic tools are necessary to infer biochemical reactions and metabolic structures that can be checked experimentally. Using an integrative approach combining genomic and metabolomic data in the red algal model Chondrus crispus, we show that, even metabolic pathways considered as conserved, like sterols or mycosporine-like amino acid synthesis pathways, undergo substantial turnover. This phenomenon, here formally defined as “metabolic pathway drift,” is consistent with findings from other areas of evolutionary biology, indicating that a given phenotype can be conserved even if the underlying molecular mechanisms are changing. We present a proof of concept with a methodological approach to formalize the logical reasoning necessary to infer reactions and molecular structures, abstracting molecular transformations based on previous biochemical knowledge., Graphical Abstract, Highlights • Combination of metabolite profiling and genome-scale metabolic networks analysis • New method to infer biochemical reactions and metabolites in promiscuous pathways • Red algal model for sterol and mycosporine-like amino acid biosynthesis pathways • Metabolic drift if pathway variation despite conserved initial and final metabolites, Bioinformatics; Genomics; Metabolomics

Published
2020
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10. The genome of Ectocarpus subulatus – A highly stress-tolerant brown alga

Author

Erwan Corre, Didier Jollivet, Xi Liu, Jonas Collén, Noé Pontoizeau, Thierry Tonon, Simon M. Dittami, Gabriel V. Markov, Alexandre Cormier, Dominique Marie, Hwan Su Yoon, Catherine Leblanc, Loraine Brillet-Guéguen, Camille Trottier, Akira F. Peters, André E. Minoche, Sylvie Doubleau, Komlan Avia, Misharl Monsoor, Amandine Siméon, Angélique Gobet, Hetty KleinJan, Catherine Boyen, Christophe Caron, Agnieszka P. Lipinska, Chung Hyun Cho, Clémence Frioux, Agnès Groisillier, Marie-Mathilde Perrineau, Pierre Pericard, Irene González-Navarrete, Heinz Himmelbauer, Cécile Hervé, Méziane Aite, Anne Siegel, Ludovic Delage, Laboratoire de Biologie Intégrative des Modèles Marins (LBI2M), Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Station biologique de Roscoff (SBR), Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), Végétaux marins et biomolécules, Station biologique de Roscoff [Roscoff] (SBR), Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS)-GOEMAR-Centre National de la Recherche Scientifique (CNRS), ABiMS - Informatique et bioinformatique = Analysis and Bioinformatics for Marine Science (FR2424), Station biologique de Roscoff (SBR), Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS), Dynamics, Logics and Inference for biological Systems and Sequences (Dyliss), Inria Rennes – Bretagne Atlantique, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-GESTION DES DONNÉES ET DE LA CONNAISSANCE (IRISA-D7), Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Université de Bretagne Sud (UBS)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Université de Rennes (UNIV-RENNES)-Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Université de Rennes (UNIV-RENNES)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Rennes (ENS Rennes)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Université de Rennes (UNIV-RENNES), Santé de la vigne et qualité du vin (SVQV), Institut National de la Recherche Agronomique (INRA)-Université de Strasbourg (UNISTRA), Unité Mathématique Informatique et Génome (MIG), Institut National de la Recherche Agronomique (INRA), Diversité, adaptation, développement des plantes (UMR DIADE), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud]), from patterns to models in computational biodiversity and biotechnology (PLEIADE), Laboratoire Bordelais de Recherche en Informatique (LaBRI), Centre National de la Recherche Scientifique (CNRS)-École Nationale Supérieure d'Électronique, Informatique et Radiocommunications de Bordeaux (ENSEIRB)-Université Sciences et Technologies - Bordeaux 1-Université Bordeaux Segalen - Bordeaux 2-Centre National de la Recherche Scientifique (CNRS)-École Nationale Supérieure d'Électronique, Informatique et Radiocommunications de Bordeaux (ENSEIRB)-Université Sciences et Technologies - Bordeaux 1-Université Bordeaux Segalen - Bordeaux 2-Inria Bordeaux - Sud-Ouest, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Biodiversité, Gènes & Communautés (BioGeCo), Université de Bordeaux (UB)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université de Bordeaux (UB)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Evolution des Protistes et Ecosystèmes Pélagiques (EPEP), Adaptation et diversité en milieu marin (AD2M), Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Station biologique de Roscoff [Roscoff] (SBR), Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), Centre for Genomic Regulation [Barcelona] (CRG), Universitat Pompeu Fabra [Barcelona]-Centro Nacional de Analisis Genomico [Barcelona] (CNAG), Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS), Tereos, ECOlogy of MArine Plankton (ECOMAP), Centre National de la Recherche Scientifique (CNRS)-Station biologique de Roscoff (SBR), Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Station biologique de Roscoff (SBR), Institut de Génomique Fonctionnelle de Lyon (IGFL), École normale supérieure - Lyon (ENS Lyon)-Institut National de la Recherche Agronomique (INRA)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon, Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189 (CRIStAL), Ecole Centrale de Lille-Université de Lille-Centre National de la Recherche Scientifique (CNRS), Laboratoire des symbioses tropicales et méditerranéennes (UMR LSTM), Université Montpellier 1 (UM1)-Institut de Recherche pour le Développement (IRD)-Institut National de la Recherche Agronomique (INRA)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)-Université de Montpellier (UM)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Université Montpellier 2 - Sciences et Techniques (UM2), University of Aberdeen, Centre National de la Recherche Scientifique (CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Station biologique de Roscoff [Roscoff] (SBR), Université Pierre et Marie Curie - Paris 6 (UPMC)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), DMAS, ONERA, Université Paris Saclay [Châtillon], ONERA-Université Paris-Saclay, Sung Kyun Kwan University, Max-Planck-Institut für Molekulare Genetik (MPIMG), Max-Planck-Gesellschaft, ABiMS - Informatique et bioinformatique = Analysis and Bioinformatics for Marine Science (ABIMS), Fédération de recherche de Roscoff (FR2424), Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Station biologique de Roscoff (SBR), Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Université de Rennes (UR)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Institut de Recherche en Informatique et Systèmes Aléatoires (IRISA), Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), Sungkyunkwan University [Suwon] (SKKU), Universitat Pompeu Fabra [Barcelona] (UPF)-Centro Nacional de Analisis Genomico [Barcelona] (CNAG), Key Laboratory of Intelligent Information Processing, Institute of Computing Technology [Beijing], Chinese Academy of Sciences [Changchun Branch] (CAS), Bezhin Rosko, Université de Rennes (UR), Université de Strasbourg (UNISTRA)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Université de Bordeaux (UB)-École Nationale Supérieure d'Électronique, Informatique et Radiocommunications de Bordeaux (ENSEIRB)-Centre National de la Recherche Scientifique (CNRS)-Université de Bordeaux (UB)-École Nationale Supérieure d'Électronique, Informatique et Radiocommunications de Bordeaux (ENSEIRB)-Centre National de la Recherche Scientifique (CNRS)-Inria Bordeaux - Sud-Ouest, Université de Bordeaux (UB)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Adaptation et diversité en milieu marin (ADMM), Institut national des sciences de l'Univers (INSU - CNRS)-Station biologique de Roscoff (SBR), Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut national des sciences de l'Univers (INSU - CNRS)-Station biologique de Roscoff (SBR), Max Planck Institute for Molecular Genetics (MPIMG), University of York [York, UK], This work was funded partially by ANR project IDEALG (ANR-10-BTBR-04) 14'Investissements d’Avenir, Biotechnologies-Bioressources', the European Union’s Horizon 2020 research and innovation Programme under the Marie Sklodowska-Curie grant agreement number 624575 (ALFF), and the CNRS Momentum call. Sequencing was performed at the Genomics Unit of the Centre for Genomic Regulation (CRG), Barcelona, Spain, Institut de Recherche pour le Développement (IRD [France-Sud])-Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad), Université de Bordeaux (UB)-Centre National de la Recherche Scientifique (CNRS)-École Nationale Supérieure d'Électronique, Informatique et Radiocommunications de Bordeaux (ENSEIRB)-Université de Bordeaux (UB)-Centre National de la Recherche Scientifique (CNRS)-École Nationale Supérieure d'Électronique, Informatique et Radiocommunications de Bordeaux (ENSEIRB)-Inria Bordeaux - Sud-Ouest, Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-Institut National de Recherche en Informatique et en Automatique (Inria)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Université de Rennes 1 (UR1), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Bretagne Sud (UBS)-École normale supérieure - Rennes (ENS Rennes)-CentraleSupélec-Centre National de la Recherche Scientifique (CNRS)-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), Université de Bretagne Sud (UBS)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National de Recherche en Informatique et en Automatique (Inria)-École normale supérieure - Rennes (ENS Rennes)-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-CentraleSupélec-IMT Atlantique Bretagne-Pays de la Loire (IMT Atlantique), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-Université de Bretagne Sud (UBS)-Institut National des Sciences Appliquées - Rennes (INSA Rennes), Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-Institut National des Sciences Appliquées (INSA)-Université de Rennes (UNIV-RENNES)-École normale supérieure - Rennes (ENS Rennes)-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes 1 (UR1), Laboratoire de Biologie Intégrative des Modèles Marins [LBI2M], ABiMS - Informatique et bioinformatique = Analysis and Bioinformatics for Marine Science [ABIMS], Dynamics, Logics and Inference for biological Systems and Sequences [Dyliss], Santé de la vigne et qualité du vin [SVQV], Unité Mathématique Informatique et Génome [MIG], Diversité, adaptation, développement des plantes [UMR DIADE], from patterns to models in computational biodiversity and biotechnology [PLEIADE], Evolution des Protistes et Ecosystèmes Pélagiques [EPEP], Centre for Genomic Regulation [Barcelona] [CRG], ECOlogy of MArine Plankton [ECOMAP], Institut de Génomique Fonctionnelle de Lyon [IGFL], Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL], Laboratoire des symbioses tropicales et méditerranéennes [UMR LSTM], DMAS, ONERA, Université Paris Saclay (COmUE) [Châtillon], and Max-Planck-Institut für Molekulare Genetik [MPIMG]

Subjects
0106 biological sciences, Victoria, Retrotransposon, Aquatic Science, Biology, Phaeophyta, 010603 evolutionary biology, 01 natural sciences, Genome, [SDV.GEN.GPL]Life Sciences [q-bio]/Genetics/Plants genetics, 03 medical and health sciences, Stress, Physiological, [SDV.BBM.GTP]Life Sciences [q-bio]/Biochemistry, Molecular Biology/Genomics [q-bio.GN], Genetics, Gene family, [SDV.BV]Life Sciences [q-bio]/Vegetal Biology, Gene, ComputingMilieux_MISCELLANEOUS, 030304 developmental biology, 0303 health sciences, Abiotic stress, Algal Proteins, Ectocarpus, biology.organism_classification, [SDV.BIBS]Life Sciences [q-bio]/Quantitative Methods [q-bio.QM], Brown algae, Multicellular organism, Multigene Family, [SDE.BE]Environmental Sciences/Biodiversity and Ecology, Metabolic Networks and Pathways, 010606 plant biology & botany
Abstract

Brown algae are multicellular photosynthetic stramenopiles that colonize marine rocky shores worldwide. Ectocarpus sp. Ec32 has been established as a genomic model for brown algae. Here we present the genome and metabolic network of the closely related species, Ectocarpus subulatus Kützing, which is characterized by high abiotic stress tolerance. Since their separation, both strains show new traces of viral sequences and the activity of large retrotransposons, which may also be related to the expansion of a family of chlorophyll-binding proteins. Further features suspected to contribute to stress tolerance include an expanded family of heat shock proteins, the reduction of genes involved in the production of halogenated defence compounds, and the presence of fewer cell wall polysaccharide-modifying enzymes. Overall, E. subulatus has mainly lost members of gene families down-regulated in low salinities, and conserved those that were up-regulated in the same condition. However, 96% of genes that differed between the two examined Ectocarpus species, as well as all genes under positive selection, were found to encode proteins of unknown function. This underlines the uniqueness of brown algal stress tolerance mechanisms as well as the significance of establishing E. subulatus as a comparative model for future functional studies.

Published
2020
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11. Inferring biochemical reactions and metabolite structures to cope with metabolic pathway drift

Author

Ludovic Delage, Erwan Corre, Catherine Leblanc, Camille Trottier, Méziane Aite, Gabriel V. Markov, Pierre Sauleau, Anne Siegel, Arnaud Belcour, Charlotte Marteau, Cédric Leroux, Catherine Boyen, Jonas Collén, Jacques Nicolas, Jean Girard, and Simon M. Dittami

Subjects
Metabolic pathway, chemistry.chemical_compound, Metabolomics, chemistry, ved/biology, Metabolite, ved/biology.organism_classification_rank.species, Biochemical reactions, Computational biology, Biology, Model organism, Phenotype
Abstract

Inferring genome-scale metabolic networks in emerging model organisms is challenging because of incomplete biochemical knowledge and incomplete conservation of biochemical pathways during evolution. This limits the possibility to automatically transfer knowledge from well-established model organisms. Therefore, specific bioinformatic tools are necessary to infer new biochemical reactions and new metabolic structures that can be checked experimentally. Using an integrative approach combining both genomic and metabolomic data in the red algal modelChondrus crispus, we show that, even metabolic pathways considered as conserved, like sterol or mycosporine-like amino acids (MAA) synthesis pathways, undergo substantial turnover. This phenomenon, which we formally define as “metabolic pathway drift”, is consistent with findings from other areas of evolutionary biology, indicating that a given phenotype can be conserved even if the underlying molecular mechanisms are changing. We present a proof of concept with a new methodological approach to formalize the logical reasoning necessary to infer new reactions and new molecular structures, based on previous biochemical knowledge. We use this approach to infer previously unknown reactions in the sterol and MAA pathways.Author summaryGenome-scale metabolic models describe our current understanding of all metabolic pathways occuring in a given organism. For emerging model species, where few biochemical data are available about really occurring enzymatic activities, such metabolic models are mainly based on transferring knowledge from other more studied species, based on the assumption that the same genes have the same function in the compared species. However, integration of metabolomic data into genome-scale metabolic models leads to situations where gaps in pathways cannot be filled by known enzymatic reactions from existing databases. This is due to structural variation in metabolic pathways accross evolutionary time. In such cases, it is necessary to use complementary approaches to infer new reactions and new metabolic intermediates using logical reasoning, based on available partial biochemical knowledge. Here we present a proof of concept that this is feasible and leads to hypotheses that are precise enough to be a starting point for new experimental work.

Published
2018
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12. Multiple scattering filter: Application to plane defect detection in a nickel alloy

Author

Sharfine Shahjhan, Arnaud Derode, Andreas Schumm, Camille Trottier, and Alexandre Aubry

Subjects
Matrix (mathematics), Materials science, Optics, Phased array, business.industry, Scattering, Ultrasonic testing, Ultrasonic sensor, Filter (signal processing), Center frequency, business, Noise (electronics)
Abstract

The ultrasonic inspection of polycrystalline media remains a challenge. The high noise levels due to interaction between the wave and the microstructure limit the efficiency of classical ultrasonic techniques to detect a defect in a coarse grain structure. The aim of this work is to reduce the influence of multiple scattering in order to increase the information obtained from the defect. The technique introduced here is based on array probes for the acquisition of the medium’s response matrix by full matrix capture, after which a filter based on random matrix theory is applied. Here an improvement of this technique is applied on nickel-based alloy mock-ups that present an unfavourable grain structure and well known bulk and plane defects. The results in normal incidence and with an angle array probe of 128 elements and 5 MHz of central frequency are compared to classical phased array probe techniques.

Published
2016
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13. Multiple Scattering Filter: Application to the Plane Defect Detection in a Nickel Alloy

Author

Camille Trottier, Arnaud Derode, Sharfine Shahjahan, Alexandre Aubry, and Andreas Schumm

Subjects
Materials science, Scattering, Phased array, business.industry, Ultrasonic testing, Filter (signal processing), Physics and Astronomy(all), Wedge, Noise (electronics), Matrix (mathematics), Optics, Multiple scattering, Coarse grains structure, Full Matrix Capture, Ultrasound, Ultrasonic sensor, Center frequency, business
Abstract

The ultrasonic inspection of polycrystalline media remains a challenge. The high noise levels due to the interaction between the wave and the microstructure limit the efficiency of classical ultrasonic techniques to detect a defect in a coarse grain structure. The aim of this work is to reduce the influence of multiple scattering in order to increase the information obtained from the defect. The technique introduced in this presentation is based on array probes for the acquisition of the medium's response matrix by full matrix capture, after which a filter based on random matrix theory is applied. Here the technique is used on a nickel alloy block that presents an unfavourable grain structure and a well known plane defect. In this paper, the results of this new technique, with an angle array probe of 128 elements and 5 MHz of central frequency are compared to classical phased array probe techniques.

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14. Multiple scattering filtering for volumetric and plane defects

Author

Pierre-Emile Lhuillier, Alexandre Aubry, Nicolas Paul, Arnaud Derode, Andreas Schumm, and Camille Trottier

Subjects
Materials science, Scattering, Plane (geometry), Attenuation, Ultrasonic testing, 02 engineering and technology, 021001 nanoscience & nanotechnology, 01 natural sciences, Noise (electronics), Rod, Computational physics, 0103 physical sciences, Grain boundary, Crystallite, 010306 general physics, 0210 nano-technology
Abstract

The ultrasonic inspection of polycrystalline coarse grain structures suffers from attenuation noise due to multiple scattering at grain boundaries within these materials. In this paper, we present the current state of affairs of our research in multiple scattering filtering, based on a method proposed by Aubry et al. [1] initially developed and validated on artificial scattering media consisting of fluids with a large number of cylindrical rods, and subsequently applied to polycrystalline alloys [2].

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15. Transcription factors in microalgae: genome-wide prediction and comparative analysis

Author

Bruno Saint-Jean, Benoît Chénais, Benoît Schoefs, Gaël Bougaran, Stanislas Thiriet-Rupert, Jean-Paul Cadoret, Gregory Carrier, Camille Trottier, Mer, molécules et santé EA 2160 (MMS), Université de Nantes - UFR des Sciences Pharmaceutiques et Biologiques, Université de Nantes (UN)-Université de Nantes (UN)-Le Mans Université (UM)-Université de Nantes - UFR des Sciences et des Techniques (UN UFR ST), Université de Nantes (UN)-Université de Nantes (UN), Physiologie et biotechnologie des Algues (PBA), and Institut Français de Recherche pour l'Exploitation de la Mer (IFREMER)

Subjects
0301 basic medicine, Cyanobacteria, Proteome, Algae, Lineage (evolution), Chlamydomonas reinhardtii, Computational biology, Genome, Haptophyte, 03 medical and health sciences, [SDV.BBM.GTP]Life Sciences [q-bio]/Biochemistry, Molecular Biology/Genomics [q-bio.GN], Transcription factors, Microalgae, Tisochrysis lutea, Genetics, [SDV.BBM]Life Sciences [q-bio]/Biochemistry, Molecular Biology, Phaeodactylum tricornutum, biology, Prediction pipeline, Haptophyta, Endosymbiotic gene transfer, biology.organism_classification, Biological Evolution, Haptophytes, 030104 developmental biology, Multigene Family, Porphyridium, Evolution Biology, Stramenopiles, Research Article, Biotechnology
Abstract

Background Studying transcription factors, which are some of the key players in gene expression, is of outstanding interest for the investigation of the evolutionary history of organisms through lineage-specific features. In this study we performed the first genome-wide TF identification and comparison between haptophytes and other algal lineages. Results For TF identification and classification, we created a comprehensive pipeline using a combination of BLAST, HMMER and InterProScan software. The accuracy evaluation of the pipeline shows its applicability for every alga, plant and cyanobacterium, with very good PPV and sensitivity. This pipeline allowed us to identify and classified the transcription factor complement of the three haptophytes Tisochrysis lutea, Emiliania huxleyi and Pavlova sp.; the two stramenopiles Phaeodactylum tricornutum and Nannochloropsis gaditana; the chlorophyte Chlamydomonas reinhardtii and the rhodophyte Porphyridium purpureum. By using T. lutea and Porphyridium purpureum, this work extends the variety of species included in such comparative studies, allowing the detection and detailed study of lineage-specific features, such as the presence of TF families specific to the green lineage in Porphyridium purpureum, haptophytes and stramenopiles. Our comprehensive pipeline also allowed us to identify fungal and cyanobacterial TF families in the algal nuclear genomes. Conclusions This study provides examples illustrating the complex evolutionary history of algae, some of which support the involvement of a green alga in haptophyte and stramenopile evolution. Electronic supplementary material The online version of this article (doi:10.1186/s12864-016-2610-9) contains supplementary material, which is available to authorized users.

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