I am a junior researcher ( "chargée de recherche" ) at the Inria centre at the University of Bordeaux, France. My research is at the interface of computational biology, computer science and systems biology. My main objective is to develop methods and models for the analysis of microbial communities, and in particular to generate hypotheses on the functions they harbour and the interactions they establish. To that end, I am interested in metagenomics, metabolic modelling and optimisation problem solving.
Below I summarise some of my recent works.
Together with colleagues, notably the Hildebrand group at the Quadram Institute and Earlham Institute, we proposed the concept of enterosignatures as a mathematical model describing the microbial guilds inhabiting the human gut microbiome. In our paper published in Cell Host and Microbe in 2023, we show that the gut microbiome variability can be accurately described by combinations of enterosignatures among five. We demonstrate the relevance of the concept to compare microbiome compositions in individuals, study the changes over lifetime and after perturbations, and also detect atypical microbiome compositions. [Read more].
In a collaborative work around the PhD of Maxime Lecomte, we built metabolic models and analysed the dynamics of a three species bacterial community during cheese production. With this digital twin obtained using metabolic network refinement, dynamic flux balance analysis and omics data integration, we showed the contribution of the species in the production of aroma compounds. This works illustrates both the potential and the complexity of inferring the dynamics of metabolic interactions within microbial community at the metabolic level, even in small communities. [Read more].
Numerical models of the metabolism are great, but they cannot always be applied. When focusing on screening the metabolic potential of large collections of microbial genomes, or large-size microbial communities, a simpler model can be useful to efficiently assess the putative roles of each species. To that end, a significant part of my research as been dedicated to use a discrete, Boolean-based, model of metabolic producibility as a proxy to understand the metabolism of species in their environment. I tackled this problem using combinatorial optimisation problem solving, for instance for minimal community selection in a paper published in Bioinformatics in 2018. One of my recent projects published in eLife is the development of an all-in-one pipeline for the screening of large microbial communities using discrete metabolic modelling [Read more].
Maxime Lecomte, Wenfan Cao, Julie Aubert, David J. Sherman, Hélène Falentin, Clémence Frioux, and Simon Labarthe. A digital twin of bacterial metabolism during cheese production. bioRxiv, 2023.
preprint
@article{Lecomte.2023_2,
year = {2023},
title = ,
author = {Lecomte, Maxime and Cao, Wenfan and Aubert, Julie and Sherman, David J. and Falentin, Hélène and Frioux, Clémence and Labarthe, Simon},
journal = {bioRxiv},
doi = {10.1101/2023.05.05.539417},
publisher = {Cold Spring Harbor Laboratory},
abstract = {Cheese organoleptic properties result from complex metabolic processes occurring in microbial communities. A deeper understanding of such mechanisms makes it possible to improve both industrial production processes and end-product quality through the design of microbial consortia. In this work, we caracterise the metabolism of a three-species community consisting of Lactococcus lactis, Lactobacillus plantarum and Propionibacterium freudenreichii during a seven-week cheese production process. Using genome-scale metabolic models and omics data integration, we modeled and calibrated individual dynamics using monoculture experiments, and coupled these models to capture the metabolism of the community. This digital twin accurately predicted the dynamics of the community, enlightening the contribution of each microbial species to organoleptic compound production. Further metabolic exploration raised additional possible interactions between the bacterial species. This work provides a methodological framework for the prediction of community-wide metabolism and highlights the added-value of dynamic metabolic modeling for the comprehension of fermented food processes.},
url = {https://www.biorxiv.org/content/10.1101/2023.05.05.539417v1},
pdf = {https://www.biorxiv.org/content/10.1101/2023.05.05.539417v1.full.pdf},
pages = {},
keywords = {preprint},
note = {preprint},
hal_id = {hal-04088301},
hal_version = {v1}
}
Clémence Frioux, Rebecca Ansorge, Ezgi Özkurt, Chabname Ghassemi Nedjad, Joachim Fritscher, Christopher Quince, Sebastian M. Waszak, and Falk Hildebrand. Enterosignatures define common bacterial guilds in the human gut microbiome. Cell Host & Microbe, 2023.
@article{Frioux.2023,
year = {2023},
title = ,
author = {Frioux, Clémence and Ansorge, Rebecca and Özkurt, Ezgi and Nedjad, Chabname Ghassemi and Fritscher, Joachim and Quince, Christopher and Waszak, Sebastian M. and Hildebrand, Falk},
journal = {Cell Host \& Microbe},
issn = {1931-3128},
doi = {10.1016/j.chom.2023.05.024},
abstract = ,
keywords = {na},
hal_id = {hal-04141300},
hal_version = {v1},
pdf = {https://www.cell.com/cell-host-microbe/fulltext/S1931-3128(23)00217-2#}
}
Arnaud Belcour, Jeanne Got, Méziane Aite, Ludovic Delage, Jonas Collén, Clémence Frioux, Catherine Leblanc, Simon M Dittami, Samuel Blanquart, Gabriel V Markov, and Anne Siegel. Inferring and comparing metabolism across heterogeneous sets of annotated genomes using AuCoMe. Genome Research, 2023.
@article{Belcour.2023,
year = {2023},
title = ,
author = {Belcour, Arnaud and Got, Jeanne and Aite, Méziane and Delage, Ludovic and Collén, Jonas and Frioux, Clémence and Leblanc, Catherine and Dittami, Simon M and Blanquart, Samuel and Markov, Gabriel V and Siegel, Anne},
journal = {Genome Research},
issn = {1088-9051},
doi = {10.1101/gr.277056.122},
abstract = ,
pages = {},
keywords = {na},
hal_id = {hal-03778267},
hal_version = {v2},
pdf = {https://genome.cshlp.org/content/early/2023/07/10/gr.277056.122.full.pdf+html}
}
Clémence Frioux, Sylvie Huet, Simon Labarthe, Julien Martinelli, Thibault Malou, David Sherman, Marie-Luce Taupin, and Pablo Ugalde-Salas. Accelerating metabolic models evaluation with statistical metamodels: application to Salmonella infection models. In: ESAIM: Proceedings and Surveys, pp. 187–217 2023.
@inproceedings{Frioux.2023sga,
year = {2023},
title = ,
author = {Frioux, Clémence and Huet, Sylvie and Labarthe, Simon and Martinelli, Julien and Malou, Thibault and Sherman, David and Taupin, Marie-Luce and Ugalde-Salas, Pablo},
booktitle = {ESAIM: Proceedings and Surveys},
booktitleaddon = {CEMRACS 2021 - Data Assimilation and Reduced Modeling for High Dimensional Problems},
doi = {10.1051/proc/202373187},
abstract = ,
pages = {187--217},
volume = {73},
keywords = {na},
pdf = {https://hal.inrae.fr/hal-03635862/file/main.pdf},
hal_id = {hal-03635862},
hal_version = {v1}
}
Arnaud Belcour, Baptiste Ruiz, Clémence Frioux, Samuel Blanquart, and Anne Siegel. EsMeCaTa: Estimating metabolic capabilities from taxonomic affiliations. bioRxiv, 2022.
preprint
@article{Belcour2022.03.16.484574,
author = {Belcour, Arnaud and Ruiz, Baptiste and Frioux, Cl{\'e}mence and Blanquart, Samuel and Siegel, Anne},
title = {EsMeCaTa: Estimating metabolic capabilities from taxonomic affiliations},
elocation-id = {2022.03.16.484574},
year = {2022},
doi = {10.1101/2022.03.16.484574},
publisher = {Cold Spring Harbor Laboratory},
abstract = {Summary Predicting the functional potential of microorganisms in environmental samples from cultivation-independent techniques is a major challenge. A persistent difficulty lies in associating taxonomic profiles obtained from metabarcoding experiment with accurate functional profiles, particularly for poorly-resolved taxonomic groups. In this paper, we present EsMeCaTa a python package predicting shared proteins from taxonomic affiliations. EsMeCaTa relies on the UniProt database to retrieve the public proteomes associated with a taxon and then uses MMseqs2 in order to compute the set of proteins shared in the taxon. Finally, Es-MeCaTa extracts the functional annotations of these proteins to provide an accurate estimate of the functional potential associated to taxonomic affiliations. Availability EsMeCaTa is available at: https://github.com/AuReMe/esmecata under the GPL-3 license.Competing Interest StatementThe authors have declared no competing interest.},
url = {https://www.biorxiv.org/content/early/2022/03/18/2022.03.16.484574},
journal = {bioRxiv},
note = {preprint},
pdf = {https://www.biorxiv.org/content/10.1101/2022.03.16.484574v1.full.pdf},
hal_id = {hal-03223662}
}
Hetty KleinJan, Clémence Frioux, Gianmaria Califano, Méziane Aite, Enora Fremy, Elham Karimi, Erwan Corre, Thomas Wichard, Anne Siegel, Catherine Boyen, and Simon M. Dittami. Insights into the potential for mutualistic and harmful host‐microbe interactions affecting brown alga freshwater acclimation. Molecular Ecology, 2022.
@article{Kleinjan2022,
year = {2022},
title = ,
author = {KleinJan, Hetty and Frioux, Clémence and Califano, Gianmaria and Aite, Méziane and Fremy, Enora and Karimi, Elham and Corre, Erwan and Wichard, Thomas and Siegel, Anne and Boyen, Catherine and Dittami, Simon M.},
journal = {Molecular Ecology},
issn = {0962-1083},
doi = {10.1111/mec.16766},
pmid = {36326449},
abstract = ,
keywords = {na},
hal_id = {hal-03868898},
pdf = {https://inria.hal.science/hal-03868898},
hal_version = {v1}
}
Paola Fournier, Lucile Pellan, Didac Barroso-Bergadà, David A. Bohan, Thierry Candresse, François Delmotte, Marie-Cécile Dufour, Virginie Lauvergeat, Claire Le Marrec, Armelle Marais, Guilherme Martins, Isabelle Masneuf-Pomarède, Patrice Rey, David Sherman, Patrice This, Clémence Frioux, Simon Labarthe, and Corinne Vacher. The functional microbiome of grapevine throughout plant evolutionary history and lifetime. Advances in Ecological Research, 2022.
@article{Fournier.2022,
year = {2022},
title = ,
author = {Fournier, Paola and Pellan, Lucile and Barroso-Bergadà, Didac and Bohan, David A. and Candresse, Thierry and Delmotte, François and Dufour, Marie-Cécile and Lauvergeat, Virginie and Marrec, Claire Le and Marais, Armelle and Martins, Guilherme and Masneuf-Pomarède, Isabelle and Rey, Patrice and Sherman, David and This, Patrice and Frioux, Clémence and Labarthe, Simon and Vacher, Corinne},
journal = {Advances in Ecological Research},
issn = {0065-2504},
doi = {10.1016/bs.aecr.2022.09.001},
abstract = ,
keywords = {na},
hal_id = {hal-03858395},
hal_version = {v1},
pdf = {https://inria.hal.science/hal-03858395}
}
Clémence Frioux and Anne Siegel. Problèmes d’optimisation combinatoire pour l’étude du métabolisme. In: Editions, I.S.T.E. (ed.) Approches symboliques de la modélisation et de l’analyse des systèmes biologiques, pp. 51–96, ISTE Group, 2022.
@inbook{frioux2022_iste,
year = {2022},
title = ,
author = {Frioux, Clémence and Siegel, Anne},
editor = {Editions, ISTE},
bookauthor = {Cédric Lhoussaine,Élisabeth Remy},
booktitle = {Approches symboliques de la modélisation et de l’analyse des systèmes biologiques},
isbn = {9781789480290},
url = {https://books.google.fr/books?id=z456EAAAQBAJ\&dq=holobiont+interaction\&lr=\&hl=fr\&source=gbs\_navlinks\_s},
pages = {51-96},
series = {SCIENCES},
publisher = {ISTE Group},
language = {French},
keywords = {book},
hal_id = {hal-03885249},
hal_version = {v1},
pdf = {https://inria.hal.science/hal-03885249v1/document}
}
Elham Karimi, Enora Geslain, Arnaud Belcour, Clémence Frioux, Méziane Aïte, Anne Siegel, Erwan Corre, and Simon M. Dittami. Robustness analysis of metabolic predictions in algal microbial communities based on different annotation pipelines. PeerJ, 9 :e11344, 2021.
@article{Karimi.2021,
year = {2021},
title = ,
author = {Karimi, Elham and Geslain, Enora and Belcour, Arnaud and Frioux, Clémence and Aïte, Méziane and Siegel, Anne and Corre, Erwan and Dittami, Simon M.},
journal = {PeerJ},
issn = {2167-8359},
doi = {10.7717/peerj.11344},
pmid = {33996285},
abstract = ,
pages = {e11344},
volume = {9},
keywords = {na},
url = {https://peerj.com/articles/11344/},
pdf = {https://peerj.com/articles/11344.pdf}
}
Falk Hildebrand, Toni I. Gossmann, Clémence Frioux, Ezgi Özkurt, Pernille Neve Myers, Pamela Ferretti, Michael Kuhn, Mohammad Bahram, Henrik Bjørn Nielsen, and Peer Bork. Dispersal strategies shape persistence and evolution of human gut bacteria. Cell Host & Microbe, 2021.
@article{Hildebrand.2021,
year = {2021},
title = ,
author = {Hildebrand, Falk and Gossmann, Toni I. and Frioux, Clémence and Özkurt, Ezgi and Myers, Pernille Neve and Ferretti, Pamela and Kuhn, Michael and Bahram, Mohammad and Nielsen, Henrik Bjørn and Bork, Peer},
journal = {Cell Host \& Microbe},
issn = {1931-3128},
doi = {10.1016/j.chom.2021.05.008},
pmid = {34111423},
abstract = ,
keywords = {na},
url = {https://doi.org/10.1016/j.chom.2021.05.008},
pdf = {https://www.cell.com/cell-host-microbe/fulltext/S1931-3128(21)00236-5?_returnURL=https%3A%2F%2Flinkinghub.elsevier.com%2Fretrieve%2Fpii%2FS1931312821002365%3Fshowall%3Dtrue#},
hal_id = {hal-03438942}
}
Arnaud Belcour*, Clémence Frioux*, Méziane Aite, Anthony Bretaudeau, Falk Hildebrand, and Anne Siegel. Metage2Metabo, microbiota-scale metabolic complementarity for the identication of key species. eLife, 9 :e61968, 2020.
@article{10.7554/elife.61968,
title = ,
author = {Belcour*, Arnaud and Frioux*, Clémence and Aite, Méziane and Bretaudeau, Anthony and Hildebrand, Falk and Siegel, Anne},
journal = {eLife},
doi = {10.7554/elife.61968},
pmid = {33372654},
abstract = ,
pages = {e61968},
volume = {9},
year = {2020},
url = {https://elifesciences.org/articles/61968},
pdf = {https://elifesciences.org/download/aHR0cHM6Ly9jZG4uZWxpZmVzY2llbmNlcy5vcmcvYXJ0aWNsZXMvNjE5NjgvZWxpZmUtNjE5NjgtdjIucGRmP2Nhbm9uaWNhbFVyaT1odHRwczovL2VsaWZlc2NpZW5jZXMub3JnL2FydGljbGVzLzYxOTY4/elife-61968-v2.pdf?_hash=EXsUlHXbjThDLgTcsexviMFFDldmHq8YSWWXdWRUaIY%3D},
hal_id = {hal-02395024}
}
Clémence Frioux, Dipali Singh, Tamas Korcsmaros, and Falk Hildebrand. From bag-of-genes to bag-of-genomes: metabolic modelling of communities in the era of metagenome-assembled genomes. Computational and Structural Biotechnology Journal, 18 :1722–1734, 2020.
@article{Frioux.2020jlpr,
title = ,
author = {Frioux, Clémence and Singh, Dipali and Korcsmaros, Tamas and Hildebrand, Falk},
journal = {Computational and Structural Biotechnology Journal},
issn = {2001-0370},
doi = {10.1016/j.csbj.2020.06.028},
pmid = {32670511},
abstract = ,
pages = {1722--1734},
volume = {18},
year = {2020},
url = {https://www.sciencedirect.com/science/article/pii/S2001037020303172?via%3Dihub},
pdf = {https://www.sciencedirect.com/science/article/pii/S2001037020303172/pdfft?md5=2853380b7d1f8beb03e3fa0676ec8dae&pid=1-s2.0-S2001037020303172-main.pdf},
hal_id = {hal-02883309}
}
Mohammad Bahram, Tarquin Netherway, Clémence Frioux, Pamela Ferretti, Luis Pedro Coelho, Stefan Geisen, Peer Bork, and Falk Hildebrand. Metagenomic assessment of the global distribution of bacteria and fungi. Environmental Microbiology, 2020.
@article{Bahram.2020zm,
title = ,
author = {Bahram, Mohammad and Netherway, Tarquin and Frioux, Clémence and Ferretti, Pamela and Coelho, Luis Pedro and Geisen, Stefan and Bork, Peer and Hildebrand, Falk},
journal = {Environmental Microbiology},
issn = {1462-2912},
doi = {10.1111/1462-2920.15314},
pmid = {33185929},
abstract = ,
year = {2020},
url = {https://sfamjournals.onlinelibrary.wiley.com/doi/10.1111/1462-2920.15314},
pdf = {https://sfamjournals.onlinelibrary.wiley.com/doi/epdf/10.1111/1462-2920.15314},
hal_id = {hal-03033570}
}
Clémence Frioux, Simon M Dittami, and Anne Siegel. Using automated reasoning to explore the metabolism of unconventional organisms: a first step to explore host–microbial interactions. Biochemical Society Transactions, 48(3) :901–913, 2020.
@article{Frioux.2020,
title = ,
author = {Frioux, Clémence and Dittami, Simon M and Siegel, Anne},
journal = {Biochemical Society Transactions},
issn = {0300-5127},
doi = {10.1042/bst20190667},
pmid = {32379295},
abstract = ,
pages = {901--913},
number = {3},
volume = {48},
url = {https://portlandpress.com/biochemsoctrans/article-abstract/48/3/901/223844/Using-automated-reasoning-to-explore-the?redirectedFrom=fulltext},
year = {2020},
hal_id = {hal-02569935},
pdf = {https://hal.science/hal-02569935v1/document}
}
Simon M. Dittami, Erwan Corre, Loraine Brillet-Guéguen, Agnieszka P. Lipinska, Noé Pontoizeau, Meziane Aite, Komlan Avia, Christophe Caron, Chung Hyun Cho, Jonas Collén, Alexandre Cormier, Ludovic Delage, Sylvie Doubleau, Clémence Frioux, Angélique Gobet, Irene González-Navarrete, Agnès Groisillier, Cécile Hervé, Didier Jollivet, Hetty KleinJan, Catherine Leblanc, Xi Liu, Dominique Marie, Gabriel V. Markov, André E. Minoche, Misharl Monsoor, Pierre Pericard, Marie Mathilde Perrineau, Akira F. Peters, Anne Siegel, Amandine Siméon, Camille Trottier, Hwan Su Yoon, Heinz Himmelbauer, Catherine Boyen, and Thierry Tonon. The genome of Ectocarpus subulatus – A highly stress-tolerant brown alga. Marine Genomics, :100740, 2020.
@article{Dittami2020,
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 K{\"{u}}tzing, 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.},
author = {Dittami, Simon M. and Corre, Erwan and Brillet-Gu{\'{e}}guen, Loraine and Lipinska, Agnieszka P. and Pontoizeau, No{\'{e}} and Aite, Meziane and Avia, Komlan and Caron, Christophe and Cho, Chung Hyun and Coll{\'{e}}n, Jonas and Cormier, Alexandre and Delage, Ludovic and Doubleau, Sylvie and Frioux, Cl{\'{e}}mence and Gobet, Ang{\'{e}}lique and Gonz{\'{a}}lez-Navarrete, Irene and Groisillier, Agn{\`{e}}s and Herv{\'{e}}, C{\'{e}}cile and Jollivet, Didier and KleinJan, Hetty and Leblanc, Catherine and Liu, Xi and Marie, Dominique and Markov, Gabriel V. and Minoche, Andr{\'{e}} E. and Monsoor, Misharl and Pericard, Pierre and Perrineau, Marie Mathilde and Peters, Akira F. and Siegel, Anne and Sim{\'{e}}on, Amandine and Trottier, Camille and Yoon, Hwan Su and Himmelbauer, Heinz and Boyen, Catherine and Tonon, Thierry},
doi = {10.1016/j.margen.2020.100740},
issn = {18747787},
journal = {Marine Genomics},
month = jan,
pages = {100740},
title = ,
pdf = {https://www.sciencedirect.com/science/article/pii/S1874778720300015/pdfft?md5=f649fadc48011123f15f7f2ea4cb0677&pid=1-s2.0-S1874778720300015-main.pdf},
url = {https://linkinghub.elsevier.com/retrieve/pii/S1874778720300015},
year = {2020},
hal_id = {hal-02866117},
month_numeric = {1}
}
Bertille Burgunter-Delamare, Hetty KleinJan, Clémence Frioux, Enora Fremy, Margot Wagner, Erwan Corre, Alicia Le Salver, Cédric Leroux, Catherine Leblanc, Catherine Boyen, Anne Siegel, and Simon M. Dittami. Metabolic Complementarity Between a Brown Alga and Associated Cultivable Bacteria Provide Indications of Beneficial Interactions. Frontiers in Marine Science, 7 :85, 2020.
@article{Burgunter-Delamare2020,
abstract = {Brown algae are key components of marine ecosystems and live in association with bacteria that are essential for their growth and development. Ectocarpus siliculosus is a genetic and genomic model for brown algae. Here we use this model to start disentangling the complex interactions that may occur between the algal host and its associated bacteria. We report the genome-sequencing of 10 alga-associated bacteria and the genome-based reconstruction of their metabolic networks. The predicted metabolic capacities were then used to identify metabolic complementarities between the algal host and the bacteria, highlighting a range of potentially beneficial metabolite exchanges between them. These putative exchanges allowed us to predict consortia consisting of a subset of these ten bacteria that would best complement the algal metabolism. Finally, co-culture experiments were set up with a subset of these consortia to monitor algal growth as well as the presence of key algal metabolites. Although we did not fully control but only modified bacterial communities in our experiments, our data demonstrated a significant increase in algal growth in cultures inoculated with the selected consortia. In several cases, we also detected, in algal extracts, the presence of key metabolites predicted to become producible via an exchange of metabolites between the alga and the microbiome. Thus, although further methodological developments will be necessary to better control and understand microbial interactions in Ectocarpus, our data suggest that metabolic complementarity is a good indicator of beneficial metabolite exchanges in the holobiont.},
author = {Burgunter-Delamare, Bertille and KleinJan, Hetty and Frioux, Cl{\'{e}}mence and Fremy, Enora and Wagner, Margot and Corre, Erwan and {Le Salver}, Alicia and Leroux, C{\'{e}}dric and Leblanc, Catherine and Boyen, Catherine and Siegel, Anne and Dittami, Simon M.},
doi = {10.3389/FMARS.2020.00085},
issn = {2296-7745},
journal = {Frontiers in Marine Science},
keywords = {Ectocarpus siliculosus,Genome-scale metabolic networks,holobiont,metabolic complementarity,symbiotic/mutualistic bacteria},
month = feb,
pages = {85},
publisher = {Frontiers},
title = ,
volume = {7},
pdf = {https://www.frontiersin.org/articles/10.3389/fmars.2020.00085/pdf},
url = {https://www.frontiersin.org/articles/10.3389/fmars.2020.00085},
year = {2020},
hal_id = {hal-02866101},
month_numeric = {2}
}
Delphine Nègre, Méziane Aite, Arnaud Belcour, Clémence Frioux, Loraine Brillet-Guéguen, Xi Liu, Philippe Bordron, Olivier Godfroy, Agnieszka P. Lipinska, Catherine Leblanc, Anne Siegel, Simon M. Dittami, Erwan Corre, and Gabriel V. Markov. Genome–scale metabolic networks shed light on the carotenoid biosynthesis pathway in the brown algae saccharina japonica and cladosiphon okamuranus. Antioxidants, 8(11) :564, 2019.
@article{Negre2019,
abstract = {Understanding growth mechanisms in brown algae is a current scientific and economic challenge that can benefit from the modeling of their metabolic networks. The sequencing of the genomes of Saccharina japonica and Cladosiphon okamuranus has provided the necessary data for the reconstruction of Genome–Scale Metabolic Networks (GSMNs). The same in silico method deployed for the GSMN reconstruction of Ectocarpus siliculosus to investigate the metabolic capabilities of these two algae, was used. Integrating metabolic profiling data from the literature, we provided functional GSMNs composed of an average of 2230 metabolites and 3370 reactions. Based on these GSMNs and previously published work, we propose a model for the biosynthetic pathways of the main carotenoids in these two algae. We highlight, on the one hand, the reactions and enzymes that have been preserved through evolution and, on the other hand, the specificities related to brown algae. Our data further indicate that, if abscisic acid is produced by Saccharina japonica, its biosynthesis pathway seems to be different in its final steps from that described in land plants. Thus, our work illustrates the potential of GSMNs reconstructions for formalizing hypotheses that can be further tested using targeted biochemical approaches.},
author = {N{\`{e}}gre, Delphine and Aite, M{\'{e}}ziane and Belcour, Arnaud and Frioux, Cl{\'{e}}mence and Brillet-Gu{\'{e}}guen, Loraine and Liu, Xi and Bordron, Philippe and Godfroy, Olivier and Lipinska, Agnieszka P. and Leblanc, Catherine and Siegel, Anne and Dittami, Simon M. and Corre, Erwan and Markov, Gabriel V.},
doi = {10.3390/antiox8110564},
issn = {20763921},
journal = {Antioxidants},
keywords = {Abscisic acid,Brown algae,Cladosiphon okamuranus,Data integration,Fucoxanthin,Genome-Scale metabolic networks (GSMNs),Oxygenated carotenoid biosynthesis,Saccharina japonica},
month = nov,
number = {11},
pages = {564},
publisher = {Multidisciplinary Digital Publishing Institute},
title = ,
url = {https://www.mdpi.com/2076-3921/8/11/564},
pdf = {https://www.mdpi.com/2076-3921/8/11/564/pdf},
volume = {8},
year = {2019},
hal_id = {hal-02395080},
month_numeric = {11}
}
Clémence Frioux, Torsten Schaub, Sebastian Schellhorn, Anne Siegel, and Philipp Wanko. Hybrid metabolic network completion. Theory and Practice of Logic Programming, 19(01) :83–108, 2019.
@article{Frioux2019,
abstract = {Metabolic networks play a crucial role in biology since they capture all chemical reactions in an organism. While there are networks of high quality for many model organisms, networks for less studied organisms are often of poor quality and suffer from incompleteness. To this end, we introduced in previous work an answer set programming (ASP)-based approach to metabolic network completion. Although this qualitative approach allows for restoring moderately degraded networks, it fails to restore highly degraded ones. This is because it ignores quantitative constraints capturing reaction rates. To address this problem, we propose a hybrid approach to metabolic network completion that integrates our qualitative ASP approach with quantitative means for capturing reaction rates. We begin by formally reconciling existing stoichiometric and topological approaches to network completion in a unified formalism. With it, we develop a hybrid ASP encoding and rely upon the theory reasoning capacities of the ASP system clingo for solving the resulting logic program with linear constraints over reals. We empirically evaluate our approach by means of the metabolic network of Escherichia coli . Our analysis shows that our novel approach yields greatly superior results than obtainable from purely qualitative or quantitative approaches.},
author = {Frioux, Cl{\'{e}}mence and Schaub, Torsten and Schellhorn, Sebastian and Siegel, Anne and Wanko, Philipp},
doi = {10.1017/S1471068418000455},
issn = {1471-0684},
journal = {Theory and Practice of Logic Programming},
keywords = {answer set programming,bioinformatics,gap-filling,hybrid solving,linear programming,metabolic network},
month = jan,
number = {01},
pages = {83--108},
publisher = {Cambridge University Press},
title = ,
url = {https://www.cambridge.org/core/product/identifier/S1471068418000455/type/journal{\_}article},
volume = {19},
year = {2019},
pdf = {https://arxiv.org/pdf/1808.04149.pdf},
optlink = {http://arxiv.org/abs/1808.04149},
month_numeric = {1}
}
Clémence Frioux, Enora Fremy, Camille Trottier, and Anne Siegel. Scalable and exhaustive screening of metabolic functions carried out by microbial consortia. Bioinformatics, 34(17) :i934–i943, 2018.
@article{Frioux2018,
author = {Frioux, Cl{\'{e}}mence and Fremy, Enora and Trottier, Camille and Siegel, Anne},
doi = {10.1093/bioinformatics/bty588},
issn = {1367-4803},
journal = {Bioinformatics},
month = sep,
number = {17},
pages = {i934--i943},
publisher = {Oxford University Press},
title = ,
url = {https://academic.oup.com/bioinformatics/article/34/17/i934/5093211},
volume = {34},
year = {2018},
pdf = {https://academic.oup.com/bioinformatics/article-pdf/34/17/i934/25702201/bty588.pdf},
hal_id = {hal-01871600},
month_numeric = {9}
}
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. Traceability, reproducibility and wiki-exploration for “à-la-carte” reconstructions of genome-scale metabolic models. PLOS Computational Biology, 14(5) :1–25, 2018.
@article{Aite2018,
author = {Aite, Méziane and Chevallier, Marie and Frioux, Clémence and Trottier, Camille and Got, Jeanne and Cortés, María Paz and Mendoza, Sebastián N. and Carrier, Grégory and Dameron, Olivier and Guillaudeux, Nicolas and Latorre, Mauricio and Loira, Nicolás and Markov, Gabriel V. and Maass, Alejandro and Siegel, Anne},
journal = {PLOS Computational Biology},
publisher = {Public Library of Science},
title = {Traceability, reproducibility and wiki-exploration for “à-la-carte” reconstructions of genome-scale metabolic models},
year = {2018},
month = may,
volume = {14},
url = {https://doi.org/10.1371/journal.pcbi.1006146},
pages = {1-25},
abstract = {Author summary Genome-scale metabolic models describe an organism’s metabolism. Building good models requires the integration of all relevant available information, obtained by exploring different data types and biological databases. This process is not straightforward and choices are made along the way, for example, which data is analyzed, with what tools. It matters that all reconstruction steps are well documented so that models can be fully exploited by the community. Having this metadata allows other researchers to reproduce, improve or reuse a model as a blueprint to create new ones. Sadly, this information is usually scattered and its proper distribution is the exception rather than the norm when using “à la carte” pipelines that combine main platforms and individual tools. We created a platform for “à la carte” metabolic model generation that responds to the need of transparency and data-connection in the field. It includes a battery of tools to exploit heterogeneous data through customizable pipelines. At each step, relevant information is stored, ensuring reproducibility and documentation of processes. Furthermore, exploration of models and metadata during the reconstruction process is facilitated through the automatic generation of local wikis. This view offers a user-friendly solution to iteratively explore genome-scale metabolic models produced with personalized pipelines and poorly interoperable tools. We highlight these benefits by building models for organisms with various input data. Among them, we show why the combination of heterogeneous information is necessary to elucidate specificities of Tisochrysis lutea, a eukaryotic microalga, for anti-oxidant production.},
number = {5},
doi = {10.1371/journal.pcbi.1006146},
pdf = {http://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1006146&type=printable},
hal_id = {hal-01819150},
month_numeric = {5}
}
Clémence Frioux. Investigating host-microbiota cooperation with gap-filling optimization problems, PhD thesis, Université de Rennes 1, November 2018.
@phdthesis{Frioux2020,
abstract = {Systems biology relies on computational biology to integrate knowledge and data, for a better understanding of organisms' physiology. Challenges reside in the applicability of methods and tools to non-model organisms, for instance in marine biology. Sequencing advances and the growing importance of elucidating microbiotas' roles, have led to an increased interest into these organisms. This thesis focuses on the modeling of the metabolism through networks, and of its functionality using graphs and constraints semantics. In particular, a first part presents work on gap-filling metabolic networks in the context of non-model organisms. A graph-based method is benchmarked and validated and a hybrid one is developed using Answer Set Programming (ASP) and linear programming. Such gap-filling is applied on algae and extended to decipher putative interactions between Ectocarpus siliculosus and a symbiotic bacterium. In this direction, the second part of the thesis aims at proposing formalisms and implementation of a tool for selecting and screening communities of interest within microbiotas. It enables to scale to large microbiotas and, with a two-step approach, to suggest symbionts that fit the desired objective. The modeling supports the computation of exchanges, and solving can cover the whole solution space. Applications are presented on the human gut microbiota and the selection of bacterial communities for a brown alga. Altogether, this thesis proposes modeling, software and biological applications using graph-based semantics to support the elaboration of hypotheses for elucidating the metabolism of organisms.},
author = {Frioux, Cl{\'{e}}mence},
month = nov,
publisher = {Universit{\'{e}} de Rennes 1},
school = {Universit{\'{e}} de Rennes 1},
title = ,
url = {https://hal.inria.fr/tel-01945853},
year = {2018},
hal_id = {hal-01945853},
pdf = {https://hal.inria.fr/tel-01945853/document},
month_numeric = {11}
}
Clémence Frioux, Torsten Schaub, Sebastian Schellhorn, Anne Siegel, and Philipp Wanko. Hybrid metabolic network completion. In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 308–321, Springer, Cham, 2017.
@inproceedings{Frioux2017,
author = {Frioux, Clémence and Schaub, Torsten and Schellhorn, Sebastian and Siegel, Anne and Wanko, Philipp},
booktitle = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
doi = {10.1007/978-3-319-61660-5_28},
isbn = {9783319616599},
issn = {16113349},
pages = {308--321},
publisher = {Springer, Cham},
title = {Hybrid metabolic network completion},
url = {http://link.springer.com/10.1007/978-3-319-61660-5{\_}28},
volume = {10377 LNAI},
year = {2017},
hal_id = {hal-01557347},
pdf = {https://hal.inria.fr/hal-01557347/document}
}
Julie Laniau, Clémence Frioux, Jacques Nicolas, Caroline Baroukh, María Paz Cortes, Jeanne Got, Camille Trottier, Damien Eveillard, and Anne Siegel. Combining graph and flux-based structures to decipher phenotypic essential metabolites within metabolic networks. PeerJ, 2017(10) 2017.
@article{Laniau2017,
author = {Laniau, Julie and Frioux, Clémence and Nicolas, Jacques and Baroukh, Caroline and Cortes, María Paz and Got, Jeanne and Trottier, Camille and Eveillard, Damien and Siegel, Anne},
doi = {10.7717/peerj.3860},
issn = {21678359},
journal = {PeerJ},
keywords = {Answer Set Programming,Constraint-based analysis,Essential metabolite,Graph-based analysis,Metabolic networks},
number = {10},
title = {Combining graph and flux-based structures to decipher phenotypic essential metabolites within metabolic networks},
volume = {2017},
year = {2017},
pdf = {https://peerj.com/articles/3860.pdf},
hal_id = {hal-01635688}
}
Sylvain Prigent, Clémence Frioux, Simon M. Dittami, Sven Thiele, Abdelhalim Larhlimi, Guillaume Collet, Fabien Gutknecht, Jeanne Got, Damien Eveillard, Jérémie Bourdon, Frédéric Plewniak, Thierry Tonon, and Anne Siegel. Meneco, a Topology-Based Gap-Filling Tool Applicable to Degraded Genome-Wide Metabolic Networks. PLoS Computational Biology, 13(1) 2017.
@article{Prigent2017,
author = {Prigent, Sylvain and Frioux, Clémence and Dittami, Simon M. and Thiele, Sven and Larhlimi, Abdelhalim and Collet, Guillaume and Gutknecht, Fabien and Got, Jeanne and Eveillard, Damien and Bourdon, Jérémie and Plewniak, Frédéric and Tonon, Thierry and Siegel, Anne},
doi = {10.1371/journal.pcbi.1005276},
issn = {15537358},
journal = {PLoS Computational Biology},
number = {1},
title = {Meneco, a Topology-Based Gap-Filling Tool Applicable to Degraded Genome-Wide Metabolic Networks},
volume = {13},
year = {2017},
pdf = {http://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1005276&type=printable},
hal_id = {hal-01449100}
}
Teemu Haikarainen, Clémence Frioux, Li-Qing Zhnag, Duo-Chuan Li, and Anastassios C. Papageorgiou. Crystal structure and biochemical characterization of a manganese superoxide dismutase from Chaetomium thermophilum. Biochimica et Biophysica Acta (BBA) - Proteins and Proteomics, 1844(2) :422–429, 2014.
@article{Haikarainen2014,
author = {Haikarainen, Teemu and Frioux, Clémence and Zhnag, Li-Qing and Li, Duo-Chuan and Papageorgiou, Anastassios C.},
doi = {10.1016/j.bbapap.2013.11.014},
issn = {15709639},
journal = {Biochimica et Biophysica Acta (BBA) - Proteins and Proteomics},
number = {2},
pages = {422--429},
title = {Crystal structure and biochemical characterization of a manganese superoxide dismutase from Chaetomium thermophilum},
volume = {1844},
year = {2014},
pdf = {https://github.com/cfrioux/cfrioux.github.io/tree/master/data/papers/haikarainen2014.pdf}
}
Clémence Frioux, Rebecca Ansorge, Ezgi Özkurt, Chabname Ghassemi Nedjad, Joachim Fritscher, Christopher Quince, Sebastian M. Waszak, and Falk Hildebrand. Enterosignatures define common bacterial guilds in the human gut microbiome. Cell Host & Microbe, 2023.
@article{Frioux.2023,
year = {2023},
title = ,
author = {Frioux, Clémence and Ansorge, Rebecca and Özkurt, Ezgi and Nedjad, Chabname Ghassemi and Fritscher, Joachim and Quince, Christopher and Waszak, Sebastian M. and Hildebrand, Falk},
journal = {Cell Host \& Microbe},
issn = {1931-3128},
doi = {10.1016/j.chom.2023.05.024},
abstract = ,
keywords = {na},
hal_id = {hal-04141300},
hal_version = {v1},
pdf = {https://www.cell.com/cell-host-microbe/fulltext/S1931-3128(23)00217-2#}
}
Arnaud Belcour, Jeanne Got, Méziane Aite, Ludovic Delage, Jonas Collén, Clémence Frioux, Catherine Leblanc, Simon M Dittami, Samuel Blanquart, Gabriel V Markov, and Anne Siegel. Inferring and comparing metabolism across heterogeneous sets of annotated genomes using AuCoMe. Genome Research, 2023.
@article{Belcour.2023,
year = {2023},
title = ,
author = {Belcour, Arnaud and Got, Jeanne and Aite, Méziane and Delage, Ludovic and Collén, Jonas and Frioux, Clémence and Leblanc, Catherine and Dittami, Simon M and Blanquart, Samuel and Markov, Gabriel V and Siegel, Anne},
journal = {Genome Research},
issn = {1088-9051},
doi = {10.1101/gr.277056.122},
abstract = ,
pages = {},
keywords = {na},
hal_id = {hal-03778267},
hal_version = {v2},
pdf = {https://genome.cshlp.org/content/early/2023/07/10/gr.277056.122.full.pdf+html}
}
Hetty KleinJan, Clémence Frioux, Gianmaria Califano, Méziane Aite, Enora Fremy, Elham Karimi, Erwan Corre, Thomas Wichard, Anne Siegel, Catherine Boyen, and Simon M. Dittami. Insights into the potential for mutualistic and harmful host‐microbe interactions affecting brown alga freshwater acclimation. Molecular Ecology, 2022.
@article{Kleinjan2022,
year = {2022},
title = ,
author = {KleinJan, Hetty and Frioux, Clémence and Califano, Gianmaria and Aite, Méziane and Fremy, Enora and Karimi, Elham and Corre, Erwan and Wichard, Thomas and Siegel, Anne and Boyen, Catherine and Dittami, Simon M.},
journal = {Molecular Ecology},
issn = {0962-1083},
doi = {10.1111/mec.16766},
pmid = {36326449},
abstract = ,
keywords = {na},
hal_id = {hal-03868898},
pdf = {https://inria.hal.science/hal-03868898},
hal_version = {v1}
}
Paola Fournier, Lucile Pellan, Didac Barroso-Bergadà, David A. Bohan, Thierry Candresse, François Delmotte, Marie-Cécile Dufour, Virginie Lauvergeat, Claire Le Marrec, Armelle Marais, Guilherme Martins, Isabelle Masneuf-Pomarède, Patrice Rey, David Sherman, Patrice This, Clémence Frioux, Simon Labarthe, and Corinne Vacher. The functional microbiome of grapevine throughout plant evolutionary history and lifetime. Advances in Ecological Research, 2022.
@article{Fournier.2022,
year = {2022},
title = ,
author = {Fournier, Paola and Pellan, Lucile and Barroso-Bergadà, Didac and Bohan, David A. and Candresse, Thierry and Delmotte, François and Dufour, Marie-Cécile and Lauvergeat, Virginie and Marrec, Claire Le and Marais, Armelle and Martins, Guilherme and Masneuf-Pomarède, Isabelle and Rey, Patrice and Sherman, David and This, Patrice and Frioux, Clémence and Labarthe, Simon and Vacher, Corinne},
journal = {Advances in Ecological Research},
issn = {0065-2504},
doi = {10.1016/bs.aecr.2022.09.001},
abstract = ,
keywords = {na},
hal_id = {hal-03858395},
hal_version = {v1},
pdf = {https://inria.hal.science/hal-03858395}
}
Elham Karimi, Enora Geslain, Arnaud Belcour, Clémence Frioux, Méziane Aïte, Anne Siegel, Erwan Corre, and Simon M. Dittami. Robustness analysis of metabolic predictions in algal microbial communities based on different annotation pipelines. PeerJ, 9 :e11344, 2021.
@article{Karimi.2021,
year = {2021},
title = ,
author = {Karimi, Elham and Geslain, Enora and Belcour, Arnaud and Frioux, Clémence and Aïte, Méziane and Siegel, Anne and Corre, Erwan and Dittami, Simon M.},
journal = {PeerJ},
issn = {2167-8359},
doi = {10.7717/peerj.11344},
pmid = {33996285},
abstract = ,
pages = {e11344},
volume = {9},
keywords = {na},
url = {https://peerj.com/articles/11344/},
pdf = {https://peerj.com/articles/11344.pdf}
}
Falk Hildebrand, Toni I. Gossmann, Clémence Frioux, Ezgi Özkurt, Pernille Neve Myers, Pamela Ferretti, Michael Kuhn, Mohammad Bahram, Henrik Bjørn Nielsen, and Peer Bork. Dispersal strategies shape persistence and evolution of human gut bacteria. Cell Host & Microbe, 2021.
@article{Hildebrand.2021,
year = {2021},
title = ,
author = {Hildebrand, Falk and Gossmann, Toni I. and Frioux, Clémence and Özkurt, Ezgi and Myers, Pernille Neve and Ferretti, Pamela and Kuhn, Michael and Bahram, Mohammad and Nielsen, Henrik Bjørn and Bork, Peer},
journal = {Cell Host \& Microbe},
issn = {1931-3128},
doi = {10.1016/j.chom.2021.05.008},
pmid = {34111423},
abstract = ,
keywords = {na},
url = {https://doi.org/10.1016/j.chom.2021.05.008},
pdf = {https://www.cell.com/cell-host-microbe/fulltext/S1931-3128(21)00236-5?_returnURL=https%3A%2F%2Flinkinghub.elsevier.com%2Fretrieve%2Fpii%2FS1931312821002365%3Fshowall%3Dtrue#},
hal_id = {hal-03438942}
}
Arnaud Belcour*, Clémence Frioux*, Méziane Aite, Anthony Bretaudeau, Falk Hildebrand, and Anne Siegel. Metage2Metabo, microbiota-scale metabolic complementarity for the identication of key species. eLife, 9 :e61968, 2020.
@article{10.7554/elife.61968,
title = ,
author = {Belcour*, Arnaud and Frioux*, Clémence and Aite, Méziane and Bretaudeau, Anthony and Hildebrand, Falk and Siegel, Anne},
journal = {eLife},
doi = {10.7554/elife.61968},
pmid = {33372654},
abstract = ,
pages = {e61968},
volume = {9},
year = {2020},
url = {https://elifesciences.org/articles/61968},
pdf = {https://elifesciences.org/download/aHR0cHM6Ly9jZG4uZWxpZmVzY2llbmNlcy5vcmcvYXJ0aWNsZXMvNjE5NjgvZWxpZmUtNjE5NjgtdjIucGRmP2Nhbm9uaWNhbFVyaT1odHRwczovL2VsaWZlc2NpZW5jZXMub3JnL2FydGljbGVzLzYxOTY4/elife-61968-v2.pdf?_hash=EXsUlHXbjThDLgTcsexviMFFDldmHq8YSWWXdWRUaIY%3D},
hal_id = {hal-02395024}
}
Clémence Frioux, Dipali Singh, Tamas Korcsmaros, and Falk Hildebrand. From bag-of-genes to bag-of-genomes: metabolic modelling of communities in the era of metagenome-assembled genomes. Computational and Structural Biotechnology Journal, 18 :1722–1734, 2020.
@article{Frioux.2020jlpr,
title = ,
author = {Frioux, Clémence and Singh, Dipali and Korcsmaros, Tamas and Hildebrand, Falk},
journal = {Computational and Structural Biotechnology Journal},
issn = {2001-0370},
doi = {10.1016/j.csbj.2020.06.028},
pmid = {32670511},
abstract = ,
pages = {1722--1734},
volume = {18},
year = {2020},
url = {https://www.sciencedirect.com/science/article/pii/S2001037020303172?via%3Dihub},
pdf = {https://www.sciencedirect.com/science/article/pii/S2001037020303172/pdfft?md5=2853380b7d1f8beb03e3fa0676ec8dae&pid=1-s2.0-S2001037020303172-main.pdf},
hal_id = {hal-02883309}
}
Mohammad Bahram, Tarquin Netherway, Clémence Frioux, Pamela Ferretti, Luis Pedro Coelho, Stefan Geisen, Peer Bork, and Falk Hildebrand. Metagenomic assessment of the global distribution of bacteria and fungi. Environmental Microbiology, 2020.
@article{Bahram.2020zm,
title = ,
author = {Bahram, Mohammad and Netherway, Tarquin and Frioux, Clémence and Ferretti, Pamela and Coelho, Luis Pedro and Geisen, Stefan and Bork, Peer and Hildebrand, Falk},
journal = {Environmental Microbiology},
issn = {1462-2912},
doi = {10.1111/1462-2920.15314},
pmid = {33185929},
abstract = ,
year = {2020},
url = {https://sfamjournals.onlinelibrary.wiley.com/doi/10.1111/1462-2920.15314},
pdf = {https://sfamjournals.onlinelibrary.wiley.com/doi/epdf/10.1111/1462-2920.15314},
hal_id = {hal-03033570}
}
Clémence Frioux, Simon M Dittami, and Anne Siegel. Using automated reasoning to explore the metabolism of unconventional organisms: a first step to explore host–microbial interactions. Biochemical Society Transactions, 48(3) :901–913, 2020.
@article{Frioux.2020,
title = ,
author = {Frioux, Clémence and Dittami, Simon M and Siegel, Anne},
journal = {Biochemical Society Transactions},
issn = {0300-5127},
doi = {10.1042/bst20190667},
pmid = {32379295},
abstract = ,
pages = {901--913},
number = {3},
volume = {48},
url = {https://portlandpress.com/biochemsoctrans/article-abstract/48/3/901/223844/Using-automated-reasoning-to-explore-the?redirectedFrom=fulltext},
year = {2020},
hal_id = {hal-02569935},
pdf = {https://hal.science/hal-02569935v1/document}
}
Simon M. Dittami, Erwan Corre, Loraine Brillet-Guéguen, Agnieszka P. Lipinska, Noé Pontoizeau, Meziane Aite, Komlan Avia, Christophe Caron, Chung Hyun Cho, Jonas Collén, Alexandre Cormier, Ludovic Delage, Sylvie Doubleau, Clémence Frioux, Angélique Gobet, Irene González-Navarrete, Agnès Groisillier, Cécile Hervé, Didier Jollivet, Hetty KleinJan, Catherine Leblanc, Xi Liu, Dominique Marie, Gabriel V. Markov, André E. Minoche, Misharl Monsoor, Pierre Pericard, Marie Mathilde Perrineau, Akira F. Peters, Anne Siegel, Amandine Siméon, Camille Trottier, Hwan Su Yoon, Heinz Himmelbauer, Catherine Boyen, and Thierry Tonon. The genome of Ectocarpus subulatus – A highly stress-tolerant brown alga. Marine Genomics, :100740, 2020.
@article{Dittami2020,
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 K{\"{u}}tzing, 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.},
author = {Dittami, Simon M. and Corre, Erwan and Brillet-Gu{\'{e}}guen, Loraine and Lipinska, Agnieszka P. and Pontoizeau, No{\'{e}} and Aite, Meziane and Avia, Komlan and Caron, Christophe and Cho, Chung Hyun and Coll{\'{e}}n, Jonas and Cormier, Alexandre and Delage, Ludovic and Doubleau, Sylvie and Frioux, Cl{\'{e}}mence and Gobet, Ang{\'{e}}lique and Gonz{\'{a}}lez-Navarrete, Irene and Groisillier, Agn{\`{e}}s and Herv{\'{e}}, C{\'{e}}cile and Jollivet, Didier and KleinJan, Hetty and Leblanc, Catherine and Liu, Xi and Marie, Dominique and Markov, Gabriel V. and Minoche, Andr{\'{e}} E. and Monsoor, Misharl and Pericard, Pierre and Perrineau, Marie Mathilde and Peters, Akira F. and Siegel, Anne and Sim{\'{e}}on, Amandine and Trottier, Camille and Yoon, Hwan Su and Himmelbauer, Heinz and Boyen, Catherine and Tonon, Thierry},
doi = {10.1016/j.margen.2020.100740},
issn = {18747787},
journal = {Marine Genomics},
month = jan,
pages = {100740},
title = ,
pdf = {https://www.sciencedirect.com/science/article/pii/S1874778720300015/pdfft?md5=f649fadc48011123f15f7f2ea4cb0677&pid=1-s2.0-S1874778720300015-main.pdf},
url = {https://linkinghub.elsevier.com/retrieve/pii/S1874778720300015},
year = {2020},
hal_id = {hal-02866117},
month_numeric = {1}
}
Bertille Burgunter-Delamare, Hetty KleinJan, Clémence Frioux, Enora Fremy, Margot Wagner, Erwan Corre, Alicia Le Salver, Cédric Leroux, Catherine Leblanc, Catherine Boyen, Anne Siegel, and Simon M. Dittami. Metabolic Complementarity Between a Brown Alga and Associated Cultivable Bacteria Provide Indications of Beneficial Interactions. Frontiers in Marine Science, 7 :85, 2020.
@article{Burgunter-Delamare2020,
abstract = {Brown algae are key components of marine ecosystems and live in association with bacteria that are essential for their growth and development. Ectocarpus siliculosus is a genetic and genomic model for brown algae. Here we use this model to start disentangling the complex interactions that may occur between the algal host and its associated bacteria. We report the genome-sequencing of 10 alga-associated bacteria and the genome-based reconstruction of their metabolic networks. The predicted metabolic capacities were then used to identify metabolic complementarities between the algal host and the bacteria, highlighting a range of potentially beneficial metabolite exchanges between them. These putative exchanges allowed us to predict consortia consisting of a subset of these ten bacteria that would best complement the algal metabolism. Finally, co-culture experiments were set up with a subset of these consortia to monitor algal growth as well as the presence of key algal metabolites. Although we did not fully control but only modified bacterial communities in our experiments, our data demonstrated a significant increase in algal growth in cultures inoculated with the selected consortia. In several cases, we also detected, in algal extracts, the presence of key metabolites predicted to become producible via an exchange of metabolites between the alga and the microbiome. Thus, although further methodological developments will be necessary to better control and understand microbial interactions in Ectocarpus, our data suggest that metabolic complementarity is a good indicator of beneficial metabolite exchanges in the holobiont.},
author = {Burgunter-Delamare, Bertille and KleinJan, Hetty and Frioux, Cl{\'{e}}mence and Fremy, Enora and Wagner, Margot and Corre, Erwan and {Le Salver}, Alicia and Leroux, C{\'{e}}dric and Leblanc, Catherine and Boyen, Catherine and Siegel, Anne and Dittami, Simon M.},
doi = {10.3389/FMARS.2020.00085},
issn = {2296-7745},
journal = {Frontiers in Marine Science},
keywords = {Ectocarpus siliculosus,Genome-scale metabolic networks,holobiont,metabolic complementarity,symbiotic/mutualistic bacteria},
month = feb,
pages = {85},
publisher = {Frontiers},
title = ,
volume = {7},
pdf = {https://www.frontiersin.org/articles/10.3389/fmars.2020.00085/pdf},
url = {https://www.frontiersin.org/articles/10.3389/fmars.2020.00085},
year = {2020},
hal_id = {hal-02866101},
month_numeric = {2}
}
Delphine Nègre, Méziane Aite, Arnaud Belcour, Clémence Frioux, Loraine Brillet-Guéguen, Xi Liu, Philippe Bordron, Olivier Godfroy, Agnieszka P. Lipinska, Catherine Leblanc, Anne Siegel, Simon M. Dittami, Erwan Corre, and Gabriel V. Markov. Genome–scale metabolic networks shed light on the carotenoid biosynthesis pathway in the brown algae saccharina japonica and cladosiphon okamuranus. Antioxidants, 8(11) :564, 2019.
@article{Negre2019,
abstract = {Understanding growth mechanisms in brown algae is a current scientific and economic challenge that can benefit from the modeling of their metabolic networks. The sequencing of the genomes of Saccharina japonica and Cladosiphon okamuranus has provided the necessary data for the reconstruction of Genome–Scale Metabolic Networks (GSMNs). The same in silico method deployed for the GSMN reconstruction of Ectocarpus siliculosus to investigate the metabolic capabilities of these two algae, was used. Integrating metabolic profiling data from the literature, we provided functional GSMNs composed of an average of 2230 metabolites and 3370 reactions. Based on these GSMNs and previously published work, we propose a model for the biosynthetic pathways of the main carotenoids in these two algae. We highlight, on the one hand, the reactions and enzymes that have been preserved through evolution and, on the other hand, the specificities related to brown algae. Our data further indicate that, if abscisic acid is produced by Saccharina japonica, its biosynthesis pathway seems to be different in its final steps from that described in land plants. Thus, our work illustrates the potential of GSMNs reconstructions for formalizing hypotheses that can be further tested using targeted biochemical approaches.},
author = {N{\`{e}}gre, Delphine and Aite, M{\'{e}}ziane and Belcour, Arnaud and Frioux, Cl{\'{e}}mence and Brillet-Gu{\'{e}}guen, Loraine and Liu, Xi and Bordron, Philippe and Godfroy, Olivier and Lipinska, Agnieszka P. and Leblanc, Catherine and Siegel, Anne and Dittami, Simon M. and Corre, Erwan and Markov, Gabriel V.},
doi = {10.3390/antiox8110564},
issn = {20763921},
journal = {Antioxidants},
keywords = {Abscisic acid,Brown algae,Cladosiphon okamuranus,Data integration,Fucoxanthin,Genome-Scale metabolic networks (GSMNs),Oxygenated carotenoid biosynthesis,Saccharina japonica},
month = nov,
number = {11},
pages = {564},
publisher = {Multidisciplinary Digital Publishing Institute},
title = ,
url = {https://www.mdpi.com/2076-3921/8/11/564},
pdf = {https://www.mdpi.com/2076-3921/8/11/564/pdf},
volume = {8},
year = {2019},
hal_id = {hal-02395080},
month_numeric = {11}
}
Clémence Frioux, Torsten Schaub, Sebastian Schellhorn, Anne Siegel, and Philipp Wanko. Hybrid metabolic network completion. Theory and Practice of Logic Programming, 19(01) :83–108, 2019.
@article{Frioux2019,
abstract = {Metabolic networks play a crucial role in biology since they capture all chemical reactions in an organism. While there are networks of high quality for many model organisms, networks for less studied organisms are often of poor quality and suffer from incompleteness. To this end, we introduced in previous work an answer set programming (ASP)-based approach to metabolic network completion. Although this qualitative approach allows for restoring moderately degraded networks, it fails to restore highly degraded ones. This is because it ignores quantitative constraints capturing reaction rates. To address this problem, we propose a hybrid approach to metabolic network completion that integrates our qualitative ASP approach with quantitative means for capturing reaction rates. We begin by formally reconciling existing stoichiometric and topological approaches to network completion in a unified formalism. With it, we develop a hybrid ASP encoding and rely upon the theory reasoning capacities of the ASP system clingo for solving the resulting logic program with linear constraints over reals. We empirically evaluate our approach by means of the metabolic network of Escherichia coli . Our analysis shows that our novel approach yields greatly superior results than obtainable from purely qualitative or quantitative approaches.},
author = {Frioux, Cl{\'{e}}mence and Schaub, Torsten and Schellhorn, Sebastian and Siegel, Anne and Wanko, Philipp},
doi = {10.1017/S1471068418000455},
issn = {1471-0684},
journal = {Theory and Practice of Logic Programming},
keywords = {answer set programming,bioinformatics,gap-filling,hybrid solving,linear programming,metabolic network},
month = jan,
number = {01},
pages = {83--108},
publisher = {Cambridge University Press},
title = ,
url = {https://www.cambridge.org/core/product/identifier/S1471068418000455/type/journal{\_}article},
volume = {19},
year = {2019},
pdf = {https://arxiv.org/pdf/1808.04149.pdf},
optlink = {http://arxiv.org/abs/1808.04149},
month_numeric = {1}
}
Clémence Frioux, Enora Fremy, Camille Trottier, and Anne Siegel. Scalable and exhaustive screening of metabolic functions carried out by microbial consortia. Bioinformatics, 34(17) :i934–i943, 2018.
@article{Frioux2018,
author = {Frioux, Cl{\'{e}}mence and Fremy, Enora and Trottier, Camille and Siegel, Anne},
doi = {10.1093/bioinformatics/bty588},
issn = {1367-4803},
journal = {Bioinformatics},
month = sep,
number = {17},
pages = {i934--i943},
publisher = {Oxford University Press},
title = ,
url = {https://academic.oup.com/bioinformatics/article/34/17/i934/5093211},
volume = {34},
year = {2018},
pdf = {https://academic.oup.com/bioinformatics/article-pdf/34/17/i934/25702201/bty588.pdf},
hal_id = {hal-01871600},
month_numeric = {9}
}
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. Traceability, reproducibility and wiki-exploration for “à-la-carte” reconstructions of genome-scale metabolic models. PLOS Computational Biology, 14(5) :1–25, 2018.
@article{Aite2018,
author = {Aite, Méziane and Chevallier, Marie and Frioux, Clémence and Trottier, Camille and Got, Jeanne and Cortés, María Paz and Mendoza, Sebastián N. and Carrier, Grégory and Dameron, Olivier and Guillaudeux, Nicolas and Latorre, Mauricio and Loira, Nicolás and Markov, Gabriel V. and Maass, Alejandro and Siegel, Anne},
journal = {PLOS Computational Biology},
publisher = {Public Library of Science},
title = {Traceability, reproducibility and wiki-exploration for “à-la-carte” reconstructions of genome-scale metabolic models},
year = {2018},
month = may,
volume = {14},
url = {https://doi.org/10.1371/journal.pcbi.1006146},
pages = {1-25},
abstract = {Author summary Genome-scale metabolic models describe an organism’s metabolism. Building good models requires the integration of all relevant available information, obtained by exploring different data types and biological databases. This process is not straightforward and choices are made along the way, for example, which data is analyzed, with what tools. It matters that all reconstruction steps are well documented so that models can be fully exploited by the community. Having this metadata allows other researchers to reproduce, improve or reuse a model as a blueprint to create new ones. Sadly, this information is usually scattered and its proper distribution is the exception rather than the norm when using “à la carte” pipelines that combine main platforms and individual tools. We created a platform for “à la carte” metabolic model generation that responds to the need of transparency and data-connection in the field. It includes a battery of tools to exploit heterogeneous data through customizable pipelines. At each step, relevant information is stored, ensuring reproducibility and documentation of processes. Furthermore, exploration of models and metadata during the reconstruction process is facilitated through the automatic generation of local wikis. This view offers a user-friendly solution to iteratively explore genome-scale metabolic models produced with personalized pipelines and poorly interoperable tools. We highlight these benefits by building models for organisms with various input data. Among them, we show why the combination of heterogeneous information is necessary to elucidate specificities of Tisochrysis lutea, a eukaryotic microalga, for anti-oxidant production.},
number = {5},
doi = {10.1371/journal.pcbi.1006146},
pdf = {http://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1006146&type=printable},
hal_id = {hal-01819150},
month_numeric = {5}
}
Julie Laniau, Clémence Frioux, Jacques Nicolas, Caroline Baroukh, María Paz Cortes, Jeanne Got, Camille Trottier, Damien Eveillard, and Anne Siegel. Combining graph and flux-based structures to decipher phenotypic essential metabolites within metabolic networks. PeerJ, 2017(10) 2017.
@article{Laniau2017,
author = {Laniau, Julie and Frioux, Clémence and Nicolas, Jacques and Baroukh, Caroline and Cortes, María Paz and Got, Jeanne and Trottier, Camille and Eveillard, Damien and Siegel, Anne},
doi = {10.7717/peerj.3860},
issn = {21678359},
journal = {PeerJ},
keywords = {Answer Set Programming,Constraint-based analysis,Essential metabolite,Graph-based analysis,Metabolic networks},
number = {10},
title = {Combining graph and flux-based structures to decipher phenotypic essential metabolites within metabolic networks},
volume = {2017},
year = {2017},
pdf = {https://peerj.com/articles/3860.pdf},
hal_id = {hal-01635688}
}
Sylvain Prigent, Clémence Frioux, Simon M. Dittami, Sven Thiele, Abdelhalim Larhlimi, Guillaume Collet, Fabien Gutknecht, Jeanne Got, Damien Eveillard, Jérémie Bourdon, Frédéric Plewniak, Thierry Tonon, and Anne Siegel. Meneco, a Topology-Based Gap-Filling Tool Applicable to Degraded Genome-Wide Metabolic Networks. PLoS Computational Biology, 13(1) 2017.
@article{Prigent2017,
author = {Prigent, Sylvain and Frioux, Clémence and Dittami, Simon M. and Thiele, Sven and Larhlimi, Abdelhalim and Collet, Guillaume and Gutknecht, Fabien and Got, Jeanne and Eveillard, Damien and Bourdon, Jérémie and Plewniak, Frédéric and Tonon, Thierry and Siegel, Anne},
doi = {10.1371/journal.pcbi.1005276},
issn = {15537358},
journal = {PLoS Computational Biology},
number = {1},
title = {Meneco, a Topology-Based Gap-Filling Tool Applicable to Degraded Genome-Wide Metabolic Networks},
volume = {13},
year = {2017},
pdf = {http://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1005276&type=printable},
hal_id = {hal-01449100}
}
Teemu Haikarainen, Clémence Frioux, Li-Qing Zhnag, Duo-Chuan Li, and Anastassios C. Papageorgiou. Crystal structure and biochemical characterization of a manganese superoxide dismutase from Chaetomium thermophilum. Biochimica et Biophysica Acta (BBA) - Proteins and Proteomics, 1844(2) :422–429, 2014.
@article{Haikarainen2014,
author = {Haikarainen, Teemu and Frioux, Clémence and Zhnag, Li-Qing and Li, Duo-Chuan and Papageorgiou, Anastassios C.},
doi = {10.1016/j.bbapap.2013.11.014},
issn = {15709639},
journal = {Biochimica et Biophysica Acta (BBA) - Proteins and Proteomics},
number = {2},
pages = {422--429},
title = {Crystal structure and biochemical characterization of a manganese superoxide dismutase from Chaetomium thermophilum},
volume = {1844},
year = {2014},
pdf = {https://github.com/cfrioux/cfrioux.github.io/tree/master/data/papers/haikarainen2014.pdf}
}
Clémence Frioux, Sylvie Huet, Simon Labarthe, Julien Martinelli, Thibault Malou, David Sherman, Marie-Luce Taupin, and Pablo Ugalde-Salas. Accelerating metabolic models evaluation with statistical metamodels: application to Salmonella infection models. In: ESAIM: Proceedings and Surveys, pp. 187–217 2023.
@inproceedings{Frioux.2023sga,
year = {2023},
title = ,
author = {Frioux, Clémence and Huet, Sylvie and Labarthe, Simon and Martinelli, Julien and Malou, Thibault and Sherman, David and Taupin, Marie-Luce and Ugalde-Salas, Pablo},
booktitle = {ESAIM: Proceedings and Surveys},
booktitleaddon = {CEMRACS 2021 - Data Assimilation and Reduced Modeling for High Dimensional Problems},
doi = {10.1051/proc/202373187},
abstract = ,
pages = {187--217},
volume = {73},
keywords = {na},
pdf = {https://hal.inrae.fr/hal-03635862/file/main.pdf},
hal_id = {hal-03635862},
hal_version = {v1}
}
Clémence Frioux, Torsten Schaub, Sebastian Schellhorn, Anne Siegel, and Philipp Wanko. Hybrid metabolic network completion. In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), pp. 308–321, Springer, Cham, 2017.
@inproceedings{Frioux2017,
author = {Frioux, Clémence and Schaub, Torsten and Schellhorn, Sebastian and Siegel, Anne and Wanko, Philipp},
booktitle = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
doi = {10.1007/978-3-319-61660-5_28},
isbn = {9783319616599},
issn = {16113349},
pages = {308--321},
publisher = {Springer, Cham},
title = {Hybrid metabolic network completion},
url = {http://link.springer.com/10.1007/978-3-319-61660-5{\_}28},
volume = {10377 LNAI},
year = {2017},
hal_id = {hal-01557347},
pdf = {https://hal.inria.fr/hal-01557347/document}
}
Clémence Frioux and Anne Siegel. Problèmes d’optimisation combinatoire pour l’étude du métabolisme. In: Editions, I.S.T.E. (ed.) Approches symboliques de la modélisation et de l’analyse des systèmes biologiques, pp. 51–96, ISTE Group, 2022.
@inbook{frioux2022_iste,
year = {2022},
title = ,
author = {Frioux, Clémence and Siegel, Anne},
editor = {Editions, ISTE},
bookauthor = {Cédric Lhoussaine,Élisabeth Remy},
booktitle = {Approches symboliques de la modélisation et de l’analyse des systèmes biologiques},
isbn = {9781789480290},
url = {https://books.google.fr/books?id=z456EAAAQBAJ\&dq=holobiont+interaction\&lr=\&hl=fr\&source=gbs\_navlinks\_s},
pages = {51-96},
series = {SCIENCES},
publisher = {ISTE Group},
language = {French},
keywords = {book},
hal_id = {hal-03885249},
hal_version = {v1},
pdf = {https://inria.hal.science/hal-03885249v1/document}
}
Clémence Frioux. Investigating host-microbiota cooperation with gap-filling optimization problems, PhD thesis, Université de Rennes 1, November 2018.
@phdthesis{Frioux2020,
abstract = {Systems biology relies on computational biology to integrate knowledge and data, for a better understanding of organisms' physiology. Challenges reside in the applicability of methods and tools to non-model organisms, for instance in marine biology. Sequencing advances and the growing importance of elucidating microbiotas' roles, have led to an increased interest into these organisms. This thesis focuses on the modeling of the metabolism through networks, and of its functionality using graphs and constraints semantics. In particular, a first part presents work on gap-filling metabolic networks in the context of non-model organisms. A graph-based method is benchmarked and validated and a hybrid one is developed using Answer Set Programming (ASP) and linear programming. Such gap-filling is applied on algae and extended to decipher putative interactions between Ectocarpus siliculosus and a symbiotic bacterium. In this direction, the second part of the thesis aims at proposing formalisms and implementation of a tool for selecting and screening communities of interest within microbiotas. It enables to scale to large microbiotas and, with a two-step approach, to suggest symbionts that fit the desired objective. The modeling supports the computation of exchanges, and solving can cover the whole solution space. Applications are presented on the human gut microbiota and the selection of bacterial communities for a brown alga. Altogether, this thesis proposes modeling, software and biological applications using graph-based semantics to support the elaboration of hypotheses for elucidating the metabolism of organisms.},
author = {Frioux, Cl{\'{e}}mence},
month = nov,
publisher = {Universit{\'{e}} de Rennes 1},
school = {Universit{\'{e}} de Rennes 1},
title = ,
url = {https://hal.inria.fr/tel-01945853},
year = {2018},
hal_id = {hal-01945853},
pdf = {https://hal.inria.fr/tel-01945853/document},
month_numeric = {11}
}
Maxime Lecomte, Wenfan Cao, Julie Aubert, David J. Sherman, Hélène Falentin, Clémence Frioux, and Simon Labarthe. A digital twin of bacterial metabolism during cheese production. bioRxiv, 2023.
preprint
@article{Lecomte.2023_2,
year = {2023},
title = ,
author = {Lecomte, Maxime and Cao, Wenfan and Aubert, Julie and Sherman, David J. and Falentin, Hélène and Frioux, Clémence and Labarthe, Simon},
journal = {bioRxiv},
doi = {10.1101/2023.05.05.539417},
publisher = {Cold Spring Harbor Laboratory},
abstract = {Cheese organoleptic properties result from complex metabolic processes occurring in microbial communities. A deeper understanding of such mechanisms makes it possible to improve both industrial production processes and end-product quality through the design of microbial consortia. In this work, we caracterise the metabolism of a three-species community consisting of Lactococcus lactis, Lactobacillus plantarum and Propionibacterium freudenreichii during a seven-week cheese production process. Using genome-scale metabolic models and omics data integration, we modeled and calibrated individual dynamics using monoculture experiments, and coupled these models to capture the metabolism of the community. This digital twin accurately predicted the dynamics of the community, enlightening the contribution of each microbial species to organoleptic compound production. Further metabolic exploration raised additional possible interactions between the bacterial species. This work provides a methodological framework for the prediction of community-wide metabolism and highlights the added-value of dynamic metabolic modeling for the comprehension of fermented food processes.},
url = {https://www.biorxiv.org/content/10.1101/2023.05.05.539417v1},
pdf = {https://www.biorxiv.org/content/10.1101/2023.05.05.539417v1.full.pdf},
pages = {},
keywords = {preprint},
note = {preprint},
hal_id = {hal-04088301},
hal_version = {v1}
}
Arnaud Belcour, Baptiste Ruiz, Clémence Frioux, Samuel Blanquart, and Anne Siegel. EsMeCaTa: Estimating metabolic capabilities from taxonomic affiliations. bioRxiv, 2022.
preprint
@article{Belcour2022.03.16.484574,
author = {Belcour, Arnaud and Ruiz, Baptiste and Frioux, Cl{\'e}mence and Blanquart, Samuel and Siegel, Anne},
title = {EsMeCaTa: Estimating metabolic capabilities from taxonomic affiliations},
elocation-id = {2022.03.16.484574},
year = {2022},
doi = {10.1101/2022.03.16.484574},
publisher = {Cold Spring Harbor Laboratory},
abstract = {Summary Predicting the functional potential of microorganisms in environmental samples from cultivation-independent techniques is a major challenge. A persistent difficulty lies in associating taxonomic profiles obtained from metabarcoding experiment with accurate functional profiles, particularly for poorly-resolved taxonomic groups. In this paper, we present EsMeCaTa a python package predicting shared proteins from taxonomic affiliations. EsMeCaTa relies on the UniProt database to retrieve the public proteomes associated with a taxon and then uses MMseqs2 in order to compute the set of proteins shared in the taxon. Finally, Es-MeCaTa extracts the functional annotations of these proteins to provide an accurate estimate of the functional potential associated to taxonomic affiliations. Availability EsMeCaTa is available at: https://github.com/AuReMe/esmecata under the GPL-3 license.Competing Interest StatementThe authors have declared no competing interest.},
url = {https://www.biorxiv.org/content/early/2022/03/18/2022.03.16.484574},
journal = {bioRxiv},
note = {preprint},
pdf = {https://www.biorxiv.org/content/10.1101/2022.03.16.484574v1.full.pdf},
hal_id = {hal-03223662}
}
Here is some computational biology software I developed or for which I was involved in the development:
2019
Metage2Metabo Automatic metabolic network reconstruction with Pathway Tools and graph-based analysis of metabolic capabilities for the collection of networks, individually and collectively package, project
2018
MiSCoTO Screening of microbiota metabolic capabilities and selection of minimal (minimal-size, minimal-exchanges) communities package, project
2017
AuReMe Traceable and reproducible reconstruction of metabolic networks image, project ↗
2017
Fluto Graph-based and constraint-based hybrid gap-filling of metabolic networks Conda package, project
2016
MeNeTools Graph-based analysis tools for metabolic networks package, project
2015
Meneco Graph-based gap-filling of metabolic networks package, project