Skip to Main content Skip to Navigation
Journal articles

Inferring Biochemical Reactions and Metabolite Structures to Understand Metabolic Pathway Drift

Arnaud Belcour 1 Jean Girard 2 Méziane Aite 1 Ludovic Delage 2 Camille Trottier 1 Charlotte Marteau 3 Cédric J-J Leroux 4 Simon Dittami 2 Pierre Sauleau 3 Erwan Corre 5 Jacques Nicolas 6 Catherine Boyen 2 Catherine Leblanc 2 Jonas Collén 2 Anne Siegel 1 Gabriel V Markov 2, *
* Corresponding author
1 Dyliss - Dynamics, Logics and Inference for biological Systems and Sequences
Inria Rennes – Bretagne Atlantique , IRISA-D7 - GESTION DES DONNÉES ET DE LA CONNAISSANCE
2 LBI2M - Laboratoire de Biologie Intégrative des Modèles Marins
3 LBCM - Laboratoire de Biotechnologie et Chimie Marines
4 SBR - Station biologique de Roscoff
5 FR2424 - ABiMS - Informatique et bioinformatique = Analysis and Bioinformatics for Marine Science
6 GenScale - Scalable, Optimized and Parallel Algorithms for Genomics
Inria Rennes – Bretagne Atlantique , IRISA-D7 - GESTION DES DONNÉES ET DE LA CONNAISSANCE
Abstract : 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.
Keywords : Sterols Metabolic pathway drift Genome-scale metabolic network Chondrus crispus Mycosporine-like amino acid
Document type :
Journal articles
Complete list of metadata

Cited literature [30 references]  Display  Hide  Download
https://hal.inria.fr/hal-01943880
Contributor : Belcour Arnaud Connect in order to contact the contributor
Submitted on : Monday, February 24, 2020 - 10:39:32 AM
Last modification on : Saturday, January 8, 2022 - 3:46:00 AM

File

Vignette du document
Belcour2020.pdf
Files produced by the author(s)

Licence

Distributed under a Creative Commons Attribution - NonCommercial - NoDerivatives 4.0 International License

Identifiers

Collections

UNIV-BREST | IUEM | UNIV-RENNES1 | INRIA | IRD | UNIV-RENNES | SORBONNE-UNIVERSITE | LBI2M | FR2424 | IRISA | CNRS | CENTRALESUPELEC | UBS | UR1-MATH-STIC | UR1-UFR-ISTIC | SU-SCIENCES | LBCM_UBS | IRISA_UBS_2 | INSU | INSA-RENNES | SU-TI | UR1-MATH-NUM

Citation

Arnaud Belcour, Jean Girard, Méziane Aite, Ludovic Delage, Camille Trottier, et al.. Inferring Biochemical Reactions and Metabolite Structures to Understand Metabolic Pathway Drift. iScience, Elsevier, 2020, 23 (2), pp.100849. ⟨10.1016/j.isci.2020.100849⟩. ⟨hal-01943880v2⟩

Export

BibTeX TEI DC DCterms EndNote

Share

Metrics

Les métriques sont temporairement indisponibles

 

Contact                    Legal Notice                    Personal Data