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14 results on '"Natacha Lenuzza"'

1. The fitness cost of horizontally transferred and mutational antimicrobial resistance in Escherichia coli

Author

Marie Vanacker, Natacha Lenuzza, and Jean-Philippe Rasigade

Subjects
conjugation, plasmid, mutation, relative fitness, compensatory evolution, Microbiology, QR1-502
Abstract

Antimicrobial resistance (AMR) in bacteria implies a tradeoff between the benefit of resistance under antimicrobial selection pressure and the incurred fitness cost in the absence of antimicrobials. The fitness cost of a resistance determinant is expected to depend on its genetic support, such as a chromosomal mutation or a plasmid acquisition, and on its impact on cell metabolism, such as an alteration in an essential metabolic pathway or the production of a new enzyme. To provide a global picture of the factors that influence AMR fitness cost, we conducted a systematic review and meta-analysis focused on a single species, Escherichia coli. By combining results from 46 high-quality studies in a multilevel meta-analysis framework, we find that the fitness cost of AMR is smaller when provided by horizontally transferable genes such as those encoding beta-lactamases, compared to mutations in core genes such as those involved in fluoroquinolone and rifampicin resistance. We observe that the accumulation of acquired AMR genes imposes a much smaller burden on the host cell than the accumulation of AMR mutations, and we provide quantitative estimates of the additional cost of a new gene or mutation. These findings highlight that gene acquisition is more efficient than the accumulation of mutations to evolve multidrug resistance, which can contribute to the observed dominance of horizontally transferred genes in the current AMR epidemic.

Published
2023
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2. Multiplatform metabolomics for an integrative exploration of metabolic syndrome in older men

Author

Blandine Comte, Stéphanie Monnerie, Marion Brandolini-Bunlon, Cécile Canlet, Florence Castelli, Emeline Chu-Van, Benoit Colsch, François Fenaille, Charlotte Joly, Fabien Jourdan, Natacha Lenuzza, Bernard Lyan, Jean-François Martin, Carole Migné, José A. Morais, Mélanie Pétéra, Nathalie Poupin, Florence Vinson, Etienne Thevenot, Christophe Junot, Pierrette Gaudreau, and Estelle Pujos-Guillot

Subjects
Metabolic syndrome, Metabolomics, Deep phenotyping, Lipidomics, Metabolic signature, Medicine, Medicine (General), R5-920
Abstract

Background: Metabolic syndrome (MetS), a cluster of factors associated with risks of developing cardiovascular diseases, is a public health concern because of its growing prevalence. Considering the combination of concomitant components, their development and severity, MetS phenotypes are largely heterogeneous, inducing disparity in diagnosis. Methods: A case/control study was designed within the NuAge longitudinal cohort on aging. From a 3-year follow-up of 123 stable individuals, we present a deep phenotyping approach based on a multiplatform metabolomics and lipidomics untargeted strategy to better characterize metabolic perturbations in MetS and define a comprehensive MetS signature stable over time in older men. Findings: We characterize significant changes associated with MetS, involving modulations of 476 metabolites and lipids, and representing 16% of the detected serum metabolome/lipidome. These results revealed a systemic alteration of metabolism, involving various metabolic pathways (urea cycle, amino-acid, sphingo- and glycerophospholipid, and sugar metabolisms…) not only intrinsically interrelated, but also reflecting environmental factors (nutrition, microbiota, physical activity…). Interpretation: These findings allowed identifying a comprehensive MetS signature, reduced to 26 metabolites for future translation into clinical applications for better diagnosing MetS.

Published
2021
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3. Metabolic reprograming of LPS-stimulated human lung macrophages involves tryptophan metabolism and the aspartate-arginosuccinate shunt.

Author

Fanta Fall, Elodie Lamy, Marion Brollo, Emmanuel Naline, Natacha Lenuzza, Etienne Thévenot, Philippe Devillier, and Stanislas Grassin-Delyle

Subjects
Medicine, Science
Abstract

Lung macrophages (LM) are in the first line of defense against inhaled pathogens and can undergo phenotypic polarization to the proinflammatory M1 after stimulation with Toll-like receptor agonists. The objective of the present work was to characterize the metabolic alterations occurring during the experimental M1 LM polarization. Human LM were obtained from resected lungs and cultured for 24 hrs in medium alone or with 10 ng.mL-1 lipopolysaccharide. Cells and culture supernatants were subjected to extraction for metabolomic analysis with high-resolution LC-MS (HILIC and reverse phase -RP- chromatography in both negative and positive ionization modes) and GC-MS. The data were analyzed with R and the Worklow4Metabolomics and MetaboAnalyst online infrastructures. A total of 8,741 and 4,356 features were detected in the intracellular and extracellular content, respectively, after the filtering steps. Pathway analysis showed involvement of arachidonic acid metabolism, tryptophan metabolism and Krebs cycle in the response of LM to LPS, which was confirmed by the specific quantitation of selected compounds. This refined analysis highlighted a regulation of the kynurenin pathway as well as the serotonin biosynthesis pathway, and an involvement of aspartate-arginosuccinate shunt in the malate production. Macrophages M1 polarization is accompanied by changes in the cell metabolome, with the differential expression of metabolites involved in the promotion and regulation of inflammation and antimicrobial activity. The analysis of this macrophage immunometabolome may be of interest for the understanding of the pathophysiology of lung inflammatory disesases.

Published
2020
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4. An efficient kinetic model for assemblies of amyloid fibrils and its application to polyglutamine aggregation.

Author

Stéphanie Prigent, Annabelle Ballesta, Frédérique Charles, Natacha Lenuzza, Pierre Gabriel, Léon Matar Tine, Human Rezaei, and Marie Doumic

Subjects
Medicine, Science
Abstract

Protein polymerization consists in the aggregation of single monomers into polymers that may fragment. Fibrils assembly is a key process in amyloid diseases. Up to now, protein aggregation was commonly mathematically simulated by a polymer size-structured ordinary differential equations (ODE) system, which is infinite by definition and therefore leads to high computational costs. Moreover, this Ordinary Differential Equation-based modeling approach implies biological assumptions that may be difficult to justify in the general case. For example, whereas several ordinary differential equation models use the assumption that polymerization would occur at a constant rate independently of polymer size, it cannot be applied to certain protein aggregation mechanisms. Here, we propose a novel and efficient analytical method, capable of modelling and simulating amyloid aggregation processes. This alternative approach consists of an integro-Partial Differential Equation (PDE) model of coalescence-fragmentation type that was mathematically derived from the infinite differential system by asymptotic analysis. To illustrate the efficiency of our approach, we applied it to aggregation experiments on polyglutamine polymers that are involved in Huntington's disease. Our model demonstrates the existence of a monomeric structural intermediate [Formula: see text] acting as a nucleus and deriving from a non polymerizing monomer ([Formula: see text]). Furthermore, we compared our model to previously published works carried out in different contexts and proved its accuracy to describe other amyloid aggregation processes.

Published
2012
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6. Metabolic reprograming of LPS-stimulated human lung macrophages involves tryptophan metabolism and the aspartate-arginosuccinate shunt

Author

Etienne A. Thévenot, Elodie Lamy, Marion Brollo, Fanta Fall, Philippe Devillier, Stanislas Grassin-Delyle, Emmanuel Naline, Natacha Lenuzza, Infection et inflammation (2I), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Laboratoire de recherche sur les mécanismes moléculaires et pharmacologiques de l’obstruction bronchique (LOBIP), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Département des maladies des voies respiratoires [Suresnes], Hôpital Foch [Suresnes], Laboratoire Sciences des Données et de la Décision (LS2D), Département Métrologie Instrumentation & Information (DM2I), Laboratoire d'Intégration des Systèmes et des Technologies (LIST), Direction de Recherche Technologique (CEA) (DRT (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Direction de Recherche Technologique (CEA) (DRT (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Laboratoire d'Intégration des Systèmes et des Technologies (LIST), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay, This work was supported by the French Ministry of Higher Education and Research (PhD grant, Fanta Fall) and by the Chancellerie des Universités de Paris (Legs Gaston Poix)., Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut National de la Santé et de la Recherche Médicale (INSERM), Laboratoire d'Intégration des Systèmes et des Technologies (LIST (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Laboratoire d'Intégration des Systèmes et des Technologies (LIST (CEA)), and Bodescot, Myriam

Subjects
Lipopolysaccharides, Male, 0301 basic medicine, Ionization, Lipopolysaccharide, Pathway analysis, Biochemistry, [SDV.MHEP.PSR]Life Sciences [q-bio]/Human health and pathology/Pulmonology and respiratory tract, Macrophage M1 polarization, White Blood Cells, chemistry.chemical_compound, Aromatic Amino Acids, 0302 clinical medicine, lung inflammatory disesase, Drug Metabolism, Animal Cells, Medicine and Health Sciences, Macrophage, Alveolar Macrophages, Amino Acids, Receptor, Cells, Cultured, pathophysiology, mass spectrometry, Gas chromatography, Multidisciplinary, [SDV.BIBS] Life Sciences [q-bio]/Quantitative Methods [q-bio.QM], Organic Compounds, Chemistry, Tryptophan, Chemical Reactions, bioinformatics, Middle Aged, inflammation regulation, metabolomics, [SDV.BIBS]Life Sciences [q-bio]/Quantitative Methods [q-bio.QM], Targeted metabolic profiling, Lung macrophage, classification, Physical Sciences, Medicine, metabolic alteration, Female, Cellular Types, medicine.symptom, Intracellular, data processing, Research Article, Signal Transduction, clustering, Cell Physiology, Immune Cells, Science, Immunology, macrophage immunometabolome, Liquid chromatography, Inflammation, spectrum analysis, Argininosuccinic Acid, Proinflammatory cytokine, lung, 03 medical and health sciences, statistical analysis, Macrophages, Alveolar, Extracellular, Metabolome, medicine, Humans, Pharmacokinetics, Aged, Pharmacology, Aspartic Acid, polarization, Blood Cells, antimicrobial activity, Macrophages, Organic Chemistry, Chemical Compounds, Biology and Life Sciences, Proteins, Cell Biology, Macrophage Activation, Cell Metabolism, Amino Acid Metabolism, Metabolism, 030104 developmental biology, 030228 respiratory system, Multivariate analysis, [SDV.MHEP.PSR] Life Sciences [q-bio]/Human health and pathology/Pulmonology and respiratory tract
Abstract

International audience; Lung macrophages (LM) are in the first line of defense against inhaled pathogens and can undergo phenotypic polarization to the proinflammatory M1 after stimulation with Toll-like receptor agonists. The objective of the present work was to characterize the metabolic alterations occurring during the experimental M1 LM polarization. Human LM were obtained from resected lungs and cultured for 24 hrs in medium alone or with 10 ng.mL-1 lipopolysaccharide. Cells and culture supernatants were subjected to extraction for metabolomic analysis with high-resolution LC-MS (HILIC and reverse phase -RP- chromatography in both negative and positive ionization modes) and GC-MS. The data were analyzed with R and the Worklow4Metabolomics and MetaboAnalyst online infrastructures. A total of 8,741 and 4,356 features were detected in the intracellular and extracellular content, respectively, after the filtering steps. Pathway analysis showed involvement of arachidonic acid metabolism, tryptophan metabolism and Krebs cycle in the response of LM to LPS, which was confirmed by the specific quantitation of selected compounds. This refined analysis highlighted a regulation of the kynurenin pathway as well as the serotonin biosynthesis pathway, and an involvement of aspartate-arginosuccinate shunt in the malate production. Macrophages M1 polarization is accompanied by changes in the cell metabolome, with the differential expression of metabolites involved in the promotion and regulation of inflammation and antimicrobial activity. The analysis of this macrophage immunometabolome may be of interest for the understanding of the pathophysiology of lung inflammatory disesases.

Published
2020
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7. A limited sampling strategy based on maximum a posteriori Bayesian estimation for a five-probe phenotyping cocktail

Author

Alain Pruvost, Thu Thuy Nguyen, Natacha Lenuzza, Henri Benech, Laboratoire d'analyse des données et d'intelligence des systèmes (LADIS), Département Métrologie Instrumentation & Information (DM2I), Laboratoire d'Intégration des Systèmes et des Technologies (LIST), Direction de Recherche Technologique (CEA) (DRT (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Direction de Recherche Technologique (CEA) (DRT (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Laboratoire d'Intégration des Systèmes et des Technologies (LIST), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay, Laboratoire d'Etude du Métabolisme des Médicaments (LEMM), Service de Pharmacologie et Immunoanalyse (SPI), Médicaments et Technologies pour la Santé (MTS), Université Paris-Saclay-Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Paris-Saclay-Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Médicaments et Technologies pour la Santé (MTS), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), CEA program 'Technologies pour la santé', Laboratoire d'Intégration des Systèmes et des Technologies (LIST (CEA)), and Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Laboratoire d'Intégration des Systèmes et des Technologies (LIST (CEA))

Subjects
PHARMACOKINETICS, PREDICTION, CYP1A2, Pilot Projects, Dextromethorphan, 030226 pharmacology & pharmacy, Bayes' theorem, Maximum a posteriori Bayesian estimation, 0302 clinical medicine, Statistics, Drug Interactions, Pharmacology (medical), Mathematics, [STAT.AP]Statistics [stat]/Applications [stat.AP], Bayes estimator, education.field_of_study, PLASMA, DRIED BLOOD SPOTS, Sampling (statistics), General Medicine, MIDAZOLAM, 3. Good health, Phenotype, 030220 oncology & carcinogenesis, Outlier, MIXED EFFECTS MODELS, symbols, Omeprazole, Tolbutamide, Bayesian probability, Population, Models, Biological, 03 medical and health sciences, symbols.namesake, [SDV.SP.MED]Life Sciences [q-bio]/Pharmaceutical sciences/Medication, Caffeine, Maximum a posteriori estimation, Humans, Computer Simulation, Phenotyping cocktail, Fisher information, education, DRUG DEVELOPMENT, Pharmacology, CYTOCHROME-P450, Bayes Theorem, [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation, Nonlinear mixed effect models, Limited sampling strategy, HEALTHY-VOLUNTEERS
Abstract

International audience; Purpose: Cocktail approach using a combination of probes to phenotype several cytochromes P450 or transporters is of high interest in anticipating drug-drug interactions and personalized medicine. Its clinical use remains however limited by the intensive sampling scheme required to obtain phenotyping indexes (PI) which consists in calculating the area under the concentration-time curves. We proposed to use maximum a posteriori Bayesian estimation (MAPBE) that incorporates available information from the whole population to derive PI from a few individual observations. The performance of a limited sampling strategy (LSS) based on MAPBE was evaluated for a five-probe cocktail. Methods: The studied cocktail included midazolam, tolbutamide, caffeine, dextromethorphan, omeprazole and their relevant metabolites. Prior information for MAPBE was obtained by nonlinear mixed-effect modelling of data from a pilot study. Sampling times were chosen based on optimal design theory using the Bayesian Fisher information matrix. Through a simulation study, we investigated the predicted PI in terms of bias and imprecision for varying number and timing of samples. Results: Some three-point Bayesian designs gave mean prediction errors in [-5 %, 5 %], root mean square errors below 30 % for all probes, except dextromethorphan whose model should be consolidated further with additional data. This approach gave overall less outlier predicted values than single-point metrics and was more flexible to the timing of the latest sampling. Conclusions: MAPBE is accurate for predicting simultaneously several PI while being flexible in terms of integrating clinical constraints. Therefore, LSS based on MAPBE could help reduce the time of presence in hospital for individuals to be phenotyped.

Published
2015
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8. A split-range acquisition method for the non-targeted metabolomic profiling of human plasma with hydrophilic interaction chromatography - high-resolution mass spectrometry

Author

Stanislas Grassin-Delyle, Emmanuel Naline, Philippe Devillier, Natacha Lenuzza, Etienne A. Thévenot, Fanta Fall, Elodie Lamy, Marion Brollo, Infection et inflammation (2I), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Institut National de la Santé et de la Recherche Médicale (INSERM), Laboratoire de recherche sur les mécanismes moléculaires et pharmacologiques de l’obstruction bronchique (LOBIP), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), MetaboHUB, Laboratoire Sciences des Données et de la Décision (LS2D), Département Métrologie Instrumentation & Information (DM2I), Laboratoire d'Intégration des Systèmes et des Technologies (LIST (CEA)), Direction de Recherche Technologique (CEA) (DRT (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Direction de Recherche Technologique (CEA) (DRT (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Laboratoire d'Intégration des Systèmes et des Technologies (LIST (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay, Hôpital Foch [Suresnes], and CCSD, Accord Elsevier

Subjects
High-resolution mass spectrometry, Hydrophilic interaction liquid chromatography, [SDV]Life Sciences [q-bio], Clinical Biochemistry, Mass spectrometry, 030226 pharmacology & pharmacy, 01 natural sciences, Biochemistry, Mass Spectrometry, Analytical Chemistry, 03 medical and health sciences, 0302 clinical medicine, Metabolomics, Ionization, Range (statistics), Metabolome, Humans, Human Metabolome Database, Chromatography, Chemistry, Hydrophilic interaction chromatography, 010401 analytical chemistry, Cell Biology, General Medicine, 0104 chemical sciences, [SDV] Life Sciences [q-bio], Human plasma, Hydrophobic and Hydrophilic Interactions, Chromatography, Liquid
Abstract

International audience; Untargeted metabolomics of human plasma with mass spectrometry is of particular interest in medical research to explore pathophysiology, find disease biomarkers or for the understanding of the response to pharmacotherapy. Since analytical performances may be impacted by the laboratory environment and the acquisition method settings, the objectives of this study were to assess the role of interfering compounds and to propose an acquisition method to maximize the metabolome coverage for human plasma metabolomic analysis. Human plasma samples were processed with liquid/liquid extraction then analysed with HILIC-high resolution mass spectrometry. A method with a single m/z range was compared to four methods with different split acquisition ranges and four sets of ionization source parameters were compared. The data were analysed with the R software and on the Worklow4Metabolomics online platform. The major interfering compounds were identified in blank samples where they accounted for up to 86% of the signal intensity. Splitting the acquisition range into 3 m/z ranges improved the number of detected features, the number of features with proposed annotation in the Human Metabolome Database, as well as signal intensity throughout the whole m/z range. The method performing best was the one using three m/z ranges of approximatively the same extent. Ionization source parameters also strongly affected the number of detected features. Splitting the acquisition range into 3 m/z ranges with optimized ionization source parameters allows a comprehensive analysis of the human plasma metabolome with perspectives for applications to pathophysiological studies.

Published
2019
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9. Safety and pharmacokinetics of the CIME combination of drugs and their metabolites after a single oral dosing in healthy volunteers

Author

Natacha Lenuzza, Xavier Duval, Grégory Nicolas, Etienne Thévenot, Sylvie Job, Orianne Videau, Céline Narjoz, Marie-Anne Loriot, Philippe Beaune, Laurent Becquemont, France Mentré, Christian Funck-Brentano, Loubna Alavoine, Philippe Arnaud, Marcel Delaforge, Henri Bénech, Laboratoire d'Intégration des Systèmes et des Technologies (LIST), Direction de Recherche Technologique (CEA) (DRT (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Infection, Anti-microbiens, Modélisation, Evolution (IAME (UMR_S_1137 / U1137)), Université Paris 13 (UP13)-Université Paris Diderot - Paris 7 (UPD7)-Université Sorbonne Paris Cité (USPC)-Institut National de la Santé et de la Recherche Médicale (INSERM), Centre d'investigation Clinique [CHU Bichat] - Épidémiologie clinique (CIC 1425), AP-HP - Hôpital Bichat - Claude Bernard [Paris], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM), Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Médecine Personnalisée, Pharmacogénomique, Optimisation Thérapeutique (MEPPOT - U1147), Université Paris Descartes - Paris 5 (UPD5)-Institut National de la Santé et de la Recherche Médicale (INSERM), Hôpital Européen Georges Pompidou [APHP] (HEGP), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO), AP-HP Hôpital Bicêtre (Le Kremlin-Bicêtre), CIC Paris Est, Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [AP-HP], Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU), Centre d'Investigations Cliniques [CHU Bichat] (CIC plurithématique), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Systèmes membranaires, photobiologie, stress et détoxification (SMPSD - UMR 8221), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Service de Pharmacologie et d'Immunoanalyse (SPI), Institut National de la Recherche Agronomique (INRA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay, Laboratoire d'analyse des données et d'intelligence des systèmes (LADIS), Département Métrologie Instrumentation & Information (DM2I), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Direction de Recherche Technologique (CEA) (DRT (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Laboratoire d'Intégration des Systèmes et des Technologies (LIST), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay, Modèles et méthodes de l'évaluation thérapeutique des maladies chroniques, Université Paris Diderot - Paris 7 (UPD7)-Institut National de la Santé et de la Recherche Médicale (INSERM), Institut de biologie et de technologies de Saclay, Hôpitaux Universitaires Paris Ouest - Hôpitaux Universitaires Île de France Ouest (HUPO)-Assistance publique - Hôpitaux de Paris (AP-HP) (APHP), Centre d'investigation Biologique (CIB), Université Paris-Sud - Paris 11 (UP11)-Assistance publique - Hôpitaux de Paris (AP-HP) (APHP)-Hôpital Bicêtre, Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris 13 (UP13)-Université Paris Diderot - Paris 7 (UPD7)-Université Sorbonne Paris Cité (USPC), Assistance publique - Hôpitaux de Paris (AP-HP) (APHP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-CHU Pitié-Salpêtrière [APHP], Hôpital Bichat - Claude Bernard, Institut national de recherches archéologiques préventives (Inrap), Département d'Electronique, des Détecteurs et d'Informatique (ex SEDI) (DEDI), Institut de Recherches sur les lois Fondamentales de l'Univers (IRFU), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay, Service de Pharmacologie et Immunoanalyse (SPI), Médicaments et Technologies pour la Santé (MTS), Université Paris-Saclay-Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Cité (UPCité)-Université Sorbonne Paris Nord, Barrière et passage des médicaments, Université Paris-Sud - Paris 11 (UP11)-IFR141, Centre d'investigation clinique Paris Est [CHU Pitié Salpêtrière] (CIC Paris-Est), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Sorbonne Université (SU), Unité de Recherche sur les Maladies Cardiovasculaires, du Métabolisme et de la Nutrition = Research Unit on Cardiovascular and Metabolic Diseases (ICAN), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Sorbonne Université (SU)-Institut de Cardiométabolisme et Nutrition = Institute of Cardiometabolism and Nutrition [CHU Pitié Salpêtrière] (IHU ICAN), CHU Pitié-Salpêtrière [AP-HP], Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)-CHU Pitié-Salpêtrière [AP-HP], and Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Sorbonne Université (SU)

Subjects
Male, Administration, Oral, Pilot Projects, Pharmacology, 030226 pharmacology & pharmacy, 0302 clinical medicine, Cytochrome P-450 Enzyme System, Renal transport, Healthy volunteers, Medicine, Pharmacology (medical), Drug Interactions, IN-VIVO, P-GLYCOPROTEIN, PK Parameters, [SDV.SP]Life Sciences [q-bio]/Pharmaceutical sciences, [SDV.BIBS]Life Sciences [q-bio]/Quantitative Methods [q-bio.QM], Healthy Volunteers, GLUCURONIDATION PARAMETERS, 3. Good health, Pharmaceutical Preparations, 030220 oncology & carcinogenesis, Female, Safety, COCKTAIL APPROACH, Adult, Signal processing, CYP2D6, Drug-Related Side Effects and Adverse Reactions, PHARMACODYNAMIC INTERACTIONS, TRANSPORTING POLYPEPTIDE 1B1, DIGOXIN PHARMACOKINETICS, HIV-INFECTED PATIENTS, INTERINDIVIDUAL VARIABILITY, 03 medical and health sciences, Young Adult, Phase I, Pharmacokinetics, In vivo, [SDV.BBM.GTP]Life Sciences [q-bio]/Biochemistry, Molecular Biology/Genomics [q-bio.GN], Humans, Dosing, Adverse effect, PARACETAMOL ACETAMINOPHEN, business.industry, CIME, [SDV.SP.PHARMA]Life Sciences [q-bio]/Pharmaceutical sciences/Pharmacology, Probes, business
Abstract

International audience; This phase I, pilot clinical study was designed to evaluate the safety and the pharmacokinetic (PK) profiles of the CIME (Metabolic Identity Card) combination of ten drugs, with a view to its use as a phenotyping cocktail. Ten healthy Caucasian subjects were orally dosed with the CIME combination (caffeine-CYP1A2, repaglinide-CYP2C8, tolbutamide-CYP2C9, omeprazole-CYP2C19, dextromethorphan-CYP2D6, midazolam-CYP3A, acetaminophen-UGT1A1, 6&9 and 2B15, digoxin-P-gp, rosuvastatin-OATP1B1&3 and memantine-active renal transport). Blood was collected over 3 days and on day 7. CIME probes and relevant metabolites were assayed by LC-MS/MS and PK parameters were calculated. Main results were: (1) good safety with reversible mild or moderate adverse effects, (2) an analytical method able to quantify simultaneously the 10 probes and the major metabolites, (3) calculation of PK parameters for all probes in general agreed with published values, and (4) identification of the low CYP2D6 metabolizer. This pilot study showed that the CIME combination was well tolerated and that its pharmacokinetics could be accurately measured in healthy volunteers. This combination can now confidently be checked for sensitivity and specificity and for lack of interaction to be validated as a phenotyping cocktail.

Published
2016
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10. Design optimisation for pharmacokinetic modeling of a cocktail of phenotyping drugs

Author

Henri Benech, Natacha Lenuzza, Thu Thuy Nguyen, Marcel Delaforge, Laboratoire d'analyse des données et d'intelligence des systèmes (LADIS), Département Métrologie Instrumentation & Information (DM2I), Laboratoire d'Intégration des Systèmes et des Technologies (LIST (CEA)), Direction de Recherche Technologique (CEA) (DRT (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Direction de Recherche Technologique (CEA) (DRT (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Laboratoire d'Intégration des Systèmes et des Technologies (LIST (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay, Service de Pharmacologie et Immunoanalyse (SPI), Médicaments et Technologies pour la Santé (MTS), Université Paris-Saclay-Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université Paris-Saclay-Direction de Recherche Fondamentale (CEA) (DRF (CEA)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), CEA program 'Technologies pour la santé', Laboratoire d'Intégration des Systèmes et des Technologies (LIST), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay-Laboratoire d'Intégration des Systèmes et des Technologies (LIST), Service de Pharmacologie et d'Immunoanalyse (SPI), and Institut National de la Recherche Agronomique (INRA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay

Subjects
Digoxin, Optimality criterion, Computer science, design, Pilot Projects, computer.software_genre, 030226 pharmacology & pharmacy, 01 natural sciences, 010104 statistics & probability, 0302 clinical medicine, Pharmacology (medical), Drug Interactions, Prospective Studies, SAMPLING WINDOWS, education.field_of_study, [STAT.AP]Statistics [stat]/Applications [stat.AP], Clinical Trials, Phase I as Topic, Estimation theory, MIXED-EFFECTS MODELS, CYTOCHROME-P450 ACTIVITY, DRIED BLOOD SPOTS, Sampling (statistics), P-GLYCOPROTEIN, POPULATION PHARMACOKINETICS, 3. Good health, FISHER INFORMATION MATRIX, symbols, Data mining, pharmacokinetics, [CHIM.CHEM]Chemical Sciences/Cheminformatics, PARAMETER-ESTIMATION, Statistics and Probability, Midazolam, Population, HIV-INFECTED PATIENTS, Machine learning, nonlinear mixed effect models, 03 medical and health sciences, symbols.namesake, [SDV.SP.MED]Life Sciences [q-bio]/Pharmaceutical sciences/Medication, Maximum a posteriori estimation, Humans, 0101 mathematics, education, Fisher information, Pharmacology, business.industry, phenotyping cocktail, Weighting, Nonlinear Dynamics, Personalized medicine, Artificial intelligence, business, computer, HEALTHY-VOLUNTEERS
Abstract

International audience; Our paper proposes a methodological strategy to select optimal sampling designs for phenotyping studies including a cocktail of drugs. A cocktail approach is of high interest to determine the simultaneous activity of enzymes responsible for drug metabolism and pharmacokinetics, therefore useful in anticipating drug-drug interactions and in personalized medicine. Phenotyping indexes, which are area under the concentration-time curves, can be derived from a few samples using nonlinear mixed effect models and maximum a posteriori estimation. Because of clinical constraints in phenotyping studies, the number of samples that can be collected in individuals is limited and the sampling times must be as flexible as possible. Therefore to optimize joint design for several drugs (i.e., to determine a compromise between informative times that best characterize each drug's kinetics), we proposed to use a compound optimality criterion based on the expected population Fisher information matrix in nonlinear mixed effect models. This criterion allows weighting different models, which might be useful to take into account the importance accorded to each target in a phenotyping test. We also computed windows around the optimal times based on recursive random sampling and Monte-Carlo simulation while maintaining a reasonable level of efficiency for parameter estimation. We illustrated this strategy for two drugs often included in phenotyping cocktails, midazolam (probe for CYP3A) and digoxin (P-glycoprotein), based on the data of a previous study, and were able to find a sparse and flexible design. The obtained design was evaluated by clinical trial simulations and shown to be efficient for the estimation of population and individual parameters.

Published
2016
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11. Prion dynamics with size dependency–strain phenomena

Author

Benoît Perthame, Natacha Lenuzza, Jean-Philippe Deslys, Franck Mouthon, Vincent Calvez, Marie Doumic, Unité de Mathématiques Pures et Appliquées (UMPA-ENSL), Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Lyon (ENS Lyon), Numerical Medicine (NUMED), Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Lyon (ENS Lyon)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Lyon (ENS Lyon)-Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Mathématiques Appliquées aux Systèmes - EA 4037 (MAS), Ecole Centrale Paris, Institut des Maladies Emergentes et des Thérapies Innovantes (IMETI), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay, Nonlinear Analysis for Biology and Geophysical flows (BANG), Laboratoire Jacques-Louis Lions (LJLL), Université Pierre et Marie Curie - Paris 6 (UPMC)-Université Paris Diderot - Paris 7 (UPD7)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Université Paris Diderot - Paris 7 (UPD7)-Centre National de la Recherche Scientifique (CNRS)-Inria Paris-Rocquencourt, Université Pierre et Marie Curie - Paris 6 (UPMC)-Université Paris Diderot - Paris 7 (UPD7)-Centre National de la Recherche Scientifique (CNRS), École normale supérieure de Lyon (ENS de Lyon)-Centre National de la Recherche Scientifique (CNRS), and École normale supérieure de Lyon (ENS de Lyon)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure de Lyon (ENS de Lyon)-Centre National de la Recherche Scientifique (CNRS)-Inria Grenoble - Rhône-Alpes

Subjects
prion kinetics, 0303 health sciences, Ecology, Strain (chemistry), Prions, 010102 general mathematics, Dynamics (mechanics), duality method, polymerization process, Models, Biological, [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation, 01 natural sciences, Duality method, Virology, Kinetics, strain phenomena, 03 medical and health sciences, Humans, Normal protein, Statistical physics, 0101 mathematics, Protein Structure, Quaternary, Ecology, Evolution, Behavior and Systematics, size repartition, 030304 developmental biology
Abstract

International audience; Models for the polymerization process involved in prion self-replication are well-established and studied [H. Engler, J. Pruss, and G.F. Webb, Analysis of a model for the dynamics of prions II, J. Math. Anal. Appl. 324 (2006), pp. 98-117; M.L. Greer, L. Pujo-Menjouet, and G.F. Webb, A mathematical analysis of the dynamics of prion proliferation, J. Theoret. Biol. 242 (2006), pp. 598-606; J. Pruss, L. Pujo-Menjouet, G.F. Webb, and R. Zacher, Analysis of a model for the dynamics of prions, Discrete Cont. Dyn. Sys. Ser. B 6(1) (2006), pp. 215-225] in the case where the dynamics coefficients do not depend on the size of polymers. However, several experimental studies indicate that the structure and size of the prion aggregates are determinant for their pathological effect. This motivated the analysis in Calvez et al. [Size distribution dependence of prion aggregates infectivity, Math Biosci. 217 (2009), pp. 88-99] where the authors take into account size-dependent replicative properties of prion aggregates. We first improve a result concerning the dynamics of prion aggregates when a pathological state exists (high production of the normal protein). Then we study the strain phenomena and more specifically we wonder what specific replicative properties are determinant in strain propagation. We propose to interpret it also as a dynamical property of size repartitions.

Published
2010
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12. An efficient kinetic model for assemblies of amyloid fibrils and its application to polyglutamine aggregation

Author

Annabelle Ballesta, Stéphanie Prigent, Marie Doumic, Pierre Gabriel, Natacha Lenuzza, Human Rezaei, Frédérique Charles, Léon Matar Tine, Unité de recherche Virologie et Immunologie Moléculaires (VIM (UR 0892)), Institut National de la Recherche Agronomique (INRA), Rythmes Biologiques et Cancers, Université Paris-Sud - Paris 11 (UP11)-Institut National de la Santé et de la Recherche Médicale (INSERM), Nonlinear Analysis for Biology and Geophysical flows (BANG), Laboratoire Jacques-Louis Lions (LJLL), Université Pierre et Marie Curie - Paris 6 (UPMC)-Université Paris Diderot - Paris 7 (UPD7)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Université Paris Diderot - Paris 7 (UPD7)-Centre National de la Recherche Scientifique (CNRS)-Inria Paris-Rocquencourt, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Université Pierre et Marie Curie - Paris 6 (UPMC)-Université Paris Diderot - Paris 7 (UPD7)-Centre National de la Recherche Scientifique (CNRS), Mathématiques Appliquées aux Systèmes - EA 4037 (MAS), Ecole Centrale Paris, Artificial Evolution and Computational Biology (BEAGLE), Laboratoire d'InfoRmatique en Image et Systèmes d'information (LIRIS), Université Lumière - Lyon 2 (UL2)-École Centrale de Lyon (ECL), Université de Lyon-Université de Lyon-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Université Lumière - Lyon 2 (UL2)-École Centrale de Lyon (ECL), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire de Biométrie et Biologie Evolutive - UMR 5558 (LBBE), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Centre National de la Recherche Scientifique (CNRS)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Centre National de la Recherche Scientifique (CNRS), Laboratoire de Mathématiques de Versailles (LMV), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Mathématiques Appliquées Paris 5 (MAP5 - UMR 8145), Université Paris Descartes - Paris 5 (UPD5)-Institut National des Sciences Mathématiques et de leurs Interactions (INSMI)-Centre National de la Recherche Scientifique (CNRS), French Agence Nationale de la Recherche, ANR grant [09-BLAN-0218-01], Unité de recherche Virologie et Immunologie Moléculaires (VIM), Laboratoire de Biométrie et Biologie Evolutive - UMR 5558 (LBBE), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Centre National de la Recherche Scientifique (CNRS)-Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire d'InfoRmatique en Image et Systèmes d'information (LIRIS), Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Université Lumière - Lyon 2 (UL2)-École Centrale de Lyon (ECL), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA), Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université de Versailles Saint-Quentin-en-Yvelines (UVSQ), Centre National de la Recherche Scientifique (CNRS)-Institut National des Sciences Mathématiques et de leurs Interactions (INSMI)-Université Paris Descartes - Paris 5 (UPD5), Unité de recherche Virologie et Immunologie Moléculaires ( VIM ), Institut National de la Recherche Agronomique ( INRA ), Université Paris-Sud - Paris 11 ( UP11 ) -Institut National de la Santé et de la Recherche Médicale ( INSERM ), Nonlinear Analysis for Biology and Geophysical flows ( BANG ), Laboratoire Jacques-Louis Lions ( LJLL ), Université Pierre et Marie Curie - Paris 6 ( UPMC ) -Université Paris Diderot - Paris 7 ( UPD7 ) -Centre National de la Recherche Scientifique ( CNRS ) -Université Pierre et Marie Curie - Paris 6 ( UPMC ) -Université Paris Diderot - Paris 7 ( UPD7 ) -Centre National de la Recherche Scientifique ( CNRS ) -Inria Paris-Rocquencourt, Institut National de Recherche en Informatique et en Automatique ( Inria ) -Institut National de Recherche en Informatique et en Automatique ( Inria ), Université Pierre et Marie Curie - Paris 6 ( UPMC ) -Université Paris Diderot - Paris 7 ( UPD7 ) -Centre National de la Recherche Scientifique ( CNRS ), Mathématiques Appliquées aux Systèmes - EA 4037 ( MAS ), Artificial Evolution and Computational Biology ( BEAGLE ), Laboratoire d'InfoRmatique en Image et Systèmes d'information ( LIRIS ), Université Lumière - Lyon 2 ( UL2 ) -École Centrale de Lyon ( ECL ), Université de Lyon-Université de Lyon-Université Claude Bernard Lyon 1 ( UCBL ), Université de Lyon-Centre National de la Recherche Scientifique ( CNRS ) -Institut National des Sciences Appliquées de Lyon ( INSA Lyon ), Université de Lyon-Institut National des Sciences Appliquées ( INSA ) -Institut National des Sciences Appliquées ( INSA ) -Université Lumière - Lyon 2 ( UL2 ) -École Centrale de Lyon ( ECL ), Université de Lyon-Institut National des Sciences Appliquées ( INSA ) -Institut National des Sciences Appliquées ( INSA ) -Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique ( Inria ) -Institut National de Recherche en Informatique et en Automatique ( Inria ) -Laboratoire de Biométrie et Biologie Evolutive ( LBBE ), Université Claude Bernard Lyon 1 ( UCBL ), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique ( Inria ) -Centre National de la Recherche Scientifique ( CNRS ) -Centre National de la Recherche Scientifique ( CNRS ) -Cardiovasculaire, métabolisme, diabétologie et nutrition ( CarMeN ), Institut National de la Santé et de la Recherche Médicale ( INSERM ) -Hospices Civils de Lyon ( HCL ) -Institut National des Sciences Appliquées de Lyon ( INSA Lyon ), Université de Lyon-Institut National des Sciences Appliquées ( INSA ) -Université de Lyon-Institut National des Sciences Appliquées ( INSA ) -Université Claude Bernard Lyon 1 ( UCBL ), Université de Lyon-Institut National de la Recherche Agronomique ( INRA ) -Institut National de la Santé et de la Recherche Médicale ( INSERM ) -Hospices Civils de Lyon ( HCL ) -Université Claude Bernard Lyon 1 ( UCBL ), Université de Lyon-Institut National de la Recherche Agronomique ( INRA ), Laboratoire de Mathématiques de Versailles ( LMV ), Université Paris-Saclay-Centre National de la Recherche Scientifique ( CNRS ) -Université de Versailles Saint-Quentin-en-Yvelines ( UVSQ ), Mathématiques Appliquées à Paris 5 ( MAP5 - UMR 8145 ), Université Paris Descartes - Paris 5 ( UPD5 ) -Institut National des Sciences Mathématiques et de leurs Interactions-Centre National de la Recherche Scientifique ( CNRS ), Doumic, Marie, Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Université de Lyon-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-École Centrale de Lyon (ECL), Université de Lyon-Université Lumière - Lyon 2 (UL2)-Institut National des Sciences Appliquées de Lyon (INSA Lyon), Université de Lyon-Institut National des Sciences Appliquées (INSA)-Institut National des Sciences Appliquées (INSA)-Centre National de la Recherche Scientifique (CNRS)-École Centrale de Lyon (ECL), and Université de Lyon-Université Lumière - Lyon 2 (UL2)

Subjects
Macromolecular Assemblies, Protein polymerization, lcsh:Medicine, Protein aggregation, Bioinformatics, 01 natural sciences, Polymerization, Amyloid disease, [ MATH.MATH-AP ] Mathematics [math]/Analysis of PDEs [math.AP], [MATH.MATH-AP] Mathematics [math]/Analysis of PDEs [math.AP], lcsh:Science, 0303 health sciences, Numerical Analysis, Quantitative Biology::Biomolecules, Multidisciplinary, Partial differential equation, Applied Mathematics, Chemical Reactions, Complex Systems, Neurodegenerative Diseases, Huntington's disease, 010101 applied mathematics, [SDV.BBM.BP]Life Sciences [q-bio]/Biochemistry, Molecular Biology/Biophysics, Chemistry, Neurology, Ordinary differential equation, Medicine, Biological system, Algorithms, Research Article, Protein Binding, Asymptotic analysis, Amyloid, [ SDV.BBM.BP ] Life Sciences [q-bio]/Biochemistry, Molecular Biology/Biophysics, Differential equation, Biophysics, amyloid diseases, [SDV.BBM.BP] Life Sciences [q-bio]/Biochemistry, Molecular Biology/Biophysics, 03 medical and health sciences, [MATH.MATH-AP]Mathematics [math]/Analysis of PDEs [math.AP], Computer Simulation, 0101 mathematics, Biology, protein polymerization, 030304 developmental biology, lcsh:R, Ode, Models, Theoretical, Kinetics, asymptotic analysis, Nonlinear Dynamics, Computer Science, lcsh:Q, Protein Multimerization, Peptides, Mathematics
Abstract

International audience; Protein polymerization consists in the aggregation of single monomers into polymers that may fragment. Fibrils assembly is a key process in amyloid diseases. Up to now, protein aggregation was commonly mathematically simulated by a polymer size-structured ordinary differential equations (ODE) system, which is infinite by definition and therefore leads to high computational costs. Moreover, this Ordinary Differential Equation-based modeling approach implies biological assumptions that may be difficult to justify in the general case. For example, whereas several ordinary differential equation models use the assumption that polymerization would occur at a constant rate independently of polymer size, it cannot be applied to certain protein aggregation mechanisms. Here, we propose a novel and efficient analytical method, capable of modelling and simulating amyloid aggregation processes. This alternative approach consists of an integro-Partial Differential Equation (PDE) model of coalescence-fragmentation type that was mathematically derived from the infinite differential system by asymptotic analysis. To illustrate the efficiency of our approach, we applied it to aggregation experiments on polyglutamine polymers that are involved in Huntington's disease. Our model demonstrates the existence of a monomeric structural intermediate [Formula: see text] acting as a nucleus and deriving from a non polymerizing monomer ([Formula: see text]). Furthermore, we compared our model to previously published works carried out in different contexts and proved its accuracy to describe other amyloid aggregation processes.

Published
2012
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13. New inhibitors of prion replication that target the amyloid precursor

Author

Eric Jacquet, Marlène Reboul, Naima Nhiri, Qian Wang, Jean-Philippe Deslys, Mathieu Charvériat, Françoise Guéritte, Jean-Yves Lallemand, Natacha Lenuzza, Franck Mouthon, Christèle Picoli, A. Montagnac, Institut de Chimie des Substances Naturelles (ICSN), and Centre National de la Recherche Scientifique (CNRS)-Institut de Chimie du CNRS (INC)

Subjects
Amyloid, Prions, animal diseases, [SDV.BC]Life Sciences [q-bio]/Cellular Biology, Protein aggregation, Biology, Cell Line, Small Molecule Libraries, Amyloid beta-Protein Precursor, Mice, 03 medical and health sciences, 0302 clinical medicine, Protein stability, Virology, Animals, Prion protein, 030304 developmental biology, 0303 health sciences, In vitro, 3. Good health, Fungal prion, nervous system diseases, Biochemistry, Direct targeting, Cell culture, Biological Assay, 030217 neurology & neurosurgery
Abstract

At present, there is no effective therapy for any of the neurodegenerative amyloidoses, despite renewed efforts to identify compounds active against the various implicated pathogenetic molecules. We have screened a library of 2960 natural and synthetic compounds in two cell lines chronically infected with mouse prions, and have identified eight new inhibitors of prion replication in vitro. They belong to two distinct chemical families that have not previously been recognised as effective in the field of transmissible spongiform encephalopathies: seven are 3-aminosteroids and one is a derivative of erythromycin A with an oxime functionality. Our results suggest that these aminosteroids inhibit prion replication by triggering a common target, possibly implicated in the regulatory pathways of cellular prion protein metabolism. Furthermore, using a quantitative approach for the study of protein stability, it was shown that the erythromycin A derivative altered prion protein stability by direct interaction. Such direct targeting of this amyloid precursor might provide new clues for the understanding of prion diseases and, more importantly, help to define new molecules that are active against prion diseases.

Published
2009
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14. Size distribution dependence of prion aggregates infectivity

Author

Natacha Lenuzza, Dietmar Oelz, Vincent Calvez, Franck Mouthon, Jean-Philippe Deslys, Pascal Laurent, Benoît Perthame, Département de Mathématiques et Applications - ENS Paris (DMA), École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS), Numerical Medicine (NUMED), Unité de Mathématiques Pures et Appliquées (UMPA-ENSL), École normale supérieure de Lyon (ENS de Lyon)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure de Lyon (ENS de Lyon)-Centre National de la Recherche Scientifique (CNRS)-Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria), Mathématiques Appliquées aux Systèmes - EA 4037 (MAS), Ecole Centrale Paris, Institut des Maladies Emergentes et des Thérapies Innovantes (IMETI), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris-Saclay, Institute for Analysis and Scientific Computing [Wien], Vienna University of Technology (TU Wien), Laboratoire Jacques-Louis Lions (LJLL), Université Pierre et Marie Curie - Paris 6 (UPMC)-Université Paris Diderot - Paris 7 (UPD7)-Centre National de la Recherche Scientifique (CNRS), Nonlinear Analysis for Biology and Geophysical flows (BANG), Université Pierre et Marie Curie - Paris 6 (UPMC)-Université Paris Diderot - Paris 7 (UPD7)-Centre National de la Recherche Scientifique (CNRS)-Université Pierre et Marie Curie - Paris 6 (UPMC)-Université Paris Diderot - Paris 7 (UPD7)-Centre National de la Recherche Scientifique (CNRS)-Inria Paris-Rocquencourt, École normale supérieure - Paris (ENS Paris), Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Lyon (ENS Lyon)-Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Lyon (ENS Lyon)-Inria Grenoble - Rhône-Alpes, Centre National de la Recherche Scientifique (CNRS)-École normale supérieure - Paris (ENS Paris), and Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)

Subjects
Statistics and Probability, prion kinetics, Prions, Protein Conformation, Prion strain, polymerization process, 01 natural sciences, Duality method, Models, Biological, General Biochemistry, Genetics and Molecular Biology, Prion Diseases, 03 medical and health sciences, Animals, Humans, Computer Simulation, Statistical physics, 0101 mathematics, 030304 developmental biology, Infectivity, 0303 health sciences, General Immunology and Microbiology, Mathematical model, Applied Mathematics, 010102 general mathematics, Size dependent, duality method, General Medicine, Virology, [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation, System of differential equations, Polymerization, Population model, Modeling and Simulation, General Agricultural and Biological Sciences, size repartition
Abstract

International audience; We consider a model for the polymerization (fragmentation) process involved in infectious prion self-replication and study both its dynamics and non-zero steady state. We address several issues. Firstly, we extend a previous study of the nucleated polymerization model [M.L. Greer, L. Pujo-Menjouet, G.F. Webb, A mathematical analysis of the dynamics of prion proliferation, J. Theoret. Biol. 242 (2006) 598; H. Engler, J. Pruss, G.F. Webb, Analysis of a model for the dynamics of prions II, J. Math. Anal. Appl. 324 (2006) 98] to take into account size dependent replicative properties of prion aggregates. This is achieved by a choice of coefficients in the model that are not constant. Secondly, we show stability results for this steady state for general coefficients where reduction to a system of differential equations is not possible. We use a duality method based on recent ideas developed for population models. These results confirm the potential influence of the amyloid precursor production rate in promoting amyloidogenic diseases. Finally, we investigate how the converting factor may depend upon the aggregate size. Besides the confirmation that size-independent parameters are unlikely to occur, the present study suggests that the PrPsc aggregate size repartition is amongst the most relevant experimental data in order to investigate this dependence. In terms of prion strain, our results indicate that the PrPsc aggregate repartition could be a constraint during the adaptation mechanism of the species barrier overcoming, that opens experimental perspectives for prion amyloid polymerization and prion strain investigation.

Published
2009
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