Computing biological functions using BioΨ, a formal description of biological processes based on elementary bricks of actions

Motivation: In the available databases, biological processes are described from molecular and cellular points of view, but these descriptions are represented with text annotations that make it difficult to handle them for computation. Consequently, there is an obvious need for formal descriptions of biological processes

Metabolic Investigation of the Mycoplasmas from the Swine Respiratory Tract

International audienceBackgroundThe respiratory tract of swine is colonized by several bacteria among which are three Mycoplasma species: Mycoplasma flocculare, Mycoplasma hyopneumoniae and Mycoplasma hyorhinis. While colonization by M. flocculare is virtually asymptomatic, M. hyopneumoniae is the causative agent of enzootic pneumonia and M. hyorhinis is present in cases of pneumonia, polyserositis and arthritis. The genomic resemblance among these three Mycoplasma species combined with their different levels of pathogenicity is an indication that they have unknown mechanisms of virulence and differential expression, as for most mycoplasmas.MethodsIn this work, we performed whole-genome metabolic network reconstructions for these three mycoplasmas. Cultivation tests and metabolomic experiments through nuclear magnetic resonance spectroscopy (NMR) were also performed to acquire experimental data and further refine the models reconstructed in silico.ResultsEven though the refined models have similar metabolic capabilities, interesting differences include a wider range of carbohydrate uptake in M. hyorhinis, which in turn may also explain why this species is a widely contaminant in cell cultures. In addition, the myo-inositol catabolism is exclusive to M. hyopneumoniae and may be an important trait for virulence. However, the most important difference seems to be related to glycerol conversion to dihydroxyacetone-phosphate, which produces toxic hydrogen peroxide. This activity, missing only in M. flocculare, may be directly involved in cytotoxicity, as already described for two lung pathogenic mycoplasmas, namely Mycoplasma pneumoniae in human and Mycoplasma mycoides subsp. mycoides in ruminants. Metabolomic data suggest that even though these mycoplasmas are extremely similar in terms of genome and metabolism, distinct products and reaction rates may be the result of differential expression throughout the species.ConclusionsWe were able to infer from the reconstructed networks that the lack of pathogenicity of M. flocculare if compared to the highly pathogenic M. hyopneumoniae may be related to its incapacity to produce cytotoxic hydrogen peroxide. Moreover, the ability of M. hyorhinis to grow in diverse sites and even in different hosts may be a reflection of its enhanced and wider carbohydrate uptake. Altogether, the metabolic differences highlighted in silico and in vitro provide important insights to the different levels of pathogenicity observed in each of the studied species

Identification de marqueurs systémiques du cancer à partir de l'investigation métabolomique par RMN de fluides biologiques humains

La métabolomique propose une approche basée sur l’étude d’une réponse métabolique globale et dynamique d’un organisme à des stimuli biologiques ou à des mutations génétiques et ainsi constitue un outil de recherche translationnel à fort potentiel en oncologie. Nous avons appliqué l’approche métabonomique par RMN à haut champ à l’analyse d’échantillons sanguins issus d’études cliniques coordonnées par le Centre Léon Bérard et pour la cohorte prospective E3N (Etude Epidémiologique auprès de femmes de la MGEN) dans le but d’identifier de marqueurs systémiques du cancer à partir de fluides biologiques humains. Tout d’abord, l’analyse statistique des profils métaboliques de sérums de patientes atteintes d’un cancer du sein a permis de mettre en évidence une signature métabolique discriminant les patients ayant un cancer localisé des patientes métastatiques et de révéler des biomarqueurs associés à la sévérité de ce cancer. D’autre part, cette approche permet des investigations sur les effets de la chimiothérapie. Ainsi, lors de l’étude de sérums de patients atteints d’un cancer du rein métastatique traités par une chimiothérapie expérimentale, une signature métabolique caractéristique de la modification plus rapide du métabolisme de l’hôte a été mise en évidence pour ce traitement en comparaison à deux thérapies conventionnelles. Enfin, l’analyse de plasmas sanguins issus de la cohorte E3N s’intéresse à l’identification de biomarqueurs associés à la survenue du cancer du sein et de son étiologie. Après identification et quantification des sources de variations systématiques impactant les profils métaboliques obtenus, une analyse stratifiée de la cohorte « cas prospectifs »-contrôles est présentée dans cette thèse.Metabolomics offers an approach based on the study of a comprehensive and dynamic metabolic response of an organism to biological stimuli or genetic mutations and thus constitutes a tool for translational research with a strong potential in oncology. We applied the metabonomic approach by high field NMR for the analysis of blood samples from clinical studies coordinated by the Centre Léon Bérard and for the prospective E3N cohort ( Etude Epidémiologique auprès de femmes de la MGEN ) in order to identify systemic cancer markers from human biological fluids . First, the statistical analysis of metabolic serum profiles from patients with breast cancer has highlighted a metabolic signature discriminating patients with localized cancer and metastatic patients and reveal biomarkers associated with severity of this cancer. Furthermore , this approach allows investigations on the effects of chemotherapy. Thus, during the study of sera from patients with metastatic renal cell carcinoma treated with experimental chemotherapy, a characteristic metabolic signature of faster modification of the host metabolism has been demonstrated for this treatment in comparison to two standard therapies. Finally, analysis of blood plasma from the E3N cohort interests the identification of biomarkers associated with the development of breast cancer and its etiology . After identification and quantification of sources of systematic variations affecting the metabolic profiles obtained, a stratified analysis of the "prospective case "- controls cohort is presented in this thesis

Evolution of urine metabolomic profiles in newborns

International audienceMetabolomics provides untargeted identification of all detectable low molecular-weight molecules by profiling without a priori the metabolic signatures of biological samples in connection to pathophysiological events. The goal of metabolomic studies is to identify relevant biomarkers or composite metabolic patterns associated with particular disease status. Urine is particularly suited for metabolomic analysis in newborns and children, due to its simple and non-invasive method of collection. Its biochemical composition is correlated to a number of factors such as genotype, gender, disease, nutritional state and age. The number of metabolomic studies in pediatrics is rising, but little is known concerning age-related changes in urine metabolic profiles and newborn metabolic maturation over time. The aim of this study was to investigate changes in urine metabolic profiles during the first four months of life using 1H-nuclear magneticresonance (NMR) spectroscopy combined with multivariate statistical analysis. Urine samples were collected from 91 newborns under 4 months old without nephrologic or urologic disease. The mean age was 68 days ± 24. The1H-NMR spectra were analyzed using Principal Component Analysis (PCA) and the effect of age on the urinary metabolite profile was observed even from this unsupervised analysis. Further analysis using Orthogonal Partial Least Squares (OPLS) methodology was performed and a model with good predictive power was calculated, allowing the identification of an age-related metabolic profile. We observed the most significant evolution between 2 and 3 months of life. Our results allow a deeper understanding of newborn metabolic maturation. They contribute to identifying potential confounding factors in the application of metabolomics in newborns

Evolution of urine metabolomic profiles in newborns

International audienceMetabolomics provides untargeted identification of all detectable low molecular-weight molecules by profiling without a priori the metabolic signatures of biological samples in connection to pathophysiological events. The goal of metabolomic studies is to identify relevant biomarkers or composite metabolic patterns associated with particular disease status. Urine is particularly suited for metabolomic analysis in newborns and children, due to its simple and non-invasive method of collection. Its biochemical composition is correlated to a number of factors such as genotype, gender, disease, nutritional state and age. The number of metabolomic studies in pediatrics is rising, but little is known concerning age-related changes in urine metabolic profiles and newborn metabolic maturation over time. The aim of this study was to investigate changes in urine metabolic profiles during the first four months of life using 1H-nuclear magneticresonance (NMR) spectroscopy combined with multivariate statistical analysis. Urine samples were collected from 91 newborns under 4 months old without nephrologic or urologic disease. The mean age was 68 days ± 24. The1H-NMR spectra were analyzed using Principal Component Analysis (PCA) and the effect of age on the urinary metabolite profile was observed even from this unsupervised analysis. Further analysis using Orthogonal Partial Least Squares (OPLS) methodology was performed and a model with good predictive power was calculated, allowing the identification of an age-related metabolic profile. We observed the most significant evolution between 2 and 3 months of life. Our results allow a deeper understanding of newborn metabolic maturation. They contribute to identifying potential confounding factors in the application of metabolomics in newborns

Batch profiling calibration for robust NMR metabonomic data analysis.

International audienceMetabonomic studies involve the analysis of large numbers of samples to identify significant changes in the metabolic fingerprints of biological systems, possibly with sufficient statistical power for analysis. While procedures related to sample preparation and spectral data acquisition generally include the use of independent sample batches, these might be sources of systematic variation whose effects should be removed to focus on phenotyping the relevant biological variability. In this work, we describe a grouped-batch profile (GBP) calibration strategy to adjust nuclear magnetic resonance (NMR) metabolomic data-sets for batch effects either introduced during NMR experiments or samples work-up. We show how this method can be applied to data calibration in the context of a large-scale NMR epidemiological study where quality control samples are available. We also illustrate the efficiency of a batch profile correction for NMR metabonomic investigation of cell extracts, where GBP can significantly improve the predictive power of multivariate statistical models for discriminant analysis of the cell infection status. The method is applicable to a broad range of NMR metabolomic/metabonomic cohort studies

A Systematic Evaluation of Blood Serum and Plasma Pre-Analytics for Metabolomics Cohort Studies

International audienceThe recent thriving development of biobanks and associated high-throughput phenotyping studies requires the elaboration of large-scale approaches for monitoring biological sample quality and compliance with standard protocols. We present a metabolomic investigation of human blood samples that delineates pitfalls and guidelines for the collection, storage and handling procedures for serum and plasma. A series of eight pre-processing technical parameters is systematically investigated along variable ranges commonly encountered across clinical studies. While metabolic fingerprints, as assessed by nuclear magnetic resonance, are not significantly affected by altered centrifugation parameters or delays between sample pre-processing (blood centrifugation) and storage, our metabolomic investigation highlights that both the delay and storage temperature between blood draw and centrifugation are the primary parameters impacting serum and plasma metabolic profiles. Storing the blood drawn at 4 degrees C is shown to be a reliable routine to confine variability associated with idle time prior to sample pre-processing. Based on their fine sensitivity to pre-analytical parameters and protocol variations, metabolic fingerprints could be exploited as valuable ways to determine compliance with standard procedures and quality assessment of blood samples within large multi-omic clinical and translational cohort studies

Evolution of Newborns’ Urinary Metabolomic Profiles According to Age and Growth

International audienc