Conception d'un web service pour la fouille de données de génomique : application à la caractérisation de la myogenèse et de l'adipogenèse

The quality of carcasses and meats depends on the balance between muscle and adipose tissue (AT) masses that determine carcass weight and performance (muscle and fat composition), but also the sensory quality of the meat (tenderness, juiciness and flavor). Understanding how to control the ratio of muscle mass relative to AT mass represents a major challenge for beef producers. The balance between these masses depends on the number and volume of muscle and AT cells. These cellular events are taking place at the early steps of fetal period in cattle, as the total number of muscle cells is fixed at 180 days post-conception (dpc) in the fetus. The analysis of the evolution of these two proteome tissues during fetal life produced original but insufficient data. In addition, it is not always easy to extract or generate relevant biological information from genomic experiments. This is particularly true in ruminant species because they are not annotated in databases and few bioinformatic resources are dedicated to them. In this context, our objective was to design an “all in one” web service to analyze genomic data in cattle in order to improve knowledge of the mechanisms involved in fetal muscle and AT growth. Thus, we have organized our thesis in two axes. We developed a genomic data analysis tool, dedicated to ruminant species (cattle, sheep and goat) and named ProteINSIDE (www.proteinside.org). In a single query, this tool synthesizes the biological information stored in public databases or provided by functional annotations from gene ontology. It also predicts proteins that are secreted (tissue secretome) and which are involved in signaling between cells or tissues. It links proteins according to their molecular interactions to identify and visualize those that contribute to the same biological processes and those that are central to a biological process. ProteINSIDE was tested with data sets of 1000 proteins by species and has been successfully compared with DAVID, BioMyn, and AgBase (designed for information retrieval and annotation), as well as PrediSi and Phobius (that predict proteins secreted). We applied ProteINSIDE to the proteome analysis of muscle and AT. A first analysis of data on the ontogenesis of the tissue revealed links between proteins of both fetal tissues and proteins involved in autophagy processes. In a second study, we constructed and described the bovine proteomes of both tissues at 140 dpc. We identified 514 muscle protein and 752 AT proteins, including 346 commons proteins. As an example, these proteins are involved in the negative regulation of apoptosis, in autophagy processes, in the regulation of cell proliferation, and in the Wnt signaling pathway. We identified 47 and 93 potentially secreted proteins by muscle and TA, including 24 commons proteins. The integration of knowledges about the secreted proteins with those available for the “surfaceome” suggested proteins which could participate in the cross-talk between muscle and AT. Thus, we produced a web server to mine genomic data from bovine, sheep, and goat species, but also from human, rat and mice species. This type of server should be particularly useful to the scientific community. Its implementation has led to the production of new knowledge and working hypotheses for the understanding of the mechanisms which regulate fetal growth of muscle and AT.La qualité des carcasses et des viandes bovines dépend de l’équilibre entre les masses musculaires et adipeuses qui conditionnent le poids de carcasse et son rendement (composition en muscle et en gras), mais aussi la qualité sensorielle de la viande (tendreté, jutosité et flaveur). Comprendre comment contrôler le rapport des masses de muscle relativement à celles des tissus adipeux (TA) représente donc un enjeu majeur pour les filières de viande bovine. Ce rapport dépend du nombre et du volume des cellules musculaires et adipeuses. Ces propriétés sont sous le contrôle d’événements cellulaires se mettant en place précocement chez le bovin puisque le nombre de cellules musculaires est fixé dès l’âge 180 jours post-conception (jpc) chez le fœtus. Des analyses de l’évolution des protéomes de ces deux tissus, au cours de la vie fœtale ont produit des données originales mais insuffisantes. En outre, il n’est pas toujours aisé d’extraire ou de générer une information biologique pertinente à partir d’expérimentations de génomique. Ceci est particulièrement vrai chez les ruminants, car ils sont peu annotés dans les bases de données et peu de ressources bioinformatiques leur sont dédiées. Dans ce contexte, notre objectif était de concevoir un serveur web « tout en un » permettant une fouille des données de génomique chez le bovin afin d’améliorer les connaissances sur les mécanismes associés à la croissance par hyperplasie et par hypertrophie des tissus musculaire et adipeux. Aussi, nous avons organisé notre travail de thèse en deux axes.Un outil d’analyse de données de génomique, dédié aux ruminants (bovin, ovin et caprin) nommé ProteINSIDE (www.proteinside.org) a été développé. En une seule requête, il synthétise l'information biologique stockée dans les bases de données publiques ou fournie par les annotations fonctionnelles issues de l’ontologie des gènes. Il prédit aussi les protéines qui sont sécrétées (sécrétome des tissus) et qui interviennent dans la signalisation entre les cellules ou tissus. Il lie les protéines selon leurs interactions moléculaires afin d’identifier et de visualiser celles qui contribuent à un même processus biologique et celles qui sont centrales à un processus biologique. ProteINSIDE a été testé avec des jeux de données de 1000 protéines par espèce et a été comparé avec succès à DAVID, BioMyn et AgBase, conçus pour la recherche d'information et l'annotation, ainsi qu'à PrediSi et Phobius qui prédisent les protéines sécrétées. ProteINSIDE a été appliqué à l’analyse des protéomes des tissus musculaires et adipeux. Une première analyse des données relatives à l’ontogenèse des tissus, a révélé des liens entre des protéines présentes dans les deux tissus fœtaux et des protéines impliquées dans les processus d’autophagie. Dans une seconde étude, nous avons décrit les protéomes des deux tissus à 140 jpc. Nous avons identifié 514 protéines musculaires et 752 protéines adipeuses, dont 346 communes. Ces protéines interviennent par exemple dans la régulation négative de l’apoptose, dans les processus d’autophagie, dans la régulation de la prolifération cellulaire et dans la voie de signalisation Wnt. Nous avons identifié 47 et 93 protéines potentiellement sécrétées par le muscle et le TA, dont 24 communes. L’intégration des connaissances sur les protéines sécrétées avec celles disponibles pour le « surfaceome » a suggéré des protéines qui participeraient au dialogue muscle-TA. Nous avons donc produit un serveur web pour la fouille de données de génomique non seulement chez le bovin, l’ovin, le caprin, mais aussi chez l’homme, le rat et la souris. Ce type de serveur devrait être particulièrement utile à la communauté scientifique. Son application a conduit à la production de connaissances nouvelles et d’hypothèses de travail pour la compréhension des mécanismes de régulation de la croissance fœtale du muscle squelettique et du tissu adipeux

Computational Studies of Glycan Conformations in Glycoproteins

N-glycans refer to oligosaccharide chains covalently attached to the side chain of asparagine (Asn) residues, and the majority of proteins synthesized in the endoplasmic reticulum (ER) are N-glycosylated. N-glycans can modulate the structural properties of proteins due to their close proximity to their parent proteins and their interactions between the glycan and the protein surface residues. In addition, N-glycans provide specific regions of recognition for cellular and molecular recognition. Despite their biological importance, the structural understanding of glycans and the impact of glycosylation to glycan or protein structure are lacking. I have explored the conformational freedom of glycans and their conformational preferences in different environments using structural databases and computer simulations. First, I have developed an algorithm to reliably annotate a given atomic structure of glycans. This algorithm is important because many glycan molecules in the crystal structure database are misannotated or contain errors. Using the algorithm, a database of glycans found in the PDB is constructed and available to the public. Second, the impact of glycosylation on the glycan conformation has been examined. Contrary to the common belief that the glycan conformations are independent to the protein structure, it appears that the protein structure can significantly affect the glycan structure upon glycosylation. This observation is significant because it may provide insight into protein-glycan interaction and opens up the possibility of a template-based glycan modeling approach. Third, the differences in conformational preference between glycans in solution and in glycoproteins has been examined. Using molecular dynamics (MD) simulations, the conformational preference of N-glycan pentassacharide in solution is exhaustively studied. Surprisingly, the conformational distribution is dominated by a single major conformational state and several minor conformational states. The dominant conformational state adopts a more extended conformation, thus it appears that entropy plays an important role in determining the conformational state. On the other hand, in glycoproteins, glycans can interact with surrounding protein side chains and, as a result, several conformational states are more equally populated. Based on these observations, a protocol is proposed for modeling the glycan portion of a known protein structure. It is typically more managable to acquire an atomic resolution structure or aglycoprotein (glycoprotein without glycan). In addition, the glycoform and the glycosylation site can be identified independently by mass spectrometry or NMR. The proposed modeling protocol assumes the glycosylation site, glycoform, and aglycoprotein structure are already known, and builds glycan structure models on top of the known aglycoprotein structure. The performance of the modeling protocol is greatly improved by using appropriate template structures. This protocol can be used to generate the initial model for MD simulations or refinement of low resolution models from experiments (small angle X-ray scattering and electron microscopy)

Recent Advances in OMICs Technologies and Application for Ensuring Meat Quality, Safety and Authenticity

Consumers and stakeholders are increasingly demanding that the meat industry guarantees high-quality meat products with stable and acceptable sensory and safety properties. To do this, it is necessary to understand the mechanisms that underlie the conversion of muscle into meat, as well as the impact of pre- and post-harvest procedures on the final quality and safety of meat products. Over the last two decades, sophisticated OMICs technologies—genomics, transcriptomics, proteomics, peptidomics, metabolomics and lipidomics, also known as foodomics—have been powerful approaches that extended the scope of traditional methods and have established impressive possibilities of addressing meat quality issues. Foodomics were further used to elucidate the biological basis/mechanisms of phenotypic variation in the technological and sensory quality traits of meat from different species. Overall, these techniques aimed to comprehensively study the dynamic link(s) between the genome and the quality traits of the meat that we eat compared to traditional methods, hence improving both the accuracy and sensitivity thanks to the large quantities of data that can be generated. This Special Issue focused on the cutting-edge research applications of OMICs tools to characterize or manage the quality of muscle foods. The research papers applied transcriptomics, targeted and untargeted proteomics, metabolomics, and genomics, among others, to evaluate meat quality, determine the molecular profiles of meat and meat products, discover and/or evaluate biomarkers of meat quality traits, and to characterize the safety, adulteration, and authenticity of meat and meat products

From a Molecule to a Drug: Chemical Features Enhancing Pharmacological Potential

This book collects contributions published in the Special Issue “From a Molecule to a Drug: Chemical Features Enhancing Pharmacological Potential” and dealing with successful stories of drug improvement or design using classic protocols, quantum mechanical mechanistic investigation, or hybrid approaches such as QM/MM or QM/ML (machine learning). In the last two decades, computer-aided modeling has strongly supported scientists’ intuition to design functional molecules. High-throughput screening protocols, mainly based on classical mechanics’ atomistic potentials, are largely employed in biology and medicinal chemistry studies with the aim of simulating drug-likeness and bioactivity in terms of efficient binding to the target receptors. The advantages of this approach are quick outcomes, the possibility of repurposing commercially available drugs, consolidated protocols, and the availability of large databases. On the other hand, these studies do not intrinsically provide reactivity information, which requires quantum mechanical methodologies that are only applicable to significantly smaller and simplified systems at present. These latter studies focus on the drug itself, considering the chemical properties related to its structural features and motifs. Overall, such simulations provide necessary insights for a better understanding of the chemistry principles that rule the diseases at the molecular level, as well as possible mechanisms for restoring the physiological equilibrium

Bioactivity of Medicinal Plants and Extracts

Medicinal plants and natural products have played a central role in therapeutics, being considered the origin of Pharmacy and Pharmacology. Plants are still a source in nature to obtain and isolate molecules with pharmacological applications (drug discovery), but can also be used as herbal medicinal products in traditional or complementary medicine.In addition, the WHO has launched a Traditional Medicine Strategy (2014–2023), including herbal medicines as medicinal therapies, with the aim to ensure the quality, safety, proper use, and effectiveness of traditional medicines, among other objectives.This is a reprint of articles from the Special Issue on “Bioactivity of Medicinal Plants and Extracts” published online in the open access journal Biology. This reprint includes a collection of original research and review articles on new advances in the development and application of bioactive compounds and extracts from plant matrices