Showing papers by "Sylvie Ricard-Blum published in 2020"

Towards a unified open access dataset of molecular interactions

Abstract: The International Molecular Exchange (IMEx) Consortium provides scientists with a single body of experimentally verified protein interactions curated in rich contextual detail to an internationally agreed standard. In this update to the work of the IMEx Consortium, we discuss how this initiative has been working in practice, how it has ensured database sustainability, and how it is meeting emerging annotation challenges through the introduction of new interactor types and data formats. Additionally, we provide examples of how IMEx data are being used by biomedical researchers and integrated in other bioinformatic tools and resources. The IMEx consortium provides one of the largest resources of curated, experimentally verified molecular interaction data. Here, the authors review how IMEx evolved into a fundamental resource for life scientists and describe how IMEx data can support biomedical research.

The IMEx coronavirus interactome: an evolving map of Coronaviridae-host molecular interactions.

Abstract: The current coronavirus disease of 2019 (COVID-19) pandemic, caused by the severe acute respiratory syndrome coronavirus (SARS-CoV)-2, has spurred a wave of research of nearly unprecedented scale. Among the different strategies that are being used to understand the disease and develop effective treatments, the study of physical molecular interactions can provide fine-grained resolution of the mechanisms behind the virus biology and the human organism response. We present a curated dataset of physical molecular interactions focused on proteins from SARS-CoV-2, SARS-CoV-1 and other members of the Coronaviridae family that has been manually extracted by International Molecular Exchange (IMEx) Consortium curators. Currently, the dataset comprises over 4400 binarized interactions extracted from 151 publications. The dataset can be accessed in the standard formats recommended by the Proteomics Standards Initiative (HUPO-PSI) at the IntAct database website (https://www.ebi.ac.uk/intact) and will be continuously updated as research on COVID-19 progresses.

The Interactome of Cancer-Related Lysyl Oxidase and Lysyl Oxidase-Like Proteins.

Abstract: The members of the lysyl oxidase (LOX) family are amine oxidases, which initiate the covalent cross-linking of the extracellular matrix (ECM), regulate ECM stiffness, and contribute to cancer progression. The aim of this study was to build the first draft of the interactome of the five members of the LOX family in order to determine its molecular functions, the biological and signaling pathways mediating these functions, the biological processes it is involved in, and if and how it is rewired in cancer. In vitro binding assays, based on surface plasmon resonance and bio-layer interferometry, combined with queries of interaction databases and interaction datasets, were used to retrieve interaction data. The interactome was then analyzed using computational tools. We identified 31 new interactions and 14 new partners of LOXL2, including the α5β1 integrin, and built an interactome comprising 320 proteins, 5 glycosaminoglycans, and 399 interactions. This network participates in ECM organization, degradation and cross-linking, cell-ECM interactions mediated by non-integrin and integrin receptors, protein folding and chaperone activity, organ and blood vessel development, cellular response to stress, and signal transduction. We showed that this network is rewired in colorectal carcinoma, leading to a switch from ECM organization to protein folding and chaperone activity.

The IMEx Coronavirus interactome: an evolving map of Coronaviridae-Host molecular interactions

Abstract: The current Coronavirus Disease 2019 (COVID-19) pandemic, caused by the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), has spurred a wave of research of nearly unprecedented scale. Among the different strategies that are being used to understand the disease and develop effective treatments, the study of physical molecular interactions enables studying fine-grained resolution of the mechanisms behind the virus biology and the human organism response. Here we present a curated dataset of physical molecular interactions, manually extracted by IMEx Consortium curators focused on proteins from SARS-CoV-2, SARS-CoV-1 and other members of the Coronaviridae family. Currently, the dataset comprises over 2,200 binarized interactions extracted from 86 publications. The dataset can be accessed in the standard formats recommended by the Proteomics Standards Initiative (HUPO-PSI) at the IntAct database website ( www.ebi.ac.uk/intact ), and will be continuously updated as research on COVID-19 progresses.

Sialic acids rather than glycosaminoglycans affect normal and sickle red blood cell rheology by binding to four major sites on fibrinogen

Abstract: and corticosteroids would not have been considered without our patient's requests, and would not have been possible without our patient's intelligence, understanding and agreement. We could confidently manage her as an outpatient because she was reliable, she lived near to the medical center, and her family could help with her management and guarantee her safety. Also, we would not have considered this treatment if her thrombocytopenia had been severe or if she had any neurologic symptoms. But with all of these supportive circumstances, we were able to manage our patient successfully. Our experience illustrates the ability of caplacizumab and rituximab, without hospitalization, to achieve a remission in patients with TTP. More importantly, our experience illustrates the value of integrating shared decision-making into clinical practice and exemplifies how shared decision-making can facilitate changes of medical practice, including utilization of new treatments.

Computational and experimental characterization of the novel ECM glycoprotein SNED1 and prediction of its interactome

Abstract: The extracellular matrix (ECM) protein SNED1 has been shown to promote breast cancer metastasis and control neural crest cell-specific craniofacial development, but the cellular and molecular mechanisms by which it does so remain unknown. ECM proteins exert their functions by binding to cell surface receptors, sequestering growth factors, and interacting with other ECM proteins, actions that can be predicted using knowledge of protein’s sequence, structure and post-translational modifications. Here, we combined in-silico and in-vitro approaches to characterize the physico-chemical properties of SNED1 and infer its putative functions. To do so, we established a mammalian cell system to produce and purify SNED1 and its N-terminal fragment, which contains a NIDO domain. We have determined experimentally SNED1’s potential to be glycosylated, phosphorylated, and incorporated into insoluble ECM produced by cells. In addition, we used biophysical and computational methods to determine the secondary and tertiary structures of SNED1 and its N-terminal fragment. The tentative ab-initio model we built of SNED1 suggests that it is an elongated protein presumably able to bind multiple partners. Using computational predictions, we identified 114 proteins as putative SNED1 interactors. Pathway analysis of the newly-predicted SNED1 interactome further revealed that binding partners of SNED1 contribute to signaling through cell surface receptors, such as integrins, and participate in the regulation of ECM organization and developmental processes. Altogether, we provide a wealth of information on an understudied yet important ECM protein with the potential to decipher its functions in physiology and diseases.

The Extracellular Matrix Goes -Omics: Resources and Tools

Abstract: The extracellular matrix (ECM) is the complex scaffold made of hundreds of proteins that governs the organization of cells and tissues in all multicellular organisms. It provides structural and mechanical properties to tissues. It also exerts signaling roles, either directly by interacting with cell surface receptors, or by interacting with growth factors and modulating their signaling activities, and by doing so regulates a multitude of cellular functions including cell-matrix interactions, cell proliferation, survival, and differentiation. The purpose of this introductory chapter is to present resources and tools developed to facilitate the identification and analysis of ECM genes and proteins across different conditions using high-throughput methodologies (i.e., genomics, transcriptomics, proteomics, and interactomics). Databases focused on specific ECM genes and ECM-related diseases including genetic diseases are highlighted in the second part of the chapter. The accessibility and standardization of -omic data are a prerequisite for the FAIR (Findability, Accessibility, Interoperability, and Reusability) guiding principles for scientific data management.

Extracellular Matrix Networks: From Connections to Functions

Abstract: The extracellular matrix (ECM) forms of a three dimensional interaction network mostly comprised of proteins, collagens being the most abundant ones (Ricard-Blum, Cold Spring Harb Perspect Biol 3:a004978, 2011), glycosaminoglycans (GAGs) and proteoglycans (PGs) (Iozzo and Schaefer, Matrix Biol 42:11–55, 2015; Karamanos et al., Chem Rev 118:9152–9232, 2018). We review here the major methods used to identify and characterize ECM protein, glycosaminoglycan, and proteoglycan interactions with a focus on high-throughput methods able to identify a number of interactions simultaneously such as yeast two hybrid assays, ECM protein and GAG arrays, and affinity purification coupled to mass spectrometry (MS). The use of large experimental interaction datasets publicly available, and of interaction databases to retrieve interaction data required to build interaction networks is discussed. The interest of the data generated from the functional and structural analyses of interactomes to decipher molecular mechanisms of biological processes, to design further functional experiments, and to select ECM proteins or GAGs and/or their biomolecular interactions as therapeutic targets is illustrated by several examples. The ultimate goal of these studies is to build three-dimensional ECM networks, integrating the 3D structure of individual ECM molecules and their complexes.