Building Protein-Protein and Protein-Glycosaminoglycan Interaction Networks Using MatrixDB, the Extracellular Matrix Interaction Database

A biological guide to glycosaminoglycans: current perspectives and pending questions

Mammalian glycosaminoglycans (GAGs), except hyaluronan (HA), are sulfated polysaccharides that are covalently attached to core proteins to form proteoglycans (PGs). This article summarizes key biological findings for the most widespread GAGs, namely HA, chondroitin sulfate/dermatan sulfate (CS/DS), keratan sulfate (KS), and heparan sulfate (HS). It focuses on the major processes that remain to be deciphered to get a comprehensive view of the mechanisms mediating GAG biological functions. They include the regulation of GAG biosynthesis and postsynthetic modifications in heparin (HP) and HS, the composition, heterogeneity, and function of the tetrasaccharide linkage region and its role in disease, the functional characterization of the new PGs recently identified by glycoproteomics, the selectivity of interactions mediated by GAG chains, the display of GAG chains and PGs at the cell surface and their impact on the availability and activity of soluble ligands, and on their move through the glycocalyx layer to reach their receptors, the human GAG profile in health and disease, the roles of GAGs and particular PGs (syndecans, decorin, and biglycan) involved in cancer, inflammation, and fibrosis, the possible use of GAGs and PGs as disease biomarkers, and the design of inhibitors targeting GAG biosynthetic enzymes and GAG-protein interactions to develop novel therapeutic approaches.

Matrisome AnalyzeR - a suite of tools to annotate and quantify ECM molecules in big datasets across organisms

The extracellular matrix (ECM) is a complex meshwork of proteins that forms the scaffold of all tissues in multicellular organisms. It plays crucial roles in all aspects of life - from orchestrating cell migration during development, to supporting tissue repair. It also plays critical roles in the etiology or progression of diseases. To study this compartment, we have previously defined the compendium of all genes encoding ECM and ECM-associated proteins for multiple organisms. We termed this compendium the 'matrisome' and further classified matrisome components into different structural or functional categories. This nomenclature is now largely adopted by the research community to annotate '-omics' datasets and has contributed to advance both fundamental and translational ECM research. Here, we report the development of Matrisome AnalyzeR, a suite of tools including a web-based application and an R package. The web application can be used by anyone interested in annotating, classifying and tabulating matrisome molecules in large datasets without requiring programming knowledge. The companion R package is available to more experienced users, interested in processing larger datasets or in additional data visualization options.

Differential analysis of the dentin soluble proteomic

OBJECTIVES

To perform a differential analysis of the dentin soluble proteomic and assess the effects of tissue health state and protocol for protein extraction. We hypothesized the dentin soluble proteomic varies according to the tissue physiopathological state (intact vs. caries-affected) and protocol used to extract its proteins.

METHODS

Dentin from freshly extracted non-carious and carious teeth were randomly assigned for protein extraction using either guanidine-HCl/ethylenediaminetetraacetic acid (EDTA) or acetic acid. Protein extracts from intact and caries-affected dentin were processed and digested with trypsin for shotgun label-free proteomic analysis (nLC-ESI-MS/MS). Peptides identification was performed on a nanoACQUITY UPLC-Xevo Q-Tof MS system. Peptides identified with scores of confidence greater than 95% were included in the quantitative statistical analysis embedded in the PLGS software. Differences between experimental conditions were calculated using Student test-t with significance pre-set at α=0.05.

RESULTS

A total of 158 human proteins were identified. Approximately one-sixth of proteins (24/158) were present in at least two different extracts. Conversely, the greatest number of proteins (134/158) was identified uniquely in only one of the extracts. Overall, a larger number of soluble proteins was retrieved from caries-affected than intact dentin (86/158). Likewise, a greater number of proteins was extracted by the guanidine-HCl/EDTA (106/158) in comparison to acetic acid protocol. Several proteins detected in dentin extracts, mainly those from caries-affected teeth, are biological and/or metabolically involved with tissue turnover/remodeling.

CONCLUSION

The identity/abundance of soluble proteins retrieved from and remained in dentin noticeably depend on this tissue physiopathological state and protocol used to remove its minerals.

CLINICAL SIGNIFICANCE

The present findings brought new insight into the proteomic phenotype of human dentin and may provide targets for the development of novel caries disease-prevention therapies.

Trends in extracellular matrix biology

Extracellular matrixes (ECMs) are intricate 3-dimensional macromolecular networks of unique architectures with regulatory roles in cell morphology and functionality. As a dynamic native biomaterial, ECM undergoes constant but tightly controlled remodeling that is crucial for the maintenance of normal cellular behavior. Under pathological conditions like cancer, ECM remodeling ceases to be subjected to control resulting in disease initiation and progression. ECM is comprised of a staggering number of molecules that interact not only with one another, but also with neighboring cells via cell surface receptors. Such interactions, too many to tally, are of paramount importance for the identification of novel disease biomarkers and more personalized therapeutic intervention. Recent advances in big data analytics have allowed the development of online databases where researchers can take advantage of a stochastic evaluation of all the possible interactions and narrow them down to only those of interest for their study, respectively. This novel approach addresses the limitations that currently exist in studies, expands our understanding on ECM interactions, and has the potential to advance the development of targeted therapies. In this article we present the current trends in ECM biology research and highlight its importance in tissue integrity, the main interaction networks, ECM-mediated cell functional properties and issues related to pharmacological targeting.

Building, Visualizing, and Analyzing Glycosaminoglycan-Protein Interaction Networks

This chapter describes how to generate, visualize, and analyze interaction networks of glycosaminoglycans (GAGs), which are linear polyanionic polysaccharides mostly located at the cell surface and in the extracellular matrix. The protocol is divided into three major steps: (1) the collection of GAG-mediated interaction data, (2) the visualization of GAG interaction networks, and (3) the computational enrichment analyses of these networks to identify their overrepresented features (e.g., protein domains, location, molecular functions, and biological pathways) compared to a reference proteome. These analyses are critical to interpret GAG interactomic datasets, decipher their specificities and functions, and ultimately identify GAG-protein interactions to target for therapeutic purpose.

The kidney matrisome in health, aging, and disease

Dysregulated extracellular matrix is the hallmark of fibrosis, and it has a profound impact on kidney function in disease. Furthermore, perturbation of matrix homeostasis is a feature of aging and is associated with declining kidney function. Understanding these dynamic processes, in the hope of developing therapies to combat matrix dysregulation, requires the integration of data acquired by both well-established and novel technologies. Owing to its complexity, the extracellular proteome, or matrisome, still holds many secrets and has great potential for the identification of clinical biomarkers and drug targets. The molecular resolution of matrix composition during aging and disease has been illuminated by cutting-edge mass spectrometry-based proteomics in recent years, but there remain key questions about the mechanisms that drive altered matrix composition. Basement membrane components are particularly important in the context of kidney function; and data from proteomic studies suggest that switches between basement membrane and interstitial matrix proteins are likely to contribute to organ dysfunction during aging and disease. Understanding the impact of such changes on physical properties of the matrix, and the subsequent cellular response to altered stiffness and viscoelasticity, is of critical importance. Likewise, the comparison of proteomic data sets from multiple organs is required to identify common matrix biomarkers and shared pathways for therapeutic intervention. Coupled with single-cell transcriptomics, there is the potential to identify the cellular origin of matrix changes, which could enable cell-targeted therapy. This review provides a contemporary perspective of the complex kidney matrisome and draws comparison to altered matrix in heart and liver disease.

Complex Portal 2022: new curation frontiers

The Complex Portal (www.ebi.ac.uk/complexportal) is a manually curated, encyclopaedic database of macromolecular complexes with known function from a range of model organisms. It summarizes complex composition, topology and function along with links to a large range of domain-specific resources (i.e. wwPDB, EMDB and Reactome). Since the last update in 2019, we have produced a first draft complexome for Escherichia coli, maintained and updated that of Saccharomyces cerevisiae, added over 40 coronavirus complexes and increased the human complexome to over 1100 complexes that include approximately 200 complexes that act as targets for viral proteins or are part of the immune system. The display of protein features in ComplexViewer has been improved and the participant table is now colour-coordinated with the nodes in ComplexViewer. Community collaboration has expanded, for example by contributing to an analysis of putative transcription cofactors and providing data accessible to semantic web tools through Wikidata which is now populated with manually curated Complex Portal content through a new bot. Our data license is now CC0 to encourage data reuse. Users are encouraged to get in touch, provide us with feedback and send curation requests through the 'Support' link.