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      Proteomic Analysis of Chicken Chorioallantoic Membrane (CAM) during Embryonic Development Provides Functional Insight

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          Abstract

          In oviparous animals, the egg contains all resources required for embryonic development. The chorioallantoic membrane (CAM) is a placenta-like structure produced by the embryo for acid-base balance, respiration, and calcium solubilization from the eggshell for bone mineralization. The CAM is a valuable in vivo model in cancer research for development of drug delivery systems and has been used to study tissue grafts, tumor metastasis, toxicology, angiogenesis, and assessment of bacterial invasion. However, the protein constituents involved in different CAM functions are poorly understood. Therefore, we have characterized the CAM proteome at two stages of development (ED12 and ED19) and assessed the contribution of the embryonic blood serum (EBS) proteome to identify CAM-unique proteins. LC/MS/MS-based proteomics allowed the identification of 1470, 1445, and 791 proteins in CAM (ED12), CAM (ED19), and EBS, respectively. In total, 1796 unique proteins were identified. Of these, 175 (ED12), 177 (ED19), and 105 (EBS) were specific to these stages/compartments. This study attributed specific CAM protein constituents to functions such as calcium ion transport, gas exchange, vasculature development, and chemical protection against invading pathogens. Defining the complex nature of the CAM proteome provides a crucial basis to expand its biomedical applications for pharmaceutical and cancer research.

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          The PRIDE database and related tools and resources in 2019: improving support for quantification data

          Abstract The PRoteomics IDEntifications (PRIDE) database (https://www.ebi.ac.uk/pride/) is the world’s largest data repository of mass spectrometry-based proteomics data, and is one of the founding members of the global ProteomeXchange (PX) consortium. In this manuscript, we summarize the developments in PRIDE resources and related tools since the previous update manuscript was published in Nucleic Acids Research in 2016. In the last 3 years, public data sharing through PRIDE (as part of PX) has definitely become the norm in the field. In parallel, data re-use of public proteomics data has increased enormously, with multiple applications. We first describe the new architecture of PRIDE Archive, the archival component of PRIDE. PRIDE Archive and the related data submission framework have been further developed to support the increase in submitted data volumes and additional data types. A new scalable and fault tolerant storage backend, Application Programming Interface and web interface have been implemented, as a part of an ongoing process. Additionally, we emphasize the improved support for quantitative proteomics data through the mzTab format. At last, we outline key statistics on the current data contents and volume of downloads, and how PRIDE data are starting to be disseminated to added-value resources including Ensembl, UniProt and Expression Atlas.
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            STRING v10: protein–protein interaction networks, integrated over the tree of life

            The many functional partnerships and interactions that occur between proteins are at the core of cellular processing and their systematic characterization helps to provide context in molecular systems biology. However, known and predicted interactions are scattered over multiple resources, and the available data exhibit notable differences in terms of quality and completeness. The STRING database (http://string-db.org) aims to provide a critical assessment and integration of protein–protein interactions, including direct (physical) as well as indirect (functional) associations. The new version 10.0 of STRING covers more than 2000 organisms, which has necessitated novel, scalable algorithms for transferring interaction information between organisms. For this purpose, we have introduced hierarchical and self-consistent orthology annotations for all interacting proteins, grouping the proteins into families at various levels of phylogenetic resolution. Further improvements in version 10.0 include a completely redesigned prediction pipeline for inferring protein–protein associations from co-expression data, an API interface for the R computing environment and improved statistical analysis for enrichment tests in user-provided networks.
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              KEGG: new perspectives on genomes, pathways, diseases and drugs

              KEGG (http://www.kegg.jp/ or http://www.genome.jp/kegg/) is an encyclopedia of genes and genomes. Assigning functional meanings to genes and genomes both at the molecular and higher levels is the primary objective of the KEGG database project. Molecular-level functions are stored in the KO (KEGG Orthology) database, where each KO is defined as a functional ortholog of genes and proteins. Higher-level functions are represented by networks of molecular interactions, reactions and relations in the forms of KEGG pathway maps, BRITE hierarchies and KEGG modules. In the past the KO database was developed for the purpose of defining nodes of molecular networks, but now the content has been expanded and the quality improved irrespective of whether or not the KOs appear in the three molecular network databases. The newly introduced addendum category of the GENES database is a collection of individual proteins whose functions are experimentally characterized and from which an increasing number of KOs are defined. Furthermore, the DISEASE and DRUG databases have been improved by systematic analysis of drug labels for better integration of diseases and drugs with the KEGG molecular networks. KEGG is moving towards becoming a comprehensive knowledge base for both functional interpretation and practical application of genomic information.
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                Author and article information

                Contributors
                Journal
                Biomed Res Int
                Biomed Res Int
                BMRI
                BioMed Research International
                Hindawi
                2314-6133
                2314-6141
                2022
                19 June 2022
                : 2022
                Affiliations
                1Department of Cellular and Molecular Medicine, Faculty of Medicine, University of Ottawa, Ottawa, Ontario, Canada
                2Department of Innovation in Medical Education, Faculty of Medicine, University of Ottawa, Ottawa, Ontario, Canada
                Author notes

                Academic Editor: Valeria Pasciu

                Article
                10.1155/2022/7813921
                9237712
                4815e0f4-0a43-4856-a1cf-e6a22f4ca7cd
                Copyright © 2022 Tamer A. E. Ahmed et al.

                This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                Funding
                Funded by: Natural Sciences and Engineering Research Council
                Award ID: RGPIN/2022-04410
                Categories
                Research Article

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