3
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Vesicular and extravesicular protein analyses from the airspaces of ozone-exposed mice revealed signatures associated with mucoinflammatory lung disease

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Lung epithelial lining fluid (ELF) harbors a variety of proteins that influence homeostatic and stress responses in the airspaces. Exosomes, nano-sized extracellular vesicles, contain many proteins that vary in abundance and composition based on the prevailing conditions. Ozone causes inflammatory responses in the airspaces of experimental animals and humans. However, the exosomal protein signatures contained within the ELF from ozone-exposed lung airspaces remain poorly characterized. To explore this, we hypothesized that ozone triggers the release of exosome-bound inflammatory proteins from various cells that reflect mucoobstructive lung disease. Accordingly, we repetitively exposed adult male and female C57BL/6 mice to HEPA-filtered air (air) or 0.8 ppm ozone (4 h per day) for 14 days (five consecutive days of exposure, 2 days of rest, five consecutive days of exposure, 2 days of rest, four consecutive days of exposure). Exosome-bound proteomic signatures, as well as the levels of soluble inflammatory mediators in the bronchoalveolar lavage fluid (BALF), were determined 12–16 h after the last exposure. Principal component analyses of the exosome-bound proteome revealed a clear distinction between air-exposed and ozone-exposed mice, as well as between ozone-exposed males and ozone-exposed females. In addition to 575 proteins that were enriched in both sexes upon ozone exposure, 243 and 326 proteins were enriched uniquely in ozone-exposed males and females, respectively. Ingenuity pathway analyses on enriched proteins between ozone- and air-exposed mice revealed enrichment of pro-inflammatory pathways. More specifically, macrophage activation-related proteins were enriched in exosomes from ozone-exposed mice. Cytokine analyses on the BALF revealed elevated levels of G-CSF, KC, IP-10, IL-6, and IL-5 in ozone-exposed mice. Finally, the histopathological assessment revealed significantly enhanced intracellular localization of mucoinflammatory proteins including MUC5B and FIZZ1 in ozone-exposed mice in a cell-specific manner indicating the cellular sources of the proteins that are ferried in the exosomes upon ozone-induced lung injury. Collectively, this study identified exosomal, secretory, and cell-specific proteins and biological pathways following repetitive exposure of mice to ozone.

          Related collections

          Most cited references89

          • Record: found
          • Abstract: found
          • Article: found
          Is Open Access

          limma powers differential expression analyses for RNA-sequencing and microarray studies

          limma is an R/Bioconductor software package that provides an integrated solution for analysing data from gene expression experiments. It contains rich features for handling complex experimental designs and for information borrowing to overcome the problem of small sample sizes. Over the past decade, limma has been a popular choice for gene discovery through differential expression analyses of microarray and high-throughput PCR data. The package contains particularly strong facilities for reading, normalizing and exploring such data. Recently, the capabilities of limma have been significantly expanded in two important directions. First, the package can now perform both differential expression and differential splicing analyses of RNA sequencing (RNA-seq) data. All the downstream analysis tools previously restricted to microarray data are now available for RNA-seq as well. These capabilities allow users to analyse both RNA-seq and microarray data with very similar pipelines. Second, the package is now able to go past the traditional gene-wise expression analyses in a variety of ways, analysing expression profiles in terms of co-regulated sets of genes or in terms of higher-order expression signatures. This provides enhanced possibilities for biological interpretation of gene expression differences. This article reviews the philosophy and design of the limma package, summarizing both new and historical features, with an emphasis on recent enhancements and features that have not been previously described.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: found
            Is Open Access

            STRING v11: protein–protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets

            Abstract Proteins and their functional interactions form the backbone of the cellular machinery. Their connectivity network needs to be considered for the full understanding of biological phenomena, but the available information on protein–protein associations is incomplete and exhibits varying levels of annotation granularity and reliability. The STRING database aims to collect, score and integrate all publicly available sources of protein–protein interaction information, and to complement these with computational predictions. Its goal is to achieve a comprehensive and objective global network, including direct (physical) as well as indirect (functional) interactions. The latest version of STRING (11.0) more than doubles the number of organisms it covers, to 5090. The most important new feature is an option to upload entire, genome-wide datasets as input, allowing users to visualize subsets as interaction networks and to perform gene-set enrichment analysis on the entire input. For the enrichment analysis, STRING implements well-known classification systems such as Gene Ontology and KEGG, but also offers additional, new classification systems based on high-throughput text-mining as well as on a hierarchical clustering of the association network itself. The STRING resource is available online at https://string-db.org/.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Biogenesis, secretion, and intercellular interactions of exosomes and other extracellular vesicles.

              In the 1980s, exosomes were described as vesicles of endosomal origin secreted from reticulocytes. Interest increased around these extracellular vesicles, as they appeared to participate in several cellular processes. Exosomes bear proteins, lipids, and RNAs, mediating intercellular communication between different cell types in the body, and thus affecting normal and pathological conditions. Only recently, scientists acknowledged the difficulty of separating exosomes from other types of extracellular vesicles, which precludes a clear attribution of a particular function to the different types of secreted vesicles. To shed light into this complex but expanding field of science, this review focuses on the definition of exosomes and other secreted extracellular vesicles. Their biogenesis, their secretion, and their subsequent fate are discussed, as their functions rely on these important processes.
                Bookmark

                Author and article information

                Contributors
                ysaini@lsu.edu
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                1 December 2021
                1 December 2021
                2021
                : 11
                : 23203
                Affiliations
                [1 ]GRID grid.64337.35, ISNI 0000 0001 0662 7451, Department of Comparative Biomedical Sciences, School of Veterinary Medicine, , Louisiana State University, ; 1909 Skip Bertman Drive, Baton Rouge, LA 70803 USA
                [2 ]GRID grid.64337.35, ISNI 0000 0001 0662 7451, Department of Pathobiological Sciences, School of Veterinary Medicine, , Louisiana State University, ; Baton Rouge, LA 70803 USA
                [3 ]GRID grid.10698.36, ISNI 0000000122483208, Department of Pathology and Laboratory Medicine, , UNC School of Medicine, ; Chapel Hill, NC 27510 USA
                Article
                2256
                10.1038/s41598-021-02256-5
                8636509
                34853335
                75624685-ff33-48bc-9162-6dd9ff439a78
                © The Author(s) 2021

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 20 December 2020
                : 8 November 2021
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/100000066, National Institute of Environmental Health Sciences;
                Award ID: R01ES030125
                Award Recipient :
                Categories
                Article
                Custom metadata
                © The Author(s) 2021

                Uncategorized
                proteomic analysis,animal disease models,respiratory system models,chronic inflammation

                Comments

                Comment on this article