2
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Burkholderia cenocepacia transcriptome during the early contacts with giant plasma membrane vesicles derived from live bronchial epithelial cells

      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

          Burkholderia cenocepacia is known for its capacity of adherence and interaction with the host, causing severe opportunistic lung infections in cystic fibrosis patients. In this work we produced Giant Plasma Membrane Vesicles (GPMVs) from a bronchial epithelial cell line and validated their use as a cell-like alternative to investigate the steps involved in the adhesion process of B. cenocepacia. RNA-sequencing was performed and the analysis of the B. cenocepacia K56-2 transcriptome after the first contacts with the surface of host cells allowed the recognition of genes implicated in bacterial adaptation and virulence-associated functions. The sensing of host membranes led to a transcriptional shift that caused a cascade of metabolic and physiological adaptations to the host specific environment. Many of the differentially expressed genes encode proteins related with central metabolic pathways, transport systems, cellular processes, and virulence traits. The understanding of the changes in gene expression that occur in the early steps of infection can uncover new proteins implicated in B. cenocepacia-host cell adhesion, against which new blocking agents could be designed to control the progression of the infectious process.

          Related collections

          Most cited references71

          • Record: found
          • Abstract: found
          • Article: not found

          KEGG: kyoto encyclopedia of genes and genomes.

          M Kanehisa (2000)
          KEGG (Kyoto Encyclopedia of Genes and Genomes) is a knowledge base for systematic analysis of gene functions, linking genomic information with higher order functional information. The genomic information is stored in the GENES database, which is a collection of gene catalogs for all the completely sequenced genomes and some partial genomes with up-to-date annotation of gene functions. The higher order functional information is stored in the PATHWAY database, which contains graphical representations of cellular processes, such as metabolism, membrane transport, signal transduction and cell cycle. The PATHWAY database is supplemented by a set of ortholog group tables for the information about conserved subpathways (pathway motifs), which are often encoded by positionally coupled genes on the chromosome and which are especially useful in predicting gene functions. A third database in KEGG is LIGAND for the information about chemical compounds, enzyme molecules and enzymatic reactions. KEGG provides Java graphics tools for browsing genome maps, comparing two genome maps and manipulating expression maps, as well as computational tools for sequence comparison, graph comparison and path computation. The KEGG databases are daily updated and made freely available (http://www. genome.ad.jp/kegg/).
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Gene Expression Omnibus: NCBI gene expression and hybridization array data repository.

            R. Edgar (2002)
            The Gene Expression Omnibus (GEO) project was initiated in response to the growing demand for a public repository for high-throughput gene expression data. GEO provides a flexible and open design that facilitates submission, storage and retrieval of heterogeneous data sets from high-throughput gene expression and genomic hybridization experiments. GEO is not intended to replace in house gene expression databases that benefit from coherent data sets, and which are constructed to facilitate a particular analytic method, but rather complement these by acting as a tertiary, central data distribution hub. The three central data entities of GEO are platforms, samples and series, and were designed with gene expression and genomic hybridization experiments in mind. A platform is, essentially, a list of probes that define what set of molecules may be detected. A sample describes the set of molecules that are being probed and references a single platform used to generate its molecular abundance data. A series organizes samples into the meaningful data sets which make up an experiment. The GEO repository is publicly accessible through the World Wide Web at http://www.ncbi.nlm.nih.gov/geo.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Toward understanding the origin and evolution of cellular organisms

              In this era of high‐throughput biology, bioinformatics has become a major discipline for making sense out of large‐scale datasets. Bioinformatics is usually considered as a practical field developing databases and software tools for supporting other fields, rather than a fundamental scientific discipline for uncovering principles of biology. The KEGG resource that we have been developing is a reference knowledge base for biological interpretation of genome sequences and other high‐throughput data. It is now one of the most utilized biological databases because of its practical values. For me personally, KEGG is a step toward understanding the origin and evolution of cellular organisms.
                Bookmark

                Author and article information

                Contributors
                afialho@tecnico.ulisboa.pt
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                11 March 2021
                11 March 2021
                2021
                : 11
                : 5624
                Affiliations
                [1 ]iBB-Institute for Bioengineering and Biosciences, Biological Sciences Research Group, Av. Rovisco Pais 1, 1049-001 Lisbon, Portugal
                [2 ]GRID grid.9983.b, ISNI 0000 0001 2181 4263, CQE Instituto Superior Técnico, Departamento de Engenharia Química, , Universidade de Lisboa, ; Av. Rovisco Pais, 1049-001 Lisbon, Portugal
                [3 ]GRID grid.9983.b, ISNI 0000 0001 2181 4263, Department of Bioengineering, Instituto Superior Técnico, , University of Lisbon, ; Lisbon, Portugal
                Article
                85222
                10.1038/s41598-021-85222-5
                7970998
                33707642
                4eff2c96-f52a-43f6-a49a-0fbe759f4195
                © 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 August 2020
                : 22 February 2021
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100001871, Fundação para a Ciência e a Tecnologia;
                Award ID: PD/BD/116940/2016
                Award ID: UID/BIO/ 04565/2020
                Award ID: UIDB/00100/2020
                Award ID: UID/BIO/ 04565/2020
                Award ID: UID/BIO/ 04565/2020
                Award Recipient :
                Categories
                Article
                Custom metadata
                © The Author(s) 2021

                Uncategorized
                cell biology,microbiology,molecular biology
                Uncategorized
                cell biology, microbiology, molecular biology

                Comments

                Comment on this article