Blog
About

10
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Human and feline adipose-derived mesenchymal stem cells have comparable phenotype, immunomodulatory functions, and transcriptome

      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

          Background

          Adipose-derived mesenchymal stem cells (ASCs) are a promising cell therapy to treat inflammatory and immune-mediated diseases. Development of appropriate pre-clinical animal models is critical to determine safety and attain early efficacy data for the most promising therapeutic candidates. Naturally occurring diseases in cats already serve as valuable models to inform human clinical trials in oncologic, cardiovascular, and genetic diseases. The objective of this study was to complete a comprehensive side-by-side comparison of human and feline ASCs, with an emphasis on their immunomodulatory capacity and transcriptome.

          Methods

          Human and feline ASCs were evaluated for phenotype, immunomodulatory profile, and transcriptome. Additionally, transwells were used to determine the role of cell-cell contact in ASC-mediated inhibition of lymphocyte proliferation in both humans and cats.

          Results

          Similar to human ASCs, feline ASCs were highly proliferative at low passages and fit the minimal criteria of multipotent stem cells including a compatible surface protein phenotype, osteogenic capacity, and normal karyotype. Like ASCs from all species, feline ASCs inhibited mitogen-activated lymphocyte proliferation in vitro, with or without direct ASC-lymphocyte contact. Feline ASCs mimic human ASCs in their mediator secretion pattern, including prostaglandin E2, indoleamine 2,3 dioxygenase, transforming growth factor beta, and interleukin-6, all augmented by interferon gamma secretion by lymphocytes. The transcriptome of three unactivated feline ASC lines were highly similar. Functional analysis of the most highly expressed genes highlighted processes including: 1) the regulation of apoptosis; 2) cell adhesion; 3) response to oxidative stress; and 4) regulation of cell differentiation. Finally, feline ASCs had a similar gene expression profile to noninduced human ASCs.

          Conclusions

          Findings suggest that feline ASCs modulate lymphocyte proliferation using soluble mediators that mirror the human ASC secretion pattern. Uninduced feline ASCs have similar gene expression profiles to uninduced human ASCs, as revealed by transcriptome analysis. These data will help inform clinical trials using cats with naturally occurring diseases as surrogate models for human clinical trials in the regenerative medicine arena.

          Electronic supplementary material

          The online version of this article (doi:10.1186/s13287-017-0528-z) contains supplementary material, which is available to authorized users.

          Related collections

          Most cited references 66

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

          Systematic and integrative analysis of large gene lists using DAVID bioinformatics resources.

          DAVID bioinformatics resources consists of an integrated biological knowledgebase and analytic tools aimed at systematically extracting biological meaning from large gene/protein lists. This protocol explains how to use DAVID, a high-throughput and integrated data-mining environment, to analyze gene lists derived from high-throughput genomic experiments. The procedure first requires uploading a gene list containing any number of common gene identifiers followed by analysis using one or more text and pathway-mining tools such as gene functional classification, functional annotation chart or clustering and functional annotation table. By following this protocol, investigators are able to gain an in-depth understanding of the biological themes in lists of genes that are enriched in genome-scale studies.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Transcript assembly and abundance estimation from RNA-Seq reveals thousands of new transcripts and switching among isoforms

            High-throughput mRNA sequencing (RNA-Seq) holds the promise of simultaneous transcript discovery and abundance estimation 1-3 . We introduce an algorithm for transcript assembly coupled with a statistical model for RNA-Seq experiments that produces estimates of abundances. Our algorithms are implemented in an open source software program called Cufflinks. To test Cufflinks, we sequenced and analyzed more than 430 million paired 75bp RNA-Seq reads from a mouse myoblast cell line representing a differentiation time series. We detected 13,692 known transcripts and 3,724 previously unannotated ones, 62% of which are supported by independent expression data or by homologous genes in other species. Analysis of transcript expression over the time series revealed complete switches in the dominant transcription start site (TSS) or splice-isoform in 330 genes, along with more subtle shifts in a further 1,304 genes. These dynamics suggest substantial regulatory flexibility and complexity in this well-studied model of muscle development.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: found
              Is Open Access

              Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists

              Functional analysis of large gene lists, derived in most cases from emerging high-throughput genomic, proteomic and bioinformatics scanning approaches, is still a challenging and daunting task. The gene-annotation enrichment analysis is a promising high-throughput strategy that increases the likelihood for investigators to identify biological processes most pertinent to their study. Approximately 68 bioinformatics enrichment tools that are currently available in the community are collected in this survey. Tools are uniquely categorized into three major classes, according to their underlying enrichment algorithms. The comprehensive collections, unique tool classifications and associated questions/issues will provide a more comprehensive and up-to-date view regarding the advantages, pitfalls and recent trends in a simpler tool-class level rather than by a tool-by-tool approach. Thus, the survey will help tool designers/developers and experienced end users understand the underlying algorithms and pertinent details of particular tool categories/tools, enabling them to make the best choices for their particular research interests.
                Bookmark

                Author and article information

                Contributors
                kcclark@ucdavis.edu
                ffierro@ucdavis.edu
                ejmills@ucdavis.edu
                njwalker@ucdavis.edu
                barzi@ucdavis.edu
                cgtepper@ucdavis.edu
                hrstewart@ucdavis.edu
                andrewcicchetto@gmail.com
                akol@ucdavis.edu
                ljmarsh@ucdavis.edu
                wmjmurphy@ucdavis.edu
                nfazel@ucdavis.edu
                (530) 754-5202 , dlborjesson@ucdavis.edu
                Journal
                Stem Cell Res Ther
                Stem Cell Res Ther
                Stem Cell Research & Therapy
                BioMed Central (London )
                1757-6512
                20 March 2017
                20 March 2017
                2017
                : 8
                Affiliations
                [1 ]ISNI 0000 0004 1936 9684, GRID grid.27860.3b, Veterinary Institute for Regenerative Cures and Department of Pathology, Microbiology and Immunology, , University of California, ; Davis, CA 95816 USA
                [2 ]ISNI 0000 0004 1936 9684, GRID grid.27860.3b, Institute for Regenerative Cures and Department of Cell Biology and Human Anatomy, , University of California, ; Davis, CA 95816 USA
                [3 ]ISNI 0000 0004 1936 9684, GRID grid.27860.3b, Department of Surgical and Radiological Sciences, School of Veterinary Medicine, , University of California, ; Davis, CA 95816 USA
                [4 ]ISNI 0000 0004 1936 9684, GRID grid.27860.3b, Department of Biochemistry and Molecular Medicine, , University of California, ; Davis, CA 95816 USA
                [5 ]ISNI 0000 0004 1936 9684, GRID grid.27860.3b, Department of Dermatology, School of Medicine, , University of California, ; Davis, CA 95816 USA
                Article
                528
                10.1186/s13287-017-0528-z
                5360077
                28320483
                © The Author(s). 2017

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/100000002, National Institutes of Health;
                Award ID: 1R21DE024711-01
                Award Recipient :
                Funded by: California Institute for Regenerative Medicine (US)
                Award ID: TB1-01184
                Award Recipient :
                Categories
                Research
                Custom metadata
                © The Author(s) 2017

                Comments

                Comment on this article