31
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Pathway Analysis of MicroRNA Expression Profile during Murine Osteoclastogenesis

      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

          To design novel therapeutics against bone loss, understanding the molecular mechanisms regulating osteoclastogenesis is critical. Osteoclast formation and function are tightly regulated by transcriptional, post-transcriptional and post-translational mechanisms. This stringent regulation is crucial to prevent excessive or insufficient bone resorption and to maintain bone homeostasis. microRNAs (miRNAs) are key post-transcriptional regulators that repress expression of target mRNAs controlling osteoclast proliferation, differentiation, and apoptosis. Disruption of miRNA-mediated regulation alters osteoclast formation and bone resorption. Prior studies profiled miRNA expression in murine osteoclast precursors treated with RANKL for 24 hours. However, a more complete miRNA signature, encompassing early, mid and late stages of osteoclastogenesis, is wanting. An Agilent microarray platform was used to analyze expression of mature miRNAs in an enriched population of murine bone marrow osteoclast precursors (depleted of B220 + and CD3 + cells) undergoing 1, 3, or 5 days of RANKL-driven differentiation. Expression of 93 miRNAs, changed by >2 fold during early, mid, and late stages of osteoclastogenesis, were identified and sorted into 7 clusters. We validated the function and expression of miR-365, miR-451, and miR-99b, which were found in distinct clusters. Inhibition of miR-365 increased osteoclast number but decreased osteoclast size, while miR-99b inhibition decreased both osteoclast number and size. In contrast, overexpression of miR-451 had no effect. Computational analyses predicted mTOR, PI3 kinase/AKT, cell-matrix interactions, actin cytoskeleton organization, focal adhesion, and axon guidance pathways to be top targets of several miRNA clusters. This suggests that many miRNA clusters differentially expressed during osteoclastogenesis converge on some key functional pathways. Overall, our study is unique in that we identified miRNAs differentially expressed during early, mid, and late osteoclastogenesis in a population of primary mouse bone marrow cells enriched for osteoclast progenitors. This novel data set contributes to our understanding of the molecular mechanisms regulating the complex process of osteoclast differentiation.

          Related collections

          Most cited references39

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

          Dysregulation of microRNAs after myocardial infarction reveals a role of miR-29 in cardiac fibrosis.

          Acute myocardial infarction (MI) due to coronary artery occlusion is accompanied by a pathological remodeling response that includes hypertrophic cardiac growth and fibrosis, which impair cardiac contractility. Previously, we showed that cardiac hypertrophy and heart failure are accompanied by characteristic changes in the expression of a collection of specific microRNAs (miRNAs), which act as negative regulators of gene expression. Here, we show that MI in mice and humans also results in the dysregulation of specific miRNAs, which are similar to but distinct from those involved in hypertrophy and heart failure. Among the MI-regulated miRNAs are members of the miR-29 family, which are down-regulated in the region of the heart adjacent to the infarct. The miR-29 family targets a cadre of mRNAs that encode proteins involved in fibrosis, including multiple collagens, fibrillins, and elastin. Thus, down-regulation of miR-29 would be predicted to derepress the expression of these mRNAs and enhance the fibrotic response. Indeed, down-regulation of miR-29 with anti-miRs in vitro and in vivo induces the expression of collagens, whereas over-expression of miR-29 in fibroblasts reduces collagen expression. We conclude that miR-29 acts as a regulator of cardiac fibrosis and represents a potential therapeutic target for tissue fibrosis in general.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Defining network topologies that can achieve biochemical adaptation.

            Many signaling systems show adaptation-the ability to reset themselves after responding to a stimulus. We computationally searched all possible three-node enzyme network topologies to identify those that could perform adaptation. Only two major core topologies emerge as robust solutions: a negative feedback loop with a buffering node and an incoherent feedforward loop with a proportioner node. Minimal circuits containing these topologies are, within proper regions of parameter space, sufficient to achieve adaptation. More complex circuits that robustly perform adaptation all contain at least one of these topologies at their core. This analysis yields a design table highlighting a finite set of adaptive circuits. Despite the diversity of possible biochemical networks, it may be common to find that only a finite set of core topologies can execute a particular function. These design rules provide a framework for functionally classifying complex natural networks and a manual for engineering networks. For a video summary of this article, see the PaperFlick file with the Supplemental Data available online.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              mir-29 regulates Mcl-1 protein expression and apoptosis.

              Cellular expression of Mcl-1, an anti-apoptotic Bcl-2 family member, is tightly regulated. Recently, Bcl-2 expression was shown to be regulated by microRNAs, small endogenous RNA molecules that regulate protein expression through sequence-specific interaction with messenger RNA. By analogy, we reasoned that Mcl-1 expression may also be regulated by microRNAs. We chose human immortalized, but non-malignant, H69 cholangiocyte and malignant KMCH cholangiocarcinoma cell lines for these studies, because Mcl-1 is dysregulated in cells with the malignant phenotype. By in silico analysis, we identified a putative target site in the Mcl-1 mRNA for the mir-29 family, and found that mir-29b was highly expressed in cholangiocytes. Interestingly, mir-29b was downregulated in malignant cells, consistent with Mcl-1 protein upregulation. Enforced mir-29b expression reduced Mcl-1 protein expression in KMCH cells. This effect was direct, as mir-29b negatively regulated the expression of an Mcl-1 3' untranslated region (UTR)-based reporter construct. Enforced mir-29b expression reduced Mcl-1 cellular protein levels and sensitized the cancer cells to tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) cytotoxicity. Transfection of non-malignant cells (that express high levels of mir-29) with a locked-nucleic acid antagonist of mir-29b increased Mcl-1 levels and reduced TRAIL-mediated apoptosis. Thus mir-29 is an endogenous regulator of Mcl-1 protein expression, and thereby, apoptosis.
                Bookmark

                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                PLoS ONE
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2014
                15 September 2014
                : 9
                : 9
                : e107262
                Affiliations
                [1 ]Center for Molecular Medicine, University of Connecticut Health Center, Farmington, Connecticut, United States of America
                [2 ]Center on Aging, University of Connecticut Health Center, Farmington, Connecticut, United States of America
                University of Ulm, Germany
                Author notes

                Competing Interests: The authors have declared that no competing interests exist.

                Conceived and designed the experiments: TF AMD SKL NSD. Performed the experiments: TF NSD CBK. Analyzed the data: TF CBK NSD AMD SKL. Wrote the paper: AMD TF SKL NSD CBK.

                Article
                PONE-D-13-50994
                10.1371/journal.pone.0107262
                4164525
                25222202
                158c0c29-b3c4-4c6e-84c7-8ed75e406e1d
                Copyright @ 2014

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 3 December 2013
                : 13 August 2014
                Page count
                Pages: 13
                Funding
                This project was supported by Grant Number AR044877 (to AMD) and AR055143 (to SKL) from the National Institute of Arthritis and Musculoskeletal and Skin Diseases/National Institutes of Health. Its contents are solely the responsibility of the authors and do not necessarily represent the official views of the NIAMS or the NIH. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Biology and Life Sciences
                Anatomy
                Biological Tissue
                Connective Tissue
                Bone
                Musculoskeletal System
                Biochemistry
                Metabolism
                Bone and Mineral Metabolism
                Nucleic Acids
                RNA
                Cell Biology
                Cellular Types
                Animal Cells
                Blood Cells
                White Blood Cells
                Monocytes
                Stem Cells
                Hematopoietic Progenitor Cells
                Bone Marrow Cells
                Immune Cells
                Molecular Cell Biology
                Computational Biology
                Genome Analysis
                Transcriptome Analysis
                Genome Expression Analysis
                Gene Regulatory Networks
                Genetics
                Gene Expression
                Gene Regulation
                Genomics
                Molecular Genetics
                Immunology
                Immune System
                Bone Marrow
                Physiology
                Immune Physiology
                Research and Analysis Methods
                Bioassays and Physiological Analysis
                Microarrays

                Uncategorized
                Uncategorized

                Comments

                Comment on this article