Effect of retinoic acid on the expression and function of AP-1 transcription factor in B16 mouse melanoma cells: role of protein kinase

Retinoic acid (RA) induces differentiation of B16 mouse melanoma cells. This differentiation is accompanied by an increase in protein kinase Ca (PKCα) protein level and selective enrichment in nuclear-associated PKCα. PKC is thought to regulate gene expression through the TPA response element (TRE). This element is specifically recognized by the AP-1 transcription factor composed of jun and fos family members. In this study, I have analyzed the effect of RA on the expression and function of AP-1 in B16 mouse melanoma cells. Transient transfection analysis of B16 cells using leuciferase reporter gene constructs with or without AP-1 elements indicated that RA induced a four- to fivefold increase in AP-1 transcriptional activity in a concentration-dependent manner. RA did not change the expression (mRNA and protein) of jun family members while the expression (mRNA and protein) of c-fos was decreased. In contrast, acute phorbol dibutyrate (PDB) treatment increased c-jun and c-fos expression. Analysis of the mobility shift assay by using an oligonucleotide containing the AP-1 element suggested that two of the complexes were negatively regulated by RA. There was no significant change in the binding of the other complexes by RA. Acute PDB treatment increased the binding where as chronic treatment decreased the binding of this complex. Use of specific antibodies indicated that complexes which were decreased by RA and increased by PDB contained fos protein. Down regulation of PKCα by chronic PDB treatment inhibited both the acute PDB and the RA-induced increase in AP-1 activity. However, the potent and selective PKC inhibitor bisindolylmaleimide inhibited the PDB induced increase in AP-1 activity but had no effect on the RA-induced increase in AP-1 activity. Our results suggest that the role played by PKC in RA induced AP-1 activity is independent of its kinase activity. I also determined the role of nuclear retinoid receptors in RA-induced PKCα expression and AP-1 transcriptional activity by using receptor-specific analogs. Results suggest that RARα and RXR play an important role in RA-mediated effect on PKCα expression and AP-1 activity

Effect of Receptor-Selective Retinoids on Growth and Differentiation Pathways in Mouse Melanoma Cells

Treatment of B16 mouse melanoma cells with all-trans-retinoic acid (ATRA) results in inhibition of cell proliferation and induction of differentiation. Accompanying these events is an induction of retinoic acid receptor β (RARβ) expression, an increase in protein kinase Cα (PKCα) expression, and enhanced activator protein-1 (AP-1) transcriptional activity. These cells express nuclear RARα and RARγ and nuclear retinoid X receptors (RXR) α and β constitutively. We tested the ability of receptor-selective retinoids to induce the biochemical changes found in ATRA-treated melanoma cells and also tested their effectiveness in decreasing anchorage-dependent and -independent growth. The RXR-selective ligand (2E,4E)-6-(5,6,7,8-tetrahydro-3,5,5,8,8-pentamethyl-2-naphthalenyl)-3,7-dimethyl-2,4,6-octatrienoic acid (SR11246) was most effective at inhibiting anchorage-dependent growth, whereas the RARγ-selective ligand 6-[(5,6,7,8-tetrahydro-5,5,8,8-tetramethyl-2-naphthalenyl)(hydroxyimino)methyl]-2-naphthalenecarboxylic acid (SR11254) was most potent at inhibiting anchorage-independent growth. In contrast, 4-(5,6,7,8-tetrahydro-5,5,8,8-tetramethyl-2-naphthalenecarboxamido)-benzoic acid (Am580), an RARα-selective ligand, was the most effective receptor-selective agonist for inducing RARβ mRNA and increasing the amount of PKCα protein. All of the retinoids induced a concentration-dependent increase in AP-1 transcriptional activity, with little difference in effectiveness among the receptor-selective retinoids. A synergistic increase in the amount of PKCα was found when an RAR-selective agonist was combined with an RXR-selective agonist. One possible explanation for this result is that an RXR–RAR heterodimer in which both receptors are liganded is required for maximum expression of this critical component of the ATRA-induced differentiation pathway. Our data suggest that synthetic retinoids can activate different growth and differentiation pathways preferentially in B16 melanoma cells, due, most likely, to their ability to activate a different subset of receptors

Mouse Phenome Database: towards a more FAIR-compliant and TRUST-worthy data repository and tool suite for phenotypes and genotypes.

The Mouse Phenome Database (MPD; https://phenome.jax.org; RRID:SCR_003212), supported by the US National Institutes of Health, is a Biomedical Data Repository listed in the Trans-NIH Biomedical Informatics Coordinating Committee registry. As an increasingly FAIR-compliant and TRUST-worthy data repository, MPD accepts phenotype and genotype data from mouse experiments and curates, organizes, integrates, archives, and distributes those data using community standards. Data are accompanied by rich metadata, including widely used ontologies and detailed protocols. Data are from all over the world and represent genetic, behavioral, morphological, and physiological disease-related characteristics in mice at baseline or those exposed to drugs or other treatments. MPD houses data from over 6000 strains and populations, representing many reproducible strain types and heterogenous populations such as the Diversity Outbred where each mouse is unique but can be genotyped throughout the genome. A suite of analysis tools is available to aggregate, visualize, and analyze these data within and across studies and populations in an increasingly traceable and reproducible manner. We have refined existing resources and developed new tools to continue to provide users with access to consistent, high-quality data that has translational relevance in a modernized infrastructure that enables interaction with a suite of bioinformatics analytic and data services

Mouse phenome database: curated data repository with interactive multi-population and multi-trait analyses.

The Mouse Phenome Database continues to serve as a curated repository and analysis suite for measured attributes of members of diverse mouse populations. The repository includes annotation to community standard ontologies and guidelines, a database of allelic states for 657 mouse strains, a collection of protocols, and analysis tools for flexible, interactive, user directed analyses that increasingly integrates data across traits and populations. The database has grown from its initial focus on a standard set of inbred strains to include heterogeneous mouse populations such as the Diversity Outbred and mapping crosses and well as Collaborative Cross, Hybrid Mouse Diversity Panel, and recombinant inbred strains. Most recently the system has expanded to include data from the International Mouse Phenotyping Consortium. Collectively these data are accessible by API and provided with an interactive tool suite that enables users\u27 persistent selection, storage, and operation on collections of measures. The tool suite allows basic analyses, advanced functions with dynamic visualization including multi-population meta-analysis, multivariate outlier detection, trait pattern matching, correlation analyses and other functions. The data resources and analysis suite provide users a flexible environment in which to explore the basis of phenotypic variation in health and disease across the lifespan