Micro RNA ‐195 controls MICU 1 expression and tumor growth in ovarian cancer
2020; Springer Nature; Volume: 21; Issue: 10 Linguagem: Inglês
10.15252/embr.201948483
ISSN1469-3178
AutoresGeeta Rao, Shailendra Kumar Dhar Dwivedi, Yushan Zhang, Anindya Dey, Khader Shameer, R. Karthik, Subramanya Srikantan, Md. Nazir Hossen, Jonathan D. Wren, Muniswamy Madesh, Joel T. Dudley, Resham Bhattacharya, Priyabrata Mukherjee,
Tópico(s)RNA modifications and cancer
ResumoArticle27 August 2020free access Transparent process MicroRNA-195 controls MICU1 expression and tumor growth in ovarian cancer Geeta Rao Department of Pathology, The University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA Search for more papers by this author Shailendra Kumar Dhar Dwivedi Department of Obstetrics and Gynecology, The University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA Search for more papers by this author Yushan Zhang Department of Pathology, The University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA Search for more papers by this author Anindya Dey Department of Obstetrics and Gynecology, The University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA Search for more papers by this author Khader Shameer Institute of Next Generation Healthcare (INGH), Icahn Institute for Data Science and Genomic Technology, Department of Genetics and Genomic Sciences, Mount Sinai Health System, New York, NY, USA Search for more papers by this author Ramachandran Karthik Department of Medicine, Cardiology Division, University of Texas Health San Antonio, San Antonio, TX, USA Search for more papers by this author Subramanya Srikantan Department of Medicine, Cardiology Division, University of Texas Health San Antonio, San Antonio, TX, USA Search for more papers by this author Md Nazir Hossen Department of Pathology, The University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA Search for more papers by this author Jonathan D Wren orcid.org/0000-0003-2776-3545 Genes & Human Disease Research Program, Oklahoma Medical Research Foundation, Oklahoma City, OK, USA Search for more papers by this author Muniswamy Madesh Department of Medicine, Cardiology Division, University of Texas Health San Antonio, San Antonio, TX, USA Search for more papers by this author Joel T Dudley Institute of Next Generation Healthcare (INGH), Icahn Institute for Data Science and Genomic Technology, Department of Genetics and Genomic Sciences, Mount Sinai Health System, New York, NY, USA Search for more papers by this author Resham Bhattacharya Corresponding Author [email protected] Department of Obstetrics and Gynecology, The University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA Peggy and Charles Stephenson Cancer Center, The University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA Search for more papers by this author Priyabrata Mukherjee Corresponding Author [email protected] orcid.org/0000-0002-0557-0833 Department of Pathology, The University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA Peggy and Charles Stephenson Cancer Center, The University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA Search for more papers by this author Geeta Rao Department of Pathology, The University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA Search for more papers by this author Shailendra Kumar Dhar Dwivedi Department of Obstetrics and Gynecology, The University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA Search for more papers by this author Yushan Zhang Department of Pathology, The University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA Search for more papers by this author Anindya Dey Department of Obstetrics and Gynecology, The University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA Search for more papers by this author Khader Shameer Institute of Next Generation Healthcare (INGH), Icahn Institute for Data Science and Genomic Technology, Department of Genetics and Genomic Sciences, Mount Sinai Health System, New York, NY, USA Search for more papers by this author Ramachandran Karthik Department of Medicine, Cardiology Division, University of Texas Health San Antonio, San Antonio, TX, USA Search for more papers by this author Subramanya Srikantan Department of Medicine, Cardiology Division, University of Texas Health San Antonio, San Antonio, TX, USA Search for more papers by this author Md Nazir Hossen Department of Pathology, The University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA Search for more papers by this author Jonathan D Wren orcid.org/0000-0003-2776-3545 Genes & Human Disease Research Program, Oklahoma Medical Research Foundation, Oklahoma City, OK, USA Search for more papers by this author Muniswamy Madesh Department of Medicine, Cardiology Division, University of Texas Health San Antonio, San Antonio, TX, USA Search for more papers by this author Joel T Dudley Institute of Next Generation Healthcare (INGH), Icahn Institute for Data Science and Genomic Technology, Department of Genetics and Genomic Sciences, Mount Sinai Health System, New York, NY, USA Search for more papers by this author Resham Bhattacharya Corresponding Author [email protected] Department of Obstetrics and Gynecology, The University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA Peggy and Charles Stephenson Cancer Center, The University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA Search for more papers by this author Priyabrata Mukherjee Corresponding Author [email protected] orcid.org/0000-0002-0557-0833 Department of Pathology, The University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA Peggy and Charles Stephenson Cancer Center, The University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA Search for more papers by this author Author Information Geeta Rao1,‡, Shailendra Kumar Dhar Dwivedi2,‡, Yushan Zhang1, Anindya Dey2, Khader Shameer3, Ramachandran Karthik4, Subramanya Srikantan4, Md Nazir Hossen1, Jonathan D Wren5, Muniswamy Madesh4, Joel T Dudley3, Resham Bhattacharya *,2,6 and Priyabrata Mukherjee *,1,6 1Department of Pathology, The University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA 2Department of Obstetrics and Gynecology, The University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA 3Institute of Next Generation Healthcare (INGH), Icahn Institute for Data Science and Genomic Technology, Department of Genetics and Genomic Sciences, Mount Sinai Health System, New York, NY, USA 4Department of Medicine, Cardiology Division, University of Texas Health San Antonio, San Antonio, TX, USA 5Genes & Human Disease Research Program, Oklahoma Medical Research Foundation, Oklahoma City, OK, USA 6Peggy and Charles Stephenson Cancer Center, The University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA ‡These authors contributed equally to this work *Corresponding author. Tel: +1 405 271 2377; E-mail: [email protected] *Corresponding author (lead contact). Tel: +1 405 271 1133; E-mail: [email protected] EMBO Rep (2020)21:e48483https://doi.org/10.15252/embr.201948483 PDFDownload PDF of article text and main figures. Peer ReviewDownload a summary of the editorial decision process including editorial decision letters, reviewer comments and author responses to feedback. ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InMendeleyWechatReddit Figures & Info Abstract MICU1 is a mitochondrial inner membrane protein that inhibits mitochondrial calcium entry; elevated MICU1 expression is characteristic of many cancers, including ovarian cancer. MICU1 induces both glycolysis and chemoresistance and is associated with poor clinical outcomes. However, there are currently no available interventions to normalize aberrant MICU1 expression. Here, we demonstrate that microRNA-195-5p (miR-195) directly targets the 3′ UTR of the MICU1 mRNA and represses MICU1 expression. Additionally, miR-195 is under-expressed in ovarian cancer cell lines, and restoring miR-195 expression reestablishes native MICU1 levels and the associated phenotypes. Stable expression of miR-195 in a human xenograft model of ovarian cancer significantly reduces tumor growth, increases tumor doubling times, and enhances overall survival. In conclusion, miR-195 controls MICU1 levels in ovarian cancer and could be exploited to normalize aberrant MICU1 expression, thus reversing both glycolysis and chemoresistance and consequently improving patient outcomes. Synopsis miR-195 represses MICU1 expression in ovarian cancer, thus reversing both glycolysis and chemoresistance and consequently improving patient survival. miR-195 might thus be a potential tool for ovarian cancer therapy. MICU1 expression is characteristic of many cancers and is associated with poor clinical outcomes. miR-195 inhibits MICU1 expression. Restoring miR-195 expression in ovarian cancer cell lines reestablishes native MICU1 expression levels and the associated phenotypes. miR-195 could be a potential therapeutic tool that could help translating MICU1-targeted therapy into clinical care. Introduction Metabolic reprogramming is characteristic of cancer cells, which generally shift toward aerobic glycolysis in order to meet the high energy demands of their uncontrolled proliferation (Lunt & Vander Heiden, 2011; Ward & Thompson, 2012). This shift to glycolysis is recognized as an important determinant of both tumor growth and chemoresistance in various malignancies (Ganapathy-Kanniappan & Geschwind, 2013; Morandi & Indraccolo, 2017). As a result, glycolytic pathways represent viable targets for therapeutic intervention, and several anti-glycolytic agents, targeting different enzymes, have been used to sensitize tumor cells to therapy (Fanciulli et al, 2000; Xu et al, 2005; Hsu & Sabatini, 2008; Dang et al, 2011; Birsoy et al, 2012; Dang, 2012; Wagner et al, 2015). Unfortunately, however, the ubiquity of enzymes involved in glycolysis results in systemic toxicity when broad-spectrum anti-glycolytic agents are used, which limits their utility (Ganapathy-Kanniappan & Geschwind, 2013). Thus, while inhibition of glycolysis remains a promising strategy for anti-cancer interventions, better-targeted treatment options are required before it can have a significant clinical impact. Mitochondrial calcium uptake 1 (MICU1) is a protein on the inner mitochondrial membrane that interacts with the mitochondrial calcium uniporter (MCU), a pore-forming unit to modulate mitochondrial Ca2+ (mCa2+) uptake in response to cytosolic Ca2+ concentration [Ca2+]c (Mishra et al, 2017; Paupe & Prudent, 2018). Disulfide-linked hetero-oligomerization of MICU1 and MICU2 regulates MCU activity depending on the cytosolic Ca2+ levels. MICU1 acts both as an activator or inhibitor of m(Ca2+) uptake (Patron et al, 2014; Matesanz-Isabel et al, 2016). Mallilankaraman et al (2012b) have demonstrated that the mitochondrial protein MICU1 is required to maintain normal mCa2+ levels under basal conditions (Nemani et al, 2020). In its absence, mitochondria become constitutively loaded with Ca2+, triggering excessive reactive oxygen species (ROS) generation, and sensitivity to apoptotic stress. MICU1 interacts with the uniporter pore-forming subunit MCU and sets a Ca2+ threshold for mCa2+ uptake without affecting the kinetic properties of MCU-mediated Ca2+ uptake (Mallilankaraman et al, 2012b). Thus, MICU1 is a gatekeeper of MCU-mediated mCa2+ uptake that is essential to prevent mCa2+ overload and associated stress. We recently demonstrated that overexpression of MICU1 in ovarian cancer cells induced both glycolysis and chemoresistance and also showed that overexpression of MICU1 in ovarian cancer patients correlated with poor overall survival (Chakraborty et al, 2017). Recent reports show that both intracellular Ca2+ homeostasis and MICU1 expression are altered in a range of cancer cells and also contribute to poor prognosis in cancer patients (Mallilankaraman et al, 2012b; Hall et al, 2014; Chakraborty et al, 2017; Monteith et al, 2017). Thus, Ca2+ homeostasis and, more specifically, MICU1 represent potential targets for interventional strategies to address the glycolytic status of cancer cells. Targeting of MICU1 would overcome the systemic toxicity associated with the use of broad-spectrum inhibitors by exploiting its overexpression in cancer cells compared to normal cells. Understanding how the expression of MICU1 is regulated in cancer cells is an important step in developing strategies to suppress its activities and thus reverse glycolysis and sensitize drug-resistant cells to therapy. However, apart from regulation by FOXD1 during development and AKT-mediated phosphorylation in tumor models (Shanmughapriya et al, 2018; Marchi et al, 2019a), regulation of MICU1 is not well understood. MicroRNAs (miRNAs) are small evolutionarily conserved single-stranded noncoding RNAs (19–25 nucleotides in length) that post-transcriptionally regulate the translation and stability of mRNAs. miRNAs are implicated in many cellular processes including cell cycle, apoptosis, autophagy, stemness, differentiation, inflammation, drug resistance, transformation, and migration, as well as Ca2+ homeostasis and oxidative phosphorylation (Ambros, 2004; Iorio & Croce, 2012; Hayes et al, 2014). Additionally, miRNAs are frequently deregulated in cancer and play a key role in the regulation of cancer-associated glycolytic pathways (Dang, 2010; Gao et al, 2012; Gomez de Cedron & Ramirez de Molina, 2016). miR-195 has been shown to be a tumor suppressor in several cancer models including breast (Singh et al, 2015), hepatocellular (Yang et al, 2014), gastric (Deng et al, 2013), and lung cancers (Yu et al, 2018). Additionally, serum levels of miR-195 are a diagnostic and prognostic marker for osteosarcoma (Cai et al, 2015), and downregulation of miR-195 is associated with both lymph node metastasis and poor prognosis in colorectal cancer patients (Wang et al, 2012). However, little is known about the role of miR-195 in regulating MICU1 expression in ovarian cancer. Herein, we show that miR-195 regulates expression of MICU1 in ovarian cancer. Normalizing MICU1 expression by ectopic expression of miR-195 increases mCa2+ uptake, reverses glycolysis, inhibits tumor growth, and increases overall survival in a human xenograft model of ovarian cancer. With the advent of therapeutic miRNAs, some of which are advancing from bench to clinic (Rupaimoole & Slack, 2017), our findings provide an opportunity to exploit miR-195 as a potential therapeutic option to normalize MICU1 expression thereby reversing glycolysis and enhancing therapeutic sensitivity, and ultimately leading to improved patient outcomes. Results miR-195 regulates expression of MICU1 As an initial step in identifying miRNAs as potential regulators of MICU1, we used the web-interface of miRWalk2 (Dweep & Gretz, 2015). miRWalk2 is a software tool that predicts miRNA targets utilizing twelve different algorithms (miRWalk, Microt4, miRanda, mirbridge, miRDB, miRMap, miRNAMap, Pictar2, PITA, RNA22, RNAhybrid, and Targetscan) and predicted a significant number of miRNAs which could potentially target MICU1. Those miRNAs predicted to target MICU1 by more than nine prediction methods are shown in Table 1 and those predicted to bind the 3′ UTR of MICU1 with a minimum seed length of 7 bp and P < 0.05 by 12 different programs are shown in Table EV1. miRNAs of the miR-15 family (namely miR-15a/b, miR-16, miR-195, and miR-497) predominated among those predicted to interact at the MICU1 3′ UTR positions (Table 1). Several members of this miR-15 family, including miR-15a/b, miR-16, miR-195, and miR-497, have demonstrable associations with ovarian cancer (Xu et al, 2015; Dwivedi et al, 2016). Based on bioinformatics analysis, we selected two representative members of the miR-15 family, miR-15a-5p (miR-15a), and miR-195-5p (miR-195) and evaluated their effect on MICU1 expression. Since miRNAs modulate gene expression by either modulating mRNA stability or by inhibiting translation, we determined target protein abundance by immunoblotting. We assayed two ovarian cancer cell lines transfected with either a non-target miR-control (miR-CTL) or one of the target miRNAs, miR-15a, or miR-195. While miR-195 significantly decreased the expression of MICU1 in both cell lines, miR-15a had no effect (Figs 1A and EV1A). However, miR-15a did reduce expression of its established targets BMI1 and BCL2 (Cimmino et al, 2005; Dwivedi et al, 2016), thereby demonstrating that it was ectopically expressed and active in the studied cell lines (Figs 1A and EV1A). Similarly, miR-195 decreased the expression of its known target BCL2 (Singh & Saini, 2012) indicating the specificity of targeting in these cells (Figs 1A and EV1A). miR-195-mediated regulation of MICU1 was further confirmed in OVCAR4, CP20, and OVSAHO cell lines; efficient transfection of miR-195 and reduced expression of MICU1 in these cells were, respectively, demonstrated by RT–qPCR and immunoblotting (Fig EV1B and C). These data conclusively showed that the MICU1 mRNA was targeted by miR-195 but not by miR-15a. Table 1. miRNAs predicted to bind the 3′ end of MICU1 with a minimum seed length of 7, by different prediction methods miRNA miRWalk Microt4 miRanda mirbridge miRDB miRMap Pictar2 PITA RNA22 RNAhybrid Targetscan SUM hsa-miR-195-5p Y Y Y N N Y Y Y Y Y Y 9 hsa-miR-15a-5p Y Y Y N N Y Y Y Y Y Y 9 hsa-miR-15b-5p Y Y Y N N Y Y Y Y Y Y 9 hsa-miR-424-5p Y Y Y N N Y Y Y Y Y Y 9 hsa-miR-497-5p Y Y Y N N Y Y Y Y Y Y 9 hsa-miR-1206 Y Y Y N Y Y N Y Y Y Y 9 hsa-miR-589-5p Y Y Y N Y Y N Y Y Y Y 9 #of predictions for MICU1 2,794 429 1,649 2 69 4,032 48 222 409 14,632 2,571 Figure 1. miR-195 and MICU1 levels are inversely related in ovarian cancer cell lines A. CP20 and OVCAR4 cells were transfected with either non-target miRNA control (miR-CTL), miR-15a, or miR-195. Seventy-two hours following transfection, cells were lysed and immunoblotted for detection of MICU1, BMI1, BCL2, and MFN2. GAPDH and VDAC were used as loading control. B. miR-195 expression in FTE188 and ovarian cell lines as determined by RT–qPCR normalized with U6. Data are mean ± SD, n = 3 (biological repeats). *P < 0.05, Student's t-test. C. Expression of MICU1 in FTE188 and various ovarian cell lines as determined by immunoblotting. Actin is used as the loading control. D. Anti-miR-195 was transfected in the FTE188 cell line, level of miR-195 was measured using RT–qPCR (left) and MICU1 levels were measured using immunoblotting (right). Data are mean ± SD, n = 3 (biological repeats). *P < 0.05, Student's t-test. Download figure Download PowerPoint Click here to expand this figure. Figure EV1. miR-195 regulates MICU1 expression A. Graph showing densitometric quantification of Western blot bands for CP20 and OVCAR4 cells in Fig 1A (n = 3, biological repeats mean ± SE) normalized with GAPDH. *P < 0.05, Student's t-test. B. Ovarian cancer cells were transfected with either non-target microRNA (miR-CTL) or miR-195. Total RNA was isolated and miR-195 levels normalized with U6 were plotted. Data are mean ± SD, n = 3 biological repeats, *P < 0.05, Student's t-test. C. MICU1 expression in cells transfected with miR-CTL and miR-195. β-Actin was used as the loading control. D. Graph showing densitometric quantification of Western blot bands for ovarian cancer cells in Fig 1C. Values are represented as mean fold change ± SD, n = 3 biological repeats, *P < 0.05, Student's t-test. Download figure Download PowerPoint Based on these findings, we next determined the relationship between the endogenous cellular expression of miR-195 and MICU1 levels. First, we used RT–qPCR to determine miR-195 levels; compared to non-malignant fallopian tube epithelial cells (FTE188), the expression of miR-195 was significantly lower in seven different ovarian cancer cell lines (Fig 1B). We then determined MICU1 protein levels in the same cell lines; in six of the ovarian cancer cell lines, MICU1 levels were significantly higher than in the non-malignant FTE188 cells (Figs 1C and EV1D). In TYK-nu cells, MICU1 levels were similar to those in FTE188 cells, suggesting complexity in MICU1 regulation in addition to that mediated by miR-195 in these particular cells (Figs 1C and EV1D). However, in general, MICU1 protein levels were inversely related to miR-195 expression in ovarian cancer cells. Targeting of endogenous MICU1 by miR-195 was confirmed by ectopic expression of anti-miR-195 in FTE188 cells, which resulted in increased MICU1 levels. The targeting of miR-195 through anti-miR-195 in FTE188 cells was confirmed using RT–qPCR (Fig 1D). Taken together these data indicate that miR-195 targets the MICU1 mRNA thereby reducing expression of MICU1. Expression of miR-195 regulates cancer-associated cellular phenotypes: clonal growth, invasion, and migration Having demonstrated that miR-195 regulates expression of MICU1, we next sought to determine the role of miR-195 in regulating several cellular phenotypes responsible for aggressiveness in cancer, specifically clonal growth, invasion, and migration. Three cell lines were selected for these experiments: OVCAR4 and OVSAHO for their characteristic miR-195 and MICU1 expression levels, as well as CP20 for its cisplatin-resistant phenotype. OVCAR4, OVSAHO, and CP20 cells were transfected with miR-195; efficient transfection was confirmed using RTqPCR (Fig EV2). Compared to the controls, a significant decrease in clonal growth occurred in all the miR-195-transfected cells. The anchorage-dependent clonal growth of OVCAR4, CP20, and OVSAHO was decreased, respectively, by 53, 42, and 36% and in the anchorage-independent assay, the clonal growth of these cells was respectively reduced by of 55, 52, and 42%. (Fig 2A and B). Having demonstrated a role for miR-195 in regulating clonal growth, we next assessed the significance of miR-195 ectopic expression on the migratory and invasive potential of CP20 and OVCAR4 cells. In a Boyden chamber-based migration and invasion assay, miR-195-transfected OVCAR4 and CP20 cells had decreased migration by 60 and 67%, (Fig 2C) and invasion by 64 and 67%, respectively (Fig 2D), when compared to control. To confirm that the decrease in the migratory and invasive potential of ovarian cancer cells was mediated through MICU1, we ectopically expressed a miR-195 non-responsive MICU1 construct (i.e., pLYS1-MICU1-Flag, with only the MICU1 coding sequence and thus not a target for miR-195) in miR-195-transfected cells. Ectopic expression of MICU1 in miR-195-transfected cells rescued the migratory and invasive potential of these cells to the levels of non-targeted miR-control-transfected cells (Fig 2C and D). Thus, re-expression of miR-195 inhibits clonal growth as well as cellular migration and invasion, all of which are hallmarks of cancer progression (Hanahan & Weinberg, 2011), and this is mediated through MICU1. Click here to expand this figure. Figure EV2. Quantitation of microRNA expressionOvarian cancer cells were transfected with either non-target microRNA (miR-CTL) or miR-195. Total RNA was isolated and miR-195 levels normalized with U6 were plotted. Data are mean ± SD, n = 3 biological repeats, *P < 0.05, Student's t-test. Download figure Download PowerPoint Figure 2. Ectopic expression of miR-195 suppresses ovarian cancer clonal growth, migration, and invasion A, B. CP20, OVCAR4, and OVSAHO cells were transfected with non-target microRNA control (miR-CTL) or miR-195; 24 h post-transfection, cells were recounted and plated as single cells for anchorage-dependent (A) or anchorage-independent (B) clonal growth. After 10 (CP20) or 14 (OVCAR4 and OVSAHO) days, colonies were quantified using an Optronix GelCount colony counter. The left panel shows representative images of the colonies and the right panel depicts a graphical representation of data presented as percent clonal growth relative to the control (miR-CTL). C. Migration of miR-CTL, miR-195, and miR-195 + MICU1 (pLYS1-MICU1-Flag) transfected cells, toward serum gradient was examined and the number of cells per field was counted. The left panel shows representative images and the right panel depicts a graphical representation of relative migration compared to the control (miR-CTL). D. Invasion of miR-CTL, miR-195, and miR-195 + MICU1 cells through fibronectin-coated filters was examined using Boyden chamber and number of cells per field was counted. Left panel shows representative images and the right panel depicts a graphical representation of relative invasion compared to the control (miR-CTL). Data information: Data are mean ± SD n = 3 (biological repeats). *P < 0.05 when comparing with miR-CTL, #P < 0.05 when comparing with miR-195 by Student's t-test. Scale bar = 0.1 mm. Download figure Download PowerPoint miR-195 targets the 3′ UTR of MICU1 Having demonstrated that miR-195 regulates expression of MICU1, we next sought to determine whether this regulation was mediated by a direct interaction between miR-195 and the MICU1 mRNA. The putative interaction site of miR-195 on the MICU1 3′ UTR was mapped using TargetScan (Fig 3A), and site-directed mutagenesis was used to delete this putative binding site from the luciferase construct. The MICU1 3′ UTR luciferase construct was used to perform reporter assays and showed that re-expression of miR-195 dose-dependently decreased MICU1 3′ UTR luciferase activity while no change was noted with a non-target miRNA control (Fig 3B). Deletion of the proposed miR-195 interaction site on the MICU1 3′ UTR almost completely reversed miR-195-mediated inhibition of luciferase activity (Fig 3B). Collectively, these results show that miR-195 directly targets the MICU1 3′ UTR. Figure 3. MICU1 is a direct target of miR-195 A. The miR-195 binding site as predicted by TargetScan. B. MICU1 3′ UTR in LightSwitch™ 3′ UTR Reporter Vector (wild type or miR-195 binding site deleted) was co-transfected with either non-target miR-control (miR-CTL) or different concentrations of miR-195. After 24-h transfection, luciferase (Renilla) activity was measured. Relative light units (RLU) compared to miR-CTL were plotted. Data are mean ± SD n = 3 (biological repeats). *P < 0.05, Student's t-test. C, D. CP20 cells were transfected as indicated, and 48 h post-transfection, 4 × 106 cells were permeabilized, and extra-mitochondrial calcium ([Ca2+]out) clearance was measured, representative traces of [Ca2+]out- clearance in miR-CTL and miR-195 or control siRNA (siCTL) and siMICU1 transfected cells. [Ca2+]out pulses and FCCP were delivered as indicated. E. Bar graph illustrating the number of Ca2+ pulses handled by control miR, miR-195, siCTL, and siMICU1 transfected cells. Mean ± SEM; n = 3–4 (biological repeats). *P < 0.05, Student's t-test. F. Representative [Ca2+](m) traces after addition of FCCP (10 μM) in permeabilized CP20 cells transfected with non-target miR-CTL or miR-195. G. Quantification of resting matrix [Ca2+](m) after addition of FCCP. n = 5 (biological repeats) *P < 0.05, Student's t-test. H. Representative traces of mitochondrial membrane potential (∆Ψμ) in CP20 cells transfected with miR-CTL or miR-195. I. Quantification of relative ∆Ψμ (n = 5, biological repeats). J. Intracellular lactate was measured in miR-CTL, miR-195, siCTL, and siMICU1 expressing OVCAR4, CP20, and OVSAHO cells. n = 3, biological repeats *P < 0.05, Student's t-test. K, L. miR-CTL, miR-195, or miR-195 + pLYS1-MICU1-Flag transfected cells were stained with MitoSOX Red, and mitochondrial ROS levels were determined by flow cytometry. The histogram shows representative staining and bar graph (right) shows results of three independent experiments. Mean ± SEM; n = 3, biological repeats. *P < 0.05 when comparing with miR-CTL, #P < 0.05 when comparing with miR-195 by Student's t-test. Download figure Download PowerPoint MICU1 mediates the effects of miR-195 As discussed above, MICU1 is an important regulator of intracellular Ca2+ homeostasis. Mallilankaraman et al (2012b) and Csordas et al (2013) revealed the importance of MICU1 in preserving normal mCa2+ under basal conditions. When MICU1 levels are high, as in cancer, mitochondrial uptake of Ca2+ is inhibited (Chakraborty et al, 2017; Marchi et al, 2019a,b). Since miR-195 targets the 3′ UTR of the MICU1 gene thus reducing MICU1 levels, we sought to determine the effect of the miR-195 expression on mCa2+ homeostasis. In theory, re-expression of miR-195 will normalize MICU1 expression in ovarian cancer cells and thus will promote Ca2+ entry into the mitochondria (Mallilankaraman et al, 2012b). We determined mCa2+ uptake capacity in miR-195 re-expressing CP-20 cells that were digitonin-permeabilized. The cells were bathed in an intracellular-like medium containing Fura-FF to monitor the Ca2+ levels in the medium (Mallilankaraman et al, 2012a). Starting at 300 s, boluses of Ca2+ were added at 50-s intervals; in response to repeated Ca2+ administration, cytosolic Ca2+ was cleared and mitochondrial uptake was increased. Compared to the control, CP20 cells expressing miR-195 demonstrated increased mCa2+ (Fig 3C and E). Having shown that miR-195 increased mCa2+ uptake in ovarian cancer cells, we next sought to determine if the silencing of MICU1 achieved the same result. We used siRNA to silence MICU1 in CP20 cells and showed that lack of MICU1 increased mCa2+ uptake (Fig 3D and E). Efficacy of MICU1 inhibition by miR-195 and siMICU1 is shown in Fig EV3. It is noteworthy that both miR-195 overexpression and siRNA-mediated knockdown of MICU1 enhanced mitochondrial Ca2+ retention capacity (Fig 3C–E). Although the extra-mitochondrial Ca2+ pulses in MICU1 siRNA-treated condition were stacking after 9 pulses, the mitochondrial Ca2+ uptake rate (1/τ) was measurable (Control = −0.193; MICU1 siRNA = 0.03171), but it was absent in control cells suggesting that MICU1 silencing enhances mitochondrial Ca2+ retention capacity. These data further reinforce that miR-195 acts via its effect on MICU1 to regulate
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