Effects of gene therapy on muscle 18S rRNA expression in mouse model of ALS
© Osta et al; licensee BioMed Central Ltd. 2010
Received: 7 October 2010
Accepted: 2 November 2010
Published: 2 November 2010
The efficiency of gene therapy experiments is frequently evaluated by measuring the impact of the treatment on the expression of genes of interest by quantitative real time PCR (qRT-PCR) and by normalizing these values to those of housekeeping (HK) genes constitutively expressed throughout the experiment. The objective of this work was to study the effects of muscle gene therapy on the expression of 18 S ribosomal RNA (Rn18S), a commonly used HK gene.
Mouse model of motor neuron disease (SOD1-G93A) was injected intramuscularly with Brain-derived neurotrophic factor (BDNF-TTC) encoding or control naked DNA plasmids. qRT-PCR expression analysis was performed for BDNF and HK genes Rn18 S, glyceraldehyde-3-phosphate dehydrogenase (Gapdh) and β-actin (Actb). We report that elevated BDNF expression in the injected muscle was accompanied with increased Rn18 S expression, whereas Gapdh and Actb were not affected. Increased "ribosomal output" upon BDNF stimulation was supported by increased steady-state levels of ribosomal protein mRNAs.
Ribosomal RNA transcription may be directly stimulated by administration of trophic factors. Caution should be taken in using Rn18 S as a HK gene in experiments where muscle metabolism is likely to be altered by therapeutic intervention.
Quantitative Real Time PCR (qRT-PCR) is an increasingly popular method for the quantitative analysis of gene expression. Despite its high sensitivity, accuracy and wide dynamic range that favour qRT-PCR in gene expression studies, some factors exist that must be taken into account as a possible source of error . A critical element in experimental design is the strategy to quantify the input template cDNA in the sample. Appropriate choice of internal references has been previously shown to be crucial for correct interpretation of expression data [1, 2] and bioinformatic approaches have been developed to increase the accuracy of normalization [3–5]. Although numerous reference genes are currently used for normalization purposes, the most commonly used are still 18 S ribosomal RNA (Rn18S), β-actin (Actb) and glyceraldehyde-3-phosphate dehydrogenase (Gapdh) due to their ubiquitous and relatively high expression levels . Actb and Gapdh are mRNA-encoding housekeeping genes (HKs), and have been claimed to be either suitable or unsuitable as reference genes depending on tissue or experimental conditions used [6–10]. On the other hand, Rn18 S encodes ribosomal RNA (rRNA). Although rRNAs are highly abundant and, therefore, untypical RNA-species in the cell, Rn18 S has been described to maintain stability under some conditions that may result in altered housekeeping mRNA levels . Rn18 S has been regarded as appropriate endogenous control in experiments including cell culture [11, 12] and tissue biopsies .
In metabolically active cells rRNA genes are transcribed efficiently to keep up with high demand for protein synthesis machinery. Traditional northern RNA quantification has favoured Rn18 S because of its conveniently high expression level which can dramatically reduce the time required for the autoradiographic detection. However, when qRT-PCR with relative quantification is used, high abundance of Rn18 S compared with target mRNA transcript becomes a hindrance as it complicates accurate subtraction of the baseline value in real-time qRT-PCR data analysis . As opposed to mRNA genes (such as Actb and Gapdh) that are transcribed by RNA polymerase II (Pol II), rRNA transcription is dependent on RNA polymerase I (Pol I) devoted exclusively to this task. Pol I activity is a crucial determinant for production of ribosomes needed for growth and cell proliferation [14, 15]. Potential differences between regulatory networks modifying transcriptional activity of Pol I and Pol II is a major criticism for using rRNA genes for normalization. Availability of extracellular stimulatory factors (such as nutrition or growth factors), intracellular conditions (such as mutations), and drugs may alter mRNA and rRNA pools in dissimilar manner, or even to opposite directions [16, 17]. Indeed, the hallmark of cancer is augmented rRNA transcription  and Rn18 S normalization has been shown to be potentially confounding in gene expression analysis of rat mammary tumors . Pol I is a known target for growth-promoting signals such as epidermal growth factor  and insulin-like growth factor 1 . This may well influence rRNA expression levels in cells where exogenous genes have been introduced to provide gene therapy, especially when introduced molecule stimulates anabolic pathways of the target cells.
Amyotrophic lateral sclerosis (ALS) is a devastating adult-onset motor neuron disease characterized by a progressive degeneration of motor neurons, skeletal muscle atrophy, paralysis and death. A well described mouse model of ALS, an overexpresser of human superoxide dismutase 1 (SOD1) carrying glycine to alanine substitution at residue 93 (SOD1-G93A) , recapitulates many features observed in human patients. Our previous work has established that the symptoms of the disease in this model can be alleviated with intramuscular injection of either recombinant proteins or "naked DNA" plasmids encoding neurotrophic factors, such as Glial cell-derived neurotrophic factor (GDNF)  or Brain-derived neurotrophic factor (BDNF), coupled with atoxic C-terminal fragment of tetanus toxin (TTC) to enhance retrograde transport from muscle to neurons . Besides delaying a functional decline and lethality of SOD1-G93A mice, these therapies activate Akt kinase by increasing PI3K-dependent signalling that promotes growth and survival .
The aim of the present study was to evaluate the effect of an exogenous BDNF-TTC fusion construct expression in vivo on the levels of Actb, Gapdh and Rn18 S in transfected tissue and, therefore, validation of these HK genes as an endogenous reference in such gene therapy studies.
Results and discussion
Briefly, BDNF-TTC-encoding (pcDNA3.1-pCMV-BDNF-TTC) or non-coding control (pcDNA3.1-pCMV) naked DNA plasmids were each injected intramuscularly into the quadriceps of ten SOD1G93A transgenic mice at 60 days of age (asymptomatic stage). Each muscle was injected with total 100 μg of plasmid in physiological saline, in two 50 μL injections. Ten days or fifty days after injections (at ages of 70 days and 110 days, respectively) the animals were anaesthetized with pentobarbital (50 mg/kg) and sacrificed by cervical dislocation. Quadriceps muscles were snap-frozen in liquid nitrogen and stored at -70°C. All experimental procedures were approved by Ethics Committee of our institution and followed the international guidelines for the use of laboratory animals. For gene expression analysis, total RNA extracted from frozen muscle tissue of each animal was DNase treated and retrotranscribed, and the cDNA was used for the expression analysis of plasmid-derived BDNF (BDNF-TTC) as well as that of HK genes Rn18S, Gapdh and Actb (see full details in additional file 1). Relative expression levels of BDNF and Rn18 S were normalized with the geometric mean of those of Actb and Gapdh . For the expression stability analysis of Actb and Gapdh, the transcripts were normalized with each other. Relative gene expression compared with control plasmid-injected animals was determined using the 2-ΔΔCT method . Student's t-test was used and statistical differences were considered significant at P ≤ 0.05 (Statistica 5.0).
Increasing evidence indicates involvement of rRNA suppression during pathogenesis of motor neuron disease. rRNA synthesis takes place in the nucleoli, which are the sites of ribosome biogenesis in the eukaryotic cells, and perturbation of nucleolar function leads to neurodegeneration in mice . Haploinsufficiency of angiogenin (ANG) has been linked to the pathogenesis of ALS, and ANG is known to stimulate rRNA transcription by direct transcriptional regulation as well as to activate synthesis of ribosomal proteins by stimulation of Akt/PI3K survival pathway . We propose that the increase in the Rn18 S transcript levels reflects a stimulus of the translation machinery occurring in the muscles and/or neuromuscular junctions of the BDNF-TTC treated SOD1-G93A animals. BDNF treatment can activate Akt/PI3K  and ERK1/2  signalling pathways, which are, respectively, required for stimulation of Pol I-dependent rRNA transcription upon IGF-1 treament  and EGF treament . BDNF has been recently shown to potentiate in vivo muscle regeneration after toxin-induced damage, and this activity may derive from its stimulatory effect on function of muscle stem cells, satellite cells . Although we did not specifically study satellite cells here, it seems possible that cell cycle activation in this normally quiescent supply of muscle progenitors may at least partially contribute to the observed induction in Rn18S. Indeed, transcription of both rRNA  and ribosomal protein mRNAs  is increased in proliferating myoblasts compared with mature myofibers. Our results are also in agreement with those reported earlier  where considerable variation in Rn18 S expression in skeletal muscle was observed in response to intense exercise which is known to activate metabolism and differentiation status of myogenic and mature muscular cells.
Discrepancies exist about the utility of Rn18 S in normalization in other types of cells. In activated lymphocytes Rn18 S transcript levels remain relatively stable compared to unstimulated ones . Similarly, constitutive expression of Rn18 S was described in myeloid leukaemia cell lines when stimulated to differentiate although, upon stimulation of apoptosis using the same cell lines, Rn18 S was found to be unreliable reference gene . Thus, it seems that the usefulness of Rn18 S for normalization purposes depends on both cell type and experimental intervention that tissue is subjected to. However, as discussed earlier, Pol I and Pol II transcription are subjects to differential regulation, which is the primary concern in using rRNAs for mRNA normalization. Data presented here and by others  indicate instability of Rn18 S under two conditions that stimulate muscle cell activity, namely gene therapy and exercise. Therefore, qRT-PCR data normalization using Rn18 S in muscle tissue under regenerative treatment or exercise is clearly not recommended.
Molecules that provide trophic support to the atrophic muscle are under vigorous investigation since they are predicted to be beneficial in patients suffering from muscular or neuromuscular diseases, and may improve the recovery from traumatic damage [38, 39]. Therefore, poor performance of Rn18 S as a HK gene needs a special recognition in the regenerative therapy field, and the same may well apply to the mRNAs encoding components of the translation machinery. On the positive note, the results presented here potentially reveal the utility of increased Rn18 S transcript levels as a surrogate marker to measure the effectiveness of therapeutic interventions in muscular and neuromuscular diseases.
This study was supported by the grant of CAJA NAVARRA: "Tú eliges, tu decides", PI071133 from the Fondo de Investigación Sanitaria of Spain, PAMER Instituto Aragonés de Ciencias de la Salud (PIPAMER 08/08) and Action COST-B30 of the EC.
- Huggett J, Dheda K, Bustin S, Zumla A: Real-time RT-PCR normalisation; strategies and considerations. Genes Immun. 2005, 6: 279-284. 10.1038/sj.gene.6364190.PubMedView ArticleGoogle Scholar
- Calvo AC, Moreno-Igoa M, Manzano R, Ordovas L, Yague G, Olivan S, Munoz MJ, Zaragoza P, Osta R: Determination of protein and RNA expression levels of common housekeeping genes in a mouse model of neurodegeneration. Proteomics. 2008, 8: 4338-4343. 10.1002/pmic.200701091.PubMedView ArticleGoogle Scholar
- Andersen CL, Jensen JL, Orntoft TF: Normalization of real-time quantitative reverse transcription-PCR data: a model-based variance estimation approach to identify genes suited for normalization, applied to bladder and colon cancer data sets. Cancer Res. 2004, 64: 5245-5250. 10.1158/0008-5472.CAN-04-0496.PubMedView ArticleGoogle Scholar
- de Jonge HJ, Fehrmann RS, de Bont ES, Hofstra RM, Gerbens F, Kamps WA, de Vries EG, van der Zee AG, te Meerman GJ, ter Elst A: Evidence based selection of housekeeping genes. PLoS One. 2007, 2: e898-10.1371/journal.pone.0000898.PubMed CentralPubMedView ArticleGoogle Scholar
- Vandesompele J, De Preter K, Pattyn F, Poppe B, Van Roy N, De Paepe A, Speleman F: Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes. Genome Biol. 2002, 3: RESEARCH0034-10.1186/gb-2002-3-7-research0034.PubMed CentralPubMedView ArticleGoogle Scholar
- Suzuki T, Higgins PJ, Crawford DR: Control selection for RNA quantitation. Biotechniques. 2000, 29: 332-337.PubMedGoogle Scholar
- Bas A, Forsberg G, Hammarstrom S, Hammarstrom ML: Utility of the housekeeping genes 18 S rRNA, beta-actin and glyceraldehyde-3-phosphate-dehydrogenase for normalization in real-time quantitative reverse transcriptase-polymerase chain reaction analysis of gene expression in human T lymphocytes. Scand J Immunol. 2004, 59: 566-573. 10.1111/j.0300-9475.2004.01440.x.PubMedView ArticleGoogle Scholar
- Foldager CB, Munir S, Ulrik-Vinther M, Soballe K, Bunger C, Lind M: Validation of suitable house keeping genes for hypoxia-cultured human chondrocytes. BMC Mol Biol. 2009, 10: 94-10.1186/1471-2199-10-94.PubMed CentralPubMedView ArticleGoogle Scholar
- Perez R, Tupac-Yupanqui I, Dunner S: Evaluation of suitable reference genes for gene expression studies in bovine muscular tissue. BMC Mol Biol. 2008, 9: 79-10.1186/1471-2199-9-79.PubMed CentralPubMedView ArticleGoogle Scholar
- Waxman S, Wurmbach E: De-regulation of common housekeeping genes in hepatocellular carcinoma. BMC Genomics. 2007, 8: 243-10.1186/1471-2164-8-243.PubMed CentralPubMedView ArticleGoogle Scholar
- Goidin D, Mamessier A, Staquet MJ, Schmitt D, Berthier-Vergnes O: Ribosomal 18 S RNA prevails over glyceraldehyde-3-phosphate dehydrogenase and beta-actin genes as internal standard for quantitative comparison of mRNA levels in invasive and noninvasive human melanoma cell subpopulations. Anal Biochem. 2001, 295: 17-21. 10.1006/abio.2001.5171.PubMedView ArticleGoogle Scholar
- Schmittgen TD, Zakrajsek BA: Effect of experimental treatment on housekeeping gene expression: validation by real-time, quantitative RT-PCR. J Biochem Biophys Methods. 2000, 46: 69-81. 10.1016/S0165-022X(00)00129-9.PubMedView ArticleGoogle Scholar
- Ho-Pun-Cheung A, Bascoul-Mollevi C, Assenat E, Bibeau F, Boissiere-Michot F, Cellier D, Ychou M, Lopez-Crapez E: Validation of an appropriate reference gene for normalization of reverse transcription-quantitative polymerase chain reaction data from rectal cancer biopsies. Anal Biochem. 2009, 388: 348-350. 10.1016/j.ab.2009.03.001.PubMedView ArticleGoogle Scholar
- Grummt I, Pikaard CS: Epigenetic silencing of RNA polymerase I transcription. Nat Rev Mol Cell Biol. 2003, 4: 641-649. 10.1038/nrm1171.PubMedView ArticleGoogle Scholar
- Stefanovsky VY, Pelletier G, Hannan R, Gagnon-Kugler T, Rothblum LI, Moss T: An immediate response of ribosomal transcription to growth factor stimulation in mammals is mediated by ERK phosphorylation of UBF. Mol Cell. 2001, 8: 1063-1073. 10.1016/S1097-2765(01)00384-7.PubMedView ArticleGoogle Scholar
- Spanakis E: Problems related to the interpretation of autoradiographic data on gene expression using common constitutive transcripts as controls. Nucleic Acids Res. 1993, 21: 3809-3819. 10.1093/nar/21.16.3809.PubMed CentralPubMedView ArticleGoogle Scholar
- Warner JR: The economics of ribosome biosynthesis in yeast. Trends Biochem Sci. 1999, 24: 437-440. 10.1016/S0968-0004(99)01460-7.PubMedView ArticleGoogle Scholar
- White RJ: RNA polymerases I and III, non-coding RNAs and cancer. Trends Genet. 2008, 24: 622-629. 10.1016/j.tig.2008.10.003.PubMedView ArticleGoogle Scholar
- Solanas M, Moral R, Escrich E: Unsuitability of using ribosomal RNA as loading control for Northern blot analyses related to the imbalance between messenger and ribosomal RNA content in rat mammary tumors. Anal Biochem. 2001, 288: 99-102. 10.1006/abio.2000.4889.PubMedView ArticleGoogle Scholar
- James MJ, Zomerdijk JC: Phosphatidylinositol 3-kinase and mTOR signaling pathways regulate RNA polymerase I transcription in response to IGF-1 and nutrients. J Biol Chem. 2004, 279: 8911-8918. 10.1074/jbc.M307735200.PubMedView ArticleGoogle Scholar
- Gurney ME, Pu H, Chiu AY, Dal Canto MC, Polchow CY, Alexander DD, Caliendo J, Hentati A, Kwon YW, Deng HX: Motor neuron degeneration in mice that express a human Cu, Zn superoxide dismutase mutation. Science. 1994, 264: 1772-1775. 10.1126/science.8209258.PubMedView ArticleGoogle Scholar
- Ciriza J, Moreno-Igoa M, Calvo AC, Yague G, Palacio J, Miana-Mena FJ, Munoz MJ, Zaragoza P, Brulet P, Osta R: A genetic fusion GDNF-C fragment of tetanus toxin prolongs survival in a symptomatic mouse ALS model. Restor Neurol Neurosci. 2008, 26: 459-465.PubMedGoogle Scholar
- Moreno-Igoa M, Calvo AC, Oliván S, Manzano R, Ciriza J, Muñoz MJ, Zaragoza P, Osta R: Naked DNA encoding for brain derived neurotrophic factor and TTC fusion protein delays the disease progression and prolongs survival in SOD1G93A mice [abstract]. Hum Gene Ther. 2009, 20: p 412-Google Scholar
- Coen L, Osta R, Maury M, Brulet P: Construction of hybrid proteins that migrate retrogradely and transynaptically into the central nervous system. Proc Natl Acad Sci USA. 1997, 94: 9400-9405. 10.1073/pnas.94.17.9400.PubMed CentralPubMedView ArticleGoogle Scholar
- Livak KJ, Schmittgen TD: Analysis of relative gene expression data using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method. Methods. 2001, 25: 402-408. 10.1006/meth.2001.1262.PubMedView ArticleGoogle Scholar
- Liao L, Pilotte J, Xu T, Wong CC, Edelman GM, Vanderklish P, Yates JR: BDNF induces widespread changes in synaptic protein content and up-regulates components of the translation machinery: an analysis using high-throughput proteomics. J Proteome Res. 2007, 6: 1059-1071. 10.1021/pr060358f.PubMedView ArticleGoogle Scholar
- Moss T, Stefanovsky VY: At the center of eukaryotic life. Cell. 2002, 109: 545-548. 10.1016/S0092-8674(02)00761-4.PubMedView ArticleGoogle Scholar
- Bortoluzzi S, d'Alessi F, Romualdi C, Danieli GA: Differential expression of genes coding for ribosomal proteins in different human tissues. Bioinformatics. 2001, 17: 1152-1157. 10.1093/bioinformatics/17.12.1152.PubMedView ArticleGoogle Scholar
- Parlato R, Kreiner G, Erdmann G, Rieker C, Stotz S, Savenkova E, Berger S, Grummt I, Schutz G: Activation of an endogenous suicide response after perturbation of rRNA synthesis leads to neurodegeneration in mice. J Neurosci. 2008, 28: 12759-12764. 10.1523/JNEUROSCI.2439-08.2008.PubMedView ArticleGoogle Scholar
- Li S, Hu GF: Angiogenin-mediated rRNA transcription in cancer and neurodegeneration. Int J Biochem Mol Biol. 1: 26-35.
- Finkbeiner S, Tavazoie SF, Maloratsky A, Jacobs KM, Harris KM, Greenberg ME: CREB: a major mediator of neuronal neurotrophin responses. Neuron. 1997, 19: 1031-1047. 10.1016/S0896-6273(00)80395-5.PubMedView ArticleGoogle Scholar
- Clow C, Jasmin BJ: Brain-derived neurotrophic factor regulates satellite cell differentiation and skeltal muscle regeneration. Mol Biol Cell. 21: 2182-2190. 10.1091/mbc.E10-02-0154.
- Bowman LH: rDNA transcription and pre-rRNA processing during the differentiation of a mouse myoblast cell line. Dev Biol. 1987, 119: 152-163. 10.1016/0012-1606(87)90217-X.PubMedView ArticleGoogle Scholar
- Agrawal MG, Bowman LH: Transcriptional and translational regulation of ribosomal protein formation during mouse myoblast differentiation. J Biol Chem. 1987, 262: 4868-4875.PubMedGoogle Scholar
- Goss JR: The therapeutic potential of gene transfer for the treatment of peripheral neuropathies. Expert Rev Mol Med. 2007, 9: 1-20. 10.1017/S1462399407000270.PubMedView ArticleGoogle Scholar
- Roge R, Thorsen J, Torring C, Ozbay A, Moller BK, Carstens J: Commonly used reference genes are actively regulated in in vitro stimulated lymphocytes. Scand J Immunol. 2007, 65: 202-209. 10.1111/j.1365-3083.2006.01879.x.PubMedView ArticleGoogle Scholar
- Ullmannova V, Haskovec C: The use of housekeeping genes (HKG) as an internal control for the detection of gene expression by quantitative real-time RT-PCR. Folia Biol (Praha). 2003, 49: 211-216.Google Scholar
- Goss JR: The therapeutic potential of gene transfer for the treatment of peripheral neuropathies. Expert Rev Mol Med. 2007, 9: 1-20. 10.1017/S1462399407000270.PubMedView ArticleGoogle Scholar
- Scicchitano BM, Rizzuto E, Musaro A: Counteracting muscle wasting in aging and neuromuscular diseases: the critical role of IGF-1. Aging (Albany NY). 2009, 1: 451-457.Google Scholar
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