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Full-length version of this article is also available, published online February 23, 2005 as doi:10.1096/fj.04-3045fje.
Published as doi: 10.1096/fj.04-3045fje.
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(The FASEB Journal. 2005;19:866-868.)
© 2005 FASEB

Skeletal muscle gene expression profiling in mitochondrial disorders

Marco Crimi*,{dagger},1, Andreina Bordoni*, Giorgia Menozzi{ddagger}, Laura Riva{ddagger},§, Francesco Fortunato*, Sara Galbiati*,{dagger}, Roberto Del Bo*,{dagger}, Uberto Pozzoli{ddagger}, Nereo Bresolin*,{dagger},{ddagger} and Giacomo Pietro Comi*,{dagger}

* Department of Neurological Science, University of Milan, Milan, Italy;
{dagger} I.R.C.C.S. Ospedale Maggiore Policlinico, "Dino Ferrari" Center and Center of Excellence for Neurodegenerative Diseases (CEND), Milan, Italy;
{ddagger} I.R.C.C.S. "E. Medea-La Nostra Famiglia," Bosisio Parini, Italy; and
§ Department of Biomedical Engineering, Polytechnic University, Milan, Italy

1 Correspondence: Department of Neurological Science (Pad.ne Ponti), University of Milan, via F. Sforza, no. 35, Milan 20122, Italy. E-mail: marcreamy@tiscali.it; neurogene{at}policlinico.mi.it

SPECIFIC AIMS

Extremely variable clinical and genetic features characterize mitochondrial encephalo-myopathy (MEM). Clinical manifestations become evident when a threshold percentage of mitochondrial DNA (mtDNA) molecules are mutated. However, other factors may contribute to the wide range of phenotypes associated with the same mutation. These complex genotype-phenotype relations must be governed by nuclear-mitochondrial interactions, but the precise nature of this genomic "cross-talk" is unknown. To establish a possible role for the nuclear genome in the variability of phenotypic presentation, we compared the muscle expression profile of twelve patients affected with three different mtDNA related disorders (MELASA3243G, PEOA3243G, and PEO associated with mtDNA macrodeletion) with three age-matched normal individuals.

PRINCIPAL FINDINGS

1. Gene expression profiling
Transcriptional profiling was carried out on muscle tissue biopsies from 12 patients affected by MEM using Affymetrix human HG-U133A GeneChip® arrays. Sample labeling, hybridization, and scanning were carried out according to Affymetrix recommendations. 114 probes demonstrated significance in the mtDNA-related disorders: 53 were identified as up-regulated and 61 as down-regulated.

When plotted in terms of fold change for the four groups analyzed, these gene expression differences showed a clustered distribution according to disease phenotypes. The profile of all the deregulated genes was visualized in dendrograms (Fig. 1 ).



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Figure 1. Dendrograms. Two-way hierarchical average linkage cluster expression analysis of genes selected as described. Rows are individual genes, columns are muscle samples of normal individuals and three different MEM-affected individuals. Each rectangle in the matrix represents the expression level of a single gene in a single sample. Green and red indicate an expression level respectively below and above the median of those genes across all the samples. Three selected clusters are shown: a) differentially expressed genes between MELASA3243G and PEOA3243G patients; b) differentially expressed genes between mtDNA macrodeletion and normal tissue biopsies; and c) OXPHOS subunits codifying genes in mtDNA macrodeletion and in normal tissues.

To verify whether the observed differences are involved in common cellular pathways, we assigned each gene to functional categories (http://www.geneontology.org). Genes associated with substrate and energy metabolism, mainly belonging to the urea-cycle and fatty acid metabolism, represented the largest single functional group, since they accounted for 24.3%. Elements controlling genetic processing (13.1%) and involved in cell cycle regulation (9.3%) were the other two major functional categories showing significant changes.

2. Commonly differentially regulated genes in mtDNA-related disorders vs. controls
Our data suggest that a metabolic complex candidate for the coordinated deregulation in mitochondrial disease would include the arginine-dependent network (including ARG2, ASNS, and ASS). The ARG2-prevailing function is to produce ornithine from arginine. A low arginine amount could determine a reduction in arginino-succinasic activity, contributing some of the characterizing aspects of the mitochondrial pathogeneses.

Analyses of microarray data also indicate that the CDKN1A (cyclin-dependent kinase inhibitor isoform 1A) gene was up-regulated. CDKN1A gene mediates the cell cycle G1 phase arrest in response to a variety of stress stimuli and plays a regulatory role in the repair of damaged mtDNA. Other cell cycle regulators are up-regulated together with CDKN transcript: one, CFLAR (caspase 8 and FADD-like apoptosis regulator), is a cell survival pathway antiapoptotic gene expressed predominantly in muscle.

3. Genes differentially expressed in MELAS vs. PEO
When comparing muscle tissues from two phenotypically distinct mitochondrial disorders that share the same mtDNA point mutation (A3243G), microarray analyses showed a restricted differential profile. Some differentially expressed genes influence the process of transcription and the regulation of RNA-polymerase II activity. We found TAF15 (a molecule interacting within the RNA-pol II) to be differentially expressed in MELASA3243G vs. PEOA3243G.

Another important class of differentially expressed probes comprises genes with a role in the development of neurobiological structures: ARIH2, CRYM, KAL1, and SEMA3C are down-regulated in PEOA3243G.

In PEOA3243G patients, we observed a decreased expression of genes related to fatty acid oxidation (the major energy source during periods of fasting) as well as the KLF4.

A3243G MELAS vs. PEO muscle biopsies GeneChip analysis also identified a differential expression of CAT (catalase), a gene involved in the process of detoxification of hydrogen peroxide after oxidative stress. Muscle cells carrying the MELASA3243G mutation show an increased catalase activity as adaptive response to an increased production of reactive oxygen species.

The RYR3 gene is up-regulated in MELASA3243G muscle. Ryanodine receptors, such as RYR3, are the channels responsible for the release of Ca2+ from intracellular stores following transduction of many different extracellular stimuli.

4. Differentially expressed genes in single mtDNA macrodeleted group only
Among differentially expressed genes, only five are down-regulated in the mtDNA macrodeletion group: they belong to heterogeneous functional categories.

Monoamine oxidase-A drives the enzymatic degradation of biogenic amines such as dopamine, serotonin, and adrenaline. MAO-catalyzed oxidation of biogenic amines contributes to the intramitochondrial concentration of H2O2, causing oxidative damage to mtDNA.

Conversely, mitochondrial translation optimization 1 (MTO1) shows increased expression levels in patients carrying mtDNA macrodeletions. MTO1 could play a role in protein biosynthesis acting on the post translational modifications of the mitochondrial tRNA. Exportin (XPOT), another RNA modulator, is down-regulated in the mtDNA common macrodeleted group.

A remarkable increase in several nuclear genes encoding OXPHOS subunits was observed. As already observed, it is likely that muscle tissue attempts to compensate for OXPHOS defects associated with mtDNA rearrangements by increasing the expression of nuclear-DNA-encoded OXPHOS components.

5. Real-time PCR
The expression level of several genes representing major functional gene families and demonstrating changes in disease phenotypes was measured using the TaqMan 5' nuclease fluorogenic RT-PCR assay. Overall, "fold change" was lower when using a microarray approach compared with RT-PCR.

Among genes assayed by RT-PCR, CDKN1A and ARG2 genes (Fig. 2 ) are commonly up-regulated in all subjects with a MEM (P<0.01, Student’s t test). High-level expression of arginase II protein was confirmed by Western blot analysis in muscle sample homogenates obtained from mtDNA-damaged patients.



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Figure 2. RT-PCR dosages. Upper: RT-PCR amplification plots of the relative fluorescence intensity vs. cycle number are shown for genes with a differentiated expression between all three MEM phenotypes and normal tissues: ARG2 (left) and CDKN1A (right) target cDNAs. Lower: Marked and statistically relevant differences for age-matched MEM groups were observed (*P<0.01, Student’s t tests). Only PEOA3243G ARG2 assay (P=0.021, Student’s t test) does not meet this stringent high cutoff. Each sample was run in quadruplicate. A higher expression of ARG2 and CDKN1A in MEM is in agreement with microarray results.

CONCLUSIONS AND SIGNIFICANCE

Genetic and biochemical mechanisms leading to MEM have been investigated extensively, which has led to well-defined genetic and biochemical information that may be seen as a solid background for further studies. Patients affected with these disorders and their biological tissues, mainly muscle biopsy samples, have been studied for respiratory chain activities, degrees of mitochondrial proliferation, basic genetics (mtDNA heteroplasmy), and potentially relevant pathogenic elements (e.g., the balance of pro- and anti-apoptotic factors). These observations have deepened our knowledge of these metabolic disorders but have left identification of potential new therapeutic targets largely unattended.

Since an identical mtDNA mutation can be associated with different clinical outcomes, it is likely that nuclear genetic factors are relevant to this marked phenotypic variability. In this paper, we presented microarray data showing the deregulation of several factors that may inhibit normal cell survival in MEM patients.

Of genes similarly regulated in the majority of the MEM patients, we identified increased expression of several genes involved in genetic information processing and of genes related to the metabolism of the amino groups. One of the pathogenic elements raised by the present study (the activation of the arginine pathway) fits well with recently proposed approaches for the treatment of the acute phase of stroke in MELAS patients. This main common feature may represent a possible adaptive overall expansion of several metabolic functions in muscle tissues.

Since the molecular pathogenesis of MEM continues to be unsupported by clear evidence, our findings together with literature data seem to confirm that the clinical phenotypes associated with a mtDNA mutation are also probably modulated by nuclear genetic factors. Should our observations be confirmed in larger disease groups, they may underline the values of large-scale expression study as a useful approach to mine new data of diagnostic use and may open new perspectives for MEM.

FOOTNOTES

To read the full text of this article, go to http://www.fasebj.org/cgi/doi/10.1096/fj.04-3045fje;




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