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Abstract

Las variaciones en el contenido de mtDNA se han asociado con diferentes situaciones patológicas. Su determinación en sangre es un parámetro de interés pero se ve afectado por numerosas variables. El objetivo del presente proyecto es analizar la influencia de estas variables de cara a establecer un protocolo eficiente y reproducible. La PCR a tiempo real es una técnica que se está aplicando ampliamente en las ciencias biomédicas para la cuantificación de DNA tanto mitocondrial como genómico. En este estudio trabajamos con sangre total para cuantificar el DNA mitocondrial, calculado como el ratio DNA mitocondrial/DNA nuclear. Hemos iniciado el estudio de diferentes variables que pueden afectar a dicha cuantificación. Así, se ha comprobado que la concentración de plaquetas, orgánulos que contienen DNA mitocondrial pero no DNA nuclear, afecta de forma significativa en la determinación final. De igual modo hemos estudiado la influencia que produce en la cuantificación el método de extracción utilizado para obtener el DNA y la variabilidad inter-día e intra-día en el método de extracción. Se han encontrado diferencias significativas en todas estas variables. Para realizar estos análisis hemos creado un plásmido fruto de la fusión de nuestros genes de estudio (mitocondrial y nuclear) con el fin de realizar una calibración de las medidas mediante una recta de calibrado realizada con diluciones seriadas de este estándar. También hemos estudiado la influencia de la conformación del material genético en la eficacia de la reacción de PCR y se ha visto que, puesto que al digerir el DNA mitocondrial con una enzima la cuantificación de DNA mitocondrial se ve aumentada. En la continuación del proyecto queremos seguir clarificando las fuentes de variabilidad que afectan a la técnica de PCR a tiempo real en la cuantificación de DNA mitocondrial. Ledesma Fuentes, Marta; Moreno Loshuertos, Raquel; Fernández Silva, Patricio; Laclaustra Gimeno, Martín

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1 Quantification of mitochondrial DNA in human whole blood using real-time quantitative PCR Memoria de Trabajo Fin de Máster para la obtención del grado de Máster en Biología Molecular y Celular Alumna: Marta Ledesma Fuentes 2 INDEX 1 INTRODUCTION ..................................................................................................................... 4 2 OBJECTIVES .......................................................................................................................... 13 2.1 Main objective ............................................................................................................. 13 2.2 Secondary objectives................................................................................................... 13 3 MATERIAL AND METHODS .................................................................................................. 14 3.1 Subjects ....................................................................................................................... 14 3.1.1 Population ........................................................................................................... 14 3.1.2 Selection Criteria ................................................................................................. 14 3.2 Collection and Measurement Methods and Laboratory Techniques ......................... 15 3.2.1 Whole blood sample collection ........................................................................... 15 3.2.2 Complete blood count ......................................................................................... 15 3.2.3 Sample conservation ........................................................................................... 15 3.2.4 DNA extraction .................................................................................................... 15 3.2.5 DNA quantification .............................................................................................. 17 3.2.6 Quantitative PCR assay (real-time qPCR) for mtDNA .......................................... 17 3.2.7 Data collection and processing ........................................................................... 20 3.2.8 Platelets isolation: ............................................................................................... 20 3.2.9 Creation of a standard ......................................................................................... 21 3.2.10 Standard plasmid and mtDNA digestion ............................................................. 27 3.2.11 Statistical analysis ................................................................................................ 28 4 EXPERIMENT PLANNING, DETAILED EXPERIMENTS AND RESULTS ..................................... 29 4.1 Experiment 1: Comparison of DNA extraction methods. ............................................ 29 4.2 Experiment 2: Comparison of Reproducibility with different DNA extraction methods. 30 4.3 Experiment 3: Influence of the qPCR instrument in the analysis. ............................... 31 3 4.4 Experiment 4: Platelet concentration effect (initial experiment – quantification of platelets yield and exploration of range of platelet effect) .................................................... 32 4.5 Experiment 5: Effect of technical parameters in real-time PCR.................................. 34 4.6 Experiment 6: Reproducibility of the DNA extraction process ................................... 36 4.7 Experiment 7: Design of a standard preparation ........................................................ 38 4.8 Experiment 8: Effect of mtDNA relaxion in final results. ............................................ 40 5 DISCUSION AND CONCLUSIONS .......................................................................................... 43 6 REFERENCES ........................................................................................................................ 46 4 1 INTRODUCTION Mitochondria are subcellular organelles of variable size and distribution that are found in the cytoplasm of most eukaryotic cells(1) and perform essential functions in cellular metabolism, reactive oxygen species (ROS) handling and in the regulation of cell death. Mitochondria possess a double-membrane structure that defines three different compartments: the cytoplasm, the intermembrane space and the mitochondrial matrix. In the matrix are placed the mitochondrial DNA, mtDNA, molecules along with their own transcription, translation, and protein assembly machinery. As such, they are able to maintain a relative genomic independence from the nucleus. Mitochondria are plastic organelles able to change their shape depending on the metabolic state of cells or tissues. Besides, mitochondria are capable to migrate through cytoplasm in association with microtubules, and experiment processes of fusion (3)(4)(5) and fission, generating networks depending on cellular metabolic state (6),(7). Figure 1 Mitochondrial Energy Production and Its Relationship to the Pathophysiology of Disease. Three features of mitochondrial metabolism relevant to the pathophysiology of disease: a) energy production by oxidative phosphorylation (OXPHOS), b) ROS generation as a toxic by-product of OXPHOS, and c) regulation of apoptosis through activation of the mitochondrial permeability transition pore (mtPTP). This figure was found in (2). 5 While the exact origin of mitochondria is still uncertain, it is widely believed that they arose from an endosymbiotic relationship between a glycolytic proto-eukaryotic cell and an oxidative bacterium (8). Although the replication of mtDNA is not synchronized with nuDNA replication, the overall number of mitochondria per cell remains fairly constant for specific cell types during proliferation, suggesting that the generation of mitochondria is largely influenced by extramitochondrial signal transduction events. The most well-known and best-characterized function of mitochondria is the production of adenosine triphosphate (ATP) through oxidative phosphorylation, OXPHOS. This process is accomplished by a series of protein complexes, collectively known as the respiratory chain, encoded by both nuDNA and mtDNA. The complete respiratory chain contains at least 87 polypeptides, 13 of which are encoded by mtDNA. Hence, the majority of the respiratory chain components are nuclear-encoded and imported into mitochondria after their translation in the cytosol. Thus, oxidative phosphorylation is a unique biochemical process achieved by a wellcoordinated effort of the protein products from two separate genomes (nuclear and mitochondrial) working in concert within the same cells (9),(10). Besides being responsible for the supply of energy in most cells, mitochondria also play a key role in detoxification of reactive oxygen species and other free radicals. Interestingly, alterations of the OXPHOS are also an important source of reactive oxygen species which can have toxic effects (11) but may have a regulatory role in the control of cell function and particularly in mitochondrial biogenesis (12)(13)(14)(15). Other metabolic processes that take Figure 2. The human OXPHOS system. Shown are the four complexes of the respiratory chain: Complex I [NADH dehydrogenase-CoQ reductase], Complex II [succinate dehydrogenase-CoQ reductase], Complex III [CoQ-cytochrome c reductase] and Complex IV [cytochrome c oxidase]), the FoF1-ATPase (complex V) and the two electron carriers, coenzyme Q (CoQ; also called ubiquinone) and cytochrome c (Cyt c). The 13 colored subunits are encoded by mtDNA while the rest are nuDNA-encoded. Each of the complexes also requires “assembly” factors, which are all nuDNA-encoded, for their synthesis and maintenance. MAT: matrix; MIM: mitochondrial inner membrane and IMS: intermembrane space. This figure was found in (9) 6 place within mitochondria are fatty acids β-oxidation, tricarboxilic acids cycle, urea cycle or pyrimidine biosynthesis(16). In addition to supplying cellular energy, mitochondria are involved in a range of other processes, such as signaling via Ca2+ (17) and ROS, cellular differentiation, cell death (18)(19), as well as the control of the cell cycle and cell growth, heme and Fe-S groups biosynthesis. (20) Mitochondria have also been implicated in several human diseases such as mitochondrial disorders(2)(21)(22)(23), cardiac dysfunction (24), and may play a role in the processes of aging (25),(26),(27),(28),(29),(30) or carcinogenesis (31)(32)(33)(34). The human mtDNA is a supercoiled, double-stranded circular molecule of 16,569 base pairs in size. As mentioned earlier, it codes for 13 of the 87 proteins required for oxidative phosphorylation as well as the 12S and 16S ribosomic RNAs (rRNA) and 22 transfer RNAs (tRNA) required for protein synthesis in the mitochondria (35). It is of interest to note that other than the aforementioned 13 respiratory chain components, no other genes for structural proteins are found in human mtDNA. Each mitochondrion contains between 2 and 10 copies of its genome. Although the mitochondrial mass per cell varies with cell type (between 1.000 and 10.000 copies of mtDNA depending on the tissue) and metabolic state, an individual cell typically contains a fairly constant copy number of mtDNA. The mtDNA is inherited maternally with a vertical non-Mendelian pattern.(36) The mother transmits her mitochondrial genome to all her children, but only the daughters will pass it on to all the members of the next generation, and so on. This is due to the high number of mtDNA molecules that exists in the ovum (between 100,000 and 200,000 copies) as compared to the few hundred in spermatozoids. It is known that mtDNA is far more vulnerable to mutations than nuclear DNA due to its lack of histone protection, limited repair capacity, and close proximity to the electron transport chain, Figure 3: Human mtDNA map 7 which constantly generates superoxide radicals (37)(38)(39). Considering mtDNA lacks introns, most mutations occur in the coding sequences and are thus, likely to be of biological consequence. It is known that deletions, mutations and replication abnormalities of mtDNA damage the mitochondrial function causing mitochondrial diseases (40). Other diseases, like diabetes mellitus type II (41), (42),(43) or cancer(44),(45),(46),(47) also share an impaired mitochondrial function. Loss of mtDNA copy number control is associated with aging(48) and is likely to be linked to either nuclear or mtDNA mutations. As a means for compensating a decreased functional capacity or an increased detoxification requirement in a highly oxidative environment, mitochondria increase their genetic load to ease transcription (49) (50) Thus, mtDNA number of copies per cell is a candidate to become a biomarker of mitochondrial function. Mitochondria morphology is dynamic, varying from tubes to spheroids, dividing and merging, making it difficult to quantify the expansion of mitochondria through microscopy techniques, therefore the importance of DNA quantification. mtDNA copy number is normally calculated by the ratio mtDNA/nuDNA using nuDNA as a reference and assuming, therefore, that all cells are nucleated and diploids. In the last years mtDNA has been detected to be increased o decreased in certain cancer types (51), it has been reported mtDNA copy number depletion in blood of population with metabolic syndrome (52) and in brain of Alzheimer and Parkinson patients (53). 8 Table 1. mtDNA copy number alterations in human cancers. Abbreviations: ALL, acute lymphoblastic leukemia; CRC, colorectal carcinoma; ESCC; esophageal squamous cell carcinoma; EWS, Ewing's sarcoma; HCC, hepatocellular carcinoma; Cancer types Sample size mtDNAcontent change References ALL 6 (54) Breast 25 60 59 51 (55) (56) (57) (58) CRC 104 (59) Endometrial 65 (60) ESCC 72 (61) EWS 17 (62) Fibrolamellar 15 (63) Gastric 31 (64) HCC 61 18 31 24 (65) (66) (67) (68) Head & Neck 14 (63) NHL 7 (69) NSCLC 29 (70) Ovarian 42 (71) RCC 37 (72) Thyroid 57 (55) Prostate 10 (73) 9 NHL, non-hodgkin lymphoma; NSCLC, non-small cell lung cancer; RCC, renal cell carcinoma. This table is a summary from table 1 found in (51) Table 2 Association studies between mtDNA number alterations and cancer risk This table is an adaptation from Table 2 found in (51) In our experiments mtDNA and nuDNA are quantified by realtime Polymerase Chain Reaction (PCR) (80)(81). Real-time PCR amplifies a specific target sequence in a sample and monitors the amplification progress using fluorescent technology. During amplification, how quickly the fluorescent signal reaches a threshold level correlates with the amount of original target sequence, thereby enabling quantification. Using peripheral blood to perform this quantification faces a potential limitation: among peripheral blood cells, leukocytes and platelets have mtDNA. However, platelets are not nucleated cells and the presence of their mtDNA might interfere with the quantification method (82)(83). Thus, our goal in this work is to evaluate the impact of this problem in the quantification of mtDNA in whole blood. Cancer types Study design Study Subjects mtDNA content change References Breast Cancer Case-control 103 cases 103 control (74) Colorectal Cancer Case-control 320 cases 320 controls (75) Lung Cancer Case-control 122 cases 122 controls (76) Prospective cohort 227 cases 227 controls (77) Non-Hodgkin lymphoma Prospective cohort 104 cases 104 controls (78) Renal carcinoma Case-control 260 cases 281 controls (79) 16 Figure 5. Diagram of the DNA extraction using QIAamp DNA mini kit (Qiagen) 4mL of blood were used with each extraction and the DNA was finally resuspended in 1 mL. This extraction was performed at the Unidad Mixta de Investigación (UMI) in Zaragoza. 3.2.4.2 QIAampDNAmini kit The DNA was extracted manually with the QIAamp DNA mini kit (Qiagen) according to manufacturer’s protocol (figure 5). This method is based on a cell lysis, followed by DNA binding to a solid-phase silica-impregnated filter membrane and washing, to remove residual contaminants. DNA is eluted with distilled water. 1mL of blood was used with each extraction and DNA was resuspended in 250 µl of distilled water. This extraction was done at the Biochemistry Department of Zaragoza University. 3.2.4.3 Phenol-chloroform method The DNA was extracted manually with the phenol-chloroform method, according to the protocol followed by Marcuello et al (92). Briefly, 200 µl of peripheral blood was diluted with four volumes of TE buffer (20 mM Tris-HCl pH=8.o, 5 mM EDTA). After gently mixing, samples were kept on ice for 15 min and then centrifuged at 600 x g, 4ºC for 15 min. The sediment was then washed with 800 µl TE buffer and centrifuged in the same conditions. The final pellet was then resuspended in 250 µl of TE and incubated at 37ºC overnight in the presence of 0.4% SDS and 200 μg/ml proteinase k. The reaction was finished by the addition of 1.5 M ammonium acetate to facilitate the precipitation of nucleic acids later. After that, the mixture was extracted twice with 1.5 volumes of phenol:chloroform:isoamyl alcohol (25:25:1) and once with 1.5 volumes of chloroform:isoamyl alcohol (24:1) The aqueous phase was recovered and two volumes of cold 99% Ethanol were added for the precipitation of Total DNA at −20 C overnight. Then, DNA was 17 washed with 75% ethanol. Total DNA was recovered, air-dried to eliminate ethanol and finally resuspended in 200 µl Tris-HCl 10 mM pH=8.0 This extraction was done at the Biochemistry Department of Zaragoza University. 3.2.5 DNA quantification Concentration and purity of DNA were measured with Nanovue spectrophotometer (Thermo Fisher Scientific, USA). A first blank measurement was required with distilled water (for DNA extracted with the QIAamp DNA mini kit) or with 10mM Tris-HCl pH 8.5 (in case of DNA obtained with FlexiGene DNA kit or phenol-chloroform extraction). DNA absorbance was measured at 260nm. A260/A280 ratio was measured to detect protein contamination in sample whereas A260/A230 ratio detected salts contamination. 3.2.6 Quantitative PCR assay (real-time qPCR) for mtDNA We implemented a quantitative real-time polymerase chain reaction method based on the SYBR Green assay. PCR process is monitored through the increase of fluorescent signal produced by the binding of SYBER Green dye to the double-stranded DNA at 530nm. We amplified mtDNA and nuDNA in different reaction wells. A fragment of mitochondrial cytochrome oxidase II gene (COII) was used as target gene and a fragment of subunit A of succinate dehydrogenase gene (SDHA) was used as reference gene (figure 3). The SDHA gene is located on the short (p) arm of chromosome 5 at position 15. Figure 6. Genetic map of human mitochondrial DNA and human chromosome 5. A. In mtDNA map, we can observe the mt-COII gene which is our target gene. B. In nuDNA map, we can observe the human SDHA gene (Reference gene) which is located in the short arm of chromosome 5. 18 qPCR is performed in different instruments:  LightCycler 2.0 Instrument (Roche Applied Science) at the Zaragoza University  ABI PRISM® 7900 Real-Time PCR System (Applied BioSystems) (384 well plate format) at the National Center of Cardiovascular Research, CNIC. 3.2.6.1 LightCycler 2.0 Instrument. With the LightCycler 2.0 Instrument, LightCycler FastStart DNA MasterPLUSSYBR Green I kit (Roche) was used. It contains FastStart Taq DNA Polymerase, reaction buffer, MgCl2, SYBR Green I dye and dNTP mix. Genomic DNA extracted following different methods, was used as a template and was amplified with specific oligodeoxynucleotides for MT-CO2 and SDHA (See Table 3 for primer sequences).These primers were designed with Primer Express 2.0 software (Applied Biosystems, they were tested functionally in quantitative analysis and the results were optimal (See Figure 7). Melting curve analysis showed that there was no primer dimer formation. Table 3. qPCR primers sequences. PCR was set up in a reaction volume of 20 µl inside glass capillaries in a 32-positions carrousel following proportions indicated in table 4. Gene Primer Name Position Sequence mt-COII (NC_001807) h_mtCo2 RTF 8080-8104 CCCCACATTAGGCTTAAAAACAGA h_mtCo2 RTR 8138-8160 TATACCCCCGGTCGTGTAGCGGT SDHA (AF171018) h_SDHA RTF 224-244 TCTCCAGTGGCCAACAGTGTT h_SDHA RTR 276-295 GCCCTCTTGTTCCCATCAAC Figure 7: qPCR primers efficiency: Logarithmic curves obtained using the different primers pairs and 10 fold seriated dilutions of genomic DNA as template. As it can be observed, both reactions produce optimal results. 19 Table 4. qPCR reaction in LightCycler 2.0. PCR reaction Volume DNA (3 ng/µl) 3 µl (9ng) Master Mix 4 μl Primer Mix (*) (5 µM each) 0. 5 μl PCR grade distilled water 12.5μl (*) Primer Mix is a mixture of h_mtCo2 RTF+h_mtCo2 RTR or h_SDH RTF+h_SDH RTR The PCR reaction was run with the program indicated in table 5. Table 5. qPCR program in LightCycler 2.0 PCR-program Temperature (ºC) Duration (sec.) Pre-incubation 95 600 Denaturation 95 10 Amplification Annealing 58 5 55 cycles Extension 72 5 Melting Curves 95 1 65 15 98 0.1ºC/s Cooling 40 30 This Real-time quantitative PCR was carried out at the Zaragoza University. 3.2.6.2 ABI PRISM® 7900 With ABI PRISM® 7900, we used SYBR Green PCR Master Mix. It contains SYBR Green I Dye, AmpliTaq Gold DNA Polymerase, dNTPs, Passive Reference (ROX) and buffer components. The primer sequences used in qPCR are presented in table 3. PCR was set up in a reaction volume of 10uL in proportions mentioned in table 6. Table 6. qPCR reaction in ABI PRISM 7900. PCR reaction volume DNA 5ng Master Mix 5 μl Primer mix (*) 5 μM 0.4 μl Distilled water Until a final volume of 10 μl (*) Primer Mix is a mixture of h_mtCo2 RTF+h_mtCo2 RTR or h_SDH RTF+h_SDH RTR 20 The PCR reaction is run with the program indicated in table 7. Table 7. qPCR program in ABI PRISM 7900. PCR-program Temperature (ºC) Duration (sec.) Pre-incubation 50 120 95 600 Denaturation 95 1 40 cycles Amplification Annealing/extension 60 20 Melting curve 60 15 60->95ºC ramp rate 2% 95 15 This Real-time quantitative PCR was carried out at the CNIC. 3.2.7 Data collection and processing The copy number of the mtDNA and nuDNA was calculated using the threshold cycle number (CT) and extrapolating from the standard curve. The threshold cycle (CT) values were obtained by the default second derivate method (SDM) on the LightCycler (4.05 software) and ABI PRISM (sequence detection system, SDS 2.4 software). Each sample was analyzed in triplicate and one negative control was included in every run. The ratio of the copy number of mtDNA to the copy number of nuDNA is the measurement of mtDNA content. Samples analyzed without standard curve were all normalized by the quantification of one sample. In that case, data are analyzed by 2-ΔΔCT method (93) 3.2.8 Platelets isolation: Platelets are isolated following the Appendix H: Protocol for Mitochondrial DNA from Platelets of QIAamp DNA Mini and Blood Mini Handbook 04/2010. 6mL of fresh blood were centrifugated in centrifuge Hettich Rotofix 32A at 100 x g for 15 min at room temperature to prepare the platelet-rich plasma. Upper layer was transferred into a new tube and residual blood cells were removed by centrifugation at 200 x g for 10 min at room temperature (15-25ºC) 21 Supernatant was transferred to a new tube. This supernatant is called hereafter platelet enriched plasma. 3.2.9 Creation of a standard In the following points it is explained in detail the steps necessaries to get a fusion fragment of mt-nuDNA and its insertion in the plasmid pCR 2.1. Besides it is explained how to select the plasmid with insert for using it as a standard in a real time qPCR assay. 3.2.9.1 Amplification of the mitochondrial and nuclear fragments Amplification of mitochondrial and nuclear fragments was done separately in two reactions depending of the pair of primers used. PCR is done in Biometra T3000 Termocycler using primers h_mtCo2_RTF(87) and h_mtCo2_RTR to amplify mtDNA (see table 3), and h_SDHA_RTF and h_SDHA_RTR to amplify nuDNA. PCR reaction was carried out in a volume of 50 µl according to proportions indicated in table 8. To obtain a large amount of PCR products three tubes per reaction were prepared. Figure 7. Diagram of the steps followed to prepare a standard plasmid. 22 Table 8. PCR reaction in Biometra T3000 Termocycler to amplify mtDNA and nuDNA fragments. PCR reaction Volume Buffer Taq 10x 5 μl dNTPs 10 mM each 1 μl Forward Primer 10 μM 2.0 μl Reverse Primer 10 μM 2.0 μl DNA 50-100 ng Taq 0.3 μl H2O Until final volume of 50 μl The PCR reaction was run with program indicated in table 9. Table 9. PCR program in Biometra T3000 Termocycler to amplify mtDNA and nuDNA fragments. PCR-program Temperature (ºC) Duration (sec.) Pre-incubation 95 120 Denaturation 95 45 Amplification Annealing 58 45 25 cycles Extension 72 45 Extension 72 300 3.2.9.2 Purification of the fragments All PCR products (150 µl) were mixed with 15 µl ficoll (10x; 30% Ficoll 400 and 0.1% (w/v) bromophenol blue in 1x TAE) and this mixture was loaded on a 1%TAE agarose gel, stained with ethidium bromide. Electrophoresis was developed at a constant voltage of 90v for 30 min. To correctly identify the PCR products obtained 2 µl of Low Mass DNA Ladder® from Invitrogen were run in parallel. Mitochondrial and nuclear amplicons were cut and introduced in 2 different eppendorf tubes and purification of DNA fragments was done with SpinClean Gel Extraction Kit (Mbiotech) according to the manufacturer’s protocol. This kit uses a spin column containing silica membrane. 3.2.9.3 Phosphorylation of h_mtCo2 and dephosphorylation of h_SDHA fragments DNA concentration of both fragments was measured with Nanovue previously to the following reactions. 23 First, mitochondrial fragment, h_mtCo2, was 5’ phosphorylated by T4 polynucleotide kinase 3’ phosphatase free (T4-PNK; Roche). Therefore 71.4 ng of purified mtDNA fragment were mixed in an eppendorf tube with 2 µl T4 DNA ligase buffer 10x (which contains 10mM ATP (NewEngland Biolabs)), 1 uL T4-PNK (10u/µl) and distilled water until 20 µl of final volume and incubated at 37ºC for 30 min. Then the reaction was stopped by heating the mixture at 70ºC for 10 min. At the same time, the nuclear fragment, h_SDHA, was 5’ dephosphorylated. Thus, 71.4 ng of purified nuDNA fragment was mixed in a tube with 2 µl of rAPid alkaline phosphatase buffer 10x (Roche), 1µl of rAPid alkaline phosphatase (1U/µl; Roche) and distilled water until a final volume of 20µl and incubated at 37º for 10 min. Phosphatase was inactivated by heating at 75ºC for 2 min. Phosphorylated and dephosphorylated fragments were kept at -20ºC until first use. 3.2.9.4 Ligation of h_mtCo2 and h_SDHA fragments Phosphorylated and dephosphorylated fragments were ligated by mixing 4 µl of 5’P-h_mtCo2, 4µl h_SDHA deP and 2µl DNA dilution buffer 5x. In a second step, 10 µl T4-DNA ligase buffer 2x and 1 µl T4 DNA ligase 5U/µl was added to the mix. After 5 minutes incubation at room temperature, the mix was kept at -20ºC until use. 3.2.9.5 Amplification of the fusion product Hundred-fold diluted fused PCR products were expanded by standard PCR using primer pairs: h_mtCo2_RTF and h_SDHA_RTR (PCR1) and h_mtCo2_RTR and h_SDHA_RTF (PCR2). 3.2.9.6 Purification of the PCR product As multiple fusion products could be obtained and amplified in previous steps, PCR products were electrophoresed in agarose 1% TAE gels. (Electrophoresis conditions: 90V. 40 min). To correctly identify the PCR products obtained 2 µl of Low Mass DNA Ladder® from Invitrogen were run in parallel. Single bands consistent with the expected length of the fused PCR product 151 bp were cut and purified with SpinClean Gel Extraction Kit (Mbiotech) according to the manufacturer’s protocol. 3.2.9.7 Amplification of the purify ligation products. In order to obtain higher amounts of fusion product with the right size, a second PCR round was performed using hundred-fold diluted product of the previous purification step. 24 An electrophoresis of 1% TAE in agarose gel was run with PCR products. Electrophoresis conditions: 100v, 30 min. 3.2.9.8 Ligation with TOPO TA cloning To validate the PCR products by sequencing, a previous cloning step was performed. Thus the TA Cloning Kit (Invitrogen) was used, following the manufacturer’s instructions. The following components are mixed: 2 µl of ligation buffer 10x, 1 µl of fresh PCR product, 2µl linear pCR2.1 50 ng/µl, 1uL ligase 4U/µl and distilled water until 10 µl. An overnight (12-16h) incubation at 14ºC was performed. Figure 8. pCR®2.1-TOPO® Vector (Invitrogen). TOPO® TA Cloning® Kits are designed for cloning PCR products directly from a PCR reaction. pCR®-TOPO® Vectors include:  3´-T overhangs for direct ligation of Taq-amplified PCR products;  M13 forward and reverse primer sites for sequencing;  EcoR I sites flanking the PCR product insertion site for easy excision of inserts  Kanamycin and ampicillin resistance genes for your choice of selection in E. coli  Easy blue/white colony screening for selection of recombinants 25 The insertion of PCR product interferes lacZ gene expression. 3.2.9.9 Transformation of DH5α bacteria Chemicompetents bacteria (E.coli strain DH5α) were transformed with 2 µl of fresh ligation product by thermal shock. Thus, 2 µl of ligation product were mixed with 50 µl of DH5α bacteria and incubated on ice for 30 minutes to introduce plasmidic DNA into bacteria. After this, a thermal shock at 42ºC during 30 seconds was applied to the cells, using the thermoblock. 250 µl of LB medium (1% Bacto tryptone, 0.5% yeast extract, 1% NaCl, pH=7.0) were added to the cells. The eppendorf tube was kept 1 hour at 37ºC in agitation in an orbital to allow bacteria to grow, recover from the shock and express antibiotic resistance A LB-agar plate was prepared with ampicillin. 40 µl of X-Gal were added to it and incubated at 37ºC. The entire sample from the transformation step was added to the plate and evenly distributed on the surface, and the plates were incubated overnight at 37ºC. 3.2.9.10 Analysis of the transformation and PCR test After incubation, only bacteria harboring plasmidic DNA were able to survive in the presence of ampicillin. We could also test the presence of insert within the plasmid thanks to the interruption of β-galactosidase gene. Thus, blue colonies were bacteria expressing lacZ gene in presence of x-gal. That means there was no insert in the pCR 2.1. On the other hand, white colonies were bacteria with our PCR product inserted in the pCR 2.1. We picked several white colonies with a sterile stick and introduced the stick in an eppendorf tube containing 50 µl of LB medium with ampicillin. With the same stick we picked again the same white colony and introduced the stick in a PCR tube with 10 µl of distilled water. The eppendorf tube with LB was kept at 4ºC. In the PCR tube the reagents indicated in table 10 were added. 32 4.4 Experiment 4: Platelet concentration effect (initial experiment – quantification of platelets yield and exploration of range of platelet effect) In order to test the influence of platelets in mtDNA copy number evaluation, we worked with the blood collected in EDTA K2 tubes from 3 participants and prepared 5 aliquots (aliquot 1-5) of 50 µl of and sixth one containing 450 µl. With the rest of the blood of each participant, the procedure of platelet separation was performed. We carried out a complete blood count in native whole blood and platelet suspensions (platelet enriched plasma), as well as, in the 5 reconstituted aliquots. We then made five different blood reconstitutions by adding growing amounts of platelets enriched plasma to the different aliquots as detailed below. The sixth aliquot was used as control sample:  400 µl of platelets enriched plasma were added to aliquot 1.  200 µl of platelets enriched plasma and 200 µl of saline solution were added to aliquot 2.  50 µl of platelets enriched plasma and 350 µl of saline solution were added to aliquot 3.  12.5 µl of platelets enriched plasma and 385 µl of saline solution were added to aliquot 4.  400 µl of saline solution were added to aliquot 5. Figure 12. Reproducibility of mtDNA/nuDNA quantification inter-instrument. DNA was extracted from 4 different samples (309, 306, 14 and 307) using the FlexiGene DNA kit (_E). MtDNA/nuDNA copy number was calculated in all samples using LightCycler 2.0 and ABI PRISM 7900. Results were normalized by quantification of sample 309_E. LightCycler measurements were made four times in all samples but 307 where n=2; with ABI PRISM n=3 in all cases. . When comparing both instruments, we only found statistically significant differences for sample 307 (p=0.0226). Dates were analyzed by ANOVA (Fisher’s PLSD test). 33 These samples were kept at 80ºC until DNA extraction. The phenol-chloroform method was used for DNA isolation. We determined the mtDNA/nuDNA ratio in all the samples mentioned above using the ABI PRISM 7900 instrument. The aim of this assay was to assess how platelet concentration affects the mtDNA/nuDNA ratio determination in blood samples. Here, we started to quantify the dynamic range (as a pilot assay) for big differences in platelets concentration. Our aim should be to study more in detail the effect of small platelet variations in a subsequent experiment in the case that they showed an influence within the normal range. Results obtained are represented in figure 13. As it is shown in the graphic, there are significant differences in mtDNA quantification when working with increased amount of platelets. With the highest amount of added platelets, the mtDNA/nuDNA ratio increased up to around 5-fold in comparison with the initial quantity of the sample without additions. In the normal healthy ranges (platelets/leukocyte ratio until 100) the amount of mtDNA molecules measured was at least twice the original one. 34 4.5 Experiment 5: Effect of technical parameters in real-time PCR The aim of this experiment is to study the primer efficiency in the standard when SYBR concentration is changed. In relative quantification, the primer efficiency in the target and the reference genes must be similar. As it is said in the protocol of ABI-PRISM (table 6), our PCR is normally made with a final volume of 10µL using 5 µL of Master Mix, which contains SYBR Green fluorescent probe. To do these experiments, we used the standard as template and we obtained similar efficiencies for both genes (1.86). Reducing 1/4-fold the quantity of Master mix in the PCR reaction, the efficiency of the genes continued similar (1.84 and 1.83). When the amount of Master Mix was reduced 1/2-fold, the efficiency of the genes started to diverge (1.82 and 1.76). Finally, a reduction of 3/4-fold the quantity of SYBR-Green resulted in a great difference between primers efficiencies (1.92 and 1.54) (table 13). Figure 13. Effect of platelets concentration in mtDNA quantification. 4 samples were aliquoted and supplemented with increasing amounts of platelets. DNA was isolated in each sample the results obtained in mtDNA quantification are shown in this figure. Graphic A shows that mtDNA copy number increases with platelet/leukocyte levels. This observation is more evident when working with high concentrations of platelets. Graphic B collects the results normalized by original values of the sample (aliquot 6). All measurements were made in triplicate. 35 Primer slope (log) R^2 Efficiency h_mtCo2_10_ 1x -3.707 0.99 1.86 h_SDHA_10_ 1x -3.698 0.98 1.86 h_mtCo2_10_ 0.75x -3.772 0.99 1.84 h_SDHA_10_ 0.75x -3.805 0.99 1.83 h_mtCo2_10_ 0.5x -3.85 0.99 1.82 h_SDHA_10_ 0.5x -4.08 0.99 1.76 h_mtCo2_10_ 0.25x -3.528 0.73 1.92 h_SDHA_10_ 0.25x -5.324 0.95 1.54 Table 13. Primers efficiencies using different proportions of Master Mix. 1x is the standard amount of Master Mix. 0.75x (0.5x, 0.25x): ¾ (½,¼ )standard proportions of Master Mix respectively. Knowing these results, we performed a qPCR with these concentrations of Master Mix using DNA obtained following the same protocol from samples 14, 306 and 309 as template (Figure 14). We saw that a reduction of half the concentration of master mix affects mtDNA quantification in all the samples whereas a 1/4-fold decrease in SYBR Green amount does not influence the determination in all samples. Figure 14. mtDNA/nuDNA quantification according to SYBR Green (Master Mix) concentration. SYBR Green concentration affects mtDNA determination only when is reduced to half the amount recommended by the manufacturer. A 1/4-fold decrease induces significant differences in sample 309. All measurements were made in duplicate. There were not significant difference in all assays except in sample 14_ when SYBR_10_x0.75 and SYBR_10_0.5 were compared (p=0.03). Dates were analyzed by ANOVA (Fisher’s PLSD test). (SYBR_10_x1: PCR reaction in 10 µl using 100% of the standardized quantity of Master Mix; SYBR_10_x0.75: PCR reaction in 10 µl using 75% of the standardized quantity of Master Mix; SYBR_10_x0.5: PCR reaction in 10 µl using 50% of the standardized quantity of Master Mix) 36 4.6 Experiment 6: Reproducibility of the DNA extraction process This experiment was performed in order to study if a DNA sample obtained the same day following the same method or isolated in the same way in different days gives comparable mtDNA copy number values. In this case, we tested the reproducibility with DNA samples obtained using the FlexiGene DNA kit (Qiagen), or the phenol-chloroform method. Blood samples of three participants were collected at the same time. 4 aliquots of 1 mL were used in the experiment. 2 aliquots of 1 ml were used for DNA extraction with FlexiGene DNA kit in 2 different days. The other 2 aliquots of 1 ml were subdivided in 3 aliquots of 250 µl and the DNA was extracted in two different days by phenol-chloroform method. In this last extraction, the first day DNA was extracted using falcon tubes while the second day DNA was extracted on 1.5 ml eppendorf tubes and using a microcentrifuge. We obtained statistically significant differences in mt/nuDNA quantification interday (figure 15) when the phenol-chloroform method was used. Besides, the intraday variation coefficient is higher the first day than the second day (table 14). FlexiGene DNA kit gives mt/nuDNA quantification more comparable when samples were extracted in different days (figure 16), being the interday variation coefficient in mt/nuDNA quantification, lower than the one obtained in the case of phenol-chloroform method (table 14). Figure 15. Reproducibility of phenolchloroform method in mtDNA/nuDNA quantification. DNA from three blood samples (10, 6 and 9) was isolated by phenol chloroform method in two different days. Each day, samples were extracted independently in triplicate. MtDNA/nuDNA quantification obtained for each sample is represented in this graphic as the mean obtained per day. In samples 10 and 6, the quantification is nearly 3 times higher the second day than the first day. All measurements were made in triplicate. There was a significant difference in all samples p<0,001). Dates were analyzed by ANOVA (Fisher’s PLSD test). 37 Table 14. Coefficient of variation interday and intraday in mt/nuDNA quantification, using FlexiGene DNA kit (_E) and phenolchloroform method (_M) in samples 10, 6 and 9. sample mean mt/nuDNA qty. per day SD per day CV% per day mean mt/nuDNA qty. interday SD interday CV% interday 10_M_day 1 15.41 7.52 48.79 26.56 15.78 59.39 10_M_day 2 37.72 3.51 9.31 6_M_day 1 7.11 5.67 79.74 16.73 13.6 81.28 6_M_day 2 26.34 5.37 20.38 9_M_day 1 33.7 3.47 10.3 36.56 4.04 11.06 9_M_day 2 39.42 2.44 6.18 10_E_day 1& 2 26.73 2.06 7.71 6_E_day 1&2 12.81 0.82 6.4 9_E_day 1&2 23.99 5.19 21.62 Figure 16. Reproducibility of FlexiGene DNA kit in mtDNA/nuDNA quantification.DNA from the same three blood samples (10, 6 and 9) was isolated using the FlexiGene DNA kit in two different days. MtDNA/nuDNA quantification obtained in each sample is represented in this graphic. All measurements were made in triplicate. There was a significant difference in samples 6 (p=0.03) and 9 (p=0.003). Dates were analyzed by ANOVA (Fisher’s PLSD test).. 38 4.7 Experiment 7: Design of a standard preparation The aim of this experiment was to obtain a DNA fragment containing our mitochondrial and nuclear fragments in a proportion 1:1 to allow absolute mtDNA quantification (copy number per cell). Both genes were amplified by PCR, ligated and cloned in the vector pCR2.1 TOPO as described before (section 3.2.1) Following point 3.2.9 we sent the fusion product to be sequenced using vector primers. Figure 17 shows the chromatogram and alignment obtained in one of the samples that were analyzed. 39 Figure 17. Plasmid 7 sequence. Sequence of nuclear and mitochondrial gene in plasmid 7. PCR forward primers for each gene are coloured in yellow while reverse primer are coloured in blue.  Nuclear gene: ref|NG_012339.1| Homo sapiens succinate dehydrogenase complex, subunit A, flavoprotein (Fp) (SDHA), RefSeqGene on chromosome 5 Length=45460 Score = 134 bits (72), Expect = 3e-34 Identities = 72/72 (100%), Gaps = 0/72 (0%) Strand=Plus/Plus Query 12 TCTCCAGTGGCCAACAGTGTTGCAAACAGGAACCCGAGGTTTTCACTTCACTGTTGATGG 71 |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||| Sbjct 10235 TCTCCAGTGGCCAACAGTGTTGCAAACAGGAACCCGAGGTTTTCACTTCACTGTTGATGG 10294 Query 72 GAACAAGAGGGC 83 |||||||||||| Sbjct 10295 GAACAAGAGGGC 10306  Mitochondrial gene : ref|NC_001807.4| Homo sapiens mitochondrion, complete genome Length=16571 Score = 150 bits (81), Expect = 1e-39 Identities = 81/81 (100%), Gaps = 0/81 (0%) Strand=Plus/Plus Query 86 CCCCACATTAGGCTTAAAAACAGATGCAATTCCCGGACGTCTAAACCAAACCACTTTCAC 145 |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||| Sbjct 8081 CCCCACATTAGGCTTAAAAACAGATGCAATTCCCGGACGTCTAAACCAAACCACTTTCAC 8140 Query 146 CGCTACACGACCGGGGGTATA 166 ||||||||||||||||||||| Sbjct 8141 CGCTACACGACCGGGGGTATA 8161 o Chromatogram: 40 4.8 Experiment 8: Effect of mtDNA relaxion in final results. Previous works had reported a critical role of DNA supercoiling in quantitative Real Time determinations (87)(88) (89). So, we wanted to see if this parameter affected or not in mtDNA copy number determination. Thus, we used two types of samples. First of all we tested the effect of DNA relaxation in our plasmidic standard and finally, we used some of the DNA samples previously isolated as template. First, the standard plasmid was digested with BamHI and XhoI enzymes. We chose these enzymes because they cut once within the plasmid and don’t recognize any restriction site within our genes. 10-fold serial dilutions of the digested and the native plasmids were used as template for mtDNA determination using the LightCycler instrument (table 15). As it can be seen in figure 18, there was no difference in working with BamHI or XhoI. Dilution (Number of copies) Ct Circular plasmid Ct Plasmid digested with BamHI Ct Plasmid digested with XhoI 1 (1.76*105) 19.14 17.55 17.67 1 (1.76*105) 19.66 17.47 17.88 0.1 (1.76*104) 22.55 21.00 21.17 0.1 (1.76*104) 22.87 21.04 21.02 0.01 (1.76*103) --- 23.90 24.26 0.01 (1.76*103) --- 23.55 24.07 0.001 (1.76*102) 27.05 25.74 25.85 0.001 (1.76*102) 26.06 25.79 26.01 0.0001 (1.76*101) 25.85 26.42 26.60 0.0001 (1.76*101) 26.32 26.05 26.54 Table 15.Standard dilution of native plasmid and plasmid digested with BamHI and XhoI. 41 When the plasmid presented the native conformation (supercoiled form), the threshold cycle was detected with a delay respect to the CT of the linear form. This fact makes the number of copies of the gene measured in the native form be lower than with the linear form. The efficiency was identical using both enzymes. A new real time PCR was performed with the native standard and standard digested with XhoI and using both primers sets (figure 19): Figure 18. Native Standard plasmid vs. standard plasmid digested. A serial 10-fold dilution of the standard digested and native standard were used as template in a qPCR where h-mtCo2 primers were the selected ones . There were no differences in qPCR efficiency induced by the enzymes (BamHI ans XhoI). 48 31. Carew JS, Huang P. Mitochondrial defects in cancer. Mol. Cancer. 2002 dic 9;1:9. 32. Cuezva JM, Krajewska M, de Heredia ML, Krajewski S, Santamaría G, Kim H, et al. The bioenergetic signature of cancer: a marker of tumor progression. Cancer Res. 2002 nov 15;62(22):6674–81. 33. Gallardo ME, Moreno-Loshuertos R, López C, Casqueiro M, Silva J, Bonilla F, et al. m.6267G>A: a recurrent mutation in the human mitochondrial DNA that reduces cytochrome c oxidase activity and is associated with tumors. Hum. Mutat. 2006 jun;27(6):575–82. 34. Petros JA, Baumann AK, Ruiz-Pesini E, Amin MB, Sun CQ, Hall J, et al. mtDNA mutations increase tumorigenicity in prostate cancer. Proc. Natl. Acad. Sci. U.S.A. 2005 ene 18;102(3):719–24. 35. Anderson S, Bankier AT, Barrell BG, de Bruijn MH, Coulson AR, Drouin J, et al. Sequence and organization of the human mitochondrial genome. Nature. 1981 abr 9;290(5806):457–65. 36. Giles RE, Blanc H, Cann HM, Wallace DC. Maternal inheritance of human mitochondrial DNA. Proc Natl Acad Sci U S A. 1980 nov;77(11):6715–9. 37. Brown MD, Wallace DC. Molecular basis of mitochondrial DNA disease. J. Bioenerg. Biomembr. 1994 jun;26(3):273–89. 38. Cantatore P, Saccone C. Organization, structure, and evolution of mammalian mitochondrial genes. Int. Rev. Cytol. 1987;108:149–208. 39. Shokolenko I, Venediktova N, Bochkareva A, Wilson GL, Alexeyev MF. Oxidative stress induces degradation of mitochondrial DNA. Nucleic Acids Res. 2009 may;37(8):2539–48. 40. Schon EA. Mitochondrial genetics and disease. Trends Biochem. Sci. 2000 nov;25(11):555–60. 41. Choi YS, Kim S, Pak YK. Mitochondrial transcription factor A (mtTFA) and diabetes. Diabetes Res. Clin. Pract. 2001 dic;54 Suppl 2:S3–9. 42. Malik AN, Shahni R, Iqbal MM. Increased peripheral blood mitochondrial DNA in type 2 diabetic patients with nephropathy. Diabetes Res. Clin. Pract. 2009 nov;86(2):e22–24. 43. Rolo AP, Palmeira CM. Diabetes and mitochondrial function: role of hyperglycemia and oxidative stress. Toxicol. Appl. Pharmacol. 2006 abr 15;212(2):167–78. 44. Xing J, Chen M, Wood CG, Lin J, Spitz MR, Ma J, et al. Mitochondrial DNA Content: Its Genetic Heritability and Association With Renal Cell Carcinoma. J Natl Cancer Inst. 2008 ago 6;100(15):1104–12. 45. Yu M, Zhou Y, Shi Y, Ning L, Yang Y, Wei X, et al. Reduced mitochondrial DNA copy number is correlated with tumor progression and prognosis in Chinese breast cancer patients. IUBMB Life. 2007 jul;59(7):450–7. 49 46. Thyagarajan B, Wang R, Barcelo H, Koh W-P, Yuan J-M. Mitochondrial Copy Number is Associated with Colorectal Cancer Risk. Cancer Epidemiol. Biomarkers Prev. [Internet]. 2012 ago 10 [citado 2012 sep 2]; Available a partir de: http://www.ncbi.nlm.nih.gov/pubmed/22787200 47. Shen J, Platek M, Mahasneh A, Ambrosone CB, Zhao H. Mitochondrial copy number and risk of breast cancer: a pilot study. Mitochondrion. 2010 ene;10(1):62–8. 48. Laderman KA, Penny JR, Mazzucchelli F, Bresolin N, Scarlato G, Attardi G. Agingdependent Functional Alterations of Mitochondrial DNA (mtDNA) from Human Fibroblasts Transferred into mtDNA-less Cells. J. Biol. Chem. 1996 may 7;271(27):15891–7. 49. Moreno-Loshuertos R, Acín-Pérez R, Fernández-Silva P, Movilla N, Pérez-Martos A, Rodriguez de Cordoba S, et al. Differences in reactive oxygen species production explain the phenotypes associated with common mouse mitochondrial DNA variants. Nat. Genet. 2006 nov;38(11):1261–8. 50. Moreno-Loshuertos R, Ferrín G, Acín-Pérez R, Gallardo ME, Viscomi C, Pérez-Martos A, et al. Evolution meets disease: penetrance and functional epistasis of mitochondrial tRNA mutations. PLoS Genet. 2011 abr;7(4):e1001379. 51. Yu M. Generation, function and diagnostic value of mitochondrial DNA copy number alterations in human cancers. Life Sci. 2011 jul 18;89(3-4):65–71. 52. Huang C-H, Su S-L, Hsieh M-C, Cheng W-L, Chang C-C, Wu H-L, et al. Depleted leukocyte mitochondrial DNA copy number in metabolic syndrome. J. Atheroscler. Thromb. 2011;18(10):867–73. 53. Coskun P, Wyrembak J, Schriner SE, Chen H-W, Marciniack C, LaFerla F, et al. A mitochondrial etiology of Alzheimer and Parkinson disease. Biochimica et Biophysica Acta (BBA) - General Subjects. 2012 may;1820(5):553–64. 54. Egan K, Kusao I, Troelstrup D, Agsalda M, Shiramizu B. Mitochondrial DNA in residual leukemia cells in cerebrospinal fluid in children with acute lymphoblastic leukemia. J Clin Med Res. 2010 oct 11;2(5):225–9. 55. Mambo E, Chatterjee A, Xing M, Tallini G, Haugen BR, Yeung S-CJ, et al. Tumor-specific changes in mtDNA content in human cancer. Int. J. Cancer. 2005 oct 10;116(6):920–4. 56. Tseng L-M, Yin P-H, Chi C-W, Hsu C-Y, Wu C-W, Lee L-M, et al. Mitochondrial DNA mutations and mitochondrial DNA depletion in breast cancer. Genes Chromosomes Cancer. 2006 jul;45(7):629–38. 57. Yu M, Shi Y, Wei X, Yang Y, Zhou Y, Hao X, et al. Depletion of mitochondrial DNA by ethidium bromide treatment inhibits the proliferation and tumorigenesis of T47D human breast cancer cells. Toxicol. Lett. 2007 abr 5;170(1):83–93. 50 58. Fan AX-C, Radpour R, Haghighi MM, Kohler C, Xia P, Hahn S, et al. Mitochondrial DNA content in paired normal and cancerous breast tissue samples from patients with breast cancer. J. Cancer Res. Clin. Oncol. 2009 ago;135(8):983–9. 59. Chen T, He J, Shen L, Fang H, Nie H, Jin T, et al. The mitochondrial DNA 4,977-bp deletion and its implication in copy number alteration in colorectal cancer. BMC Med. Genet. 2011;12:8. 60. Wang Y, Liu VWS, Xue W-C, Tsang PCK, Cheung ANY, Ngan HYS. The increase of mitochondrial DNA content in endometrial adenocarcinoma cells: a quantitative study using laser-captured microdissected tissues. Gynecol. Oncol. 2005 jul;98(1):104–10. 61. Lin C-S, Chang S-C, Wang L-S, Chou T-Y, Hsu W-H, Wu Y-C, et al. The role of mitochondrial DNA alterations in esophageal squamous cell carcinomas. J. Thorac. Cardiovasc. Surg. 2010 ene;139(1):189–197.e4. 62. Yu M, Wan Y, Zou Q. Decreased copy number of mitochondrial DNA in Ewing’s sarcoma. Clin. Chim. Acta. 2010 may 2;411(9-10):679–83. 63. Vivekanandan P, Daniel H, Yeh MM, Torbenson M. Mitochondrial mutations in hepatocellular carcinomas and fibrolamellar carcinomas. Mod. Pathol. 2010 jun;23(6):790–8. 64. Wu C-W, Yin P-H, Hung W-Y, Li AF-Y, Li S-H, Chi C-W, et al. Mitochondrial DNA mutations and mitochondrial DNA depletion in gastric cancer. Genes Chromosomes Cancer. 2005 sep;44(1):19–28. 65. Lee H-C, Li S-H, Lin J-C, Wu C-C, Yeh D-C, Wei Y-H. Somatic mutations in the D-loop and decrease in the copy number of mitochondrial DNA in human hepatocellular carcinoma. Mutat. Res. 2004 mar 22;547(1-2):71–8. 66. Yin PH, Lee HC, Chau GY, Wu YT, Li SH, Lui WY, et al. Alteration of the copy number and deletion of mitochondrial DNA in human hepatocellular carcinoma. Br. J. Cancer. 2004 jun 14;90(12):2390–6. 67. Yamada S, Nomoto S, Fujii T, Kaneko T, Takeda S, Inoue S, et al. Correlation between copy number of mitochondrial DNA and clinico-pathologic parameters of hepatocellular carcinoma. Eur J Surg Oncol. 2006 abr;32(3):303–7. 68. Kim MM, Clinger JD, Masayesva BG, Ha PK, Zahurak ML, Westra WH, et al. Mitochondrial DNA quantity increases with histopathologic grade in premalignant and malignant head and neck lesions. Clin. Cancer Res. 2004 dic 15;10(24):8512–5. 69. Kusao I, Agsalda M, Troelstrup D, Villanueva N, Shiramizu B. Chemotoxicity recovery of mitochondria in non-Hodgkin lymphoma resulting in minimal residual disease. Pediatr Blood Cancer. 2008 ago;51(2):193–7. 51 70. Lin C-S, Wang L-S, Tsai C-M, Wei Y-H. Low copy number and low oxidative damage of mitochondrial DNA are associated with tumor progression in lung cancer tissues after neoadjuvant chemotherapy. Interact Cardiovasc Thorac Surg. 2008 dic;7(6):954–8. 71. Wang Y, Liu VWS, Xue WC, Cheung ANY, Ngan HYS. Association of decreased mitochondrial DNA content with ovarian cancer progression. Br. J. Cancer. 2006 oct 23;95(8):1087–91. 72. Meierhofer D, Mayr JA, Foetschl U, Berger A, Fink K, Schmeller N, et al. Decrease of mitochondrial DNA content and energy metabolism in renal cell carcinoma. Carcinogenesis. 2004 jun;25(6):1005–10. 73. Mizumachi T, Muskhelishvili L, Naito A, Furusawa J, Fan C-Y, Siegel ER, et al. Increased distributional variance of mitochondrial DNA content associated with prostate cancer cells as compared with normal prostate cells. Prostate. 2008 mar 1;68(4):408–17. 74. Shen J, Platek M, Mahasneh A, Ambrosone CB, Zhao H. Mitochondrial copy number and risk of breast cancer: a pilot study. Mitochondrion. 2010 ene;10(1):62–8. 75. Qu F, Liu X, Zhou F, Yang H, Bao G, He X, et al. Association between mitochondrial DNA content in leukocytes and colorectal cancer risk: a case-control analysis. Cancer. 2011 jul 15;117(14):3148–55. 76. Bonner MR, Shen M, Liu C-S, Divita M, He X, Lan Q. Mitochondrial DNA content and lung cancer risk in Xuan Wei, China. Lung Cancer. 2009 mar;63(3):331–4. 77. Hosgood HD 3rd, Liu C-S, Rothman N, Weinstein SJ, Bonner MR, Shen M, et al. Mitochondrial DNA copy number and lung cancer risk in a prospective cohort study. Carcinogenesis. 2010 may;31(5):847–9. 78. Lan Q, Lim U, Liu C-S, Weinstein SJ, Chanock S, Bonner MR, et al. A prospective study of mitochondrial DNA copy number and risk of non-Hodgkin lymphoma. Blood. 2008 nov 15;112(10):4247–9. 79. Xing J, Chen M, Wood CG, Lin J, Spitz MR, Ma J, et al. Mitochondrial DNA content: its genetic heritability and association with renal cell carcinoma. J. Natl. Cancer Inst. 2008 ago 6;100(15):1104–12. 80. Valasek MA, Repa JJ. The power of real-time PCR. Adv Physiol Educ. 2005 sep;29(3):151–9. 81. VanGuilder HD, Vrana KE, Freeman WM. Twenty-five years of quantitative PCR for gene expression analysis. BioTechniques. 2008 abr;44(5):619–26. 82. Urata M, Koga-Wada Y, Kayamori Y, Kang D. Platelet contamination causes large variation as well as overestimation of mitochondrial DNA content of peripheral blood mononuclear cells. Ann. Clin. Biochem. 2008 sep;45(Pt 5):513–4. 52 83. Banas B, Kost BP, Goebel FD. Platelets, a typical source of error in real-time PCR quantification of mitochondrial DNA content in human peripheral blood cells. Eur. J. Med. Res. 2004 ago 31;9(8):371–7. 84. Andreu AL, Martinez R, Marti R, García-Arumí E. Quantification of mitochondrial DNA copy number: pre-analytical factors. Mitochondrion. 2009 jul;9(4):242–6. 85. Guo W, Jiang L, Bhasin S, Khan SM, Swerdlow RH. DNA extraction procedures meaningfully influence qPCR-based mtDNA copy number determination. Mitochondrion. 2009 jul;9(4):261–5. 86. Demeke T, Jenkins GR. Influence of DNA extraction methods, PCR inhibitors and quantification methods on real-time PCR assay of biotechnology-derived traits. Anal Bioanal Chem. 2010 mar;396(6):1977–90. 87. Chen J, Kadlubar FF, Chen JZ. DNA supercoiling suppresses real-time PCR: a new approach to the quantification of mitochondrial DNA damage and repair. Nucleic Acids Res. 2007;35(4):1377–88. 88. Lin C-H, Chen Y-C, Pan T-M. Quantification bias caused by plasmid DNA conformation in quantitative real-time PCR assay. PLoS ONE. 2011;6(12):e29101. 89. Hou Y, Zhang H, Miranda L, Lin S. Serious overestimation in quantitative PCR by circular (supercoiled) plasmid standard: microalgal pcna as the model gene. PLoS ONE. 2010;5(3):e9545. 90. Bustin SA, Benes V, Garson JA, Hellemans J, Huggett J, Kubista M, et al. The MIQE guidelines: minimum information for publication of quantitative real-time PCR experiments. Clin. Chem. 2009 abr;55(4):611–22. 91. Casasnovas JA, Alcalde V, Civeira F, Guallar E, Ibanez B, Jimenez-Borreguero J, et al. Aragon workers’ health study - design and cohort description. BMC cardiovascular disorders. 2012 jun 19;12(1):45. 92. Marcuello A, Martínez-Redondo D, Dahmani Y, Casajús JA, Ruiz-Pesini E, Montoya J, et al. Human mitochondrial variants influence on oxygen consumption. Mitochondrion. 2009 feb;9(1):27–30. 93. 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 dic;25(4):402–8. 94. Jackson CB, Gallati S, Schaller A. qPCR-based mitochondrial DNA quantification: Influence of template DNA fragmentation on accuracy. Biochem. Biophys. Res. Commun. 2012 jul 6;423(3):441–7. 95. Souza ACR, Ferreira RC, Gonçalves SS, Quindós G, Eraso E, Bizerra FC, et al. Accurate identification of Candida parapsilosis (sensu lato) by use of mitochondrial DNA and real-time PCR. J. Clin. Microbiol. 2012 jul;50(7):2310–4. 53 96. Pyle A, Burn DJ, Gordon C, Swan C, Chinnery PF, Baudouin SV. Fall in circulating mononuclear cell mitochondrial DNA content in human sepsis. Intensive Care Med. 2010 jun;36(6):956–62. 97. Bernth Jensen JM, Petersen MS, Stegger M, Østergaard LJ, Møller BK. Real-time relative qPCR without reference to control samples and estimation of run-specific PCR parameters from run-internal mini-standard curves. PLoS ONE. 2010;5(7):e11723. 98. Lippi G, Plebani M. EDTA-dependent pseudothrombocytopenia: further insights and recommendations for prevention of a clinically threatening artifact. Clin. Chem. Lab. Med. 2012 ago 1;50(8):1281–5.