Is mitochondrial DNA content a potential biomarker of mitochondrial dysfunction?
Introduction
Mitochondria are independent double membrane organelles found in the cytosol of eukaryotic cells which are involved in energy production, specifically they carry out oxidative phosphorylation (OXPHOS), to produce ATP for the many functions in the cell that require energy (Wojtczak and Zabłocki, 2008). As well as energy production, mitochondria are also involved in the regulation of numerous other cellular functions including cell proliferation, apoptosis, and intracellular calcium homeostasis. Mitochondria are a major site of reactive oxygen species (ROS) generation, produced as a side product of ATP production through electron leakage from the electron transport chain. Because of their involvement in several fundamental cellular processes, mitochondrial dysfunction can affect a range of important cellular functions and can result in a variety of diseases (Michel et al., 2012, Wallace, 1999).
Mitochondria contain their own a circular DNA genome which unlike the nuclear genome is unmethylated (Groot and Kroon, 1979) and consists of a heavy and light strand, organised into a nucleoprotein as a complex with the transcription factor A (TFAM) protein, and termed a nucleoid, which is found associated with the inner mitochondrial membrane (Bogenhagen, 2011, Falkenberg et al., 2007). Individual mitochondria can contain several copies of the mitochondrial genome (Cavelier et al., 2000, Navratil et al., 2007, Veltri et al., 1990). Under normal conditions, the maternally inherited mitochondrial genome in an individual will be the same in all cell types unless it has been damaged via mutations or deletions, in which case cells may exhibit heteroplasmy in their mitochondria (Chinnery et al., 2000, Moraes et al., 2003). The replication and transcription of the mitochondrial genome are regulated via the actions of a combination of proteins including TFAM, RNA polymerase (POLRMT), DNA polymerase POLG, transcription factors 1 and 2 (TFB1M and TFB2M), nuclear respiratory factors 1 and 2 (NRF-1, NRF-2) and peroxisome proliferator-coactivated receptor gamma co-activator 1-alpha (PGC1-α) (Campbell et al., 2012, Falkenberg et al., 2007, Hock and Kralli, 2009, Leigh-Brown et al., 2010, Moraes, 2001).
The human mitochondrial genome is 16,569 bp long and consists of 37 genes, 13 of which code for components of the respiratory chain, known as the electron transport chain, and the remainder make transfer RNA and ribosomal RNAs needed for mitochondrial protein synthesis. The nuclear genome encodes the remaining mitochondrial messenger RNAs, which are translated at cytosolic ribosomes and their corresponding proteins are transported into mitochondria for assembly (Scheffler, 2008). Although mitochondria contain large numbers of different proteins, estimated to be 500–1000 or greater in different studies, the mitochondrial proteome shows tissue specific profiles (Johnson et al., 2007, Smith et al., 2012, Taylor et al., 2003). Oxidative phosphorylation capacity, as distinct from mitochondrial mass, is also diverse in different rat tissues and is determined by a combination of mitochondrial content and the amounts of the respiratory chain complexes as well as their intrinsic activity (Benard et al., 2006, Fernandez-Vizarra et al., 2011). The number of mitochondria in a cell varies depending on the energetic requirements of the cell, for example a brain cell may have around 2000 mitochondria (Uranova et al., 2001), a white blood cell may have less than a hundred (Selak et al., 2011) whereas oocytes may contain several hundred thousand mitochondria (Duran et al., 2011, Piko and Matsumoto, 1976). The number of mitochondria in a particular cell type can also vary depending on many factors, including the stage in the cell cycle, the environment and redox balance of the cell, the stage of differentiation, and a number of cell signalling mechanisms (Michel et al., 2012, Rodriguez-Enriquez et al., 2009).
As mitochondria contain their own DNA outside of the nuclear genome, a convenient way to measure mitochondrial DNA content in a cell is to measure mitochondrial versus nuclear genome ratio, termed Mt/N (Malik et al., 2009, Malik et al., 2011). This approach is attractive as the methodology for quantifying nucleic acids is more advanced and available widely compared to methods for measuring the whole mitochondrial organelle or components of the OXPHOS system using imaging, cell biology or protein quantification techniques. Earlier studies measured Mt/N using nucleic acid hybridisation, for example slot blot or Southern blotting, but in the last decade real time quantitative PCR (qPCR) has become the method of choice. The method involves isolation of genomic DNA from cells or tissues of choice, and the use of qPCR to quantify a mitochondrial and a nuclear gene (Andreu et al., 2009, Gourlain et al., 2003, Malik et al., 2011). In order to determine if Mt/N is a potential biomarker of mitochondrial dysfunction, it is important to validate methods for accurate and reproducible measurement of cellular MtDNA content. In the current review, we will first make the case that changes in MtDNA content could be used as a biomarker to detect mitochondrial dysfunction. We will briefly describe some of the many studies which have shown that changes in MtDNA content correlate with numerous diseases, and we will discuss how the current methodology may be leading to confusing data in the literature.
Section snippets
The Mt/N hypothesis
In the current article we propose the theory that MtDNA content measured as Mt/N (mitochondrial to nuclear genome ratio) is a biomarker of mitochondrial dysfunction. The premise of this theory is that the Mt/N value of particular cell type, normally within a healthy range, could change in conditions of oxidative stress. The initial response to increased oxidative stress would be an adaptive response where Mt/N values would increase as a result of increased mitochondrial biogenesis. In
Oxidative stress
Oxidative stress has emerged as a key feature in many common diseases including diabetic complications, cardiovascular disease, neurodegenerative disease, cancer, renal disease and others (Halliwell and Gutteridge, 2007). Oxidative stress is the result of a disturbance in the redox balance of the cell, resulting in excessive oxidation (or conversely, excessive reduction) of intracellular proteins. Oxidation and reduction of proteins is a major signalling mechanism of intracellular control and
Oxidative stress can lead to mitochondrial damage and mitochondrial biogenesis
In normal healthy cells mitochondria are present as an interconnected network or several networks rather than the old fashioned view of solitary organelles (Bereiter-Hahn et al., 2008). Mitochondrial mass in a cell is controlled through both biogenesis and degradation of the mitochondria, however abnormal signalling could result in an adaptive response through enhanced production of mitochondria (Michel et al., 2012). The shape of mitochondria can change via processes known as fission and
Methods for measuring mitochondrial DNA content biogenesis and mass
As our hypothesis centres around the idea that oxidative stress can result in changes in mitochondrial biogenesis and possibly the amount of mitochondria in a cell, it is necessary to measure mitochondrial content in cells in order to test the hypothesis. However the methodology for the measurement of the mitochondrial content of a cell is not straightforward as mitochondria usually exist as an interconnected network rather than solitary organelles. Mitochondrial biogenesis and mass can be
Mitochondrial DNA changes in human disease
Mutations in MtDNA have been known for some time to lead to genetic mitochondrial disease which can be multi-organ and affect individuals at a young age. It has become apparent that acquired pathogenic mutations in MtDNA are involved in numerous common adult diseases including neurodegenerative disease, diabetes, cancer and ageing (Chinnery and Samuels, 1999, Wallace, 1999, Wallace, 2010). Discussion of pathogenic mutations in mitochondrial genetic or more common diseases of adults is beyond
Could altered mitochondrial DNA content contribute directly to pathology?
Our intention in the above section was to show the large number of studies reporting changes in MtDNA content in body fluids, cells and tissues from the human body in a wide range of diseases and in other situations such as development and response to exercise. Our list is by no means exhaustive and does not attempt to relate these changes to or comment on the integrity of the MtDNA being measured. It is difficult to reconcile the view that in health more mitochondria are viewed as beneficial
Problems with methods for measurement of mitochondrial DNA content
Despite the large numbers of studies where changes in MtDNA content have been reported, in many cases the methodology being used leads to data which cannot be compared between studies. There is little consensus on actual copy numbers of MtDNA in specific cells or organs. For example despite the numerous human studies using whole blood, plasma, lymphocytes or mononuclear peripheral blood cells, comparison of the data across the studies does not allow a clear consensus of Mt/N values in the
Concluding remarks
MtDNA content changes have been reported using DNA isolated from various body fluids such as circulating blood cells, cell free serum, saliva, sperm, urine and cerebrospinal fluid (Table 2a) and also in tissue samples such as tumour tissue and various organs and biopsy materials (Table 2b). There is clearly a widespread interest in measuring Mt/N in different body fluids and tissues in a very wide range of human diseases as well as in development, ageing and effects of the environment (see
Acknowledgements
We are grateful to Targeting Mitochondria Conference for inviting this review, Dr Rojeen Shahni for contribution of figures, Dr Joe Bateman, Dr Mike Christie and Dr Saima Ajaz for proof reading the manuscript. Thanks also to members of the NIH mitochondria interest group for providing information on some aspects reviewed here. AC is supported by a King's College London PhD studentship.
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