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Mitochondrion

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Short communication

Predicted ionisation in mitochondria and observed acute changes in themitochondrial transcriptome after gamma irradiation: A Monte Carlo simulation andquantitative PCR study

Winnie Wai-Ying Kam a,d,⁎,1, Aimee L. McNamara b,1, Vanessa Lake a, Connie Banos a, Justin B. Davies a,b,Zdenka Kuncic b, Richard B. Banati a,c,d

a Australian Nuclear Science and Technology Organisation, Lucas Heights, Sydney, New South Wales 2234, Australiab School of Physics, University of Sydney, Camperdown, Sydney, New South Wales 2006, Australiac National Imaging Facility at Brain and Mind Research Institute (BMRI), University of Sydney, Camperdown, Sydney, New South Wales 2050, Australiad Medical Radiation Sciences, Faculty of Health Sciences, University of Sydney, Cumberland, Sydney, New South Wales 2141, Australia

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⁎ Corresponding author at: AustralianNuclear Science andHeights, Sydney, New SouthWales 2234, Australia. Tel.: +69262.

E-mail addresses: wik@ansto.gov.au, winikam@gma1 These authors contributed equally to this work.

1567-7249/$ – see front matter © 2013 Elsevier B.V. anhttp://dx.doi.org/10.1016/j.mito.2013.02.005

Please cite this article as: Kam, W.W.-Y.,transcriptome after gamma irradiation: ..., M

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Article history:Received 7 November 2012Received in revised form 14 January 2013Accepted 13 February 2013Available online xxxx

Keywords:MitochondriaIonising radiationMonte Carlo radiation transportQuantitative polymerase chain reaction(qPCR)RNA

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RECTED It is a widely accepted that the cell nucleus is the primary site of radiation damage while extra-nuclear

radiation effects are not yet systematically included into models of radiation damage.We performed Monte Carlo simulations assuming a spherical cell (diameter 11.5 μm) modelled after JURKATcells with the inclusion of realistic elemental composition data based on published literature. The cell modelconsists of cytoplasm (density 1 g/cm3), nucleus (diameter 8.5 μm; 40% of cell volume) as well as cylindricalmitochondria (diameter 1 μm; volume 0.5 μm3) of three different densities (1, 2 and 10 g/cm3) and totalmitochondrial volume relative to the cell volume (10, 20, 30%). Our simulation predicts that if mitochondriatake up more than 20% of a cell's volume, ionisation events will be the preferentially located in mitochondriarather than in the cell nucleus.Using quantitative polymerase chain reaction, we substantiate in JURKAT cells that human mitochondriarespond to gamma radiation with early (within 30 min) differential changes in the expression levels of 18mitochondrially encoded genes, whereby the number of regulated genes varies in a dose-dependent butnon-linear pattern (10 Gy: 1 gene; 50 Gy: 5 genes; 100 Gy: 12 genes).The simulation data as well as the experimental observations suggest that current models of acute radiationeffects, which largely focus on nuclear effects, might benefit frommore systematic considerations of the earlymitochondrial responses and how these may subsequently determine cell response to ionising radiation.

© 2013 Elsevier B.V. and Mitochondria Research Society. All rights reserved.

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UNCO1. Introduction

Most studies of cellular responses to ionising radiation are centredon the nuclear DNA, whereby the DNA repair processes, rather thanthe damage directly, are used as proxy read-outs to determine theextent of nuclear DNA damage (Aziz et al., 2012). However, significanteffects of ionising radiation on mitochondrial functions (Hwang et al.,1999; Yukawa et al., 1985), mitochondrial oxidative stress (Hosoki etal., 2012; Kobashigawa et al., 2011; Motoori et al., 2001; Tulard et al.,2003) and apoptotic pathways (Belka et al., 2000; Chen et al., 2003;Leach et al., 2001; Zhao et al., 1999) have been reported. Indeed, someexperimental observations indicate that the mitochondrial genomemay be more susceptible to damaging effects by gamma irradiation

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il.com (W.W.-Y. Kam).

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et al., Predicted ionisation iitochondrion (2013), http://d

than the nuclear genome (Gong et al., 1998; May and Bohr, 2000;Morales et al., 1998), possibly by virtue of the greater likelihood ofmitochondria suffering oxidative damage (Yakes and Houten, 1997).In addition to direct radiation effects on mitochondria, mitochondriadysfunction may exert an indirect influence on the nucleus andperpetuate radiation-induced genomic instability (Kim et al., 2006a,2006b; Miller et al., 2008).

Monte Carlo track structure simulations (Zaider et al., 1983) can beused to estimate likely regions of radiation damage within the cell(Alard et al., 2002; Chauvie et al., 2007; Miller et al., 2000). Todate, however, track structure simulations have mostly focused onpredicting the occurrence of single or double strand breaks in nuclearDNA as a result of physical processes leading to ionisation formation(Grosswendt, 2005; Nikjoo and Goodhead, 1991; Nikjoo et al., 1999).Here, we employ Monte Carlo simulation and develop a more realisticcell model containing both cell nucleus and mitochondria, as well ascurrently available data on the elemental concentration in mitochon-dria (Ernster and Lindberg, 1958; Taylor et al., 1999), in order to predictregionsmostly likely to be subject to damage from ionisation formation.

ll rights reserved.

n mitochondria and observed acute changes in the mitochondrialx.doi.org/10.1016/j.mito.2013.02.005

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We base our model for the simulation on the human leukemic JURKATcell line, which has previously been used to investigate radiation effectsin vitro (Cataldi et al., 2009; Syljuasen andMcBride, 1999; Vigorito et al.,1999). In suspension, the cells are of near-spherical shape (Rosenbluthet al., 2006; Roskams and Rodgers, 2002) and are well characterisedwith respect to the relative volume taken up by mitochondria (Cataldiet al., 2009; Chaigne-Delalande et al., 2008; Kawahara et al., 1998;Ueda et al., 1998; Yasuhara et al., 2003), and their geometry can,therefore, be modelled relatively easily.

PCR or quantitative PCR (qPCR) has previously been used tomeasure changes in gene expression levels after radiation exposure(Gong et al., 1998; Gubina et al., 2010; Kulkarni et al., 2010). To validatein vitro the predictions made by our Monte Carlo simulation thatmitochondria respond to radiation exposure, we quantify by qPCRin JURKAT cells the acute changes in the expression levels of mitochon-drial electron transport chain genes as well as mitochondrial transferRNAs and ribosomal RNAs, in response to a single radiation doseranging from 10 to 100 Gy.

In the present study, we introduce for the first time a modelthat specifically includes the mitochondrial compartment, and makesrealistic assumptions in regard to the content of those atomic elementsin mitochondria that are important for predicting the likely localisationof ionisation events. The qPCR results provide biological evidence thatmitochondria are involved in the early cell response to gammaradiation.

2. Material and methods

2.1. Monte Carlo simulation

Simulations were performed using the open-source, general-purposeMonte Carlo radiation transport simulation toolkit Geant4 version9.4.p02 (Agostinelli et al., 2003; Allison et al., 2006).

2.1.1. A compartmental cell modelA single JURKAT cell was modelled to predict the distribution of

energy deposition and ionisation events within 3 different cellular

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Fig. 1. Illustration of the geometry used in the Geant4 Monte Carlo radiation transportsimulation. The cell is filled with a realistic cytoplasm material. Two specific cell organ-elles are modelled: nucleus (red sphere) and mitochondria (blue cylinders) randomlydistributed throughout the cell. The geometry is realistically based on the spherical cellshape of JURKAT cell in suspension.

Please cite this article as: Kam, W.W.-Y., et al., Predicted ionisation itranscriptome after gamma irradiation: ..., Mitochondrion (2013), http://d

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components, namely the cell cytoplasm, nucleus and mitochondria(Fig. 1).

The cell was modelled as a sphere of diameter 11.5 μm containing acentrally located spherical nucleus with a calculated diameter of 8.5 μm(Rosenbluth et al., 2006). Individual mitochondria were modelled ascylinders with a diameter of 1 μm and total volume of 0.5 μm3

(Roskams and Rodgers, 2002), randomly distributed throughout thecytoplasm. The cell was filled with a uniform cell cytoplasm materialof density 1 g/cm3 and a chemical mass fractional constituent ofH (8.93%), O (58.09%), C (19.97%), N (8.47%) and P (4.54%) (Alard etal., 2002). Similarly, the nucleus was filled with a uniform material ofdensity 2.0 g/cm3 and a mass fractional composition of H (10.64%),O (74.5%), C (9.04%), N (3.21%) and P (2.61%) (Alard et al., 2002).Using published electron-microscopic data (Cataldi et al., 2009;Chaigne-Delalande et al., 2008; Kawahara et al., 1998; Ueda et al.,1998; Yasuhara et al., 2003), indicates that in un-stimulatedJURKAT cells, a cell type that is near-spherical, mitochondria take upapproximately 20–30% of the cell volume. Additionally, it has beenreported that the total mitochondrial volume in mammalian cells is~13% (Kilby, 1979), and that of a lymphocyte is also in a similarrange (Mayhew et al., 1979). For this reason, 3 different mitochondrialvolumes were investigated: 10%, 20% and 30% of the total cellvolume. The density and chemical mass-fraction constituents formitochondria is yet to be fully determined, however, the presenceof heavy ions (e.g. Ca, Mg and Na) have been reported in mitochondria(Ernster and Lindberg, 1958; Taylor et al., 1999). We investigated 3different mitochondrial densities in the simulations, 1, 2 and 10 g/cm3

(based on net wet weight calculations in (He et al., 2010)) and thechemical mass fractional composition was set to H (10.64%),O (71.5%), C (9.04%), N (3.21%), P (2.61%), Na (1%), Ca (1%) and Mg(1%) as a first approximation for all cases. The cell was modelled atthe centre of a liquid water 1.5 ml volume cylinder.

Photons were randomly selected from a 60Co source at a distance of9 mm from the cell centre and emitted across the entire cell volume foreach simulation case. The photon interactions within the volume weremodelled with the Geant4 Low Energy Electromagnetic Package basedon the Livermore libraries, valid down to particle energies of 250 eV.The physics processes included the photoelectric effect, Comptonscattering, Rayleigh scattering and pair production for photons.Additionally, secondary electrons were tracked and the processesactivated included ionisation, bremsstrahlung and multiple scattering.Secondary electron ionisations were modelled and the low energycut-off for the production of secondary particles was set to 250 eV. Atotal of 1.9976×108 incident photons (energies 1.33 MeV and1.1732 MeV sampled from a 60Co source) were simulated for eachcase. The absorbed dose as well as the total number of ionisationsoccurring within each cellular component was calculated.

2.2. Cell irradiation and RT-qPCR

2.2.1. Sample preparationWild type JURKAT cells were maintained at 37 °C with 5% CO2 in

DMEM supplemented with 10% FBS, 2 mM L-glutamine, 100 units/mlpenicillin and 100 μg/ml streptomycin until the day of the experiment.For testing the radiation effect on nucleic acids within cells, cells wereirradiated at a density of 0.16×106 in 1 ml medium (as describedabove) in a 1.5 ml-Eppendorf tube at room temperature.

2.2.2. Gamma irradiationJURKAT cells were gamma irradiated, at room temperature (21±2 °C

in this study), using a 60Co irradiator (GammaCell 220) at 10, 50, 100 Gywhich is the total dose range generally delivered in radiation therapy orused in radiation experiments (see Section 3.2).

The dose rate of 39.0±0.8 Gy/min was determined using thestandard Fricke dosimeter (Fricke and Hart, 1966). At this dose rate,the effect of the dose during transit of the GammaCell 220 chamber

n mitochondria and observed acute changes in the mitochondrialx.doi.org/10.1016/j.mito.2013.02.005

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(5.2±0.4 Gy) was significant and was taken into account whencalculating the exposure times.

2.2.3. RNA isolation and reverse transcriptionCell cultures were kept under the same experimental conditions

except variation in delivered radiation dose, i.e. the RNA wasextracted after 25 min after commencement of the irradiation. Duringthis 25-minute period, the samples were kept at 21 °C (in atemperature-controlled room) at all times. Total RNA extraction wasperformed using PureLink™ RNA Mini Kit (Invitrogen, Carlsbad, CA,USA) following the manufacturer's protocol. To remove residualcontaminant, DNase treatment was done. RNA was eluted inDEPC-treated water. The concentration of the RNA was determinedusing the NanoDrop 2000c Spectrophotometer (Thermo FisherScientific, Waltham, MA, USA). The purity of the extracted RNA wasassessed spectrophotometrically using the A260/A280 ratio.

First strand cDNA was synthesized by oligo(dT) primers from 6 ngof total RNA using the SuperScript® III First-Strand Synthesis kit,according to the manufacturer's protocol (Invitrogen, Carlsbad, CA,USA). Freshly prepared cDNA of each sample was equally dilutedwith DEPC-treated water for the subsequent qPCR assay.

2.2.4. Quantitative PCR (qPCR)Mitochondria PCR arrays are commercially available; however, the

primer and amplicon details are not transparent to users. In order toincrease experimental flexibility, PCR primers were selected frompublished literature. In this study, we obtained specific primers for18, out of a total of 37, mitochondrial genes. These primers were todetect all ribosomal RNAs (2), all messenger RNAs (13) and 3 transferRNAs (3 out of 22) of the mitochondrial genome. Primers for several(3) nuclear subunits of the mitochondrial electron transport chain,as well as actin (a nuclear gene), were also included (Table S1).Primer specificity was confirmed in-house by melt curve analysisprior to the experiment. The specificity of the complex IV subunit 2primer set was further confirmed by sequencing (Accession:AF004339) as the original paper did not specify the target subunit(Cheng et al., 2003). In addition, the annealing temperature wasdetermined empirically to accommodate all primers in a singleqPCR run.

qPCR was performed using the CFX 384™ Real-Time PCR DetectionSystem (BioRad, Hercules, CA, USA). Diluted cDNA or DNA of 1 μl wasadded to 4 μl of reaction mixture containing 2.5 μl of SsoFast™EvaGreen® Supermix (BioRad, Hercules, CA, USA) and 5 pM of each ofthe forward and reverse primers. A common sample was run in eachqPCR as a calibrator to account for the inter-assay variability(determined in-house as 0.76% only). Each samplewas run in duplicate.

The thermal cycling conditions were 98 °C for 30 s, followed by45 cycles at 98 °C for 5 s, 63 °C for 10 s. At the end of the 45th cycle,the temperature was raised to 72 °C for 10 min to ensure the completeextension of the products. A melt curve analysis was performed afterthe qPCR to confirm the specificity of the results. The mean Cq valueof each sample was quantified using the CFXManager™ Software (ver-sion 1.5) (BioRad, Hercules, CA, USA). The amount of gene amplifiedafter radiation treatment was quantified relative to the un-irradiatedsample i.e. 2Cq (un-irradiated sample)−Cq (irradiated sample).

3. Results and discussion

3.1. Energy deposition and ionisation events in nucleus, cytoplasm andmitochondria

Using a cell model based on the idealised geometry of JURKAT cells(Fig. 1), we performed Monte Carlo radiative transport simulations toexamine the dose received as well as the total number of ionisationsformed in different compartments of the cell (nucleus, cytoplasm,

Please cite this article as: Kam, W.W.-Y., et al., Predicted ionisation itranscriptome after gamma irradiation: ..., Mitochondrion (2013), http://d

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mitochondria). Fig. 2 shows the dose and ionisation number foreach organelle in the left and right panels, respectively.

A higher mitochondrial density increases the overall dose receivedby each cellular component considered. However, the dose depositedin each organelle for a given mitochondrial density only differsslightly (less than 0.5 mGy for most cases). Introducing mitochondrialvolumes into the cell model can also increase the absorbed energyreceived by the rest of the cell. For a total mitochondrial volume of30%, the absorbed dose in the different components shows the largestdeviation, with the highest dose now occurring in the cytoplasm. Thisis attributed to an increased number of secondary electrons producedin the mitochondria, which can then traverse the organelle anddeposit energy in the cytoplasm or nucleus (Fig. 2, left panel, bottomimage).

Wefind that a large number of ionisation events ismostly associatedwith low energy depositions and Fig. 2 (right panel) indeed shows thatincreasing the mitochondrial density in turn increases the frequency oflow energy depositions in themitochondria. Specifically, the number ofionisation events occurring within the components increases withmitochondrial density as well as with total mitochondrial volume.There is a large difference in ionisation number between componentsfor a given mitochondrial density, especially for densities larger than2 g/cm3 (Fig. 2, right panel). Single or double strand breaks innucleic acid molecules from the direct effects of ionising radiation arepredominantly caused by multiple ionisations occurring within sitesof 2 to 3 nm (Brenner and Ward, 1992). Simulations have shown thatlow energy secondary electrons (b1 keV) can be responsible for up to50% of ionisations (Nikjoo and Goodhead, 1991) and this is possibly amore biologically pertinent quantity than the total absorbed dose,since ionisations directly correlate with free radical production(Morales et al., 1998), which would be expected to cause a higher rateof strand breaks.

Our predicted differences in dose and ionisation number betweenthe different components can be attributed to the composition anddensity differences between the media since, for the case of 1 g/cm3

the cytoplasm and mitochondria (with same density but slightlydifferent composition) have similar dose and total ionisationnumbers.

The chemical composition and density of the mitochondria arechallenging to determine experimentally. The mitochondrion modelconsidered here is a first approximation and we only consider the traceamounts of heavy ions in the mitochondria, with a range of densities.Here we show that the dose and ionisation event distribution in the cellis sensitive to the mitochondrial volume and density. Thus a moreaccurate model, with refined experimentally specified mitochondrialdensity and chemical composition, is warranted for a better under-standing of the radiation response of the cell. Additionally the clusteringof ionisations on the nanometre scale could be further investigated topredict the probability of strand breaks occurring in molecules withinthe mitochondria (McNamara et al., 2012).

3.2. Acute change in nuclear and mitochondrial gene expression inresponse to gamma irradiation

The responses of the irradiated cells are usually studied afterhours or days of recovery and information on the acute cellularchanges after irradiation is limited. In this study, RNA was harvestedwithout a prolonged recovery (within 30 min post irradiation) inorder to determine the acute cellular response to radiation stress.

A total dose of 10, 50 or 100 Gy was delivered to the cells.These doses were chosen to cover the dose range generally used inexperimental and clinical settings. For example, cell culture, isolatedcells or animal irradiation may be performed at a dose of ~10 to 50 Gyin a single exposure (Epperly et al., 2000, 2003, 2009; Gubina et al.,2010; Indo et al., 2012; Pearce et al., 2001; Prithivirajsingh et al.,2004; Yamamori et al., 2012). The total dose for a set of standard

n mitochondria and observed acute changes in the mitochondrialx.doi.org/10.1016/j.mito.2013.02.005

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Fig. 2. Total absorbed dose and ionisation number in a compartmental cell model of different mitochondrial densities and volumes. Three different cellular components are con-sidered: the cytoplasm (green), nucleus (red) and mitochondria (blue) for different mitochondrial densities. The mitochondrial volumes considered are 10%, 20% and 30% of thetotal cell volume. The absorbed dose distribution and number of ionisations are shown on the left and right panel, respectively.

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20 to 60 Gy (Chan et al., 2001; Steen et al., 2001; Tanriover et al.,2007). Radiation studies using doses up to 150 Gy (Richter et al.,1988), 250 Gy (Pinto et al., 2002) or even 560 Gy (May and Bohr,2000), have also been reported.

Our qPCR results are presented as fold change relative to theun-irradiated control, with value>1 indicates an increase in geneexpression after irradiation while valueb1 represents the opposite(Fig. 3, dashed line). In our study, we observed that the number ofgenes that show expression changes increases with an increase inradiation dose. Specifically, at 10 Gy of irradiation at room tempera-ture, transcription levels of 4 out of 22 tested genes showed a change.At 50 Gy, there were 9 genes; at 100 Gy, there were 16 genes (Fig. 3,red boxes).

For the tested nuclear genes, the level of change ranged from ~30to 330%, and was an increase (Fig. 3, white region, black dots).Radiation-induced changes in nuclear gene expression have beenpreviously reported (Chaudhry, 2008; Kis et al., 2006; Smirnov etal., 2009). Our results additionally reveal that such nuclear geneexpression changes can be measured soon after irradiation (Fig. 3;white region, black dots).

Furthermore, a few studies reported expression changes inmitochondrial genes after X-ray (Gubina et al., 2010; Kulkarni et al.,2010) or gamma-ray (Gong et al., 1998) irradiation. However, onlya small number of mitochondrial genes were examined in thosereports as well as raising some technical issues in PCR quantification(see Section 3.3). Here, we examined 18 mitochondrially encodedgenes, including not only the messenger RNAs but also the transferand ribosomal RNAs of the mitochondria. We observed acute (within30 min) differential changes in the expression of the ribosomal and

Please cite this article as: Kam, W.W.-Y., et al., Predicted ionisation itranscriptome after gamma irradiation: ..., Mitochondrion (2013), http://d

the tested transfer RNAs, in addition to messenger RNAs across aradiation dose range frequently applied in clinical and experimentalsettings (10 to 100 Gy). The level of change ranged from ~30 to80%, and that could either be an increase or a decrease (Fig. 3,grey-shaded region, black dots).

The Monte Carlo simulations predicted that mitochondria are sitesof potentially significant ionisation clustering (Fig. 2, right panel) andthus raises the question whether the extra-nuclear mitochondrialgenome might acutely respond to gamma-irradiation. Our qPCRresults (Fig. 3) indicate that radiation indeed leads to acute changesin the transcript levels of genes known to be crucial for cellularenergy production, such as the mitochondrial electron transportchain. Not only are mitochondria important for normal cellfunctioning, but their mitochondrial DNA repair system appears tobe relatively inefficient compared to nuclear DNA (Clayton et al.,1974; Croteau et al., 1999; Lansman and Clayton, 1975; Larsen et al.,2005). For example, it has been shown that after ionising radiationthe rate DNA repair in mitochondria is less than in the nucleus(May and Bohr, 2000). Others have shown a link between the stateof mitochondria and radiation-induced genomic instability (Kim etal., 2006a, 2006b; Miller et al., 2008). This raises the possibility thatmitochondria are not only a preferential site for ionisation eventsbut that the acute radiation-induced changes in mitochondrial geneexpression may cause secondary effects on nuclear DNA.

3.3. Technical consideration — PCR quantification

Housekeeping genes are generally assumed to stably expressacross experimental conditions and are frequently used in PCRquantification including those in radiation studies (Gubina et al.,

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Fig. 3. Mitochondrial and nuclear-encoded gene expressions after irradiation at room temperature. JURKAT cells were exposed to 0 (control), 10, 50, 100 Gy of gamma radiation atroom temperature (21±2 °C). Total RNA was extracted soon after the irradiation and reversed-transcribed to cDNA for qPCR assay. Quantification was performed relative to theun-irradiated sample i.e. 2Cq (un-irradiated sample)−Cq (irradiated sample). Fold change at 1 indicates identical expression level of the tested gene before and after irradiation (dashed line).The expression of the tested mitochondrial (grey-shaded box) and nuclear-encoded (white box) genes is shown. Error bar represents standard deviation (N=3). rRNA=ribosomalRNA; tRNA=transfer RNA; mRNA=messenger RNA. Red box indicates the gene from samples irradiated at room temperature with a fold change in expression of ±~30% or more.

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2010; Kulkarni et al., 2010). However, housekeeping genes have beenshown to respond to variations in experimental conditions (de Kok etal., 2005; Oikarinen et al., 1991; Spanakis, 1993) and can substantiallyaffect the accuracy of gene expression analysis. In this study, we avoidthe above problem by using another commonly used method i.e. foldchange, for gene expression quantification. This method comparesthe expression between the irradiated and un-irradiated samples.

Using fold change for gene quantification, we found that that thecommonly used housekeeping gene, actin, was not stable across thedose range used in our and many other radiation experiments.When compared to the un-irradiated control, the expression ofactin of the irradiated cells increased ~30% at 10 Gy, ~90% at 50 Gyand ~220% at 100 Gy (Fig. 3, black dot, “Actin” column). If actinswere used as the normalizer in this study, our gene expressionresults would be incorrect. The choice of PCR quantificationmethod is thus important and has to be borne in mind when PCRdata from different studies are compared. Future work will need to

Please cite this article as: Kam, W.W.-Y., et al., Predicted ionisation itranscriptome after gamma irradiation: ..., Mitochondrion (2013), http://d

systematically identify suitable genes that are stably expressedunder the specific experimental conditions used here. The identifica-tion of such housekeeping genes would allow for a more sensitivedetection of subtle variations in gene expression and would beappropriate for studies of the mitochondrial gene regulation at lowdose irradiation (b10 Gy).

4. Conclusions

Our predicted and observed results draw attention to the importanceofmitochondria as a direct target that is likely to influence the immediateresponse to radiation. Current models do not specifically take intoaccount any possibility of mitochondrially mediated post-radiationeffects. However, for a more comprehensive understanding of theoverall cellular radiation effects, not only the changes in the nuclearbut also the mitochondrial genome is important (Schilling-Toth etal., 2011). Apart from affecting cell survival and functioning,

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radiation-induced mitochondrial dysfunction can indirectly increasein nuclear genome instability (Kim et al., 2006a, 2006b; Miller et al.,2008).

Future modelling of radiation effects could thus be made morerealistic by taking into account the likely amount of radiation receivedby mitochondria and their response to radiation as well as its contribu-tion to delayed outcomes. The inclusion of mitochondrial dosemodelling would be in addition and not in lieu of the currentsimplifying assumptions that focus on the effects of radiation in thecell nucleus only. Future work needs to link microdosimetricmeasurements of ionisation events occurring in subcellularcompartments and organelles directly with biologically relevantmeasurements of the acute radiation-induced changes in organicmolecules and the early cascade of biological responses.

Supplementary data to this article can be found online at http://dx.doi.org/10.1016/j.mito.2013.02.005.

5. Uncited references

Baird et al., 2011Brzozowska et al., 2009Dang et al., 2012de Vries et al., 1993Garbian et al., 2010Gaspari et al., 2004Haynes, 2011Kitano et al., 2007Lundgren-Eriksson et al., 2001aLundgren-Eriksson et al., 2001bOwens et al., 2011Rorbach et al., 2008Uchiumi et al., 2010Wilkening et al., 2003

Acknowledgements

Special thanks should be given to Mr Sohil Sheth and Mr AllanPerry, for their technical assistance in performing the irradiationexperiments. Dr Cy Jeffries, for his suggestions on the experimentaldesign and critical comments on this manuscript. Dr AlessandraMalaroda, for her critical reading and discussion of the manuscript.Mrs Geetanjali Dhand, for her generous assistance in improving theimage quality.

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