Transitional correlation between inner-membrane potential and ATP levels of neuronal mitochondria

The importance of highly active mitochondria and their contribution to neuronal function has been of recent interest. In most cases, however, mitochondrial activity is estimated using measurements of mitochondrial inner membrane potential (IMPmito), and little is known about the dynamics of native mitochondrial ATP (ATPmito). This study conducted simultaneous imaging of IMPmito and ATPmito in neurons to explore their behaviour and their correlation during physiological mitochondrial/neuronal activity. We found that mitochondrial size, transport velocity and transport direction are not dependent on ATPmito or IMPmito. However, changes in ATPmito and IMPmito during mitochondrial fission/fusion were found; IMPmito depolarized via mitochondrial fission and hyperpolarized via fusion, and ATPmito levels increased after fusion. Because the density of mitochondria is higher in growth cones (GCs) than in axonal processes, integrated ATPmito signals (density × ATPmito) were higher in GCs. This integrated signal in GCs correlated with axonal elongation. However, while the averaged IMPmito was relatively hyperpolarized in GCs, there was no correlation between IMPmito in GCs and axonal elongation. A detailed time-course analysis performed to clarify the reason for these discrepancies showed that IMPmito and ATPmito levels did not always correlate accurately; rather, there were several correlation patterns that changed over time.

. Furthermore, a consensus regarding a mutual relationship between IMP mito and direction of transport has not been established. Miller and Sheetz suggested that 90% of mitochondria with high IMP mito move anterogradely, whereas 80% of those with low IMP mito move retrogradely 22 , while another study showed no correlation between IMP mito and the direction of axonal transport 23 . Due to the mutual dependency and complexity of several mitochondrial properties, it is necessary to study mitochondrial function without artificial interruption to clarify native mitochondrial behaviour.
To clarify native mitochondrial behaviour, especially regarding energy metabolism abilities, direct measurements of ATP mito , IMP mito and other properties such as transport, morphology or distribution under physiological condition are necessary. Although mitochondrial isolation 24 is one of effective method for characterisation of a mitochondrion, some property such as transport or distribution need to be measured within cells. However, little research has been conducted investigating ATP mito measurements under physiological conditions or with other mitochondrial parameters in living cells. There are several reasons for this: (1) there are limited methods to directly measure ATP mito with high spatiotemporal resolution 25,26 ; (2) in general, change in ATP levels without extensive stimulation is subtle, and therefore hard to evaluate; and (3) assessing a variety of properties simultaneously requires elaborate and careful preparation, conditioning and treatment in both experimentation and analysis. However, we recently used spatiotemporal image processing analysis to overcome such problems and have demonstrated relationships between biological signals collected from simultaneous fluorescent imaging under physiological conditions 27,28 .
With this background, we conducted simultaneous fluorescent imaging of ATP mito , IMP mito , and other mitochondrial or neuronal properties in neurons using mitAT1.03 25,29,30 , an ATP mito indicator, and tetramethylrhodamine ethyl ester (TMRE) 31,32 , an IMP mito indicator, in this present study. Detailed analysis of the relationships revealed that not all ATP mito and IMP mito correlated accurately, and as for axonal elongation, ATP mito is more a dominant factor than IMP mito .

Results
IMP mito and ATP mito in transport. Firstly, to investigate ATP mito or IMP mito dependency on transportation, we compared ATP mito or IMP mito among anterogradely transported, stationary and retrogradely transported mitochondria within axonal processes using kymographs (Figs 1, S1, S2). Mitochondria that moved anterogradely had relatively higher levels of ATP mito ; however, the difference was not significant (Fig. 1h). IMP mito was relatively depolarized in retrogradely transported mitochondria compared to anterogradely transported mitochondria. However, there was no significant difference between the IMP mito of anterogradely transported mitochondria and stationary mitochondria (Fig. 1i). No ATP mito or IMP mito dependence on mitochondrial velocity and transported distance was found ( Supplementary Fig. S3). Results of ATP mito and IMP mito were expected to be similar; however, our result showed that they did not accurately coincide. IMP mito and ATP mito in fission/fusion. In addition to transported mitochondria, some mitochondria underwent fusion or fission events during observations. Using kymograph, we explored ATP mito and IMP mito behaviour during fusion or fission events. During fusion events, IMP mito more polarized in a post-fusion mitochondrion compared to the average of the two pre-fusion mitochondria (Fig. 2, left). Likewise, ATP mito in a post-fusion mitochondrion were higher than the average of the two pre-fusion mitochondria (Fig. 2, left). During fission events, there was a difference in IMP mito between the two post-fission mitochondria. Then, we compared the changes in IMP mito and ATP mito in both of the two post-fission mitochondria, respectively: one with a relatively highly polarized and the other with a relatively less polarized IMP mito (named Post-1 and Post-2 in Fig. 2, right, respectively). During fission events, the IMP mito of Post-2 was less polarized than that of the pre-fission mitochondrion as previously reported 33 , while that of Post-1 was the same as that of a pre-fission mitochondrion (Fig. 2, right); however, no ATP mito changes were observed. This result also indicated that ATP mito and IMP mito are not always behave similarly. IMP mito and ATP mito in distribution. We next assessed mitochondrial density using still images ( Supplementary Fig. S4). Mitochondrial density was defined as: (sum of area dominated by all mitochondria)/ (area size of GC or axonal process). We confirmed that mitochondrial density was higher in the GCs compared to the axonal process (Fig. 3a). Although average ATP mito were slightly lower in the GCs compared to the axonal process, integrated ATP mito signals (calculated by multiplying average ATP mito and mitochondrial density) were high in the GCs due to the high mitochondrial density (Fig. 3b,c). Average IMP mito relatively hyperpolarized in the GCs than in the axonal process (Fig. 3d). ATP mito in GCs and axonal elongation have a positive correlation. Because GC is a structure related to axonal elongation, we quantified the distance of axonal elongation, and examined the role of mitochondrial dynamics in elongation. Among neurons grown during 10 min observation, the distance of axonal elongation and ATP mito or integrated ATP mito signals in the GCs showed a positive correlation (Fig. 3e,f). This correlation was stronger in GCs than in axonal processes (Fig. 3h,i,k,l). Furthermore, no correlation was found between elongation and IMP mito for both GCs and axonal processes (Fig. 3g,j,m). These results suggest that ATP mito in GCs, but not IMP mito in GCs, contribute to axonal elongation.

ATP mito in GCs are involved in axonal elongation and GC morphological change.
To verify the importance of ATP mito in GCs for elongation, we further examined the effect of artificially disrupting IMP mito or ATP mito on axonal elongation using a mitochondrial uncoupler, carbonyl cyanide-p-trifluoromethoxyphenylhydrazone (FCCP), or the ATP synthase inhibitor, Oligomycin A, respectively.
Both FCCP and Oligomycin A induced apparent drawing back of neurons compared to the control condition (i.e., neurons without drug treatment; Supplementary Fig. S5a-c). However, the detail of change in IMP mito and ATP mito differed between FCCP and Oligomycin A, as well as between GCs and axonal processes. In GCs treated with FCCP, IMP mito depolarized and ATP mito decreased, and the declines correlated with axonal drawing backs ( Supplementary Fig. S5d, upper). On the other hand, in axonal processes treated with FCCP, although IMP mito depolarized, ATP mito did not significantly change ( Supplementary Fig. S5d, lower). As a result, no correlation was observed in axonal processes between the decrease in ATP mito and axonal drawing back. Although drawing back and depolarization of IMP mito showed a correlation in axonal processes, the peak was lower than that in GCs. After treatment with Oligomycin A, ATP mito decreased both in GCs and axonal processes; however, IMP mito levels did not change for either GCs or axonal processes ( Supplementary Fig. S5e). Therefore, no correlation was found between IMP mito and drawing back while there was a correlation between the decrease in ATP mito and drawing back. Again, the correlation was more remarkable in GCs.
Axons drew back even when IMP mito did not show depolarization ( Supplementary Fig. S5c-e). Additionally, axonal drawing back correlated more with the decrease in ATP mito than in IMP mito , and this correlation was higher in GCs than in the axonal processes. These results again indicated that ATP mito , especially in GCs, are crucial for axonal elongation.
In addition to axonal process drawing back, GC collapse was observed. To examine this change quantitatively, we conducted additional analyses of the changes in GC morphology, with a focus on the effect of Oligomycin A because it induced more drastic morphological changes than FCCP. The indices that we quantified were (i) area, (ii) newly appeared area, (iii) newly disappeared area, (iv) the sum of the newly appeared area and the newly disappeared area, (v) edge length and (vi) the ratio of edge length to area of both the peripheral-(P-) and the central-(C-) domains of the GC ( Supplementary Fig. S6). The (ii) newly appeared area, (iii) newly disappeared area and (iv) their sum in the P-domain correlated positively with axonal drawing back after treatment with Oligomycin A. This means that these indices decreased along with drawing back of the axonal process. The (i) area of the C-domain and the (v) edge length of both the P-and C-domains exhibited peaks before (negative time lag values) and after (positive time lag values) drawing back. This means that axonal drawing back occurred after the C-domain area decreased (the positive peak at negative time lag), and that the C-domain area relatively increased after drawing back (the negative peak at positive time lag). Peaks in the (v) edge length and (vi) ratio of edge length to area of the P-domain shows that the P-domain attains a less protrusive morphology before axonal  Moreover, correlation analysis between these indices and ATP mito revealed that the (ii) newly appeared area, (iii) the newly disappeared area and (iv) their sum in the P-domain correlated positively with ATP mito in the GC ( Supplementary Fig. S7). Importantly, none of these indices correlated in the C-domain or the axonal process. These results indicate that although ATP mito decrease and axonal drawing back were positively correlated ( Supplementary Fig. S5e), analysis focused on GC morphology revealed that ATP downregulation manifested as less dynamic morphological changes in the P-domain of the GC. Because morphological changes in the P-domain relies mainly on actin dynamics, these results suggest the importance of ATP in actin turnover in GCs.
Actin turnover is one processes related to neuronal ATP dynamics. To clarify the relevance of actin dynamics, we explored the changes in the GC morphology and cytosolic/mitochondrial ATP levels in response to treatment with Latrunculin A, an inhibitor of actin turnover ( Supplementary Fig. S8). Latrunculin A treatment led to a decrease in the number of newly appeared area in the P-domain, but not the C-domain ( Supplementary  Fig. S8a). Latrunculin A treatment caused no change in ATP mito ( Supplementary Fig. S8d); however, cytosolic ATP levels increased both in the P-and C-domains ( Supplementary Fig. S8b). Thus, this increase in cytosolic ATP is not because of enhancement of mitochondrial ATP, but may be because of suppression of actin turn over caused by Latrunculin A. Importantly, the increase in cytosolic ATP and the decrease in P-domain area were positively correlated ( Supplementary Fig. S8c). The above indicates that actin turnover is a potential mechanism producing the correlation between ATP and neuronal dynamics.
Correlation between ATP mito and IMP mito . Although ATP mito and IMP mito showed similar trends in some cases, different behaviour was found during transport, fission/fusion and axonal elongation. To investigate the relation of them in more detail, we visualised IMP mito and ATP mito over time (Fig. 4a). Each track was classified as (i) a positive correlation, (ii) a negative correlation, (iii) changing with time (drawing circle either clockwise or anti-clock wise), (iv) no correlation, or (v) other. Tracks classified as (iii) were further divided into eight parts by every 90 degree for both clockwise and anti-clockwise rotation directions. Here, clockwise rotation represents ATP mito following IMP mito and vice versa ( Supplementary Fig. S9). Concurrently, cross-correlation functions between IMP mito and ATP mito were calculated. Conceptual wave-forms of the cross-correlation function are illustrated for (i), (ii), (iv), (v) and for the eight parts of (iii) in Supplementary Fig. S9. These results show that IMP mito and ATP mito are not necessarily correlated, although we cannot exclude the possibility that this is because of differences in the ability of the two probes to detect changes in each signal.
Considering the frequency of each type of events, it is understandable that an average of cross-correlation functions between ATP mito and IMP mito of all mitochondria showed a delayed positive peak (ATP mito changed following IMP mito change; Fig. 4b). The observed peak was statistically significant as randomly-shuffled data did not show a peak (Fig. 4b).

Discussion
We conducted simultaneous imaging and spatiotemporal analyses of ATP mito and IMP mito during mitochondrial transport, fission/fusion and axonal elongation. We demonstrated that ATP mito and IMP mito are not always accurately correlated, and for axonal elongation, ATP mito is a more dominant factor than IMP mito .
The role of mitochondria in axonal elongation has been reported previously; mitochondrial transport responds to axonal outgrowth or growth factors 34,35 , and the number and positioning of mitochondria is related to neurite elongation [8][9][10]13 . These reports suggest that mitochondrial localisation and ATP generation are crucial for axonal elongation. Although some of these previous studies measured cytosolic ATP levels directly or indirectly, no report has explored native ATP mito under physiological conditions. In this study, we successfully demonstrated a correlation between ATP mito within GCs with axonal elongation under physiological conditions.
Our results are also consistent with recent research demonstrating the importance of cytosolic ATP in the cellular motility of non-neuronal cells 28,36 . These studies explored cytosolic ATP, not ATP mito , possibly because these cell types have greater dependency on glycolysis compared to others 37,38 . Nevertheless, this study is one of the few that measured mitochondrial/cytosolic ATP itself to demonstrate their relevance in cellular morphological changes.
We have found that ATP mito and IMP mito are not necessarily correlated under physiological conditions. Some background phenomena may have contributed to this discrepancy. Firstly, differences in the ability of two probes to detect changes in each signal could obscure any potential correlation. Secondly, there is a possibility that the ATP mito value reflects an accumulative IMP mito value up to that time, instead of IMP mito at the time, because IMP mito at any given time is simply the difference in voltage in the mitochondrial inner membrane. On the other hand, ATP mito has been considered to represent the net ATP pool in mitochondria at a given time. ATP mito and summation of IMP mito also positively correlated, and the correlation peak was highest when the IMP mito summation period was approximately 2 min ( Supplementary Fig. S10a). However, the 2 min period was an average, and the duration at which the strongest correlation was observed differed depending on each individual mitochondrion ( Supplementary Fig. S10b). This may be because ATP mito is a result of not only production, but also consumption and flux from the mitochondrial matrix. IMP mito is generally considered an index linked to ATP mito production, and the ATP mito measured in this present study is a result of production and consumption/efflux. Thus, a decrease in the ATP mito signal can be the result of either a reduction of ATP mito production or an increase in ATP mito consumption/efflux. This could also contribute to discrepancies in the correlation between the ATP mito and IMP mito signals.
Moreover, activities of electron transport chain (ETC) and ATP synthase activity are known to be flexible. Post-translational acetylation is one of the most representative modulations of mitochondrial activity. NDUFA9, an ETC complex I component, is known to be acetylated, which decreases ATP levels 39 . ATP synthase is also known to be acetylated 40 ; however, this is only one facet of ATP synthase regulation, and ATP synthase activity is also under control of ADP inhibition 41 or ATP synthase inhibitor (IF 1 ) [42][43][44] .
In addition to direct effects on ETC or ATP synthase, there are other effectors that mediate IMP mito and ATP mito levels. The most well-known phenomenon involves proton leak via uncoupling protein (UCP) 45 , which diminishes the correlation between IMP mito and ATP mito by decreasing the number of protons that pass through ATP synthase.
Besides UCP-mediated uncoupling, mitochondrial permeability transition (MPT) 46 is another major phenomenon caused by mitochondrial permeability transition pores (PTP) 46 . A PTP is a structure consisting of adenosine nucleotide translocase (ANT; translocator of ATP/ADP in mitochondrial inner membrane), voltage-dependent anion channel (VDAC; also called porin; a pore located at the mitochondrial outer membrane) and cyclophilin D 47 . The opening of PTP increases the permeability of mitochondrial membranes to molecules including proton, ATP and ADP 48 . Appropriate ATP/ADP translocation is essential for ATP mito production in matrix, and MPT leads to loss of IMP mito ; thus, opening of PTP would disrupt the balance between ATP mito and IMP mito under physiological conditions. Furthermore, MPT is known to be induced without PTP; rapid depolarization depending on the net translocation of protons from matrix to the intermembrane space has been reported in isolated mitochondria 49 .
Previous biochemical research on mammalian oxygen consumption by mitochondria in the standard state suggested that approximately 20% was uncoupled by mitochondrial proton leak and 80% was coupled to ATP synthesis 50 . Recently, a positive feedback mechanism that alters the response of IMP mito to glucose concentrations was reported 51 , and the working condition of the mitochondrial uncoupling protein also differed with regards to IMP mito 52 . Clockwise or anti-clockwise trajectories of ATP mito and IMP mito also suggest that the relation between them is not linear, but rather influence each other, and the extent of the influence changes with time and condition.
In summary, we conducted simultaneous imaging of several mitochondrial properties in neurons. Detailed spatiotemporal image processing directly showed that the affect of native IMP mito and ATP mito are mutual; therefore, the correlation between the two properties changes over time under physiological conditions.

Materials and Methods
Experimental design. The sample size was not determined prior to experimentations. Pixels with an outlier value were excluded when calculating the average during image processing.
The number and composition of experiments are noted in figure legends. All data were statically evaluated by comparing with control conditions or random shuffled-datasets. Alternatively, when there was no control group, datasets were compared by suitable statistic tests (Refer to "Statistical analysis"). Plasmid. The mitAT1.03 plasmid 25,29,30 was kindly provided by Professor Imamura (Kyoto University, Kyoto, Japan).
All animal procedures were approved by the Ethics Committee of Keio University (permit number, 09106-(1)). In addition, all experiments were performed in accordance with relevant guidelines and regulations.
Measurement of ATP mito using mitAT1.03. Neurons were transfected with mitAT1.03 by electroporation using Neon (Life Technologies) just before plating. mitAT1.03 is a fluorescence resonance energy transfer (FRET)-based indicator, and is composed of the epsilon subunit of the F o F 1 -ATP synthase sandwiched by the cyan-and yellow-fluorescent proteins 25,29,30 . Additionally, this indicator accompanies the duplex of the mitochondrial targeting signal of cytochrome c oxidase subunit VIII, which is a protein that is normally localised to the mitochondrial inner-membrane 25 . FRET refers to a phenomenon between donor and acceptor molecules in which the energy from the excited donor is transferred to the acceptor when the emission spectrum of a donor overlaps the absorption spectrum of an acceptor. This phenomenon occurs when the two molecules are in close proximity, although the extent of the spectral overlap and orientation between the donor and the acceptor also affect FRET efficiency. The epsilon subunit assumes its folded form upon ATP binding, and is relaxed in the absence of ATP. As a result, changes in ATP levels can be estimated from the changes in FRET signal intensity, which is derived from alternation of the relative distance and orientation between the two fluorophores.

Measurement of IMP mito using TMRE.
Neurons were stained 6-24 h after transfection with 25 nM TMRE for 10 min at 37 °C and imaged. TMRE was not removed after the initial staining; therefore, there was additional TMRE dye at 5 nM concentration in the cytoplasm and medium during observation. TMRE is a cell-permeant and positively-charged dye, which accumulates in the relatively negatively-charged mitochondria. Because the extent of TMRE incorporation depends on the extent of mitochondrial polarization, mitochondrial polarization could be estimated from TMRE fluorescence; higher TMRE intensity indicates a greater extent of IMP mito polarization (hyperpolarization).
Fluorescence microscopy. All fluorescent imaging experiments were performed using a confocal laser-scanning microscope (FV1000 IX81; OLYMPUS) with a ×60 oil immersion objective lens (Supplementary Figs S11, S12). mitAT1.03 and TMRE were excited by a diode laser (440 nm) and a helium-neon laser (559 nm), respectively, through a 20/80 beam splitter. Emitted fluorescence was separated by dichroic mirrors (510 nm and 560 nm), and signals from mseCFP, mVenus and TMRE were detected at 460-500 nm, 510-530 nm and 575-675 nm, respectively, using band pass filters. The widths of the 460-500 nm and 510-530 nm filters were manually adjusted using monochromators to ensure the lowest amount of background and fluorescence leakage from other channels or excitation lights. Width of 575-675 nm was a specified value of a barrier filter in our system.
Images were acquired at regions approximately 0-150 µm from the edge of axons, with a resolution of 0.132 μm/pixel every 10 sec for 10-15 min. During imaging, cells were maintained at 37 °C and in a 5% CO 2 atmosphere using a stage chamber (TOKAI HIT).
Image processing and analysis of mitochondrial behaviour. Acquired images were processed using our novel image processing software (Supplementary Figs S13, S14). It was written in MATLAB, and developed for this study referring to previous researches 27,28 .
Acquired fluorescent images were median filtered (3 × 3) and the background was subtracted. The background-subtracted images were again median filtered (3 × 3).
Next, to obtain signals from each fluorescent proteins or dye, linear-unmixing processing was conducted for each pixel (refer to Supplementary Fig. S13 and the following paragraph titled "Unmixing processing" for detail procedure).
After linear-unmixing, images were again median filtered (3 × 3). Then, merged images of mseCFP and mVenus from mitAT1.03 were aligned in order of time to obtain a kymograph. A kymograph based on TMRE fluorescence was also produced. Each mitochondrial track was manually identified while referring to the both kymographs. This double check enhanced the certainness of mitochondrial detection. Position, moving direction, displacement and velocities of each mitochondrion for each time point was calculated based on the tracks. When calculating mitochondrial displacement and velocity, axonal elongation was considered. The curve of the axonal process was also corrected for the estimation of displacement and velocity. The time course of each IMP mito and ATP mito was estimated from averaged TMRE intensities or from the pixel-by-pixel value of mVenus/mseCFP of mitAT1.03 within a mitochondrion, respectively.
Unmixing processing. Cells labelled with cytosolic CFP, cytosolic Venus or TMRE were prepared and excited under experimental filter, laser and detection wavelength conditions (Supplementary Fig. S13). The acquired images were processed with background noise reduction and median filtration. Then, the cellular (for CFP-or Venus-expressing cells) or mitochondrial area (for TMRE-labelled cells) was automatically detected in each channel (Ch. 1, CFP-expressing cells; Ch. 2, Venus-expressing cells; Ch. 3, TMRE-stained cells). Relative leakage matrix was derived by quantifying the average fluorescence from the detected areas in each channel. Finally, intrinsic signals were obtained by multiplying the inverse matrix of the leakage matrix to the acquired signals pixel-by-pixel.

Image processing and analysis of neuronal behaviour. Axonal elongation and drawing back after
Oligomycin A or FCCP treatment were estimated by identifying neck position of the GC as a landmark in DIC (differential interference contrast) images.
The neck position is a boundary point between GC and the axonal process. Because the width of the axonal process is mostly constant, the point where the width increases compared to the adjacent point was determined as the neck position. The GC neck position was visually detected in every third image, and automatically complemented for the remaining images. Axonal elongation and drawing back distances were quantified from the displacement of two neck positions. The distance of axonal elongation is a displacement of the neck positions for 10 min observation. The distance of drawing back was defined as the distance over which the GC neck position moved back at 10 minutes after drug treatment.
The software used to analyse the DIC images was originally developed for this study; however, the main procedure that utilised the manually-detected neck position as a landmark of axonal elongation was based on a previously published protocol 27 .
Distinguishing transport categories. The novel software used to generate kymographs was developed for the purposes of this study.
Mitochondria with an average velocity larger than |±0.5 × 10 −2 | µm/sec were classified as moving mitochondria. However, some mitochondria showed not only a move status but also a pause status during the observation; mitochondria displaced more than |±1| µm were also considered as moving mitochondria. Mitochondria other than moving mitochondria were classified as stationary mitochondria. Anterograde or retrograde transport was classified based on the direction of movement. Here, velocity of a mitochondrion was estimated as (displacement distance from first position to final position during an observation [µm])/(time of the observation [sec]), even mitochondria showed bidirectional movements. Therefore, the velocity of a mitochondrion that stopped during movement or moved bidirectionally was calculated to be slower. Other parameters such as ATP mito or IMP mito of a mitochondrion were calculated by averaging all time flames of which the mitochondrion was detected. For this reason, mitochondria moving across each other during the observation were excluded when deriving Figs 1, S2, S3 and S9.

Analysis of fusion and fission events.
Fusion or fission events were manually identified by referring to the corresponding kymographs and movies; kymographs provide information related to mitochondrial dynamics or the time course of ATP mito or IMP mito , and movies enable us to differentiate between a fusion/fission event and the overlapping/separation of two mitochondrial moving across each other. Events found in the kymograph that could not be confirmed as fission/fusion using the corresponding movies were excluded from the analysis in Fig. 2. During fusion events, the average IMP mito or ATP mito levels of two pre-fusion mitochondria were compared with those of a post-fusion mitochondrion. During fission events, the IMP mito or ATP mito levels of two post-fission mitochondria were compared with those of a pre-fission mitochondrion.
Visualising the correlation between ATP mito levels and IMP mito . We applied moving averages (1.5 min before and after) to the relative ATP mito and IMP mito , and demonstrated the time transition of the values using pseudo colour.
Correlation analysis and random shuffling. The cross-correlation function was calculated using a MATLAB function after smoothing and normalising the original sequential data. As a control, random-shuffled datasets were generated from the original datasets, and the correlation between the two control datasets was calculated.
Comparison of mitochondrial properties in the GC and axonal process. Mitochondrial density, IMP mito and ATP mito of Fig. 3 were derived from a single image that correspond to the first image of a time-lapse observation. Additionally, the morphology of the axonal process was detected using the first DIC image. Distances of axonal elongation were calculated by comparing the first and the last DIC image. Density was calculated as a ratio: (sum of area dominated by all mitochondria)/(area size of GC or axonal process). ATP mito and IMP mito were calculated from the average of all mitochondria included in the area of interest. The integrated ATP mito signal was estimated as: (density) × (ATP mito ). The widths of axonal process regions (20 µm) were decided so as to have the same area as that of GCs. cone morphology of every single image was manually detected for all time flames. In addition, morphology of C-domain and GC neck position were defined by manually for all these images. P-domain was defined by subtracting C-domain area from GC area. From these morphologies, area and edge length were calculated for both P-domain and C-domain, respectively. Newly appeared area and newly disappeared area were quantified by comparing the two sequential images. Supplementary Fig. S8, neurons expressing cytosolic ATP sensor AT1.03 25 were imaged. The AT1.03 plasmid was also provided by Professor Imamura (Kyoto University, Kyoto, Japan). Cytosolic ATP levels were estimated by calculating mVenus/mseCFP ratio. GC morphology was defined from fluorescence of mseCFP + mVenus automatically. Procedures of these image processing were based on previous study 27 . Latrunculin A (TOCRIS) was applied at the final concentration of 100 nM. Statistical analysis. Data were evaluated using the Mann-Whitney U-test or Wilcoxon signed-rank test. When more than three groups were compared, Bonferroni correction was performed. As for Fig. 3e-m, Spearman's rank correlation coefficient was used. Asterisks (***, **, *) indicate a significance of <0.001, <0.01 and <0.05, respectively. Data Availability. The datasets generated and analysed during the current study are available from the corresponding author on reasonable request.