Folding latency of fluorescent proteins affects the mitochondrial localization of fusion proteins

The discovery of fluorescent proteins (FPs) has revolutionized cell biology. The fusion of targeting sequences to FPs enables the investigation of cellular organelles and their dynamics; however, occasionally, such fluorescent fusion proteins (FFPs) exhibit behavior different from that of the native proteins. Here, we constructed a color pallet comprising different organelle markers and found that FFPs targeted to the mitochondria were mislocalized when fused to certain types of FPs. Such FPs included several variants of Aequorea victoria green FP (aqGFP) and a monomeric variant of the red FP. Because the FFPs that are mislocalized include FPs with faster maturing or folding mutations, the increase in the maturation rate is likely to prevent their expected localization. Indeed, when we reintroduced amino acid substitutions so that the FP sequences were equivalent to that of wild-type aqGFP, FFP localization to the mitochondria was significantly enhanced. Moreover, similar amino acid substitutions improved the localization of mitochondria-targeted pHluorin, which is a pH-sensitive variant of GFP, and its capability to monitor pH changes in the mitochondrial matrix. Our findings demonstrate the importance of selecting FPs that maximize FFP function.


INTRODUCTION
Eukaryotic cells contain highly developed membrane-bound organelles with unique morphologies and functions. Each organelle dynamically alters its size, abundance, and intracellular localization in response to a variety of extracellular and intracellular signals.
Such organelle dynamics play an important role in cell physiology and pathophysiology. For example, mitochondria are highly mobile structures and continuously change their number, mass, and shape through fusion and fission to maintain functional mitochondria (Archer, 2013;Youle and van der Bliek, 2012). By using quantitative live-cell imaging, it was demonstrated that mitochondria transiently form an enormous, hyperfused network in G1-S phase to enhance their ATP production capacity, thereby playing a regulatory role in G1-S transition (Mitra et al., 2009). Thus, the observation of organelle dynamics is mandatory for a better understanding of biological phenomena at the cellular level.
The morphological examination of organelles had been performed exclusively with electron microscopy until the middle of the last century (Dalton, 1951;Scotuzzi et al., 2017;Seno and Yoshizawa, 1960). This technique allows for the simultaneous observation of all organelles at nanometer resolution; however, live-cell imaging cannot be performed due to the need for fixation (van Zutphen and van der Klei, 2011). The identification of proteins that are specifically localized in a certain organelle (organelle markers) has opened a window for optical microscopy to visualize specific organelles. For instance, the development of specific antibodies against organelle marker proteins has enabled us to paint organelles with colors by an immunofluorescence technique (Johmann and Gorovsky, 1976;Lee et al., 1989;Ralston, 1993). Nevertheless, the fixation process that is required at the first step of this method stops the clock in specimens, thereby discouraging the visualization of organelle dynamics in living cells. Chemically engineered fluorescent dyes targeting specific organelles are available; however, only a limited number of dyes can be used in live-cell imaging because hydrophilic compounds require modifications to break through an aliphatic barrier, the plasma membrane.
Fluorescent proteins (FPs) are powerful tools for live-cell imaging and visualizing organelle dynamics. The introduction of a gene encoding a FP is a simple way to introduce an 5/41 intrinsic fluorescent dye into living cells because it requires no additional enzymes or cofactors for fluorophore formation (Reid and Flynn, 1997). Because of this advantageous feature, FPs have shed light on molecular dynamics in living cells and even cellular dynamics in living organisms through the development of biosensors to monitor molecular or cellular behaviors (Day and Davidson, 2009;Timpson et al., 2011). Since the first discovery of green fluorescent protein (GFP) in the jellyfish Aequorea victoria (Shimomura et al., 1962), the properties of FPs themselves have also evolved through genetic engineering. Such improvements include an extended color pallet (Heim et al., 1994;Ormö et al., 1996), increased fluorescence quantum yield (Bajar et al., 2016;Heim et al., 1995), enhanced folding efficiency at 37ºC (Nagai et al., 2002;Pédelacq et al., 2006), and improved photostability (Griesbeck et al., 2001;Lam et al., 2012;Mena et al., 2006). Despite this series of radical improvements, no versatile FPs have become available thus far. Thus, it is necessary to carefully consider the properties of each FP and the possible unfavorable effects of FP expression in cells.
A good example of this is FP-based organelle markers. Fluorescent fusion proteins (FFPs), which combine FPs and proteins (either full length or portions that include organelle-targeting sequences), are widely used as genetically encoded organelle markers. Such FFPs enable us to visualize time-dependent changes in morphology, subcellular localization, and function in organelles of interest (Chudakov et al., 2010;Rizzuto et al., 1995;Takeuchi and Ozawa, 2007). For instance, the real-time tracking of early, late, and recycling endosomes with FFPs revealed that early endosomes are comprised of two dynamically distinct populations, and such differences are crucial for determining the fate of endocytic cargos in terms of undergoing degradation or recycling (Lakadamyali et al., 2006). However, FFPs do not always exhibit the expected localization. Such mislocalization of FFPs, which might be accounted for by an attribute of either or both the organelle-targeting protein or the FP, is a possible cause of data misinterpretation. For example, the mislocalization in the cytosol of a mitochondria-targeted fluorescent cAMP sensor resulted in "false-positive" findings for changes in mitochondrial cAMP concentration, as it appeared that the cAMP concentration 6/41 was affected by changes in the cytosol even though it was expected to be unchanged (DiPilato et al., 2004). In fact, an improvement in mitochondrial targeting by fusing repetitive mitochondrial-targeting sequences produced no significant change in the mitochondrial cAMP concentration under the same conditions (Di Benedetto et al., 2013). In addition, the expression of FFPs occasionally affects organelle morphology. In the case of endoplasmic reticulum (ER) markers, the oligomerization of FFPs with dimerizing or tetramerizing FPs resulted in the transformation of an organized smooth ER into a tightly stacked ER (Snapp et al., 2003). Therefore, it is critical to carefully examine whether the developed FFPs indeed localize to the intended organelle and whether they have any adverse effects on organelle morphology or function.
Here, we synthetically constructed a series of FFPs that consist of different organelletargeting proteins/peptides and a variety of spectral variants of FPs. Among them, we found that mitochondrial matrix markers in combination with FPs with fast maturation rates were mislocalized, as a substantial fraction of such FFPs was observed not in the mitochondria but in the cytoplasm. The cytosolic fraction was significantly reduced by the reintroduction of a mutation that restored the maturation rate to normal. Given that the acceleration of the maturation process is generally thought to be conducive to the performance of FPs, our results suggest that the selection of FPs during the development of FFPs, particularly mitochondrial matrix markers, should be made more carefully.
These sequences were then subcloned into the XhoI/NotI sites of the pFX-CAAX vectors , which contains human cytomegalovirus (CMV) promoter (Fujioka et al., 2019).
The coding sequence of AcGFP1 was amplified by PCR with the AcGFP_F and AcGFP_R primers and subcloned into the AgeI/NotI sites of pDsRed2-Mito (Clontech). The coding sequence of Venus (cDNA was obtained from Dr. Atsushi Miyawaki; Nagai et al., 2002) with four mutations (E116Q/G117D/D118G/T119C, RFPized Venus, DsVenus) was obtained by PCR-based mutagenesis with the following primers: EGFP_F and QDGC_R and QDGC_F and CFP_R. After gel extraction, the two products were mixed and subjected to a 2 nd PCR to obtain the full-length DsVenus sequence with the primers EGFP_F and CFP_R. To generate the sequence encoding the A163V and/or G175S mutants of pHluorin, PCR-based mutagenesis with a QuickChange Site-Directed Mutagenesis Kit (Agilent Technologies, Santa Clara, CA, USA) was performed with the primers A163V_F and/or G175S_F. The primers used in this study are listed in Table S1. (1 µg/ml) for 30 min at 37ºC (for the measurement of mitochondrial pH) before imaging.
Alternatively, cells plated on collagen-coated 96-well glass-bottom plates (AGC techno glass) were transfected with expression vectors. After 24 h, the cells were fixed in 3% paraformaldehyde for 15 min at room temperature, transferred into PBS, and then imaged.

Quantification of FFP Localization and Mitochondrial Fragmentation
Mitochondrial masked images were generated based on images obtained through the MitoTracker channel as described previously with slight modifications (Iannetti et al., 2016).
In brief, the background-corrected MitoTracker image was subjected to the 'rolling ball' collection algorithm. The resulting image was processed with a Mexican Hat filter to extract the particle objects, followed by noise reduction with a Median filter. A mitochondrial binary image was obtained by the ImageJ plugins "Auto Threshold" and 'Remove Outliers.' Fluorescence intensity in the mitochondrial area in the masked image was recorded for the determination of the mitochondrial intensity. The fluorescence intensity of the whole cell was measured within the area that used for the determination according to the DIC images. The 10/41 ratio of the mitochondrial intensity to the whole cell intensity was calculated to evaluate the extent of the mitochondrial localization of the FFPs.
For the analysis of mitochondrial fragmentation, according to the mitochondrial mask images obtained as described above, the number of mitochondrial particles ´ 10,000/total area of the mitochondria (in pixels) was calculated and plotted as the mitochondrial fragmentation count [AU] as described previously (Rehman et al., 2012).

In Vitro pH Titration
Total cell lysates were prepared as described in the immunoblotting section and were mixed with 20 mM citrate phosphate buffer (containing 150 mM NaCl) to obtain a pH value ranging minimum values (a) were normalized to 1 and 0, respectively.

Measurement of Mitochondrial pH
Cos-1 cells expressing mito-pHluorin or mito-at pHluorin were pretreated with TMRM and Hoechst 33342 and subjected to time-lapse fluorescence microscopy. At time 0, the cells were exposed to 10 µM FCCP, which is an uncoupler that lowers both the cytosolic and 11/41 mitochondrial pH (Berezhnov et al., 2016). After background subtraction, the fluorescence intensity within the cells was quantified by using the Multi Wavelength Cell Scoring module in MetaMorph. The weighted average of the fluorescence intensity at each time point normalized to that at time 0 was calculated and plotted.

Statistical Analyses
The quantitative data are presented as the mean ± s.e.m. of at least three independent experiments (unless indicated otherwise) and were compared by one-way analysis of variance 12/41
Cos-1 cells (Figures 1 and S1) and HeLa cells ( Figure S2) were transfected with expression vectors for these FFPs and observed with confocal microscopy. Most of the FFPs displayed the expected localization in the targeted organelles or structures without any visible abnormality in terms of cell morphology, except that the excess expression of TOM20-iRFP occasionally induced mitochondrial aggregation ( Figure S3A). For example, FP-tagged Lifeact, an F-actin marker, clearly depicted a fibrous structure, while the Golgi apparatuslocalizing enzyme GalT was localized only to the perinuclear region (Figures 1, Figure S1 and S2). However, some FFPs were also found to be distributed to a compartment different from that of the expected organelle in a manner that was dependent on the utilized FP. For example, whereas EGFP-tagged mito, a common mitochondria marker (De Michele et al., 2014), clearly localized only to the mitochondria, other FFPs exhibited "cytosolic and nuclear leaks" in addition to their expected localization (mitochondria) (Figure 1, left column).

Tagged FP-dependent Localization of Mitochondrial Matrix Markers
To determine whether the mislocalization of FFPs was due to the mitochondrial-targeting sequences or the FPs, alternative mitochondrial matrix markers with mitochondrial proteins other than mito were prepared. We used succinate dehydrogenase [ubiquinone] iron-sulfur subunit (SDHB, a mitochondrial matrix protein) and cytochrome b-c1 complex subunit 10 (UQCR11, a mitochondrial inner membrane protein) because these proteins, when tagged with the GFP variant mCitrine, have been reported to be localized to the mitochondria (Söhnel et al., 2016). Nevertheless, SECFP-tagged SDHB displayed similar cytoplasmic and nuclear mislocalization as that of mito-SECFP. Moreover, to make matters worse, its expression induced severe mitochondrial fragmentation ( Figure S4). The localization of UQCR11-SECFP was more mitochondria specific; however, it resulted in mitochondrial swelling and fragmentation ( Figure S4). These results together indicated that mitochondrial-targeting sequences might not dictate the mitochondrial localization of FFPs. In addition, the mitochondrial targeting sequences used for developing FFPs should be selected with care because the mitochondrial architecture is likely to be susceptible to the overexpression of component proteins.
We therefore prepared mitochondria matrix markers that consisted of mito and other color variants of FPs to evaluate the effects of different types of FPs on FFP localization. The transfection of pDsRed-mito, a commercially available expression vector for mito tagged with RFP from Discosoma sp., into Cos-1 cells resulted in distribution exclusively in the mitochondria (Figure 2). We also prepared expression vectors for mito tagged with MiCy, mKate2, and eqFP650 (Karasawa et al., 2004;Shcherbo et al., 2009;, none of which originate from Aequorea victoria, and found that these FFPs also localized preferentially to mitochondria (Figure 2). In contrast, Sirius, SECFP, Venus, and mCherry-tagged mito failed to do so (Figure 2). Such mislocalization of mitochondria-targeted FFPs was also observed in other cell lines besides Cos-1 cells (Figures S5, A and B Benedetto et al., 2013). Therefore, we obtained a series of cell images at 24, 48, and 72 h after transfection, which did not show any significant differences in localization (Figures S5, C and D).

Construction of the RFPized Venus containing FFP
Next, we examined the properties of the FPs utilized for the mitochondrial markers and noticed that almost all the mislocalized FFPs, except for mito-EGFP, utilized FPs derived from Aequorea victoria. In addition, the majority of the FFPs that harbored RFP (DsRed, mKate2, and eqFP650, but not mCherry) was clearly localized only to mitochondria ( Figure   2). To examine whether the origin of the FPs affected the mitochondrial localization of the markers, we generated red fluorescent proteinized (RFPized) Venus, into which several amino acid substitutions (E116Q/G117D/D118G/T119C) was introduced (DsVenus) and constructed an expression vector for mito-DsVenus ( Figure 3A). However, unexpectedly, mito-DsVenus was still localized in the cytosol and nucleus in addition to mitochondria ( Figure 3B). To quantify the extent of the mitochondrial localization of the markers, we calculated the ratios of the fluorescence intensity in the mitochondria to those in the cytosol and nucleus ( Figure   S3A). Although the mitochondrial localization of mito-DsVenus was likely to be higher than that of mito-Venus, there was no significant difference between the two conditions ( Figure   3C). These results indicated that the origin of the FP does not affect the localization of mitochondria-targeted FFPs.

Mislocalization of Mitochondria-targeted FFPs Induced by Folding Mutations
We next generated mitochondria-targeted FFPs with two Aequorea victoria-derived FPs, roGFP2 (Hanson et al., 2004; hereafter roGFP) and superecliptic pHluorin (Sankaranarayanan et al., 2000; hereafter pHluorin), as well as Aequorea coerulescens-derived GFP, AcGFP1 (Gurskaya et al., 2003;hereafter AcGFP). roGFP and pHluorin are widely used as subcellular redox and pH sensors, respectively. It is worth noting that commercially available mito-AcGFP is shown to be localized only to the mitochondria. It was revealed that roGFP-and

15/41
AcGFP-tagged mito were exclusively localized to the mitochondria (Figure 4A), whereas pHluorin-tagged mito exhibited cytosolic and nuclear leakage, as did SECFP-or Venustagged mito. We collectively compared the amino acid sequences of the utilized FPs and found that amino acid substitutions (M153T/V163A/S175G) that promote their protein folding (so-called "folding mutations"; Nagai et al., 2002) had been introduced into the FPs of the mislocalized FFPs (Figures 4B and 4C).

Improvement of the Mitochondrial Localization of FFPs by Reverse Mutation of the FPs
The above results raised the possibility that folding mutations in FPs inhibited the accurate mitochondrial localization of FFPs. To test this hypothesis, we prepared mito-tagged EYFP and mito-tagged Venus and compared their localization. These two FPs have essentially same excitation/emission spectra, but only the latter has a folding mutation. As expected, whereas the fluorescence signal of mito-Venus was mainly observed in the cytosol and nucleus, mito-EYFP was preferentially localized to the mitochondria (Figures 5, A and B). We further evaluated the localization of mito tagged with superfolder GFP (sfGFP corresponds to aqGFP M153T/V163A), which is a fast-folding EGFP variant generated by DNA shuffling (Pédelacq et al., 2006). In contrast to mito-EGFP, mito-sfGFP showed mislocalization in the cytosol and nucleus ( Figure 5C). To provide more evidence for this notion, we constructed a pHluorin revertant in which the folding mutations of pHluorin (V163A/S175G) were restored to those of the original aqGFP (V163/A175). The revertant pHluorin-tagged mito was indeed clearly localized to the mitochondria, and the degree of this localization compared to that of the original pHluorin-tagged mito was dependent on the number of restored amino acids ( Figures   5, E and F). The double mutant was therefore named at pHluorin after the musical term "a tempo," which means "at original speed" or "cancelation of the last speed change."

Precise Measurement of Mitochondrial pH by at pHluorin
We finally compared the properties of mitochondria-targeted FFPs with pHluorin and at pHluorin in terms of specific measurement of the mitochondrial pH. An in vitro titration assay revealed that the amino acid substitution resulted in no difference in pH sensitivity ( Figure   6A). Under these conditions, changes in pH in the mitochondrial matrix induced by carbonyl 16/41 cyanide p-trifluoromethoxyphenylhydrazone (FCCP) were evaluated. FCCP is a chemical uncoupler that promotes mitochondrial membrane permeability to proton ions and acidifies the mitochondrial matrix (Aw and Jones, 1989). Intriguingly, while the fluorescence intensities of both mito-pHluorin and mito-at pHluorin were decreased by FCCP treatment, the extent of the decrease in the intensity of mito-at pHluorin was smaller than that of mito-pHluorin ( Figure 6B). However, when the changes in mitochondrial pH were separately quantified via mitochondrial masked images, which were generated based on the images of the chemical mitochondrial marker MitoTracker™ Red CMXRos as a guide, it was revealed that mito-at pHluorin indeed reported essentially the same dynamics in terms of pH change in mitochondria as those reported by mito-pHluorin ( Figure S6A). Given that FCCP was reported to decrease the cytosolic pH more than that of the mitochondrial matrix by increasing plasma membrane permeability to proton ions (Berezhnov et al., 2016), the presence of cytoplasmic mito-pHluorin resulted in the overestimation of the mitochondrial pH. Indeed, the fluorescence intensity of cytosolic pHluorin was decreased by FCCP treatment ( Figure   S6B). Overall, the preferential localization of mito-at pHluorin enables the specific measurement of pH changes in the mitochondrial matrix without the use of other complementary fluorescent dyes. This would be advantageous for multidimensional imaging with multiple FFPs and for flow cytometry analyses.

DISCUSSION
In this study, we constructed more than 80 organelle-targeted FFPs and found that several sets of FFPs localized to organelles other than those expected. In the case of mitochondrial matrix markers, it was demonstrated that mutations that accelerate the folding process of FPs reduced the expected (mitochondrial) localization. Endosomal markers also exhibited a similar tendency. Following the discovery and cloning of GFP and its relatives, FPs have facilitated the routine monitoring of protein and organelle dynamics in living cells and cellular dynamics in whole animal bodies (Chudakov et al., 2010;Day and Davidson, 2009 however, in most cases, there is no rational basis for the design of FFPs and a trial-and-error strategy must be used. Because of the size of a fluorescent protein, the resulting perturbations to the overall folding and function of the protein of interest can be significant. When designing an FFP, linkers can be used to join the two sequences. This strategy helps to overcome the aforementioned challenges of protein folding and function, but the sequence itself is also critical for the proper functioning of tagged proteins. In addition to the above issues (the site and method used to add FPs), we propose that the properties of the FP itself can determine FFP function, particularly in the case of mitochondrial and endosomal markers.
Major mitochondrial proteins are synthesized in the cytosol and transported to the mitochondria. To be localized within mitochondria, the precursors need to be imported across one or both of the mitochondrial membranes through a pore formed by the TOM complex (Chacinska et al., 2009). Given the diameters of pores, which range from 13 Å (Tim23) to 20 Å (Tom40), only unfolded proteins can pass through them (Pfanner and Truscott, 2002). It is generally assumed that mitochondrial preproteins are usually unfolded or loosely folded in the cytosol and guided by cytosolic targeting factors or chaperones to the mitochondria.
Furthermore, it has also been reported that several preproteins contain stably folded domains in the cytosol (Bömer et al., 1997;Wienhues et al., 1991). For such proteins, the 18/41 mitochondrial import machinery actively unfolds and imports the preprotein. Indeed, the importing efficiency of a protein is correlated with the ease of its unfolding and resistance to mechanical unfolding of the folded proteins (Eilers and Schatz, 1986;Sato et al., 2005;Wilcox et al., 2005). In the case of mitochondria-targeted FFPs with aqGFP, we clearly demonstrated that the fast folding of FPs prevented their proper localization. It is noteworthy that only mCherry is found to be mislocalized among the RFPs tested. Given that mCherry horbors the mutations V7I and M182K, which promote the protein folding (half time for maturation of DsRed and mCherry are ~10h and 15 min, respectively) (Shaner et al., 2008), the relationship between folding latency and mitochondria targeting might serve as a common future for different FPs. It might be possible that once fast-folding FPs are folded, they become stable in the folded state and are resistant to unfolding by the mitochondrial protein import machinery. Indeed, it has been reported that GFP39N (F99S/M153T/V163A) displays higher thermostability than wild-type aqGFP (Aliye et al., 2015). Another possibility is that folded FPs prevent the binding of FFPs to mitochondrial-targeting factors or chaperones in the cytosol, which guide them to the mitochondrial surface. For FFPs to be incorporated into mitochondria, the FPs within FFPs must be in an unfolded state. Given that mito-DsRed, which is more stable than EGFP when folded (Verkhusha et al., 2003), and mito-EGFP were preferentially localized to the mitochondria, the latter possibility might be more plausible. A systematic examination of the mechanical unfolding kinetics of FPs by atomic-force microscopy will be of great help in clarifying this issue (Perez-Jimenez et al., 2006).
Our observations demonstrated that mutations that accelerate the folding process of FPs disturb the mitochondrial localization of FFPs. There are a great number of FP variants that have been developed with the aim of improving brightness (via increased quantum yield and folding efficacy at 37ºC), changing the excitation and emission spectra, and decreasing the chemical and photochemical sensitivity (Day and Davidson, 2009;Tsien, 1998). Among them, those with mutations that improve the folding efficiency of FP at 37ºC (often called "folding" mutations; (Fukuda et al., 2000) exhibit enhanced brightness due to an increased proportion of mature, light-emitting FP molecules. Therefore, these mutations are generally 19/41 considered to be favorable, which has encouraged the construction of new FFPs and the substitution of classical FPs with improved FPs. These results may lead to the questioning of this trend because fast-folding FP variants hamper the correct localization of FFPs to the mitochondrial matrix, and a reverse mutation causes them to localize specifically to the mitochondria. A similar tendency was also observed for the endosomal markers.
In conclusion, we hereby suggest that slow-folding FPs might occasionally be suitable for FFPs targeting certain organelles, including the mitochondria and endosome. An increase in the extent of specific localization to the targeted organelle will improve the signal to noise ratio, which will improve the detection of not only organelle morphology but also organellespecific changes in ion concentration, signaling, and protein-protein interactions with FFPs.
This will definitely improve the elucidation of cell physiological functions in detail. Blue and red boxes indicate amino acids conserved in the RFP and GFP groups, respectively, but that are distinct among the groups. ".", ":", and "*" indicate low homology, high homology, and identical amino acids, respectively. (B) Cos-1 cells expressing the FFPs indicated at the top were observed with confocal microscopy. Representative images are shown. (C) Cos-1 cells expressing the FFPs indicated at the bottom were observed with confocal microscopy, and the extent of mitochondrial localization was quantitated and plotted. The data shown represent the mean ± s.e.m. from three independent experiments (n > 10). **, p < 0.0001, as calculated by one-way ANOVA with a post hoc Tukey HSD test. n.s., not significant. The fluorescence intensities at each pH were normalized to the maximum intensity and plotted against the pH. The data were fitted to Hill's equation, and the fitted curves are also shown. The pKa for mito-EGFP, mito-pHluorin, and mito-at pHluorin was 5.80, 7.05, and 6.98, respectively. (B) Cos-1 cells expressing the proteins indicated at the bottom were subjected to time-lapse fluorescence microscopy. At time 0, the cells were exposed to FCCP. The normalized fluorescence intensities were plotted over time. The data shown are the mean ± s.e.m. from three independent experiments (n > 145). p-values were calculated by MANOVA. **, p < 0.0001, n.s., not significant. . The extent of mitochondrial localization was quantitated and plotted (C). Data shown represent the mean ± s.e.m. from three independent experiments (n > 10) and were analyzed by one-way ANOVA with a post hoc Tukey HSD test. **, p < 0.0001, n.s., not significant. (D) The extent of mitochondrial fragmentation was quantitated and plotted. Data shown are the mean ± s.e.m. from three independent experiments (n > 10). **, p < 0.0001, as calculated by one-way ANOVA with a post hoc Tukey HSD test. n.s., not significant.  Figure 6). (A) Fluorescence intensity in the mitochondrial area was separately quantified using the mitochondria-masked images from Figure 6. (B) Cos-1 cells expressing the proteins indicated at the bottom were subjected to time-lapse fluorescence microscopy. At time 0, the cells were exposed to FCCP. The normalized fluorescence intensities in the entire cell area were plotted over time. The data shown are the mean ± s.e.m. from three independent experiments (n > 60). p-values were calculated by MANOVA. **, p < 0.0001, n.s., not significant.