Determination of Mitochondrial Morphology in Live Cells Using Confocal Microscopy

Summary

In this study, we describe a step-by-step protocol and emphasize the key details for determining morphological characteristics of mitochondria in live cells, including sample preparation, image acquisition, and data analysis. This method is commonly used to examine mitochondrial morphology for studying various conditions.

Abstract

The dynamic balance of mitochondrial fusion and fission directly contributes to mitochondrial homeostasis, which influences numerous cellular functions in addition to adenosine triphosphate (ATP) homeostasis. Therefore, assessing mitochondrial morphology under stress conditions is essential for mechanistic research. This study describes a detailed protocol for analyzing mitochondrial morphology, encompassing the preparation of a MitoTracker solution, staining of mitochondria, optimization of imaging parameters, and detection of morphological features. MitoTrackers are commonly used, cost-effective mitochondrion-specific dyes. However, some changes in mitochondrial morphology may occur owing to inappropriate handling, which can be unperceivable and fail to reflect the true state of mitochondria. Therefore, it is necessary to understand how to analyze changes in mitochondrial morphology using MitoTrackers. The protocol utilized SH-SY5Y cells stimulated with 1-methyl-4-phenylpyridinium iodide (MPP⁺) to illustrate the protocol of mitochondrial morphological analysis. Compared with control cells, MPP⁺-stimulated cells exhibited smaller and more fragmented mitochondria, with morphological parameters indicating decreased mitochondrial footprint. These results suggest that MitoTracker staining is an effective and feasible method for mitochondrial morphological analysis that (with minor modifications) can be applied to study various conditions.

Introduction

Mitochondrial morphology is maintained by the dynamic balance of mitochondrial fusion and fission, and hence, affects energy homeostasis and numerous other cellular functions, leading to various pathologies such as neurodegenerative diseases, cancer, and inflammation^1,2,3,4,5. To observe mitochondrial morphology, several mitochondrion-selective stains, including both probes and antibodies, have been developed for use with a confocal microscope. Some mitochondrion-specific probes, like tetramethylrosamine and rhodamine 123, function based on the mitochondrial membrane potential (MMP), which limits their applicability in studies of MMP-disrupting conditions^6,7. Conversely, antibody staining provides MMP-independent morphological assessment for examining mitochondrial morphology in fixed cells. Although a suitable stain allows for the assessment of mitochondrial morphology in fixed cells, examining mitochondrial morphology in live cells impaired by some inducers remains challenging. MitoTracker, a cell-permeable cationic and mitochondrion-specific fluorescent probe, offers a solution to this challenge, allowing staining of both live and fixed cells. This probe has been widely utilized to examine mitochondrial morphology in studies of various diseases^8,9,10,11. Nevertheless, some studies have reported issues such as high background signal and non-specific binding, even when the probe is utilized in strict accordance with the guidelines provided by the manufacturer. These observations highlight the importance of a thorough understanding of sample preparation and image acquisition for the successful analysis of mitochondrial morphology.

To facilitate analysis of mitochondrial morphology, various image processing programs and algorithms have been developed^{12,13,14,15,16}. In this study, we employed the macro tool Mitochondrial Network Analysis (MiNA) in ImageJ to analyze mitochondrial morphology¹³. This tool effectively identifies and characterizes morphological features of mitochondrial networks by calculating nine descriptive parameters, including the number of individuals (structures without any branches), number of networks (number of objects with at least one junction pixel), mean length (average length of all rods and branches), median length (median length of all rods and branches), length standard deviation (standard deviation of individual lengths), mean Network Size (the average number of branches per network), median Network Size (the middle value of the number of branches per network), network Size Standard Deviation (standard deviation of the number of branches per network), and the mitochondrial footprint (total signal area after background separation). In this protocol, the mitochondrial footprint was selected as a representative parameter.

The objective of this study is to provide a step-by-step protocol for mitochondrial morphological analysis, focusing on key details. We used MPP⁺-induced SH-SY5Y cells to demonstrate this protocol. MPP⁺ inhibits complex I of the mitochondrial respiratory chain in dopaminergic neurons, resulting in damage to mitochondrial morphology and function^8,17. The morphological analysis protocol described in this study enables the acquisition of high-resolution images and the assessment of relevant parameters to define morphological features of mitochondrial networks.

Protocol

1. Preparation

1. Dissolve MPP⁺ with dimethyl sulfoxide (DMSO) to make a 1 mM stock solution and store it at -30 °C in the dark (see Table of Materials).
2. Dissolve 50 µg of MitoTracker (MitoTracker Red CMXRos) in 94 µL of DMSO to make a 1 mM stock solution. Aliquot the stock solution into several microcentrifuge tubes and store protected from light at -30 °C until further use.
3. Incubate SH-SY5Y cells in flasks with Dulbecco's Modified Eagle Medium/Nutrient Mixture F-12 medium supplemented with 10% (v/v) fetal bovine serum (FBS) in a humidified environment with 5% CO₂ and 95% air at 37 °C. For passaging, detach the cells with 0.05% trypsin solution for 1 min and centrifuge at 100 × g for 3 min.

2. MPP⁺ stimulation

1. Seed SH-SY5Y cells on confocal dishes with a glass bottom and maintain them in DMEM/F12 medium supplemented with 1% (v/v) FBS overnight.
2. Replace the culture medium, then incubate the cells with or without MPP⁺ for 24 h.

3. MitoTracker staining

1. Prewarm DMEM/F12, then dilute the MitoTracker stock solution with DMEM/F12 to obtain a 50 nM working solution. Keep the solution protected from light during the whole procedure.
2. Remove the cell culture medium and wash the confocal dishes 2x with fresh DMEM/F12.
3. Incubate cells in each dish with 1 mL of the MitoTracker working solution for 15 min at 37 °C in the dark.
4. Remove the MitoTracker working solution and wash 2x with DMEM/F12.
5. Add 1 mL of DMEM/F12 to each dish and incubate in the cell incubator before imaging.

4. Imaging parameters for confocal microscope

1. Preequilibrate the microscope for subsequent operations. Under the acquisition panel, adjust the light path-related parameters by setting the excitation and emission wavelengths.
2. Set the parameters as follows: pinhole size, 1.2 AU; pixel scan size, 1,024 x 1,024; pixel dwell time, 2.4 µs (average 2x) (keep it consistent for calibration purposes).

5. Optimizing the imaging parameters

CAUTION: Avoid eye exposure to both direct and scattered radiation from a visible and/or invisible laser.

1. Use the halogen light to focus on the cells using a plan apochromatic 60x objective lens (1.4 NA) to avoid phototoxicity.
2. Adjust the laser power and high voltage (HV) to just below the saturation level, set the zoom factor to 3 and then capture the images.
3. Move the region of interest and focus on the cells to capture images without changing any settings.

6. Data analysis

NOTE: Data were analyzed using ImageJ preinstalled with the MiNA plug-in¹³. To obtain accurate relevant measurements, images should capture independently resolved mitochondria with clean and bright staining.

1. To enhance image quality prior to binary transformation and skeletonization, open the image and conduct preliminary processing. Use the ROI tool to select the area of a single cell. Apply the Process | Filters | Unsharp Mask function to enhance sharpness, and use the Process | Enhance Contrast feature to reduce noise over-amplification. To remove salt and pepper noise specifically, use the Process | Filters | Median function (see Supplemental Figure S1).
2. To construct a simplified morphological model to calculate descriptive parameters, convert the image to binary via thresholding (click on Process | Binary | Make Binary), and then skeletonize the binary image using the Skeletonize function (click on Process | Binary | Skeletonize) (see Supplemental Figure S2).
3. Group all pixels within the skeleton using the Analyze | Skeleton | Analyze Skeleton (2D/3D) function. Simplify the analysis by using the MiNA tool to calculate nine descriptive parameters in the skeletonized image (see Supplemental Figure S3).

Results

This protocol outlines a detailed, step-by-step procedure for mitochondrial morphological analysis through three interdependent optimization modules: standardization of specimen preparation protocols, systematic optimization of optical parameters for confocal microscopy imaging, and computational image processing guidelines. Optimal sample preparation protocol is critical for obtaining reliable mitochondrial imaging data. Systematic evaluation of MitoTracker Red CMXRos concentrations demonstrated concentration-dependent fluorescence characteristics. The 25 nM treatment resulted in significantly weaker fluorescence signals compared to higher concentrations (Figure 1A). Notably, while no significant differences in labeling efficiency were observed between 50 nM and 100 nM treatments, the 200 nM condition exhibited two critical limitations: increased photosensitivity requiring lower laser irradiation thresholds, and substantial cytoplasmic background staining.

Additionally, the impact of PBS and culture medium on background fluorescence signals was assessed. The results indicated that rigorous PBS washing, combined with PBS-filled imaging, effectively reduced autofluorescence from culture medium. However, this approach was associated with a time-dependent degradation of mitochondrial structure, with noticeable morphological alterations observed 1 h post staining with MitoTracker (Figure 1B). Conversely, mitochondrial morphology was remarkably preserved in DMEM/F12 medium, but this preservation came at the cost of higher background signal intensity.

This study employed laser scanning confocal microscopy (LSCM) for image acquisition, critical for reducing out-of-focus fluorescence in mitochondrial network analysis. Systematic parameter optimization yielded three key findings: (1) Dual-frame averaging enhanced the signal-to-noise ratio (SNR) compared to single-scan acquisition (Figure 1C). The unprocessed single-scan mode exhibited pronounced stochastic Poisson noise, consistent with photon-counting statistics in low-signal conditions. (2) Optimization of pixel dwell time revealed a fundamental trade-off: increasing dwell time from 2.4 µs to 10.8 µs resulted in higher peak fluorescence intensity but accelerated photobleaching (Figure 1C). (3) Regarding the optimization of laser power and HV settings, the data indicated that higher HV settings increased background noise levels, while increased laser power led to photobleaching (Figure 1D).

The MiNA analytical platform incorporates multiple configurable threshold parameters to accommodate diverse experimental conditions in mitochondrial morphology analysis. Crucially, fluorescence intensity can profoundly impact thresholding and skeletonization of the mitochondrial signal, directly influencing quantitative assessment of mitochondrial network architecture. Establishing an optimal fluorescence intensity range to ensure reproducible quantifications via empirical validation is therefore an essential prerequisite for reliable MiNA implementation. Through systematic acquisition of image datasets with differential fluorescence intensities, we performed comparative analyses using the MiNA toolbox with default settings. The algorithm generated precise segmentation masks with high fidelity to original fluorescence patterns across intensity variations (Figure 1E). Notably, skeletonization outputs maintained remarkable consistency between low-intensity and high-intensity images. Quantitative comparison revealed the average fluorescence intensity value of the bright original image is 5.5x that of the dim original image, confirming the platform's robustness across this dynamic range.

To induce oxidative stress, SH-SY5Y cells were subjected to treatment with MPP⁺ or no treatment. A specific MitoTracker dye was used to detect morphological changes in mitochondria. Analysis of mitochondrial footprint revealed that MPP⁺ treatment reduced the absolute mitochondria footprint in cells and disrupted the mitochondrial network (Figure 2).

Figure 1: Optimization of experimental conditions for detecting mitochondrial morphology. (A) The impact of MitoTracker concentration on mitochondrial morphology in SH-SY5Y cells. Varying concentrations of MitoTracker dye (ranging from 25 to 200 nM) were used to stain the cells to visualize the variances in mitochondrial morphology. (B) The impact of PBS and culture medium on fluorescence signals. After staining, the samples were washed, and then confocal dishes were filled with either PBS or culture medium. Mitochondria were observed under the microscope at either 0 h or 1 h post staining with MitoTracker. (C) The importance of optimization of frame averaging and pixel dwell time in mitochondrial imaging. Different frame averaging and pixel dwell time settings were employed to capture images, followed by a comparison of mitochondrial imaging outcomes. (D) Optimization of laser power and HV settings to reduce photobleaching and phototoxicity. Various HV and laser power settings were employed to capture images, followed by a comparison of mitochondrial imaging outcomes. (E) Images with diverse fluorescence intensities are employed to assess MiNA's capacity to generate an accurate skeletal structure. Images with varying fluorescence intensity values were acquired to assess the impact on the skeletonization of the mitochondrial signal. Scale bars = 10 µm, 0.14 µm/pixel. Please click here to view a larger version of this figure.

Figure 2: MPP⁺ treatment disrupted mitochondrial morphology in SH-SY5Y cells. (A) MPP⁺ was administered to SH-SY5Y cells for 24 h; subsequently, mitochondria were labeled with a MitoTracker and visualized via a laser confocal microscope (scale bar = 10 µm, 0.14 µm/pixel). (B) The mitochondrial footprint was analyzed using the MiNA tool in ImageJ, and statistical analysis was performed using the Student's unpaired t-test. Data are demonstrated as the mean ± standard deviation. *p < 0.05 versus the control group. Please click here to view a larger version of this figure.

Supplemental Figure S1: Optional preprocessing steps to enhance image quality before binarization and skeletonization using ImageJ. The source image undergoes processing using (A) the unsharp mask by selecting Process | Filters | Unsharp Mask with (B) the default setting. Contrast enhancement is processed by (C) selecting Process | Enhance Contrast with (D) the default setting. Median filtering is chosen to reduce salt and pepper noise by clicking (E) Process | Filters | Median with (F) the default setting. Please click here to download this File.

Supplemental Figure S2: Morphological simplification for structural modeling via ImageJ. (A) The image is binarized by selecting Process | Binary | Make Binary. (B) The binary image is transformed into a skeletal representation through the Process | Binary | Skeletonize function. All skeletal pixels are systematically classified into three distinct categories by clicking on (C) Analyze | Skeleton | Analyze Skeleton (2D/3D) with (D) the default setting. Please click here to download this File.

Supplemental Figure S3: Calculation of descriptive parameters from the skeletonized image using MiNA. MiNA is employed to assess the mitochondrial network skeleton in the images by selecting (A) Plugins | Macros | MiNA-Analyze Morphology with (B) the default setting. Please click here to download this File.

Discussion

The present study establishes a systematic methodology for analyzing mitochondrial morphology in live cells under stress conditions. Crucial procedural steps in mitochondrial imaging involve: an appropriate concentration of MitoTracker probes, thoroughly washing confocal dishes prior to image acquisition, minimizing disturbances to the cellular state, and setting suitable imaging parameters.

Using higher concentrations of MitoTracker can induce cytotoxicity, rendering mitochondria sensitive to laser power and potentially causing the dye to stain other cellular structures (Figure 1A). Based on these findings, 50 nM was determined to be the optimal concentration, balancing strong signal intensity with minimal phototoxic effects. Similarly, the experimental concentration and incubation time of MitoTrackers should be determined for other cell types. Generally, the working concentrations of MitoTrackers range from 25 nM to 200 nM, and the incubation time ranges from 10 to 30 min^9,10.

Thorough washing of culture media containing MitoTracker is necessary to reduce high background fluorescence prior to imaging. The solution used for cell incubation also significantly affects imaging quality (Figure 1B). It is recommended to fill confocal dishes with culture medium after staining to achieve an optimal balance between background suppression and physiological maintenance.

When evaluating mitochondrial morphology, it is necessary to exclude extraneous factors that can disrupt the cellular state. The structural characteristics of the mitochondrial network are susceptible to perturbations in the cellular state, including stimulation with cold PBS or culture medium, prolonged incubation at room temperature, and exposure to phototoxicity from high-energy lasers. Given these sensitivities, it is crucial to prewarm all solutions, whether PBS or culture medium, before adding them to confocal dishes. All experimental procedures should be completed quickly to avoid adverse conditions affecting the cells, helping to maintain cellular integrity and mitochondrial morphology, and thus allowing for a more accurate assessment of mitochondrial structure.

The optimization of confocal microscopy parameters encompasses two interdependent aspects: hardware configuration and optical system calibration. Hardware optimization requires strict adherence to the Nyquist sampling criterion, which is determined by three fundamental optical parameters: objective numerical aperture (NA), total system magnification, and excitation wavelength. In this study, an oil immersion objective with an NA of 1.40 was utilized to enhance image resolution. MitoTracker with an excitation wavelength of 561 nm was selected to reduce potential phototoxic effects that are more prevalent with shorter wavelengths. Regarding the pinhole size, a value of 1.2 Airy units (AU) was judiciously chosen. This selection optimally balances several key factors, effectively rejecting out-of-focus photons and maximizing photon collection efficiency, enhancing resolution, and improving the SNR.

Subsequent optical optimization is centered on achieving a balance between imaging fidelity and cellular viability, taking into account three key considerations: maintaining non-saturated signals at minimal laser power, carefully limiting cumulative light exposure to prevent mitochondrial morphological artifacts, and adopting acquisition speeds that are in line with dynamic biological processes. A univariate experimental design was employed to systematically assess individual effects of multiple parameters on mitochondrial architecture, facilitating the development of system-specific experimental protocols. Although implementation details may differ across different microscope platforms, the core optimization principles remain applicable across systems. This optimization framework provides a reproducible methodology for live-cell imaging, ensuring both technical reproducibility and biological relevance in various experimental systems.

After systematic optimization, confocal images were acquired from SH-SY5Y cells and analyzed using the MiNA with its default settings. The results generated a binary mask that more accurately visually represented the original images, indicating that the default parameters are practical for general use. However, it should be noted that in certain scenarios, different thresholding methods may be required to effectively analyze the mitochondrial network. For instance, morphological skeletonization was performed with iterative thinning in this study, which was achieved by utilizing the Skeletonize plugin. This method required well-resolved, completely segmented mitochondria within the binary mask. Ridge detection, an intensity-based skeletonization method, was also incorporated but required parameter optimization. Researchers seeking comprehensive guidance on thresholding algorithm selection and parametric sensitivity analyses are advised to refer to the foundational work¹³, which systematically evaluates these computational approaches. The postprocessing quantification yielded nine parameters to characterize the mitochondrial network morphology. To effectively apply these parameters to specific research, investigators should consult established literature, which provides detailed guidance on parameter selection and interpretation¹³. In this study, the mitochondrial footprint was chosen for subsequent analysis due to its potential significance and relevance in reflecting the overall characteristics of the mitochondrial network.

In conclusion, the protocol detailed in this study, encompassing sample preparation, image acquisition, and data analysis, enables assessment of relevant parameters to delineate mitochondrial morphology. Integrating a simple and widely used mitochondrial stain, an easy and effective fluorescence imaging technique, and an open-source data analysis tool, this protocol represents a reproducible approach that can be easily applied to investigate various pathological conditions.

Materials

List of materials used in this article

Name	Company	Catalog Number	Comments
1-methyl-4-phenylpyridinium iodide (MPP+)	Macklin	M875357	Used to induce oxidative stress
Confocal dish	NEST	801001	Used to culture the cells
Confocal microscope	Nikon	C2	Used to capture images
Dulbecco's Modified Eagle Medium/Nutrient Mixture F-12	ThermoFisher Scientific	11320033	Used to provide nutrition to cells
Dimethyl sulfoxide (DMSO)	Beyotime	ST038	Used to dissolve the mitotracker probe
Fetal bovine serum (FBS)	ThermoFisher Scientific	A3161001C	Used to provide nutrition to cells
ImageJ	National Institutes of Health	ImageJ	Used to analyze mitochondrial morphology
MitoTracker Red CMXRos	ThermoFisher Scientific	M7512	Used to visualize mitochondria
Phosphate Buffer Saline (PBS)	ThermoFisher Scientific	C10010500BT	Used to wash the cells on confocal dishes
SH-SY5Y cell	ATCC	CRL-2266	Used to demonstrate the workflow of analyzing mitochondrial morphology
TI-SH-U Stage Adapter	Nikon	MEC59110	Used to secure specimens