Assessing Mitochondrial Redox Status by Flow Cytometric Methods: Vascular Response to Fluid Shear Stress

Abstract

Mitochondria are an important source of superoxide production contributing to physiological and pathological responses, including vascular oxidative stress that is relevant to cardiovascular diseases. Vascular oxidative stress is intimately linked with pro-inflammatory states and atherosclerosis. Oxidized low density lipoprotein (OxLDL) modulates intracellular redox status and induces apoptosis in endothelial cells. Hemodynamic, specifically, fluid shear stress imparts both biomechanical and metabolic effects on vasculature. Mitochondria are an important source of superoxide production contributing to vascular oxidative stress with relevance to cardiovascular diseases. We hereby present biophysical and biochemical approaches, including fluorescence-activate cell sorting, to assess the dynamics of vascular redox status

INTRODUCTION

Growing evidence supports the role of reactive oxygen and nitrogen species in the etiology of atherosclerosis. The manifestations of atherosclerosis tend to be focal and eccentric (Harrison, Griendling et al. 2003; Sorescu, Song et al. 2004; Hsiai, Hwang et al. 2007). Vascular oxidative stress and pro-inflammatory states mediate endothelial cell homeostasis with relevance to the initiation of atherosclerosis. Low-density lipoprotein (LDL), a major risk factor of atherosclerosis, transmigrates across the vascular wall to the subendothelial layer in which it undergoes oxidative modifications (Navab, Berliner et al. 1996; Stocker and Keaney Jr 2004). Oxidized LDL (OxLDL) mediates endothelial redox status (Cominacini, Pasini et al. 2002) and apoptosis at a high concentration (Dimmeler, Haendeler et al. 1997; Harada-Shiba, Kinoshita et al. 1998; Martinet and Kockx 2001). Hemodynamic, namely, fluid shear forces, regulates the generation of reactive nitrogen species (RNS) and reactive oxygen species (ROS)(Hwang, Ing et al. 2003; Hwang, Saha et al. 2003; Hsiai, Hwang et al. 2007). While endothelial nitric oxide synthase (eNOS) is the major source of reactive nitrogen species (RNS), NADPH oxidase is considered a major source of ROS in vascular endothelial cells (Gorlach, Brandes et al. 2000; Hsiai, Hwang et al. 2007). Mitochondria are also an important source of cellular superoxide anion (O₂^·−) and hydrogen peroxide (H₂O₂) (Griendling and FitzGerald 2003). In particular, OxLDL induces mitochondrial superoxide (mtO₂^·−) production (Zmijewski, Moellering et al. 2005; Gutierrez, Ballinger et al. 2006; Davidson and Duchen 2007) and apoptosis in vascular cells, including endothelial cells (de Nigris, Franconi et al. 2000; Li, Wang et al. 2006; Cheng, Cui et al. 2007; Deng, Zhang et al. 2009; Liu, Zhao et al. 2009). Our study has demonstrated that fluid shear stress also modulated mitochondrial superoxide production.

In the mitochondria, oxidative phosphorylation from complexes I to II, III and IV drives the proton translocation across the inner membrane to the intermembrane space (Duchen, Surin et al. 2003). The proton gradient is expressed as mitochondrial membrane potential (ΔΨ_m)(Chen 1988); this gradient drives the production of ATP by complex V, ATP synthetase. The transfer of of electrons from ubisemiquinone through the mitochondrial respiratory chain more than 98% efficient, however, 1.5 to 2 % of electrons leak out to form superoxide anion (O₂^·−) mainly at complex I (NADH coenzymeQ reductase) and III (ubiquinol cytochrome c reductase) (Forman 1999). The superoxide anion is converted to H₂O₂ in mitochondria by superoxide dismutase.

The application of flow cytometry or fluorescence-activate cell sorting (FACS) has enabled a quantitative approach to assess mitochondrial redox status in terms of ΔΨ _m and mtO₂^·−production. In this chapter, we will address the methodology to assess the dynamics of mitochondrial redox status and vascular oxidative stress in response to fluid shear stress.

BASIC PROTOCOL

ASSESSING MITOHCONDRRIAL REDOX STATUS IN RESPONSE TO FLUID SHEAR STRESS

Mitochondrial function is relevant to metabolic homeostasis (Nisoli, Clementi et al. 2007).ΔΨ_m is an important indicator of mitochondrial energetic state and cell viability (Chen 1988). ΔΨ_m is coupled with oxidative phosphorylation to drive ATP synthesis (Liberman, Topaly et al. 1969; Senior 1988). During myocardial reperfusion injury, opening of the mitochondrial permeability transition pore (MPTP) collapses ΔΨ_m and uncouples oxidative phosphorylation, resulting in ATP depletion and apoptosis (Beltran, Mathur et al. 2000; Hausenloy and Yellon 2003). Fluid shear stress is reported to influence mitochondrial ATP synthesis, which is coupled with ΔΨ_m (Mitchell and Thomas 1979; Kudo, Morigaki et al. 2000). The formation of mitochondrial ROS (mtROS) is dependent on ΔΨ_m (Korshunov, Skulachev et al. 1997), and mtROS level increases exponentially as ΔΨ_m is increased or hyperpolarized above -140 mV (Lee, Bender et al. 2002). In response to oxidative stress, mitochondrial manganese superoxide dismutase (Mn-SOD) is up-regulated (Storz 2007), and dismutates O₂^·− anion to H₂O₂. In response to laminar shear stress, cytosolic CuZn-SOD expression is up-regulated (Inoue, Ramasamy et al. 1996).

In this protocol, method and experimental design will be provided to demonstrate that (1) pulsatile shear stress (PSS) increased ΔΨ_m via up-regulation of Mn-SOD activities, whereas (2) oscillatory shear stress (OSS) increases mtO₂^·− production via NADPH Oxidase and c-Jun NH₂-terminal kinase (JNK) signaling.

Materials

• Bovine (BAEC) or human aortic endothelial cells (HAEC)

• Glass slides (5 cm²; BD Bioscience)

• Collagen Type I (BD Bioscience)

• High glucose (4.5 g/l) DMEM (Invitrogen)

• Heat-inactivated fetal bovine serum (Hyclone)

• 100 U/ml L-glutamine-penicillin-streptomycin (Sigma)

• JNK inhibitor SP600125 (10μM)

• NADPH oxidase inhibitor apocynin (1mM)

• Anti-oxidant N-acetyl cysteine (NAC, 5mM)

• siRNA target sequence for Bovine JNK1: 5′-CATGGAGCTCATGGATGCAAA-TCTT-3′ (30 nM)

• siRNA target sequence for Bovine JNK2: 5′-CATGAAAGAATGTCCTACCTTCTTT-3′. (30 nM)

• Lipofectamine RNAiMAX (Invitrogen)

• Negative control siRNA (Qiagen)

• Cationic fluorescent dye, tetramethylrhodamine methyl ester (TMRM⁺) (Molecular probes)

• Dulbecco’s Phosphate Buffered Saline (DPBSInvitrogen)

• High performance digital CCD camera (Pixelfly II, Cooke Corporation)

• IPlab software (BD bioscience)

• Rotenone (Sigma)

• Oligomycin (Alexora)

• FCCP (Carbonylcyanide-4-(trifluoromethoxy)-phenylhydrazone) (Sigma)

• MnTMPyP (Alexora)

• Trypsin (Invitrogen)

• MitoSOX Red (Invitrogen)

• Dulbecco’s Phosphate Buffered Saline supplemented with 2% FBS (Hyclone)

• 2% Paraformaldehyde

• Flow cytometer (e.g. BD LSR II, BD Biosciences)

• LDL (isolated from blood samples of fasting adults; (Hwang, Ing et al. 2003)

• CuSO4 (Sigma)

• EDTA (Signma)

• 0.22μm filter (Fisher Scientific)

Seed and prepare cells

• 1Seed BAEC or HAEC cells on glass slides at 1.5 × 10⁵ cells per slide and grow to confluent monolayers in high glucose (4.5 g/l) DMEM supplemented with 10% heat-inactivated fetal bovine serum, 100 U/ml L-glutamine-penicillin-streptomycin for 48 h in 5% CO2 at 37°C.
• 2Starve cells in DMEM with 0.5% FBS overnight to reduce phosphorylative background prior to shear stress exposure.

Perform dynamic flow inhibitor study or modulation of gene expression with siRNA

• 3For inhibitor studies, pre-treat cells with either JNK inhibitor SP600125 (10μM) for 30 minutes, NADPH oxidase inhibitor apocynin (1mM) for 2 hours or anti-oxidant N-acetyl cysteine (NAC, 5mM) prior to shear stress exposure. For modulating gene expression, BAEC were transfected with 30 nM of siRNA using Lipofectamine RNAiMAX, and negative control siRNA as the scramble siRNA. siRNA transfected cells were used 48 hours afterward for confirmation of gene knockdown or functional assay.
• 4BAEC or HAEC were exposed to the following conditions: (1) Control at static conditions, (2)PSS at a time-averaged shear stress (τ_ave) of 23 dyn.cm⁻² and temporal gradient (∂τ/∂t) of 71 dyn·cm⁻²·s⁻¹ or (3) OSS at τ_ave= 0.02 and ∂τ/∂t at ± 3 dyn·cm⁻²·s⁻¹ for indicated time using A dynamic flow channel simulating hemodynamics in arteries (Hsiai, Cho et al. 2001).

After flow exposure, the cells will undergo parallel procedures either to measure mitochondrial membrane potential (Step 5–9) or measure mitochondrial superoxide production (Step 10–14).

Measure mitochondrial membrane potential (ΔΨ_m)

• 5To examine Δψ_m in response to mitochondrial respiratory chain inhibitors and uncouplers, confluent monolayers of endothelial cells were treated for 1 hour at 37°C with: (i) 1μM of rotenone to inhibit the electron transfer from Fe-S centers in Complex I to ubiquinone, (ii) 5μg/mL of oligomycin to inhibit ATP synthase, (iii) 1μM of FCCP, a protonophore and potent uncoupler of oxidative phosphorylation, (iv) 10μM Cyclosporine-A, an inhibitor of mitochondrial permeability transition pores, and (v) 50μM MnTMPyP, a Mn-SOD mimic
• 6Following flow exposure or inhibitor treatment, cells were washed and incubate at 37°C with 10 nM of TMRM⁺ for 30 min in DPBS
• 7After the incubation, cells were washed with PBS and trypsinized off and re-suspended in 0.5ml of DPBS.
• 8TMRM⁺ was excited at 488nm, and fluorescence emitted at 588 nm was measured with (FL2) channel by FACS using the FACS Caliber system (BD Biosciences, San Jose, CA).
• 9Fluorescence intensity was used to calculate mitochondrial membrane potential as described in the background information section.

Quantify mitochondrial superoxide production

• 10Following flow exposure, the cells were incubated with MitoSOX Red (3 μM) at 37°C for 10 minutes.
• 11The cells were then collected by trypsinization and washed with DPBS supplemented with 2% FBS.
• 12The cells were then fixed in 2% paraformaldehyde for 10 min and re-suspended in 0.5ml of PBS with 2% FBS.
• 13Using a flow cytometer, MitoSOX Red was excited at 488 nm and fluorescence emission at 575 was measured.
• 14Relative fluorescence intensity was used as measurement of mitochondrial superoxide production.

Perform statistical analysis

Experimental data from step 9 or 14 were analyzed and expressed as mean ± SD. Comparisons of multiple groups were analyzed by one-way analysis of variance (ANOVA). Statistical significance for pairwise comparison was determined by using the Tukey test. P-values of < 0.05 are considered statistically significant.

COMMENTARY

Background Information

A dynamic flow channel is used to implement pulsatile shear stress (PSS) or oscillatory shear stress (OSS) simulating hemodynamics in human carotid arterial bifurcations. OSS is commonly considered to be an inducer of vascular oxidative stress whereas PSS is considered to reduce oxidative stress (Ku, Giddens et al. 1985; De Keulenaer, Chappell et al. 1998).The flow system is designed to generate well-defined flow profiles across the width of the parallel flow chamber at various temporal gradients (∂τ/∂t), frequencies, and amplitudes (Hsiai, Cho et al. 2001). Endothelial cells are exposed to the following conditions: (i) Control at static conditions, (ii) PSS at a time-averaged shear stress (τ_ave) of 23 dyn·cm⁻² with a temporal gradient (∂τ/∂t) of 71 dyn.cm^·−2·sec⁻²; and (iii) OSS at τ_ave= 0.02 and ∂τ/∂t at ±3 dyn·cm⁻²·s⁻¹.

MitoSOX Red is a fluorgenic dye selective for mitochondrial superoxide in live cells (Robinson, Janes et al. 2006). It localizes into cellular mitochondria and is readily oxidized by superoxide, but not other sources of reactive oxygen or nitrogen species. Mitosox is hexyl triphenylphosphonium conjugated to hydroethidine (HE); while both HE and Mito-SOX can be oxidized by mitochondrial superoxide, only the later can used to detect mitochondrial specific oxidation when excited at selective wavelength(Robinson, Janes et al. 2006).

TMRM⁺ is a non-invasive cationic fluorescent dye used to quantify changes in mitochondrial membrane potential (Floryk and Houstek 1999; Scaduto and Grotyohann 1999). TMRM+ is a permeable dye that does not bind to cells and accumulates in the negatively charged mitochondria by electrostatic attraction. A shift in fluorescent intensity corresponds to a depolarization event due to a change in the dye’s concentration in the mitochondria. Mitochondrial membrane potential (ΔΨ_m) was established by probing the fluorescent intensity, followed by applying the Nernst equation(Ehrenberg, Farkas et al. 1987):

$$E=E_0-\frac{RT}{nF}·log(\frac{{[{\mathit{TMRM}}^{+}]}_{in}}{{[{\mathit{TMRM}}^{+}]}_{\mathit{out}}})$$

where R denotes the universal gas constant, “T” the temperature in Kelvin, “F” the Faraday constant and “n” the number of electrons transferred in the half reaction. [TMRM⁺]_in denoted TMRM⁺ concentration inside and [TMRM⁺]_out outside the mitochondria. The value of “RT/nF” was calculated to be 61mV at 37°C (Cortese 1999; Nicholls 2006). [TMRM⁺]_out was constant due to the relatively higher concentration than [TMRM⁺]_in, assuming that E₀ = ΔΨ_m = −140mV at equilibrium under non-stimulation condition(Ehrenberg, Farkas et al. 1987; Loew, Tuft et al. 1993; Nicholls 2006). The changes in ΔΨ_m [mV] was determined as follows (Ehrenberg, Farkas et al. 1987; Loew, Tuft et al. 1993; Chacon, Reece et al. 1994; Nicholls 2006):

$$\mathrm{\Delta }\mathrm{\Psi }{m}_{\mathit{stimulation}}=-140-61·log(\frac{{\mathit{TMRM}}^{+}int{\mathit{ensity}}_{\mathit{stimulation}}}{{\mathit{TMRM}}^{+}int{\mathit{ensity}}_{\mathit{non}-\mathit{stimulation}}})[\text{mV}]$$

Critical Parameters and Troubleshooting

The measurement of mitochondrial redox status in terms of membrane potential and superoxide production with fluorescence dye is a delicate method. Optimization of experimental conditions and performance of a numbers of trials can reduce the inter-observer variations. The factors that affect the reproducibility include cell conditions, dye concentration, incubation intervals and timing of measurements. The mitochondrial specificity of the fluorescence dye also depends on the concentration of dye and the incubation time with cells. High concentration of dye or prolonged incubation time will likely increase non-specific incorporation of the dyes into other intracellular compartments. Reagents that disrupt membrane potential will also affect the measurement. Cells should be quickly prepared in a dark setting to prevent degradation or shift in fluorescent signals. These issues can be partially alleviated by fixing cells prior to FACS analysis. For superoxide production, MitoSox Red incorporation into mitochondrial relies on mitochondrial membrane potential. Damages to cells may cause mitochondria rupture leading to dye localization to nucleus and non-specific readings. Thus, the metabolic status of the cells constitutes a major confounding variable to the experimental outcomes. Table 9.36.1 provides a list of troubleshooting guides.

Table 9.36.1.

List of problems and suggested solutions.

Potential Problem	Possible Reason	Suggested Solution
High Background	Cells metabolically too active Fluorescence dye concentration too high Incubation time too long Cell death and aggregation	Starve cells for 4 hours or over night Reduce and optimize fluorescence dye amount Reduce incubation time Avoid damaging cells and optimize dissociation of cells
Low signal	Dye leaching out of cells Not optimized dye concentration, incubation time or reagent degradation Bleaching of signals	Analyze sample immediately Use positive and negative control to optimize conditions Avoid exposure to light
No difference in fluorescence	Not optimized conditions Reagent disrupt membrane potential and subsequent specific dye uptake Superoxide reaction with NO to form peroxynitrite	See above to control background and optimize dye concentration and incubation time Control cell culture condition to ensure cell health status and no membrane potential disruptors. Use pan-NO synthesis inhibitor

Anticipated Results

Characterization of Δψ_m in intact endothelial cells

Mitochondrial respiratory chain inhibitors and uncouplers can be employed to assess the characteristics of TMRM⁺ dye in intact HAEC (Fig. 9.36.1). Addition of FCCP, a protonophore to uncouple oxidative phosphorylation, will depolarize ΔΨ_m in intact cells and decrease the TMRM⁺ intensity by 25% compared to the control (P < 0.05, n=5). Treatment with rotenone, an NADH dehydrogenase inhibitor, will depolarize ΔΨ_m and decrease the TMRM⁺ intensity by 55% (P < 0.05, n=5). Treatment with oligomycin, an ATP synthase inhibitor, will hyperpolarize ΔΨ_m and increase TMRM⁺ intensity by 2.5-fold (P < 0.05, n=5). Furthermore, cyclosporine-A, an inhibitor of mitochondrial permeability transition pores (MPTP), will increase the TMRM⁺ intensity by 2.6-fold (P < 0.05, n=5). Treatment with FCCP, oligomycin and rotenone will further depolarize ΔΨ_m and decrease TMRM⁺ intensity by 71% (P < 0.05, n=5). The changes of ΔΨ_m (mV) are in agreement with published results (Cassarino, Swerdlow et al. 1998; Ward, Rego et al. 2000) (Table 9.36.2). Hence, the dynamic range of TMRM⁺ provides a basis to characterize ΔΨ_m in response to shear stress.

Fig. 9.36.1.

Mitochondrial membrane potential (ΔΨ_m) in response to mitochondrial respiratory chain inhibitors and uncouplers in endothelial cells. (a) Flow cytometry analysis was performed to monitor the TMRM⁺-stained HAEC. In the presence of FCCP and rotenone, the TMRM⁺ intensity was decreased by 25% and 55%, respectively, in comparison with the control (*,** P < 0.05, n = 5). In the presence of oligomycin and Cyclosporine-A, the TMRM⁺ intensity was increased by about 2.5-fold (*** P < 0.05). Treatment with a combination of FCCP, oligomycin and rotenone decreased TMRM⁺ intensity by 71% (****P < 0.05, n = 5). (b) Nernst equation was applied to convert TMRM+ signals to ΔΨ_m. The changes in ΔΨ_m in response to mitochondrial respiratory chain inhibitors and uncouplers followed the trends in TMRM⁺ intensity.

Table 9.36.2.

ΔΨ_m in response to electron transport chain inhibitors and uncouplers.

	ΔΨm (mean)	± STD
Control	−140.00	6.89
FCCP	−118.64	4.98
Rotenone	−107.81	7.34
Oligomycine	−165.01	4.23
Cyclosporine A	−165.29	9.80
rotenone/FCCP/Oligomycin	−88.00	3.90

Pulsatile Shear Stress Increases ΔΨ_m

While the molecular mechanisms whereby pulsatile versus oscillatory shear stress mediated-mtO₂^·− remain to be addressed, we have provided the innovative insights into the dynamics of mitochondrial redox status: (i) Pulsatile shear stress (PSS) increases ΔΨ_m in HAEC (Fig. 9.36.2a,b), (ii) PSS up-regulated Mn-SOD mRNA and protein expression (Figs. 9.36.2d–e), and (iii) Mn-SOD up-regulation represents a potential pathway whereby shear stress influenced ΔΨ_m (Figs. 9.36.2e) (Li, Beebe et al. 2009).

Fig. 9.36.2.

Pulsatile shear stress increases mitochondrial membrane potential by up-regulating Mn-SOD activities. (a) & (b) PSS exposure for 2 hours increases TMRM⁺ cationic dye intensity for ΔΨ_m in HAEC compared to the static condition. (c) TMRM⁺ intensity was measured by FACS and calibrated to voltage (mV) for ΔΨ_m. (* p < 0.05 versus static condition, n = 4) (d) PSS exposure for 4 hours increased Mn-SOD protein expression normalized to β-tubulin. (e) Mn-SOD activities were also up-regulated in response to PSS. (f) HAEC were transfected with control siRNA (Scr) or siMn-SOD (si), followed by exposure to shear stress or static condition. siMn-SOD attenuated PSS induced ΔΨ_m as compared to control siRNA (* p< 0.05, n = 3).

PSS is considered to be cardioprotective (Hwang, Ing et al. 2003) and our observations suggest that one of the possible mechanisms whereby PSS confers cardioprotection may be due to an increase in ΔΨ_m that is important for oxidative phosphorylation and ATP synthesis (Chen 1988).

Although long term PSS reduces oxidative stress, we found that short term exposure of endothelial cells to PSS induced transient mitochondrial superoxide production (Fig. 9.36.3).

Fig. 9.36.3.

HAECs were exposed to PSS for 30 minutes or 2 hours. Mitochondrial superoxide production was measured by flow cytometry using mitochondrial superoxide probe MitoSOX Red. Relative superoxide production was calculated based on fluorescence intensity.

Oscillatory shear stress induced mtO₂^·− production via NADPH oxidase and JNK activation

To examine the mechanisms of shear stress induced mitochondrial superoxide production, we assessed whether NADPH oxidase and JNK activation were implicated. We tested the effects of Apocynin (inhibitor of NADPH Oxidase), JNK inhibitor (SP600125), and JNK knock-down (with JNK siRNA, siJNK) on mitochondrial superoxide (mtO₂^·−) production in response to OSS. Flow cytometry was employed to quantify MitoSOX Red intensities specific for mtO₂^·−.

Oscillatory shear stress induced JNK activation (Fig. 9.36.4, Fig. 9.36.6a) and a 2.57-fold increase in mitochondrial superoxide production as compared to the static condition (Fig. 9.36.5). The induction of mitochondrial superoxide by OSS was inhibited by SP600125 (10μM) by 62% (Fig. 9.36.5).

Fig. 9.36.4.

JNK Activation in Response to OSS. (a) p-JNK was stained with FITC-anti-p-JNK (green). Active cellular mitochondria were localized using MitoTracker Red. Nuclei were stained with DAPI (blue). Under static conditions, JNK green fluorescence was hardly visible. (b) In response to OSS, a significant JNK green fluorescence developed after 30 minutes, accompanied with yellowish/orange signals as a result of merged spectra between FITC and MitoTracker Red.

Fig. 9.36.6.

Oscillatory shear stress increased MitoSOX Red intensities via JNK activation. (a) BAEC monolayers were exposed to static condition versus oscillatory shear stress (OSS) for 30 minutes, 1 hour, or 2 hours. Phosphorylated JNK was expressed as fold ratios relative to total JNK and static conditions. OSS induced a peaked JNK activation at 1 hour (both JNK isoforms) (*P < 0.01, n=3). (b) Flow cytometry analyses of the mean intensities of MitoSOX fluorescence normalized to the static controls in response to OSS, static + siJNK, and OSS + siJNK. (c) Small interfering JNK-1 and JNK-2 (siJNK) significantly knocked down JNK from 2.1- to 0.65-fold as compared to the control and scrambled JNK (Scr). (d) The histograms showed that transfecting siJNK significantly reduced OSS-mediated MitoSOX intensity (^#P < 0.01, n=3)

Fig. 9.36.5.

Inhibition of JNK attenuated MitoSOX Red intensities. BAEC monolayers were pre-treated with JNK inhibitor, SP600125, and mitochondrial O₂^·− specific dye, Mitosox Red, prior to flow exposure. Measurements were performed in duplicates using BD LSR II flow cytometer. (a) The data were presented by histograms in terms of the mean intensity of MitoSOX fluorescence normalized to those of the static conditions. (b) OSS-induced MitoSOX intensity was significantly attenuated in response to JNK inhibitor (^# P < 0.01, n=3).

Next, we demonstrated the effect of JNK on mtO₂^·− production with siJNK. The knockdown of JNK with siRNA was confirmed by western blot analysis (Fig. 9.36.6c). JNK1 protein level was decreased by 71% and JNK2 by 74% following siJNK transfection. JNK knockdown with siJNK completely inhibited OSS-induced MitoSOX Red intensity as compared to the static condition (Fig. 9.36.6b,d).

Pre-treatment of cells with Apocynin (1mM) also reduced OSS-mediated Mitosox Red intensity from 1.80- to 0.89-fold as compared to the static conditions (Fig. 9.36.7). Taken together, these findings demonstrated the notion that OSS mediated mtO₂^·− production via NADPH oxidase and JNK activation.

Fig. 9.36.7.

Inhibition of NADPH oxidase attenuated OSS-induced MitoSOX intensities. MitoSOX fluorescence was measured by flow cytometer. (a) The data were presented by histograms in terms of the mean intensity of MitoSOX fluorescence normalized to those of the static controls. (b) While OSS induced an increase in MitoSOX fluorescence by 1.75±0.2 (*P < 0.01 versus static conditions, n=3), pre-treatment with Apocynin significantly attenuated OSS-induced MitoSOX intensity (^#P < 0.01, n=3).

In corollary, we assessed whether OxLDL induced generation of endothelial mtO₂^·− and change in the ΔΨ_m via JNK pathway. We silenced JNK1 and JNK2 gene expression with siRNA (siJNK). In response to OxLDL at 50μg/mL for 1 hour, MitoSOX Red intensity was significantly increased by 1.88±0.19-fold (n=3, P<0.05) (lane 1 vs. 3) and this increase was reversed by siJNK (88.4% reduced, n=3, P<0.05) (lane 3 vs. 6) (Fig. 9.36.8a,b). Similarly, ΔΨ_m as converted from the TMRM⁺ intensity, was significantly increased by 18%, from −149.60±5.64mV to −180.97±0.64mV (n=3, P<0. 05) (lane 1 vs. 3) in response to OxLDL. This increase was attenuated by siJNK (61.7% reduction, n=3, P<0.05), (lane 3 vs. 6) (Fig. 9.36.8c). Native LDL (nLDL) had no effects on mtO₂^·− and ΔΨ_m (lanes 2 and 5 in Fig. 9.36.8b,c) (n=3, P>0.05). Hence, OxLDL-activated JNK influenced mitochondrial redox status.

Fig. 9.36.8.

SiJNK attenuated OxLDL-induced mitochondrial redox status. HAEC were transfected with siJNK or scramble siRNA for 48 hours. (a) Cell lysate was used to verify the efficiency of siJNK on the protein level of JNK. (b) Cells were pre-incubated with 5μmol/L of MitoSox Red for 10 minutes at 37°C. Next, cells were cultured in the absence or presence of 50μg/mL of OxLDL for 1 hour. Cells were fixed by 1% PFA and fluorescent intensity was measured by FACS. Left, typical histograms were showed in the absence and presence of LDLs (Top: scr siRNA, bottom: siJNK). Right, bar-graph was quantified from gated area shown in the histograms. *P<0.05 vs. in the absence of OxLDL and in the presence of scramble siRNA (lane 1), †P<0.05 vs. in the presence of OxLDL and in the presence of scramble siRNA (lane 3). (c) Cells were exposed to 50μg/mL of OxLDL for 1 hour and TMRM⁺ intensity was measured by FACS. The fluorescence intensity was converted to mitochondrial membrane polarization (ΔΨ_m) as described in the background information section *P<0.05 vs. in the absence of OxLDL and in the presence of scramble siRNA (lane 1), †P<0.05 vs. in the presence of OxLDL and in the presence of scramble siRNA (lane 3). These data represented the means from triplicates of two independent experiments. Scr. denoted scramble; n native LDL; and ox OxLDL.

Overall, we demonstrated that pro-atherogenic factors such as OSS and OxLDL modulate mitochondrial redox status in terms of mtO₂^·− production and ΔΨ_m, which can be quantitatively measured with mitochondrial specific fluorescence dye-based flow cytometry.

Time considerations

The overall time span for the procedure will be three days for basic protocol and four days if perform gene modulation step. The hands-on time range from 4.5 to 6.5 hours combining all the experimental steps.