Optical estimation of absolute membrane potential using fluorescence lifetime imaging

All cells maintain ionic gradients across their plasma membranes, producing transmembrane potentials (Vmem). Mounting evidence suggests a relationship between resting Vmem and the physiology of non-excitable cells with implications in diverse areas, including cancer, cellular differentiation, and body patterning. A lack of non-invasive methods to record absolute Vmem limits our understanding of this fundamental signal. To address this need, we developed a fluorescence lifetime-based approach (VF-FLIM) to visualize and optically quantify Vmem with single-cell resolution in mammalian cell culture. Using VF-FLIM, we report Vmem distributions over thousands of cells, a 100-fold improvement relative to electrophysiological approaches. In human carcinoma cells, we visualize the voltage response to growth factor stimulation, stably recording a 10–15 mV hyperpolarization over minutes. Using pharmacological inhibitors, we identify the source of the hyperpolarization as the Ca2+-activated K+ channel KCa3.1. The ability to optically quantify absolute Vmem with cellular resolution will allow a re-examination of its signaling roles.

Membrane potential (Vmem) is an essential facet of cellular physiology. In electrically excitable cells, such as neurons and cardiomyocytes, voltage-gated ion channels enable rapid changes in membrane potential. These fast membrane potential changes, on the order of milliseconds to seconds, trigger release of neurotransmitters in neurons or contraction in myocytes. The resting membrane potentials of these cells, which change over longer timescales, affect their excitability. In non-electrically excitable cells, slower changes in Vmem—on the order of seconds to hours—are linked to a variety of fundamental cellular processes (Abdul Kadir et al., 2018), including mitosis (Cone and Cone, 1976), cell cycle progression (Huang and Jan, 2014), and differentiation (Tsuchiya and Okada, 1982). Mounting lines of evidence point to the importance of electrochemical gradients in development, body patterning, and regeneration (Levin, 2014).

Despite the importance of membrane potential to diverse processes over a range of time scales, the existing methods for recording Vmem are inadequate for characterizing distributions of Vmem states in a sample or studying gradual shifts in resting membrane potential (Figure 1—source data 1). Patch clamp electrophysiology remains the gold standard for recording cellular electrical parameters, but it is low throughput, highly invasive, and difficult to implement over extended time periods. Where reduced invasiveness or higher throughput analyses of Vmem are required, optical methods for detecting events involving Vmem changes (e.g. whether an action potential occurred) are often employed (Huang et al., 2006; McKeithan et al., 2017; Zhang et al., 2016). However, optical approaches generally use fluorescence intensity values as a readout, which cannot report either the value of Vmem in millivolts (‘absolute Vmem’) or the millivolt amount by which Vmem changed (Peterka et al., 2011). Variations in dye environment (Ross and Reichardt, 1979), dye loading, illumination intensity, fluorophore bleaching, and/or cellular morphology complicate fluorescence intensity measurements, making calibration and determination of absolute membrane potential difficult or impossible. This limitation restricts optical analysis to detection of acute Vmem changes, which can be analyzed without comparisons of Vmem between cells or over long timescales.

One strategy to address these fluorescence intensity artifacts and quantify cellular parameters optically is ratio-based imaging. For Vmem specifically, ratio-based signals can be accessed either with a two-component system or with an electrochromic voltage sensitive dye, but neither strategy has enabled accurate absolute Vmem recordings. Two-component FRET-oxonol systems, with independent chromophores for ratio-based calibration, have seen limited success (González and Tsien, 1997), and they confer significant capacitive load on the cell (Briggman et al., 2010). Further, their performance hinges on carefully tuned loading procedures of multiple lipophilic indicators (Adams and Levin, 2012), which can be challenging to reproduce across different samples and days. On the other hand, electrochromic probes report voltage as changes in excitation and emission wavelengths of a single chromophore (Loew et al., 1979). While they benefit from simpler loading procedures, signals from electrochromic styryl dyes require normalization with an electrode on each cell of interest to determine absolute Vmem accurately (Montana et al., 1989; Zhang et al., 1998; Bullen and Saggau, 1999). As a result, ratiometric Vmem sensors cannot be used to optically quantify slow signals in the resting Vmem, which may be on the order of tens of millivolts. Indeed, ratiometric Vmem probes are most commonly applied to detect - rather than quantify - fast changes in Vmem (Zhang et al., 1998), much like their single wavelength counterparts.

An alternative approach to improved quantification in optical measurements is fluorescence lifetime (τfl) imaging (FLIM), which measures the excited state lifetime of a population of fluorophores. Because fluorescence lifetime is an intrinsic property, FLIM can avoid many of the artifacts that confound extrinsic fluorescence intensity measurements, such as uneven dye loading, fluorophore bleaching, variations in illumination intensity, and detector sensitivity (Berezin and Achilefu, 2010; Yellen and Mongeon, 2015). If a fluorescent probe responds to the analyte of interest via changes in the lifetime of its excited state, there is the opportunity to use fluorescence lifetime to provide a more quantitative estimate of analyte parameters than can be achieved with fluorescence intensity alone. Although FLIM measurements can be affected by environmental factors such as temperature, ionic strength and local environment (Berezin and Achilefu, 2010), FLIM has been widely employed to record a number of biochemical and biophysical parameters, including intracellular Ca2+ concentration (Zheng et al., 2015), viscosity (Levitt et al., 2009), GTPase activity (Harvey et al., 2008), kinase activity (Lee et al., 2009), and redox state (NADH/NAD+ ratio) (Blacker and Duchen, 2016), among others (Yellen and Mongeon, 2015). Attempts to record absolute voltage with FLIM, however, have been limited in success (Dumas and Stoltz, 2005; Hou et al., 2014; Brinks et al., 2015). Previous work focused on genetically encoded voltage indicators (GEVIs), which either possess complex relationships between τfl and voltage (Hou et al., 2014) or show low sensitivity to voltage in lifetime (Brinks et al., 2015) and require complex and technically challenging measurements of fast photochemical kinetics to estimate voltage (Hou et al., 2014).

Because of this poor voltage resolution, the fluorescence lifetimes of GEVIs cannot be used to detect most biologically relevant voltage changes, which are on the order of tens of millivolts.

Fluorescent voltage indicators that use photoinduced electron transfer (PeT) as a voltage-sensing mechanism are promising candidates for a FLIM-based approach to optical Vmem quantification. Because PeT affects the nonradiative decay rate of the fluorophore excited state, it has been successfully translated from intensity to τfl imaging with a number of small molecule probes for Ca2+ (Lakowicz et al., 1992). We previously established that VoltageFluor (VF)-type dyes transduce changes in cellular membrane potential to changes in fluorescence intensity and that the voltage response of VF dyes is consistent with a PeT-based response mechanism (Miller et al., 2012; Woodford et al., 2015). Changes in the transmembrane potential alter the rate of PeT (Li, 2007; de Silva et al., 1995) from an electron-rich aniline donor to a fluorescent reporter, thereby modulating the fluorescence intensity of VF dyes (Miller et al., 2012) (Figure 1A,B). VoltageFluors also display low toxicity and rapid, linear responses to voltage.

Here, we develop fluorescence lifetime imaging of VoltageFluor dyes (VF-FLIM) as a quantitative, all-optical approach for recording absolute membrane potential with single cell resolution. Using patch-clamp electrophysiology as a standard, we demonstrate that VF-FLIM reports absolute membrane potential in single trials with 10 to 23 mV accuracy (root mean square deviation, RMSD; 15 s acquisition), depending on the cell line. In all cases tested, VF-FLIM tracks membrane potential changes with better than 5 mV accuracy (RMSD). We benchmark VF-FLIM against previously reported optical absolute Vmem recording approaches and demonstrate resolution improvements of 8-fold over ratiometric strategies and 19-fold over other lifetime-based strategies. To highlight the increased throughput relative to manual patch-clamp electrophysiology, we document resting membrane potentials of thousands of cells. To our knowledge, this work represents the first broad view of the distribution of resting membrane potentials present in situ. VF-FLIM is limited to acquisition speeds on the order of seconds, but it is well-suited for studying gradual Vmem dynamics. Using VF-FLIM, we quantify and track the evolution of a 10–15 mV Vmem hyperpolarization over minutes following epidermal growth factor (EGF) stimulation of human carcinoma cells. Through pharmacological perturbations, we conclude that the voltage changes following EGF stimulation arise from activation of the calcium-activated potassium channel KCa3.1. Our results show that fluorescence lifetime of VF dyes is a generalizable and effective approach for studying resting membrane potential in a range of cell lines (Lakowicz et al., 1992).

To characterize how the photoinduced electron transfer process affects fluorescence lifetime, we compared the τfl of the voltage-sensitive dye VF2.1.Cl with its voltage-insensitive counterpart VF2.0.Cl (Figure 1B). We recorded the τfl of bath-applied VF dyes in HEK293T cells using time-correlated single-photon counting (TCSPC) FLIM (Figure 1C–E, Scheme 1). VF2.1.Cl is localized to the plasma membrane and exhibits a biexponential τfl decay with decay constants of approximately 0.9 and 2.6 ns (Figure 1—figure supplement 1). For all subsequent analysis of VF2.1.Cl lifetime, we refer to the weighted average τfl, which is approximately 1.6 ns in HEK293T cell membranes at rest. VF2.0.Cl (Figure 1B), which lacks the aniline substitution and is therefore voltage-insensitive (Woodford et al., 2015), shows a τfl of 3.5 ns in cell membranes, which is similar to the lifetime of an unsubstituted fluorescein (Magde et al., 1999) (Figure 1—source data 2). We also examined VoltageFluor lifetimes at a variety of dye loading concentrations to test for concentration-dependent changes in dye lifetime, which have been reported for fluorescein derivatives (Chen and Knutson, 1988). Shortened VF lifetimes were observed at high dye concentrations (Figure 1—figure supplement 2); all subsequent VF-FLIM studies were conducted at dye concentrations low enough to avoid this concentration-dependent change in lifetime.

To assess the voltage dependence of VoltageFluor τfl, we controlled the plasma membrane potential of HEK293T cells with whole-cell voltage-clamp electrophysiology while simultaneously measuring the τfl of VF2.1.Cl (Figure 1C). Single-cell recordings show a linear τfl response to applied voltage steps, and individual measurements deviate minimally from the linear fit (Figure 1F–H). VF2.1.Cl τfl is reproducible across different cells at the same resting membrane potential, allowing determination of Vmem from τfl images taken without concurrent electrophysiology (Figure 1I). Voltage-insensitive VF2.0.Cl shows no τfl change in response to voltage (Figure 1J, Figure 1—figure supplement 3), consistent with a τfl change in VF2.1.Cl arising from a voltage-dependent PeT process. In HEK293T cells, VF2.1.Cl exhibits a sensitivity of 3.50 ± 0.08 ps/mV and a 0 mV lifetime of 1.77 ± 0.02 ns, corresponding to a fractional change in τfl (Δτ/τ) of 22.4 ± 0.4% per 100 mV. These values are in good agreement with the 27% ΔF/F intensity change per 100 mV originally observed for VF2.1.Cl (Miller et al., 2012; Woodford et al., 2015). Because %ΔF/F is a fluorescence intensity-based metric, it cannot be used to measure absolute Vmem; however, agreement between %ΔF/F and %Δτ/τ is consistent with a PeT-based Vmem sensing mechanism in VFs. To estimate the voltage resolution of VF-FLIM, we analyzed the variability in successive measurements on the same cell (intra-cell resolution) and on different cells (inter-cell resolution, see Materials and methods).

We estimate that the resolution for tracking and quantifying voltage changes in a single HEK293T cell is 3.5 ± 0.4 mV (intra-cell resolution, average RMSD from each electrophysiological calibration, Scheme 2), whereas the resolution for single-trial determination of a particular HEK293T cell’s absolute Vmem is 19 mV (inter-cell resolution, RMSD of each calibration slope to the average calibration, Scheme 2) within a 15 s bandwidth.

We compared the performance of VF-FLIM in HEK293T cells to that of two previously documented strategies for optical absolute Vmem determination. We first tested the voltage resolution of CAESR, the best previously reported GEVI for recording absolute Vmem with FLIM (Brinks et al., 2015). Using simultaneous FLIM and voltage-clamp electrophysiology, we determined the relationship between τfl and Vmem for CAESR under one photon excitation (Figure 1—figure supplement 4). We recorded a sensitivity of −1.2 ± 0.1 ps/mV and a 0 mV lifetime of 2.0 ± 0.2 ns, which corresponds to a −6.1 ± 0.8% Δτ/τ per 100 mV (mean ± SEM of 9 measurements), in agreement with the reported sensitivity of −0.9 ps/mV and 0 mV lifetime of 2.7 ns with 2 photon excitation (Brinks et al., 2015). Relative to VF2.1.Cl, CAESR displays 3-fold lower sensitivity (−1.2 ps/mV vs 3.5 ps/mV in HEK293T cells) and 7-fold higher voltage-independent variability in lifetime (0.46 ns vs 0.07 ns, standard deviation of the 0 mV lifetime measurement). For CAESR in HEK293T cells, we calculate a voltage resolution of 33 ± 7 mV for quantifying voltage changes on an individual cell (intra-cell RMSD, compared to 3.5 mV for VF2.1.Cl, see Materials and methods) and resolution of 370 mV for determination of a particular cell’s absolute Vmem (inter-cell RMSD, compared to 19 mV for VF2.1.Cl).

We also measured the absolute voltage resolution of the ratio-based sensor di-8-ANEPPS, which reports membrane potential by the wavelength of its excitation and emission spectra (Loew et al., 1979). Ratio-based imaging can be achieved by comparing the fluorescence emission at different excitation wavelengths (Zhang et al., 1998); here, we used the ratio, R, of the blue-excited emission to the green-excited emission (see Materials and methods). Via simultaneous ratio imaging and whole cell voltage clamp electrophysiology, we record a sensitivity of 0.0039 ± 0.0004 R per mV, with a y-intercept (0 mV) R value of 1.8 ± 0.2 (Figure 1—figure supplement 5; mean ± SEM of n = 16 HEK293T cells). R depends on the excitation and emission conditions used but should be relatively reproducible on a given microscope rig. To compare R from our system with previous work, we normalized all R values to the R value at 0 mV for each cell. Using the above data, we obtain a sensitivity of 0.0022 ± 0.0002 normalized R per mV, with a 0 mV normalized R of 1.02 ± 0.02, in good agreement with reported values (0.0015 normalized R per mV) (Zhang et al., 1998). For analysis of voltage resolution, we compare VF-FLIM to the non-normalized R, since normalization requires an electrode-based measurement for every recording and is thus not a truly optical strategy. From the non-normalized di-8-ANEPPS R, we obtain an intra-cell resolution (RMSD) of 18 ± 3 mV (5-fold less accurate than VF-FLIM) and an inter-cell resolution (RMSD) of 150 mV (8-fold less accurate than VF-FLIM). The sensitivities and resolutions of VF-FLIM, CAESR, and di-8-ANEPPS in HEK293T are tabulated in Figure 1—source data 3. Because cellular resting membrane potentials and voltage changes (e.g.

action potentials) are on the order of tens of millivolts, the resolution improvements achieved by VF-FLIM enable biologically relevant absolute Vmem recordings: impossible with previous approaches.

To test the generalizability of VF-FLIM, we determined τfl-Vmem calibrations in four additional commonly used cell lines: A431, CHO, MDA-MB-231, and MCF-7 (Figure 2, Figure 2—figure supplement 1, Figure 2—figure supplement 2). We observe a linear τfl response in all cell lines tested. The slope (voltage sensitivity) and y-intercept (0 mV lifetime) of the τfl-Vmem response varied slightly across cell lines, with average sensitivities of 3.1 to 3.7 ps/mV and average 0 mV lifetimes ranging from 1.74 to 1.87 ns. In all cell lines, we observed better voltage resolution for quantification of Vmem changes on a given cell versus comparisons of absolute Vmem between cells. Changes in voltage for a given cell could be quantified with resolutions at or better than 5 mV (intra-cell resolution, Materials and methods). For absolute Vmem determination of a single cell, we observed voltage resolutions ranging from 10 to 23 mV (inter-cell resolution, 15 s acquisition time, Figure 2—source data 1). Statistically significant differences among the cell lines tested were observed for cellular τfl-Vmem calibrations in both the slope (One-way ANOVA with Welch’s correction: F(4, 23.07)=18.12, p<0.0001) and average 0 mV lifetime (One-way ANOVA: F(4, 67)=14.43, p<0.0001). There were no statistically significant differences between A431, CHO, and HEK293T cells (p>0.05, Games-Howell and Tukey-Kramer post hoc tests for the slope and 0 mV lifetime respectively). MDA-MB-231 and MCF-7 cells showed statistically significant variability from other cell lines in slope and/or 0 mV lifetime.

To verify that VF-FLIM was robust in groups of cells in addition to the isolated, single cells generally used for patch clamp electrophysiology, we determined lifetime-voltage relationships for small groups of A431 cells (Figure 2—figure supplement 3A–E). We found that calibrations made in small groups of cells are nearly identical to those obtained on individual cells, indicating that VF-FLIM only needs to be calibrated once for a given type of cell. For pairs or groups of three cells we recorded a sensitivity of 3.3 ± 0.2 ps/mV and a 0 mV lifetime of 1.78 ± 0.02 ns (mean ± SEM of 7 cells (5 pairs and 2 groups of 3); values are for the entire group, not just the cell in contact with the electrode), which is similar to the sensitivity of 3.55 ± 0.08 ps/mV and 0 mV lifetime of 1.74 ± 0.02 ns we observe in single A431 cells. The slight reduction in sensitivity seen in cell groups is likely attributable to space clamp error, which prevents complete voltage clamp of the cell group (Williams and Mitchell, 2008; Armstrong and Gilly, 1992). Indeed, when we analyzed only the most responsive cell in the group (in contact with the electrode), we obtained a slope of 3.7 ± 0.1 ps/mV and 0 mV lifetime of 1.79 ± 0.02 ns, in good agreement with the single cell data. The space clamp error can be clearly visualized in Figure 2—figure supplement 3E, where one cell in the group of 3 responded much less to the voltage command.

To test whether VF-FLIM is also extensible to cells maintained with different culture conditions, we recorded lifetime-Vmem relationship in serum-starved A431 cells (Figure 2—figure supplement 3F–K), obtaining an average sensitivity of 3.6 ± 0.1 ps/mV and a 0 mV lifetime of 1.76 ± 0.01 ns (n = 7; two single cells, two pairs, 3 groups of 3 cells; values are average lifetime across the whole cell group), in excellent agreement with the values obtained for non-serum starved cells. We also tested for concentration-dependent changes in VF lifetime in all five cell lines and in serum starvation conditions. Similar to VF2.1.Cl lifetime in HEK293T cells (Figure 1—figure supplement 2), we observed shortening of VF2.1.Cl lifetimes beginning between 200 and 500 nM dye in all cases (Figure 2—figure supplement 4). All subsequent experiments were carried out at VF2.1.Cl concentrations well below the regime where VF concentration-dependent lifetime changes were observed.

The throughput of VF-FLIM enables cataloging of resting membrane potentials of thousands of cells in only a few hours of the experimenter’s time. We optically recorded resting membrane potential distributions for A431, CHO, HEK293T, MCF-7, and MDA-MB-231 cells using VF-FLIM (Figure 3, Figure 3—figure supplement 1, Figure 3—figure supplement 2). We report resting membrane potentials by cell group (Materials and methods, Figure 1—figure supplement 1) because adjacent cells in these cultures are electrically coupled to some degree via gap junctions (Meşe et al., 2007). Each group of cells represents an independent sample for Vmem. In addition, the fluorescent signal originating from membranes of adjacent cells cannot be separated with a conventional optical microscope, so assignment of a region of membrane connecting multiple cells would be arbitrary. VF-FLIM images (Figure 3, Figure 3—figure supplement 1, Figure 3—figure supplement 2) contain spatially resolved voltage information, but caution should be employed in interpreting pixel to pixel differences in lifetime. Because VF-FLIM was calibrated here using the average plasma membrane τfl for each cell, optical Vmem should be interpreted per cell or cell group.

Mean resting membrane potentials recorded by VF-FLIM range from −53 to −29 mV, depending on the cell line. These average Vmem values fall within the range reported in the literature for all of the cell lines we measured (Figure 3—source data 1). We also recorded resting membrane potentials in a high K+ buffer (120 mM K+, ‘high K+ HBSS’), where we observed a depolarization of 15 to 41 mV, bringing the mean Vmem up to −26 mV to +4 mV, again depending on the cell line. Although 120 mM extracellular K+ should be strongly depolarizing, it will not necessarily produce a membrane potential of 0 mV. Because few literature reports of electrophysiological measurements in 120 mM K+ exist as a point of comparison, we obtained a rough estimate of Vmem in 6 mM extracellular K+ and 120 mM extracellular K+ using the Goldman-Hodgkin-Katz (GHK) equation (Hodgkin and Katz, 1949). Under our imaging conditions and with a broad range of possible ion permeabilities and intracellular ion concentrations, the GHK equation allows Vmem ranging from −91 to −27 mV in 6 mM extracellular K+ and −25 to +2 mV in 120 mM extracellular K+ (see Materials and methods). Recorded VF-FLIM values fall well within this allowed range. Notably, although the GHK equation can determine ranges of reasonable Vmem values, GHK-based Vmem results are approximate at best because of the difficulty in obtaining accurate values of permeabilities and intracellular ion concentrations for specific cell lines. Direct measurement of Vmem, rather than theoretical calculation, is required to obtain accurate values.

We thought VF-FLIM was a promising method for elucidating the roles of membrane potential in non-excitable cell signaling. Specifically, we wondered whether VF-FLIM might be well-suited to dissect conflicting reports surrounding changes in membrane potential during EGF/EGF receptor (EGFR)-mediated signaling. Receptor tyrosine kinase (RTK)-mediated signaling is a canonical signaling paradigm for eukaryotic cells, transducing extracellular signals into changes in cellular state. Although the involvement of second messengers like Ca2+, cyclic nucleotides, and lipids are well characterized, membrane potential dynamics and their associated roles in non-excitable cell signaling remain less well-defined. In particular, the activation of EGFR via EGF has variously been reported to be depolarizing (Rothenberg et al., 1982), hyperpolarizing (Pandiella et al., 1989), or electrically silent (Moolenaar et al., 1982; Moolenaar et al., 1986).

We find that treatment of A431 cells with EGF results in a 15 mV hyperpolarization within 60–90 s in approximately 80% of cells (Figure 4A–C, Figure 4—figure supplement 1, Figure 4—figure supplement 2), followed by a slow return to baseline within 15 min (Figure 4D–F, Figure 4—figure supplements 3 and 0 second acquisitions). The voltage response to EGF is dose-dependent, with an EC50 of 90 ng/mL (14 nM) (Figure 4—figure supplement 4). Vehicle-treated cells show very little τfl change (Figure 4A–F). Identical experiments with voltage-insensitive VF2.0.Cl (Figure 4G–H, Figure 4—figure supplement 1, Figure 4—figure supplement 3, Figure 4—figure supplement 5) reveal little change in τfl upon EGF treatment, indicating the drop in τfl arises from membrane hyperpolarization. We observe the greatest hyperpolarization 1 to 3 min after treatment with EGF, which is abolished by inhibition of EGFR and ErbB2 tyrosine kinase activity with the covalent inhibitor canertinib (Figure 4I–J, Figure 4—figure supplement 6). Blockade of the EGFR kinase domain with gefitinib, a non-covalent inhibitor of EGFR, also results in a substantial decrease in the EGF-evoked hyperpolarization (Figure 4I–J, Figure 4—figure supplement 6). Together, these results indicate that A431 cells exhibit an EGF-induced hyperpolarization, which depends on the kinase activity of EGFR and persists on the timescale of minutes.

Outward K+ currents could mediate EGF-induced hyperpolarization. Consistent with this hypothesis, dissipation of the K+ driving force by raising extracellular [K+] completely abolishes the typical hyperpolarizing response to EGF and instead results in a small depolarizing potential of approximately 3 mV (Figure 5A, Figure 5—figure supplement 1B). Blockade of voltage-gated K+ channels (Kv) with 4-aminopyridine (4-AP) prior to EGF treatment enhances the hyperpolarizing response to EGF (Figure 5A and B, Figure 5—figure supplement 1C). In contrast, blockade of Ca2+-activated K+ channels (KCa) with charybdotoxin (CTX) results in a depolarizing potential of approximately 4 mV after exposure to EGF, similar to that observed with high extracellular [K+] (Figure 5A and B, Figure 5—figure supplement 1D). TRAM-34, a specific inhibitor of the intermediate-conductance Ca2+ activated potassium channel KCa3.1 (Wulff et al., 2000), also abolishes EGF-induced hyperpolarization (Figure 5A, Figure 5—figure supplement 1E). CTX treatment has little effect on the resting membrane potential, while TRAM-34 or 4-AP depolarizes cells by approximately 5–10 mV (Figure 5—figure supplement 2).

To explore the effects of other components of the EGFR pathway on EGF-induced hyperpolarization, we perturbed intra- and extracellular Ca2+ concentrations during EGF stimulation. Reduction of extracellular Ca2+ concentration did not substantially alter the EGF response (Figure 5A, Figure 5—figure supplement 1F). However, sequestration of intracellular Ca2+ with BAPTA-AM disrupts the hyperpolarization response. BAPTA-AM treated cells show a small, 4 mV depolarization in response to EGF treatment, similar to CTX-treated cells (Figure 5A, Figure 5—figure supplement 1G). Perturbation of Ca2+ levels had little effect on the resting membrane potential (Figure 5—figure supplement 2). Introduction of wortmannin (1 μM) to block downstream kinase activity has no effect on the membrane potential response to EGF, while orthovanadate addition (Na3VO4, 100 μM) to block phosphatase activity results in a small increase in the hyperpolarizing response (Figure 5A, Figure 5—figure supplement 1H–I). These results support a model for EGF-EGFR mediated hyperpolarization in which RTK activity of EGFR causes release of internal Ca2+ stores to in turn open KCa channels and hyperpolarize the cell (Figure 5C).

We report the design and implementation of a new method for optically quantifying absolute membrane potential in living cells. VF-FLIM enjoys 100-fold improved throughput over patch clamp electrophysiology, as well as improved spatial resolution. The performance of VF-FLIM hinges on a balance between resolution in three dimensions: membrane potential, space, and time. We discuss the advantages and disadvantages of VF-FLIM in this light, as well as the new application space that is made accessible by VF-FLIM.

The key advantage of VF-FLIM over previously reported optical approaches is its superior Vmem resolution. Resolution can be interpreted as stability of the τfl-Vmem calibration over time and between cells. Any factors other than Vmem that change τfl decrease resolution. VF-FLIM exhibits a 19-fold improvement in inter-cell Vmem resolution over FLIM with the GEVI CAESR (Brinks et al., 2015) and a 8-fold improvement over di-8-ANEPPS excitation ratios (Zhang et al., 1998). Although all optical strategies, including VF-FLIM, have worse Vmem resolution than modern electrophysiology, the greater throughput, improved spatial resolution, and reduced invasiveness of optical strategies make them a powerful complement to electrode-based recordings.

The sources of variability that reduce resolution of optical Vmem measurements are manifold, but two major contributors are membrane specificity of the stain and the complexity of the lipid environment. Nonspecific staining is fluorescence signal from anywhere other than the plasma membrane, such as contaminating intracellular staining from poorly trafficked (CAESR) or internalized (ANEPPS) sensor. In contrast, exogenously loaded VF2.1.Cl exhibits little fluorescence contribution from regions other than the plasma membrane. Secondly, membrane composition and dipole potential can vary between cells and cell lines, changing the local environment of the fluorescent indicator (Wang, 2012; Brügger, 2014). Styryl dyes like di-8-ANEPPS can respond to changes in dipole potential (Zhang et al., 1998; Gross et al., 1994), and VF dyes may be similarly sensitive to dipole potential. Additionally, fluorescence lifetime depends on certain environmental factors (e.g. temperature, viscosity, ionic strength) (Berezin and Achilefu, 2010), which may introduce variability. These parameters are usually determined by the biological system under study, and re-calibration is important if they change dramatically in an experiment.

VF-FLIM, like all optical approaches, improves upon the spatial resolution of patch clamp electrophysiology. While VF-FLIM records the Vmem of an optically defined region of interest (in this study a cell or cell group), electrophysiology records Vmem at an individual cell or part of a cell where the electrode makes contact, which may or may not reflect the Vmem of the entire cell or group. In this study, we interpret VF-FLIM at the whole cell level only, since that is the smallest unit in which the Vmem can be reliably calibrated by whole cell patch clamp electrophysiology. Intriguingly, there are differences in lifetime within some cells in VF-FLIM images at the pixel to pixel level. In small, mostly spherical cells under voltage clamp, one would expect uniform membrane potential (Armstrong and Gilly, 1992), so these subcellular differences are most likely noise in the measurement. We speculate that most of this pixel-to-pixel noise comes from variability in fitting the biexponential lifetime model. Lifetime estimates at each pixel are calculated from 20 to 100-fold fewer photons than the lifetime value for the entire ROI. These lower photon counts at the single pixel level produce Vmem estimates that are less precise than the Vmem estimate for the entire ROI. Collection of more photons at each pixel could likely reduce this noise but would require longer acquisition times. We also cannot fully rule out an alternative explanation that the observed subcellular variability is the result of local differences in membrane composition (Gross et al., 1994).

Vmem recordings in systems too large or too small for electrophysiological study could be an important application of VF-FLIM. Despite the improbability of Vmem compartmentalization in individual HEK293T cells, other cells with complex morphology and processes may display real, subcellular Vmem differences. In addition, delocalized Vmem patterns across tissues could in theory be stable (Cervera et al., 2016a) and have been proposed to contribute to tissue development (Levin, 2014). One remaining challenge in expanding VF-FLIM to these areas is the requirement for an initial calibration with voltage clamp electrophysiology. Alternative ways to control Vmem, such as ionophores or optogenetic actuators (Berndt et al., 2009), may prove useful in these systems. When applying VF-FLIM to tissues, the cellular specificity of the VF stain becomes a consideration, as the VF2.1.Cl indicator used in this study labels all cell membranes efficiently. Looking ahead, recordings in tissue are an exciting area for future development of VF-FLIM, particularly in conjunction with cellular and sub-cellular strategies for targeting VF dyes (Liu et al., 2017; Grenier et al., 2019).

To obtain absolute Vmem measurements with fluorescence lifetime, VF-FLIM sacrifices some of the temporal resolution of electrophysiology or intensity-based voltage imaging. VF-FLIM acquisition times are limited by the large numbers of photons needed per pixel in time-correlated single photon counting (see Materials and methods). As a result, VF-FLIM in its current implementation can track Vmem events lasting longer than a few seconds. For ‘resting’ membrane potential or Vmem dynamics associated with cell growth or differentiation, this temporal resolution is likely sufficient. Nevertheless, in the future, we envision allying VF-FLIM with recently developed, faster lifetime imaging technology to enable optical quantification of more rapid Vmem responses (Raspe et al., 2015; Gao et al., 2014).

Using the improved Vmem resolution and throughput of VF-FLIM, we optically documented resting membrane potential distributions in cultured cells to characterize the membrane potential state(s) present. The presence and significance of distinct Vmem states in cell populations is mostly uncharacterized due to the throughput limitations of patch-clamp electrophysiology, but some reports suggest that distinct Vmem states arise during the various phases of the cell cycle (Ouadid-Ahidouch et al., 2001; Wonderlin et al., 1995). Vmem histograms presented in this work appear more or less unimodal, showing no clear sign of cell cycle-related Vmem states (Figure 3A,D; Figure 3—figure supplement 1A,D,G). We considered the possibility that VF-FLIM does not detect cell-cycle-related Vmem states because we report average Vmem across cell groups in cases where cells are in contact (Figure 1—figure supplement 1). This explanation is unlikely for two reasons. First, Vmem distributions for CHO cells appear unimodal, even though CHO cultures were mostly comprised of isolated cells under the conditions tested (Figure 3D–F). Second, theoretical work suggests that dramatically different Vmem states in adjacent cells are unlikely, as electrical coupling often leads to equilibration of Vmem across the cell group (Cervera et al., 2016a; Cervera et al., 2016b). Although we cannot rule out the possibility of poorly separated Vmem populations (i.e. with a mean difference in voltage below our resolution limit), VF-FLIM both prompts and enables a re-examination of the notion that bi- or multimodal Vmem distributions exist in cultured cells. Furthermore, VF-FLIM represents an exciting opportunity to experimentally visualize theorized Vmem patterns in culture and in more complex tissues. Studies towards this end are ongoing in our laboratory.