Quantitative Visualization of Nanoscale Ion Transport

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Quantitative Visualization of Nanoscale Ion Transport Lushan Zhou, Yongfeng Gong, Jianghui Hou, and Lane A Baker Anal. Chem., Just Accepted Manuscript • DOI: 10.1021/acs.analchem.7b04139 • Publication Date (Web): 22 Nov 2017 Downloaded from http://pubs.acs.org on November 29, 2017

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Analytical Chemistry

[Submitted to Analytical Chemistry as an article]

Quantitative Visualization of Nanoscale Ion Transport Lushan Zhou1, Yongfeng Gong2,3, Jianghui Hou2,3 and Lane A. Baker1* 1

Department of Chemistry, Indiana University, 800 E. Kirkwood Avenue, Bloomington, Indiana 47405; 2 Renal Division, Washington University Medical School, 660 South Euclid Avenue, St. Louis, Missouri 63110. 3 Center for Investigation of Membrane Excitability Diseases, Washington University Medical School, 660 South Euclid Avenue, St Louis, Missouri 63110.

*

Corresponding authors: Lane A. Baker Department of Chemistry Indiana University 800 E. Kirkwood Avenue Bloomington, Indiana 47405 (812) 856-1873; (812) 856-8300 (fax); E-mail: [email protected]

Keywords: Potentiometric scanning ion conductance microscopy (P-SICM), ion transport, topography-conductance imaging, tight junction (TJ), membranes

1 ACS Paragon Plus Environment


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ABSTRACT

Understanding ion transport properties at various interfaces, especially at small length scales, is critical in advancing our knowledge of membrane materials and cell biology. Recently, we described potentiometric-scanning ion conductance microscopy (P-SICM) for ion conductance measurement in polymer membranes and epithelial cell monolayers at discrete points in a sample. Here, we combine hopping mode techniques with PSICM to allow simultaneous nanometer scale conductance and topography mapping. First validated with standard synthetic membranes and then demonstrated in living epithelial cell monolayers under physiological conditions, this new method allows direct visualization of heterogeneous ion transport of biological samples for the first time. These advances provide a non-contact local probe, require no labeling, and present a new tool for quantifying intrinsic transport properties of a variety of biological samples.


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INTRODUCTION While faradaic electron transfer is typically the initial and/or final step in an energy transfer process, ions often serve as currency in the exchange of electrons. As such, batteries, fuel cells and living systems all rely intimately on the transport, selectivity and concentration of ions for critical processes.1,2 Tools to directly visualize and quantify ion transport at a range of length scales provide opportunities to understand chemical and biochemical principles of materials and physiochemical transport processes. For instance, for living systems, the Ussing chamber3 has long been the gold standard for the study of ion transport through tissues. Likewise, patch-clamp techniques4,5 have proven immensely valuable to understanding ion transport of isolated ion channel(s) in cell membranes. Ion transport at size scales between tissues and the membrane of individual cells proves difficult to address, especially in respect to investigating unique heterogeneous intra/intercellular structures. Optical techniques can prove useful, but tracking transport of ions in extracellular space, in particular monovalent ions, is difficult if not impossible. Scanning probe microscopy techniques such as atomic force microscopy (AFM)6 coupled to electrical measurement might achieve nanoscale resolution, but routine probe construction and application for such biological measurements have not been realized. Scanning ion conductance microscopy (SICM) allows imaging of soft biological samples under physiological conditions in a non-contact manner and provides an ideal platform for recording local ion transport on subcellular scales.7-12 In SICM, the electrolyte-filled nanoscale pipette scans a surface based on the ion current-distance feedback, where ion current decreases as the nanopipette tip approaches the surface



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caused by the hindrance of ion flow through the reduced space between tip and surface. Previous applications of SICM in local ion transport studies were restricted to “fixedposition” point measurements10-12 due to experimental limitations in control of probe position and current measurement. Specifically, the external transmembrane potential applied to drive ion transport in the measurements affects pipette ion current, and hence interrupts the feedback control. The convolution of topography and local conductance measurements were avoided with “fixed-position” point measurements by manual positioning the probe to single points based on pre-topography scan and turning off SICM feedback control during measurement. Point measurements suffer ultimately, as drift can result in inaccuracy in probe positioning and comparative analysis of the entire sample is not possible. Moreover, the low data acquisition rate limits the ultimate utility of fixed-position measurements. To address these limitations, a topographyconductance (quantification of ion transport) imaging platform that allows direct visualization of nanoscale transport at surface/interface is needed. Here,

we

introduce an advanced potentiometric-scanning ion

conductance

microscopy (P-SICM) combined with hopping mode feedback8 and additional electronics to allow simultaneous, label-free mapping of topography and apparent local conductance at cellular interfaces. In this method, local electrical measurements were done in real-time for each imaging point during scanning by adding two “pause” states at beginning/end of the hop, where the SICM feedback control is by-passed. In addition to two orders of magnitude increase in total data acquisition rate, the spatially resolved local

conductance

map

provides

information

of

previously

unseen

transport

heterogeneities within epithelial cell layers. We have also demonstrated the utility of this


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method in visualizing heterogeneous real-time transport change within epithelia under unusual external electrical perturbations with supporting evidence from biological assays. Such unique information from our topography-conductance mapping technique cannot be achieved with previous methods and can be expanded to various samples and stimulate interesting findings in life science and beyond.

Experimental Section Solutions All solutions were prepared with deionized water (resistivity ca. 18 MΩ·cm at 25 °C, Millipore Corp., Danvers, MA). The electrolytes used for filling nanopipettes were: phosphate-buffered saline (PBS) (137 mM NaCl, 8.2 mM Na2HPO4, 1.8 mM KH2PO4, 2.7 mM KCl, pH 7.4) for imaging cell monolayer; and 0.1 M KCl for imaging nanopore membrane. Modified DMEM (Dulbecco’s Modified Eagle’s Medium) without NaHCO3 (D7777, Sigma-Aldrich, St. Louis, MO) supplemented with 10% (v/v) fetal bovine serum (FBS, F4135, Sigma-Aldrich), 44 mM NaCl, and 25 mM 4-(2-hydroxyethyl)-1piperazineethanesulfonic acid (HEPES, Sigma-Aldrich) was used as external buffer for cell monolayer recording. All solutions were filtered with sterile 0.22 µm PVDF filters (membrane, Millipore Corp., Danvers, MA) to avoid blockage of nanopipettes.

Nanopipette Fabrication Dual-barrel nanopipettes were pulled from quartz theta capillaries (QT120-90-7.5, Sutter Instrument, Novato, CA) using a CO2-laser puller (P-2000, Sutter Instrument, Novato, CA); pulling parameters: Heat = 690, Fil = 3, Vel = 35, Del = 160 Pull = 160.



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The tip inner diameter of each barrel typically ranges from 50 nm to 80 nm (determined from scanning electron micrographs, see Figure S4 in supporting information, SEM, FEI Quanta-FEG). A Ag/AgCl wire electrode was inserted into each barrel for current and potential sensing, respectively.

Membrane Preparation Nanopore membranes were prepared from ion-tracked polyimide films (track density 104 tracks/cm2, thickness 25 µm, it4ip, Belgium) through chemical etching.13 Membrane was kept in etchant (13% hypochlorite solution) at 70 °C for ~ 5 min (yielded nanopores with average diameter: 272 nm, see Figure S4 in supporting information) and was immediately transferred to 1 M potassium iodide solution for 30 min to neutralize residual etchant. The nanopore membrane was rinsed with Milli-Q water before use.

Instrumentation The experiments were performed with a home-built SICM. First, the SICM scan head (Figure S1, supporting information) was built on top of an inverted Nikon TE2000 microscope (Nikon Corporation, Japan) and consists two parts: Z translational assembly moves nanopipette in the Z or vertical direction normal to sample surface; and XY translational assembly, onto which the sample is placed, scans sample in the XY plane. A 65 µm Z-nanopositioner (Nano-OP65, Mad City Labs Inc. Madison, WI) attached to a 25 mm Z-micropositioner (MMP1-50E, Mad City Labs Inc.) controls the movement of the nanopipette tip in the Z direction. Coarse Z positioning is achieved with a 3-axis manual linear micrometer stage (460A-XYZ, 12.7 mm range for each axis, Newport


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Corporation, Irvine, CA). For the XY movement, a 2-axis planar nanopositioner (NanoBio200, Mad City Labs Inc.) stage with 200 x 200 µm motion range and large central aperture for sample mount is used and is supported by a customized XY coarse translation stage with 25 mm travel range for both axis. Both piezo elements operate in closed-loop mode (controlled with Nano-Drive® controller, Mad City Labs Inc.) and the basic hopping mode scanning8 were performed using a SICM scanner controller (Ionscope, UK). A customer-built current amplifier was used to monitor pipette ion current with a gain of 1 mV/1 pA and 2 kHz low-pass filter. Pipette electrode bias used here was +0.2 V. To demonstrate the basic topography imaging ability of our home-built SICM, standard synthetic substrate – PDMS inverse of a TEM grid with raised square features (Figure S2a, supporting information) and live epithelial cell monolayer (Figure 4) were imaged. Subcellular structures – microvilli – on epithelial cell surface can also be clearly resolved with our setup (Figure S2b, supporting information) P-SICM setup was the same as described previously (see Figure S3 in supporting information for detailed five-electrode setup schematic).10,12 Briefly, sample was mounted between two chambers of a perfusion cell and both chambers were filled with electrolyte (KCl for polymer membrane and PBS buffer for live-cell monolayer). Reference electrode (RE, Ag/AgCl) and counter electrode (CE, Pt) were placed in the top chamber and held at ground potential with customized electrode control module. Another Ag/AgCl electrode – working electrode (WE) – placed in the bottom chamber was used to apply transmembrane potential across the sample. Dual-barrel nanopipette with tip diameter around 50 nm for each barrel was used for SICM topography scanning (pipette electrode, PE) and local potentiometric recording (potential electrode, UE).



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For “on-line” P-SICM measurements, the basic SICM feedback loop was controlled with a customized FPGA board (Digilent Inc. Pullman, WA) and user interface. Briefly, at the beginning and end of the “hop” at each imaging point/pixel, the feedback control is bypassed and paused for a pre-set duration and a 4 V pulse is generated from the FPGA to trigger an external transmembrane potential (VTM). The VTM is applied to working electrode (WE) from an Agilent 33220A function generator (Agilent Technologies, Santa Clara, CA) with respect to ground (RE and CE). Potentiometric signal is recorded using a customized differential amplifier with x100 gain and 20 Hz low-pass filter. All channel data (XYZ piezo sensor voltages, ion current, VTM, trigger pulse, potentiometric signal) are collected through the FPGA card and are monitored real-time with Axon Digidata 1440A (Molecular Devices, Sunnyvale, CA) and Clampex 10.6 (Molecular Devices). Apparent local conductance calculation was also performed via the FPGA card and the results are used to generate conductance map from the FPGA card.

Cell Culture Madin-Darby Canine Kidney strain II cells (MDCKII, ATCC, Manassas, VA) were cultured in Dulbecco’s Modified Eagle’s Medium (DMEM, D6429, Sigma-Aldrich) supplemented with 10% FBS (v/v), 100 U/mL penicillin and 100 µg/mL streptomycin (P0781, Sigma-Aldrich). Cells were maintained at 37 °C in a humidified air- 5% CO2 atmosphere to achieve confluence and were then harvested with trypsin− EDTA (T4174, Sigma-Aldrich) and seeded (density: 106 cells/cm2) onto a collagen-coated membrane in a perfusion cell. The customized perfusion cell has a transparent porous PET


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membrane (pore diameter 0.4 µm, pore density 2 x106 pores/cm2, Corning, NY) mounted between two chambers with effective exposed area of ~8 x 10-3 cm2 and the PET membrane was coated with 150 µg/cm2 collagen (C8919, Sigma-Aldrich).

Electrochemical Impedance Spectroscopy Electrochemical impedance spectra were taken for samples grown on perfusion cells with modified DMEM buffer (without NaHCO3) on both sides before and after the SICM scanning. A CHI 660C potentiostat (CH Instruments, Austin, TX) was used for the measurements in a three-electrode configuration. The frequency range used for the 10 mV peak-to-peak sinusoidal wave excitation was 1 Hz and 100 kHz, and current was recorded at 60 discrete frequencies. A semicircular response was observed in Nyquist plots (ZIm vs. ZRe), from which the resistances of PET supporting membrane and cell monolayer were determined.

Immunolabeling and Confocal Microscopy Cells grown on Transwell inserts (Corning, NY) were fixed with cold methanol at – 20 °C, followed by blocking with PBS containing 10% FBS and incubation with primary antibodies (diluted 1:300) and FITC- or rhodamine-labeled secondary antibodies (diluted 1:200).

After washing with PBS, slides were mounted with Mowiol

(CalBiochem). Confocal analyses were performed using the Nikon TE2000 confocal microscopy system equipped with Plan-Neofluar ×40 (NA 1.3 oil) and ×63 (NA 1.4 oil) objectives and krypton-argon laser (488 and 543 lines). For the dual imaging of FITC and rhodamine, fluorescent images were collected by exciting the fluorophores at 488



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nm (FITC) and 543 nm (rhodamine) with argon and HeNe lasers, respectively. Emissions from FITC and rhodamine were detected with the bandpass FITC filter set of 500–550 nm and the long-pass rhodamine filter set of 560 nm, respectively.

Quick-Freeze Deep-Etch Electron Microscopy Quick-freeze Deep-etch EM was performed according to published protocol, with minor modifications.14 Cultured epithelial cells were fixed with 2% glutaraldehyde and frozen by abrupt application of the sample against a liquid helium cooled copper block with a Cryopress freezing machine. Frozen samples were transferred to a liquid nitrogen cooled Balzers 400 vacuum evaporator, fractured and etched at minus 104°C for 2.5 minutes, then rotarily replicated with ~ 2 nm platinum deposited from a 20° angle above the horizontal plane, followed by an immediate ~10 nm stabilization film of pure carbon deposited from an 85° angle. Replicas were floated onto a dish of bleach and transferred through several rinses of dH2O, picked up onto formvar coated grids, and imaged on a JEM1400 transmission microscope (JEOL, Peabody, MA) at 80 kV with attached AMT XR111 4k digital camera.

Results and Discussion Simultaneous topography-conductance scanning protocol To measure the apparent local conductance of a feature with SICM, local I-V (or V-V for more sensitive potentiometric signal used here) is recorded at surface with nanopipette and is then referenced to the measurement in bulk solution far above the surface. Therefore, hopping mode SICM8 is used. In hopping mode SICM, the


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nanopipette tip approaches an interface from a far distance/position and stops when ion current drops by a pre-set amount (e.g. 1%) to record topography at each imaging point (pixel). The probe is translated in XY to then generate a three-dimensional representation of the surface. To adapt hopping mode imaging to our measurements, a “pause” state is immediately followed as the tip reaches the closest approach as shown schematically in Figure 1a. In the representative scan traces for all signal channels (Figure 1b), Z scanner voltage (blue) ramps during approach and reaches a plateau at the end when the “pause” trigger is on (green). During this “pause” state, the tip remains stationary (XYZ values fixed) and a trigger pulse is used to turn on a transmembrane potential (VTM, magenta) that drives ion transport across conductive pathways within the sample. Typically, VTM is swept in a linear manner by applying ±50-100 mV triangle wave at 5 Hz. PE and UE in each barrel of the nanopipette measure ion current (red) and potential deflection (induced by VTM, purple) at tip vicinity, respectively. At the end of the “pause” state, VTM is turned off, SICM feedback control resumes to retract the tip by a pre-defined distance. A second “pause” state is enabled before the probe moves to the next pixel to allow a bulk/background measurement under the same conditions. Due to the enhanced sensitivity, recorded potential deflections at two heights are used to calculate the apparent local conductance (G) based on equation (1).10,15 =

∆ ∆ ∆∙∙

(1)

In equation (1), ∆ is the local potential deflection recorded by the potential electrode of the dual-barrel nanopipette, ∆ refers to the vertical travel of the nanopipette between two “pause” states, and represents the solution resistivity. By repeating the above process for each pixel, a topography and an apparent local conductance () map are 11 ACS Paragon Plus Environment


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obtained simultaneously from one scan. This method allows quick visualization of the sample conductance distribution without tedious post-data processing and statistical analysis, and effectively avoids inaccuracy in probe positioning caused by drift relative to “fixed-position” measurements.

Mapping apparent local conductance of nanoporous membrane and hop height selection We first demonstrate the method with nanoporous membrane, a simplified model for biological membranes (Figure 2). A polyimide nanoporous membrane (cylindrical nanopores: 272 nm in diameter, 104 pores/cm2) mounted between two chambers of a customized perfusion cell was imaged in 0.1 M KCl. Four nanopores can be clearly identified in both topography (Figure 2a) and conductance (Figure 2b, bottom left) maps generated from a single scan. The ion transport pathways – nanopores here – are clearly visualized in the conductance map and show higher G values compared to surrounding membrane area. To further demonstrate mapping changes in local conductance, the same area was imaged when electrolyte on the bottom side of the membrane was changed to concentrations: 10, and 50 mM, and 2 M. Since the conductance of a nanopore is determined by both pore geometry and the conductivity of electrolyte inside the pore, changes in electrolyte concentration (hence conductivity) result in changes of G values as shown in conductance maps plotted with the same color scale in Figure 2b (resistivity of the 0.1 M KCl solution filled in the top chamber and the nanopipette was used for calculation of G values based on equation (1), see detailed discussion in Supporting Information). Such differences are more clearly seen


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in line profiles (Figure 2c) of the top two nanopores in images (dashed line). Especially in the 2 M image (Figure 2b, bottom right), the nanopore becomes highly conductive and the local “field” appears to broaden significantly, which can be easily captured with our conductance mapping method. From a practical point of view, moderate pixel density was chosen here to prevent the probe from being stuck inside the pore during imaging. One caveat of mapping and quantifying local conductance of a feature is the selection of “hop height”. Equation (1) calculates the apparent conductance of a transport feature under the tip sensing zone with a simplified linear electric field model. Specifically,

∆ ∆ ∆

defines the average electric field over nanopipette travel range

“∆”. Such estimation is ∆-dependant if the local electric field over a pore or any transport pathways is non-linear. With a cylindrical nanopore, the Newman model16 predicts the electric field above the pore center decays rapidly within the first 5-10 times of the nanopore radius (Figure 3b, simulation details see supporting information), a feature captured in approach curves measured experimentally in previous work.17 Systematic conductance mapping of an individual nanopore revealed the effect of ∆, as plotted in conductance maps (Figure 3a, same color scale for comparison). In these experiments, 0.1 M KCl electrolyte was used on both sides of the membrane and the same probe and scanning parameters were used, except for hop height (∆). By using the same probe and same approach setpoint, we ensure that the local or close (Equation 1) potentiometric measurements were taken at the same probe-sample distance (Dps). Therefore, changes in hop height effectively affects the bulk measurements position and hence the calculated apparent conductance value. 13 ACS Paragon Plus Environment


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Clearly, conductance values measured over nanopore area decrease as ∆ increases (Figure 3a), a result of averaging the local electric field over a larger range, while the conductance stays relatively constant and lower over the membrane areas. Therefore, as the roughness of the sample permits, lower hop height in imaging provides gains in sensitivity in mapping local conductive pathways. On the contrary, conductance shows a broader distribution at smaller ∆ , suggesting possible “overlapping” of closely-spaced conductive features when ∆ is too small. These phenomena are better shown in the selected line profiles across the nanopore (Figure 3c). Therefore, a proper hop height need to be tested and picked for specific samples to yield the best sensitivity and resolution in conductance mapping. Taken the single nanopore model as a general model for most transmembrane transport pathways, 5-10 times of the feature lateral dimension can serve as a good practical start based on the previous discussion that the electric field decays most rapidly within the first 5-10 times of the nanopore (Figure 3b). However, imaging parameters (in particular, ∆) should maintain constant in one scan for comparative analysis within a sample.

Visualizing ion transport across epithelia After validating the conductance mapping method with the simple model – nanopores in membranes, which can be resolved under a wide range of scanning conditions (Figure 2-3), we imaged live epithelial cell monolayers under physiological conditions that require higher sensitivity and robustness of the technique. Epithelia lining body surfaces are critical barriers for maintaining unique internal chemical environments and hence the proper functions of different organs through selectively transporting ions and


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molecules from one side to another. Understanding the transport properties across epithelial cell layers, especially the relatively loose intercellular transport pathways composed of tight junction (TJ)18 pores, is therefore of great importance. Recently, we have demonstrated the utility of P-SICM in monitoring ionic transport at individual cell junctions, resolving epithelial transport heterogeneity and studying TJ protein functions at previously unachieved resolution with point measurements.10-12 However, by performing statistical analysis of multiple recordings from multiple samples, transport heterogeneity along each individual cell junction and dynamic changes in topography and transport properties are averaged out. Additionally, inaccuracy and low data acquisition rate can limit the utility of the technique as mentioned above. These limitations are addressed in our new topography-conductance mapping method. Figure 4 shows the topography and local conductance maps obtained with cultured Madin-Darby Canine Kidney strain II (MDCKII) – a widely used mammalian epithelial cell line for TJ protein function studies – bathed in physiological buffer. The local conductance map clearly showed that paracellular pathways – cell junctions – are more conductive than transcellular pathways, consistent with previous estimations1,15,19 and fixed-position recordings.10-12 G values are not uniform along individual bicellular junctions and also vary between different bicellular junctions, which may provide insight to TJ pore distribution or transport heterogeneity within individual cell junction (this assumes TJ pore forming proteins are stationary on the time scale of our imaging and measurements). This observation demonstrates that the new conductance mapping method, compared to the fixed-position measurements where only one single measurement is taken at the center of an individual bicellular junction, fully exploits the



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nanoscale pipette in nanoscale ion transport recording. Also, some tricellular junctions20 (for example, the one indicated with dashed circle in Figure 4) appeared to be more conductive than bicellular paracellular pathways. Direct visualization of local transport heterogeneity within live epithelial layers is revealed for the first time without the use of any molecular markers that can affect intrinsic transport properties.

In addition to

observing heterogeneity in transport, at least two orders of magnitude gain in data acquisition rate is observed relative to previous fixed-position measurements. Figure 4 shows a scan of 15 x 30 µm2 area imaged at 60x192 pixel resolution with 0.2 second pauses. Collection of this frame takes ~3.5 hours which would take hundreds of hours with fixed-position measurements. With the demonstrated significant improvement in data collection rate as well as gains in information profile of local transport heterogeneity, this method provides promises in capturing real-time changes of local conductance and direct correlation with morphological change, which is unachievable with any other technique. For example, we swept the transmembrane potential (VTM) to ±400 mV – a high voltage range that was rarely explored previously – and recorded topography and conductance maps of the cell monolayer (Figure 5a). Researchers have tested the high voltage effect on epithelial tissues with bulk recording methods and have observed voltage-induced conductance change.21 However, no direct evidence can be obtained with previous techniques to clearly show which part, among the entire sample, contributes the most to the conductance change and whether the high voltage disrupts the epithelial barrier. With our method, obvious topographical changes in cell junctions were seen (Figure 5a) where the junctional areas became broader with increased height. Interestingly, the


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bicellular junction conductance – when plotted under similar color gradient as in Figure 4b– was significantly reduced in the conductance image while tricellular junction conductance remained unchanged (additional discussion see Supporting Information). In other words, the high voltage tightened the epithelial barrier by reducing bicellular tight junction permeability, a fact contrary to intuition that high voltage may break the barrier. Electrochemical impedance spectra taken for the sample before and after high voltage VTM imaging shown in Figure 5b agrees with the finding that high voltage tightens the epithelial barrier. In both spectra, the semicircle shape indicates a complete monolayer and the circle “diameter” reflects ohmic resistance of the entire sample including all transcellular and paracellular channels. To reveal the underlying ultrastructure and protein expression change of the cell junctions after exposed to high VTM, immunofluorescence staining with anti-ZO-1 (zonula occludens-1, important scaffold protein that anchors TJ strand proteins22,23) and freeze-fracture electron microscopy (FF-EM) were performed on MDCKII cell monolayers with (Figure 5c, right column “High Voltage Exposure”) or without (Figure 5c, left column “Control”) experiencing high VTM. The increase in ZO-1 expression in the high voltage exposed cells indicates tighter epithelial barrier due to more TJ strands, which can also be seen in the freeze fracture electron micrographs (Figure 5c arrows). In general, the number of TJ strands is inversely correlated with TJ conductance.24 Applying ±400 mV VTM altered TJ morphology and increased the TJ strand number and complexity, which can explain the changes seen for cell junction architecture in SICM topography image (Figure 5a left), since cell plasma membranes must rearrange to accommodate more TJ strands.



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CONCLUSIONS P-SICM combined with hopping mode feedback, as described here, provides a promising new route to characterize nanoscale ion transport of complex biological samples and to generate high resolution topography and conductance images simultaneously. At least two orders of magnitude gain in data acquisition rate compared to previous fixed-position measurements has been achieved and comparative analysis within one sample was demonstrated with live epithelial cell monolayer. For quantitation of ion transport and resolving multiple transport pathways in apparent local conductance images, hop height has been shown to be an important factor and needs to be carefully picked for specific samples to realize best sensitivity and resolution. Potentiometric measurements for conductance quantification can be expanded to essentially all electrochemical measurements and to stimulate a series of new discoveries based upon nanoscale topo-electrochemical microscopy methods.

Supporting Information Additional experimental details, local potential gradient simulation, SEM of nanopipette and nanopore membrane, extended discussion on high voltage induced topography and conductance change.

ACKNOLEDGMENT This work was supported by National Institute of Diabetes and Digestive and Kidney Diseases

Grant

R01DK084059

and

American


Heart

Association

Grant

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17SDG33410806 and Department of Defense Grant HDTRA11510032. We thank David Bancroft for the great help with the modification of FPGA of the customized instrument.

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FIGURE CAPTIONS Figure 1. (a) Schematic of P-SICM scanning with pauses. Nanopipette is approached to surface and is withdrawn by a pre-set amount at each pixel to map the topography with a “pause” period added to both heights for local conductance recording. (b) Traces (top to bottom) of X, Y, Z piezo, trigger pulse (to enable VTM), VTM, nanopipette ion current, and local potentiometric signal (EMF) showing the scanning process. Each step in the X trace (black) indicates one pixel in scan.

Figure 2. Topography (a) and apparent conductance (b) images of four nanopores in a membrane. (b) Apparent conductance images of the same area are shown as a function of KCl concentration in bottom chamber of the perfusion cell (values indicated in images) while top chamber concentration was maintained at 0.1 M. (c) Line profiles extracted from the conductance maps (dashed line).

Figure 3. (a) Conductance maps of the same nanopore obtained with different hop heights (value indicated in images) used in scanning. (b) Calculated local electric field distribution over the center of a nanopore, normalized local electric field as a function of normalized vertical displacement from surface. Φ represents the potential at a certain point above nanopore, Φ is the pore center potential at surface, z defines the probesurface distance (Dps) and r is the radius of nanopore. (c) Selected line profiles of the conductance maps shown in a.



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Figure 4. Topography (a) and conductance (b) images of MDCKII cell monolayer in PBS buffer, VTM was swept between ±100 mV.

Figure 5. (a) Topography (left) and conductance (right) images of MDCKII cell monolayer under high VTM: ±400 mV). (b) Electrochemical impedance spectra of MDCKII cell monolayer used for (a) before (black square) and after (red circle) the application of high voltage. (c) (top) Immunofluorescence staining of frozen monolayer of normal MDCKII cells (left, “Control”) and MDCKII cells subjected to ±400 mV (right, “High Voltage Exposure”) showing an increased ZO-1 expression after high voltage exposure. (bottom) Freeze-fracture electron micrographs revealed more TJ strands with high complexity in MDCKII cell monolayer that was subjected to ±400 mV (right, “High Voltage Exposure”).


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Figure 1 / ZhouL.



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Figure 2 / ZhouL.


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Figure 3 / ZhouL.



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Figure 4 / ZhouL.


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Figure 5 / ZhouL.



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Quantitative Visualization of Nanoscale Ion Transport

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