Observations of Tunable Resistive Pulse Sensing for Exosome

May 13, 2015 - †Centre for Personalized NanoMedicine, ‡Australian Institute for Bioengineering and Nanotechnology, and §School of Chemistry and M...
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Observations of Tunable Resistive Pulse Sensing for Exosome Analysis: Improving System Sensitivity and Stability Will Anderson,*,†,‡,⊥ Rebecca Lane,†,‡,⊥ Darren Korbie,†,‡ and Matt Trau*,†,‡,§ †

Centre for Personalized NanoMedicine, ‡Australian Institute for Bioengineering and Nanotechnology, and §School of Chemistry and Molecular Biosciences, The University of Queensland, St. Lucia, QLD Australia S Supporting Information *

ABSTRACT: Size distribution and concentration measurements of exosomes are essential when investigating their cellular function and uptake. Recently, a particle size distribution and concentration measurement platform known as tunable resistive pulse sensing (TRPS) has seen increased use for the characterization of exosome samples. TRPS measures the brief increase in electrical resistance (a resistive pulse) produced by individual submicrometer/nanoscale particles as they translocate through a size-tunable submicrometer/micrometer-sized pore, embedded in an elastic membrane. Unfortunately, TRPS measurements are susceptible to issues surrounding system stability, where the pore can become blocked by particles, and sensitivity issues, where particles are too small to be detected against the background noise of the system. Herein, we provide a comprehensive analysis of the parameters involved in TRPS exosome measurements and demonstrate the ability to improve system sensitivity and stability by the optimization of system parameters. We also provide the first analysis of system noise, sensitivity cutoff limits, and accuracy with respect to exosome measurements and offer an explicit definition of system sensitivity that indicates the smallest particle diameter that can be detected within the noise of the trans-membrane current. A comparison of exosome size measurements from both TRPS and cryo-electron microscopy is also provided, finding that a significant number of smaller exosomes fell below the detection limit of the TRPS platform and offering one potential insight as to why there is such large variability in the exosome size distribution reported in the literature. We believe the observations reported here may assist others in improving TRPS measurements for exosome samples and other submicrometer biological and nonbiological particles.

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INTRODUCTION

certain cellular proteins has been found to substantially affect the size of exosomes,15 suggesting that exosome size alone may be reflective of cellular origin. A report suggesting that exosomes in the range of 30−100 nm diameter are able to transverse the blood−brain barrier11 further implicates vesicle size as a critical determinant of in vivo function. Given these observations, the development of exosome characterization platforms has therefore received a great deal of attention.16 A number of techniques are already routinely used to characterize exosomes, including flow cytometry,17 dynamic light scattering,4 nanoparticle tracking analysis,18 electron microscopy,4,19 and atomic force microscopy.14 However, each of these techniques has its own limitations that must be

Exosomes are nanoscaled extracellular vesicles reported to be between 30 and 150 nm in diameter1 which are shed by cells in what is hypothesized to be a form of cell−cell communication.2,3 Because exosomes are present in blood and retain the molecular features of their cell of origin, they have attracted interest as biomarkers for disease4−6 as well as potential therapeutic agents7−9 and drug delivery molecules.10,11 Exosome size distribution and concentration measurements are a critical component in all exosome studies, which frequently assess the quality of exosome extraction and isolation techniques12,13 and compare samples of different cellular origins. For example, it has been observed that salivary exosomes from oral cancer patients are larger and more morphologically heterogeneous and prone to aggregation than those from healthy controls.14 Moreover, the inhibition of © 2015 American Chemical Society

Received: October 22, 2014 Published: May 13, 2015 6577

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Figure 1. TRPS (qNano) system. (a), (i) The Izon qNano unit with attached VPM unit. (ii) The elastic membrane containing a single submicrometer pore in its center. The cruciform shape allows the pore to be stretched axially by geared teeth in the qNano system. (iii) A close-up view of an elastic pore membrane mounted in the qNano system. The teeth that allow for stretching of the membrane are visible. (b) A schematic of the strain of a pore being reduced so as to increase the sensitivity of the system. (c) The corresponding change in the trans-membrane current trace and the increase in magnitude of the resistive pulse as the pore size is decreased.

operates. The system consists of two electrode containing fluid cells, between which a nonconductive, elastic, polyurethane membrane containing a single conical micrometer-sized pore is placed.21 Samples for TRPS analysis are prepared by diluting in a conductive electrolyte buffer and dispensing into the top fluid cell. A trans-membrane electric potential is applied to the system, and as individual particles pass through the pore, a resistive pulse event, ΔR, in the trans-membrane current trace is observed, which, under ideal conditions, is proportional to the volume of the particle as described by

taken into consideration for exosome characterization. Flow cytometry has been used extensively to analyze extracellular vesicles; however, the lower detection limit of conventional flow cytometry is reported to be as large as 300−500 nm,17,20 making the detection of single exosomes difficult. Dynamic light scattering (DLS) characterizes a dispersion distribution of hydrodynamic diameters from fluctuations in the light scattered by particles undergoing Brownian motion; however, DLS is limited in its ability to resolve polydisperse samples, preferentially detecting the larger particles in a sample.21 Similarly, nanoparticle tracking analysis (NTA) observes and tracks the Brownian motion of many individual particles to build a particle size distribution.18 NTA has a lower detection limit of 40−50 nm,22 making it ideal for exosome samples; however, this technique is limited by the number of particles that can be simultaneously analyzed and the large error in measured particle diameters that can occur when the particle tracking time is short.18,20,21 Microscopy techniques including electron microscopy and atomic force microscopy are capable of high-resolution characterization; however, microscopy analysis is typically ex situ, prone to user bias affecting the measured particle-size distribution,4 and has very low sample throughput. Tunable resistive pulse sensing (TRPS) is emerging as a technique for the in situ single-particle characterization of exosomes. A major benefit, which distinguishes TRPS from the previously mentioned methods, is that it is capable of nonsubjective characterization on a particle-by-particle basis. TRPS has been used to successfully measure a variety of nanoparticle suspensions, including magnetic beads,23 and DNA/protein−particle hybrids24−27 and biological particles, including cyanobacteria28 and viruses.29 Comparative studies have also been made between several other methods, finding good correlation between established platforms.21,30,31 TRPS has also already been used in several studies to measure the exosome particle size and concentration distributions.30,32−34 However, a detailed study outlining the quality of the data obtained from TRPS measurements specific to exosome samples has yet to be undertaken. Herein, we assess how changes in the key parameters of the TRPS system (e.g., pore size tuning, electrolyte composition, trans-membrane voltage, and applied particle driving pressure) affect system sensitivity (i.e., the smallest measurable particle) and stability (i.e., pore blockages and system noise) in exosome sample characterization. Principles of Tunable Resistive Pulse Sensing. Figure 1 outlines the equipment and mechanism by which TRPS

ΔR = (4ρd3)/(πD4 )

(1)

where d is the diameter of the particle, D is the diameter of the pore, and ρ is the resistivity of the medium filling the pore.35 A benefit of the TRPS system is the ability to reduce the pore size in real time and thus, according to eq 1, increase the magnitude of ΔR to improve the system signal against the noise in the background trans-membrane current. This is accomplished by tuning the pore geometry by reducing the axial strain on the membrane, as shown in Figure 1(b). For example, Roberts et al.25 reported that a 1.63 mm reduction in pore strain increased the blockade magnitude for a sample of 100 nm polystyrene beads approximately 2.1-fold. In this article, we define pore strain as the distance between opposite facing teeth in the qNano system. Because of the variable pore geometry, single-point calibrations are performed using spherical polystyrene standards of known volume, allowing for the magnitude of the resistive pulse events of an unknown sample to be obtained, but it is imperative that all system variables remain constant between the unknown and calibration measurements to obtain accurate concentration and size measurements. Using a calibration standard of known concentration also enables concentration measurements to be made by comparing the rate of resistive pulse events, g1, of the calibration particle set, C1, (typically measured in particles/mL) to the rate of the unknown samples, g2, of concentration C2 so that C2 = (g2 /g1)C1

(2)

The use of particle driving pressure is required for concentration measurements using the variable pressure module (VPM, Figure 1(a)(i)) to nullify electrokinetic and diffusive particle transport effects.36

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EXPERIMENTAL METHODS

Sample Preparation. Exosome samples were obtained from a variety of cellular sources for experiments; refer to Supporting 6578

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Figure 2. Noise in the trans-membrane current. (a) Three typical noise spectra in the qNano system. (i) Typical system noise and (ii), (iii) deviations due to high system voltage and a system short circuit, respectively. The insets show a 1 s recording of the unnormalized trans-membrane current trace. (b), (i) Resistive pulse magnitude histogram of the exosome sample. (ii) 99% confidence intervals in the resistive pulse magnitude (red lines) and calibrated particle diameters (vertical error bars) after analysis of the σrms noise in the trans-membrane current signal. The dashed red lines in (i) and (ii) show the 0.05 nA cutoff limit for pulse magnitude detection. The histogram shows the distribution of the trans-membrane current noise and that it is within the 0.05 nA cutoff. (c) Three typical resistive pulse events, with the red lines showing the σrms noise in the trans-membrane current. Smaller pulses have a greater % error than larger particles. are denoted by + or − suffixes (e.g., NP100−). Approximately 75−80 μL of buffer solution was dispensed into the bottom fluid cell, and 40 μL of sample was dispensed into the top fluid cell. Trans-membrane voltage was applied and adjusted using Izon Control Suite (ICS v2.1) software. A detailed methods section for each experiment presented in this article, including measurement parameters and a comprehensive list of quantitative measurement results, is outlined in Supporting Information Tables 2 and 3, respectively. For a video protocol of the qNano system used to perform particle size and concentration measurements, please see Maas et al.37 DLS Measurements. Twenty-five microliters of cell culture medium or 1 μL of concentrated exosomes was diluted into 1 mL

Information Table 1 for details. Fluorescein-labeled liposomes (∼100 nm, 1,2-dioleoyl-sn-glycero-3-phosphocholine (DOPC)/cholesterol/ fluorescein-DHPE in a 54:45:1 mol/mol/mol ratio) were obtained from FormuMax (USA). Samples were typically diluted in phosphatebuffered saline (PBS) containing 0.05% Tween-20 (Sigma-Aldrich, USA) for measurements, unless otherwise stated. TRPS Measurements. TRPS measurements were performed using a qNano platform (Izon Science, U.K.). A variety of pore sizes were used in these experiments and are classified by a size rating system that denotes the optimal particle size that the pore size is suited for (e.g, NP100 (100 nm particles), NP200 (200 nm particles), etc.). We were also supplied with pores rated between the standard NP ratings that 6579

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Figure 3. Changes in system sensitivity due to variations in TRPS variables. (a) Frequency (%) by size (nm) of iPS cell-derived exosomes as measured at (i) 48, (ii) 47, (iii) 46, (iv) 45, and (v) 44 mm applied pore stretch. (b) Frequency (%) by size (nm) of mouse brain-derived exosomes as measured in (i) NP100- and (ii) NP200-rated pores. (c) Frequency (%) by size (nm) of fluorescein-labeled liposomes as measured at (i) 120, (ii) 80, and (iii) 40 nA current flow. Insets show the signal trace for each respective measurement. The dashed red line indicates the lower limit of particle detection. 6580

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Langmuir of buffer, and measurements were taken on a Zetasizer 3000HsA (Malvern Instruments, U.K.). The concentration of sample was incrementally increased until the count rate reached a medium value at the highest laser attenuator value. This dilution was then used for TRPS measurements. Three ×10 technical replicates were used with system constants of RI = 1.331 and viscosity = 0.89. Data were analyzed using the monomodal algorithm. Cryo-Electron Microscopy. Exosomes were isolated from 2 mL of BT474 cell culture medium using the Invitrogen total exosome isolation kit (Life Technologies, USA) per the manufacturer’s instructions. Four microliters of exosome preparations was directly adsorbed onto lacey carbon grids (Quantifoil, Germany) and plunged into liquid ethane using an FEI Vitrobot Mark 3 (FEI Company, The Netherlands). Grids were blotted at 100% humidity at 4 °C for about 3 to 4 s. Frozen/vitrified samples were imaged using a Tecnai T12 transmission electron microscope (FEI Company) operating at an acceleration voltage of 120 kV. Images were taken at 30 000× magnification (approximate dose of 13.6 electrons/Å2) using an FEI Eagle 4k CCD (FEI Company) and Serial EM image acquisition software. Exosome size analysis was performed in ImageJ (version 1.47) using the four-point oval tool for area to diameter analysis.

always fall within 0.05 nA of the average trans-membrane current. As such, we reasoned that any value greater than 0.05 nA should be considered to be a resistive pulse event, and a 0.05 nA cutoff threshold was applied to the peak detection algorithm in the ICS software. Figure 2(b)(i) shows the pulse magnitude histogram of an exosome sample (data taken from Figure 3(a)(iii)) with the 0.05 nA cutoff threshold outlined by the vertical dashed red line. The error in individual resistive pulse measurements could also be inferred with 99% confidence by extrapolation of the range of a detected resistive pulse from the local σrms value. Figure 2(b)(ii) shows the 99% confidence interval of both the resistive pulse magnitude and the calibrated particle diameter of the exosomes measured in Figure 2(b)(i); the 99% confidence intervals in the diameter are shown as vertical error bars. Local σrms values were obtained from a 100 ms analysis window around each pulse in the ICS software, where the red lines represent the error in both the particle diameter and in the resistive pulse magnitude from the average rms measurement of the entire current trace. A histogram of the trans-membrane current noise is also included to show the appropriateness of the 0.05 nA cutoff threshold as described above. Because of the cubic relationship between particle diameter and resistive pulse magnitude (as outlined in eq 1), smaller resistive pulses will have significantly greater error in their measured particle diameters. This relationship is illustrated in Figure 2(c), where it can be seen that the smaller resistive pulses in (i) and (ii) have a greater fraction of their resistive pulse magnitude in uncertainty at the 99% confidence level (horizontal red lines), compared to the larger pulse in (iii). Because the use of the pulse height cutoff threshold resulted in particles below 0.05 nA not being detected by the ICS software, the system sensitivity was therefore explicitly defined as the diameter of a particle that would cause a resistive pulse of 0.05 nA after system calibration. We considered this to be the smallest possible particles the TRPS system can reasonably detect after taking into consideration the expected transmembrane current noise. For example, Figure 3(c)(i) shows a resistive pulse that fell below the threshold cutoff of 0.05 nA, whereas in Figure 3(c)(ii), the resistive pulse was able to be adequately distinguished from the trans-membrane current noise and was defined as being caused by a particle in the ICS software. As such, the 0.05 nA cutoff threshold is shown in all particle size distribution histograms presented in this article as a vertical, dashed, red line to allow visualization of the measurement sensitivity. Furthermore, although the default cutoff threshold can be adjusted along with other variables such as pulse duration cutoff thresholds, in this article only default system detection parameters in the ICS software were used because they were found to be suitable for exosome samples as shown below.

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SYSTEM SENSITIVITY AND ERROR The sensitivity of the TRPS system is limited to the smallest particle that can be detected within the noise of the transmembrane current trace. Our experience with the TRPS system is that exosome samples frequently appear to have particles that fall within this system noise. Therefore, there is a need to establish the sensitivity of the TRPS system so that measurement limitations can be defined. For this reason, the following analysis of system noise and how it affects system sensitivity is provided. Defining Trans-Membrane Noise. The noise in the transmembrane current was observed to vary depending on a variety of system parameters, which in turn affected the system’s ability to detect resistive pulse events close to the trans-membrane current. The distribution of three different levels of noise in the trans-membrane current is shown in Figure 2(a). Because the trans-membrane current noise appeared to follow a Gaussian distribution, we defined system noise as the root mean square (rms) of the trans-membrane current, calculated as the standard deviation (σrms) of all current data points over intervals of 100 ms. With the qNano’s measurement bandwidth being 50 kHz, 100 ms of recording provided sufficient data points (5000) for statistical analysis of the trans-membrane current noise while preventing global changes in the transmembrane current from affecting σrms measurements. To construct robust noise spectrum histograms in Figure 2(a), 100 rms intervals for each example were normalized and combined. Under ideal conditions, system noise was typically seen to have σrms values of ∼6−9 pA (Figure 2(a)(i)). However, it was also found that medium-level σrms values (∼10−12 pA) could occur when larger trans-membrane voltages were applied, when ionic strengths differed across the two fluid cells (Figure 2(a)(ii)), when the pore was semiblocked by stuck particles, and when very low ionic strength liquids were used (data not shown). High-level system noise (i.e., >∼15 pA) occurred when the system was not correctly operating under ideal conditions; for example, shorting of the current around the pore due to leakage of the fluid cells (which would manifest itself as a slowly increasing trans-membrane current drift) (Figure 2(a)(iii)) and major pore blockages (Supporting Information). Defining System Sensitivity. For trans-membrane current noise at a nominal 6−9 pA, 99% of all values (∼2.58σrms) will

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RESULTS Membrane Strain. As shown in Figure 3(a), a change in axial strain from 48 to 44 mm in an NP100-rated membrane resulted in an ∼0.53-fold decrease in the lower limit of particle detection (from 66 to 35 nm), an ∼6.7-fold increase in signal sensitivity according to eq 1; similarly, the modal particle diameter decreased ∼0.6-fold (from 73 to 52 nm). However, a decrease in pore stability was observed because the pore strain was reduced as shown in the example signal trace insets in Figure 3(a). No pore blockages were observed over the 120 s measurement at 48 mm strain; however, at 44 mm strain, three 6581

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Figure 4. Changes in system stability due to variation in TRPS variables. (a) Frequency (%) by size (nm) of mouse brain-derived exosomes measured in (i) PBS only, (ii) PBS + 0.01% Tween-20, and (iii) 0.05% Tween-20 buffer in an NP100 pore. Insets show the signal trace for each respective measurement. (b) Frequency (%) by size (nm) of iPS cell-derived exosomes prepared by (i) no filtration, (ii) filtration to 0.22 μm, and (iii) filtration to 0.1 μm as measured in an NP100 pore. The measurement duration and number of observed particles are indicated for each respective measurement. (c) Relative particle flow rate (normalized to the observed maximum rate for each sample) by applied pressure (cm/H2O) for (i) PC3 cell-derived exosomes and 115 nm polystyrene beads measured in an NP100 pore and (ii) PC3 cell-derived exosomes and 203 nm polystyrene beads measured in an NP200 pore. (d) Frequency (%) by size (nm) of liposomes as measured with an NP150 pore in the cis−trans (n = 5) and trans−cis (n = 5) orientations. 6582

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larger than the filter size. In the sample measured with a 0.22 μm filter, the largest particle observed was 338 nm, representing an ∼0.6-fold decrease in the maximum detected particle size from the unfiltered sample. Similarly, for the 0.1 μm filtered sample, the maximum particle diameter measured was 169 nm, an ∼0.3-fold decrease compared to the unfiltered sample. Moreover, filtration was also found to have a significant impact on the particle size distribution; the modal particle diameter for the unfiltered sample was 104 nm, with a 0.79-fold decrease to a modal diameter of 82 nm for both filtered samples. A substantial decrease in particle concentration was also observed after filtration, with the measured particle concentrations for the unfiltered sample being 4.2 × 1011 particles/mL, compared to a measurement of 1.6 × 1010 particles/mL for samples passed through a 0.22 μm filter and 9.7 × 109 particles/mL for samples passed through a 0.1 μm filter. Particle Driving Pressure. Increasing the pressure from 0 to 10 cm/H2O with monodisperse 115 nm polystrene particle standards in an NP100- pore caused an increase in the particle flow rate from 106 to 360 particles per minute, although at pressures higher than 11 cm/H2O (1079 Pa) the system became unstable, likely due to the high concentration of particles present near the sensing area. For 203 nm polystyrene particle standards in an NP200 pore, an increase in pressure from 0 to 10 cm/H2O (0 to 980 Pa) similarly increased the rate of particle flow from 48 to 242 particles per minute; notably no blockages were noted in the NP200 pore, even at the maximum (15 cm/H2O) pressure. The effect of different driving pressures during the measurement of cell-derived exosomes was also investigated, using exosomes collected from prostate cancer PC3 cells by ultracentrifugation.39,40 Similar to the polystyrene standards, increased pressure was observed to cause an increased rate of particle flow with a concomitant decrease in system stability, particularly in pores rated for smaller particles. (Figure 4(c)). For example, in an NP100-pore at 48 mm strain, an increase in pressure from 0 to 10 cm/H2O (0 to 980 Pa) led to an increase in the particle flow rate from 19 to 68 particles/min; however, when the pressure exceeded 13 cm/H2O (1274 Pa) the system became unstable with several blockages noted. In comparison, for an NP200 pore at 48 mm strain a lower particle flow rate was observed at lower pressures and a pressure increase from 0 to 10 cm/H2O (0 to 980 Pa) resulted in an increased particle flow rate from 2 to 35 particles/min. Notably, no blockages occurred in the NP200 pore at increased pressure, even at a maximal pressure of 15 cm/H2O (1470 Pa). The linear correlation of pressure and particle rate appeared to be far weaker for exosome samples as compared to monodisperse 115 and 203 nm polystyrene particle standards in the NP100 and NP200 pores, respectively. Particle Translocation Direction. The pores used in the TRPS system have conical geometry. The standard protocol is to orientate the pore so that particles in the top fluid cell translocate the pore in a direction from the small to large (trans−cis) openings (Figure 1). Investigations into how pore orientation affects measurement quality were performed using the same model liposome system as previously described in the Trans-Membrane Voltage section. Liposomes were measured five times with the pore alternating between the standard (trans−cis) orientation and inverted such that particles translocated in the opposite (cis−trans) pore opening direction. Overall, the orientation of the pore was found to have no

blockage events, which appear as sudden decreases in the transmembrane current usually associated with an increase in system noise, were observed over the same time period requiring user intervention to unblock the pore. Observations of pore blockages, their effect on system stability, and methods to remove them are provided in the Supporting Information. Decreasing pore strain also resulted in decreases in the particle flow rate from 128 particles/min (measured as total counts over the 120 s recording period) at 48 mm to 79 particles/min at 44 mm strain. Pore Rating. Figure 3(b) shows the size distribution of mouse brain-derived exosomes measured in both NP100- and NP200-rated membranes at an equal strain of 48 mm. Measurements taken with the NP200 membrane showed an ∼1.6-fold increase in the modal size (from 101 to 163 nm), an ∼1.2-fold increase in the maximum size (from 580 to 727 nm), and an ∼1.6-fold increase (from 90 to 142 nm) in the minimum particle diameter observed as compared to measurements taken with the NP100 membrane. Additionally, an increase in the rate of resistive pulse events in larger-rated pores was observed, with a 4-fold increase in the rate of particle flow through the pore (from 32 to 128 particles per minute). Trans-Membrane Voltage. Figure 3(c) shows example size distribution histograms for measurements made using a liposome sample which we have found to be an excellent model system for exosomes.38 The relative stability of the liposomes allowed for longer measurement duration analysis which was required for this part of the study. Measurements were made at a constant stretch of 48 mm in an NP100 pore. Over a transmembrane voltage range from 0.34 to 1.10 V, we found that the minimum particle diameter detected at the 0.05 nA cutoff decreased from 72 to 54 nm, respectively, corresponding to a 3.15-fold increase in system sensitivity. Noise in the background current trace increased at higher voltages, with an increase in system noise from 6.48σrms at 0.34 V to 11.60σrms at 1.10 V. Addition of Surfactant. Exosomes isolated from wild-type mouse brain were diluted 1:1000 in buffer solutions containing PBS, PBS + 0.01% Tween-20, and PBS + 0.05% Tween-20. For a measurement duration of 180 s, no blockage events were observed with samples containing 0.05% Tween-20, and three blockage events were observed for samples containing 0.01% Tween-20. For the sample in PBS only, measurements were terminated after 60 s due to the system being extremely unstable, with four blockage events noted in this time. A significant decrease in the modal particle diameter was also observed with increasing Tween-20 concentration, with values of 120, 108, and 101 nm measured for samples diluted in neat PBS (n = 122), 0.01% Tween-20 (n = 181), and 0.05% Tween20 (n = 98), respectively. Overall these results indicate that the addition of surfactant to buffer solution can lead to an increase in system stability and can assist in decreasing particle aggregation. Prefiltration. Figure 4(b) shows an unfiltered sample of iPS cell-derived exosomes measured with an NP100-rated pore, and the maximum particle diameter measured was 554 nm (n = 226). For comparison, exosome samples were diluted 1:20 in PBS + 0.05% Tween-20 and prefiltered with both 0.22 and 0.1 μm micropore filter membranes (Merck Millipore, MA, USA). Filtration was found to have no impact on the stability of this sample as no major blockage events were noted during the measurement of any of the three samples; however, after filtration the particle size distribution still contained particles 6583

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both system stability and the sensitivity of TRPS for exosome measurements and how system variables can improve or impede these issues and have empirically demonstrated the ability to improve system sensitivity and stability by the optimization of system parameters. However, an observation of this study was that optimizing for sensitivity can lead to a concomitant decrease in system stability; for example, while decreasing membrane strain was found to increase sensitivity, it also resulted in a loss of system stability at the lower strain values due to random blocking of the pore by larger particles in the sample. Thus, while enabling the TRPS system for both high sensitivity and high stability is a difficult and sometimes stochastic process, the following discussion may provide assistance to others performing exosome measurements by TRPS. Sensitivity. Our results have outlined several system variables that can be tuned to improve the sensitivity of the TRPS system, enabling the detection of particles that may have otherwise fallen below the sensitivity cutoff limit had parameters not been optimized. Significant increases in sensitivity were seen by

substantial impact on the stability or sensitivity of measurements. The size distribution did not appear to be dependent on the orientation of the pore, and the mean, modal, minimum, and maximum particle diameters were in agreement between the two experimental conditions (Figure 4(d)). Furthermore, the pore direction did not appear to have an impact on system stability; when the pore was orientated in the trans−cis orientation, blockages were observed at a frequency of approximately 0.4/min compared to the cis−trans orientation, where the blockage frequency was 0.7/min. Verification of TRPS with Cryo-Electron Microscopy. A comparison of the relative size distribution of exosomes measured by TRPS and cryo-electron microscopy (cryo-EM) is provided in Figure 5. TRPS measurements were performed

(1) increasing the trans-membrane voltage (Figure 3(c)), (2) using smaller-rated pore membranes (Figure 3(b)), and (3) decreasing membrane strain (Figure 3(a)). Overall, our highest sensitivity measurement was achieved with an NP100 pore at 1.28 V and 44 mm strain (Figure 3(a)(v)) and resulted in the measurement of a 37 nm particle. To our knowledge, this is also the smallest particle measured from an exosome sample by TRPS, improving upon the minimum diameters of ∼70 nm reported by Van der Pol et al.30 and De Vrij et al.33 However, it must be noted that the conditions required for this measurement made the system extremely unstable and multiple pore blockage events occurred. We hypothesize that all exosome samples measured in this study have a substantial percentage of their size distribution falling significantly below the calculated sensitivity cutoff for the measurement. This conclusion is supported foremost by the cryo-EM data presented in Figure 5, where the majority of particles appeared to be in the range of ∼25−30 nm, well below our most sensitive TRPS measurement with a 37 nm sensitivity cutoff. Furthermore, the observation that all measurements had particles detected down to the 0.05 nA cutoff also suggests that exosomes exist below the sensitivity cutoff limit of TRPS measurements. It is important to be aware that the noise in the trans-membrane current makes it difficult for the ICS software to detect resistive pulse events at or near the 0.05 nA cutoff, resulting in frequency size distributions that drop in particle frequency near the sensitivity cutoff limit. The resulting frequency size distributions can then appear to have a normal/log-normal appearance, which must not be interpreted as though the modal exosome size has been found. Finally, past studies have observed particles as small at 30 nm in exosome samples.1,14 Critically, the variability in TRPS measurements and the differences between the TRPS and cryo-EM measurements, in particular, the contrasting preferences of the cryo-EM to detect smaller exosomes and the TRPS system to detect larger exosomes, suggests why such a large size range has been reported in the literature and indicates that multiple techniques should be used to characterize exosome samples. We also note that the error at smaller pulses is significant (as defined in the “System Sensitivity and Error” section of the Supporting Information), indicating that particles near the 0.05

Figure 5. Relative size distributions of BT474-derived exosome as analyzed by cryo-EM and TRPS analysis performed in both NP100 and NP150 pores. Frequency distribution analysis was performed with 5 nm bins. Insets show representative exosomes from the cryo-EM imaging, with scale bars representing 100 nm.

with an NP100 pore and an NP150 pore to capture a fuller range of sizes present in the sample, as outlined in the Pore Rating section above. To compare the relative size distribution of exosomes across the different measurement conditions, the number of exosomes assayed in each measurement, here cryoEM (n = 505), TRPS NP100 (n = 211), and TRPS NP150 (n = 334), was divided by the total number of exosome assayed across all measurements. This enabled the frequency of particles observed across the differed size ranges measured to be compared. The majority of vesicles measured by cryo-EM had diameters below the detection limit of the TRPS measurement (insets in Figure 5); however, a number of larger vesicles were also observed in the cryo-EM measurement that fell within the TRPS size distributions. Despite these larger vesicles being observed in the cryo-EM analysis, they were found to be present in lower concentrations than expected from the TRPS analysis, indicating that there is an upper detection limit in the cryo-EM data.

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DISCUSSION TRPS measurements are susceptible to issues surrounding system stability, where the pore can become blocked by particles, and sensitivity issues, where particles are too small to be detected against the background noise of the system. Here we have investigated the critical parameters which relate to 6584

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tration of exosomes in the sample increased so did the frequency of blockage events. This is most likely due to particle aggregation at the pore opening; however, the increased concentration of larger-than-pore particles present will also play a significant role in obstructing the pore. As such, defining the exosome concentration that causes aggregation is a nontrivial issue due to the polydisperse nature of exosome samples and sample-to-sample variability, but a general observation of this study was that a resistive pulse rate of 100−200 particles per minute in the smallest pores (NP100 and NP100) typically resulted in stable measurements when other factors influencing stability were controlled for. A method for optimizing sample dilution is described in the methods section of the Supporting Information. Attempts to improve stability by the removal of larger particles in the system through filtration had both positive and negative effects. There was a cutoff of larger particles in the sample for both filter sizes used, suggesting that filtration may improve stability where large particles or aggregates are present. However, there was also significant loss of sample through filtration as indicated by the decrease in measured particle concentrations for both 0.22 and 0.1 μm filtration. Additionally, we noted that particles greater than the 0.1 μm filter size were present after filtration, suggesting that exosomes have the ability to “squeeze” through pores of the filter membrane. Because filtering the sample alters the size distribution and concentration measurements, which may lead to spurious conclusions, we therefore recommend against sample filtration until further research into the impact of filtration on exosome samples is performed. The particle driving pressure was found to exert different effects on system stability, depending on pore rating and sample composition. The exosome flow rate through the pore showed weak linear correlation as the applied pressure increased, in contrast to the polystyrene calibration standard as shown in Figure 5(c), although this difference was most likely a result of the low exosome concentrations used to maintain pore stability. Moreover, whereas pressure was required to promote particle translocation from the upper to the lower chamber (data not shown), high pressure values were also correlated with more pore blockages, most likely a result of having too many particles entering the pore opening simultaneously. A significant decrease in the resistive pulse magnitude as pressure was increased was also observed, although currently we have no obvious explanation for this phenomenon. Such an effect will reduce system sensitivity and as such represents a parameter which should be adjusted cautiously. For samples at low concentration which also suffer from stability issues (such as for exosomes), we therefore suggest taking several measurements at different pressures to ensure that the linear pressure/translocation relationship has been maintained. The protocol we suggest for the optimization of particle translocation rate and system stability is to apply pressure in increasing 1 cm/H2O (98 Pa) increments until system stability becomes compromised and frequent pore blockages are observed, at which point the measurement should be taken to obtain the number of resistive pulse events needed for robust measurements. Membrane strain was also seen to affect system sensitivity. To find a point of maximum stability and sensitivity, users should attempt a measurement procedure that incorporates initially stretching the pore to a maximum value and then incrementally decreasing the stretch until stability becomes

nA cutoff may be reported as substantially larger or smaller than their actual size. For example, assuming a trans-membrane current noise σrms of 9 pA, a particle with a resistive pulse magnitude of 0.05 nA will be within ∼18.22% below and ∼13.26% above the calculated particle diameter at the 99% confidence interval. This uncertainty will diminish significantly as the ratio of the pulse height to the trans-membrane current noise increases. For example, a resistive pulse at 0.5 nA will be within ∼1.50% below and 1.49% above the calculated particle diameter at a 99% confidence interval. Given the limitations detailed above, one key understanding when using TRPS for exosome measurements is that some particles of interest will most likely always fall below the lower limit of detection. For size distribution measurements under ideal conditions, where the smallest particle detected falls well away from the sensitivity cutoff at 0.05 nA, it can be reasonably assumed that all of the smallest particles in the sample are being detected and accurately sized. However, for size distributions near or on the cutoff limit we recommend that a sensitivity limit, expressed as the smallest possible particle diameter able to be detected at the 0.05 nA level, should be reported, along with the σrms of the trans-membrane current as an indication of the error in the measurement. Because these limits can change slightly between replicate measurements, it may be useful for researchers to truncate their data above this value to ensure that size and concentration measurements are conserved between samples. Stability. A major limitation of Coulter counter style devices is system stability issues. Such issues occur when particles stick to the pore surface, disrupting particle flow, or when particles larger than the pore become stuck in the pore opening, blocking it entirely.35 Exosomes in particular are known to block TRPS pores and affect pore stability16 and are also consistently shown to be polydisperse in size,1,19,41 which can be problematic in TRPS as even a small number of large particles in the sample can lead to stochastic blocking of the pore during a measurement. These pore blockages require frequent pausing of the measurement so that the blockage can be resolved, typically by means of mechanical agitation16 (i.e., tapping the upper fluid cell to dislodge the blockage at the pore). Also, the likelihood of larger particles blocking the pore in TRPS can be decreased by increasing the pore geometry by stretching the pore membrane; however, this also leads to a decrease in the relative magnitude of resistive pulse events,36 thereby reducing system sensitivity. It has previously been observed that exosomes in solution are prone to spontaneous aggregation,14 and a key finding of this study was the need for nonionic surfactant Tween-20 in PBS buffer to reduce exosome aggregation and obtain stable measurements (Figure 5(a)). The observation that surfactant was necessary to improve stability for isolated exosome samples as well as apparently removing larger particles from the measurement leads us to hypothesize that the isolation techniques used (which employ precipitation and sedimentation42) may leave exosomes in a state of aggregation for further downstream analysis. Critically, our additional investigations have found that Tween-20 at 0.05% does not disrupt vesicle morphology or appear to induce vesicle lysis.38 As such, we therefore highly recommend the use of Tween-20 at or below 0.05% as a stabilization agent in exosome measurements. Exosome concentration and its effect on system stability were difficult to quantify due to the stochastic nature of pore blockages. Our general observation was that as the concen6585

DOI: 10.1021/acs.langmuir.5b01402 Langmuir 2015, 31, 6577−6587

Langmuir

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ACKNOWLEDGMENTS We acknowledge Jayde Ruelcke, Dr. Michelle Hill (The University of Queensland Diamantina Institute, Translational Research Institute, Brisbane, Australia), Associate Professor Ernst Wolvetang, Dr. Dmitry Ovchinnikov and Sam Nayler (Australian Institute for Bioengineering and Nanotechnology, The University of Queensland, St. Lucia, QLD, Australia), and Dr. Juan Carlos Polanco (Queensland Brain Institute, The University of Queensland, St. Lucia, QLD, Australia) for providing the exosome samples used in these experiments. We acknowledge the National Breast Cancer Foundation (NBCF) and Australian Research Council (ARC) for ongoing financial support of our group’s research activities. We also acknowledge the facilities and the scientific and technical assistance of the Australian Microscopy & Microanalysis Research Facility at the Centre for Microscopy and Microanalysis, The University of Queensland.

compromised and frequent pore blockages are observed; the last stable stretch should then be used to obtain a measurement. Finally, to our knowledge, it is a general convention in the TRPS system to run particles through the pore in the trans−cis direction (i.e., when the smallest opening of the pore is orientated upward). Upon investigation, no major difference in the measured size distribution or system stability was seen by running the particles in either a cis−trans or trans−cis direction (Figure 5(d)). There was minor evidence that running the pores in the cis−trans direction may fractionally decrease the chance of blockage; however, this has not yet been fully substantiated. Any changes to this convention should be noted by researchers, however, to maintain interlab measurement consistency.

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CONCLUSIONS We have presented experiments highlighting several issues with the TRPS system in regard to system sensitivity and measurement stability for exosome samples. The sensitivity of TRPS was found to be highly tunable; however, increasing the system sensitivity often led to decreases in system stability, requiring fine-tuning of both parameters for optimized measurements. System variables which affect both system sensitivity and stability must therefore carefully be determined for complex polydisperse samples such as exosomes. Of note was the requisite need for surfactant in the sample buffer to reduce the tendency of exosome samples to spontaneously block at the pore opening. Additionally, the polydispersity of these samples was problematic for achieving maximum sensitivity. In conclusion, it is hoped that these observations will allow other TRPS users to optimize conditions for the measurement of exosome samples. However, further empirical optimization must still be undertaken before the TRPS platform is suitable for use for high-throughput applications.

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REFERENCES

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ASSOCIATED CONTENT

S Supporting Information *

Detailed description of sample preparation, measurement settings, and results. The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.langmuir.5b01402.

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AUTHOR INFORMATION

Corresponding Authors

*Phone: +61 7 3346 4171. Fax: +61 7 3346 3973. E-mail: will. [email protected]. *Phone: +61 7 3346 4173. Fax: +61 7 3346 3973. E-mail: m. [email protected]. Author Contributions ⊥

W.A. and R.L. made equal contributions to this work. The manuscript was written through the contributions of all authors. All authors have given approval to the final version of the manuscript.

Notes

The authors declare the following competing financial interest(s): The authors are pleased to acknowledge a scientific collaboration with Izon Science Ltd. that was initiated at the time that the manuscript was prepared. In this collaboration Izon Science Ltd. provided the researchers with equipment so that fundamental investigations into the qNano platform could be made. The authors gratefully acknowledge the receipt of this equipment. 6586

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