Article pubs.acs.org/ac
Droplet Microfluidic Platform for the Determination of Single-Cell Lactate Release Amy Mongersun,† Ian Smeenk,‡ Guillem Pratx,§ Prashanth Asuri,† and Paul Abbyad*,‡ †
Department of Bioengineering, Santa Clara University, Santa Clara, California 95053, United States Department of Chemistry and Biochemistry, Santa Clara University, Santa Clara, California 95053, United States § Division of Radiation Physics, Department of Radiation Oncology, Stanford University School of Medicine, Stanford, California 94304, United States ‡
S Supporting Information *
ABSTRACT: Cancer cells release high levels of lactate that has been correlated to increased metastasis and tumor recurrence. Single-cell measurements of lactate release can identify malignant cells and help decipher metabolic cancer pathways. We present here a novel droplet microfluidic method that allows the fast and quantitative determination of lactate release in many single cells. Using passive forces, droplets encapsulated cells are positioned in an array. The single-cell lactate release rate is determined from the increase in droplet fluorescence as the lactate is enzymatically converted to a fluorescent product. The method is used to measure the cell-to-cell variance of lactate release in K562 leukemia and U87 glioblastoma cancer cell lines and under the chemical inhibition of lactate efflux. The technique can be used in the study of cancer biology, but more broadly in cell biology, to capture the full range of stochastic variations in glycolysis activity in heterogeneous cell populations in a repeatable and high-throughput manner. requires irreversible permeabilization of cells. An optical fiber probe has been used to measure extracellular lactate;15 however, the probe needs to be carefully positioned near the plasma membrane for each cell, severely limiting the multiplexing capabilities. The measurement is also dependent on the distance between the sensor probe and cell. Another competing technology is Laconic, a genetically encoded FRET sensor capable of binding to intracellular lactate.16 The technique is powerful but remains semiquantitative and requires genetically modified cancer cell lines, making it not readily adaptable to any study or cell line. Intracellular lactate concentration is also not representative of lactate production and efflux. Droplet microfluidics,17 allowing the encapsulation of cells in nanoliter droplets surrounded by inert oil, presents an alternative to these techniques that can offer advantages in both multiplex capacity and ease of installation and implementation. Droplet microfluidics has rapidly advanced in recent years to a broad range of chemical18 and biological assays.19 This progression has been driven by the large number of independent measurements made possible by nanoliter droplets. Droplets can encapsulate cells for sequential or parallel large-scale biological assays.20−23 Droplets can be sorted and selected24 as shown in a recent study that enriched yeast cells based on metabolic production of lactate.25 The parallel analysis of droplet-encapsulated single cells is of particular interest for sensitive studies as molecules released
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actate is an organic compound and end product of glycolysis. High glucose metabolism and lactate production is one of the hallmarks of cancer, and cancer cells are programed to convert glucose to lactate, even in the presence of adequate oxygen levels, through aerobic glycolysis via a phenomenon referred to as the Warburg effect.1 The cellular release of lactate leads to an acidification of the extracellular environment creating a hostile environment for other cells.2 Furthermore, a high concentration of lactate in tumors has been shown to promote metastasis and tumor recurrence.3−6 Recent studies have revealed an ever complex role of lactate in cancer as lactate can be shuttled between cancer cells in different oxygen environments7 and acts as a signaling molecule for angiogenesis.8,9 The measurement of metabolites at the level of single cells allows the observation of cell heterogeneity and is advantageous over bulk measurements in deciphering the role and modulation of lactate release in cancer cells. We present here a novel droplet microfluidic method that allows the fast and quantitative determination of lactate release in many single cells and use this technique to measure the distribution of lactate release in cancer cells. Due to its importance in cell biology and disease pathology, many different lactate assays have been developed. Techniques that measure bulk lactate concentration utilize diverse readouts that include fluorescence, absorbance, and electrochemical signals.10−13 A few technologies have been developed that allow the measurement of lactate at the level of single cells. An integrated microfluidic platform utilizing microelectrodes was developed to measure the lactate release of heart cells.14 The general use of this device is limited to certain applications as it © XXXX American Chemical Society
Received: December 10, 2015 Accepted: February 7, 2016
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DOI: 10.1021/acs.analchem.5b04681 Anal. Chem. XXXX, XXX, XXX−XXX
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Measurements. Droplets formed from a flow focuser29 were flowed into a 3 mm wide channel with a height of 50 μm containing an array of circular anchors with a diameter of 150 μm and a depth of 25 μm. 2% w/w of 008-fluorosurfactant (Ran Biotechnologies) in FC40 (3M) was used as the external oil phase. For this combination of channel depth, anchor depth, and fluid, droplets would remain in the anchors for external oil flows less than 100 μL/min. The array could be cleared of all droplets at higher external oil flows of about 200 μL/min. Fluid flow was controlled using computer-controlled syringe pumps (Nemesys, Cetoni). Images were taken with a 4× objective on an inverted fluorescence microscope (Olympus IX-50) equipped with shuttered LED fluorescence excitation source (Sola SE-II). Fluorescence images were obtained every minute using a filter cube with an excitation filter at 540 nm (bandpass 20 nm), a 570 nm dichroic mirror, and a 590 nm long-pass emission filter. These wavelengths overlap well with the lactate assay kit’s recommended excitation and emission wavelengths of 530 and 585 nm. The integration time for all fluorescence measurements was 280 ms. Calibration solutions of lactate were obtained by dissolving sodium L-lactate (Sigma-Aldrich) at varying concentrations in deproteinated media and mixing the resulting solution in a 1:1 ratio by volume with working reagent. Lactate concentration ranged from 0 to 400 μM. At each lactate concentration, droplets were produced and anchored into a droplet array. For cellular experiments, bright-field images were acquired before and after fluorescence experiments to determine the number of cells per droplet. Image Analysis and Quantitation. Fluorescent time sequences were analyzed in ImageJ.30 The fluorescence time series were analyzed by defining a region of interest (ROI) containing the entirety of a droplet to obtain the average droplet fluorescence as a function of time. This average droplet fluorescence is used for the calibration curves of defined lactate concentration. For the determination of cell lactate release, the average droplet fluorescence is blank subtracted from the fluorescence of a droplet containing no cells. The remaining fluorescence signal is fit to a polynomial of the general form of at2 + c. The pre-exponential (a) is then used to determine the average single-cell lactate release rate (L′) in femtomoles per minute according to the equation:
from the cells remain confined in the droplet at a high effective concentration. We use this principle here, combined with the use of a droplet array, to make quantitative measurements of lactate release on many single cells. This new approach presents a number of advantages: first, because the cells are encapsulated in a hermetic droplet, we measured not only extracellular-lactate concentration, as reported in other studies,14,15,26 but single-cell lactate release rates. This is a more relevant biological readout as it is a characteristic of the cell and is independent of the measurement technique. Second, by the positioning of droplets in a droplet array using a technique called “Rails and Anchors”,27 many single cells are measured simultaneously. Third, the technique is quantitative, allowing measurements of femtomoles of released lactate. Lastly, the technique is easy and fast to set up and conduct. It uses a commercial lactate kit and requires no genetic modification. We present the technique below and its application to the profiling of single-cell lactate release rates on cancer cell lines.
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MATERIALS AND METHODS Cells. U87 human glioblastoma cancer cells and K562 human chronic myelogenous leukemia cells were grown at 37 °C and 5% CO2 in DMEM medium supplemented with 10% and 15% fetal bovine serum, respectively, 1% penicillin− streptomycin, 1% GlutaMAX, 1% sodium pyruvate, and 1% MEM nonessential amino acids. U87 cells were trypsinized and counted before being used in microscopy or microfluidic studies. Both U87 and K562 cells were rinsed three times with 1× PBS to remove residual lactate. Prior to imaging, cells were incubated in 1× PBS for 30−60 min at room temperature. PBS was then removed by pelleting the cells. Immediately before introduction into the microfluidic device, pelleted cells were resuspended in DMEM media without fetal bovine serum (deproteinated media). To make the final cell solution, working reagent comprised of the individual reagents in the Enzyfluo Llactate Assay kit (EFFLC-100, BioAssay System) was added to the resuspended cells in a 1:1 ratio by volume. The kit’s working reagent was prepared as specified immediately prior to use and consisted of solutions containing buffer, NAD+, probe, and enzymes including lactate dehydrogenase (LDH). For inhibitor experiments, solid αCHC (α-cyano-4-hydroxycinnamic acid) dissolved in DMSO was diluted with deproteinated media to a final concentration of 3 mM. Adherent U87 cells were washed three times with 1× PBS and then exposed to 3 mM αCHC solution for 24 h at 37 °C and 5% CO2. Cells were then trypsinized and prepared for microscopy as stated above. Control U87 cells were treated identically but without the addition of αCHC. Microfluidic Device. Polydimethylsiloxane (PDMS) microfluidic chips with channel depth modulations were fabricated using the dry-film photoresist soft lithography technique described by Stephan et al.28 since the technique enabled rapid prototyping of multilevel structures. The PDMS chips were then plasma-bonded to a glass slide. To render the internal channel surface hydrophobic, Novec 1720 Electronic grade Coating (3M) was flowed into the microchannel and the chip was heated for 30 min at 150 °C. The surface treatment prevented wetting and contact of the aqueous droplets with the channel walls. During the experiments, the microfluidic chip was sealed in a plastic bag with moist towels to minimize droplet shrinking from dehydration.
L′ =
2Va nk
(1)
where V is the droplet volume, n is the number of cells in the droplet, and k is the slope of the calibration curve. The model assumes a constant release of lactate by the cells and no release from the hermetic droplet. The model and determination of droplet volume is presented in detail in the Supporting Information.
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RESULTS AND DISCUSSION Confining cells in droplets is an effective analytical tool as metabolites released from the cell remain trapped in the nanoliter droplet at a high effective concentration, allowing sensitive measurements on individual cells that are typically not accessible via bulk cellular measurements.31−33 While droplets are ideal vessels for carrying cells, techniques are needed to control the position of these nanoliter droplets for extended observation. Positioning droplets in a two-dimensional array simplifies the observation, manipulation, and analysis of many droplets. To control the position of these nanoliter droplets, a technique called “Rails and Anchors”27 is used to produce a B
DOI: 10.1021/acs.analchem.5b04681 Anal. Chem. XXXX, XXX, XXX−XXX
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Figure 1. (A) Average fluorescence change in time for droplets of varying concentrations of lactate. The initial fluorescence has been subtracted from all curves. Arbitrary units correspond to grayscale intensity of the camera. (B) The lactate calibration curve demonstrating the initial rate of fluorescence increases at varying lactate concentrations. Error bars (95% confidence interval) were obtained from the measurement of several droplets at each concentration.
droplet array. Droplets are produced with flow focusers and flow into a wide channel containing an anchor array, which consists of microfabricated circular wells at the top of the channel. The droplets are “pancake” shaped rather than spherical, squeezed between the top and bottom surfaces of the channel. Droplets expand into the anchors and are therefore fixed in place via a reduction in surface energy despite the external flow of oil. This method allows the quick and passive formation of an array of droplets. It enables the extended observation of stationary droplets containing cells for quantitative analysis. After data acquisition, high external oil flow rates are used to eject the droplets from the anchors for subsequent experiments. The determination of lactate concentration was performed using a commercial lactate kit (EnzyFluo by BioAssay Systems). The use of a commercial kit simplified sample preparation and increased reproducibility. The kit utilizes a working reagent that converts lactate to a fluorescent product through a two-step enzymatic process. Lactate dehydrogenase (LDH) catalyzes the oxidation of lactate by nicotinamide adenine dinucleotide (NAD+), which yields pyruvate and NADH. The resulting NADH then enzymatically reduces the probe to a fluorescent molecule which is utilized to quantify lactate concentration. Our usage differs from the kit’s manufacturer protocol, where the lactate concentration of a cell supernatant or cell lysate solution is determined 60 min after the complete enzymatic conversion of lactate to a fluorophore. The assay is typically read on a 96-well plate with a series of lactate calibration standards. Instead, we use the kit to measure the time-varying lactate concentration in droplets using time lapse fluorescence microscopy. To validate our procedure and obtain a calibration curve for cellular experiments, droplets of known lactate concentration were first measured in the microfluidic device. The average fluorescence intensity of single anchored droplets containing varying lactate concentration is shown as a function of time in Figure 1A. The fluorescence at the initial time was subtracted for each lactate concentration. The fluorescence intensity increases with time as the predetermined concentration of lactate confined within the droplets is converted enzymatically to a fluorescence product. The rate at which fluorescence increases over time is proportional to the lactate concentration within the droplet. Thus, when lactate concentration is fixed, the fluorescence increases linearly over time (R2 > 0.99). This linear increase indicates that within the observed time the following are negligible: leaking of reagents from the droplet, depletion of the probe or lactate, and
denaturation of the reagents and enzymes at the droplet interface. These processes would be expected to produce a deviation from linear behavior. This linear behavior was observed over time periods of 20 min or longer for low concentrations of lactate. However, at high concentrations (greater than 500 μM) and at longer time measurements (over 40 min), fluorescence was observed to reach a plateau, becoming nonlinear (data not shown). This behavior can be attributed to the depletion of the fluorescent probe, depletion of the lactate analyte, or the accumulation of the intermediates or product resulting in an increase in the rate of the reverse reactions. Short measurement times, when the initial rate of the reaction is purely dependent on lactate concentration, were chosen to avoid the aforementioned issues. The initial rate of fluorescence increase was obtained by linear regression for the first 5 min, at each lactate concentration, to produce a calibration curve (Figure 1B). Fitting longer times, such as the initial 15 or 20 min of fluorescence, led to similar results. The initial rate scales linearly with lactate concentration (R2 = 0.999) indicating that the enzyme is not saturated within this range of concentrations. Error bars were obtained from measurements of several individual droplets at each lactate concentration. The calibration curve has a y-intercept close to zero, indicating that that there is very little change in fluorescence in the absence of lactate. Using the standard deviation of the blank and of the lowest concentration measured (50 μM), the limit of detection34 was determined to be 13 μM. The slope of the calibration curve (k) is used in the model to determine the rate of single-cell release of lactate for cells encapsulated by the droplet. Calibration curves were obtained within 24 h of the cellular lactate measurements presented below and were consistently linear but had variable k-values. Prior to on-chip measurements, U87 glioblastoma cells and K562 chronic myelogenous leukemia cells were washed with PBS buffer to remove extracellular lactate, incubated for 30−60 min in PBS buffer, and centrifuged to a create a cell pellet. The cell pellet was resuspended in deproteinated media. Within 2−3 min of the addition of media and working reagent, the cell solution was introduced into the chip and cells were encapsulated into droplets. The droplets were populated with cells according to a Poisson distribution of cell occupancy,35 resulting in droplets with occupancies ranging from no to a few cells. The droplets containing cells were flowed into a wider channel and anchored in place as shown in a bright-field image (Figure 2A). In a time series of the anchored droplet (Figure C
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Figure 2. (A) Bright-field image of a droplet in a well. A single U87 human glioblastoma cancer cell is circled in red. (B) Fluorescence time series of the same droplet as shown in (A). The fluorescence is observed to steadily increase with time. (C) Bright-field image of a subsection of the droplet array. Individual U87 human glioblastoma cells are circled in red. (D) Fluorescence image of the same subsection as shown in (C) at 15 min after droplet formation and cell encapsulation. Droplets containing cells show higher fluorescence that scales with the number of cells in the droplet.
2B), a steady increase in droplet fluorescence is observed. In this series, and in all analyses below, time zero is set to the time of droplet formation. The observation of a subsection of the droplet array (Figure 2C) allows for the observation of trends based on the number of cells contained in each droplet. At the start of the fluorescence time series (2 min after droplet formation), all droplets have very similar initial fluorescence intensities. This is expected as the droplets are made near the same time resulting in droplets with almost identical initial lactate concentrations. The fluorescence of all droplets in the array increases with time (Figure 2D, Video S1). At 15 min, the droplets containing cells are brighter than the empty droplets, with the brightest droplets containing the largest number of encapsulated cells. Figure 3A shows the fluorescence of individual droplets as a function of time from 2 to 17 min after droplet formation and
droplet formation. The lactate concentration in empty droplets can also be used to estimate the bulk cellular release rate of lactate under the assumption that the washed cells contain no extracellular lactate before the addition of media. Therefore, using the initial lactate concentration at the time of droplet formation, the concentration of cells in the bulk solution (∼106 cells/mL), the volume of the cell solution (1 mL), and the time between the addition of the media and droplet encapsulation (3 min), the lactate release rate for the bulk cells is found to be 32 ± 2 fm/min per cell. This estimated value is in the range of the single-cell lactate release rates (L′) obtained below, although as an average it does not provide any information on the heterogeneity and cell-to-cell variance of the individual cells in the sample. The droplets containing cells show a larger change in fluorescence (Figure 3A). The slope of the curve scales with the number of cells per droplet and clearly deviates from linearity for droplets containing 2 or 3 cells. This larger slope in comparison to the empty droplets can be attributed to lactate released by the cell that remains trapped within the droplet. By subtracting the fluorescence intensity of empty droplets, the contribution to fluorescence attributed to the lactate released by the encapsulated cell is isolated. Using a model described in detail in the Supporting Information, the resulting fluorescence signal was fit to a second degree polynomial to obtain the cellular lactate release rate per cell in femtomoles per minute (fits are shown in Figure 3A). The model assumes a constant cellular release of lactate during the time of measurement. This assumption can be justified as the measurement is limited to an early time period after the addition of media (first 2 to 15 min). The use of early time also limits many potential complications due to degradation of enzymes or cells, acidification of the droplet, leakage of reagents from droplets, droplet dehydration, and the depletion of the fluorescent probe or lactate. The total lactate release rate, L′, for droplets containing one, two, or three cells is shown in Figure 3B. At the cell concentration used (∼1 cell/nanoliter), droplets containing many encapsulated cells (3 or more) are rare due to Poisson statistics. Each point in the figure represents an individual droplet taken from the combined data of two subsequent runs. The total lactate release rate scales with the number of encapsulated cells, as the average lactate release was determined to be 20.4 ± 3.5 fm/min (N = 30), 39.2 ± 4.2 fm/min (N =
Figure 3. (A) Fluorescence for single droplets containing zero to three U87 human glioblastoma cancer cells. (B) Lactate release rates in femtomol/min for individual droplets containing one to three cells. The average value is indicated by a red line. The standard deviation and the 95% confidence interval are indicated by a blue and red bar, respectively.
cell encapsulation. Droplets containing no cells show a linear increase in fluorescence. Using the calibration curve (Figure 1B), the slope of this curve can be used to determine the lactate concentration of these droplets. Through the analysis of several empty droplets, the lactate concentration was found to be 97.2 ± 5.0 μM (N = 20) (average ± error of mean). This value defines the initial lactate concentration at the time of droplet formation. Upon resuspension of the cell pellet in deproteinated media, the washed cells will start producing lactate. For droplets without cells, the lactate concentration is fixed upon D
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variation values indicate that there is considerable cell-to-cell variability in lactate release rate within each cell type. This is consistent with variations of extracellular lactate concentration measured for other cancer cell lines.15 The variability of lactate release is a parameter not accessible by bulk cellular measurements. The measurement of single-cells lactate release may allow the identification of more malignant cells within a cell population.40 Lactate release rates were also obtained for cells exposed to αCHC, an inhibitor of MCT (Figure 4B).7,41 αCHC is known to severely affect viability of U87 with a LD30 value of 10 mM.42 As such, a treatment concentration below this value, but at a high enough concentration to inhibit lactate release, was chosen, 3 mM. This concentration of αCHC did not adversely affect cell viability as determined by a WST assay and the use of CellTracker probe retained only in live cells. Adhered U87 glioblastoma cells were exposed for 24 h to αCHC diluted in deproteinated media, rinsed, and trypsinized for microscopy. An average L′ value of 9.4 ± 1.2 fm/min (N = 50) was found for the αCHC treated cells, compared to an average L′ value of 19.3 ± 4.8 fm/min (N = 26) for untreated U87 cells, a difference which was found to be significant (P < 0.001). αCHC inhibits lactate efflux by competitive inhibition of the MCT protein and has differing affinities for various isotypes of MCT, with a Ki value that is 5 times higher (50−100 mM)39 for MCT4 than for MCT1. Therefore, at the concentration used, αCHC will primarily influence the efflux of lactate of MCT1. Figure 4B shows an average of 52% inhibition in lactate release rate between αCHC treated U87 cells and untreated cell populations. This value is consistent with our bulk cell measurements that showed a 30−50% inhibition (data not shown). The coefficient of variances for the two cell populations are 64% and 47% for untreated and αCHC treated cells, respectively. Although the inhibitor influences the average L′ values, individual cells in the inhibited population show L′ values that are comparable to untreated cells.
11), and 72.7 fm/min (N = 1) for droplets containing one, two, and three cells, respectively. This data suggests that multiple cells in a droplet lead to a simple scaling of the lactate release rate of the individual encapsulated cells. Using the same procedure, L′ values of two cancer lines, U87 glioblastoma and K562 leukemia cells, were compared (Figure 4A). In droplets with multiple cells, L′ values were obtained by
Figure 4. (A) Lactate release rates in femtomol/min for single cells in droplets of K562 human chronic myelogenous leukemia cells and U87 human glioblastoma cancer cells. (B) Lactate release rates in femtomol/min for single U87 cells treated with 3 mM αCHC and control cells (P < 0.001). For both plots, the average value is indicated by a red line. The standard deviation and the 95% confidence interval are indicated by a blue and red bar, respectively.
normalizing the number of cells; however, exclusion of droplets containing multiple cells yields very similar results. The average L′ for U87 glioblastoma cells was found to be 20.3 ± 2.6 fm/ min (N = 42) while the average L′ for K562 leukemia cells was found to be 8.9 ± 1.3 fm/min (N = 38). These L′ determinations were found to be consistent with multiple experiments performed on different days. Due to the Warburg effect, cancer cells exhibit increased glycolysis1 resulting in higher lactate production and release. Therefore, we expect these L′ values to be higher than measurements on normal cells.3,36 The higher L′ for U87 compared to K562 cells could possibly be attributed to fundamental differences in cell type, as U87 glioblastoma cells are known for their high rates of glycolytic activity,35 and subsequent increase in lactate production. The difference in L′ between U87 and K562 cells can also depend on the number and isoform type of each cell line’s monocarboxylate transporters (MCT), plasma membrane proteins that are responsible for lactate efflux from the cell.37,38 There are four main isoforms (MCT1−MCT4) of MCT proteins associated with lactate efflux, with the number and expression of each isoform being influenced by the cell type. U87 glioblastoma cells express both MCT1 and MCT4 isoforms, while K562 leukemia cells express only MCT1.39 MCT4 is predominantly expressed in cancer cells that are highly glycolytic preventing cell acidification by lactate accumulation, and both MCT1 and MCT4 are upregulated in highly glycolytic cancer cell lines, such as U87.36 As such, cancer cells, such as U87s, expressing both MCT1 and MCT4 isoforms are likely to produce higher rates of lactate efflux than cancer cells expressing only the MCT1 isoform. Even within the same cell population, there is substantial cellto-cell variability in the lactate release rate, for example, spanning 8.3 to 42.3 fm/min for U87 cells. We measure a spread in single-cell release values, which is reported here by the coefficient of variation (standard deviation divided by the mean lactate release rate, L′) of 42% for U87 glioblastoma cells and 46% for K562 leukemia cells. These large coefficients of
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CONCLUSIONS In summary, we have presented here a method to determine the lactate release in single cells, an important parameter in cancer cell biology. We have used the technique to measure the cell to cell variance in two cancer cell lines and under chemical inhibition of lactate efflux. The method is facile to set up and implement and provides a measurement in a few minutes. It uses a commercial lactate kit and would be adaptable to other lactate kits. The immobilization of droplets in an array enables the collection of a fluorescence time series, rather than a single time-point measurement, leading to a more robust determination. Unlike other single-cell lactate measurements, it determines a cellular characteristic, the cellular lactate release rate, rather than the extracellular lactate concentration. The model utilized here assumed a constant rate of lactate release; however, it could be modified to account for variable lactate rates for longer studies or droplet cell culture. A major benefit of the technique is that it allows the multiplex determination of cells. Our platform allowed the simultaneous analysis of over 50 droplets or about 20 single cells per run at optimal cell density. Droplets are expelled from the anchors at higher external oil flows allowing the results from multiple runs to be aggregated. The per run throughput can be easily improved by using denser droplets arrays or by incorporating microfluidic techniques that ensure single-cell occupancy in droplets.43,44 The throughput could be increased E
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National Institutes of Health under Grants 1R21CA193001 and 5R01CA186275.
by using an automated microscope stage and imaging multiple viewing fields containing arrayed droplets. This option is attractive as the droplets are only imaged once a minute. The droplets used in this analysis ranged from 0.5 to 1.2 nL. Smaller droplets and anchors would allow the analysis of droplet arrays containing hundreds or even thousands of droplets; however, reagent concentrations or measurement intervals may need to be adjusted to remain in the linear range of the calibration curve. Although the focus of this study was on cancer cell lines, glycolysis and lactate release is of general interest in many fields of cell biology. The most performant multicell device for this measurement is likely the XF24 Extracellular Flux Analyzer electrode system45 created by Seahorse Bioscience, capable of measuring oxygen consumption and glycolysis generated by bulk adherent cell populations. Though the analyzer electrode system is highly automated, it can only provide bulk and not single-cell measurements. Furthermore, the system does not directly measure lactate production and release, but makes the indirect determination via the acidification of the surrounding environment. Our microfluidic device thus presents an alternative for the direct measurement of lactate on single cells. The lactate determination is quick and uses a single fluorescent channel; therefore, the technique is amenable to correlations of lactate with standard measurements of cellular states (e.g., cell cycle, redox status, proliferation, ROS production, etc.) obtained using the other fluorescence channels. This technique can also be used as a viability assay in toxicity and drug studies. In the future, droplets can also be recovered off-chip and coupled to techniques that have been developed for droplet sorting and selection.24,25 Furthermore, with the addition of a destabilizing surfactant,21 droplets can be broken to recover cells which can then be further analyzed (genomics, proteomics, metabolomics, etc.). This general technique provides a robust method to quantify the rate of lactate release at the level of single cells, providing a novel tool for the study of highly heterogeneous cell populations.
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ASSOCIATED CONTENT
S Supporting Information *
The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acs.analchem.5b04681. Single-cell lactate production model and volume of anchored droplet (PDF) Bright-field image followed by a fluorescence video of a subsection of the droplet array with single U87 human glioblastoma cells (AVI)
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REFERENCES
(1) Warburg, O. Science 1956, 123, 309−314. (2) Wike-Hooley, J. L.; Haveman, J.; Reinhold, H. S. Radiother. Oncol. 1984, 2, 343−366. (3) Walenta, S.; Mueller-Klieser, W. F. Semin. Radiat. Oncol. 2004, 14, 267−274. (4) Doherty, J.; Cleveland, J. J. Clin. Invest. 2013, 123, 3685−3692. (5) Martinez-Outschoorn, U. E.; Prisco, M.; Ertel, A.; Tsirigos, A.; Lin, Z.; Pavlides, S.; Wang, C.; Flomenberg, N.; Knudsen, E. S.; Howell, A.; Pestell, R. G.; Sotgia, F.; Lisanti, M. P. Cell Cycle 2011, 10, 1271−1286. (6) Cairns, R. A.; Harris, I. S.; Mak, T. W. Nat. Rev. Cancer 2011, 11, 85−95. (7) Sonveaux, P.; Végran, F.; Schroeder, T.; Wergin, M. C.; Verrax, J.; Rabbani, Z. N.; De Saedeleer, C. J.; Kennedy, K. M.; Diepart, C.; Jordan, B. F.; Kelley, M. J.; Gallez, B.; Wahl, M. L.; Feron, O.; Dewhirst, M. W. J. Clin. Invest. 2008, 118, 3930−3942. (8) Végran, F.; Boidot, R.; Michiels, C.; Sonveaux, P.; Feron, O. Cancer Res. 2011, 71, 2550−2560. (9) Sonveaux, P.; Copetti, T.; De Saedeleer, C. J.; Végran, F.; Verrax, J.; Kennedy, K. M.; Moon, E. J.; Dhup, S.; Danhier, P.; Frérart, F.; Gallez, B.; Ribeiro, A.; Michiels, C.; Dewhirst, M. W.; Feron, O. PLoS One 2012, 7, e33418. (10) Rassaei, L.; Olthuis, W.; Tsujimura, S.; Sudhölter, E. J. R.; Van Den Berg, A. Anal. Bioanal. Chem. 2014, 406, 123−137. (11) Wangsa, J.; Arnold, M. A. Anal. Chem. 1988, 60, 1080−1082. (12) Ignatov, S. G.; Ferguson, J. A.; Walt, D. R. Biosens. Bioelectron. 2001, 16, 109−113. (13) Jena, B. K.; Raj, C. R. Anal. Chem. 2006, 78, 6332−6339. (14) Cheng, W.; Klauke, N.; Sedgwick, H.; Smith, G. L.; Cooper, J. M. Lab Chip 2006, 6, 1424. (15) Zheng, X. T.; Yang, H. B.; Li, C. M. Anal. Chem. 2010, 82, 5082−5087. (16) San Martín, A.; Ceballo, S.; Ruminot, I.; Lerchundi, R.; Frommer, W. B.; Barros, L. F. PLoS One 2013, 8, No. e57712. (17) Thorsen, T.; Roberts, R. W.; Arnold, F. H.; Quake, S. R. Phys. Rev. Lett. 2001, 86, 4163−4166. (18) Song, H.; Chen, D. L.; Ismagilov, R. F. Angew. Chem., Int. Ed. 2006, 45, 7336−7356. (19) Guo, M. T.; Rotem, A.; Heyman, J. A.; Weitz, D. A. Lab Chip 2012, 12, 2146−2155. (20) Brouzes, E.; Medkova, M.; Savenelli, N.; Marran, D.; Twardowski, M.; Hutchison, J. B.; Rothberg, J. M.; Link, D. R.; Perrimon, N.; Samuels, M. L. Proc. Natl. Acad. Sci. U. S. A. 2009, 106, 14195. (21) Debs, B. El; Utharala, R.; Balyasnikova, I. V.; Griffiths, A. D.; Merten, C. A. Proc. Natl. Acad. Sci. U. S. A. 2012, 109, 11570−11575. (22) Agresti, J. J.; Antipov, E.; Abate, A. R.; Ahn, K.; Rowat, A. C.; Baret, J.-C.; Marquez, M.; Klibanov, A. M.; Griffiths, A. D.; Weitz, D. A. Proc. Natl. Acad. Sci. U. S. A. 2010, 107, 4004−4009. (23) Huebner, A.; Bratton, D.; Whyte, G.; Yang, M.; Demello, A. J.; Abell, C.; Hollfelder, F. Lab Chip 2009, 9, 692. (24) Baret, J.-C.; Miller, O. J.; Taly, V.; Ryckelynck, M.; El-Harrak, A.; Frenz, L.; Rick, C.; Samuels, M. L.; Hutchison, J. B.; Agresti, J. J.; Link, D. R.; Weitz, D. A.; Griffiths, A. D. Lab Chip 2009, 9, 1850− 1858. (25) Wang, B. L.; Ghaderi, A.; Zhou, H.; Agresti, J.; Weitz, D. a; Fink, G. R.; Stephanopoulos, G. Nat. Biotechnol. 2014, 32, 473−478. (26) Ciobanu, M.; Taylor, D. E.; Wilburn, J. P.; Cliffel, D. E. Anal. Chem. 2008, 80, 2717−2727. (27) Abbyad, P.; Dangla, R.; Alexandrou, A.; Baroud, C. N. Lab Chip 2011, 11, 813−821. (28) Stephan, K.; Pittet, P.; Renaud, L.; Kleimann, P.; Morin, P.; Ouaini, N.; Ferrigno, R. J. Micromech. Microeng. 2007, 17, N69. (29) Anna, S. L.; Bontoux, N.; Stone, H. A. Appl. Phys. Lett. 2003, 82, 364−366.
AUTHOR INFORMATION
Corresponding Author
*E-mail:
[email protected]. Notes
The authors declare no competing financial interest.
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ACKNOWLEDGMENTS The authors gratefully acknowledge Soojung Claire Hur for providing the K562 leukemia cells. We would also like to thank International Electronic Components Inc. for their generous donation of dry photoresist films and Rob Campell for the notBoxPlot matlab function. G.P. receives support from the F
DOI: 10.1021/acs.analchem.5b04681 Anal. Chem. XXXX, XXX, XXX−XXX
Article
Analytical Chemistry (30) Abramoff, M. D.; Magalhaes, P. J.; Ram, S. J. Biophotonics Int. 2004, 11, 36−43. (31) Pekin, D.; Skhiri, Y.; Baret, J.-C.; Le Corre, D.; Mazutis, L.; Salem, C. B.; Millot, F.; El Harrak, A.; Hutchison, J. B.; Larson, J. W.; Link, D. R.; Laurent-Puig, P.; Griffiths, A. D.; Taly, V. Lab Chip 2011, 11, 2156−2166. (32) Rane, T. D.; Zec, H. C.; Puleo, C.; Lee, A. P.; Wang, T.-H. Lab Chip 2012, 12, 3341−3347. (33) Huebner, A.; Srisa-Art, M.; Holt, D.; Abell, C.; Hollfelder, F.; deMello, A. J.; Edel, J. B. Chem. Commun. 2007, 2007, 1218−1220. (34) Armbruster, D. A.; Pry, T. Clin. Biochem. Rev. 2008, 29 (Suppl1), S49−S52. (35) Clausell-Tormos, J.; Lieber, D.; Baret, J. C.; El-Harrak, A.; Miller, O. J.; Frenz, L.; Blouwolff, J.; Humphry, K. J.; Köster, S.; Duan, H.; Holtze, C.; Weitz, D. A.; Griffiths, A. D.; Merten, C. A. Chem. Biol. 2008, 15, 427−437. (36) Ganapathy, V.; Thangaraju, M.; Prasad, P. D. Pharmacol. Ther. 2009, 121, 29−40. (37) Enerson, B. E.; Drewes, L. R. J. Pharm. Sci. 2003, 92, 1531− 1544. (38) Pinheiro, C.; Longatto-Filho, A.; Azevedo-Silva, J.; Casal, M.; Schmitt, F. C.; Baltazar, F. J. Bioenerg. Biomembr. 2012, 44, 127−139. (39) Miranda-Gonçalves, V.; Honavar, M.; Pinheiro, C.; Martinho, O.; Pires, M. M.; Pinheiro, C.; Cordeiro, M.; Bebiano, G.; Costa, P.; Palmeirim, I.; Reis, R. M.; Baltazar, F. Neuro. Oncol. 2013, 15, 172− 188. (40) Hirschhaeuser, F.; Sattler, U. G. a.; Mueller-Klieser, W. Cancer Res. 2011, 71, 6921−6925. (41) Kennedy, K. M.; Dewhirst, M. W. Future Oncol. 2010, 6, 127− 148. (42) Colen, C. B.; Seraji-Bozorgzad, N.; Marples, B.; Galloway, M. P.; Sloan, A. E.; Mathupala, S. P. Neurosurgery 2006, 59, 1313−1324. (43) Chabert, M.; Viovy, J.-L. L. Proc. Natl. Acad. Sci. U. S. A. 2008, 105, 3191. (44) Edd, J. F.; Di Carlo, D.; Humphry, K. J.; Köster, S.; Irimia, D.; Weitz, D. A.; Toner, M. Lab Chip 2008, 8, 1262−1264. (45) Wu, M.; Neilson, A.; Swift, A. L.; Moran, R.; Tamagnine, J.; Parslow, D.; Armistead, S.; Lemire, K.; Orrell, J.; Teich, J.; Chomicz, S.; Ferrick, D. A. Am. J. Physiol. Cell Physiol. 2007, 292, C125−C136.
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DOI: 10.1021/acs.analchem.5b04681 Anal. Chem. XXXX, XXX, XXX−XXX
