We demonstrate the use of an evaporating, sessile droplet on a nonwetting substrate as a miniature micromixing device to conduct sample-dye reactions for absorbance-based colorimetry. The nonwetting substrate supports buoyancy-induced mixing inside the droplet for rapid completion of the measurement. The Bradford assay is used as a proof of concept, where a protein-containing sample is reacted with a reagent dye to measure the protein concentration. Viability of absorbance measurement through the droplet is first established using droplets in which the reactants are mixed prior to their deposition onto the substrate. In a second set of experiments involving in situ mixing, the reagent is directly added to a sessile droplet of the protein-containing sample, allowing the reactants to mix while the absorbance is being measured. Interplay between buoyancy-induced mixing, protein-reagent reaction, and protein adsorption onto the substrate leads to a complex temporal absorbance measurement signal. Videos corresponding to the signal data show that each of these mechanisms dominates during different phases of droplet evolution, causing a signal pattern containing peaks and valleys having a strong monotonic trend with the protein concentration. Overall, the second absorbance peak at which the reaction nears completion is the most sensitive to sample concentration. Heating of the substrate is demonstrated to dramatically speed up the mixing process. These protein concentration measurements, obtained with a simpler system and low reactant volumes, demonstrate that this droplet micromixing concept is a viable alternative to microtiter plates for colorimetric applications.
We demonstrate the use of an evaporating, sessile droplet on a nonwetting substrate as a miniature micromixing device to conduct sample-dye reactions for absorbance-based colorimetry. The nonwetting substrate supports buoyancy-induced mixing inside the droplet for rapid completion of the measurement. The Bradford assay is used as a proof of concept, where a protein-containing sample is reacted with a reagent dye to measure the protein concentration. Viability of absorbance measurement through the droplet is first established using droplets in which the reactants are mixed prior to their deposition onto the substrate. In a second set of experiments involving in situ mixing, the reagent is directly added to a sessile droplet of the protein-containing sample, allowing the reactants to mix while the absorbance is being measured. Interplay between buoyancy-induced mixing, protein-reagent reaction, and protein adsorption onto the substrate leads to a complex temporal absorbance measurement signal. Videos corresponding to the signal data show that each of these mechanisms dominates during different phases of droplet evolution, causing a signal pattern containing peaks and valleys having a strong monotonic trend with the protein concentration. Overall, the second absorbance peak at which the reaction nears completion is the most sensitive to sample concentration. Heating of the substrate is demonstrated to dramatically speed up the mixing process. These protein concentration measurements, obtained with a simpler system and low reactant volumes, demonstrate that this droplet micromixing concept is a viable alternative to microtiter plates for colorimetric applications.
Colorimetry is a widely
used approach for measurement of the concentration
of biological samples in a liquid. Colorimetry techniques have been
developed to detect concentrations of glucose,[1] protein,[2−4] fatty acids,[5] nucleic
acids,[6] and so forth. In colorimetry, the
sample is mixed with a reagent that causes a color change in the sample–reagent
mixture that is a function of the concentration of the sample. Conventional
colorimetric analysis involves measuring the mixture absorbance at
a specific wavelength using either a colorimeter, spectrophotometer,
or microtiter plate reader.[7] Miniaturization
of this process has the benefits of reducing the quantity of the reagent
and the sample needed, thus allowing for less invasive testing in
clinical applications. The measurement time can also be significantly
reduced because of the faster mixing process in miniaturized systems.The Bradford assay is one of the most commonly used protein quantitation
techniques. The technique involves mixing a protein-containing sample
with the reagent dye Coomassie Brilliant Blue G-250. This reagent
dye is known to exist in three ionic states: anionic, cationic, and
neutral.[8] The neutral and anionic states
both react to the amino acids in the protein, the former by hydrophobic
and electrostatic interactions and the latter by electrostatic interactions.[9] These reactions form protein–dye complexes
that shift the absorbance spectrum of the mixture. The measured absorbance
change is correlated with a set of standard concentrations to determine
the protein concentration in the sample.[2] The noninstantaneous nature of this protein–dye reaction
means that there is likely a combined effect of the reaction and the
mixing on the signal during the measurement timescale. In conventional
Bradford assays that are conducted in macroscale cuvettes, the measurement
requires on the order of 5 min for the reaction to be completed[7] because of the longer time for mixing in macroscale
devices. Macroscale mixing can also lead to protein denaturation and
foaming with excessive vortexing.[10] A quicker
method of mixing that avoids denaturation, as is possible at the smaller
length scales of micromixing techniques, can allow the reaction to
be completed more rapidly.Several techniques for miniaturized
colorimetry have been presented
in the literature, with microfluidic electrowetting-on-dielectric
(EWOD) devices[11] and paper-based devices[12] representing a majority of the efforts. Some
devices rely on EWOD as an actuation method for transporting droplets
to a sensor.[11,13] This approach typically involves
use of a hydrophobic substrate to ease droplet transport. A process
of shuttling the droplet is utilized to ensure mixing of the sample
and reagent. A significant challenge from the use of hydrophobic substrates
is the irreversible adsorption of hydrophobic proteins onto the substrate,
causing contamination of the sample and device.[14] This is often mitigated by using oil as a separation layer.[15] Paper-based microfluidic devices rely on capillary
action to drive the fluids.[12] This approach
provides the benefit of low-cost, passively-driven flow. Some of the
limitations of using this approach for colorimetry include low sample
flow efficiency, potential for leakage, and inability to measure extremely
low concentrations.[16] An alternative, sessile
droplet-based technique was recently demonstrated for a hue-based
colorimetry system that relies on measuring the color of the sample
using an imaging system.[17] Absorbance-based
colorimetry, which is required for many commonly used techniques like
the Bradford and Lowry assays, has not been previously explored using
sessile droplets.Recent efforts have attempted high-throughput
screening of sample
concentration using absorbance-based colorimetry by fabricating miniaturized
wells with higher density of wells per unit area than previously achieved;[18] however, these techniques require complex machining
to create precise wells at such high density. Furthermore, a key issue
that must be addressed in these low-volume microwells is the thorough
mixing of the samples.[19] Several active
micromixing approaches have been proposed in the literature, including
ultrasonication,[20] external vibration of
T-junction microchannels,[21] magnetohydrodynamic
stirrers,[22] and electro-osmotic flow in
microchannels.[23] Most of these approaches
demand complex control schemes and additional manufacturing requirements.
Multilaminar mixing is another approach that uses intricate patterns
of channels to induce chaotic flows.[24] This
technique often requires longer flow lengths[21] and still requires complex fabrication to create the complex flow
patterns necessary for mixing. A simpler micromixing system could
thus benefit high-throughput microplate-based colorimetric analysis.Several characteristics of droplets placed on nonwetting surfaces
make such surfaces an attractive platform for miniaturized colorimetry.
Droplets on nonwetting surfaces demonstrate significantly lower evaporation
rates than droplets on wetting substrates[25] because of the suppression of evaporation at the contact line of
the droplet due to vapor confinement[25] combined
with evaporative cooling.[26,27] This suppression is
an important feature for colorimetric applications, where the reaction
needs to be completed and the absorbance measurement taken before
too much evaporation has occurred. Furthermore, aqueous droplets demonstrate
buoyancy-driven convection on nonwetting substrates,[28] which offers an order of magnitude higher internal flow
velocities[28] compared to wetting surfaces.[29] This leads to buoyancy-induced mixing rates
that are two orders of magnitude higher than simple diffusion-based
mixing,[28] without requiring long flow lengths
as in other passive micromixers. This aspect of the droplet-based
system reduces the time to complete the reaction between the dye and
the reagent. Finally, sessile droplets of known volumes and contact
angles can be simply placed on a hydrophobic substrate with a small
footprint, without the need for complex fabrication of microplates.
Materials and Methods
Figure shows a
schematic diagram of the experimental setup used for the absorbance
measurements. The setup detects the light transmitted through a sessile
droplet placed on a transparent, nonwetting substrate. An InGaAlP
light-emitting diode (LED) with a peak wavelength of 590 ± 10
nm (LED591E, Thorlabs) is aligned with a silicon photodiode (FD11A,
Thorlabs) through a 0.84 mm-diameter aperture that confines the area
of illumination to within the radius of the droplet base footprint.
The photodiode, which has a wavelength range of 320–1100 nm,
is connected to a digital multimeter (34410A, Keysight) that records
the signal at 10 Hz using a LabVIEW interface. The nonwetting substrate
is fabricated using a glass slide of 1 mm thickness (3057, Gold Seal).
The slide is cut into a 25 mm × 25 mm square substrate and cleaned
in succession with acetone, methanol, and deionized (DI) water. Teflon
granules (Teflon AF2400, Dupont) are dissolved in a solvent (Fluorinert
Electronic Liquid FC-72, 3M) to create a 1% weight/volume solution.
This solution is then spin-coated onto clean glass at 1500 rpm. The
coated slides are then baked on a hot plate at 150 °C for 2 h.
The resulting low-surface-energy surface exhibits a contact angle
of 125° for the sample–reagent mixture used in the experiments.
It should be noted that protein irreversibly adsorbs onto hydrophobic
surfaces, making these surfaces single-use at a specific location.
Figure 1
Schematic
diagram of the sessile-droplet-based absorbance measurement.
Schematic
diagram of the sessile-droplet-based absorbance measurement.Experiments are conducted in
two different configurations: (1)
a premixed case to confirm that the absorbance signals measured through
the droplet medium have a detectable change over the target range
of sample concentrations and (2) an in situ mixing case to demonstrate
the proposed concept of using the droplet as a self-contained passive
mixing apparatus to make colorimetric measurements. All of the aforementioned
experiments are performed at room temperature (21.5 °C) and both
the sample and reagent are filtered before the experiments. For the
premixed case, the sample and reagent are thoroughly mixed in a sample
to reagent ratio of 1:5 in a test tube. After the sample is thoroughly
mixed and the reaction is complete, a 10 μL droplet of this
mixture is deposited on the substrate, quickly aligned between the
LED and photodiode, and the signal recorded in volts. This approach
effectively measures the signal of the completely reacted mixture,
without introducing the complexities of real-time mixing and any reactions
within the droplet. For the in situ mixing case, a 1.7 μL droplet
of the sample is first placed on the nonwetting substrate. The reagent
in the amount of 8.3 μL is then added to the sample droplet,
thereby creating an approximately 1:5 sample to reagent ratio. The
droplet is then aligned with the photodiode and the signal measured
in real time for 1000 s. The experiments for both configurations are
conducted at three sample concentrations: 0.1 mg/mL (1.51 μM),
0.15 mg/mL (2.26 μM), and 0.3 mg/mL (4.51 μM). These were
selected to avoid the saturation effects that are present in the Bradford
assay at higher concentrations and limit protein aggregation. Three
trials are conducted at each sample concentration to ensure repeatability.
Three additional trials are performed at a concentration of 0.15 mg/mL
(2.26 μM) with the substrate heated to 40 °C to demonstrate
acceleration of the mixing process at elevated temperatures.In order to calculate an absorbance metric from the raw signal,
a “blank” sample is used for reference, as is the case
in conventional colorimetry. A droplet of a sample without protein (0 mg/mL concentration) is used
as the blank, which allows a reference signal to be measured that
takes into account the curvature of the droplet and the resulting
lensing effects. Use of a blank sample for reference in this manner
is possible because the pinned evaporation characteristics of the
blank sample droplets are nearly identical to those of droplets with
protein samples, as confirmed by the goniometric measurements shown
in Figure S1 of the Supporting Information; the volume and height evolution of the droplets with and without
protein in the sample during evaporation are identical. A key assumption
in the absorbance metric is that the intensity of light incident on
the photodiode is linearly proportional to the voltage signal output
read by the multimeter. Based on this assumption, a formulation analogous
to Beer’s law is used to calculate the absorbance metricwhere A is the absorbance
metric, Vo is the voltage reading from
the blank sample, and V is the voltage reading from
the sample that is being measured. The signal measured from the blank
sample is relatively constant throughout evaporation at a mean value
of 0.1303 V. The overall lack of change in the signal with evaporation
indicates that any changes in lensing with changes in droplet volume
are negligible with respect to the measured absorbance signal. As
the sample concentration increases, it is expected that the absorbance
signal at the LED will increase (i.e., the raw voltage signal will
decrease) because of the liquid color change.
Results and Discussion
Figure shows the
absorbance metric measurements for premixed sample concentrations
of 0.1 mg/mL (1.51 μM), 0.15 mg/mL (2.26 μM), and 0.3
mg/mL (4.51 μM). The raw voltage measurements that were used
to calculate these values are provided for reference in Figure S2
of the Supporting Information. As can be
clearly seen in Figure , the absorbance generally increases with concentration. There is
an initial valley in the absorbance signal that becomes more pronounced
at higher concentrations. This valley is likely due to buoyant convection
in the droplet initially mixing the components and temporarily diluting
the protein faster than it can react. There is also a gradual monotonic
decrease in the absorbance with time toward the end of the measurement
period as the protein absorbs onto the Teflon-coated substrate, reducing
the droplet concentration. This trend is more apparent with increasing
concentration because of the higher contrast in the signal between
the blank and the test samples. Figure shows the absorbance metric value at 400 s as a function
of the sample concentration, with a linear fit and an 80% prediction
interval. A strong monotonic increase in absorbance is observed with
increasing concentration. With this experimental confirmation of a
measurable trend in the absorbance for a sessile droplet configuration,
the proposed method of mixing in situ without resorting to an external
mixing apparatus is explored next.
Figure 2
Time-resolved absorbance measurements
for premixed sample droplets
at concentrations of (a) 1.51, (b) 2.26, and (c) 4.51 μM.
Figure 3
Absorbance metric values for the sample at 400 s (extracted
from Figure ) plotted
as a function
of concentration, along with a linear fit (dashed line) and an 80%
prediction interval (dash-dotted line).
Time-resolved absorbance measurements
for premixed sample droplets
at concentrations of (a) 1.51, (b) 2.26, and (c) 4.51 μM.Absorbance metric values for the sample at 400 s (extracted
from Figure ) plotted
as a function
of concentration, along with a linear fit (dashed line) and an 80%
prediction interval (dash-dotted line).The in situ mixing absorbance measurements, at
sample concentrations
of 0.1 mg/mL (1.51 μM), 0.15 mg/mL (2.26 μM), and 0.3
mg/mL (4.51 μM), are shown in Figure a–c, respectively. Raw signal measurements
for these test cases are included in Figure S3 of the Supporting Information. A complex temporal absorbance
signal is recorded for all samples, consistently featuring a slight
increase followed by a slight decrease and then a large increase (approximately
within the first ∼400 s). Lastly, there is a gradual monotonic
decrease in the absorbance metric that continues to the end of the
experiment. This signal evolution results in two initial absorbance
metric peaks (local maxima) with a valley (local minimum) in between.
Overall, the absorbance increases with increasing protein concentration,
as was observed in the premixed cases; this concentration dependence
is especially prominent for the peak and valley values.
Figure 4
Time-resolved
absorbance measurements for in situ mixed droplets
at sample concentrations of (a) 1.51, (b) 2.26, and (c) 4.51 μM.
Time-resolved
absorbance measurements for in situ mixed droplets
at sample concentrations of (a) 1.51, (b) 2.26, and (c) 4.51 μM.To understand the complexities of this evolution,
videos were collected
during the mixing and reaction process for the sample droplet of concentration
0.3 mg/mL (4.51 μM). At this concentration, color changes due
to the reaction are clearly observable in the visible spectrum. A
camera is placed horizontally facing the droplet to obtain a simultaneous
record through the time period of the absorbance measurement. Images
extracted from this video at 100 s increments are shown in Figure . The images illustrate
the interplay of buoyancy-induced mixing, chemical reaction, and protein
adsorption, which play a significant role in determining the signal
measured through the droplet as it progresses through multiple color
levels of darker blue (higher absorbance at the 590 nm wavelength)
and lighter blue or brown (lower absorbance at the 590 nm wavelength).
Alongside the discussion to follow, the reader is encouraged to view
the videos included as the Supporting Information, which best illustrate this progression.
Figure 5
Image frames, captured
at 100 s increments from the droplet video
(available in the Supporting Information) for the in situ mixing case at a concentration of 0.3 mg/mL (4.51
μM). The image background outside the droplet profile is cropped
for clarity.
Image frames, captured
at 100 s increments from the droplet video
(available in the Supporting Information) for the in situ mixing case at a concentration of 0.3 mg/mL (4.51
μM). The image background outside the droplet profile is cropped
for clarity.The color distribution observed in the video is
analyzed to determine
the dominant mechanisms that lead to the different phases of the droplet
temporal absorbance signal. These phases are determined by observing
the peaks and valleys, and the trends in-between, in the absorbance
metric plot shown in Figure c. The phases and associated mechanisms are illustrated in
the representative inset diagrams of Figure : (1) Initially, the protein sample amasses
at the top of the droplet and the initial reaction creates a dark
blue region directly in the path between the light source and the
photodiode. Buoyant convection then distributes this mass through
the droplet in the subsequent (2) mixing phase, causing more of the
protein to react and resulting in the absorbance increasing slightly
during this phase. However, the mixing eventually dilutes the color
faster than the reaction occurs in the (3) dilution phase, resulting
in the droplet absorbance decreasing slightly. Once the sample is
thoroughly mixed, the droplet enters a (4) reaction phase where the
reaction dominates dilution, thus darkening the droplet and increasing
the absorbance dramatically. Once most of the protein has reacted
into protein–dye complexes, the droplet enters the (5) adsorption
phase, where the protein adsorbs onto the Teflon-coated substrate
faster than any continuing reaction. This causes the droplet to revert
to the native reddish-brown color of the reagent, and the absorbance
metric drops monotonically till the end of the experiment. The time
difference between the two peaks in the absorbance signal was analyzed
and found to be virtually identical across all concentrations (293.3
± 12.9 s), indicating that the mixing and reaction time scales
do not change discernibly with concentration. This is expected as
the substrate temperature is held constant in all the trials, resulting
in the same extent of buoyancy-induced convection.
Figure 6
Plot of the temporal
absorbance metric for a selected trial at
a sample concentration of 0.3 mg/mL (4.51 μM) with inset schematic
drawings showing the various phases of in situ mixing of the reactant
and sample, including: (1) the initial droplet, (2) the mixing phase,
(3) the dilution phase, (4) the reaction phase, and (5) the adsorption
phase.
Plot of the temporal
absorbance metric for a selected trial at
a sample concentration of 0.3 mg/mL (4.51 μM) with inset schematic
drawings showing the various phases of in situ mixing of the reactant
and sample, including: (1) the initial droplet, (2) the mixing phase,
(3) the dilution phase, (4) the reaction phase, and (5) the adsorption
phase.Figure shows an
analysis of the measured absorbance metric at the peaks and valley.
The values for the first peak, the valley, and the second peak are
plotted as a function of concentration in Figure a–c along with a linear fit and an
80% prediction interval to determine whether these values may be used
to determine concentration. Figure d shows corresponding positions of these data points
for a selected trial at a sample concentration of 0.3 mg/mL (4.51
μM). For all three positions, the linear fit and prediction
intervals show strong monotonic relationships between the absorbance
metric value and the concentration. The statistical significance of
the difference in absorbance was assessed using Welch’s t-test, once for comparing the absorbances of the 0.10 and
0.15 mg/mL cases and another time for comparing the 0.15 and 0.30
mg/mL cases. With a chosen significance criterion of 0.05, the t-test was conducted with the null hypothesis that there
is not a significant difference between two datasets. In both cases,
the p-values output by the t-test
(0.0024 and 0.0039, respectively) were significantly lower than the
significance criteria. This allows us to reject the null hypothesis
and confirm that there is a statistically significant difference between
the absorbances of different concentrations. Furthermore, the second
peak shows the strongest linear relationship, with a slope of 0.892
μM–1, compared to slopes of the first peak
and valley, respectively, 0.453 μM–1 and 0.515
μM–1. For comparison, the premixed cases exhibited
a slope of 0.616 μM–1 (Figure ). Therefore, the second peak demonstrates
the best sensitivity for a colorimetric assay.
Figure 7
Absorbance metric is
shown as a function of sample concentration
at (a) the first peak, (b) the first valley, and (c) the second peak,
along with their respective linear fits (dashed lines) and 80% prediction
intervals (dash-dotted lines). The corresponding locations of the
peaks and valleys in the temporal data are illustrated for one example
trial in (d).
Absorbance metric is
shown as a function of sample concentration
at (a) the first peak, (b) the first valley, and (c) the second peak,
along with their respective linear fits (dashed lines) and 80% prediction
intervals (dash-dotted lines). The corresponding locations of the
peaks and valleys in the temporal data are illustrated for one example
trial in (d).Figure shows the
results for the case with the substrate heated to a temperature of
40 °C, compared to those at room temperature. A comparison of
the timescales of the peaks and valleys demonstrate a dramatically
increased rate of mixing (mixing time down from ∼200 to ∼125
s and reaction completion time down from ∼400 to ∼200
s) and, consequently, earlier completion of the reaction at a higher
temperature. In our previous study of buoyancy-induced convection
in droplets on nonwetting surfaces, Dash et al. demonstrated that
mixing times on hydrophobic surfaces similar to those used in the
current study are ∼15 times longer than that on superhydrophobic
surfaces.[28] At a substrate temperature
of 40 °C, the hydrophobic surface used here may be expected to
exhibit a mixing time of ∼150 s, based on the mixing time of
∼10 s for superhydrophobic substrates.[28] For the heated substrate case in Figure , the mixing is complete at ∼125 s.
Clearly, heating of the substrate is a viable method for dramatically
speeding the time to measurement, as long as the denaturation temperature
of the protein (60 °C[30]) is not reached.
Furthermore, the volume of the droplet can be adjusted, with smaller
volumes likely to result in faster mixing times. Given this reaction
speed-up, along with the miniaturization of the measurement platform,
droplet-based micromixing is demonstrated to be a viable alternative
to microtiter plates for colorimetric measurements, which require
longer or more complex mixing processes and complex fabrication.
Figure 8
Time-resolved
absorbance measurements for in situ mixed droplets
at a sample concentration of 0.15 mg/mL (2.26 μM) for a substrate
temperature of (a) 40 °C and (b) room temperature (21.5 °C).
Time-resolved
absorbance measurements for in situ mixed droplets
at a sample concentration of 0.15 mg/mL (2.26 μM) for a substrate
temperature of (a) 40 °C and (b) room temperature (21.5 °C).
Conclusions
Absorbance-based colorimetry
is conducted using a sessile droplet
on a nonwetting substrate. A discernible trend in the measured absorbance
with sample concentration is first demonstrated in a sessile droplet
for a case when the sample and reagent are premixed. The sample and
reagent are then mixed in situ within a droplet, and the absorbance
is measured in real time throughout the process. The measured temporal
absorbance signal results from combined interactions between buoyancy-induced
mixing, reaction between the sample and reagent, and adsorption of
the protein molecules onto the nonwetting substrate. Analysis of videos
of the reacting medium reveals the phases where each of these mechanisms
dominates the trend in droplet absorbance. Statistical analysis of
the absorbance data shows that the difference in signal between concentrations
is statistically significant. The second transient peak in the absorbance
measurement, associated with completion of the reaction, provides
the highest sensitivity to sample concentration, and is therefore
recommended for colorimetric quantitation during in situ mixing. Heating
the substrate is shown to dramatically increase the rate of mixing,
allowing for rapid concentration measurements. Overall, this sessile-droplet-based
approach for absorbance-based colorimetry on a heated substrate provides
a promising alternative to microwells for high-throughput parallel
assays because of simple implementation and enhanced passive micromixing.
Future work could involve optimization of surface modification, mixture
ratios of the sample and reagent, and parallelization, in order to
improve the efficiency of mixing, measurement accuracy, and device
reusability.
Authors: Nikolaus Ivo Sarafoff; Jan Bieschke; Armin Giese; Petra Weber; Uwe Bertsch; Hans A Kretzschmar Journal: J Biochem Biophys Methods Date: 2005-06-30
Authors: P K Smith; R I Krohn; G T Hermanson; A K Mallia; F H Gartner; M D Provenzano; E K Fujimoto; N M Goeke; B J Olson; D C Klenk Journal: Anal Biochem Date: 1985-10 Impact factor: 3.365