Digital single-molecule technologies are expanding diagnostic capabilities, enabling the ultrasensitive quantification of targets, such as viral load in HIV and hepatitis C infections, by directly counting single molecules. Replacing fluorescent readout with a robust visual readout that can be captured by any unmodified cell phone camera will facilitate the global distribution of diagnostic tests, including in limited-resource settings where the need is greatest. This paper describes a methodology for developing a visual readout system for digital single-molecule amplification of RNA and DNA by (i) selecting colorimetric amplification-indicator dyes that are compatible with the spectral sensitivity of standard mobile phones, and (ii) identifying an optimal ratiometric image-process for a selected dye to achieve a readout that is robust to lighting conditions and camera hardware and provides unambiguous quantitative results, even for colorblind users. We also include an analysis of the limitations of this methodology, and provide a microfluidic approach that can be applied to expand dynamic range and improve reaction performance, allowing ultrasensitive, quantitative measurements at volumes as low as 5 nL. We validate this methodology using SlipChip-based digital single-molecule isothermal amplification with λDNA as a model and hepatitis C viral RNA as a clinically relevant target. The innovative combination of isothermal amplification chemistry in the presence of a judiciously chosen indicator dye and ratiometric image processing with SlipChip technology allowed the sequence-specific visual readout of single nucleic acid molecules in nanoliter volumes with an unmodified cell phone camera. When paired with devices that integrate sample preparation and nucleic acid amplification, this hardware-agnostic approach will increase the affordability and the distribution of quantitative diagnostic and environmental tests.
Digital single-molecule technologies are expanding diagnostic capabilities, enabling the ultrasensitive quantification of targets, such as viral load in HIV and hepatitis C infections, by directly counting single molecules. Replacing fluorescent readout with a robust visual readout that can be captured by any unmodified cell phone camera will facilitate the global distribution of diagnostic tests, including in limited-resource settings where the need is greatest. This paper describes a methodology for developing a visual readout system for digital single-molecule amplification of RNA and DNA by (i) selecting colorimetric amplification-indicator dyes that are compatible with the spectral sensitivity of standard mobile phones, and (ii) identifying an optimal ratiometric image-process for a selected dye to achieve a readout that is robust to lighting conditions and camera hardware and provides unambiguous quantitative results, even for colorblind users. We also include an analysis of the limitations of this methodology, and provide a microfluidic approach that can be applied to expand dynamic range and improve reaction performance, allowing ultrasensitive, quantitative measurements at volumes as low as 5 nL. We validate this methodology using SlipChip-based digital single-molecule isothermal amplification with λDNA as a model and hepatitis C viral RNA as a clinically relevant target. The innovative combination of isothermal amplification chemistry in the presence of a judiciously chosen indicator dye and ratiometric image processing with SlipChip technology allowed the sequence-specific visual readout of single nucleic acid molecules in nanoliter volumes with an unmodified cell phone camera. When paired with devices that integrate sample preparation and nucleic acid amplification, this hardware-agnostic approach will increase the affordability and the distribution of quantitative diagnostic and environmental tests.
This paper
shows that single
nucleic acid molecules confined in nanoliter volumes in microfluidic
devices can be detected and counted by an unmodified cell phone camera,
in combination with isothermal amplification chemistry, a judiciously
chosen indicator dye and ratiometric image processing. We describe
a novel methodology that can be used to develop a visual readout for
digital single-molecule amplification of sequence-specific RNA and
DNA that can be used with any camera phone, without modifications
or attachments. Single-molecule visual readout has never been achieved
before with an unmodified cell phone camera. Diagnostic tests that
incorporate such a visual readout will greatly expand the applicability
of emerging digital single-molecule technologies, including in limited
resource settings (LRS). Ultrasensitive and quantitative detection
of nucleic acid molecules is of particular interest for infectious
disease diagnosis in LRS, such as the quantification of viral load
for humanimmunodeficiency virus (HIV) and hepatitis C virus (HCV),[1−3] as many of these infections occur far from centralized laboratories
where diagnostic tests are routine. Increasing diagnoses in these
locations will lead to faster and more appropriate treatment and have
a major impact on disease burden.[4,5] Most point
of care (POC) tests are not amenable to LRS because they do not meet
the World Health Organization’s ASSURED criteria of being affordable,
sensitive, specific, user-friendly, rapid, robust, equipment-free
and deliverable.[5] The tests that do meet
the requirements for LRS (e.g., immunochromatography
to detect antigens or antibodies in a dipstick or lateral-flow format;
or the visualization of antigen–antibody lattice formation)
have poor reported sensitivities and thus are unable to detect and
quantify analytes at low concentrations.[4,6] Nucleic acid
amplification tests (NAATs), such as PCR, have the desired high sensitivity
and target specificity, providing accurate quantification, but these
technologies are costly, time-consuming, and require skilled technicians
and laboratory settings.[7]Of the
NAATs, isothermal amplification methods (e.g., loop-mediated
isothermal amplification, LAMP) are among the most
attractive for LRS because they do not require thermocycling or capital
equipment and can be run in water baths, using simple heaters or with
exothermic chemical heating that does not require electricity.[8−11] Still, acquiring quantitative and ultrasensitive measurements outside
of the lab remains challenging because the methods are not robust
to variability in reaction conditions and readouts rely on precise
measures of fluorescence intensity. Running isothermal amplification
chemistries in a digital, single-molecule format maintains the high
sensitivity and quantification capabilities typically achieved only
in lab settings.[12−15] In digital single-molecule isothermal amplification, single, stochastically
confined DNA or RNA molecules are randomly distributed among discrete
nanoliter or picoliter volumes and amplified under controlled conditions.[16−18] This creates relatively high local concentrations of target DNA
or RNA, making digital amplification more efficient and robust compared
to bulk reactions with the same number of starting target molecules.
Nucleic acid amplification of even a single target molecule produces
a clear fluorescent signal and the results of digital amplification
can be read by a modified cell phone (e.g., a phone
camera with an optical filter) under dim lighting.[14]Microfluidic technology has been an instrumental
tool in developing
single nucleic acid molecule capabilities,[19−27] and the integration of sample-preparation modules into portable
microfluidic devices will further enable their use by untrained users
in any setting.[28−30] To bring these emerging technological capabilities
to LRS, however, such devices capable of ultrasensitive, quantitative
measurements should provide a rapid, visual readout that can be captured
easily, e.g., by any mobile phone without modifications
or attachments. Cell phone cameras provide a convenient, nearly universal
tool to pair with emerging diagnostic technologies to transform global
healthcare as ∼7 billion mobile cellular subscribers exist
worldwide and 70% of users live in developing countries.[31] Mobile devices are emerging as a powerful platform
to create cost-effective alternatives for molecular diagnostics in
LRS[32−42] and colorimetric diagnostics based on unmodified cell phones have
been used before,[38,43−46] but not in a digital format,
where the short path lengths and nanoliter volumes have constrained
visual-based methods. Here, we describe an approach that enables visual
readout of single nucleic acid molecule amplification by (i) selecting
an appropriate colorimetric indicator dye based on spectral properties
that align well with the RGB sensitivities of common cell phone camera
sensors and (ii) identifying the optimal ratiometric image-processing
for the selected dye to achieve a readout that is robust to lighting
conditions and camera hardware. With this approach, after sequence-specific
single-molecule isothermal amplification, a visual readout is captured
by an unmodified camera phone and the resulting image is analyzed
using a ratiometric approach, wherein the measured intensities of
two of the three RGB color channels are divided to provide a binary
result (a positive or negative reaction) for each well. The automation
of this ratiometric analysis provides a clear, reliable digital readout
without requiring the user to differentiate color change by eye or
manipulate lighting (Figure a). We further show how limitations related to reaction inhibition
by the readout dye can be solved with SlipChip microfluidics technology
to decouple the amplification and readout steps. We validated our
visual readout method with SlipChip-based digital single-molecule
isothermal amplification reactions using phage lambda DNA (λDNA)
as a model and HCV RNA as a clinically relevant target, in reaction
volumes as low as 5 nL, using a variety of common cell phones and
a range of illumination conditions.
Figure 1
A visual readout approach for digital
single-molecule isothermal
amplification for use with an unmodified cell phone camera. (a) A
workflow for visual readout of digital single-molecule amplification.
Single nucleic acid molecules are compartmentalized on a microfluidic
device with indicator dye and followed by isothermal nucleic acid
amplification. Positive reaction solutions are blue; negative reactions
are purple. After ratiometric image processing, positive reactions
become white and negative reactions become black, an unambiguous binary
result. The number of positive wells is then used to quantify the
concentration of the input target. (b) A diagram for delineating the
optimal range of dye concentrations as a factor of path length (reaction
volume) and the threshold for reaction inhibition. The green-shaded
region indicates the range of acceptable dye concentrations for visualization
with an unmodified cell phone camera. Concentrations to the left of
the green region are too low for visualization; concentrations to
the right of the green region are too high. Within this green region,
the dotted area indicates dye concentrations that both enable readout
with an unmodified cell phone camera and do not inhibit the amplification
reaction. The area to the right of the red line indicates dye concentrations
that interfere with amplification making accurate quantification based
on real-time data challenging.
A visual readout approach for digital
single-molecule isothermal
amplification for use with an unmodified cell phone camera. (a) A
workflow for visual readout of digital single-molecule amplification.
Single nucleic acid molecules are compartmentalized on a microfluidic
device with indicator dye and followed by isothermal nucleic acid
amplification. Positive reaction solutions are blue; negative reactions
are purple. After ratiometric image processing, positive reactions
become white and negative reactions become black, an unambiguous binary
result. The number of positive wells is then used to quantify the
concentration of the input target. (b) A diagram for delineating the
optimal range of dye concentrations as a factor of path length (reaction
volume) and the threshold for reaction inhibition. The green-shaded
region indicates the range of acceptable dye concentrations for visualization
with an unmodified cell phone camera. Concentrations to the left of
the green region are too low for visualization; concentrations to
the right of the green region are too high. Within this green region,
the dotted area indicates dye concentrations that both enable readout
with an unmodified cell phone camera and do not inhibit the amplification
reaction. The area to the right of the red line indicates dye concentrations
that interfere with amplification making accurate quantification based
on real-time data challenging.
Results and Discussion
Selecting an Indicator Dye
To eliminate
the need for
a fluorescent readout in single-molecule amplification and produce
a readout that can be imaged by any cell phone camera under various
illumination conditions, one can use a nucleic acid amplification-indicator
dye that changes color in response to amplification. A robust colorimetric
readout balances two opposing requirements: the indicator dye must
be sufficiently concentrated (or present in a large enough volume)
to provide readable absorbance (i.e., smaller volumes
and shorter path lengths require greater concentrations of dye for
sufficient absorbance to be detected) but not so concentrated that
the dye interferes with the amplification reaction. To optimize a
visual readout system for single-molecule counting with an unmodified
cell phone camera, we first identified the factors that contribute
to hypothetical limitations of a visual readout system, including
the range of reaction volumes (or path lengths) at which a particular
indicator could be used to monitor amplification and the range of
indicator concentrations that would not interfere with the amplification
reaction. Where these ranges overlap are the optimal volumes and dye
concentrations at which a reaction is not inhibited and can provide
a change in absorbance that is sufficient for readout with an unmodified
camera phone (dotted green region of Figure b).We validated this visual readout
approach using loop-mediated isothermal amplification (LAMP)[47,48] (Supporting Information Tables S1 and
S2) because this method has been well characterized and validated
previously for single-molecule analyses.[12,14−17,49] LAMP chemistry is based on an
autocycling strand displacement reaction performed at a constant temperature
to synthesize large amounts of amplified product; a LAMP reaction
generates more than 109 copies of template within 1 h of
incubation at 60–65 °C.[48] We
used a cubic reaction volume of 8 nL (200 × 200 × 200 μm3), which is in the range of volumes used in digital experiments.[12,14,15,17,49] We assume that an appropriate indicator
of an amplification reaction will have a change in absorbance that
equates to a change of extinction coefficient of ∼25 000
L mol–1 cm–1 upon reaction (this
number approaches the maximum achievable change in absorbance for
small-molecule dyes). We use the Beer–Lambert law (A = εLc), which describes the relevant parameters
to consider for visualization, wherein A = absorbance;
ε = extinction coefficient (L mol–1 cm–1); L = length of the light’s
path through the solution (cm); c = concentration
of absorbing species (mol/L). At a path length of 0.2 mm, an estimated
∼2 mM concentration of the dye is required to reach a change
of absorbance of 1 unit. Given these parameters, to obtain a readout
that can be captured by an unmodified mobile phone, we predicted that
an appropriate indicator dye would be one that responds to the incorporation
of each nucleotide (present in mM concentrations), as opposed to responding
only to the number of produced molecules (amplicons), which would
not exceed primer concentration (present in the μM range).Colorimetric approaches to visual detection of nucleic acid amplification
typically measure absolute changes in color intensity;[50−54] however, distinguishing color change, e.g., purple vs blue, is difficult and therefore not an appropriate way
to quantify readout under variable conditions, such as in LRS. Ratiometric
measurements, which take the ratio of two independent measurements
under the same conditions, improve the robustness of a colorimetric
approach, converting results to a yes/no binary outcome, eliminating
the need for the user to differentiate colors. We hypothesized that
a cell phone camera’s sensor, which reads in three color channels
(red, green, and blue, RGB) could provide suitable information for
using a ratiometric approach to read amplification reactions at the
single molecule level. The example we considered here is the back-illuminated
Exmor R CMOS image sensor[55] used on popular
cell phones such as the Samsung Galaxy 4, iPhone 4S, and iPhone 5,
which has a sensitivity maxima of ∼520 nm (green), ∼459
nm (blue), and ∼597 nm (red) (Figure a).
Figure 2
Predicted values and experimental validation
of the first step
of the ratiometric approach. (a) Measured spectral transmittance (%)
in the range of visible light (400–700 nm) for positive (solid
blue line) and negative (solid purple line) RT-LAMP reaction solutions,
each containing 0.7 mM of eriochrome black T (EBT) as the amplification
indicator dye. Dashed lines correspond to normalized spectral responses
for red (R), green (G), and blue (B) channels of an Exmor R CMOS sensor,
a common sensor in cell phone cameras. (b–e) Analysis of the
three possible RGB ratiometric combinations for positive and negative
RT-LAMP reaction solutions. (b) The predicted RGB values and corresponding
colors for positive and negative LAMP amplification reactions obtained
by convoluting the transmittance spectrum and Exmor R spectral responses
described in panel a. (c) The cropped and enlarged color images collected
with an Apple iPhone 4S for positive and negative RT-LAMP reaction
solutions containing 90 μM of EBT dye. (d) Predicted images
and ratiometric values for positive and negative amplification reactions
processed for each ratiometric combination, G/R, B/R, and G/B. (e)
Experimental images and ratiometric values for positive and negative
amplification reactions for each combination: G/R, B/R, and G/B. All
experiments were performed with HCV RNA as template.
Predicted values and experimental validation
of the first step
of the ratiometric approach. (a) Measured spectral transmittance (%)
in the range of visible light (400–700 nm) for positive (solid
blue line) and negative (solid purple line) RT-LAMP reaction solutions,
each containing 0.7 mM of eriochrome black T (EBT) as the amplification
indicator dye. Dashed lines correspond to normalized spectral responses
for red (R), green (G), and blue (B) channels of an Exmor R CMOS sensor,
a common sensor in cell phone cameras. (b–e) Analysis of the
three possible RGB ratiometric combinations for positive and negative
RT-LAMP reaction solutions. (b) The predicted RGB values and corresponding
colors for positive and negative LAMP amplification reactions obtained
by convoluting the transmittance spectrum and Exmor R spectral responses
described in panel a. (c) The cropped and enlarged color images collected
with an Apple iPhone 4S for positive and negative RT-LAMP reaction
solutions containing 90 μM of EBT dye. (d) Predicted images
and ratiometric values for positive and negative amplification reactions
processed for each ratiometric combination, G/R, B/R, and G/B. (e)
Experimental images and ratiometric values for positive and negative
amplification reactions for each combination: G/R, B/R, and G/B. All
experiments were performed with HCV RNA as template.To illustrate our methodology for a hardware-agnostic
visual readout
with a ratiometric approach, we selected eriochrome black T (EBT),
a magnesium ion indicator that meets the aforementioned dye specifications
and has been used previously for visualization of LAMP products.[56,57] During an isothermal amplification reaction, as nucleotides are
incorporated, protons and byproduct pyrophosphate ions (P2O74–) are produced, and these ions can
strongly bind metal ions (e.g., Mg2+ ions)
and form insoluble salts, decreasing the concentration of metal ions
in the reaction solution. Before the amplification reaction, EBT is
bound to magnesium ions and the reaction solution is purple. As a
LAMP reaction proceeds in the presence of target nucleic acid, it
is suggested that EBT is deprived of Mg2+ by newly generated
pyrophosphate ions, and the reaction solution turns blue.We
hypothesized that EBT would be amenable to colorimetric analysis
with a cell phone camera because, in RGB terms, in a positive LAMP
reaction containing EBT dye, there is a peak in the spectral transmittance
in the blue channel (blue LAMP reaction solution), while in a negative
LAMP reaction, transmittance remains high in the blue and red channels
(purple LAMP reaction solution) (Figure a). These observed changes in transmittance
between positive and negative reactions can be captured by the Exmor
R optical sensor (Figure a), which matches well with the observed differences between
positive and negative transmittance profiles of LAMP reactions containing
EBT (Figure a).
Selecting the Optimal Ratiometric Approach
We tested
whether the suitability of an indicator dye can be evaluated for a
ratiometric approach prior to experimental validation by predicting
the RGB values read by a cell phone camera for a positive and a negative
reaction. First, we took the transmittance spectra for positive and
negative amplification reactions containing EBT and convoluted them
with the normalized spectral responses for each of the RGB channels
in an Exmor R CMOS sensor[58] providing six
curves (a positive and negative for each of the three color channels).
Next, we calculated the area under each curve and took its square
root (to account for the standard square-root scaling that occurs
with nonscientific devices used for imaging), providing the predicted
RGB values (Figure b) for positive (R = 185, G = 197, and B = 209) and negative (R =
219, G = 190, and B = 212) RT-LAMP reaction solutions in the presence
of EBT at this particular concentration. These values can then be
evaluated to select the optimal ratiometric approach for this particular
indicator dye. In an RGB color scheme, there are three possible combinations
for ratiometric analysis: G/R, B/R, or G/B. The predicted RGB values
for a positive and a negative reaction are used to calculate the ratios
for each channel combination (Figure d); the ratio with the greatest difference between
positive and negative outcomes (G/R in this example) is predicted
to be the most robust ratiometric analysis.Using the approach
described above, we predicted the RGB ratios for a positive and negative
RT-LAMP reaction in the presence of two additional indicator dyes:
hydroxynaphthol blue (HNB) and calmagite. HNB is being reported increasingly
in the literature for LAMP visualization[50,59−62] and calmagite is an analogue of EBT dye with the nitro group absent
(more stable version).[63] A side-by-side
comparison showed that the greatest predicted difference between positive
and negative RT-LAMP reaction, as captured by an unmodified cell phone
camera, would be achieved using EBT as the indicator dye and G/R as
the ratiometric combination (Figure S11). On the basis of these predicted ratios, we decided to validate
our methodology using EBT as the indicator dye. We confirmed the storage
stability of the EBT dye stock solution in the dried state (Figure S13), as this is a critical requirement
for the use of a dye in real point-of-need diagnostic applications.
EBT serves as our validation dye in this paper, however our methodology
is designed to be applicable to alternative dyes.To experimentally
validate this approach of predicting an optimal
ratiometric combination, we performed an RT-LAMP reaction for HCV
RNA containing EBT as the indicator dye and captured an image of the
readout with an unmodified camera phone (iPhone 4S) (Figure c). We processed the readout
image; color channels of the original image were split and all three
channel ratios (G/R, B/R, G/B) were calculated to derive a ratiometric
image for each ratiometric combination. These experimental ratios
obtained with an unmodified cell phone camera (Figure e) matched well with the predicted values
(Figure d) for each
of the three ratiometric combinations, confirming the predictive power
of this approach. The G/B ratio was identified as less appropriate
for distinguishing positive and negative reactions because the values
for positive and negative reactions were similar; G/R and B/R ratios
were identified as suitable because there was sufficient contrast
between the values for positive and negative reactions. For the G/R
combination, the ratio obtained after a negative reaction was 0.91
and the ratio from a positive reaction was 1.03, a difference of 0.12
(Figure e). For the
B/R combination, the ratios for negative and positive reactions were
0.98 and 1.07, a difference of 0.09 (Figure e). Therefore, we selected the G/R combination
for our subsequent validation experiments. Counting positives is a
more intuitive approach, so the B/R ratio (where the positive ratio
had the greatest difference from the background) can be a useful and
attractive method. However, it is generally more desirable to select
a ratio that includes the green channel because most single-chip digital
image sensors used in digital cameras, including cell phones, utilize
a Bayer filter mosaic pattern that is composed of 50% green, 25% red,
and 25% blue pixels.[64]To test the
robustness of our approach to different hardware and
illumination conditions, we used HCV RNA amplified by RT-LAMP at 2-fold
increasing concentrations of indicator dye ranging from 10.9 μM
to 1.4 mM (for a total of eight dye concentrations). After RT-LAMP
amplification, 50 μL of each reaction solution was transferred
to 96-well plates (path length of ∼1.5 mm) and the readout
was imaged with cameras from four common cell phone models: Apple
iPhone 4S (Figure a), HTC inspire 4G (Figure b), Motorola Moto G (Figure c), and Nokia 808 PureView (Figure d). Under fluorescent light and using the
G/R ratiometric process (green channel divided by red channel followed
by a threshold adjustment to generate a binarized black and white
image), we determined that EBT concentrations lower than 0.175 mM
provided an insufficient color change for detection with a cell phone
camera (Figure , region
I, white background), while concentrations of 1.4 mM inhibited the
amplification reaction (Figure , region III, red background). For this particular indicator
dye, the range of concentrations at which color change could be detected
by an unmodified cell phone camera and no inhibition was observed
at the end point of the reaction (Supporting Information Figure S1) was identified as 0.175–0.7 mM (Figure , region II, green background).
Some cell phone cameras were more sensitive (e.g., HTC inspire 4G was able to distinguish a positive result at EBT
concentrations as low as 0.0875 mM) (Figure b), but all four cell phone models distinguished
a positive reaction at concentrations between 0.175 and 0.7 mM (Figure , region II, green
background). We then chose one cell phone with the most representative
performance (Apple iPhone 4S) to test the robustness of the G/R approach
to different lighting conditions. Under all conditions tested: incandescent
light (Figure e),
direct sunlight (Figure f) and indirect sunlight (Figure g), the optimal EBT concentration range that we identified
under fluorescent light (0.175–0.7 mM) could be read clearly,
confirming the robustness of the ratiometric approach to variations
in illumination.
Figure 3
Validation of the robustness of the G/R ratiometric approach
to
different hardware (cell phone cameras) and lighting conditions. (a–g)
Enlarged and cropped color images (top two rows of each individual
panel) captured by an unmodified cell phone camera from positive (+)
and negative (−) RT-LAMP reactions at 2-fold increases in EBT
concentration from 10.9 μM to 1.4 mM (1 = 0.011 mM; 2 = 0.022
mM; 3 = 0.044 mM, 4 = 0.088 mM, 5 = 0.175 mM; 6 = 0.35 mM; 7 = 0.7
mM; 8 = 1.4 mM). Positive wells are blue and negative wells are purple.
After G/R ratiometric processing (bottom two rows of each individual
panel), negative wells are black. Regions I, II, III in each panel
indicate the effect of dye concentration: (II) acceptable concentration
range for visualization (green regions); (I) concentrations too low
for visualization (white regions); and (III) concentrations too high
for visualization (red regions). (a–d) Images captured by four
common cell phones under fluorescent light: (a) Apple iPhone 4S, (b)
HTC inspire 4G, (c) Motorola Moto G, and (d) Nokia 808 PureView. (e–g)
Images captured by an Apple iPhone 4S under three additional light
conditions: (e) incandescent light, (f) direct sunlight, and (g) indirect
sunlight. All experiments were performed with HCV RNA as a clinically
relevant target. All images were acquired with unmodified cell phone
cameras. Detailed information for the G/R ratiometric process (Figure
S2) and additional cell phone camera images (Figure S3) are provided
in the Supporting Information.
Validation of the robustness of the G/R ratiometric approach
to
different hardware (cell phone cameras) and lighting conditions. (a–g)
Enlarged and cropped color images (top two rows of each individual
panel) captured by an unmodified cell phone camera from positive (+)
and negative (−) RT-LAMP reactions at 2-fold increases in EBT
concentration from 10.9 μM to 1.4 mM (1 = 0.011 mM; 2 = 0.022
mM; 3 = 0.044 mM, 4 = 0.088 mM, 5 = 0.175 mM; 6 = 0.35 mM; 7 = 0.7
mM; 8 = 1.4 mM). Positive wells are blue and negative wells are purple.
After G/R ratiometric processing (bottom two rows of each individual
panel), negative wells are black. Regions I, II, III in each panel
indicate the effect of dye concentration: (II) acceptable concentration
range for visualization (green regions); (I) concentrations too low
for visualization (white regions); and (III) concentrations too high
for visualization (red regions). (a–d) Images captured by four
common cell phones under fluorescent light: (a) Apple iPhone 4S, (b)
HTC inspire 4G, (c) Motorola Moto G, and (d) Nokia 808 PureView. (e–g)
Images captured by an Apple iPhone 4S under three additional light
conditions: (e) incandescent light, (f) direct sunlight, and (g) indirect
sunlight. All experiments were performed with HCV RNA as a clinically
relevant target. All images were acquired with unmodified cell phone
cameras. Detailed information for the G/R ratiometric process (Figure
S2) and additional cell phone camera images (Figure S3) are provided
in the Supporting Information.
One-Step Method for Digital Visual Readout
Microfluidic
devices enable ultrasensitive digital quantification. Small well volumes
are valuable because they enable faster reactions (because concentrations
are high in single wells), minimize the effects of inhibitory materials
(due to their isolation into wells) and expand the upper limit of
the dynamic range (because single molecules can be confined from samples
containing high template concentrations).[18,65,66] However, as well volumes (and path lengths)
decrease, color visualization becomes challenging for a mobile phone.
To compensate, the concentration of the indicator dye can be increased;
however, high concentrations of some dyes inhibit amplification reactions.
Thus, there are inherent physical limits to a colorimetric approach.
To validate that this visual readout approach could be applied to
single-molecule amplification at nanoliter volumes, we used digital
LAMP (dLAMP) and phage λDNA as a target. We specifically aimed
to resolve three questions: (i) Can we obtain a visual readout for
amplified single molecules that can be captured by an unmodified cell
phone camera? (ii) Is volume a factor in achieving a digital visual
readout? (iii) Does ratiometric processing work for small volumes?To answer these questions, we designed a multivolume rotational
SlipChip device containing 1240 wells of eight volumes ranging from
15 to 50 nL (Figures S4 and S5). We loaded
these devices with LAMP reaction solution containing an appropriate
target concentration in the middle of the device’s dynamic
range, a fluorescent DNA-detecting intercalation dye (Syto 9), and
EBT dye at 0.7 mM (the highest noninhibiting concentration identified
in Figure ). We imaged
this device with a house-built real-time fluorescence imager, with
a Leica stereoscope (optimal imaging conditions) and with an Apple
iPhone 4S. The number of positive counts based on fluorescence was
261, while 260 positives were counted using the indicator dye and
G/R process both with the stereoscope and the cell phone (Figure ). This experiment
showed that the G/R method could be used in place of fluorescence
readout to count amplified single molecules and that the readout capture
and G/R processing performed on an unmodified cell phone matched the
results obtained under optimal lighting conditions (stereoscope).
Additionally, using a device containing 800 wells of 27 nL, we observed
excellent correlation among positive counts obtained from the stereoscope,
fluorescence imager and cell phone camera (Figure S6).
Figure 4
Readout from single-molecule digital LAMP reactions performed with
λDNA on a multivolume rotational SlipChip device imaged by (a)
a stereoscope, (b) a fluorescence microscope, and (c) an unmodified
cell phone camera. (e–g) Callouts are magnified to show visual
correlation among the three imaging methods. (d) The results of the
ratiometric processing for the stereoscope G/R-processed image and
(h) the cell phone G/R-processed image. Colors were enhanced in these
figures for clarity of publication; raw images were used in all ratiometric
analyses. These devices contained 1240 wells of eight volumes ranging
from 15 to 50 nL.
Readout from single-molecule digital LAMP reactions performed with
λDNA on a multivolume rotational SlipChip device imaged by (a)
a stereoscope, (b) a fluorescence microscope, and (c) an unmodified
cell phone camera. (e–g) Callouts are magnified to show visual
correlation among the three imaging methods. (d) The results of the
ratiometric processing for the stereoscope G/R-processed image and
(h) the cell phone G/R-processed image. Colors were enhanced in these
figures for clarity of publication; raw images were used in all ratiometric
analyses. These devices contained 1240 wells of eight volumes ranging
from 15 to 50 nL.While investigating the
limits that reaction volume may impose
on visual readout, we observed that the estimated template concentration
determined from each of the eight well volumes produced similar Most
Probable Numbers (MPN) of molecules (mean 8500 ± 1500 copies/mL)
(Figure a) (estimated
concentration from all volumes are within 95% confidence interval
at each volume, detailed in Figure S7).
In addition, all SlipChip devices, analyzed independently, gave similar
target concentrations (8400 ± 500 copies/mL) (Figure b), suggesting that the selected
indicator dye did not impair quantification of single molecules in
well sizes 15–50 nL and that these well volumes can be imaged
reliably with either a stereoscope or an unmodified cell phone camera.
However, the cell phone camera images of well volumes of 15 nL were
less clear than those obtained from the stereoscope, suggesting that
volumes of ∼15 nL may approach the limit of colorimetric imaging
with current camera phone sensors, although as higher quality sensors
are integrated into commercial cell phones, this limit would change.
Figure 5
Robustness
of digital visual readout at different well volumes.
Concentration of λDNA was estimated by digital LAMP using five
multivolume rotational SlipChip devices, each of which contained eight
well volumes ranging from 15 to 50 nL. (a) Measured template concentration
for each well volume averaged over five devices. (b) Mean template
concentration for each of five rotational SlipChip devices. Concentrations
were calculated using MPN theory[65] and
error bars represent standard deviation. Images were captured by a
stereoscope and processed with the ratiometric approach (G/R process).
Robustness
of digital visual readout at different well volumes.
Concentration of λDNA was estimated by digital LAMP using five
multivolume rotational SlipChip devices, each of which contained eight
well volumes ranging from 15 to 50 nL. (a) Measured template concentration
for each well volume averaged over five devices. (b) Mean template
concentration for each of five rotational SlipChip devices. Concentrations
were calculated using MPN theory[65] and
error bars represent standard deviation. Images were captured by a
stereoscope and processed with the ratiometric approach (G/R process).
Two-Step Method for Digital
Visual Readout
We next
developed a method to apply the visual readout approach to digital
devices that contain smaller well volumes. To be able to image at
small volumes (e.g., 5 nL) on a microfluidic device,
one must balance the need for greater indicator color intensity for
visualization with the need to keep dye concentrations below the level
of inhibition (Figure , region III) for an amplification reaction. High concentrations
of indicator dye can completely halt an amplification reaction, and
we knew from performing real-time bulk experiments that even when
reactions are positive, an indicator dye can still interfere to some
extent with isothermal nucleic acid amplification—for both
RNA and DNA, we observed delays in the time-to-positive, and this
delay increased at greater concentrations of the indicator dye, even
though reactions were positive (Figure S8). We hypothesized that we could prevent inhibition completely by
decoupling the amplification step from the readout step. To do this,
we designed a two-step SlipChip device (based on previous SlipChip
designs)[13] (Figures S9 and S10) in which the amplification solution and the detection
solution are loaded into separate wells (Figure a). We validated this two-step protocol with
a clinically relevant target, purified HCV RNA, using digital reverse
transcription-LAMP (dRT-LAMP). First, we performed digital isothermal
amplification in the set of small (5 nL) amplification wells (in the
absence of the indicator dye) (Figure a(i)). After amplification, a “slip”
was performed and the amplification wells came into contact with a
second set of larger (9.5 nL) wells, which contained the indicator
dye, for a total well volume of 14.5 nL (Figure a(ii)). After mixing, negative wells lacking
target molecules are purple and wells containing positive reactions
are blue (Figure a(iii)).
Counts obtained by a house-built real-time imaging instrument (to
read fluorescence), and counts obtained by G/R processing from an
image captured by an unmodified cell phone camera were significantly
correlated (Pearson’s Corr = 0.9998; R2 = 0.9996) (Figure h), showing that this two-step SlipChip-based protocol provides
a suitable visual readout for digital single-molecule amplification
for devices containing wells of small volumes.
Figure 6
Experimental validation
of two-step SlipChip devices for single
molecule counting with an unmodified cell phone camera. (a) A flow-chart
of detection of single molecules in two-step SlipChip: (i) 5 nL amplification
wells are loaded with amplification reaction solution (RXN) and 9.5
nL detection wells are loaded with indicator dye (DYE). (ii) After
amplification, a slip is performed and the RXN and DYE wells are combined.
(iii) Immediately after mixing, positive reaction solutions become
blue, while negative reactions remain purple. The readout is imaged
by an unmodified cell phone camera. (iv) Ratiometric image processing
(G/R process) provides a single binary result (positive or negative).
(b) Stereoscope image of the device before the amplification and readout
wells are merged (arrow designates direction of slip). (c) Stereoscope,
(d) cell phone camera and (e) fluorescent images after the device
is slipped and the wells are merged. (f) Stereoscope and (g) cell
phone camera images after G/R image processing. (h) Correlation between
fluorescence counts and cell phone (G/R processed) counts. Colors
were enhanced in figure panels b–d, and f for clarity of publication;
raw images were used in all ratiometric analyses. In these experiments,
HCV RNA was amplified by dRT-LAMP.
Experimental validation
of two-step SlipChip devices for single
molecule counting with an unmodified cell phone camera. (a) A flow-chart
of detection of single molecules in two-step SlipChip: (i) 5 nL amplification
wells are loaded with amplification reaction solution (RXN) and 9.5
nL detection wells are loaded with indicator dye (DYE). (ii) After
amplification, a slip is performed and the RXN and DYE wells are combined.
(iii) Immediately after mixing, positive reaction solutions become
blue, while negative reactions remain purple. The readout is imaged
by an unmodified cell phone camera. (iv) Ratiometric image processing
(G/R process) provides a single binary result (positive or negative).
(b) Stereoscope image of the device before the amplification and readout
wells are merged (arrow designates direction of slip). (c) Stereoscope,
(d) cell phone camera and (e) fluorescent images after the device
is slipped and the wells are merged. (f) Stereoscope and (g) cell
phone camera images after G/R image processing. (h) Correlation between
fluorescence counts and cell phone (G/R processed) counts. Colors
were enhanced in figure panels b–d, and f for clarity of publication;
raw images were used in all ratiometric analyses. In these experiments,
HCV RNA was amplified by dRT-LAMP.Devices shown in this manuscript were not designed to achieve
clinically
relevant concentrations in the lower detection limit of quantification
(LDL) because larger well volumes do not represent a challenge when
imaging with a mobile phone. Instead, we studied the performance of
our approach with wells of small volumes to ensure that this method
meets the upper limit of quantification (ULQ) required for clinical
relevance. The ULQ is determined by the smallest well volume and the
total number of wells at that volume. As an example, for SlipChip
devices with 800 wells of 5 nL, the ULQ is 1 162 413
copies/mL, while a SlipChip device with 10 000 wells of 5 nL,
the ULQ is 1 622 660 (calculations performed according
to Kreutz et al. 2011).[65]
Conclusions
Here we show that single nucleic acid molecules
can be detected
and counted with an unmodified cell phone camera by employing microfluidic
technology, sequence-specific isothermal amplification, and a judiciously
chosen amplification-indicator dye. We further show that ratiometric
processing of the cell phone image enables robust quantification without
the need for a user to differentiate colors. The general methodology
we developed can be used as a guideline to enable others to develop
their own cell phone based single-molecule counting approach. The
methodology includes the following steps: First, an appropriate amplification
indicator should be selected. Indicators should respond optically
to each nucleotide incorporation event (as opposed to responding to
number of produced molecules) resulting in a change in the transmittance
profile in the wavelength range of visible light (400–700 nm).
The indicator dye should have a change in absorbance matched to the
spectral sensitivity of the image sensor in an unmodified cell phone;
for ratiometric processing, the solution should have a large relative
change in transmittance in color channels for which the camera’s
image sensor is most sensitive. Second, the color ratio used in the
ratiometric approach is chosen based on the spectral sensitivity of
the image sensor in an unmodified cell phone. This step can be done in silico to identify the dye with the ratio that provides
an unambiguous binary readout of positive and negative reactions that
is robust to illumination and hardware conditions. We hope others
will use this algorithm to identify even better dyes that will move
this field forward. Third, the selected dye and ratiometric approach
should be validated using the desired amplification chemistry. Experiments
should be performed to establish the range of dye concentrations and
well volumes at which an amplification reaction is not inhibited and
at which imaging can be done with an unmodified cell phone. For some
indicator dyes, the range of suitable well volumes and concentrations
will be too narrow. In such situations, an alternative approach is
to use a two-step device that separates the amplification and readout
steps. Processing can be done directly on a cell phone or uploaded
wirelessly to a cloud server to swiftly communicate results, as we
have shown previously.[14] We anticipate
that the capabilities of visual readout for counting single molecules
will extend further as cell phone camera technology advances, as additional
indicators are available (e.g., metal ions, pH indicators)
and as additional types of amplification reactions are developed.
Devices that integrate sample preparation, nucleic acid amplification,
and a visual digital readout that can be captured easily will be a
critical breakthrough toward bringing quantitative, ultrasensitive
measurements outside of central laboratories, a key step for in vitro diagnostics, pandemic surveillance, and environmental
monitoring. We hope this work will stimulate regulatory agencies such
as the FDA to consider the use of cell phones as valuable diagnostic
components.
Methods
Chemicals and Materials
All chemicals were purchased
from commercial sources. The LoopAmp RNA amplification kit (Eiken
Chemical Co., Ltd., Japan) was purchased from SA Scientific (San Antonio,
TX, USA). The LoopAmp RNA amplification kit contains 2× Reaction
Mix (RM) (40 mM Tris-HCl, pH 8.8, 20 mM KCl, 16 mM MgSO4, 20 mM (NH4)2SO4, 0.2% Tween 20,
1.6 M betaine, and dNTPs 2.8 mM each), Enzyme Mix (EM) (mixture of
Bst DNA polymerase and AMV reverse transcriptase), and distilled water
(DW). Bovine serum albumin (BSA) was purchased from Roche Diagnostics
(Indianapolis, IN, USA). Phage λDNA (500 μg), SUPERase
In RNase Inhibitor (20 U/μL), Eriochrome Black T (EBT) dye,
mineral oil (DNase, RNase, and Protease free), tetradecane, Costar
Clear Polystyrene 96-Well Plates, Corning Universal Optical Microplate
Sealing Tape, and DEPC-treated nuclease-free water were purchased
from Thermo Fisher Scientific (Hanover Park, IL, USA). Chelex 100
resin was purchased from Bio-Rad (Hercules, CA, USA). Trehalose solution
(1 M) was purchased from Amersham Life Science (Cleveland, OH, USA).
Tris-HCl buffer stock solution (1 M, pH 8.0) was purchased from Affymetrix
(Santa Clara, CA, USA). All primers were produced by Integrated DNA
Technologies (Coralville, IA, USA). Dichlorodimethylsilane was purchased
from Sigma-Aldrich (St. Louis, MO, USA). SYTO 9 Stain and AcroMetrix
HCV High Control were purchased from Life Technologies (Grand Island,
NY, USA). Nucleic acid extraction kit QIAamp Viral RNA Mini kit was
purchased from QIAGEN, Inc. (Valencia, CA, USA). Eppendorf Mastercycler
Gradient PCR Themal Cycler was purchased from Eppendorf (Hamburg,
Germany). POLARstar Omega microplate reader was purchased from BMG
Labtech (Durham, NC, USA). Leica MZ Fl III stereoscope with PLAN 0.5×
lens was purchased from Leica Microsystems (Bannockburn, IL, USA).
Photomasks were designed in AutoCAD 2013 and ordered from CAD/Art
Services, Inc. (Bandon, OR, USA). Soda-lime glass plates coated with
layers of chromium and photoresist were ordered from the Telic Company
(Valencia, CA, USA).
SlipChip Device Design
The multivolume
rotational SlipChip
device design was used to demonstrate the one-step method for digital
visual readout; this device was composed of 1240 microfluidic wells,
with the following volumes: 160 wells × 15 nL, 160 × 17.5
nL, 160 × 20 nL, 160 × 22.5 nL, 160 × 25 nL, 160 ×
40 nL, 160 × 45 nL, 120 × 50 nL (Figure S4). The total combined volume of all wells was 35.6 μL.
For loading, one inlet hole (in the middle ring structure) and four
oil escape holes (in the outer ring structure) were drilled in the
top plate. The two-step SlipChip device was used to demonstrate a
two-step method for digital visual readout; this device was based
on previously published SlipChip designs.[13] For the two-step SlipChip design used in this study, the device
was modified in the following ways: (i) the number of each type of
well was reduced to 800; (ii) space was added between the arrays to
allow for the incubation conformation; (iii) the sequence of well
loading was reversed (the smaller 5 nL wells are loaded before the
larger 9.5 nL wells). See Figure S9 for
more details. Examples of SlipChip multivolume designs for HCV and
HIV viral load quantification at clinically relevant dynamic ranges[67−69] are provided in the Supporting Information (Table S3).
SlipChip Device Fabrication
The
procedure for fabricating
the multivolume rotational SlipChip and two-step SlipChip devices
was based on previous work.[70] The device
features were etched to a depth of ∼100 μm for the multivolume
rotational SlipChip devices and ∼67 μm for the two-step
SlipChip devices. After etching and drilling through-holes, both devices
were subjected to the same glass silanization process, previously
described,[66] where the glass plates were
first thoroughly cleaned with piranha solution and dried sequentially
with 200 proof ethanol and nitrogen gas, and then oxidized in a plasma
cleaner for 2 min and immediately transferred into a vacuum desiccator
for 1.5 h for silanization with dimethyldichlorosilane. After silanization,
the devices were rinsed thoroughly with chloroform, acetone, and ethanol,
and dried with nitrogen gas before use. When a glass SlipChip device
needed to be reused, it was first cleaned with acid piranha solution
and then subjected to the same silanization and rinsing procedure
described above.
Assembling and Loading SlipChips
The SlipChips used
for both the dLAMP and the dRT-LAMP reactions were assembled under
degassed oil (mineral oil/tetradecane 1:4 v/v). Both top and bottom
plates were immersed in the oil phase and placed face to face. The
two plates were aligned under a stereoscope (Leica, Germany) and stabilized
using binder clips. Through-holes were drilled into the top plate
to serve as fluid inlets and oil outlets in dead-end filling. The
reagent solutions were loaded through the inlets by pipetting.
HCV Viral
RNA Purification from AcroMetrix HCV High Control
A total
of 200 μL of plasma containing HCV RNA (viral load
estimate provided by AcroMetrix: 1.1–3.5 IU/mL) was extracted
using the QIAamp Viral RNA Mini Kit (QIAGEN, Inc., Valencia, CA, USA)
according to the manufacturer’s instructions. The elution volume
was 60 μL. The purified HCV viral RNA was analyzed immediately
or stored at −80 °C until further analysis.
Preparation
of EBT Solution
The EBT stock solutions
were prepared by dissolving EBT dye in deionized water. The aqueous
solution was sonicated for 10–20 min and the free volume was
filled with argon gas and mixed on a rotator at 65 °C for 1 h.
To remove any potential impurities from the EBT dye, Chelex 100 ion-exchange
resin was added to the resulting solution (5% w/v) and placed on rotator
for 1 h. Resin was centrifuged at 3000 rpm for 5 min and the top fraction
was collected in a Falcon tube, flushed with argon, and stored at
room temperature for no more than 2 days. A comparison of EBT, HNB,
and calmagite indicator dye stock solutions before and after treatment
with Chelex 100 is provided in the Supporting Information (Figure S12).
Storage Stability of Amplification
Indicator Dyes by Drying
in the Presence of Stabilizer Trehalose
EBT, HNB, and calmagite
stock solutions at 0.7 mM were prepared by dissolving the dyes in
20 mM Tris-HCl buffer (pH 8.8) and adding 30 mM of trehalose. The
solutions were sonicated for 10 min and mixed on a rotator at room
temperature for 1 h. Chelex 100 ion-exchange resin was added (5% w/v)
and placed on rotator for 1 h. Resin was centrifuged at 3000 rpm for
5 min and the top fraction was collected in a Falcon tube. The resulting
stock solutions were transferred to a Costar Clear Polystyrene 96-Well
Plate (40 μL per well) and sealed with Corning Universal Optical
Microplate Sealing Tape before spectrophotometric analysis (time 0
h). Immediately after analysis, the sealing cover was removed and
the plate was placed in a desiccator under vacuum overnight until
the dye stock solutions were completely dry. Then, at 24-h time points
over the next 120 h (for a total of 5 time points), three wells of
each dried amplification indicator solution were resuspended with
40 μL of deionized water and spectrophotometric analyses were
performed. After each measurement, the plate was sealed again (to
prevent hydration of the dried solutions in the other wells) and kept
in the dark at room temperature. The absorption spectra analyses were
performed using the POLARstar Omega microplate reader with Omega Data
analysis software. Absorbance in the range of 400–700 nm was
recorded at 2 nm intervals. Blank solutions (20 mM Tris-HCl buffer
with 30 mM trehalose) were also loaded at time 0 h, desiccated after
the first measurement, and treated as the rest of the solutions. The
measured spectral absorbance from these control solutions was subtracted
at each time point from the plotted data (Figure S13).
RT-LAMP Amplification of HCV RNA in-Tube
The purified
HCV RNA described above was used for in-tube RT-LAMP amplification.
The RT-LAMPmix contained the following: 20 μL of RM, 2 μL
of EM, 2 μL of SYTO 9 Stain from a 40 μM stock, 4 μL
of LAMP primer mixture (20 μM BIP/FIP, 10 μM LB/LF, and
2.5 μM B3/F3), 1 μL of SUPERase In RNase Inhibitor (20
U/μL), EBT solutions of various concentrations and with various
amounts of RNA template solution, and enough nuclease-free water to
bring the volume to 40 μL. The solution was loaded into 0.2
mL PCR tubes and heated at 63 °C for 50 min and 85 °C for
5 min (heat inactivation) on an Eppendorf Mastercycler Gradient PCR
Themal Cycler.
Spectrophotometric Analysis for Positive
and Negative RT-LAMP
Reactions
Fifty microliters of positive and negative RT-LAMP
reaction solutions containing 0.7 mM of EBT, HNB, and calmagite dyes
was transferred to a Costar Clear Polystyrene 96-Well Plates, the
plate was sealed with a Corning Universal Optical Microplate Sealing
Tape and then used for spectrophotometric analysis. An absorption
spectra analysis was performed using the POLARstar Omega microplate
reader with Omega Data analysis software. The instrument was first
set to zero at 700 nm for distilled water, and absorbance in the range
of 400–700 nm was recorded at 2 nm intervals. Transmittance
was calculated from absorbance values using the following equation: T = 10(2–.
Prediction
of RGB Values
Predicted RGB values for a
positive and negative LAMP amplification reaction containing EBT were
calculated as follows: (i) The spectral response curves for a Exmor
R CMOS image sensor were available only in a graphical format, so
data was extracted using Plot Digitizer (ver. 2.6.6) and new plots
were generated. (ii) The area under the curve for each of the three
color channel spectra was normalized (selecting 1000 arbitrary values
under each curve). Uniform white-balanced light source was assumed.
(iii) Convolution of the spectral transmittance spectral profiles
of the indicator dye for a positive and a negative LAMP reaction solution
(experimentally obtained) with the normalized spectral responses from
the Exmor R CMOS image sensor was performed. We ignored the light
scattering caused by pyrophosphate release during the amplification
reaction. As a result, six curves were generated (a positive and negative
for each of the three color channels). (iv) The area under each curve
was calculated and its square root taken, providing the predicted
RGB values for positive and negative RT-LAMP reaction solutions in
the presence of EBT at this particular concentration.
dLAMP Amplification
of Phage λDNA on Multivolume Rotational
SlipChip Devices
To amplify λ phage DNA using dLAMP
method, the LAMPmix contained the following: 20 μL of RM, 2
μL of EM, 2 μL of SYTO 9 Stain from 40 μM stock,
4 μL of primer mixture (20 μM BIP/FIP, 10 μM LB/LF,
and 2.5 μM B3/F3), 2 μL of BSA (20 mg/mL), various amounts
of DNA template solution, 4.7 μL of 6 mM EBT dye (0.7 mM final
concentration), and enough nuclease-free water to bring the volume
to 40 μL. The solution was loaded onto a multivolume rotational
SlipChip device and heated at 63 °C for 50 min on flat block
PCR machine (Eppendorf Mastercycler). Five minutes of heating at 85
°C was used to stop the reaction.
Real-Time dRT-LAMP of HCV
RNA on Two-Step SlipChip Devices
To amplify HCV viral RNA
using dRT-LAMP method on house-built real-time
instrument, the RT-LAMPmix contained the following: 20 μL of
RM, 2 μL of EM, 2 μL of SYTO 9 Stain from 40 μM
stock, 4 μL of primer mixture (20 μM BIP/FIP, 10 μM
LB/LF, and 2.5 μM B3/F3), 2 μL of BSA (20 mg/mL), 1 μL
of SUPERase In RNAase inhibitor, various amounts of RNA template solution,
and enough nuclease-free water to bring the volume to 40 μL.
The solution was loaded into the 5 nL wells of two-step SlipChip devices.
Other set of wells (9.5 nL) were loaded with 2.4 mM solution of EBT
solution (1.57 mM final concentration). SlipChips were heated at 63
°C for 50 min on a house-built real-time instrument; reactions
were stopped by heating to 85 °C for 5 min.
House-Built
Real-Time Instrument Imaging
Experiments
were performed on a Bio-Rad PTC-200 thermocycler with a custom machined
block. The block contains a flat 3 × 3 in.2 portion
onto which the devices are placed ensuring optimal thermal contact.
The excitation light source used was a Philips Luxeon S (LXS8-PW30)
1315 lm LED module with a Semrock filter (FF02-475). Image acquisition
was performed with a VX-29MG camera and a Zeiss Macro Planar T F2-100mm
lens. A Semrock filter (FF01-540) was used as an emission filter.
Images acquired were analyzed using LabVIEW software.
House-Built
Real-Time Instrument Data Analysis
Fluorescent
images were analyzed using self-developed Labview software. The data
were analyzed by first creating a binary mask that defined the location
of each reaction volume within the image. The masked spots were then
overlaid on the stack of images collected over the course of the experiment
and the average intensity of each individual masked spot was tracked
over the course of the stack. Background subtraction of the real-time
trace was performed by creating a least mean square fit of each individual
trace. Threshold was then manually set at the half height of the averaged
maximum intensity, and the time-to-positive of each reaction was then
determined as the point at which the real-time curve crossed the defined
threshold.
Bright-Field Image Acquisition
A
mobile phone was used
to capture the readout under standard fluorescent light, using the
camera’s default autofocus and autoexposure settings. Photographs
of the 96-well plate were also taken using alternate commercial cell
phones and under different lighting conditions (Figure and Figure S3). Stereoscope imaging was done using Leica MZ Fl III stereoscope
with a PLAN 0.5× lens. The stereoscope was equipped with a Diagnostic
Instruments color mosaic model 11.2 megapixel camera and images were
acquired using Spot imaging software. An automatic white-balance adjustment
was done for each image using Spot software. Multiple images were
acquired to capture all wells in the device, and assembled to form
a complete image of the device to compare with the image acquired
from the cell phone camera by using the freeware Image Composite Editor
(ver. 2.0).
Bright Field Image Processing and Data Analysis
Images
acquired with cell phone and stereoscope were processed using open
source ImageJ software (ver.1.49) according to the standard procedure.
Briefly: (i) white balance was corrected as needed, (ii) color channels
of the original image were split, (iii) one channel was divided by
a second channel (e.g., green channel divided by
the red channel in the G/R approach) to derive a ratiometric image,
and (iv) automatic thresholding was applied to make a binary (black
and white) image. Semiautomatic counting on the two-step Slipchip
images was accomplished using a freeware Fiji image processing. Acquired
bright field images for the multivolume rotational SlipChips were
counted manually.
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