Palm-Sized Device for Point-of-Care Ebola Detection - Analytical

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Palm-sized device for point-of-care Ebola detection Christian D. Ahrberg, Andreas Manz, and Pavel Neuzil Anal. Chem., Just Accepted Manuscript • DOI: 10.1021/acs.analchem.6b00278 • Publication Date (Web): 11 Apr 2016 Downloaded from http://pubs.acs.org on April 12, 2016

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Analytical Chemistry

Palm-sized device for point-of-care Ebola detection Christian D. Ahrberg,1 Andreas Manz,1 and Pavel Neuzil2,3* 1

KIST Europe, Campus E7.1, 66123 Saarbrücken

2

Northwestern Polytechnical University (NPU), School of Mechanical Engineering, Department of Microsystem Engineering, 127 West Youyi Road, Xi'an, Shaanxi, 710072, P. R. China

3

Brno University of Technology, Antonínská 548/1, Brno 601 90, Czech Republic

*Corresponding author: [email protected]

Abstract We show the utilization of a recently developed cellphone-sized real-time polymerase chain reaction (PCR) device to detect Ebola virus RNA using single-step reverse transcription PCR (RT-PCR). The device was shown to concurrently perform four PCRs, each with a sample volume of 100 nL: one positive control with both Ebola and GAPDH RNA and one negative control. The last two positions were used to measure the GAPDH and the Ebola content of a sample. A comparison of threshold cycles (CT) from the two samples provided relative quantification. The entire process, which consisted of reverse transcription, PCR amplification, and melting curve analysis (MCA), was conducted in less than 37 min. The next step will be integration with a sample preparation unit to form an integrated sample-to-answer system for point-of-care infectious disease diagnostics.

Introduction The recent epidemic of Ebola in West Africa was one of the largest and most complex in the history of this virus1. Despite DNA sequencing2, the origin of this virus remains a mystery.

ACS Paragon Plus Environment


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Many infectious diseases native to this particular region of the world present with similar symptoms as Ebola. This greatly exacerbates the difficulties in patient management and treatment decisions. Some reports found more than half of suspected Ebola cases in a treatment facility eventually had an alternate diagnosis1. A rapid, sensitive, and accurate detection method is crucial to verify Ebola infection and make timely quarantine and treatment decisions. Both false negative as well as false positive test results are highly undesirable and have a potentially damaging impact on the patient. Reverse transcription polymerase chain reaction (RT-PCR) method is clinically proven to be the diagnostic test of choice.3 The world health organization (WHO) currently suggests the diagnosis of Ebola either using RT-PCR or antigen tests.4 Laboratories capable of safe handling of potentially highly contagious samples need to fulfill biosafety hazard level 3 or 4. However, their numbers and their access to patient samples are limited, especially in remote locations. Logistics are complicated as the samples have to be transferred triple-packed in cooled containers, often for long distances. Mobile laboratories were specifically designed to solve this problem by testing samples in remote affected locations and, thus, contain the spread of infectious diseases5. The modular laboratories constructed in a sea container can be helicoptered into practically any places including jungle6 solve the problem only partially, as their numbers are also limited; thus, they have to be placed in a few centralized locations, with clinical samples shipped to them. Even though there are some solutions to help cope with the situation, such as shipping samples in dried form7 and antigen–antibody based point-of-care (POC) tests suitable for remote locations,8,9 a robust Ebola diagnostics method suitable for remote locations is still a challenge.


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To tackle this problem, a variety of solutions have been suggested, starting from ELISA tests, which could be run on oral swabs, thus making sample collection simpler.10 More recently, a portable biosensor based on surface acoustic waves was suggested that can detect the virus in less than 10 min.11 Furthermore, Pardee et al.12 presented synthetic gene networks in a recent paper; with the aid of these freeze-dried networks, they were able to detect the virus with a simple optical readout. However, until these new methods and devices are available and tested, the WHO focuses on providing a better access to PCR as a short-term solution.13 The worst Ebola disease outbreak to date is over. Affected countries are now facing the highest number of Ebola survivors in history. Patients with negative results of the RT-PCR test were released from hospitals and treatment units as healthy,14 although many reported health problems later on. Among the most common were joint pain, eye problems, severe fatigue, and headaches as well as mental health problems and depression.15 These maladies are often described as postEbola virus disease syndrome and very little is known about their origin. Nevertheless, Ebola virus RNA in the semen and eye-liquid of survivors was recently discovered, so it is assumed that the virus might be harbored in immunologically privileged sites like joint cartilage and gonads.16 More studies of Ebola virus presence using readily available and robust techniques such as RTPCR to understand its behavioral patterns are urgently needed. Recently, a handheld, real-time PCR device was presented.17 In this contribution, we show how this device can be used for RT-PCR diagnostic testing for Ebola ribonucleic acid (RNA) (Figure 1). This simple device performs a quantitative analysis of patient samples to determine viral load and, hence, the effectiveness of the Ebola treatment. Such devices are urgently required in remote locations during epidemic outbreaks. Here we demonstrate this device to quickly identify the presence of Ebola virus RNA in a small sample volume. Suspected patients may or may not



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exhibit Ebola symptoms. The device is demonstrated as capable of detecting minute quantities of RNA from Ebola or any other RNA-linked virus by replacement of cDNA-specific oligonucleotides (primers) used for PCR. This real-time PCR device is 100 mm × 60 mm × 33 mm and weighs less than 80 g. It is powered by an external 12 V power supply provided by a car battery or a charger. The device is capable of concurrently processing four 100 nL samples, designed for positive and negative control as well as two actual samples. Samples placed on a hydrophobically coated disposable glass microscope cover slip are covered with mineral oil (1 µL) to form a virtual reaction chamber (VRC).18,19 Only the disposable glass microscope cover slip is in contact with the sample. New glass for every four samples guarantees no run-to-run cross contamination. A micro-machined silicon heater under the VRC provides heating of the samples through the glass, achieving heating rates ≈20 °C/s while a rate of ≈− 20 °C/s was accomplished by passive cooling. We integrated a miniaturized fluorescence housing to monitor the progress of PCR in real-time in each VRC. Blue light was emitted by light emitting diodes (LEDs) to illuminate the samples. The emitted fluorescence was processed by a fluorescein isothiocyanate (FITC) filter set. The fluorescence amplitude was detected by photodiodes. The LED light was modulated and, together with photocurrent induced in the photodiodes, the signal was processed using an embedded lockin amplifier, which greatly improved the signal-to-noise ratio (SNR). Viral loads are usually determined by comparison with a housekeeping gene. Human transcript glyceraldehyde-3-phosphate dehydrogenase (GAPDH) has constant expression at moderate levels inside human cells20 making it a popular choice as a housekeeping gene. Out of four samples


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processed by the device, two were used as controls. One contained RNAs from both Ebola virus and the GAPDH gene as the positive control while a no-template control (NTC) acted as the negative control. The two remaining locations were utilized to measure (1) the number of copies of Ebola RNA, and (2) GAPDH RNA of a simulated patient sample. A relative quantification of Ebola to GAPDH expression was used to determine the viral load in the simulated patient sample.

Materials and Methods Synthesis of RNA template We added 10 µL of aqueous solution containing 5×10−5 ng/µL frame-shifted cDNA of Ebola virus RNA (ATG:biosynthetics GmbH, Germany) to a solution consisting of 10 µL of 5× Transcription Buffer and 1.5 µL of T3 RNA polymerase (20 U/µL) (both Thermo Fisher Scientific, USA) to synthesize RNA templates for the reverse transcription PCR. Furthermore, we added 10 µL of a nucleotide triphosphate (dNTP) solution containing 10 mM each of the four nucleotides: adenosine triphosphate (ATP), guanosine triphosphate (GTP), cytidine triphosphate (CTP), and uridine triphosphate (UTP) (all Thermo Fisher Scientific, USA) and 1.25 µL of RiboLock RNAse Inhibitor (40 U/µL) (Thermo Fisher Scientific, USA). The solution volume was adjusted to 50 µL by adding deionized (DI) water prepared by a Progard® T3 pre-treatment pack with reverse osmoses-based Milli-Q® direct water purification system (Merck KGaA, Germany) and incubated at 37 °C for 2 h. Afterwards, we added 1 µL of HL-ds DNAse and 5 µL of 10× Reaction Buffer (both ArcticZymes, Norway) to remove the complementary deoxyribonucleic acid (cDNA) template.



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The mixture was incubated at 37°C for 10 min followed by a second incubation step at 58 °C for 5 min to deactivate the DNAse. Complete removal of cDNA was verified using standard quantitative PCR (qPCR) without a reverse transcription step. RNA for GAPDH was prepared in a similar manner, starting with a synthetic cDNA (ATG: biosynthetics GmbH, Germany) solution with a concentration of 5×10−6 ng/µL. For the GAPDH/Ebola control reactions, both RNAs were prepared in the same vial starting from the mentioned cDNA stock solutions.

Reverse Transcription PCR The prepared RNA samples were analyzed by reverse transcription qPCR. For this 5 µL of 4× One-Step Grand Master Mix (TATAA), 1 µL of one-step reverse transcriptase mix, and 1 µL of 20×

EvaGreen

(both

TATAA,

Sweden)

in

DI

water

were

prepared.

Forward

(GGTCAGTTTCTATCCTTTGC) and reverse (CATGTGTCCAACTGATTGCC) primers (Eurofines MWG Operon, Germany) for cDNA of Ebola virus RNA21 were added to a final concentration of 1.8 µM. Lastly, RNA template was added and the entire solution volume adjusted to 20 µL by adding DI water. For the one-step reverse transcription qPCR, a 5 min reverse transcription step at 50 °C was carried out first, followed by a hot start at 95°C for 30 s. Forty consecutive cycles consisted of a 5 s denaturation at 95 °C, a 10 s annealing conducted at 55 °C, and a 30 s extension at 60 °C. Finally, an MCA was performed to identify the products of the reaction to make sure no nonspecific PCR amplification took place. We

used

forward

(AGCCCACATCGCTCAGACAC)

and

reverse

(CGAGCAAGACGTTCAGTCCT) primers by (Eurofines MWG Operon, Germany) to amplify the cDNA of GAPDH gene in a final concentration of 1.8 µM. The concentrations of both


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primers for co-amplification of cDNA of Ebola virus and GAPDH gene were also used in final concentrations of 1.8 µM for each primer. We performed control qPCR experiment in 20 µL glass capillaries using the LightCycler (Roche, Germany). Experiments on the handheld device were carried out in the form of a virtual reaction chamber (VRC). The sample volume was 100 nL covered with 2 µL of M5904 light mineral oil from Sigma Aldrich, Germany. Both samples as well as the oil were pipetted onto a hydrophobically coated disposable glass microscope cover slip using a micropipette.

Results During 40 cycles of PCR, the fluorescence amplitudes were extracted at the end of the extension steps and stored in an internal device memory. Once the PCR was completed, the MCA was performed. These results are displayed as Figure 1. The overall analysis time for reverse transcription (5 min), amplification (30 min), and MCA (90 s) required less than 37 min. The PCR results can be also normalized and plotted as function of cycle number (Figure 2). Intersects with an arbitrary threshold of 0.1 were used to extract CT values resulting in 21.5 cycle for the positive control of Ebola RNA and GAPDH RNA, 27.4 cycle for the test sample with Ebola RNA, and 28.1 cycle for the test sample containing GAPDH RNA. As expected, the no-template control did not show any amplification, verifying that no contamination of the NTC occurred. The difference in CT for PCR amplification between samples with Ebola RNA and GAPDH gene was ∆CT = 1.3 cycle. We can conclude that for every RNA copy of the GAPDH gene in the starting sample there exist statistically 2.5 copies of Ebola RNA ((1+E)∆CT). The PCR amplification efficiency (E) was assumed to be equal for both cDNAs. Each experiment was conducted three times (S1 in supplementary data). Samples containing both RNAs (viral RNA



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and GAPDH RNA) exhibited values of CT of (21.5 ± 0.4) cycle, samples with only GAPDH primers had a CT of (28.1 ± 0.2) cycle and samples with only Ebola primers (27.4 ± 0.5) cycle, all (mean ± standard deviation), respectively. The extracted melting curves (Figure 3A) and their negative derivatives (Figure 3B) show the purity of the RT-PCR product. The melting temperature (TM) of Ebola virus and GAPDH RNA amplicons were (78.58 ± 0.04) °C and (83.08 ± 0.04) °C (fitted value and standard error), respectively. Extracted TM values correspond to the temperatures extracted from LightCycler (78.2 °C for Ebola and 82.7 °C for GAPDH). The positive control containing Ebola RNA as well as GAPDH DNA amplicons produced two distinct steps in the melting curve, resulting in two peaks after derivation. The first peak TM is (78.72 ± 0.05) °C (fitted value and standard error) and (83.06 ± 0.05) °C (fitted value and standard error), corresponding, respectively, to the MT of Ebola RNA and GAPDH DNA amplicons. Each experiment was performed three times (MCA results are shown as S2 and S3 in supplementary data) and we extracted values of TM. Repetitions of the positive control containing primers for both Ebola and GAPDH gave TM of (78.82 ± 0.13) °C for Ebola and (82.15 ± 0.26) °C for GAPDH. Samples only containing the GAPDH primers resulted in a TM of (83.37 ± 0.75) °C in the repetitions and samples with only Ebola primers gave TM of (77.12 ± 0.41) °C, all (mean ± standard deviation). Standard deviation of the extracted values of TM is probably caused by differences in the samples’ positions above the silicon micro-machined heater. Nevertheless, the standard deviation was rather small and we were able to clearly determine each amplicon as well as its purity.


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Discussion Here we show the performance of a handheld, real-time PCR device capability of performing RTPCR to detect RNA of an Ebola virus with a housekeeping gene for quantification and MCA to check the RT-PCR specificity. The total time for this analysis was less than 37 min, including reverse transcription, amplification, and MCA. This time could be shortened by the employment of different polymerases or optimization of the system, such as increasing the DC voltage of the power supply. The device processed four samples concurrently, which is sufficient for POC applications.22 One sample is suspected of containing viral RNA, the second sample contains a housekeeping gene, such as the RNA for GAPDH, the third sample combines both RNAs (positive control), and the last sample is the negative control. Once the positive control is confirmed by multiplexing in the same VRCs of both Ebola RNA and GAPDH reference RNA, the relative viral load of the target RNA with respect to the reference RNA can be estimated. This option could be especially useful for determining viral loads required for monitoring the post-Ebola disease syndrome. We estimated that the Ebola RNA was 2.5 times more prevalent than the GAPDH RNA reference gene. Therefore, we used a 10 times higher amount of template for Ebola RNA than for GAPDH RNA, so one might expect a corresponding difference in CT of the PCRs. We can hypothesize that there might be two main reasons for this discrepancy. First, we assumed that the amplification efficiency of both amplicons is the same as well as both reserve transcriptions. We performed standard PCR curves for both cDNAs using the Roche LightCycler. Amplification efficiency of Ebola virus cDNA was close to unity (E = 0.99), whereas the efficiency of GAPDH gene cDNA was only 0.89. However, these differences in PCR efficiencies cannot explain the



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significantly lower than expected CT. We suspect that there were also differences in efficiency in the reverse transcription steps.

Conclusion Here we demonstrate a smartphone-sized device capable of detecting RNA of an Ebola virus and comparing its viral load to a housekeeping gene in less than 37 min using single-step real-time RT-PCR, including MCA. TM of both amplicons confirmed PCR specificity. The device is battery-powered, with a size of only 100 mm × 60 mm × 33 mm and weighing less than 80 g. The system can be further integrated with a previously developed sample preparation module23,24 into an integrated sample-to-answer system suitable for decentralized laboratories. Employment of simple, portable, and easy-to-use systems would help medical staff tackle the next Ebola virus or any other infectious disease outbreak. Due to its simplicity and small size, it could be distributed in large numbers into areas with infectious disease outbreaks or even just suspected outbreaks. In future work, real patient samples should be tested. For this, blood samples (≈2 µL) could be taken from patients using a pinprick and analyzed directly by PCR.25 Recent advances in DNA and RNA polymerases might provide opportunities for direct reverse transcription PCR from these samples, without any prior purification steps.26,27 References: (1) O'Shea, M. K.; Clay, K. A.; Craig, D. G.; Matthews, S. W.; Kao, R. L. C.; Fletcher, T. E.; Bailey, M. S.; Hutley, E. Clinical Infectious Diseases 2015, 61, 795-798. (2) Lam, T. T.-Y.; Zhu, H.; Chong, Y. L.; Holmes, E. C.; Guan, Y. Journal of Virology 2015, 89, 10130-10132. (3) Drosten, C.; Gottig, S.; Schilling, S.; Asper, M.; Panning, M.; Schmitz, H.; Gunther, S. Journal of Clinical Microbiology 2002, 40, 2323-2330. (4) WHO. 2015. (5) Pas, S. D.; Reusken, C.; Haagmans, B. L.; Koopmans, M. P. Journal of Clinical Virology 2015, 70, S3-S3. (6) Marx, V. Nat Meth 2015, 12, 393-397. (7) Sarkar, S.; Singh, M. P.; Ratho, R. K. Lancet Infectious Diseases 2015, 15, 1005-1005. (8) Bhadelia, N. Lancet 2015, 386, 833-835.


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(9) Broadhurst, M. J.; Kelly, J. D.; Miller, A.; Semper, A.; Bailey, D.; Groppelli, E.; Simpson, A.; Brooks, T.; Hula, S.; Nyoni, W.; Sankoh, A. B.; Kanu, S.; Jalloh, A.; Ton, Q.; Sarchet, N.; George, P.; Perkins, M. D.; Wonderly, B.; Murray, M.; Pollock, N. R. Lancet 2015, 386, 867-874. (10) Formenty, P.; Leroy, E. M.; Epelboin, A.; Libama, F.; Lenzi, M.; Sudeck, H.; Yaba, P.; Allarangar, Y.; Boumandouki, P.; Nkounkou, V. B.; Drosten, C.; Grolla, A.; Feldmann, H.; Roth, C. Clinical Infectious Diseases 2006, 42, 1521-1526. (11) Baca, J.; Severns, V.; Lovato, D.; Branch, D.; Larson, R. Sensors 2015, 15, 8605. (12) Pardee, K.; Green, Alexander A.; Ferrante, T.; Cameron, D. E.; DaleyKeyser, A.; Yin, P.; Collins, James J. Cell 2014, 159, 940-954. (13) Vogel, G. Science 2014, 345, 1549-1550. (14) Qureshi, A. I.; Chughtai, M.; Loua, T. O.; Pe Kolie, J.; Camara, H. F. S.; Ishfaq, M. F.; N'Dour, C. T.; Beavogui, K. Clinical Infectious Diseases 2015, 61, 1035-1042. (15) Gulland, A. Bmj-British Medical Journal 2015, 351. (16) Carod-Artal, F. J. Expert Review of Anti-infective Therapy 2015, 13, 1185-1187. (17) Ahrberg, C. D.; Ilic, B. R.; Manz, A.; Neuzil, P. Lab on a Chip 2016, 16, 586-592. (18) Guttenberg, Z.; Muller, H.; Habermuller, H.; Geisbauer, A.; Pipper, J.; Felbel, J.; Kielpinski, M.; Scriba, J.; Wixforth, A. Lab on a Chip 2005, 5, 308-317. (19) Neuzil, P.; Pipper, J.; Hsieh, T. M. Molecular Biosystems 2006, 2, 292-298. (20) Tan, S.; Carr, C.; Yeoh, K.; Schofield, C.; Davies, K.; Clarke, K. Mol Biol Rep 2012, 39, 4857-4867. (21) Towner, J. S.; Rollin, P. E.; Bausch, D. G.; Sanchez, A.; Crary, S. M.; Vincent, M.; Lee, W. F.; Spiropoulou, C. F.; Ksiazek, T. G.; Lukwiya, M.; Kaducu, F.; Downing, R.; Nichol, S. T. Journal of Virology 2004, 78, 4330-4341. (22) Sharma, S.; Zapatero-Rodriguez, J.; Estrela, P.; O'Kennedy, R. Biosensors 2015, 5, 577-601. (23) Pipper, J.; Inoue, M.; Ng, L. F. P.; Neuzil, P.; Zhang, Y.; Novak, L. Nature Medicine 2007, 13, 12591263. (24) Pipper, J.; Zhang, Y.; Neuzil, P.; Hsieh, T.-M. Angewandte Chemie-International Edition 2008, 47, 3900-3904. (25) Mercier, B.; Gaucher, C.; Feugeas, O.; Mazurier, C. Nucleic Acids Research 1990, 18, 5908-5909. (26) Kranaster, R.; Drum, M.; Engel, N.; Weidmann, M.; Hufert, F. T.; Marx, A. Biotechnology Journal 2010, 5, 224-231. (27) Kranaster , R.; Marx, A. ChemBioChem 2010, 11, 2077-2084.



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Figure 1: (A) Smartphone-sized real-time PCR capable of four reactions at a time, demonstrated here to detect Ebola virus RNA, followed by (B) MCA, and (C) its derivation. The system was powered by an external 12 V DC power supply connected by a 2-wire cable (see arrow). The PCR unit can be optionally connected to a PC via USB interface to upload PCR protocols and transfer data for further analysis if needed.


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~ 30 min 1.00

Normalized Fluorescence

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GAPDH+Ebola GAPDH EBOLA NTC

0.75

0.50

0.25

0.00 0

5

10

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20

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30

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40

Cycle Number

Figure 2: Normalized PCR amplification curves for the positive control containing Ebola RNA and GAPDH gene (black squares), a sample with GAPDH RNA (red circles), Ebola RNA (green upward triangles), and the no-template control (NTC) (blue downward triangles). An arbitrary threshold was set at 0.1 (magenta dashed-line), resulting in a CT of 21.2 cycle for the sample with both RNAs (GAPDH gene + Ebola virus), CT of 28.1 cycle for sample with GAPDH RNA only, and CT 27.3 cycle for the sample with Ebola RNA.


GAPDH + Ebola GAPDH Ebola NTC

1.00

0.75

0.50

0.25

Derivation -dF/dT (AU/K)

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Normalized Fluorescence


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GAPDH + Ebola GAPDH Ebola NTC

0.4

0.3

0.2

0.1

0.0

0.00 70

75

80

85

90

70

75

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90

o

o

Temperature ( C)

Temperature ( C)

Figure 3: (left) Melting curves recorded after reverse transcription and 40 cycles of PCR amplification for samples containing GAPDH RNA (red circles), Ebola RNA (green upward triangles), and a positive control containing both RNAs (black squares). The no-template control (NTC) sample (blue downwards triangles) does not exhibit nonlinearity in the melting curve, proving the absence of amplified DNA. (right) The first negative derivative of fluorescence F with respect to temperature T extracted from recorded melting curves. The samples with Ebola RNA (green upward triangles) and GAPDH RNA (red circles) each show a single individual peak, indicating TM of (78.58 ± 0.04) °C and (83.08 ± 0.04) °C (fitted value and standard error), respectively. The positive control with both viral RNA and GAPDH RNA (black squares) exhibits two peaks at (78.72 ± 0.05) °C and (83.06 ± 0.05) °C (fitted value and standard error), respectively. This result demonstrates the successful amplification of both targets with nearly identical TM as the individual samples. The no-template control (NTC) (blue downwards triangles) showed no peaks at the MCA confirming no sample-to-sample contamination.


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(A) Smartphone-sized real-time PCR capable of four reactions at a time, demonstrated here to detect Ebola virus RNA, followed by (B) MCA, and (C) its derivation. The system was powered by an external 12 V DC power supply connected by a 2-wire cable (see arrow). The PCR unit can be optionally connected to a PC via USB interface to upload PCR protocols and transfer data for further analysis, if needed. 416x190mm (150 x 150 DPI)



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284x199mm (300 x 300 DPI)


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277x101mm (150 x 150 DPI)



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Palm-Sized Device for Point-of-Care Ebola Detection - Analytical

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