Archived content. See more recent content: Application notes & reviews
Authors: Houssin, Timothée; Elvesys – Innovation Center; Ecole Normale Supérieure-PSL Research University // Cramer, Jérémy; Cherry Biotech; Ecole Normale Supérieure-PSL Research University // Grojsman, Rébecca; Elvesys – Innovation Center // Bellahsene, Lyes; Elvesys – Innovation Center // Colas, Guillaume; Elvesys – Innovation Center // Moulet, Hélène; Elvesys – Innovation Center // Minnella, Walter; Elvesys – Innovation Center // Pannetier, Christophe ; Episteme Research and Consulting // Le Berre, Maël; Elvesys – Innovation Center // Plecis, Adrien; Elvesys – Innovation Center // Chen, Yong; Ecole Normale Supérieure-PSL Research University
To control future infectious disease outbreaks, like the 2014 Ebola epidemic, it is necessary to develop ultrafast molecular assays enabling rapid and sensitive diagnoses. To that end, several ultrafast real-time PCR systems have been previously developed, but they present issues that hinder their wide adoption, notably regarding their sensitivity and detection volume. An ultrafast, sensitive and large-volume real-time PCR system based on microfluidic thermalization is presented herein. The method is based on the circulation of pre-heated liquids in a microfluidic chip that thermalize the PCR chamber by diffusion and ultrafast flow switches. The system can achieve up to 30 real-time PCR cycles in around 2 minutes, which makes it the fastest PCR thermalization system for regular sample volume to the best of our knowledge. After biochemical optimization, anthrax and Ebola simulating agents could be detected in a 7-minute real-time PCR and a 7.5-minute reverse transcription real-time PCR (for 30 PCR cycles), respectively 6.4 and 7.2 times faster than with an off-the-shelf apparatus, while conserving real-time PCR sample volume, efficiency, selectivity and sensitivity. The highspeed thermalization also enabled us to perform sharp melting curve analyses in only 20s and to discriminate amplicons of different lengths by rapid real-time PCR. This real-time PCR microfluidic thermalization system is cost-effective, versatile and can be then further developed for point-of-care, multiplexed, ultrafast and highly sensitive molecular diagnoses of bacterial and viral diseases.
The 2014 Ebola outbreaks in West Africa demonstrated that fast, specific and sensitive diagnostic tools for effectively containing widespread epidemics are still lacking1. Indeed, rapid detection of viral infection currently relies mostly on immunoassays, such as the detection of antibodies specific to a viral infections or viral antigens developed on the surface of infected cells using the enzyme-linked immunosorbent assay (ELISA) in a strip format. This approach has been recently approved by the World Health Organization (WHO) for the detection of Ebola infection in 15-25 minutes2. Nevertheless, these types of assays still present several drawbacks: first, they are several orders of magnitude less sensitive than molecular assays and are thus not recommended for early diagnosis3,4. Furthermore, they may generate false positive results due to cross reactivity of other organisms that present the same antigen as the virus or elicit similar antibody responses5. In the case of the recent Ebola epidemic, this was particularly likely since Africans can present antibodies to pathogens like those causing malaria, tuberculosis and hepatitis, which obstruct results for Ebola detection, especially with field real samples1. For microbiological diagnoses (i.e. detection of bacteria, virus, fungi and parasites), the most reliable and sensitive methods rely on the real-time polymerase chain reaction (rtPCR) for DNA detection (e.g. for bacteria detection) and the reverse transcription real-time polymerase chain reaction (RT-rtPCR) for RNA analyses (e.g. for viral RNA detection)6,7. Nevertheless, these techniques typically last about one to three hours8,9 and faster systems present drawbacks that will be discussed subsequently. The highspeed thermalization also enabled us to perform sharp melting curve analyses in only 20s and to discriminate amplicons of different lengths by rapid real-time PCR. This real-time PCR microfluidic thermalization system is cost-effective, versatile and can be then further developed for point-of-care, multiplexed, ultrafast and highly sensitive molecular diagnoses of bacterial and viral diseases. Thus, the whole RT-rtPCR test for the diagnosis of the Ebola virus infection takes two to six hours10. Though this duration is a significant improvement over conventional culture-based microbiological assays, a faster diagnosis of epidemic diseases would enable healthcare providers to guide more efficiently the clinical decision for the improvement of treatment outcomes10 and save more lives1, especially when a large number of patients needs to be rapidly diagnosed and health care centers are overwhelmed11.
The ideal diagnostic test must therefore combine the advantage of ELISA and rtPCR/RT-rtPCR for, respectively, faster detection and a more sensitive diagnosis. The WHO is therefore still looking for rapid assays enabling molecular diagnoses in less than 30 minutes to contain more efficiently Ebola virus outbreaks and more generally, other similar epidemics10. Regarding molecular amplification processes, new Droplet-rtPCR systems can be more sensitive than regular single-phase methods but assays also last longer (around 50% longer to ensure no temperature gradient through the droplet reservoir). Isothermal molecular amplification processes such as LAMP, NASBA, or RCA12 are particularly interesting for pointof- care (POC) applications, but they remain relatively long (30-40 min)13,14 and less flexible. Moreover, non-isothermal rtPCR relies on temperature cycles that allow matchless control of hybridization of primers to their cognate targets, so that it is essentially limited by thermalization ramps. In this regard, it is therefore possible to achieve ultrafast and non-isothermal rtPCR by accelerating thermalization speeds. Previously, several ultrafast PCR and rtPCR systems (30 cycles in 2-15 min.) have been reported. For example, Moschou et al.15 and Fuchiwaki et al.16 developed respectively flow-through ultra-rapid PCR and rtPCR devices by displacing the sample between different temperature zones. In a similar manner, but without a fixed number of cycles, Brunklaus et al. used an oscillatory flow to perform ultrafast PCR17. Alternatively, by using a fixed PCR sample chamber exposed to temperature changes, i.e. static methods, Neuzil et al.18 and Kim et al.19 developed ultrafast rtPCR systems for nanoliter and biphasic samples using respectively thin films heaters and infra-red laser heating. Besides, Wheeler et al.20 and Terazono et al.21 used a liquid-based thermalization system method, close to the one presented herein, to demonstrate respectively ultrafast PCR and rtPCR based detection. Among industrial systems, BJS Technology recently commercialized the ultrafast XXpress rtPCR system, which can achieve 40 rtPCR cycles in 8-10 minutes22. Samsung developed the GenSpector systems based also on the Joule effect23 with silicon heater that can detect the sacbrood virus in 22 minutes in a 1 μL sample24 with off-chip RNA reverse transcription (RT). Analytik Jena commercializes the qTower which enables analyses in around 25 minutes with a volume range of 5 to 20 μL25. NanoBioSys developed an ultrafast rtPCR system which can reach 30 cycles in 15 minutes from a15 μL sample with a conserved efficiency and sensibility but off-chip RT as well26. Cepheid proposes the GeneXpert system that can carry out automatically sample preparation and multiplex rtPCR in approximately one hour27. All these systems showed interesting results for ultrafast rtPCR but present also disadvantages that limit their practical applications.
First, regarding sample volume, large systems present high thermal inertia and potential temperature inhomogeneity. Indeed, temperature differences of up to +/- 65°C could be observed during the transient time with conventional rtPCR systems using multi-well plates28 (typical volumes of 20-25 μL). Whereas, it is important to maintain a good thermal homogeneity throughout the reaction to ensure the best rtPCR efficiency29–32 and specificity33. For the ultrafast PCR and rtPCR systems listed above, the use of smaller sample volumes thus facilitates faster thermalization and a better temperature homogeneity but decreases intrinsically the system sensitivity (or limit of detection, i.e. the minimum detectable copy number). Indeed, low-volume rtPCR chambers will more likely yield no amplifications due to the initial absence of DNA targets in low-concentration samples used in sensitive detections (e.g. from saliva and ocular samples34) caused by the stochastic variation of sample copy number with Poisson distribution35,36. Furthermore, a larger reaction chamber also enables the integration of complementary operations for POC PCR analysis in the same PCR chamber34: e.g. DNA solid phase extraction through alumina nano-membranes37 or dry-stored PCR reagents in paraffin38,39. Regarding flow-through systems, they present the disadvantage of not being flexible about the number of PCR cycles, which is fixed by the device design. This drawback can be avoided by using an oscillatory flow design but, to our knowledge, this type of system has not been used for real-time amplification detection. Noteworthy, flow through systems can be used for melting curve analyses like static rt-PCR systems as shown by Crews et al.40. Finally, both flow-through and oscillatory flow systems complicate the straightforward adjustment of PCR phase times and sample volumes. Lastly, for all the above-mentioned systems (except for the GeneXpert), the sensitivity and/or amplification efficiency was either decreased compared to commercial PCR-rtPCR systems or not characterized. Other works also presented ultrafast PCR systems (25-30 cycles in 2-6 minutes), but are not applicable yet to more sensitive real time detections (i.e. rtPCR)15,17,20,41,42. The system presented here aims to increase drastically the rtPCR thermalization speed and to improve temperature homogeneity while conserving the advantage of conventional rtPCR systems i.e. a high efficiency/sensitivity associated with a large reaction volume (20-25 μL).
This ultrafast rtPCR system consists of a liquid-based thermalization system using a transparent microfluidic device associated with high speed microfluidic switches (i.e. microfluidic thermalization). These nearly instantaneous injections, associated with the improved thermal conduction of liquids compared to air and the large surface to volume ratio inherent to microfluidics, enables thermalization speeds up to 8 times faster than regular air thermalization and a perfect temperature homogeneity. Thus, we achieved rtPCR-based bacteria detections in 7 minutes while displaying sensitivity and efficiency very similar to conventional rtPCR systems and RT-rtPCR-based viral analyses in 7.5 minutes, both assays being carried out within regular 25 μL sample volumes. Our system is thus compatible with a broad range of sample volumes from nanoliters to tens of microliters and therefore, with applications requiring excellent limit of detection. The microfluidic device and system are first described. The rtPCR and RT-rtPCR protocols as well as the rtPCR curve modeling are then presented. Thermalization performances have been characterized. rtPCR and RT rtPCR durations have been optimized and compared to those of a commercial rtPCR system using anthrax (bacteria) and Ebola (virus) simulating agents. rtPCR sensitivity and efficiency have been determined and compared as well. Precise melting curve analyses are then obtained in a few seconds. Finally, the discrimination of different amplicon lengths by ultrafast rtPCR is demonstrated.
Ultrafast rtPCR system The whole rtPCR system (Fig. 1d) consists of a temperature controller with two heat exchangers (adapted from the Cherry Temp system, Cherry Biotech). These heat exchangers adjust the temperatures of heat-transfer liquids injected into the thermalization chamber in order to obtain the two desired rtPCR temperatures.
The two fluids are continuously heated and sequentially injected from the reservoirs through microfluidic caps (100 mL Large Microfluidic Reservoir Kit, Elveflow) via flexible tubing (Microfluidic 1/16-23G Tygon Tubing Kit, Elveflow). The fluorescence detection is carried out by a fluorescence measuring system (Fluoreader, Elveflow) placed under the microfluidic device and its PCR chamber (Fig. 1e). The pressure control and fluorescence detection are synchronized by an Elveflow Matlab script (Mathworks) and the temperature control is managed by the Cherry Temp software (Cherry Biotech). The whole system weighs less than 10 kg making its potential adaptation to POC detections readily conceivable.
PCR, rtPCR and RT-rtPCR protocols
For PCR & rtPCR assays, DNA extracted and purified from Bacillus atrophaeus subsp. globigii (BG) bacteria (Directorate General of Armaments (DGA), CBRN Defense) was used. For each assay, 125 ng of genomic DNA were used except when otherwise specified. Two different rtPCR master mix kits were used at a 1X concentration: Sso Advance Universal SYBR Green Super Mix (Biorad) for SYBR Green assays and QuantiFast Probe PCR + ROX Vial Kit (Qiagen) for probe assays. For RT-rtPCR assays, extracted and purified MS2 virus RNA was amplified (DGA, CBRN Defense and Roche). For each assay, 100 ng of initial RNA were used except when otherwise specified. QuantiFast Probe RT-PCR + ROX vial Kit (Qiagen) was used as a master RT-rtPCR mix at a 1X concentration for probe assays. All oligonucleotides (primers and probes) were purchased from DGA, CBRN Defense and Eurogentec. Amplicons sequences and characteristics are presented in table S1 (ESI†).
For PCR and rtPCR, primers and probes were used at a concentration of 500 and 100 nM respectively. For RT-rtPCR, primers and probes were used at a concentration of 800 and 200 nM respectively. For PCR, rtPCR and RT-rtPCR, a denaturation temperature of 96 °C was used. For PCR and rtPCR, the annealing/elongation temperature was optimized by a PCR temperature gradient assay (Fig. S1, ESI†) and, a temperature of 64 °C was then chosen. For RT-rtPCR, reverse-transcription and annealing/elongation temperatures of respectively 50 °C and 60 °C were used. The durations of the different rtPCR and RT-rtPCR phases were optimized (see Results and methods).
For molecular assays done in microfluidic devices, the Geneframe frame was first bonded to the glass substrate of the microfluidic device, under the thermalization chamber, by 5 min heating at 95 °C (through liquid thermalization). Then 40 μL of rtPCR and RT-rtPCR mixes were prepared, thoroughly mixed and pipetted onto the glass substrate. The 25 μL Geneframe chamber was then sealed with the polyester coverslip. The overflowing mix was then carefully removed by capillarity through a clean-room paper sheet. The microfluidic device containing the DNA sample was then placed into the rtPCR set-up, above the fluorescence detector, and connected to the heat exchangers and outlet reservoir via microfluidic tubes. The microfluidic device and the fluorescence detector were placed into an opaque box to avoid ambient optical noise. The assay was then started and automatically managed via the Elveflow Matlab script. For rtPCR assays with the microfluidic device, rtPCR and RT-rtPCR phases times mentioned take into account the thermalization times. For comparative PCR and rtPCR assays done in conventional commercial systems, a 3prime thermal cycler (Techne) with 0.5 mL tube and a Light Cycler 480 (LC480, Roche) with 96 well plates were respectively used, keeping the same reagent concentrations and mix volumes as for the assays in microfluidic devices. For assays in the LC480, the rtPCR and RTrtPCR phases times mentioned do not include the thermalization times. For the determination of rtPCR sensitivity with 100 genomic DNA copies, the initial DNA stock was serially diluted into a salmon sperm DNA solution at 100 μg/mL (UltraPure Salmon Sperm DNA Solution, Life Technologies) used as carrier DNA instead of deionized (Milli-Q) water to avoid the loss of material due to non-specific DNA binding during dilution or on the sample chamber surfaces.
Melting curve analysis with the microfluidic device
For the melting curve analysis, the temperature in one of the heaters was ramped up from 70°C to 90°C while exposing the microfluidic chamber to the heat transfer fluids from this heater. The thermal kinetic was first characterized with the infrared thermometer and the fluorescent measurement from the melting curve assay was then correlated with this thermal kinetic to obtain the melting curve from the microfluidic device.
Numerical simulation and rtPCR curves fitting
The speed of microfluidic thermalization was analyzed using multiphysics modeling (Comsol, France). The cycle threshold (Ct) for rtPCR and RT-rtPCR was determined by amplification curves fitting the following 5 parameters log-logistic model44:
Then, the maximum flow rate that the rtPCR system could withstand at PCR temperatures was first assessed. For flow rate ≥ 18 mL/min, the heating exchangers could not sufficiently heat the carrier liquids so that 17 mL/min was considered as the upper flow rate limit ensured to remain on the thermalization plateau (low influence of flow fluctuations on temperature control). With this flow rate and a temperature switch between 72 and 98 °C (typical rtPCR temperatures used for commercial rtPCR kits), the microfluidic thermalization could achieve 30 cycles in ≈ 2 min (127.5 s) (Fig 2.a), i.e. 4.25 s per cycle. To the best of our knowledge, this makes it the fastest static (i.e. unlike flow-through or oscillatory methods) rtPCR thermalization system using regular sample volume. At this speed, the annealing/elongation (between 72 and 75 °C) and denaturation (above 95 °C) plateaus lasted 1.05 s and 0.5 s respectively. The maximum heating ramp rate was 25 °C/s and the maximum cooling ramp rate was 18 °C/s. For comparison, the shortest rtPCR assays achievable with a commercial system for 30 rtPCR cycles with 30s initial denaturation, 1s denaturation and 1s annealing/elongation lasted 18.4 min. Thus, our microfluidic thermalization system enables a rtPCR cycling that is 8.7 times faster than conventional ones.
The microfluidic thermalization also enabled a better thermal homogeneity of the PCR samples during each temperature cycles despite a large volume. Indeed, the results of infrared imaging showed a temperature homogeneity of 0.03 °C (maximum temperature difference) during ultrafast thermalization (less than 2s for cooling). After optimization of the thermal performances, we carried out an ultrafast rtPCR of BG DNA through temperature cycling between 64 and 96 °C with a SYBR Green reporter, but no exponential amplification occurred. This might be explained by the fact that rtPCR cycles, notably the annealing-elongation step, were too short. Indeed, the shortest annealing times described last around 1 s46. Then, the Sso7d fusion DNA polymerase used in the SYBR Green rtPCR master mix (see Materials and Methods) has a polymerisation rate of 100 bases per sec. in optimal conditions. Thus, the 1 s annealing/extension around 64°C might not be long enough for the primers annealing and the complete amplicons extension.
Determination of optimal amplification parameters
To confirm the specificity of the amplification process in the presence of SYBR Green, PCR amplification with a SYBR Green mix has been carried out in the microfluidic device and a thermocycler, followed by a DNA electrophoresis analysis which shows that expected specific amplicons have been obtained (Figure S3, ESI†). To reduce rtPCR and RT-rtPCR durations while maintaining amplification efficiency, we achieved a dichotomous reduction of rtPCR time parameters validated with the conservation of Ct for both reporters (probes and SYBR Green). Thus, this Ct was first determined with a commercial rtPCR system (cf material and methods) and the microfluidic device using recommended rtPCR times (180 s for initial denaturation, 5 s for denaturation and 30 s for annealing/elongation time) and BG DNA to validate our rtPCR system in regular conditions.
The initial denaturation time was then first reduced, secondly the denaturation time was decreased, and finally, the annealing/elongation time was diminished. The dichotomous reduction of rtPCR time parameters and its different results is presented in detail in the table S2 (ESI†). The results obtained for the annealing/elongation time reduction with both reporters are represented in the Fig. 3a. As it can be seen, for both SYBR Green and probe reporters, Ct is first conserved or slightly decreased as the annealing-elongation time is progressively reduced before increasing. This Ct increase for shorter elongation times can be explained by the fact that DNA polymerases have less time to replicate DNA amplicons and thus partially replicate them. It can also be explained by the fact that primers/probes or SYBR Green do not have the time to bind with DNA targets or double-stranded DNA respectively. This maximal rtPCR speed for ultrafast rtPCR has also been observed previously18. The shorter annealing-elongation time obtained with probes compared to SYBR Green is consistent with the observation that DNA intercalating dyes like SYBR Green decrease the polymerase polymerization rate47. To obtain the lowest cycle thresholds while maintaining state-of-the art sensitivity, we could select the following rtPCR optimized time parameters:
Compared to the commercial rtPCR system (cf table S2, ESI†), we also observed that the rtPCR cycle thresholds obtained with probes and the microfluidic thermalization are lower (from 14.55 to 12.27 cycles with the microfluidic thermalization and 15.89 with the commercial rtPCR system). On the contrary, the rtPCR cycle thresholds obtained with SYBR Green and the microfluidic thermalization are first higher, but reach the same order when annealing/elongation time is reduced (from 16.34 to 15.26 with the microfluidic thermalization and 14.93 with the commercial rtPCR system).
By comparing rtPCR curves with probes and SYBR Green for regular (30 s) and fast (8-10 s) annealing-elongation phases (cf Fig. 3b), it can be noticed that fast and regular rtPCR curves for both reporters have the same Ct but different exponential phase slopes and thus, different final fluorescence intensities. These differences can be explained by the fact that the amplification efficiencies are identical during the first cycles, when reagents are in excess, and therefore yield highly similar Ct. When the number of amplicons increase exponentially in the following exponential phase with a constant amount of DNA polymerase, DNA polymerases need to amplify more DNA amplicons with the same efficiencies during the same annealingelongation phase time, which may not be possible with fast and shorter annealing-elongation phases. This decrease of efficiency in ultrafast PCR when the ratio of polymerase to targets decreases also sustains that in the present experimentations, the binding of the polymerase became the limiting factor in term of rtPCR rapidity. Furthermore, when the number of amplicons increases exponentially after the Ct, single-stranded complementary amplicons compete with primers for hybridization48,49, which decreases amplification efficiency in late PCR cycles, especially with short annealing-elongation phases. Most importantly, this effect does not influence the cycle threshold determining the amplification efficiency and system sensitivity. It can also be seen that the fast rtPCR curve obtained with probes has no plateau phase like it is the case for regular rtPCR curves, the ones obtained with regular annealing-elongation phases and the one obtained with SYBR Green and fast annealing-elongation phase. Therefore, to keep the same regular rtPCR amplification behaviour presenting saturation phases, only SYBR Green reporters have been used for the subsequent rtPCR assays. We assume this biochemical phenomenon related to the amplification speed could be explained by the fact that, when the number of amplicon increases exponentially after the Ct, single-stranded complementary amplicons compete with primers but also with probes for hybridization48,49, unlike SYBR Green that binds to single-stranded or double-stranded DNA regardless of potential hybridization50. Thus the probes are maintained in excess, unlike SYBR Green, causing no plateau phase.
To assess whether this fast amplification is also applicable to RNA targets, RT-rtPCR has been carried out in the microfluidic device with MS2 RNA. Using regular time parameters (600 s RT, 300 s initial denaturation, 10 s denaturation, 30 s annealing/elongation, i.e. 35 min for 30 RT-rtPCR cycles), a Ct of 10.88 was obtained (Fig S4, ESI†). By reducing the RT duration 20 fold, the Ct only varied from less than 1 cycle (600 s: Ct = 9.45, 30 s: Ct = 10.3) (Fig. 3c). After optimization, we achieved an on-chip RT-rtPCR of 30 cycles in 7.5 minutes with a Ct of 7.84 (30 s RT, 30 s initial denaturation, 3 s denaturation, 10 s annealing/elongation, i.e. 7 minutes 30 s for 30 RT-rtPCR cycles) (Fig S5, ESI†). It can be noticed that the ultrafast RT-rtPCR curves obtained with probes also presented no plateau phase like the ultrafast rtPCR curves obtained with probes.
Performance comparison of microfluidic rtPCR and RT-rtPCR with conventional system
Time optimization with our device could have been obtained at the expense of PCR efficiency. To assess whether this was the case, we compared the rtPCR and RT-rtPCR amplification efficiency from our microfluidic device to that of a state-of-the-art commercial (real-time) thermal cyclers (cf Experimental). First, we compared rtPCR and RT-rtPCR amplification efficiencies with both systems under non-optimized time conditions and with the microfluidic device under optimized time conditions (Fig 4.a & b, respectively). It can be seen that rtPCR durations can be reduced from 40 min for 30 cycles with the commercial rtPCR system to 20.5 min with the microfluidic chip and non-optimized time parameters and further down to 7 min with optimized time parameters (Fig 4.a), i.e. a molecular detection of anthrax simulating agent that is 5.7 times faster. Likewise, RT-rtPCR durations could be reduced from 54 min for 30 cycles with the commercial rtPCR system to 35 min with the microfluidic chip under non-optimized time parameters and further down to 7.5 min with optimized time parameters (Fig 4.b), i.e. a molecular detection of Ebola simulating agent that is 7.2 times faster.
It is important that the reduction in rtPCR and RT-rtPCR durations does not compromise amplification efficiency, which is critical for sensitive molecular detections. So we characterized rtPCR amplification efficiencies with the standard curve method by measuring the Ct from sample serial dilutions with the commercial rtPCR system and the microfluidic thermalization systems (same samples analyzed in parallel with both systems) (Fig 4.c). It can be noted that amplification efficiencies obtained were almost identical with a 5% variation between standard curves slopes. Therefore, the amplification efficiency obtained with the commercial rtPCR system was conserved with our microfluidic thermalization system, though the rtPCR assay duration was decreased by more than 6 times. In the previous optimization experiments, we had used rather high numbers of DNA copies (in the range of 27 million copies for rtPCR). Having made sure that the efficiency was maintained for these number of targets, we next wanted to assess the sensitivity, i.e. the lowest detectable amount of initial DNA copies, achievable with our system. It has been previously shown that the sensitivity of Light Cycler systems is around 100 copies for a close to 100 % probability of detection51,52. Therefore, we chose to assess whether the limit of detection of our microfluidic thermalization system was comparable. To do so, we serially diluted BG DNA samples in a salmon sperm DNA solution instead of purified water, as described in the material & methods section, in order to avoid loss of DNA by non-specific DNA binding during the dilution process and/or on the sample chamber surfaces. Using the same optimized protocol, we were able to detect as few as 100 initial copies of BG DNA within 7 min without observing a reduction of the rtPCR amplification efficiency (cf Fig 4.c), thus obtaining a sensitivity comparable to the state-of-the-art systems (our primers target a DNA sequence that is present only once in the BG genome). To confirm that this result was not due to sample contamination, we carried out a negative control in parallel by replacing the initial DNA sample with purified water. As expected, compared to the rtPCR curve obtained for 100 initial BG DNA copies, no amplification occurred (Fig S6, ESI†).
Concerning the amplification efficiency of ultrafast RT-rtPCR, it can be noted also that the RT-rtPCR carried out in 7.5 minutes for 30 rtPCR cycles (9.67 minutes for 40 rtPCR cycles) with the microfluidic device presents a Ct of 7.84 (cf previous paragraph and Fig S5, ESI†) equivalent to the Ct of 7.72 +/- 0.16 obtained with the commercial rtPCR system in 66.75 minutes for 40 cycles i.e. in a duration 6.9 times longer than with microfluidic thermalization.
Ultrafast melting curve analysis
For molecular assays using intercalating dyes like SYBR Green, melting or dissociation curve analysis is required to ensure the specificity of the amplification since these dyes will interact with any double stranded DNA like primer dimers and non-specific products. Interestingly, melting curve analysis can also be used with probes like molecular beacons, for the identification of single-nucleotide polymorphisms53 (SNPs) for instance. Melting curves are obtained by exposing the resulting rtPCR product to a temperature increase and monitoring in parallel the resulting fluorescence. If a single peak can be observed at the expected temperature value on the first negative derivative of the fluorescence as a function of the temperature, the amplification is confirmed to be specific. Therefore, we used the microfluidic thermalization system to carry out an ultrafast temperature modification for melting curve analysis (fig 5). The assay was carried out in only 20s and its derivative showed a single peak, demonstrating thus a specific rtPCR amplification. Melting temperatures for the BG amplicons should be comprised between 75 °C and 81 °C according to two different rtPCR software54,55 so the obtained experimental melting temperature of 77.5 °C corresponds to the theoretical results. Interestingly, the Full Width at Half Maximum (FWHM) for the derivative of this melting transition is very narrow: 1.7 °C. This sharp melting transition is an important property for highresolution melting curves and, thus, the discrimination of different amplicons and SNPs56. Therefore, interestingly, our microfluidic system is able to perform fast and sharp melting curve analyses, which is in agreement with the achieved temperature homogeneity that we noted previously.
Amplicon length discrimination with ultrafast rtPCR analysis
For unknown pathogen detection and other applications, multiplex rtPCR is a critical technology that is still hindered by the unexpected formation of non-specific PCR products due notably to too long elongation phases57. Ultrafast rtPCR and its short elongation phases could be naturally endowed with the ability to distinguish relevant short amplicons from unwanted long non-specific amplicons. To demonstrate this feature, 65-bp long BG amplicons and approximatively 10 times longer (500bp) BG amplicons were therefore analyzed by ultrafast rtPCR within the microfluidic device to study whether their distinction was possible. For this purpose, for each type of amplicon length, two rtPCRs were carried out with different annealing-elongation phase times: a short (10 s) and a long one (30 s) (fig 6).
For more tutorial about microfluidics, please visit our other tutorials here: «Microfluidics tutorials».
This work was supported by the ANR-DGA, BPI France and European Commission through respectively funding ASTRID n°ANR-11-ASTR-0019-01, AIMA Laboratoire n°A1402022 Q and FP7-PEOPLE-2013-ITN – Marie-Curie Action: LAPASO grant agreement n°607350. The authors thank Alice Pinheiro and François Radvanyi (Institut Curie) for their collaborations, technical advices and support; Yohan Farouz, Diana Molino, Jacques Fattacioli (École Normale Supérieure de Paris) for the fruitful discussions and advices; Guilhem Larigauderie and the DGA, CBRN Defense for providing biological samples and reagents; Damien Baigl and the technical department of the École Normale Supérieure de Paris for technical support and help; Sage Morghan for the English proofreading of the manuscript.
1 D. Butler, Nature, 2014, 516, 154–155.
2 Nature News, Nature, 2015, 518, 460–461.
3 W. Chen, B. He, C. Li, X. Zhang, W. Wu, X. Yin, B. Fan, X. Fan and J. Wang, J. Med. Microbiol., 2007, 56, 603–607.
4 K. V. Mohan, K. G. Murugavel, Rajanikanth, S. Mathews, K. Raghuram, P. Rajasambandam, A. Murali, U. Srinivas, Mathiazhagan, K. R. Palaniswamy, S. K. Panda and S. P. Thyagarajan, Indian J. Gastroenterol., 1999, 18, 73–75.
5 L. Durnez, W. Van Bortel, L. Denis, P. Roelants, A. Veracx, H. D. Trung, T. Sochantha and M. Coosemans, Malaria J., 2011, 10, 195.
6 I. M. Mackay, K. E. Arden and A. Nitsche, Nucleic Acids Res., 2002, 30, 1292– 1305.
7 M. J. Espy, J. R. Uhl, L. M. Sloan, S. P. Buckwalter, M. F. Jones, E. A. Vetter, J. D. C. Yao, N. L. Wengenack, J. E. Rosenblatt, F. R. Cockerill and T. F. Smith, Clin. Microbiol. Rev., 2006, 19, 165–256.
8 D. Fraga, T. Meulia and S. Fenster, in Current Protocols Essential Laboratory Techniques, John Wiley & Sons, Inc., 2008.
9 G. Wong, I. Wong, K. Chan, Y. Hsieh and S. Wong, PLoS ONE, 2015, 10(7): e0131701.
10 World Health Organization, Urgently needed: rapid, sensitive, safe & simple diagnostic tests, and diagnostics/en/ (accessed February 2016).
11 D. S. Chertow, C. Kleine, J. K. Edwards, R. Scaini, R. Giuliani and A. Sprecher, N. Engl. J. Med., 2014, 371, 2054–2057.
12 C.-M. Chang, W.-H. Chang, C.-H. Wang, J.-H. Wang, J. D. Mai and G.-B. Lee, Lab Chip, 2013, 13, 1225–1242.
13 Y. Sun, T. L. Quyen, T. Q. Hung, W. H. Chin, A. Wolff and D. D. Bang, Lab Chip, 2015, 15, 1898–1904.
14 Z. Ma, R. W. Lee, B. Li, P. Kenney, Y. Wang, J. Erikson, S. Goyal and K. Lao, Proc. Natl. Acad. Sci., 2013, 110, 14320–14323.
15 D. Moschou, N. Vourdas, G. Kokkoris, G. Papadakis, J. Parthenios, S. Chatzandroulis and A. Tserepi, Sens. Actuators B Chem., 2014, 199, 470–478.
16 Y. Fuchiwaki, H. Nagai, M. Saito and E. Tamiya, Biosens. Bioelectron., 2011, 27, 88–94.
17 S. Brunklaus, T. E. Hansen-Hagge, J. Erwes, J. Höth, M. Jung, D. Latta, X. Strobach, C. Winkler, M. Ritzi-Lehnert and K. S. Drese, Electrophoresis, 2012, 33, 3222–3228.
18 P. Neuzil, C. Zhang, J. Pipper, S. Oh and L. Zhuo, Nucleic Acids Res., 2006, 34, e77–e77.
19 H. Kim, S. Dixit, C. J. Green and G. W. Faris, Opt. Express, 2009, 17, 218–227.
20 E. K. Wheeler, C. A. Hara, J. Frank, J. Deotte, S. B. Hall, W. Benett, C. Spadaccini and N. R. Beer, Analyst, 2011, 136, 3707–3712.
21 H. Terazono, H. Takei, A. Hattori and K. Yasuda, Jpn. J. Appl. Phys., 2010, 49, 06GM05.
22 BJS Technologies, XXpress, https://www.fastmdx.com/ (accessed February 2016).
23 Y.-K. Cho, J. Kim, Y. Lee, Y.-A. Kim, K. Namkoong, H. Lim, K. W. Oh, S. Kim, J. Han, C. Park, Y. E. Pak, C.-S. Ki, J. R. Choi, H.-K. Myeong and C. Ko, Biosens. Bioelectron., 2006, 21, 2161–2169.
24 M.-S. Yoo, K. C. N. Thi, P. Van Nguyen, S.-H. Han, S.-H. Kwon and B.-S. Yoon, J. Virol. Methods, 2012, 179, 195–200.
25 Analytik Jena, qTower, https://www.analytik-jena.fr/fr.html products/products-dynamic/cat/real-time-rapidpcr/prod/qtower.html (accessed February 2016).
26 H.-O. Song, J.-H. Kim, H.-S. Ryu, D.-H. Lee, S.-J. Kim, D.-J. Kim, I. B. Suh, D. Y. Choi, K.-H. In, S.-W. Kim and H. Park, PLoS One, 2012, 7, e53325.
27 Cepheid, GeneXpert system, http://www.cepheid.com/us/cepheidsolutions/ systems/genexpert-systems/genexpert-i (accessed February 2016).
28 R. Abdul Khaliq, R. Kafafy, H. M. Salleh and W. F. Faris, Nanotechnology, 2012, 23, 455106.
29 I. Erill, S. Campoy, J. Rus, L. Fonseca, A. Ivorra, Z. Navarro, J. A. Plaza, J. Aguiló and J. Barbé, J. Micromechanics Microengineering, 2004, 14, 1558.
30 J. Noh, S. W. Sung, M. K. Jeon, S. H. Kim, L. P. Lee and S. I. Woo, Sens. Actuators Phys., 2005, 122, 196–202.
31 R. P. Oda, M. A. Strausbauch, A. F. R. Huhmer, N. Borson, S. R. Jurrens, J. Craighead, P. J. Wettstein, B. Eckloff, B. Kline and J. P. Landers, Anal. Chem., 1998, 70, 4361–4368.
32 J. R. Peham, L.-M. Recnik, W. Grienauer, M. J. Vellekoop, C. Nöhammer and H. Wiesinger-Mayr, Microsyst. Technol., 2011, 18, 311–318.
33 A. J. De Mello, Lab Chip, 2001, 1, 24N–29N.
34 X. Qiu, M. G. Mauk, D. Chen, C. Liu and H. H. Bau, Lab Chip, 2010, 10, 3170–3177.
35 D. Rawer, A. Borkhardt, M. Wilda, S. Kropf and J. Kreuder, Leukemia, 2003, 17, 2527–2528.
36 P. Rossmanith and M. Wagner, J. Food Prot., 2011, 74, 1404–1412.
37 J. Kim, M. Mauk, D. Chen, X. Qiu, J. Kim, B. Gale and H. H. Bau, Analyst, 2010, 135, 2408–2414.
38 D. Chen, M. Mauk, X. Qiu, C. Liu, J. Kim, S. Ramprasad, S. Ongagna, W. R. Abrams, D. Malamud, P. L. A. M. Corstjens and H. H. Bau, Biomed. Microdevices, 2010, 12, 705–719.
39 J. Kim, D. Byun, M. G. Mauk and H. H. Bau, Lab Chip, 2009, 9, 606–612.
40 N. Crews, C. Wittwer, R. Palais and B. Gale, Lab Chip, 2008, 8, 919–924.
41 C. J. Easley, J. A. C. Humphrey and J. P. Landers, J. Micromechanics Microengineering, 2007, 17, 1758.
42 G. Maltezos, M. Johnston, K. Taganov, C. Srichantaratsamee, J. Gorman, D. Baltimore, W. Chantratita and A. Scherer, Appl. Phys. Lett., 2010, 97, 264101.
43 Y. Xia and G. M. Whitesides, Angew. Chem. Int. Ed., 1998, 37, 550–575.
44 A.-N. Spiess, C. Feig and C. Ritz, BMC Bioinformatics, 2008, 9, 221.
45 R. Rasmussen, in Rapid Cycle Real-Time PCR, eds. P. D. med S. Meuer, P. D. C. Wittwer and D. K.-I. Nakagawara, Springer Berlin Heidelberg, 2001, pp. 21–34.
46 C. T. Wittwer and D. J. Garling, BioTechniques, 1991, 10, 76–83.
47 J. L. Montgomery and C. T. Wittwer, Clin. Chem., 2014, 60, 334–340.
48 I. V. Kutyavin, Nucleic Acids Res., 2010, 38, e29–e29.
49 US Pat., 20040053254 A1, 2004.
50 H. Zipper, H. Brunner, J. Bernhagen and F. Vitzthum, Nucleic Acids Res., 2004, 32, e103.
51 D. Lee, P.-J. Chen and G.-B. Lee, Biosens. Bioelectron., 2010, 25, 1820–1824.
52 S. Kirchner, K. M. Krämer, M. Schulze, D. Pauly, D. Jacob, F. Gessler, A. Nitsche, B. G. Dorner and M. B. Dorner, Appl. Environ. Microbiol., 2010, 76, 4387–4395.
53 M. Liew, R. Pryor, R. Palais, C. Meadows, M. Erali, E. Lyon and C. Wittwer, Clin. Chem., 2004, 50, 1156–1164.
54 uMELT, https://www.dna-utah.org/umelt/umelt.html (accessed February 2016). 55 Oligonucleotide Properties Calculator, http://www.basic.northwestern.edu/biotools/oligocalc.html (accessed February 2016).
56 T. A. Taton, C. A. Mirkin and R. L. Letsinger, Science, 2000, 289, 1757–1760.
57 M. C. Edwards and R. A. Gibbs, Genome Res., 1994, 3, S65–S75.
Email* I hereby agree than Elveflow uses my personal data
Get a quote
Name*
Email*
Message
Newsletter subscription
We will answer within 24 hours
By filling in your info you accept that we use your data.
Collaborations
Need customer support?
Serial Number of your product
Support Type AdviceHardware SupportSoftware Support
Subject*
I hereby agree that Elveflow uses my personal data Newsletter subscription
How can we help you?
Message I hereby agree that Elveflow uses my personal data Newsletter subscription