qPCR multiplex detection of microRNA and messenger RNA in a single reaction

Minimum information for publication of qPCR experiments

Compliance with the Minimum Information for the Publication of Real-Time Quantitative PCR Experiments (MIQE) guidelines (Bustin et al., 2009) has been provided and all experiments performed in triplicate.

RNA isolation and quantification of HEK 293, HeLa cell lines and human serum

HEK 293 (ATCC) and HeLa cell (ATCC) lines were grown to 90% confluency in DMEM, Glutamax (GIBCO) was supplemented with 10% FBS (GIBCO) and 1% Penicillin-Streptomycin-Glutamine (GIBCO) and total RNA was isolated using the Trizol method (Molecular Research Centre Inc). Total RNA from human serum was extracted and isolated using the Tri-reagent RT-LS protocol (Molecular Research Centre Inc.) (Khoury, Ajuyah & Tran, 2014). Serum samples were from cancer patients and healthy volunteers obtained from clinical collaborators at Royal Prince Alfred Hospital Sydney. The samples were stored at -80C till use. (Protocol number X10-0016 and HREC/10/RPAH/24). HREC was granted (UTS HREC 2013000471) by UTS Human Research Ethics Committee for use of the serum. Written consent for the human serum used in these experiments were provided by the patient utilising our HREC form. RNA quality and concentration were assessed with a Nanodrop 1000 (ThermosFisher) (See Table S1) and resuspended with RNase free dH₂0 to concentrations of 50 ng/µl, 100 ng/µl and 200 ng/µl for use in RT-qPCR.

miRNA mimic transfections in HeLa cell lines

HeLa cells were transfected with the Ambion Pre-miR miRNA Precursors (ThermosFisher) hsa-miR-21 mimic (20 pmol) (Invitrogen), as well as a Scramble #1 control (20 pmol) (ThermosFisher), in triplicate using Lipofectamine RNAiMAX Transfection Reagent (Thermo). Cells were seeded at a density of 4 × 10⁵ into a 6 well plate and incubated for 24 h prior to transfection. All cells were collected 24 h post-transfection and total RNA extracted.

RT Priming strategies for synthesis of cDNA products

HEK 293 and HeLa total RNA were prepared using three different RT cycle conditions (See Table S2). MicroRNA and mRNA cDNA synthesis were performed according to the manufacturer’s protocol (Applied Biosystems) using stem loop and random primers respectively. RNAmp combines both primer sets to generate both mRNA and miRNA transcripts. All three RT approaches were generated with the High-capacity TaqMan miRNA Reverse Transcription Kit (ThermoFisher) using clear 0.5ml PCR grade tubes on an Eppendorf Mastercycler Pro S Vapoprotect.

For the first condition, we generated a 15.0 µl microRNA synthesis cDNA reaction. The included 4 U of 20 U/µL RNase inhibitor, a total volume of 6 µl miRNA RT primer mix, 50 U of MultiScribe™ Reverse Transcriptase, 50 Units/µL, 1× volume of 10× RT Buffer, 1 mM dNTP were combined and mixed with total RNA (See Tables S2 and S3). To generate the random prime cDNA reaction, 20 U of 20 U/µL RNase inhibitor, 1× of 10× RT Random primer, 50 U of MultiScribe™ Reverse Transcriptase 50 Units/µL, 1× of 10× RT Buffer and 4 mM dNTP were mixed and combined with total RNA (See Tables S2 and S3). Our third condition was the RNAmp which is a 15.0 µl mixture consisting of the following; 4 U of 20 U/µL RNase inhibitor, a total volume of 6 Textmu l miRNA RT primer mix, 50 U of MultiScribe™ Reverse Transcriptase, 50 Units/µL, 1× of 10× RT Buffer, supplemented with MgCl2 25 mM, 1.6 mM of 100 mM dNTP, and 1× of 10× RT Random primer (See Tables S2 and S3).

Singleplex and duplex hydrolysis based quantitative PCRs

Complementary DNA products from all three RT methods (micoRNA cDNA synthesis,mRNA cDNA synthesis and RNAmp) were diluted 1:4 with water and added to a Hydrolysis based Universal PCR master mix in four different volumes, 20 µl, 10 µl, 5 µl and 2.5 µl. Refer to Tables S4 and S5 for the composition of subsequent singleplex and duplex reactions. Hydrolysis probes were labelled as VIC; B2M, ACTB, GAPDH, 18S, hsa-miR-21 and FAM; P53, p16, JAG1, CDKN1, Dicer, Ago2, hsa-miR-99b, hsa-miR16, U75, JAG1, hsa-miR-486-5p, hsa-miR-451 and ordered from the manufacturer (Applied Biosystems). Singleplex reactions had a 1× volume of Taqman Universal PCR Master and 0.5 × (20.0 µl Final Volume), 1 × (15.0 µl Final Volume), 2 × (10.0 µl Final Volume), 4 × (5.0 µl Final Volume) and concentration of the target-specific TaqMan Real Time PCR primer probe set (Applied Biosystems). Those designated for duplex had a 1× concentration of Taqman Universal PCR Master for all except the 2.5 µl final volume reaction of 0.8×. The Taqman specific primer probe sets had 0.5× each (20.0 µl Final Volume), 1× each (15.0 µl Final Volume), 2× each (10.0 µl Final Volume), and 4× each (5.0 µl Final Volume) also from Applied Biosystems. From these master-mix solutions, triplicate qPCR reactions were carried out on an Applied Biosystems Step One with the following thermal-cycling procedure; 95 °C for 10 min, followed by 40 cycles of 95 °C for 15 s and 60 °C for 1 min (1.6 °C/s ramp rate) as specified by the manufacturer (Applied Biosystems). The experimental design for duplex qRT-PCR is more complicated than a single-plex. To avoid overlap of emission spectra we chose dyes with appropriate excitation wavelengths and little to no overlap in their emission spectra: VIC, FAM and ROX (Step One Plus passive reference dye). The settings for excitation and emission filters of real-time detection using Thermofisher reagents on a Step One Plus has been supplied in Table S7. The Step One Plus instrument was calibrated for each compatible dye; VIC, ROX and FAM as part of the experiment optimization process and per manufacturer recommendations. Appropriate calibration and choice of dye combinations enhance the dye specificity, and minimizes background and overlap of fluorescent signals.

LinRegPCR analysis of RT-qPCR data

Step One plus experimental files were exported and reformatted for LinRegPCR analysis and determination of Cq (Tuomi et al., 2010). Baselines were determined and amplicon groups were assigned with the following exclusion criteria; samples under analysis; samples without amplification, samples without plateau phase, samples with low Cq value and samples being outside of the 5% of the group median efficiency per amplicon. Furthermore, a log linear phase parameter during estimation of baseline was included. The qPCR efficiencies were exported and statistically analysed.

Statistical analysis

Mean values and efficiency for each Amplicon and reaction were calculated throughout with Standard Error of the Mean, Minimum, Maximum, Mean, and Standard Deviation. One-way ANOVA analysis was performed on multiple groups, to determine statistical significance. P values range from **** P < 0.0001, *** P < 0.001 and analysed using the Prism 6 software package.

Low volume qPCR reactions improves PCR detection

First, we sought to improve the fluorescent based qPCR without the additional need of increasing RNA input and reagents. The standard TaqMan singleplex reaction volume was modified and compared between 20.0 µl, 10.0 µl, 5 µl to 2.5 µL (See Table S4). Two categories of RNA transcripts Reference genes and miRNAs, were quantified by Quantification cycle (Cq). The Cq is defined by the first detection of the amplicon above the RNA background and inversely correlated with abundance. For example, a lower Cq represents higher abundance of the original target RNA.

The results indicate the Cq value of Beta-2-Microglobulin (B2M) and Beta-Actin were decreased with smaller reaction volumes (Fig. 1A and Table S6). At the 2.5 µl reaction volume, the Cq value of Beta-Actin was 17, a difference of 9 Cq values from the 20 µl reaction. A similar trend of Cq was also observed for B2M. This change in the Cq threshold in decreasing reaction volumes was also observed for hsa-miR-21 and hsa-miR-99b (Fig. 1B and Table S6) with an average improvement of 5 Cq’s. These Cq shifts are equivalent to a 128- and 32-fold increase in detection for hsa-miR-21 and hsa-miR-99b, respectively. Furthermore, these changes in Cq values across the smaller volume groups for both B2M, Beta-Actin, hsa-miR-21 and hsa-miR-99b were statistically significant as determined by one-way ANOVA. Given the interest in using serum miRNAs as biomarkers, we tested if a commonly deregulated microRNA, hsa-miR-16, could be detected in human serum and improved by using smaller reaction volumes (Fig. 1C and Table S6). A similar outcome was observed at smaller reaction volumes.

Most miRNA qPCR hydrolysis probe-based assays are run as singleplex reactions. When detecting multiple miRNAs, this method increases reagent usage and is problematic when using limiting or rare samples. To alleviate this constraint, we evaluated duplexing for the detection of hsa-miR-21 and another RNA, U75 in working volumes of 10.0, 5.0, and 2.5 µL. U75 was selected, as it is a common small nucleolar RNA used as a reference gene for normalizing miRNA qPCR expression data (Livak & Schmittgen, 2001). As seen in Fig. 1D, the two targets were detected across the different reaction volumes. Moreover, these amplicons were detected at lower Cq values in smaller reaction volumes.

To eliminate any possibility of amplification bias at these lower volumes, we determined the qPCR efficiency using the software LinRegPCR (Ramakers et al., 2003; Tuomi et al., 2010). Using representative examples, B2M and hsa-miR-21, the qPCR efficiencies were similar in all the volumes tested (Table 1). Statistically there were no significant differences between the group means as determined by one-way ANOVA. Therefore, the reduction in reaction volumes does not impact on qPCR efficiency and PCR detection is directly dependent on smaller reaction volumes.

We then investigated whether RNA concentration influences Cq values at these low volumes. Total RNA inputs of 50 ng, 100 ng and 200 ng were used to generate the two-standard manufacturer RT reactions for individual detection of RNA and miRNA species. Please refer to Table S1 for RNA Concentration and Quality. For the RNA species, Beta-Actin, GAPDH, 18s and p53 (Fig. 2A), a consistent Cq level was observed across these concentrations. Applying the manufacturer’s protocol to small RNAs (Fig. 2B) hsa-miR-21, hsa-miR-99b, U75 and Let-7b, the same result was obtained. Taken together, these results suggest qPCR detection at low reaction volumes does not solely depend on the starting input of RNA.

Duplex detection for both mRNA and miRNAs

To further expand upon this utility, we formulated a qPCR reaction to allow parallel detection of both miRNA and RNA transcripts within the same reaction (Table S3). A combination of random primers and miRNA stem loop primers were added into the same reaction mix. RT was performed at the thermal cycling conditions as described in Table S4. For direct comparisons, RNAmp was vetted against the established protocols using random or stem loop primers. A comparison of qPCR output expression of the common reference genes, 18S, Beta-Actin, GAPDH and B2M (Fig. 3A), oncogenes or drivers of cancer progression, CDKN1, p53 and p16 (Fig. 3B) and miRNA biogenesis genes, Dicer and Ago2 (Fig. 3C) was then performed across these 3 RT priming strategies. With RNAmp, there was a decrease of 5 Cq values for the reference genes. p53 and p16 were detected within the shorter cycling timeframe of 3 Cq’s, interpreted as an 8-fold gain. To assess the scope of RNAmp, miRNA machinery genes were additionally examined and detection of the product was increased by four-fold. Importantly, across these gene-sets, RNAmp, when compared to standard approaches did not compromise qPCR detection but instead, enhanced it.

RNAmp was applied to quantify RNA subclasses in a typical siRNA/miRNA knockdown condition using a miRNA and scramble control. Following transfection of VIC labeled hsa-miR-21 or a scramble mimic into HeLa cells, RNA was isolated at 24hrs post transfection and cDNA products generated using RNAmp, random primers and stem loop primers RT protocols. Using the standard methods, hsa-miR-21 could be detected at basal levels in the scramble control and increased in transfected cells. JAG1 is a target of hsa-miR-21 regulation (Hashimi et al., 2009) and a decrease in JAG1 RNA levels was observed in hsa-miR-21 overexpressing cells. This trend was accurately quantified with RNAmp (Fig. 4A). Analysis of the fold change for JAG1 using 2 Delta Cq showed no difference in outcome with either RNAmp or the standard approach (Fig. 4B).

As RNAmp is a mixture of stem loop and random primers, this setup may introduce amplification bias when compared to single random and stem loop priming methodologies. Thus, qPCR efficiencies were determined for p53, Dicer, and JAG1 using LinRegPCR (Table 2). There was no difference in qPCR efficiencies between RNAmp and standard procedures. This demonstrates that RNAmp exhibits the same qPCR efficiency as random priming methods but provides the parallel detection of different RNA and miRNA species.

Having shown RNAmp as a singleplex qPCR, we evaluated if this approach was applicable in a duplex reaction. Using HeLa samples, hsa-miR-21 (VIC) and JAG1 (FAM) were quantified in a duplex reaction and compared to the standard singleplex qPCR (See Table S5). Both the Cq values and the pattern of gene expression from either the duplex or singleplex RNAmp were similar (Fig. 4C). There was also a shift of 3 Cq’s for JAG1, translating to an 8-fold detection increase. This outcome was also the case for hsa-miR-21, detecting at an earlier cycling frame of 2 Cq’s in the duplex format (4-fold increase in detection).

To expand on the utility of RNAmp for clinical applications the expression of selected miRNAs and mRNA in cancer serum using both the duplex and singleplex qPCR approach was performed (Fig. 4D). In the duplex format, hsa-miR-486-5p, hsa-miR-451 and B2M were all detected in cancer serum. The Cq for the miRNAs were similar in duplex or singleplex format. However, for B2M, the duplex approach offered lower detection limits.