Comparison of different extraction techniques to profile microRNAs from human sera and peripheral blood mononuclear cells
© Monleau et al.; licensee BioMed Central Ltd. 2014
Received: 11 December 2013
Accepted: 6 May 2014
Published: 23 May 2014
microRNAs (miRNAs) play crucial roles in major biological processes and their deregulations are often associated with human malignancies. As such, they represent appealing candidates as targets of innovative therapies. Another interesting aspect of their biology is that they are present in various biological fluids where, advantageously, they appear to be very stable. A plethora of studies have now reported their potential as biomarkers that can be used in diagnosis, prognosis and/or theranostic issues. However, the application of circulating miRNAs in clinical practices still requires the identification of highly efficient, robust and reproducible methods for their isolation from biological samples.
In that context, we performed an independent cross-comparison of three commercially available RNA extraction kits for miRNAs isolation from human blood samples (Qiagen and Norgen kits as well as the new NucleoSpin miRNAs Plasma kit from Macherey-Nagel). miRNAs were further profiled using the Taqman Low Density Array technology.
We found that, although these 3 kits had equal performances in extracting miRNAs from peripheral blood mononuclear cells, the Macherey-Nagel kit presented several advantages when isolating miRNAs from sera. Besides, our results have indicated that, depending on the quantity of the biological samples used, the extraction procedure directly impacted on the G/C composition of the miRNAs detected.
Overall, our study contributes to the definition of a reliable framework for profiling circulating miRNAs.
MicroRNAs (miRNAs) are a class of small noncoding RNAs (typically 20–23 nt) that are important regulators of gene expression at the post-transcriptional level. In recent years, numerous studies have involved miRNA disregulations in various diseases and the number of miRNA publications is growing each year. To date, more than a thousand miRNAs have been identified and their presence in various body fluids (plasma, serum, urine…) as well as their remarkable stability make them excellent candidates for non-invasive biomarkers of various human diseases . For the development of miRNAs-based biomarkers, several issues associated with samples manipulation, miRNAs extraction, measurements and statistics need to be addressed [2–4]. For instance, several studies have shown the importance of samples processing [5, 6]. Likewise, it was reported that hemolysis occurring during blood collection has significant impact on the miRNAs content in plasma/serum [7–10]. The evaluation of the quantity and quality of miRNAs isolated from biological samples is indeed a key step in miRNA profiling studies. Although methods for miRNA extraction are usually similar to that used in the case of total RNAs (with only slight modifications required to retain the small RNA fraction), the sizes and relative abundance of ribosomal RNAs cannot give information about the integrity of the miRNA preparation. In addition, the quantification of miRNA preparations can only be accurate in samples where larger RNAs are not degraded as the degradation products can compromise this quantification. Moreover, the low concentration of RNAs present in body fluids makes the estimation of miRNAs abundance particularly difficult . Another aspect that can impact miRNA profiling is the qPCR efficiency that can be affected by minute amounts of inhibiting compounds co-extracted with RNA . Besides, it has been reported that short RNAs with low GC content may be selectively lost during extraction from a small number of cells, depending on the extraction methods . It is thus crucial to compare different protocols in order to identify the most reproducible and reliable method. Several studies have indeed tackled this point, revealing different performances between the commercially available kits for the isolation of miRNAs [12, 14–17]. Here, we broadened these analyses and compared, using Taqman Low Density Arrays, miRNAs profiles of peripheral blood mononuclear cells (PBMCs) and sera from human healthy donors, obtained with three distinct commercial kits: Qiagen, Norgen Biotek Corporation and Macherey-Nagel. To the best of our knowledge the Macherey-Nagel kit for plasma/serum has not been studied before. In this paper, we showed that the quantity and the quality of RNAs extracted from PBMCs with these three kits did not significantly differ. This was in contrast to miRNAs extraction from serum for which the Macherey-Nagel kit presented several advantages. Besides, we found that, irrespective of the kit used, increasing the quantity of the starting biological materials (PBMC or serum) introduced a bias in the isolation of miRNAs and favored the extraction of G/C low miRNAs. We also bring evidence that the optimal detection of miRNAs is not necessarily obtained with the maximum quantity of total RNAs.
Blood samples were obtained from ten blood donors who underwent a brief medical examination (Etablissement Français du Sang (EFS) Montpellier, France). These blood samples were obtained in accordance to the ethical guidelines of the French Ministry of Health (Code de Santé Publique Article L1131-1 and next). This study was approved by the ethics committee of the EFS-Pyrénées-Méditerranée (EFS-PM- Agreement: # 21/PLER/MTP/CNR02/2013-007). All donors have given their written consent for non-therapeutic use of their blood sample donation. Whole blood samples from each donors were collected in two Vacutainer tubes, one being EDTA coated and the other non-EDTA coated. RNase-free protocols were followed throughout all procedures. Sera were prepared from blood collection tubes without anticoagulant after centrifugation at 500 g for 10 minutes at room temperature and inspected visually for any pink hue, which is indicative of hemolysis , and then, immediately frozen at −80°C. PBMCs were isolated, from EDTA tubes, by Ficoll density gradient centrifugation (Sigma-Aldrich). 3×106 or 1×106 cells were mixed with lysis buffer according to the manufacturers’ instructions for each RNA extraction kit, in order to achieve lysis and inactivate endogenous RNAses. Lysates from PBMCs were frozen in the lysis buffer at −80°C until next steps of RNA purification. Experiments were performed with RNAs thawed only once.
RNA extraction from PBMCs and serum samples
Total RNA was extracted from the PBMCs lysates (1×106 or 3×106 cells) using the miRNeasy mini kit (reference 217004, Qiagen, CA), the Total RNA Purification Kit (product 17200, Norgen Biotek Corporation, Canada) and the NucleoSpin miRNAs kit (reference 740971, Macherey-Nagel, Düren, Germany) following the manufacturers’ protocols. Qiagen and Norgen kits require a Phenol/Chloroform extraction step unlike the kits from Macherey-Nagel. The Macherey-Nagel protocol allows isolating both small and large RNAs in one or two fractions. Here, we have chosen to extract total RNAs in one fraction. Total RNAs were eluted in 30 μL nuclease-free water for Qiagen kit or 50 μL for Norgen and for Macherey Nagel kits.
Total RNAs were extracted from thawed serum samples using the miRNeasy mini kit (Qiagen, CA), the Plasma/Serum Circulating RNA purification Kit (product 30000, Norgen Biotek Corporation, Canada) and the NucleoSpin miRNAs Plasma kit (reference 740981, Macherey-Nagel, Düren, Germany). For both Qiagen and Macherey Nagel kits, total RNAs were extracted from 300 μL or 600 μL of serum and further eluted in 30 μL of nuclease-free water. For the Norgen kit, total RNAs were extracted from 200 μL of serum and eluted in 50 μL of nuclease-free water.
Total RNA concentration was expressed as micrograms or nanograms RNA per million cells (for PBMCs) or per milliliter of serum. The RNA concentration and quality were first assessed using the NanoDrop ND-1000 spectrophotometer (NanoDrop Technologies, DE). PBMC sample purity was estimated by measuring the ratio of spectrophotometric absorbance (260 nm/280 nm). For a pure RNA sample, this ratio should be comprised between 1.8 and 2 RNAs were further analyzed with the Bioanalyzer 2100 (Agilent Technologies, CA) using small RNA and RNA 6000 Nano chips (Agilent, CA). The RNA Integrity Number (RIN) obtained by the Nano 6000 kit for PBMCs indicates the RNA quality of a sample (RIN values >8 are commonly considered as high-quality RNA). Small RNA (from 6 to 150 nt) and miRNAs (from 6 to 40 nt) concentrations as well [micro/small] RNA ratio were calculated from the electropherogram of the Small RNA kit for PBMC and sera.
TaqMan low-density arrays (TLDA) for miRNAs profiling
MicroRNA profiling of samples was performed using TaqMan Array Human MicroRNA panels A and B (Life technologies, CA). Each TLDA card detects 384 features including 377 human miRNAs, three endogenous small RNA controls (one of them being in quadruplicate), and a negative control. 754 human miRNAs were quantified in total. Reverse transcription and pre-amplification were performed following the manufacturer’s instructions (Life technologies, CA). Briefly, 3 μL RNAs from serum or 10 to 300 ng RNAs from PBMCs were reverse transcribed using the Megaplex reverse transcription (RT) reaction in a final volume of 7.5 μL using stem-loop primers designed by Life Technologies. 2.5 μL of this cDNA solution were used for a pre-amplification step in a final volume of 25 μL then diluted four times in distilled water DNase/RNase free (Life Technologies Gibco). Nine μL of diluted pre-amplified product added to 900 μL of total mix were used per TLDA card. Real time quantitative PCR was performed with ViiA7 real-time PCR system, and data were collected with the manufacturer’s ViiA™ Software. Gene Expression Suite software (Applied Biosystems, CA) was further used to process the array data. Automatic thresholds were checked individually and corrected when necessary.
Data analysis and statistical methods
Data processing and analysis were conducted using tools from Microsoft Excel and Prism GraphPad V5.0d software (GraphPad Software, CA). Comparisons of quantity and quality data were performed using Mann Whitney or Kruskal-Wallis test depending on the distribution of the data. Only miRNAs with a cut-off of cycle threshold (Ct) < 32 were considered in PBMCs while no cut-off was applied in the case of serum since in this fluid, the quantities of starting materials are much lower. Correlations were calculated using the Spearman method. For the Bland-Altman analysis, the association between the difference and the average was evaluated by the coefficient of correlation and tested by the non-zero correlation test. Wilcoxon test was used to assess whether the median difference (bias) between the two conditions was significantly different from 0 and the limits of agreement were defined as median difference +/−1.96 SD. The thermodynamic stability of miRNAs (kcal/mol) was calculated using Quikfold from the DINAMelt web server (http://mfold.rna.albany.edu/?q=DINAMelt/Quickfold) .
Reproducibility of miRNAs expression profiles using TLDA cards
Comparison of RNA quality and quantity
Assessment of quantity and quality of RNA isolated
Total RNA: Mean quantity (ug/1×106 cells or ml serum) (SD)
Ratio OD (260 nm/280 nm) (SD)
Agilent Nano 6000 Chip
Total RNA: Mean Quantity (ug/1×106 cells or ml serum) (SD)
RIN mean (SD)
Total RNA: Mean quantity (ug/1×106 cells or ml serum) (SD)
Ratio OD (260 nm/280 nm) (SD)
Second, the quantity and quality of RNAs extracted from the serum samples were analyzed. No significant difference was observed in term of RNA quantities as measured by Nanodrop (Table 1B). Likewise, Agilent small RNA chip analyses did not indicate significant difference in small RNA and miRNAs quantities, although, for some samples, the MN extraction kit yielded higher quantities (Additional file 1: Figure S1 and Table 1B, mean miRNAs concentration of 80, 22 and 11 ng/mL for MN, Qiagen and Norgen extraction protocols, respectively). However the quality of RNA obtained with the MN isolation kit was higher (as indicated by the ratio miRNAs/smallRNA, 61.3%) compared to those obtained with the two other kits (44.5% with Qiagen and 32.9%, p = 0.026 with Norgen-t-test). Again, RIN variability obtained with the Norgen kit was higher than that observed with the two other kits (Table 1, compared sd = 0.52 vs. 0.11 (MN) and 1.4 (Qiagen)). As previously observed , the 260 nm/280 nm ratio (<1.8) did not appear as a relevant parameter to assess the miRNA quality in serum. Overall, the MN kit seemed to yield better results compared to the two other kits. However, the Norgen kit presented some inconstancy in term of RNA quality extracted from both PBMCs and sera. We therefore decided to pursue our comparison by TLDA profiling focusing on the MN and Qiagen kits. It is worth mentioning that the MN kit has never been extensively tested.
Comparison of PBMCs and serum miRNAs profiles
In the case of serum samples, more variability in the number of miRNAs detected by TLDA for each isolation methods was observed within the biological triplicate (Additional file 2: Figure S2B, Bland-Altman analysis, mean differences ranging from 0.04 to 2.45). However, no significant difference in the Ct values of commonly detected miRNAs (Figure 3D) was observed (p = 0.33 for MN and p = 0.85 for Qiagen extraction kit, Kruskal-Wallis test). 83 miRNAs (11%) were amplified from serum after MN extraction while 41 miRNAs (5.4%) could be detected after Qiagen extraction (Figure 3D). 36 miRNAs were commonly detected with both kits (Figure 3D). Quantities of miRNAs detected in serum samples were very low, with median Ct values around 34 (Figure 3D). Nonetheless, the miRNAs expression profiles evaluated with RNA isolated from both extraction kits correlated (ρ = 0.71, p < 0.0001, Figure 3E). The amounts of miRNAs detected with both kits were similar, with a mean difference of −0.5 (Figure 3F). Only two miRNAs had Ct values outside the limits of agreement of the Bland-Altman test (Figure 3F). Overall, our results indicated that miRNAs profiles from serum samples could be highly variable. These results confirmed that robust statistical tests should be performed when evaluating the potential of circulating miRNAs as diagnostic/prognostic markers . Moreover, we provide evidence that the NucleoSpin miRNAs Plasma kit from Macherey-Nagel is more efficient in extracting miRNAs from serum than the Qiagen miRNeasy mini kit as it allowed detecting twice as many miRNAs.
Impact of the quantity of the starting biological material on miRNAs profiles
To investigate whether these observations were limited to the MN kit or whether RNA extraction with the Qiagen kit could introduce similar bias. Total RNAs were extracted from 1×106 or 3×106 PBMCs using the Qiagen miRNeasy mini kit and further profiled with TLDA cards. Similar to the results obtained after MN extraction, a Bland-Altman plot of the Ct values of the 61 miRNAs detected in both settings showed that the mean difference in Ct values of miRNAs detected in 3×106 cells vs 1×106 cells equaled −1 (Additional file 3: Figure S3A). This difference tends to correlate with the GC content (ρ = 0.29, p = 0.02, Additional file 3: Figure S3B although to a lesser extent, than observed in the case of MN extraction. Together these results confirmed at a genome-scale level and for two different miRNAs extraction kits previous observations made with Trizol RNA extraction procedures from human cell lines . Kim et al. also reported that miRNAs extraction could be biased by RNA structures . The existence of such bias was evaluated in our settings but any significant correlation was observed between the thermodynamic stability of miRNAs, as assessed by Quikfold, and the difference in Ct values (Additional file 4: Figure S4). Hence, this suggests that the extraction procedures used here did not introduce biases related to miRNA structures (Additional file 4: Figure S4).
Circulating miRNAs have recently emerged as non-invasive biomarkers of diverse pathologies. For a routine clinical use, technical standardization in the preparation of the samples and profiling methods are therefore important. The first factor that can affect the reproducibility of results is the quality of isolated RNA from human blood samples. In this study, we performed an independent cross-comparison of three extraction procedures for miRNA isolation from human blood samples using Macherey-Nagel, Qiagen, and Norgen kits. In order to facilitate comparison, we have deliberately chosen not to modify the manufacturer’s protocols. The originality of our study is that we compared miRNA profiles based on a TLDA platform.
The miRNAs were further profiled using the genome-scale Taqman Low Density Array technology. We indeed verified that this technology was reproducible in term of qPCR (ρ = 0.93) and RT (ρ = 0.90), with good agreement in Bland-Altman plots. Similarly, Chen et al. tested TLDA reproducibility on miRNAs detected in two different RTs and two different qPCRs using rodent cards and RNAs isolated from proliferating murine myoblast cells with Trizol method (from 500 ng RNA without pre-amplification and from 150 ng with or without pre-amplification) . The comparison of the two replicates showed a strong correlation (ρ =0.978 for experiment using 500 ng RNA and ρ = 0.985 and ρ = 0.990 using 150 ng without and with pre-amplification, respectively). Wang and colleagues observed a correlation coefficient of 0.812 in the TLDA results using the same sample (human osterosarcoma xenografts, RNA isolated by Trizol, no pre-amplification) . Jensen et al. tested specificity, reproducibility and sensibility of TLDA and miRCURY platforms using both synthetic miRNAs and plasma samples isolated by miRNeasy kit from Qiagen . Concerning TLDA platform (protocol with pre-amplification) and plasma sample, reproducibility was assessed from one sample using two separate RT reactions and the products of each reaction were used in separate qPCR amplifications. The comparison of every duplicate pairs demonstrated a median correlation coefficient of 0.96 (cutoff Ct < 30) .
Given that, the 3 kits were first compared for their performances in extracting miRNAs from PBMCs in term of RNA quantity and quality. However, the new Macherey-Nagel kit was more efficient in extracting miRNAs from sera. Another advantage of this kit is that, unlike the Qiagen and Norgen extraction kits, it does not require the cumbersome phenol/chloroform step. Several previous reports have compared miRNAs extraction kits. Notably, Kroh et al. have tested variations on two extraction kits from plasma and serum samples: Ambion mirVana PARIS (with addition of an additional organic extraction step), and the Qiagen miRNeasy kit (with a modified protocol to use 10 volumes of Qiazol reagent per volume of plasma or serum). They showed that, although both protocols have proven effectiveness, the Qiagen protocol appears to produce 2–3-fold greater RNA yield . Likewise, Li and colleagues evaluated the performances of the miRNeasy kit (Qiagen, CA), the miRVana PARIS kit (Ambion, TX) and the total RNA isolation kit (Norgen Biotek, Canada) . They concluded that RNAs isolated by the Qiagen or Ambion kits had better quality (in terms of % of miRNAs in small RNA fraction) than those extracted with the Norgen kit. In term of RNA quantity, the concentrations of miRNAs in serum were 49 pg/μL, 29 pg/μL and 12 pg/μL from the Qiagen, Ambion and Norgen kits, respectively. Here, we obtained comparable amount of RNAs ranging from 11 (Norgen) to 80 (Macherey-Nagel) pg/μL.
Using TLDA profiling, we showed that the Macherey-Nagel kit allowed the detection of more miRNAs than the Qiagen kit (83 vs 41) in serum. Previous reports have shown a higher number of miRNAs detectable from serum samples by TLDA (around 170 miRNAs with RNA isolation with the Qiagen miRNeasy or the Ambion miRVana miRNA kits) [23–26]. However, in these studies, TLDA experiments were performed on serum pool of 10 to 20 samples.
One striking finding in our study is that, comparing two different volumes of serum or PBMCs numbers used to extract miRNAs with the Macherey-Nagel or the Qiagen kits, we showed that the quantity of the biological samples directly impacted the GC content of the miRNAs detected. These results are reminiscent of the results obtained by Kim et al., who showed that specific miRNAs can be lost during RNA extraction using TRIzol protocol (not with the Ambion miRVana miRNAs kit) depending on their GC content and their thermodynamic stability . These results were obtained using cells from different density culture as starting RNA materials and miRNAs were detected by northern blotting. With these findings, Kim et al. hypothesized that small RNAs could require larger RNA carriers . However, our results do not support this hypothesis as we found similar GC content bias in serum samples (Figure 4B) wherein no large RNAs was detected (Additional file 1: Figure S1B). We rather postulate that the presence of additional compounds (proteins and/or lipids that are associated with miRNAs, [27, 28] and whose quantity increase with starting material) can affect the nature of the miRNAs extracted. These compounds could further be lost during the RNA purification procedure implying that their concentrations would not show intrinsic linear relationship between cell input and total RNA. However, their presence in the initial steps of the purification could truly influence the GC composition of the purified RNAs. Together with that of Kim et al., our study support the use of identical quantities/volumes for starting materials to compare miRNA profiles.
Overall, our results emphasize the importance of comparing miRNAs extraction protocols in order to standardize RNA isolation and to compare miRNAs profiles. In fact, numerous high-profile preclinical studies have already yielded conflicting data and outcomes due to differences in methodologies [29, 30]. There is therefore an urgent need of protocol standardization to enhance the future prospects of extracellular miRNAs in diagnosis, prognosis, and surveillance, even in therapeutic application. These types of study are all the more warranted, as the assays based on the extracellular miRNAs expression signatures prove useful as a noninvasive test to guide a physician’s clinical decision on comprehensive management of patients.
This work was supported by Theradiag compagny, as part of a collaborative research project between Prestizia (Theradiag’s affiliate), University of Montpellier 2 and CNRS (#CNRS---069146/UM2---2110797). SB, MM, TG, VC and CHL are supported by the Centre National de la Recherche Scientifique (CNRS). DB is supported by Theradiag. We thank O. Prigneau (Theradiag), for critical reading of the manuscript and providing constructive comments. We are grateful to the EFS and the anonymous blood donors for their contribution.
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