Comparison of Reverse Transcription∓Quantitative Polymerase Chain

Comparison of Reverse Transcription∓Quantitative Polymerase Chain

Analytical Biochemistry 427 (2012) 178–186 Contents lists available at SciVerse ScienceDirect Analytical Biochemistry journal homepage: www.elsevier.com/locate/yabio Comparison of reverse transcription–quantitative polymerase chain reaction methods and platforms for single cell gene expression analysis ⇑ Bridget C. Fox, Alison S. Devonshire , Marc-Olivier Baradez, Damian Marshall, Carole A. Foy LGC Limited, Teddington, Middlesex TW11 0LY, UK article info abstract Article history: Single cell gene expression analysis can provide insights into development and disease progression by Received 6 February 2012 profiling individual cellular responses as opposed to reporting the global average of a population. Reverse Received in revised form 10 May 2012 transcription–quantitative polymerase chain reaction (RT–qPCR) is the ‘‘gold standard’’ for the quantifi- Accepted 13 May 2012 cation of gene expression levels; however, the technical performance of kits and platforms aimed at sin- Available online 19 May 2012 gle cell analysis has not been fully defined in terms of sensitivity and assay comparability. We compared three kits using purification columns (PicoPure) or direct lysis (CellsDirect and Cells-to-CT) combined Keywords: with a one- or two-step RT–qPCR approach using dilutions of cells and RNA standards to the single cell Single cell level. Single cell-level messenger RNA (mRNA) analysis was possible using all three methods, although RT–qPCR mRNA the precision, linearity, and effect of lysis buffer and cell background differed depending on the approach RNA standard used. The impact of using a microfluidic qPCR platform versus a standard instrument was investigated for potential variability introduced by preamplification of template or scaling down of the qPCR to nanoliter volumes using laser-dissected single cell samples. The two approaches were found to be comparable. These studies show that accurate gene expression analysis is achievable at the single cell level and high- light the importance of well-validated experimental procedures for low-level mRNA analysis. Ó 2012 Elsevier Inc. All rights reserved. For the majority of gene expression studies, a population mean most commonly used approach in research laboratories [10]. The is taken as a measure of specific gene expression levels. Although MIQE (minimum information for publication of quantitative real- this method is suitable for many studies, it does not yield informa- time PCR experiments) guidelines for reporting of RT–qPCR experi- tion on the differences in expression between cells within a heter- ments [11] call for thorough characterization of RT–qPCR assays ogeneous population or account for transcriptional responses and upstream sample processing steps such as cell isolation and lysis occurring in ‘‘transcriptional bursts’’ [1,2]. Hence, single cell gene that may affect RT–qPCR performance. Validation of the quantitative expression analysis may yield greater insights into cell biology, accuracy of single cell RT–qPCR is important due to the low levels of and this approach has many applications in the fields of diagnos- messenger RNA (mRNA) levels in each sample [12], whereas techni- tics [3], embryology [4], stem cell biology, and tissue engineering cal validation is less straightforward due to the heterogeneous nat- [5]. ure of the samples and limited scope for technical replicates [13]. Global analysis of single cell transcriptomes is possible using There are currently a variety of techniques available to isolate DNA microarray [6] and, more recently, RNA–seq technologies single cells, including micromanipulation, laser dissection micros- [7,8]. However, reverse transcription–quantitative polymerase copy, and FACS (fluorescence-activated cell sorting) [14,15]. chain reaction (RT–qPCR)1 is the ‘‘gold standard’’ for quantitative Whichever single cell isolation method is employed, it is vital to measurement of transcript abundance in single cells [9] and the employ lysis conditions that ensure complete cell lysis [16]. There are several lysis methods in use—some that enable the use of the ⇑ Corresponding author. Fax: +44 0208 9432767. lysate directly in RT–qPCR [10,13] and others that involve cell lysis E-mail address: [email protected] (A.S. Devonshire). and subsequent purification of the total RNA prior to RT–qPCR [17]. 1 Abbreviations used: RT–qPCR, reverse transcription–quantitative polymerase For all of these procedures, there is a need to understand any bias chain reaction; mRNA, messenger RNA; cDNA, complementary DNA; NIST, National that could be introduced due to incomplete lysis, differing elution Institute of Standards; CE, cell equivalent; HFF-1, human foreskin fibroblast-1; yields from purification steps, and potential inhibition of the RT– DMEM, Dulbecco’s modified Eagle’s medium; PBS, phosphate-buffered saline; Cq, quantification cycle; IVT, in vitro transcribed; COL6A1, collagen-type VI alpha 1; qPCR by the presence of lysis components. M6PRBP1, mannose-6-phosphate receptor binding protein 1; TNFR12A, tumor In addition to stringent cell isolation and lysis conditions at low necrosis factor receptor superfamily member 12A; CSF3, colony-stimulating factor mRNA levels, special attention must be given to factors that can 3 (granulocyte); ANOVA, analysis of variance; SD, standard deviation; MMLV, lead to unreliable RT–qPCR data. Several studies have shown that Moloney murine leukemia virus; tRNA, transfer RNA. 0003-2697/$ - see front matter Ó 2012 Elsevier Inc. All rights reserved. http://dx.doi.org/10.1016/j.ab.2012.05.010 RT–qPCR methods for single cell analysis / B.C. Fox et al. / Anal. Biochem. 427 (2012) 178–186 179 at low complementary DNA (cDNA) levels, inhibition of real-time qPCR assays PCR by reverse transcriptase can be significant [18,19]. In addition, obtaining reliable data from copy numbers below 102 per qPCR has Predesigned TaqMan qPCR assays were supplied by Applied Bio- been shown to be problematic and the technical error associated systems (Foster City, CA, USA) as a 20Â premix containing both with both the RT and the PCR steps can become more significant primers and FAM–nonfluorescent quencher (NFQ) probe (see Sup- as the template level decreases [13]. plementary Table 1 in supplementary material). The efficiencies of Alongside reagent kits applicable to single cell gene expression these assays were characterized with a dilution series of HFF-1 analysis, microfluidic PCR platforms such the BioMark (Fluidigm) cDNA (see Supplementary Methods and Supplementary Table 2 [20] and OpenArray (Life Technologies) [21] facilitate thousands in supplementary material). Primers and hydrolysis probe (FAM– of assays to be performed in parallel. This technology has been TAMRA) to ERCC-84 (GenBank accession: DQ883682) were used applied to single cell analysis using both digital PCR (dPCR) [22] as described previously [26] and supplied by Sigma–Aldrich (Poole, and qPCR approaches. The latter enables the analysis of tens UK). The final concentrations of each primer and probe for all as- to hundreds of gene targets in single cells to be performed says were 900 and 250 nM, respectively. RT–qPCR and qPCR were [5,23,24]. Preamplification of template is required for these performed in MicroAmp Optical 96-Well Reaction Plates (Applied high-throughput approaches at the single cell level, although Biosystems). PCR-based preamplification has been suggested to introduce amplification bias [25]. Although the BioMark platform has been Comparison of Cellsdirect, Cells-to-CT, and PicoPure RT–qPCR kits characterized for larger inputs of template RNA [26], the effect using a cell dilution series of preamplification and the scaling down of reaction volumes to the nanoliter scale has not been investigated for the low-level For cell dilutions, the number of HFF-1 cells was determined by mRNA quantities found in a single cell. Recent advances in micro- averaging five counts using a hemocytometer, and the cell suspen- fluidic approaches have also applied miniaturization not only to sion was then diluted in phosphate-buffered saline (PBS) by serial qPCR but also to the cell capture, lysis, and RT steps of single cell dilution to 103,102, 10, and 1 cell(s)/ll(n = 3). Lysates were pre- analysis. Microfluidic chip- and droplet-based technologies enable pared and RT–qPCR was performed using the CellsDirect (Invitro- effective concentration of the mRNA transcripts found in a single gen, Paisley, UK), Cells-to-CT (Applied Biosystems), and PicoPure cell [27–29]. (Arcturus/Life Technologies)/Message Sensor (Ambion) kits accord- In this study, we compared three commercially available RT– ing to the manufacturers’ instructions as described below. For all qPCR kits designed for low-level mRNA analysis (CellsDirect, three kits, 20% of the original lysate was used per RT–qPCR (Cells- Cells-to-CT, and a combination of the PicoPure purification col- Direct and Message Sensor) or per qPCR (Cells-to-CT) (n = 1 RT– umns and Message Sensor RT–qPCR kit) for their suitability for sin- qPCR or qPCR per gene assay). Real-time PCR was performed on gle cell gene expression analysis. The CellsDirect and Cells-to-CT the ABI PRISM 7900HT Sequence Detection System (Applied Bio- kits are designed for direct input of the cell lysate in the RT–qPCR, systems). A DNA standard curve composed of a 10-fold serial dilu- whereas the PicoPure/Message Sensor kit combination involves tion of GAPDH or B2M DNA standards (see ‘‘Preparation of DNA purification of total RNA prior to the RT–qPCR. Dilutions of fibro- standards’’ section below) from 106 to 10 copies (n = 3) was per- blast cells to the single cell level were used to test all technical fac- formed on each qPCR plate to quantify the number of cDNA copies tors contributing to the qPCR measurement, namely efficiency of produced by each RT reaction. In this and other experiments, raw lysis/extraction, RT, and qPCR steps. In addition, an RNA standard data from the 7900HT system were processed using SDS (Sequence (ERCC-84) from the set of controls developed by the External Detection System) software (version 2.3) with automatic baseline RNA Controls Consortium (ERCC), an ad hoc group of 70 members setting and manual threshold setting.

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