To study the function of genes and biological pathways, researchers often use techniques such as RNA interference (RNAi) to modify gene expression.1 In RNAi experiments, it is important to determine the efficiency of the gene knockdown, but there are significant challenges associated with commonly used techniques. One method is to use transfected reporter constructs; however, this technique cannot reveal endogenous gene expression and can negatively affect cell health. The most widely used detection methods destroy cell samples through lysis or permeabilization and fixation, and yield results that only reflect the average expression of the gene in the whole cell population.
SmartFlare™ RNA detection probes (EMD Millipore, Billerica, MA) address these issues with their noninvasive approach to interrogating gene expression and ability to sort and separate live cells that can be directly used for downstream analysis. The probes, which can detect target mRNA and microRNA levels in live, intact cells, enable users to quickly verify gene expression and isolate desired cell populations. In addition, they require no sample preparation or carrier agent to enter cells. They also have no toxic effect on cell health, leaving cells intact and allowing for downstream studies.2
Using this approach, accurate, efficient detection of small interfering RNA (siRNA)-mediated gene knockdown has been demonstrated using a probe specific for a target of interest. The probes allow fast and accurate detection of target gene expression at single cell resolution. The ability to specifically detect RNA levels on a cell-by-cell basis provides new opportunities to link biological pathways and physiological processes to gene functions.
Materials and methods
Messenger RNA (mRNA) knockdown
SCC12 (human squamous cell carcinoma) and LNCaP (human prostate adenocarcinoma) cells were seeded in 96-well plates at 10,000 cells/well. Twenty-four hours after seeding, the cells were transiently transfected with control or survivin-targeted siRNA and incubated for 48 hr. Survivin is an antiapoptotic gene that is highly upregulated in many cancer cell lines.3 After the incubation period, the medium was changed to remove the siRNA and transfection agent.
After the siRNA treatment, the SCC12 and LNCaP cells were incubated with 1000× dilution of stock survivin-specific SmartFlare probe or control SmartFlare probe overnight in cell growth medium. The next morning, cells were trypsinized and analyzed using the guava® easyCyte™ 8HT flow cytometer (EMD Millipore). Concurrently, siRNA-treated cells not interrogated with SmartFlare probes were also harvested for comparative analysis by quantitative reverse transcription-polymerase chain reaction (qRT-PCR).
Total RNA was extracted using the RNeasy™ kit (QIAGEN, Germantown, MD) and added to the TaqMan® RNA-to-Ct™ 1-step kit (Life Technologies, Grand Island, NY). qRT-PCR was carried out using a LightCycler® 480 system (Roche Diagnostics Corp., Indianapolis, IN).
TaqMan probe: 5’-TGGTGCCACCAGCCTTCCTGTG-3’
Sense primer: 5’-GCACCACTTCCAGGGTTTATTC -3’
Antisense primer: 5’-TCTCCTTTCCTAAGACATTGCTAAGG-3’
TaqMan probe: 5’-ACCACAGTCCATGCCATCACTGCCA-3’
Sense primer: 5’-CAAGGTCATCCATGACAACTTTG-3’
Antisense primer: 5’-GGCCATCCACAGTCTTCTGG-3’
mRNA detection by flow cytometry
To detect gene knockdown, survivin-targeted probes were incubated with SCC12 and LNCaP cells that had been treated with survivin and control siRNAs. Differences in expression levels of the target gene were detectable using flow cytometry analysis of cells treated with target-specific probes (Figure 1).
Figure 1 – Survivin gene knockdown in LNCaP and SCC12 cells was distinguishable by measuring relative SmartFlare signals. Histograms of SmartFlare signals corresponding to survivin expression in a) LNCaP cells and b) SCC12 cells, with or without siRNA knockdown of survivin.
mRNA detection by qRT-PCR
To detect gene knockdown using qRT-PCR, survivin-targeted SmartFlare probes and control probes were incubated with SCC12 and LNCaP cells that had been treated with survivin and control siRNAs. Relative gene expression levels determined using SmartFlare technology were plotted as bar graphs and compared with qRT-PCR data. This comparison showed that the relative gene expression levels were qualitatively similar regardless of which technology was used to measure knockdown (Figure 2).
Figure 2 – Survivin gene knockdown in LNCaP and SCC12 cells by RNAi are distinguishable by SmartFlare detection as well as by qRT-PCR. a) Survivin expression in LNCaP cells with or without survivin knockdown as determined using SmartFlare technology and analyzed by flow cytometry. b) Confirmation of relative survivin expression levels with or without survivin knockdown in LNCaP cells by qRT-PCR. c) Survivin expression in SCC12 cells with or without survivin knockdown as determined using SmartFlare technology and analyzed by flow cytometry. d) Confirmation of relative survivin expression levels with or without survivin knockdown in SCC12 cells by qRT-PCR.
Because SmartFlare technology enabled the researchers to analyze expression in individual, intact cells, they obtained additional information about the population distribution of the various treated cells. Specifically, they observed that LNCaP cells treated with a survivin-specific SmartFlare probe exhibited a unimodal distribution of survivin signal, while SCC12 cells displayed a bimodal distribution.
The ability to detect intracellular gene expression in individual, live cells was demonstrated using SmartFlare technology. This is crucial when performing RNAi-mediated gene knockdown studies, in which it has been traditionally difficult to determine the cause of incomplete knockdown. Specifically, traditional methods of RNA measurement (which measure average RNA levels) cannot distinguish between inefficient knockdown due to a poorly designed siRNA sequence, inefficient entry of the siRNA into target cells, or vast differences in endogenous gene expression within the target cells.
Use of this technology reveals the degree of gene expression knockdown in individual cells, thereby providing information on cell-to-cell variation in expression, knockdown, and efficiency of siRNA entry. Such information may greatly facilitate the interpretation of analyses performed subsequent to RNAi treatment.
Furthermore, the technology makes it possible to sort cells and return them to culture, enabling downstream analyses, such as antibody staining, flow cytometry, and qRT-PCR. As a result, it is now possible to measure physiological changes in the exact same cell samples assessed for gene knockdown, increasing the strength of observed correlations between gene expression and cell phenotype.
- Hannon, G.J. Nature 2002, 418, 244–51.
- Seferos, D.S.; Giljohann, D.A. et al. J. Am. Chem. Soc. 2007, 129, 15,477–9.
- Ambrosini, G.; Adida, C. et al. Nat. Med. 1997, 3, 917–21.
- Carrasco, R.A.; Stamm, N.B. et al. Mol. Cancer Ther. 2011 Feb, 10(2), 221–32.
- Tang, Y.; Kesavan, P. et al. Mol. Cancer Res. 2004 Feb, 2(2), 73–80.
Don Weldon is R&D Manager, and Grace Johnston, Ph.D., is Segment Market Manager, EMD Millipore, 28820 Single Oak Dr., Temecula, CA, 92590, U.S.A.; tel.: 951-514-4566; e-mail: firstname.lastname@example.org.