Functional microRNA screening using a comprehensive lentiviral human microRNA expression library
© Poell et al; licensee BioMed Central Ltd. 2011
Received: 18 August 2011
Accepted: 3 November 2011
Published: 3 November 2011
MicroRNAs (miRNAs) are a class of small regulatory RNAs that target sequences in messenger RNAs (mRNAs) to inhibit their protein output. Dissecting the complexities of miRNA function continues to prove challenging as miRNAs are predicted to have thousands of targets, and mRNAs can be targeted by dozens of miRNAs.
To systematically address biological function of miRNAs, we constructed and validated a lentiviral miRNA expression library containing 660 currently annotated and 422 candidate human miRNA precursors. The miRNAs are expressed from their native genomic backbone, ensuring physiological processing. The arrayed layout of the library renders it ideal for high-throughput screens, but also allows pooled screening and hit picking. We demonstrate its functionality in both short- and long-term assays, and are able to corroborate previously described results of well-studied miRNAs.
With the miRNA expression library we provide a versatile tool for the systematic elucidation of miRNA function.
MicroRNAs (miRNAs) were discovered as a class of small regulatory molecules ten years ago [1–3]. These ~21 nucleotide (nt), small RNAs recognize partially complementary sequences on target mRNAs [4, 5]. Following the initial discovery of miRNAs, substantial effort has gone into characterization of the canonical miRNA pathway [6, 7] and into miRNA discovery; by identifying miRNAs in more species and by adding to the list of known miRNAs . Although cDNA cloning and northern blotting techniques can be used to detect the most abundant miRNAs, the advent of massively parallel sequencing technologies has propelled the miRNA field, allowing for both discovery and quantification of all miRNAs in a given sample [9, 10].
With the bulk of the miRNAs revealed in commonly studied species, the next challenge lies in elucidating the biological processes in which miRNAs play a role. Current bioinformatic approaches rely on the identification of partially complementary sequences in mRNAs to predict miRNA targeting. Yet these approaches still come with one limitation; the exact parameters governing targeting remain unknown. Several prediction algorithms have been developed to overcome this difficulty by ascribing different weights to key parameters, such as binding energy between target and miRNA, conservation of the target site, quality of the "seed pairing", et cetera . Still no single algorithm emerges as the best performer , and most algorithms predict thousands of targets for each miRNA . Combining different target prediction algorithms generates shorter list of targets by creating more stringent cut-offs. This can provide some enrichment in true positives, but at the cost of more false negatives . In addition to bioinformatics prediction, several approaches to genome-wide experimental miRNA target identification have been developed. These experiments utilize Argonaute pull-down assays (HITS-CLIP and PAR-CLIP) [15, 16], changes in mRNA levels , and protein expression after introduction or ablation of a specific miRNA [18–20]. These studies support that miRNAs indeed function by targeting hundreds of genes. Still, it is a daunting task to derive a function for a miRNA from these long lists of potential target genes. Despite progress in systematic approaches to find sets of related gene that are enriched within these long target lists , we are still far from satisfactory in silico prediction of miRNA function.
Alternatively, differential expression of a miRNA is commonly used to infer its function [22, 23]. Identification of conditions where a specific miRNA is expressed versus an opposing condition where it is not, offers some clues as to the potential action of the miRNA. While this approach has been very successful in leading investigators to uncover miRNA functions, it still requires direct experimentation to prove effects due to miRNA activity beyond providing an only coincidental biomarker.
Another approach to determine the function of a miRNA is by knocking it down [24–26], or knocking it out, of the genome of a model organism [27–29]. Experimental knockdown of miRNAs may confirm or invalidate predicted functions, but it requires prior knowledge where a miRNA is expressed. Even with this knowledge, sufficient knockdown to demonstrate an observable effect is not guaranteed. Complete knockout delivers a clean result, but may not result in an obvious phenotype. Adding to this challenge is the possibility that many miRNAs may elicit only subtle changes or are redundant with other family members entirely. Indeed, only a fraction of all C. elegans miRNA families display pronounced abnormal phenotypes when deleted . Given these challenges, knocking out a miRNA in mice or in a human cell line may often prove a fruitless endeavor.
In order to unravel the functions of specific miRNAs, while overcoming much of the challenges discussed above, we proposed to introduce or overexpress miRNAs in a system of interest. Moreover, we argue that it is more efficient to examine the effect of any miRNA for a predetermined phenotype, rather than blindly investigating one miRNA at a time. Such screens have been performed on different scales. Most are based on transfection of miRNA mimics ; synthetic RNAs that usually have a modified backbone. Although this approach ensures the presence of the mature miRNA in the target cells, a miRNA mimic is not processed via the canonical miRNA biogenesis pathway. This multi-cleavage process starts with the recognition of a hairpin in the primary transcript and ends with a mature miRNA produced from one or both of the arms of the hairpin . Bypassing this physiological processing step has several implications. For instance, several variants of a miRNA from the same primary transcript can arise due to variations in the processing pathway, such as arm switching, non-templated additions of adenines or uracils, and variations in the 3' and 5' cleavage sites [33, 34]. Besides the loss of miRNA variants, the most-widely used miRNA mimics have modified backbones to increase stability within the cell. Consequently, they are not cleared naturally from the cells as endogenous miRNAs. Furthermore, it is possible that miRNA mimic transfection achieves cellular concentrations beyond physiological relevance. On the other hand, loading into the RISC complex, which is essential for biological activity, is not necessarily efficient for mimic transfection, as this process is known to be coupled to hairpin processing [35, 36]. To express transcripts for endogenous processing into mature miRNAs, plasmid  or viral vectors [38, 39] can be employed. While the retroviral library described by Agami and colleagues is a valuable tool for miRNA functional screens in pooled format, the viral supernatants are not available as individual isolates amenable to arrayed high-throughput screens .
Here, we describe the construction and application of a lentiviral human miRNA expression library. This library contains 660 annotated human miRNAs and 422 candidate miRNAs [10, 40]. All are expressed from their genomic backbone, ensuring physiological processing of the miRNAs. The library is organized for high-throughput screening to provide a resource for the systematic elucidation of miRNA function. In addition, all lentiviral miRNA expression constructs can be applied individually to evaluate primary results. Lastly, we demonstrate the utility of this library in various types of screens to present the miRNA expression library as a versatile tool to study miRNA function.
Results and Discussion
Approach and setup
We aimed for the construction of a miRNA expression library that fulfills four criteria: 1) the library contains all human miRNAs; 2) each miRNA is represented in a separate stock to allow for arrayed screening; 3) the library can be used over a wide range of different cell types; 4) the miRNAs are swiftly and stably overexpressed. The first two criteria will be discussed below. The third and fourth criteria were met by choosing a lentiviral expression system, employing the pCDH vector. The lentiviral particles express VSV-G, a glycoprotein that grants broad tropism . The glycoprotein's receptor is a lipid component of the plasma membrane that occurs on most cell types over a wide range of species. Lentiviruses integrate into the host genome , but unlike other retroviruses, lentiviruses do not require cell division for genomic integration [43, 44]. For instance, the lentivirus is able to transduce quiescent stem cells and terminally differentiated neurons . By integrating into the host genome, the construct is retained through cell divisions and can be stably expressed for an indefinite period of time. We chose a lentiviral backbone with a puromycin-resistance cassette to be able to select for successfully transduced cells .
To create a comprehensive library containing all human miRNAs, we included all miRNAs known at the time we started composing the library. We obtained genomic loci from the widely adopted miRBase miRNA repository (version 14) . We also included a set of candidate miRNAs from previous experiments [10, 40]. Although we did not update the library after viral particles for the entire library were produced, some of the candidate miRNAs have since entered the registry. See additional file 1, table S1 for a list of the current annotation of all miRNAs in the library.
As mentioned, lentivirus is a favorable vector for its ability to transduce cells that are hard to transfect, such as stem cells. We have successfully transduced primary human intestinal cells using a GFP-encoding vector. These cells were subsequently used to create intestinal organoids in vitro. After prolonged culture, entire organoid bodies turned fluorescent, indicating the stem cells from which the organoids developed were also successfully transduced (Figure 2c).
Overexpression of miRNAs in various cell lines after lentiviral transduction
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For long-term experiments, it is necessary for miRNA expression to be sustained. 72 hours after infection with let-7a or miR-372, we passaged A375 cells and cultured them either with or without puromycin selection. We examined miRNA expression by miRNA qPCR at 5, 9 and 20 days after infection (Figure 3c). A decline in miRNA expression was observed with both miRNAs between day 3 and day 5 after infection. This may be caused either by passaging or changed culture conditions, but it is also possible that it is a secondary effect of highly elevated miRNA processing. This effect was markedly stronger in the let-7a-infected cells, which may indicate that there is a selection disadvantage for cells with high let-7a expression. Despite the small drop after three days, overexpression of both miRNAs stabilized and persisted for weeks. Even after prolonged culture without puromycin selection, miRNA overexpression was sustained. We conclude there is little or no genetic loss or epigenetic silencing of the integrated construct.
For the entire library, we performed an arrayed screen by MTS assay, which measures the viability of cells in a well . This measure is reported to correlate strongly with cell number. All samples were tested in duplicate, and for each replicate a B-score was calculated . This method calculates how a miRNA scores relative to the other miRNAs on the same plate. It is a robust method as it is not sensitive to outliers. B-scores of replicates are shown in Figure 5b. Also shown are the measures for all let-7a constructs and miR-372. The strong correlation between replicates indicates a high reproducibility of the assay. The effects of let-7a and miR-372 are similar as in the cell count assay. Importantly, all let-7a constructs cluster together. Since these constructs have different backbones but produce the same mature miRNA, we surmise the observed effects are likely to be caused by the mature miRNA. A confounding factor in short-term arrayed screens can be the range of virus titers of the different constructs. However, we saw no correlation between virus titer and cell viability (additional file 3, figure S1). Thus, with these experimental conditions, virus titers were not a significant factor contributing to toxicity.
In a pooled invasion screen, as performed above, the possibility exists that a portion of the hits can be "passenger hits" that do not impart invasive capacity, but are present in cells that trail the truly invasive cells as they make their way through the extracellular matrix. To distinguish these two types, we subjected each hit individually to an invasion assay. We were able to confirm 23 miRNAs that increase invasiveness of HCT15 cells (Figure 6b).
We present a lentiviral miRNA expression library that is optimized for use in arrayed screens. The library allows miRNAs to be individually assessed in any gain-of-function screen. We envision the library being used in a wide range of functional screens. To name some possibilities: reporter-based assay screens, screens to study cell cycle, senescence, and epithelial-to-mesenchymal transition. The broad tropism of the lentivirus makes it applicable to infect cells of different species. This may prove particularly valuable, since lentivirus can be directly used in vivo. Thus, the same lentivirus can be used to screen for a miRNA function in vitro and verify this functionality in vivo.
We have demonstrated the transduction of stem cells that were subsequently used for in vitro organ culture. The ability to stably transduce stem cells opens up avenues for studying miRNAs required for differentiation and stemness.
An arrayed library comes with several advantages. Arrayed screening offers more sensitivity and faster results than pooled screening, without the need of data deconvolution. It also allows for the assessment of several more complex parameters, as is commonplace in high-content screens. Assays that require long-term culture may not be amenable to arrayed screening and require pooling. Still, infecting cells individually before pooling is likely to decrease false-negative results in pooled screens, suggesting that even for pooled screens an arrayed library may be preferred.
Our library currently contains the majority of all human miRNAs. However, the most recent update (version 17) of miRBase includes a large number of newly identified miRNAs. While we do not wish to question their validity or understate their potential, we argue that most miRNA functions will be covered by the most highly expressed or broadly conserved miRNAs, which were already present in earlier versions of miRBase and thus represented in our library. By the same token, the merit of candidate miRNAs in our library can be questioned. In anticipation of this, candidate miRNAs were positioned on separate plates in the library, presenting researchers the choice to screen the entire library, only the annotated miRNAs, or only the candidate miRNAs.
Expression of the miRNAs from their native genomic background ensures the physiological processing of the miRNA. Not only the pre-miRNA hairpin, but also the flanking sequence contributes to proper processing . Transcribing the miRNA from an integrated construct enables expression of both arms and all isomiRs that would naturally derive from the primary transcript. Therefore, the library could be employed for further characterization and validation of the included miRNAs. Such experiments have been extensively done for mouse miRNAs , but not for human miRNAs.
We have shown that ectopic expression of miRNAs using a lentiviral vector can be used to screen for biologically relevant effects. While the library is widely applicable and can be used to study various aspects of biology, our primary focus is on cancer-related processes. A first screen assessing miRNA-induced effects on melanoma cell growth demonstrated the value of the library in an arrayed screen. The next step is to perform such screens over a panel of cell lines to determine which miRNAs may have a growth effect on specific cancer indications, and which miRNAs have a general growth inhibitory or stimulatory function. These results will aid in finding miRNAs suited for tumor-specific treatment. Indeed, such therapeutic options have been successfully explored in a murine model of hepatocellular carcinoma . With the miRNA expression library, we offer a platform that facilitates the identification of miRNAs with therapeutically relevant functions.
Construction of the lentiviral library and other constructs
Backbone for all constructs in the library is the lentiviral expression construct pCDH (cat. no. CD510B-1, System Biosciences). Individual loci containing a single miRNA hairpin were PCR amplified from human genomic DNA and cloned into the multiple cloning site of the plasmid. Loci were either obtained from miRBase http://mirbase.org/ or from mapping of candidate miRNAs found in previous experiments [10, 40]. Primers were designed using Primer3. PCR was performed using Pfu polymerase (Agilent). The cloned fragments contain the full-length miRNA hairpin and approximately 100 flanking base pairs on both sides. An expression construct with EGFP was cloned by excision and ligation of the EGFP sequence from pEGFP-N1 (Clontech) into the multiple cloning site of pCDH. All constructs were packaged into lentiviral particles commercially by System Biosciences using the pPACKH1 HIV-based lentiviral packaging kit (cat. no. LV500A-1, System Biosciences). Viral particles were recieved in concentrated form with a median titer of 5.9*108 IFU/mL in a 96-well format. Sequence of all inserts was confirmed from both the plasmid and the virus supernatant (we were able to obtain high-quality specific sequences from the virus supernatant using universal primers, most likely due to trace amounts of plasmid). A list of all included miRNAs in their current annotation (miRBase17) is available in additional file 1, table S1. Lentiviral particles for pCDH with copGFP instead of puroR (cat. no. CD511B-1) were ordered separately from System Biosciences.
Cell culture and viral infections
293T, A375, MDA-MB-231, A549, MCF-7, IMR-90, PC-3, and HCT15 cells were maintained on 10% FCS complete medium: DMEM Glutamax (GIBCO) with 10% FCS (Sigma) supplemented with non-essential amino acids (GIBCO) and penicillin/streptomycin (GIBCO). All viral infections followed by RNA isolation were done 8 hours after seeding 10, 000 cells in a 6-well plate in 2 mL 10% FCS complete medium. All transduction efficiency experiments were performed by infection with pCDH-MCS-EF1-copGFP, except for the organoid culture, for which we used pCDH-EGFP-EF1-PuroR. Infection mix contained 2 μL virus supernatant, 12 μL 1 mg/mL polybrene (Sigma), and 86 μL PBS0, unless stated otherwise. Intestinal organoid bodies were cultured as described before . Because the organoids are grown in Matrigel, cells were infected before seeding. Cells were infected in 250 μL Wnt-3a-conditioned medium containing 2 μL virus supernatant. Infection took place during a centrifugation step at 150 rcf for 1 hour at room temperature. Unless indicated otherwise, infections were performed in 96-well plates using the following set-up: 1000 cells were seeded in 100 μL 5% FCS complete medium per well of a 96-well plate and infected after 8 hours with 10 μL infection mix. 10 μL infection mix contained 0.6 μL 1 mg/mL polybrene, 0.5 μL virus supernatant, and 8.9 μL PBS0. In the arrayed screen, medium was replaced with 150 μL fresh medium 24 hours after infection.
Five days after infection, 30 μL MTS One Solution (Promega) was added to all samples. After each hour, plates were gently tapped to disperse the coloration of the MTS, and absorbance was measured at 492 nm. Last measurements were taken 4 hours after start of the assay. The time point with measurements showing the highest dynamic range without saturation of signal was used for data analysis.
Nuclear staining, GFP quantification and high-content applications
Five days after infection, 100 μL 8% PFA (Sigma) was added to all samples. Cells were fixed for 15 minutes. Samples were washed once with PBS0 followed by 10 minutes staining in 100 μL PBS0 containing 0.5 μg/mL Hoechst 33342 (Sigma). Cells were washed twice with PBS0 and kept on PBS0 at 4°C. Cells were quantified on a Cellomics ArrayScan VTI using the accompanying software by counting nuclei in 4 fields per well under 10× magnification. Nuclei were identified as shapes with a contiguous Hoechst stain. Nuclear demarcations were used to quantify GFP intensity. All data acquisition was done using adaptions of the TargetActivation program of the ArrayScan software. Data and images displayed in table 1 and Figure 4 were generated by Cenix BioScience, GmbH.
RNA isolation and miRNA qPCRs
RNA was isolated using TRIzol (Invitrogen) isolation following the manufacturer's protocol. Small RNAs qPCR reactions were performed using the TaqMan MicroRNA reverse transcription kit (ABI), Taqman MicroRNA qPCR assays (ABI) and TaqMan Universal PCR Master Mix, No AmpErase UNG (ABI) using 10 ng total RNA input. qPCR reactions were set up using the suggested reaction conditions on a Bio-Rad MyiQ thermal cycler. U6 was used as a housekeeping control RNA in the experiments concerning Figure 3, RNU6B was used in the experiments concerning table 1. Relative expression was calculated using the 2-ΔΔCt method. miRNA qPCR data in table 1 were generated by Cenix BioScience GmbH.
HCT15 cells were seeded at 2500 cells per well in a 96-well plate in 10% complete medium. Cells were infected with individual virus supernatants (0.5 μL per well) after 24 hours. 72 hours after infection cells were selected with puromycin-containing medium and subsequently grown to 100% confluency. Pools were made of 40 samples per pool and grown for another 3 days on puromycin-containing medium. Half of the pooled culture was used for genomic DNA isolation, the other half was subjected to two rounds of invasion assay. For each pool, 2*105 cells were applied to the upper compartment of a Boyden chamber (BD Fluoroblok 24-Multiwell, 8 μm pores) coated with extracellular matrix (ECM, Sigma) and containing serum-free medium, and allowed to invade the lower compartment containing 10% FCS medium. Cells were collected from the bottom compartment and expanded for 2-3 weeks on complete medium. 2*105 cells of this subculture were applied to a second round of invasion as described above. Cells in the resulting bottom compartment were subcultured to be used for genomic DNA isolation.
Genomic DNA isolation and massively parallel sequencing
Genomic DNA was isolated from cells using a Qiagen Genomic Tip kit following the manufacterer's instructions. For both the invasive fraction and the control fraction, 10 ng DNA of each pool was pooled together and subjected to PCR-amplification (20 cycles) of integrated constructs using Platinum PCR Supermix (Invitrogen) and primers flanking the inserts. In a subsequent, secondary (3 cycles) and tertiary (3 cycles) PCR the adapters and barcodes used for massively parallel sequencing were added to the flanks of the products. Samples were sequenced on the ABI SOLiD platform. The invasive and control fraction yielded 1.0*106 and 0.9*106 reads that mapped to integrated constructs respectively.
Both the plasmid and virus library are publicly available when requested through InteRNA Technologies. Contact information is available at http://www.interna-technologies.com.
This work was financially supported by the Netherlands Genomics Initiative through the Cancer Genomics Center. InteRNA Technologies BV and TI Pharma funded construction of the lentiviral miRNA expression library. We thank T. Sato for assistance with intestinal organoid culture.
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