A simple high-throughput technology enables gain-of-function screening of human microRNAs

Abstract

MicroRNAs (miRs) regulate cellular processes by modulating gene expression. Although transcriptomic studies have identified numerous miRs differentially expressed in diseased versus normal cells, expression analysis alone cannot distinguish miRs driving a disease phenotype from those merely associated with the disease. To address this limitation, we developed miR-HTS, a method for unbiased high-throughput screening of the miRNome to identify functionally relevant miRs. Herein, we applied miR-HTS to simultaneously analyze the effects of 578 lentivirally transduced human miRs or miR clusters on growth of the IMR90 human lung fibroblast cell line. Growth-regulatory miRs were identified by quantitating the representation (i.e., relative abundance) of cells overexpressing each miR over a one-month culture of IMR90, using a panel of custom-designed quantitative real-time PCR (qPCR) assays specific for each transduced miR expression cassette. The miR-HTS identified 4 miRs previously reported to inhibit the growth of human lung-derived cell lines and 55 novel growth-inhibitory miR candidates. Nine of 12 (75%) selected candidate miRs were validated and shown to inhibit IMR90 cell growth. Thus, this novel lentiviral library- and qPCR-based miR-HTS technology provides a sensitive platform for functional screening that is straightforward and relatively inexpensive.

Figure 1

Design of nested PCR strategy and miR-HTS. (A) Illustration of SBI’s miR lentiviral integrants in the host genome (double helices) between the two viral long terminal repeats (LTRs). Positions of the primers and probes used in this study are depicted relative to the features of lentiviral integrant. CMV, cytomegalovirus promoter; miR, miR cassette; EF1α, human elongation factor 1α promoter; GFP, green fluorescence protein. (B) Experimental design of the miR-HTS conducted in this study. Each green circle is a cell transduced with 1 miR lentivirus. The letter in a green circle denotes the miR being overexpressed in the transduced cell. Open circles represent untransduced cells. Green circle with dashed outline depicts a transduced cell disappearing from the culture (e.g. miR-X). The abundance of miR-infected cells at each time point is determined by GRE-qPCR assays, normalized by GFP loading control qPCR assay, and compared to its starting representation at t₀ to calculate fold change in abundance.

Figure 2

Dynamic range of GRE-qPCR assays. (A, B) IMR90 cells separately infected with either miR-155 or miR-222 lentivirus at 20% transduction efficiency were mixed at different ratios as described in the text. Genomic DNA samples were harvested from each mixture and used as templates for each GRE-qPCR assay for either miR-155 (A) or miR-222 (B), to measure the abundance of each lenti-miR barcode. Number of cells infected with either virus (X-axis) was plotted against corrected Ct values (Y-axis; Ct corrected for template amounts). The numbers of cells infected with each virus are labeled above or below each symbol through panels A-D. Regression lines were fitted for cell numbers ≥50 for miR-155 virus infected cells, but for all cell numbers for miR-222 virus infected cells. (C, D) Using the same genomic DNA samples as in panels A and B, the external common forward and reverse primers (illustrated in Figure 1) were used to amplify the miR cassettes from infected cells. Then, purified PCR amplicons were used as templates for each GRE-qPCR assay for either miR-155 (C) or miR-222 (D), to measure the abundance of each lenti-miR barcode. Similar to panels A and B, the number of cells infected with each virus (X-axis, 25-10⁴ cells) was plotted against corrected Ct values (Y-axis). Regression lines were fitted to all cell numbers in panels C and D. (A-D) The r² value of the fitted regression line is provided at the lower right corner of each panel.

Figure 3

Reproducibility of GRE-qPCR assays. (A) The same batch of PCR amplicons (generated using external common primers) was subjected to 304 miR-specific GRE-qPCR assays, in duplicate. The resulting corrected Ct values from each replicate were plotted against each other to examine technical reproducibility of the GRE-qPCR step. Each circle is a different lenti-miR. (B) Two batches of PCR amplicons generated separately were each subjected to 304 GRE-qPCR assays (same assays used in panel A). The resulting corrected Ct values from each batch were plotted against each other to examine the reproducibility of the amplification step using the external common primers. The circles outside of or on the solid lines are GRE-qPCR assays with ≥3 cycles of difference between the 2 batches of templates. The r² value of fitted regression line (not shown) on the lower right corner of each panel.

Figure 4

Results of miR-HTS conducted in IMR90. (A) Venn diagram of all growth-regulatory miR candidates identified from 2 independent miR-HTS replicates, including both growth-inhibitory and growth-promoting candidates. Numbers of candidates identified in the first replicate only (left), the second replicate only (right), and both replicates (middle) were indicated. (B) The average fold changes in abundance of the 2 miR-HTS replicates were log2-transformed, sorted from low to high for each experimental time point. Growth-regulatory miR candidates are located in the shaded area above or below the dashed lines at log2=3 (i.e. t_N/t₀=8) or log2= -3 (i.e. t_N/t₀=0.125). For legibility, data are only shown for miR-HTS replicates whose fold changes are consistent in direction. t₁, t₂, and t₃ were days 11, 19 and 27 post-infection, respectively, corresponding to every 2 passages. (C) Example miR candidates of different growth-inhibitory kinetics were summarized from 2 miR-HTS replicates (mean ± SD). The dashed horizontal line marks Y=0.125; equivalent to 8-fold decrease in abundance. MiR-892b illustrated the candidates that were never detected at any time points examined during the miR-HTS in IMR90.

Figure 5

Validation and characterization of selected growth-inhibitory miR candidates. (A) IMR90 cells were transfected with 10 nM miR mimics as indicated. On day 5 post-transfection, cell growth was assessed by the alamarBlue proliferation assay and normalized to the mock (no miR mimic)-transfected sample (i.e. mock as 100%). The cel-miR-67 mimic and miR-937 were negative controls (hatched bars). MiR candidates were plotted using 4 different bar patterns (black, white, gray, checker board) matching respective growth-inhibitory kinetics illustrated in Figure 4C. Mean ± SE are presented for 3 independent experiments. *, p< 0.05; **, p<0.005; ***, p<0.0005; ****, p<0.0001, each miR mimic versus cel-miR-67. Some of these candidates showed significant growth-inhibition as early as day 3 post-transfection; some showed significant growth-inhibition with 5 nM miR mimics (see Supplementary Figure S2). (B) IMR90 cells were transfected with 10 nM miR mimics. On day 4 post-transfection, caspase-3/7 activity was measured and fold increase in caspase activity was normalized to mock-transfected sample (i.e. mock as 1). Mean ± SE are presented for 3 independent experiments. *, p<0.05, each miR mimic versus cel-miR-67.