Polysome shift assay for direct measurement of miRNA inhibition by anti-miRNA drugs

Abstract

Anti-miRNA (anti-miR) oligonucleotide drugs are being developed to inhibit overactive miRNAs linked to disease. To help facilitate the transition from concept to clinic, new research tools are required. Here we report a novel method--miRNA Polysome Shift Assay (miPSA)--for direct measurement of miRNA engagement by anti-miR, which is more robust than conventional pharmacodynamics using downstream target gene derepression. The method takes advantage of size differences between active and inhibited miRNA complexes. Active miRNAs bind target mRNAs in high molecular weight polysome complexes, while inhibited miRNAs are sterically blocked by anti-miRs from forming this interaction. These two states can be assessed by fractionating tissue or cell lysates using differential ultracentrifugation through sucrose gradients. Accordingly, anti-miR treatment causes a specific shift of cognate miRNA from heavy to light density fractions. The magnitude of this shift is dose-responsive and maintains a linear relationship with downstream target gene derepression while providing a substantially higher dynamic window for aiding drug discovery. In contrast, we found that the commonly used 'RT-interference' approach, which assumes that inhibited miRNA is undetectable by RT-qPCR, can yield unreliable results that poorly reflect the binding stoichiometry of anti-miR to miRNA. We also demonstrate that the miPSA has additional utility in assessing anti-miR cross-reactivity with miRNAs sharing similar seed sequences.

Figure 1.

Schematic overview of available methods for measuring pharmacodynamics (PD) of anti-miR drugs. Following in vivo dosing tissue is harvested and processed for total RNA using phenol/chloroform (Trizol) and cartridge purification. RNA can be analyzed with RT-qPCR using gene specific primers to measure functional changes in miRNA regulated gene expression, or using miRNA primers to measure direct PD/drug-target engagement (TE) by RT-interference. An alternative strategy for measuring direct PD reported herein is the miRNA Polysome Shift Assay, which adds a fractionation step before RNA processing and miRNA RT-qPCR. This adds several benefits as described in the main text.

Figure 2.

RT-interference poorly reflects ratios of anti-miR inhibited miRNA. (A) An in vitro annealing experiment was used to assess the ability of RT-interference to distinguish between free and anti-miR bound miRNA. Synthetic miRNA guide strand was annealed with cognate anti-miR in increasing ratios. Polyacrylamide gel electrophoresis (PAGE) was used to confirm duplex formation as ground truth for bench marking RT-interference. (B) Annealing efficiency of miR-122:anti-miR-122 as assessed by PAGE. A Cy3 version of miR-122 guide strand was used for detection. Duplex formation at each A:M ratio was determined by relative densitometry of lower (single-stranded) and upper (double-stranded) bands. Dashed line shows fit by least-squares linear regression (R² = 0.972). (C) RT-interference results using miR-122 (1e7 copies/ng RNA) and anti-miR-122 combination. Grey dashed line represents expected loss of miR-122 for each A:M ratio shown. NTC = no template control. Data are normalized to samples without anti-miR (A:M = 0). Error bars represent s.d. for n = 3 replicates. (D) PAGE annealing assessment of miR-21 and anti-miR-21 combination (R² = 0.970). (E-F) RT-interference results with (E) low miR-21 copy number (1e6 copies/ng RNA) and (F) high miR-21 (1e7 copies/ng RNA).

Figure 3.

Measurement of miR-122 inhibition by miPSA (A) Representative UV absorbance trace of liver lysates fractionated by ultracentrifugation through sucrose gradients. Fractions were collected from top (light) -to- bottom (dense) and are marked by their leading edge. For 15 fraction gradients, fractions 7-15 were identified as containing polysomes. In all plots, grey bar along x-axis marks polysome fractions. (B-E) Anti-miR-122 causes a specific dose-dependent shift of miR-122 out of polysome fractions. (B) RNA was isolated from each fraction and RT-qPCR was used to quantify miRNA levels. Shown are the proportions of miR-122 (open shapes) and let-7d (filled shapes) in each fraction 24 hours after treatment with anti-miR-122 or saline. For each miRNA, data were normalized to total miRNA detected across all fractions and are expressed as percent per fraction. (C) Cumulative percent miR-122 (black bars) or let-7d (grey bars) in polysome fractions. (D) The same data shown in (B) now showing fold-change displacement of miR-122 per fraction for each dose level of anti-miR-122 or saline. Positive displacement values are interpreted as displacement or loss of miRNA and negative values are interpreted as enrichment or gain of miRNA, relative to let-7d reference in log₂ scale. (E) Final summary plot of average loss of miR-122 from polysome fractions for each treatment at 24 hours. ** P < 0.01, *** P < 0.001, ns = non-significant by one-way ANOVA with Tukey's post-hoc test. (F) (Upper graph) Quantification by HPLC-FL of anti-miR-122 (black bars) or anti-miR-21 (grey bars) in the top 5 fractions of an 8 fraction gradient. For both anti-miRs, the bulk of the oligo remained at the top of the gradient, consistent with its low molecular weight. For anti-miR-122, no anti-miR was detectable in polysome fractions above the limit of detection (LOD, marked by dotted line for each anti-miR). For anti-miR-21, trace amounts were detected in polysome fractions close to the LOD. ULOQ = upper limit of quantification. Error bars represent s.d. for n = 3 biological replicates. †One of these samples was below the LOD. (Lower table; top row) Distribution of anti-miR-21 detected in the gradient represented as percent per fraction measured. (Lower table; bottom row) Anti-miR-21 distribution in each measured fraction estimated as a percent of total anti-miR-21 in tissue based on Supplementary Figure S3.

Figure 4.

Comparison of miPSA with other PD methods. (A) Comparison of miPSA displacement (black triangle, dashed line) and mRNA expression changes of miR-122 target genes Aldoa (black circle, solid line) and Cd320 (grey square, solid line) at 24 hours and 7 days post-injection of an anti-miR-122. (B) Time course of plasma concentrations of anti-miR-122 measured by hybridization ELISA following injection at 0.3 mpk (light grey triangle), 1.0 mpk (grey square), and 3.0 mpk (black circle). LLOQ = lower limit of quantification. (C) Correlation of miPSA vs Aldoa (left; Pearson r = 0.947, P < 0.0001) or Cd320 (right; Pearson r = 0.952, P <0.0001). Line represents linear regression. (D) Relationship between negative RT-interference and target gene derepression in log₂ scale. Data shown fit with non-linear hyperbolic equation (R² = 0.882 for Aldoa; R² = 0.907 for Cd320), which fit better than linear regression (R² = 0.642 for Aldoa; R² = 0.684 for Cd320). For all plots, error bars represent s.e.m. for n ≥ 3 replicates.

Figure 5.

Measurement of miR-21 inhibition by miPSA in non-stressed tissue. (A) Comparison of miR-21 miPSA displacement (black squares) and target gene derepression (empty circles) in liver as a function of dose 7 days post injection. Target gene derepression represents a composite score of summed log₂ fold-changes for three miR-21 seed-matched genes: Spg20, Rnf167, and Taf7. Error bars represent s.e.m. for n = 4 animals per group. (B) Correlation between miPSA and composite target gene score in liver across two independent experiments with a total n = 90 animals. Inset shows correlations for the individual miR-21 target genes. For each plot, Pearson correlation coefficients are shown with linear regression fits (dotted black lines). (C) Comparison of miR-21 displacement in liver (black squares) and kidney (empty circles) from the same animals. Error bars represent s.e.m. for n = 4-5 animals per group. (D) Time course of miR-21 displacement in kidney in dose response at day 1 (empty squares, light grey dashed line), day 4 (dark grey filled squares, solid line), day 7 (empty circles, black solid line), and day 10 (black filled circles, solid line). Error bars represent s.e.m. for n = 7 animals per group. (E) RT-interference measured with RNA input isolated from intact liver pieces (black bars) or S16 liver lysates (grey bars). The same data are represented on both graphs, with y-axes shown in log (left) and linear (right) scales. Data represent linear fold-changes in miR-122 normalized to let-7d and PBS samples. Error bars represent s.d. for n = 3 per group. (F) Correlation between target gene composite score and negative RT-interference measured from intact liver (left; black) and S16 lysates (right; grey).

Figure 6.

Assessment of anti-miR cross-reactivity using miPSA. (A) Alignment of mature miRNA sequences showing a common seed between miR-17 and family members miR-20b and miR-106a. Although not part of the miR-17 family, miR-18a has a near identical seed sequence apart from a single A to G change at position 4. This base could theoretically form a G:U wobble with anti-miR-17. (B) Heat map showing displacement of miR-17 family members and other miRNAs in response to anti-miR-17 transfected into cultured cells in dose response at 1, 3, 10, 30, and 100 nM compared to mock (PBS). Darker shades of blue represent greater mean miRNA displacement as depicted in the key.