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Mutational interference mapping experiment (MIME) for studying RNA structure and function

Abstract

RNA regulates many biological processes; however, identifying functional RNA sequences and structures is complex and time-consuming. We introduce a method, mutational interference mapping experiment (MIME), to identify, at single-nucleotide resolution, the primary sequence and secondary structures of an RNA molecule that are crucial for its function. MIME is based on random mutagenesis of the RNA target followed by functional selection and next-generation sequencing. Our analytical approach allows the recovery of quantitative binding parameters and permits the identification of base-pairing partners directly from the sequencing data. We used this method to map the binding site of the human immunodeficiency virus-1 (HIV-1) Pr55Gag protein on the viral genomic RNA in vitro, and showed that, by analyzing permitted base-pairing patterns, we could model RNA structure motifs that are crucial for protein binding.

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Figure 1: A model protein-RNA interaction and a schematic for MIME.
Figure 2: Modeling the effects of mutations on Pr55Gag-RNA interaction.
Figure 3: Single-variation analysis identifies RNA structure and sequence requirements for Pr55Gag binding.
Figure 4: Identification of RNA structures important for Pr55Gag binding through covariation analysis.
Figure 5: Mapping the mutational effects on binding affinity to the structure of the HIV genomic RNA.

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Acknowledgements

This work was supported by grants from Sidaction and the French Agence Nationale de Recherches sur le SIDA et les Hépatites Virales (ANRS) to R.M. R.P.S. was supported by fellowships from the ANRS and from the Initiative d'excellence (IDEX), Par-delà les frontières, l'Université de Strasbourg. J.M. was funded by grants from the US National Institutes of Health (NIH), the Australian National Health and Medical Research Council (NHMRC) and the Australian Research Council (ARC). M.v.K. acknowledges funding from the German Ministry for Education & Science (BMBF) through grant number 031A307 and from the Einstein Center for Mathematics Berlin (ECMath) through project CH5. We thank A. Tomasini and P. Romby (Institut de Biologie Moléculaire et Cellulaire du Centre National de la Recherche Scientifique, Université de Strasbourg) for the gift of the MS2 phage coat protein.

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Authors and Affiliations

Authors

Contributions

R.P.S. and R.M. designed the study. R.P.S. generated the libraries for sequencing and performed the MIME experiments. R.P.S., L.D., F.J. and M.v.K. developed bioinformatic tools. M.v.K. developed binding models and statistical tools. M.H. and J.M. expressed and purified the Pr55Gag protein. S.B. characterized the Pr55Gag protein. G.H. and L.W. performed DNA sequencing. R.P.S., J.-C.P., M.v.K. and R.M. analyzed the data. R.P.S., M.v.K. and R.M. wrote the paper with contributions from the other authors.

Corresponding authors

Correspondence to Redmond P Smyth, Max von Kleist or Roland Marquet.

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The authors declare no competing financial interests.

Integrated supplementary information

Supplementary Figure 1 Raw mutation rate of DNA libraries

Two independent mutated libraries were generated by PCR mutagenesis. Sequencing of these mutant libraries showed that we had introduced a mutation rate (μ) of approximately 0.006 mutations per nucleotide, respectively. Coefficient of variation was 37% in both libraries. Wild-type DNA was sequenced to measure errors introduced during library preparation and sequencing. Wild-type DNA showed a mutation rate of 0.0013 mutations per nucleotide with a coefficient of variation of 117%.

Supplementary Figure 2 Comparison of relative Kd values obtained from experimental replicates

Left: Significant median Kdm(max)/Kdw values computed from technical replicate 1 (experiment 1) compared to replicate/experiment 2, showing the Pearson correlation between the quantitative Kd estimates and the corresponding P-value for assessing non-zero correlation. ‘Median’ denotes the median of the re-sampling distribution obtained after computational analysis (see eq. (6) in the Online Methods. Significance is determined using eqs. (7)-(8) in the Online Methods after multiple test correction. The vertical- and horizontal dashed lines separate Kdm(max)/Kdw estimates that are significantly larger- or smaller than 1 in the respective experiments and thus allow a qualitative assessment of the respective relative Kd estimates between experimental replicates. For example, in 1% of all depicted relative Kd estimates, replicate 2 yielded Kdm(max)/Kdw > 1 vs. Kdm(max)/Kdw < 1 in experimental replicate 1. The diagonal dashed line indicates the line of unity. Right: Cross-tabulation of the estimated number of positions significantly altering (increasing/decreasing) Pr55Gag binding. Congruent estimates, in terms of labeling the position as significantly vs. not significantly altering Pr55Gag binding, are found on the diagonal. Incongruent estimates are found on the anti-diagonal.

Supplementary Figure 3 Relative Kd values for each Pr55Gag concentration respectively vs. values obtained for the pooled (all concentrations) dataset

Left panels: Significant median log2(Kdm(max)/Kdw) QUOTE values of pooled data compared to (a) low Pr55Gag:RNA ratio (20nM Pr55Gag). (b) Equimolar Pr55Gag:RNA ratio (200nM Pr55Gag). (c) High Pr55Gag:RNA ratio (2000nM Pr55Gag), showing the Pearson correlation between the quantitative Kd estimates and the corresponding P-value for assessing non-zero correlation. ‘Median’ denotes the median of the re-sampling distribution obtained after computational analysis (see eq.(6) in the Online Methods). Significance is determined using eqs.(7)-(8) in the Online Methods after multiple test correction. Filled circles indicate Kdm(max)/Kdw estimates that are significantly smaller- or greater than 1 using either dataset, whereas red unfilled circles indicate Kdm(max)/Kdw estimates that are significantly smaller/greater 1 in the pooled dataset, but not in the dataset using the individual Pr55Gag concentration. Blue unfilled circles indicate Kdm(max)/Kdw estimates that are not significantly smaller/greater 1 in the pooled dataset, but which are estimated to be significantly altered when using the dataset with the individual Pr55Gag concentration. The vertical- and horizontal dashed lines separate Kdm(max)/Kdw estimates that are significantly larger- or smaller than 1 using the respective datasets and thus allow a qualitative assessment of the respective relative Kd estimates between datasets. The indicated percentages are computed on the bases of all Kdm(max)/Kdw estimates that are significantly smaller- or greater than 1 using either dataset (filled circles). Right panels: Cross-tabulation of the estimated number of positions significantly altering (increasing/decreasing) Pr55Gag binding. Congruent estimates, in terms of labeling the position as significantly vs. not significantly altering Pr55Gag binding, are found on the diagonal. Incongruent estimates are found on the anti-diagonal.

Supplementary Figure 4 Binding of Pr55Gag to the core-binding domain by filter binding assay

(a) Schematic of RNA (b) Binding of RNA (NL 1-532) and RNA corresponding to Pr55Gag core binding domain (NL 227-377) analyzed by filter binding assay.

Supplementary Figure 5 Interaction between MS2 coat protein and MS2 stem loop in non-cognate RNA

(a) Mapping of the effect of mutations on relative binding affinity, depicted as Kdm(max)/Kdw QUOTE , to a structural representation of the HIV-1 genome including the MS2 stem loop, which was inserted between the TAR and polyA hairpins. (b) Median effect of mutations on relative binding affinity, Kdm(max)/Kdw, in the HIV-1 genome containing the MS2 stem loop (red) and the HIV-1 genome without the MS2 stem loop (blue; negative control). Weak unspecific binding of the MS2 coat protein to the polyA and SL1 hairpins was detected irrespective of the presence of MS2 stem loop. (c) Effect of specific mutations on log2(Kdm/Kdw), for positions 52-92. MS2 stem loop spans positions 61-79. Box and whisker plots show effect of each class of mutation on relative binding affinity expressed as log2(Kdm/Kdw) where black and white circle shows median, box shows quartiles (25% and 75%) and whiskers show extremes (excluding outliers). Mutation classes are colour coded: red mutated to A; green mutated to C; blue mutated to G; yellow mutated to U. (d) Zoom on MS2 stem loop structure showing mutation with maximum effect on relative Kd, Kdm(max)/Kdw. Colour scale shows red with decreased binding affinity, blue increased binding affinity.

Supplementary Figure 6 Single variation analysis of Pr55Gag core binding domain

Positions where certain classes of mutations have statistically different effects on Pr55Gag binding. Green circle: structure-affecting mutations significantly impair binding and structure-preserving mutations impair binding significantly less than other possibilities. Yellow circles: structure-affecting mutations significantly impair binding and structure-preserving mutations impairs binding significantly less than one of the other possible mutations. Blue circles: structure-modulating mutations significantly impair Pr55Gag binding and where structure-preserving mutations improve Pr55Gag binding. Grey Circles: other sites of interest. Box and whisker plots show effect of each class of mutation on relative binding affinity expressed as QUOTE where black and white circle shows median, box shows quartiles (25% and 75%) and whiskers show extremes (excluding outliers). Mutation classes are colour coded: red mutated to A; green mutated to C; blue mutated to G; yellow mutated to U. Statistical tests are listed in Online Methods , P-values are listed in Supplementary Data 3.

Supplementary Figure 7 Binding of Pr55Gag to mutant RNA

HIV-1 genomic RNA containing point mutations was tested by filter binding experiments. These mutations were selected to be representative of the MIME data, including positions predicted to be single stranded, double stranded, positions showing strong evidence of RNA structure, and several positions where MIME indicates that co-variation maintains Pr55Gag binding.

Supplementary Figure 8 Comparison of relative dissociation constants obtained from filter binding experiments vs. MIME

Comparison of relative dissociation constants (expressed as log2(Kdm/Kdw)) for binding of Pr55Gag to HIV-1 genomic RNA, containing single point mutations, obtained from the filter binding experiments displayed in Supplementary Figure 7 vs. MIME. The left panel (a) compares the relative dissociation constants quantitatively. The black circles have the median log2(Kdm/Kdw) from the filter binding experiments vs. MIME as x- and y coordinates. The grey vertical bars show the quartiles of the MIME prediction, whereas the horizontal grey bars show the quartiles of the log2(Kdm/Kdw) estimate obtained from the filter binding experiment. The line of unity is indicated by a diagonal red dashed line and the vertical- and horizontal dashed black lined separate filter binding and MIME estimates that increase or decrease binding respectively. The right panel (b) shows a cross-tabulation comparing the qualitative outcome of the two assays. E.g. the upper left entry shows the number of Kdm/Kdw values that were estimated to be significantly different from 1 by MIME, but not by the filter binding experiment, whereas the upper right corner shows the number of Kdm/Kdw values that were estimated to be significantly different from 1 by both assays.

Supplementary Figure 9 Mapping of effects of mutations on binding affinity to the structure of the HIV genomic RNA

Effect of mutations mapped to the structure of the HIV-1 genome proposed by Siegfried et al. Mutation with maximum effect on Kd expressed as log2(Kdm(max)/Kdw). Postitions in red significantly impair Pr55Gag binding when mutated. Positions in blue significantly improve Pr55Gag binding when mutated. Positions with no significant change are shown in grey.

Siegfried, N. A., Busan, S., Rice, G. M., Nelson, J. A. E. & Weeks, K. M. RNA motif discovery by SHAPE and mutational profiling (SHAPE-MaP). Nat. Methods (2014). doi:10.1038/nmeth.3029

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–9, Supplementary Tables 1 and 2 and Supplementary Notes 1–4 (PDF 4821 kb)

Supplementary Data 1

Table containing complete dataset of relative Kd values for each genome position. (XLSX 39 kb)

Supplementary Data 2

Table containing complete dataset of relative Kd values for each class of mutation and each genome position. (XLSX 94 kb)

Supplementary Data 3

Table containing results of statistical test to assess whether different classes of mutation have comparable effects on Pr55Gag binding affinity. (XLSX 20 kb)

Supplementary Data 4

Table containing stems predicted to be important for Pr55Gag binding. (XLSX 10 kb)

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Smyth, R., Despons, L., Huili, G. et al. Mutational interference mapping experiment (MIME) for studying RNA structure and function. Nat Methods 12, 866–872 (2015). https://doi.org/10.1038/nmeth.3490

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