Advanced characterization of RNA-ligand binding dynamics through MMS technology

RNA molecules play multiple roles in the complex network of intracellular molecular interactions, beyond their typical function as mediators in gene expression. Among these diverse functions, RNA riboswitches are key regulatory elements that control gene expression in response to small molecule ligands.

Dynamic interactions between RNA and ligands are central to many biological processes, from human disease pathways to microbial pathogenesis.¹ Understanding RNA–ligand binding through riboswitches can help explain the fundamental mechanisms of gene regulation and provide avenues for targeted therapeutic interventions.

RNA molecules have exceeded their traditional role as messengers of genetic information and evolved into sophisticated regulators of gene expression through complex structural motifs called riboswitches.

Among them, the S-adenosylmethionine (SAM)-I riboswitch controls gene expression in reaction to intracellular SAM concentration fluctuations.² SAM is an important metabolite involved in numerous cellular processes, playing a crucial role as both a cofactor and regulatory molecule in various biological pathways, including transsulfuration, transmethylation, and polyamine synthesis.³

SAM-I riboswitches have unique SAM specificity and affinity that serve as molecular sentinels and regulate gene expression to sustain cellular homeostasis and adapt to environmental stimuli.

The SAM-I riboswitch consists of two distinct domains: the aptamer domain for SAM recognition (Figure 1) and the downstream expression platform that controls gene expression.

During SAM binding, conformational rearrangements occur to the aptamer domain, which transmits signals to the expression platform to regulate translational or transcriptional outputs (Figure 2).

This allosteric regulation mechanism is characteristic of riboswitches and provides cells with a precise and rapid means to sense and respond to fluctuations in SAM levels, fine-tuning metabolic pathways, and ensuring cellular health.⁴

Figure 1. X-Ray crystal structure of SAM-I riboswitch with a bound ligand (PDB: 2GIS) and the chemical structure of SAM. Adapted from ref. 4. Copyright 2017 by the RNA Society.

Understanding the structure and function of the SAM-I riboswitch has provided extraordinary insights into the dynamic relationship between RNA and ligand molecules.

Structural studies using nuclear magnetic resonance (NMR) spectroscopy, X-Ray crystallography, and cryo-electron microscopy (cryo-EM) have provided a comprehensive picture of the SAM-binding pocket and allosteric communication pathways within riboswitch.

Biochemical assays, combined with biophysical techniques such as single-molecule imaging and fluorescence spectroscopy, have revealed the kinetic parameters that govern SAM binding and riboswitch folding dynamics.

However, these techniques only provide binding and structural information on the RNA–ligand complex.

Figure 2. Binding-induced conformational changes in SAM-I riboswitch. Upon binding of SAM at the four-way junction, the P1 domain rotates to bind the ligand, which in turn causes a large allosteric change on the P4 domain. Adapted from ref. 4. Copyright 2017 by the RNA Society.

This article showcases a study that employed microfluidic modulation spectroscopy (MMS) to examine SAM-I riboswitch structural changes upon binding. MMS was used to probe the nucleic acid bases in the Amide-I infrared (IR) range to interrogate the base pairing/stacking during RNA folding and unfolding.

The Amide-I band is usually used to study the secondary structures of proteins. However, this IR region also contains extensive structural information about nucleic acid bases, which have largely been ignored.

To achieve accurate background correction in real time, MMS continuously modulates against a reference buffer. This technique's sensitivity makes it particularly applicable to quality control and compatible with various formulation buffers.

This study employed the Apollo MMS system, an instrument that uses a high-power quantum cascade laser, which is significantly more intense than conventional FTIR light sources.

The light source and modulating background subtraction combine to make MMS 30x more sensitive than FTIR and 5x more sensitive than CD with respect to structural changes.⁵

Methods

SAM-I riboswitches (apo and ligand-bound) were obtained from Arrakis (Waltham, MA). The RNA samples were buffer-exchanged three times to their formulation buffer (20 mM HEPES pH 7.5, 100 mM KCl, 3 mM MgCl₂, 0.05% TWEEN-20, and 2% DMSO) and the final eluent was employed as the reference buffer. The buffer-exchanged RNA samples were run in triplicate on the Apollo with a final concentration of 0.67 mg/mL (22 μM).

A backing pressure of 5 psi was employed to move samples into the flow cell, where they were modulated at 1 Hz between the sample and reference buffer for background subtraction.

The differential absorbance was measured between 1580 and 1765 cm^-1. Replicates were averaged, and all samples were normalized for concentration and interpolated to generate the absolute absorbance spectra.

Data processing followed the procedures used in a previous article.⁶ The raw differential absorbance was converted to absolute absorbance, normalized by concentration and optical pathlength. The second derivatives of the absolute absorbance spectra were taken to enhance spectral features. The second derivative was then inverted and baselined to produce a similarity plot, where the area of overlap is calculated compared to a control to quantitate similarity between samples.⁷

Results

The MMS results indicated subtle structural changes, reflected by the spectral differences due to ligand binding on the SAM-I riboswitch, as shown in Figure 3. The regions of change were the peaks positioned at 1690, 1640–1670, and 1604 cm^-1, assigned mainly to guanine, uracil/cytosine, and adenine, respectively, as shown in Figure 4.

Specifically, the increase in intensity at 1690 cm^-1 indicated the guanine C=O stretch in a double-strand or base-paired state. The crystal structure of ligand-bound SAM-I riboswitch (PDB: 2GIS) demonstrated that the binding involved interactions of SAM with U57, A45, A46, G11, and G58 in the riboswitch.

These base-ligand interactions likely contributed to the spectral change at the noted peaks in Figure 3 (with peak assignments shown in Figure 4).⁸

Figure 3. MMS spectra (similarity plot) of the apo riboswitch and ligand-bound riboswitch. Image Credit: RedShiftBio 

Figure 4. MMS spectra (similarity plot) of the apo riboswitch and ligand-bound riboswitch with peak assignments. (ss: single strand. ds: double strand. ts: triple strand.). Image Credit: RedShiftBio

A dose-dependent titration between SAM and the SAM-I riboswitch was also conducted, and the samples were structurally characterized using MMS. The MMS spectra in Figure 5 highlight two regions of gradual change upon SAM titration.

The first is the increase at 1695 cm^-1, indicating guanine base-pairing according to Figure 4. In this case, the increasing concentrations of SAM result in greater interaction between G11, G58, and SAM.

The second region is the 3-wavenumber shift from 1604 to 1607 cm^-1. This shift is less studied, but in this case is likely due to the interactions of the two adenines (A45 and A46) with SAM.

Notably, the spectral change in the 1640–1670 cm^-1 region does not exhibit a clear dependence on SAM concentration and requires further investigation for an explanation.

Figure 5. Dose-dependent titration of SAM into SAM-I riboswitch. Gradual change in spectra has been observed as the SAM concentration increases. Image Credit: RedShiftBio

The area of overlap (AO) method was employed to calculate the spectral differences in similarity between samples to demonstrate that the spectral changes observed were real rather than noise.^5,7

Table 1 displays the repeatability of measurements versus the sample-to-sample similarity using the AO method. Generally, repeatability indicates how well the repeat spectra overlay; hence, a similarity below this value indicates significant spectral change. All samples are significantly different from the reference (Apo riboswitch).

Table 1. Repeatability of measurement and sample-to-sample similarity (Apo riboswitch as reference: 100% similarity). Source: RedShiftBio 

To address the question of whether the conformational change in the RNA due to ligand binding or the IR signal change from the bound ligand caused the spectral changes, the spectral difference (1—similarity) between the titrated samples and the apo riboswitch was plotted, as shown in Figure 6.

The spectral change (blue line) plateaus after ∼20 μM of SAM concentration, close to 1:1 ligand–riboswitch molar ratio, indicating that the spectral change observed is the result of ligand binding.

The first derivative of the spectral difference (shown as the red line in Figure 6) highlights that the SAM concentration at which spectral change occurred most rapidly was 4 μM.

Despite using riboswitch concentrations exceeding the apparent dissociation constant (Kd) of the binding, this study demonstrates the effectiveness of MMS as a rapid and easy tool for both detecting structural change and determining Kd (in the micromolar range) of RNA–ligand binding.

Figure 6. Spectral change in area of overlap (AO) in response to SAM titration. Apo riboswitch was used as the reference. Spectral change increases as the SAM concentration increases. Blue: spectral change. Red: 1st derivative of spectral change. Image Credit: RedShiftBio

Conclusion

The study discussed here highlights the utility of MMS as a practical orthogonal assay for detecting RNA structural change due to small molecule ligands.

The study also demonstrates the potential of MMS in determining apparent Kd of RNA–ligand binding in the micromolar range by sensitively differentiating structural changes in the RNA riboswitch due to ligand binding.

Acknowledgments

Produced from materials authored by Richard Huang and Valerie Collins from RedShiftBio and Scott Gorman from Arrakis Therapeutics.

References

1. Zhou, Y., Jiang, Y., Chen, S. J. (2022). RNA–Ligand Molecular Docking: Advances and Challenges. Wiley Interdisciplinary Reviews: Computational Molecular Science. https://doi.org/10.1002/wcms.1571
2. Montange, R. K., Batey, R. T. (2006). Structure of the S-Adenosylmethionine Riboswitch Regulatory MRNA Element. Nature, 441(7097), pp.1172–1175. https://doi.org/10.1038/ nature04819
3. Ouyang, Y., Wu, Q., Li, J., Sun, S., Sun, S. (2020). S-Adenosylmethionine: A Metabolite Critical to the Regulation of Autophagy. Cell Proliferation. https://doi.org/10.1111/cpr.12891
4. Dussault, A.-M., Dubé, A., Jacques, F., Grondin, J. P., Lafontaine, D. A. (2017). Ligand Recognition and Helical Stacking Formation Are Intimately Linked in the SAM-I Riboswitch Regulatory Mechanism. RNA. https://doi.org/10.1261/ rna.061796
5. Kendrick, B. S., Gabrielson, J. P., Solsberg, C. W., Ma, E., Wang, L. (2020). Determining Spectroscopic Quantitation Limits for Misfolded Structures. J Pharm Sci, 109(1), pp.933–936. https://doi.org/10.1016/j.xphs.2019.09.004
6. Huang, R.; Collins, V.; Gillingham, D. Structural Comparisonof the Matrix Metalloproteinase Proenzymes Using MicrofluidicModulation Spectroscopy; 2023. www.redshiftbio.com.
7. Kendrick, B. S., Dong, A., Dean Allison, S., Manning, M. C., Carpenter, J. F. (1996). Quantitation of the Area of Overlap between Second-Derivative Amide I Infrared Spectra To Determine the Structural Similarity of a Protein in Different States. J Pharm Sci, 85(2), pp.155–158. https://doi.org/10.1021/ js950332f
8. Banyay, M., Sarkar, M., Graslund, A. (2003). A Library of IR Bands of Nucleic Acids in Solution. Biophys Chem, 104, pp.477–488. https://doi.org/10.1016/S0301-4622Ž03.00035-8

About RedShiftBio

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RedShiftBio has developed a proprietary life sciences platform combining our Microfluidic Modulation Spectroscopy (MMS) and expertise in high-powered quantum cascade lasers that provide ultra-sensitive and ultra-precise measurements of molecular structure. These structural changes affect critical quality attributes governing the safety, efficacy, and stability of biomolecules and their raw materials.  This combination of technologies is available to researchers in our fully-automated Aurora and Apollo systems and is backed by a global network of sales, applications, service, and support teams to address all market needs.

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