Structural and Biophysical Properties of Supercharged and Circularized Nanodiscs

Abstract

Nanodiscs based on membrane scaffold proteins (MSPs) and phospholipids are used as membrane mimics to stabilize membrane proteins in solution for structural and functional studies. Combining small-angle X-ray scattering (SAXS), differential scanning calorimetry (DSC), and time-resolved small-angle neutron scattering (TR-SANS), we characterized the structure and lipid bilayer properties of five different nanodiscs made with dimyristoylphosphatidylcholine and different MSPs varying in size, charge, and circularization. Our SAXS modeling showed that the structural parameters of the embedded lipids are all similar, irrespective of the MSP properties. DSC showed that the lipid packing is not homogeneous in the nanodiscs and that a 20 Å wide boundary layer of lipids with perturbed packing is located close to the MSP, while the packing of central lipids is tighter than in large unilamellar vesicles. Finally, TR-SANS showed that lipid exchange rates in nanodiscs decrease with increasing nanodisc size and are lower for the nanodiscs made with supercharged MSPs compared to conventional nanodiscs. Altogether, the results provide a thorough biophysical understanding of the nanodisc as a model membrane system, which is important in order to carry out and interpret experiments on membrane proteins embedded in such systems.

Global fitting of multiple data frames from SEC–SAXS to investigate the structure of next-generation nanodiscs

“…Unlike previous reports (Johansen et al, 2021), we do not see a simple linear correlation between axis ratio and length of the MSP here, despite larger discs theoretically being more structurally flexible. csMSP1D1 nanodiscs persistently have the largest axis ratio, which varies between 1.6 and 1.8, whereas csMSP1D1ÁH5 nanodiscs have the smallest, varying between 1.3 and 1.5, and csMSP1E3D1 lies in between with values varying between 1.45 and 1.65.…”

“…Although prone to local fluctuations, the refined value of the area per headgroup should also remain stable. For the three nanodiscs, A L was refined to values of between 49.5 and 53.5 A ˚2, which is in good agreement with previous values of 47.5 A ˚2 for DMPC-loaded nanodiscs (Johansen et al, 2021), 52.1 A ˚2 for DMPC-loaded peptide discs (Midtgaard et al, 2014) and 47.2 A ˚2 for a pure DMPC bilayer (Tristram-Nagle et al, 2002), all of which were recorded at 10 C. We mention that since the temperature is not controlled over the entire SEC-SAXS instrumentation, the temperature of the sample may be slightly above 10 C. This may affect the lipid packing slightly; however, as the temperature was kept below the melting temperature of DMPC at 24 C the effect will not be prominent (Johansen et al, 2021). v L becomes up to 5% larger than the reported value of 1041 A ˚3 (Tristram-Nagle et al, 2002).…”

“…The smallest nanodisc that we investigate, csMSP1D1ÁH5, is approximately 8 nm in diameter (Hagn et al, 2013), followed by csMSP1D1, which is approximately 10 nm in diameter (Hagn et al, 2013), and finally csMSP1E3D1, which is 13 nm in diameter (Johansen et al, 2019). The solution structures of these three nanodiscs have been studied previously by offline SEC purification and standard robot SAXS measurements (Johansen et al, 2019(Johansen et al, , 2021, however, without a focus on the underlying size and shape distributions within the populations. In this study, we demonstrate that this kind of information is easily accessible via SEC-SAXS.…”

“…MSP-based nanodiscs were prepared as described elsewhere (Johansen et al, 2021), excluding the final size-exclusion chromatography (SEC) purification. Briefly, DMPC was solubilized to 50 mM with reconstitution buffer (20 mM Tris-HCl pH 7.5, 150 mM NaCl) containing 100 mM sodium cholate.…”

“…where N k is the number of data points in the kth data set, of which there are M, which now prompts us to denote the jth data point in the kth data set by (q k,j , I k,j , k,j ). Note that the model function now depends on not only the parameters specific to the kth data set, h k , but also the 'global' parameters that are identical across all of the data sets, H. This is an adaptation of a similar scheme to analyze temperature series of SAXS data (Johansen et al, 2021). Additionally, rather than allowing the individual parameters in h k to vary irrespective to the other data sets, this scheme allows us to assume and enforce, for example, linear trends between the various frames to lower the total number of parameters refined in the scheme: i.e.…”