Quantitative mass imaging of single biological macromolecules

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Science  27 Apr 2018:
Vol. 360, Issue 6387, pp. 423-427
DOI: 10.1126/science.aar5839

Watching proteins' weight

Careful measurements of light scattering can provide information on individual macromolecules and complexes. Young et al. used a light-scattering approach for accurate mass determination of proteins as small as 20 kDa (see the Perspective by Lee and Klenerman). Movies of protein complex association and dissociation were analyzed to extract biophysical parameters from single molecules and assemblies without labeling. Using this approach, the authors determined in vitro kinetics of fibril and aggregate growth and association constants for a complex protein-glycoprotein assembly.

Science, this issue p. 423; see also p. 378


The cellular processes underpinning life are orchestrated by proteins and their interactions. The associated structural and dynamic heterogeneity, despite being key to function, poses a fundamental challenge to existing analytical and structural methodologies. We used interferometric scattering microscopy to quantify the mass of single biomolecules in solution with 2% sequence mass accuracy, up to 19-kilodalton resolution, and 1-kilodalton precision. We resolved oligomeric distributions at high dynamic range, detected small-molecule binding, and mass-imaged proteins with associated lipids and sugars. These capabilities enabled us to characterize the molecular dynamics of processes as diverse as glycoprotein cross-linking, amyloidogenic protein aggregation, and actin polymerization. Interferometric scattering mass spectrometry allows spatiotemporally resolved measurement of a broad range of biomolecular interactions, one molecule at a time.

Biomolecular interactions and assemblies are central to a wide range of physiological and pathological processes spanning length scales from small complexes (1) to the mesoscale (2, 3). Despite considerable developments in techniques capable of providing high-resolution structural information (4), such techniques are typically static, involve averaging over many molecules in the sample, and therefore often do not fully capture the diversity of structures and interactions. Solution-based ensemble methods enable dynamic studies but lack the resolution of separation required to distinguish different species (57). Single-molecule methods offer a means to circumvent heterogeneity in both structure and dynamics, and progress has been made in terms of characterizing interactions (8) and mechanisms (9, 10). So far, however, no single-molecule approach has been capable of quantifying and following the diversity of interactions of biomolecules with the required spatiotemporal accuracy and resolution.

Given sufficient sensitivity, light scattering is an ideal means for detecting and characterizing molecules in low-scattering in vitro conditions because of its universal applicability. In an interferometric detection scheme (Fig. 1A), the scattering signal scales with the polarizability, which is a function of the refractive index and proportional to the particle volume (11). Combining the approximation that single amino acids effectively behave like individual nano-objects with the observation that the specific volumes of amino acids and refractive indices of proteins vary by only ~1% (fig. S1 and table S1) suggests that the number of amino acids in a polypeptide, and thus its mass, are proportional to its scattering signal. This close relationship between mass and interferometric contrast, which has been predicted (12, 13) and observed (14, 15) to hold coarsely even at the single-molecule level, could thus in principle be used to achieve high mass accuracy.

Fig. 1 Concept of interferometric scattering mass spectrometry (iSCAMS).

(A) Schematic of the experimental approach relying on immobilization of individual molecules near a refractive index interface. Oligomeric states are colored differently for clarity. (B) Differential interferometric scattering image of BSA. Scale bar, 0.5 μm. (C) Representative images of monomers (top left), dimers (bottom left), trimers (top right), and tetramers (bottom right) of BSA. Scale bars, 200 nm. (D) Scatter plot of single-molecule binding events and their scattering contrasts for 12 nM BSA from 14 movies (lower panel). Corresponding histogram (n = 12,209) with a zoomed-in view of the region for larger species (upper panel). The reduction in landing rate results from a drop in BSA concentration with time owing to the large surface-to-volume ratio of our sample cell (supplementary materials).

Building on recent advances in the experimental approach (fig. S2) that improved imaging contrasts for interferometric scattering microscopy (15, 16), we were able to obtain high-quality images of single proteins as they diffused from solution to bind nonspecifically to the microscope coverslip/solution interface (Fig. 1, B and C, and movie S1). Reaching signal-to-noise ratios >10, even for small proteins such as bovine serum albumin (BSA), together with an optimized data analysis approach (16), allowed us to extract the scattering contrast for each molecular binding event with high precision (Fig. 1D and fig. S3). These data revealed clear signatures of different oligomeric states of BSA, with relative abundances for monomer to tetramer of 88.63, 9.94, 1.18, and 0.25% of the detected particles. For nonspecific binding to an unfunctionalized microscope coverslip, surface attachment was effectively irreversible (12,209 binding versus 372 unbinding events). As a result, we could determine (bulk) binding rate constants, which generally exhibited only small variations with oligomeric state. These could be accommodated to obtain minor corrections to the recorded mass spectra and yield the solution distribution (fig. S4). Our results, including the detection and quantification of rare complexes such as BSA tetramers, demonstrate the ability of interferometric scattering mass spectrometry (iSCAMS) to characterize solution distributions of oligomeric species and molecular complexes at high dynamic range.

The regular spacing in the contrast histogram of BSA tentatively confirms the expected linear scaling between mass and interferometric contrast. Repeating these measurements for eight different proteins, spanning 53 to 803 kDa, validates the linear relationship (Fig. 2A and fig. S5A). The deviation between measured and sequence mass was <5 kDa, resulting in an average error of 1.9%, and this deviation showed no detectable correlation with refractivity in relation to the overall shape of the molecule (fig. S6A). Even for large structural differences, such as those between the extended and folded conformations of smooth-muscle myosin (530.6 kDa; Fig. 2A and figs. S5B and S7), we did not find measurable differences in the apparent molecular mass beyond the increase expected for the addition of glutaraldehyde molecules used to cross-link myosin into the folded conformation (extended, 528.4 ± 16.2 kDa; folded, 579.4 ± 14.8 kDa; fig. S5B). The resolution, as defined by the full width at half-maximum of the measured contrast, reached 19 kDa for streptavidin. In all cases, the resolution was limited by photon shot noise and influenced by molecular mass, increasing from 19 kDa for streptavidin to 102 kDa for thyroglobulin (fig. S6, B and C). The <0.5% deviation from sequence mass for species of >100 kDa compares well with native mass spectrometry (17) and demonstrates the intrinsic utility of iSCAMS for the accurate mass measurement of biomolecules with oligomeric resolution.

Fig. 2 Characterization of iSCAMS accuracy, precision, and dependence on molecular shape and identity.

(A) Contrast versus molecular mass, including for proteins used for mass calibration (black), characterization of shape dependence (yellow), protein-ligand binding (green), lipid nanodisc composition (red), and glycosylation (blue). Mass error (upper panel) is given as a percentage of the sequence mass relative to the given linear fit. (B) Nanodisc mass measurement for different lipid compositions and protein belts. Masses obtained by alternative methodologies for MSP1D1/DMPC are marked and extrapolated to the other compositions. The horizontal bars indicate the expected mass range as a function of characterization technique, with the thin bars indicating the contrast measured and the thick bars representing the measurement uncertainty in terms of the standard error of the mean (SEM) for repeated experiments. For each sample, the upper text denotes the membrane scaffold protein (MSP) used, and the lower text indicates the lipids in the nanodisc. (C) Recorded differential contrast for Env expressed in the presence or absence of kifunensine and associated mass ranges expected for different glycosylation levels. (D) Mass-sensitive detection of ligand binding in the biotin-streptavidin system, according to the sequence mass of streptavidin and the masses of biotin and two biotinylated peptides relative to the calibration obtained from (A). Abbreviations are defined in table S8. In (A) and (D), error bars represent SEM.

Moving beyond species composed solely of amino acids, lipid nanodiscs are an ideal system for testing the broad applicability of iSCAMS owing to their flexibility in terms of polypeptide and lipid content (18). For nanodiscs composed of the MSP1D1 belt protein and DMPC (1,2-dimyristoyl-sn-glycero-3-phosphocholine) lipids, we obtained a mass of 141.0 ± 1.6 kDa, in good agreement with the range of masses spanning 124 to 158 kDa reported from other methods (Fig. 2B and fig. S5D). Replacing MSP1D1 with the smaller MSP1ΔH5 reduced the nanodisc diameter and the lipid content by ~20%, after accounting for the thickness of the protein belt (19). Given the masses of MSP1D1 and MSP1ΔH5 (47 and 42 kDa, respectively), we predicted a mass for the MSP1ΔH5 nanodisc of 113.6 kDa, in excellent agreement with our measurement (114.1 ± 1.9 kDa). Mass shifts associated with changes in lipid composition, such as those introduced by partially unsaturated lipids and cholesterol, matched those predicted from the assembly ratios (Fig. 2B and tables S2 to S6).

To see whether our approach also applies to solvent-exposed moieties that experience a different dielectric environment from those buried within a protein, we selected the HIV envelope glycoprotein complex (Env), which is a trimer of gp41-gp120 heterodimers. Env is extensively N-glycosylated, with the carbohydrates contributing almost half of its mass (20). For an Env trimer mimic expressed in the presence of kifunensine, a mannosidase inhibitor that leads predominantly to unprocessed Man9GlcNAc2 glycans (Man, mannose; GlcNAc, N-acetylglucosamine) (fig. S8), we recorded a mass of 350.0 ± 5.7 kDa. Making the crude approximation that glycans and amino acids have similar polarizabilities, this corresponds to a glycan occupancy of 74 ± 3 out of 84 possible sites (Fig. 2C and fig. S5E), consistent with recent observations of high occupancy for gp120 expressed with kifunensine (21). For Env expressed without kifunensine, we recorded a lower mass of 315.3 ± 10.5 kDa. The mass difference can be attributed only in part to the lower average mass of the processed glycans (fig. S8) and yields a total N-glycan occupancy of 61 ± 6. Although the exact values for occupancy are beholden to our calibration (Fig. 2A), the presence of unoccupied sites is consistent with their observation in proteomics data (22).

The high precision of 1.8 ± 0.5% with respect to the protein mass (Fig. 2A) indicates the potential for direct detection of small-molecule binding. To probe the current limits of iSCAMS in terms of precision, we therefore examined the biotin-streptavidin system (Fig. 2D and fig. S5C). We measured masses for streptavidin in the absence (55.7 ± 1.1 kDa) and presence (57.4 ± 0.9 kDa) of biotin, finding a difference of 1.7 ± 1.4 kDa, in good agreement with the expected 0.98 kDa for complete occupancy of the four binding sites. Upon addition of two different biotinylated peptides (3705.9 and 4767.4 Da), we found increases of 16.1 ± 2.8 and 22.0 ± 2.2 kDa (compared with the expected 14.8 and 19.1 kDa) (Fig. 2D and fig. S5C). These data show that iSCAMS can detect the association of kilodalton-sized ligands, demonstrating its suitability for sensitive ligand-binding studies in solution.

After having established the capabilities of iSCAMS, we sought to test it on more complex systems that are difficult to assess quantitatively with existing techniques as a consequence of heterogeneity and multistep assembly mechanisms (Fig. 3). In addition, we aimed to monitor nucleation and polymerization dynamics of mesoscopic structures down to the single-molecule level, which is challenging because of the simultaneous requirement for high dynamic range, high imaging speed, and direct correlation between the observed signals and the associated molecular events. The biotin-streptavidin system exhibits nearly covalent binding, raising the question of whether iSCAMS is capable not only of determining mass distributions, but also of quantifying weaker equilibria, as are often encountered for protein-protein interactions.

Fig. 3 Single-molecule mass analysis of heterogeneous protein assembly.

(A) Mass distributions for Env in the presence of 0.5 to 40 nM BanLec monomer, alongside expected positions for multiples of bound BanLec tetramers. Inset, a zoomed-in view of the region for larger species. (B) Oligomeric fractions colored according to (A) versus BanLec concentration, including predictions (curves) using the model shown.

We therefore investigated the interaction of Env with the antiviral lectin BanLec, which neutralizes HIV by binding to surface N-glycans (23, 24) through an unknown mechanism. We were able to monitor the interactions and short-lived complexes before aggregation, with the addition of BanLec to Env resulting in a reduction of single Env units coupled to the appearance of dimers and higher-order assemblies (Fig. 3A). Describing the experimental oligomeric evolution with a simple model (Fig. 3B) enabled us to extract the underlying association constants [KBanLec = 0.12 nM−1; KEnv = 8 nM−1; KBanLec = 0.4 nM−1 (as defined in Fig. 3B)], in good agreement with recent bulk studies (KBanLec = 0.19 nM−1), which also found signatures of a secondary binding event (2.85 nM−1) (25). Our ability to follow and model the evolution of different oligomeric species allowed us to extract the interaction mechanism and the energetics underlying the lectin-glycoprotein interaction, despite the heterogeneity of this multicomponent system. As a result, we could show that binding of Env to BanLec that is already bound to Env (KEnv) is much stronger than to free BanLec (KBanLec), a key characteristic of cooperative behavior. Moreover, the mass resolution of our approach enabled us to quantify the number of BanLecs bound per dimer (one to two), trimer (two to three), and tetramer (three to four) of Env, demonstrating bivalent binding. These results are directly relevant to the characterization and optimization of antiretrovirals, given that multivalency and aggregation have been proposed to be linked to neutralization potency (25). We anticipate similar quantitative insights to be achievable for other therapeutic target proteins and protein-protein interactions in general.

An advantage of our imaging-based approach is its ability to time-resolve mass changes in a position- and local concentration–sensitive manner. This enables us to examine surface-catalyzed nucleation events that may eventually lead to amyloid formation (26). Previous studies using fluorescence labeling found aggregates of ~0.6 μm in diameter within a minute of addition of the amyloidogenic protein α-synuclein at 10 μM to an appropriately charged bilayer (27). Upon adding α-synuclein to a planar, negatively charged DOPC (1,2-dioleoyl-sn-glycero-3-phosphocholine)/DOPS (1,2-dioleoyl-sn-glycero-3-phospho-l-serine) (3:1) membrane at physiological pH, we observed the appearance and growth of nanoscopic objects within seconds, even at low micromolar concentrations (Fig. 4A and movie S2). We were unable to determine the sizes of the initial nucleating species or individual assembly steps owing to the low molecular mass of α-synuclein (14 kDa), but we could monitor the nanoscale formation of associated structures in the range of hundreds of kilodaltons and determine the kinetics (Fig. 4B). Growth of these clusters was uniform across the field of view, with the initial rates following expectations for a first-order process (Fig. 4B and fig. S9A), pointing to a simple growth mechanism. We did not detect such structures on neutral, DOPC-only bilayers, and we found evidence for thioflavin T–positive aggregates after overnight incubation (fig. S9B), suggesting that our assay probes early stages of amyloid assembly.

Fig. 4 Mass imaging of mesoscopic dynamics.

(A) Schematic and iSCAMS images of α-synuclein (1 μM) aggregation on a negatively charged bilayer membrane. (B) Initial growth rate versus α-synuclein concentration, shown with the best fit assuming first-order kinetics. Error bars denote SEM for different particles. Inset, individual (gray) and average (black) growth trajectories for 21 particles from (A). (C) Schematic and iSCAMS images of actin polymerization. The arrow highlights a growing filament. (D) Representative traces of actin filament tip position (gray) and corresponding detected steps (black). (E) Step and mass histogram from 1523 steps and 33 filaments, including a fit to a Gaussian mixture model (black) and individual contributions (colored according to fig. S10G). Scale bars, 1 μm. In these experiments, background correction involved removal of the static background before acquisition, rather than continuous differential imaging as in Figs. 2 and 3 (supplementary materials).

At the extremes of its current sensitivity, iSCAMS enables mass imaging of mesoscopic self-assembly, molecule by molecule. In an actin polymerization assay, subtraction of the constant background revealed the growth of surface-immobilized filaments. In contrast to α-synuclein, where the growth of interest took place within a diffraction-limited spot, in this case we could quantify length changes of filaments larger than the diffraction limit upon the attachment and detachment of actin subunits (Fig. 4C, fig. S10C, and movie S3). We observed distinct, stepwise changes in the filament length (Fig. 4D; fig. S10, D to F; and movie S4), the most frequent forward and backward step sizes in the traces being 3.0 ± 0.8 and 2.7 ± 0.7 nm, respectively—very close to the expected length increase of 2.7 nm upon binding of a single actin subunit to a filament (Fig. 4E). Detection of larger step sizes represents the addition of multiple actin subunits within our detection time window. The contrast changes associated with the different step sizes corresponded to mass changes of one, two, or three actin monomers binding to (and unbinding from) the tip of the growing filaments during acquisition (fig. S10, G and H). Even though we cannot yet distinguish between models invoking monomer (28) or oligomer (29) addition to a growing filament at the current level of spatiotemporal resolution, these results demonstrate the capability of iSCAMS to quantitatively image mesoscopic dynamics and determine how they are influenced by associated proteins at the single-molecule level.

We anticipate that combining iSCAMS with established surface modifications (30) will dramatically expand its capabilities. Passivation decreases surface binding probabilities and thereby should provide access to much higher analyte concentrations (greater than micromolar), and surface activation will reduce measurement times at low concentrations (less than nanomolar). Specific functionalization and immobilization of individual subunits or binding partners could allow for the determination of on and off rates, in addition to equilibrium constants, and enable targeted detection in the presence of other analytes (14). Although studies within complex three-dimensional environments such as the cell may prove to be beyond reach, the advances reported here will make iSCAMS a key approach for dynamic in vitro studies of biomolecular interactions, assembly, and structure at the single-molecule level.

Supplementary Materials

Materials and Methods

Figs. S1 to S10

Tables S1 to S8

References (3151)

Movies S1 to S4

References and Notes

Acknowledgments: J.R.S. thanks F. Zhang for technical assistance and the NHLBI electron microscopy core facility. Funding: G.Y. was supported by a Zvi and Ofra Meitar Magdalen Graduate Scholarship. N.H. was supported by a DFG (German Research Foundation) research fellowship (HU 2462/1-1). E.G.M. thanks the Swedish Research Council and the European Commission for a Marie Skłodowska Curie International Career Grant (2015-00559). M.P.C. is a Clarendon Scholar supported by the Oxford University Press. S.A.C. is supported by the Biotechnology and Biological Sciences Research Council and Waters Corp through the iCASE studentship BB/L017067/1 to J.L.P.B. O.T. acknowledges a Lamb and Flag Scholarship from St John’s College, University of Oxford, and an Engineering and Physical Sciences Research Council (EPSRC) Studentship. J.Al. and M.C. were supported by the National Institute of Allergy and Infectious Diseases (Center for HIV/AIDS Vaccine Immunology and Immunogen Discovery grant UM1AI100663). J.R.S. was supported by NHLBI intramural program HL0001786. C.E. is supported by a Swiss National Science Foundation advanced postdoctoral mobility fellowship (P300PA160979). P.S. is funded by a European Research Council (ERC) Consolidator Grant (NeuroInCellNMR, 647474). J.L.P.B. thanks the EPSRC for EP/J01835X/1. P.K. was supported by an ERC Starting Investigator Grant (Nanoscope, 337577). Author contributions: Conceptualization: W.B.S., J.L.P.B., and P.K. Methodology: G.Y., N.H., D.C., J.An., E.G.M., C.E., P.S., M.R.G., W.B.S., J.L.P.B., and P.K. Software: G.Y. and N.H. Validation: G.Y., N.H., J.L.P.B., and P.K. Formal analysis: G.Y., N.H., A.T., A.A., A.O., J.An., E.G.M., and M.R.G. Investigation: G.Y., N.H., D.C., A.F., J.An., A.T., A.A., N.B., Y.T., and C.E. Resources: M.P.C., S.A.C., O.T., J.Al., M.C., N.B., Y.T., J.R.S., C.E., P.S., L.F., R.R., and W.B.S. Writing of original draft: G.Y., J.L.P.B., and P.K. Revision and editing: G.Y., N.H., A.F., A.O., E.G.M., M.P.C., S.A.C., O.T., M.C., J.R.S., C.E., P.S., R.R., M.R.G., W.B.S., J.L.P.B., and P.K. Visualization: G.Y., N.H., J.L.P.B., and P.K. Supervision: P.K. Competing interests: P.K. has filed a patent for the contrast enhancement methodology and its application to mass measurement of single biomolecules. All other authors declare no competing interests. Data and materials availability: All data necessary to support the conclusions are available in the manuscript or supplementary materials and are deposited in the University of Oxford Research Archive (DOI, 10.5287/bodleian:PmA5Va0a2).

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