Abstract
Mutations in SARS-CoV-2 have shown effective evasion of population immunity and increased affinity to the cellular receptor angiotensin-converting enzyme 2 (ACE2). However, in the dynamic environment of the respiratory tract, forces act on the binding partners, which raises the question of whether not only affinity but also force stability of the SARS-CoV-2–ACE2 interaction might be a selection factor for mutations. Using magnetic tweezers, we investigate the impact of amino acid substitutions in variants of concern (Alpha, Beta, Gamma and Delta) and on force-stability and bond kinetic of the receptor-binding domain–ACE2 interface at a single-molecule resolution. We find a higher affinity for all of the variants of concern (>fivefold) compared with the wild type. In contrast, Alpha is the only variant of concern that shows higher force stability (by 17%) compared with the wild type. Using molecular dynamics simulations, we rationalize the mechanistic molecular origins of this increase in force stability. Our study emphasizes the diversity of contributions to the transmissibility of variants and establishes force stability as one of the several factors for fitness. Understanding fitness advantages opens the possibility for the prediction of probable mutations, allowing a rapid adjustment of therapeutics, vaccines and intervention measures.
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References
Laffeber, C., Koning, K. D., Kanaar, R. & Lebbink, J. H. G. Experimental evidence for enhanced receptor binding by rapidly spreading SARS-CoV-2 variants. J. Mol. Biol. 433, 167058–167058 (2021).
Barton, M. I. et al. Effects of common mutations in the SARS-CoV-2 spike RBD and its ligand, the human ACE2 receptor on binding affinity and kinetics. eLife 10, e70658 (2021).
Majumdar, P. & Niyogi, S. SARS-CoV-2 mutations: the biological trackway towards viral fitness. Epidemiol. Infect. 149, E110 (2021).
Bayarri-Olmos, R. et al. The alpha/B.1.1.7 SARS-CoV-2 variant exhibits significantly higher affinity for ACE-2 and requires lower inoculation doses to cause disease in K18-hACE2 mice. eLife 10, e70002 (2021).
Hill, D. B. et al. Force generation and dynamics of individual cilia under external loading. Biophys. J. 98, 57–66 (2010).
Wu, C.-T. et al. SARS-CoV-2 replication in airway epithelia requires motile cilia and microvillar reprogramming. Cell 186, 112–130.e20 (2023).
Milles, L. F., Schulten, K., Gaub, H. E. & Bernardi, R. C. Molecular mechanism of extreme mechanostability in a pathogen adhesin. Science 359, 1527–1533 (2018).
Alsteens, D. et al. Nanomechanical mapping of first binding steps of a virus to animal cells. Nat. Nanotechnol. 12, 177–183 (2017).
Koehler, M., Delguste, M., Sieben, C., Gillet, L. & Alsteens, D. Initial step of virus entry: virion binding to cell-surface glycans. Annu. Rev. Virol. 7, 143–165 (2020).
Sokurenko, E. V., Vogel, V. & Thomas, W. E. Catch-bond mechanism of force-enhanced adhesion: counterintuitive, elusive, but…widespread? Cell Host Microbe 4, 314–323 (2008).
Tian, F. et al. N501Y mutation of spike protein in SARS-CoV-2 strengthens its binding to receptor ACE2. eLife 10, e69091 (2021).
Zheng, Bin, et al. S373P mutation stabilizes the receptor-binding domain of the spike protein in omicron and promotes binding. JACS Au https://doi.org/10.1021/jacsau.3c00142 (2023).
Koehler, M. et al. Molecular insights into receptor binding energetics and neutralization of SARS-CoV-2 variants. Nat. Commun. 12, 6977 (2021).
Yang, J. et al. Molecular interaction and inhibition of SARS-CoV-2 binding to the ACE2 receptor. Nat. Commun. 11, 4541 (2020).
Cao, W. et al. Biomechanical characterization of SARS-CoV-2 spike RBD and human ACE2 protein-protein interaction. Biophys. J. 120, 1011–1019 (2021).
Zhang, X. et al. Pathogen-host adhesion between SARS-CoV-2 spike proteins from different variants and human ACE2 studied at single-molecule and single-cell levels. Emerging Microbes Infect. 11, 2658–2669 (2022).
Zhu, R. et al. Force-tuned avidity of spike variant-ACE2 interactions viewed on the single-molecule level. Nat. Commun. 13, 7926 (2022).
Bauer, M. S. et al. A tethered ligand assay to probe SARS-CoV-2:ACE2 interactions. Proc. Natl Acad. Sci. USA 119, e2114397119 (2022).
Bauer, M. S. et al. A tethered ligand assay to probe the SARS-CoV-2 ACE2 interaction under constant force. Preprint at biorxiv https://doi.org/10.1101/2020.09.27.315796 (2020).
Löf, A. et al. Multiplexed protein force spectroscopy reveals equilibrium protein folding dynamics and the low-force response of von Willebrand factor. Proc. Natl Acad. Sci. USA 116, 18798–18807 (2019).
Lansdorp, B. M. & Saleh, O. A. Power spectrum and Allan variance methods for calibrating single-molecule video-tracking instruments. Rev. Sci. Instrum. 83, 025115 (2012).
Velthuis, A. J. W. T., Kerssemakers, J. W. J., Lipfert, J. & Dekker, N. H. Quantitative guidelines for force calibration through spectral analysis of magnetic tweezers data. Biophys. J. 99, 1292–1302 (2010).
Neuman, K. C. & Nagy, A. Single-molecule force spectroscopy: optical tweezers, magnetic tweezers and atomic force microscopy. Nat. Methods 5, 491–505 (2008).
Lipfert, J., Hao, X. & Dekker, N. H. Quantitative modeling and optimization of magnetic tweezers. Biophys. J. 96, 5040–5049 (2009).
Ott, W. et al. Elastin-like polypeptide linkers for single-molecule force spectroscopy. ACS Nano 11, 6346–6354 (2017).
Kim, J., Zhang, C. Z., Zhang, X. & Springer, T. A. A mechanically stabilized receptor-ligand flex-bond important in the vasculature. Nature 466, 992–995 (2010).
Shrestha, P. et al. Single-molecule mechanical fingerprinting with DNA nanoswitch calipers. Nat. Nanotechnol. 16, 1362–1370 (2021).
Yang, D., Ward, A., Halvorsen, K. & Wong, W. P. Multiplexed single-molecule force spectroscopy using a centrifuge. Nat. Commun. 7, 11026 (2016).
Kilchherr, F. et al. Single-molecule dissection of stacking forces in DNA. Science 353, aaf5508 (2016).
Le, S., Yu, M. & Yan, J. Direct single-molecule quantification reveals unexpectedly high mechanical stability of vinculin—talin/α-catenin linkages. Sci. Adv. 5, eaav2720 (2019).
Halvorsen, K., Schaak, D. & Wong, W. P. Nanoengineering a single-molecule mechanical switch using DNA self-assembly. Nanotechnology 22, 494005 (2011).
Kostrz, D. et al. A modular DNA scaffold to study protein-protein interactions at single-molecule resolution. Nat. Nanotechnol. 14, 988–993 (2019).
Gong, S. Y. et al. Contribution of single mutations to selected SARS-CoV-2 emerging variants spike antigenicity. Virology 563, 134–145 (2021).
Rajah, M. M. et al. SARS‐CoV‐2 Alpha, Beta, and Delta variants display enhanced spike‐mediated syncytia formation. EMBO J. 40, e108944 (2021).
Gobeil, S. M. C. et al. Effect of natural mutations of SARS-CoV-2 on spike structure, conformation, and antigenicity. Science 373, eabi6226 (2021).
Ren, W. et al. Characterization of SARS-CoV-2 variants B.1.617.1 (Kappa), B.1.617.2 (Delta), and B.1.618 by cell entry and immune evasion. mBio 13, e00099–00022 (2022).
McCallum, M. et al. Molecular basis of immune evasion by the Delta and Kappa SARS-CoV-2 variants. Science 374, 1621–1626 (2021).
Albrecht, C. et al. DNA: a programmable force sensor. Science 301, 367–370 (2003).
Gruber, S. et al. Designed anchoring geometries determine lifetimes of biotin–streptavidin bonds under constant load and enable ultra-stable coupling. Nanoscale 12, 21131–21137 (2020).
Webb, B. & Sali, A. Comparative protein structure modeling using MODELLER. Curr. Protoc. Bioinform 54, 5.6.1–5.6.37 (2016).
Phillips, J. C. et al. Scalable molecular dynamics on CPU and GPU architectures with NAMD. J. Chem. Phys. 153, 044130 (2020).
Melo, M. C. R., Bernardi, R. C., Fuente-Nunez, C. D. L. & Luthey-Schulten, Z. Generalized correlation-based dynamical network analysis: a new high-performance approach for identifying allosteric communications in molecular dynamics trajectories. J. Chem. Phys. 153, 134104 (2020).
Schoeler, C. et al. Mapping mechanical force propagation through biomolecular complexes. Nano Lett. 15, 7370–7376 (2015).
Lan, J. et al. Structure of the SARS-CoV-2 spike receptor-binding domain bound to the ACE2 receptor. Nature 581, 215–220 (2020).
Liu, H. et al. The basis of a more contagious 501Y.V1 variant of SARS-CoV-2. Cell Res. 31, 720–722 (2021).
Han, P. et al. Receptor binding and complex structures of human ACE2 to spike RBD from Omicron and Delta SARS-CoV-2. Cell 185, 630–640.e610 (2022).
Dulin, D., Lipfert, J., Moolman, M. C. & Dekker, N. H. Studying genomic processes at the single-molecule level: introducing the tools and applications. Nat. Rev. Genet. 14, 9–22 (2013).
Shang, J. et al. Cell entry mechanisms of SARS-CoV-2. Proc. Natl Acad. Sci. USA 117, 11727–11734 (2020).
V’kovski, P., Kratzel, A., Steiner, S, Stalder, H. & Thiel, V. Coronavirus biology and replication: implications for SARS-CoV-2. Nat. Rev. Microbiol. 19, 155–170 (2020).
Michaud, W. A., Boland, G. M. & Rabi, S. A. The SARS-CoV-2 spike mutation D614G increases entry fitness across a range of ACE2 levels, directly outcompetes the wild type, and is preferentially incorporated into trimers. Preprint at bioRxiv https://doi.org/10.1101/2020.08.25.267500 (2020).
Jackson, C. B., Farzan, M., Chen, B. & Choe, H. Mechanisms of SARS-CoV-2 entry into cells. Nat. Rev. Mol. Cell Biol. 23, 3–20 (2022).
Harvey, W. T. et al. SARS-CoV-2 variants, spike mutations and immune escape. Nat. Rev. Microbiol. 19, 409–424 (2021).
Escalera, A. et al. Mutations in SARS-CoV-2 variants of concern link to increased spike cleavage and virus transmission. Cell Host Microbe 30, 373–387.e377 (2022).
Ulrich, L. et al. Enhanced fitness of SARS-CoV-2 variant of concern Alpha but not Beta. Nature 602, 307–313 (2022).
Buss, L. F. et al. Three-quarters attack rate of SARS-CoV-2 in the Brazilian Amazon during a largely unmitigated epidemic. Science 371, 288–292 (2021).
Sun, K. et al. SARS-CoV-2 transmission, persistence of immunity, and estimates of Omicron’s impact in South African population cohorts. Sci. Transl. Med. 14, eabo7081 (2022).
Starr, T. N. et al. Deep mutational scanning of SARS-CoV-2 receptor binding domain reveals constraints on folding and ACE2 binding. Cell 182, 1295–1310.e1220 (2020).
Liu, C. et al. The antibody response to SARS-CoV-2 Beta underscores the antigenic distance to other variants. Cell Host Microbe 30, 53–68.e12 (2022).
Bayarri-Olmos, R. et al. Functional effects of receptor-binding domain mutations of SARS-CoV-2 B.1.351 and P.1 variants. Front. Immunol. 12, 757197 (2021).
Mlcochova, P. et al. SARS-CoV-2 B.1.617.2 Delta variant replication and immune evasion. Nature 599, 114–119 (2021).
Hu, J. et al. Increased immune escape of the new SARS-CoV-2 variant of concern Omicron. Cell Mol. Immunol. 19, 293–295 (2022).
Ju, B. et al. Immune escape by SARS-CoV-2 Omicron variant and structural basis of its effective neutralization by a broad neutralizing human antibody VacW-209. Cell Res. 32, 491–494 (2022).
Fan, Y. et al. SARS-CoV-2 Omicron variant: recent progress and future perspectives. Sig. Transduct. Target Ther. 7, 141 (2022).
Planas, D. et al. Considerable escape of SARS-CoV-2 Omicron to antibody neutralization. Nature 602, 671–675 (2022).
Li, B. et al. Viral infection and transmission in a large, well-traced outbreak caused by the SARS-CoV-2 Delta variant. Nat. Commun. 13, 460 (2022).
Komatsu, T. et al. Molecular cloning, mRNA expression and chromosomal localization of mouse angiotensin-converting enzyme-related carboxypeptidase (mACE2). DNA Sequence 13, 217–220 (2002).
Marra, M. A. et al. The genome sequence of the SARS-associated coronavirus. Science 300, 1399–1404 (2003).
Li, F., Li, W., Farzan, M. & Harrison, S. C. Structure of SARS coronavirus spike receptor-binding domain complexed with receptor. Science 309, 1864–1868 (2005).
Milles, L. F. & Gaub, H. E. Is mechanical receptor ligand dissociation driven by unfolding or unbinding? Preprint at bioRxiv https://doi.org/10.1101/593335 (2019).
Wu, F. et al. A new coronavirus associated with human respiratory disease in China. Nature 579, 265–269 (2020).
Walker, P. U., Vanderlinden, W. & Lipfert, J. Dynamics and energy landscape of DNA plectoneme nucleation. Phys. Rev. E 98, 042412 (2018).
van Loenhout, M. T., Kerssemakers, J. W., De Vlaminck, I. & Dekker, C. Non-bias-limited tracking of spherical particles, enabling nanometer resolution at low magnification. Biophys. J. 102, 2362–2371 (2012).
Cnossen, J. P., Dulin, D. & Dekker, N. H. An optimized software framework for real-time, high-throughput tracking of spherical beads. Rev. Sci. Instrum. 85, 103712 (2014).
Lipfert, J. et al. Methods and protocols. Methods Mol. Biol. 582, 71–89 (2009).
Yu, Z. et al. A force calibration standard for magnetic tweezers. Rev. Sci. Instrum. 85, 123114 (2014).
De Vlaminck, I., Henighan, T., van Loenhout, M. T., Burnham, D. R. & Dekker, C. Magnetic forces and DNA mechanics in multiplexed magnetic tweezers. PLoS ONE 7, e41432 (2012).
Zimmermann, J. L., Nicolaus, T., Neuert, G. & Blank, K. Thiol-based, site-specific and covalent immobilization of biomolecules for single-molecule experiments. Nat. Protoc. 5, 975–985 (2010).
Yin, J., Lin, A. J., Golan, D. E. & Walsh, C. T. Site-specific protein labeling by Sfp phosphopantetheinyl transferase. Nat. Protoc. 1, 280–285 (2006).
Chen, I., Dorr, B. M. & Liu, D. R. A general strategy for the evolution of bond-forming enzymes using yeast display. Proc. Natl Acad. Sci. USA 108, 11399–11404 (2011).
Durner, E., Ott, W., Nash, M. A. & Gaub, H. E. Post-translational sortase-mediated attachment of high-strength force spectroscopy handles. ACS Omega 2, 3064–3069 (2017).
Humphrey, W., Dalke, A. & Schulten, K. VMD: visual molecular dynamics. J. Mol. Graph. 14, 33–38 (1996).
Ribeiro, J. V. et al. QwikMD—integrative molecular dynamics toolkit for novices and experts. Sci. Rep. 6, 26536 (2016).
Bernardi, R. C. et al. Mechanisms of nanonewton mechanostability in a protein complex revealed by molecular dynamics simulations and single-molecule force spectroscopy. J. Am. Chem. Soc. 141, 14752–14763 (2019).
Best, R. B. et al. Optimization of the additive CHARMM all-atom protein force field targeting improved sampling of the backbone ϕ, ψ and side-chain χ1 and χ2 dihedral angles. J. Chem. Theory Comput. 8, 3257–3273 (2012).
MacKerell, A. D. et al. All-atom empirical potential for molecular modeling and dynamics studies of proteins. J. Phys. Chem. B 102, 3586–3616 (1998).
Jorgensen, W. L., Chandrasekhar, J., Madura, J. D., Impey, R. W. & Klein, M. L. Comparison of simple potential functions for simulating liquid water. J. Chem. Phys. 79, 926–935 (1998).
Darden, T., York, D. & Pedersen, L. Particle mesh Ewald: an N⋅log(N) method for Ewald sums in large systems. J. Chem. Phys. 98, 10089–10092 (1993).
Phillips, J. C. et al. Scalable molecular dynamics with NAMD. J. Comput. Chem. 26, 1781–1802 (2005).
Efron, B. & Tibshirani, R. J. An Introduction to the Bootstrap 372–391 (CRC Press, 1994).
Virtanen, P. et al. SciPy 1.0: fundamental algorithms for scientific computing in Python. Nat. Methods 17, 261–272 (2020).
Pedregosa, F. et al. Scikit-learn: machine learning in Python. J. Mach. Learn. Res. 12, 2825–2830 (2011).
Hagberg, A. A., Schult, D. A. & Swart, P. J. ExplorkX. In Proc. 7th Python in Science Conference https://www.osti.gov/servlets/purl/960616 (2008).
Hunter, J. D. Matplotlib: a 2D graphics environment. Comput. Sci. Eng. 9, 90–95 (2007).
Acknowledgements
We thank M. Bos, J. de Graf and D. Dulin for helpful discussions and L. Schendel, N. Beier, B. Böck, E. Durner, S. D. Pritzl and C. Körösy for help with experiments. This study was supported by German Research Foundation Projects 386143268 and 111166240, a Human Frontier Science Program Cross Disciplinary Fellowship (LT000395/2020C); European Molecular Biology Organization Non-Stipendiary long-term fellowship (ALTF 1047-2019) to L.F.M.; ERC Consolidator grant ‘ProForce’; and the Physics Department of LMU Munich. R.C.B., P.S.F.C.G. and M.C.R.M. are supported by the National Science Foundation under grant MCB-2143787, by start-up funds provided by Auburn University, and R.C.B. additionally receives support from the National Institute of General Medical Sciences (NIGMS) of NIH through grant R24-GM145965.
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M.S.B., S.G., A.H., M.C.R.M., P.S.F.C.G., H.E.G., R.C.B. and J.L. designed the research. M.S.B., S.G. and A.H. built the instruments and performed the experiments. P.S.F.C.G., M.C.R.M. and R.C.B. performed and analysed the simulations. M.S.B., S.G., A.H., L.F.M. and T.N. contributed the new reagents and analytic tools. M.S.B., S.G. and A.H. analysed the experimental data. M.S.B., S.G., A.H., M.C.R.M., P.S.F.C.G., H.E.G., R.C.B. and J.L. wrote the paper with input from all authors.
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Source Data Fig. 1
Example results from MT force spectroscopy: fraction bound versus force determined by MT: example magnetic traces, lifetimes bound and dissociated versus force from the MT data. Source Data Fig. 2 Results from MT force spectroscopy and affinity measurements for VOCs. Source Data Fig. 3 Results from the correlation analysis based on MD simulations.
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Bauer, M.S., Gruber, S., Hausch, A. et al. Single-molecule force stability of the SARS-CoV-2–ACE2 interface in variants-of-concern. Nat. Nanotechnol. 19, 399–405 (2024). https://doi.org/10.1038/s41565-023-01536-7
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DOI: https://doi.org/10.1038/s41565-023-01536-7