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Scaling analysis reveals the mechanism and rates of prion replication in vivo

Nature Structural & Molecular Biology volume 28, pages 365–372 (2021)Cite this article

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Abstract

Prions consist of pathological aggregates of cellular prion protein and have the ability to replicate, causing neurodegenerative diseases, a phenomenon mirrored in many other diseases connected to protein aggregation, including Alzheimer’s and Parkinson’s diseases. However, despite their key importance in disease, the individual processes governing this formation of pathogenic aggregates, as well as their rates, have remained challenging to elucidate in vivo. Here we bring together a mathematical framework with kinetics of the accumulation of prions in mice and microfluidic measurements of aggregate size to dissect the overall aggregation reaction into its constituent processes and quantify the reaction rates in mice. Taken together, the data show that multiplication of prions in vivo is slower than in in vitro experiments, but efficient when compared with other amyloid systems, and displays scaling behavior characteristic of aggregate fragmentation. These results provide a framework for the determination of the mechanisms of disease-associated aggregation processes within living organisms.

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Fig. 1: Principle of mechanistic analysis and increase of infectivity over time.
Fig. 2: PrPC and PrPSc concentrations over time for different mouse lines.
Fig. 3: Scaling exponents of the rate of infectivity and of PrPSc increase.
Fig. 4: Reaction network and consistent mechanisms.
Fig. 5: Sizing prions in brain homogenate.
Fig. 6: Individual rates in vivo and in vitro.

Data availability

All data generated or analyzed during this study are included in this published article (and its Supplementary information files). Source data are provided with this paper.

References

  1. Aguzzi, A. & Polymenidou, M. Mammalian prion biology. Cell 116, 313–327 (2004).

    Article  CAS  PubMed  Google Scholar 

  2. Prusiner, S. Novel proteinaceous infectious particles cause scrapie. Science 216, 136–144 (1982).

    Article  CAS  PubMed  Google Scholar 

  3. Sandberg, M. K., Al-Doujaily, H., Sharps, B., Clarke, A. R. & Collinge, J. Prion propagation and toxicity in vivo occur in two distinct mechanistic phases. Nature 470, 540–542 (2011).

    Article  CAS  PubMed  Google Scholar 

  4. Eigen, M. Prionics or the kinetic basis of prion diseases. Biophys. Chem. 63, A1–18 (1996).

    Article  CAS  PubMed  Google Scholar 

  5. Cohen, F. et al. Structural clues to prion replication. Science 264, 530–531 (1994).

    Article  CAS  PubMed  Google Scholar 

  6. Mudher, A. et al. What is the evidence that tau pathology spreads through prion-like propagation? Acta Neuropathol. Commun. 5, 99 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  7. Goedert, M., Clavaguera, F. & Tolnay, M. The propagation of prion-like protein inclusions in neurodegenerative diseases. Trends Neurosci. 33, 317–325 (2010).

    Article  CAS  PubMed  Google Scholar 

  8. Meisl, G., Knowles, T. P. & Klenerman, D. The molecular processes underpinning prion-like spreading and seed amplification in protein aggregation. Curr. Opin. Neurobiol. 61, 58–64 (2020).

    Article  CAS  PubMed  Google Scholar 

  9. Prusiner, S. B. et al. Measurement of the scrapie agent using an incubation time interval assay. Ann. Neurol. 11, 353–358 (1982).

    Article  CAS  PubMed  Google Scholar 

  10. Klohn, P.-C., Stoltze, L., Flechsig, E., Enari, M. & Weissmann, C. A quantitative, highly sensitive cell-based infectivity assay for mouse scrapie prions. Proc. Natl. Acad. Sci. USA 100, 11666–11671 (2003).

    Article  PubMed  Google Scholar 

  11. Caughey, B., Kocisko, D. A., Raymond, G. J. & Lansbury, P. T. Aggregates of scrapie-associated prion protein induce the cell-free conversion of protease-sensitive prion protein to the protease-resistant state. Chem. Biol. 2, 807–817 (1995).

    Article  CAS  PubMed  Google Scholar 

  12. Prusiner, S. B. Molecular biology of prion diseases. Science 252, 1515–1522 (1991).

    Article  CAS  PubMed  Google Scholar 

  13. Come, J. H., Fraser, P. E. & Lansbury, P. T. A kinetic model for amyloid formation in the prion diseases: importance of seeding. Proc. Natl. Acad. Sci. USA 90, 5959–5963 (1993).

    Article  CAS  PubMed  Google Scholar 

  14. Leffers, K.-W. et al. Assembly of natural and recombinant prion protein into fibrils. Biol. Chem. 386, 569–580 (2005).

    Article  CAS  PubMed  Google Scholar 

  15. Stöhr, J. et al. Mechanisms of prion protein assembly into amyloid. Proc. Natl Acad. Sci. USA 105, 2409–2414 (2008).

    Article  PubMed  Google Scholar 

  16. Knowles, T. P. J. et al. An analytical solution to the kinetics of breakable filament assembly. Science 326, 1533–1537 (2009).

    Article  CAS  PubMed  Google Scholar 

  17. Aguzzi, A. Understanding the diversity of prions. Nat. Cell Biol. 6, 290–292 (2004).

    Article  CAS  PubMed  Google Scholar 

  18. Nowak, M. A., Krakauer, D. C., Klug, A. & May, R. M. Prion infection dynamics. Integr. Biol. 1, 3–15 (1998).

    Article  Google Scholar 

  19. Masel, J., Jansen, V. A. & Nowak, M. A. Quantifying the kinetic parameters of prion replication. Biophys. Chem. 77, 139–152 (1999).

    Article  CAS  PubMed  Google Scholar 

  20. Serio, T. R. et al. Nucleated conformational conversion and the replication of conformational information by a prion determinant. Science 289, 1317–1321 (2000).

    Article  CAS  PubMed  Google Scholar 

  21. Poeschel, T., Brilliantov, N. V. & Froemmel, C. Kinetics of prion growth. Biophys. J. 85, 3460–3474 (2003).

    Article  CAS  Google Scholar 

  22. Greer, M. L., Pujo-Menjouet, L. & Webb, G. F. A mathematical analysis of the dynamics of prion proliferation. J. Theor. Biol. 242, 598–606 (2006).

    Article  PubMed  Google Scholar 

  23. Calvez, V. et al. Size distribution dependence of prion aggregates infectivity. Math. Biosci. 217, 88–99 (2009).

    Article  CAS  PubMed  Google Scholar 

  24. Kulkarni, R. V., Slepoy, A., Singh, R. R. P., Cox, D. L. & Pázmándi, F. Theoretical modeling of prion disease incubation. Biophys. J. 85, 707–718 (2003).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  25. Meisl, G., Dear, A. J., Michaels, T. C. T. & Knowles, T. P. J. Mechanism, scaling and rates of protein aggregation from in vivo measurements. Preprint at arXiv https://arxiv.org/abs/2008.09699 (2020).

  26. Mays, C. E. et al. Prion infectivity plateaus and conversion to symptomatic disease originate from falling precursor levels and increased levels of oligomeric prpsc species. J. Virol. 24, 12418–12426 (2015).

    Article  Google Scholar 

  27. Sandberg, M. K. et al. Prion neuropathology follows the accumulation of alternate prion protein isoforms after infective titre has peaked. Nat. Commun. 5, 4347 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Sorce, S. et al. Genome-wide transcriptomics identifies an early preclinical signature of prion infection. PLoS Pathog. 16, 1–26 (2020).

    Article  Google Scholar 

  29. Meisl, G. et al. Scaling behaviour and rate-determining steps in filamentous self-assembly. Chem. Sci. 8, 7087–7097 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Meisl, G. et al. Molecular mechanisms of protein aggregation from global fitting of kinetic models. Nat. Protoc. 11, 252–272 (2016).

    Article  CAS  PubMed  Google Scholar 

  31. Ferrone, F. A., Hofrichter, J. & Eaton, W. A. Kinetics of sickle hemoglobin polymerization. ii. a double nucleation mechanism. J. Mol. Biol. 183, 611–631 (1985).

    Article  CAS  PubMed  Google Scholar 

  32. Gaspar, R. et al. Secondary nucleation of monomers on fibril surface dominates α-synuclein aggregation and provides autocatalytic amyloid amplification. Q. Rev. Biophys. 50, E6 (2017).

    Article  PubMed  Google Scholar 

  33. Törnquist, M. et al. Secondary nucleation in amyloid formation. Chem. Commun. 54, 8667–8684 (2018).

    Article  Google Scholar 

  34. Törnquist, M. et al. Ultrastructural evidence for self-replication of alzheimer-associated Aβ42 amyloid along the sides of fibrils. Proc. Natl Acad. Sci. USA 117, 11265–11273 (2020).

    Article  PubMed  Google Scholar 

  35. Aguzzi, A., Heikenwalder, M. & Polymenidou, M. Insights into prion strains and neurotoxicity. Nat. Rev. Mol. Cell Biol. 8, 552–561 (2007).

    Article  CAS  PubMed  Google Scholar 

  36. Lau, A. et al. α-synuclein strains target distinct brain regions and cell types. Nat. Neurosci. 23, 21–31 (2020).

    Article  CAS  PubMed  Google Scholar 

  37. Peretz, D. et al. Antibodies inhibit prion propagation and clear cell cultures of prion infectivity. Nature 412, 739–743 (2001).

    Article  CAS  PubMed  Google Scholar 

  38. Safar, J. G. et al. Prion clearance in bigenic mice. J. Gen. Virol. 86, 2913–2923 (2005).

    Article  CAS  PubMed  Google Scholar 

  39. Oosawa, F. A historical perspective of actin assembly and its interactions. Results Probl. Cell Differ. 32, 9–21 (2001).

    Article  CAS  PubMed  Google Scholar 

  40. Cohen, S. I. A. et al. Proliferation of amyloid-β42 aggregates occurs through a secondary nucleation mechanism. Proc. Natl Acad. Sci. USA 110, 9758–9763 (2013).

    Article  CAS  PubMed  Google Scholar 

  41. Dear, A. J. et al. The catalytic nature of protein aggregation. J. Chem. Phys. 152, 045101 (2020).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Sang, J. C. et al. Direct observation of murine prion protein replication in vitro. J. Am. Chem. Soc. 140, 14789–14798 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  43. Ballmer, B. A. et al. Modifiers of prion protein biogenesis and recycling identified by a highlyparallel endocytosis kinetics assay. J. Biol. Chem. 292, 8356–8368 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Müller, T. et al. Particle-based montecarlo simulations of steady-state mass transport at intermediate péclet numbers. Int. J. Nonlinear Sci. Numer. Simul. 17, 175–183 (2016).

    Article  Google Scholar 

  45. Terry, C. et al. Ex vivo mammalian prions are formed of paired double helical prion protein fibrils. Open Biol. 6, 160035 (2016).

    Article  PubMed  PubMed Central  Google Scholar 

  46. Wenborn, A. et al. A novel and rapid method for obtaining high titre intact prion strains from mammalian brain. Sci. Rep. 5, 10062 (2015).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Rouvinski, A. et al. Live imaging of prions reveals nascent PrPSc in cellsurface, raft-associated amyloid strings and webs. J. Cell Biol. 204, 423–441 (2014).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  48. Silveira, J. R. et al. The most infectious prion protein particles. Nature 237, 257–261 (2005).

    Article  Google Scholar 

  49. Kundel, F. et al. Measurement of tau filament fragmentation provides insights into prion-like spreading. ACS Chem. Neurosci. 9, 1276–1282 (2018).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Meisl, G., Yang, X., Dobson, C. M., Linse, S. & Knowles, T. P. J. Modulation of electrostatic interactions to reveal a reaction network unifying the aggregation behaviour of the Aβ42 peptide and its variants. Chem. Sci. 8, 4352–4362 (2017).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  51. Fischer, M. et al. Prion protein (prp) with amino-proximal deletions restoring susceptibility of prp knockout mice to scrapie. EMBO J. 15, 1255–1264 (1996).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  52. Bueler, H. et al. Mice devoid of prp are resistant to scrapie. Cell 73, 1339–1347 (1993).

    Article  CAS  PubMed  Google Scholar 

  53. Karber, G. Beitrag zur kollektiven behandlung pharmakologischer reihenversuche. Naunyn Schmiedebergs Arch. Pharmacol. 162, 480–483 (1931).

    Article  Google Scholar 

  54. Lau, A. L. et al. Characterization of prion protein (prp)-derived peptides that discriminate full-length prpsc from prpc. Proc. Natl. Acad. Sci. USA 104, 11551–11556 (2007).

    Article  CAS  PubMed  Google Scholar 

  55. Polymenidou, M. et al. The pom monoclonals: A comprehensive set of antibodies to non-overlapping prion protein epitopes. PLoS ONE 3, 1–17 (2008).

    Article  Google Scholar 

  56. Mahal, S. P., Demczyk, C. A., Smith, E. W., Klohn, P.-C. & Weissmann, C. Assaying prions in cell culture: the standard scrapie cell assay (ssca) and the scrapie cell assay in end point format (scepa). Methods Mol. Biol. 459, 49–68 (2008).

    Article  CAS  PubMed  Google Scholar 

  57. Nuvolone, M. et al. Strictly co-isogenic c57bl/6j-prnp-/- mice: A rigorous resource for prion science. J. Exp. Med. 213, 313–327 (2016).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Brody, J. & Yager, P. Diffusion-based extraction in a microfabricated device. Sens. Actuators A Phys. 58, 13–18 (1997).

    Article  CAS  Google Scholar 

  59. Arosio, P. et al. Microfluidic diffusion analysis of the sizes and interactions of proteins under native solution conditions. ACS Nano 10, 333–341 (2016).

    Article  CAS  PubMed  Google Scholar 

  60. Ahmad, A., Uversky, V. N., Hong, D. & Fink, A. L. Early events in the fibrillation of monomeric insulin. J. Biol. Chem. 280, 42669–42675 (2005).

    Article  CAS  PubMed  Google Scholar 

  61. Bloom, C. R. et al. Ligand binding to wild-type and e-b13q mutant insulins: A three-state allosteric model system showing half-site reactivity. J. Mol. Biol. 245, 324–330 (1995).

    Article  CAS  PubMed  Google Scholar 

  62. Oliva, A., Farina, J. & Llabres, M. Development of two high-performance liquid chromatographic methods for the analysis and characterization of insulin and its degradation products in pharmaceutical preparations. J. Chromatogr. B Biomed. Sci. Appl. 749, 25–34 (2000).

    Article  CAS  PubMed  Google Scholar 

  63. Safar, J. et al. Eight prion strains have prp(sc) molecules with different conformations. Nat. Med. 4, 1157–1165 (1998).

    Article  CAS  PubMed  Google Scholar 

  64. Serban, D., Taraboulos, A., DeArmond, S. J. & Prusiner, S. B. Rapid detection of Creutzfeldt-Jakob disease and scrapie prion proteins. Neurology 40, 110–117 (1990).

    Article  CAS  PubMed  Google Scholar 

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Acknowledgements

We thank to P. Schwarz and R. Moos for technical help. We acknowledge funding from Sidney Sussex College Cambridge (G.M.), the Mexican National Council of Science and Technology (I.C.-M.) and Cambridge Trust (I.C.-M.), the Synapsis Foundation (S.S.), the ERC (T.P.J.K.), the Amyloidosis Foundation (M.N.) and Peterhouse College Cambridge (T.C.T.M.).

Author information

Author notes

  1. These authors contributed equally: Georg Meisl, Timothy Kurt, Itzel Condado-Morales.

Authors and Affiliations

  1. Centre for Misfolding Diseases, Yusuf Hamied Department of Chemistry, University of Cambridge, Cambridge, UK

    Georg Meisl, Itzel Condado-Morales, Thomas C. T. Michaels, Samuel I. A. Cohen, Christopher M. Dobson & Tuomas P. J. Knowles

  2. Department of Pathology, UC San Diego, San Diego, CA, USA

    Timothy Kurt, Cyrus Bett & Christina J. Sigurdson

  3. Institute of Neuropathology, University of Zurich, Zurich, Switzerland

    Itzel Condado-Morales, Silvia Sorce, Mario Nuvolone, Daniel Heinzer, Merve Avar, Simone Hornemann & Adriano Aguzzi

  4. Amyloidosis Research and Treatment Center, Foundation IRCCS Policlinico San Matteo, Department of Molecular Medicine, University of Pavia, Pavia, Italy

    Mario Nuvolone

  5. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA, USA

    Thomas C. T. Michaels

  6. Wren Therapeutics, Cambridge, UK

    Samuel I. A. Cohen

  7. Cavendish Laboratory, University of Cambridge, Cambridge, UK

    Tuomas P. J. Knowles

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Contributions

A.A., C.M.D., C.J.S. and T.P.J.K. conceived the study. T.K. and C.B. performed the PrPC and PrPSc measurement time courses in the four mouse lines. S.S., M.N., D.H. and M.A. performed the measurements of the infectivity by SSCA. I.C.-M. and S.H. designed and performed the prion size determination experiments. G.M. developed the theory and analyzed the data. G.M., S.I.A.C., T.C.T.M. and T.P.J.K. interpreted the data. G.M. wrote the manuscript. All authors contributed to editing the manuscript.

Corresponding authors

Correspondence to Christina J. Sigurdson or Tuomas P. J. Knowles.

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The authors declare no competing interests.

Additional information

Peer review information Nature Structural and Molecular Biology thanks Byron Caughey, Suzanne Sindi and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Inês Chen was the primary editor on this article and managed its editorial process and peer review in collaboration with the rest of the editorial team.

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Extended data

Extended Data Fig. 1 Comparison of infectivity and PrPSc amounts from Sandberg et al.

The data (open and filled circles) were obtained from Sandberg et al.27 Fig. 1 (PrP measurements, filled circles) and Fig. 2 (infectivity measurement, open circles). The infectivity data are given on a logarithmic scale but are here plotted on a linear scale, with the corresponding values given on the left axis. The PrPSc measurements are plotted on the right axis. Dotted lines connect the PrPSc measurements and are a guide to the eye. There is no clear systematic difference between PrPSc and infectivity when they are rescaled and both plotted in linear space. Data behind graphs are available as Source Data.

Source data

Extended Data Fig. 2 Sigmoidal and exponential fits of PrPSc measurements obtained here.

Data as shown in the main text (a-d), as well as the data obtained without PK digestion (e-g), fitted to both a sigmoidal function (solid line) and a simple exponential (dotted line). All data points (filled and open circles) are used in the sigmoidal fits, only pre-plateau data points (filled circles) are used in the exponential fits. The data include samples from different mice as well as technical repeats of the ELISA measurements (3-4 at each timepoint). Data behind graphs are available as Source Data.

Source data

Extended Data Fig. 3 Sigmoidal and exponential fits of data from Mays et al.

The data (open and filled circles) were obtained from Mays et al. 26 Fig. 2 (PrP measurements) and Fig. 4 (infectivity measurement). In the original paper the data are given for 10 different size fractions, the data here are a sum of all fractions. Fits to both a sigmoidal function (solid line) and a simple exponential (dotted line) are shown. All data points (filled and open circles) are used in the sigmoidal fits, only pre-plateau data points (filled circles) are used in the exponential fits. Data behind graphs are available as Source Data online.

Source data

Extended Data Fig. 4 Sigmoidal and exponential fits of data from Sandberg et al.

The data (open and filled circles) were obtained from Sandberg et al.27 Fig. 1. The infectivity data are given on a logarithmic scale and are analysed separately in Fig. 1 of the main text. Fits to both a sigmoidal function (solid line) and a simple exponential (dotted line) are shown. All data points (filled and open circles) are used in the sigmoidal fits, only pre-plateau data points (filled circles) are used in the exponential fits. Data behind graphs are available as Source Data.

Source data

Extended Data Fig. 5 Simulation and validation of microfluidic sizing.

a,b, Linking the ratio of concentrations in the diffused and the non-diffused halves of the channel to the hydrodynamic radius was accomplished by solving the diffusion equation for the relevant device geometry using finite element integration software. Shown are the results of simulations of the diffusion profiles (inset) and ratio of intensities from the non-diffused channel and the diffused channel, fnd/fd, for species with a range of hydrodynamic radii, for the device with 200 µm and 80 µm channel width, respectively. c. Validation was performed using lyophilised human insulin (Sigma-Aldrich UK). An insulin stock of 10 mg/ml was prepared in 50 mM HCl, filtered through a 22 µm filter. The concentration was measured in the NanoDrop 2000c (ThermoFisher Scientific) by UV absorbance at 276 nm, using an extinction coeffcient value of 1 for 1 mg/ml60. Insulin hexamer was prepared as described previously61. Monomeric or hexameric samples were injected into the microuidic device at a total flow rate of 400 µl/h, using a flow ratio of 19:21 protein to auxiliary buffer. For detection, the commercial HTRF immunoassay kit was used (Cisbio Bioassays, Codolet, France). Samples after diffusion (2 µl per well) were mixed with the antibody-pair (18 µl per well) and incubated for 30 min at room temperature. The TR-FRET readings were performed in Clariostar (BMG Labtech) in the time-resolved fluorescence mode, simultaneously with a standard curve made of 1:2 serial dilutions starting from 2 nM insulin. Quoted values are hydrodynamic radii, errors are standard deviations from 3 repeats, literature values from Oliva et al.62.

Extended Data Fig. 6 Separation and quantification of PrPC and PrPSc from prion-infected animals by centrifugation and size exclusion chromatography.

a, Brain homogenate from a WT mouse at the terminal stage of disease was subjected to centrifugation followed by FPLC. Aliquots (10 µl each) from fractions 2–12 and 13–23 were analysed by SDS-PAGE and western blotting without PK digestion was used to monitor PrP elution from the column, and revealed two distinct populations (indicated at top of panel a). b, PK digestion (20 µg/mL) of aliquots from fractions 3–6 (PrPSc) and 14–19 (PrPC) in (A) was used to reveal proteinase-resistant PrPSc. c, Aliquots (10 µl total) from fractions 15–19 of mice (genotype indicated) from shortly after inoculation and at the terminal stage of disease, labelled ‘early’ and ‘late’ respectively, were assessed by semi-quantitative dot blotting. PrPC was found primarily in fractions 16–19. d, Levels of PrPSc in aliquots (10 µl total) from (a) as assessed by peptide ELISA. Values were interpolated from a standard curve (R2=0.96) generated using recombinant mouse PrP. e, Aliquots (10 µl total) from (a) were mixed with an equal volume of 8 M Gdn-HCl or PBS and heated for 5 min at 80 °C prior to ELISA. Gdn-HCl denaturation increases the signal intensity of PrPSc by its disaggregation but does not alter the PrPC signals63,64. Samples were run in triplicate and the values were interpolated from a standard curve (R2=0.98) generated using recombinant mouse PrP.

Supplementary information

Supplementary Information

Supplementary Notes 1–5.

Reporting Summary

Supplementary Table 1

Summary of numbers of mice used. Figure 2a of the main text shows the averages of the PrPC measurements at early time and terminal disease. Figure 2b–e shows all technical repeats of the PrPSc ELISA measurements. Three technical repeats for each mouse are performed for the Prnp0/+ line, and four technical repeats for all the others. The table gives the time-point and the number of mice used in PrPSc ELISA measurements at that time-point in round brackets for each of the lines. The numbers of mice used to determine the early time and terminal disease levels of PrPC are also given in square brackets.

Supplementary Table 2

Summary of scaling exponents. The scaling exponents determined from all three datasets by the different methods, as well as their standard errors from a linear regression analysis, are given. Both the mean value for the scaling and the mean errors are calculated. Details are in Supplementary Note 2.

Source data

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Meisl, G., Kurt, T., Condado-Morales, I. et al. Scaling analysis reveals the mechanism and rates of prion replication in vivo. Nat Struct Mol Biol 28, 365–372 (2021). https://doi.org/10.1038/s41594-021-00565-x

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