Single Protein Characterization Methods with Nanopores

Transcription

1 Single Protein Characterization Methods with Nanopores Michael Mayer 1 Erik C. Yusko 1, Jay Johnson 1, Alex M. Petti 1, Panchika Prangkio 1, Sheereen Majd 1, Brandon R. Bruhn 1, Ryan C. Rollings 2, Jiali Li 2, David Sept 1, Jerry Yang 3 1 University of Michigan, Ann Arbor, MI USA, 2 University of Arkansas, Fayetteville, AR USA, 3 University of California, San Diego, CA USA mimayer@umich.edu

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3 Sensing particles with nanopores: the experiment electrolyte-filled nanopore Count single molecules only single molecule method which measures a particle volumetrically. R.W. Lines pg. 352 Particle Size Analysis, 1992 I Protein volume t d 1 / Electrophoretic mobility f Concentration or interaction rates 3

4 Importance of nanopores Single particle detection: Beads Viruses Nucleic acids Proteins J. D. Uram, K. Ke, A. J. Hunt, M. Mayer, Small 2006, 2, 967 Small molecules Kaufmann B. et al, 2006, PNAS, 103,

5 Other unique capabilities of nanopores Label-free One particle at a time Example: In Situ Monitoring of Immunoprecipitation True size distributions Small footprint Low power Simple operation J. D. Uram, K. Ke, A. J. Hunt, M. Mayer, Angew. Chem. Int. Ed. 2006, 45,

6 Challenges of sensing proteins with nanopores - t d values are often not timeresolved inaccurate I signals. - Non-specific adsorption clogs nanopores and affects t d. - All proteins in solution contribute to the signal not specific. - Surface chemistry is ill-defined. - Fine tuning the pore size is difficult. - Real-time, dynamic changes in pore size are rarely realized. Wei R. et al, Nat. Nanotechnol., 2012 Sexton et al, JACS, 2010 Jovanovic-Talisman et al. Nature, 2009 Ding et al, Anal. Chem., 2009 Wanunu and Meller, Nano Letters, 2007 Kowalczyk et al. Nat. Nanotechnol.,

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8 Add fluid walls with mobile ligands 8

9 Mobile ligands provide sensitivity and specificity organisms handle some of the problems of timing and efficiency,, by reducing the dimensionality in which diffusion takes place G. Adam & M. Delbrück Reduction of Dimensionality in Biological Diffusion Processes. pg. 198 in Structural Chemistry and Molecular Biology Frequency of Events, s -1 Streptavidin IgG anti-biotin Fab anti-biotin 500x increase in f 10x increase in f 100x increase in f 9

10 enable controlled translocation of proteins Control and predict P(t d ) because t d bilayer viscosity Determine protein charge because non-specific adsorption is reduced and t d drift velocity Modified from Talaga and Li. JACS Yusko et al. Nature Nanotechnol

11 enable accurate measurements of volume I l V P A 1.6r P 2 Measured Volume = 94 ± 18 nm 3 Expected: 105 ± 3 nm 3 11

12 and enable calculation of affinity constants. 2 (,) rt (,) rt 1 (,) rt D 2 t r r r Numerically approximate and add binding isotherm f T 4 D 4Dt ln 2 r0 L[P] [P] K Szabo et al. J. Electroanal. Chem. (1987) D D r O L 2-1 Diffusion constant [m s ] Radius of the pore [m] -2 Ligand density [# m ] [P] Protein concentration [M] K D Dissociation constant [M]

13 f T ln Affinity constants testing f (D, L ) 4 D 4Dt r 2 0 L[P] [P] K D L = Biotin-PE 10,000 fold molar excess of Streptavidin L = PL f T 4 D L ln 4Dt 2 r 0 Binding Kinetics Expected vs. Measured Frequency Frequency (s -1 ) E-3 0.5E E-3 2.0E-3 4.0E-3 25 L (mol%) Frequency (s -1 ) Expected f for L = PL 95% CI for expected f Time (h) L (mol%)

14 anti-biotin mab IgG 1 : biotinyl-cap-pe affinity Frequency (s -1 ) K D = 0.93 ± 0.03 M R 2 = [mab] (nm) f T 4 D L [P] ln 4Dt [P] K D 2 r 0 Affinity Capillary Electrophoresis - Anti-biotin mab IgG 1 : Biotin-Fluorescein K D = 0.35 ± 0.04 M

15 Monitor membraneactive enzymes Yusko et al. Nature Nanotechnol

16 Determining the shape of proteins Yusko et al. submitted

17 Widely varying maximum I values due to IgG antibodies 17

18 Varying I values are not due to impurities 18

19 Varying I values are not due to IgG 1 dimers nm IgG 1 in 2 M KCl 500 nm IgG 1 in 8 M Urea nm nm G(D) 0.5 D H = nm Jøssang et al. J. Protein Chem Bermudez et al. J. Chromatgro. B Diameter (nm) 19

20 Distributions of I due to spherical proteins are Normal I l V P A 1.6r P 2 where = 1.5 for spheres 20

21 Extremes of Orientation during Translocation 21

22 Values of the shape factor 1 II n m II 1 ( ) 1 1 n ( m) n is a depolarization factor well tabulated by Osborn in 1945 D.C. Golibersuch. Biophysical J J.A. Osborn. Physical Review

23 Values of the shape factor 2 cos ll 90 D.C. Golibersuch. Biophysical J

24 Rotation of oblates in a resistive-pulse sensor D.C. Golibersuch. Biophysical J EM Image Courtesy of NASA 24

25 P(energy of a dipole) D.C. Golibersuch. Biophysical J P( ) d d 2 1/2 II 0.5 E 1 1 II P( ) d exp d 1/2 A KT 2 II 25

26 Possible orientations of proteins IgG 1 antibody V I S D D A ( / ) M P l r P P = volume of the protein = shape factor Fab fragment GPI anchored acetylcholinesterase 26

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28 p[ ] I Fitting P(I) to determine the shape of proteins p( I) p[ I ] p( I ) I min ( min ) I max ( max ) p( ) I 28

29 With I min and I max Shape and Volume I( ( m), ) ( mv ) l P A 1.6r P 2 I min ( min, ) I max ( max, ) min( m), I m max( m), I min max solve for and m 29

30 IgG 1 antibodies 30

31 Fab GPI-acetylcholinesterase 31

32 Calculated volumes and shapes of proteins Protein Measured Volume (nm 3 ) Expected Volume (nm 3 ) Measured Shape Parameter, m Expected Shape Parameter, m IgG ± ± ± ,55 GPI AchE 216 ± a 0.53 or Fab fragment 160 ± a ± or Streptavidin 110 ±25 b 94 ± ±

33 Dipole moment of IgG 1 and acetylcholinesterase AchE IgG 1 33

34 Single events and rotational diffusion of IgG 1 34

35 Rotational diffusion of acetylcholinesterase 35

36 Rotational diffusion coefficient and dipole moment of IgG, GPI-AChE and SA from single translocation events T C as expected IgG D R = 3,700 rad 2 /s = 1,220 D T C as expected GPI AChE D R = 6,000 rad 2 /s = 730 D Literature: D R = 6,000 14,000 rad 2 /s = 700 1,000 D T C factor 1.5 shorter than expected SA D R = 7,200 rad 2 /s = 1,750 D 36

37 Single particle characterization of A oligomers in solution. Yusko et al. ACS Nano

38 A is implicated in Alzheimer s disease - Various shapes - Heterogeneous, dynamic populations Well-suited for the volumetric, singleparticle capabilities of nanopores. Adapted from: Arispe et al. Biochimica Et. Biophysica Acta. 2007; Shirwany et al. Neuropsychiatry 38 Dis Trett. 2007; Demuro et al. J. Biol. Chem

39 Connection between pore formation and cytotoxicity due to A aggregates Prangkio P., Yusko E.C., Sept D., Yang J., Mayer M. PLOS ONE

40 Uncoated nanopores clog with A I(t) = min 40

41 Nanopores with fluid walls did not clog 4 min 41

42 Track aggregation over time 42

43 Grouping A by I (iii) (i) l M >> l P l M << l P (ii) (iv) l M ~ l P l M >> l P VA (1) I for l l VA AX (2) I for l l M P lp rp l 1.6r P P M P

44 Grouping A oligomers by I Fibrils with l M > l P Protofibrils with l M > l P Protofibrils with l M < l P Spherical oligomers with l M < l P 44

45 Spherical oligomers Yusko et al. ACS Nano

46 Protofibrils and fibers longer than the length of the nanopore Yusko et al. ACS Nano

47 Coating nanopore walls with fluid, lipid bilayers makes it possible to: Capture and concentrate specific proteins Control and predict the translocation speed of proteins Determine, in the same experiment, a proteins size, shape, charge, dipole moment, rotational diffusion coefficient, and affinity for a ligand. Generate non-fouling pores which enables characterization of the size and concentration of Alzheimer s Disease-related A peptides. 47

48 Prof. Michael Mayer Prof. Jerry Yang (UCSD) Prof. Jiali Li (U. Arkansas) Prof. David Sept (U. Mich.) Erik Yusko Alex Petti Jay Johnson Dr. Panchika Prangkio Dr. Sheereen Majd Brandon Bruhn Ryan Rollings (U. Arkansas) Funding: NSF CAREER (M.M.) NIH RO1 (M.M.) Coulter Foundation (M.M.) GAANN Fellowship, Rackham Predoc (E.Y.)