Engineering and Modeling the Electrophoretic Trapping of a Single Protein Inside a Nanopore
Source abstract
Abstract
High Resolution Image Download MS PowerPoint Slide The ability to confine and to study single molecules has enabled important advances in natural and applied sciences. Recently, we have shown that unlabeled proteins can be confined inside the biological nanopore Cytolysin A (ClyA) and conformational changes monitored by ionic current recordings. However, trapping small proteins remains a challenge. Here, we describe a system where steric, electrostatic, electrophoretic, and electro-osmotic forces are exploited to immobilize a small protein, dihydrofolate reductase (DHFR), inside ClyA. Assisted by electrostatic simulations, we show that the dwell time of DHFR inside ClyA can be increased by orders of magnitude (from milliseconds to seconds) by manipulation of the DHFR charge distribution. Further, we describe a physical model that includes a double energy barrier and the main electrophoretic components for trapping DHFR inside the nanopore. Simultaneous fits to the voltage dependence of the dwell times allowed direct estimates of the cis and trans translocation probabilities, the mean dwell time, and the force exerted by the electro-osmotic flow on the protein (≅9 pN at −50 mV) to be retrieved. The observed binding of NADPH to the trapped DHFR molecules suggested that the engineered proteins remained folded and functional inside ClyA. Contact-free confinement of single proteins inside nanopores can be employed for the manipulation and localized delivery of individual proteins and will have further applications in single-molecule analyte sensing and enzymology studies.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Nanopore and Nanochannel Transport Studies · Microfluidic and Bio-sensing Technologies · Microfluidic and Capillary Electrophoresis Applications
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Chemistry, KU Leuven, Celestijnenlaan 200F, B-3001 Leuven, Belgium
imec, Kapeldreef 75, B-3001 Leuven, Belgium
Department of Physics and Astronomy, KU Leuven, Celestijnenlaan 200D, B-3001 Leuven, Belgium
Groningen Biomolecular Sciences & Biotechnology Institute, University of Groningen, 9747 AG Groningen, The Netherlands
Funding
Fonds Wetenschappelijk Onderzoek · Agentschap voor Innovatie door Wetenschap en Technologie · FP7 Ideas: European Research Council
References (82)
Show source-provided references
1. 10.1002/anie.20160049510.1002/anie.201600495 ↗
2. 10.1002/1438-5171(200112)2:4<229::AID-SIMO229>3.0.CO;2-910.1002/1438-5171(200112)2:4<229::AID-SIMO229>3.0.CO;2-9 ↗
3. 10.1098/rstb.2016.023010.1098/rstb.2016.0230 ↗
4. 10.1038/nature0940410.1038/nature09404 ↗
5. 10.1038/nnano.2015.17310.1038/nnano.2015.173 ↗
6. 10.1063/1.178584410.1063/1.1785844 ↗
7. 10.1002/wnan.147710.1002/wnan.1477 ↗
8. 10.1002/adom.20180000510.1002/adom.201800005 ↗
9. 10.1038/nature0759310.1038/nature07593 ↗
10. 10.1021/nl902922510.1021/nl9029225 ↗
11. 10.1038/nphys142210.1038/nphys1422 ↗
12. 10.1021/nl203145810.1021/nl2031458 ↗
13. 10.1021/nl203719v10.1021/nl203719v ↗
14. 10.3791/442410.3791/4424 ↗
15. 10.1117/12.206205110.1117/12.2062051 ↗
16. 10.1039/C5NR05341B10.1039/C5NR05341B ↗
17. 10.1038/s41467-018-04118-710.1038/s41467-018-04118-7 ↗
18. 10.1002/smtd.20180046510.1002/smtd.201800465 ↗
19. 10.1063/1.187222010.1063/1.1872220 ↗
20. 10.1073/pnas.050997610310.1073/pnas.0509976103 ↗
21. 10.1038/nchem.54510.1038/nchem.545 ↗
22. 10.1073/pnas.111357210810.1073/pnas.1113572108 ↗
23. 10.1073/pnas.110355410810.1073/pnas.1103554108 ↗
24. 10.1002/cbic.20090052610.1002/cbic.200900526 ↗
25. 10.1016/j.ymeth.2016.03.02610.1016/j.ymeth.2016.03.026 ↗
26. 10.1039/C8CS00106E10.1039/C8CS00106E ↗
27. 10.1063/1.276720610.1063/1.2767206 ↗
28. 10.1021/nl304267810.1021/nl3042678 ↗
29. 10.1021/nn400456710.1021/nn4004567 ↗
30. 10.1016/j.bpj.2013.12.02510.1016/j.bpj.2013.12.025 ↗
31. 10.1021/acsnano.7b0121210.1021/acsnano.7b01212 ↗
32. 10.1021/acsnano.8b0073410.1021/acsnano.8b00734 ↗
33. 10.1021/acsnano.8b0955510.1021/acsnano.8b09555 ↗
34. 10.1038/nnano.2012.2410.1038/nnano.2012.24 ↗
35. 10.1038/nnano.2011.1210.1038/nnano.2011.12 ↗
36. 10.1038/nnano.2016.26710.1038/nnano.2016.267 ↗
37. 10.1021/ja210565310.1021/ja2105653 ↗
38. 10.1021/nl302443810.1021/nl3024438 ↗
39. 10.1021/ja108761210.1021/ja1087612 ↗
40. 10.1038/nbt.335710.1038/nbt.3357 ↗
41. 10.1038/srep1164310.1038/srep11643 ↗
42. 10.1021/acs.nanolett.8b0296810.1021/acs.nanolett.8b02968 ↗
43. 10.1063/1.489440110.1063/1.4894401 ↗
44. 10.1529/biophysj.104.05740610.1529/biophysj.104.057406 ↗
45. 10.1038/srep0388510.1038/srep03885 ↗
46. 10.1021/acsami.6b0369710.1021/acsami.6b03697 ↗
47. 10.1038/srep1041910.1038/srep10419 ↗
48. 10.1021/ja710787a10.1021/ja710787a ↗
49. 10.1021/ja405339810.1021/ja4053398 ↗
50. 10.1021/jacs.5b0152010.1021/jacs.5b01520 ↗
51. 10.1021/acsnano.6b0776010.1021/acsnano.6b07760 ↗
52. 10.1021/jacs.7b1010610.1021/jacs.7b10106 ↗
53. 10.1038/s41467-018-06534-110.1038/s41467-018-06534-1 ↗
54. 10.1021/nn506077e10.1021/nn506077e ↗
55. 10.1021/acs.nanolett.5b0230910.1021/acs.nanolett.5b02309 ↗
56. 10.1038/nature0802610.1038/nature08026 ↗
57. 10.1006/jmbi.1993.162610.1006/jmbi.1993.1626 ↗
58. 10.1016/0263-7855(96)00018-510.1016/0263-7855(96)00018-5 ↗
59. 10.1002/jcc.2028910.1002/jcc.20289 ↗
60. 10.1021/acsnano.6b0315910.1021/acsnano.6b03159 ↗
61. 10.1073/pnas.18134239810.1073/pnas.181342398 ↗
62. 10.1093/nar/gkh38110.1093/nar/gkh381 ↗
63. 10.1093/nar/gkm27610.1093/nar/gkm276 ↗
64. 10.1093/nar/gks41910.1093/nar/gks419 ↗
65. 10.1021/ct500592m10.1021/ct500592m ↗
66. Stone, J. An Efficient Library for Parallel Ray Tracing and Animation. M.Sc. Thesis, Computer Science Department, University of Missouri-Rolla, 1998.
67. 10.12688/f1000research.6968.110.12688/f1000research.6968.1 ↗
68. 10.1002/prot.2066010.1002/prot.20660 ↗
69. 10.1021/ja901088b10.1021/ja901088b ↗
70. 10.1529/biophysj.105.06203410.1529/biophysj.105.062034 ↗
71. 10.1038/nphys34410.1038/nphys344 ↗
72. 10.1038/nphys123010.1038/nphys1230 ↗
73. 10.1103/PhysRevE.86.01192110.1103/PhysRevE.86.011921 ↗
74. 10.1021/nn103479510.1021/nn1034795 ↗
75. 10.1529/biophysj.107.10473710.1529/biophysj.107.104737 ↗
76. 10.1021/ac402176910.1021/ac4021769 ↗
77. 10.1093/bioinformatics/btp16310.1093/bioinformatics/btp163 ↗
78. 10.1002/jcc.2335410.1002/jcc.23354 ↗
79. Maglia G. · 2010 · 475 · 59110.1016/S0076-6879(10)75022-9 ↗
80. 10.1109/MCSE.2011.3710.1109/MCSE.2011.37 ↗
81. McKinney, W. Data Structures for Statistical Computing in Python. Proceedings of the 9th Python in Science Conference, Austin, Texas (https://conference.scipy.org/scipy2010/); 2010; pp 51–56.10.25080/Majora-92bf1922-00a ↗
82. 10.5281/zenodo.1181310.5281/zenodo.11813 ↗