Fast translocation of proteins through solid state nanopores

Abstract

Measurements on protein translocation through solid-state nanopores reveal anomalous (non-Smoluchowski) transport behavior, as evidenced by extremely low detected event rates; that is, the capture rates are orders of magnitude smaller than what is theoretically expected. Systematic experimental measurements of the event rate dependence on the diffusion constant are performed by translocating proteins ranging in size from 6 to 660 kDa. The discrepancy is observed to be significantly larger for smaller proteins, which move faster and have a lower signal-to-noise ratio. This is further confirmed by measuring the event rate dependence on the pore size and concentration for a large 540 kDa protein and a small 37 kDa protein, where only the large protein follows the expected behavior. We dismiss various possible causes for this phenomenon and conclude that it is due to a combination of the limited temporal resolution and low signal-to-noise ratio. A one-dimensional first-passage time-distribution model supports this and suggests that the bulk of the proteins translocate on time scales faster than can be detected. We discuss the implications for protein characterization using solid-state nanopores and highlight several possible routes to address this problem.

Figure 1

a) Schematic illustration of the nanopore setup, with the 20 nm thick SiN membrane and a β-Galactosidase protein shown to scale. Insert: TEM image of one of the 40 nm nanopores used in this study. b) Current trace of β-Galactosidase translocating through a 40 nm pore. c) Representative translocation events, shown at better temporal resolution.

Figure 2

(Left) The ratio of the observed event rate to the event rate predicted by the Smoluchowski rate equation for dsDNA (white diamonds) and protein (red stars). We expect all points to be in the green area with a ratio larger than one. Instead, we see that all protein measurements yield a ratio less than 1, with some values even up to five orders of magnitude smaller. This study focuses on explaining this discrepancy. (Right) Same data set versus the molecular weight. Proteins have been separated into positively charged (red triangles) and negatively charged (blue triangles) proteins. The ratio becomes worse as the size of the protein becomes smaller, which can be attributed to their faster diffusion as well as smaller excluded volumes.

Figure 3

a) The distortion of rectangular pulses of 10 to 200 μs duration by a 10 kHz Gaussian filter. For a 100 μs pulse duration the dashed red line shows an ideal pulse (delayed 40 μs for visual clarity), before filtering, while the solid red line shows the same 100 μs pulse after filtering. All pulses have the same amplitude before filtering. Due to the limited rise time of the filter, any pulse with a duration less than twice the filter rise time (2T_r = 66 μs) is distorted. b) A simulated dwell-time histogram showing visible (green) and lost (red) events given a resolution limit of 20 μs. At this resolution we expect the smallest protein, Ovalbumin, to show the most events (insert). If the temporal resolution would be improved to below 6 μs, however, the largest protein, Thyroglobulin, would produce the most observable events. c) The percentage of events below the temporal resolution (color scale) for various values of the diffusion coefficient and electrophoretic drift velocity. The estimated positions of four proteins are shown. We expect the majority of events for these proteins to be lost.

Figure 4

a) The event rate of protein translocation through a 40 nm nanopore for Aprotinin (6.5 kDa), Ovalbumin (45 kDa), B-Amylase (200 kDa), Ferritin (450 kDa), Thyroglobulin (660 kDa) at 1 μM concentration. The event rate is observed to decrease as the protein becomes smaller, i.e., when the diffusion constant becomes larger. This is counter to the predictions by both Smoluchowski and the FPTD model and is attributed to the reduction in the SNR as the proteins become smaller. b) The pore-size dependence of the event rate for 46 nM 540 kDa β-Galactosidase and 1.35 μM 37 kDa hCG. The event rate of β-Galactosidase increases linearly with pore size, as expected, while no change is observed for hCG. c) The concentration dependence of the event rate for these proteins. The event rate of β-Galactosidase increases linearly with concentration, as predicted by Smoluchowski. The event rate of hCG remains within the noise floor for all measurements.