Label-Free Characterization of Single Proteins Using Synthetic Nanopores

Abstract

Molecular diagnosis has proven to be a powerful tool for early detection of neurodegenerative disease, but research in this field is still relatively nascent. In Alzheimer's Disease specifically, levels of microtubule associated protein tau and amyloid beta in cerebrospinal fluid are becoming reliable pathological indicators. The current gold standard for detecting these biomarkers is an enzyme-linked immunosorbent assay, and while this method has a limit of detection on the order of picograms per mL, it lacks the ability to provide information about aggregation extent and structure on a per-protein basis. From a disease standpoint, neurological pathologies are often extremely complex in their biological manifestation, and precise mechanisms for many of these diseases are still being discovered and revised. A thorough understanding of in situ structure and properties of neurological disease-related proteins would likely help clarify some of these complicated mechanisms. Resistive-pulse methods may be useful in this effort, as they can determine specific biomarker concentrations and can also unveil multiple physical qualities of single proteins or protein aggregates in an aqueous sample. The latter capability is critical, and could allow for both earlier diagnoses and a stronger mechanistic understanding of neurological disease progression.

The work presented in this dissertation, therefore, represents broad efforts toward developing a nanopore-based system able to characterize amyloids and protein complexes related to neurodegenerative disease. These efforts range from upstream fabrication and characterization of nanopores in synthetic substrates to downstream techniques for optimizing the accuracy and efficiency of analyses on resistive pulses. Single proteins rotating and translating while tethered to the surface of a nanopore provide rich information during transit through the pore that makes it possible to determine their ellipsoidal shape, volume, dipole moment, charge, and rotational diffusion coefficient in a time frame of just a few hundred microseconds. This five-dimensional protein fingerprint, however, requires chemical modification of each protein and is thus not ideal for studying protein dynamics or transient protein complexes, both of which are relevant when characterizing amyloids. Transitioning to low-noise nanopore substrates and high-bandwidth recordings enables label-free identification and quantification of unperturbed, natively-folded proteins and protein complexes in solution -- no chemical tags, tethers, or fluorescent labels are needed. Such a transition is nontrivial; proteins passing uninhibited through the strong electric field inside of a nanopore rotate and translocate rapidly, posing a challenge to time-resolve their various orientations adequately while circumventing adhesion to nanopore walls. Furthermore, during their translocation through the nanopore, untethered, native proteins diffuse laterally, generating asymmetric disturbances of the electric field and larger-than-expected resistive pulse magnitudes. Known as off-axis effects, these latter phenomena add a noise-like element to the electrical recordings. We evaluate, both computationally and experimentally, the influence of such label-free complications on resulting parameter estimates, and place these results in the context of developing future iterations of nanopore-based protein sensors.

In light of the spectacular recent success of nanopore-based nucleic acid sequencing, it is likely that the next frontier for nanopore-based analysis is the characterization of single proteins and, in particular, the characterization of protein aggregates such as amyloids. The experiments and results presented here enable future particle-by-particle analysis of amyloids with nanopores to rapidly reconstruct their heterogeneity in size and shape, both of which are correlated with the neurotoxicity of amyloid samples and are being investigated as biomarkers for neurodegenerative diseases.