Multiplexed Digital Characterization of Misfolded Protein Oligomers via Solid-State Nanopores

Abstract

Misfolded protein oligomers are of central importance in both the diagnosis and treatment of Alzheimer's and Parkinson's diseases. However, accurate high-throughput methods to detect and quantify oligomer populations are still needed. We present here a single-molecule approach for the detection and quantification of oligomeric species. The approach is based on the use of solid-state nanopores and multiplexed DNA barcoding to identify and characterize oligomers from multiple samples. We study α-synuclein oligomers in the presence of several small-molecule inhibitors of α-synuclein aggregation as an illustration of the potential applicability of this method to the development of diagnostic and therapeutic methods for Parkinson's disease.

Figure 1

Schematic illustration of the process of αS oligomer formation in Parkinson’s disease, of its inhibition by compounds that can block secondary nucleation, and of the method reported here to measure the efficacy of these compounds, which is based on DNA nanostructures. (A) Age-related progressive impairment of the protein homeostasis system leads to the aberrant misfolding and aggregation of αS into toxic oligomeric species, which eventually convert to amyloid fibrils. These fibrils are observed as the primary constituents of Lewy bodies, a hallmark structure observed in brain cells of patients suffering from the disease. Fibrils can act as a catalyst for further oligomer formation via secondary processes, such as secondary nucleation from catalytic sites on the fibril surface and fragmentation of the fibrils into smaller species. Secondary processes are the key generators of oligomeric species. (B) Structure-based iterative machine learning strategy composed of docking simulations followed by cycles of active machine learning was employed in a parallel work by the authors to identify secondary nucleation inhibitors. I3.08 from that work is used here as a tool compound here. (C) Oligomer inhibitors have different efficacies, which have previously been challenging to establish, given how difficult oligomers are to measure. (D) Previous approaches to oligomer measurement in nanopores have attempted to measure protein levels in the absence of any tagging methods, which is a difficult task prone to error given how challenging individual oligomer translocations are to reliably differentiate from each other and from monomer. Monomer (i) and heavily oligomerized (ii) samples are shown as examples in an uncoated pore with a diameter of ∼15 nm. Oligomers cannot be readily probed at a single-molecule level via this approach, meaning that only bulk levels can be measured. (E) A novel oligomer measurement approach employing unique DNA nanostructure barcoding of each particle in a sample enables both single-molecule resolution of oligomers and multiplexing of samples, delivering improved metrics of inhibitor efficacy and increased throughput. (i) Monomeric protein with an attached barcode exhibits no adjacent spike, as the nanopore diameter has been tailored so that monomers do not generate a signal. (ii) Lightly oligomerized sample exhibits a clear spike in association with the unique barcode. The barcoded protein can enter the pore in either orientation (barcode first or protein first).

Figure 2

Design of a DBCO-DNA nanostructure for the capture of azide-labeled αS aggregates. (A) Schematic of the DNA nanostructure containing the DNA barcode region and a DBCO-tagged dsDNA overhang for click coupling to azide-tagged N122C-αS. DNA barcodes allow for a digital read-out of the single-molecule translocations using DNA dumbbells to create distinct 1 or 0 bits. (B) N122C-αS is tagged with iodoacetamide-PEG₃-azide and then incubated with the DBCO-tagged nanostructure, allowing facile click coupling of the two components.

Figure 3

Detection of stabilized αS oligomers using nanopores. (A) Nanopore schematic representing the nanostructures with and without αS oligomers bound. (B) Current trace of the nanopore with no protein bound (left) and with an αS oligomer bound (right). (C) Percentage of events with spike for a control sample without αS added (N = 48), an αS monomer sample (N = 154), and an αS oligomer sample (N = 248). The samples with just αS monomers and stabilized αS oligomers act as negative and positive controls, respectively, and show a low percentage of false positives. (D) Normalized event duration (normalized to pore baseline current) for samples with barcode only (monomeric and oligomeric αS) or with a barcode and spike (oligomeric αS).

Figure 4

Preparation of an αS aggregation time-course in the absence and presence of inhibitor molecules, and extraction of oligomers. (A, B) Kinetic traces are shown of a 10 μM solution of azide-tagged N122C-αS supplemented with 100 nM preformed seeds (pH 7.4, 37 °C, shaking at 200 rpm, error bars denote SD) in the presence of 1% DMSO (purple), 25 μM Anle-138b (blue), or I3.08 (orange). The raw fluorescence (A) and normalized fluorescence (B) are shown. The end points were normalized to the αS monomer concentration at the end of the experiment, which was detected via the Pierce BCA Protein Assay at t = 100 h. Anle-138b could not be suitably normalized due to the noise of the sample. (C) Samples were extracted at 32 h from the time course of aggregation and centrifuged to remove fibrils from the mixture, leaving only αS monomers and soluble oligomeric species for analysis. These samples were then incubated with a unique DBCO-tagged DNA barcode overnight before analysis via solid-state nanopore detection.

Figure 5

Schematic of the multiplexing pipeline and comparison of two different inhibitor molecules’ effects against time-course samples. (A) Samples are tagged with a unique DNA barcode that allows identification in a multiplexed mixture, increasing the throughput. The events observed as the oligomers translocate through the nanopore can then be analyzed to give an oligomer number per tag, and a relative area under the curve of each tag, proportional to oligomer size. (B) Fraction of events with an oligomer bound to the DNA barcode: DMSO (purple) (N = 114 ± 7), Anle-138b (blue) (N = 43 ± 16), and I3.08 (orange) (N = 90 ± 4). The standard deviation comes from repeats where the samples were combined, diluted in measurement buffer, and measured for ∼1 h. (C) Area of the current drop of the protein spike caused by bound oligomer in the DMSO (purple), Anle-138b (blue), and I3.08 (orange) samples. A larger area implies that larger species are bound to the barcode on average.