On-chip protein separation with single-molecule resolution

Abstract

Accurate identification of both abundant and rare proteins hinges on the development of single-protein sensing methods. Given the immense variation in protein expression levels in a cell, separation of proteins by weight would improve protein classification strategies. Upstream separation facilitates sample binning into smaller groups while also preventing sensor overflow, as may be caused by highly abundant proteins in cell lysates or clinical samples. Here, we scale a bulk analysis method for protein separation, sodium dodecyl sulfate–polyacrylamide gel electrophoresis (SDS-PAGE), to the single-molecule level using single-photon sensitive widefield imaging. Single-molecule sensing of the electrokinetically moving proteins is achieved by in situ polymerization of the PAGE in a low-profile fluidic channel having a depth of only ~ 0.6 µm. The polyacrylamide gel restricts the Brownian kinetics of the proteins, while the low-profile channel ensures that they remain in focus during imaging, allowing video-rate monitoring of single-protein migration. Calibration of the device involves separating a set of Atto647N-covalently labeled recombinant proteins in the size range of 14–70 kDa, yielding an exponential dependence of the proteins’ molecular weights on the measured mobilities, as expected. Subsequently, we demonstrate the ability of our fluidic device to separate and image thousands of proteins directly extracted from a human cancer cell line. Using single-particle image analysis methods, we created detailed profiles of the separation kinetics of lysine and cysteine -labeled proteins. Downstream coupling of the device to single-protein identification sensors may provide superior protein classification and improve our ability to analyze complex biological and medical protein samples.

The emerging landscape of single-molecule protein sequencing technologies

“…Classic approaches such as reductive amination with aldehydes or acylation with NHS esters, which rely on pH control residues in short polypeptides through specific coupling to fluorescent tags while using a solid-state nanopore with low fluorescence background 80 . In all these approaches, separating the proteins by mass before single-molecule sensing may have greatly facilitated the identification of proteins in complex samples containing many different proteins 81 . Nanopore protein fingerprinting can make extensive use of advanced deep learning artificial intelligence (AI) strategies to identify patterns in noisy signals.…”

Full‐Length Single Protein Molecules Tracking and Counting in Thin Silicon Channels

“…c) Top: a magnified white light view of the main channel showing the polymer plug section in which proteins are separated by mass/charge. Bottom: Fluorescence images of: c‐i) the labeled proteins during loading into the double “T” junction, c‐ii) stacking at the liquid/polymer interface, and c‐iii) during electrophoretic migration in the polymer plug (reproduced with permission [ 26 ] Copyright 2020, NPG). d) Fluorescence Kymograph of a run consisting of four labeled proteins with different molecular weights, visibly separated along the channel.…”

“…We found that the solid material fabrication was necessary to support the high aspect ratio of the device, without collapsing. [ 26 ] The filling zone of the devices consisted of a double “T” offset junction, which defined a precise sample volume loading of 4 pL. This is an outstanding feature of our device because ultra‐small volume analysis represents an ongoing challenge for current methodologies.…”

Single protein molecules separation, tracking and counting in ultra-thin silicon channels

“…We found that the solid material fabrication is necessary to support the high width/height aspect ratio of the device, without collapsing. 25 The filling zone of the devices consists of a double "T" offset junction, which defines a precise sample volume loading of 4 pL. This is an outstanding feature of our device since ultra-small volume analysis represents a significant challenge for the currently established detection methodologies.…”