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

Emerging single-molecule protein sensing techniques are ushering in a transformative era in biomedical research. Nevertheless, challenges persist in realizing ultra-fast full-length protein sensing, including loss of molecular integrity due to protein fragmentation, biases introduced by antibodies affinity, identification of proteoforms, and low throughputs. Here, a single-molecule method for parallel protein separation and tracking is introduced, yielding multi-dimensional molecular properties used for their identification. Proteins are tagged by chemo-selective dual amino-acid specific labels and are electrophoretically separated by their mass/charge in custom-designed thin silicon channel with subwavelength height. This approach allows analysis of thousands of individual proteins within a few minutes by tracking their motion during the migration. The power of the method is demonstrated by quantifying a cytokine panel for host-response discrimination between viral and bacterial infections. Moreover, it is shown that two clinically-relevant splice isoforms of Vascular endothelial growth factor (VEGF) can be accurately quantified from human serum samples. Being non-destructive and compatible with full-length intact proteins, this method opens up ways for antibody-free single-protein molecule quantification.

Single-File Translocation Dynamics of SDS-Denatured, Whole Proteins through Sub-5 nm Solid-State Nanopores.

The ability to routinely identify and quantify the complete proteome from single cells will greatly advance medicine and basic biology research. To meet this challenge of single-cell proteomics, single-molecule technologies are being developed and improved. Most approaches, to date, rely on the analysis of polypeptides, resulting from digested proteins, either in solution or immobilized on a surface. Nanopore biosensing is an emerging single-molecule technique that circumvents surface immobilization and is optimally suited for the analysis of long biopolymers, as has already been shown for DNA sequencing. However, proteins, unlike DNA molecules, are not uniformly charged and harbor complex tertiary structures. Consequently, the ability of nanopores to analyze unfolded full-length proteins has remained elusive. Here, we evaluate the use of heat denaturation and the anionic surfactant sodium dodecyl sulfate (SDS) to facilitate electrokinetic nanopore sensing of unfolded proteins. Specifically, we characterize the voltage dependence translocation dynamics of a wide molecular weight range of proteins (from 14 to 130 kDa) through sub-5 nm solid-state nanopores, using a SDS concentration below the critical micelle concentration. Our results suggest that proteins' translocation dynamics are significantly slower than expected, presumably due to the smaller nanopore diameters used in our study and the role of the electroosmotic force opposing the translocation direction. This allows us to distinguish among the proteins of different molecular weights based on their dwell time and electrical charge deficit. Given the simplicity of the protein denaturation assay and circumvention of the tailor-made necessities for sensing protein of different folded sizes, shapes, and charges, this approach can facilitate the development of a whole proteome identification technique.

The emerging landscape of single-molecule protein sequencing technologies.

Single-cell profiling methods have had a profound impact on the understanding of cellular heterogeneity. While genomes and transcriptomes can be explored at the single-cell level, single-cell profiling of proteomes is not yet established. Here we describe new single-molecule protein sequencing and identification technologies alongside innovations in mass spectrometry that will eventually enable broad sequence coverage in single-cell profiling. These technologies will in turn facilitate biological discovery and open new avenues for ultrasensitive disease diagnostics.

On-chip protein separation with single-molecule resolution.

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.

Simulation of single-protein nanopore sensing shows feasibility for whole-proteome identification.

Single-molecule techniques for protein sequencing are making headway towards single-cell proteomics and are projected to propel our understanding of cellular biology and disease. Yet, single cell proteomics presents a substantial unmet challenge due to the unavailability of protein amplification techniques, and the vast dynamic-range of protein expression in cells. Here, we describe and computationally investigate the feasibility of a novel approach for single-protein identification using tri-color fluorescence and plasmonic-nanopore devices. Comprehensive computer simulations of denatured protein translocation processes through the nanopores show that the tri-color fluorescence time-traces retain sufficient information to permit pattern-recognition algorithms to correctly identify the vast majority of proteins in the human proteome. Importantly, even when taking into account realistic experimental conditions, which restrict the spatial and temporal resolutions as well as the labeling efficiency, and add substantial noise, a deep-learning protein classifier achieves 97% whole-proteome accuracies. Applying our approach for protein datasets of clinical relevancy, such as the plasma proteome or cytokine panels, we obtain ~98% correct protein identification. This study suggests the feasibility of a method for accurate and high-throughput protein identification, which is highly versatile and applicable.

Designing Bacterial Chemotactic Receptors Guided by Photonic Femtoliter Well Arrays for Quantifiable, Label-Free Measurement of Bacterial Chemotaxis.

Whole cell bioreporters, such as bacterial cells, can be used for environmental and clinical sensing of specific analytes. However, the current methods implemented to observe such bioreporters in the form of chemotactic responses heavily rely on microscope analysis, fluorescent labels, and hard-to-scale microfluidic devices. Herein, we demonstrate that chemotaxis can be detected within minutes using intrinsic optical measurements of silicon femtoliter well arrays (FMAs). This is done via phase-shift reflectometric interference spectroscopic measurements (PRISM) of the wells, which act as silicon diffraction gratings, enabling label-free, real-time quantification of the number of trapped bacteria cells in the optical readout. By generating unsteady chemical gradients over the wells, we first demonstrate that chemotaxis toward attractants and away from repellents can be easily differentiated based on the signal response of PRISM. The lowest concentration of chemorepellent to elicit an observed bacterial response was 50 mM, whereas the lowest concentration of chemoattractant to elicit a response was 10 mM. Second, we employed PRISM, in combination with a computational approach, to rapidly scan for and identify a novel synthetic histamine chemoreceptor strain. Consequently, we show that by using a combined computational design approach, together with a quantitative, real-time, and label-free detection method, it is possible to manufacture and characterize novel synthetic chemoreceptors in Escherichia coli (E. coli).

A Synthetic Oligo Library and Sequencing Approach Reveals an Insulation Mechanism Encoded within Bacterial σ54 Promoters.

We use an oligonucleotide library of >10,000 variants to identify an insulation mechanism encoded within a subset of σ54 promoters. Insulation manifests itself as reduced protein expression for a downstream gene that is expressed by transcriptional readthrough. It is strongly associated with the presence of short CT-rich motifs (3-5 bp), positioned within 25 bp upstream of the Shine-Dalgarno (SD) motif of the silenced gene. We provide evidence that insulation is triggered by binding of the ribosome binding site (RBS) to the upstream CT-rich motif. We also show that, in E. coli, insulator sequences are preferentially encoded within σ54 promoters, suggesting an important regulatory role for these sequences in natural contexts. Our findings imply that sequence-specific regulatory effects that are sparsely encoded by short motifs may not be easily detected by lower throughput studies. Such sequence-specific phenomena can be uncovered with a focused oligo library (OL) design that mitigates sequence-related variance, as exemplified herein.