Amit Meller

Nanopore sensors are at the heart of a technological shift, driven by their ability to detect biologically and medically relevant molecules one at a time.

Recent advances in single-molecule technologies are transforming the field of protein analysis. Solid-state nanopores provide an effective method to linearize and thread full-length proteins in a single file. However, slowing their rapid translocation remains a challenge for accurate, time-resolved ion-current-based fingerprinting. In this work, we present a click-chemistry-based strategy for covalently attaching short oligonucleotides to cysteine residues on denatured proteins across a broad range of molecular weights. The negatively charged oligonucleotides increase the capture rate by a factor of ten compared with native proteins and induce a distinct ‘stick–slip’ motion that slows protein passage through the nanopore by more than 20-fold. These oligonucleotide tags also produce characteristic, time-resolved ion current pulses that serve as unique protein-specific signatures. To uncover the physical mechanism responsible for the protein translocation dynamics, we model our system using all-atom molecular dynamics and finite element simulations. By leveraging a supervised machine learning classifier, we demonstrate that a small number of translocation events is sufficient to identify individual proteins, achieving near-perfect classification accuracy. To demonstrate the robustness of the method, we successfully distinguish between VEGF-A isoforms (VEGF-165 and VEGF-121), which are relevant to cancer diagnostics, within a mixed protein sample. Our nanopore-based fingerprinting technique eliminates the need for affinity reagents, such as protein-specific antibodies, or motor proteins, offering a rapid, direct and cost-effective approach for single-molecule protein identification and classification.

Driven by recent advancements in nanofabrication techniques, single-molecule sensing and manipulations in nanofluidic devices are rapidly evolving. These sophisticated biosensors have already had significant impacts on basic research as well as on applications in molecular diagnostics. The nanoscale dimensions of these devices introduce new physical phenomena by confining the biomolecules in at least one dimension, creating effects such as biopolymer linearization, stretching, and separation by mass that are utilized to enhance the biomolecule sensing resolutions. At the same time, the suppressed diffusional motion allows for better single-molecule SNR (signal-to-noise ratio) sensing over time. In particular, nanofluidic devices based on nanochannels have been established as promising technologies for the linearization of ultralong genomic DNA molecules and for optical genome mapping, opening a window to directly observe and infer genome organization. More recently, nanochannels have shown promising capabilities for single-molecule protein sizing, separation, and identification. Consequently, this technology is attracting remarkable interest for applications in single-molecule proteomics. In this review, we discuss the recent advancements of nanochannel-based technologies, focusing on their applications for single-molecule sensing and the characterization of a wide range of biomolecules.

Mitochondrial DNA (mtDNA) quantification is crucial in understanding mitochondrial dysfunction, which is linked to a variety of diseases, including cancer and neurodegenerative disorders. Traditional methods often rely on amplification-based techniques, which can introduce bias and lack the precision needed for clinical diagnostics. Solid-state nanopores, an emerging biosensing platform, have the advantage of offering single-molecule and label-free approaches by enabling the direct counting of DNA molecules without amplification. The ion-current signatures obtained from each DNA molecule contain rich information on the molecules’ lengths and origin. In this study, we present an amplification-free method for mtDNA quantification using solid-state nanopores and machine learning. Intriguingly, we find that native (unamplified) mtDNA translocations harbor structurally distinctive features that can be exploited to specifically detect and quantify mtDNA copies over the background of genomic DNA fragments. By combining selective degradation of linear genomic DNA (gDNA) via exonuclease V with a support vector machine (SVM)-based model, we isolate and quantify mtDNA directly from biological samples. We validate our method using plasmids or isolated mtDNAs by spiking in predetermined quantities. We then quantify endogenous mtDNAs in a cancer cell line and in blood cells and compare our results with qPCR-based quantification of the mtDNA/nuclear DNA ratios. To elucidate the source of the ion-current signatures from the native mtDNA molecules, we perform synchronous electro-optical sensing of mtDNAs during passage through the nanopore after NHS ester reaction with fluorophore compounds. Our results show correlated electro-optical events, indicating that the mtDNA is complexed with packaging proteins. Our assay is robust, with a high classification accuracy and is capable of detecting mtDNA at picomolar levels, making it suitable for low-abundance samples. This technique requires minimal sample preparation and eliminates the need for amplification or purification steps. The developed approach has significant potential for point-of-care applications, offering a low-cost and scalable solution for accurate mtDNA quantification in clinical settings.

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.

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

Solid-state nanopores (ssNPs) are single-molecule sensors capable of label-free quantification of different biomolecules, which have become highly versatile with the introduction of different surface treatments. By modulating the surface charges of the ssNP, the electro-osmotic flow (EOF) can be controlled in turn affecting the in-pore hydrodynamic forces. Herein, we demonstrate that negative charge surfactant coating to ssNPs generates EOF that slows-down DNA translocation speed by >30-fold, without deterioration of the NP noise, hence significantly improving its performances. Consequently, surfactant-coated ssNPs can be used to reliably sense short DNA fragments at high voltage bias. To shed light on the EOF phenomena inside planar ssNPs, we introduce visualization of the electrically neutral fluorescent molecule's flow, hence decoupling the electrophoretic from EOF forces. Finite elements simulations are then used to show that EOF is likely responsible for in-pore drag and size-selective capture rate. This study broadens ssNPs use for multianalyte sensing in a single device.

Inspired by the biological processes of molecular recognition and transportation across membranes, nanopore techniques have evolved in recent decades as ultrasensitive analytical tools for individual molecules. In particular, nanopore-based single-molecule DNA/RNA sequencing has advanced genomic and transcriptomic research due to the portability, lower costs and long reads of these methods. Nanopore applications, however, extend far beyond nucleic acid sequencing. In this Review, we present an overview of the broad applications of nanopores in molecular sensing and sequencing, chemical catalysis and biophysical characterization. We highlight the prospects of applying nanopores for single-protein analysis and sequencing, single-molecule covalent chemistry, clinical sensing applications for single-molecule liquid biopsy, and the use of synthetic biomimetic nanopores as experimental models for natural systems. We suggest that nanopore technologies will continue to be explored to address a number of scientific challenges as control over pore design improves.

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.