
Amit Meller
· Affiliate Faculty (Associate Professor – ENG/BME)VerifiedBoston University · Physics
Active 1958–2026
About
Amit Meller is an Affiliate Faculty (Associate Professor) in the Department of Physics at Boston University, with a focus on developing novel experimental techniques for studying biomolecular interactions and dynamics at the single molecule or single complex level. His research employs nanopore force spectroscopy to investigate RNA unfolding and re-folding kinetics, DNA switches, transcription initiation kinetics, RNA helicases activity, and the mapping of transcription factors interactions with DNA. Additionally, his work includes ultra-fast DNA sequencing and the development of innovative optical methods for single molecule detection in biomedical applications. Dr. Meller holds a Ph.D. in Physics and Biophysics from the Weizmann Institute of Science, along with an M.Sc. in Physics from the same institution and a B.Sc. in Physics and Astronomy from Tel Aviv University. His research aims to advance understanding of biomolecular processes through cutting-edge experimental techniques, contributing to the fields of biophysics and biomedical research.
Research topics
- Computer Science
- Biology
- Genetics
- Computational biology
- Nanotechnology
- Materials science
- Bioinformatics
- Molecular biology
Selected publications
Interrogating nanopores with light: optipore sensing for single molecule analyses
Journal of Nanobiotechnology · 2026-05-13
articleOpen accessSenior authorCorrespondingBACKGROUND: 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. Electrical nanopore measurements have already transformed the field, yet they can struggle to distinguish analytes with similar ionic current signatures or to provide robust quantification in complex samples. Combining electrical and optical readouts addresses these limitations. Electro-optical nanopores enable multimodal single-molecule measurements, delivering reliable quantification alongside richer qualitative information. MAIN BODY: This review focuses on synergetic integration of solid-state nanopores with advanced optical modalities, also referred to as optipore technology, as a unified framework that combines ionic current measurements with optical approaches such as fluorescence and scattering for synchronized, single-molecule analysis. Rather than treating electrical and optical methods independently, we emphasize their integration as a hybrid sensing paradigm that enables multidimensional characterization of molecular events. We examine key design considerations for nanopore membranes and microfluidic architectures, along with optical configurations ranging from confocal to wide-field microscopy, optimized to maximize photon-collection efficiency and enable high-throughput detection. Attention is given to strategies for background suppression, event validation, and molecular selectivity enabled by synchronized electro-optical readout. Recent developments in single-photon detectors and imaging technologies that improve sensitivity, throughput, and scalability are also highlighted. We analyze how these integrated platforms enable quantitative analysis of DNA, proteins, and protein-DNA complexes through chemo-selective labeling. CONCLUSION: Electro-optical nanopores provide a versatile framework for multimodal single-molecule analysis, offer enhanced selectivity, improved confidence in event identification, and access to richer molecular information than purely electrical methods. By summarizing current methodologies, technological advances, and emerging applications, this review outlines the opportunities and remaining challenges for optipore technologies and their potential impact on next-generation single-molecule biosensing and diagnostic platforms.
npj Biosensing · 2026-05-20
articleOpen accessSenior authorCorrespondingCell-free DNA (cfDNA) is a promising non-invasive biomarker for cancer detection; however, its clinical utility is often limited by its low abundance, short and heterogeneous fragment lengths. Here, we present a label and amplification-free strategy for cfDNA analysis and colorectal cancer (CRC) stage classification using an ultra-small (<3 nm) solid-state nanopore probed by high-bandwidth electronics. We analyzed cfDNA samples from healthy donors and CRC patients across multiple independent experimental runs to assess reproducibility. While conventional event-averaged descriptors captured broad group-level differences, they were insufficient for reliable cancer staging. In contrast, analysis of the high-temporal-resolution ionic current fluctuations revealed heterogeneous fragment populations and molecular features preserved in the native cfDNA. To decode these signatures, we developed a hybrid convolutional neural network (CNN)-transformer framework that directly processes raw current time series. This approach achieved ~95% accuracy in distinguishing healthy from CRC samples and enabled discrimination among cancer stages, significantly outperforming feature-averaged metrics and length-based baselines. Blind testing on previously unseen samples yielded consistent healthy vs. sick and stage-specific predictions, demonstrating robust generalization across patient cohorts. Together, these results establish high-bandwidth nanopore sensing coupled with time-resolved machine learning as a potential point of care framework for direct cfDNA profiling.
Single‐molecule electrical protein fingerprinting in solid‐state nanopores
Clinical and Translational Medicine · 2026-01-01
articleOpen accessSenior authorCorrespondingProteins play a central role in virtually all biological processes and serve as critical indicators of health and disease. Despite their importance, protein-based diagnostics remain far less developed than nucleic acid-based approaches. A major limitation is the insufficient sensitivity of current proteomic technologies, which typically require either enzymatic digestion of proteins into peptides or their immobilisation on surfaces for affinity-based detection.1 These strategies inherently discard information encoded in full-length proteins and rely heavily on the availability and performance of high-quality antibodies. Soni et al.2 report a fundamentally different approach for antibody-free, full-length protein fingerprinting based on solid-state nanopores. A nanopore is a nanometre-scale aperture in a thin insulating membrane that separates two electrolyte reservoirs. When a biopolymer translocates through the pore under an applied electric field, it transiently modulates the ionic current, producing a signal that reflects the molecule's physical and chemical properties.3 This principle underpins nanopore-based DNA sequencing, in which variations in ionic current are used to infer the nucleotide sequence of individual DNA molecules. The success of nanopore DNA sequencing is attributable to several intrinsic features of DNA: a uniformly charged backbone, the closely related chemical structures of its four nucleotides and the availability of enzymes that regulate DNA motion through the pore. Extending this framework to proteins, however, is substantially more challenging because of the immense diversity in protein size, charge distribution and three-dimensional structure. Additionally, unlike DNA, proteins cannot be amplified, imposing stringent requirements on the sensor's limit of detection (LoD). To overcome key barriers such as single-file translocation and limited temporal resolution,4 Soni et al.2 introduce a chemo-selective labelling strategy (Figure 1). Proteins are denatured and site-specifically conjugated at cysteine residues with short single-stranded DNA oligonucleotides (5- or 10-mers) using click chemistry. Remarkably, proteins labelled with a 5-mer oligonucleotide exhibit a distinctive stick–slip translocation mechanism, characterised by prolonged transient binding within the nanopore at the oligonucleotide–cysteine junction. This behaviour is absent in unconjugated proteins and results in an approximately 20-fold slowing of translocation dynamics. Molecular dynamics simulations corroborate the mechanistic origin of these interactions. This controlled slowdown enables the generation of time-resolved ionic current pulses, which serve as proxies for the positions of cysteine residues along the protein backbone. These pulse patterns constitute protein-specific fingerprints. Using only a few tens of translocation events, dynamic time-warping analysis produces consensus signal maps, successfully implemented across six distinct proteins. The clinical relevance of this approach is further demonstrated using two isoforms of vascular endothelial growth factor. Conventional nanopore metrics ‘blockade current’ and ‘dwell time’ show complete overlap between the isoforms, rendering discrimination infeasible. In contrast, the number and temporal arrangement of conductive pulses provide a robust feature for isoform-level differentiation, even when just a few copies of the proteins are sampled by the nanopore. Moreover, machine-learning-assisted classification enables accurate identification of target proteins even within complex mixtures. Beyond fingerprinting, oligonucleotide conjugation substantially enhances protein delivery to the nanopore due to the added negative charge. This is particularly significant for clinical samples, where many protein biomarkers are present at extremely low endogenous concentrations and, unlike nucleic acids, cannot be amplified. Soni et al.2 demonstrate a >10-fold increase in capture rate following oligo conjugation, which directly translate to an order of magnitude boost in the nanopore LoD. Emerging biological nanopore approaches for full-length protein analysis, whether enzyme-guided or enzyme-free, have achieved improved resolution, but often at the expense of delivery efficiency.5 By contrast, the present work attains high sensitivity while simultaneously improving the nanopore's LoD, all without relying on enzymatic motors. Together, these results establish a scalable, antibody-free nanopore platform capable of identifying full-length proteins at ultralow concentrations. This strategy marks a significant step toward clinically translatable proteomic diagnostics, providing a pathway to highly sensitive, label-minimal and information-rich protein detection directly from complex biological samples. This project has received funding from the European Research Council (ERC) number 833399 (NanoProt-ID) under the European Union's Horizon 2020 research and innovation programme grant agreements The authors declare no conflicts of interest.
Advanced Functional Materials · 2025-11-10 · 3 citations
articleOpen accessSenior authorCorrespondingAbstract Nanopore sensors detect individual molecules by monitoring ionic current as analytes translocate through nanometer‐scale pores. The resolution of molecular features depends on both the translocation speed and the dimensions of the pore. Here, a three‐layer solid‐state nanopore architecture engineered to optimize both parameters is presented. A 3 nm‐thick hafnium dioxide (HfO 2 ) layer is embedded between two supporting layers. Laser‐assisted drilling reliably forms 3–5 nm pores in aqueous solution within the HfO 2 layer, while simultaneously creating Gaussian‐shaped cavities that enhance molecular translocation dynamics. High‐resolution electron microscopy and cross‐sectional analysis confirm the structural integrity and uniformity of the layered architecture. Compared to conventional single‐layer silicon nitride (SiN x ) nanopores, the three‐layer pores slow DNA translocation by a factor of 12, enabling the detection of short 10 base pairs DNA. This enhanced spatial resolution also allows for label‐free detection of 21‐nucleotide microRNA (miRNA), with secondary current blockades revealing structural features. Protein detection is demonstrated by conjugating short oligonucleotides to cysteine residues, with secondary blockade signals corresponding to the number of cysteines within the protein. This robust nanopore platform combines the mechanical stability of a wide‐bandgap metal oxide with a chemically etchable support structure, offering a versatile and high‐resolution approach for single‐molecule biomolecular analysis.
Full-length protein classification via cysteine fingerprinting in solid-state nanopores
Nature Nanotechnology · 2025-09-24 · 9 citations
articleSenior authorCorrespondingThe Emergence of Nanofluidics for Single-Biomolecule Manipulation and Sensing
Analytical Chemistry · 2025-04-17 · 8 citations
reviewOpen accessSenior authorCorrespondingDriven 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.
ACS Nano · 2025-03-13 · 8 citations
articleOpen accessSenior authorCorrespondingMitochondrial 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.
Full‐Length Single Protein Molecules Tracking and Counting in Thin Silicon Channels
Advanced Materials · 2024-03-09 · 7 citations
articleOpen accessSenior authorCorrespondingEmerging 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 protein molecules separation, tracking and counting in ultra-thin silicon channels
bioRxiv (Cold Spring Harbor Laboratory) · 2023-11-13
preprintOpen accessSenior authorCorrespondingAbstract 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.
Nano Letters · 2023-05-07 · 19 citations
articleOpen accessSenior authorCorrespondingSolid-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.
Recent grants
NIH · $597k · 2009
NIH · $444k · 2016
DNA Bubble Formation and Kinetics Studies by Single-Molecule FRET
NSF · $91k · 2006–2008
Electronic Recognition of Gene Regulatory Proteins Bound to DNA
NSF · $585k · 2007–2012
NIH · $627k · 2007
Frequent coauthors
- 85 shared
W. MARINGGELE
- 37 shared
U. Klingebiel
- 28 shared
Mathias Noltemeyer
- 23 shared
Allison H. Squires
- 22 shared
George M. Sheldrick
University of Göttingen
- 22 shared
Regine Herbst‐Irmer
University of Göttingen
- 21 shared
Tal Gilboa
Harvard University
- 19 shared
Meni Wanunu
Northeastern University
Education
- 1998
Ph.D., Physics
Harvard University
- 1994
M.S., Physics
Harvard University
- 1992
B.S., Physics
Technion - Israel Institute of Technology
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