Label-free nanofluidic scattering microscopy of size and mass of single diffusing molecules and nanoparticles

Label-free detection and profiling of individual solution-phase molecules

Most chemistry and biology occurs in solution, in which conformational dynamics and complexation underlie behaviour and function. Single-molecule techniques1 are uniquely suited to resolving molecular diversity and new label-free approaches are reshaping the power of single-molecule measurements. A label-free single-molecule method2-16 capable of revealing details of molecular conformation in solution17,18 would allow a new microscopic perspective of unprecedented detail. Here we use the enhanced light-molecule interactions in high-finesse fibre-based Fabry-Pérot microcavities19-21 to detect individual biomolecules as small as 1.2 kDa, a ten-amino-acid peptide, with signal-to-noise ratios (SNRs) >100, even as the molecules are unlabelled and freely diffusing in solution. Our method delivers 2D intensity and temporal profiles, enabling the distinction of subpopulations in mixed samples. Notably, we observe a linear relationship between passage time and molecular radius, unlocking the potential to gather crucial information about diffusion and solution-phase conformation. Furthermore, mixtures of biomolecule isomers of the same molecular weight and composition but different conformation can also be resolved. Detection is based on the creation of a new molecular velocity filter window and a dynamic thermal priming mechanism that make use of the interplay between optical and thermal dynamics22,23 and Pound-Drever-Hall (PDH) cavity locking24 to reveal molecular motion even while suppressing environmental noise. New in vitro ways of revealing molecular conformation, diversity and dynamics can find broad potential for applications in the life and chemical sciences.

Deep-Learning Driven, High-Precision Plasmonic Scattering Interferometry for Single-Particle Identification

Label-free probing of the material composition of (bio)nano-objects directly in solution at the single-particle level is crucial in various fields, including colloid analysis and medical diagnostics. However, it remains challenging to decipher the constituents of heterogeneous mixtures of nano-objects with high sensitivity and resolution. Here, we present deep-learning plasmonic scattering interferometric microscopy, which is capable of identifying the composition of nanoparticles automatically with high throughput at the single-particle level. By employing deep learning to decode the quantitative relationship between the interferometric scattering patterns of nanoparticles and their intrinsic material properties, this technique is capable of high-throughput, label-free identification of diverse nanoparticle types. We demonstrate its versatility in analyzing dynamic surface chemical reactions on single nanoparticles, revealing its potential as a universal platform for nanoparticle imaging and reaction analysis. This technique not only streamlines the process of nanoparticle characterization, but also proposes a methodology for a deeper understanding of nanoscale dynamics, holding great potential for addressing extensive fundamental questions in nanoscience and nanotechnology.

Label-Free Single Nanoparticle Identification and Characterization in Demanding Environment, Including Infectious Emergent Virus

Unknown particle screening-including virus and nanoparticles-are keys in medicine, industry, and also in water pollutant determination. Here, RYtov MIcroscopy for Nanoparticles Identification (RYMINI) is introduced, a staining-free, non-invasive, and non-destructive optical approach that is merging holographic label-free 3D tracking with high-sensitivity quantitative phase imaging into a compact optical setup. Dedicated to the identification and then characterization of single nano-object in solution, it is compatible with highly demanding environments, such as level 3 biological laboratories, with high resilience to external source of mechanical and optical noise. Metrological characterization is performed at the level of each single particle on both absorbing and transparent particles as well as on immature and infectious HIV, SARS-CoV-2 and extracellular vesicles in solution. The capability of RYMINI to determine the nature, concentration, size, complex refractive index and mass of each single particle without knowledge or model of the particles' response is demonstrated. The system surpasses 90% accuracy for automatic identification between dielectric/metallic/biological nanoparticles and ≈80% for intraclass chemical determination of metallic and dielectric. It falls down to 50-70% for type determination inside the biological nanoparticle's class.

Extracellular Vesicles Slow Down Aβ(1-42) Aggregation by Interfering with the Amyloid Fibril Elongation Step

Formation of amyloid-β (Aβ) fibrils is a central pathogenic feature of Alzheimer's disease. Cell-secreted extracellular vesicles (EVs) have been suggested as disease modulators, although their exact roles and relations to Aβ pathology remain unclear. We combined kinetics assays and biophysical analyses to explore how small (<220 nm) EVs from neuronal and non-neuronal human cell lines affected the aggregation of the disease-associated Aβ variant Aβ(1-42) into amyloid fibrils. Using thioflavin-T monitored kinetics and seeding assays, we found that EVs reduced Aβ(1-42) aggregation by inhibiting fibril elongation. Morphological analyses revealed this to result in the formation of short fibril fragments with increased thicknesses and less apparent twists. We suggest that EVs may have protective roles by reducing Aβ(1-42) amyloid loads, but also note that the formation of small amyloid fragments could be problematic from a neurotoxicity perspective. EVs may therefore have double-edged roles in the regulation of Aβ pathology in Alzheimer's disease.

Label-Free Optical Imaging of Nanoscale Single Entities

The advancement of optical microscopy technologies has achieved imaging of nanoscale objects, including nanomaterials, virions, organelles, and biological molecules, at the single entity level. Recently developed plasmonic and scattering based optical microscopy technologies have enabled label-free imaging of single entities with high spatial and temporal resolutions. These label-free methods eliminate the complexity of sample labeling and minimize the perturbation of the analyte native state. Additionally, these imaging-based methods can noninvasively probe the dynamics and functions of single entities with sufficient throughput for heterogeneity analysis. This perspective will review label-free single entity imaging technologies and discuss their principles, applications, and key challenges.

Label-Free Tracking of Proteins through Plasmon-Enhanced Interference

Single unmodified biomolecules in solution can be observed and characterized by interferometric imaging approaches; however, Rayleigh scattering limits this to larger proteins (typically >30 kDa). We observe real-time image tracking of unmodified proteins down to 14 kDa using interference imaging enhanced by surface plasmons launched at an aperture in a metal film. The larger proteins show slower diffusion, quantified by tracking. When the diffusing protein is finally trapped by the nanoaperture, we perform complementary power spectral density and noise amplitude analysis, which gives information about the protein. This approach allows for rapid protein characterization with minimal sample preparation and opens the door to characterizing protein interactions in real time.

Dual-Angle Interferometric Scattering Microscopy for Optical Multiparametric Particle Characterization

Traditional single-nanoparticle sizing using optical microscopy techniques assesses size via the diffusion constant, which requires suspended particles to be in a medium of known viscosity. However, these assumptions are typically not fulfilled in complex natural sample environments. Here, we introduce dual-angle interferometric scattering microscopy (DAISY), enabling optical quantification of both size and polarizability of individual nanoparticles (radius <170 nm) without requiring a priori information regarding the surrounding media or super-resolution imaging. DAISY achieves this by combining the information contained in concurrently measured forward and backward scattering images through twilight off-axis holography and interferometric scattering (iSCAT). Going beyond particle size and polarizability, single-particle morphology can be deduced from the fact that the hydrodynamic radius relates to the outer particle radius, while the scattering-based size estimate depends on the internal mass distribution of the particles. We demonstrate this by differentiating biomolecular fractal aggregates from spherical particles in fetal bovine serum at the single-particle level.

Surface-emitting lasers meet metasurfaces

The integration between vertical-cavity surface-emitting lasers and metasurfaces has been demonstrated to enable on-chip high-angle illumination for total internal reflection and dark-field microscopy. Such an ultracompact combined laser-beam shaper system provides a versatile illumination module for high-contrast imaging, thus leveraging biophotonics and lab-on-a-chip devices and facilitating life-science applications.

Roadmap on Label-Free Super-Resolution Imaging

Label-free super-resolution (LFSR) imaging relies on light-scattering processes in nanoscale objects without a need for fluorescent (FL) staining required in super-resolved FL microscopy. The objectives of this Roadmap are to present a comprehensive vision of the developments, the state-of-the-art in this field, and to discuss the resolution boundaries and hurdles which need to be overcome to break the classical diffraction limit of the LFSR imaging. The scope of this Roadmap spans from the advanced interference detection techniques, where the diffraction-limited lateral resolution is combined with unsurpassed axial and temporal resolution, to techniques with true lateral super-resolution capability which are based on understanding resolution as an information science problem, on using novel structured illumination, near-field scanning, and nonlinear optics approaches, and on designing superlenses based on nanoplasmonics, metamaterials, transformation optics, and microsphere-assisted approaches. To this end, this Roadmap brings under the same umbrella researchers from the physics and biomedical optics communities in which such studies have often been developing separately. The ultimate intent of this paper is to create a vision for the current and future developments of LFSR imaging based on its physical mechanisms and to create a great opening for the series of articles in this field.

Label-Free Imaging of Catalytic H2O2 Decomposition on Single Colloidal Pt Nanoparticles Using Nanofluidic Scattering Microscopy

Single-particle catalysis aims at determining factors that dictate the nanoparticle activity and selectivity. Existing methods often use fluorescent model reactions at low reactant concentrations, operate at low pressures, or rely on plasmonic enhancement effects. Hence, methods to measure single-nanoparticle activity under technically relevant conditions and without fluorescence or other enhancement mechanisms are still lacking. Here, we introduce nanofluidic scattering microscopy of catalytic reactions on single colloidal nanoparticles trapped inside nanofluidic channels to fill this gap. By detecting minuscule refractive index changes in a liquid flushed trough a nanochannel, we demonstrate that local H2O2 concentration changes in water can be accurately measured. Applying this principle, we analyze the H2O2 concentration profiles adjacent to single colloidal Pt nanoparticles during catalytic H2O2 decomposition into O2 and H2O and derive the particles' individual turnover frequencies from the growth rate of the O2 gas bubbles formed in their respective nanochannel during reaction.

An optical nanofibre-enabled on-chip single-nanoparticle sensor

Single-nanoparticle detection has received tremendous interest due to its significance in fundamental physics and biological applications. Here, we demonstrate an optical nanofibre-enabled microfluidic sensor for the detection and sizing of nanoparticles. Benefitting from the strong evanescent field outside the nanofibre, a nanoparticle close to the nanofibre can scatter a portion of the field energy to the environment, resulting in a decrease in the transmitted intensity of the nanofibre. On the other hand, the narrow and shallow microfluidic channel provides a femtoliter-scale detection region, making nanoparticles flow through the detection region one by one. By real-time monitoring of the transmitted intensity of the nanofibre, the detection of a single polystyrene (PS) nanoparticle as small as 100 nm in diameter and exosomes in solution is realised. Based on a statistical analysis, the mean scattering signal is related to the size of the nanoparticle. Experimentally, a mixture of nanoparticles of different diameters (200, 500, and 1000 nm) in solution is identified. To demonstrate its potential in biological applications, high-throughput counting of yeasts using a pair of microchannels and dual-wavelength detection of fluorescently labelled nanoparticles are realised. We believe that the developed nanoparticle sensor holds great potential for the multiplexed and rapid sensing of diverse viruses.

High-angle deflection of metagrating-integrated laser emission for high-contrast microscopy

Flat metaoptics components are looking to replace classical optics elements and could lead to extremely compact biophotonics devices if integrated with on-chip light sources and detectors. However, using metasurfaces to shape light into wide angular range wavefronts with high efficiency, as is typically required in high-contrast microscopy applications, remains a challenge. Here we demonstrate curved GaAs metagratings integrated on vertical-cavity surface-emitting lasers (VCSELs) that enable on-chip illumination in total internal reflection and dark field microscopy. Based on an unconventional design that circumvents the aspect ratio dependent etching problems in monolithic integration, we demonstrate off-axis emission centred at 60° in air and 63° in glass with > 90% and > 70% relative deflection efficiency, respectively. The resulting laser beam is collimated out-of-plane but maintains Gaussian divergence in-plane, resulting in a long and narrow illumination area. We show that metagrating-integrated VCSELs of different kinds can be combined to enable rapid switching between dark-field and total internal reflection illumination. Our approach provides a versatile illumination solution for high-contrast imaging that is compatible with conventional microscopy setups and can be integrated with biophotonics devices, such as portable microscopy, NIR-II range bioimaging, and lab-on-a-chip devices.

Label-free optical biosensing: going beyond the limits

Label-free optical biosensing holds great promise for a variety of applications in biomedical diagnostics, environmental and food safety, and security. It is already used as a key tool in the investigation of biomolecular binding events and reaction constants in real time and offers further potential additional functionalities and low-cost designs. However, the sensitivity of this technology does not match the routinely used but expensive and slow labelling methods. Therefore, label-free optical biosensing remains predominantly a research tool. Here we discuss how one can go beyond the limits of detection provided by standard optical biosensing platforms and achieve a sensitivity of label-free biosensing that is superior to labelling methods. To this end we review newly emerging optical implementations that overcome current sensitivity barriers by employing novel structural architectures, artificial materials (metamaterials and hetero-metastructures) and using phase of light as a sensing parameter. Furthermore, we elucidate the mechanism of plasmonic phase biosensing and review hyper-sensitive transducers, which can achieve detection limits at the single molecule level (less than 1 fg mm-2) and make it possible to detect analytes at several orders of magnitude lower concentrations than so far reported in literature. We finally discuss newly emerging layouts based on dielectric nanomaterials, bound states in continuum, and exceptional points.

A Quantitative Description for Optical Mass Measurement of Single Biomolecules

Label-free detection of single biomolecules in solution has been achieved using a variety of experimental approaches over the past decade. Yet, our understanding of the magnitude of the optical contrast and its relationship with the underlying atomic structure as well as the achievable measurement sensitivity and precision remain poorly defined. Here, we use a Fourier optics approach combined with an atomic structure-based molecular polarizability model to simulate mass photometry experiments from first principles. We find excellent agreement between several key experimentally determined parameters such as optical contrast-to-mass conversion, achievable mass accuracy, and molecular shape and orientation dependence. This allows us to determine detection sensitivity and measurement precision mostly independent of the optical detection approach chosen, resulting in a general framework for light-based single-molecule detection and quantification.

Plasmonic Scattering Microscopy for Label-Free Imaging of Molecular Binding Kinetics: From Single Molecules to Single Cells

Measuring molecular binding kinetics represents one of the most important tasks in molecular interaction analysis. Surface plasmon resonance (SPR) is a popular tool for analyzing molecular binding. Plasmonic scattering microscopy (PSM) is a newly developed SPR imaging technology, which detects the out-of-plane scattering of surface plasmons by analytes and has pushed the detection limit of label-free SPR imaging down to a single-protein level. In addition, PSM also allows SPR imaging with high spatiotemporal resolution, making it possible to analyze cellular response to the molecular bindings. In this Mini Review, we present PSM as a method of choice for chemical and biological imaging, introduce its theoretical mechanism, present its experimental schemes, summarize its exciting applications, and discuss its challenges as well as the promising future.

Engineering Extracellular Vesicles as Delivery Systems in Therapeutic Applications

Extracellular vesicles (EVs) are transport vesicles secreted by living cells and released into the extracellular environment. Recent studies have shown that EVs serve as "messengers" in intercellular and inter-organismal communication, in both normal and pathological processes. EVs, as natural nanocarriers, can deliver bioactivators in therapy with their endogenous transport properties. This review article describes the engineering EVs of sources, isolation method, cargo loading, boosting approach, and adjustable targeting of EVs. Furthermore, the review summarizes the recent progress made in EV-based delivery systems applications, including cancer, cardiovascular diseases, liver, kidney, nervous system diseases, and COVID-19 and emphasizes the obstacles and challenges of EV-based therapies and possible strategies.

Self-supervised machine learning pushes the sensitivity limit in label-free detection of single proteins below 10 kDa

Interferometric scattering (iSCAT) microscopy is a label-free optical method capable of detecting single proteins, localizing their binding positions with nanometer precision, and measuring their mass. In the ideal case, iSCAT is limited by shot noise such that collection of more photons should extend its detection sensitivity to biomolecules of arbitrarily low mass. However, a number of technical noise sources combined with speckle-like background fluctuations have restricted the detection limit in iSCAT. Here, we show that an unsupervised machine learning isolation forest algorithm for anomaly detection pushes the mass sensitivity limit by a factor of 4 to below 10 kDa. We implement this scheme both with a user-defined feature matrix and a self-supervised FastDVDNet and validate our results with correlative fluorescence images recorded in total internal reflection mode. Our work opens the door to optical investigations of small traces of biomolecules and disease markers such as α-synuclein, chemokines and cytokines.

Rapid Identification and Monitoring of Multiple Bacterial Infections Using Printed Nanoarrays

Fast and accurate detection of microbial cells in clinical samples is highly valuable but remains a challenge. Here, a simple, culture-free diagnostic system is developed for direct detection of pathogenic bacteria in water, urine, and serum samples using an optical colorimetric biosensor. It consists of printed nanoarrays chemically conjugated with specific antibodies that exhibits distinct color changes after capturing target pathogens. By utilizing the internal capillarity inside an evaporating droplet, target preconcentration is achieved within a few minutes to enable rapid identification and more efficient detection of bacterial pathogens. More importantly, the scattering signals of bacteria are significantly amplified by the nanoarrays due to strong near-field localization, which supports a visualizable analysis of the growth, reproduction, and cell activity of bacteria at the single-cell level. Finally, in addition to high selectivity, this nanoarray-based biosensor is also capable of accurate quantification and continuous monitoring of bacterial load on food over a broad linear range, with a detection limit of 10 CFU mL^-1 . This work provides an accessible and user-friendly tool for point-of-care testing of pathogens in many clinical and environmental applications, and possibly enables a breakthrough in early prevention and treatment.

Ultraviolet Nanophotonics Enables Autofluorescence Correlation Spectroscopy on Label-Free Proteins with a Single Tryptophan

Using the ultraviolet autofluorescence of tryptophan amino acids offers fascinating perspectives to study single proteins without the drawbacks of fluorescence labeling. However, the low autofluorescence signals have so far limited the UV detection to large proteins containing several tens of tryptophan residues. This limit is not compatible with the vast majority of proteins which contain only a few tryptophans. Here we push the sensitivity of label-free ultraviolet fluorescence correlation spectroscopy (UV-FCS) down to the single tryptophan level. Our results show how the combination of nanophotonic plasmonic antennas, antioxidants, and background reduction techniques can improve the signal-to-background ratio by over an order of magnitude and enable UV-FCS on thermonuclease proteins with a single tryptophan residue. This sensitivity breakthrough unlocks the applicability of UV-FCS technique to a broad library of label-free proteins.

Simultaneous Sizing and Refractive Index Analysis of Heterogeneous Nanoparticle Suspensions

Rapid and reliable characterization of heterogeneous nanoparticle suspensions is a key technology across the nanosciences. Although approaches exist for homogeneous samples, they are often unsuitable for polydisperse suspensions, as particles of different sizes and compositions can lead to indistinguishable signals at the detector. Here, we introduce holographic nanoparticle tracking analysis, holoNTA, as a straightforward methodology that decouples size and material refractive index contributions. HoloNTA is applicable to any heterogeneous nanoparticle sample and has the sensitivity to measure the intrinsic heterogeneity of the sample. Specifically, we combined high dynamic range k-space imaging with holographic 3D single-particle tracking. This strategy enables long-term tracking by extending the imaging volume and delivers precise and accurate estimates of both scattering amplitude and diffusion coefficient of individual nanoparticles, from which particle refractive index and hydrodynamic size are determined. We specifically demonstrate, by simulations and experiments, that irrespective of localization uncertainty and size, the sizing sensitivity is improved as our extended detection volume yields considerably longer particle trajectories than previously reported by comparable technologies. As validation, we measured both homogeneous and heterogeneous suspensions of nanoparticles in the 40-250 nm size range and further monitored protein corona formation, where we identified subtle differences between the nanoparticle-protein complexes derived from avidin, bovine serum albumin, and streptavidin. We foresee that our approach will find many applications of both fundamental and applied nature where routine quantification and sizing of nanoparticles are required.

Determining the Local Refractive Index of Single Particles by Optical Imaging Technique

The refractive index points to the interplay between light and objects, which is rarely studied down to micronano scale. Herein, we demonstrated a conventional bright-field imaging technique to determine the local refractive index of single particles combined with a series of refractive index standard solutions. This intrinsic optical property is independent with the particle size and surface roughness with a single chemical component. Furthermore, we accurately tuned refractive index of homemade core-shell nanoparticles by adjusting the ratio of core-to-shell geometry. This simple and effective strategy reveals extensive applications in exploring, designing and optimizing the physical and optical characterizations of composite photonic crystals with high precision. It also indicates potentials in the field of reflective displays, optical identification, and encryption.

Single planar photonic chip with tailored angular transmission for multiple-order analog spatial differentiator

Analog spatial differentiation is used to realize edge-based enhancement, which plays an important role in data compression, microscopy, and computer vision applications. Here, a planar chip made from dielectric multilayers is proposed to operate as both first- and second-order spatial differentiator without any need to change the structural parameters. Third- and fourth-order differentiations that have never been realized before, are also experimentally demonstrated with this chip. A theoretical analysis is proposed to explain the experimental results, which furtherly reveals that more differentiations can be achieved. Taking advantages of its differentiation capability, when this chip is incorporated into conventional imaging systems as a substrate, it enhances the edges of features in optical amplitude and phase images, thus expanding the functions of standard microscopes. This planar chip offers the advantages of a thin form factor and a multifunctional wave-based analogue computing ability, which will bring opportunities in optical imaging and computing.

Single-shot self-supervised object detection in microscopy

Object detection is a fundamental task in digital microscopy, where machine learning has made great strides in overcoming the limitations of classical approaches. The training of state-of-the-art machine-learning methods almost universally relies on vast amounts of labeled experimental data or the ability to numerically simulate realistic datasets. However, experimental data are often challenging to label and cannot be easily reproduced numerically. Here, we propose a deep-learning method, named LodeSTAR (Localization and detection from Symmetries, Translations And Rotations), that learns to detect microscopic objects with sub-pixel accuracy from a single unlabeled experimental image by exploiting the inherent roto-translational symmetries of this task. We demonstrate that LodeSTAR outperforms traditional methods in terms of accuracy, also when analyzing challenging experimental data containing densely packed cells or noisy backgrounds. Furthermore, by exploiting additional symmetries we show that LodeSTAR can measure other properties, e.g., vertical position and polarizability in holographic microscopy.