Nanopore Trap for Label‐Free Fingerprinting of Surface‐modified Single Nanoparticles

N. Cai; T. Chen; Y. Teng; A. S. Naidu; A. Radenovic 

Label‐free characterization of nanoparticle surface functionalization at single‐particle resolution is essential for a wide range of applications. Solid‐state nanopore sensing provides a direct electrical readout that is intrinsically sensitive to the size, surface layer, and interfacial chemistry of single particles in liquid environments. The trapping‐based nanopore sensing regime further enables probing surface‐dependent particle‐pore interactions with extended observation time. Here, a solid‐state nanopore trap‐based fingerprinting method is presented to differentiate single nanoparticles with distinct surface modifications. The method combines a “trap‐release” measurement protocol with a multi‐metric analysis workflow that extracts blockade distributions, sub‐level statistics and frequency‐domain signatures from trapping events, and constructs a unique fingerprint for each particle species. Applied to silica cores (≈25–30 nm) functionalized with APTES, NHS‐PEG 4 ‐Biotin and Tween‐20, the approach generates distinct fingerprints that map to surface charge, coating conformation and configuration heterogeneity. Moreover, in situ detection of surface chemical transformation via specific streptavidin binding is demonstrated, with stoichiometry‐dependent progression of the fingerprints. This platform provides a complementary tool to optical, spectral and ensemble assays for characterizing engineered nanoparticle surfaces and tracking interfacial molecular interactions in solution with label‐free and single‐particle sensitivity.

Wide-field fluorescence lifetime imaging of single molecules with a gated single-photon camera

N. Ronceray; S. Bennani; M. F. Mitsioni; N. Siegel; M. J. Marcaida et al. 

Fluorescence lifetime imaging microscopy (FLIM) is a powerful tool to discriminate fluorescent molecules or probe their nanoscale environment. Traditionally, FLIM uses time-correlated single-photon counting (TCSPC), which is precise but intrinsically low-throughput due to its dependence on point detectors. Although time-gated cameras have demonstrated the potential for high-throughput FLIM in bright samples with dense labeling, their use in single-molecule microscopy has not been explored extensively. Here, we report fast and accurate single-molecule FLIM with a commercial time-gated single-photon camera. Our optimized acquisition scheme achieves single-molecule lifetime measurements with a precision only about three times less than TCSPC, while imaging with a large number of pixels (512 × 512) allowing for the spatial multiplexing of over 3000 molecules. With this approach, we demonstrate parallelized lifetime measurements of large numbers of labeled pore-forming proteins on supported lipid bilayers, and temporal single-molecule Förster resonance energy transfer measurements at 5-25 Hz. This method holds considerable promise for the advancement of multi-target single-molecule localization microscopy and biopolymer sequencing.

Lumen charge governs gated ion transport in β-barrel nanopores

S. F. Mayer; M. F. Mitsioni; P. Robin; L. van den Heuvel; N. Ronceray et al. 

β-Barrel nanopores are involved in crucial biological processes, from ATP export in mitochondria to bacterial resistance, and represent a promising platform for emerging sequencing technologies. However, in contrast to ion channels, the understanding of the fundamental principles governing ion transport through these nanopores remains largely unexplored. Here we integrate experimental, numerical and theoretical approaches to elucidate ion transport mechanisms in β-barrel nanopores. We identify and characterize two distinct nonlinear phenomena: open-pore rectification and gating. Through extensive mutation analysis of aerolysin nanopores, we demonstrate that open-pore rectification is caused by ionic accumulation driven by the distribution of lumen charges. In addition, we provide converging evidence suggesting that gating is controlled by electric fields dissociating counterions from lumen charges, promoting local structural deformations. Our findings establish a rigorous framework for characterizing and understanding ion transport processes in protein-based nanopores, enabling the design of adaptable nanofluidic biotechnologies. We illustrate this by optimizing an aerolysin mutant for computing applications.

Assessment of neurobehavioural traits under gnotobiotic conditions: an approach for multiple analyses in the same mouse

A. Rutsch; M. Iachizzi; J. Kirundi; J. B. Kantsjö; A. L. Planchette et al. 

The gut-microbiota-brain axis influences neuroinflammation, neural development and behaviour such as sociability, memory and anxiety. To study these traits in vivo, especially during development or disease, it is crucial to analyse them over time and with multiple analyses in the same animal. With a growing understanding of the role of specific bacteria in neurodegenerative disease and behaviour, the demand for gnotobiotic mouse models has increased. However, maintaining stable hygienic conditions during behavioural testing is challenging, as exposure to conventional environments can alter the hygienic status of mice and affect behaviour. We established protocols to perform behavioural tests assessing memory, anxiety, exploration, learning and recognition under axenic conditions using flexible film isolators. Our study compared the behaviour of germ-free mice with mice carrying a defined minimal or moderately diverse microbiota. The results showed no effect of the microbiota on short- and long-term memory or novel object recognition. However, we showed that mice colonised with defined moderately diverse commensal bacteria exhibited more anxiety-like behaviour than germ-free mice. In addition, we showed that microbiota complexity is important, as only mice colonised with moderately diverse microbiota exhibited anxiety-like behaviour, allowing us to disentangle the contribution of specific microbial species or community interactions to this phenotype. This phenotype associated with differences in hippocampal and serum metabolic profiles between colonised and germ-free mice. We propose a novel approach to study rodent behaviour at different physiological and pathological stages in their life without compromising hygiene, thus promoting the refinement and reduction of mice used in experiments.

Deep‐Learning‐Assisted SICM for Enhanced Real‐Time Imaging of Nanoscale Biological Dynamics

Z. Ayar; M. Penedo; B. Drake; J. Shi; S. M. Leitao et al. 

Scanning Ion Conductance Microscopy (SICM) provides high‐resolution, nanoscale imaging of living cells, but it is generally limited by a slow scan rate, making it challenging to capture dynamic processes in real time. To tackle this challenge, an integrated data acquisition and computational framework is proposed that improves the temporal resolution of SICM by selectively skipping certain scan lines. A partial convolutional neural network (Partial‐CNN) model is developed and trained on SICM images and their corresponding masks to reconstruct the complete images from the undersampled data, ensuring the retention of structural integrity. This approach significantly reduces the image acquisition time (i.e., by 30–63%) without compromising quality, as validated through multiple quantitative metrics. Compared to conventional deep learning methods, the Partial‐CNN demonstrates higher accuracy in reconstructing fine details and maintaining consistent height maps across skipped regions. It is shown that this method provides an increased temporal resolution and retains image fidelity, making it suitable for real‐time dynamic SICM imaging and improving the smart scanning microscopy applications in time‐resolved biological imaging.

Square Kilometre Array Science Data Challenge 3a: foreground removal for an EoR experiment

A. Bonaldi; P. Hartley; R. Braun; S. Purser; A. Acharya et al. 

We present and analyse the results of the Science data challenge 3a (SDC3a, https://sdc3.skao.int/challenges/foregrounds), an EoR foreground-removal exercise organised by the Square Kilometre Array Observatory (SKAO) on SKA simulated data. The challenge ran for 8 months, from March to October 2023. Participants were provided with realistic simulations of SKA-Low data between 106 MHz and 196 MHz, including foreground contamination from extragalactic and Galactic emission, instrumental and systematic effects. They were asked to deliver cylindrical power spectra of the EoR signal, cleaned from all corruptions, and the corresponding confidence levels. Here we describe the approaches taken by the 17 teams that completed the challenge, and we assess their performance using different metrics. The challenge results provide a positive outlook on the capabilities of current foreground-mitigation approaches to recover the faint EoR signal from SKA-Low observations. The median error committed in the EoR power spectrum recovery is below the true signal for seven teams, although in some cases there are some significant outliers. The smallest residual overall is $4.2_{-4.2}^{+20} \times 10^{-4}\, \rm {K}^2h^{-3}$cMpc3 across all considered scales and frequencies. The estimation of confidence levels provided by the teams is overall less accurate, with the true error being typically under-estimated, sometimes very significantly. The most accurate error bars account for 60 ± 20% of the true errors committed. The challenge results provide a means for all teams to understand and improve their performance. This challenge indicates that the comparison between independent pipelines could be a powerful tool to assess residual biases and improve error estimation.

Self-driving microscopy detects the onset of protein aggregation and enables intelligent Brillouin imaging

K. A. Ibrahim; C. Cathala; C. Bevilacqua; L. Feletti; R. Prevedel et al. 

The process of protein aggregation, central to neurodegenerative diseases like Huntington’s, is challenging to study due to its unpredictable nature and relatively rapid kinetics. Understanding its biomechanics is crucial for unraveling its role in disease progression and cellular toxicity. Brillouin microscopy offers unique advantages for studying biomechanical properties, yet is limited by slow imaging speed, complicating its use for rapid and dynamic processes like protein aggregation. To overcome these limitations, we developed a self-driving microscope that uses deep learning to predict the onset of aggregation from a single fluorescence image of soluble protein, achieving 91% accuracy. The system triggers optimized multimodal imaging when aggregation is imminent, enabling intelligent Brillouin microscopy of this dynamic biomechanical process. Furthermore, we demonstrate that by detecting mature aggregates in real time using brightfield images and a neural network, Brillouin microscopy can be used to study their biomechanical properties without the need for fluorescence labeling, minimizing phototoxicity and preserving sample health. This autonomous microscopy approach advances the study of aggregation kinetics and biomechanics in living cells, offering a powerful tool for investigating the role of protein misfolding and aggregation in neurodegeneration.

Sum-Frequency Scattering Spectroscopy Reveals the Charging Mechanism and Surface Structure of hBN Nanoflakes in Solution

B. Rehl; N. Ronceray; L. Zhang; A. Rađenović; S. Roke 

A molecular understanding of the interactions between two-dimensional (2D) layered materials and liquids is crucial for nanofluidics, catalysis, and solution-based 2D material processing. Among 2D materials, hexagonal boron nitride (hBN) has a number of outstanding properties, but its interactions with liquids remain poorly characterized. Here, we investigate the interfacial structure of few-layer hBN nanoflakes suspensions in ethanol and ethanol−water mixtures. Electrophoretic light scattering suggests that the nanoflakes are effectively positively charged in ethanol and negatively charged in an ethanol−water mixture. Vibrational sum-frequency scattering spectroscopy reveals the surface structural changes underlying this charge reversal. Signatures of charge transfer of opposite direction are detected on both the flake lattice and in the liquid. The different (partial) charge distributions in ethanol and water explain the apparent charge reversal.

Fast Tracking with SPADs from Binary 1-Bit Per Pixel Output: Single-Photon Single-Particle Tracking

L. W. Q. Xu; N. Ronceray; M. Mitsioni; A. Radenovic; S. Pressé 

Resolution in super-resolution microscopy – facts, artifacts, technological advancements and biological applications

K. Prakash; D. Baddeley; C. Eggeling; R. Fiolka; R. Heintzmann et al. 

Super-resolution microscopy (SRM) has undeniable potential for scientific discovery, yet still presents many challenges that hinder its widespread adoption, including technical trade-offs between resolution, speed and photodamage, as well as limitations in imaging live samples and larger, more complex biological structures. Furthermore, SRM often requires specialized expertise and complex instrumentation, which can deter biologists from fully embracing the technology. In this Perspective, a follow-up to our recent Q&A article, we aim to demystify these challenges by addressing common questions and misconceptions surrounding SRM. Experts offer practical insights into how biologists can maximize the benefits of SRM while navigating issues such as photobleaching, image artifacts and the limitations of existing techniques. We also highlight recent developments in SRM that continue to push the boundaries of resolution. Our goal is to equip researchers with the crucial knowledge they need to harness the full potential of SRM.

Bottom-up designing nanostructured oxide libraries under a lab-on-chip paradigm towards a low-cost highly-selective E-nose

M. A. Solomatin; F. S. Fedorov; D. A. Kirilenko; V. Trouillet; A. S. Varezhnikov et al. 

Background: The multisensor concept has been developed as a powerful alternative to well-known gas-analytical instrumentation for applications where a fast but accurate and reliable assessment of the environment is required. The concept follows a biology-inspired approach where the selectivity towards various gases/odors is attained via pattern recognition of multisensory signal vectors. Herein, we discuss how to design a selective multisensor library based on various metal oxide nanostructures like a lab-on-chip using a simple but efficient bottom-up growth of materials over the multi-electrode chip under robust dc electrochemical protocols. Results: In addition to a conventional growth of oxide layers over the metal electrodes, we show that the fine nanowall-like oxide structures appear as a quasi-matrixed percolation film over the SiO2 substrate surface in the inter-electrode gaps to constitute a chemiresistive film. We have tested two directions while applying the technique to grow Co, Ni, Mn, and Zn oxides to develop on-chip sensor arrays of, (i) monoxide type employing the oxide films with gradual change of growth time, and (ii) multi-oxide type based on the four oxides. The materials were thoroughly characterized by electron microscopy, X-ray diffraction, thermogravimetric analysis, and X-ray photoelectron spectroscopy/mapping to prove the composition and structure. Among tested oxides, ZnO readily appears not only at the electric potential-targeted chip zone but also in other areas to dope the films for yielding heterojunctions with other oxides that enhances a variability of functional properties in the on-chip sensor array. The gas-sensing performance of the chips has been tested versus various chemically akin alcohol vapors at the sub- and low ppm range of concentrations in a mixture with air. Significance: We show that the grown oxide nanostructures exhibit a high-sensitive chemiresistive signal which allows one to build a multisensor vector signal, selective to the kind of alcohols, even at sub-ppm concentrations. Moreover, the multi-oxide library yields options for a superior selectivity under LDA metrics than the gradient-grown mono-oxide one due to the versatility of materials while the low-cost growth protocols remain to be the same in both cases. The delivered method to produce multisensor arrays allows one producing low-cost but efficient electronic nose units for numerous applications.

Controlled Sensing of User-Defined Aptamer-Based Targets Using Scanning Ionic Conductance Spectroscopy

H. Miljkovic; L. Feletti; G. Pistoletti Blanchet; M. Penedo; Z. Ayar et al. 

Solid-state nanopores offer the possibility of detecting disease biomarkers in early diagnostic applications. Standard approaches harness fingerprinting, where protein targets are bound to DNA carriers and detected in free translocation with a solid-state nanopore. However, they suffer from several drawbacks, including uncontrolled fast translocations, which lead to low detection accuracy and a low signal-to-noise ratio (SNR). This has hampered their application in clinical settings. Here, we propose a nanopore-based system capable of sensing selected molecules of interest from biological fluids by harnessing programmable aptamer sequences attached to DNA carrier systems that are tethered to glass surfaces. This allows for spatial and velocity control over translocation in the x, y, and z directions and enables the repeated scanning of the same analyte. The scanning ion conductance spectroscopy (SICS) based approach distinguishes itself from standard nanopore-based approaches with its ability to repeatedly scan the same aptamer molecule target site more than 5 times. We designed a DNA carrier with multiple binding sites for different aptamers to increase the yield of the experiment. Our approach achieves a detection rate of up to 74%, significantly higher than the 14% achieved with standard solid-state nanopore measurements. The strong spatial control also allows for significantly increased densities of aptamer target sites along the same DNA carrier, thereby paving the way for multiplexed sensing. The system offers user-defined programmability with different aptamer sequences, potentially expanding the use of our system to sense other disease biomarkers.

Functionalized Solid-State Nanopore: Energy Harvesting and Ionic Circuitry

Intelligent and Self-Driving Microscopy of Protein Aggregation in Neurodegenerative Diseases

Monitoring Electrochemical Dynamics through Single-Molecule Imaging of hBN Surface Emitters in Organic Solvents

E. Mayner; N. Ronceray; M. Lihter; T-H. Chen; K. Watanabe et al. 

Electrochemical techniques conventionally lack spatial resolution and average local information over an entire electrode. While advancements in spatial resolution have been made through scanning probe methods, monitoring dynamics over large areas is still challenging, and it would be beneficial to be able to decouple the probe from the electrode itself. In this work, we leverage single molecule microscopy to spatiotemporally monitor analyte surface concentrations over a wide area using unmodified hexagonal boron nitride (hBN) in organic solvents. Through a sensing scheme based on redox-active species interactions with fluorescent emitters at the surface of hBN, we observe a region of a linear decrease in the number of emitters against increasingly positive potentials applied to a nearby electrode. We find consistent trends in electrode reaction kinetics vs overpotentials between potentiostat-reported currents and optically read emitter dynamics, showing Tafel slopes greater than 290 mV·decade-1. Finally, we draw on the capabilities of spectral single-molecule localization microscopy (SMLM) to monitor the fluorescent species’ identity, enabling multiplexed readout. Overall, we show dynamic measurements of analyte concentration gradients on a micrometer-length scale with nanometer-scale depth and precision. Considering the many scalable options for engineering fluorescent emitters with two-dimensional (2D) materials, our method holds promise for optically detecting a range of interacting species with exceptional localization precision.

Improvement of DERA activity and stability in the synthesis of statin precursors by immobilization on magnetic nanoparticles

D. Skendrović; A. Švarc; T. Rezić; A. Chernev; A. Radenovic et al. 

Higher stability and hyperactivation of the DERA enzyme were achieved by covalent bonding to magnetic nanoparticles with succinic anhydride as an activating agent.

CVD graphene contacts for lateral heterostructure MoS2 field effect transistors

D. S. Schneider; L. Lucchesi; E. Reato; Z. Wang; A. Piacentini et al. 

Intensive research has been carried out on two-dimensional materials, in particular molybdenum disulfide, towards high-performance field effect transistors for integrated circuits 1 . Fabricating transistors with ohmic contacts is a challenging task due to the formation of a high Schottky barrier that severely limits the performance of the transistors for real-world applications. Graphene-based heterostructures can be used in addition to, or as a substitute for unsuitable metals. In this paper, we present lateral heterostructure transistors made of scalable chemical vapor-deposited molybdenum disulfide and chemical vapor-deposited graphene achieving a low contact resistances of about 9 k Omegamu m and high on/off current ratios of 108. Furthermore, we also present a theoretical model calibrated on our experiments showing further potential for scaling transistors and contact areas into the few nanometers range and the possibility of a substantial performance enhancement by means of layer optimizations that would make transistors promising for use in future logic integrated circuits.

Resolution in super-resolution microscopy — definition, trade-offs and perspectives

Kirti Prakash; David Baddeley; Christian Eggeling; Reto Fiolka; Rainer Heintzmann et al. 

Super-resolution microscopy (SRM) is gaining popularity in biosciences; however, claims about optical resolution are contested and often misleading. In this Viewpoint, experts share their views on resolution and common trade-offs, such as labelling and post-processing, aiming to clarify them for biologists and facilitate deeper understanding and best use of SRM.

Fluorescence microscopy: A statistics-optics perspective

M. Fazel; K. S. Grussmayer; B. Ferdman; A. Radenovic; Y. Shechtman et al. 

Fundamental properties of light unavoidably impose features on images collected using fluorescence microscopes. Accounting for these features is often critical in quantitatively interpreting microscopy images, especially those gathering information at scales on par with or smaller than light’s emission wavelength. Here the optics responsible for generating fluorescent images, fluorophore properties, and microscopy modalities leveraging properties of both light and fluorophores, in addition to the necessarily probabilistic modeling tools imposed by the stochastic nature of light and measurement, are reviewed.

Label-Free Techniques for Probing Biomolecular Condensates

K. A. Ibrahim; A. S. Naidu; H. Miljkovic; A. Radenovic; W. Yang 

Biomolecular condensates play important roles in a wide array of fundamental biological processes, such as cellular compartmentalization, cellular regulation, and other biochemical reactions. Since their discovery and first observations, an extensive and expansive library of tools has been developed to investigate various aspects and properties, encompassing structural and compositional information, material properties, and their evolution throughout the life cycle from formation to eventual dissolution. This Review presents an overview of the expanded set of tools and methods that researchers use to probe the properties of biomolecular condensates across diverse scales of length, concentration, stiffness, and time. In particular, we review recent years’ exciting development of label-free techniques and methodologies. We broadly organize the set of tools into 3 categories: (1) imaging-based techniques, such as transmitted-light microscopy (TLM) and Brillouin microscopy (BM), (2) force spectroscopy techniques, such as atomic force microscopy (AFM) and the optical tweezer (OT), and (3) microfluidic platforms and emerging technologies. We point out the tools’ key opportunities, challenges, and future perspectives and analyze their correlative potential as well as compatibility with other techniques. Additionally, we review emerging techniques, namely, differential dynamic microscopy (DDM) and interferometric scattering microscopy (iSCAT), that have huge potential for future applications in studying biomolecular condensates. Finally, we highlight how some of these techniques can be translated for diagnostics and therapy purposes. We hope this Review serves as a useful guide for new researchers in this field and aids in advancing the development of new biophysical tools to study biomolecular condensates.