Biology subjects

Radenovic, A.

Publications and source records attributed to Radenovic, A..

17 recordsLinked to original sources

bioRxiv2026

A generalizable codesigned platform for solid-state nanopore sensing beyond the capacitive-noise constraints

Solid-state nanopores offer label-free, real-time single-molecule sensing, yet resolving rapidly translocating biomolecules requires high-bandwidth data acquisition, where increased high-frequency noise fundamentally limits reliable recovery of informative events. Here we establish a hardware-software co-designed nanopore sensing platform that overcomes this bandwidth-noise limitation by integrating scalable low-noise device engineering with deep learning-based signal reconstruction. A wafer-scale dielectric-engineering strategy using low-dielectric SU8 photoresist reduces total device capacitance to the picofarad regime and suppresses high-frequency noise by up to fivefold while maintaining facile, controllable and reproducible fabrication. This extends usable acquisition rate to 40 MHz and enables capture of fast molecular features. Combined with a reconstruction neural network trained on synthetic translocation signals embedded in experimentally measured noise, the platform recovers transient blockade sublevels while preserving temporal fidelity. Using engineered DNA molecules carrying dumbbell-like barcodes, we resolve nanometer-scale structural features on sub-microsecond timescales, and experimentally measure translocation velocity within the sub-5 nm regime. Dual-channel measurement on a single nanopore device further demonstrates transferability of the platform by showing robust cross-channel signal reconstruction across distinct baseline noise levels. This platform provides a general route for reliable recovery of previously inaccessible molecular information from high-bandwidth nanopore measurements.

biophysics↗

bioRxiv2026

Non-contact direct sensing of material properties of biomolecular condensate using Scanning Ionic Conductance Microscopy

Biomolecular condensates are important regulators of cellular compartmentalization and biochemical processes. Understanding their material properties is critical to elucidate how they control molecular organization and dynamics within cells. However, quantitatively probing these properties remains challenging due to the wide range of length scales, concentrations, and timescales over which condensates operate, as well as the limited force ranges accessible to current nanoscale mechanical mapping methods. We explored the use of a non-contact 3D imaging tool Scanning Ion Conductance Microscopy (SICM) for stiffness measurements of liquid-liquid phase-separated biomolecular condensates. We focus on the Dhh1 protein, which is a regulator of cytoplasmic processing bodies (PBs) membrane-less cytoplasmic condensates that control the storage and degradation of untranslated mRNA. In our study, we investigate the properties of mCherry2- or His-mCherry2-tagged full-length Dhh1 and N- or C-terminus tail-deletion constructs, as well as the catalytically inactive mutant DQAD, under different pH and incubation times. We mapped both spatial and temporal changes in the material properties of the condensates, highlighting the capabilities of the instrument. We found that the removal of either of the two tails led to an increase in condensate stiffness upon shifting the pH from a stress-associated cellular environment (pH 6.5) to physiological conditions (pH 7.5). Additionally, the choice of protein tags led to vastly different results depending on the pH where mCherry2-Dhh1 exhibited a stiffening going from pH 6.0 to 6.5 while the double-tagged His-mCherry2 did not. Our measurements are verified and corroborated by established techniques such as optical tweezer-based fusion assays and fluorescence recovery after photobleaching (FRAP). Furthermore, we were able to track the same biomolecular condensate sample for up to 20 days getting insights on the ageing and evolution of the condensates. Overall, our study demonstrates the applicability of SICM for direct measurement of the material properties of biomolecular condensate.

biophysics↗

bioRxiv2025

Spatial Polarization-Induced Fluorescence Fluctuation Imaging (SPIFFI) Enables Single-shot Super-Resolution and Multidimensional Imaging

Fluorescence super-resolution microscopy has advanced optical imaging into the nanoscale regime, transforming biological and interdisciplinary research. However, conventional wide-field super-resolution techniques often compromise temporal resolution, thereby limiting the ability to capture rapid and transient biological events in living systems. Here, we introduce spatial polarization-induced fluorescence fluctuation imaging (SPIFFI), a multi-channel polarimetric method that enables single-shot super-resolution imaging and six-dimensional information extraction. By leveraging the inherently smaller point spread function (PSF) under polarized detection and capturing polarization-dependent spatial fluctuations across multiplexed channels, SPIFFI achieves instant resolution enhancement from a single exposure. This capability substantially enhances the feasibility of volumetric live-cell super-resolution imaging. Moreover, SPIFFI images can be seamlessly integrated with existing fluctuation-based methods for further post-processing and resolution improvement. We demonstrate the versatility of SPIFFI through experiments on both fixed and live cells, capturing rapid subcellular dynamics and enabling high-throughput, multidimensional imaging beyond the diffraction limit. SPIFFI thus offers a practical and robust platform for real-time super-resolution imaging in biological research.

biophysics↗

bioRxiv2025

Deep-learning-assisted SICM for enhanced real-time imaging of nanoscale biological dynamics

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, we propose an integrated data acquisition and computational framework 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 under-sampled data, ensuring the retention of structural integrity. This approach significantly reduces the image acquisition time (i.e., by 30-60%) 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. We show 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. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=92 SRC="FIGDIR/small/663539v1_ufig1.gif" ALT="Figure 1"> View larger version (37K): org.highwire.dtl.DTLVardef@562d32org.highwire.dtl.DTLVardef@1b12dcaorg.highwire.dtl.DTLVardef@13535f3org.highwire.dtl.DTLVardef@6904f0_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioengineering↗

bioRxiv2025

Single-Photon Single-Particle Tracking

Mobile biological particles, ranging from biomolecules to viral capsids, often diffuse faster than 1 {micro}m2/s, resulting in severe motion blur in conventional millisecond-scale imaging. While shorter exposures may help provide the data needed to capture faster dynamics, quantization of signal intensity per pixel at such exposures eventually interferes with our ability to track. In the extreme case of binary (1-bit-per-pixel) output-- where going from 8-bit conventional grayscale imaging to 1-bit directly corresponds to a 255-fold faster acquisition rate--no existing tracking methods can be used, as these methods fundamentally rely on intensity-based localization, which does not leverage the binary output. For this reason, we introduce single-photon single-particle tracking (SP2T), a framework that bypasses localization and linking by estimating particle numbers and trajectories directly by jointly considering 1-bit image stacks. While cameras capable of microsecond-scale exposures, typically based on scientific CMOS (sCMOS) sensors or single-photon detectors (SPDs), are increasingly central to this effort, in this work, we focus on single-photon avalanche diode (SPAD). Single-photon detector (SPD) arrays offer microsecond exposures over large fields of view (512x512 pixels). SP2T accounts for detector-specific artifacts such as hot and cold pixels and is validated with programmed fluorescent bead trajectories and biological systems (aerolysin and ganglioside). These experiments, in addition to simulations, reveal that analysis performed with longer exposures can bias diffusion coefficient estimates (up to 70% for particles with diffusion coefficients of 5 {micro}m2/s) and distort jump-distance distributions, underscoring the need for photon-by-photon tracking in fast-diffusion regimes. Moreover, SP2T delivers substantial computational gains--achieving more than a 50-fold GPU speedup over CPU-based likelihood tracking methods that assume continuous intensity, when compared on datasets with the same frame size and number of frames. Together, these advances establish SP2T as a robust, data-efficient solution for unbiased particle tracking with millisecond-to-microsecond temporal resolution.

biophysics↗

bioRxiv2024

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

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 for the first time that mice colonised with defined 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 correlated 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.

animal behavior and cognition↗

bioRxiv2024

Lumen charge governs ion transport in β-barrel nanopores

{beta}-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 in its early stages. In this study, we integrate experimental, numerical, and theoretical approaches to elucidate ion transport mechanisms in these biological nanopores. We identify and characterise 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. Additionally, 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 the characterisation and understanding of biological ion transport processes, enabling the design of adaptable biosensors. We illustrate this by optimizing an aerolysin mutant for computing applications, paving the way for novel nanofluidic technologies.

biophysics↗

bioRxiv2024

Multiplexed lifetime imaging of single molecules with a gated single-photon camera

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 (512x512) 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 Forster 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.

biophysics↗

bioRxiv2023

Label-free imaging of DNA interactions with 2D materials

Two-dimensional (2D) materials offer potential as substrates for biosensing devices, as their properties can be engineered to tune interactions between the surface and biomolecules. Yet, not many methods can measure these interactions in a liquid environment without introducing labeling agents such as fluorophores. In this work, we harness interferometric scattering (iSCAT) microscopy, a label-free imaging technique, to investigate the interactions of single molecules of long dsDNA with 2D materials. The millisecond temporal resolution of iSCAT allows us to capture the transient interactions and to observe the dynamics of unlabeled DNA binding to a hexagonal boron nitride (hBN) surface in solution for extended periods (including a fraction of 10%, of trajectories lasting longer than 110 ms). Using a Focused Ion Beam (FIB) technique to engineer defects, we find that DNA binding affinity is enhanced at defects; when exposed to long lanes, DNA binds preferentially at lane edges. Overall, we demonstrate that iSCAT imaging is a useful tool to study how biomolecules interact with 2D materials, a key component in engineering future biosensors.

biophysics↗

bioRxiv2023

OpenSIM: open source microscope add-on for structured illumination microscopy

Super-resolution techniques expand the abilities of researchers who have the knowledge and resources to either build or purchase a system. This excludes the part of the research community without these capabilities. Here we introduce the openSIM add-on to upgrade existing optical microscopes to Structured Illumination super-resolution Microscopes (SIM). The openSIM is an open-hardware system, designed and documented to be easily duplicated by other laboratories, making super-resolution modality accessible to facilitate innovative research. The add-on approach gives a performance improvement for pre-existing lab equipment without the need to build a completely new system.

bioengineering↗

bioRxiv2023

Label-free Identification of Protein Aggregates Using Deep Learning

Protein misfolding and aggregation play central roles in the pathogenesis of various neurodegenerative diseases (NDDs), including Huntingtons disease, which is caused by a genetic mutation that leads to a polyglutamine repeat length > 35 in exon 1 of the Huntingtin protein (Httex1). Current research on protein aggregation often involves the use of fluorescent labels to visualize and monitor the dynamics of protein expression, which can alter the biophysical properties of proteins and the final ultrastructure, composition, and toxic properties of the formed aggregates. To overcome this limitation, we present a method for label-free identification of NDD-associated aggregates (LINA). Our approach utilizes deep learning to detect unlabeled and unaltered Httex1 aggregates in living cells from transmitted-light images, without the need for fluorescent labeling. We developed pixel-classification and pixel-regression models, which are robust across imaging conditions, and validated them on aggregates formed by different constructs of Httex1. Our results reveal that Httex1 proteins with shorter polyglutamine repeat lengths form aggregates with a higher average dry mass and area, highlighting the differences in their ultrastructure and aggregation mechanisms. LINA enables the dynamic identification of label-free aggregates and measurement of their dry mass and area changes during their growth process. Our highly-robust models offer high speed, specificity, and simplicity to analyze label-free protein aggregation dynamics and obtain high-fidelity information.

bioengineering↗

bioRxiv2022

Spatially Multiplexed Single-molecule Translocations through a Nanopore at Controlled Speeds

Nanopores are one of the most successful label-free single-molecule techniques with several sensing applications such as biological screening, diagnostics, DNA and protein sequencing1-4. In current nanopore technologies, stochastic processes influence both the selection of the translocating molecule, translocation rate and translocation velocity5,6. As a result, single-molecule translocations are difficult to control spatially and temporally. Here we present a novel method where we engineer precise spatial and temporal control into the single-molecule experiment. We use a glass nanopore mounted on a 3D nanopositioner to spatially select molecules, deterministically tethered on a glass surface, for controlled translocations. By controlling the distance between the nanopore and the glass surface, we can actively select the region of interest on the molecule and scan it a controlled number of times and at controlled velocity. Decreasing the velocity and averaging thousands of consecutive readings of the same molecule increases the signal-to-noise ratio (SNR) by two orders of magnitude compared to free translocations. We applied our method to various DNA constructs, achieving down to single nucleotide gap resolution. The spatial multiplexing combined with the sub-nanometer resolution could be used in conjunction with micro-array technologies to enable screening of DNA, improving point of care devices, or enabling high-density, addressable DNA data storage.

biophysics↗

bioRxiv2021

Time-resolved scanning ion conductance microscopy for three-dimensional tracking of nanoscale cell surface dynamics

Nanocharacterization plays a vital role in understanding the complex nanoscale organization of cells and organelles. Understanding cellular function requires high-resolution information about how the cellular structures evolve over time. A number of techniques exist to resolve static nanoscale structure of cells in great detail (super-resolution optical microscopy1, EM2, AFM3). However, time-resolved imaging techniques tend to either have lower resolution, are limited to small areas, or cause damage to the cells thereby preventing long-term time-lapse studies. Scanning probe microscopy methods such as atomic force microscopy (AFM) combine high-resolution imaging with the ability to image living cells in physiological conditions. The mechanical contact between the tip and the sample, however, deforms the cell surface, disturbs the native state, and prohibits long-term time-lapse imaging. Here, we develop a scanning ion conductance microscope (SICM) for high-speed and long-term nanoscale imaging. By utilizing recent advances in nanopositioning4, nanopore fabrication5, microelectronics6, and controls engineering7 we developed a microscopy method that can resolve spatiotemporally diverse three-dimenional processes on the cell membrane at sub-5nm axial resolution. We tracked dynamic changes in live cell morphology with nanometer details and temporal ranges of sub-second to days, imagining diverse processes ranging from endocytosis, micropinocytosis, and mitosis, to bacterial infection and cell differentiation in cancer cells. This technique enables a detailed look at membrane events and may offer insights into cell-cell interactions for infection, immunology, and cancer research.

biophysics↗

bioRxiv2020

Correlative 3D microscopy of single cells using super-resolution and scanning ion-conductance microscopy

High-resolution live-cell imaging is necessary to study complex biological phenomena. Modern fluorescence microscopy methods are increasingly combined with complementary, label-free techniques to put the fluorescence information into the cellular context. The most common high-resolution imaging approaches used in combination with fluorescence imaging are electron microscopy and atomic-force microscopy (AFM), originally developed for solid-state material characterization. AFM routinely resolves atomic steps, however on soft biological samples, the forces between the tip and the sample deform the fragile membrane, thereby distorting the otherwise high axial resolution of the technique. Here we present scanning ion-conductance microscopy (SICM) as an alternative approach for topographical imaging of soft biological samples, preserving high axial resolution on cells. SICM is complemented with live-cell compatible super-resolution optical fluctuation imaging (SOFI). To demonstrate the capabilities of our method we show correlative 3D cellular maps with SOFI implementation in both 2D and 3D with self-blinking dyes for two-color high-order SOFI imaging. Finally, we employ correlative SICM/SOFI microscopy for visualizing actin dynamics in live COS-7 cells with subdiffractional resolution.

biophysics↗

bioRxiv2020

Bioorthogonal red and far-red fluorogenic probes for wash-free live-cell and super-resolution microscopy

Small-molecule fluorophores enable the observation of biomolecules in their native context with fluorescence microscopy. Specific labelling via bioorthogonal tetrazine chemistry confers minimal label size and rapid labelling kinetics. At the same time, fluorogenic tetrazine-dye conjugates exhibit efficient quenching of dyes prior to target binding. However, live-cell compatible long-wavelength fluorophores with strong fluorogenicity have been difficult to realize. Here, we report close proximity tetrazine-dye conjugates with minimal distance between tetrazine and fluorophore. Two synthetic routes give access to a series of cell permeable and impermeable dyes including highly fluorogenic far-red emitting derivatives with electron exchange as dominant excited state quenching mechanism. We demonstrate their potential for live-cell imaging in combination with unnatural amino acids, wash-free multi-colour and super-resolution STED and SOFI imaging. These dyes pave the way for advanced fluorescence imaging of biomolecules with minimal label size.

cell biology↗

bioRxiv2019

High speed multi-plane super-resolution structured illumination microscopy of living cells using an image-splitting prism

Super-resolution structured illumination microscopy (SR-SIM) can be conducted at video-rate acquisition speeds when combined with high-speed spatial light modulators and sCMOS cameras, rendering it particularly suitable for live cell imaging. If, however, three-dimensional (3D) information is desired, the sequential acquisition of vertical image stacks employed by current setups significantly slows down the acquisition process. In this work we present a multi-plane approach to SR-SIM that overcomes this slowdown via the simultaneous acquisition of multiple object planes, employing a recently introduced multi-plane image splitting prism combined with high-speed SR-SIM illumination. This strategy requires only the introduction of a single optical element and the addition of a second camera to acquire a laterally super-resolved three-dimensional image stack. We demonstrate the performance of multi-plane SR-SIM by applying this instrument to the dynamics of live mitochondrial network.

biophysics↗

bioRxiv2019

Identifying microbial species by single-molecule DNA optical mapping and resampling statistics

Single molecule DNA mapping has the potential to serve as a powerful complement to high-throughput sequencing in metagenomic analysis. Offering longer read lengths and forgoing the need for complex library preparation and amplification, mapping stands to provide an unbiased view into the composition of complex viromes and/or microbiomes. To fully enable mapping-based metagenomics, sensitivity and specificity of DNA map analysis and identification need to be improved. Using detailed simulations and experimental data, we first demonstrate how fluorescence imaging of surface stretched, sequence specifically labeled DNA fragments can yield highly sensitive identification of targets. Secondly, a new analysis technique is introduced to increase specificity of the analysis, allowing even closely related species to be resolved. Thirdly, we show how an increase in resolution improves sensitivity. Finally, we demonstrate that these methods are capable of identifying species with long genomes such as bacteria with high sensitivity.

genomics↗