Label-Free Super-Resolution Imaging Techniques

Advancing Platelet Research Through Live-Cell Imaging: Challenges, Techniques, and Insights

Platelet cells are essential to maintain haemostasis and play a critical role in thrombosis. They swiftly respond to vascular injury by adhering to damaged vessel surfaces, activating signalling pathways, and aggregating with each other to control bleeding. This dynamic process of platelet activation is intricately coordinated, spanning from membrane receptor maturation to intracellular interactions to whole-cell responses. Live-cell imaging has become an invaluable tool for dissecting these complexes. Despite its benefits, live imaging of platelets presents significant technical challenges. This review addresses these challenges, identifying key areas in need of further development and proposing possible solutions. We also focus on the dynamic processes of platelet adhesion, activation, and aggregation in haemostasis and thrombosis, applying imaging capacities from the microscale to the nanoscale. By exploring various live imaging techniques, we demonstrate how these approaches offer crucial insights into platelet biology and deepen our understanding of these three core events. In conclusion, this review provides an overview of the imaging methods currently available for studying platelet dynamics, guiding researchers in selecting suitable techniques for specific studies. By advancing our knowledge of platelet behaviour, these imaging methods contribute to research on haemostasis, thrombosis, and platelet-related diseases, ultimately aiming to improve clinical outcomes.

Surpassing the Diffraction Limit in Label-Free Optical Microscopy

Super-resolution optical microscopy has enhanced our ability to visualize biological structures on the nanoscale. Fluorescence-based techniques are today irreplaceable in exploring the structure and dynamics of biological matter with high specificity and resolution. However, the fluorescence labeling concept narrows the range of observed interactions and fundamentally limits the spatiotemporal resolution. In contrast, emerging label-free imaging methods are not inherently limited by speed and have the potential to capture the entirety of complex biological processes and dynamics. While pushing a complex unlabeled microscopy image beyond the diffraction limit to single-molecule resolution and capturing dynamic processes at biomolecular time scales is widely regarded as unachievable, recent experimental strides suggest that elements of this vision might be already in place. These techniques derive signals directly from the sample using inherent optical phenomena, such as elastic and inelastic scattering, thereby enabling the measurement of additional properties, such as molecular mass, orientation, or chemical composition. This perspective aims to identify the cornerstones of future label-free super-resolution imaging techniques, discuss their practical applications and theoretical challenges, and explore directions that promise to enhance our understanding of complex biological systems through innovative optical advancements. Drawing on both traditional and emerging techniques, label-free super-resolution microscopy is evolving to offer detailed and dynamic imaging of living cells, surpassing the capabilities of conventional methods for visualizing biological complexities without the use of labels.

Single-Molecule Spectroscopy and Super-Resolution Mapping of Physicochemical Parameters in Living Cells

By superlocalizing the positions of millions of single molecules over many camera frames, a class of super-resolution fluorescence microscopy methods known as single-molecule localization microscopy (SMLM) has revolutionized how we understand subcellular structures over the past decade. In this review, we highlight emerging studies that transcend the outstanding structural (shape) information offered by SMLM to extract and map physicochemical parameters in living mammalian cells at single-molecule and super-resolution levels. By encoding/decoding high-dimensional information-such as emission and excitation spectra, motion, polarization, fluorescence lifetime, and beyond-for every molecule, and mass accumulating these measurements for millions of molecules, such multidimensional and multifunctional super-resolution approaches open new windows into intracellular architectures and dynamics, as well as their underlying biophysical rules, far beyond the diffraction limit.

Bridging Smart Nanosystems with Clinically Relevant Models and Advanced Imaging for Precision Drug Delivery

Intracellular delivery of nano-drug-carriers (NDC) to specific cells, diseased regions, or solid tumors has entered the era of precision medicine that requires systematic knowledge of nano-biological interactions from multidisciplinary perspectives. To this end, this review first provides an overview of membrane-disruption methods such as electroporation, sonoporation, photoporation, microfluidic delivery, and microinjection with the merits of high-throughput and enhanced efficiency for in vitro NDC delivery. The impact of NDC characteristics including particle size, shape, charge, hydrophobicity, and elasticity on cellular uptake are elaborated and several types of NDC systems aiming for hierarchical targeting and delivery in vivo are reviewed. Emerging in vitro or ex vivo human/animal-derived pathophysiological models are further explored and highly recommended for use in NDC studies since they might mimic in vivo delivery features and fill the translational gaps from animals to humans. The exploration of modern microscopy techniques for precise nanoparticle (NP) tracking at the cellular, organ, and organismal levels informs the tailored development of NDCs for in vivo application and clinical translation. Overall, the review integrates the latest insights into smart nanosystem engineering, physiological models, imaging-based validation tools, all directed towards enhancing the precise and efficient intracellular delivery of NDCs.

NDUFS4 regulates cristae remodeling in diabetic kidney disease

The mitochondrial electron transport chain (ETC) is a highly adaptive process to meet metabolic demands of the cell, and its dysregulation has been associated with diverse clinical pathologies. However, the role and nature of impaired ETC in kidney diseases remains poorly understood. Here, we generate diabetic mice with podocyte-specific overexpression of Ndufs4, an accessory subunit of mitochondrial complex I, as a model investigate the role of ETC integrity in diabetic kidney disease (DKD). We find that conditional male mice with genetic overexpression of Ndufs4 exhibit significant improvements in cristae morphology, mitochondrial dynamics, and albuminuria. By coupling proximity labeling with super-resolution imaging, we also identify the role of cristae shaping protein STOML2 in linking NDUFS4 with improved cristae morphology. Together, we provide the evidence on the central role of NDUFS4 as a regulator of cristae remodeling and mitochondrial function in kidney podocytes. We propose that targeting NDUFS4 represents a promising approach to slow the progression of DKD.

Super resolution label-free dark-field microscopy by deep learning

Dark-field microscopy (DFM) is a powerful label-free and high-contrast imaging technique due to its ability to reveal features of transparent specimens with inhomogeneities. However, owing to the Abbe's diffraction limit, fine structures at sub-wavelength scale are difficult to resolve. In this work, we report a single image super resolution DFM scheme using a convolutional neural network (CNN). A U-net based CNN is trained with a dataset which is numerically simulated based on the forward physical model of the DFM. The forward physical model described by the parameters of the imaging setup connects the object ground truths and dark field images. With the trained network, we demonstrate super resolution dark field imaging of various test samples with twice resolution improvement. Our technique illustrates a promising deep learning approach to double the resolution of DFM without any hardware modification.

Deep Learning Approach for the Localization and Analysis of Surface Plasmon Scattering

Surface plasmon resonance microscopy (SPRM) combines the principles of traditional microscopy with the versatility of surface plasmons to develop label-free imaging methods. This paper describes a proof-of-principles approach based on deep learning that utilized the Y-Net convolutional neural network model to improve the detection and analysis methodology of SPRM. A machine-learning based image analysis technique was used to provide a method for the one-shot analysis of SPRM images to estimate scattering parameters such as the scatterer location. The method was assessed by applying the approach to SPRM images and reconstructing an image from the network output for comparison with the original image. The results showed that deep learning can localize scatterers and predict other variables of scattering objects with high accuracy in a noisy environment. The results also confirmed that with a larger field of view, deep learning can be used to improve traditional SPRM such that it localizes and produces scatterer characteristics in one shot, considerably increasing the detection capabilities of SPRM.

Ultrafast and Nanoscale Energy Transduction Mechanisms and Coupled Thermal Transport across Interfaces

The coupled interactions among the fundamental carriers of charge, heat, and electromagnetic fields at interfaces and boundaries give rise to energetic processes that enable a wide array of technologies. The energy transduction among these coupled carriers results in thermal dissipation at these surfaces, often quantified by the thermal boundary resistance, thus driving the functionalities of the modern nanotechnologies that are continuing to provide transformational benefits in computing, communication, health care, clean energy, power recycling, sensing, and manufacturing, to name a few. It is the purpose of this Review to summarize recent works that have been reported on ultrafast and nanoscale energy transduction and heat transfer mechanisms across interfaces when different thermal carriers couple near or across interfaces. We review coupled heat transfer mechanisms at interfaces of solids, liquids, gasses, and plasmas that drive the resulting interfacial heat transfer and temperature gradients due to energy and momentum coupling among various combinations of electrons, vibrons, photons, polaritons (plasmon polaritons and phonon polaritons), and molecules. These interfacial thermal transport processes with coupled energy carriers involve relatively recent research, and thus, several opportunities exist to further develop these nascent fields, which we comment on throughout the course of this Review.

NDUFS4 Regulates Cristae Remodeling in Diabetic Kidney Disease

The mitochondrial electron transport chain (ETC) is a highly adaptive process to meet metabolic demands of the cell, and its dysregulation has been associated with diverse clinical pathologies. However, the role and nature of impaired ETC in kidney diseases remains poorly understood. Here, we generated diabetic mice with podocyte-specific overexpression of Ndufs4, an accessory subunit of mitochondrial complex I, as a model to investigate the role of ETC integrity in diabetic kidney disease (DKD). We find that these conditional mice exhibit significant improvements in cristae morphology, mitochondrial dynamics, and albuminuria. By coupling proximity labeling with super-resolution imaging, we also identify the role of cristae shaping proteins in linking NDUFS4 with improved cristae morphology. Taken together, we discover the central role of NDUFS4 as a powerful regulator of cristae remodeling, respiratory supercomplexes assembly, and mitochondrial ultrastructure in vitro and in vivo. We propose that targeting NDUFS4 represents a promising approach to slow the progression of DKD.

Distinguishing Single-Metal Nanoparticles with Subdiffraction Spatial Resolution Using Variable-Polarization Fourier Transform Nonlinear Optical Microscopy

The development and use of interferometric variable-polarization Fourier transform nonlinear optical (vpFT-NLO) imaging to distinguish colloidal nanoparticles colocated within the optical diffraction limit is described. Using a collinear train of phase-stabilized pulse pairs with orthogonal electric field vectors, the polarization of nonlinear excitation fields are controllably modulated between linear, circular, and various elliptical states. Polarization modulation is achieved by precise control over the time delay separating the orthogonal pulse pairs to within hundreds of attoseconds. The resultant emission from gold nanorods is imaged to a 2D array detector and correlated to the excitation field polarization and plasmon resonance frequency by Fourier transformation. Gold nanorods with length-to-diameter aspect ratios of 2 support a longitudinal surface plasmon resonance at approximately 800 nm, which is resonant with the excitation fundamental carrier wavelength. Differences in the intrinsic linear and circular dichroism resulting from variation in their relative alignment with respect to the laboratory frame enable optical differentiation of nanorods separated within 50 nm, which is an approximate 5-fold improvement over the diffraction limit of the microscope. The experimental results are supported by analytical simulations. In addition to subdiffraction spatial resolution, the vpFT-NLO method intrinsically provides the polarization- and frequency-dependent resonance response of the nanoparticles-providing spectroscopic information content along with super-resolution imaging capabilities.

3D nanopolymerization and damage threshold dependence on laser wavelength and pulse duration

The dependence of the polymerization and optical damage thresholds in multi-photon polymerization (MPP) lithography was studied using a broadly-tunable laser system with group delay dispersion (GDD) control. The order of non-linearity and the light-matter interaction mechanisms were investigated using the resolution bridges method for non-photosensitized SZ2080TM and photosensitized SZ2080TM + IRG369 prepolymers. Energy deposition, voxel dimension growth, and the size of the dynamic fabrication window (DFW) were measured in the 700-1300 nm wavelength range at three different pulse durations measured at the sample - 100, 200 and 300 fs. Polymerization was observed at all wavelengths and pulse durations without significant differences in the achieved minimal spatial dimension ( < 300 nm). This was achieved despite the broad range of excitation wavelengths used which spanned two- and three-photon absorption bands, and the differences in the absorption spectra of the prepolymers. The lateral and longitudinal voxel growth dynamics revealed an abrupt change in the power dependence of polymerization and a significant variation of the DFW - from 1 at 1250 nm to 29 at 700 nm. This result can be interpreted as a consequence of a change in the instantaneous refractive index and a lowering of the polymerization but not the damage threshold. The optimization of energy delivery to the material by a wavelength-tunable laser source with pulse duration control was experimentally validated. These findings are uncovering the complexity of polymerization mechanisms and are useful in further development of MPP technology.

Stimulated Raman versus Inverse Raman: Investigating Depletion Mechanisms for Super-Resolution Raman Microscopy

Super-resolution fluorescence microscopy has been critical in elucidating the nanoscale structure of biological systems. However, fluorescent labels bring difficulties such as perturbative labeling steps and photobleaching. Thus, label-free super-resolution techniques are of great interest, like our group's 2016 stimulated Raman scattering (SRS) technique, stimulated Raman depletion microscopy (SRDM). Inspired by stimulated emission depletion microscopy, SRDM uses a toroidally shaped beam to deplete the signal formed on the edges of the focal spot, resulting in SRS signal being detected from only a subdiffraction limited region. In initial works, the cause of the depletion was not thoroughly characterized. Here, we conclusively demonstrate suppression mechanisms in SRDM, while also contrasting approaches to super-resolution Raman microscopy on the Stokes and anti-Stokes sides of the spectrum. By monitoring the depletion of both the SRS and inverse Raman scattering (IRS) signal at a range of depletion powers, we observed other four-wave coherent Raman pathways that correspond to the introduction of the femtosecond depletion beam. In addition, we showed the depletion of the IRS signal, paving the way for a super-resolution imaging technique based on IRS, inverse raman depletion microscopy (IRDM). Combined, SRDM and IRDM offer label-free super-resolution imaging over a large spectral range to accommodate a variety of different sample constraints.