Single-molecule spectroscopy and imaging over the decades

Hexylation Stabilises Twisted Backbone Configurations in the Prototypical Low-Bandgap Copolymer PCDTBT

Conjugated donor-acceptor copolymers hold great potential as materials for high-performance organic photovoltaics, organic transistors and organic thermoelectric devices. Their low optical bandgap is achieved by alternation of donor and acceptor moieties along the polymer chain, leading to a pronounced charge-transfer character of electronic excitations. However, the influence of appended side chains and of chemical defects of the backbone on their photophysical and conformational properties remains largely unexplored on the level of individual chains. Here, we employ room temperature single-molecule photoluminescence spectroscopy on four compounds based on the prototypical copolymer PCDTBT with systematically changed chemical structure. Our results show that an increasing density of statistically added hexyl chains to the TBT comonomer distorts the molecular conformation, likely through the increase of average dihedral angles along the backbone. We find that, although the conformation becomes more twisted with high hexyl density, the side chains appear to stabilize the backbone in this twisted conformation. In addition, we demonstrate that homocoupling defects along the backbone barely influence the PL spectra of single chains, and thus intra-chain electronic properties.

A Brief Introduction to Single-Molecule Fluorescence Methods

One of the most popular single-molecule approaches in biological science is single-molecule fluorescence microscopy, which will be the subject of the following section of this volume. Fluorescence methods provide the sensitivity required to study biology on the single-molecule level, but they also allow access to useful measurable parameters on time and length scales relevant for the biomolecular world. Before several detailed experimental approaches will be addressed, we will first give a general overview of single-molecule fluorescence microscopy. We start with discussing the phenomenon of fluorescence in general and the history of single-molecule fluorescence microscopy. Next, we will review fluorescent probes in more detail and the equipment required to visualize them on the single-molecule level. We will end with a description of parameters measurable with such approaches, ranging from protein counting and tracking, single-molecule localization super-resolution microscopy, to distance measurements with Förster resonance energy transfer and orientation measurements with fluorescence polarization.

Plasmonic Probing of Deoxyribonucleic Acid Hybridization at the Single Base Pair Resolution

Partial DNA duplex formation greatly impacts the quality of DNA hybridization and has been extensively studied due to its significance in many biological processes. However, traditional DNA sensing methods suffer from time-consuming amplification steps and hinder the acquisition of information about single-molecule behavior. In this work, we developed a plasmonic method to probe the hybridization process at a single base pair resolution and study the relationship between the complementarity of DNA analytes and DNA hybridization behaviors. We measured single-molecule hybridization events with Au NP-modified ssDNA probes in real time and found two hybridization adsorption events: stable and transient adsorption. The ratio of these two hybridization adsorption events was correlated with the length of the complementary sequences, distinguishing DNA analytes from different complementary sequences. By using dual incident angle excitation, we recognized different single-base complementary sequences. These results demonstrated that the plasmonic method can be applied to study partial DNA hybridization behavior and has the potential to be incorporated into the identification of similar DNA sequences, providing a sensitive and quantitative tool for DNA analysis.

Deep learning-driven adaptive optics for single-molecule localization microscopy

The inhomogeneous refractive indices of biological tissues blur and distort single-molecule emission patterns generating image artifacts and decreasing the achievable resolution of single-molecule localization microscopy (SMLM). Conventional sensorless adaptive optics methods rely on iterative mirror changes and image-quality metrics. However, these metrics result in inconsistent metric responses and thus fundamentally limit their efficacy for aberration correction in tissues. To bypass iterative trial-then-evaluate processes, we developed deep learning-driven adaptive optics for SMLM to allow direct inference of wavefront distortion and near real-time compensation. Our trained deep neural network monitors the individual emission patterns from single-molecule experiments, infers their shared wavefront distortion, feeds the estimates through a dynamic filter and drives a deformable mirror to compensate sample-induced aberrations. We demonstrated that our method simultaneously estimates and compensates 28 wavefront deformation shapes and improves the resolution and fidelity of three-dimensional SMLM through >130-µm-thick brain tissue specimens.

Fluorescence Microscopy: a statistics-optics perspective

Fundamental properties of light unavoidably impose features on images collected using fluorescence microscopes. Modeling these features is ever more important in quantitatively interpreting microscopy images collected at scales on par or smaller than light's wavelength. Here we review the optics responsible for generating fluorescent images, fluorophore properties, 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.

Strategies for Overcoming the Single-Molecule Concentration Barrier

Fluorescence-based single-molecule approaches have helped revolutionize our understanding of chemical and biological mechanisms. Unfortunately, these methods are only suitable at low concentrations of fluorescent molecules so that single fluorescent species of interest can be successfully resolved beyond background signal. The application of these techniques has therefore been limited to high-affinity interactions despite most biological and chemical processes occurring at much higher reactant concentrations. Fortunately, recent methodological advances have demonstrated that this concentration barrier can indeed be broken, with techniques reaching concentrations as high as 1 mM. The goal of this Review is to discuss the challenges in performing single-molecule fluorescence techniques at high-concentration, offer applications in both biology and chemistry, and highlight the major milestones that shatter the concentration barrier. We also hope to inspire the widespread use of these techniques so we can begin exploring the new physical phenomena lying beyond this barrier.

Active-Feedback 3D Single-Molecule Tracking Using a Fast-Responding Galvo Scanning Mirror

Real-time three-dimensional single-particle tracking (RT-3D-SPT) allows continuous detection of individual freely diffusing objects with high spatiotemporal precision by applying closed-loop active feedback in an optical microscope. However, the current tracking speed in RT-3D-SPT is primarily limited by the response time of the control actuators, impeding long-term observation of fast diffusive objects such as single molecules. Here, we present an RT-3D-SPT system with improved tracking performance by replacing the XY piezoelectric stage with a galvo scanning mirror with an approximately 5 times faster response rate (∼5 kHz). Based on the previously developed 3D single-molecule active real-time tracking (3D-SMART), this new implementation with a fast-responding galvo mirror eliminates the mechanical movement of the sample and allows a more rapid response to particle motion. The improved tracking performance of the galvo mirror-based implementation is verified through simulation and proof-of-principle experiments. Fluorescent nanoparticles and ∼1 kB double-stranded DNA molecules were tracked via both the original piezoelectric stage and new galvo mirror implementations. With the new galvo-based implementation, notable increases in tracking duration, localization precision, and the degree to which the objects are locked to the center of the detection volume were observed. These results suggest that faster control response elements can expand RT-3D-SPT to a broader range of chemical and biological systems.

Recent Advances in Single-Molecule Tracking and Imaging Techniques

Since the early 1990s, single-molecule detection in solution at room temperature has enabled direct observation of single biomolecules at work in real time and under physiological conditions, providing insights into complex biological systems that the traditional ensemble methods cannot offer. In particular, recent advances in single-molecule tracking techniques allow researchers to follow individual biomolecules in their native environments for a timescale of seconds to minutes, revealing not only the distinct pathways these biomolecules take for downstream signaling but also their roles in supporting life. In this review, we discuss various single-molecule tracking and imaging techniques developed to date, with an emphasis on advanced three-dimensional (3D) tracking systems that not only achieve ultrahigh spatiotemporal resolution but also provide sufficient working depths suitable for tracking single molecules in 3D tissue models. We then summarize the observables that can be extracted from the trajectory data. Methods to perform single-molecule clustering analysis and future directions are also discussed.

Spectroelectrochemical behavior of parallel arrays of single vertically oriented Pseudomonas aeruginosa cells

Pseudomonas aeruginosa is a Gram-negative opportunistic human pathogen responsible for a number of healthcare-associated infection. It is currently difficult to assess single cell behaviors of P. aeruginosa that might contribute to acquisition of antibiotic resistance, intercellular communication, biofilm development, or virulence, because mechanistic behavior is inferred from ensemble collections of cells, thus averaging effects over a population. Here, we develop and characterize a device that can capture and trap arrays of single P. aeruginosa cells in individual micropores in order to study their behaviors using spectroelectrochemistry. Focused ion beam milling is used to fabricate an array of micropores in a Au/dielectric/Au/SiO₂-containing multilayer substrate, in which individual micropores are formed with dimensions that facilitate the capture of single P. aeruginosa cells in a predominantly vertical orientation. The bottom Au ring is then used as a working electrode to explore the spectroelectrochemical behavior of parallel arrays of individual P. aeruginosa cells. Application of step-potential or swept-potential waveforms produces changes in the fluorescence emission that can be imaged and correlated with applied potential. Arrays of P. aeruginosa cells typically exhibit three characteristic fluorescence behaviors that are sensitive to nutritional stress and applied potential. The device developed here enables the study of parallel collections of single bacterial cells with well-defined orientational order and should facilitate efforts to elucidate methods of bacterial communication and multidrug resistance at the single cell level.

Neuro-nanotechnology: diagnostic and therapeutic nano-based strategies in applied neuroscience

Artificial, de-novo manufactured materials (with controlled nano-sized characteristics) have been progressively used by neuroscientists during the last several decades. The introduction of novel implantable bioelectronics interfaces that are better suited to their biological targets is one example of an innovation that has emerged as a result of advanced nanostructures and implantable bioelectronics interfaces, which has increased the potential of prostheses and neural interfaces. The unique physical-chemical properties of nanoparticles have also facilitated the development of novel imaging instruments for advanced laboratory systems, as well as intelligently manufactured scaffolds and microelectrodes and other technologies designed to increase our understanding of neural tissue processes. The incorporation of nanotechnology into physiology and cell biology enables the tailoring of molecular interactions. This involves unique interactions with neurons and glial cells in neuroscience. Technology solutions intended to effectively interact with neuronal cells, improved molecular-based diagnostic techniques, biomaterials and hybridized compounds utilized for neural regeneration, neuroprotection, and targeted delivery of medicines as well as small chemicals across the blood-brain barrier are all purposes of the present article.

Fluorescence microscopy imaging of a neurotransmitter receptor and its cell membrane lipid milieu

Hampered by the diffraction phenomenon, as expressed in 1873 by Abbe, applications of optical microscopy to image biological structures were for a long time limited to resolutions above the ∼200 nm barrier and restricted to the observation of stained specimens. The introduction of fluorescence was a game changer, and since its inception it became the gold standard technique in biological microscopy. The plasma membrane is a tenuous envelope of 4 nm-10 nm in thickness surrounding the cell. Because of its highly versatile spectroscopic properties and availability of suitable instrumentation, fluorescence techniques epitomize the current approach to study this delicate structure and its molecular constituents. The wide spectral range covered by fluorescence, intimately linked to the availability of appropriate intrinsic and extrinsic probes, provides the ability to dissect membrane constituents at the molecular scale in the spatial domain. In addition, the time resolution capabilities of fluorescence methods provide complementary high precision for studying the behavior of membrane molecules in the time domain. This review illustrates the value of various fluorescence techniques to extract information on the topography and motion of plasma membrane receptors. To this end I resort to a paradigmatic membrane-bound neurotransmitter receptor, the nicotinic acetylcholine receptor (nAChR). The structural and dynamic picture emerging from studies of this prototypic pentameric ligand-gated ion channel can be extrapolated not only to other members of this superfamily of ion channels but to other membrane-bound proteins. I also briefly discuss the various emerging techniques in the field of biomembrane labeling with new organic chemistry strategies oriented to applications in fluorescence nanoscopy, the form of fluorescence microscopy that is expanding the depth and scope of interrogation of membrane-associated phenomena.

Infrared nanospectroscopic imaging of DNA molecules on mica surface

Significant efforts have been done in last two decades to develop nanoscale spectroscopy techniques owning to their great potential for single-molecule structural detection and in addition, to resolve open questions in heterogeneous biological systems, such as protein-DNA complexes. Applying IR-AFM technique has become a powerful leverage for obtaining simultaneous absorption spectra with a nanoscale spatial resolution for studied proteins, however the AFM-IR investigation of DNA molecules on surface, as a benchmark for a nucleoprotein complexes nanocharacterization, has remained elusive. Herein, we demonstrate methodological approach for acquisition of AFM-IR mapping modalities with corresponding absorption spectra based on two different DNA deposition protocols on spermidine and Ni²⁺ pretreated mica surface. The nanoscale IR absorbance of distinctly formed DNA morphologies on mica are demonstrated through series of AFM-IR absorption maps with corresponding IR spectrum. Our results thus demonstrate the sensitivity of AFM-IR nanospectroscopy for a nucleic acid research with an open potential to be employed in further investigation of nucleoprotein complexes.

Plasmonic phenomena in molecular junctions: principles and applications

Molecular junctions are building blocks for constructing future nanoelectronic devices that enable the investigation of a broad range of electronic transport properties within nanoscale regions. Crossing both the nanoscopic and mesoscopic length scales, plasmonics lies at the intersection of the macroscopic photonics and nanoelectronics, owing to their capability of confining light to dimensions far below the diffraction limit. Research activities on plasmonic phenomena in molecular electronics started around 2010, and feedback between plasmons and molecular junctions has increased over the past years. These efforts can provide new insights into the near-field interaction and the corresponding tunability in properties, as well as resultant plasmon-based molecular devices. This Review presents the latest advancements of plasmonic resonances in molecular junctions and details the progress in plasmon excitation and plasmon coupling. We also highlight emerging experimental approaches to unravel the mechanisms behind the various types of light-matter interactions at molecular length scales, where quantum effects come into play. Finally, we discuss the potential of these plasmonic-electronic hybrid systems across various future applications, including sensing, photocatalysis, molecular trapping and active control of molecular switches.

Single-Molecule Sensor for High-Confidence Detection of miRNA

MicroRNAs (miRNAs) play a crucial role in regulating gene expression and have been linked to many diseases. Therefore, sensitive and accurate detection of disease-linked miRNAs is vital to the emerging revolution in early diagnosis of diseases. While the detection of miRNAs is a challenge due to their intrinsic properties such as small size, high sequence similarity among miRNAs and low abundance in biological fluids, the majority of miRNA-detection strategies involve either target/signal amplification or involve complex sensing designs. In this study, we have developed and tested a DNA-based fluorescence resonance energy transfer (FRET) sensor that enables ultrasensitive detection of a miRNA biomarker (miRNA-342-3p) expressed by triple-negative breast cancer (TNBC) cells. The sensor shows a relatively low FRET state in the absence of a target but it undergoes continuous FRET transitions between low- and high-FRET states in the presence of the target. The sensor is highly specific, has a detection limit down to low femtomolar (fM) without having to amplify the target, and has a large dynamic range (3 orders of magnitude) extending to 300 000 fM. Using this strategy, we demonstrated that the sensor allows detection of miRNA-342-3p in the miRNA-extracts from cancer cell lines and TNBC patient-derived xenografts. Given the simple-to-design hybridization-based detection, the sensing platform developed here can be used to detect a wide range of miRNAs enabling early diagnosis and screening of other genetic disorders.

Single molecule detection; from microscopy to sensors

Single molecule detection is necessary to find out physical, chemical properties and their mechanism involved in the normal functioning of body cells. In this way, they can provide a new direction to the healthcare system. Various techniques have been developed and employed for their successful detection. Herein, we have emphasized various traditional methods as well as biosensing technology which offer single molecule sensitivity. The various methods including plasmonic resonance, nanopores, whispering gallery mode, Simoa assay and recognition tunneling are discussed in the initial part which has been followed by a discussion about biosensor-based detection. Plasmonic, SERS, CRISPR/Cas, and other types of biosensors are focused in this review and found to be highly sensitive for single molecule detection. This review provides an overview of progression in different techniques employed for single molecule detection.

Displacement Statistics of Unhindered Single Molecules Show no Enhanced Diffusion in Enzymatic Reactions

Recent studies have sparked debate over whether catalytic reactions enhance the diffusion coefficients D of enzymes. Through high statistics of the transient (600 μs) displacements of unhindered single molecules freely diffusing in common buffers, we here quantify D for four enzymes under catalytic turnovers. We thus formulate how ∼ ±1% precisions may be achieved for D, and show no changes in diffusivity for catalase, urease, aldolase, and alkaline phosphatase under the application of wide concentration ranges of substrates. Our single-molecule approach thus overcomes potential limitations and artifacts underscored by recent studies to show no enhanced diffusion in enzymatic reactions.

Influence of bulky substituents on single-molecule SERS sensitivity

The surface-enhanced Raman spectroscopy (SERS) detection limit strongly depends on the molecular structure, which we demonstrate for a family of tert-butyl-substituted porphycenes. Even though the investigated species present very similar photophysical properties, the ratio between the SERS signal and fluorescence background depends on the number of bulky tert-butyl groups. Moreover, the probability of single molecule detection systematically drops with the number of the moieties attached to the pyrrole ring. As steric hindrance is the only significantly changing feature among the studied chromophores, we attribute the observed phenomena to the spatial structure. We also show that the sensitivity of the SERS technique can be improved by lowering the temperature. We managed to observe single-molecule spectra for derivatives for which this was unattainable at room temperature.

Joint Detection of Change Points in Multichannel Single-Molecule Measurements

Recent developments in single-molecule measurement technology have expanded the capability to measure multiple parameters. These emergent modalities provide more holistic observations of complex biomolecular processes and call for new analysis methods to detect state changes in multichannel data. Here we develop an algorithm called MULLR (MUlti-channel Log-Likelihood Ratio test) to jointly identify change points in multichannel single-molecule measurements. MULLR is an extension of the popular single-channel implementation for change point detection based on a binary segmentation and log-likelihood ratio test framework. We validate the algorithm on simulated data and characterize the power of detection and false positive rate. We show that MULLR can identify change points in experimental multichannel data and naturally works with different noise statistics and time resolutions across channels. Further, we quantify the benefit of MULLR compared to single-channel analysis. We envision that the MULLR algorithm will be useful to a range of multiparameter single-molecule measurements.

Single plasmonic nanostructures for biomedical diagnosis

The field of single nanoparticle plasmonics has grown enormously. There is no doubt that a wide diversity of the nanoplasmonic techniques and nanostructures represents a tremendous opportunity for fundamental biomedical studies as well as sensing and imaging applications. Single nanoparticle plasmonic biosensors are efficient in label-free single-molecule detection, as well as in monitoring real-time binding events of even several biomolecules. In the present review, we have discussed the prominent advantages and advances in single particle characterization and synthesis as well as new insight into and information on biomedical diagnosis uniquely obtained using single particle approaches. The approaches include the fundamental studies of nanoplasmonic behavior, two typical methods based on refractive index change and characteristic light intensity change, exciting innovations of synthetic strategies for new plasmonic nanostructures, and practical applications using single particle sensing, imaging, and tracking. The basic sphere and rod nanostructures are the focus of extensive investigations in biomedicine, while they can be programmed into algorithmic assemblies for novel plasmonic diagnosis. Design of single nanoparticles for the detection of single biomolecules will have far-reaching consequences in biomedical diagnosis.

The Benefits of Unnatural Amino Acid Incorporation as Protein Labels for Single Molecule Localization Microscopy

Single Molecule Localization Microscopy (SMLM) is an imaging method that allows for the visualization of structures smaller than the diffraction limit of light (~200 nm). This is achieved through techniques such as stochastic optical reconstruction microscopy (STORM) and photoactivated localization microscopy (PALM). A large part of obtaining ideal imaging of single molecules is the choice of the right fluorescent label. An upcoming field of protein labeling is incorporating unnatural amino acids (UAAs) with an attached fluorescent dye for precise localization and visualization of individual molecules. For this technique, fluorescent probes are conjugated to UAAs and are introduced into the protein of interest (POI) as a label. Here we contrast this labeling method with other commonly used protein-based labeling methods such as fluorescent proteins (FPs) or self-labeling tags such as Halotag, SNAP-tags, and CLIP-tags, and highlight the benefits and shortcomings of the site-specific incorporation of UAAs coupled with fluorescent dyes in SMLM.

Radiative heat transfer at the nanoscale: experimental trends and challenges

Energy transport theories are being revisited at the nanoscale, as macroscopic laws known for a century are broken at dimensions smaller than those associated with energy carriers. For thermal radiation, where the typical dimension is provided by Wien's wavelength, Planck's law and associated concepts describing surface-to-surface radiative transfer have to be replaced by a full electromagnetic framework capturing near-field radiative heat transfer (photon tunnelling between close bodies), interference effects and sub-wavelength thermal emission (emitting body of small size). It is only during the last decade that nanotechnology has allowed for many experimental verifications - with a recent boom - of the large increase of radiative heat transfer at the nanoscale. In this minireview, we highlight the parameter space that has been investigated until now, showing that it is limited in terms of inter-body distance, temperature and object size, and provide clues about possible thermal-energy harvesting, sensing and management applications. We also provide an outlook on open topics, underlining some difficulties in applying single-wavelength approaches to broadband thermal emitters while acknowledging the promise of thermal nanophotonics and observing that molecular/chemical viewpoints have been hardly addressed.

Fluorescence Microscopic Investigations of Molecular Dynamics in Self-Assembled Nanostructures

Many analytical methods employ self-assembled nanostructured materials as chemical recognition media. Molecular permeation through these materials exhibits unique selectivity owing to nanoconfinement-induced enhancement of permeant-nanostructure interactions. This Personal Account introduces our efforts to investigate the detailed dynamics of single or a small number of molecules in nanostructured materials. We developed new experimental and analysis approaches built upon laser-based fluorescence microscopy to measure the detailed translational and orientational dynamics of molecules diffusing in horizontally-oriented, cylindrical nanostructures, including surfactant micelles, silica mesopores, block copolymer microdomains, and bolaamphiphile-based organic nanotubes. Our studies clarified nanoscale details on the structural/chemical heterogeneity of the nanostructures, and their impacts on molecular mass transport dynamics.

Photothermal Microscopy: Imaging the Optical Absorption of Single Nanoparticles and Single Molecules

The photothermal (PT) signal arises from slight changes of the index of refraction in a sample due to absorption of a heating light beam. Refractive index changes are measured with a second probing beam, usually of a different color. In the past two decades, this all-optical detection method has reached the sensitivity of single particles and single molecules, which gave birth to original applications in material science and biology. PT microscopy enables shot-noise-limited detection of individual nanoabsorbers among strong scatterers and circumvents many of the limitations of fluorescence-based detection. This review describes the theoretical basis of PT microscopy, the methodological developments that improved its sensitivity toward single-nanoparticle and single-molecule imaging, and a vast number of applications to single-nanoparticle imaging and tracking in material science and in cellular biology.

Quantifying accuracy and heterogeneity in single-molecule super-resolution microscopy

The resolution and accuracy of single-molecule localization microscopes (SMLMs) are routinely benchmarked using simulated data, calibration rulers, or comparisons to secondary imaging modalities. However, these methods cannot quantify the nanoscale accuracy of an arbitrary SMLM dataset. Here, we show that by computing localization stability under a well-chosen perturbation with accurate knowledge of the imaging system, we can robustly measure the confidence of individual localizations without ground-truth knowledge of the sample. We demonstrate that our method, termed Wasserstein-induced flux (WIF), measures the accuracy of various reconstruction algorithms directly on experimental 2D and 3D data of microtubules and amyloid fibrils. We further show that WIF confidences can be used to evaluate the mismatch between computational models and imaging data, enhance the accuracy and resolution of reconstructed structures, and discover hidden molecular heterogeneities. As a computational methodology, WIF is broadly applicable to any SMLM dataset, imaging system, and localization algorithm.

Standard benchmarking of single-molecule localization microscopy cannot quantify nanoscale accuracy of arbitrary datasets. Here, the authors present Wasserstein-induced flux, a method using a chosen perturbation and knowledge of the imaging system to measure confidence of individual localizations.

100th Anniversary of Macromolecular Science Viewpoint: Enabling Advances in Fluorescence Microscopy Techniques

In the past few decades there has been a revolution in the field of optical microscopy with emerging capabilities such as super-resolution and single-molecule fluorescence techniques. Combined with the classical advantages of fluorescence imaging, such as chemical labeling specificity, and noninvasive sample preparation and imaging, these methods have enabled significant advances in our polymer community. This Viewpoint discusses several of these capabilities and how they can uniquely offer information where other characterization techniques are limited. Several examples are highlighted that demonstrate the ability of fluorescence microscopy to understand key questions in polymer science such as single-molecule diffusion and orientation, 3D nanostructural morphology, and interfacial and multicomponent dynamics. Finally, we briefly discuss opportunities for further advances in techniques that may allow them to make an even greater contribution in polymer science.

Fast-tracking of single emitters in large volumes with nanometer precision

Multifocal plane microscopy allows for capturing images at different focal planes simultaneously. Using a proprietary prism which splits the emitted light into paths of different lengths, images at 8 different focal depths were obtained, covering a volume of 50x50x4 µm³. The position of single emitters was retrieved using a phasor-based approach across the different imaging planes, with better than 10 nm precision in the axial direction. We validated the accuracy of this approach by tracking fluorescent beads in 3D to calculate water viscosity. The fast acquisition rate (>100 fps) also enabled us to follow the capturing of 0.2 µm fluorescent beads into an optical trap.

Tuning the Baird aromatic triplet-state energy of cyclooctatetraene to maximize the self-healing mechanism in organic fluorophores

Bright, photostable, and nontoxic fluorescent contrast agents are critical for biological imaging. "Self-healing" dyes, in which triplet states are intramolecularly quenched, enable fluorescence imaging by increasing fluorophore brightness and longevity, while simultaneously reducing the generation of reactive oxygen species that promote phototoxicity. Here, we systematically examine the self-healing mechanism in cyanine-class organic fluorophores spanning the visible spectrum. We show that the Baird aromatic triplet-state energy of cyclooctatetraene can be physically altered to achieve order of magnitude enhancements in fluorophore brightness and signal-to-noise ratio in both the presence and absence of oxygen. We leverage these advances to achieve direct measurements of large-scale conformational dynamics within single molecules at submillisecond resolution using wide-field illumination and camera-based detection methods. These findings demonstrate the capacity to image functionally relevant conformational processes in biological systems in the kilohertz regime at physiological oxygen concentrations and shed important light on the multivariate parameters critical to self-healing organic fluorophore design.

Sub-Bandgap Optical Modulation of Quantum Dot Blinking Statistics

Colloidal quantum dots (QDs) suffer from pervasive photoluminescence intermittency that frustrates applications and correlates with irreversible photodegradation. In single-QD spectroscopies, blinking manifests as sporadic switching between ON and OFF states without a characteristic time scale, and the longstanding search for mechanisms has been recently accelerated by techniques to controllably modulate the QD environment. Here, we develop an all-optical modulation scheme and demonstrate that sub-bandgap light tuned to the stimulated emission transition perturbs the blinking statistics of individual CdSe/ZnS core/shell QDs. Resonant optical modulation progressively suppresses long-duration ON events, quantified by a power-law slope that is more negative on average (Δα_ON = 0.46 ± 0.09), while OFF distributions and truncation times are unaffected. This characteristic effect is robust to choices in background subtraction and statistical analysis but supports mechanistic descriptions beyond first-order kinetics. This demonstration of all-optical perturbation of QD blinking dynamics provides an experimental avenue to disentangle the complex photophysics of photoluminescence intermittency.

Top-down machine learning approach for high-throughput single-molecule analysis

Single-molecule approaches provide enormous insight into the dynamics of biomolecules, but adequately sampling distributions of states and events often requires extensive sampling. Although emerging experimental techniques can generate such large datasets, existing analysis tools are not suitable to process the large volume of data obtained in high-throughput paradigms. Here, we present a new analysis platform (DISC) that accelerates unsupervised analysis of single-molecule trajectories. By merging model-free statistical learning with the Viterbi algorithm, DISC idealizes single-molecule trajectories up to three orders of magnitude faster with improved accuracy compared to other commonly used algorithms. Further, we demonstrate the utility of DISC algorithm to probe cooperativity between multiple binding events in the cyclic nucleotide binding domains of HCN pacemaker channel. Given the flexible and efficient nature of DISC, we anticipate it will be a powerful tool for unsupervised processing of high-throughput data across a range of single-molecule experiments.

Simultaneous and ultrasensitive detection of multiple microRNAs by single-molecule fluorescence imaging

Cell status changes are typically accompanied by the simultaneous changes of multiple microRNA (miRNA) levels. Thus, simultaneous and ultrasensitive detection of multiple miRNA biomarkers shows great promise in early cancer diagnosis. Herein, a facile single-molecule fluorescence imaging assay was proposed for the simultaneous and ultrasensitive detection of multiple miRNAs using only one capture anti-DNA/RNA antibody (S9.6 antibody). Two complementary DNAs (cDNAs) designed to hybridize with miRNA-21 and miRNA-122 were labelled with Cy3 (cDNA1) and Cy5 (cDNA2) dyes at their 5'-ends, respectively. After hybridization, both miRNA-21/cDNA1 and miRNA-122/cDNA2 complexes were captured by S9.6 antibodies pre-modified on a coverslip surface. Subsequently, the Cy3 and Cy5 dyes on the coverslip surface were imaged by the single-molecule fluorescence setup. The amount of miRNA-21 and miRNA-122 was quantified by counting the image spots from the Cy3 and Cy5 dye molecules in the green and red channels, respectively. The proposed assay displayed high specificity and sensitivity for singlet miRNA detection both with a detection limit of 5 fM and for multiple miRNA detection both with a detection limit of 20 fM. Moreover, it was also demonstrated that the assay could be used to detect multiple miRNAs simultaneously in human hepatocellular cancer cells (HepG2 cells). The proposed assay provides a novel biosensing platform for the ultrasensitive and simple detection of multiple miRNA expressions and shows great prospects for early cancer diagnosis.

Deep learning in single-molecule microscopy: fundamentals, caveats, and recent developments [Invited]

Deep learning-based data analysis methods have gained considerable attention in all fields of science over the last decade. In recent years, this trend has reached the single-molecule community. In this review, we will survey significant contributions of the application of deep learning in single-molecule imaging experiments. Additionally, we will describe the historical events that led to the development of modern deep learning methods, summarize the fundamental concepts of deep learning, and highlight the importance of proper data composition for accurate, unbiased results.

Protein adsorption measurements on low fouling and ultralow fouling surfaces: A critical comparison of surface characterization techniques

Ultralow protein fouling behavior is a common target for new high-performance materials. Ultralow fouling is often defined based on the amount of irreversibly adsorbed protein (< 5 ng cm^-2) measured by a surface ensemble averaging method. However, protein adsorption at solid interfaces is a dynamic process involving multiple steps, which may include adsorption, desorption, and irreversible protein denaturation. In order to better optimize the performance of antifouling surfaces, it is imperative to fully understand how proteins interact with surfaces, including kinetics of adsorption and desorption, conformation, stability, and amount of adsorbed proteins. Defining ultralow fouling surfaces based on a measurement at or near the limit of detection of a surface-averaged measurement may not capture all of this behavior. Single-molecule microscopy techniques can resolve individual protein-surface interactions with high temporal and spatial resolution. This information can be used to tune the properties of surfaces to better resist protein adsorption. In this work, we demonstrate how combining surface plasmon resonance, X-ray photoelectron spectroscopy, atomic force microscopy, and single-molecule localization microscopy provides a more complete picture of protein adsorption on low fouling and ultralow fouling polyelectrolyte multilayer and polymer brush surfaces, over different regimes of protein concentration. In this case, comparing the surfaces using surface plasmon resonance alone is insufficient to rank their resistance to protein adsorption. Our results suggest a revision of the accepted definition of ultralow fouling surfaces is timely: with the advent of time-resolved studies of protein adsorption kinetics at the single-molecule level, it is neither necessary nor sufficient to rely on a surface averaging techniques to qualify ultralow fouling surfaces. Since protein adsorption is a dynamic process, understanding how surface properties affect the kinetics of protein adsorption will enable the design of future generations of advanced antifouling materials. STATEMENT OF SIGNIFICANCE: The design of ultralow fouling surfaces is often optimized based on a single surface-averaging technique measuring the amount of irreversibly adsorbed protein. This work provides a critical comparison of alternative techniques for evaluating protein adsorption on low fouling and ultralow fouling surfaces, and demonstrates how additional information about the dynamics of protein-surface interactions at the interface can be obtained by application of single-molecule microscopy. This approach could be used to better elucidate mechanisms of protein resistance and design principles for advanced ultralow fouling materials.

Monte Carlo Simulation of Brownian Motion using a Piezo-Actuated Microscope Stage

Single particle tracking is a powerful tool for studying and understanding the motions of biological macromolecules integral to cellular processes. In the past three decades there has been continuous and rapid development of these techniques in both optical microscope design and in algorithms to estimate the statistics and positions of the molecule's trajectory. Although there has been great progress, comparison between different microscope configurations and estimation algorithms has been difficult beyond simulated data. In this paper we explore using a piezo actuated microscope stage to reproduce Brownian motion. Our goal is to use this as a tool to test performance of single particle tracking optical microscopes and estimation algorithms. In this study, Monte Carlo simulations were used to assess the ability of piezo actuated microscope stages for reproducing Brownian motion. Surprisingly, the dynamics of the stage together with configuration of the system allow for preservation of the Brownian motion statistics. Further, feed forward model inverse control allows for low error tracking of Brownian motion trajectories over a wide range of diffusion constants, varying stage response times, and trajectory discrete time steps. These results show great promise in using a piezo actuated microscope stage for testing single particle tracking experimental setups.

Quantum electrodynamics at room temperature coupling a single vibrating molecule with a plasmonic nanocavity

Interactions between a single emitter and cavity provide the archetypical system for fundamental quantum electrodynamics. Here we show that a single molecule of Atto647 aligned using DNA origami interacts coherently with a sub-wavelength plasmonic nanocavity, approaching the cooperative regime even at room temperature. Power-dependent pulsed excitation reveals Rabi oscillations, arising from the coupling of the oscillating electric field between the ground and excited states. The observed single-molecule fluorescent emission is split into two modes resulting from anti-crossing with the plasmonic mode, indicating the molecule is strongly coupled to the cavity. The second-order correlation function of the photon emission statistics is found to be pump wavelength dependent, varying from g(2)(0) = 0.4 to 1.45, highlighting the influence of vibrational relaxation on the Jaynes-Cummings ladder. Our results show that cavity quantum electrodynamic effects can be observed in molecular systems at ambient conditions, opening significant potential for device applications.

Generalized method to design phase masks for 3D super-resolution microscopy

Point spread function (PSF) engineering by phase modulation is a novel approach to three-dimensional (3D) super-resolution microscopy, with different point spread functions being proposed for specific applications. It is often not easy to achieve the desired shape of engineered point spread functions because it is challenging to determine the correct phase mask. Additionally, a phase mask can either encode 3D space information or additional time information, but not both simultaneously. A robust algorithm for recovering a phase mask to generate arbitrary point spread functions is needed. In this work, a generalized phase mask design method is introduced by performing an optimization. A stochastic gradient descent algorithm and a Gauss-Newton algorithm are developed and compared for their ability to recover the phase masks for previously reported point spread functions. The new Gauss-Newton algorithm converges to a minimum at much higher speeds. This algorithm is used to design a novel stretching-lobe phase mask to encode temporal and 3D spatial information simultaneously. The stretching-lobe phase mask and other masks are fabricated in-house for proof-of-concept using multi-level light lithography and an optimized commercially sourced stretching-lobe phase mask (PM) is validated experimentally to encode 3D spatial and temporal information. The algorithms' generalizability is further demonstrated by generating a phase mask that comprises four different letters at different depths.

Amorphous Quantum Nanomaterials

In quantum materials, macroscopic behavior is governed in nontrivial ways by quantum phenomena. This is usually achieved by exquisite control over atomic positions in crystalline solids. Here, it is demonstrated that the use of disordered glassy materials provides unique opportunities to tailor quantum material properties. By borrowing ideas from single-molecule spectroscopy, single delocalized π-electron dye systems are isolated in relatively rigid ultrasmall (<10 nm diameter) amorphous silica nanoparticles. It is demonstrated that chemically tuning the local amorphous silica environment around the dye over a range of compositions enables exquisite control over dye quantum behavior, leading to efficient probes for photodynamic therapy (PDT) and stochastic optical reconstruction microscopy (STORM). The results suggest that efficient fine-tuning of light-induced quantum behavior mediated via effects like spin-orbit coupling can be effectively achieved by systematically varying averaged local environments in glassy amorphous materials as opposed to tailoring well-defined neighboring atomic lattice positions in crystalline solids. The resulting nanoprobes exhibit features proven to enable clinical translation.

Statistical Learning of Discrete States in Time Series

Time series obtained from time-dependent experiments contain rich information on kinetics and dynamics of the system under investigation. This work describes an unsupervised learning framework, along with the derivation of the necessary analytical expressions, for the analysis of Gaussian-distributed time series that exhibit discrete states. After the time series has been partitioned into segments in a model-free manner using the previously developed change-point (CP) method, this protocol starts with an agglomerative hierarchical clustering algorithm to classify the detected segments into possible states. The initial state clustering is further refined using an expectation-maximization (EM) procedure, and the number of states is determined by a Bayesian information criterion (BIC). Also introduced here is an achievement scalarization function, usually seen in artificial intelligence literature, for quantitatively assessing the performance of state determination. The statistical learning framework, which is comprised of three stages, detection of signal change, clustering, and number-of-state determination, was thoroughly characterized using simulated trajectories with random intensity segments that have no underlying kinetics, and its performance was critically evaluated. The application to experimental data is also demonstrated. The results suggested that this general framework, the implementation of which is based on firm theoretical foundations and does not require the imposition of any kinetics model, is powerful in determining the number of states, the parameters contained in each state, as well as the associated statistical significance.

The future of quantum biology

Biological systems are dynamical, constantly exchanging energy and matter with the environment in order to maintain the non-equilibrium state synonymous with living. Developments in observational techniques have allowed us to study biological dynamics on increasingly small scales. Such studies have revealed evidence of quantum mechanical effects, which cannot be accounted for by classical physics, in a range of biological processes. Quantum biology is the study of such processes, and here we provide an outline of the current state of the field, as well as insights into future directions.

Single-Molecule Kinetics in Living Cells

In the past decades, advances in microscopy have made it possible to study the dynamics of individual biomolecules in vitro and resolve intramolecular kinetics that would otherwise be hidden in ensemble averages. More recently, single-molecule methods have been used to image, localize, and track individually labeled macromolecules in the cytoplasm of living cells, allowing investigations of intermolecular kinetics under physiologically relevant conditions. In this review, we illuminate the particular advantages of single-molecule techniques when studying kinetics in living cells and discuss solutions to specific challenges associated with these methods.

Single-molecule optical absorption imaging by nanomechanical photothermal sensing

Absorption microscopy is a promising alternative to fluorescence microscopy for single-molecule imaging. So far, molecular absorption has been probed optically via the attenuation of a probing laser or via photothermal effects. The sensitivity of optical probing is not only restricted by background scattering but it is fundamentally limited by laser shot noise, which minimizes the achievable single-molecule signal-to-noise ratio. Here, we present nanomechanical photothermal microscopy, which overcomes the scattering and shot-noise limit by detecting the photothermal heating of the sample directly with a temperature-sensitive substrate. We use nanomechanical silicon nitride drums, whose resonant frequency detunes with local heating. Individual Au nanoparticles with diameters from 10 to 200 nm and single molecules (Atto 633) are scanned with a heating laser with a peak irradiance of 354 ± 45 µW/µm² using 50× long-working-distance objective. With a stress-optimized drum we reach a sensitivity of 16 fW/Hz^1/2 at room temperature, resulting in a single-molecule signal-to-noise ratio of >70. The high sensitivity combined with the inherent wavelength independence of the nanomechanical sensor presents a competitive alternative to established tools for the analysis and localization of nonfluorescent single molecules and nanoparticles.

Ultrabright Room-Temperature Sub-Nanosecond Emission from Single Nitrogen-Vacancy Centers Coupled to Nanopatch Antennas

Solid-state quantum emitters are in high demand for emerging technologies such as advanced sensing and quantum information processing. Generally, these emitters are not sufficiently bright for practical applications, and a promising solution consists in coupling them to plasmonic nanostructures. Plasmonic nanostructures support broadband modes, making it possible to speed up the fluorescence emission in room-temperature emitters by several orders of magnitude. However, one has not yet achieved such a fluorescence lifetime shortening without a substantial loss in emission efficiency, largely because of strong absorption in metals and emitter bleaching. Here, we demonstrate ultrabright single-photon emission from photostable nitrogen-vacancy (NV) centers in nanodiamonds coupled to plasmonic nanocavities made of low-loss single-crystalline silver. We observe a 70-fold difference between the average fluorescence lifetimes and a 90-fold increase in the average detected saturated intensity. The nanocavity-coupled NVs produce up to 35 million photon counts per second, several times more than the previously reported rates from room-temperature quantum emitters.

Light sheet approaches for improved precision in 3D localization-based super-resolution imaging in mammalian cells [Invited]

The development of imaging techniques beyond the diffraction limit has paved the way for detailed studies of nanostructures and molecular mechanisms in biological systems. Imaging thicker samples, such as mammalian cells and tissue, in all three dimensions, is challenging due to increased background and volumes to image. Light sheet illumination is a method that allows for selective irradiation of the image plane, and its inherent optical sectioning capability allows for imaging of biological samples with reduced background, photobleaching, and photodamage. In this review, we discuss the advantage of combining single-molecule imaging with light sheet illumination. We begin by describing the principles of single-molecule localization microscopy and of light sheet illumination. Finally, we present examples of designs that successfully have married single-molecule super-resolution imaging with light sheet illumination for improved precision in mammalian cells.

Toward dynamic structural biology: Two decades of single-molecule Förster resonance energy transfer

Classical structural biology can only provide static snapshots of biomacromolecules. Single-molecule Förster resonance energy transfer (smFRET) paved the way for studying dynamics in macromolecular structures under biologically relevant conditions. Since its first implementation in 1996, smFRET experiments have confirmed previously hypothesized mechanisms and provided new insights into many fundamental biological processes, such as DNA maintenance and repair, transcription, translation, and membrane transport. We review 22 years of contributions of smFRET to our understanding of basic mechanisms in biochemistry, molecular biology, and structural biology. Additionally, building on current state-of-the-art implementations of smFRET, we highlight possible future directions for smFRET in applications such as biosensing, high-throughput screening, and molecular diagnostics.