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

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

A 2D chiral microcavity based on apparent circular dichroism.

Engineering asymmetric transmission between left-handed and right-handed circularly polarized light in planar Fabry-Pérot (FP) microcavities would enable a variety of chiral light-matter phenomena, with applications in spintronics, polaritonics, and chiral lasing. Such symmetry breaking, however, generally requires Faraday rotators or nanofabricated polarization-preserving mirrors. We present a simple solution requiring no nanofabrication to induce asymmetric transmission in FP microcavities, preserving low mode volumes by embedding organic thin films exhibiting apparent circular dichroism (ACD); an optical phenomenon based on 2D chirality. Importantly, ACD interactions are opposite for counter-propagating light. Consequently, we demonstrated asymmetric transmission of cavity modes over an order of magnitude larger than that of the isolated thin film. Through circular dichroism spectroscopy, Mueller matrix ellipsometry, and simulation using theoretical scattering matrix methods, we characterize the spatial, spectral, and angular chiroptical responses of this 2D chiral microcavity.

Theory predicts 2D chiral polaritons based on achiral Fabry-Pérot cavities using apparent circular dichroism.

Realizing polariton states with high levels of chirality offers exciting prospects for quantum information, sensing, and lasing applications. Such chirality must emanate from either the involved optical resonators or the quantum emitters. Here, we theoretically demonstrate a rare opportunity for realizing polaritons with so-called 2D chirality by strong coupling of the optical modes of (high finesse) achiral Fabry-Pérot cavities with samples exhibiting "apparent circular dichroism" (ACD). ACD is a phenomenon resulting from an interference between linear birefringence and dichroic interactions. By introducing a quantum electrodynamical theory of ACD, we identify the design rules based on which 2D chiral polaritons can be produced, and their chirality can be optimized.

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.

The Role of Experimental Noise in a Hybrid Classical-Molecular Computer to Solve Combinatorial Optimization Problems.

Chemical and molecular-based computers may be promising alternatives to modern silicon-based computers. In particular, hybrid systems, where tasks are split between a chemical medium and traditional silicon components, may provide access and demonstration of chemical advantages such as scalability, low power dissipation, and genuine randomness. This work describes the development of a hybrid classical-molecular computer (HCMC) featuring an electrochemical reaction on top of an array of discrete electrodes with a fluorescent readout. The chemical medium, optical readout, and electrode interface combined with a classical computer generate a feedback loop to solve several canonical optimization problems in computer science such as number partitioning and prime factorization. Importantly, the HCMC makes constructive use of experimental noise in the optical readout, a milestone for molecular systems, to solve these optimization problems, as opposed to in silico random number generation. Specifically, we show calculations stranded in local minima can consistently converge on a global minimum in the presence of experimental noise. Scalability of the hybrid computer is demonstrated by expanding the number of variables from 4 to 7, increasing the number of possible solutions by 1 order of magnitude. This work provides a stepping stone to fully molecular approaches to solving complex computational problems using chemistry.

A path towards single molecule vibrational strong coupling in a Fabry-Pérot microcavity.

Interaction between light and molecular vibrations leads to hybrid light-matter states called vibrational polaritons. Even though many intriguing phenomena have been predicted for single-molecule vibrational strong coupling (VSC), several studies suggest that these effects tend to be diminished in the many-molecule regime due to the presence of dark states. Achieving single or few-molecule vibrational polaritons has been constrained by the need for fabricating extremely small mode volume infrared cavities. In this theoretical work, we propose an alternative strategy to achieve single-molecule VSC in a cavity-enhanced Raman spectroscopy (CERS) setup, based on the physics of cavity optomechanics. We then present a scheme harnessing few-molecule VSC to thermodynamically couple two reactions, such that a spontaneous electron transfer can now fuel a thermodynamically uphill reaction that was non-spontaneous outside the cavity.

Label-free observation of individual solution phase molecules.

The vast majority of chemistry and biology occurs in solution, and new label-free analytical techniques that can help resolve solution-phase complexity at the single-molecule level can provide new microscopic perspectives of unprecedented detail. Here, we use the increased light-molecule interactions in high-finesse fiber Fabry-Pérot microcavities to detect individual biomolecules as small as 1.2 kDa with signal-to-noise ratios >100, even as the molecules are freely diffusing in solution. Our method delivers 2D intensity and temporal profiles, enabling the distinction of sub-populations in mixed samples. Strikingly, we observe a linear relationship between passage time and molecular radius, unlocking the potential to gather crucial information about diffusion and solution-phase conformation. Furthermore, mixtures of biomolecule isomers of the same molecular weight can also be resolved. Detection is based on a novel molecular velocity filtering and dynamic thermal priming mechanism leveraging both photo-thermal bistability and Pound-Drever-Hall cavity locking. This technology holds broad potential for applications in life and chemical sciences and represents a major advancement in label-free in vitro single-molecule techniques.

Compounding a High-Permittivity Thermoplastic Material and Its Applicability in Manufacturing of Microwave Photonic Crystals.

Additive Manufacturing (AM) techniques allow the production of complex geometries unattainable through other traditional technologies. This advantage lends itself well to rapidly iterating and improving upon the design of microwave photonic crystals, which are structures with intricate, repeating features. The issue tackled by this work involves compounding a high-permittivity material that can be used to produce 3D microwave photonic structures using polymer extrusion-based AM techniques. This material was acrylonitrile butadiene styrene (ABS)-based and used barium titanate (BaTiO3) ceramic as the high-permittivity component of the composite and involved the use of a surfactant and a plasticizer to facilitate processing. Initial small amounts of the material were compounded using an internal batch mixer and studied using polymer thermal analysis techniques, such as thermogravimetric analysis, rheometry, and differential scanning calorimetry to determine the proper processing conditions. The production of the material was then scaled up using a twin-screw extruder system, producing homogeneous pellets. Finally, the thermoplastic composite was used with a screw-based, material extrusion additive manufacturing technique to produce a slab for measuring the relative permittivity of the material, as well as a preliminary 3D photonic crystal. The real part of the permittivity was measured to be 12.85 (loss tangent = 0.046) in the range of 10 to 12 GHz, representing the highest permittivity ever demonstrated for a thermoplastic AM composite at microwave frequencies.

Active Control of Plasmonic-Photonic Interactions in a Microbubble Cavity.

Active control of light-matter interactions using nanophotonic structures is critical for new modalities for solar energy production, cavity quantum electrodynamics (QED), and sensing, particularly at the single-particle level, where it underpins the creation of tunable nanophotonic networks. Coupled plasmonic-photonic systems show great promise toward these goals because of their subwavelength spatial confinement and ultrahigh-quality factors inherited from their respective components. Here, we present a microfluidic approach using microbubble whispering-gallery mode cavities to actively control plasmonic-photonic interactions at the single-particle level. By changing the solvent in the interior of the microbubble, control can be exerted on the interior dielectric constant and, thus, on the spatial overlap between the photonic and plasmonic modes. Qualitative agreement between experiment and simulation reveals the competing roles mode overlap and mode volume play in altering coupling strengths.

Theory of Apparent Circular Dichroism Reveals the Origin of Inverted and Noninverted Chiroptical Response under Sample Flipping.

Circular dichroism (CD) finds widespread application as an optical probe for the structure of molecules and supramolecular assemblies. Its underlying chiral light-matter interactions effectively couple between photonic spin states and select quantum-mechanical degrees of freedom in a sample, implying an intricate connection with photon-to-matter quantum transduction. However, effective transduction implementations likely require interactions that are antisymmetric with respect to the direction of light propagation through the sample, yielding an inversion of the chiroptical response upon sample flipping, which is uncommon for CD. Recent experiments on organic thin films have demonstrated such chiroptical behavior, which was attributed to "apparent CD" resulting from an interference between the sample's linear birefringence and linear dichroism. However, a theory connecting the underlying optical selection rules to the microscopic electronic structure of the constituent molecules remains to be formulated. Here, we present such a theory based on a combination of Mueller calculus and a Lorentz oscillator model. The theory reaches good agreement with experimental CD spectra and allows for establishing the (supra)molecular design rules for maximizing or minimizing this chiroptical effect. It furthermore highlights that, in addition to antisymmetrically, it can manifest symmetrically such that no chiroptical response inversion occurs, which is a consequence of a helical stacking of molecules in the light propagation direction.

cAMP binding to closed pacemaker ion channels is non-cooperative.

Electrical activity in the brain and heart depends on rhythmic generation of action potentials by pacemaker ion channels (HCN) whose activity is regulated by cAMP binding1. Previous work has uncovered evidence for both positive and negative cooperativity in cAMP binding2,3, but such bulk measurements suffer from limited parameter resolution. Efforts to eliminate this ambiguity using single-molecule techniques have been hampered by the inability to directly monitor binding of individual ligand molecules to membrane receptors at physiological concentrations. Here we overcome these challenges using nanophotonic zero-mode waveguides4 to directly resolve binding dynamics of individual ligands to multimeric HCN1 and HCN2 ion channels. We show that cAMP binds independently to all four subunits when the pore is closed, despite a subsequent conformational isomerization to a flip state at each site. The different dynamics in binding and isomerization are likely to underlie physiologically distinct responses of each isoform to cAMP5 and provide direct validation of the ligand-induced flip-state model6-9. This approach for observing stepwise binding in multimeric proteins at physiologically relevant concentrations can directly probe binding allostery at single-molecule resolution in other intact membrane proteins and receptors.

Role of Collagen Fiber Morphology on Ovarian Cancer Cell Migration Using Image-Based Models of the Extracellular Matrix.

Remodeling of the extracellular matrix (ECM) is an important part in the development and progression of many epithelial cancers. However, the biological significance of collagen alterations in ovarian cancer has not been well established. Here we investigated the role of collagen fiber morphology on cancer cell migration using tissue engineered scaffolds based on high-resolution Second-Harmonic Generation (SHG) images of ovarian tumors. The collagen-based scaffolds are fabricated by multiphoton excited (MPE) polymerization, which is a freeform 3D method affording submicron resolution feature sizes (~0.5 µm). This capability allows the replication of the collagen fiber architecture, where we constructed models representing normal stroma, high-risk tissue, benign tumors, and high-grade tumors. These were seeded with normal and ovarian cancer cell lines to investigate the separate roles of the cell type and matrix morphology on migration dynamics. The primary finding is that key cell-matrix interactions such as motility, cell spreading, f-actin alignment, focal adhesion, and cadherin expression are mainly determined by the collagen fiber morphology to a larger extent than the initial cell type. Moreover, we found these aspects were all enhanced for cells on the highly aligned, high-grade tumor model. Conversely, the weakest corresponding responses were observed on the more random mesh-like normal stromal matrix, with the partially aligned benign tumor and high-risk models demonstrating intermediate behavior. These results are all consistent with a contact guidance mechanism. These models cannot be synthesized by other conventional fabrication methods, and we suggest this approach will enable a variety of studies in cancer biology.

From Absorption Spectra to Charge Transfer in Nanoaggregates of Oligomers with Machine Learning.

Fast and inexpensive characterization of materials properties is a key element to discover novel functional materials. In this work, we suggest an approach employing three classes of Bayesian machine learning (ML) models to correlate electronic absorption spectra of nanoaggregates with the strength of intermolecular electronic couplings in organic conducting and semiconducting materials. As a specific model system, we consider poly(3,4-ethylenedioxythiophene) (PEDOT) polystyrene sulfonate, a cornerstone material for organic electronic applications, and so analyze the couplings between charged dimers of closely packed PEDOT oligomers that are at the heart of the material's unrivaled conductivity. We demonstrate that ML algorithms can identify correlations between the coupling strengths and the electronic absorption spectra. We also show that ML models can be trained to be transferable across a broad range of spectral resolutions and that the electronic couplings can be predicted from the simulated spectra with an 88% accuracy when ML models are used as classifiers. Although the ML models employed in this study were trained on data generated by a multiscale computational workflow, they were able to leverage experimental data.

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.

During a chemical or biological process, a molecule may transition through a series of states, many of which are rare or short-lived. Advances in technology have made it easier to detect these states by gathering large amounts of data on individual molecules. However, the increasing size of these datasets has put a strain on the algorithms and software used to identify different molecular states. Now, White et al. have developed a new algorithm called DISC which overcomes this technical limitation. Unlike most other algorithms, DISC requires minimal input from the user and uses a new method to group the data into categories that represent distinct molecular states. Although this new approach produces a similar end-result, it reaches this conclusion much faster than more commonly used algorithms. To test the effectiveness of the algorithm, White et al. studied how individual molecules of a chemical known as cAMP bind to parts of proteins called cyclic nucleotide binding domains (or CNDBs for short). A fluorescent tag was attached to single molecules of cAMP and data were collected on the behavior of each molecule. Previous evidence suggested that when four CNDBs join together to form a so-called tetramer complex, this affects the binding of cAMP. Using the DISC system, White et al. showed that individual cAMP molecules interact with all four domains in a similar way, suggesting that the binding of cAMP is not impacted by the formation of a tetramer complex. Analyzing this data took DISC less than 20 minutes compared to existing algorithms which took anywhere between four hours and two weeks to complete. The enhanced speed of the DISC algorithm could make it easier to analyze much larger datasets from other techniques in addition to fluorescence. This means that a greater number of states can be sampled, providing a deeper insight into the inner workings of biological and chemical processes.

Optical monitoring of polymerizations in droplets with high temporal dynamic range.

The ability to optically monitor a chemical reaction and generate an in situ readout is an important enabling technology, with applications ranging from the monitoring of reactions in flow, to the critical assessment step for combinatorial screening, to mechanistic studies on single reactant and catalyst molecules. Ideally, such a method would be applicable to many polymers and not require only a specific monomer for readout. It should also be applicable if the reactions are carried out in microdroplet chemical reactors, which offer a route to massive scalability in combinatorial searches. We describe a convenient optical method for monitoring polymerization reactions, fluorescence polarization anisotropy monitoring, and show that it can be applied in a robotically generated microdroplet. Further, we compare our method to an established optical reaction monitoring scheme, the use of Aggregation-Induced Emission (AIE) dyes, and find the two monitoring schemes offer sensitivity to different temporal regimes of the polymerization, meaning that the combination of the two provides an increased temporal dynamic range. Anisotropy is sensitive at early times, suggesting it will be useful for detecting new polymerization "hits" in searches for new reactivity, while the AIE dye responds at longer times, suggesting it will be useful for detecting reactions capable of reaching higher molecular weights.

Exploiting chemistry and molecular systems for quantum information science.

The power of chemistry to prepare new molecules and materials has driven the quest for new approaches to solve problems having global societal impact, such as in renewable energy, healthcare and information science. In the latter case, the intrinsic quantum nature of the electronic, nuclear and spin degrees of freedom in molecules offers intriguing new possibilities to advance the emerging field of quantum information science. In this Perspective, which resulted from discussions by the co-authors at a US Department of Energy workshop held in November 2018, we discuss how chemical systems and reactions can impact quantum computing, communication and sensing. Hierarchical molecular design and synthesis, from small molecules to supramolecular assemblies, combined with new spectroscopic probes of quantum coherence and theoretical modelling of complex systems, offer a broad range of possibilities to realize practical quantum information science applications.

Elucidating Energy Pathways through Simultaneous Measurement of Absorption and Transmission in a Coupled Plasmonic-Photonic Cavity.

Control of light-matter interactions is central to numerous advances in quantum communication, information, and sensing. The relative ease with which interactions can be tailored in coupled plasmonic-photonic systems makes them ideal candidates for investigation. To exert control over the interaction between photons and plasmons, it is essential to identify the underlying energy pathways which influence the system's dynamics and determine the critical system parameters, such as the coupling strength and dissipation rates. However, in coupled systems which dissipate energy through multiple competing pathways, simultaneously resolving all parameters from a single experiment is challenging as typical observables such as absorption and scattering each probe only a particular path. In this work, we simultaneously measure both photothermal absorption and two-sided optical transmission in a coupled plasmonic-photonic resonator consisting of plasmonic gold nanorods deposited on a toroidal whispering-gallery-mode optical microresonator. We then present an analytical model which predicts and explains the distinct line shapes observed and quantifies the contribution of each system parameter. By combining this model with experiment, we extract all system parameters with a dynamic range spanning 9 orders of magnitude. Our combined approach provides a full description of plasmonic-photonic energy dynamics in a weakly coupled optical system, a necessary step for future applications that rely on tunability of dissipation and coupling.

Extended Range of Dipole-Dipole Interactions in Periodically Structured Photonic Media.

The interaction between quantum two-level systems is typically short range in free space and in most photonic environments. We show that diminishing momentum isosurfaces with equal frequencies can create a significantly extended range of interaction between distant quantum systems. The extended range is robust and does not rely on a specific location or orientation of the transition dipoles. A general relation between the interaction range and properties of the isosurface is described for structured photonic media. It provides a new way to mediate long-range quantum behavior.

Migration dynamics of ovarian epithelial cells on micro-fabricated image-based models of normal and malignant stroma.

A profound remodeling of the collagen in the extracellular matrix (ECM) occurs in human ovarian cancer but it is unknown how this affects migration dynamics and ultimately tumor growth. Here, we investigate the influence of collagen morphology on ovarian cell migration through the use of second harmonic generation (SHG) image-based models of ovarian tumors. The scaffolds are fabricated by multiphoton excited (MPE) polymerization, where the process is akin to 3D printing except it achieves much greater resolution (∼0.5 µm) and utilizes collagen and collagen analogs. We used this technique to create scaffolds with complex 3D submicron features representing the collagen fiber morphology in normal stroma, high risk stroma, benign tumors, and high grade ovarian tumors. We found the highly aligned malignant stromal structure promoted enhanced motility and also increased cell and f-Actin alignment relative to the other tissues. However, using models based on fiber crimping characteristics, we found cells seeded on linear fibers based on normal stromal models yielded the highest degree of alignment but least motility. These results show that both the fiber properties themselves and as well as their overall alignment govern the resulting migration dynamics. These models cannot be synthesized by other conventional fabrication methods and we suggest the MPE image-based fabrication method will enable a variety of studies in cancer biology. STATEMENT OF SIGNIFICANCE: The extracellular matrix collagen in ovarian cancer is highly remodeled but the consequences on cell function remain unknown. It is important to understand the operative cell matrix interactions, as this could lead to better prognostics and better prediction of therapeutic efficacy. We probe migration dynamics using high resolution (∼0.5 µm) multiphoton excited fabrication to synthesize scaffolds whose designs are derived directly from Second Harmonic Generation microscope images of the collagen in normal ovarian tissues as well as benign and malignant tumors. Collectively our results show the importance of the matrix morphology (fiber shape and alignment) on driving cell motility, cell shape and f-Actin alignment. These collagen-based models have complex fiber morphology and cannot be created by conventional fabrication technologies.

Toward Real-Time Monitoring and Control of Single Nanoparticle Properties with a Microbubble Resonator Spectrometer.

Optical microresonators have widespread application at the frontiers of nanophotonic technology, driven by their ability to confine light to the nanoscale and enhance light-matter interactions. Microresonators form the heart of a recently developed method for single-particle photothermal absorption spectroscopy, whereby the microresonators act as microscale thermometers to detect the heat dissipated by optically pumped, nonluminescent nanoscopic targets. However, translation of this technology to chemically dynamic systems requires a platform that is mechanically stable, solution compatible, and visibly transparent. We report microbubble absorption spectrometers as a versatile platform that meets these requirements. Microbubbles integrate a two-port microfluidic device within a whispering gallery mode microresonator, allowing for the facile exchange of chemical reagents within the resonator's interior while maintaining a solution-free environment on its exterior. We first leverage these qualities to investigate the photoactivated etching of single gold nanorods by ferric chloride, providing a method for rapid acquisition of spatial and morphological information about nanoparticles as they undergo chemical reactions. We then demonstrate the ability to control nanorod orientation within a microbubble through optically exerted torque, a promising route toward the construction of hybrid photonic-plasmonic systems. Critically, the reported platform advances microresonator spectrometer technology by permitting room-temperature, aqueous experimental conditions, which may be used for time-resolved single-particle experiments on non-emissive, nanoscale analytes engaged in catalytically and biologically relevant chemical dynamics.