Electrostatic Assemblies of Single-Walled Carbon Nanotubes and Sequence-Tunable Peptoid Polymers Detect a Lectin Protein and Its Target Sugars.

A primary limitation to real-time imaging of metabolites and proteins has been the selective detection of biomolecules that have no naturally occurring or stable molecular recognition counterparts. We present developments in the design of synthetic near-infrared fluorescent nanosensors based on the fluorescence modulation of single-walled carbon nanotubes (SWNTs) with select sequences of surface-adsorbed N-substituted glycine peptoid polymers. We assess the stability of the peptoid-SWNT nanosensor candidates under variable ionic strengths, protease exposure, and cell culture media conditions and find that the stability of peptoid-SWNTs depends on the composition and length of the peptoid polymer. From our library, we identify a peptoid-SWNT assembly that can detect lectin protein wheat germ agglutinin (WGA) with a sensitivity comparable to the concentration of serum proteins. To demonstrate the retention of nanosensor-bound protein activity, we show that WGA on the nanosensor produces an additional fluorescent signal modulation upon exposure to the lectin's target sugars, suggesting the lectin protein remains active and selectively binds its target sugars through ternary molecular recognition interactions relayed to the nanosensor. Our results inform design considerations for developing synthetic molecular recognition elements by assembling peptoid polymers on SWNTs and also demonstrate these assemblies can serve as optical nanosensors for lectin proteins and their target sugars. Together, these data suggest certain peptoid sequences can be assembled with SWNTs to serve as versatile optical probes to detect proteins and their molecular substrates.

Chemometric Approaches for Developing Infrared Nanosensors To Image Anthracyclines.

Generation, identification, and validation of optical probes to image molecular targets in a biological milieu remain a challenge. Synthetic molecular recognition approaches leveraging the intrinsic near-infrared fluorescence of single-walled carbon nanotubes are promising for long-term biochemical imaging in tissues. However, generation of nanosensors for selective imaging of molecular targets requires a heuristic approach. Here, we present a chemometric platform for rapidly screening libraries of candidate single-walled carbon nanotube nanosensors against biochemical analytes to quantify the fluorescence response to small molecules, including vitamins, neurotransmitters, and chemotherapeutics. We further show this method can be applied to identify biochemical analytes that selectively modulate the intrinsic near-infrared fluorescence of candidate nanosensors. Chemometric analysis thus enables identification of nanosensor-analyte "hits" and also nanosensor fluorescence signaling modalities such as wavelength shifts that are optimal for translation to biological imaging. Through this approach, we identify and characterize a nanosensor for the chemotherapeutic anthracycline doxorubicin (DOX), which provides a ≤17 nm fluorescence red-shift and exhibits an 8 µM limit of detection, compatible with peak circulatory concentrations of doxorubicin common in therapeutic administration. We demonstrate the selectivity of this nanosensor over dacarbazine, a chemotherapeutic commonly co-injected with doxorubicin. Lastly, we establish nanosensor tissue compatibility for imaging of doxorubicin in muscle tissue by incorporating nanosensors into the mouse hindlimb and measuring the nanosensor response to exogenous DOX administration. Our results motivate chemometric approaches to nanosensor discovery for chronic imaging of drug partitioning into tissues and toward real-time monitoring of drug accumulation.

Changes in Spectra and Conformation of Hairpin DNA-Stabilized Silver Nanoclusters Induced by Stem Sequence Perturbations.

It is well-known that even small perturbations of the DNA sequence can drastically and unpredictably disrupt or alter the fluorescence of DNA-stabilized silver nanoclusters (DNA-AgNCs). Understanding how the structure of DNA affects the nanocluster that it stabilizes is the key to rationalizing such effects. We approach this challenge by strategically modifying the stem sequence of a hairpin DNA that hosts a spectrally pure, red-emitting nanocluster. Most of our modifications (base composition, sequence orientation, and loop location) reduce AgNC fluorescence in purity and shift it in wavelength, but one modification (appending poly(thymidine) to the 3' end of the stem) is inert with respect to fluorescence. Microfluidic capillary electrophoresis reveals that all of the modifications induce conformational changes of the DNA and that the original, spectrally pure nanocluster exists in two structurally distinct conformations. Interestingly, appending five or more thymidines, despite having no effect on fluorescence, eliminates this structural degeneracy. To explain this result, we propose that the original spectrally pure cluster is stabilized by a pair of hairpins whose stems can arrange in either a cis or trans orientation. Finally, we quantify the extent to which thymidine appendages of different lengths can be used to fine-tune the electrophoretic mobility of DNA-AgNC.

Hybridization thermodynamics of DNA oligonucleotides during microchip capillary electrophoresis.

Capillary electrophoresis (CE) is a powerful analytical tool for performing separations and characterizing properties of charged species. For reacting species during a CE separation, local concentrations change leading to nonequilibrium conditions. Interpreting experimental data with such nonequilibrium reactive species is nontrivial due to the large number of variables involved in the system. In this work we develop a COMSOL multiphysics-based numerical model to simulate the electrokinetic mass transport of short interacting ssDNAs in microchip capillary electrophoresis. We probe the importance of the dissociation constant, K(D), and the concentration of DNA on the resulting observed mobility of the dsDNA peak, µ(w), by using a full sweep of parametric simulations. We find that the observed mobility is strongly dependent on the DNA concentration and K(D), as well as ssDNA concentration, and develop a relation with which to understand this dependence. Furthermore, we present experimental microchip capillary electrophoresis measurements of interacting 10 base ssDNA and its complement with changes in buffer ionic strength, DNA concentration, and DNA sequence to vary the system equilibria. We then compare our results to thermodynamically calculated K(D) values.

Fluorescent silver nanocluster DNA probes for multiplexed detection using microfluidic capillary electrophoresis.

DNA-stabilized fluorescent silver nanoclusters (AgNC DNA) are a new class of fluorophore that are formed by sequence specific interactions between silver and single-stranded DNA. By incorporating both target-binding and fluorescent-reporting sequences into a single synthetic DNA oligomer, AgNC DNA probes eliminate the need to conjugate dye or quencher molecules. In this study, we modify a AgNC DNA probe to demonstrate single-color multiplexed detection of DNA targets. We show that appending different lengths of poly-dT to the probe sequences tunes the electrophoretic mobility of AgNC DNA probes without affecting their fluorescence spectra. We use this to introduce a set of AgNC DNA probes selective for Hepatitis A, B and C target sequences that can be processed together in a simple, single-step protocol and distinguished with a resolution of 3.47 and signal to noise ratio of 17.23 in under 10 seconds by microfluidic capillary electrophoresis.

Supervised learning model predicts protein adsorption to carbon nanotubes.

Engineered nanoparticles are advantageous for biotechnology applications including biomolecular sensing and delivery. However, testing compatibility and function of nanotechnologies in biological systems requires a heuristic approach, where unpredictable protein corona formation prevents their effective implementation. We develop a random forest classifier trained with mass spectrometry data to identify proteins that adsorb to nanoparticles based solely on the protein sequence (78% accuracy, 70% precision). We model proteins that populate the corona of a single-walled carbon nanotube (SWCNT)­based nanosensor and study the relationship between the protein's amino acid­based properties and binding capacity. Protein features associated with increased likelihood of SWCNT binding include high content of solvent-exposed glycines and nonsecondary structure­associated amino acids. To evaluate its predictive power, we apply the classifier to identify proteins with high binding affinity to SWCNTs, with experimental validation. The developed classifier provides a step toward undertaking the otherwise intractable problem of predicting protein-nanoparticle interactions.

Synthetic nanosensors for imaging neuromodulators.

Neuromodulation plays a critical role in regulating brain function and its dysregulation is implicated in the pathogenesis of numerous neurological and psychiatric disorders. However, only in the last few years have optical tools become available to probe the spatial and temporal profiles of neuromodulator signaling, including dopamine, with the requisite resolution to uncover mechanisms of neuromodulation. In this review, we summarize the current state of synthetic nanomaterial-based optical nanosensors for monitoring neurotransmission with high spatial and temporal resolution. Specifically, we highlight how synthetic nanosensors can elucidate the spatial distribution of neuromodulator release sites and report the temporal dynamics and spatial diffusion of neuromodulator release. Next, we outline advantages and limitations of currently available nanosensors and their recent application to imaging endogenous dopamine release in brain tissue. Finally, we discuss strategies to improve nanosensors for in vivo use, with implications for translational applications.

Near-infrared catecholamine nanosensors for high spatiotemporal dopamine imaging.

Dopamine neuromodulation of neural synapses is a process implicated in a number of critical brain functions and diseases. Development of protocols to visualize this dynamic neurochemical process is essential to understanding how dopamine modulates brain function. We have developed a non-genetically encoded, near-IR (nIR) catecholamine nanosensor (nIRCat) capable of identifying ~2-µm dopamine release hotspots in dorsal striatal brain slices. nIRCat is readily synthesized through sonication of single walled carbon nanotubes with DNA oligos, can be readily introduced into both genetically tractable and intractable organisms and is compatible with a number of dopamine receptor agonists and antagonists. Here we describe the synthesis, characterization and implementation of nIRCat in acute mouse brain slices. We demonstrate how nIRCat can be used to image electrically or optogenetically stimulated dopamine release, and how these procedures can be leveraged to study the effects of dopamine receptor pharmacology. In addition, we provide suggestions for building or adapting wide-field microscopy to be compatible with nIRCat nIR fluorescence imaging. We discuss strategies for analyzing nIR video data to identify dopamine release hotspots and quantify their kinetics. This protocol can be adapted and implemented for imaging other neuromodulators by using probes of this class and can be used in a broad range of species without genetic manipulation. The synthesis and characterization protocols for nIRCat take ~5 h, and the preparation and fluorescence imaging of live brain slices by using nIRCats require ~6 h.

Mitigation of Carbon Nanotube Neurosensor Induced Transcriptomic and Morphological Changes in Mouse Microglia with Surface Passivation.

Single-walled carbon nanotubes (SWCNT) are used in neuroscience for deep-brain imaging, neuron activity recording, measuring brain morphology, and imaging neuromodulation. However, the extent to which SWCNT-based probes impact brain tissue is not well understood. Here, we study the impact of (GT)6-SWCNT dopamine nanosensors on SIM-A9 mouse microglial cells and show SWCNT-induced morphological and transcriptomic changes in these brain immune cells. Next, we introduce a strategy to passivate (GT)6-SWCNT nanosensors with PEGylated phospholipids to improve both biocompatibility and dopamine imaging quality. We apply these passivated dopamine nanosensors to image electrically stimulated striatal dopamine release in acute mouse brain slices, and show that slices labeled with passivated nanosensors exhibit higher fluorescence response to dopamine and measure more putative dopamine release sites. Hence, this facile modification to SWCNT-based dopamine probes provides immediate improvements to both biocompatibility and dopamine imaging functionality with an approach that is readily translatable to other SWCNT-based neurotechnologies.

High-throughput evolution of near-infrared serotonin nanosensors.

Imaging neuromodulation with synthetic probes is an emerging technology for studying neurotransmission. However, most synthetic probes are developed through conjugation of fluorescent signal transducers to preexisting recognition moieties such as antibodies or receptors. We introduce a generic platform to evolve synthetic molecular recognition on the surface of near-infrared fluorescent single-wall carbon nanotube (SWCNT) signal transducers. We demonstrate evolution of molecular recognition toward neuromodulator serotonin generated from large libraries of ~6.9 × 1010 unique ssDNA sequences conjugated to SWCNTs. This probe is reversible and produces a ~200% fluorescence enhancement upon exposure to serotonin with a K d = 6.3 µM, and shows selective responsivity over serotonin analogs, metabolites, and receptor-targeting drugs. Furthermore, this probe remains responsive and reversible upon repeat exposure to exogenous serotonin in the extracellular space of acute brain slices. Our results suggest that evolution of nanosensors could be generically implemented to develop other neuromodulator probes with synthetic molecular recognition.

Imaging striatal dopamine release using a nongenetically encoded near infrared fluorescent catecholamine nanosensor.

Neuromodulation plays a critical role in brain function in both health and disease, and new tools that capture neuromodulation with high spatial and temporal resolution are needed. Here, we introduce a synthetic catecholamine nanosensor with fluorescent emission in the near infrared range (1000-1300 nm), near infrared catecholamine nanosensor (nIRCat). We demonstrate that nIRCats can be used to measure electrically and optogenetically evoked dopamine release in brain tissue, revealing hotspots with a median size of 2 µm. We also demonstrated that nIRCats are compatible with dopamine pharmacology and show D2 autoreceptor modulation of evoked dopamine release, which varied as a function of initial release magnitude at different hotspots. Together, our data demonstrate that nIRCats and other nanosensors of this class can serve as versatile synthetic optical tools to monitor neuromodulatory neurotransmitter release with high spatial resolution.

Advances in Nanomaterials for Brain Microscopy.

Microscopic imaging of the brain continues to reveal details of its structure, connectivity, and function. To further improve our understanding of the emergent properties and functions of neural circuits, new methods are necessary to directly visualize the relationship between brain structure, neuron activity, and neurochemistry. Advances in engineering the chemical and optical properties of nanomaterials concurrent with developments in deep-tissue microscopy hold tremendous promise for overcoming the current challenges associated with in vivo brain imaging, particularly for imaging the brain through optically-dense brain tissue, skull, and scalp. To this end, developments in nanomaterials offer much promise toward implementing tunable chemical functionality for neurochemical targeting and sensing, and fluorescence stability for long-term imaging. In this review, we summarize current brain microscopy methods and describe the diverse classes of nanomaterials recently leveraged as contrast agents and functional probes for microscopic optical imaging of the brain.

A universal design for a DNA probe providing ratiometric fluorescence detection by generation of silver nanoclusters.

DNA-stabilized silver nanoclusters (AgNCs), the fluorescence emission of which can rival that of typical organic fluorophores, have made possible a new class of label-free molecular beacons for the detection of single-stranded DNA. Like fluorophore-quencher molecular beacons (FQ-MBs) AgNC-based molecular beacons (AgNC-MBs) are based on a single-stranded DNA that undergoes a conformational change upon binding a target sequence. The new conformation exposes a stretch of single-stranded DNA capable of hosting a fluorescent AgNC upon reduction in the presence of Ag(+) ions. The utility of AgNC-MBs has been limited, however, because changing the target binding sequence unpredictably alters cluster fluorescence. Here we show that the original AgNC-MB design depends on bases in the target-binding (loop) domain to stabilize its AgNC. We then rationally alter the design to overcome this limitation. By separating and lengthening the AgNC-stabilizing domain, we create an AgNC-hairpin probe with consistent performance for arbitrary target sequence. This new design supports ratiometric fluorescence measurements of DNA target concentration, thereby providing a more sensitive, responsive and stable signal compared to turn-on AgNC probes. Using the new design, we demonstrate AgNC-MBs with nanomolar sensitivity and singe-nucleotide specificity, expanding the breadth of applicability of these cost-effective probes for biomolecular detection.