Ultralarge Modulation of Fluorescence by Neuromodulators in Carbon Nanotubes Functionalized with Self-Assembled Oligonucleotide Rings

Sequence-Dependent Surface Coverage of ssDNA Coatings on Single-Wall Carbon Nanotubes

A combination of experimental measurements and molecular dynamics (MD) simulations was used to investigate how the surfaces of single-wall carbon nanotubes (SWCNTs) are covered by adsorbed ssDNA oligos with different base compositions and lengths. By analyzing the UV absorption spectra of ssDNA-coated SWCNTs before and after coating displacement by a transparent surfactant, the mass ratios of adsorbed ssDNA to SWCNTs were determined for poly-T, poly-C, GT-containing, and AT-containing ssDNA oligos. Based on the measured mass ratios, it is estimated that an average of 20, 22, 26, or 32 carbon atoms are covered by one adsorbed thymine, cytosine, adenine, or guanine nucleotide, respectively. In addition, the UV spectra revealed electronic interactions of varying strengths between the nucleobase aromatic rings and the nanotube π-systems. Short poly-T DNA oligos show stronger π-π stacking interactions with SWCNT surfaces than do short poly-C DNA oligos, whereas both long poly-C and poly-T DNA oligos show strong interactions. These experiments were complemented by MD computations on simulated systems that were constrained to match the measured ssDNA/SWCNT mass ratios. The surface coverages computed from the MD results varied with oligo composition in a pattern that correlates higher measured yields of nanotube fluorescence with greater surface coverage.

Near-infrared nanosensors enable optical imaging of oxytocin with selectivity over vasopressin in acute mouse brain slices

Oxytocin plays a critical role in regulating social behaviors, yet our understanding of its function in both neurological health and disease remains incomplete. Real-time oxytocin imaging probes with spatiotemporal resolution relevant to its endogenous signaling are required to fully elucidate oxytocin's role in the brain. Herein, we describe a near-infrared oxytocin nanosensor (nIROXT), a synthetic probe capable of imaging oxytocin in the brain without interference from its structural analogue, vasopressin. nIROXT leverages the inherent tissue-transparent fluorescence of single-walled carbon nanotubes (SWCNT) and the molecular recognition capacity of an oxytocin receptor peptide fragment to selectively and reversibly image oxytocin. We employ these nanosensors to monitor electrically stimulated oxytocin release in brain tissue, revealing oxytocin release sites with a median size of 3 µm in the paraventricular nucleus of C57BL/6 mice, which putatively represents the spatial diffusion of oxytocin from its point of release. These data demonstrate that covalent SWCNT constructs, such as nIROXT, are powerful optical tools that can be leveraged to measure neuropeptide release in brain tissue.

Systematic Selection of High-Affinity ssDNA Sequences to Carbon Nanotubes

Single-walled carbon nanotubes (SWCNTs) have gained significant interest for their potential in biomedicine and nanoelectronics. The functionalization of SWCNTs with single-stranded DNA (ssDNA) enables the precise control of SWCNT alignment and the development of optical and electronic biosensors. This study addresses the current gaps in the field by employing high-throughput systematic selection, enriching high-affinity ssDNA sequences from a vast random library. Specific base compositions and patterns are identified that govern the binding affinity between ssDNA and SWCNTs. Molecular dynamics simulations validate the stability of ssDNA conformations on SWCNTs and reveal the pivotal role of hydrogen bonds in this interaction. Additionally, it is demonstrated that machine learning could accurately distinguish high-affinity ssDNA sequences, providing an accessible model on a dedicated webpage (http://service.k-medai.com/ssdna4cnt). These findings open new avenues for high-affinity ssDNA-SWCNT constructs for stable and sensitive molecular detection across diverse scientific disciplines.

Predicting Serotonin Detection with DNA-Carbon Nanotube Sensors across Multiple Spectral Wavelengths

Owing to the value of DNA-wrapped single-walled carbon nanotube (SWNT)-based sensors for chemically specific imaging in biology, we explore machine learning (ML) predictions DNA-SWNT serotonin sensor responsivity as a function of DNA sequence based on the whole SWNT fluorescence spectra. Our analysis reveals the crucial role of DNA sequence in the binding modes of DNA-SWNTs to serotonin, with a smaller influence of SWNT chirality. Regression ML models trained on existing data sets predict the change in the fluorescence emission in response to serotonin, ΔF/F, at over a hundred wavelengths for new DNA-SWNT conjugates, successfully identifying some high- and low-response DNA sequences. Despite successful predictions, we also show that the finite size of the training data set leads to limitations on prediction accuracy. Nevertheless, incorporating entire spectra into ML models enhances prediction robustness and facilitates the discovery of novel DNA-SWNT sensors. Our approaches show promise for identifying new chemical systems with specific sensing response characteristics, marking a valuable advancement in DNA-based system discovery.

Monitoring Enzyme Activity Using Near-Infrared Fluorescent Single-Walled Carbon Nanotubes

Enzymes serve as pivotal biological catalysts that accelerate essential chemical reactions, thereby influencing a variety of physiological processes. Consequently, the monitoring of enzyme activity and inhibition not only yields crucial insights into health and disease conditions but also forms the basis of research in drug discovery, toxicology, and the understanding of disease mechanisms. In this context, near-infrared (NIR) fluorescent single-walled carbon nanotubes (SWCNTs) have emerged as effective tools for tracking enzyme activity and inhibition through diverse strategies. This perspective explores the physicochemical attributes of SWCNTs that render them well-suited for such monitoring. Additionally, we delve into the various strategies developed so far for successfully monitoring enzyme activity and inhibition, emphasizing the distinctive features of each principle. Furthermore, we contrast the benefits of SWCNT-based NIR probes with conventional gold standards in monitoring enzyme activity. Lastly, we highlight the current challenges faced in this field and suggest potential solutions to propel it forward. This perspective aims to contribute to the ongoing progress in biodiagnostics and seeks to engage the wider community in developing and applying enzymatic assays using SWCNTs.

Carbon Nanomaterial Fluorescent Probes and Their Biological Applications

Fluorescent carbon nanomaterials have broadly useful chemical and photophysical attributes that are conducive to applications in biology. In this review, we focus on materials whose photophysics allow for the use of these materials in biomedical and environmental applications, with emphasis on imaging, biosensing, and cargo delivery. The review focuses primarily on graphitic carbon nanomaterials including graphene and its derivatives, carbon nanotubes, as well as carbon dots and carbon nanohoops. Recent advances in and future prospects of these fields are discussed at depth, and where appropriate, references to reviews pertaining to older literature are provided.

Mapping the Morphology of DNA on Carbon Nanotubes in Solution Using X-ray Scattering Interferometry

Single-walled carbon nanotubes (SWCNTs) with adsorbed single-stranded DNA (ssDNA) are applied as sensors to investigate biological systems, with potential applications ranging from clinical diagnostics to agricultural biotechnology. Unique ssDNA sequences render SWCNTs selectively responsive to target analytes such as (GT)n-SWCNTs recognizing the neuromodulator, dopamine. It remains unclear how the ssDNA conformation on the SWCNT surface contributes to functionality, as observations have been limited to computational models or experiments under dehydrated conditions that differ substantially from the aqueous biological environments in which the nanosensors are applied. We demonstrate a direct mode of measuring in-solution ssDNA geometries on SWCNTs via X-ray scattering interferometry (XSI), which leverages the interference pattern produced by AuNP tags conjugated to ssDNA on the SWCNT surface. We employ XSI to quantify distinct surface-adsorbed morphologies for two (GT)n ssDNA oligomer lengths (n = 6, 15) that are used on SWCNTs in the context of dopamine sensing and measure the ssDNA conformational changes as a function of ionic strength and during dopamine interaction. We show that the shorter oligomer, (GT)6, adopts a more periodically ordered ring structure along the SWCNT axis (inter-ssDNA distance of 8.6 ± 0.3 nm), compared to the longer (GT)15 oligomer (most probable 5'-to-5' distance of 14.3 ± 1.1 nm). During molecular recognition, XSI reveals that dopamine elicits simultaneous axial elongation and radial constriction of adsorbed ssDNA on the SWCNT surface. Our approach using XSI to probe solution-phase morphologies of polymer-functionalized SWCNTs can be applied to yield insights into sensing mechanisms and inform future design strategies for nanoparticle-based sensors.

Nitric Oxide Detection Using a Corona Phase Molecular Recognition Site on Chiral Single-Walled Carbon Nanotubes

Semiconducting single-walled carbon nanotubes (s-SWCNT) are structures that fluoresce in the near-infrared region. By coating SWCNT surfaces with polymeric materials such as single-chain DNA, changes in fluorescence emission occur in the presence of reagents. In this way, polymer-coated SWCNT structures allow them to be used as optical sensors for single molecule detection. Especially today, the inadequacy of the methods used in the detection of cellular molecules makes the early diagnosis of diseases such as cancer difficult at the single-molecule level. In this study, the detection of nitric oxide (NO) signals, which are a marker of cancer, was carried out at the single-molecule level. In this context, a sensor structure was formed by coating the 7,6-chiral s-SWCNT surface with ssDNA with different oligonucleotide lengths (AT). The sensor structure was characterized by using UV-vis spectroscopy and Raman spectroscopy microscopy. After formation of the sensor structure, a selectivity library was created using various molecules. As a result of the coating of the SWCNT (7,6) surface with DNA corona phase formation, Raman peaks at 195 and 276 cm-1 were observed to shift to the right. Additionally, the selectivity library results showed that the (AT)30 sequence can be used in NO detection. As a result of the studies using SWCNT (7.6)- (AT)30, the limit of detection (LOD) and limit of determination (LOQ) values of the sensor against NO were found to be 1.24 and 4.13 μM, respectively.

A Photoactivatable Norepinephrine for Probing Adrenergic Neural Circuits

Norepinephrine (NE) is a critical neuromodulator that mediates a wide range of behavior and neurophysiology, including attention, arousal, plasticity, and memory consolidation. A major source of NE is the brainstem nucleus the locus coeruleus (LC), which sends widespread projections throughout the central nervous system (CNS). Efforts to dissect this complex noradrenergic circuitry have driven the development of many tools that detect endogenous NE or modulate widespread NE release via LC activation and inhibition. While these tools have enabled research that elucidates physiological roles of NE, additional tools to probe these circuits with a higher degree of spatial precision could enable a finer delineation of function. Here, we describe the synthesis and chemical properties of a photo-activatable NE, [Ru(bpy) 2 (PMe 3 )(NE)]PF 6 (RuBi-NE). We validate the one-photon (1P) release of NE using whole-cell patch clamp electrophysiology in acute mouse brain slices containing the LC. We show that a 10 ms pulse of blue light, in the presence of RuBi-NE, briefly modulates the firing rate of LC neurons via α-2 adrenergic receptors. The development of a photo-activatable NE that can be released with light in the visible spectrum provides a new tool for fine-grained mapping of complex noradrenergic circuits, as well as the ability to probe how NE acts on non-neuronal cells in the CNS.

Detecting and differentiating neurotransmitters using ultraviolet plasmonic engineered native fluorescence

Detecting neurotransmitters with high sensitivity and selectivity is important to understand their roles in biological functions. Current detection methods for neurotransmitters suffer from poor sensitivity or selectivity. In this article, we propose ultraviolet (UV) plasmonic engineered native fluorescence as a new sensing mechanism to detect neurotransmitters with high sensitivity and selectivity. We measured the native fluorescence of three monoamine neurotransmitters, dopamine (DA), norepinephrine (NE), and 3,4-dihydroxyphenylacetic acid (DOPAC). The average net enhancement and total photon yield enhancement on an aluminum hole array with 300 nm hole spacing substrate were found to be 50× and 60×, for the three molecules. We also observed a 1.5-1.7× reduction in the dominant photon bleaching rate on an aluminum hole array compared to an aluminum-thin film substrate. The photobleaching rates of the native fluorescence of DA, NE and DOPAC were found to be highly sensitive to their molecular structures and can be further engineered by UV plasmonic substrates. The differences in the photobleaching rates for DA and NE were 2× and 1.6× larger on an aluminum thin film and an aluminum hole array than on a silicon substrate. As a proof-of-concept experiment, we mixed DA with NE at different concentration ratios and measured the average photobleaching rates of the mixture. We found that the average photobleaching rate is proportional to the concentration of NE in the mixture. Our findings demonstrate the potential of UV plasmonic engineered native fluorescence to achieve sensitive and selective detection of neurotransmitters.

Single-Walled Carbon Nanotube Sensor Selection for the Detection of MicroRNA Biomarkers for Acute Myocardial Infarction as a Case Study

MicroRNAs (miRNAs) are single-stranded non-coding short ribonucleic acid sequences that take part in many cellular and biological processes. Recent studies have shown that altered expression of miRNAs is involved in pathological processes, and they can thus be considered biomarkers for the early detection of various diseases. Here, we demonstrate a selection and elimination process of fluorescent single-walled carbon nanotube (SWCNT) sensors for miRNA biomarkers based on RNA-DNA hybridization with a complementary DNA recognition unit bound to the SWCNT surface. We use known miRNA biomarkers for acute myocardial infarction (AMI), commonly known as a heart attack, as a case study. We have selected five possible miRNA biomarkers which are selective and specific to AMI and tested DNA-SWCNT sensor candidates with the target DNA and RNA sequences in different environments. Out of these five miRNA sensors, three could recognize the complementary DNA or RNA sequence in a buffer, showing fluorescence modulation of the SWCNT in response to the target sequence. Out of the three working sensors in buffer, only one could function in serum and was selected for further testing. The chosen sensor, SWCNT-miDNA208a, showed high specificity and selectivity toward the target sequence, with better performance in serum compared to a buffer environment. The SWCNT sensor selection pipeline highlights the importance of testing sensor candidates in the appropriate environment and can be extended to other libraries of biomarkers.

Identifying Neural Signatures of Dopamine Signaling with Machine Learning

The emergence of new tools to image neurotransmitters, neuromodulators, and neuropeptides has transformed our understanding of the role of neurochemistry in brain development and cognition, yet analysis of this new dimension of neurobiological information remains challenging. Here, we image dopamine modulation in striatal brain tissue slices with near-infrared catecholamine nanosensors (nIRCat) and implement machine learning to determine which features of dopamine modulation are unique to changes in stimulation strength, and to different neuroanatomical regions. We trained a support vector machine and a random forest classifier to decide whether the recordings were made from the dorsolateral striatum (DLS) versus the dorsomedial striatum (DMS) and find that machine learning is able to accurately distinguish dopamine release that occurs in DLS from that occurring in DMS in a manner unachievable with canonical statistical analysis. Furthermore, our analysis determines that dopamine modulatory signals including the number of unique dopamine release sites and peak dopamine released per stimulation event are most predictive of neuroanatomy. This is in light of integrated neuromodulator amount being the conventional metric used to monitor neuromodulation in animal studies. Lastly, our study finds that machine learning discrimination of different stimulation strengths or neuroanatomical regions is only possible in adult animals, suggesting a high degree of variability in dopamine modulatory kinetics during animal development. Our study highlights that machine learning could become a broadly utilized tool to differentiate between neuroanatomical regions or between neurotypical and disease states, with features not detectable by conventional statistical analysis.

Characterizing the Interactions of Cell-Membrane-Disrupting Peptides with Lipid-Functionalized Single-Walled Carbon Nanotubes

Lipid-functionalized single-walled carbon nanotubes (SWNTs) have garnered significant interest for their potential use in a wide range of biomedical applications. In this work, we used molecular dynamics simulations to study the equilibrium properties of SWNTs surrounded by the phosphatidylcholine (POPC) corona phase and their interactions with three cell membrane disruptor peptides: colistin, TAT peptide, and crotamine-derived peptide. Our results show that SWNTs favor asymmetrical positioning within the POPC corona, so that one side of the SWNT, covered by the thinnest part of the corona, comes in contact with charged and polar functional groups of POPC and water. We also observed that colistin and TAT insert deeply into the POPC corona, while crotamine-derived peptide only adsorbs to the corona surface. In separate simulations, we show that three examined peptides exhibit similar insertion and adsorption behaviors when interacting with POPC bilayers, confirming that peptide-induced perturbations to POPC in conjugates and bilayers are similar in nature and magnitude. Furthermore, we observed correlations between the peptide-induced structural perturbations and the near-infrared emission of the lipid-functionalized SWNTs, which suggest that the optical signal of the conjugates transduces the morphological changes in the lipid corona. Overall, our findings indicate that lipid-functionalized SWNTs could serve as simplified cell membrane model systems for prescreening of new antimicrobial compounds that disrupt cell membranes.

Characterizing the Interactions of Cell Membrane-Disrupting Peptides with Lipid-Functionalized Single-Walled Carbon Nanotube Systems for Antimicrobial Screening

Lipid-functionalized single-walled carbon nanotubes (SWNTs) have garnered significant interest for their potential use in a wide range of biomedical applications. In this work, we used molecular dynamics simulations to study the equilibrium properties of SWNTs surrounded by the phosphatidylcholine (POPC) corona phase, and their interactions with three cell membrane disruptor peptides: colistin, TAT peptide, and crotamine-derived peptide. Our results show that SWNTs favor asymmetrical positioning within the POPC corona, so that one side of the SWNT, covered by the thinnest part of the corona, comes in contact with charged and polar functional groups of POPC and water. We also observed that colistin and TAT insert deeply into POPC corona, while crotamine-derived peptide only adsorbs to the corona surface. Compared to crotamine-derived peptide, colistin and TAT also induce larger perturbations in the thinnest region of the corona, by allowing more water molecules to directly contact the SWNT surface. In separate simulations, we show that three examined peptides exhibit similar insertion and adsorption behaviors when interacting with POPC bilayers, confirming that peptide-induced perturbations to POPC in conjugates and bilayers are similar in nature and magnitude. Furthermore, we observed correlations between the peptide-induced structural perturbations and the near-infrared emission of the lipid-functionalized SWNTs, which suggest that the optical signal of the conjugates transduces the morphological changes in the lipid corona. Overall, our findings indicate that lipid-functionalized SWNTs could serve as simplified cell membrane model systems for pre-screening of new antimicrobial compounds that disrupt cell membranes.

Compositional Analysis of ssDNA-Coated Single-Wall Carbon Nanotubes through UV Absorption Spectroscopy

Aqueous suspensions of single-wall carbon nanotubes (SWCNTs) coated by ssDNA are analyzed using UV absorption and total carbon measurements. The results give absolute average concentrations of both components in samples without free ssDNA. From those values, the average mid-UV SWCNT absorptivity is deduced for three different batches of relatively small diameter nanotubes: two HiPco and one CoMoCAT. The absorptivity values enable the use of simple spectrophotometry to measure absolute concentrations of similar SWCNT samples in aqueous SDS. The results also quantify the mass ratio of ssDNA to SWCNT, defining the average number of nanotube carbon atoms suspended by one ssDNA strand of T₁₅GT₁₅ or T₃₀G. Comparing this experimental parameter with results from replica exchange molecular dynamics simulations of one ssDNA strand freely adsorbed on a (6,5) segment shows close agreement between the computed number of SWCNT atoms covered per strand and the measured number of SWCNT atoms suspended per strand.

Visualizing synaptic dopamine efflux with a 2D composite nanofilm

Chemical neurotransmission constitutes one of the fundamental modalities of communication between neurons. Monitoring release of these chemicals has traditionally been difficult to carry out at spatial and temporal scales relevant to neuron function. To understand chemical neurotransmission more fully, we need to improve the spatial and temporal resolutions of measurements for neurotransmitter release. To address this, we engineered a chemi-sensitive, two-dimensional composite nanofilm that facilitates visualization of the release and diffusion of the neurochemical dopamine with synaptic resolution, quantal sensitivity, and simultaneously from hundreds of release sites. Using this technology, we were able to monitor the spatiotemporal dynamics of dopamine release in dendritic processes, a poorly understood phenomenon. We found that dopamine release is broadcast from a subset of dendritic processes as hotspots that have a mean spatial spread of ≈ 3.2 µm (full width at half maximum [FWHM]) and are observed with a mean spatial frequency of one hotspot per ≈ 7.5 µm of dendritic length. Major dendrites of dopamine neurons and fine dendritic processes, as well as dendritic arbors and dendrites with no apparent varicose morphology participated in dopamine release. Remarkably, these release hotspots co-localized with Bassoon, suggesting that Bassoon may contribute to organizing active zones in dendrites, similar to its role in axon terminals.

To form the vast and complex network necessary for an organism to sense and react to the world, neurons must connect at highly specialized junctions. Individual cells communicate at these ‘synapses’ by releasing chemical signals (or neurotransmitters) such as dopamine, a molecule involved in learning and motivation.

Despite the central role that synapses play in the brain, it remains challenging to measure exactly where neurotransmitters are released and how far they travel from their release site. Currently, most tools available to scientists only allow bulk measurements of neurotransmitter release.

To tackle this limitation, Bulumulla et al. developed a new way to measure neurotransmitter release from neurons, harnessing a technique which uses fluorescent nanosensors that glow brighter when exposed to dopamine. These sensors form a very thin film upon which neurons can grow; when the cells release dopamine, the sensors ‘light up’ as they encounter the molecule. Dubbed DopaFilm, the technology reveals exactly where the neurotransmitter comes from and how it spreads between cells in real time. In particular, the approach showed that dopamine emerges from 'hot spots' at specific sites in cells; it also helped Bulumulla et al. study how dopamine is released from subcellular compartments that have previously not been well characterized.

Improving the sensors so that the film could detect other neurotransmitters besides dopamine would broaden the use of this approach. In the future, combining this technology with other types of imaging should enable studies of individual synapses with intricate detail.

Aggregation Reduces Subcellular Localization and Cytotoxicity of Single-Walled Carbon Nanotubes

The non-covalent biomolecular functionalization of fluorescent single-walled carbon nanotubes (SWCNTs) has resulted in numerous in vitro and in vivo sensing and imaging applications due to many desirable optical properties. In these applications, it is generally presumed that pristine, singly dispersed SWCNTs interact with and enter live cells at the so-called nano-biointerface, for example, the cell membrane. Despite numerous fundamental studies published on this presumption, it is known that nanomaterials have the propensity to aggregate in protein-containing environments before ever contacting the nano-biointerface. Here, using DNA-functionalized SWCNTs with defined degrees of aggregation as well as near-infrared hyperspectral microscopy and toxicological assays, we show that despite equal rates of internalization, initially aggregated SWCNTs do not further accumulate within individual subcellular locations. In addition to subcellular accumulations, SWCNTs initially with a low degree of aggregation can induce significant deleterious effects in various long-term cytotoxicity and real-time proliferation assays, which are markedly different when compared to those of SWCNTs that are initially aggregated. These findings suggest the importance of the aggregation state as a critical component related to intracellular processing and toxicological response of engineered nanomaterials.

Biosensing with Fluorescent Carbon Nanotubes

Biosensors are powerful tools for modern basic research and biomedical diagnostics. Their development requires substantial input from the chemical sciences. Sensors or probes with an optical readout, such as fluorescence, offer rapid, minimally invasive sensing of analytes with high spatial and temporal resolution. The near‐infrared (NIR) region is beneficial because of the reduced background and scattering of biological samples (tissue transparency window) in this range. In this context, single‐walled carbon nanotubes (SWCNTs) have emerged as versatile NIR fluorescent building blocks for biosensors. Here, we provide an overview of advances in SWCNT‐based NIR fluorescent molecular sensors. We focus on chemical design strategies for diverse analytes and summarize insights into the photophysics and molecular recognition. Furthermore, different application areas are discussed—from chemical imaging of cellular systems and diagnostics to in vivo applications and perspectives for the future.

Guanine-Specific Chemical Reaction Reveals ssDNA Interactions on Carbon Nanotube Surfaces

Understanding the conformations of physisorbed single-stranded DNA (ssDNA) oligos on single-wall carbon nanotube (SWCNT) surfaces is important for advancing basic nanoscience and for developing applications in biomedicine and quantum information processing. Here we report evidence that the ssDNA strands are partly desorbed from the nanotube surface under common conditions. SWCNT suspensions were prepared in eight ssDNA oligos, each containing 1 guanine and 30 thymine bases but differing in the position of the guanine within the strand. Singlet oxygen exposure then covalently functionalized the guanine to the SWCNT surface, red-shifting the nanotube fluorescence by an amount reflecting the guanine spatial density at the surface. Spectral shifts were greatest for central guanine positions and smallest for end positions. In conjunction with steered molecular dynamics simulations, the results suggest that steric interference between neighboring ssDNA strands on an individual nanotube causes significant dislocation or desorption of the strand ends while central regions remain better wrapped around the nanotube. This effect decreases with decreasing concentrations of free ssDNA.

Discovery of DNA-Carbon Nanotube Sensors for Serotonin with Machine Learning and Near-infrared Fluorescence Spectroscopy

DNA-wrapped single walled carbon nanotube (SWNT) conjugates have distinct optical properties leading to their use in biosensing and imaging applications. A critical limitation in the development of DNA-SWNT sensors is the current inability to predict unique DNA sequences that confer a strong analyte-specific optical response to these sensors. Here, near-infrared (nIR) fluorescence response data sets for ∼100 DNA-SWNT conjugates, narrowed down by a selective evolution protocol starting from a pool of ∼10¹⁰ unique DNA-SWNT candidates, are used to train machine learning (ML) models to predict DNA sequences with strong optical response to neurotransmitter serotonin. First, classifier models based on convolutional neural networks (CNN) are trained on sequence features to classify DNA ligands as either high response or low response to serotonin. Second, support vector machine (SVM) regression models are trained to predict relative optical response values for DNA sequences. Finally, we demonstrate with validation experiments that integrating the predictions of ensembles of the highest quality neural network classifiers (convolutional or artificial) and SVM regression models leads to the best predictions of both high and low response sequences. With our ML approaches, we discovered five DNA-SWNT sensors with higher fluorescence intensity response to serotonin than obtained previously. Overall, the explored ML approaches, shown to predict useful DNA sequences, can be used for discovery of DNA-based sensors and nanobiotechnologies.

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 acid–based properties and binding capacity. Protein features associated with increased likelihood of SWCNT binding include high content of solvent-exposed glycines and nonsecondary structure–associated 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.

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 acid–based properties and binding capacity. Protein features associated with increased likelihood of SWCNT binding include high content of solvent-exposed glycines and nonsecondary structure–associated 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.

Harnessing selectivity in chemical sensing via supramolecular interactions: from functionalization of nanomaterials to device applications

Chemical sensing is a strategic field of science and technology ultimately aiming at improving the quality of our lives and the sustainability of our Planet. Sensors bear a direct societal impact on well-being, which includes the quality and composition of the air we breathe, the water we drink, and the food we eat. Pristine low-dimensional materials are widely exploited as highly sensitive elements in chemical sensors, although they suffer from lack of intrinsic selectivity towards specific analytes. Here, we showcase the most recent strategies on the use of (supra)molecular interactions to harness the selectivity of suitably functionalized 0D, 1D, and 2D low-dimensional materials for chemical sensing. We discuss how the design and selection of receptors via machine learning and artificial intelligence hold a disruptive potential in chemical sensing, where selectivity is achieved by the design and high-throughput screening of large libraries of molecules exhibiting a set of affinity parameters that dictates the analyte specificity. We also discuss the importance of achieving selectivity along with other relevant characteristics in chemical sensing, such as high sensitivity, response speed, and reversibility, as milestones for true practical applications. Finally, for each distinct class of low-dimensional material, we present the most suitable functionalization strategies for their incorporation into efficient transducers for chemical sensing.

Single-Walled Carbon Nanotube-Based Biosensors for Detection of Bronchial Inflammation

Inflammation is a protective mechanism against invading pathogens and tissue damage. However, the inflammatory process is implicated in a wide range of diseases affecting all organs and body systems. Nitric oxide — a multifunctional signaling molecule that plays a critical role in systemic blood pressure homeostasis, prevention of platelet aggregation, antimicrobial resistance, immunoregulation, tumor suppression and as a neurotransmitter — is used as a surrogate marker for inflammation. However, the most commonly used Griess assay is an indirect and expensive method for the determination of nitric oxide concentration. Hence, single-walled carbon nanotube-based biosensors have been explored as real-time, sensitive, selective and safe methods to determine nitric oxide released during the inflammatory process. In this review, we explore current developments in single-walled carbon nanotube-based biosensors for the detection of nitric oxide in exhaled breath as a direct and noninvasive test for detection of bronchial inflammation.

Transcutaneous Measurement of Essential Vitamins Using Near-Infrared Fluorescent Single-Walled Carbon Nanotube Sensors

Vitamins such as riboflavin and ascorbic acid are frequently utilized in a range of biomedical applications as drug delivery targets, fluidic tracers, and pharmaceutical excipients. Sensing these biochemicals in the human body has the potential to significantly advance medical research and clinical applications. In this work, a nanosensor platform consisting of single-walled carbon nanotubes (SWCNTs) with nanoparticle corona phases engineered to allow for the selective molecular recognition of ascorbic acid and riboflavin, is developed. The study provides a methodological framework for the implementation of colloidal SWCNT nanosensors in an intraperitoneal SKH1-E murine model by addressing complications arising from tissue absorption and scattering, mechanical perturbations, as well as sensor diffusion and interactions with the biological environment. Nanosensors are encapsulated in a polyethylene glycol diacrylate hydrogel and a diffusion model is utilized to validate analyte transport and sensor responses to local concentrations at the boundary. Results are found to be reproducible and stable after exposure to 10% mouse serum even after three days of in vivo implantation. A geometrical encoding scheme is used to reference sensor pairs, correcting for in vivo optical and mechanical artifacts, resulting in an order of magnitude improvement of p-value from 0.084 to 0.003 during analyte sensing.

Photoluminescent Nanoparticles for Chemical and Biological Analysis and Imaging

Research related to the development and application of luminescent nanoparticles (LNPs) for chemical and biological analysis and imaging is flourishing. Novel materials and new applications continue to be reported after two decades of research. This review provides a comprehensive and heuristic overview of this field. It is targeted to both newcomers and experts who are interested in a critical assessment of LNP materials, their properties, strengths and weaknesses, and prospective applications. Numerous LNP materials are cataloged by fundamental descriptions of their chemical identities and physical morphology, quantitative photoluminescence (PL) properties, PL mechanisms, and surface chemistry. These materials include various semiconductor quantum dots, carbon nanotubes, graphene derivatives, carbon dots, nanodiamonds, luminescent metal nanoclusters, lanthanide-doped upconversion nanoparticles and downshifting nanoparticles, triplet-triplet annihilation nanoparticles, persistent-luminescence nanoparticles, conjugated polymer nanoparticles and semiconducting polymer dots, multi-nanoparticle assemblies, and doped and labeled nanoparticles, including but not limited to those based on polymers and silica. As an exercise in the critical assessment of LNP properties, these materials are ranked by several application-related functional criteria. Additional sections highlight recent examples of advances in chemical and biological analysis, point-of-care diagnostics, and cellular, tissue, and in vivo imaging and theranostics. These examples are drawn from the recent literature and organized by both LNP material and the particular properties that are leveraged to an advantage. Finally, a perspective on what comes next for the field is offered.

The chemical tools for imaging dopamine release

Dopamine is a modulatory neurotransmitter involved in learning, motor functions, and reward. Many neuropsychiatric disorders, including Parkinson's disease, autism, and schizophrenia, are associated with imbalances or dysfunction in the dopaminergic system. Yet, our understanding of these pervasive public health issues is limited by our ability to effectively image dopamine in humans, which has long been a goal for chemists and neuroscientists. The last two decades have witnessed the development of many molecules used to trace dopamine. We review the small molecules, nanoparticles, and protein sensors used with fluorescent microscopy/photometry, MRI, and PET that shape dopamine research today. None of these tools observe dopamine itself, but instead harness the biology of the dopamine system-its synthetic and metabolic pathways, synaptic vesicle cycle, and receptors-in elegant ways. Their advantages and weaknesses are covered here, along with recent examples and the chemistry and biology that allow them to function.

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.

Nanotransducers for Wireless Neuromodulation

Understanding the signal transmission and processing within the central nervous system (CNS) is a grand challenge in neuroscience. The past decade has witnessed significant advances in the development of new tools to address this challenge. Development of these new tools draws diverse expertise from genetics, materials science, electrical engineering, photonics and other disciplines. Among these tools, nanomaterials have emerged as a unique class of neural interfaces due to their small size, remote coupling and conversion of different energy modalities, various delivery methods, and mitigated chronic immune responses. In this review, we will discuss recent advances in nanotransducers to modulate and interface with the neural system without physical wires. Nanotransducers work collectively to modulate brain activity through optogenetic, mechanical, thermal, electrical and chemical modalities. We will compare important parameters among these techniques including the invasiveness, spatiotemporal precision, cell-type specificity, brain penetration, and translation to large animals and humans. Important areas for future research include a better understanding of the nanomaterials-brain interface, integration of sensing capability for bidirectional closed-loop neuromodulation, and genetically engineered functional materials for cell-type specific neuromodulation.

Near-infrared nanoscopy with carbon-based nanoparticles for the exploration of the brain extracellular space

Understanding the physiology and pathology of the brain requires detailed knowledge of its complex structures as well as dynamic internal processes at very different scales from the macro down to the molecular dimensions. A major yet poorly described brain compartment is the brain extracellular space (ECS). Signalling molecules rapidly diffuse through the brain ECS which is complex and dynamic structure at numerous lengths and time scales. In recent years, characterization of the ECS using nanomaterials has made remarkable progress, including local analysis of nanoscopic dimensions and diffusivity as well as local chemical sensing. In particular, carbon nanomaterials combined with advanced optical technologies, biochemical and biophysical analysis, offer novel promises for understanding the ECS morphology as well as neuron connectivity and neurochemistry. In this review, we present the state-of-the-art in this quest, which mainly focuses on a type of carbon nanomaterial, single walled carbon nanotubes, as fluorescent nanoprobes to unveil the ECS features in the nanometre domain.

Rapid SARS-CoV-2 Spike Protein Detection by Carbon Nanotube-Based Near-Infrared Nanosensors

To effectively track and eliminate COVID-19, it is critical to develop tools for rapid and accessible diagnosis of actively infected individuals. Here, we introduce a single-walled carbon nanotube (SWCNT)-based optical sensing approach toward this end. We construct a nanosensor based on SWCNTs noncovalently functionalized with ACE2, a host protein with high binding affinity for the SARS-CoV-2 spike protein. The presence of the SARS-CoV-2 spike protein elicits a robust, 2-fold nanosensor fluorescence increase within 90 min of spike protein exposure. We characterize the nanosensor stability and sensing mechanism and passivate the nanosensor to preserve sensing response in saliva and viral transport medium. We further demonstrate that these ACE2-SWCNT nanosensors retain sensing capacity in a surface-immobilized format, exhibiting a 73% fluorescence turn-on response within 5 s of exposure to 35 mg/L SARS-CoV-2 virus-like particles. Our data demonstrate that ACE2-SWCNT nanosensors can be developed into an optical tool for rapid SARS-CoV-2 detection.

Plant Nanobionic Sensors for Arsenic Detection

Arsenic is a highly toxic heavy-metal pollutant which poses a significant health risk to humans and other ecosystems. In this work, the natural ability of wild-type plants to pre-concentrate and extract arsenic from the belowground environment is exploited to engineer plant nanobionic sensors for real-time arsenic detection. Near-infrared fluorescent nanosensors are specifically designed for sensitive and selective detection of arsenite. These optical nanosensors are embedded in plant tissues to non-destructively access and monitor the internal dynamics of arsenic taken up by the plants via the roots. The integration of optical nanosensors with living plants enables the conversion of plants into self-powered autosamplers of arsenic from their environment. Arsenite detection is demonstrated with three different plant species as nanobionic sensors. Based on an experimentally validated kinetic model, the nanobionic sensor could detect 0.6 and 0.2 ppb levels of arsenic after 7 and 14 days respectively by exploiting the natural ability of Pteris cretica ferns to hyperaccumulate and tolerate exceptionally high level of arsenic. The sensor readout could also be interfaced with portable electronics at a standoff distance, potentially enabling applications in environmental monitoring and agronomic research.

Quantitative Protein Corona Composition and Dynamics on Carbon Nanotubes in Biological Environments

When nanoparticles enter biological environments, proteins adsorb to form the "protein corona" which alters nanoparticle biodistribution and toxicity. Herein, we measure protein corona formation on DNA-functionalized single-walled carbon nanotubes (ssDNA-SWCNTs), a nanoparticle used widely for sensing and delivery, in blood plasma and cerebrospinal fluid. We characterize corona composition by mass spectrometry, revealing high-abundance corona proteins involved in lipid binding, complement activation, and coagulation. We investigate roles of electrostatic and entropic interactions driving selective corona formation. Lastly, we study real-time protein binding on ssDNA-SWCNTs, obtaining agreement between enriched proteins binding strongly and depleted proteins binding marginally, while highlighting cooperative adsorption mechanisms. Knowledge of protein corona composition, formation mechanisms, and dynamics informs nanoparticle translation from in vitro design to in vivo application.

Rapid SARS-CoV-2 Detection by Carbon Nanotube-Based Near-Infrared Nanosensors

To effectively track and eliminate COVID-19, it is critical to develop tools for rapid and accessible diagnosis of actively infected individuals. Here, we introduce a single-walled carbon nanotube (SWCNT)-based optical sensing approach towards these ends. We construct a nanosensor based on SWCNTs noncovalently functionalized with ACE2, a host protein with high binding affinity for the SARS-CoV-2 spike protein. Presence of the SARS-CoV-2 spike protein elicits a robust, two-fold nanosensor fluorescence increase within 90 min of spike protein exposure. We characterize the nanosensor stability and sensing mechanism, and passivate the nanosensor to preserve sensing response in saliva and viral transport medium. We further demonstrate that these ACE2-SWCNT nanosensors retain sensing capacity in a surface-immobilized format, exhibiting a 73% fluorescence turn-on response within 5 s of exposure to 35 mg/L SARS-CoV-2 virus-like particles. Our data demonstrate that ACE2-SWCNT nanosensors can be developed into an optical tool for rapid SARS-CoV-2 detection.

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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.

Dye Quenching of Carbon Nanotube Fluorescence Reveals Structure-Selective Coating Coverage

Many properties and applications of single-wall carbon nanotubes (SWCNTs) depend strongly on the coatings that allow their suspension in aqueous media. We report that SWCNT fluorescence is quenched by reversible physisorption of dye molecules such as methylene blue, and that measurements of that quenching can be used to infer structure-specific exposures of the nanotube surface to the surrounding solution. SWCNTs suspended in single-stranded DNA oligomers show quenching dependent on the combination of nanotube structure and ssDNA base sequence. Several sequences are found to give notably high or low surface coverages for specific SWCNT species. These effects seem correlated with the selective recognitions used for DNA-based structural sorting of nanotubes. One notable example is that dye quenching of fluorescence from SWCNTs coated with the (ATT)₄ base sequence is far stronger for one (7,5) enantiomer than for the other, showing that coating coverage is associated with the coating affinity difference reported previously for this system. Equilibrium modeling of quenching data has been used to extract parameters for comparative complexation constants and accessible surface areas. Further insights are obtained from molecular dynamics simulations, which give estimated contact areas between ssDNA and SWCNTs that correlate with experimentally inferred surface exposures and account for the enantiomeric discrimination of (ATT)₄.

The Role of Amino Acids in Neurotransmission and Fluorescent Tools for Their Detection

Neurotransmission between neurons, which can occur over the span of a few milliseconds, relies on the controlled release of small molecule neurotransmitters, many of which are amino acids. Fluorescence imaging provides the necessary speed to follow these events and has emerged as a powerful technique for investigating neurotransmission. In this review, we highlight some of the roles of the 20 canonical amino acids, GABA and β-alanine in neurotransmission. We also discuss available fluorescence-based probes for amino acids that have been shown to be compatible for live cell imaging, namely those based on synthetic dyes, nanostructures (quantum dots and nanotubes), and genetically encoded components. We aim to provide tool developers with information that may guide future engineering efforts and tool users with information regarding existing indicators to facilitate studies of amino acid dynamics.

Carbon nanocarriers deliver siRNA to intact plant cells for efficient gene knockdown

Posttranscriptional gene silencing (PTGS) is a powerful tool to understand and control plant metabolic pathways, which is central to plant biotechnology. PTGS is commonly accomplished through delivery of small interfering RNA (siRNA) into cells. Standard plant siRNA delivery methods (Agrobacterium and viruses) involve coding siRNA into DNA vectors and are only tractable for certain plant species. Here, we develop a nanotube-based platform for direct delivery of siRNA and show high silencing efficiency in intact plant cells. We demonstrate that nanotubes successfully deliver siRNA and silence endogenous genes, owing to effective intracellular delivery and nanotube-induced protection of siRNA from nuclease degradation. This study establishes that nanotubes could enable a myriad of plant biotechnology applications that rely on RNA delivery to intact cells.

Dispersion quality of single-walled carbon nanotubes reveals the recognition sequence of DNA

The specific recognition between DNA and single-walled carbon nanotubes (SWCNTs) has enabled wide applications, especially in the chiral sorting of SWCNTs. However, the molecular recognition mechanism has not been fully understood. In our work, various DNA-SWCNT dispersions were prepared by the ultrasonic dispersion method, and characterized by UV absorption spectroscopy, fluorescence emission spectroscopy, zeta potential measurement, SDBS exchange kinetics and computer simulation. The effect of DNA sequence on the structure and properties of hybrid molecules was analyzed. Data analysis showed that DNA with specific recognition had better dispersion quality of the corresponding SWCNT, which means that higher content of monodispersed SWCNTs was obtained. The high-quality dispersion of the DNA-SWCNT pair was attributed to the stronger binding between DNA and SWCNT, resulting in a tighter conformation of DNA on the SWCNT surface and a larger zeta potential of DNA-SWCNT hybrids. Consequently, DNA-SWCNT dispersions of the recognition pair exhibited better stability against salt and stronger fluorescence emission intensity. However, the correlation between specific recognition and DNA coverage on SWCNT was not observed. This work gives more insight into the recognition mechanism between DNA and SWCNTs.

Multifunctional Heterogeneous Carbon Nanotube Nanocomposites Assembled by DNA-Binding Peptide Anchors

Although carbon nanotubes (CNTs) are remarkable materials with many exceptional characteristics, their poor chemical functionality limits their potential applications. Herein, a strategy is proposed for functionalizing CNTs, which can be achieved with any functional group (FG) without degrading their intrinsic structure by using a deoxyribonucleic acid (DNA)-binding peptide (DBP) anchor. By employing a DBP tagged with a certain FG, such as thiol, biotin, and carboxyl acid, it is possible to introduce any FG with a controlled density on DNA-wrapped CNTs. Additionally, different types of FGs can be introduced on CNTs simultaneously, using DBPs tagged with different FGs. This method can be used to prepare CNT nanocomposites containing different types of nanoparticles (NPs), such as Au NPs, magnetic NPs, and quantum dots. The CNT nanocomposites decorated with these NPs can be used as reusable catalase-like nanocomposites with exceptional catalytic activities, owing to the synergistic effects of all the components. Additionally, the unique DBP-DNA interaction allows the on-demand detachment of the NPs attached to the CNT surface; further, it facilitates a CNT chirality-specific NP attachment and separation using the sequence-specific programmable characteristics of oligonucleotides. The proposed method provides a novel chemistry platform for constructing new functional CNTs suitable for diverse applications.

Corona Exchange Dynamics on Carbon Nanotubes by Multiplexed Fluorescence Monitoring

Noncovalent adsorption of DNA on nanoparticles has led to their widespread implementation as gene delivery tools and optical probes. Yet, the behavior and stability of DNA-nanoparticle complexes once applied in biomolecule-rich, in vivo environments remains unpredictable, whereby biocompatibility testing usually occurs in serum. Here, we demonstrate time-resolved measurements of exchange dynamics between solution-phase and adsorbed corona-phase DNA and protein biomolecules on single-walled carbon nanotubes (SWCNTs). We capture real-time binding of fluorophore-labeled biomolecules, utilizing the SWCNT surface as a fluorescence quencher, and apply this corona exchange assay to study protein corona dynamics on ssDNA-SWCNT-based dopamine sensors. We study exchange of two blood proteins, albumin and fibrinogen, adsorbing to and competitively displacing (GT)6 vs (GT)15 ssDNA from ssDNA-SWCNTs. We find that (GT)15 binds to SWCNTs with a higher affinity than (GT)6 and that fibrinogen interacts with ssDNA-SWCNTs more strongly than albumin. Albumin and fibrinogen cause a 52.2% and 78.2% attenuation of the dopamine nanosensor response, coinciding with 0.5% and 3.7% desorption of (GT)6, respectively. Concurrently, the total surface-adsorbed fibrinogen mass is 168% greater than that of albumin. Binding profiles are fit to a competitive surface exchange model which recapitulates the experimental observation that fibrinogen has a higher affinity for SWCNTs than albumin, with a fibrinogen on-rate constant 1.61-fold greater and an off-rate constant 0.563-fold smaller than that of albumin. Our methodology presents a generic route to assess real-time corona exchange on nanoparticles in solution phase and more broadly motivates testing of nanoparticle-based technologies in blood plasma rather than the more ubiquitously tested serum conditions.

Templating colloidal sieves for tuning nanotube surface interactions and optical sensor responses

Surfactants offer a tunable approach for modulating the exposed surface area of a nanoparticle. They further present a scalable and cost-effective means for suspending single-walled carbon nanotubes (SWCNTs), which have demonstrated practical use as fluorescence sensors. Though surfactant suspensions show record quantum yields for SWCNTs in aqueous solutions, they lack the selectivity that is vital for optical sensing. We present a new method for controlling the selectivity of optical SWCNT sensors through colloidal templating of the exposed surface area. Colloidal nanotube sensors were obtained using various concentrations of sodium cholate, and their performances were compared to DNA-SWCNT optical sensors. Sensor responses were measured against a library of bioanalytes, including neurotransmitters, amino acids, and sugars. We report an intensity response towards dopamine and serotonin for all sodium cholate-suspended SWCNT concentrations. We further identify a selective, 14.1 nm and 10.3 nm wavelength red-shifting response to serotonin for SWCNTs suspended in 1.5 and 0.5 mM sodium cholate, respectively. Through controlled, adsorption-based tuning of the nanotube surface, this study demonstrates the applicability of sub-critical colloidal suspensions to achieve selectivities exceeding those previously reported for DNA-SWCNT sensors.

Fluorescent Single-Walled Carbon Nanotubes for Protein Detection

Nanosensors have a central role in recent approaches to molecular recognition in applications like imaging, drug delivery systems, and phototherapy. Fluorescent nanoparticles are particularly attractive for such tasks owing to their emission signal that can serve as optical reporter for location or environmental properties. Single-walled carbon nanotubes (SWCNTs) fluoresce in the near-infrared part of the spectrum, where biological samples are relatively transparent, and they do not photobleach or blink. These unique optical properties and their biocompatibility make SWCNTs attractive for a variety of biomedical applications. Here, we review recent advancements in protein recognition using SWCNTs functionalized with either natural recognition moieties or synthetic heteropolymers. We emphasize the benefits of the versatile applicability of the SWCNT sensors in different systems ranging from single-molecule level to in-vivo sensing in whole animal models. Finally, we discuss challenges, opportunities, and future perspectives.

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.

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.

Structural Properties of Small Single-Stranded Circular Nucleic Acids

One strategy to avoid rapid degradation of small nucleic acids in biomedical applications is to covalently link their 3'- and 5'-ends, turning them into circular nucleic acids (circNAs). Here, we examine structural properties of flexible non-base-paired circNAs, containing 6-48 nucleotides, in aqueous solution, using microsecond long molecular dynamics simulations. Analyses of conformational ensembles of circular DNA (circDNA) and RNA (circRNA) molecules of different lengths and sequences reveal how their structures and dynamics are affected by the constraints of their geometries. The circDNAs are more bent and flexible than circRNAs, with distinctly different arrangements of phosphate backbones and bases. Small circNAs can sequester counterions in conformations that resemble crown ethers for the smallest (6-8 nucleotide long) molecules examined, in contrast to their linear counterparts. At millimolar concentrations (7.9 mM), circNA molecules were observed to aggregate, adopting linear chain shapes at physiological ionic strengths.