Optical Fibers Functionalized with Single-Walled Carbon Nanotubes for Flexible Fluorescent Catecholamine Detection.

Despite the blockbuster popularity of drugs that act on catecholamine receptors, catecholamine dynamics in human health and disease remain an incomplete picture. Recent advances in fluorescent sensors have enabled unprecedented access to catecholamine dynamics in preclinical animal models, but the requirements of these technologies limit translational value for clinical diagnostics. Here, we present a flexible and convenient tool for fluorescent catecholamine detection by functionalizing optical fibers with single-walled carbon nanotube (SWNT)-based near-infrared catecholamine sensors (nIRCats), a form factor that has potential for more convenient and less invasive clinical translation. We show that these near-infrared functionalized (nIRF) fibers respond to dopamine in a biologically-relevant concentration range (10nM through 1 µM) with a mean ΔF/F0 of 0.022 through 0.411, with no statistically significant effect on signal magnitude after 16-hour exposure to human blood plasma. We further demonstrate the utility of these fibers in as little as 10 µL volumes of clinically relevant biofluids up to 24 weeks after preparation, with a ΔF/F0 of up to 0.059 through 1.127 for 10 nM through 1 µM dopamine. We also introduce a compact, mobile dual-near-infrared fiber photometry rig and demonstrate its success detecting dopamine with 0.005 ΔF/F0 in acute brain slices with nIRF fibers. Together, this fiber-based tool and photometry rig expand the toolbox of catecholamine detection technologies to a broader range of applications.

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.

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.

Near infrared fluorescent nanosensors for high spatiotemporal oxytocin imaging.

Oxytocin is a neuropeptide thought to play a central role in regulating social and emotional behavior. Current techniques for neuropeptide imaging are generally limited in spatial and temporal resolution, real-time imaging capacity, selectivity for oxytocin over vasopressin, and application in young and non-model organisms. To avoid the use of endogenous oxytocin receptors for oxytocin probe development, we employed a protocol to evolve purely synthetic molecular recognition on the surface of near-infrared fluorescent single-walled carbon nanotubes (SWCNT) using single-stranded DNA (ssDNA). This probe reversibly undergoes up to a 172% fluorescence increase in response to oxytocin with a K d of 4.93 µM. Furthermore, this probe responds selectively to oxytocin over oxytocin analogs, receptor agonists and antagonists, and most other neurochemicals. Lastly, we show our probe can image synaptic evoked oxytocin release in live mouse brain slices. Optical probes with the specificity and resolution requisite to image endogenous oxytocin signaling can advance the study of oxytocin neurotransmission for its role in both health and disease.

Deep Plasma Proteome Profiling by Modulating Single Nanoparticle Protein Corona with Small Molecules.

The protein corona, a dynamic biomolecular layer that forms on nanoparticle (NP) surfaces upon exposure to biological fluids is emerging as a valuable diagnostic tool for improving plasma proteome coverage analyzed by liquid chromatography-mass spectrometry (LC-MS/MS). Here, we show that spiking small molecules, including metabolites, lipids, vitamins, and nutrients, into plasma can induce diverse protein corona patterns on otherwise identical NPs, significantly enhancing the depth of plasma proteome profiling. The protein coronas on polystyrene NPs when exposed to plasma treated with an array of small molecules (n=10) allowed for detection of 1793 proteins marking an 8.25-fold increase in the number of quantified proteins compared to plasma alone (218 proteins) and a 2.63-fold increase relative to the untreated protein corona (681 proteins). Furthermore, we discovered that adding 1000 µg/ml phosphatidylcholine could singularly increase the number of unique proteins within the protein corona (897 proteins). This specific concentration of phosphatidylcholine selectively depleted the four most abundant plasma proteins, including albumin, thus reducing concentration dynamic range of plasma proteome and boosting LC-MS/MS sensitivity for detection of proteins with lower abundance. By employing an optimized data-independent acquisition (DIA) approach, the inclusion of phosphatidylcholine led to the detection of 1436 proteins in plasma. This significant achievement is made utilizing only a single NP type and one small molecule to analyze a single plasma sample, setting a new standard in proteomic depth of the plasma sample. Given the critical role of plasma proteomics in biomarker discovery and disease monitoring, we anticipate widespread adoption of this methodology for identification and clinical translation of proteomic biomarkers into FDA approved diagnostics.

A uniform data processing pipeline enables harmonized nanoparticle protein corona analysis across proteomics core facilities.

Protein corona, a layer of biomolecules primarily comprising proteins, forms dynamically on nanoparticles in biological fluids and is crucial for predicting nanomedicine safety and efficacy. The protein composition of the corona layer is typically analyzed using liquid chromatography-mass spectrometry (LC-MS/MS). Our recent study, involving identical samples analyzed by 17 proteomics facilities, highlighted significant data variability, with only 1.8% of proteins consistently identified across these centers. Here, we implement an aggregated database search unifying parameters such as variable modifications, enzyme specificity, number of allowed missed cleavages and a stringent 1% false discovery rate at the protein and peptide levels. Such uniform search dramatically harmonizes the proteomics data, increasing the reproducibility and the percentage of consistency-identified unique proteins across distinct cores. Specifically, out of the 717 quantified proteins, 253 (35.3%) are shared among the top 5 facilities (and 16.2% among top 11 facilities). Furthermore, we note that reduction and alkylation are important steps in protein corona sample processing and as expected, omitting these steps reduces the number of total quantified peptides by around 20%. These findings underscore the need for standardized procedures in protein corona analysis, which is vital for advancing clinical applications of nanoscale biotechnologies.

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.

Covalent Attachment of Horseradish Peroxidase to Single-Walled Carbon Nanotubes for Hydrogen Peroxide Detection.

Single-walled carbon nanotubes (SWCNTs) are desirable nanoparticles for sensing biological analytes due to their photostability and intrinsic near-infrared fluorescence. Previous strategies for generating SWCNT nanosensors have leveraged nonspecific adsorption of sensing modalities to the hydrophobic SWCNT surface that often require engineering new molecular recognition elements. An attractive alternate strategy is to leverage pre-existing molecular recognition of proteins for analyte specificity, yet attaching proteins to SWCNT for nanosensor generation remains challenging. Towards this end, we introduce a generalizable platform to generate protein-SWCNT-based optical sensors and use this strategy to synthesize a hydrogen peroxide (H 2 O 2 ) nanosensor by covalently attaching horseradish peroxidase (HRP) to the SWCNT surface. We demonstrate a concentration-dependent response to H 2 O 2 , confirm the nanosensor can image H 2 O 2 in real-time, and assess the nanosensor's selectivity for H 2 O 2 against a panel of biologically relevant analytes. Taken together, these results demonstrate successful covalent attachment of enzymes to SWCNTs while preserving both intrinsic SWCNT fluorescence and enzyme function. We anticipate this platform can be adapted to covalently attach other proteins of interest including other enzymes for sensing or antibodies for targeted imaging and cargo delivery.