Rationally Designed Functionalization of Single-Walled Carbon Nanotubes for Real-Time Monitoring of Cholinesterase Activity and Inhibition in Plasma.

Enzymes play a pivotal role in regulating numerous bodily functions. Thus, there is a growing need for developing sensors enabling real-time monitoring of enzymatic activity and inhibition. The activity and inhibition of cholinesterase (CHE) enzymes in blood plasma are fluorometrically monitored using near-infrared (NIR) fluorescent single-walled carbon nanotubes (SWCNTs) as probes, strategically functionalized with myristoylcholine (MC)- the substrate of CHE. A significant decrease in the fluorescence intensity of MC-suspended SWCNTs upon interaction with CHE is observed, attributed to the hydrolysis of the MC corona phase of the SWCNTs by CHE. Complementary measurements for quantifying choline, the product of MC hydrolysis, reveal a correlation between the fluorescence intensity decrease and the amount of released choline, rendering the SWCNTs optical sensors with real-time feedback in the NIR biologically transparent spectral range. Moreover, when synthetic and naturally abundant inhibitors inhibit the CHE enzymes present in blood plasma, no significant modulations of the MC-SWCNT fluorescence are observed, allowing effective detection of CHE inhibition. The rationally designed SWCNT sensors platform for monitoring of enzymatic activity and inhibition in clinically relevant samples is envisioned to not only advance the field of clinical diagnostics but also deepen further understanding of enzyme-related processes in complex biological fluids.

Single-Walled Carbon Nanotubes as Fluorescent Probes for Monitoring the Self-Assembly and Morphology of Peptide/Polymer Hybrid Hydrogels.

Hydrogels formed via supramolecular self-assembly of fluorenylmethyloxycarbonyl (Fmoc)-conjugated amino acids provide excellent scaffolds for 3D cell culture, tissue engineering, and tissue recovery matrices. Such hydrogels are usually characterized by rheology or electron microscopy, which are invasive and cannot provide real-time information. Here, we incorporate near-infrared fluorescent single-walled carbon nanotubes (SWCNTs) into Fmoc-diphenylalanine hydrogels as fluorescent probes, reporting in real-time on the morphology and time-dependent structural changes of the self-assembled hydrogels in the transparency window of biological tissue. We further demonstrate that the gelation process and structural changes upon the addition of cross-linking ions are transduced into spectral modulations of the SWCNT-fluorescence. Moreover, morphological differences of the hydrogels induced by polymer additives are manifested in unique features in fluorescence images of the incorporated SWCNTs. SWCNTs can thus serve as optical probes for noninvasive, long-term monitoring of the self-assembly gelation process and the fate of the resulting peptide hydrogel during long-term usage.

Monitoring the Activity and Inhibition of Cholinesterase Enzymes using Single-Walled Carbon Nanotube Fluorescent Sensors.

Cholinesterase enzymes are involved in a wide range of bodily functions, and their disruption is linked to pathologies such as neurodegenerative diseases and cancer. While cholinesterase inhibitors are used as drug treatments for diseases such as Alzheimer and dementia at therapeutic doses, acute exposure to high doses, found in pesticides and nerve agents, can be lethal. Therefore, measuring cholinesterase activity is important for numerous applications ranging from the search for novel treatments for neurodegenerative disorders to the on-site detection of potential health hazards. Here, we present the development of a near-infrared (near-IR) fluorescent single-walled carbon nanotube (SWCNT) optical sensor for cholinesterase activity and demonstrate the detection of both acetylcholinesterase and butyrylcholinesterase, as well as their inhibition. We show sub U L-1 sensitivity, demonstrate the optical response at the level of individual nanosensors, and showcase an optical signal output in the 900-1400 nm range, which overlaps with the biological transparency window. To the best of our knowledge, this is the longest wavelength cholinesterase activity sensor reported to date. Our near-IR fluorescence-based approach opens new avenues for spatiotemporal-resolved detection of cholinesterase activity, with numerous applications such as advancing the research of the cholinergic system, detecting on-site potential health hazards, and measuring biomarkers in real-time.

Super-Resolution Radial Fluctuations (SRRF) nanoscopy in the near infrared.

Super resolution microscopy methods have been designed to overcome the physical barrier of the diffraction limit and push the resolution to nanometric scales. A recently developed super resolution technique, super-resolution radial fluctuations (SRRF) [Nature communications, 7, 12471 (2016)10.1038/ncomms12471], has been shown to super resolve images taken with standard microscope setups without fluorophore localization. Herein, we implement SRRF on emitters in the near-infrared (nIR) range, single walled carbon nanotubes (SWCNTs), whose fluorescence emission overlaps with the biological transparency window. Our results open the path for super-resolving SWCNTs for biomedical imaging and sensing applications.

Inferring entropy production rate from partially observed Langevin dynamics under coarse-graining.

The entropy production rate (EPR) measures time-irreversibility in systems operating far from equilibrium. The challenge in estimating the EPR for a continuous variable system is the finite spatiotemporal resolution and the limited accessibility to all of the nonequilibrium degrees of freedom. Here, we estimate the irreversibility in partially observed systems following oscillatory dynamics governed by coupled overdamped Langevin equations. We coarse-grain an observed variable of a nonequilibrium driven system into a few discrete states and estimate a lower bound on the total EPR. As a model system, we use hair-cell bundle oscillations driven by molecular motors, such that the bundle tip position is observed, but the positions of the motors are hidden. In the observed variable space, the underlying driven process exhibits second-order semi-Markov statistics. The waiting time distributions (WTD), associated with transitions among the coarse-grained states, are non-exponential and convey the information on the broken time-reversal symmetry. By invoking the underlying time-irreversibility, we calculate a lower bound on the total EPR from the Kullback-Leibler divergence (KLD) between WTD. We show that the mean dwell-time asymmetry factor - the ratio between the mean dwell-times along the forward direction and the backward direction, can qualitatively measure the degree of broken time reversal symmetry and increases with finer spatial resolution. Finally, we apply our methodology to a continuous-time discrete Markov chain model, coarse-grained into a linear system exhibiting second-order semi-Markovian statistics, and demonstrate the estimation of a lower bound on the total EPR from irreversibility manifested only in the WTD.

Optical Nanosensors for Real-Time Feedback on Insulin Secretion by ß-Cells.

Quantification of insulin is essential for diabetes research in general, and for the study of pancreatic ß-cell function in particular. Herein, fluorescent single-walled carbon nanotubes (SWCNT) are used for the recognition and real-time quantification of insulin. Two approaches for rendering the SWCNT sensors for insulin are compared, using surface functionalization with either a natural insulin aptamer with known affinity to insulin, or a synthetic lipid-poly(ethylene glycol) (PEG) (C16 -PEG(2000Da)-Ceramide), both of which show a modulation of the emitted fluorescence in response to insulin. Although the PEGylated-lipid has no prior affinity to insulin, the response of C16 -PEG(2000Da)-Ceramide-SWCNTs to insulin is more stable and reproducible compared to the insulin aptamer-SWCNTs. The SWCNT sensors successfully detect insulin secreted by ß-cells within the complex environment of the conditioned media. The insulin is quantified by comparing the SWCNTs fluorescence response to a standard calibration curve, and the results are found to be in agreement with an enzyme-linked immunosorbent assay. This novel analytical tool for real time quantification of insulin secreted by ß-cells provides new opportunities for rapid assessment of ß-cell function, with the ability to push forward many aspects of diabetes research.

Nonequilibrium self-assembly of multiple stored targets in a dimer-based system.

Nonequilibrium self-assembly can be found in various biological processes where chemical potential gradients are exploited to steer the system to a desired organized structure with a particular function. Microtubules, for example, are composed of two globular protein subunits, α-tubulin and ß-tubulin, which bind together to form polar dimers that self-assemble a hollow cylinder structure in a process driven by GTPase activity. Inspired by this process, we define a generic self-assembly lattice model containing particles of two subunits, which is driven out-of-equilibrium by a dimer-favoring local driving force. Using Monte Carlo simulations, we characterize the ability of this system to restore pre-encoded target structures as a function of the initial seed size, interaction energy, chemical potential, number of target structures, and strength of the nonequilibrium drive. We demonstrate some intriguing consequences of the drive, such as a smaller critical seed and an improved target assembly stability, compared to the equilibrium scenario. Our results can expand the theoretical basis of nonequilibrium self-assembly and provide deeper understanding of how nonequilibrium driving can overcome equilibrium constraints.

Nonequilibrium associative retrieval of multiple stored self-assembly targets.

Many biological systems rely on the ability to self-assemble different target structures using the same set of components. Equilibrium self-assembly suffers from a limited capacity in such cases, due to an increasing number of decoy states that grows rapidly with the number of targets encoded. Moreover, improving the kinetic stability of a target at equilibrium carries the price of introducing kinetic traps, leading to slower assembly. Using a toy physical model of interacting particles, we demonstrate that local driving can improve both the assembly time and kinetic stability of multitarget self-assembly, as well as reduce fluctuations around the target configuration. We further show that the local drive can result in a steady-state probability distribution over target structures that deviates from the Boltzmann distribution in a way that depends on the types of interactions that stabilize the targets. Our results illustrate the role that nonequilibrium driving plays in overcoming tradeoffs that are inherent to equilibrium assemblies.

A Paper-Based Near-Infrared Optical Biosensor for Quantitative Detection of Protease Activity Using Peptide-Encapsulated SWCNTs.

A protease is an enzyme that catalyzes proteolysis of proteins into smaller polypeptides or single amino acids. As crucial elements in many biological processes, proteases have been shown to be informative biomarkers for several pathological conditions in humans, animals, and plants. Therefore, fast, reliable, and cost-effective protease biosensors suitable for point-of-care (POC) sensing may aid in diagnostics, treatment, and drug discovery for various diseases. This work presents an affordable and simple paper-based dipstick biosensor that utilizes peptide-encapsulated single-wall carbon nanotubes (SWCNTs) for protease detection. Upon enzymatic digestion of the peptide, a significant drop in the photoluminescence (PL) of the SWCNTs was detected. As the emitted PL is in the near-infrared region, the developed biosensor has a good signal to noise ratio in biological fluids. One of the diseases associated with abnormal protease activity is pancreatitis. In acute pancreatitis, trypsin concentration could reach up to 84 µg/mL in the urine. For proof of concept, we demonstrate the feasibility of the proposed biosensor for the detection of the abnormal levels of trypsin activity in urine samples.

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.

Nitroaromatic detection and infrared communication from wild-type plants using plant nanobionics.

Plant nanobionics aims to embed non-native functions to plants by interfacing them with specifically designed nanoparticles. Here, we demonstrate that living spinach plants (Spinacia oleracea) can be engineered to serve as self-powered pre-concentrators and autosamplers of analytes in ambient groundwater and as infrared communication platforms that can send information to a smartphone. The plants employ a pair of near-infrared fluorescent nanosensors-single-walled carbon nanotubes (SWCNTs) conjugated to the peptide Bombolitin II to recognize nitroaromatics via infrared fluorescent emission, and polyvinyl-alcohol functionalized SWCNTs that act as an invariant reference signal-embedded within the plant leaf mesophyll. As contaminant nitroaromatics are transported up the roots and stem into leaf tissues, they accumulate in the mesophyll, resulting in relative changes in emission intensity. The real-time monitoring of embedded SWCNT sensors also allows residence times in the roots, stems and leaves to be estimated, calculated to be 8.3 min (combined residence times of root and stem) and 1.9 min mm-1 leaf, respectively. These results demonstrate the ability of living, wild-type plants to function as chemical monitors of groundwater and communication devices to external electronics at standoff distances.

Microfluidic Fabrication of Colloidal Nanomaterials-Encapsulated Microcapsules for Biomolecular Sensing.

Implantable sensors that detect biomarkers in vivo are critical for early disease diagnostics. Although many colloidal nanomaterials have been developed into optical sensors to detect biomolecules in vitro, their application in vivo as implantable sensors is hindered by potential migration or clearance from the implantation site. One potential solution is incorporating colloidal nanosensors in hydrogel scaffold prior to implantation. However, direct contact between the nanosensors and hydrogel matrix has the potential to disrupt sensor performance. Here, we develop a hollow-microcapsule-based sensing platform that protects colloidal nanosensors from direct contact with hydrogel matrix. Using microfluidics, colloidal nanosensors were encapsulated in polyethylene glycol microcapsules with liquid cores. The microcapsules selectively trap the nanosensors within the core while allowing free diffusion of smaller molecules such as glucose and heparin. Glucose-responsive quantum dots or gold nanorods or heparin-responsive gold nanorods were each encapsulated. Microcapsules loaded with these sensors showed responsive optical signals in the presence of target biomolecules (glucose or heparin). Furthermore, these microcapsules can be immobilized into biocompatible hydrogel as implantable devices for biomolecular sensing. This technique offers new opportunities to extend the utility of colloidal nanosensors from solution-based detection to implantable device-based detection.

Mechanism of immobilized protein A binding to immunoglobulin G on nanosensor array surfaces.

Protein A is often used for the purification and detection of antibodies such as immunoglobulin G (IgG) because of its quadrivalent domains that bind to the Fc region of these macromolecules. However, the kinetics and thermodynamics of the binding to many sensor surfaces have eluded mechanistic description due to complexities associated with multivalent interactions. In this work, we use a near-infrared (nIR) fluorescent single-walled carbon nanotube sensor array to obtain the kinetics of IgG binding to protein A, immobilized using a chelated Cu(2+)/His-tag chemistry to hydrogel dispersed sensors. A bivalent binding mechanism is able to describe the concentration dependence of the effective dissociation constant, KD,eff, which varies from 100 pM to 1 µM for IgG concentrations from 1 ng mL(-1) to 100 µg mL(-1), respectively. The mechanism is shown to describe the unusual concentration-dependent scaling demonstrated by other sensor platforms in the literature as well, and a comparison is made between resulting parameters. For comparison, we contrast IgG binding with that of human growth hormone (hGH) to its receptor (hGH-R) which displays an invariant dissociation constant at KD = 9 µM. These results should aid in the use of protein A and other recognition elements in a variety of sensor types.

Experimental tools to study molecular recognition within the nanoparticle corona.

Advancements in optical nanosensor development have enabled the design of sensors using synthetic molecular recognition elements through a recently developed method called Corona Phase Molecular Recognition (CoPhMoRe). The synthetic sensors resulting from these design principles are highly selective for specific analytes, and demonstrate remarkable stability for use under a variety of conditions. An essential element of nanosensor development hinges on the ability to understand the interface between nanoparticles and the associated corona phase surrounding the nanosensor, an environment outside of the range of traditional characterization tools, such as NMR. This review discusses the need for new strategies and instrumentation to study the nanoparticle corona, operating in both in vitro and in vivo environments. Approaches to instrumentation must have the capacity to concurrently monitor nanosensor operation and the molecular changes in the corona phase. A detailed overview of new tools for the understanding of CoPhMoRe mechanisms is provided for future applications.

Single-walled carbon nanotubes as near-infrared fluorescent probes for bio-inspired supramolecular self-assembled hydrogels.

Hydrogels derived from fluorenylmethoxycarbonyl (Fmoc)-conjugated amino acids and peptides demonstrate remarkable potential in biomedical applications, including drug delivery, tissue regeneration, and tissue engineering. These hydrogels can be injectable, offering a minimally invasive approach to hydrogel implantation. Given their potential for prolonged application, there is a need for non-destructive evaluation of their properties over extended periods. Thus, we introduce a hydrogel characterization platform employing single-walled carbon nanotubes (SWCNTs) as near-infrared (NIR) fluorescent probes. Our approach involves generating supramolecular self-assembling hydrogels from aromatic Fmoc-amino acids. Integrating SWCNTs into the hydrogels maintains their structural and mechanical properties, establishing SWCNTs as optical probes for hydrogels. We demonstrate that the SWCNT NIR-fluorescence changes during the gelation process correlate to rheological changes within the hydrogels. Additionally, single particle tracking of SWCNTs incorporated in the hydrogels provides insights into differences in hydrogel morphologies. Furthermore, the disassembly process of the hydrogels can be monitored through the SWCNT fluorescence modulation. The unique attribute of SWCNTs as non-photobleaching fluorescent sensors, emitting at the biologically transparent window, offers a non-destructive method for studying hydrogel dynamics over extended periods. This platform could be applied to a wide range of self-assembling hydrogels to advance our understanding and applications of supramolecular assembly technologies.

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.

Enhanced cellular internalization of near-infrared fluorescent single-walled carbon nanotubes facilitated by a transfection reagent.

Functionalized single-walled carbon nanotubes (SWCNTs) hold immense potential for diverse biomedical applications due to their biocompatibility and optical properties, including near-infrared fluorescence. Specifically, SWCNTs have been utilized to target cells as a vehicle for drug delivery and gene therapy, and as sensors for various intracellular biomarkers. While the main internalization route of SWCNTs into cells is endocytosis, methods for enhancing the cellular uptake of SWCNTs are of great importance. In this research, we demonstrate the use of a transfecting reagent for promoting cell internalization of functionalized SWCNTs. We explore different types of SWCNT functionalization, namely single-stranded DNA (ssDNA) or polyethylene glycol (PEG)-lipids, and two different cell types, embryonic kidney cells and adenocarcinoma cells. We show that internalizing PEGylated functionalized SWCNTs is enhanced in the presence of the transfecting reagent, where the effect is more pronounced for negatively charged PEG-lipid. However, ssDNA-SWCNTs tend to form aggregates in the presence of the transfecting reagent, rendering it unsuitable for promoting internalization. For all cases, cellular uptake is visualized by near-infrared fluorescence microscopy, showing that the SWCNTs are typically localized within the lysosome. Generally, cellular internalization was higher in the adenocarcinoma cells, thereby paving new avenues for drug delivery and sensing in malignant cells.

A Stochastic Landscape Approach for Protein Folding State Classification.

Protein folding is a critical process that determines the functional state of proteins. Proper folding is essential for proteins to acquire their functional three-dimensional structures and execute their biological role, whereas misfolded proteins can lead to various diseases, including neurodegenerative disorders like Alzheimer's and Parkinson's. Therefore, a deeper understanding of protein folding is vital for understanding disease mechanisms and developing therapeutic strategies. This study introduces the Stochastic Landscape Classification (SLC), an innovative, automated, nonlearning algorithm that quantitatively analyzes protein folding dynamics. Focusing on collective variables (CVs) - low-dimensional representations of complex dynamical systems like molecular dynamics (MD) of macromolecules - the SLC approach segments the CVs into distinct macrostates, revealing the protein folding pathway explored by MD simulations. The segmentation is achieved by analyzing changes in CV trends and clustering these segments using a standard density-based spatial clustering of applications with noise (DBSCAN) scheme. Applied to the MD-based CV trajectories of Chignolin and Trp-Cage proteins, the SLC demonstrates apposite accuracy, validated by comparing standard classification metrics against ground-truth data. These metrics affirm the efficacy of the SLC in capturing intricate protein dynamics and offer a method to evaluate and select the most informative CVs. The practical application of this technique lies in its ability to provide a detailed, quantitative description of protein folding processes, with significant implications for understanding and manipulating protein behavior in industrial and pharmaceutical contexts.

Nonequilibrium Self-Assembly Time Forecasting by the Stochastic Landscape Method.

Many biological systems rely on the ability to self-assemble target structures from different molecular building blocks using nonequilibrium drives, stemming, for example, from chemical potential gradients. The complex interactions between the different components give rise to a rugged energy landscape with a plethora of local minima on the dynamic pathway to the target assembly. Exploring a toy physical model of multicomponents nonequilibrium self-assembly, we demonstrate that a segmented description of the system dynamics can be used to provide predictions of the first assembly times. We show that for a wide range of values of the nonequilibrium drive, a log-normal distribution emerges for the first assembly time statistics. Based on data segmentation by a Bayesian estimator of abrupt changes (BEAST), we further present a general data-based algorithmic scheme, namely, the stochastic landscape method (SLM), for assembly time predictions. We demonstrate that this scheme can be implemented for the first assembly time forecast during a nonequilibrium self-assembly process, with improved prediction power compared to a naïve guess based on the mean remaining time to the first assembly. Our results can be used to establish a general quantitative framework for nonequilibrium systems and to improve control protocols of nonequilibrium self-assembly processes.

Monitoring the Formation of Fibrin Clots as Part of the Coagulation Cascade Using Fluorescent Single-Walled Carbon Nanotubes.

Blood coagulation is a critical defense mechanism against bleeding that results in the conversion of liquid blood into a solid clot through a complicated cascade, which involves multiple clotting factors. One of the final steps in the coagulation pathway is the conversion of fibrinogen to insoluble fibrin mediated by thrombin. Because coagulation disorders can be life-threatening, the development of novel methods for monitoring the coagulation cascade dynamics is of high importance. Here, we use near-infrared (NIR)-fluorescent single-walled carbon nanotubes (SWCNTs) to image and monitor fibrin clotting in real time. Following the binding of fibrinogen to a tailored SWCNT platform, thrombin transforms the fibrinogen into fibrin monomers, which start to polymerize. The SWCNTs are incorporated within the clot and can be clearly visualized in the NIR-fluorescent channel, where the signal-to-noise ratio is improved compared to bright-field imaging in the visible range. Moreover, the diffusion of individual SWCNTs within the fibrin clot gradually slows down after the addition of thrombin, manifesting a coagulation rate that depends on both fibrinogen and thrombin concentrations. Our platform can open new opportunities for coagulation disorder diagnostics and allow for real-time monitoring of the coagulation cascade with a NIR optical signal output in the biological transparency window.