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.

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.

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 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.

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.

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.

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.

A wavelength-induced frequency filtering method for fluorescent nanosensors in vivo.

Fluorescent nanosensors hold the potential to revolutionize life sciences and medicine. However, their adaptation and translation into the in vivo environment is fundamentally hampered by unfavourable tissue scattering and intrinsic autofluorescence. Here we develop wavelength-induced frequency filtering (WIFF) whereby the fluorescence excitation wavelength is modulated across the absorption peak of a nanosensor, allowing the emission signal to be separated from the autofluorescence background, increasing the desired signal relative to noise, and internally referencing it to protect against artefacts. Using highly scattering phantom tissues, an SKH1-E mouse model and other complex tissue types, we show that WIFF improves the nanosensor signal-to-noise ratio across the visible and near-infrared spectra up to 52-fold. This improvement enables the ability to track fluorescent carbon nanotube sensor responses to riboflavin, ascorbic acid, hydrogen peroxide and a chemotherapeutic drug metabolite for depths up to 5.5 ± 0.1 cm when excited at 730 nm and emitting between 1,100 and 1,300 nm, even allowing the monitoring of riboflavin diffusion in thick tissue. As an application, nanosensors aided by WIFF detect the chemotherapeutic activity of temozolomide transcranially at 2.4 ± 0.1 cm through the porcine brain without the use of fibre optic or cranial window insertion. The ability of nanosensors to monitor previously inaccessible in vivo environments will be important for life-sciences research, therapeutics and medical diagnostics.

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.

In vivo imaging of fluorescent single-walled carbon nanotubes within C. elegans nematodes in the near-infrared window.

Caenorhabditis elegans (C. elegans) nematodes serve as a model organism for eukaryotes, especially due to their genetic similarity. Although they have many advantages like their small size and transparency, their autofluorescence in the entire visible wavelength range poses a challenge for imaging and tracking fluorescent proteins or dyes using standard fluorescence microscopy. Herein, near-infrared (NIR) fluorescent single-walled carbon nanotubes (SWCNTs) are utilized for in vivo imaging within the gastrointestinal track of C. elegans. The SWCNTs are biocompatible, and do not affect the worms' viability nor their reproduction ability. The worms do not show any autofluorescence in the NIR range, thus enabling the spectral separation between the SWCNT NIR fluorescence and the strong autofluorescence of the worm gut granules. The worms are fed with ssDNA-SWCNT which are visualized mainly in the intestine lumen. The NIR fluorescence is used in vivo to track the contraction and relaxation in the area of the pharyngeal valve at the anterior of the terminal bulb. These biocompatible, non-photobleaching, NIR fluorescent nanoparticles can advance in vivo imaging and tracking within C. elegans and other small model organisms by overcoming the signal-to-noise challenge stemming from the wide-range visible autofluorescence.

Dendron-Polymer Hybrids as Tailorable Responsive Coronae of Single-Walled Carbon Nanotubes.

Functional composite materials that can change their spectral properties in response to external stimuli have a plethora of applications in fields ranging from sensors to biomedical imaging. One of the most promising types of materials used to design spectrally active composites are fluorescent single-walled carbon nanotubes (SWCNTs), noncovalently functionalized by synthetic amphiphilic polymers. These coated SWCNTs can exhibit modulations in their fluorescence spectra in response to interactions with target analytes. Hence, identifying new amphiphiles with interchangeable building blocks that can form individual coronae around the SWCNTs and can be tailored for a specific application is of great interest. This study presents highly modular amphiphilic polymer-dendron hybrids, composed of hydrophobic dendrons and hydrophilic polyethylene glycol (PEG) that can be synthesized with a high degree of structural freedom, for suspending SWCNTs in aqueous solution. Taking advantage of the high molecular precision of these PEG-dendrons, we show that precise differences in the chemical structure of the hydrophobic end groups of the dendrons can be used to control the interactions of the amphiphiles with the SWCNT surface. These interactions can be directly related to differences in the intrinsic near-infrared fluorescence emission of the various chiralities in a SWCNT sample. Utilizing the susceptibility of the PEG-dendrons toward enzymatic degradation, we demonstrate the ability to monitor enzymatic activity through changes in the SWCNT fluorescent signal. These findings pave the way for a rational design of functional SWCNTs, which can be used for optical sensing of enzymatic activity in the near-infrared spectral range.

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.

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.

A nanoscale paper-based near-infrared optical nose (NIRON).

Electronic noses (e-nose) and optical noses (o-nose) are two emerging approaches for the development of artificial olfactory systems for flavor and smell evaluation. The current work leverages the unique optical properties of semiconducting single-wall carbon nanotubes (SWCNTs) to develop a prototype of a novel paper-based near-infrared optical nose (NIRON). We have drop-dried an array of SWCNTs encapsulated with a wide variety of peptides on a paper substrate and continuously imaged the emitted SWCNTs fluorescence using a CMOS camera. Odors and different volatile molecules were passed above the array in a flow chamber, resulting in unique modulation patterns of the SWCNT photoluminescence (PL). Quartz crystal microbalance (QCM) measurements performed in parallel confirmed the direct binding between the vapor molecules and the peptide-SWCNTs. PL levels measured before and during exposure demonstrate distinct responses to the four tested alcoholic vapors (ethanol, methanol, propanol, and isopropanol). In addition, machine learning tools directly applied to the fluorescence images allow us to distinguish between the aromas of red wine, beer, and vodka. Further, we show that the developed sensor can detect limonene, undecanal, and geraniol vapors, and differentiate between their smells utilizing the PL response pattern. This novel paper-based optical biosensor provides data in real-time, and is recoverable and suitable for working at room temperature and in a wide range of humidity levels. This platform opens new avenues for real-time sensing of volatile chemical compounds, odors, and flavors.

Implantable Nanosensors for Human Steroid Hormone Sensing In Vivo Using a Self-Templating Corona Phase Molecular Recognition.

Dynamic measurements of steroid hormones in vivo are critical, but steroid sensing is currently limited by the availability of specific molecular recognition elements due to the chemical similarity of these hormones. In this work, a new, self-templating synthetic approach is applied using corona phase molecular recognition (CoPhMoRe) targeting the steroid family of molecules to produce near infrared fluorescent, implantable sensors. A key limitation of CoPhMoRe has been its reliance on library generation for sensor screening. This problem is addressed with a self-templating strategy of polymer design, using the examples of progesterone and cortisol sensing based on a styrene and acrylic acid copolymer library augmented with an acrylated steroid. The pendant steroid attached to the corona backbone is shown to self-template the phase, providing a unique CoPhMoRE design strategy with high efficacy. The resulting sensors exhibit excellent stability and reversibility upon repeated analyte cycling. It is shown that molecular recognition using such constructs is viable even in vivo after sensor implantation into a murine model by employing a poly (ethylene glycol) diacrylate (PEGDA) hydrogel and porous cellulose interface to limit nonspecific absorption. The results demonstrate that CoPhMoRe templating is sufficiently robust to enable a new class of continuous, in vivo biosensors.

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.