Glutathione-S-transferase Fusion Protein Nanosensor

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.

Ratiometric Imaging of Catecholamine Neurotransmitters with Nanosensors

Neurotransmitters are important signaling molecules in the brain and are relevant in many diseases. Measuring them with high spatial and temporal resolutions in biological systems is challenging. Here, we develop a ratiometric fluorescent sensor/probe for catecholamine neurotransmitters on the basis of near-infrared (NIR) semiconducting single wall carbon nanotubes (SWCNTs). Phenylboronic acid (PBA)-based quantum defects are incorporated into them to interact selectively with catechol moieties. These PBA-SWCNTs are further modified with poly(ethylene glycol) phospholipids (PEG-PL) for biocompatibility. Catecholamines, including dopamine, do not affect the intrinsic E11 fluorescence (990 nm) of these (PEG-PL-PBA-SWCNT) sensors. In contrast, the defect-related E11* emission (1130 nm) decreases by up to 35%. Furthermore, this dual functionalization allows tuning selectivity by changing the charge of the PEG polymer. These sensors are not taken up by cells, which is beneficial for extracellular imaging, and they are functional in brain slices. In summary, we use dual functionalization of SWCNTs to create a ratiometric biosensor for dopamine.

Nanomaterial surface modification toolkit: Principles, components, recipes, and applications

Surface-functionalized nanostructures are at the forefront of biotechnology, providing new opportunities for biosensors, drug delivery, therapy, and bioimaging applications. The modification of nanostructures significantly impacts the performance and success of various applications by enabling selective and precise targeting. This review elucidates widely practiced surface modification strategies, including click chemistry, cross-coupling, silanization, aldehyde linkers, active ester chemistry, maleimide chemistry, epoxy linkers, and other protein and DNA-based methodologies. We also delve into the application-focused landscape of the nano-bio interface, emphasizing four key domains: therapeutics, biosensing, environmental monitoring, and point-of-care technologies, by highlighting prominent studies. The insights presented herein pave the way for further innovations at the intersection of nanotechnology and biotechnology, providing a useful handbook for beginners and professionals. The review draws on various sources, including the latest research articles (2018-2023), to provide a comprehensive overview of the field.

Direct and Specific Detection of Glyphosate Using a Phosphatase-like Nanozyme-Mediated Chemiluminescence Strategy

Most organophosphorus pesticide (OP) sensors reported in the literature rely on the inhibition effect of OPs on the activity of acetylcholinesterase (AChE), which suffer from the drawbacks of lack of selective recognition of OPs, high cost, and poor stability. Herein, we proposed a novel chemiluminescence (CL) strategy for the direct detection of glyphosate (an organophosphorus herbicide) with high sensitivity and specificity, which is based on the porous hydroxy zirconium oxide nanozyme (ZrO_X-OH) obtained via a facile alkali solution treatment of UIO-66. ZrO_X-OH displayed excellent phosphatase-like activity, which could catalyze the dephosphorylation of 3-(2'-spiroadamantyl)-4-methoxy-4-(3'-phosphoryloxyphenyl)-1,2-dioxetane (AMPPD) to generate strong CL. The experimental results showed that the phosphatase-like activity of ZrO_X-OH is closely related to the content of hydroxyl groups on their surface. Interestingly, ZrO_X-OH with phosphatase-like properties exhibited a unique response to glyphosate because of the consumption of the surface hydroxyl group by the unique carboxyl group of glyphosates and was thus employed to develop a CL sensor for direct and selective detection of glyphosate without using bio-enzymes. The recovery for glyphosate detection of cabbage juice ranged from 96.8 to 103.0%. We believe that the as-proposed CL sensor based on ZrO_X-OH with phosphatase-like properties supplies a simpler and more highly selective approach for OP assay and provides a new method for the development of CL sensors for the direct analysis of OPs in real samples.

1Progress, applications, challenges and prospects of protein purification technology

Protein is one of the most important biological macromolecules in life, which plays a vital role in cell growth, development, movement, heredity, reproduction and other life activities. High quality isolation and purification is an essential step in the study of the structure and function of target proteins. Therefore, the development of protein purification technologies has great theoretical and practical significance in exploring the laws of life activities and guiding production practice. Up to now, there is no forthcoming method to extract any proteins from a complex system, and the field of protein purification still faces significant opportunities and challenges. Conventional protein purification generally includes three steps: pretreatment, rough fractionation, and fine fractionation. Each of the steps will significantly affect the purity, yield and the activity of target proteins. The present review focuses on the principle and process of protein purification, recent advances, and the applications of these technologies in the life and health industry as well as their far-reaching impact, so as to promote the research of protein structure and function, drug development and precision medicine, and bring new insights to researchers in related fields.

Novel Split Intein-Mediated Enzymatic Channeling Accelerates the Multimeric Bioconversion Pathway of Ginsenoside

Cascade reaction systems, such as protein fusion and synthetic protein scaffold systems, can both spatially control the metabolic flux and boost the productivity of multistep enzymatic reactions. Despite many efforts to generate fusion proteins, this task remains challenging due to the limited expression of complex enzymes. Therefore, we developed a novel fusion system that bypasses the limited expression of complex enzymes via a post-translational linkage. Here, we report a split intein-mediated cascade system wherein orthogonal split inteins serve as adapters for protein ligation. A genetically programmable, self-assembled, and traceless split intein was utilized to generate a biocatalytic cascade to produce the ginsenoside compound K (CK) with various pharmacological activities, including anticarcinogenic, anti-inflammatory, and antidiabetic effects. We used two types of split inteins, consensus atypical (Cat) and Rma DnaB, to form a covalent scaffold with the three enzymes involved in the CK conversion pathway. The multienzymatic complex with a size greater than 240 kDa was successfully assembled in a soluble form and exhibited specific activity toward ginsenoside conversion. Furthermore, our split intein cascade system significantly increased the CK conversion rate and reduced the production time by more than 2-fold. Our multienzymatic cascade system that uses split inteins can be utilized as a platform for regulating multimeric bioconversion pathways and boosting the production of various high-value substances.

Protein-structure-dependent spectral shifts of near-infrared photoluminescence from locally functionalized single-walled carbon nanotubes based on avidin-biotin interactions

Single-walled carbon nanotubes (SWCNTs) emit photoluminescence (PL) in the near-infrared (NIR) region (>900 nm). To enhance their PL properties, defect doping via local chemical functionalization has been developed. The locally functionalized SWCNTs (lf-SWCNTs) emit red-shifted and bright E₁₁* PL originating from the excitons localized at the defect-doped sites. Here, we observe the E₁₁* PL energy shifts induced by protein adsorption via the avidin-biotin interactions at the doped sites of lf-SWCNTs. We establish that the difference in the structures of the avidin derivatives notably influences the energy shifts. First, lf-SWCNT-tethering biotin groups (lf-SWCNTs-b) are synthesized based on diazonium chemistry, followed by post-modification. The responsiveness of the lf-SWCNTs-b to different microenvironments is investigated, and a correlation between the E₁₁* PL energy shift and the induction-polarity parameters of surrounding solvents is established. The adsorption of neutravidin onto the lf-SWCNTs-b induces an increase in the induction-polarity parameters around the biotin-doped sites, resulting in the red-shift of the E₁₁* PL peak. The E₁₁* PL shift behaviors of the lf-SWCNTs-b change noticeably when avidin and streptavidin are introduced compared to the case with neutravidin. This is due to the different microenvironments formed at the biotin-doped sites, attributed to the difference in the structural features of the introduced avidin derivatives. Moreover, we successfully enhance the detection signals of lf-SWCNTs-b (>three fold) for streptavidin detection using a fabricated film device. Therefore, lf-SWCNTs exhibit significant promise for application in advanced protein detection/recognition devices based on NIR PL.

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.

Hyperspectral Counting of Multiplexed Nanoparticle Emitters in Single Cells and Organelles

Nanomaterials are the subject of a range of biomedical, commercial, and environmental investigations involving measurements in living cells and tissues. Accurate quantification of nanomaterials, at the tissue, cell, and organelle levels, is often difficult, however, in part due to their inhomogeneity. Here, we propose a method that uses the distinct optical properties of a heterogeneous nanomaterial preparation in order to improve quantification at the single-cell and organelle level. We developed "hyperspectral counting", which employs diffraction-limited imaging via hyperspectral microscopy of a diverse set of fluorescent nanomaterials to estimate particle number counts in live cells and subcellular structures. A mathematical model was developed, and Monte Carlo simulations were employed, to improve the accuracy of these estimates, enabling quantification with single-cell and single-endosome resolution. We applied this nanometrology technique with single-walled carbon nanotubes and identified an upper limit of the rate of uptake into cells─approximately 3,000 nanotubes endocytosed within 30 min. In contrast, conventional region-of-interest counting results in a 230% undercount. The method identified significant heterogeneity and a broad non-Gaussian distribution of carbon nanotube uptake within cells. For example, while a particular cell contained an average of 1 nanotube per endosome, the heterogeneous distribution resulted in over 7 nanotubes localizing within some endosomes, substantially changing the accounting of subcellular nanoparticle concentration distributions. This work presents a method to quantify the cellular and subcellular concentrations of a heterogeneous carbon nanotube reference material, with implications for the nanotoxicology, drug/gene delivery, and nanosensor fields.

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.

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

Quantification of insulin is essential for diabetes research in general, and for the study of pancreatic β-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 β-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 β-cells provides new opportunities for rapid assessment of β-cell function, with the ability to push forward many aspects of diabetes research.