Project description:We report here a method for the determination of the pKa of histidine in complex or heterogeneous systems amenable to neither solid-state nor solution NMR spectroscopy. Careful synthesis of a fluorenylmethyloxycarbonyl- and trityl-protected, C2-deuterated histidine produces a vibrational-probe-equipped amino acid that can readily be incorporated into any peptide accessible by standard solid-phase methods. The frequency of the unique, Raman-active stretching vibration of this C2-D probe is a clear reporter of the protonation state of histidine. We investigate here a pH-sensitive peptide that self-assembles to form a hydrogel at neutral pH. The pKa of the lone histidine residue in the peptide, which is likely responsible for this pH-dependent behavior, cannot be investigated by NMR spectroscopy because of the supramolecular, soft nature of the gel. However, after synthesizing a C2-deuterated-histidine-containing peptide, we were able to follow the protonation state of histidine throughout a pH titration using Raman difference spectroscopy, thereby precisely determining the pKa of interest.
Project description:Multiple respiratory viruses can concurrently or sequentially infect the respiratory tract, making their identification crucial for diagnosis, treatment, and disease management. We present a label-free diagnostic platform integrating surface-enhanced Raman scattering (SERS) with deep learning for rapid, quantitative detection of respiratory virus coinfections. Using sensitive silica-coated silver nanorod array substrates, over 1.2 million SERS spectra are collected from 11 viruses, nine two-virus mixtures, and four three-virus mixtures at various concentrations in saliva. A deep learning model, MultiplexCR, is developed to simultaneously predict virus species and concentrations from SERS spectra. It achieves an impressive 98.6% accuracy in classifying virus coinfections and a mean absolute error of 0.028 for concentration regression. In blind tests, the model demonstrates consistent high accuracy and precise concentration predictions. This SERS-MultiplexCR platform completes the entire detection process in just 15 min, offering significant potential for rapid, point-of-care diagnostics in infection detection, as well as applications in food safety and environmental monitoring.
Project description:We propose a Bayesian statistical model for analyzing coherent anti-Stokes Raman scattering (CARS) spectra. Our quantitative analysis includes statistical estimation of constituent line-shape parameters, the underlying Raman signal, the error-corrected CARS spectrum, and the measured CARS spectrum. As such, this work enables extensive uncertainty quantification in the context of CARS spectroscopy. Furthermore, we present an unsupervised method for improving spectral resolution of Raman-like spectra requiring little to no a priori information. Finally, the recently proposed wavelet prism method for correcting the experimental artifacts in CARS is enhanced by using interpolation techniques for wavelets. The method is validated using CARS spectra of adenosine mono-, di-, and triphosphate in water, as well as equimolar aqueous solutions of d-fructose, d-glucose, and their disaccharide combination sucrose.
Project description:A novel ratiometric Raman spectroscopic (RMRS) method has been developed for quantitative determination of protein carbonyl levels. Oxidized bovine serum albumin (BSA) and oxidized lysozyme were used as model proteins to demonstrate this method. The technique involves conjugation of protein carbonyls with dinitrophenyl hydrazine (DNPH), followed by drop coating deposition Raman spectral acquisition (DCDR). The RMRS method is easy to implement because it requires only one conjugation reaction, uses a single spectral acquisition, and does not require sample calibration. Characteristic peaks from both protein and DNPH moieties are obtained in a single spectral acquisition, allowing the protein carbonyl level to be calculated from the peak intensity ratio. Detection sensitivity for the RMRS method is approximately 0.33 pmol carbonyl per measurement. Fluorescence and/or immunoassay-based techniques only detect a signal from the labeling molecule and, thus, yield no structural or quantitative information for the modified protein, whereas the RMRS technique allows protein identification and protein carbonyl quantification in a single experiment.
Project description:Circulating exosomes in body fluids are involved in many diseases and have important roles in pathophysiological processes. Specifically, they have emerged as a promising new class of biomarkers in cancer diagnosis and prognosis because of their high concentration and availability in a variety of biological fluids. The ability to quantitatively detect and characterize these nano-sized vesicles is crucial to make use of exosomes as a reliable biomarker for clinical applications. However, current methods are mostly technically challenging and time-consuming which prevents them from being adopted in clinical practice. In this work, we have developed a rapid sensitive platform for exosome detection and quantification by employing MoS2-multiwall carbon nanotubes as a fluorescence quenching material. This exosome biosensor shows a sensitive and selective biomarker detection. Using this MoS2-MWCNT based fluorometric nanosensor to analyze exosomes derived from MCF-7 breast cancer cells, we found that CD63 expression could be measured based on the retrieved fluorescence of the fluorophore with a good linear response range of 0-15% v/v. In addition, this nanosensing technique is able to quantify exosomes with different surface biomarker expressions and has revealed that exosomes secreted from MCF-7 breast cancer cells have a higher CD24 expression compared to CD63 and CD81.
Project description:We present a pH nanosensor conceived for single intracellular measurements. The sensing architecture consisted of a two-electrode system evaluated in the potentiometric mode. We used solid-contact carbon nanopipette electrodes tailored to produce both the indicator (pH nanosensor) and reference electrodes. The indicator electrode was a membrane-based ion-selective electrode containing a receptor for hydrogen ions that provided a favorable selectivity for intracellular measurements. The analytical features of the pH nanosensor revealed a Nernstian response (slope of -59.5 mV/pH unit) with appropriate repeatability and reproducibility (variation coefficients of <2% for the calibration parameters), a fast response time (<5 s), adequate medium-term drift (0.7 mV h-1), and a linear range of response including physiological and abnormal cell pH levels (6.0-8.5). In addition, the position and configuration of the reference electrode were investigated in cell-based experiments to provide unbiased pH measurements, in which both the indicator and reference electrodes were located inside the same cell, each of them inside two neighboring cells, or the indicator electrode inside the cell and the reference electrode outside of (but nearby) the studied cell. Finally, the pH nanosensor was applied to two cases: (i) the tracing of the pH gradient from extra-to intracellular media over insertion into a single PC12 cell and (ii) the monitoring of variations in intracellular pH in response to exogenous administration of pharmaceuticals. It is anticipated that the developed pH nanosensor, which is a label-free analytical tool, has high potential to aid in the investigation of pathological states that manifest in cell pH misregulation, with no restriction in the type of targeted cells.
Project description:Here, we present a surface-enhanced Raman spectroscopy (SERS) nanosensor for environmental pollutants detection. This study was conducted on three polycyclic aromatic hydrocarbons (PAHs): benzo[a]pyrene (BaP), fluoranthene (FL), and naphthalene (NAP). SERS substrates were chemically functionalized using 4-dodecyl benzenediazonium-tetrafluoroborate and SERS analyses were conducted to detect the pollutants alone and in mixtures. Compounds were first measured in water-methanol (9:1 volume ratio) samples. Investigation on solutions containing concentrations ranging from 10-6 g L-1 to 10-3 g L-1 provided data to plot calibration curves and to determine the performance of the sensor. The calculated limit of detection (LOD) was 0.026 mg L-1 (10-7 mol L-1) for BaP, 0.064 mg L-1 (3.2 × 10-7 mol L-1) for FL, and 3.94 mg L-1 (3.1 × 10-5 mol L-1) for NAP, respectively. The correlation between the calculated LOD values and the octanol-water partition coefficient (Kow) of the investigated PAHs suggests that the developed nanosensor is particularly suitable for detecting highly non-polar PAH compounds. Measurements conducted on a mixture of the three analytes (i) demonstrated the ability of the developed technology to detect and identify the three analytes in the mixture; (ii) provided the exact quantitation of pollutants in a mixture. Moreover, we optimized the surface regeneration step for the nanosensor.
Project description:Plants communicate through volatile organic compounds (VOCs), but real-time monitoring of VOCs for plant intercommunication is not practically possible yet. A nanobionic VOC sensor plant is created to study VOC-mediated plant intercommunication by incorporating surface-enhanced Raman scattering (SERS) nanosensors into a living plant. This sensor allows real-time monitoring of VOC with a sensitivity down to the parts per trillion level. A quantitative VOC diffusion model in plants is proposed to describe this extreme sensitivity. The sensor plant is paired with a customized portable Raman device, demonstrating its ability to detect multiple VOCs on-field. The sensor demonstrated that plants collect VOCs emitted from neighboring plants and hazardous volatile chemicals in the air at a certain distance. As a feasibility study, this nanobionic VOC sensor plant successfully monitored the early stages of fungal infection in strawberry fruits. This result suggests that interfacing nanosensors with plants offers an innovative approach to studying interplant communication and can be used as a compelling tool for monitoring VOC occurrence.
Project description:Ion-specific probes and fluorescent indicators have been key in establishing the role of ion signaling, namely calcium, protons, and anions, in plant development, providing a robust approach for monitoring spatiotemporal changes in intracellular ion dynamics. The integration of protons/pH in signaling mechanisms is especially important as reports of their biological functions continue to expand; however, attaining quantitative estimates with high spatiotemporal resolution in single cells poses a major research challenge. Here, we detail the use of the genetically encoded pH-sensitive pHluorin reporter expressed in Arabidopsis thaliana pollen tubes to assess cytosolic measurements with calibration to provide actual pH values. This technique enabled us to identify critical phenotypes and establish the importance of tip-focused pH gradient for pollen tube growth, although it can be adapted to other experimental systems.
Project description:Wheat flour is widely used on an industrial scale in baked goods, pasta, food concentrates, and confectionaries. Ash content and moisture can serve as important indicators of the wheat flour's quality and use, but the routinely applied assessment methods are laborious. Partial least squares regression models, obtained using Raman spectra of flour samples and the results of reference gravimetric analysis, allow for fast and reliable determination of ash and moisture in wheat flour, with relative standard errors of prediction of the order of 2%. Analogous calibration models that enable quantification of carbon, oxygen, sulfur, and nitrogen, and hence protein, in the analyzed flours, with relative standard errors of prediction equal to 0.1, 0.3, 3.3, and 1.4%, respectively, were built combining the results of elemental analysis and Raman spectra.