Fractal SERS nanoprobes for multiplexed quantitative gene profiling

Rapid Identification of Drug Mechanisms with Deep Learning-Based Multichannel Surface-Enhanced Raman Spectroscopy

Rapid identification of drug mechanisms is vital to the development and effective use of chemotherapeutics. Herein, we develop a multichannel surface-enhanced Raman scattering (SERS) sensor array and apply deep learning approaches to realize the rapid identification of the mechanisms of various chemotherapeutic drugs. By implementing a series of self-assembled monolayers (SAMs) with varied molecular characteristics to promote heterogeneous physicochemical interactions at the interfaces, the sensor can generate diversified SERS signatures for directly high-dimensionality fingerprinting drug-induced molecular changes in cells. We further train the convolutional neural network model on the multidimensional SAM-modulated SERS data set and achieve a discriminatory accuracy toward 99%. We expect that such a platform will contribute to expanding the toolbox for drug screening and characterization and facilitate the drug development process.

A self-calibrating flexible SERS substrate incorporating PB@Au assemblies for reliable and reproducible detection

The precise quantitative analysis using surface-enhanced Raman spectroscopy (SERS) in an uncontrollable environment still faces a significant obstacle due to the poor reproducibility of Raman signals. Herein, we propose a facile method to fabricate a self-calibrating substrate based on a flexible polyvinyl alcohol (PVA) film comprising assemblies of Prussian blue (PB) and Au NPs (PB@Au) for reliable detection. PB cores were coated with an Au shell through simple electrostatic interaction, forming core-shell nanostructure PB@Au assemblies within the PVA film. The outer Au layer provided identical trends in enhancement for both the PB core and neighboring targets while PB cores served as an internal standard (IS) to correct signal fluctuations. The prevention of competitive adsorption on the metal surface between targets and ISs was achieved. The proposed PVA/PB@Au film exhibited enhanced stability of Raman signals after IS correction, resulting in improved spot-to-spot and batch-to-batch reproducibility with significantly reduced standard deviation (RSD) values from 11.42% and 25.02% to 4.43% and 9.39%, respectively. Simultaneously, a higher accuracy in the quantitative analysis of 4-mercaptobenzoic acid (4-MBA) and malachite green (MG) was achieved with fitting coefficient (R2) values improving from 0.9675 and 0.9418 to 0.9974 and 0.9832, respectively. Moreover, the PVA/PB@Au film was successfully applied to detect residual MG in real fish samples. This work opens up an avenue to improve the reproducibility of Raman signals for flexible SERS substrates in the detection of residues under various complex conditions.

Generalized ratiometric surface-enhanced Raman scattering biosensor for okadaic acid in food based on Au-triggered signal amplification

BACKGROUND

Reliability and robustness have been recognized as key challenges for Surface-enhanced Raman scattering (SERS) analytical techniques. Quantifying the concentration of an analyte using a single characteristic peak from SERS has been a controversial topic because the Raman signal is susceptible to highly concentrated electromagnetic hotspots, inhomogeneity of SERS substrate, or non-standardization of measurement conditions. Ratiometric SERS strategies have been demonstrated as a promising solution to effectively balance and compensate for signal fluctuations caused by matrix heterogeneity. However, it is not easy to construct ratiometric SERS sensors with monitoring the ratio of two different signal intensities for target analysis.

RESULTS

An attempt has been made to develop a novel ratiometric biosensor that can be applied to detect okadaic acid (OA). Aptamer-anchored magnetic particles were first combined with gold-tagged short complementary DNA (Au-cDNA) to create heterogeneous nanostructures. When the target was present, the Au-cDNA was dissociated from nanostructures, and 4-nitrothiophenol (4-NTP) was initiated to reduce to 4-aminothiophenol (4-ATP) in the presence of hydrogen sources. The SERS ratio change of 4-NTP and 4-ATP was finally detected by AuNPs-coated film. OA was successfully quantified, and the detection limit was as low as 2.4524 ng/mL. The constructed biosensor had good stability and reproducibility with a relative standard deviation of less than 4.47%. The proposed method used gold nanoparticles as an intermediate to achieve catalytic signal amplification and subsequently increased the sensitivity of the biosensor.

SIGNIFICANCE AND NOVELTY

Catalytic reaction-based ratiometric SERS biosensors combine the multiple advantages of catalytic signal amplification and signal self-calibration and provide new insights into the development of stable, reproducible, and reliable SERS detection techniques. This ratiometric SERS technique offered a universal method that is anticipated to be applicable for the detection of other targets by substituting the aptamer.

CRISPR Cas12a-Powered Silicon Surface-Enhanced Raman Spectroscopy Ratiometric Chip for Sensitive and Reliable Quantification

Sensitive and reliable clustered regularly interspaced short palindromic repeats (CRISPR) quantification without preamplification of the sample remains a challenge. Herein, we report a CRISPR Cas12a-powered silicon surface-enhanced Raman spectroscopy (SERS) ratiometric chip for sensitive and reliable quantification. As a proof-of-concept application, we select the platelet-derived growth factor-BB (PDGF-BB) as the target. We first develop a microfluidic synthetic strategy to prepare homogeneous silicon SERS substrates, in which uniform silver nanoparticles (AgNPs) are in situ grown on a silicon wafer (AgNPs@Si) by microfluidic galvanic deposition reactions. Next, one 5'-SH-3'-ROX-labeled single-stranded DNA (ssDNA) is modified on AgNPs via Ag-S bonds. In our design, such ssDNA has two fragments: one fragment hybridizes to its complementary DNA (5'-Cy3-labeled ssDNA) to form double-stranded DNA (dsDNA) and the other fragment labeled with 6'-carboxy-X-rhodmine (ROX) extends out as a substrate for Cas12a. The cleavage of the ROX-tagged fragment by Cas12a is controlled by the presence or not of PDGF-BB. Meanwhile, Cy3 molecules serving as internal standard molecules still stay at the end of the rigid dsDNA, and their signals remain constant. Thereby, the ratio of ROX signal intensity to Cy3 intensity can be employed for the reliable quantification of PDGF-BB concentration. The developed chip features an ultrahigh sensitivity (e.g., the limit of detection is as low as 3.2 pM, approximately 50 times more sensitive than the fluorescence counterpart) and good reproducibility (e.g., the relative standard deviation is less than 5%) in the detection of PDGF-BB.

An Improved Multiple Competitive Immuno-SERS Sensing Platform and Its Application in Rapid Field Chemical Toxin Screening

Improving the signal-to-noise ratio (SNR) by amplifying the outputting signal or reducing nonspecific binding (NSB) are the key techniques in multiple immunoassay. Aiming at these issues, this paper presents an improved multiple indirect competitive immune surface-enhanced Raman scattering (ci-SERS) assay for the rapid screening of highly toxic rodenticides in food and biological samples, which ensured remarkable accuracy, ultra-sensitivity and reproducibility. The non-fouling polymer brush grafted magnetic beads (the MB@P-CyM) were prepared as multiple competitive recognition substrates after conjugating triplex haptens (the MB@P-CyM-hap). It was demonstrated that the particular 3D hair-like structures of P-CyM not only facilitate conjugate high-density hapten but reduce the steric hindrance from SERS probes recognition, thus enhancing SNB. On the other hand, Au nanoflowers (AuNFs) of high SERS activity were synthesized using a simple one-pot hydrazine reduction. For simultaneously detecting three highly toxic rodenticides, i.e., diphacinone (DPN), bromadiolone (BRD) and tetramine (TET), the obtained AuNFs were fabricated as a SERS-encoded nanoprobe cocktail after successively labeling mono-antibodies/Raman probes. By integrating the MB@P-CyM-hap with the SERS-encoded cocktail, a highly sensitive multiple SERS assay was achieved in less than 2 h with a limit of detection of 0.62 ng mL^-1 for BRD, 0.42 ng mL^-1 for TET and 1.37 ng mL^-1 for DPN, respectively. The recoveries of these rodenticides in spiked food and biological samples were determined and ranged from 72 to 123%. Above all, the proposed modifications show remarkable improvements for high efficient multiple chemical toxin immunoassay.

Quantitative SERS sensing mediated by internal standard Raman signal from silica nanoparticles in flexible polymer matrix

Attributed to poor signal uniformity and external interference, ultrasensitive surface-enhanced Raman spectroscopy (SERS) still faces difficulties in the reliable and quantitative detection of trace molecules. Here, a facile Ag/Si/sodium carboxy methyl cellulose (NaCMC) film with internal standard (IS) was promoted for quantitative determination of thiram. The effects of preparation conditions on SERS activity of the film were systematically investigated and then a flexible SERS substrate with high sensitivity and uniformity was fabricated. The enhancement factor was calculated to be 1.12 × 10⁶ and SERS mapping was recorded with a relative standard deviation value of 19.8% by utilizing 4-mercaptobenzoic acid (4-MBA) as target molecule. Additionally, the dominant contribution of the IS from encapsulated Si nanoparticles (NPs) was confirmed in the quantitative assay of 4-MBA and thiram, facilitating attractive fitting coefficients (R²) as 0.991 and 0.998. Besides that, the proposed flexible film was conducted to scrub trace thiram from the surfaces of apple, orange, and cucumber, resulting in recoveries of 89%, 94%, and 91%. A smart and facile quantitative SERS substrate was developed here for monitoring trace biochemical molecules, verifying its potential utilizations in monitoring pesticide residues.

Surface-enhanced Raman scattering biosensors for detection of oncomiRs in breast cancer

Surface-enhanced Raman scattering (SERS) has emerged as one of the most promising platforms for various biosensing applications. These sensing systems encompass the advantages of specificity, ultra-high sensitivity, stability, low cost, repeatability, and easy-to-use methods. Moreover, their ability to offer a molecular fingerprint and identify the target analyte at low levels make SERS a promising technique for detecting circulating cancer biomarkers with greater sensitivity and reliability. Among the various circulating biomolecules, oncomiRs are emerging as prominent biomarkers for the early screening of breast cancers (BCs). In this review, we provide a comprehensive understanding of different SERS-based biosensors and their application to identify BC-specific oncomiRs. We also discuss different SERS-based sensing strategies, nano-analytical frameworks, and challenges to be addressed for effective clinical translation.

Self-Referenced Surface-Enhanced Raman Scattering Nanosubstrate for the Quantitative Detection of Neurotransmitters

Quantitative, label-free detection of neurotransmitters is of vital importance to the diagnosis and treatment of neurologic diseases. The surface-enhanced Raman scattering (SERS) effect has great application prospects in the field of biosensing and bioimaging because of its unique nondestructive testing and its capability of being used in molecular fingerprint identification. However, the quantitative SERS analysis of neurotransmitters is still a great challenge because of the poor reproducibility of the SERS-active sites, as well as the small Raman cross-section and low physiological concentration of neurotransmitter molecules. Here, we report the development of a stellate gold nanostructure with a 1 nm interior gap for the quantitative detection of neurotransmitters. The internal reference embedded into the hollow gap of the stellate gold nanoparticle allows the calibration of the signal of analytes absorbed on the surface, which improves the R-squared value of the linear fitting curve from 0.56 to 0.97 for quantitative dopamine detection. Our developed self-referenced SERS substrate holds great potential for label-free, quantitative SERS-based biosensing.

Simultaneous extraction and surface enhanced Raman spectroscopy detection for the rapid and reliable identification of nicotine released from snus products

Surface enhanced Raman spectroscopy (SERS) is a highly sensitive analytical detection technique that provides unique chemical and structural information on target molecules. Here, simultaneous extraction and SERS detection of nicotine for the rapid and reliable identification of nicotine released from snus products were performed based on a nano-Au assembly hierarchy structure in the capillary. Based on this strategy, the time evolution of the concentrations of nicotine released from the snus products was measured. Through comparison of the intensities of the spectral peaks of the symmetrical breathing of the pyridine moiety of nicotine molecules, with the prolongation of time, the concentration of nicotine released decreased significantly, which is helpful for establishing a method for the rapid evaluation of the processing and selection of excipients of snus products, and provides a new idea for further study of the production of snus pouches and related tobacco products. Moreover, based on data fitting, it can be calculated that the concentration of nicotine in the extraction presented an obvious quadratic relationship with time, and the release of most of the nicotine in the snus pouch, which is held through the gums and palate, was basically completed after ∼15 min. Such destruction-free simultaneous measurements of snus products are opening up new perspectives for further research about the impact of nicotinoids on smokers' health and cessation programs.

Amplification-Free Identification and Determination of Nucleic Acids by Surface Plasmon Resonance and Surface-Enhanced Raman Spectroscopy

This review discusses contemporary approaches to designing sensory systems for the identification and determination of nucleic acids (NAs) without amplifying target molecules. Here we summarize the data about methods based on surface plasmon resonance and surface-enhanced Raman spectroscopy, as well as their possibilities, limitations, and prospects for further development.

CRISPR-/Cas12a-Mediated Liposome-Amplified Strategy for the Surface-Enhanced Raman Scattering and Naked-Eye Detection of Nucleic Acid and Application to Food Authenticity Screening

Surface-enhanced Raman scattering (SERS) has been recognized as a powerful tool for biosensors due to the ultrahigh sensitivity and unique fingerprint information. However, there are some limitations in trace target nucleic acid detection for the restricted signal-transducing and amplification strategies. Inspired by CRISPR/Cas12a with specific target DNA-activated collateral single-strand DNA (ssDNA) cleavage activity and liposome with signal molecule-loading properties, we first proposed a sensitive SERS-based on-site nucleic acid detection strategy mediated by CRISPR/Cas12a with trans-cleavage activity on ssDNA linkers utilized to capture liposomes. Liposomes loading two kinds of signal molecules, 4-nitrothiophenol (4-NTP) and cysteine, could achieve the dual-mode detection of target DNA with SERS and naked eye, respectively. The promptly amplified signals were initiated by the triggered breakdown of signal molecule-loaded liposomes. Emancipated 4-NTP, a biological-silent Raman reporter, would achieve highly selective and sensitive SERS measurement. Released cysteine induced the aggregation of plasmonic gold nanoparticles, leading to an obvious red to blue colorimetric shift to realize portable naked-eye detection. With this strategy, target nucleic acid concentration was dexterously converted into SERS and visualization signals and could be detected as low as 100 aM and 10 pM, respectively. The approach was also successfully applied to determine meat adulteration, achieving the detection of a low adulteration ratio in the complicated food matrix. We anticipate that this strategy will not only be regarded as a universal platform for the on-site detection of food authenticity but also broaden SERS application for the accurate determination of diverse biomarkers.

In Situ Growth Large Area Silver Nanostructure on Metal Phenolic Network Coated NAAO Film and Its SERS Sensing Application for Monofluoroacetic Acid

Rapid screening monofluoroacetic acid (FAcOH) is responsible for preventing chemical poisoning and food safety events. Whereas surface enhanced Raman scattering (SERS) spectra is an effective tool for detecting forbidden chemicals, it is difficult to directly detect FAcOH due to its small Raman scattering cross section as well as weak adsorption on SERS substrates. In this work, the metal phenolic supramolecular networks (MPNs, i.e., the tannic acid and Fe³⁺ complex) were fabricated on the commercial nanoanodic aluminum oxide film (NAAO) for assisting in situ chemical deposition highly uniform Ag nanostructure over large areas (the NAAO@AgNS). The low cost and simple fabrication process made the NAAO@AgNS a single-use consumable. For FAcOH detection, a specific derivative reaction between FAcOH and thiosalicylic acid (TSA) was introduced. By taking TSA as the Raman probe, its SERS signal attenuated constantly with the increasing amount of FAcOH. For improving quantitative accuracy, thiocyanate (SCN^-) was introduced on the NAAO@AgNS as an internal standard; thus, the characteristic peak intensity ratios associated with TSA and SCN^- (I₁₀₃₅/I₂₁₂₅) were fitted to the concentration of FAcOH. It was demonstrated that the SERS assay achieved good sensitivity and selection toward FAcOH with the limit of quantitation (LOD) as low as 50 nmol L^-1. The NAAO@AgNS featured with highly sensitive, uniform, and consistent SERS performances could easily extend to wide SERS applications.

Profiling DNA mutation patterns by SERS fingerprinting for supervised cancer classification

Profiling DNA mutation patterns for cancer classification plays an essential role in precision and personalized medicine. Conventional PCR-based mutation assay is limited by the extensive labour on target amplification. We herein create an amplification-free surface enhanced Raman spectroscopy (SERS) biochip which enables direct and simultaneous identification of multiple point mutations in tumor cells. Without pre-amplifying the target sequences, the SERS assay reads out the presence of cellular mutations through the interpretation of Raman fingerprints. The SERS sensor is integrated into a microfluidic chip, achieving one-step multiplex analysis within 40 min. Importantly, by combining SERS spectra encoding technique with supervised learning algorithm, a panel of nucleotide mixtures can be well distinguished according to their mutation profiles. We initially demonstrate an excellent levels of classification in samples from colorectal cancer and melanoma cell lines. For final clinical validation, the system performance is verified by classifying cancer patient samples, which shows an accuracy above 90%. Due to the simplicity and rapidness, the SERS biosensor is expected to become a promising tool for clinical point-of-care diagnosis towards precision medicine.