Surface-enhanced Raman scattering for protein detection

SERS in 3D cell models: a powerful tool in cancer research

Unraveling the cellular and molecular mechanisms underlying tumoral processes is fundamental for the diagnosis and treatment of cancer. In this regard, three-dimensional (3D) cancer cell models more realistically mimic tumors compared to conventional 2D cell cultures and are more attractive for performing such studies. Nonetheless, the analysis of such architectures is challenging because most available techniques are destructive, resulting in the loss of biochemical information. On the contrary, surface-enhanced Raman spectroscopy (SERS) is a non-invasive analytical tool that can record the structural fingerprint of molecules present in complex biological environments. The implementation of SERS in 3D cancer models can be leveraged to track therapeutics, the production of cancer-related metabolites, different signaling and communication pathways, and to image the different cellular components and structural features. In this review, we highlight recent progress in the use of SERS for the evaluation of cancer diagnosis and therapy in 3D tumoral models. We outline strategies for the delivery and design of SERS tags and shed light on the possibilities this technique offers for studying different cellular processes, through either biosensing or bioimaging modalities. Finally, we address current challenges and future directions, such as overcoming the limitations of SERS and the need for the development of user-friendly and robust data analysis methods. Continued development of SERS 3D bioimaging and biosensing systems, techniques, and analytical strategies, can provide significant contributions for early disease detection, novel cancer therapies, and the realization of patient-tailored medicine.

Advancements in Neurosurgical Intraoperative Histology

Despite their relatively low incidence globally, central nervous system (CNS) tumors remain amongst the most lethal cancers, with only a few other malignancies surpassing them in 5-year mortality rates. Treatment decisions for brain tumors heavily rely on histopathological analysis, particularly intraoperatively, to guide surgical interventions and optimize patient outcomes. Frozen sectioning has emerged as a vital intraoperative technique, allowing for highly accurate, rapid analysis of tissue samples, although it poses challenges regarding interpretive errors and tissue distortion. Raman histology, based on Raman spectroscopy, has shown great promise in providing label-free, molecular information for accurate intraoperative diagnosis, aiding in tumor resection and the identification of neurodegenerative disease. Techniques including Stimulated Raman Scattering (SRS), Coherent Anti-Stokes Raman Scattering (CARS), Surface-Enhanced Raman Scattering (SERS), and Tip-Enhanced Raman Scattering (TERS) have profoundly enhanced the speed and resolution of Raman imaging. Similarly, Confocal Laser Endomicroscopy (CLE) allows for real-time imaging and the rapid intraoperative histologic evaluation of specimens. While CLE is primarily utilized in gastrointestinal procedures, its application in neurosurgery is promising, particularly in the context of gliomas and meningiomas. This review focuses on discussing the immense progress in intraoperative histology within neurosurgery and provides insight into the impact of these advancements on enhancing patient outcomes.

Efficient, automatic, and optimized portable Raman-spectrum-based pesticide detection system

Raman spectroscopy can be used for accurately detecting pesticides and determining the chemical composition of a pesticide. To facilitate field detection, the present study used a portable Raman spectrometer for analysis. However, this spectrometer was found to be susceptible to noise interference and signal offsets, which increased the difficulty of pesticide identification. The most commonly used algorithm for Raman spectrum identification is principal component analysis (PCA). However, accurate classification often cannot be achieved with PCA because of the offset and noise in the Raman spectrum data. Therefore, in this study, after the collected Raman spectrum data were processed using the small-step, center-weighted moving-average method, these data were employed to train a convolutional neural network (CNN) model for prediction. To optimize the CNN model, the hyperparameters of the CNN were adjusted using various optimization algorithms, and the optimal solution was obtained after multiple iterations. Data preprocessing and architecture training models were then constructed in a self-optimized manner to improve the ability of the algorithm model to handle diverse types of data. Finally, a CNN model optimized using the cat swarm optimization algorithm was developed. This model was trained on 3000 samples containing three pesticides, and its accuracy for pesticide composition identification was discovered to be 89.33%.

Raman spectroscopy and its plasmon-enhanced counterparts: A toolbox to probe protein dynamics and aggregation

Protein unfolding and aggregation are often correlated with numerous diseases such as Alzheimer's, Parkinson's, Huntington's, and other debilitating neurological disorders. Such adverse events consist of a plethora of competing mechanisms, particularly interactions that control the stability and cooperativity of the process. However, it remains challenging to probe the molecular mechanism of protein dynamics such as aggregation, and monitor them in real-time under physiological conditions. Recently, Raman spectroscopy and its plasmon-enhanced counterparts, such as surface-enhanced Raman spectroscopy (SERS) and tip-enhanced Raman spectroscopy (TERS), have emerged as sensitive analytical tools that have the potential to perform molecular studies of functional groups and are showing significant promise in probing events related to protein aggregation. We summarize the fundamental working principles of Raman, SERS, and TERS as nondestructive, easy-to-perform, and fast tools for probing protein dynamics and aggregation. Finally, we highlight the utility of these techniques for the analysis of vibrational spectra of aggregation of proteins from various sources such as tissues, pathogens, food, biopharmaceuticals, and lastly, biological fouling to retrieve precise chemical information, which can be potentially translated to practical applications and point-of-care (PoC) devices. This article is categorized under: Therapeutic Approaches and Drug Discovery > Emerging Technologies Diagnostic Tools > Diagnostic Nanodevices Nanotechnology Approaches to Biology > Nanoscale Systems in Biology.

Recent Advances of Biosensors for Detection of Multiple Antibiotics

The abuse of antibiotics has caused a serious threat to human life and health. It is urgent to develop sensors that can detect multiple antibiotics quickly and efficiently. Biosensors are widely used in the field of antibiotic detection because of their high specificity. Advanced artificial intelligence/machine learning algorithms have allowed for remarkable achievements in image analysis and face recognition, but have not yet been widely used in the field of biosensors. Herein, this paper reviews the biosensors that have been widely used in the simultaneous detection of multiple antibiotics based on different detection mechanisms and biorecognition elements in recent years, and compares and analyzes their characteristics and specific applications. In particular, this review summarizes some AI/ML algorithms with excellent performance in the field of antibiotic detection, and which provide a platform for the intelligence of sensors and terminal apps portability. Furthermore, this review gives a short review of biosensors for the detection of multiple antibiotics.

SERS-based biosensor for detection of f-PSA%: Implications for the diagnosis of prostate cancer

In diagnosing prostate cancer and distinguishing it from other prostate diseases, the ratio of the concentration of free prostate-specific antigen (f-PSA) to total prostate-specific antigen (t-PSA), i.e., (f-PSA%) is more accurate than the concentration of t-PSA alone. Immunoassay based on surface-enhanced Raman scattering (SERS) frequency shift has been proven to be particularly suitable for detecting large biomolecules with high reproducibility. Along similar lines, the present study developed a SERS-based biosensor that simultaneously detects t-PSA and f-PSA. The 4-mercaptobenzoic acid (MBA) on the immunocapture substrate is coupled to the t-PSA antibody through the carboxyl group, and the combination of t-PSA induces the Raman frequency shifts of MBA. The immunocolloidal gold attached with f-PSA antibodies selectively capture the f-PSA that immobilized on the MBA-modified SERS substrates, allowing for f-PSA quantification according to the SERS intensities of the 5, 5'-Dithiobis (succinimidyl-2-nitrobenzoate) (DSNB) probe. The results show that f-PSA and t-PSA have good linear response in the concentration scale of 0.1-20 ng/mL, and 1-200 ng/mL, respectively. The biosensor combines Raman frequency shifts and intensities, which greatly simplifies traditional procedures for f-PSA% detection. All the results demonstrated the great potential of the proposed biosensor in highly reproducible and accurate diagnosis of prostate cancers.

Universal Method for Label-Free Detection of Pathogens and Biomolecules by Surface-Enhanced Raman Spectroscopy Based on Gold Nanoparticles

The detection of biomolecules is the key to basic molecular research, diagnostics, drug screening, and other biomedical applications. However, the existing detection techniques can only detect single classes of biomolecules, which warrant the development of a versatile biomolecule detection platform. Here, we developed a universal method for label-free detection of biomolecules via surface-enhanced Raman spectroscopy (SERS) by using sulfhydryl-modified gold nanoparticles as the substrate. The biomolecules can be adsorbed on the surface of gold nanoparticles cleaned by bromide ions to obtain initially enhanced Raman signals, and the aggregator (calcium ion) was further added to form a "hot spot", which enhanced the biomolecular signal again. Through the "two-step enhancement method", we were able to obtain fingerprints of DNA, RNA, amino acids, peptides, proteins, viruses, bacteria, and lipid molecules. This low-toxic, highly sensitive, and widely applicable technique has potential applications in biomedical research, clinical testing, and disease diagnosis and lays the foundation for the development of SERS technology in various fields.

Label-Free Surface-Enhanced Raman Spectroscopic Analysis of Proteins: Advances and Applications

Surface-enhanced Raman spectroscopy (SERS) is powerful for structural characterization of biomolecules under physiological condition. Owing to its high sensitivity and selectivity, SERS is useful for probing intrinsic structural information of proteins and is attracting increasing attention in biophysics, bioanalytical chemistry, and biomedicine. This review starts with a brief introduction of SERS theories and SERS methodology of protein structural characterization. SERS-active materials, related synthetic approaches, and strategies for protein-material assemblies are outlined and discussed, followed by detailed discussion of SERS spectroscopy of proteins with and without cofactors. Recent applications and advances of protein SERS in biomarker detection, cell analysis, and pathogen discrimination are then highlighted, and the spectral reproducibility and limitations are critically discussed. The review ends with a conclusion and a discussion of current challenges and perspectives of promising directions.

Human Angiotensin I-Converting Enzyme Produced by Different Cells: Classification of the SERS Spectra with Linear Discriminant Analysis

Angiotensin I-converting enzyme (ACE) is a peptidase widely presented in human tissues and biological fluids. ACE is a glycoprotein containing 17 potential N-glycosylation sites which can be glycosylated in different ways due to post-translational modification of the protein in different cells. For the first time, surface-enhanced Raman scattering (SERS) spectra of human ACE from lungs, mainly produced by endothelial cells, ACE from heart, produced by endothelial heart cells and miofibroblasts, and ACE from seminal fluid, produced by epithelial cells, have been compared with full assignment. The ability to separate ACEs’ SERS spectra was demonstrated using the linear discriminant analysis (LDA) method with high accuracy. The intervals in the spectra with maximum contributions of the spectral features were determined and their contribution to the spectrum of each separate ACE was evaluated. Near 25 spectral features forming three intervals were enough for successful separation of the spectra of different ACEs. However, more spectral information could be obtained from analysis of 50 spectral features. Band assignment showed that several features did not correlate with band assignments to amino acids or peptides, which indicated the carbohydrate contribution to the final spectra. Analysis of SERS spectra could be beneficial for the detection of tissue-specific ACEs.

Chemical and Biophysical Signatures of the Protein Corona in Nanomedicine

An inconvenient hurdle in the practice of nanomedicine is the protein corona, a spontaneous collection of biomolecular species by nanoparticles in living systems. The protein corona is dynamic in composition and may entail improved water suspendability and compromised delivery and targeting to the nanoparticles. How much of this nonspecific protein ensemble is determined by the chemistry of the nanoparticle core and its surface functionalization, and how much of this entity is dictated by the biological environments that vary spatiotemporally in vivo? How do we "live with" and exploit the protein corona without significantly sacrificing the efficacy of nanomedicines in diagnosing and curing human diseases? This article discusses the chemical and biophysical signatures of the protein corona and ponders challenges ahead for the field of nanomedicine.

Exosome detection via surface-enhanced Raman spectroscopy for cancer diagnosis

As nanoscale extracellular vesicles, exosomes are secreted by various cell types, and they are widely distributed in multiple biological fluids. Studies have shown that tumor-derived exosomes can carry a variety of primary tumor-specific molecules, which may represent a novel tool for the early detection of cancer. However, the clinical translation of exosomes remains a challenge due to the requirement of large quantities of samples when enriching the cancer-related exosomes in biological fluids, the insufficiency of traditional techniques for exosome subpopulations, and the complex exosome isolation of the current commercially available exosome phenotype profiling approaches. The evolving surface-enhanced Raman scattering (SERS) technology, with properties of unique optoelectronics, easy functionalization, and the particular interaction between light and nanoscale metallic materials, can achieve sensitive detection of exosomes without large quantities of samples and multiplexed phenotype profiling, providing a new mode of real-time and noninvasive analysis for cancer patients. In the present review, we mainly discussed exosome detection based on SERS, especially SERS immunoassay. The basic structure and function of exosomes were firstly introduced. Then, recent studies using the SERS technique for cancer detection were critically reviewed, which mainly included various SERS substrates, biological modification of SERS substrates, SERS-based exosome detection, and the combination of SERS and other technologies for cancer diagnosis. This review systematically discussed the essential aspects, limitations, and considerations of applying SERS technology in the detection and analysis of cancer-derived exosomes, which could provide a valuable reference for the early diagnosis of cancer through SERS technology. STATEMENT OF SIGNIFICANCE: Surface-enhanced Raman scattering (SERS) has been applied to exosomes detection to obtain better diagnostic results. In past three years, several reviews have been published in exosome detection, which were narrowly focus on methods of exosome detection. Selection and surface functionalization of the substrate and the combination detection with different methods based on SERS will provide new strategies for the detection of exosomes. This review will focus on the above aspects. This emerging detection method is constantly evolving and contributing to the early discovery of diseases in the future.

Novel Field-Based Protein Detection Method Using Light Transmission Spectroscopy and Antibody Functionalized Gold Nanoparticles

Protein detection is a universal tool critical to many applications in medicine, agriculture, and biotechnology. We developed a novel protein detection method combining light transmission spectroscopy and particle-size analysis of gold nanospheres monovalently functionalized with polyclonal antibodies and applied it to an emerging challenge for such technologies─the monitoring of environmental proteins (eProteins) present in natural aquatic systems. These are an underreported source of pollution and include the pseudopersistent Cry toxins that enter aquatic ecosystems from surrounding genetically engineered crops. The assay is capable of detecting proteins in complex matrices, such as water samples collected in the field, making it a competitive assay for eProtein detection. It is sensitive, reaching 1.25 ng mL^-1, and we demonstrate its application to the detection of Cry1Ab from subsurface tile-drain and streamwater samples from agricultural waterways. The assay can also be quickly adapted for other protein detection applications in the future.

Label-Free Protein Analysis by Pyro-Electrohydrodynamic Jet Printing of Gold Nanoparticles

The pyro-electrohydrodynamic jet (p-jet) printing technology has been used for the fabrication of confined assemblies of gold nanoparticles with a round shape and a diameter ranging between 100 and 200 μm. The surface-enhanced Raman spectroscopy (SERS) performance of the p-jet substrate was evaluated by using Rhodamine 6G (R6G) as a reference. The results demonstrate that this kind of SERS substrate exhibits strong plasmonic effects and a significant reproducibility of the signal with a coefficient of variation below 15%. We tested the signal behavior also in case of the bovine serum albumin (BSA) as a model analyte, to demonstrate the affinity with biomolecules. Strong SERS activity was measured also for BSA across the whole spot area. The spectral patterns collected in different locations of the sensing area were highly reproducible. This observation was substantiated by multivariate analysis of the imaging datasets and opens the route towards a potential application of this kind of SERS substrate in biosensing.

Intelligent Detection and Analysis of Polycyclic Aromatic Hydrocarbons Based on Surface-Enhanced Raman Scattering Spectroscopy

Cycloaromatic hydrocarbons are a type of potentially hazardous chemicals that are widely present in the environment and pose a serious threat to human health. However, the traditional research methods for their detection process are cumbersome, the detection cycle is long, and the sensitivity is low. In response to the above problems, this article combines the molecular fingerprint information characteristics of surface-enhanced Raman scattering technology to simulate the four polycyclic aromatic hydrocarbons of pyrene, anthracene, phenanthrene, and trichenium and quantitative detection of cyclic aromatic hydrocarbons and four kinds of polycyclic aromatic hydrocarbon mixtures. The experimental results show that the PAHs based on SERS have the advantages of higher sensitivity and high selectivity, which verifies the accuracy and feasibility of the method in this article.

Tracking structural changes of protein residues by two-dimensional correlation surface-enhanced Raman spectroscopy

In-situ tracking structural changes of protein residues was developed by two-dimensional correlation surface-enhanced Raman spectroscopy (2DC-SERS). The change order of SERS fingerprints during artificial nitrification of edible bird's nest (EBN) was interpreted as the structural changes of amino acid residues. It inherently realizes reliable recognition of natural EBN and artificially dyed fakes. Both this direct structural tracking of protein residues and the indirect azo dye testing of nitrites/nitrosamines could be used as indicators for discriminating different EBN before and after the artificial dyeing. Limit of detection (LOD) for nitrite and NDMA is about 40.6 ppb and 88.1 ppb, respectively. A conceptual logical circuit of the OR gate was constructed by considering the protein structural indicator (INPUT1) and the nitrite indicator (INPUT2) as two independent inputs for automatic recognition of different EBN samples. A data-driven analog soft independent modeling (DD-SIMCA) model could quickly distinguish normal EBN from A-EBN with 98% specificity.

A direct method for detecting proteins in body fluids by Surface-Enhanced Raman Spectroscopy under native conditions

Surface enhanced Raman spectroscopy (SERS) is widely used in biomolecular detection. However, maintaining the native structure of proteins while obtaining sensitive and reproducible SERS signals of unlabeled proteins remains a challenge. In this study, dichloromethane (DCM) and CaCl₂ were used to optimize the aggregation of Ag nanoparticles (AgNPs), and several proteins were analyzed comprehensively. Calcium ions removed citrate ions outside AgNPs, inducing hot spots and achieving high-sensitivity SERS signals of proteins. Furthermore, 20 random samples of 0.5 μg/mL hemoglobin were analyzed by this method. The obtained spectra showed good repeatability and a high quality. Using the peak intensity of DCM as internal parameter, the differences in peak intensities at the same position were analyzed to distinguish different proteins and evaluate changes in protein structure. Subsequently, the protein content in protein mixtures and serum was quantified and a good linear relationship between peak intensity and protein concentration was obtained. This method shows great promise in the fields of food testing and clinical diagnosis.

Label-free diagnosis of breast cancer based on serum protein purification assisted surface-enhanced Raman spectroscopy

Serum protein is generally used to assess the severity of disease, as well as cancer progression and prognosis. Herein, a simple and rapid serum proteins analysis method combined with surface-enhanced Raman spectroscopy (SERS) technology was applied for breast cancer detection. The cellulose acetate membrane (CA) was employed to extract human serum proteins from 30 breast cancer patients and 45 healthy volunteers and then extracted proteins were mixed with silver nanoparticles for SERS measurement. Additionally, we also mainly assessed the use of different ratios of proteins-silver nanoparticles (Ag NPs) mixture to generate maximum SERS signal for clinical samples detection. Two multivariate statistical analyses, principal component analysis-linear discriminate analysis (PCA-LDA) and partial least square-support vector machines (PLS-SVM) were used to analyze the obtained serum protein SERS spectra and establish the diagnostic model. The results demonstrate that the PLS-SVM model provides superior performance in the classification of breast cancer diagnosis compared with PCA-LDA. This exploratory work demonstrates that the label-free SERS analysis technique combined with CA membrane purified serum proteins has great potential for breast cancer diagnosis.

Construction of Optimal SERS Hotspots Based on Capturing the Spike Receptor-Binding Domain (RBD) of SARS-CoV-2 for Highly Sensitive and Specific Detection by a Fish Model

It is highly challenging to construct the best SERS hotspots for the detection of proteins by surface-enhanced Raman spectroscopy (SERS). Using its own characteristics to construct hotspots can achieve the effect of sensitivity and specificity. In this study, we built a fishing mode device to detect the receptor-binding domain (RBD) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) at low concentrations in different detection environments and obtained a sensitive SERS signal response. Based on the spatial resolution of proteins and their protein-specific recognition functions, SERS hotspots were constructed using aptamers and small molecules that can specifically bind to RBD and cooperate with Au nanoparticles (NPs) to detect RBD in the environment using SERS signals of beacon molecules. Therefore, two kinds of AuNPs modified with aptamers and small molecules were used in the fishing mode device, which can specifically recognize and bind RBD to form a stable hotspot to achieve high sensitivity and specificity for RBD detection. The fishing mode device can detect the presence of RBD at concentrations as low as 0.625 ng/mL and can produce a good SERS signal response within 15 min. Meanwhile, we can detect an RBD of 0.625 ng/mL in the mixed solution with various proteins, and the concentration of RBD in the complex environment of urine and blood can be as low as 1.25 ng/mL. This provides a research basis for SERS in practical applications for protein detection work.

Potential of Raman spectroscopic techniques to study proteins

Proteins are large, complex molecules responsible for various biological processes. However, protein misfolding may lead to various life-threatening diseases. Therefore, it is vital to understand the shape and structure of proteins. Despite numerous techniques, a mechanistic understanding of the protein folding process is still unclear. Therefore, new techniques are continually being explored. In the present article, we have discussed the importance of Raman spectroscopy, Raman Optical Activity (ROA) and various other advancements in Raman spectroscopy to understand protein structure and conformational changes based on the review of our earlier work and recent literature. A Raman spectrum of a protein provides unique signatures for various secondary structures like helices, beta-sheets, turns, random structures, etc., and various amino acid residues such as tyrosine, tryptophan, and phenylalanine. We have shown how Raman spectra can differentiate between bovine serum albumin (BSA) and lysozyme protein based on their difference in sequence and structure (primary, secondary and tertiary). Although it is challenging to elucidate the structure of a protein using a Raman spectrum alone, Raman spectra can be used to differentiate small changes in conformations of proteins such as BSA during melting. Various new advancements in technique and data analyses in Raman spectroscopic studies of proteins have been discussed. The last part of the review focuses on the importance of the ROA spectrum to understand additional features about proteins. The ROA spectrum is rich in information about the protein backbone due to its rigidity compared to its side chains. Furthermore, the ROA spectra of lysozyme and BSA have been presented to show how ROA provides extra information about the solvent properties of proteins.

Probing protein dissociation from gold nanoparticles and the influence of temperature from the protein corona formation mechanism

Gold nanoparticles (AuNPs) provide a novel approach for protein enrichment and analysis due to their protein adsorption properties, forming a so called protein corona. This corona can significantly influence the protein's structure and characteristics, hindering their identification in situ. Dissociation is an important solution to analyze and identify the composition of protein coronas. However, a comprehensive picture of adsorbed protein dissociation is lacking. In this study, the protein dissociation from the protein corona and influencing factors were investigated on the basis of the formation mechanism and time evolution. Temperature and cysteine are the key factors influencing protein dissociation by altering the protein's binding ability. The results showed that half Au–S formation time is an important time point for thio-protein dissociation by the method of high speed centrifugation. When incubated for longer than that time, the thio-protein located in the hard corona could only be separated by β-mercaptoethanol replacement under analytical ultracentrifugation. However, Fourier-transform infrared spectroscopy (FTIR) revealed significant changes that occurred in βlg's secondary structure after ultracentrifugation. The Au–S bond formation time offers the potential to define the protein enrichment time of AuNPs.

A protein corona changes protein's structure and characteristics, hindering their identification in situ. Dissociation is an important solution to identify their composition.

Analysis of Chemisorbed Tribo-Film for Ceramic-on-Ceramic Hip Joint Prostheses by Raman Spectroscopy

To understand the possible lubricant mechanism in ceramic-on-ceramic hip joint prostheses, biochemical reactions of the synovial fluid and the corresponding frictional coefficients were studied. The experiments were performed in a hip joint simulator using the ball-on-cup configuration with balls and cups made from two types of ceramics, BIOLOX^®forte and BIOLOX^®delta. Different lubricants, namely albumin, γ-globulin, hyaluronic acid and three model synovial fluids, were studied in the experiments and Raman spectroscopy was used to analyze the biochemical responses of these lubricants at the interface. BIOLOX^®delta surface was found less reactive to proteins and model fluid lubricants. In contrast, BIOLOX^®forte ball surface has shown chemisorption with both proteins, hyaluronic acid and model fluids imitating total joint replacement and osteoarthritic joint. There was no direct correlation between the measured frictional coefficient and the observed chemical reactions. In summary, the study reveals chemistry of lubricant film formation on ceramic hip implant surfaces with various model synovial fluids and their components.

Interfacial interactions of SERS-active noble metal nanostructures with functional ligands for diagnostic analysis of protein cancer markers

Noble metal nanostructures with designed hot spots have been widely investigated as surface-enhanced Raman spectroscopy (SERS)-active substrates, particularly for selective and sensitive detection of protein cancer markers. For specific target recognition and efficient signal amplification, SERS probe design requires a choice of SERS-active nanostructures as well as their controlled functionalization with Raman dyes and target recognition entities such as antibodies. However, the chemical conjugation of antibodies and Raman dyes to SERS substrates has rarely been discussed to date, despite their substantial roles in detection schemes. The interfacial interactions of metal nanostructures with functional ligands during conjugation are known to be strongly influenced by the various chemical and physical properties of the ligands, such as size, molecular weight, surface charge, 3-dimensional structures, and hydrophilicity/hydrophobicity. In this review, we discuss recent developments in the design of SERS probes over the last 4 years, focusing on their conjugation chemistry for functionalization. A strong preference for covalent bonding is observed with Raman dyes having simpler molecular structures, whereas more complicated ones are non-covalently adsorbed. Antibodies are both covalently and non-covalently bonded to nanostructures, depending on their activity in the SERS probes. Considering that ligand conjugation is highly important for chemical stability, biocompatibility, and functionality of SERS probes, this review is expected to expand the understanding of their interfacial design, leading to SERS as one of the most promising spectroscopic analytical tools for the early detection of protein cancer markers.

Optical tweezers-controlled hotspot for sensitive and reproducible surface-enhanced Raman spectroscopy characterization of native protein structures

Surface-enhanced Raman spectroscopy (SERS) has emerged as a powerful tool to detect biomolecules in aqueous environments. However, it is challenging to identify protein structures at low concentrations, especially for the proteins existing in an equilibrium mixture of various conformations. Here, we develop an in situ optical tweezers-coupled Raman spectroscopy to visualize and control the hotspot between two Ag nanoparticle-coated silica beads, generating tunable and reproducible SERS enhancements with single-molecule level sensitivity. This dynamic SERS detection window is placed in a microfluidic flow chamber to detect the passing-by proteins, which precisely characterizes the structures of three globular proteins without perturbation to their native states. Moreover, it directly identifies the structural features of the transient species of alpha-synuclein among its predominant monomers at physiological concentration of 1 μM by reducing the ensemble averaging. Hence, this SERS platform holds the promise to resolve the structural details of dynamic, heterogeneous, and complex biological systems.

Vibrational Spectra of Nucleotides in the Presence of the Au Cluster Enhancer in MD Simulation of a SERS Sensor

Surface-enhanced Raman scattering (SERS) nanoprobes have shown tremendous potential in in vivo imaging. The development of single oligomer resolution in the SERS promotes experiments on DNA and protein identification using SERS as a nanobiosensor. As Raman scanners rely on a multiple spectrum acquisition, faster imaging in real-time is required. SERS weak signal requires averaging of the acquired spectra that erases information on conformation and interaction. To build spectral libraries, the simulation of measurement conditions and conformational variations for the nucleotides relative to enhancer nanostructures would be desirable. In the molecular dynamic (MD) model of a sensing system, we simulate vibrational spectra of the cytosine nucleotide in FF2/FF3 potential in the dynamic interaction with the Au20 nanoparticles (NP) (EAM potential). Fourier transfer of the density of states (DOS) was performed to obtain the spectra of bonds in reaction coordinates for nucleotides at a resolution of 20 to 40 cm-1. The Au20 was optimized by ab initio density functional theory with generalized gradient approximation (DFT GGA) and relaxed by MD. The optimal localization of nucleotide vs. NP was defined and the spectral modes of both components vs. interaction studied. Bond-dependent spectral maps of nucleotide and NP have shown response to interaction. The marker frequencies of the Au20-nucleotide interaction have been evaluated.

Controllable Self-Assembly of SERS Hotspots in Liquid Environment

Controllable synthesis of novel metal nanoparticles and effective capture of hotspots are of great significance for SERS (surface-enhanced Raman spectroscopy) detection. Therefore, in this paper, a green controllable synthesis method of gold nanoparticle was achieved via epigallocatechin gallate reduction. Different morphologies of gold nanoparticles were synthesized just by changing the solution pH values, and the growth kinetics of AuNPs (gold nanoparticles) were systematically studied. The synthetic AuNPs were put in a droplet to study dynamic variations of self-assembly SERS hotspots from the liquid sol state to the solid dry state. The addition of halogen ions in the droplet can controllably regulate the self-assembly three-dimensional hotspot model of gold nanoparticles in the evaporation process of a droplet, during which the most enhancement effect can be easily captured. The dynamically changing images of nanoparticles in the process were graphically described based on the internal interaction forces of a droplet. Two stronger areas in the changes of SERS intensity were achieved with a high concentration of halogen ions, while only one maximum intensity area was obtained with a low concentration of halogen ions added. This method can effectively avoid complex and unpredictable microenvironments of SERS substrates in the liquid drop, further improving the reproducibility of SERS detection as well as broadening it to biological applications.

Review of Stimulated Raman Scattering Microscopy Techniques and Applications in the Biosciences

Stimulated Raman scattering (SRS) microscopy is a nonlinear optical imaging method for visualizing chemical content based on molecular vibrational bonds. Featuring high speed, high resolution, high sensitivity, high accuracy, and 3D sectioning, SRS microscopy has made tremendous progress toward biochemical information acquisition, cellular function investigation, and label-free medical diagnosis in the biosciences. In this review, the principle of SRS, system design, and data analysis are introduced, and the current innovations of the SRS system are reviewed. In particular, combined with various bio-orthogonal Raman tags, the applications of SRS microscopy in cell metabolism, tumor diagnosis, neuroscience, drug tracking, and microbial detection are briefly examined. The future prospects for SRS microscopy are also shared.

Application of Multiplexed Aptasensors in Food Contaminants Detection

The existence of contaminants in food poses a serious threat to human health. In recent years, aptamer sensors (aptasensors) have been developed rapidly for the detection of food contaminants because of their high specificity, design flexibility, and high efficiency. However, the development of high-throughput, highly sensitive, on-site, and cost-effective methods for simultaneous detection of food contaminants is still restricted due to multiple signal overlap or mutual interference and cross-reaction between different analytes with similar molecular structures. To overcome these problems, this Review summarizes some effective strategies from the articles published in recent years about multiplexed aptasensors for the simultaneous detection of food contaminants. This work focuses on the application of multiplexed aptasensors to simultaneously detect antibiotics, pathogens, and mycotoxins in food. These aptasensors mainly contain fluorescent aptasensors, electrochemical aptasensors, surface-enhanced Raman scattering-based aptasensors, microfluidic chip aptasensors, and paper-based multiplexed aptasensors. In addition, this Review also covers the application of nucleic acid cycle amplification and nanomaterial amplification strategies to improve the detection sensitivity. Finally, the limitations and challenges in the design of multiplexed aptasensor are also taken into account.

Rapid and label-free urine test based on surface-enhanced Raman spectroscopy for the non-invasive detection of colorectal cancer at different stages

The concept of being able to urinate in a cup and screen for colorectal cancer (CRC) is fascinating to the public at large. Here, a simple and label-free urine test based on surface-enhanced Raman spectroscopy (SERS) was employed for CRC detection. Significant spectral differences among normal, stages I-II, and stages III-IV CRC urines were observed. Using discriminant function analysis, the diagnostic sensitivities of 95.8%, 80.9%, and 84.3% for classification of normal, stages I-II, and stages III-IV CRC were achieved in training model, indicating the great promise of urine SERS as a rapid, convenient and noninvasive method for CRC staging detection.

Prediction of Cancer Stem Cell Fate by Surface-Enhanced Raman Scattering Functionalized Nanoprobes

Cancer stem cells (CSCs) are the fundamental building blocks of cancer dissemination, so it is desirable to develop a technique to predict the behavior of CSCs during tumor initiation and relapse. It will provide a powerful tool for pathological prognosis. Currently, there exists no method of such prediction. Here, we introduce nickel-based functionalized nanoprobe facilitated surface enhanced Raman scattering (SERS) for prediction of cancer dissemination by undertaking CSC-based surveillance. SERS profiling of CSCs of various cell lines (breast cancer, cervical cancer, and lung cancer) was compared with their cancer counterparts for the prediction of prognosis, with statistical significance of single-cell sensitivity. The single-cell sensitivity is critical as even a few CSCs are capable of initiating a tumor. Intermediate states of CSC transmutation to cancer cells and its reverse were monitored, and nanoprobe-assisted SERS profiling was undertaken. We experimentally demonstrated that the quasi-intermediate CSC states have dissimilar profiles during the transformation from cancer to CSC and vice versa enabling statistical differentiation without ambiguity. It was also observed that molecular signatures of these opposite pathways are cancer-type specific. This observation provided additional clarity to the current understanding of relatively unfamiliar quasi-intermediate states; making it possible to predict CSC dissemination for variety of cancers with ∼99% accuracy. Nano probe-based prediction of CSC fate is a powerful prediction tool for ultrasensitive prognosis of malignancy in a complex environment. Such CSC-based cancer prognosis has never been proposed before. This prediction technique has potential to provide insights for cancer diagnosis and prognosis as well as for obtaining information instrumental in designing of meaningful CSC-based cancer therapeutics.

Biomarkers Determination Based on Surface-Enhanced Raman Scattering

An overview of noteworthy new methods of biomarker determination based on surface-enhanced Raman scattering (SERS) is presented. Biomarkers can be used to identify the occurrence and development of diseases, which furthers the understanding of biological processes in the body. Accurate detection of a disease-specific biomarker is helpful for the identification, early diagnosis and prevention of a disease and for monitoring during treatment. The search for and discovery of valuable biomarkers have become important research hotspots. Different diseases have different biomarkers, some of which are involved in metabolic processes. Therefore, the fingerprint characteristics and band intensities in SERS spectra have been used to identify metabolites and analyze markers. As a promising technique, SERS has been widely used for the quantitative and qualitative determination of different types of biomarkers for different diseases. SERS techniques provide new technologies for the diagnosis of disease-related markers and determining the basis for clinical treatment. Herein, several SERS-based methods with excellent sensitivity and selectivity for the determination of biomarkers for tumors, viruses, Alzheimer’s disease, cardiac muscle tissue injury, and cell activity are highlighted.

Shell-isolated nanoparticle-enhanced Raman spectroscopy for characterization of living yeast cells

Studying the biochemistry of yeast cells has enabled scientists to understand many essential cellular processes in human cells. Further development of biotechnological and medical progress requires revealing surface chemistry in living cells by using a non-destructive and molecular structure sensitive technique. In this study shell-isolated nanoparticle-enhanced Raman spectroscopy (SHINERS) was applied for probing the molecular structure of Metschnikowia pulcherrima yeast cells. Important function of studied cells is the ability to eliminate iron from growth media by precipitating the insoluble pigment pulcherrimin. Comparative SERS and SHINERS analysis of the yeast cells in combination with bare Au and shell-isolated Au@SiO₂ nanoparticles were performed. It was observed that additional bands, such as adenine ring-related vibrational modes appear due to interaction with bare Au nanoparticles; the registered spectra do not coincide with the spectra where Au@SiO₂ nanoparticles were used. SHINERS spectra of M. pulcherrima were significantly enhanced comparing to the Raman spectra. Based on first-principles calculations and 830-nm excited Raman analysis of pulcherrimin, the SHINERS signatures of iron pigment in yeast cells were revealed. Being protected from direct interaction of metal with adsorbate, Au@SiO₂ nanoparticles yield reproducible and reliable vibrational signatures of yeast cell wall constituents.

Nano-substructured plasmonic pore arrays: a robust, low cost route to reproducible hierarchical structures extended across macroscopic dimensions

Plasmonic nanostructures are important across diverse applications from sensing to renewable energy. Periodic porous array structures are particularly attractive because such topography offers a means to encapsulate or capture solution phase species and combines both propagating and localised plasmonic modes offering versatile addressability. However, in analytical spectroscopic applications, periodic pore arrays have typically reported weaker plasmonic signal enhancement compared to particulate structures. This may be addressed by introducing additional nano-structuring into the array to promote plasmonic coupling that promotes electric field-enhancement, whilst retaining pore structure. Introducing nanoparticle structures into the pores is a useful means to promote such coupling. However, current approaches rely on either expensive top-down methods or on bottom-up methods that yield random particle placement and distribution. This report describes a low cost, top-down technique for preparation of nano-sub-structured plasmonic pore arrays in a highly reproducible manner that can be applied to build arrays extending over macroscopic areas of mm² to cm². The method exploits oxygen plasma etching, under controlled conditions, of the cavity encapsulated templating polystyrene (PS) spheres used to create the periodic array. Subsequent metal deposition leads to reproducible nano-structuring within the wells of the pore array, coined in-cavity nanoparticles (icNPs). This approach was demonstrated across periodic arrays with pore/sphere diameters ranging from 500 nm to 3 μm and reliably improved the plasmonic properties of the substrate across all array dimensions compared to analogous periodic arrays without the nano-structuring. The enhancement factors achieved for metal enhanced emission and surface enhanced Raman spectroscopy depended on the substrate dimensions, with the best performance achieved for nanostructured 2 μm diameter pore arrays, where a more than 10⁴ improvement over Surface Enhanced Raman Spectroscopy (SERS) and 200-fold improvement over Metal Enhanced Fluorescence (MEF) were observed for these substrates compared with analogous unmodified pore arrays. The experiments were supported by Finite-Difference Time-Domain (FDTD) calculations used to simulate the electric field distribution as a function of pore nano-structuring.

A ten-minute, single step, label-free, sample-to-answer assay for qualitative detection of cytokines in serum at femtomolar levels

Label-free electronic affinity based immuno-sensing is an attractive candidate as a platform technology for analyzing biomarkers due to the ease of miniaturization and minimal use of reagents. Electronic based sensing approaches, however, have lagged behind their optical counterparts in terms of detection limit, selectivity, and reliability. Also, the matrix dependent nature of electronic sensing modalities makes difficult the analysis of biomarkers in high salt concentration samples such as serum due to charge screening. We present a novel sensing platform, the micro-well sensor, that works by functionalizing nanoscale volume wells with antibodies and monitoring the impedance change inside the wells due binding of target protein. This detection modality is advantageous to many label-free electronic sensors in that signal power scales with increase in salt concentration, thus improving the sensitivity of the platform. We demonstrate rapid label-free qualitative detection of cytokines within ten minutes at femtoMolar concentrations and a dynamic range of 3 orders of magnitude in serum samples. We describe the design, fabrication, and characterization of the micro-well sensor in serum samples using inflammatory protein biomarkers.

Surface-enhanced Raman scattering analysis of serum albumin via adsorption-exfoliation on hydroxyapatite nanoparticles for noninvasive cancers screening

Combining serum albumin via adsorption-exfoliation on hydroxyapatite particles (HAp) with surface-enhanced Raman scattering (SERS), we developed a novel quantitative analysis of albumin method from blood serum for cancers screening applications. The quantitatively analysis obtained by our HAp method had a good linear relationship from 1 to 10 g/dL, and the lower limit of detection was less than the albumin prognostic factor for disease (3.5 g/dL). Serum albumin was adsorbed and exfoliated by HAp from serum samples of liver cancer patients, breast cancer patients and healthy volunteers and mixed with silver colloids to perform SERS spectral analysis. Based on the PLS-SVM algorithm, the diagnostic accuracies of liver cancer patients and breast cancer patients were 100% and 96.68%, respectively. Moreover, this algorithm successfully predicted the unidentified subjects with a diagnostic accuracy of 93.75%. This exploratory work demonstrated that HAp-adsorbed-exfoliated serum proteins combined with SERS spectroscopy has great potential for cancer screening.

Electrofluidynamic Patterning of Tailorable Nanostructured Substrates for Surface-Enhanced Raman Scattering

The unique attributes of surface enhanced Raman spectroscopy (SERS) make it well suited to address the challenges associated with portable diagnostics. However, despite the remarkable progress in this field, where the instrumentation has made great strides forward providing a route to the miniaturization of sensing devices, to date producing three-dimensional low-cost SERS substrates which simultaneously fulfill the multitude of criteria of high sensitivity, reproducibility, tunability, multiplexity, and integratability for rapid sensing has not yet been accomplished. Successful implementation of SERS requires readily fine-tuned nanostructures, which create a high enhancement. Here, an advanced electrofluidynamic patterning (EFDP) technique enables rapid fabrication of SERS active topographic morphologies with high throughput and at a nanoresolution via the spatial and lateral modulation of the dielectric discontinuity due to the high electric field generated across the polymer nanofilm and air gap. The subsequent formation of displacement charges within the nanofilm by coupling to the electric field yield a destabilizing electrostatic pressure and amplification of EFDP instabilities enabling the controllable pattern formation. The top of each gold coated EFDP fabricated pillar generates controllable high SERS enhancement by coupling of surface plasmon modes on top of the pillar, with each nanostructure acting as an individual sensing unit. The absolute enhancement factor depends on the topology as well as the tunable dimensions of the nanostructured units, and these are optimized in the design and engineering of the dedicated EFDP apparatus for reproducible, low-cost fabrication of the three-dimensional nanoarchitectures on macrosurfaces, rendering them for easy integration in further lab-on-a-chip devices. This unique combination of nanomaterials and nanospectroscopic systems lay the platform for a variety of applications in chemical and biological sensing.

Reliable Quantification of pH Variation in Live Cells Using Prussian Blue-Caged Surface-Enhanced Raman Scattering Probes

Intracellular pH is an important parameter that is highly associated with diverse physiological processes. The reliable measurement of pH values inside cells remains a formidable challenge because of the complexity of cytoplasm. Herein, we report a robust Prussian blue (PB)-caged pH-responsive surface-enhanced Raman scattering (SERS) probe for precisely mapping the dynamic pH values in live cells. The PB shell has a subnanoscale porous structure that allows only very small biospecies such as H⁺ or OH^- to pass freely through the shell and react with the encased pH-responsive SERS probe, while physically resisting the entry of large biomolecules. This probe achieved unmatched detection linearity (R² > 0.999) for pH measurements in diverse complex biological samples. Moreover, the nitrile (C≡N) in PB shows a sharp band in the cellular Raman-silent region, which serves as a background-free internal standard for accurate profiling of the probe distribution inside the cells. We applied the proposed probe to monitor the dynamic pH changes during cellular autophagy induced by different stimuli and thereby demonstrated that the PB-caged probe can reliably quantify subtle intracellular pH variations, providing an effective tool for revealing the relationship between abnormal intracellular pH and cellular functions.

Molecular Spectroscopic Markers of Abnormal Protein Aggregation

Abnormal protein aggregation has been intensively studied for over 40 years and broadly discussed in the literature due to its significant role in neurodegenerative diseases etiology. Structural reorganization and conformational changes of the secondary structure upon the aggregation determine aggregation pathways and cytotoxicity of the aggregates, and therefore, numerous analytical techniques are employed for a deep investigation into the secondary structure of abnormal protein aggregates. Molecular spectroscopies, including Raman and infrared ones, are routinely applied in such studies. Recently, the nanoscale spatial resolution of tip-enhanced Raman and infrared nanospectroscopies, as well as the high sensitivity of the surface-enhanced Raman spectroscopy, have brought new insights into our knowledge of abnormal protein aggregation. In this review, we order and summarize all nano- and micro-spectroscopic marker bands related to abnormal aggregation. Each part presents the physical principles of each particular spectroscopic technique listed above and a concise description of all spectral markers detected with these techniques in the spectra of neurodegenerative proteins and their model systems. Finally, a section concerning the application of multivariate data analysis for extraction of the spectral marker bands is included.

Hierarchical Fabrication of Plasmonic Superlattice Membrane by Aspect-Ratio Controllable Nanobricks for Label-Free Protein Detection

Plasmonic superlattice membrane exhibits remarkable functional properties that are emerging from engineered assemblies of well-defined “meta-atoms,” which is featured as a conceptual new category of two-dimensional optical metamaterials. The ability to build plasmonic membranes over macroscopic surfaces but with nanoscale ordering is crucial for systematically controlling the light-matter interactions and represents considerable advances for the bottom-up fabrication of soft optoelectronic devices and circuits. Through rational design, novel nanocrystals, and by engineering the packing orders, the hybridized plasmon signature can be customized, promoting controllable near-field confinement for surface-enhanced Raman scattering (SERS) based detection. However, building such 2D architectures has proven to be remarkably challenging due to the complicated interparticle forces and multiscale interactions during self-assembly. Here, we report on the fabrication of ultralong-nanobrick-based giant plasmonic superlattice membranes as high-performance SERS substrates for ultrasensitive and label-free protein detection. Using aspect-ratio controllable short-to-ultralong nanobricks as building blocks, we construct three distinctive plasmonic membranes by polymer-ligand-based strategy in drying-mediated self-assembly at the air/water interfaces. The plasmonic membranes exhibit monolayered morphology with nanoscale assembled ordering but macroscopic lateral dimensions, inducing enhanced near-field confinement and uniform hot-spot distribution. By choosing 4-aminothiophenol and bovine serum albumin (BSA) as a model analyte, we establish an ultrasensitive assay for label-free SERS detection. The detection limit of BSA can reach 15 nM, and the enhancement factor reached 4.3 × 10⁵, enabling a promising avenue for its clinical application in ultrasensitive biodiagnostics.

3D Ultrasensitive Polymers-Plasmonic Hybrid Flexible Platform for In-Situ Detection

This paper introduces a three-dimensional (3D) pyramid to the polymers-plasmonic hybrid structure of polymethyl methacrylate (PMMA) composite silver nanoparticle (AgNPs) as a higher quality flexible surface-enhanced Raman scattering (SERS) substrate. Benefiting from the effective oscillation of light inside the pyramid valley could provide wide distributions of 3D “hot spots” in a large space. The inclined surface design of the pyramid structure could facilitate the aggregation of probe molecules, which achieves highly sensitive detection of rhodamine 6G (R6G) and crystal violet (CV). In addition, the AgNPs and PMMA composite structures provide uniform space distribution for analyte detection in a designated hot spot zone. The incident light can penetrate the external PMMA film to trigger the localized plasmon resonance of the encapsulated AgNPs, achieving enormous enhancement factor (~6.24×108). After undergoes mechanical deformation, the flexible SERS substrate still maintains high mechanical stability, which was proved by experiment and theory. For practical applications, the prepared flexible SERS substrate is adapted to the in-situ Raman detection of adenosine aqueous solution and the methylene-blue (MB) molecule detection of the skin of a fish, providing a direct and nondestructive active-platform for the detecting on the surfaces with any arbitrary morphology and aqueous solution.

6-Aza-2-Thio-Thymine Stabilized Gold Nanoclusters as Photoluminescent Probe for Protein Detection

This study puts forward an efficient method for protein detection in virtue of the tremendous fluorescence enhancement property of 6-aza-2-thio-thymine protected gold nanoclusters (ATT-AuNCs). In-depth studies of the protein-induced photoluminescence enhancement mechanism illustrate the mechanism of the interaction between ATT-AuNCs and protein. This new-established probe enables feasible and sensitive quantification of the concentrations of total protein in real samples, such as human serum, human plasma, milk, and cell extracts. The results of this proposed method are in good agreement with those determined by the classical bicinchoninic acid method (BCA method).

Sensing of circulating cancer biomarkers with metal nanoparticles

The analysis of circulating cancer biomarkers, including cell-free and circulating tumor DNA, circulating tumor cells, microRNA and exosomes, holds promise in revolutionizing cancer diagnosis and prognosis using body fluid analysis, also known as liquid biopsy. To enable clinical application of these biomarkers, new analytical tools capable of detecting them in very low concentrations in complex sample matrixes are needed. Metal nanoparticles have emerged as extraordinary analytical scaffolds because of their unique optoelectronic properties and ease of functionalization. Hence, multiple analytical techniques have been developed based on these nanoparticles and their plasmonic properties. The aim of this review is to summarize and discuss the present development on the use of metal nanoparticles for the analysis of circulating cancer biomarkers. We examine how metal nanoparticles can be used as (1) analytical transducers in various sensing principles, such as aggregation induced colorimetric assays, plasmon resonance energy transfer, surface enhanced Raman spectroscopy, and refractive index sensing, and (2) signal amplification elements in surface plasmon resonance spectroscopy and electrochemical detection. We critically discuss the clinical relevance of each category of circulating biomarkers, followed by a thorough analysis of how these nanoparticle-based designs have overcome some of the main challenges that gold standard analytical techniques currently face, and what new directions the field may take in the future.

Challenges in SERS-based pesticide detection and plausible solutions

Surface-enhanced Raman spectroscopy (SERS) can be used for the detection of trace amounts of pesticides in foods to ensure consumer safety. In this perspective, we highlight the trends of SERS-based assays in pesticide detection and the various challenges associated with their selectivity, reproducibility, and nonspecific binding. We also discuss and compare the target analyte capture techniques, such as the use of antibodies, aptamers, and molecularly imprinted polymers (MIPs), coupled with SERS to overcome the drawbacks as mentioned above. In addition, issues related to the nonspecific binding of analytes and its potential solution are discussed.

Reusable Silicon-Based SERS Chip for Ratiometric Analysis of Fluoride Ion in Aqueous Solutions

An innovative ratiometric surface-enhanced Raman scattering (SERS) sensor using a 4-mercaptoboric acid (4-MPBA)-modified silver nanoparticle-decorated silicon wafer (Si@Ag NPs chip) was proposed for the ultrasensitive determination of F^- ions in aqueous solutions. The principle of sensing strategy is based on fluoride-induced structural symmetry breaking and charge redistribution of phenylboronic acid, leading to a band shift of the C-C stretching mode of 4-MPBA from 1589 to 1576 cm^-1. Accordingly, a ratiometric signal of the area ratio (A₁₅₇₆/A₁₅₈₉) between the fluoride-bond MPBA molecules and unoccupied MPBA molecules can be used for the quantitative response of F^- ions. In comparison with other SERS-based sensing methods, this ratiometric method can avoid a large error resulting from the inhomogeneity of substrates. Under the optimized analytical conditions, the proposed SERS sensor possesses a quick response to F^- ions within 2 min and exhibits high selectivity for F^- ions with the determination limit of 10^-8 M, which is over 3 orders of magnitude lower than the World Health Organization (WHO) guideline value for F^- ions in drinking water. Of particular significance, the present sensor features favorable recyclability, which preserves suitable reproducibility during 6-time cyclic determination of F^- ions. The practical utility of this sensing system for the determination of F^- ions was tested with real water and toothpaste samples, and the results demonstrate that this sensor shows high recoveries (90-110%). Given its simple principle and easy operation, the present silicon-based SERS sensor could serve as a promising sensor for various practical applications.

SERS-Active Substrates Nanoengineering Based on e-Beam Evaporated Self-Assembled Silver Films

Surface-enhanced Raman spectroscopy (SERS) has been intensely studied as a possible solution in the fields of analytical chemistry and biosensorics for decades. Substantial research has been devoted to engineering signal enhanced SERS-active substrates based on semi-continuous nanostructured silver and gold films, or agglomerates of micro- and nanoparticles in solution. Herein, we demonstrate the high-amplitude spectra of myoglobin precipitated out of ultra-low concentration solutions (below 10 μg/mL) using e-beam evaporated continuous self-assembled silver films. We observe up to 105 times Raman signal amplification with purposefully designed SERS-active substrates in comparison with the control samples. SERS-active substrates are obtained by electron beam evaporation of silver thin films with well controlled nanostructured surface morphology. The characteristic dimensions of the morphology elements vary in the range from several to tens of nanometers. Using optical confocal microscopy we demonstrate that proteins form a conformation on the surface of the self-assembled silver film, which results in an effective enhancement of giant Raman scattering signal. We investigate the various SERS substrates surface morphologies by means of atomic force microscopy (AFM) in combination with deep data analysis with Gwyddion software and a number of machine learning techniques. Based on these results, we identify the most significant film surface morphology patterns and evaporation recipe parameters to obtain the highest amplitude SERS spectra. Moreover, we demonstrate the possibility of automated selection of suitable morphological parameters to obtain the high-amplitude spectra. The developed AFM data auto-analysis procedures are used for smart optimization of SERS-active substrates nanoengineering processes.