Label-Free SERS Selective Detection of Dopamine and Serotonin Using Graphene-Au Nanopyramid Heterostructure

Oppositely-charged silver nanoparticles enable selective SERS molecular enhancement through electrostatic interactions

Label-free surface-enhanced Raman spectroscopy (SERS) has attracted extensive attention as an emerging technique for molecular phenotyping of biological samples. However, the selective enhancement property of SERS mediated by complicated interactions between substrates and analytes is unfavorable for molecular profiling. The electrostatic force is among the most dominating interactions that can cause selective adsorption of molecules to charged substrates. This means if only negatively- or positively-charged SERS substrates are applied, then considerable SERS information from a portion of analytes would be lost, hindering comprehensive SERS sensing. In this work, we utilize both negatively- and positively-charged colloidal silver (Ag) nanoparticles (NPs) to detect various charged molecules. The negatively-charged citrate-stabilized Ag and the positively-charged Ag prepared via a cetyltrimethyl-ammonium chloride-based charge reversal protocol have been adopted as SERS substrates. The Ag NPs are all relatively well-dispersed with good uniformity. After applying the oppositely-charged NPs to the detection of charged molecules, we find the SERS results explicitly demonstrate the electrostatically-driven SERS selective enhancement, which is further supported and clarified by molecular electrostatic potential calculations. Our work highlights the importance of developing SERS substrates modified with appropriate surface charges for various analytes, and enlightens us that potentially more molecular SERS information can be acquired from complex bio-samples using combinations of oppositely-charged substrates.

Surface-Enhanced Raman Scattering Nanosensing and Imaging in Neuroscience

Monitoring neurochemicals and imaging the molecular content of brain tissues in vitro, ex vivo, and in vivo is essential for enhancing our understanding of neurochemistry and the causes of brain disorders. This review explores the potential applications of surface-enhanced Raman scattering (SERS) nanosensors in neurosciences, where their adoption could lead to significant progress in the field. These applications encompass detecting neurotransmitters or brain disorders biomarkers in biofluids with SERS nanosensors, and imaging normal and pathological brain tissues with SERS labeling. Specific studies highlighting in vitro, ex vivo, and in vivo analysis of brain disorders using fit-for-purpose SERS nanosensors will be detailed, with an emphasis on the ability of SERS to detect clinically pertinent levels of neurochemicals. Recent advancements in designing SERS-active nanomaterials, improving experimentation in biofluids, and increasing the usage of machine learning for interpreting SERS spectra will also be discussed. Furthermore, we will address the tagging of tissues presenting pathologies with nanoparticles for SERS imaging, a burgeoning domain of neuroscience that has been demonstrated to be effective in guiding tumor removal during brain surgery. The review also explores future research applications for SERS nanosensors in neuroscience, including monitoring neurochemistry in vivo with greater penetration using surface-enhanced spatially offset Raman scattering (SESORS), near-infrared lasers, and 2-photon techniques. The article concludes by discussing the potential of SERS for investigating the effectiveness of therapies for brain disorders and for integrating conventional neurochemistry techniques with SERS sensing.

Label-free single-vesicle based surface enhanced Raman spectroscopy: A robust approach for investigating the biomolecular composition of small extracellular vesicles

Small extracellular vesicles (sEVs) are cell-released vesicles ranging from 30-150nm in size. They have garnered increasing attention because of their potential for both the diagnosis and treatment of disease. The diversity of sEVs derives from their biological composition and cargo content. Currently, the isolation of sEV subpopulations is primarily based on bio-physical and affinity-based approaches. Since a standardized definition for sEV subpopulations is yet to be fully established, it is important to further investigate the correlation between the biomolecular composition of sEVs and their physical properties. In this study, we employed a platform combining single-vesicle surface-enhanced Raman spectroscopy (SERS) and machine learning to examine individual sEVs isolated by size-exclusion chromatography (SEC). The biomolecular composition of each vesicle examined was reflected by its corresponding SERS spectral features (biomolecular "fingerprints"), with their roots in the composition of their collective Raman-active bonds. Origins of the SERS spectral features were validated through a comparative analysis between SERS and mass spectrometry (MS). SERS fingerprinting of individual vesicles was effective in overcoming the challenges posed by EV population averaging, allowing for the possibility of analyzing the variations in biomolecular composition between the vesicles of similar and/or different sizes. Using this approach, we uncovered that each of the size-based fractions of sEVs contained particles with predominantly similar SERS spectral features. Indeed, more than 84% of the vesicles residing within a particular group were clearly distinguishable from that of the other EV sub-populations, despite some spectral variations within each sub-population. Our results suggest the possibility that size-based EV fractionation methods produce samples where similarly eluted sEVs are correlated with their respective biochemical contents, as reflected by their SERS spectra. Our findings therefore highlight the possibility that the biogenesis and respective biological functionalities of the various sEV fractions may be inherently different.

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.

Nonlinear study of indolamines: A hidden property that might have possible implications in neurodegeneration

Indolamines (e.g., serotonin and melatonin) are tryptophan-derived class of neurotransmitters and neuromodulators that play crucial roles in mood regulation, sleep-wake cycles, and gastrointestinal functions. These biogenic amines exert their effects by binding to specific receptors in the central nervous system, influencing neuronal activity and signalling cascades. Indolamines are vital in maintaining homeostasis, and imbalances in their levels have been implicated in various neurological and psychiatric disorders. Hence, in the present study, we have investigated the nonlinear properties of indolamines under a continuous wave (CW) and pulsed laser excitation using the closed-aperture (CA) Z-scan technique. The CA Z-scan is a cost-effective and sensitive analytical tool for investigating nonlinear properties. It is observed that indolamines show negative refractive and positive absorptive nonlinearity under in vitro physiological conditions. The origin of nonlinearity is ascribed to the thermo-optical effect governed by the saturated atomic absorption and molecular orientation mechanisms under CW and pulsed laser excitation, respectively. The strength of nonlinearity is found to vary linearly with the concentration of indolamines. Overall, serotonin possesses stronger nonlinearity than melatonin. The maximum nonlinearity (refractive index (n2) & absorption coefficient (β)) for melatonin under CW and pulsed laser excitations are (-1.266 × 10-12 m2W-1 and -1.883 × 10-17 m2W-1) & (8.046 × 10-8 mW-1 and 1.516 × 10-13 mW-1), respectively. Meanwhile, the maximum n2 and β under pulsed laser excitation for serotonin are obtained as -3.195 × 10-17 m2W-1 and 6.149 × 10-12 mW-1, respectively. The outcome of the results may be utilized in understanding processes mediated by indolamines and designing therapeutic interventions.

AI-Driven Spectral Decomposition: Predicting the Most Probable Protein Compositions from Surface Enhanced Raman Spectroscopy Spectra of Amino Acids

Surface-enhanced Raman spectroscopy (SERS) is a powerful tool for elucidating the molecular makeup of materials. It possesses the unique characteristics of single-molecule sensitivity and extremely high specificity. However, the true potential of SERS, particularly in capturing the biochemical content of particles, remains underexplored. In this study, we harnessed transformer neural networks to interpret SERS spectra, aiming to discern the amino acid profiles within proteins. By training the network on the SERS profiles of 20 amino acids of human proteins, we explore the feasibility of predicting the predominant proteins within the µL-scale detection volume of SERS. Our results highlight a consistent alignment between the model's predictions and the protein's known amino acid compositions, deepening our understanding of the inherent information contained within SERS spectra. For instance, the model achieved low root mean square error (RMSE) scores and minimal deviation in the prediction of amino acid compositions for proteins such as Bovine Serum Albumin (BSA), ACE2 protein, and CD63 antigen. This novel methodology offers a robust avenue not only for protein analytics but also sets a precedent for the broader realm of spectral analyses across diverse material categories. It represents a solid step forward to establishing SERS-based proteomics.

Transferable G/Au Film for Constructing a Variety of SERS Substrates

Surface-enhanced Raman scattering (SERS), as one of the most powerful analytical methods, undertakes important inspection tasks in various fields. Generally, the performance of an SERS-active substrate relies heavily on its structure, which makes it difficult to integrate multiple-functional detectability on the same substrate. To address this problem, here we designed and constructed a film of graphene/Au nanoparticles (G/Au film) through a simple method, which can be conveniently transferred to different substrates to form various composite SERS substrates subsequently. By means of the combination of the electromagnetic enhancement mechanism (EM) and the chemical enhancement mechanism (CM) of this structure, the film realized good SERS performance experimentally, with the enhancement factor (EF) approaching ca. 1.40 × 105. In addition, the G/Au film had high mechanical strength and had large specific surface area and good biocompatibility that is beneficial for Raman detection. By further transferring the film to an Ag/Si composite substrate and PDMS flexible film, it showed enhanced sensitivity and in situ detectability, respectively, indicating high compatibility and promising prospect in Raman detection.

Recent progress in SERS monitoring of photocatalytic reactions

Surface-enhanced Raman spectroscopy (SERS) is a powerful analytical technique renowned for its ultra-high sensitivity. Extensive research in SERS has led to the development of a wide range of SERS substrates, including plasmonic metals, semiconductors, metal organic frameworks, and their assemblies. Some of these materials are also excellent photocatalysts, and by taking advantage of their bifunctional characteristics, the photocatalytic processes that occur on their surface can be monitored in situ via SERS. This provides us with unique opportunities to gain valuable insights into the intricate details of the photocatalytic processes that are challenging to access using other techniques. In this review, we highlight key development in in situ and/or real-time SERS-tracking of photocatalytic reactions. We begin by providing a brief account of recent developments in SERS substrates, followed by discussions on how SERS can be used to elucidate crucial aspects of photocatalytic processes, including: (1) the influence of the surrounding media on charge carrier extraction; (2) the direction of charge carrier transfer; (3) the pathway of photocatalytic activation; and (4) differentiation between the effects of photo-thermal and energetic electrons. Additionally, we discuss the benefits of tip-enhanced Raman spectroscopy (TERS) due to the ability to achieve high-spatial-resolution measurements. Finally, we address major challenges and propose potential directions for the future of SERS monitoring of photocatalytic reactions. By leveraging the capabilities of SERS, we can uncover new insights into photocatalytic processes, paving the way for advancements in sustainable energy and environmental remediation.

Aggregation of Ag nanoparticle based on surface acoustic wave for surface-enhanced Raman spectroscopy detection of dopamine

BACKGROUND

Dopamine (DA), a vital neurotransmitter, plays a critical role in the human brain and relates to neuropsychiatric disorders such as Parkinson's disease and schizophrenia. Numerous studies have explored detection of such biomarkers through surface-enhanced Raman spectroscopy (SERS). However, most of the studies focused on SERS detection face significant challenges with plasmonic nanostructure development. Such challenges often include time-consuming processes, complex fabrication, specialized chemical labeling, poor reproducibility, and random hotspot generation. Therefore, the need for simple and rapid nanostructure development is evident in SERS.

RESULTS

We propose an innovative SERS-active sensing technique for 50 nm silver nanoparticle (AgNP) clustering based on surface acoustic wave (SAW). When a 1 μL droplet of AgNP colloid is dispensed onto the SAW-propagation zone, the AgNP cluster is deposited after the droplet completely evaporates, developing plasmonic nanogaps for SERS hotspot caused by spherical AgNP aggregation. By optimizing the SAW system through the hydrophobic treatment and modulation of the operational power, the SAW-induced AgNP clustering showed densely packed AgNP within a dot-like configuration (∼2200 AgNP μm-2), effectively preventing particle welding. The characterization of 4-mercaptobenzoic acid as a probe analyte revealed that concentrations as low as 1.14 pM was detected using our SAW-SERS system under 785 nm laser excitation. Moreover, DA was detected up to 4.28 nM with a determination of 0.99 (R2).

SIGNIFICANCE

This technique for AgNP clustering induced by SAW provides a rapid, in situ, label-free SERS sensing method with outstanding sensitivity and linearity. A mere act of dropping can create extensive plasmonic hotspots featuring nanogap of ∼1.5 nm. The SAW-induced AgNP clustering can serve as an ultrasensitive SERS-active substrate for diverse molecular detections, including neurotransmitter detection.

Controlling the Nucleation and Growth of Salt from Bodily Fluid for Enhanced Biosensing Applications

Surface-enhanced Raman spectroscopy (SERS) represents a transformative tool in medical diagnostics, particularly for the early detection of key biomarkers such as small extracellular vesicles (sEVs). Its unparalleled sensitivity and compatibility with intricate biological samples make it an ideal candidate for revolutionizing noninvasive diagnostic methods. However, a significant challenge that mars its efficacy is the throughput limitation, primarily anchored in the prerequisite of hotspot and sEV colocalization within a minuscule range. This paper delves deep into this issue, introducing a never-attempted-before approach which harnesses the principles of crystallization-nucleation and growth. By synergistically coupling lasers with plasmonic resonances, we navigate the challenges associated with the analyte droplet drying method and the notorious coffee ring effect. Our method, rooted in a profound understanding of crystallization's materials science, exhibits the potential to significantly increase the areal density of accessible plasmonic hotspots and efficiently guide exosomes to defined regions. In doing so, we not only overcome the throughput challenge but also promise a paradigm shift in the arena of minimally invasive biosensing, ushering in advanced diagnostic capabilities for life-threatening diseases.

An electrochemical ratiometric biosensor for the detection of dopamine based on an MXene-Au nanocomposite

Compared with single signal detection, a ratiometric biosensor could offer more accurate and reliable results. Here, a ratiometric electrochemical biosensor for the sensitive and accurate detection of dopamine was developed based on the strong adsorption ability of MXene-Au toward methylene blue, an inner reference element. This ratiometric sensing strategy opened up a new avenue for the development of a ratiometric platform.

Nano-biosensor for SARS-CoV-2/COVID-19 detection: methods, mechanism and interface design

The epidemic of coronavirus disease 2019 (COVID-19) was a huge disaster to human society. The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which led to COVID-19, has resulted in a large number of deaths. Even though the reverse transcription-polymerase chain reaction (RT-PCR) is the most efficient method for the detection of SARS-CoV-2, the disadvantages (such as long detection time, professional operators, expensive instruments, and laboratory equipment) limit its application. In this review, the different kinds of nano-biosensors based on surface-enhanced Raman scattering (SERS), surface plasmon resonance (SPR), field-effect transistor (FET), fluorescence methods, and electrochemical methods are summarized, starting with a concise description of their sensing mechanism. The different bioprobes (such as ACE2, S protein-antibody, IgG antibody, IgM antibody, and SARS-CoV-2 DNA probes) with different bio-principles are introduced. The key structural components of the biosensors are briefly introduced to give readers an understanding of the principles behind the testing methods. In particular, SARS-CoV-2-related RNA mutation detection and its challenges are also briefly described. We hope that this review will encourage readers with different research backgrounds to design SARS-CoV-2 nano-biosensors with high selectivity and sensitivity.

A Review on Integrated ZnO-Based SERS Biosensors and Their Potential in Detecting Biomarkers of Neurodegenerative Diseases

Surface-enhanced Raman spectroscopy (SERS) applications in clinical diagnosis and spectral pathology are increasing due to the potential of the technique to bio-barcode incipient and differential diseases via real-time monitoring of biomarkers in fluids and in real-time via biomolecular fingerprinting. Additionally, the rapid advancements in micro/nanotechnology have a visible influence in all aspects of science and life. The miniaturization and enhanced properties of materials at the micro/nanoscale transcended the confines of the laboratory and are revolutionizing domains such as electronics, optics, medicine, and environmental science. The societal and technological impact of SERS biosensing by using semiconductor-based nanostructured smart substrates will be huge once minor technical pitfalls are solved. Herein, challenges in clinical routine testing are addressed in order to understand the context of how SERS can perform in real, in vivo sampling and bioassays for early neurodegenerative disease (ND) diagnosis. The main interest in translating SERS into clinical practice is reinforced by the practical advantages: portability of the designed setups, versatility in using nanomaterials of various matter and costs, readiness, and reliability. As we will present in this review, in the frame of technology readiness levels (TRL), the current maturity reached by semiconductor-based SERS biosensors, in particular that of zinc oxide (ZnO)-based hybrid SERS substrates, is situated at the development level TRL 6 (out of 9 levels). Three-dimensional, multilayered SERS substrates that provide additional plasmonic hot spots in the z-axis are of key importance in designing highly performant SERS biosensors for the detection of ND biomarkers.

Analyzing bronchoalveolar fluid derived small extracellular vesicles using single-vesicle SERS for non-small cell lung cancer detection

An emerging body of research by biologists and clinicians has demonstrated the clinical application of small extracellular vesicles (sEVs, also commonly referred to as exosomes) as biomarkers for cancer detections. sEVs isolated from various body fluids such as blood, saliva, urine, and cerebrospinal fluid have been used for biomarker discoveries with highly encouraging outcomes. Among the biomarkers discovered are those responsible for multiple cancer types and immune responses. These biomarkers are recapitulated from the tumor microenvironments. Yet, despite numerous discussions of sEVs in scientific literature, sEV-based biomarkers have so far played only a minor role for cancer diagnostics in the clinical setting, notably less so than other techniques such as imaging and biopsy. In this paper, we report the results of a pilot study (n = 10 from each of the patient and the control group) using bronchoalveolar lavage fluid to determine the presence of sEVs related to non-small cell lung cancer in twenty clinical samples examined using surface enhanced Raman spectroscopy (SERS).

Plier Ligands for Trapping Neurotransmitters into Complexes for Sensitive Analysis by SERS Spectroscopy

Catecholamines-dopamine, noradrenaline and adrenaline are important biomarkers of neurotransmitter metabolism, indicating neuroendocrine tumors and neurodegenerative diseases. Surface-enhanced Raman spectroscopy (SERS) is a promising analytical technique with unprecedented multiplexing capabilities. However, not all important analytes exhibit strong SERS signals on stable and robust nanostructured substrates. In this work, we propose a novel indicator system based on the formation of mixed ligand complexes with bispidine-based bis-azole ligands which can serve as pliers to trap Cu(II) ions and stabilize its complexes with catecholamines. Four synthesized ligands with different functional groups: carboxyl, amino, benzyl, and methoxybenzyl, were applied for forming stable complexes to shift maximum absorbance of catecholamines from the ultraviolet region to 570-600 nm. A new absorbance band in the visible range resonates with the local surface plasmon resonance (LSPR) band of metal nanoparticles and most used laser wavelengths. This match allowed use of Molecular Immobilization and Resonant Raman Amplification by Complex-Loaded Enhancers (MIRRACLE) methodology to measure intense Raman signals on a nanostructured silver-based SERS-active substrate. The synthesized plier-like ligands fixed and stabilized catecholamine complexes with Cu(II) on the SERS sensor surface, which facilitated the determination of dopamine in a 3.2 × 10^-12-1 × 10^-8 M concentration range.

Advanced theragnostics for the central nervous system (CNS) and neurological disorders using functional inorganic nanomaterials

Various types of inorganic nanomaterials are capable of diagnostic biomarker detection and the therapeutic delivery of a disease or inflammatory modulating agent. Those multi-functional nanomaterials have been utilized to treat neurodegenerative diseases and central nervous system (CNS) injuries in an effective and personalized manner. Even though many nanomaterials can deliver a payload and detect a biomarker of interest, only a few studies have yet to fully utilize this combined strategy to its full potential. Combining a nanomaterial's ability to facilitate targeted delivery, promote cellular proliferation and differentiation, and carry a large amount of material with various sensing approaches makes it possible to diagnose a patient selectively and sensitively while offering preventative measures or early disease-modifying strategies. By tuning the properties of an inorganic nanomaterial, the dimensionality, hydrophilicity, size, charge, shape, surface chemistry, and many other chemical and physical parameters, different types of cells in the central nervous system can be monitored, modulated, or further studies to elucidate underlying disease mechanisms. Scientists and clinicians have better understood the underlying processes of pathologies for many neurologically related diseases and injuries by implementing multi-dimensional 0D, 1D, and 2D theragnostic nanomaterials. The incorporation of nanomaterials has allowed scientists to better understand how to detect and treat these conditions at an early stage. To this end, having the multi-modal ability to both sense and treat ailments of the central nervous system can lead to favorable outcomes for patients suffering from such injuries and diseases.

Surface potential modulation as a tool for mitigating challenges in SERS-based microneedle sensors

Raman spectroscopic-based biosensing strategies are often complicated by low signal and the presence of multiple chemical species. While surface-enhanced Raman spectroscopy (SERS) nanostructured platforms are able to deliver high quality signals by focusing the electromagnetic field into a tight plasmonic hot-spot, it is not a generally applicable strategy as it often depends on the specific adsorption of the analyte of interest onto the SERS platform. This paper describes a strategy to address this challenge by using surface potential as a physical binding agent in the context of microneedle sensors. We show that the potential-dependent adsorption of different chemical species allows scrutinization of the contributions of different chemical species to the final spectrum, and that the ability to cyclically adsorb and desorb molecules from the surface enables efficient application of multivariate analysis methods. We demonstrate how the strategy can be used to mitigate potentially confounding phenomena, such as surface reactions, competitive adsorption and the presence of molecules with similar structures. In addition, this decomposition helps evaluate criteria to maximize the signal of one molecule with respect to others, offering new opportunities to enhance the measurement of analytes in the presence of interferants.

Gold Nanopyramid Arrays for Non-Invasive Surface-Enhanced Raman Spectroscopy-Based Gastric Cancer Detection via sEVs

Gastric cancer (GC) is one of the most common and lethal types of cancer affecting over one million people, leading to 768,793 deaths globally in 2020 alone. The key for improving the survival rate lies in reliable screening and early diagnosis. Existing techniques including barium-meal gastric photofluorography and upper endoscopy can be costly and time-consuming and are thus impractical for population screening. We look instead for small extracellular vesicles (sEVs, currently also referred as exosomes) sized ⌀ 30-150 nm as a candidate. sEVs have attracted a significantly higher level of attention during the past decade or two because of their potentials in disease diagnoses and therapeutics. Here, we report that the composition information of the collective Raman-active bonds inside sEVs of human donors obtained by surface-enhanced Raman spectroscopy (SERS) holds the potential for non-invasive GC detection. SERS was triggered by the substrate of gold nanopyramid arrays we developed previously. A machine learning-based spectral feature analysis algorithm was developed for objectively distinguishing the cancer-derived sEVs from those of the non-cancer sub-population. sEVs from the tissue, blood, and saliva of GC patients and non-GC participants were collected (n = 15 each) and analyzed. The algorithm prediction accuracies were reportedly 90, 85, and 72%. "Leave-a-pair-of-samples out" validation was further performed to test the clinical potential. The area under the curve of each receiver operating characteristic curve was 0.96, 0.91, and 0.65 in tissue, blood, and saliva, respectively. In addition, by comparing the SERS fingerprints of individual vesicles, we provided a possible way of tracing the biogenesis pathways of patient-specific sEVs from tissue to blood to saliva. The methodology involved in this study is expected to be amenable for non-invasive detection of diseases other than GC.

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.

Prospects of Surface-Enhanced Raman Spectroscopy for Biomarker Monitoring toward Precision Medicine

Future precision medicine will be undoubtedly sustained by the detection of validated biomarkers that enable a precise classification of patients based on their predicted disease risk, prognosis, and response to a specific treatment. Up to now, genomics, transcriptomics, and immunohistochemistry have been the main clinically amenable tools at hand for identifying key diagnostic, prognostic, and predictive biomarkers. However, other molecular strategies, including metabolomics, are still in their infancy and require the development of new biomarker detection technologies, toward routine implementation into clinical diagnosis. In this context, surface-enhanced Raman scattering (SERS) spectroscopy has been recognized as a promising technology for clinical monitoring thanks to its high sensitivity and label-free operation, which should help accelerate the discovery of biomarkers and their corresponding screening in a simpler, faster, and less-expensive manner. Many studies have demonstrated the excellent performance of SERS in biomedical applications. However, such studies have also revealed several variables that should be considered for accurate SERS monitoring, in particular, when the signal is collected from biological sources (tissues, cells or biofluids). This Perspective is aimed at piecing together the puzzle of SERS in biomarker monitoring, with a view on future challenges and implications. We address the most relevant requirements of plasmonic substrates for biomedical applications, as well as the implementation of tools from artificial intelligence or biotechnology to guide the development of highly versatile sensors.

DNA Origami-Templated Bimetallic Nanostar Assemblies for Ultra-Sensitive Detection of Dopamine

The abundance of hotspots tuned via precise arrangement of coupled plasmonic nanostructures highly boost the surface-enhanced Raman scattering (SERS) signal enhancements, expanding their potential applicability to a diverse range of applications. Herein, nanoscale assembly of Ag coated Au nanostars in dimer and trimer configurations with tunable nanogap was achieved using programmable DNA origami technique. The resulting assemblies were then utilized for SERS-based ultra-sensitive detection of an important neurotransmitter, dopamine. The trimer assemblies were able to detect dopamine with picomolar sensitivity, and the assembled dimer structures achieved SERS sensitivity as low as 1 fM with a limit of detection of 0.225 fM. Overall, such coupled nanoarchitectures with superior plasmon tunability are promising to explore new avenues in biomedical diagnostic applications.

A digital SERS sensing platform using 3D nanolaminate plasmonic crystals coupled with Au nanoparticles for accurate quantitative detection of dopamine

We report a digital surface-enhanced Raman spectroscopy (SERS) sensing platform using the arrays of 3D nanolaminate plasmonic crystals (NLPC) coupled with Au nanoparticles and digital (on/off) SERS signal analysis for the accurate quantitative detection of dopamine (DA) at ultralow concentrations. 3D NLPC SERS substrates were fabricated to support the optically dense arrays of vertically-stacked multi-nanogap hotspots and combined with Raman tag-conjugated Au nanoparticles for NLPC-based dual-recognition structures. We demonstrate that the 3D NLPC-based dual-recognition structures including Au nanoparticle-induced additional hotspots can enable more effective SERS enhancement through the molecular recognition of DA. For the accurate quantification of DA at ultralow concentrations, we conducted digital SERS analysis to reduce stochastic signal variation due to various microscopic effects, including molecular orientation/position variation and the spatial distribution of nanoparticle-coupled hotspots. The digital SERS analysis allowed the SERS mapping results from the DA-specific dual-recognition structures to be converted into binary "On/Off" states; the number of "On" events was directly correlated with low-abundance DA molecules down to 1 pM. Therefore, the digital SERS platform using the 3D NLPC-based dual-recognition structures coupled with Au nanoparticles and digital SERS signal analysis can be used not only for the ultrasensitive, accurate, and quantitative determination of DA, but also for the practical and rapid analysis of various molecules on nanostructured surfaces.

Nanoparticle-based colorimetric sensors to detect neurodegenerative disease biomarkers

Neurodegenerative disorders (NDDs) are progressive, incurable health conditions that primarily affect brain cells, and result in loss of brain mass and impaired function. Current sensing technologies for NDD detection are limited by high cost, long sample preparation, and/or require skilled personnel. To overcome these limitations, optical sensors, specifically colorimetric sensors, have garnered increasing attention towards the development of a cost-effective, simple, and rapid alternative approach. In this review, we evaluate colorimetric sensing strategies of NDD biomarkers (e.g. proteins, neurotransmitters, bio-thiols, and sulfide), address the limitations and challenges of optical sensor technologies, and provide our outlook on the future of this field.

Preparation of a superhydrophobic AgNP/GF substrate and its SERS application in a complex detection environment

Surface-enhanced Raman scattering (SERS) is widely considered to be a fingerprint spectrum that can realize molecular identification, and it continues to receive a lot of attention due to its high sensitivity and powerful qualitative analysis capabilities. In recent years, there has been a lot of work and reports on super-sensitive SERS substrates, but often the enhanced ability of the substrate is also effective for impurities and irrelevant molecules. Therefore, a problem that still remains to be solved is how to perform effective trace detection of specific substances in a complex detection environment. Herein, a superhydrophobic Ag nanoparticle/glass microfibre filter (AgNP/GF) substrate was designed to realize the Raman detection of complex multiphase solutions. The hydrophobic three-dimensional net-like structure provides efficient Raman enhancement, making the substrate have extremely high detection limits for dye molecules and even achieving specific detection of the hexane phase component (thiram molecule) in a multiphase solution.

Sensitive, Reusable, Surface-Enhanced Raman Scattering Sensors Constructed with a 3D Graphene/Si Hybrid

Surface-enhanced Raman scattering (SERS) substrates based on graphene and its derivatives have recently attracted attention among those interested in the detection of trace molecules; however, these substrates generally show poor uniformity, an unsatisfactory enhancement factor, and require a complex fabrication process. Herein, we design and fabricate three-dimensional (3D) graphene/silicon (3D-Gr/Si) heterojunction SERS substrates to detect various types of molecules. Notably, the detection limit of 3D-Gr/Si can reach 10^-10 M for rhodamine 6G (R6G) and rhodamine B (RB), 10^-7 M for crystal violet (CRV), copper(II) phthalocyanine (CuPc), and methylene blue (MB), 10^-8 M for dopamine (DA), 10^-6 M for bovine serum albumin (BSA), and 10^-5 M for melamine (Mel), which is superior to most reported graphene-based SERS substrates. Besides, the proposed 3D-Gr/Si heterojunction SERS substrates can achieve a high uniformity with relative standard deviations (RSDs) of less than 5%. Moreover, the 3D-Gr/Si SERS substrates are reusable after washing with ethyl alcohol to remove the adsorbed molecules. These excellent SERS performances are attributed to the novel 3D structure and abundantly exposed atomically thin edges, which facilitate charge transfer between 3D-Gr and probe molecules. We believe that the 3D-Gr/Si heterojunction SERS substrates offer potential for practical applications in biochemical molecule detection and provide insight into the design of high-performance SERS substrates.

Silver nanocube coupling with a nanoporous silver film for dual-molecule recognition based ultrasensitive SERS detection of dopamine

Dopamine (DA) is one of the catecholamine neurotransmitters used for the treatment of neural disorders. In this study, a novel sensor based on surface-enhanced Raman scattering (SERS) with dual molecule-recognition for ultrasensitive detection of DA was presented, with a limit of detection (LOD) of 40 fM, without any pretreatment of clinical samples. To realize the sensitive and selective detection of DA in complex samples, the nanoporous silver film (AgNF) surfaces were functionalized with mercaptopropionic acid (MPA) to accurately capture DA, while silver nanocubes (AgNCs) were modified with 4-mercaptobenzene boronic acid (4-MPBA) as a Raman reporter for the quantitative detection of DA. The nanogaps between AgNCs and the AgNF led to the generation of an abundance of hot spots for the SERS signal and thus effectively improved the sensitivity of DA detection. Measurements of DA concentrations in clinical body fluids such as human serum and urine samples are also demonstrated, showing excellent performance for DA detection in a complex environment. Our results demonstrate the promising potential for the ultrasensitive detection of DA for the potential diagnosis of DA-related diseases.

An antibody-free liver cancer screening approach based on nanoplasmonics biosensing chips via spectrum-based deep learning

The clinical needs of rapidly screening liver cancer in large populations have asked for a facile and low-cost point-of-care testing (POCT) method. We present a nanoplasmonics biosensing chip (NBC) that would empower antibody-free detection with simplified analysis procedures for POCT. The cheaply fabricable NBC consists of multiple silver nanoparticle-decorated ZnO nanorods on cellulose filter paper and would enable one-drop blood tests through surface-enhanced Raman spectroscopy (SERS) detection. In this work, utilizing such an NBC and deep neural network (DNN) modeling, a direct serological detection platform was constructed for automatically identifying liver cancer within minutes. This chip could enhance Raman signals enough to be applied to POCT. A classification DNN model was established by spectrum-based deep learning with 1140 serum SERS spectra in equal proportions from hepatocellular carcinoma (HCC) patients and healthy individuals, achieving an identification accuracy of 91% on an external validation set of 100 spectra (50 HCC versus 50 healthy). The intelligent platform, based on the biosensing chip and DNN, has the potential for clinical applications and generalizable use in quickly screening or detecting other types of cancer.

Application of NaYF4:Yb/Er/Tm UCNPs in Array-Based Sensing of Neurotransmitters: From a Single Particle to a Multichannel Sensor Array

A novel multichannel sensor array has been designed using a single, yet multiemissive lanthanide-doped upconversion nanoparticle (UCNP). The energy levels of lanthanide ions gave rise to several emission bands which were exploited as individual sensor elements for the recognition of four important neurotransmitters (NTs): dopamine, norepinephrine, levodopa, and serotonin. At alkaline conditions, the oxidation products of these NTs quenched the fluorescence emissions of UCNPs with different quenching degrees. The resulting fingerprint multichannel emission profiles from NaYF₄:Yb/Er/Tm UCNPs allowed the discrimination of NTs with excellent accuracy. The recognition was further verified in artificial cerebrospinal fluid, as a complex biological media. We believe that the designed UCNP-based multichannel sensor array offers innovative insights into the discrimination of various chemical signatures using a single measurement.

In Situ Detection of Neurotransmitters from Stem Cell-Derived Neural Interface at the Single-Cell Level via Graphene-Hybrid SERS Nanobiosensing

In situ quantitative measurements of neurotransmitter activities can provide useful insights into the underlying mechanisms of stem cell differentiation, the formation of neuronal networks, and neurodegenerative diseases. Currently, neurotransmitter detection methods suffer from poor spatial resolution, nonspecific detection, and a lack of in situ analysis. To address this challenge, herein, we first developed a graphene oxide (GO)-hybrid nanosurface-enhanced Raman scattering (SERS) array to detect dopamine (DA) in a selective and sensitive manner. Using the GO-hybrid nano-SERS array, we successfully measured a wide range of DA concentrations (10^-4 to 10^-9 M) rapidly and reliably. Moreover, the measurement of DA from differentiating neural stem cells applies to the characterization of neuronal differentiation. Given the challenges of in situ detection of neurotransmitters at the single-cell level, our developed SERS-based detection method can represent a unique tool for investigating single-cell signaling pathways associated with DA, or other neurotransmitters, and their roles in neurological processes.

High-sensitivity SERS based sensing on the labeling side of glass slides using low branched gold nanoparticles prepared with surfactant-free synthesis

Surface-enhanced Raman scattering (SERS) has become a more attractive tool for biological and chemical sensing due to having a great detection potential to extremely low concentrations of analyte. Here, we report high-sensitivity SERS detection of low branched gold nanoparticles which are produced by a surfactant-free synthesis method. The effects of the size and branches of nanoparticles on the SERS signal intensity were also investigated. Among the prepared nanoparticles, a new type of nanoparticle with small protrusions produced by using a very low concentration of silver ions (2 μM in final solution) achieved the best enhancement factor of ∼4 × 10⁵ for DTNB used as a probe molecule. SERS measurements were performed on the labeling side of microscope glass slides for the first time. The substrate exhibited a good reproducible SERS signal with a relative standard deviation (RSD) of 1.7%. SERS signal intensity obtained using the labelling side was three times larger compared to that obtained using bare glass. To validate the sensing platform, dopamine, an important modulatory neurotransmitter in the brain, was tested. The reported platform was able to achieve label-free detection of dopamine at picomolar and nanomolar concentration level in aqueous and fetal bovine serum (FBS) solution at pH 8.5 respectively. Due to its surfactant-free preparation and enhanced SERS-based sensing features, our reported platform represents a strong alternative to be used in SERS-based sensing applications.

High-sensitivity dopamine detection on aggregated low branched nanoparticles on labelling side of glass slide as a SERS based sensor.

Plasmon-exciton coupling for nanophotonic sensing on chip

The monolayer graphene-noble metallic nanostructure hybrid system with excellent optical characteristic, which is deserved pay attentions in the study of surface-enhanced Raman scattering spectroscopy. In this work, a hybrid sandwich structure is designed to transfer single-layer graphene to the surface of discs substrate covered by silver film and assembly of the dense Au nanoparticles (AuNPs). Blu-ray disc has a cycle density of approximately 5.7 times that of DVD-R due to the different storage capacities of these optical discs. In the research, enhancement effects have been explored for two different periodic grating structures. Compared to spectra of Si/G structure, Graphene Raman spectra from Blu-grating/AuNPs/G structure and Blu-grating/G/AuNPs enhancement multiples at the 2D peak position possesses different Raman responses of 1.09 and 2.51 times, respectively. The sandwich hybrid structure of Ag grating/graphene/AuNPs obtains a Raman enhancement factor (EF) of 6.2×10⁸ for Rhodamine 6G and surface-enhanced Raman Scattering(SERS) detection limit of 0.1 nM. These findings can be attributed to the electric field enhancement of the hybrid structure and the chemical enhancement of graphene. This study provides a new approach for SERS detection and offers a new technique for designing SERS sensors with grapheme-plasmon hybrid structures.

Immunomagnetic separation and Listeriamonocytogenes detection with surface-enhanced Raman scattering

Background/aim

We aimed to develop a rapid method to enumerate Listeria monocytogenes (L. monocytogenes) utilizing magnetic nanoparticle based preconcentration and surface-enhanced Raman spectroscopy measurements.

Materials and methods

Biological activities of magnetic Au-nanoparticles have been observed to have the high biocompatibility, and a sample immunosensor model has been designed to use avidin attached Au-nanoparticles for L. monocytogenes detection. Staphylococcus aureus (S. aureus) and Salmonella typhimurium (S. typhimurium) bacteria cultures were chosen for control studies. Antimicrobial activity studies have been done to identify bio-compatibility and bio-characterization of the Au-nanoparticles in our previous study and capturing efficiencies to bacterial surfaces have been also investigated.

Results

We constructed the calibration graphs in various population density of L. monocytogenes as 2.2 × 101 to 2.2 × 106 cfu/mL and the capture efficiency was found to be 75%. After the optimization procedures, population density of L. monocytogenes and Raman signal intensity showed a good linear correlation (R2 = 0.991) between 102 to 106 cfu/mL L. monocytogenes. The presented sandwich assay provides low detection limits and limit of quantification as 12 cfu/mL and 37 cfu/mL, respectively. We also compared the experimental results with reference plate-counting methods and the practical utility of the proposed assay is demonstrated using milk samples.

Conclusion

It is focused on the enumeration of L. monocytogenes in milk samples and the comparision of results of milk analysis obtained by the proposed SERS method and by plate counting method stay in food agreement. In the present study, all parameters were optimized to select SERS-based immunoassay method for L. monocytogenes bacteria to ensure LOD, selectivity, precision and repeatablity.

The Principle of Nanomaterials Based Surface Plasmon Resonance Biosensors and Its Potential for Dopamine Detection

For a healthy life, the human biological system should work in order. Scheduled lifestyle and lack of nutrients usually lead to fluctuations in the biological entities levels such as neurotransmitters (NTs), proteins, and hormones, which in turns put the human health in risk. Dopamine (DA) is an extremely important catecholamine NT distributed in the central nervous system. Its level in the body controls the function of human metabolism, central nervous, renal, hormonal, and cardiovascular systems. It is closely related to the major domains of human cognition, feeling, and human desires, as well as learning. Several neurological disorders such as schizophrenia and Parkinson’s disease are related to the extreme abnormalities in DA levels. Therefore, the development of an accurate, effective, and highly sensitive method for rapid determination of DA concentrations is desired. Up to now, different methods have been reported for DA detection such as electrochemical strategies, high-performance liquid chromatography, colorimetry, and capillary electrophoresis mass spectrometry. However, most of them have some limitations. Surface plasmon resonance (SPR) spectroscopy was widely used in biosensing. However, its use to detect NTs is still growing and has fascinated impressive attention of the scientific community. The focus in this concise review paper will be on the principle of SPR sensors and its operation mechanism, the factors that affect the sensor performance. The efficiency of SPR biosensors to detect several clinically related analytes will be mentioned. DA functions in the human body will be explained. Additionally, this review will cover the incorporation of nanomaterials into SPR biosensors and its potential for DA sensing with mention to its advantages and disadvantages.

Electrochemical Micropyramid Array-Based Sensor for In Situ Monitoring of Dopamine Released from Neuroblastoma Cells

Abnormal dopamine neurotransmission is associated with several neurological and psychiatric disorders such as Parkinson's disease, schizophrenia, attention deficiency and hyperactivity disorder, and addiction. Developing highly sensitive, selective, and fast dopamine monitoring methods is of high importance especially for the early diagnosis of these diseases. Herein, we report a new ultrasensitive electrochemical sensing platform for in situ monitoring of cell-secreted dopamine using Au-coated arrays of micropyramid structures integrated directly into a Petri dish. This approach enables the monitoring of dopamine released from cells in real-time without the need for relocating cultured cells. According to the electrochemical analyses, our dopamine sensing platform exhibits excellent analytical characteristics with a detection limit of 0.50 ± 0.08 nM, a wide linear range of 0.01-500 μM, and a sensitivity of 0.18 ± 0.01 μA/μM. The sensor also has remarkable selectivity toward DA in the presence of different potentially interfering small molecules. The developed electrochemical sensor has great potential for in vitro analysis of neuronal cells as well as early diagnosis of different neurological diseases related to abnormal levels of dopamine.

Enhancement of Signal-to-Noise Ratio for Serotonin Detection with Well-Designed Nanofilter-Coated Potentiometric Electrochemical Biosensor

In this paper, we proposed to enhance a signal-to-noise (S/N) ratio for detecting a primary stress marker, serotonin, using a potentiometric biosensor modified by a well-designed nanofilter film. An extended-Au-gate field-effect transistor (EG-Au-gate FET) biosensor exhibits highly sensitive electrochemical detection toward various small biomolecules, including serotonin. Therefore, to enhance the S/N ratio for the serotonin detection, we designed an appropriate nanofilter film on the Au electrode by combining the aryldiazonium salt reduction strategy and boronate affinity. That is, only serotonin can approach the Au sensing surface to generate an electrical signal; interfering biomolecules are prevented from penetrating through the nanofilter, either because large interfering biomolecules cannot permeate through the highly dense, nanoporous multilayer film, or because phenylboronic acids included in the nanofilter captures small interfering biomolecules (e.g., catecholamines). The potentiometric biosensor modified by such a nanofilter film detected serotonin in a model sample solution containing catecholamines, cortisol, and human serum albumin with a high S/N ratio for the serotonin levels in the blood. Furthermore, we found that the effect of the nanofilter directly reflects the binding affinity of the receptors such as phenylboronic acids included in the nanofilter; thus, the selectivity and dynamic range of small target biomolecules can be tuned freely by designing the appropriate receptors for the nanofilter. The results show that a well-designed nanofilter biointerface can be a versatile biosensing platform for point-of-care testing, particularly for a simple stress check.

Ultrasensitive amyloid β-protein quantification with high dynamic range using a hybrid graphene-gold surface-enhanced Raman spectroscopy platform

Surface enhanced Raman spectroscopy (SERS) holds great promise in biosensing because of its single-molecule, label-free sensitivity. We describe here the use of a graphene-gold hybrid plasmonic platform that enables quantitative SERS measurement. Quantification is enabled by normalizing analyte peak intensities to that of the graphene G peak. We show that two complementary quantification modes are intrinsic features of the platform, and that through their combined use, the platform enables accurate determination of analyte concentration over a concentration range spanning seven orders of magnitude. We demonstrate, using a biologically relevant test analyte, the amyloid β-protein (Aβ), a seminal pathologic agent of Alzheimer's disease (AD), that linear relationships exist between (a) peak intensity and concentration at a single plasmonic hot spot smaller than 100 nm, and (b) frequency of hot spots with observable protein signals, i.e. the co-location of an Aβ protein and a hot spot. We demonstrate the detection of Aβ at a concentration as low as 10-18 M after a single 20 μl aliquot of the analyte onto the hybrid platform. This detection sensitivity can be improved further through multiple applications of analyte to the platform and by rastering the laser beam with smaller step sizes.

Recent Advances in Electrochemical and Optical Sensing of Dopamine

Nowadays, several neurological disorders and neurocrine tumours are associated with dopamine (DA) concentrations in various biological fluids. Highly accurate and ultrasensitive detection of DA levels in different biological samples in real-time can change and improve the quality of a patient's life in addition to reducing the treatment cost. Therefore, the design and development of diagnostic tool for in vivo and in vitro monitoring of DA is of considerable clinical and pharmacological importance. In recent decades, a large number of techniques have been established for DA detection, including chromatography coupled to mass spectrometry, spectroscopic approaches, and electrochemical (EC) methods. These methods are effective, but most of them still have some drawbacks such as consuming time, effort, and money. Added to that, sometimes they need complex procedures to obtain good sensitivity and suffer from low selectivity due to interference from other biological species such as uric acid (UA) and ascorbic acid (AA). Advanced materials can offer remarkable opportunities to overcome drawbacks in conventional DA sensors. This review aims to explain challenges related to DA detection using different techniques, and to summarize and highlight recent advancements in materials used and approaches applied for several sensor surface modification for the monitoring of DA. Also, it focuses on the analytical features of the EC and optical-based sensing techniques available.

Graphene and Graphene Oxide Applications for SERS Sensing and Imaging

Surface Enhanced Raman Spectroscopy (SERS) has a long history as an ultrasensitive platform for the detection of biological species from small aromatic molecules to complex biological systems as circulating tumor cells. Thanks to unique properties of graphene, the range of SERS applications has largely expanded. Graphene is efficient fluorescence quencher improving quality of Raman spectra. It contributes also to the SERS enhancement factor through the chemical mechanism. In turn, the chemical flexibility of Reduced Graphene Oxide (RGO) enables tunable adsorption of molecules or cells on SERS active surfaces. Graphene oxide composites with SERS active nanoparticles have been also applied for Raman imaging of cells. This review presents a survey of SERS assays employing graphene or RGO emphasizing the improvement of SERS enhancement brought by graphene or RGO. The structure and physical properties of graphene and RGO will be discussed too.

The fabrication of a gold nanoelectrode–nanopore nanopipette for dopamine enrichment and multimode detection

It is important to further improve the electrophysiology and electrochemistry techniques of neurotransmitter detection.

Ultrasensitive SERS detection of rhodamine 6G and p-nitrophenol based on electrochemically roughened nano-Au film

Quantitative analysis of organic pollutants in environmental water is an important issue for ecological environment and human health. In this paper, the quantitative analysis of rhodamine 6G (R6G) and p-nitrophenol (PNP) is performed by the surface enhanced Raman scattering (SERS) technology. The enhancement of Raman signals is achieved on the surface of an electrochemically roughened nano-Au film. The SERS performance depends on the microstructure of roughened nano-Au films, which is affected by the thickness of Au films and electrochemical roughening parameters. The structure-dependence of SERS performance is validated by finite element simulation of local electromagnetic field distribution. An obvious SERS effect of R6G with an enhancement factor of 10⁸ is obtained on the roughened nano-Au film. A sensitive SERS detection of R6G with a linear range of 10^-9-10^-5 M and a detection limit of 10^-11 M is realized. Moreover, a wide linear range of 10^-9-10^-3 M is obtained for the detection of PNP. The roughened nano-Au film is an effective substrate for the SERS detection of organic pollutants with high reproducibility and good stability. Therefore, the electrochemical technology in this study is expected to be a very promising method for the fabrication of high-performance SERS substrate.

High-throughput evolution of near-infrared serotonin nanosensors

Imaging neuromodulation with synthetic probes is an emerging technology for studying neurotransmission. However, most synthetic probes are developed through conjugation of fluorescent signal transducers to preexisting recognition moieties such as antibodies or receptors. We introduce a generic platform to evolve synthetic molecular recognition on the surface of near-infrared fluorescent single-wall carbon nanotube (SWCNT) signal transducers. We demonstrate evolution of molecular recognition toward neuromodulator serotonin generated from large libraries of ~6.9 × 1010 unique ssDNA sequences conjugated to SWCNTs. This probe is reversible and produces a ~200% fluorescence enhancement upon exposure to serotonin with a K d = 6.3 μM, and shows selective responsivity over serotonin analogs, metabolites, and receptor-targeting drugs. Furthermore, this probe remains responsive and reversible upon repeat exposure to exogenous serotonin in the extracellular space of acute brain slices. Our results suggest that evolution of nanosensors could be generically implemented to develop other neuromodulator probes with synthetic molecular recognition.

Dual-Enhanced Raman Scattering-Based Characterization of Stem Cell Differentiation Using Graphene-Plasmonic Hybrid Nanoarray

Surface-enhanced Raman scattering (SERS) has demonstrated great potential to analyze a variety of bio/chemical molecular interactions within cells in a highly sensitive and selective manner. Despite significant advancements, it remains a critical challenge to ensure high sensitivity and selectivity, while achieving uniform signal enhancement and high reproducibility for quantitative detection of targeted biomarkers within a complex stem cell microenvironment. Herein, we demonstrate an innovative sensing platform, using graphene-coated homogeneous plasmonic metal (Au) nanoarrays, which synergize both electromagnetic mechanism (EM)- and chemical mechanism (CM)-based enhancement. Through the homogeneous plasmonic nanostructures, generated by laser interference lithography (LIL), highly reproducible enhancement of Raman signals could be obtained via a strong and uniform EM. Additionally, the graphene-functionalized surface simultaneously amplifies the Raman signals by an optimized CM, which aligns the energy level of the graphene oxide with the target molecule by tuning its oxidation levels, consequently increasing the sensitivity and accuracy of our sensing system. Using the dual-enhanced Raman scattering from both EM from the homogeneous plasmonic Au nanoarray and CM from the graphene surface, our graphene-Au hybrid nanoarray was successfully utilized to detect as well as quantify a specific biomarker (TuJ1) gene expression levels to characterize neuronal differentiation of human neural stem cells (hNSCs). Collectively, we believe our unique graphene-plasmonic hybrid nanoarray can be extended to a wide range of applications in the development of simple, rapid, and accurate sensing platforms for screening various bio/chemical molecules.