Recent progress of surface-enhanced Raman spectroscopy for subcellular compartment analysis

In situ surface-enhanced Raman spectroscopy for membrane protein analysis and sensing

Membrane proteins are involved in a variety of dynamic cellular processes and exploration of the structural basis of membrane proteins is of significance for a better understanding of their functions. In situ analysis of membrane proteins and their dynamics is, however, challenging for conventional techniques. Surface-enhanced Raman spectroscopy (SERS) is powerful in protein structural characterization, allowing for sensitive, in-situ and real-time identification and dynamic monitoring under physiological conditions. In this review, the applications of SERS in probing membrane proteins are outlined, discussed and prospected. It starts with a brief introduction to membrane proteins, SERS theories and SERS-based strategies that commonly-used for membrane proteins. How to assemble phospholipid biolayers on SERS-active materials is highlighted, followed by respectively discussing about direct and indirect strategies for membrane protein sensing. SERS-based monitoring of protein-ligand interactions is finally introduced and its potential in biomedical applications is discussed in detail. The review ends with critical discussion about current challenges and limitations of this research field, and the promising perspectives in both fundamental and applied sciences.

SERS analysis of single cells and subcellular components: A review

SERS is a rapidly advancing and non-destructive technique that has been proven to be more reliable and convenient than other traditional analytical methods. Due to its sensitivity and specificity, this technique is earning its place as a routine and powerful tool in biological and medical studies, especially for the analysis of living cells and subcellular components. This paper reviewed the research progress of single-cell SERS that has been made in the last few years and discussed challenges and future perspectives of this technique. The reviewed SERS platforms have been categorized according to their nature into the following types: (1) colloid-based, substrate-based, or hybrid; (2) ligand-based or ligand-free, and (3) label-based or label-free. The advantages and disadvantages of each type and their potential applications in various fields are thoroughly discussed.

Transcriptional switches in melanoma T Cells: Facilitating polarizing into regulatory T cells

Melanoma is a malignant skin tumor with a high mortality rate. Regulatory T cells (Tregs) are immune cells with immunosuppressive roles, however, the precise mechanisms governing Treg involvement in melanoma remain enigmatic. Experimental findings unveiled different transcription factor switches between normal and tumor T cell, with heightened FOXP3 and BATF in the latter. These factors induced immunosuppressive molecules and Treg maintenance genes, polarizing tumor T cells into Tregs. Spatial transcriptomics illuminated the preferential settlement of Tregs at the melanoma periphery. Within this context, FOXP3 in Tregs facilitated direct enhancement of specific ligand gene expression, fostering communication with neighboring cells. Novel functional molecules bound to FOXP3 or BATF in Tregs, such as SPOCK2, SH2D2A, and ligand molecules ITGB2, LTA, CLEC2C, CLEC2D, were discovered, which had not been previously reported in melanoma Treg studies. Furthermore, we validated our findings in a large number of clinical samples and identified the Melanoma Treg-Specific Regulatory Tag Set (Mel TregS). ELISA analysis showed that the protein levels of Mel TregS in melanoma Tregs were higher than in normal Tregs. We then utilized SERS technology to measure the signal values of Mel TregS in exosome, and successfully discriminated between healthy individuals and melanoma patients, as well as early and late-stage patients. This approach significantly enhanced detection sensitivity. In sum, our research elucidated fresh insights into the mechanisms governing Treg self-maintenance and communication with surrounding cells in melanoma. We also introduced an innovative method for clinical disease monitoring through SERS technology.

Tailoring strategies of SERS tags-based sensors for cellular molecules detection and imaging

As an emerging nanoprobe, surface enhanced Raman scattering (SERS) tags hold significant promise in sensing and bioimaging applications due to their attractive merits of anti-photobleaching ability, high sensitivity and specificity, multiplex, and low background capabilities. Recently, several reviews have proposed the application of SERS tags in different fields, however, the specific sensing strategies of SERS tags-based sensors for cellular molecules have not yet been systematically summarized. To provide beneficial and comprehensive insights into the advanced SERS tags technique at the cellular level, this review systematically elaborated on the latest advances in SERS tags-based sensors for cellular molecules detection and imaging. The general SERS tags-based sensing strategies for biomolecules and ions were first introduced according to molecular classes. Then, aiming at such molecules located in the extracellular, cellular membrane and intracellular regions, the tailored strategies by designing and manipulating SERS tags were summarized and explored through several key examples. Finally, the challenges and perspectives of developing high performance of advanced SERS tags were briefly discussed to provide effective guidance for further development and extended applications.

Machine Learning-Driven SERS Nanoendoscopy and Optophysiology

A frontier of analytical sciences is centered on the continuous measurement of molecules in or near cells, tissues, or organs, within the biological context in situ, where the molecular-level information is indicative of health status, therapeutic efficacy, and fundamental biochemical function of the host. Following the completion of the Human Genome Project, current research aims to link genes to functions of an organism and investigate how the environment modulates functional properties of organisms. New analytical methods have been developed to detect chemical changes with high spatial and temporal resolution, including minimally invasive surface-enhanced Raman scattering (SERS) nanofibers using the principles of endoscopy (SERS nanoendoscopy) or optical physiology (SERS optophysiology). Given the large spectral data sets generated from these experiments, SERS nanoendoscopy and optophysiology benefit from advances in data science and machine learning to extract chemical information from complex vibrational spectra measured by SERS. This review highlights new opportunities for intracellular, extracellular, and in vivo chemical measurements arising from the combination of SERS nanosensing and machine learning.

Deciphering biomolecular complexities: the indispensable role of surface-enhanced Raman spectroscopy in modern bioanalytical research

Surface-enhanced Raman spectroscopy (SERS) has emerged as an indispensable analytical tool in biomolecular research, providing unmatched sensitivity critical for the elucidation of biomolecular structures. This review presents a thorough examination of SERS, outlining its fundamental principles, cataloging its varied applications within the biomolecular sphere, and contemplating its future developmental trajectories. We begin with a detailed analysis of SERS's mechanistic principles, emphasizing both the phenomena of surface enhancement and the complexities inherent in Raman scattering spectroscopy. Subsequently, we delve into the pivotal role of SERS in the structural analysis of diverse biomolecules, including proteins, nucleic acids, lipids, carbohydrates, and biochromes. The remarkable capabilities of SERS extend beyond mere detection, offering profound insights into biomolecular configurations and interactions, thereby enriching our comprehension of intricate biological processes. This review also sheds light on the application of SERS in real-time monitoring of various bio-relevant compounds, from enzymes and coenzymes to metal ion-chelate complexes and cellular organelles, thereby providing a holistic view and empowering researchers to unravel the complexities of biological systems. We also address the current challenges faced by SERS, such as enhancing sensitivity and resolution, developing stable and reproducible substrates, and conducting thorough analyses in complex biological matrices. Nonetheless, the continual advancements in nanotechnology and spectroscopy solidify the standing of SERS as a formidable force in biomolecular research. In conclusion, the versatility and robustness of SERS not only deepen our understanding of biomolecular intricacies but also pave the way for significant developments in medical research, therapeutic innovation, and diagnostic approaches.

3D superstructure based metabolite profiling for glaucoma diagnosis

Metabolome analysis has gained widespread application in disease diagnosis owing to its ability to provide comprehensive information, including disease phenotypes. In this study, we utilized 3D superstructures fabricated through evaporation-induced microprinting to analyze the metabolome for glaucoma diagnosis. 3D superstructures offer the following advantages: high hotspot density per unit volume of the structure extending from two to three dimensions, excellent signal repeatability due to the reproducibility and defect tolerance of 3D printing, and high thermal stability due to the PVP-enclosed capsule form. Leveraging the superior optical properties of the 3D superstructure, we aimed to classify patients with glaucoma. The signal obtained from the 3D superstructure was employed in a Deep Neural Network (DNN) classification model to accurately classify glaucoma patients. The sensitivity and specificity of the model were determined as 92.05% and 93.51%, respectively. Additionally, the fabrication of 3D superstructures can be performed at any stage, significantly reducing measurement time. Furthermore, their thermal stability allows for the analysis of smaller samples. One notable advantage of 3D superstructures is their versatility in accommodating different target materials. Consequently, they can be utilized for a wide range of metabolic analyses and disease diagnoses.

Enhancement and quenching of plasmon-enhanced spectroscopy of single molecule confined in metallic nanoparticle dimers

We present a theoretical analysis of plasmon-enhanced fluorescence (PEF) and Raman scattering (PERS) spectroscopy of a single molecule confined in the laser-irradiated metallic nanoparticles (NPs) dimer, focusing on the origin of the spectral enhancement and quenching effects. The theoretical method ofD-parameters has been used to calculate the dimer distance-dependent nonlocal dielectric effect in Ag and Au NPs. Meanwhile, other damping rates and electric field enhancements are quantitatively computed by finite element method. Moreover, PEF and PERS spectra of rhodamine 6G are obtained within the density-functional theory. Our calculated results show that the PERS mainly depend on the excitation and emission field enhancements, and thus it occurs at the narrower dimer gap due to the stronger localized plasmon coupling. The PEF is related to fluorescence rate caused by the competition between excitation electric field and quantum efficiency, and the increase of former may enhance the fluorescence intensity while the lower latter lead to reduce the intensity as decreasing the dimer distance. The contribution of nonlocal dielectric effect can significantly reduce the quantum efficiency at smaller distance so that it overcomes the excitation field enhancement, leading to the fluorescence quenching for Au NPs dimer. Furthermore, by optimizing the dimer distance and NPs size, the maximum PERS and PEF cross sections reach 10-14and 10-15under 2.45 eV laser excitation for Ag NPs dimer, and 10-18for Au NPs. Our study finely explains the experiment results showed either fluorescence enhancement or quenching with the change of molecule-NPs distance, and better guidance for optimizing the experiments.

Spectroscopic techniques for monitoring stem cell and organoid proliferation in 3D environments for therapeutic development

Spectroscopic techniques for monitoring stem cell and organoid proliferation have gained significant attention in therapeutic development. Spectroscopic techniques such as fluorescence, Raman spectroscopy, and infrared spectroscopy offer noninvasive and real-time monitoring of biochemical and biophysical changes that occur during stem cell and organoid proliferation. These techniques provide valuable insight into the underlying mechanisms of action of potential therapeutic agents, allowing for improved drug discovery and screening. This review highlights the importance of spectroscopic monitoring of stem cell and organoid proliferation and its potential impact on therapeutic development. Furthermore, this review discusses recent advances in spectroscopic techniques and their applications in stem cell and organoid research. Overall, this review emphasizes the importance of spectroscopic techniques as valuable tools for studying stem cell and organoid proliferation and their potential to revolutionize therapeutic development in the future.

Intracellular spatiotemporal metabolism in connection to target engagement

The metabolism in eukaryotic cells is a highly ordered system involving various cellular compartments, which fluctuates based on physiological rhythms. Organelles, as the smallest independent sub-cell unit, are important contributors to cell metabolism and drug metabolism, collectively designated intracellular metabolism. However, disruption of intracellular spatiotemporal metabolism can lead to disease development and progression, as well as drug treatment interference. In this review, we systematically discuss spatiotemporal metabolism in cells and cell subpopulations. In particular, we focused on metabolism compartmentalization and physiological rhythms, including the variation and regulation of metabolic enzymes, metabolic pathways, and metabolites. Additionally, the intricate relationship among intracellular spatiotemporal metabolism, metabolism-related diseases, and drug therapy/toxicity has been discussed. Finally, approaches and strategies for intracellular spatiotemporal metabolism analysis and potential target identification are introduced, along with examples of potential new drug design based on this.

Single-Cell Analysis and Classification according to Multiplexed Proteins via Microdroplet-Based Self-Driven Magnetic Surface-Enhanced Raman Spectroscopy Platforms Assisted with Machine Learning Algorithms

A microdroplet-based surface-enhanced Raman spectroscopy (microdroplet SERS) platform was constructed to envelop individual cells in microdroplets, followed by the SERS detection of their extracellular vesicle-proteins (EV-proteins) via the in-drop immunoassays by use of immunomagnetic beads (iMBs) and immuno-SERS tags (iSERS tags). A unique phenomenon is found that iMBs can start a spontaneous reorientation on the probed cell surface based on the electrostatic force-driven interfacial aggregation effect, which leads EV-proteins and iSERS tags to be gathered from a liquid phase to a cell membrane interface and significantly improves SERS sensitivity to the single-cell analysis level due to the formation of numbers of SERS hotspots. Three EV-proteins from two breast cancer cell lines were collected and further analyzed by machine learning algorithmic tools, which will be helpful for a deeper understanding of breast cancer subtypes from the view of EV-proteins.

Extracellularly Detectable Electrochemical Signals of Living Cells Originate from Metabolic Reactions

Direct detection of cellular redox signals has shown immense potential as a novel living cell analysis tool. However, the origin of such signals remains unknown, which hinders the widespread use of electrochemical methods for cellular research. In this study, the authors found that intracellular metabolic pathways that generate adenosine triphosphate (ATP) are the main contributors to extracellularly detectable electrochemical signals. This is achieved through the detection of living cells (4,706 cells/chip, linearity: 0.985) at a linear range of 7,466-48,866. Based on this discovery, the authors demonstrated that the cellular signals detected by differential pulse voltammetry (DPV) can be rapidly amplified with a developed medium containing metabolic activator cocktails (MACs). The DPV approach combined with MAC treatment shows a remarkable performance to detect the effects of the anticancer drug CPI-613 on cervical cancer both at a low drug concentration (2 µm) and an extremely short treatment time (1 hour). Furthermore, the senescence of mesenchymal stem cells could also be sensitively quantified using the DPV+MAC method even at a low passage number (P6). Collectively, their findings unveiled the origin of redox signals in living cells, which has important implications for the characterization of various cellular functions and behaviors using electrochemical approaches.

Advances in surface-enhanced Raman spectroscopy technology for detection of foodborne pathogens

Rapid control and prevention of diseases caused by foodborne pathogens is one of the existing food safety regulatory issues faced by various countries and has received wide attention from all sectors of society. The development of rapid and reliable detection methods for foodborne pathogens remains a hot research area for food safety and public health because of the limitations of complex steps, time-consuming, low sensitivity, or poor selectivity of commonly used methods. Surface-enhanced Raman spectroscopy (SERS), as a novel spectroscopic technique, has the advantages of high sensitivity, selectivity, rapid and nondestructive detection and has exhibited broad application prospects in the determination of pathogenic bacteria. In this study, the enhancement mechanisms of SERS are briefly introduced, then the characteristics and properties of liquid-phase, rigid solid-phase, and flexible solid-phase are categorized. Furthermore, a comprehensive review of the advances in label-free or label-based SERS strategies and SERS-compatible techniques for the detection of foodborne pathogens is provided, and the advantages and disadvantages of these methods are reviewed. Finally, the current challenges of SERS technology applied in practical applications are listed, and the possible development trends of SERS in the field of foodborne pathogens detection in the future are discussed.

An in situ protonation-activated supramolecular self-assembly for selective suppression of tumor growth

An in situ supramolecular self-assembly in the subcellular organelles could provide a new strategy to treat diseases. Herein, we report a protonation-activated in situ supramolecular self-assembly system in the lysosomes, which could destabilize the lysosome membrane, resulting in the selective suppression of cancer cells. In this system, pyridyl-functionalized tetraphenylethylene (TPE-Py) was protonated in the lysosomes of A549 lung cancer cells to form octahedron-like structures with cucurbit[8]uril (CB[8]), which impaired the integrity of the lysosome membrane, resulting in selective suppression of cancer cells. Moreover, its anticancer efficiency was also systematically evaluated in vivo, triggering the apoptosis of tumor tissues with ignorable effects on normal organs. Overall, the protonation-activated self-assembly in the lysosomes based on the host-guest complexation would provide a method for novel anti-cancer systems.

Ultrasensitive Optical Fingerprinting of Biorelevant Molecules by Means of SERS-Mapping on Nanostructured Metasurfaces

The most relevant technique for portable (on-chip) sensors is Surface Enhanced Raman Scattering (SERS). This strategy crashes in the case of large (biorelevant) molecules and nano-objects, whose SERS spectra are irreproducible for "homeopathic" concentrations. We suggested solving this problem by SERS-mapping. We analyzed the distributions of SERS parameters for relatively "small" (malachite green (MG)) and "large" (phthalocyanine, H₂Pc*) molecules. While fluctuations of spectra for "small" MG were negligible, noticeable distribution of spectra was observed for "large" H₂Pc*. We show that the latter is due to a random arrangement of molecules with respect to "hot spot" areas, which have limited sizes, thus amplifying the lines corresponding to vibrations of different molecule parts. We have developed a method for engineering low-cost SERS substrates optimized for the best enhancement efficiency and a measurement protocol to obtain a reliable Raman spectrum, even for a countable number of large molecules randomly distributed over the substrate.

Minimally invasive detection of cancer using metabolic changes in tumor-associated natural killer cells with Oncoimmune probes

Natural Killer (NK) cells, a subset of innate immune cells, undergo cancer-specific changes during tumor progression. Therefore, tracking NK cell activity in circulation has potential for cancer diagnosis. Identification of tumor associated NK cells remains a challenge as most of the cancer antigens are unknown. Here, we introduce tumor-associated circulating NK cell profiling (CNKP) as a stand-alone cancer diagnostic modality with a liquid biopsy. Metabolic profiles of NK cell activation as a result of tumor interaction are detected with a SERS functionalized OncoImmune probe platform. We show that the cancer stem cell-associated NK cell is of value in cancer diagnosis. Through machine learning, the features of NK cell activity in patient blood could identify cancer from non-cancer using 5uL of peripheral blood with 100% accuracy and localization of cancer with 93% accuracy. These results show the feasibility of minimally invasive cancer diagnostics using circulating NK cells.

NK cells can be affected by tumour cells and this difference could be utilised as a cancer diagnostic. Here the authors use a nickel based plasmonic spectroscopy system to measure metabolic differences in NK cells that have been exposed to cancer cells as a method of cancer detection.

Accurate Tumor Subtype Detection with Raman Spectroscopy via Variational Autoencoder and Machine Learning

Accurate diagnosis of cancer subtypes is a great guide for the development of surgical plans and prognosis in the clinic. Raman spectroscopy, combined with the machine learning algorithm, has been demonstrated to be a powerful tool for tumor identification. However, the analysis and classification of Raman spectra for biological samples with complex compositions are still challenges. In addition, the signal-to-noise ratio of the spectra also influences the accuracy of the classification. Herein, we applied the variational autoencoder (VAE) to Raman spectra for downscaling and noise reduction simultaneously. We validated the performance of the VAE algorithm at the cellular and tissue levels. VAE successfully downscaled high-dimensional Raman spectral data to two-dimensional (2D) data for three subtypes of non-small cell lung cancer cells and two subtypes of kidney cancer tissues. Gaussian naïve bayes was applied to subtype discrimination with the 2D data after VAE encoding at both the cellular and tissue levels, significantly outperforming the discrimination results using original spectra. Therefore, the analysis of Raman spectroscopy based on VAE and machine learning has great potential for rapid diagnosis of tumor subtypes.

SERS Tags for Biomedical Detection and Bioimaging

Surface-enhanced Raman scattering (SERS) has emerged as a valuable technique for molecular identification. Due to the characteristics of high sensitivity, excellent signal specificity, and photobleaching resistance, SERS has been widely used in the fields of environmental monitoring, food safety, and disease diagnosis. By attaching the organic molecules to the surface of plasmonic nanoparticles, the obtained SERS tags show high-performance multiplexing capability for biosensing. The past decade has witnessed the progress of SERS tags for liquid biopsy, bioimaging, and theranostics applications. This review focuses on the advances of SERS tags in biomedical fields. We first introduce the building blocks of SERS tags, followed by the summarization of recent progress in SERS tags employed for detecting biomarkers, such as DNA, miRNA, and protein in biological fluids, as well as imaging from in vitro cell, bacteria, tissue to in vivo tumors. Further, we illustrate the appealing applications of SERS tags for delineating tumor margins and cancer diagnosis. In the end, perspectives of SERS tags projecting into the possible obstacles are deliberately proposed in future clinical translation.

Advances in the Application of Exosomes Identification Using Surface-Enhanced Raman Spectroscopy for the Early Detection of Cancers

Exosomes are small nanoscale vesicles with a double-layered lipid membrane structure secreted by cells, and almost all types of cells can secrete exosomes. Exosomes carry a variety of biologically active contents such as nucleic acids and proteins, and play an important role not only in intercellular information exchange and signal transduction, but also in various pathophysiological processes in the human body. Surface-enhanced Raman Spectroscopy (SERS) uses light to interact with nanostructured materials such as gold and silver to produce a strong surface plasmon resonance effect, which can significantly enhance the Raman signal of molecules adsorbed on the surface of nanostructures to obtain a rich fingerprint of the sample itself or Raman probe molecules with ultra-sensitivity. The unique advantages of SERS, such as non-invasive and high sensitivity, good selectivity, fast analysis speed, and low water interference, make it a promising technology for life science and clinical testing applications. In this paper, we briefly introduce exosomes and the current main detection methods. We also describe the basic principles of SERS and the progress of the application of unlabeled and labeled SERS in exosome detection. This paper also summarizes the value of SERS-based exosome assays for early tumor diagnosis.

Positively-charged plasmonic nanostructures for SERS sensing applications

Surface-enhanced Raman (SERS) spectroscopy has been establishing itself as an ultrasensitive analytical technique with a cross-disciplinary range of applications, which scientific growth is triggered by the continuous improvement in the design of advanced plasmonic materials with enhanced multifunctional abilities and tailorable surface chemistry. In this regard, conventional synthetic procedures yield negatively-charged plasmonic materials which can hamper the adhesion of negatively-charged species. To tackle this issue, metallic surfaces have been modified via diverse procedures with a broad array of surface ligands to impart positive charges. Cationic amines have been preferred because of their ability to retain a positive zeta potential even at alkaline pH as well as due to their wide accessibility in terms of structural features and cost. In this review, we will describe and discuss the different approaches for generating positively-charged plasmonic platforms and their applications in SERS sensing.

Surface-enhanced Raman spectroscopy for bioanalysis and diagnosis

In recent years, bioanalytical surface-enhanced Raman spectroscopy (SERS) has blossomed into a fast-growing research area. Owing to its high sensitivity and outstanding multiplexing ability, SERS is an effective analytical technique that has excellent potential in bioanalysis and diagnosis, as demonstrated by its increasing applications in vivo. SERS allows the rapid detection of molecular species based on direct and indirect strategies. Because it benefits from the tunable surface properties of nanostructures, it finds a broad range of applications with clinical relevance, such as biological sensing, drug delivery and live cell imaging assays. Of particular interest are early-stage-cancer detection and the fast detection of pathogens. Here, we present a comprehensive survey of SERS-based assays, from basic considerations to bioanalytical applications. Our main focus is on SERS-based pathogen detection methods as point-of-care solutions for early bacterial infection detection and chronic disease diagnosis. Additionally, various promising in vivo applications of SERS are surveyed. Furthermore, we provide a brief outlook of recent endeavours and we discuss future prospects and limitations for SERS, as a reliable approach for rapid and sensitive bioanalysis and diagnosis.

Targets and Tools: Nucleic Acids for Surface-Enhanced Raman Spectroscopy

Surface-enhanced Raman spectroscopy (SERS) merges nanotechnology with conventional Raman spectroscopy to produce an ultrasensitive and highly specific analytical tool that has been exploited as the optical signal read-out in a variety of advanced applications. In this feature article, we delineate the main features of the intertwined relationship between SERS and nucleic acids (NAs). In particular, we report representative examples of the implementation of SERS in biosensing platforms for NA detection, the integration of DNA as the biorecognition element onto plasmonic materials for SERS analysis of different classes of analytes (from metal ions to microorgniasms) and, finally, the use of structural DNA nanotechnology for the precise engineering of SERS-active nanomaterials.

Paper-based plasmonic substrates as surface-enhanced Raman scattering spectroscopy platforms for cell culture applications

The engineering of advanced materials capable of mimicking the cellular micro-environment while providing cells with physicochemical cues is central for cell culture applications. In this regard, paper meets key requirements in terms of biocompatibility, hydrophilicity, porosity, mechanical strength, ease of physicochemical modifications, cost, and ease of large-scale production, to be used as a scaffold material for biomedical applications. Most notably, paper has demonstrated the potential to become an attractive alternative to conventional biomaterials for creating two-dimensional (2D) and three-dimensional (3D) biomimetic cell culture models that mimic the features of in vivo tissue environments for improving our understanding of cell behavior (e.g. growth, cell migration, proliferation, differentiation and tumor metastasis) in their natural state. On the other hand, integration of plasmonic nanomaterials (e.g. gold nanoparticles) within the fibrous structure of paper opens the possibility to generate multifunctional scaffolds equipped with biosensing tools for monitoring different cell cues through physicochemical signals. Among different plasmonic based detection techniques, surface-enhanced Raman scattering (SERS) spectroscopy emerged as a highly specific and sensitive optical tool for its extraordinary sensitivity and the ability for multidimensional and accurate molecular identification. Thus, paper-based plasmonic substrates in combination with SERS optical detection represent a powerful future platform for monitoring cell cues during cell culture processes. To this end, in this review, we will describe the different methods for fabricating hybrid paper-plasmonic nanoparticle substrates and their use in combination with SERS spectroscopy for biosensing and, more specifically, in cell culture applications.