Characterization of yeast species using surface-enhanced Raman scattering

Machine learning-assisted SERS approach enables the biochemical discrimination in Bcl-2 and Mcl-1 expressing yeast cells treated with ketoconazole and fluconazole antifungals

Antifungal medications are important due to their potential application in cancer treatment either on their own or with traditional treatments. The mechanisms that prevent the effects of these medications and restrict their usage in cancer treatment are not completely understood. The evaluation and discrimination of the possible protective effects of the anti-apoptotic members of the Bcl-2 family of proteins, critical regulators of mitochondrial apoptosis, against antifungal drug-induced cell death has still scientific uncertainties that must be considered. Novel, simple, and reliable strategies are highly demanded to identify the biochemical signature of this phenomenon. However, the complex nature of cells poses challenges for the analysis of cellular biochemical changes or classification. In this study, for the first time, we investigated the probable protective activities of Bcl-2 and Mcl-1 proteins against cell damage induced by ketoconazole (KET) and fluconazole (FLU) antifungal drugs in a yeast model through surface-enhanced Raman spectroscopy (SERS) approach. The proposed SERS platform created robust Raman spectra with a high signal-to-noise ratio. The analysis of SERS spectral data via advanced unsupervised and supervised machine learning methods enabled unquestionable differentiation (100 %) in samples and biomolecular identification. Various SERS bands related to lipids and proteins observed in the analyses suggest that the expression of these anti-apoptotic proteins reduces oxidative biomolecule damage induced by the antifungals. Also, cell viability assay, Annexin V-FITC/PI double staining, and total oxidant and antioxidant status analyses were performed to support Raman measurements. We strongly believe that the proposed approach paves the way for the evaluation of various biochemical structures/changes in various cells.

Surface-enhanced Raman spectral characterization of antifungal activity of selenium and zinc based organometallic compounds

Surface-enhanced Raman spectroscopy (SERS) is used to identify the biochemical changes associated with the antifungal activities of selenium and zinc organometallic complexes against Aspergillus niger fungus. These biochemical changes identified in the form of SERS peaks can help to understand the mechanism of action of these antifungal agents which is important for development of new antifungal drugs. The SERS spectral changes indicate the denaturation and conformational changes of proteins and fungal cell wall decomposition in complex exposed fungal samples. The SERS spectra of these organometallic complexes exposed fungi are analyzed by using statistical tools like principal component analysis (PCA) and partial least square discriminant analysis (PLS-DA). PCA is employed to differentiate the SERS spectra of fungal samples exposed to ligands and complexes. The PLS-DA discriminated different groups of spectra with 99.8% sensitivity, 100% specificity, 98% accuracy and 86 % area under receiver operating characteristic (AUROC) curve.

SERS-PLSR Analysis of Vaginal Microflora: Towards the Spectral Library of Microorganisms

The accurate identification of microorganisms belonging to vaginal microflora is crucial for establishing which microorganisms are responsible for microbial shifting from beneficial symbiotic to pathogenic bacteria and understanding pathogenesis leading to vaginosis and vaginal infections. In this study, we involved the surface-enhanced Raman spectroscopy (SERS) technique to compile the spectral signatures of the most significant microorganisms being part of the natural vaginal microbiota and some vaginal pathogens. Obtained data will supply our still developing spectral SERS database of microorganisms. The SERS results were assisted by Partial Least Squares Regression (PLSR), which visually discloses some dependencies between spectral images and hence their biochemical compositions of the outer structure. In our work, we focused on the most common and typical of the reproductive system microorganisms (Lactobacillus spp. and Bifidobacterium spp.) and vaginal pathogens: bacteria (e.g., Gardnerella vaginalis, Prevotella bivia, Atopobium vaginae), fungi (e.g., Candida albicans, Candida glabrata), and protozoa (Trichomonas vaginalis). The obtained results proved that each microorganism has its unique spectral fingerprint that differentiates it from the rest. Moreover, the discrimination was obtained at a high level of explained information by subsequent factors, e.g., in the inter-species distinction of Candida spp. the first three factors explain 98% of the variance in block Y with 95% of data within the X matrix, while in differentiation between Lactobacillus spp. and Bifidobacterium spp. (natural flora) and pathogen (e.g., Candida glabrata) the information is explained at the level of 45% of the Y matrix with 94% of original data. PLSR gave us insight into discriminating variables based on which the marker bands representing specific compounds in the outer structure of microorganisms were found: for Lactobacillus spp. 1400 cm⁻¹, for fungi 905 and 1209 cm⁻¹, and for protozoa 805, 890, 1062, 1185, 1300, 1555, and 1610 cm⁻¹. Then, they can be used as significant marker bands in the analysis of clinical subjects, e.g., vaginal swabs.

Recent Developments in Surface-Enhanced Raman Spectroscopy and Its Application in Food Analysis: Alcoholic Beverages as an Example

Surface-enhanced Raman spectroscopy (SERS) is an emerging technology that combines Raman spectroscopy and nanotechnology with great potential. This technology can accurately characterize molecular adsorption behavior and molecular structure. Moreover, it can provide rapid and sensitive detection of molecules and trace substances. In practical application, SERS has the advantages of portability, no need for sample pretreatment, rapid analysis, high sensitivity, and ‘fingerprint’ recognition. Thus, it has great potential in food safety detection. Alcoholic beverages have a long history of production in the world. Currently, a variety of popular products have been developed. With the continuous development of the alcoholic beverage industry, simple, on-site, and sensitive detection methods are necessary. In this paper, the basic principle, development history, and research progress of SERS are summarized. In view of the chemical composition, the beneficial and toxic components of alcoholic beverages and the practical application of SERS in alcoholic beverage analysis are reviewed. The feasibility and future development of SERS are also summarized and prospected. This review provides data and reference for the future development of SERS technology and its application in food analysis.

Endophytes from blueberry (Vaccinium sp.) fruit: Characterization of yeast and bacteria via label-free surface-enhanced Raman spectroscopy (SERS)

Blueberries (Vaccinium sp.) are consumed all around the globe, however, their endophytic community has not been thoroughly researched, specifically their fruit endophytes. We aimed to isolate and analyze easily cultivable blueberry fruit endophytes to help in future research, concerning probiotic microorganisms. Twelve strains were isolated in this pilot study, genetically homologous with Staphylococcus hominis, Staphylococcus cohnii, Salmonella enterica, Leuconostoc mesenteroides, and [Candida] santamariae. To determine the molecular composition of these isolates we used label-free surface-enhanced Raman spectroscopy (SERS). To our knowledge, this is the first time that SERS spectra for L. mesenteroides and C. santamariae are presented, as well as the first report of Candida yeast, isolated specifically from blueberry fruits. Our findings suggest that the differences in tested yeast and bacteria SERS spectra and subsequent differentiation are facilitated by minor shifts in spectral peak positions as well as their intensities. Moreover, we used principal component and discriminant function analyses to differentiate chemotypes within our isolate group, proving the sensitivity of the technique and its usefulness to recognize different strains in plant-associated microbe samples, which will aid to streamline future studies in biofertilizers and biocontrol agents.

Surface-enhanced infrared absorption spectroscopy for microorganisms discrimination on silver nanoparticle substrates

Extracting molecular level label-free information from complex biological processes for a range of purposes including disease diagnosis and microbial identification and discrimination is always a challenging task. This is mostly due to lack of a technique providing rich molecular information with a high spatial and temporal resolution properties. Two surface-enhanced vibrational spectroscopic (SEVS) techniques, surface-enhanced Raman scattering (SERS) and surface-enhanced infrared absorption spectroscopy (SEIRAS), are recently attracting considerable attention to study biosystems at an interface since they can satisfy these requirements to a certain level by providing rich intrinsic molecular information from molecules and molecular systems in a close proximity of nanostructured noble metal surfaces. In this study, these two surface-enhanced vibrational spectroscopic techniques are comparatively evaluated for the discrimination and identification of Candida albicans (C. albicans), Escherichia coli (E. coli) and Staphylococcus aureus (S. aureus) by paying attention to the source of the observed spectral pattern. The citrate-reduced colloidal silver nanoparticles (AgNPs) were used as substrates. The results show that the SEIRAS provides very rich molecular information about the biomolecular species adsorbed onto AgNPs similar to the case of SERS. The discrimination power of SEIRAS is much improved compared to FTIR demonstrated by PCA analysis. This study suggests that SEIRAS can be a potential technique for microbial analysis.

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

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

Green synthesis of garlic oil nanoemulsion using ultrasonication technique and its mechanism of antifungal action against Penicillium italicum

Penicillium italicum (P. italicum) can cause significant economic loss of fruits and vegetables. Although garlic oil (GO) is an effective antimicrobial agent, the unstability and hydrophobicity limit its use as an environmentally friendly alternative to the conventional antibiotics against P. italicum. In this study, we focused on the fabrication and characterization of a functional GO nanoemulsion (NE) using ultrasonic technique and revealed the antifungal mechanism of the GO NE on P. italicum based on morphological, structural and molecular analyses. The optimal hydrophilic lipophilic balance (HLB) value determined for GO was 14 through the combination of Tween 80 and Span 80. Then the Box-Benhnken Design (BBD) was applied to produce the GO NE and the effects of different fabrication parameters on the particle size were evaluated. The optimal GO NE was selected with the GO concentration of 5.5%, the Smix concentration of 10%, the ultrasonic time of 5 min and the power of 50%. This GO NE had the smallest particle size of 52.27 nm, the best antifungal effect and the most stability. Furthermore, the antifungal mechanism of the GO NE on P. italicum was evaluated by extracellular conductivity, micro-Raman spectra, fluorescence imaging and scanning electron microscopy (SEM) imaging. The results presented that the GO NE retained the antifungal active ingredients. The fungal cell structure and morphology were malformed after treated with the GO NE and the lipids, nucleic acids and protein of P. italicum were destructed. Finally, the optimal GO NE was applied in vivo and P. italicum in citrus was successfully inhibited. It indicated that the optimal GO NE had the better antifungal activity against P. italicum than the pure GO. Besides, the minimum inhibitory concentration (MIC) of GO after preparing into the NE was changed from 3.7% to 0.01265% with about 300 times improvement of bioavailability. Therefore, the synthetic GO NE which promoted the bioavailability of GO was recommended as a promising alternative to inhibit P. italicum in vegetables and fruits.

Microfluidic device for concentration and SERS-based detection of bacteria in drinking water

There is a constant need for the development of easy-to-operate systems for the rapid and unambiguous identification of bacterial pathogens in drinking water without the requirement for time-consuming culture processes. In this study, we present a disposable and low-cost lab-on-a-chip device utilizing a nanoporous membrane, which connects two stacked perpendicular microfluidic channels. Whereas one of the channels supplies the sample, the second one attracts it by potential-driven forces. Surface-enhanced Raman spectrometry (SERS) is employed as a reliable detection method for bacteria identification. To gain the effect of surface enhancement, silver nanoparticles were added to the sample. The pores of the membrane act as a filter trapping the bodies of microorganisms as well as clusters of nanoparticles creating suitable conditions for sensitive SERS detection. Therein, we focused on the construction and characterization of the device performance. To demonstrate the functionality of the microfluidic chip, we analyzed common pathogens (Escherichia coli DH5α and Pseudomonas taiwanensis VLB120) from spiked tap water using the optimized experimental parameters. The obtained results confirmed our system to be promising for the construction of a disposable optical platform for reliable and rapid pathogen detection which couples their electrokinetic concentration on the integrated nanoporous membrane with SERS detection.

Yeast cell wall - Silver nanoparticles interaction: A synergistic approach between surface-enhanced Raman scattering and computational spectroscopy tools

Candida species are becoming one of the pathogens developing antifungal resistance due to inappropriate treatment and overuse of antimycotic drugs in building construction and agriculture. Further, fungal infections are often difficult to detect, also due to slow in vitro growth of the organisms from clinical specimens. Thus, fast detection and discrimination of yeast cells in direct patient materials is essential for an adequate treatment and success rate. In this work, we investigated Candida species isolated from patients, by using surface-enhanced Raman scattering (SERS) combined with computational spectroscopy tools, aiming to detect and discriminate between the three considered species, Candida albicans, Candida glabrata, and Candida parapsilosis. Density functional theory (DFT) was used to calculate Raman spectra of yeasts' main cell wall components for elucidating the origin of the observed bands. Accurate assignments of normal modes helped for a better understanding of the interaction between silver nanoparticles with yeasts' cell wall. Further, SERS spectra were used as samples in a database on which we performed multivariate analyses. By Principal component analysis (PCA), we obtained a maximum variation of 79% between the three samples. Linear discriminant analysis (LDA) was successfully used to discriminate between the three species.

Identifying yeasts using surface enhanced Raman spectroscopy

The molecular fingerprints of yeasts Saccharomyces cerevisiae, Dekkera bruxellensis, and Wickerhamomyces anomalus (former name Pichia anomala) have been examined using surface-enhanced Raman spectroscopy (SERS) and helium ion microscopy (HIM). The SERS spectra obtained from cell cultures (lysate and non-treated cells) distinguish between these very closely related fungal species. Highly SERS active silver nano-particles suitable for detecting complex biomolecules were fabricated using a simple synthesis route. The yeast samples mixed with aggregated Ag nanoparticles yielded highly enhanced and reproducible Raman signal owing to the high density of the hot spots at the junctions of two or more Ag nanoparticles and enabled to differentiate the three species based on their unique features (spectral fingerprint). We also collected SERS spectra of the three yeast species in beer medium to demonstrate the potential of the method for industrial application. These findings demonstrate the great potential of SERS for detection and identification of fungi species based on the biochemical compositions, even in a chemically complex sample.

Synergistic effect between silver nanoparticles and antifungal agents on Candida albicans revealed by dynamic surface-enhanced Raman spectroscopy

Identifying the mechanisms of action of new potential antibiotics is a necessary but time-consuming and costly process. We have developed an ultra-rapid, highly sensitive, and reproducible dynamic surface-enhanced Raman spectroscopy (D-SERS) method to discriminate and evaluate the sensitivity of Candida albicans to antifungal agents with different mechanisms by using silver nanoparticles (Ag NPs). Although Ag NPs have been used conventionally for the enhancement of Raman signals, the accompanying influence of Ag NPs on the microbes has not been investigated. Herein, surface charge and concentration of Ag NPs are likely to be the main influencing factors. Then different concentrations of Ag NPs with the same surface charge as C. albicans were prepared to find the optimal conditions for enhancement of Raman signals while minimally affecting tested fungi. Spectral variations were observed with increasing concentrations of Ag NPs, as well as those of antifungal agents, including echinocandin and azole drugs. The results indicated that the combination of sub-lethal Ag NPs and echinocandin drugs revealed potent synergistic effects against fungi. This could be explained by the metabolism of fungi, the result of which has also been verified by transmission electron microscopy (TEM). Lastly, the combination of sub-lethal Ag NPs and echinocandin drugs was used for a mammalian cell toxicity assay to demonstrate whether the optimal combination could cause lower cytotoxicity to mammalian cells. This work opens a window not only for the evaluation of antifungal agents with different mechanisms, but also for the clinical treatment of fungal infections or even new drug development.

Genus- and species-level identification of dermatophyte fungi by surface-enhanced Raman spectroscopy

This paper demonstrates that surface-enhanced Raman spectroscopy (SERS) coupled with principal component analysis (PCA) can serve as a fast and reliable technique for detection and identification of dermatophyte fungi at both genus and species level. Dermatophyte infections are the most common mycotic diseases worldwide, affecting a quarter of the human population. Currently, there is no optimal method for detection and identification of fungal diseases, as each has certain limitations. Here, for the first time, we have achieved with a high accuracy, differentiation of dermatophytes representing three major genera, i.e. Trichophyton, Microsporum, and Epidermophyton. Two first principal components (PC), namely PC-1 and PC-2, gave together 97% of total variance. Additionally, species-level identification within the Trichophyton genus has been performed. PC-1 and PC-2, which are the most diagnostically significant, explain 98% of the variance in the data obtained from spectra of: Trichophyton rubrum, Trichophyton menatgrophytes, Trichophyton interdigitale and Trichophyton tonsurans. This study offers a new diagnostic approach for the identification of dermatophytes. Being fast, reliable and cost-effective, it has the potential to be incorporated in the clinical practice to improve diagnostics of medically important fungi.

Characterization of Clinically Relevant Fungi via SERS Fingerprinting Assisted by Novel Chemometric Models

Nonculture-based tests are gaining popularity and upsurge in the diagnosis of invasive fungal infections (IFI) fostered by their main asset, the reduced analysis time, which enables a more rapid diagnosis. In this project, three different clinical isolates of relevant filamentous fungal species were discriminated by using a rapid (less than 5 min) and sensitive surface-enhanced Raman scattering (SERS)-based detection method, assisted by chemometrics. The holistic evaluation of the SERS spectra was performed by employing appropriate chemometric tools-classical and fuzzy principal component analysis (FPCA) in combination with linear discriminant analysis (LDA) applied to the first relevant principal components. The efficiency of the proposed robust algorithm is illustrated on the data set including three fungal isolates (Aspergillus fumigatus sensu stricto, cryptic A. fumigatus complex species, and Rhizomucor pusillus) that were isolated from patient materials. The accurate and reliable discrimination between species of common fungal pathogen strains suggest that the developed method has the potential as an alternative, spectroscopic-based routine analysis tool in IFI diagnosis.

Recent advances of microbial breeding via heavy-ion mutagenesis at IMP

Nowadays, the value of heavy-ion mutagenesis has been accepted as a novel powerful mutagen technique to generate new microbial mutants due to its high linear energy transfer and high relative biological effectiveness. This paper briefly reviews recent progress in developing a more efficient mutagenesis technique for microbial breeding using heavy-ion mutagenesis, and also presents the outline of the beam line for microbial breeding in Heavy Ion Research Facility of Lanzhou. Then, new insights into microbial biotechnology via heavy-ion mutagenesis are also further explored. We hope that our concerns will give deep insight into microbial breeding biotechnology via heavy-ion mutagenesis. We also believe that heavy-ion mutagenesis breeding will greatly contribute to the progress of a comprehensive study industrial strain engineering for bioindustry in the future.

SIGNIFICANCE AND IMPACT OF THE STUDY

There is currently a great interest in developing rapid and diverse microbial mutation tool for strain modification. Heavy-ion mutagenesis has been proved as a powerful technology for microbial breeding due to its broad spectrum of mutation phenotypes with high efficiency. In order to deeply understand heavy-ion mutagenesis technology, this paper briefly reviews recent progress in microbial breeding using heavy-ion mutagenesis at IMP, and also presents the outline of the beam line for microbial breeding in Heavy Ion Research Facility of Lanzhou (HIRFL) as well as new insights into microbial biotechnology via heavy-ion mutagenesis. Thus, this work can provide the guidelines to promote the development of novel microbial biotechnology cross-linking heavy-ion mutagenesis breeding that could make breeding process more efficiently in the future.

Understanding and Discrimination of Biofilms of Clinically Relevant Microorganisms Using Surface-Enhanced Raman Scattering

Biofilm formation is a defense mechanism for microorganisms to survive under both natural and stress conditions. Clinically relevant microorganisms threaten patient health through biofilm formation on medical devices and implants. It is very important to identify biofilm formation in order to suppress their pathogenic activities in early stages. With the aim for better understanding biofilm formation and possibility of detection, in this study, biofilm formation of clinically important microorganisms, Pseudomonas aeruginosa, Staphylococcus epidermidis, and Candida albicans are monitored with surface-enhanced Raman scattering (SERS). The SERS spectra were collected by mapping a dried droplet area where a volume of colloidal silver nanoparticle (AgNP) suspension is placed on microorganism culture plate. The spectral changes on the SERS spectra with increasing incubation time of the model microorganisms from 4 to 120 h are monitored. The unique spectra originating from the biofilms of three pathogenic microorganisms and the spectral changes as a result of time-dependent concentration fluctuations of biomolecular species in their biofilms including carbohydrates, lipids, proteins, and genetic materials allow not only identification but also discrimination of biofilms using principal component analysis.

Screening of Astaxanthin-Hyperproducing Haematococcus pluvialis Using Fourier Transform Infrared (FT-IR) and Raman Microspectroscopy

Haematococcus pluvialis has promising applications owing to its ability to accumulate astaxanthin under stress conditions. In order to acquire higher astaxanthin productivity from H. pluvialis, it is critical not only to develop efficient mutagenesis techniques, but also to establish rapid and effective screening methods which are highly demanded in current research and application practice. In this work, we therefore attempted to develop a new approach to screening the astaxanthin-hyperproducing strains based on spectroscopic tools. Using Fourier transform infrared (FT-IR) and Raman microspectroscopy, we have achieved rapid and quantitative analysis of the algal cells in terms of astaxanthin, β-carotene, proteins, lipids, and carbohydrates. In particular, we have found that the ratio of the IR absorption band at 1740 cm^-1 to the band at 1156 cm^-1 can be utilized for identifying astaxanthin-hyperproducing strains. This work may therefore open a new avenue for developing high-throughput screening methods necessary for the microbial mutant breeding industry.

Thermodynamic and conformational changes of protein toward interaction with nanoparticles: a spectroscopic overview

Nanoparticles (NPs) in different forms have been widely used in medicine and pharmaceutics for diagnosis and drug delivery.

Surface-enhanced Raman scattering: an emerging label-free detection and identification technique for proteins

The detection and identification of biologically important molecules has critical importance in several fields such as medicine, biotechnology, and pharmacology. Surface-enhanced Raman scattering (SERS) is a powerful emerging vibrational spectroscopic technique that allows not only for the characterization, but also for the identification and detection of biomacromolecules in a very short time. In this review, efforts to utilize SERS for label-free protein detection and identification is summarized after a short introduction of proteins and the technique.

Inhibition assay of yeast cell walls by plasmon resonance Rayleigh scattering and surface-enhanced Raman scattering imaging

We report on plasmon resonance Rayleigh scattering (PRRS) and surface enhanced Raman scattering (SERS) imaging for inhibition assay of yeast cell walls. This assay reveals that the proteins having alkali sensitive linkage bound to β1,3 glucan frameworks in cell walls are involved in SERS activity. The result is further confirmed by comparison of genetically modified cells and wild type cells. Finally, we find that PRRS and SERS spots do not appear on cell walls when daughter cells are enough smaller than parent ones, but appear when size of daughter cells are comparable to parent cells. This finding indicates the relationship between expression of the proteins that generate SERS spots and cell division. These results demonstrate that PRRS and SERS imaging can be a convenient and sensitive method for analysis of cell walls.

Surface-Enhanced Raman Scattering as an Emerging Characterization and Detection Technique

While surface-enhanced Raman spectroscopy (SERS) has been attracting a continuously increasing interest of scientific community since its discovery, it has enjoyed a particularly rapid growth in the last decade. Most notable recent advances in SERS include novel technological approaches to SERS substrates and innovative applications of SERS in medicine and molecular biology. While a number of excellent reviews devoted to SERS appeared in the literature over the last two decades, we will focus this paper more specifically on several promising trends that have been highlighted less frequently. In particular, we will briefly overview strategies in designing and fabricating SERS substrates using deterministic patterning and then cover most recent biological applications of SERS.

Surface-enhanced Raman scattering biomedical applications of plasmonic colloidal particles

This review article presents a general view of the recent progress in the fast developing area of surface-enhanced Raman scattering spectroscopy as an analytical tool for the detection and identification of molecular species in very small concentrations, with a particular focus on potential applications in the biomedical area. We start with a brief overview of the relevant concepts related to the choice of plasmonic nanostructures for the design of suitable substrates, their implementation into more complex materials that allow generalization of the method and detection of a wide variety of (bio)molecules and the strategies that can be used for both direct and indirect sensing. In relation to indirect sensing, we devote the final section to a description of SERS-encoded particles, which have found wide application in biomedicine (among other fields), since they are expected to face challenges such as multiplexing and high-throughput screening.