Surface-Enhanced Raman Spectroscopy for ... - ACS Publications

Review Cite This: Chem. Rev. XXXX, XXX, XXX−XXX

pubs.acs.org/CR

Surface-Enhanced Raman Spectroscopy for Bioanalysis: Reliability and Challenges Cheng Zong, Mengxi Xu, Li-Jia Xu, Ting Wei, Xin Ma, Xiao-Shan Zheng, Ren Hu, and Bin Ren* State Key Laboratory of Physical Chemistry of Solid Surfaces, MOE Key Laboratory of Spectrochemical Analysis and Instrumentation, Collaborative Innovation Center of Chemistry for Energy Materials, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, China ABSTRACT: Surface-enhanced Raman spectroscopy (SERS) inherits the rich chemical fingerprint information on Raman spectroscopy and gains sensitivity by plasmonenhanced excitation and scattering. In particular, most Raman peaks have a narrow width suitable for multiplex analysis, and the measurements can be conveniently made under ambient and aqueous conditions. These merits make SERS a very promising technique for studying complex biological systems, and SERS has attracted increasing interest in biorelated analysis. However, there are still great challenges that need to be addressed until it can be widely accepted by the biorelated communities, answer interesting biological questions, and solve fatal clinical problems. SERS applications in bioanalysis involve the complex interactions of plasmonic nanomaterials with biological systems and their environments. The reliability becomes the key issue of bioanalytical SERS in order to extract meaningful information from SERS data. This review provides a comprehensive overview of bioanalytical SERS with the main focus on the reliability issue. We first introduce the mechanism of SERS to guide the design of reliable SERS experiments with high detection sensitivity. We then introduce the current understanding of the interaction of nanomaterials with biological systems, mainly living cells, to guide the design of functionalized SERS nanoparticles for target detection. We further introduce the current status of label-free (direct) and labeled (indirect) SERS detections, for systems from biomolecules, to pathogens, to living cells, and we discuss the potential interferences from experimental design, measurement conditions, and data analysis. In the end, we give an outlook of the key challenges in bioanalytical SERS, including reproducibility, sensitivity, and spatial and time resolution.

CONTENTS 1. Introduction 2. Principle of SERS 2.1. Electromagnetic Enhancement 2.2. SERS Hot Spots 2.3. Plasmon-Shaping Effect 3. Rational Design of SERS for Bioanalysis 3.1. Preparation of Nanostructures with a High SERS Activity 3.2. Improving SERS Sensitivity by Fast Acquisition 3.3. Impurity 3.4. Reproducibility 3.5. Reliable Qualitative Analysis and Quantitative Analysis 4. When SERS Nanoparticles Meet Biological Systems 4.1. Nanobio Interface: Protein Corona 4.2. Nanoparticle Endocytosis 4.2.1. Endocytic Pathways 4.2.2. Endocytic Process 4.2.3. Factors Affecting Nanoparticle Endocytosis 4.3. Cellular Organelle Targeting © XXXX American Chemical Society

4.3.1. Cell-Penetrating Peptides 4.3.2. Nucleus Locating Signal Peptide 4.3.3. Mitochondrial Targeting 4.4. Biocompatibility and Nanotoxicity 5. Direct Bioanalytical SERS Detection 5.1. Biomolecules 5.1.1. Proteins 5.1.2. DNA 5.1.3. Metabolites 5.2. Living Cells 5.2.1. Cell Identification and Classification 5.2.2. Cellular Processes 6. Indirect Bioanalytical SERS Detection 6.1. Selection of Raman Reporter Molecules 6.2. Stability of NPs in a Cell 6.3. Biocompatibility 6.4. Interference of the Biological Environment to SERS Detection 6.5. Multimodular Imaging and Therapy 7. Summary, Challenges, and Outlooks 7.1. Summary 7.2. Challenges and Outlooks

B C C D E E E F G G H I I J J J J J

J K K K K L L M M N O P S T U V V W X X Y

Received: November 6, 2017

A

DOI: 10.1021/acs.chemrev.7b00668 Chem. Rev. XXXX, XXX, XXX−XXX

Chemical Reviews 7.2.1. Sensitivity 7.2.2. Time and Spatial Resolution Associated Content Special Issue Paper Author Information Corresponding Author ORCID Notes Biographies Acknowledgments Abbreviations References

Review

enables the observation of a signal from a monolayer species on metal surfaces, and more recently the single molecule sensitivity has been demonstrated by SERS.3−6 In the past over 40 years, SERS has found important applications in chemistry, material sciences, analytical sciences, surface sciences, biomedical research, etc. SERS shows particular advantages for bioanalysis compared with conventional bioanalysis methods: (1) SERS has an ultrahigh surface sensitivity even down to single molecule level.3,4,7−9 (2) SERS signals can reflect the intrinsic molecular fingerprint information on biological systems; (3) SERS is resistant to photobleaching and photodegradation compared with fluorescence and suitable for long-term monitoring; (4) The bandwidth of SERS peaks is usually very narrow, which is 10− 100 times narrower than that of fluorescence emission from organic dyes or quantum dots;10,11 (5) SERS enables convenient multiplex detection with single wavelength excitation; (6) SERSactive nanostructures can be designed with different sizes, shapes, and coatings for different detection purposes. Especially the SERS substrate can be optimized for the near-infrared laser to avoid the native autofluorescence from the biological samples and to minimize the photo damage of visible laser to living cells. As a result, there have been many impressive developments on SERS and its biomedical and bioanalytical applications. For example, SERS has been successfully used to detect biomolecules, pathogens, cancer cells, in vivo tumor imaging, etc.12−15 However, much efforts should be devoted to improving the reliability of SERS detection in living systems before SERS can be applied in practical clinic diagnosis. Some key issues as follows should be addressed so that SERS can solve the problems that cannot be solved by other bioanalytical techniques: (1) What do biological systems (cells, tissues, or even the living body) feel and respond to when SERS nanoparticles interact with them? Will the nanoparticles disrupt the normal biological processes? (2) What kinds of molecules can be detected by SERS in biological systems? Do SERS signals come from native biomolecules or transformed species? (3) Will the properties of nanoparticles and the sensing capability be altered in biological environments? (4) Why do SERS signals continue fluctuating during SERS detection? Can the observed SERS signals faithfully reflect the molecular evolution during the cellular or life processes? If not, how can we obtain reproducible and reliable SERS spectra to monitor cellular or life processes? In this review, we will focus on the reliability issue in SERSbased bioanalysis, addressing the above issues. Bioanalytical SERS is a very complex field and requires a comprehensive understanding of the complicated chemical and physical interactions between photons, nanomaterials, and biological systems. To guide the readers from different fields to understand bioanalytical SERS and the various factors that may deteriorate the reliability of bioanalytical SERS, we begin with a brief introduction of the enhancement mechanisms of SERS. We then outline the strategies for a better design of SERS detection for bioanalysis guided by the physical understanding of SERS. Thereafter, we introduce the current understandings of the interactions between nanoparticles and biological systems for a better design of a bioanalytical SERS detection scheme. We then address the reliability issue in bioanalytical SERS from both the label-free SERS detection and labeled SERS detection (SERS tags) of biomolecules, bacteria, and living cells. Special emphasis is placed on the feasible approaches for improving reliability in

Y Y Z Z Z Z Z Z Z AA AA AA

1. INTRODUCTION The pursuit of a sensitive and specific method for analyzing biomolecules has never been stopped for a comprehensive understanding of biological processes and early diagnosis of disease. The life processes involve the dynamic changes in the conformation, distribution, and interaction of various biomolecules, such as proteins, nucleic acids, and metabolites, in both time and space. The presence and evolution of disease generally involves the excess or deficiency of biomolecules or the presence of dysfunctional ones. Monitoring the dynamic changing events related to these biomolecules and the changes of microenvironment within a biological system is crucial to a better understanding of life processes and the evolution mechanisms of various diseases and to establishing reliable and highly sensitive diagnostic methods. Various techniques, including nuclear magnetic resonance, mass spectroscopy, electrochemistry, and cryoelectron microscopy, have provided fruitful information for the development of biomedical and bioanalytical research. However, they have some limitations either in the spatial resolution or for in vivo studying of single cells. In comparison, optical techniques, especially fluorescence microscopy, are by far the most important techniques for studying life processes, especially at the single cell level. Fluorescence microscopy offers high contrast images containing rich information on biological structures and functions by proper modification with fluorescent dyes. The development of confocal microscopy, total internal fluorescence microscopy, and recent super-resolution fluorescence microscopy has pushed our understanding of biological systems with unprecedented and explicit details. Unlike fluorescence microscopy relying on the labeling with external dye molecules, Raman spectroscopy, on the other hand, relies on the inelastic light scattering of the sample itself, as shown in Figure 1a. A Raman spectrum contains the native fingerprint vibrational information on the sample determined by the constituents, the symmetry, and the environment. Therefore, Raman spectroscopy has been successfully used to determine the chemical components, the molecular structure, the conformation, and the interaction between molecules. Raman spectroscopy can use the light from UV to near-infrared as the excitation source, offering a high spatial resolution. Furthermore, the Raman signal of water is very weak, so this technique can conveniently work in aqueous solutions without any difficulty. However, the sensitivity of Raman scattering is intrinsically low, which limits its wide application in the biomedical field. The observation and confirmation of surface-enhanced Raman scattering (SERS) phenomena on a roughened Ag metal surface in the 1970s have significantly improved the detection sensitivity of Raman spectroscopy.1,2 The million-fold enhancement B


Chemical Reviews

Review

Figure 1. Schematics of (a) normal Raman, (b) localized surface plasmon resonance (LSPR), and (c) electromagnetic enhancement mechanism in SERS, including the two-step enhancements. Reproduced with permission from ref 18. Copyright 2016 Nature Publishing Group.

phenomenon. When the incident laser impinges at the metal and dielectric interfaces, the electromagnetic wave can drive the delocalized conduction electrons of the metal nanostructures into collective oscillation. When the frequency of the incident light matches with the inherent oscillation frequency of free electrons in the metal, surface plasmon resonance (SPR) occurs. The resonance frequency depends on the size, shape, dielectric environment, and electron density of particles, the effective electron mass, etc. In metal nanostructures, the SPR can be highly localized to a specific position, which is termed localized SPR (LSPR). The nanoparticles that are able to generate a strong LSPR effect are called plasmonic nanoparticles (PNP), which are usually Ag, Au, and Cu because they show strong SPR in the visible to near-infrared region. LSPR will lead to the resonant absorption or scattering of the incident light. Thereby, the incident light energy can be effectively coupled into the metal nanoparticles and results in a 2 to 5 orders of magnitude enhancement in the local electromagnetic field intensity at the nanoparticle surface, which is the key to the huge enhancement in SERS.18 When molecules are placed near a plasmonic material, the Raman process can be significantly enhanced, leading to the socalled SERS process. The SERS process can be understood by a two-step enhancement process, as shown in Figure 1c.18 The first step results from the enhanced local field (near field) surrounding the PNPs (as receiving optical antennae) at the exciting wavelength (λex): Eloc(λex) = G1E0, where G1 is the enhancement factor of the electromagnetic field in the near field at λex, and E0 the exciting light with λex. In the second step, the PNPs serve as transmitting optical antennae to transfer Raman signal from the near field to the far field, and the Raman signal is proportional to the enhanced local electric field at the Raman emission wavelength of λem: Eloc(λem) = G2E0. Therefore, the overall SERS enhancement depends on the “exciting” and “emitting” field: GSERS ∝ [Eloc(λex)/E0]2[Eloc(λem)/E0]2 = G12G22. The optimal SERS enhancement requires a delicate balance between exciting and emitting wavelengths with the plasmon peak of the metal nanostructure. When the wavelengths of incident laser and Stokes Raman scattering signal are close to each other, G1 equals G2, and the SERS enhancement factor is

bioanalytical SERS detection on the basis of physical characteristics of SERS and biological−chemical interaction between nanoparticles and biological systems. We conclude with an indepth discussion on the challenges and the future of bioanalytical SERS from the aspect of sensitivity and spatial and temporal resolution. We hope this article may aid in designing and performing reliable bioanalytical SERS experiments and exerting the full potential of SERS in biomedical applications. Considering that a huge amount of papers related to bioanalytical SERS have been published, it is impossible for us to include all of them here. We highly recommend the readers refer to some comprehensive reviews covering the topic of the design of SERS nanostructures16−18 and SERS applications in the biomedical field13,19 and surface science20 to have a better understanding of the whole field.

2. PRINCIPLE OF SERS Since the first observation of SERS spectra in 1974,1 various physical and chemical enhancement mechanisms have been proposed to understand the SERS mechanisms. Electromagnetic enhancement (EM) and chemical enhancement (CE) are the two most widely accepted mechanisms. It is well accepted that the EM mechanism contributes dominantly to the total SERS enhancement, showing enhancements from 4 to 11 orders of magnitude. Although CE is only 10−100 times, it can significantly modify the SERS features. Up to now, the physical basis of EM is relatively clear and has been successfully applied to guide the experimental design of SERS to achieve a high detection sensitivity. The physics of CE is yet to be further explored to achieve a comprehensive understanding. In this section, we will first introduce the fundamental principles of EM and then present the key concepts of SERS hot spots, which are important to sensitive and reliable bioanalytical SERS. 2.1. Electromagnetic Enhancement

Surface-enhanced Raman scattering is a phenomenon that combines the light−metal interaction (plasmonic process, see Figure 1b) and the light−molecule interaction (the vibrational spectroscopy, see Figure 1a). It is necessary to understand the two interactions explicitly in order to understand the C


Chemical Reviews

Review

(SHINERS) method, with the inert silica or alumina shell and the Au or Ag nanoparticles as the core. SHINERS has been successfully applied to bioanalytical SERS for studying the membrane protein on bacteria and the glycan on the live-cell membrane.32,33 More recently, silica coated PNPs were utilized to study the protein corona.34

approximately proportional to the fourth power of the enhancement of the local electric field. Because the strength of the local electric field depends on the distance between the molecule and the metal surface (r) by E(r) ∝ (1 + r/a)−3 (see Figure 2a), the SERS enhancement may scale

2.2. SERS Hot Spots

In the previous section, we mainly concentrated on the general phenomenon of EM using the single PNP as example to simplify the discussion. Unfortunately, single PNP, in most cases, is not able to provide sufficient enhancement for practical applications. However, when two nanoparticles are brought close enough to each other, they can create an extremely large SERS enhancement in the gap. Such a spatially much localized volume that exhibits extremely high electric field enhancement and produces strong SERS signal is called a hot spot. Hot spots are commonly found in the gaps between nanoparticle aggregates. Figure 3a shows a model to simplify the understanding of the highly enhanced EM field in the hot spot even without considering the LSPR effect.35 When two nanoparticles with a diameter of D and a gap distance of d are placed in a uniform electrostatic field E0 polarized along the dimer axis, the local field in the gap can be estimated to be Eloc = E0(D + d)/d. The EF, i.e. (D/d + 1),4 can be 6.7 × 106 for D = 50 nm and d = 1 nm, which is much higher than that obtained from a single particle even without considering the LSPR effect.35 Theoretical calculation of the enhancement factor of an Ag dimer with 2 nm gap (∼109) is about 104 larger than that of Ag sphere (∼105) (see Figure 3b); that is, a single dimer can produce a SERS signal equal to that of tens of thousands of single PNPs. The EF can reach 1011 with the further decrease of the gap size.36 Such a high enhancement enables even single-molecule sensitivity for a variety of resonant and nonresonant molecules.37 Therefore, it is highly important for bioanalytical SERS to design SERS substrates with effective coupling between nanostructures to offer the highest sensitivity. A common strategy in bioanalytical SERS is to use the target molecules (e.g., antibody−antigen,38,39 protein,40 aptamer,41 and DNA42) to induce the aggregation or deaggregation, so that the SERS signal will turn on and off, respectively. Unfortunately, only a small portion of the whole SERS substrate can be considered as hot spots.43 It was found that 80% of the total SERS signals originate from 35% of the surface of the Ag sphere and from 0.6% of the surface of the Ag dimer.37 Furthermore, the enhancement drops by orders of magnitude over a few nanometers away from hot spot. The higher the enhancement is, the smaller the hot spot volume will be, and the lower probability to find the hot spot (Figure 3c).43,37 Consequently, during the routine SERS measurement under

Figure 2. (a) Finite difference time domain (FDTD) simulation of the electric field distribution of an Au NP. (b) Dependence of SERS enhancement on the distance from Au surfaces.

with r roughly by (1 + r/a)−12; a is the radius of NP. This relationship indicates that SERS intensity will decrease significantly with the increase of the distance (see Figure 2b).21,22 Therefore, it is necessary to anchor the molecules at the surface with the highest enhancement to achieve the highest sensitivity in SERS measurements. Three strategies have been commonly applied for anchoring molecules on the surface: (1) Electrostatic and hydrophobic interactions. For example, (1mercaptoundeca-11-yl)tri(ethylene glycol) was employed as the coating monolayer on a Ag surface to enrich glucose close to the Ag surface.23 (2) Host−guest interaction. This interaction is very universal in supermolecular chemistry and is based on the noncovalent bonding, including hydrogen bonds, ionic bonds, van der Waals forces and hydrophobic interaction, between the host (such as cyclodextrins, calixanrenes, and cucurbiturils) and guest (analytes) molecules to realize molecular recognition.24−27 For instance, the hydrobenzoin, which is hard to be detected due to the weak affinity to Ag surfaces, was successfully detected with the help of cyclodextrins modified on the Ag surface. (3) Biomolecular recognition, such as antibody−antigen, nucleic acid pairs, aptamers-target molecule, etc.28−31 It can also be seen from Figure 2b that when the analyte is located in a close vicinity to the PNP surface (within 5 nm), it can still experience some, although not the highest, enhanced electromagnetic field from the PNP (Figure 2). In other words, the Raman signals of the molecules that are not in direct contact with the PNP surface can be enhanced as well. This phenomenon is called the long-range effect, which was used to develop the shell-isolated nanoparticle-enhanced Raman spectroscopy

Figure 3. (a) Simplified model to understand the high electromagnetic field inside the gap of two nanoparticles. (b) Gap-size dependent SERS enhancement (G) of Au NPs dimer. Reproduced with permission from ref 18. Copyright 2016 Nature Publishing Group. (c) Measured distribution of enhancement factor of a SERS substrate. Reproduced with permission from ref 43. Copyright 2008 American Association for the Advancement of Science. D


Chemical Reviews

Review

Figure 4. (a) Original SERS spectra for malachite green isothiocyanate (MGITC) covalently bound to five Au nanorods with different LSPR wavelengths, showing a clear plasmon spectral shaping effect. (b) Corrected spectra for the five spectra shown in (a) by normalizing the backgroundsubtracted spectra with their background. Reproduced with permission from ref 45. Copyright 2017 Nature Publishing Group. (c−f) Four typical measuring situations in SERS detection. (g) Schematic drawing of the LSPR response from different substrates: 1 refers to (c) and (d), 2 and 3 refers to (e) and (f) respectively.

the ambient condition, the molecules can easily diffuse into and out of the hot spot, leading to a significant variation in the SERS signals (known as the blinking effect frequently observed in single-molecule SERS). If a single target molecule is replaced by another species in hot spots, the SERS spectrum will be completely altered. These two phenomena are the key issues related to reliability in both quantitative and qualitative SERS bioanalysis. It is ideal to produce a “hot surface” rather than “hot spots” to overcome the problem.

spectra will be affected by the local LSPR profile. Therefore, the PSSE effect should also be corrected. However, when a full monolayer of molecules is adsorbed on a very complicated SERS substrate (Figure 4f), the spectral features will be an average of a huge amount of local LSPR modes, giving a SERS spectrum with almost flat SERS background. In this case, PSSE does not need to be corrected, which is the case for most of the early SERS studies of full monolayer species.

2.3. Plasmon-Shaping Effect

3. RATIONAL DESIGN OF SERS FOR BIOANALYSIS Following the understanding of the SERS mechanism, we will discuss in this section the rational experimental designs/ strategies to improve the SERS detection sensitivity and reproducibility. Thereby, we hope SERS can be effectively applied to bioanalysis.

According to the two-step EM mechanism of SERS, LSPR not only provides a large electromagnetic enhancement but also modifies the relative intensity of the different SERS peaks because the LSPR strength differs at different wavelengths, which can be clearly seen in Figure 4a for malachite green isothiocyanate (MGITC) adsorbed on Au nanorods with different LSPR wavelengths. Such an effect was termed the plasmonic spectral shaping effect (PSSE).44 The spectrum distorted by the PSSE can severely mislead the interpretation of the experimental data when extracting chemical information such as molecular orientation, charge transfer mechanism, and local chemical properties. The PSSE can be corrected by normalizing the background subtracted SERS signals with the SERS background (BG): (SERS-BG)/BG, see Figure 4b.45 The corrected SERS spectra become identical to each other, and such spectra can be a good starting point to further analyze native chemical interaction. In Figure 4c−f, we list several common situations occurring in SERS measurements. Figure 4c and 4d are typical cases for SERS measurements of single molecule and full monolayer molecules, respectively, by using a dimer of PNPs (or nanoparticle over a metal film or tip over a single crystal surface). The LSPR line shape of a dimer is usually sharp (Spectrum 1 in Figure 4g) and the PSSE will be severe. The experimental spectra should be corrected by the above method in order to achieve the chemical interaction information on the molecule with the substrate. If an aggregate of nanoparticles is used as SERS substrate for single molecule SERS measurement (Figure 4e), the LSPR spectrum of the aggregate may be broader consisting of the contribution of different coupled conditions at different positions of the surface. However, when a single molecule travels along the surface, it may probe a different local sharp LSPR peak. The produced SERS

3.1. Preparation of Nanostructures with a High SERS Activity

PNP plays the key role in SERS. Therefore, in the past over 40 years, a lot of efforts have been devoted to preparing various types of PNPs and plasmonic nanostructures, and some very good reviews have already been published.18,46−48 Although a clear correlation between the SERS enhancement and the LSPR peak position has not yet been convincingly established, especially for the plasmonic coupling system, SERS substrates with optimized SERS enhancement at the desired laser wavelength, especially near-infrared laser for the bioanalysis, can still be obtained via rational design of nanostructures by controlling the sizes, shapes, materials, and coupling modes.16,18,46 Au and Ag are two of the most common materials used for bioanalytical SERS. Au nanostructures are good for excitation longer than 600 nm and are commonly used in intracellular or in vivo studies due to their excellent biocompatibility. Ag nanomaterials are good for excitation longer than 400 nm and have a better enhanced performance. Due to its strong toxicity to living systems, Ag is seldom used for in vivo analysis, but it is good for in vitro ultrasensitive detection. Up to now, various shapes of PNPs, such as nanorods,49 nanocubes,50−52 nanoplates,53−55 nanostars,56−58 and nanowires,59−61 have been synthesized and applied in SERS. Among these nanoparticles, the LSPR of nanorods can be most effectively tuned by changing the aspect ratio of nanorods.49 In addition, there are increasing reports on using multicomponent nanoparticles, including core− E


Chemical Reviews

Review

Figure 5. Scheme of dynamics SERS detection. (a) When targets are far away from the substrate, the SERS spectra are dominated by noise; (b) If the impurities move into the hot spot, the signal will be dominated by impurities; (c) When the targets move into the hot spot, the signal of the target appears; (d) is the same as (a). Therefore, the SERS signal of the target can be detected only when the target species are in the hot spots.

the LSPR in the colloidal solution of PNPs. (3) If nanoparticles assembled on solid substrates (either metallic or dielectric) are used as SERS substrates, the LSPR should be measured on the SERS substrates, which will also lead to a longer wavelength than the isolated PNP.

shell and alloyed nanoparticles, as SERS substrate for achieving optimized performance.16 Due to the poor enhancement of single nanoparticle, the above-mentioned PNPs are more often just used as building blocks for preparing SERS substrates with a high density of hot spots. More recently, there are increasing efforts to synthesize nanostructures containing interior gaps, such as core−satellite nanoparticles and yolk−shell and coremolecule-shell (CMS) structures.62−65 Especially for the CMS nanostructures, the presence of the extremely small gap by the molecule template will significantly enhance the Raman signals of the molecules in the gap as well as adsorbed on the shell.64 Although the detailed enhancement mechanism in gap is yet to be explored,64,65 CMS has been demonstrated to give signals even at the single particle level.63 Impressively, compared with nanoparticle aggregates, CMS has a very uniform enhancement without compromising the sensitivity. The readers may refer to the reviews covering the topics of hot spots18,66 and interior gap nanoparticles.17 In addition to nanoparticles, solid SERS substrates have also been widely used in bioanalytical SERS analysis. Both top-down and bottom-up approaches have been developed to achieve SERS substrates with a good uniformity.46 The readers may refer to the reviews covering the topics of SERS substrate engineering.67−69 With the PNPs and plasmonic nanostructures in hand, the experimentalists must choose the right measuring condition to fully exert the high detection sensitivity of SERS and maintain the reliability of the measurement. The complex interactions of SERS substrates with the target system will significantly modify the LSPR response of the plasmonic structures. Therefore, it is important to consider the following points when choosing the excitation wavelength for the SERS measurement: (1) If the measurement is performed on single PNPs without the formation of aggregates, one may directly use the LSPR peak position measured from either UV−vis absorption of the colloidal solution or dark-field scattering of single PNP in the same solvent as the measuring environment. (2) If the SERS measurement relies on the formation of nanoparticle aggregates to enhance the signal, the LSPR wavelength of the aggregates will shift to a much longer wavelength than the isolated single PNP. Therefore, it is suggested to measure the LSPR wavelength under the same condition of SERS measurement, rather than measuring

3.2. Improving SERS Sensitivity by Fast Acquisition

As both SERS mechanisms require the molecules to stay at a close distance to the metal surface to produce strong SERS signal,70 the diffusion of molecules on the surface and in the solution may lead to varying SERS signals with time, particularly when the target molecule has a weak affinity for the surface or their concentration is ultralow (Figure 5). When the molecule is in the hot spot, it can produce a very strong SERS signal (Figure 5c). However, when the molecule moves out of the hot spot, the Raman signal of the molecule cannot be efficiently enhanced and the detected signal will be contributed by the photoluminescence of SERS substrates,71 Raman signals of the solvent or impurity, fluorescence from free fluorescent molecules, etc (Figure 5a and d).72,73 will become the noise in the obtained SERS spectrum. Therefore, the SERS spectrum is an average of SERS signal and noise (Figure 5). When the surface coverage of the molecules is very low or the molecules have a weak affinity with the metal surface, the detected signal will be dominated by the noise. However, if the acquisition time can be shortened to the characteristic time scale of the dwell-time of the target molecule on the surface, those spectra with SERS signals of target molecules can be picked out and those spectra containing only noise background can be discarded. In this way, we can significantly improve the signal-noise ratio (SNR) of SERS detection by removing the noise spectra. Such an approach has been demonstrated to enhance the signal-to-noise ratio by 10 times by using a short acquisition on the millisecond scale.74 In addition, the SERS spectra of molecules of interest can be refined from the time series spectra while excluding irrelevant signals from impurities. However, when the SERS signal is stable during SERS experiments (high concentration experiments or high affinity molecules), long exposure time will certainly help improve SNR by averaging out the random noises. F


Chemical Reviews

Review

3.3. Impurity

parameter of the Raman instrument, including laser power, polarization, and spot size of the laser as well as the throughput of the Raman instrument. Thus, the reproducibility during SERS measurement is governed by the following three factors: substrates, molecules, and instruments. As discussed in the EM mechanism above, the electric field strength and LSPR wavelength are enormously sensitive to the sizes, shapes, and coupling modes of nanostructures, which may lead to poor reproducibility as the structure of plasmonic nanoparticles varies by nanometer-scale distance. It is still quite challenging to acquire a simultaneous high sensitivity, uniformity, and reproducibility with the state-of-the-art of nanotechnology. One promising method to improve the reproducibility is to combine SERS with microfluidics by controlling colloid aggregation and uniform analyte adsorption on solid SERS substrates.84 The microfluidic approach can help precisely control the aggregation time of colloid and the mixing efficiency of colloid and analyte solution via the flow rate and functional structure (zigzag shape structure). The fluctuation is less than 5% as shown in Figure 7.85

Metal nanoparticles are usually synthesized by reducing metal salts with specific reductants (citrate, ascorbic acid, etc.) and even with some surfactants (CTAB, PVP, etc.) to obtain a certain shape. Consequently, the surface of the nanoparticles will be inevitably covered by both reductants, surfactants, and even byproducts. Typical SERS spectra of impurities were shown in Figure 6. When the SERS substrates are exposed to air, the

Figure 6. Time series SERS spectra obtained from a Au NP assembled substrate without any probe molecules, reflecting the signal fluctuation from impurities. The spectra were excited with a laser of 785 nm wavelength and 5 mW power at an interval of 5 s. With the continuous exposure, the SERS spectra exhibit a fluctuating signal at around 1300 and 1600 cm−1. The average spectrum shows a clear graphite band.

contaminants in the environment, such as carbon and sulfur species, can be easily adsorbed onto nanostructures to produce carbonaceous signals.75 The presence of these contaminant species on the nanoparticle surface can lead to three primary results: (1) the impurity species may hinder the adsorption of the molecules of interest at the surface, especially for molecules with a weak affinity, which weakens their SERS signal; (2) the SERS signals generated by impurities will seriously interfere with the signals of target molecules and even overwhelm the detected signal; (3) the decomposition of the impurities induced by the photothermal effect or photoinduced hot carriers as a result of SPR excitation during the SERS measurement can result in the signal of amorphous carbon, which produces fluctuating peaks that will overwhelm the SERS signals from analytes even if the analytes themselves do not decompose.76 These interfering signals from impurities make it difficult to identify the target molecules or to monitor the evolution of biomolecules. To circumvent these problems, impurities can be removed just before use by rinsing substrates with a sufficient amount of solvents (water, ethanol, etc.), O2, or Ar plasma cleaning, applying negative potential, or chemical replacement using high affinity molecules such as thiol monolayers, spermine, iodide ion, etc.76−81 Iodide ion has been used to replace the impurities on the nanoparticles surface present in metal sol and self-assembled substrates.77 The iodide cleaning method significantly improved the reproducibility of SERS spectra and allowed reliable SERS detection of native proteins and DNAs, as will be introduced in the following section.82,83

Figure 7. (a) Picture of microfluidic SERS chip and (b) schematic diagram of the flow cell setup. (c) Time series of integrated Raman intensity which is nearly constant over a measuring period. Reproduced with permission from ref 85. Copyright 2007 American Chemical Society.

In practical SERS application, the SERS intensity is expected to be proportional to the number of adsorbed molecules. However, the average intensity is in reality determined by the effective number of molecules in hot spots, especially for the very low concentration case. When the molecule diffuses in and out of the hot spot, the SERS signal may vary by several orders of magnitude due to the very large electric field gradient in the hot spot region. In a more complex situation, changes in the orientation of adsorbed molecules can also lead to spectral fluctuation, because only the vibrational modes of analytes perpendicular to the surface can be amplified by the local electric field and vibrational modes oriented parallel to the surface will be weak in intensity or entirely undetectable.86 The molecule trapping method, as we discussed in section 2.1, may help to improve the reproducibility of SERS detection by avoiding the fluctuation from molecular diffusion and orientation change. Furthermore, it is necessary to maintain a good stability of a Raman instrument, including the objective, laser intensity, laser wavelength, polarization, light path, and detector, to achieve high reproducibility. Before an SERS experiment, the instrument should be carefully calibrated in both intensity and frequency. It

3.4. Reproducibility

SERS intensity is determined by the following three factors: (1) the local electric field strength near the metal surface; (2) the number of analytes within an enhanced zone and their corresponding Raman cross sections; (3) the measuring G


Chemical Reviews

Review

is noteworthy that the uniformity of SERS detection on substrates is strongly influenced by the size of the laser spot. A better result with small deviation, high accuracy, and increased precision was obtained by employing a larger laser spot, due to the average effect.87

range, large number of hot spots, or homogeneous SERS substrates or to use a microfluidic channel,85 so that we can average over either time or space to reduce the signal fluctuation and improve the reliability of quantitative analysis. Another more active approach is to use an internal standard to correct the intensity fluctuation. A common way to realize this purpose is to adsorb the internal standard molecules on the surface where the target molecules are to be adsorbed. To optimize the correction reliability, the internal standard molecules are chosen with similar chemical properties to those of the target molecules, especially in regard to the affinity for the surface.89,90 An ideal case is to use the structural analogue or isotope of the target molecule.91−93 However, the dynamic exchange and competitive adsorption of target molecules with the internal standard molecules, especially when the target concentration is high, may deteriorate the performance. In addition, the selection of internal standard requires prior knowledge concerning the target analytes, so this method is not suitable for multicomponent detection in living cells. To overcome these problems, a core-molecule-shell (CMS) nanoparticle was developed by embedding the internal standard molecules between core and shell, while target molecules were to be adsorbed on the bare shell surface, as shown in Figure 8.

3.5. Reliable Qualitative Analysis and Quantitative Analysis

Qualitative analysis and quantitative analysis constitutes two of the most important aspects of SERS application in analytical science. In qualitative analysis, the frequency (also called Raman shift, which is the frequency difference between the excitation light and the Raman light expressed in wavenumber, cm−1) of a certain Raman peak and the intensity and/or relative intensity of some characteristic peaks are used to determine the chemical content (such as the relative content of different bases in DNA) and chemical structure of species. By comparing the SERS spectrum with that from the species in their native states, the environment and the configuration of the molecules in the solution or on the surface can be further determined.82,88 The Raman shift should be precisely calibrated over a broad range of frequency from usually 100 to 4000 cm−1, to achieve a reliable qualitative analysis. Every instrument has its unique wavelength response curve as a combinatory result of the wavelength dependent response of the CCD detector, the gratings, and the mirrors, and Raman peaks at different wavelengths may experience different detection efficiencies. Therefore, the experimentally obtained Raman spectra should be calibrated by the wavelength response to obtain the native relative intensity for a reliable qualitative analysis. In SERS, before qualitative analysis, it is necessary to perform the PSSE correction if peaks with large separation (for example larger than 200 cm−1) are to be used for analysis.44,45 Alternatively, a ratiometric strategy, which depends on the relative intensity change of two very closely located Raman peaks as a response to the target concentration, has been widely used to circumvent the large error introduced by the intensity fluctuation. For instance, SERS-based pH sensors rely on the relative intensity change of the SERS spectra of pH sensitive molecules in the protonated and deprotonated states to reflect the pH of an environment. On the other hand, employing SERS as a quantitative technique is and remains challenging because the SERS signal being predominantly contributed by the molecules in the hot spots. For instance, the SERS signal from one molecule in a hot spot (with EF = 109) is comparable to that from 105 molecules in a regular area (with EF = 104).6 Therefore, a molecule in the hot spot and out of the hot spot can result in the concentration difference of about 5 orders of magnitude. Furthermore, the field enhancement in the hot spots is highly sensitive to the detailed local structures. A slight variation of the geometric structure, such as interparticle distance or molecule diffusion, may result in a signal change by several orders of magnitude. It is a common practice to produce a working curve of the SERS signal intensity with the solution concentration or in their logarithm scale. Usually the linear response region is chosen as the working region. According to the Langmuir adsorption isotherm, the very high and very low concentration ranges are not suitable for the quantitative analysis. At the high end, the SERS signal will not change with the solution concentration any longer as the surface coverage has already approached a compact full monolayer. At the low end, in an extreme case of a single molecule, when the molecule moves in and out of the hot spot, the signal difference may be of several orders of magnitude. Therefore, in practical analysis, it is more appropriate to have a moderate concentration

Figure 8. (a) Schemes of core−molecule−shell nanoparticles designed to improve SERS performance in quantitative analysis. (b) A plot of SERS intensities (solid circle) of uric acid and internal standard corrected intensity (open square) at various uric acid concentrations with physiological importance. The green and purple lines are the normal uric acid ranges for man and woman, respectively. Reproduced with permission from ref 64. Copyright 2015 John Wiley and Sons.

Therefore, the competitive adsorption between the internal standard and the target (or the species in complex biological environments) can be avoided, which is particularly valuable in biological systems. The signal of the internal standard could be effectively used to correct the signal fluctuation resulting from the different aggregation states and measuring conditions.64 This label free method does not require the internal standard molecules to display similar properties. Instead, the signal from the internal standard can be conveniently adjusted so that they will show similar Raman intensity in the detected Raman H


Chemical Reviews

Review

spectrum by choosing the right type of molecules with comparable Raman cross section to the target molecule or by adjusting the surface coverage of the molecules on the core surface. More importantly, this strategy can be used to correct any molecules adsorbed on the surface in a complex molecule environment. Another important issue that should be addressed is still related to the PSSE. During SERS detection, the size of aggregates may be different at different target concentrations, especially for the solution sol based detection. Different aggregation states may lead to different LSPR responses, which may enhance different Raman peaks at different extents as a result of PSSE. Special attention should also be taken to correct the effect and improve the reliability to obtain a quantitative relationship.45

4. WHEN SERS NANOPARTICLES MEET BIOLOGICAL SYSTEMS In sections 2 and 3, we introduced the correlation between the optical properties of a SERS substrate and its size, shape, and surface chemistry. Based on the physical mechanism of SERS, one can design nanostructures for bioanalytical SERS for improved performance while keeping the physical and chemical parameters constant. However, the biological system is very complex and dynamic. When such fabricated nanostructures are exposed to biological environments such as cells, biological fluids, tissues, or animals, the performance of the nanomaterials is typically compromised due to the unforeseen physical−chemical phenomena in physiological environments (e.g., corrosion, aggregation, unspecific absorption of biomolecules).94 Furthermore, undesirable adverse biological effects can be triggered (e.g., toxicity, allergy, genotoxicity) by the nanomaterials.95 In this case, the interaction between nanomaterials and biological systems, known as nanobio interaction, must be fully understood before bioanalytical SERS can become a practical and reliable bioanalysis technique.

Figure 9. Scheme of the endocytic process of NPs, target NPs delivery, and potential toxicity produced by NPs. Left: fundamental steps of receptor-mediated endocytosis. NPs interact with protein to form the protein corona in the culture medium before entering into the cell. The interaction may sometimes lead to aggregation of NPs. With the aid of specific receptors residing on the plasma membrane, NPs are packed into a weak vesicle and transferred into early endosome. The receptors return to the plasma membrane for next cycle of endocytosis. The early endosomes evolve into multivesicular bodies and then late endosomes. Late endosomes receive newly synthesized endolysosomal proteins from the trans-Golgi network for changing into the lysosome. Upper right: nanoparticles modified with three common cellular organelle targeting ligands, including cell-penetrating peptides (CPP), nuclear locating signal peptide (NLS), and mitochondrial targeting (MTS). Bottom right: potential toxicity caused by NPs in cells, such as reactive oxygen species.

4.1. Nanobio Interface: Protein Corona

At the interface between nanomaterials and biological systems, the organic and artificial worlds merge into a new research field that concerns itself with nanomaterial for biological applications.96 Understanding the nanobio interface may help us improve the performance of SERS nanoprobes and understand the species contributing to the SERS signals. As soon as nanomaterials are introduced to a biological environment, proteins and other biomolecules from the surroundings are rapidly adsorbed on the nanomaterial surfaces, resulting in a biomolecular layer comprised predominantly of proteins, called the “protein corona” (Figure 9).97 The “protein corona” alters the size, interfacial composition, charge, and function of nanomaterials, giving them novel physical and chemical properties different from their original ones.98,99 During the in situ measurement, this protein corona is the closest layer to the metal surfaces, which most likely contributes to the majority of the SERS signal. The material, size, shape, and surface ligand (e.g., byproduct or surfactants or premodified ligand) of original nanomaterials can influence their initial nanobio interface.96 An even more important difference may be introduced when nanoparticles approach the cell. First, the proteins adsorbed on nanoparticles may experience association and dissociation, concurrent exchange with free proteins from the medium environment. The lifetime of one protein−metal complex can range from

microseconds to days.100 The competitive binding interaction depends on the protein concentration and their affinity with the surface. Free high-affinity proteins in the medium have the capacity to cover nanomaterials as a “hard” corona, which is surrounded by a rapid exchanging outer layer formed by weakly interacting proteins.101 Second, a living cell is a heterogeneous system with diverse kinds of organelles, which contains different kinds of surface proteins. Therefore, the protein corona on nanomaterials may vary greatly depending on its location inside the cells. The third complexity arises from the cellular processes. So cells can modify the adsorbed protein layer by cellular activities such as secreting biomolecules (e.g., protein, enzyme) and transporting NPs to a new biological environment (e.g., lysosome, nucleus).99 In summary, the protein corona is a dynamic system with properties highly depending on its initial physical and chemical features, cellular microenvironment, biological processes, etc. Furthermore, the protein corona can affect the physical and chemical properties of the NPs. For instance, proteins with high dielectric constant induce a red shift of the LSPR of nanoparticles and, in certain cases, induce the dissolution of metal nanoparticles.102 In addition, reporter molecules residing on nanoI


Chemical Reviews

Review

particles can be replaced by proteins,103 leading to the aggregation induced by proteins, alteration of surface charge, and hydrophilic or hydrophobic interactions, etc.104 For small analytes, they can transport through the protein corona shell to the nanoparticle surface and can be selected by different corona according to their charges, sizes, hydrophobicity, etc. In fact, it becomes a common practice to modify the nanomaterial surfaces with polymeric moieties (e.g., PEG, BSA) as steric hindrance to prevent the nonspecific bindings of biomolecules.105

by proton-pumping vacuolar ATPases. Lysosomes are in charge of the degradation of intracellular materials.107 Biomolecules adsorbed on nanoparticles such as proteins are decomposed into various small molecules, making the lysosome a complex molecular environment.113 4.2.3. Factors Affecting Nanoparticle Endocytosis. It is reported that the endocytosis efficiency of nanoparticles depends on their physical and chemical properties, such as size, shape, composition, surface characteristics, and cell types.112 Considering that Au and Ag nanoparticles are predominantly used in SERS detection, we summarize the contributing factors influencing the cellular uptake of Au and Ag nanomaterials below. The size-dependent cellular uptake of nanoparticles has been extensively investigated in various cell lines. In the study of the uptake of 14, 50, and 74 nm Au nanoparticles in Hela cells,114 50 nm size particles were found to show the highest efficiency of cellular uptake. As mentioned above, nanoparticles smaller than 300 nm undergo receptor-mediated endocytosis. Smaller nanoparticles need fewer ligands than larger nanoparticles, and therefore, they can bind to the membrane more quickly than the larger ones. On the other hand, the larger nanoparticles have a higher efficiency to remodel the cell membrane to accelerate the internalization process. The combination of these two effects results in the optimal nanoparticle size of 50 nm. The shape of nanoparticles also influences their endocytosis behavior. It was found that the internalization efficiency decreases with the increasing aspect ratio of Au nanorods for HeLa cells, and the spherical nanoparticles showed the highest efficiency.106,114,115 The surface charge can also affect the uptake efficiency and pathway.116 Compared to nanoparticles with a neutral or negative charge, the positively charged nanoparticles exhibit a higher endocytosis uptake efficiency117 because the cell membrane has a slightly negative charge, and the cell uptake is driven by electrostatic attractions.116 As we mentioned in section 4.1, biological systems consist of numerous biomolecules with different charges; some of them will quickly cover the nanoparticle surface to form the protein corona. Therefore, study of the effect of positively and negatively charged nanoparticles should consider the surface charging effect of nanoparticle−protein complex systems.116,118

4.2. Nanoparticle Endocytosis

4.2.1. Endocytic Pathways. For studying intracellular processes, PNPs must be introduced into cells. A common method is to add nanoparticles into the cell culturing medium. Most cells uptake nanoparticles through endocytosis. Endocytosis is an energy-dependent process that describes the transfer of species from biological environments into cells.106 Endocytosis pathways are typically classified into receptor-mediated endocytosis, phagocytosis, and pinocytosis. Receptor-mediated endocytosis includes the clathrin and caveolae mediated process.107 Many types of cells use clathrin- and caveolaemediated endocytosis pathways to internalize materials with size less than 300 nm.108−110 The phagocytosis pathway is used when phagocytic cells internalize foreign materials with sizes larger than 0.5 μm.110 The phagocytosis pathway is actin-dependent and restricted to professional phagocytes, such as neutrophils, dendritic cells, and macrophages.111 The pinocytosis pathway is a nonspecific process that internalizes biological fluids from the external environment of a cell, which is very important to translocate a single nanoparticle with size below 10 nm into the cell.112 Therefore, in intracellular SERS detection, the clathrin and caveolae mediated endocytosis pathways are the most important pathways for the internalization of nanoparticles with sizes of tens of nanometer into cells. 4.2.2. Endocytic Process. Here, we briefly introduce the fundamental steps of receptor-mediated endocytosis, as shown in Figure 9. The endocytic process is comprised of several fundamental steps. The nanoparticles bind with specific receptors on the cell surface. Such an interaction may generate sufficient thermodynamic energy to overcome the elastic recoil of the membrane, which will lead to the deformation of the local membrane (also known as the membrane remodeling) and generate a vesicle.96 Once the membrane deformation reaches a point that a vesicle is budded, the vesicle will detach from the plasma membrane and then be pinched off from the membrane.107 The vesicle carries the nanoparticles with it while wandering inside the cell and delivers the nanoparticles to other subcellular locations. It should be noted that the endocytic pathway usually follows the endolysosome path, which is a spatiotemporal succession of different compartments continuously exchanging their content while undergoing structural transformation and functional makeovers.107 The first step during this process involves the early endosome that serves as a sorting station. The receptors currently binding with nanoparticles return to the plasma membrane for the next cycle of endocytosis while the nanoparticles continue transporting to lysosomes. Then, the early endosome buds off toward the inner side to form multivesicular bodies, rapidly acidifies to a pH of about 5.5, and reaches the form of late endosomes. Late endosomes receive newly synthesized endolysosomal proteins from the trans-Golgi network. Finally, the internalized nanoparticles reach the destination of the endocytic pathway: the lysosome. The pH of lysosomes is maintained at around 4.0−5.0

4.3. Cellular Organelle Targeting

According to the SERS mechanism, SERS-active nanoparticles should be located at a close distance of less than several nanometers to the target species or organelle in order to generate strong and detectable SERS signals. Consequently, intracellular SERS detection sensitivity strongly depends on the transportation efficiency of SERS nanoprobes to the interested intracellular location. For example, in order to analyze the nucleus by SERS, the SERS probes should be effectively internalized into the cell, escape the endolysosome path, and maintain the strong affinity for the nucleus. It is therefore vitally important and has been the key research field in intracellular SERS to develop SERS methods that can effectively deliver SERS nanoparticles to the specific subcellular compartments, such as the nucleus and mitochondria. Figure 9 summarizes three common cellular organelle target modified nanoparticles, such as cell-penetrating peptide (CPP), nuclear locating signal peptide (NLS), and mitochondrial targeting (MTS). 4.3.1. Cell-Penetrating Peptides. Cell-penetrating peptides (CPPs) are widely utilized to overcome the cell membrane J


Chemical Reviews

Review

reduced the ATP content, caused damage to mitochondria, and increased the production of reactive oxygen species (ROS) that damage DNA.136 In addition, both Au and Ag surfaces can induce the protein conformational change by interacting with disulfide bonds and lead to the decrease or even loss of protein activities.96 In addition, various photoinduced effects resulting from plasmon excitation of Ag or Au NPs during the SERS measurement should be carefully considered. Under the resonant excitation of the plasmonic NPs by laser, especially in the case of Au NPs, the local temperature may increase well above the physiological temperature. Such a photothermal effect during SERS detection could induce cell cytoxicity.137 On the other hand, the excitation of the LSPR of the Au and Ag NPs may generate hot carriers (hot electrons and hot holes) on the nanoparticles. These energetic carriers can react with the species on or in close vicinity to the nanoparticle surface. For example, the produced hot electrons can reduce the surface species and the hot holes can oxidize the surface species.138,139 These reactions may result in a detrimental effect on the cell. Au NPs and Ag NPs supported on dielectric materials (SiO2) were able to oxidize HCHO and incite the degradation of sulforhodamine-B (SRB).139 We observed an SPR-assisted activation of oxygen on Au and Ag nanoparticles, which induces the oxidative coupling of aromatic amine to azo species, producing a very strong SERS signal of the azo group.140 The spectral features of azo species have also been observed in early SERS studies of adenine and its derivatives, such as adenosine monophosphate (AMP) and nicotinamide adenine dinucleotide phosphate (NADP+), on Ag substrates, indicating that the biomolecules had already undergone plasmon-assisted reaction during SERS measurements.141−143 Considering the importance of adenine and its derivatives on gene structure, energy transfer, and the metabolism of live cells, such a plasmon-induced reaction may lead to the adverse effect on the cell activity. It will also mislead our understanding of the cell behavior with the spectra of reaction products. In this regard, it is highly important to carefully control the experimental conditions of SERS to prevent the photocatalytic reactions of biomolecules and minimize the potential interference with normal cellular processes. In this section, we briefly introduced the nanobio interaction, which is important for reliable SERS bioanalysis and a better understanding of the observed SERS spectra. With these understandings, the experimental conditions should be carefully controlled to avoid the potential changes of the physical− chemical properties of SERS substrates in biological environments as well as to avoid the disturbance of nanomaterials to the biological systems. In the following sections, we will critically overview the recent advances in bioanalytical SERS.

barrier to deliver therapeutic molecules (e.g., drug, nucleic acid, imaging probe) into cells. CPPs are short polycationic or amphiphilic peptides with positive charge. They can enter cells primarily via the endocytosis pathway. They have a strong electrostatic interaction with the negatively charged components of the membrane (e.g., glycosaminoglycans, GAGs) resulting in the clustering of GAGs, activation of intracellular signals, and actin remodeling, which triggers the endocytosis. The most widely used CPPs include the transactivator of transcription (TAT), arginine-rich peptides, and penetratin.119−121 CPPs have been widely used to modify the SERS active nanoparticles to improve the delivering efficiency of these nanoparticles into cells for intracellular SERS analysis.122−124 4.3.2. Nucleus Locating Signal Peptide. The nucleus is surrounded by a double-membrane nuclear envelope. Nuclear pores (ca. 30 nm) connect the nucleus and the cytoplasm to allow passive diffusion of ions and small molecules. Nanoparticles should have a small size, positive charge, and proper shape to go through the nuclear pore.105,125 Moreover, nanoparticles are usually modified with nuclear-localization signal (NLS) peptides to help nanoparticles pass through the barrier on the membrane via a signal and energy dependent process. The most frequently used NLS are PKKKRKV, CGGGPKKKRKVGG, etc.126−128 4.3.3. Mitochondrial Targeting. The mitochondrion is also a double-membrane bound organelle, which generates most of the adenosine triphosphate (ATP) in the cell and is fundamentally important for cellular energy production. Mitochondrion also plays a vital role in the regulation of apoptosis. Moreover, mitochondrion, as the powerhouse in the cell, will produce reactive oxygen species due to the high-energy electrons, leading to the oxidative stress, which is one of the leading causes of cellular toxicity.105 Mitochondrial-targeting peptide sequences (MTSs) such as MLALLGWWWFFSRKKC can be used for preparing probes for the mitochondrial SERS imaging.124 4.4. Biocompatibility and Nanotoxicity

When SERS-active Au and Ag nanoparticles are used for biomedical application, especially for in vivo detection, the nanomaterials may enter cells and interact with intracellular components such as proteins, lipids, or nucleic acids.129 The potentially hazardous effects of these nanoparticles need to be considered. Au is known to be a biocompatible material. Even so, there have been numerous investigations on the cell toxicity of Au nanoparticles in various cell lines.130 However, the toxicity issue is still controversial. Goering et al. found that 60 nm Au NPs neither were cytotoxic nor elicited pro-inflammatory responses.131 El-Sayed et al. showed that nuclear targeting of Au NPs could induce DNA damage and lead to programmed cell death due to the failure of complete cell division.132 Chen et al. found that CTAB-coated Au NRs were much more toxic than the PSS- or PDDAC-coated ones, and the membrane integrity could be damaged by the surface CTAB. Thus, they concluded that the toxicity of Au NPs is due to their surface ligand rather than the Au NPs themselves.115,130 Murphy et al. found out that gene expression related to cell cycle regulation and oxidative stress was disrupted after long-term Au NPs exposure in both an acute burst of nanoparticle exposure or a continuous, chronic exposure.133 In comparison, Ag NPs are considered to be more toxic. They can induce oxidative stress, cell cycle arrest, chromosome aberration, and DNA strand breakdown.130,134,135 The presence of Ag NPs

5. DIRECT BIOANALYTICAL SERS DETECTION Direct detection, also called the label-free method, presents the most unique advantages of SERS, in which it can provide molecular fingerprint information for both identification and detection without the presence of labeled molecules (Figure 10). In addition, the observed spectrum contains the conformation and orientation information on adsorbed biomolecules.144 Labelfree SERS has been utilized in the study of many common (macro-)biomolecules, such as amino acids and proteins, bases, and nucleic acids, as well as other metabolites in living cells.145−149 K


Chemical Reviews

Review

complicated chemical composition and relatively low Raman scattering cross sections of the functional groups that are in proximity to the nanoparticles. Even worse, the SERS spectra of the same protein obtained by different research groups (shown in Figure 11) are quite different, possibly due to the denaturation or different adsorption orientations, which may confuse new incoming researchers.46,161−165

Figure 10. Scheme of the direct SERS detection, in which the SERS signal is from the biomolecules located on the SERS substrate with a high enhancement.

5.1. Biomolecules

The SERS database of biomolecules is highly important to the identification and detection of living cells or pathogen and the understanding of the structure and configuration of biomarkers, which may help advance SERS studies in biological systems, discover potential biomedical applications, and ultimately create a biological impact. However, it is highly challenging to obtain reproducible and reliable SERS spectra to build the database because most biomolecules have relatively low Raman scattering cross sections and low binding affinity for the surface. There is a dilemma: to achieve a strong signal, the biomolecules must bind close to the metal surface and a strong interaction will remarkably modify the spectral features (especially relative intensity of different peaks) of the molecules with further complication by the coadsorbed species and the microenvironments. Thus, the same molecule can produce dramatically different spectral features on different metal surfaces under diverse conditions. Furthermore, the storage time and condition of biological samples before SERS detection may also influence the reliability because of degradation or denaturation during storage.150−152 A recent SERS study of the whole blood showed a storage time dependence, and hypoxanthine (a product of purine degradation) will be released into the plasma during about 10−20 h of storage at 8 °C.152 In this section, we will discuss the existing problems and feasible solutions in label-free SERS detection of three kinds of important biomolecules: proteins, nucleic acids, and metabolites. 5.1.1. Proteins. Label-free detection of proteins and their structures remains to be important to life sciences, including drug screening, early diagnosis, clinical therapy, and proteomics.153−156 Label-free SERS detection can provide the fingerprint information on proteins directly related to their structure in a simpler and more cost-effective way. Some proteins containing chromophore groups (e.g., cytochrome c, hemoglobin, and myoglobin) can be well characterized and detected by SERS, even at the single-molecule level, because the chromophores usually have large Raman scattering cross sections under resonance conditions.157−160 However, because the majority of proteins do not contain chromophore groups, and the size of the protein is usually over the effective range of the enhancing field from the substrate, the direct detection of such proteins remains challenging due to their

Figure 11. SERS spectra of lysozyme from different papers. Reproduced with permission from refs 163−165. Copyright 2009 American Chemistry Society, 2011 John Wiley and Sons, and 2012 Royal Society Chemistry.

Han et al. conducted systematic tests to promote the reliability and versatility of label-free SERS detection of proteins.163,164,166−168 Particularly, they developed an analytical procedure known as “Western SERS” which combines Western blotting with SERS detection.167 They used Western blotting to purify and separate protein mixtures, and the separated and purified proteins were then stained with Ag colloids to allow subsequent SERS detection. Western SERS has been successfully applied to analyze solutions of myoglobin and bovine serum albumin (BSA). On the other hand, we developed a method known as the iodide-modified Ag nanoparticles method (Ag IMNPs) to avoid protein denaturation and equalize adsorption orientations, with the ability to obtain highly reproducible and reliable SERS spectra of proteins (Figure 12a).83 The coated iodide layer on Ag nanoparticles not only eliminates the surface impurities but also offers a barrier to prevent the direct and strong interaction between the proteins and the metal surface, which can help preserve the native structures of proteins.77 The SERS features of the proteins without chromophore are almost identical to the corresponding normal Raman spectra, indicating that the native structures of proteins are well maintained. This unique feature allows for the qualitative identification of proteins by simply calculating the intensity ratio of Raman peaks (tryptophan to phenylalanine residues), which are significant for the reliable identification of proteins. Moreover, this method can be used to accurately analyze protein mixtures on the basis of their known individual SER spectra. The Matteini group used individual Ag nanocubes for the direct SERS detection of proteins, as shown in Figure 12b.169 The corner sites of the Ag nanocube serve as the SERS hot spots, which provide 80% of the total SERS signal. The PVP coating layer on the metal faces of nanocubes prevents the direct contact of proteins with the faces, driving the preferential L


Chemical Reviews

Review

Figure 13. Schematic diagram of the DNA detection. (a) SERS detection of DNA by the thermal annealing method. Reproduced with permission from ref 171. Copyright 2010 American Chemical Society. (b) Iodide modified Ag NPs for DNA detection. Reproduced with permission from ref 82. Copyright 2015 American Chemical Society. (c) Spermine-modified Ag NPs for DNA detection. Reproduced with permission from ref 78. Copyright 2015 John Wiley and Sons.

Figure 12. Label-free SERS detection of protein. (a) Normal Raman (green) and SERS spectra (red) of avidin from the Ag IMNPs colloid. Reproduced with permission from ref 83. Copyright 2014 American Chemical Society. (b) FEM simulation of the electric field distribution of a 50 nm nanocube and SERS spectra of cytochrome c obtained on Ag nanocubes by using 532 nm (black) and 638 nm (red) excitation wavelengths. The concentration of cytochrome c is 0.1 nM. The Raman signal of a 1 mM cytochrome c solution is also given for comparison (blue). Reproduced with permission from ref 169. Copyright 2017 American Chemical Society.

better if the DNA molecules can be measured in their native state without thermal annealing. Another challenge is to improve the reproducibility, which may improve the capacity of SERS to reliably distinguish between DNAs of different compositions by the minor differences in relative intensity under its native condition. To address the reproducibility issue in label-free SERS detection of DNA, we modified the Ag IMNPs method described in the previous section (Figure 13b).82 MgSO4 was added to neutralize the surface charge and enhance the electrostatic interaction between DNA and the Ag IMNPs, so that strong and reproducible SERS signals could be detected. We found that the vibrational band of the phosphate backbone could serve as an internal standard signal to calibrate the absolute signal of each base for a reliable determination of the DNA structure. With this calibration, we were able to determine the fraction of each base in oligonucleotides and obtain the absolute content of each base in a DNA sequence. Using this strategy, SERS detection of single and double-stranded DNAs with single-base sensitivity and relative nucleobase content quantification in adenine/cytosine biopolymers was fully realized. Alternatively, the Alvarez-Puebla group synthesized positively charged Ag nanoparticles with spermine molecule coating (Ag NPs@Sp) for DNA detection, depicted in Figure 13c.78 The negatively charged DNA could bind to the Ag NPs@Sp surface via electrostatic interaction, leading to stable aggregation kinetics. They were able to obtain reproducible and reliable SERS spectra of DNA duplexes. They further compared the positively charged spermine coated Ag NPs with the negatively charged halide anion-coated Ag NPs for SERS detection of DNA.172 Their results illustrated that seemingly minor experimental changes can dramatically modify the affinity and the final SERS spectral profiles of single- and double-stranded DNAs on Ag nanoparticles. 5.1.3. Metabolites. Metabolites are usually small biomolecules that play a vital role in life processes and disease diagnosis.

interaction of proteins with the corners where PVP are rare. In this way, it could circumvent the signal fluctuation caused by variable adsorption configurations at different particle areas and inside the clustered nanoparticle aggregates. This approach was used to study the interactions between cytochrome c and the Ag surface, and a quantitative analysis of cytochrome c at low concentrations was achieved. Although the reliability of label-free SERS detection of proteins has been improved, the practical diagnostic applications still remain challenging. Quantitative analysis, high-throughput detection, and dynamic conformational monitoring of proteins are the encouraged areas. 5.1.2. DNA. In addition to the challenges previously described for protein identification, SERS identification of DNA has additional difficulty because DNA molecules are formed by four bases with different relative contents and sequences. Therefore, the difference becomes very trivial with the increase of the DNA chain, especially when the content of different bases is close. The Bell group obtained the first SERS spectra for all the DNA/RNA mononucleotides with Ag colloids using MgSO4 as aggregating reagent.170 The Halas group developed a gentle thermal cycling method to relax DNA strands into an extended conformation to increase the reproducibility of the spectrum (Figure 13a).146 They further designed an adenine-free DNA sequence by substituting all the adenines by 2-aminopurine to preserve the same hybridization feature as adenine while presenting a distinct Raman spectrum.171 The amount of target strands hybridized to the probes was measured from the band intensity ratio of the Raman characteristic peaks of adenine and 2-aminopurine. It would be M


Chemical Reviews

Review

Some common metabolites, such as glucose,149,173,174 uric acid,64,175 hypoxanthine,175 and lactic acid,176 have been studied by SERS in a label-free way. The most meaningful context of metabolite detection is in body fluids or in vivo. We systematically compared drop-coating deposition Raman spectroscopy (DCDRS) and SERS techniques for the detection of microliter quantities of whole human tears.175 Interestingly, we found that the major contributors to DCDRS of tear were the high-abundant proteins, whereas SERS spectra were dominated by the uric acid and hypoxanthine, which have low abundance but strong interactions with the Ag nanoparticles. This result indicates that SERS spectra are dominated by the biomolecules with a high affinity to SERSactive metal surfaces. More significantly, the two Raman-based techniques apparently complement each other: DCDRS is advantageous for detection of high-abundant components such as protein while SERS is capable of detecting low-abundant components such as metabolites with a high affinity for surfaces in the whole tears. A combination of both techniques provided multiparameter information for a systematic analysis of clinical tears and can be further extended to the analysis of other body fluids.175 A continuous glucose monitoring method is highly desirable for the diagnosis and control of diabetes. SERS has the potential to be an alternative glucose sensor for a rapid and minimally invasive diabetes analysis. However, it is very challenging to obtain the SERS signal from glucose due to its small Raman scattering cross section and its weak affinity for metal surfaces. The Van Duyne group designed a SERS glucose sensor based on their previously developed Ag film over nanosphere (AgFON) substrates. The substrates were functionalized with a mixed selfassemble monolayer (SAM) of decanethiol (DT) and mercaptohexanol (MH) to improve the affinity of glucose with the SAM layer. As a result, they realized the first in vivo SERS glucose detection.173 Through a combination of SERS and spatially offset Raman spectroscopy (SORS), the sensor was successfully utilized for in vivo transcutaneous monitoring of glucose over the course of 17 days via subcutaneous implants in rats.149,174 The SERS database of biomolecules is in no doubt important for the future development of bioanalytical SERS, which needs the cooperation of many groups. The prerequisite to build such a database requires that every group can obtain a similar spectrum for a certain biomolecule. The surface modification strategy, which prevents denaturation of biomolecules and control of the adsorption/orientation of biomolecules on the surface, is a feasible method to achieve this goal.

enhance any molecules near the surface and the spectra obtained are too complicated to analyze for a dynamic and complex system. Statistical methods, such as principal component analysis (PCA), multivariate curve resolution (MCR), or clustering, are necessary to extract the useful biomolecular information. For studying the intracellular processes with SERS, it is necessary to introduce SERS-active nanoparticles into cells. The most common method to transport the nanoparticles into cells is to coculture cells with the nanoparticle sols via the endocytosis process as we introduced in section 4.2.108,109,113 The SERS spectra from the microenvironments surrounding nanoparticles are obtained for cell identification and classification177,178 as well as for analyzing cellular living processes,152 cellular stress responses, and nanoparticle and cell interactions.99 To explore other cellular organelles other than lysosomes, target peptide modification can effectively incite nanoparticles to escape from lysosomes and come closer to the target organelles such as nucleus125 or mitochondria.105 For the rapid delivery of metal colloids into living cells, an electroporation method was proposed to transfer Ag NPs.179 In response to the applied high voltage pulses across the cells, cell membranes will open nanoscale pores which allow metal nanoparticles to transfer into the cells. After the electric pulse, the cell membrane will recover its integrity while maintaining the nanoparticle inside the cytoplasm. It takes less than 30 min for the whole process. By this method, the retention time for the nanoparticles inside the culture medium can be significantly shortened to avoid the formation of a very thick protein corona shell, which can increase the chance to detect the intracellular components. Another method involves the internal synthesis of nanoparticles in living cells via native reduction chemistry.180,181 In this case, a solution of Au or Ag salt is introduced to the culture medium and the metal ions will be transferred into cells and reduced to nanoparticles by the cells themselves. Due to the supply of reductive species, most of the intracellular-synthesized nanoparticles naturally reside near the cytoplasm or the nucleus. The SERS signal obtained by this method is quite different from that of the uptaken nanoparticles due to the different intracellular locations. To study the cell membrane, one successful technique utilizes a SERS-active solid substrate, prepared either by a bottom-up method such as self-assembled nanoparticles on a cover glass or by top-down methods such as focused ion beam or electron beam lithography.77,182−186 The top-down methods are capable of fabricating highly uniform and reproducible substrates, but typically their enhancement is not as high as those prepared by self-assembled methods because the gap between nanostructures is limited by the spatial resolution of the fabrication method. Alternatively, we optimized the assembly method of spherical Au nanoparticles over glass or ITO substrates and have successfully obtained highly uniform SERS substrates. The substrates have been successfully employed for live-cell studies.77,187 Different from the above passive forms of detection, the SERSactive nanopipette method was proposed to precisely control the detecting location in an active way.188 It could be realized by simply assembling Au nanoparticles on the capillary or microfiber surfaces. By positioning the nanopipettes at different locations of the cell, the method can be used for intracellular and extracellular detection. The Gogotsi group developed a tipopened SERS-active nanopipette to simultaneously inject drugs and monitor the cell response via SERS signals.188 The Masson group used a nanopipette to monitor the chemical gradient of

5.2. Living Cells

With its molecular fingerprint information, SERS can easily reflect the constitution of living organisms, like living cells. SERS detection of living cells can be roughly classified into two types according to the detection modes: static detection and dynamic detection. In static detection, SERS is only used as a diagnostic method to identify and classify cells. For example, it has been used to identify different viruses and bacteria and to distinguish cancerous cells from normal ones. In dynamic detection, the focus is on the monitoring of the molecular evolution in time and space during the cellular processes, such as division, differentiation, and apoptosis. These time series SERS spectra or images can help advance the current understanding of biological processes and the evolution mechanisms of various diseases. The challenge of direct detection is that SERS-active substrates can N


Chemical Reviews

Review

wash; see Figure 15.194 This result suggests that the SERS vibrational features of bacteria could be strongly affected by the

extracellular metabolites near living cells, and the method was named the SERS optophysiology technique.189 5.2.1. Cell Identification and Classification. Pathogens. The demands of food safety and public health have created an urgent need for a rapid and portable pathogen detection technique.190 Traditional methods such as polymerase chain reaction (PCR) or enzyme-linked immunosorbent assay (ELISA) have shown robustness, yet they are limited in their ease-of-use and cost effectiveness. SERS possesses several attractive properties, such as ultrahigh sensitivity, high speed, comparatively low cost, and multiplexed capability. Cui et al. demonstrated the potential of SERS for multiplex analysis by monitoring the development of a dual-species biofilm formed by two model bacteria on a mixed cellulose ester membrane surface. The highly distinguishable SERS features of the two types of bacteria were used to characterize dynamic changes of the dominant species within the biofilm with the culture time in a semiquantitative way.191 SERS analysis of bacteria involves sampling, SERS measurement, and spectral analysis. In the sampling step, the pathogens need to be isolated from their cell medium or biological fluid. Then the bacteria are spread over a SERS-active substrate for SERS measurement. Afterward, the SERS spectra are analyzed to filter out the biochemical information on pathogens, usually assisted by chemometric methods. To fully exploit the capabilities of SERS for pathogen identification, it is essential to obtain robust and reproducible SERS signals as well as a consistent method for understanding the molecular and their corresponding biochemical origins of SERS spectra. It is crucial to optimize the preparation and enrichment procedures for handling infectious human body fluids to obtain reliable SERS spectra of bacteria. Reliable, as it is used here, has two meanings: (1) signals originate as exclusively as possible from the cells of interest; and (2) signals reflect the chemical components of cells under their natural condition. It is indeed very challenging to satisfy both requirements simultaneously. Bottomley et al. demonstrated that small quantities of residual medium in the sample could result in a strong SERS response, which would overwhelm the SERS spectra of bacteria, see Figure 14.192 Ziegler et al. then proposed water washing and centrifugation cycles to minimize signal interference from the growth media in a simple and convenient manner.193 However, they found out later that the SERS spectra of bacteria were essentially contributed by the metabolites of purine degradation from the starvation response of the bacteria during the pure water

Figure 15. Comparison of SERS spectra of three bacterial species and some model compounds. The SERS spectra of Staphylococcus aureus, Enterococcus faecalis, and Acinetobacter baumannii are compared with adenine, hypoxanthine, and xanthine SERS spectra, respectively. The SERS spectra of the model compounds are shown in red, which clearly reveal the dominant compounds in these bacteria. Reproduced with permission from ref 194. Copyright 2016 Springer Berlin Heidelberg.

nutrition-free condition during the preparation and measurement process, although pure water washing could remove the impurities. These results indicate that it is highly important to find an optimized preparation and measurement procedure to obtain reliable SERS spectra of bacteria. For instance, the mimic culture solution, which maintains the minimum amount of nutrients necessary for bacteria with little interference to the SERS signals, can be used as a washing solution to improve the reliability of SERS measurement. Cancer Cell. The SERS method, usually coupled with multivariate data analysis, has been examined for its capacity to distinguish cancer cells from healthy ones. Different SERS vibrational features associated with normal cells and cancer cells were assigned to intracellular molecules and cell surface components, such as nucleic acids, proteins, saccharides, and lipids.177,178 However, the cellular metabolite evolution that occurs during the detection process (and can therefore affect the final identification) is often ignored. Ziegler et al. demonstrated that the SERS spectra of renal cancer cells changed continuously over the 2-h duration (Figure 16). The species that contributed to the time-dependent SERS spectra are dominantly adenine, hypoxanthine, and adenosine. The spectral features evolved from an adenine-like species to the hypoxanthine-like species (The vertical black line at 736 cm−1 is to guide the identification of the Raman shift). These adenine-related species were secreted from cells as a consequence of the metabolic process and of the responses to the nutrient-free environments.195 Therefore, an improper detection environment could distort the native fingerprint information on living cells, making the identification of cancer cells and normal cells unreliable. Therefore, it is highly important to rationally control the detection environment and time to obtain reliable spectra that can reflect the different components between healthy cells and cancer cells. Even in normal Raman study, Ziegler et al. discovered that the photoinduced denaturation of hemoglobin could occur under a

Figure 14. SERS spectrum of 1:100 (v/v) diluted culture medium Nutrient Broth (a) and B. cereus: 106 cfu/mL in diluted Nutrient Broth prepared by 1:100 (v/v) dilution in nanopure water (b). The SERS spectrum of bacteria shows the spectral feature similar to that obtained in the diluted culture medium. Reproduced with permission from ref 192. Copyright 2010 Optical Society of America. O


Chemical Reviews

Review

early stage. It gives SERS spectra with sharp, fluctuating peaks spanning over the range of 1300 and 1600 cm−1. Each of the spectra looks different from the broad feature of graphite. However, when we add all these spectra together, it gives the typical broad bands of graphite. The photoinduced graphitization process can produce thousands of unstable graphitic carbon fragments. When they diffuse in and out of SERS hot spots, they produce SERS spectra with extremely fluctuating signals. This phenomenon has been pointed out in several single-molecule SERS studies.196 In order to mitigate photodamage problems, a low laser power is usually needed to measure the biological samples. In addition, we propose a defocusing method in a Raman microscope system to reduce the laser power density to minimize the photodamage effect while retaining a high detection sensitivity for systems in which the vertical spatial resolution is not of major concern. In this method, the sample stage is adjusted in a defocused state and meanwhile the slit and/ or pinhole of the Raman microscope is enlarged to detect as much signal as possible (Figure 17). For example, the defocusing method retains over 80% of the original signal intensity if the laser power density is reduced to 1% of the original value. In comparison, the signal intensity will linearly reduce to 1% of the signal intensity by reducing the laser power under the focused condition, see Figure 17b.46 As shown in Figure 17c, the SERS spectrum of an oligonucleotide obtained by a focused laser displays remarkable graphitic features, whereas the defocusing method produces clear and typical peaks of an oligonucleotide. Although the defocusing method sacrifices the spatial resolution as a result of the increased laser spot size, it is suitable for the single spot detection of photosensitive biological samples. 5.2.2. Cellular Processes. With the development of nanotechnology and electro-optical instruments, the spatiotemporal resolution of SERS has been improved significantly, allowing it to record intracellular spectra during dynamic cellular processes such as endocytic uptake, cell division, apoptosis, differentiation, and secretion. Endocytic Uptake. As we introduced in section 4.2, most of the Au or Ag particles are internalized through the endocytosis process and transported with an endocytic vesicle to different locations of the cell. Thus, the SERS spectra can reflect the molecular information in the endolysosome pathway for untargeted NPs. Understanding the endocytosis process is helpful to understand the cellular process, the nanobio interaction, and drug delivery. Kneipp et al. obtained time-series SERS spectra during the uptake process reflecting the change of

Figure 16. SERS spectra of renal cancer cells as a function of time in saline solution. SERS spectra of adenine, hypoxanthine, and AMP are shown for comparison. Reproduced with permission from ref 195. Copyright 2014 John Wiley and Sons.

high laser power even in the nonresonant NIR region.150 Furthermore, they demonstrated that the Raman peaks assigned to fibrin in early research were actually the signatures of localheating-induced heme aggregate product by a high excitation power. Such a photodegradation effect is more severe in SERS studies in the presence of metal colloids and can easily cause irreversible damage to biomolecules and cells. Therefore, it should be very cautious about the photodamage during SERS detection. Without careful control of the laser power, the organic components of cells tend to become graphitic, exhibiting broad D and G bands of graphite at 1350 and 1580 cm−1.46 The graphitic species have strong Raman signals and can quickly cover the signals of biomolecules. Under such circumstance, it is very tricky and risky to use the spectra for cell identification. Although this phenomenon is well-known to experienced groups and can be effectively avoided by controlling the experimental conditions, quite a few papers still ignored this problem and even incorrectly assigned the graphitic peaks to biomolecules. Another kind of photodamage is more deceptive and usually occurs at the

Figure 17. (a) Scheme of defocusing method. (b) Cependence of normalized Raman intensity on the laser power density obtained by the defocusing method (left) and by lowering the laser power (right). (c) Dependence of the surface-enhanced Raman spectra of an oligonucleotide-modified SERSactive Au surface on the defocusing distance of the sample to the ideal focal plane. Reproduced with permission from ref 46. Copyright 2009 Springer Science & Business Media B.V. P


Chemical Reviews

Review

Figure 18. (a) Assignments of components from the LD1 scores to lysosomes with LD1 score > −0.35 and to endosomes with LD1 score < −0.45, highlighted in blue and green, respectively. The light gray region between the green and blue regions is a transition region to guarantee an accurate classification. (b) LD1 scores were projected back into a false-color PCA-LDA map showing endosomes (green) and lysosomes (blue). Reproduced with permission from ref 198. (c) 3D plot of SERS intensity of ribose phosphate (blue), phosphate n(PO2−) (red), and COO− mode (green) and the integrated intensity map of these vibration modes during tracking single NP movements in a cell.

Figure 19. Real-time dark-field images and spectra of the targeted nucleus during the complete cycle of a single HSC-3 cell: (a) the phase of a cell cycle; (b) dark field images of living cells revealing the position of plasmonic nanoparticles; (c) correlation between cell cycle phase progressions recorded with flow cytometry; (d) SERS spectra. Dashed blue lines indicate Raman peaks associated with the G1 phase, while peaks associated with the S and G2/M phases are shown by green and orange dashed lines, respectively. Reproduced with permission from ref 126. Copyright 2012 American Chemical Society.

chemometric analysis with tailored sample preparation. The novelty of their work is that they created a sample state with a wide distribution of Au NPs within various types of vesicles as well as a reference state in which all of the NPs were localized in lysosomes by coculturing cells with sol for a long duration of time. The reference-based PCA-LDA method was able to distinctly cluster the endocytic compartments inside cells, i.e., the endosome and the lysosome (Figure 18a−b). They further found

cellular nanoenvironments, mainly from the endosomes. They found an increase of the SERS signals with the prolonged incubation of nanoparticles with the living cells, as a result of the formation of Au NPs dimer and trimer forms.197 Intracellular SERS investigations enable sensitive and controlled molecular probing from the nanometer volume near the Au NPs. Mahajan et al. identified and visualized the individual stages of endocytosis of Au NPs through the endolysosomal pathway by combining the Q


Chemical Reviews

Review

development, tumorigenesis, metastases, and tissue regeneration.205,206 Mahajan employed intracellular SERS nanoprobes modified with NLS peptide for targeting the cytoplasm as well as the cell nucleus of undifferentiated and fully differentiated human neuroblastoma cell lines. PCA of the SERS spectra from the whole cell area as well as from only the nucleus revealed a clear distinction between the undifferentiated and differentiated cells (Figure 20a). SERS spectra from the nuclear region depicted the

the variations of SERS spectra during the endocytosis process and attributed the variations to the breakdown of proteins and lipids and the rising acidity and degradation of DNA/RNA in lysosomes.198 To further improve the spatiotemporal resolution, the Fujita group combined confocal Raman microscopy with dual-focus dark-field microscopy to track single Au NPs during the endocytic process in three dimensions. The individual Au NPs were imaged by dual-focus dark-field imaging, which served as a feedback signal to steer the laser beam right on the moving Au NPs. With this technique, the confocal Raman microscopy recorded evolving SERS signals from the same Au nanoparticle moving throughout a cell. In the moving trace of the Au NPs, the SERS signals of ribose phosphate, phosphate, and carboxylic groups were obtained, which could be stacked to see the colocalization of these species during the cell motion inside the cell. The simultaneous detection of motion and the SERS spectrum enable the visualization of the endocytosis pathways (Figure 18c).199,200 In addition to metal NPs, nanomaterials such as carbon materials can also be used in SERS to monitor the endocytosis uptake process and drug delivery system. Zhang et al. employed Au NPs on the graphene oxide (GO) surface to amplify the intrinsic Raman signal of GO to investigate its cellular internalization. The SERS results revealed an inhomogeneous distribution of GO inside cells and a clathrin-mediated endocytosis mechanism of the GO uptake process.201 In their follow-up work, an anticancer drug (doxorubicin, DOX) loading system based on Ag NPs modified GO was developed for labelfree traceable drug delivery. Real-time measurement of DOX via SERS monitored the process of the drug release inside the living cell.202 The results indicate the great potential of the SERS method for in situ monitoring of drug delivering. The Cell Cycle and Apoptosis Process. The cell cycle and apoptosis process are important phenomena in cell life. They include cell growth, regular DNA duplication, cellular division, and programmed cell death.203 The El-Sayed group demonstrated SERS monitoring of the cell cycle (Figure 19a) continuously in a living human malignant cell line using nuclear-targeted Au NPs. They used PEG, RGD, and NLS modified Au NPs to increase the endocytic uptake and aid their translocation to the nucleus. As shown in Figure 19b, enhanced by the LSPR of Au NPs, the scattering signals of Au NPs could be clearly observed by dark-field-guided SERS and used to gather chemical information around NPs. SERS spectra of DNA and protein at the cell nucleus appeared to be associated with the varying stages of the cell cycle (Figure 19d). The SERS results were correlated with the gold standard of cell cycle, PI-staining of flow cytometry (Figure 19c).126 This molecular imaging platform was further employed to accurately determine drug efficacy of popular chemotherapeutics through the identification and use of the relative intensity of the 1000 and 1585 cm−1 bands. This platform also allowed the apoptotic molecular events to be monitored in real-time. The observed bands were assigned to molecular events corresponding to protein denaturation, proteolysis, and DNA fragmentation.204 The ratio of these two bands increased along with the apoptosis process. A possible reason for this could be that once apoptosis is triggered, DNA begins to fragment and lose its double-stranded feature, thereby allowing the −NH groups to be exposed to metal surfaces. More recently, this method was used to study plasmonic photothermal cell death and hyperoxia induced intracellular acidification.52,137 Differentiation. Differentiation is regarded as a vital component of various life processes, including proper embryonic

Figure 20. Analysis of nuclear SERS spectra of undifferentiated and differentiated cells. (a) PCA analysis of nuclear spectra shown as a scatter plot and 1D intensity plots for PC1 against PC2 scores. (b) Combined bar and line plots showing the normalized difference in the spectrum of nuclear peak occurrences (bars) and the PC1 loadings. Bars or peaks pointing to the upper and lower side of the plot refer to the differentiated and undifferentiated cells, respectively. Reproduced with permission from ref 207. Copyright 2013 American Chemical Society.

development that occurs during cellular differentiation by identifying an increase in DNA/RNA ratio and the amount of transcribed proteins (Figure 20b). The spectral feature indicated a higher nuclear packaging in differentiated compared with undifferentiated cells.207 Choi used electrodeposited Au nanostars on ITO as a SERS substrate to monitor the in vitro stepwise differentiation process of isolated mouse neural stem cells. The SERS spectra showed a decrease in certain DNA peaks, an increase in the percentage of proteins present, and the irregular behavior of some peaks related to both nucleic acids and proteins. Furthermore, they found the differentiated cells showed higher reversibility than the undifferentiated cells. The increase R


Chemical Reviews

Review

Figure 21. (a) Scheme of the concept of a SERS nanosensor to monitor the cellular secretion. (b) Typical response for the temporal detection of pyruvate and lactate near cells with dynamic SERS. (c) Relative number of events (%) for lactate (gray squares) and pyruvate (black triangles) near cells measured at different nanopipette−cell distances in the absence of saponin. Reproduced with permission from ref 189. Copyright 2016 American Chemical Society.

reproducibility of SERS signals. Although with the increase of the incubation time, the iodide will be replaced by molecules in an environment with a strong affinity, it offered a good chance to detect clean SERS data allowing for reliable SERS analysis.77 There is an increasing use of PEG modified target specified NPs for cellular SERS study to achieve a higher reproducibility.126,204 It can be found from the literature that PEG and organelle targeting modification may help improve the reproducibility in bioanalytical SERS, by comparing the spectra from citratecovered Au NPs,197 NLS modified Au NPs,207,210 hard shell (SiO2) covered Au NPs,34 and PEG-NLS modified Au NPs.52,126,137,204 The following reasons may account for the improved reproducibility: (1) PEG is a biocompatible polymer which can prevent nonspecific adsorption of proteins and other cellular components while keeping proteins away from the metal surface to reduce the chance of denaturation. Furthermore, thiol modified PEG can strongly adsorb on the surface, and the exchange between PEG and the biomolecules can be dramatically reduced. (2) PEG reduces the uncontrolled aggregation of Au NPs in solution with a high ion strength. (3) The dendritic structure of PEG shell could serve as a size-selective channel, exclusively permitting small biomolecules to approach the surface. Such a property may also prevent the detection of other biomolecules with high biology relevance. (4) The target specified NPs could escape from lysosomes to approach the nucleus. The molecular environment is much simpler in the nucleus than that in the lysosomes, where large biomolecules are degraded into various small molecules to compete for surface sites on the NP surfaces.

in protein percentage could indicate local variations in protein structure as well as a shift in maturation.208 Cell Secretion. Cells transport certain bioactive molecules such as hormones, neurotransmitters, or metabolites into their extracellular environment. This transportation is related to both cell−cell communication and cellular metabolism. Meulen et al. used SERS imaging to spatially resolve the depolarization-evoked catecholamine secretion by PC12 cells that occurred when Ag colloids attached to a cell membrane. The spatial resolution of SERS imaging was deteriorated by the movement and heterogeneous dispersion of the Ag NPs.209 To overcome such limits, Masson et al. decorated borosilicate nanopipettes with Au NPs to fabricate a SERS nanoprobe with addressable location, which is called dynamic-SERS optophysiology, as shown in Figure 21a. A series of SERS spectra were acquired rapidly, and the molecules secreted by cells were identified. On the basis of this identification capability, a SERS database was constructed. As the SERS-active nanopipette could be placed close to living cells, it was able to simultaneously detect multiple metabolites, such as pyruvate, lactate, ATP, and urea (Figure 21b). More interestingly, this method also allowed the quantification of the chemical gradient of metabolites near cells. Figure 21c demonstrated a decrease in the relative concentration of lactate to pyruvate with the increase of the distance of the nanopipette from the cells.189 It should be especially pointed out that a reproducible SERS signal is the prerequisite for reliable label-free SERS bioanalysis, especially for detection of cell processes. In early live-cell studies, it was often observed that SERS signals fluctuated in both frequency and intensity, making it hard to correlate the evolution of the spectra with the cellular processes. The following factors may account for the fluctuating signals from physical and biological points of view: (1) diffusion of surface molecule in and out of hot spots; (2) changes of molecular structure and orientation on the surface; (3) dynamic NPs aggregation induced change of hot spots; (4) impurities from synthesis and culture media; (5) the change of adsorbed protein corona and microenvironment; (6) the change of the molecular environments due to life processes. The last point is the main reason to perform bioanalytical SERS study of the living cells. However, it is still very challenging to extract the information on the molecules of interest from that of interfering molecules (such as impurities or other biomolecules). It is important to remove interfering molecules from the SERS-active substrate surface to produce a clean surface and to minimize the SERS signals from impurities. We proposed a method to coat a monolayer iodide on the SERS substrate to replace the surface impurities, which significantly improved the

6. INDIRECT BIOANALYTICAL SERS DETECTION The problem of direct bioanalytical SERS detection is that the resulting spectra are far too complex to be analyzed effectively, and the process of extracting meaningful data from the abundant information contained in the spectra remains an arduous task. In addition, the signals of some molecules of interest are intrinsically low and can be easily overwhelmed by other irrelevant molecules. More importantly, some physical properties, such as the local pH and the temperature inside a cell, are impossible to monitor by direct SERS detection, since there are no inherent molecules which can directly reflect such properties. Therefore, the indirect SERS method has been widely applied to the qualitative and quantitative sensing of such molecules and environment properties. In this case, the nanoparticles are labeled by SERS tags with targeting ligands, and SERS signals of tags will generate when the ligands bind to targets. Alternatively, if the molecular structure is sensitive to specific chemical or S


Chemical Reviews

Review

reporter molecules selection. (2) Raman reporter molecules should have a strong affinity for the metal surface to avoid the desorption during further modification or replacement by biomolecules in the detection environment. For example, Copper found that the signals from physisorbed labels including R6G, nile blue, crystal violet, and methylene blue decreased with increasing incubation time in the culture medium and cells due to the detachment of reporter molecules from the metal surface over time. However, chemisorbed labels provided stable signals inside cells for over 24 h.103 (3) The molecules with characteristic and well-assigned Raman peaks could be helpful to avoid signal overlapping during multiplex detection. Traditional Raman reporters and biomolecules both present multiple Raman peaks in the fingerprint region, which may overlap with each other and are difficult to separate. Several chemical groups have been developed as Raman tags including alkyne, azide, nitrile, deuterium, and metal−carbonyl possessing characteristic peaks in the Raman silent region (2000−2700 cm−1 range). Olivo et al. designed a metal carbonyl based SERS tag by combining osmium carbonyl clusters with Au nanoparticles and used the enhanced CO signal at 2030 cm−1 to perform high-contrast live-cell imaging.220 Tan et al. used diphenylacetylene functionalized PEG as a Raman reporter which showed a characteristic peak around 2030 cm−1 and obtained high-resolution Raman images of cells.221 Recently, Liu et al. prepared prussian blue coated Au nanoparticles as background-free SERS tags, as shown in Figure 23a. Prussian blue presents a strong and sharp single vibrational peak at 2156 cm−1 and, more impressively, produces surfaceenhanced resonant Raman scattering in the visible light range.222 4-Mercaptobenzonitrile was also embedded in a core−shell nanostructure, which depicted a sharp Raman peak around 2232 cm−1, to further enhance the SERS signal of Raman tags and achieve cell imaging with a high signal-to-background ratio in the following work.223 All these tags possessed the capacity to avoid overlapping with the peaks from the intracellular species and provided a very clear and high-contrast image of cells, especially when the concentration of target is low in the biosystems. However, compared with fluorescence microscopy, single component analysis by SERS is not advantageous. Since the bandwidth of SERS peaks is much narrower than that of fluorescence, SERS-based detection using functionalized nanotags possesses the capacity of multiplex detection with singlewavelength excitation. The multiplexed sensing ability is of great importance to a comprehensive understanding of the cell processes, monitoring of cell events, as well as accurate diagnosis of disease. For an efficient SERS-based multiplex detection, Raman tags must possess high stability when integrated into a system and well separated distinguishable peaks. Moreover, probes must be targeted with precision without cross interference to ensure that detected signals come from the components of interest. Lim et al. inserted three different Raman-active molecules into the narrow intrananogap of Au nanoparticles with different subcellular-organelle targeting peptides. The extra enhancement within the nanogap allowed them to create high speed, high resolution multiplexed cellular imaging (Figure 23b).124 Hu et al. carefully designed three 4ethynylbenzenethiol derivatives (OPE molecules) with different substitution groups. Therefore, these three molecules showed a marked difference in the Raman peak position of the alkyne group. Three color interference-free SERS multiplex cellular imaging has been demonstrated by modifying the three SERS tags with different receptors to anchor to different positions of the cell (Figure 23c).224 They further performed multiplexed

physical properties, the spectral feature will change with the change of environment properties. Such type of molecules can be used as SERS reporters for sensing. The observation of the specific Raman spectra of tags or the spectral change may indicate the presence of the target molecules or reflect the physical or chemical properties of the sample (Figure 22). Due to the

Figure 22. Scheme of the indirect SERS detection. (a) The PNPs are first labeled with reporters to form SERS reporters, which are then modified with targeting ligand to specifically bind with the target. The appearance of the SERS signal of reporters indicates the presence of the target. If the target can form multivalent interaction with the targeting ligand with either another plasmonic nanoparticle or a plasmonic metal substrate, it will lead to formation of a hot spot to give a strong SERS signal. (b) The PNPs were modified with environment (pH, temperature, potential, etc.) sensitive molecules; the change of the SERS signal of the reporter molecule can reflect the physical and chemical properties.

introduction of reporter molecules, indirect detection loses the advantage of SERS to provide fingerprint information. Generally, SERS tags play the same role as fluorescent molecules. Compared with fluorescence microscopy, indirect SERS detection possesses the following merits: (1) a stable signal devoid of photobleaching, (2) multiplex detection with single wavelength excitation due to its narrow peak width, and (3) excitation via an NIR laser with low autofluorescence interference. The indirect bioanalytical SERS method has been widely applied in the detection of protein,211,212 DNA,213,214 livecell imaging,215,216 and cancer diagnosis.217−219 The key issue in indirect detection is to design and develop multifunctional SERS tags possessing high sensitivity, specificity, and selectivity. The challenges of reliability in indirect detection can be summarized in the following aspects. 6.1. Selection of Raman Reporter Molecules

The main requirements of an ideal Raman reporter molecule are as follows: (1) The reporter molecules must have a relatively large Raman scattering cross section to produce strong SERS signals. The optimal scenario involves an optical absorption of the Raman reporter that matches the excitation laser as well as the LSPR of the nanostructure, leading to an extra 102−103 enhancement due to the surface-enhanced resonance Raman scattering. For example, Graham et al. reported one of the first comprehensive studies of SERRS for DNA analysis with R6G labeled probes.213 Their results showed a sensitivity comparable to fluorescence microscopy which illustrated the importance of T


Chemical Reviews

Review

different Raman active molecules to obtain rapid, high-spatial resolution spectroscopic imaging over a wide-area of living mice via their self-designed small animal Raman instrument.225 Chang et al. combined three different lipoic acid-containing NIR active tricarbocyanine reporter molecules for the multiplex imaging of tumor sites in mice226 in 2014. They then utilized easily obtained Raman reporters, including MGITC, Cy5, and R6G modified Au nanoparticles, to perform an in vivo time series multiplexed detection of xenograft tumor biomarkers.227 In summary, all of these multiplex SERS imaging methods resulted in the nonoverlapping peaks of reporter molecules and created images with great detail and clarity for multicomponent analysis. Very recently, Min et al. created a palette of triple bond-conjugated near-infrared dyes with each of them displaying a single peak in the cell-silent Raman spectral window. This palette provided 24 resolvable colors via stimulated Raman scattering, which exemplified the great power of multiplexed cell Raman imaging.228 However, if various colored images were constructed when all of the 24 tags were taken from the same cell, it would be of much interest and significance. A common problem for multiplexed SERS imaging is the limitation in the choice of tags. The overlapping of peaks may occur with the increased number of targets and when the biological system in question becomes increasingly complex. These factors lead to a change in the sensing capability while the SERS peaks of biomolecules simultaneously incite additional overlaps in the presented peaks. To overcome this problem, it is necessary to apply additional Raman molecules possessing distinct peaks and to employ appropriate algorithms that can separate out the necessary information. 6.2. Stability of NPs in a Cell

When nanoparticles enter a cell, the competitive adsorption of biomolecules inside the cells may strongly disturb the reporter molecules, potentially causing the desorption of the tags. This phenomenon was observed and studied by Baranska et al. when they used R6G conjugated nanoparticles for intracellular SERS imaging.229 They found that the Raman reporters were detached from the surface of the SERS substrate in the intracellular environment after just 0.5 h of the incubation time because the SERS signals of biomolecules were observed. This may imply that the exchanging of adsorbates is driven by the local optical field of the metal nanoaggregates and/or the rearrangement of Au nanoaggregates in such a way that causes SERS hot spots to form around molecules other than the dye. There are two main ways to prevent the desorption of SERS tags. The first is to modify the surface of the nanoparticles with an extra molecular layer to protect the nanoparticles and tune their surface properties. We used BSA as a coating layer to protect the pH sensing SERS nanoparticles, which significantly improved the reproducibility of intracellular pH sensing.230 Dacarro et al. investigated the impact of PEG molecules as a coating layer, and reported that the stability of nanoparticles could be improved and the SERS signals of reporter molecules preserved for as long as 24 h. In addition, the outer sphere of these nanoparticles could be further functionalized with extra groups to tune the surface properties.231 Domenici et al. studied the function of another common surface coating molecule, folic acid.232 They demonstrated via size distribution measurements that the stability of the nanoparticles in cell culture medium was improved due to the negative surface charge provided by carboxylic groups. Folic acid was able to prevent the formation of an adhesion layer of proteins around nanoparticles, which could both protect Raman tags from

Figure 23. Appropriate selection of Raman tags for improved cellular imaging and multiplex bioanalytical SERS analysis. (a) Schematic structure and SER spectra of prussian blue encoded nanoparticles for interference-free SERS imaging of a single cell. Reproduced with permission from ref 222. Copyright 2017 American Chemical Society. (b) High resolution multiplexed live-cell SERS imaging using subcellular organelle-targeting Au nanoparticles with a highly narrow intrananogap. Reproduced with permission from ref 124. Copyright 2015 American Chemical Society. (c) Three-color SERS imaging of HeLa cells using SERS probes of an alkyne SERS palette, the SERS probes were modified with OPE0 (red), OPE1 (green), and OPE2 (blue). Reproduced with permission from ref 224. Copyright 2016 American Chemical Society.

SERS imaging in single cells for 3D imaging.128 They fabricated nucleus and membrane targeting Au nanoparticles respectively and modified them with different Raman probes. In combination with the confocal Raman system, the high-resolution 3D image of a single cell could be obtained. In addition to cell detection, Gambhir et al. used silica coated Au nanoparticles with four U


Chemical Reviews

Review

nanostructure with an embedded Raman probe acting as an internal standard to correct the fluctuation of samples and monitor measuring conditions for the sake of attaining the reliable quantitative analysis of target molecules.64 Several other similar core−shell structures were also applied in cellular imaging.239,240 Compared with silica coating, the formation of a metal shell provides an increased enhancement for Raman molecules embedded in the nanogap, greatly increasing the sensitivity.

undergoing desorption and improve the selectivity. Besides polymer protection, silica or mesoporous silica is another widely utilized surface protecting material that can improve stability. The Schlücker group reported the silica encapsulation of a layer of Raman reporter on metallic nanoparticles.233 In this way, the Raman reporter could be optimized for excitation and the silica served as a protective layer as well as efficient bioconjugation sites. He et al. demonstrated multilayer-coated Au nanorods, which contained dyes doped in silica and polymer layers.234 They found that upon silica coating, SERS and fluorescence signals remained stable between pH values of 1−12. An extra advantage of the silica coating is that the silica layer on the metal surface can be functionalized with fluorophores, and a new protecting layer can be easily added for multimodal imaging.235,236 The Choo group designed silica-encapsulated hollow Au nanosphere tags using a layer-by-layer method.237 The presence of a PAA layer in this method extended the range of Raman reporters with either strong or weak binding sites. In this manner, multiplexed SERS imaging was performed with improved image quality. The second way to protect reporter molecules is to fabricate another metal surface on the outer sphere to form a corereporter-shell structure. This unique structure can prevent the competitive adsorption of molecules in cells with the Raman tags and may also provide an extra enhancement to the molecules embedded between the core and the shell. Nam et al. proposed that DNA on Au nanoparticles could facilitate the formation of well-defined Au nanobridged nanogap particles (Au-NNP) that generated a highly stable and reproducible SERS signal, see Figure 24a.63 The uniform and hollow nanogap between the Au

6.3. Biocompatibility

When nanoparticles are functionalized with reporter molecules, the generation of ROS and singlet oxygen can potentially cause damage to living cells. This is a well-documented phenomenon in fluorescence microscopy.241,242 To overcome this problem, Tan et al. developed a graphene-isolated-Au-nanocrystal (GIAN) for SERS detection (Figure 25a).243 The graphitic shell of GIAN

Figure 25. Special design of nanoparticles for improved biocompatibility. (a) Schematic structure of graphene-isolated-Au-nanocrystal for quantitative analysis with improved stability upon laser irradiation and oxides. Reproduced with permission from ref 243. Copyright 2016 American Chemical Society. (b) Mesoporous silica-coated gapenhanced Raman tags with reduced photothermal effects and ultrastability. Reproduced with permission from ref 244. Copyright 2017 American Chemical Society. Figure 24. Core−shell structure nanoparticles for enhanced SERS signal and protection of Raman tags. (a) Schematic structure and SER spectra of DNA-tailorable Au nanoparticles with 1 nm interior gap. Reproduced with permission from ref 63. Copyright 2011 Nature Publishing Group. (b) Schematic illustration of the synthesis and the chemical structure of the Raman dye-tagged amphiphilic block copolymer and its applications in cell imaging. Reproduced with permission from ref 238. Copyright 2014 American Chemical Society.

could transfer laser heat rapidly, thus avoiding the inner Au catalysis of unnecessary reactions as well as the photocarbonization induced by strong laser irradiation during Raman detection. Moreover, the 2D band of GIAN located in the Raman silent region served as an internal standard possessing low background interference. Ye et al. has also recently developed mesoporous silica coated gap-enhanced Raman tags with built in Raman reporters (Figure 25b).244 These tags exhibited reduced photothermal effects because of off-resonance laser excitation. Furthermore, they are tolerant to pH change and serum and have a long storage, photostability, and favorable biocompatibility.

core and shell could generate a high SERS enhancement and uniform SERS intensity while guarding the Raman reporters. The Duan group reported a new strategy to synthesize core−shell metal nanoparticles with an interior, Raman tag-encoded nanogap by taking advantage of the nanoparticle templated self-assembly of amphiphilic block copolymers as well as the localized metal precursor reduction via redox-active polymer brushes to perform SERS imaging of living cells; see Figure 24b.238 The stability of reporter molecules was improved and the distance of the interior nanogap became easily adjustable for broader applications. We designed a core−molecule−shell

6.4. Interference of the Biological Environment to SERS Detection

When designing sensing probes, it is imperative high selectivity should be attained. Long et al. has developed three sensing probes based on the selective palladacycle carbonylation of CO, the reaction between H2S and 4-acetamidobenzenesulfonyl azide, and Au NPs modified with oxidized cytochrome c for V


Chemical Reviews

Review

the intracellular sensing of CO, H2S, and O2•− molecules, respectively.245−247 They carefully studied the interference of biological species with similar chemical properties and their effects on the sensing capability and high selectivity of their sensing procedures, as shown in Figure 26a. Moreover, they also

evaluation of microenvironment pH (Figure 26b). Therefore, the reliability of pH sensing based on 4-MPy molecules should be comprehensively investigated. Some other molecules used for intracellular sensing may also be sensitive to more than one factor. Campbell et al. developed a quinone based nanoparticle for intracellular redox potential sensing.259 However, the electron transfer scheme is related to hydrogen ions so the changes of pH may influence the potential dependent response. This serves as a reminder that the calibration of a single curve is not enough for the reliable characterization of living cells, thus creating a need to achieve multicomponent detection in such a system. To calibrate and investigate the actual influence of pH on the sensing capabilities, they added MBA modified nanoparticles for simultaneous sensing of intracellular pH and redox potential.260 This multiplexed sensing technique provided dual channel information to validate gathered results as well as complementary information, allowing them to gain a more comprehensive understanding of the cellular process. However, if only the influence of pH on the sensing capabilities of the redox potential was able to be tested (without contributions from other factors), the reliability of the results could be further improved. When performing intracellular sensing, it is important to note that the state of particles is different in cells from that in buffer solution. The interaction between particles and biomolecules could change the surface coating and aggregation state of sensing probes as well as the state of Raman active molecules on the surface. This means that the calibration curve obtained in buffer solution may not reflect the actual response of a real sample system. To overcome this problem in live cell pH sensing, we systematically studied the response of a SERS-based pH nanosensor after BSA coating in PBS and culture media.230 The reproducibility and stability were both improved. Furthermore, the pH response remained unchanged in various solutions within solutions possessing high ionic strength as well as the cell culture medium (Figure 26b). The results indicate that the calibration curve obtained in buffer is still effective even in the context of severe aggregation conditions or complex real systems. However, even after protecting the tags from directly interacting with the surrounding environment by adding new layers, the complex interaction between the biosystem and nanoparticles could still create a significant detection difference between nanoparticles in buffer solution and nanoparticles within a real biological sample. As a result, the experimental conditions for the calibration curve obtained in buffer solution are still quite different from the conditions of the real sample, so the reliability of the calibration curve in question remains uncertain when it is applied to cell sensing. One way to overcome this problem is to perform calibration in a system that mimics the cellular environment to mitigate potential differences. This concept has been successfully utilized in fluorescence microscopy, intracellular calibration, and artificial cytoplasm calibration.261

Figure 26. Strategies for calibration of intracellular sensing. (a) 4Acetamidobenzenesulfonyl azide modified nanoparticles for high specificity and selectivity intracellular H2S sensing. Reproduced with permission from ref 245. Copyright 2015 John Wiley and Sons. (b) BSA coated 4-MPy modified nanoparticles for improved stability and reproducibility, which allow the plot of a reliable calibration curve. Reproduced with permission from ref 230. Copyright 2014 American Chemical Society.

tested several other properties, such as pH, to further prove the single variate based sensing property. Similar methods have also been developed for the sensing of intracellular hypochlorite and glutathione,248 NO,249 and H2O2.250 Similar specific recognition properties have also been applied to real sample sensing such as glucose in urine and serum,251 histone demethylase activity,252 fructose,253 and protein c-MYC in blood samples.254 Moreover, the Olivo group found that the specific antibody−antigen binding may lead to the shift of the vibrational frequencies of the conjugated SERS reporters as a result of the antibody−antigen interaction forces, which broadens the way for detecting binding events by SERS.255 Another important topic of SERS sensing is related to the design of probes. It is usually expected that a probe is sensitive to only one variate, yet in reality, many other factors may influence the sensing capability. For example, the intracellular pH is an important parameter in live cell study and has been initially investigated by Kneipp and other groups with the SERS technique.256−258 The sensing performance of pH sensitive molecules may be affected by several factors. We have studied the influence of laser power and irradiation time on the relative intensity of the Raman peaks of a pH sensitive molecule, 4Mpy.187 We found that the single-/double-end-bonded state of 4-MPy transformed due to laser irradiation, a phenomenon reflected by the relative intensity ratio of I1575/I1610 in the

6.5. Multimodular Imaging and Therapy

It is crucial to provide extra evidence and experimental data for validating the accuracy of SERS information and providing multiparameter information. This is particularly important in the accurate diagnosis of diseases. For this purpose, since the first SERS imaging of tissue by the Schlücker group,262 much effort has been devoted to developing nanostructures with the capacity of dual imaging or multi-imaging. The multiple channel information obtained can verify among different channels of signals, thus improving the reliability. Moreover, with a W


Chemical Reviews

Review

combination of techniques (first, fluorescence, then SERS) one can rapidly obtain a rough view of an investigated area before utilizing SERS to gather a precise diagnosis.263 In this way, the imaging speed can also be greatly improved. The Jeong group developed a dual modal fluorescence-Raman endomicroscopic system and realized real-time, in vivo, and multiple target detection of a specific cancer.264 We developed an Au@ organosilica nanoparticle with embedded Raman reporters and surface modification with fluorescence markers (Figure 27).265

functions such as photothermal and photodynamic therapy, drug delivery, and magnetic separation, etc. In this case, SERS tags can be combined with the various therapy and detection methods to fabricate an “all-in-one” multifunctional nanoparticle.202,218,234,265,266,270−273 For instance, Halas et al. investigated the nanoshell-based photothermal therapy of cancer274,275 and EI-Sayed et al. studied the same process by using nanorods.276,277 Following these pioneering works, He et al. developed a Au nanorod platform doped with SERS and fluorescence tags as well as photosensitizers for simultaneous multimodal tumor detection and simultaneous photodynamic therapy (Figure 28).234 Wang et al. developed the double-walled

Figure 27. Au@organosilica nanoparticles for multiplex detection. (a) SERS spectra of FITC-MGITC Au@organosilica nanoparticles, XRITC-MGITC Au@organosilica nanoparticles, and their 1:1 mixture. (b) Confocal microscopic fluorescence images showing the distribution of FITC-MGITC Au@organosilica nanoparticles and FITC-XRITC Au@organosilica nanoparticles in the cell. (c) Bright field microscopic image of a HeLa cell. SERS images produced by using the baseline corrected intensity of the 1613 cm−1 Raman band of MGITC (d) and the 1502 cm−1 Raman band of XRITC (e), respectively. (f) The merged figure of (d) and (e) to illustrate the distribution of two types of labeled multifunctional nanoparticles in the cell. (g) Typical SERS spectra obtained at different locations of (f). Reproduced with permission from ref 265. Copyright 2011 Royal Society of Chemistry.

Figure 28. Multifunctional Au nanorods for in vivo fluorescence imaging and SERS detection of tumor. (a) Fluorescence image with three locations emitting strong signals (red arrows). (b) Fluorescence spectra and (c) 508 cm−1 SERS intensities from three locations. The inset in (d) shows an SERS trace. Reproduced with permission from ref 234. Copyright 2013 John Wiley and Sons.

Au nanocage/SiO2 nanorattle for SERS, drug delivery, and photothermal therapy. These unique nanorattle nanoplatforms could serve as a highly efficient antidrug carrier, a sensitive SERS substrate, as well as an effective NIR photothermal agent.273

7. SUMMARY, CHALLENGES, AND OUTLOOKS

The nanoparticle can provide Rayleigh scattering of the Au core, fluorescence signals of the fluorophores, and SERS detection of the Raman reporters for live cell imaging and related biological research. Zhang et al. developed a γFe2O3@Au core/shell type nanostructure for combined magnetic resonance and photoacoustic and SERS imaging of tumors in mice which provided ultrasensitivity, precise localization, and high spatial resolution due to multimodal imaging.266 Gambhir et al. developed a triplemodality, MRI-photoacoustic-Raman nanoparticle for brain tumor imaging.267 Both Cui and Chourpa groups developed SERS and fluorescence dual-encoded magnetic nanoprobes for multiplexed cancer cell detection and separation.268,269 In addition to imaging and sensing capability, the native properties of metal nanoparticles lead to potential biomedical

7.1. Summary

SERS is by far the most fascinating technique that can offer intrinsic molecular fingerprint information with ultrahigh sensitivity under aqueous environment. Great successes have been achieved by using SERS for the sensitive and specific detection of biomolecules, pathogens, cancer cells, cellular processes, etc., resulting in a fast-growing field called bioanalytical SERS. However, there is still much work to be done in the field before SERS can be fully implemented in practice to answer significant biomedical questions. The reliability of SERS relies on the rational design of SERS substrates, appropriate sample preparation, delicate control of the measurement conditions, and adequate data analysis. We X


Chemical Reviews

Review

Table 1. Tips for Reliable Bioanalytical SERS Experiments Substrate design

Sample preparation

SERS measurement

Data analysis

(1) High enhancement, uniform, clean, and anti-interference. (2) High biocompatibility, ideally with protecting layer to effectively avoid unspecific protein adsorption. (3) Capable of targeting the analytes of interest. (4) Capable of trapping the analytes in the “hot spots” with the functionalized molecules. (5) Ideal Raman reporter molecules for indirect detection: large Raman cross section, high affinity to the surface, simple and sharp bands, and specific response to target molecule and physical and chemical properties. (1) Properly store the biomolecules to avoid degradation. (2) Retain the biomolecules in their native state. (3) Keep the cell and tissue samples under proper control of temperature, humidity and nutrition. (1) Proper laser wavelength and power to prevent photothermal and photochemical reactions of target molecule. Caution: graphitic signal at 1350 and 1580 cm−1 and early graphite signal as sharp, fluctuating peaks spanning over the range of 1300 and 1600 cm−1. (2) Appropriate exposure time and accumulation times for optimized SNR. Faster exposure time to improve SNR for weak interaction analyte on the surface and very low concentration. (3) Appropriate detection environments, including solution, pH, temperature, and atmosphere etc., to avoid introducing interfering species. Attention to the protein corona formed on nanoprobes. (4) Measurement under a similar environment to that of the normal state of biological samples. (1) Accurate biomolecule database for spectral assignments. (2) Calibration of the sensor in both the buffer and real/or mimic environment. (3) Calibration of the relative intensity of SERS spectra by (SERS-BG)/BG strategy to achieve the native chemical information. (4) Use of internal standard for reliable quantitative study. (5) Proper data preprocessing and statistical analysis.

dimer structures with strong plasmonic coupling from sub5 nm gap size were formed, which allowed for the label-free detection of the DNA coated on the NPs and provided great potential for a wide variety of biosensing and single-molecule applications.284 Another important approach to increase the detection sensitivity is to ensure that the molecules can always be maximally enhanced while they diffuse over the SERS substrate. It requires a SERS substrate with a high density of “hot spots” with uniform SERS enhancement, which is the key to the reproducibility of the SERS technique. In addition, the substrate should have a good chemical and photostability during storage and measurement. During the SERS measurement, the laser will excite the LSPR of the SERS substrate, which may elevate the surface temperature or produce high-energy hot carriers, leading to the desorption, photodecomposition, or photobleaching of the molecules.43,285,286 Therefore, one should be very cautious to control the laser power density and the laser wavelength to minimize all these possible effects. Especially, for the photochemical reaction case, the signal detected is no longer from the molecule we are really interested in. The detection sensitivity can also be improved by reducing the noise resulting from impurities, the photoluminescence from nanostructures, and the fluorescence signals of the dye reporter, as well as the noise levels of the detector.71,73 Indeed, there is still plenty of progress to be made before single-molecule detection can be achieved in real complex biological systems. 7.2.2. Time and Spatial Resolution. Time Resolution. Biological processes occur at a time scale spanning over ten orders of magnitude. There is endless pursuit for higher time resolution to decipher the processes occurring in dynamic systems, such as living cells. There are increasing efforts to improve the time resolution of the SERS technique for live-cell studies. Fujita et al. combined confocal Raman microscopy and dark-field microscopy to steer the laser on the moving single Au NP inside the cell. In this way they were able to obtain the SERS spectra at a time resolution of 50 ms.287 Yet, this technique can only probe one nanoparticle at a time, and therefore, the throughput of this method is low. This problem may be overcome by using a recently developed wide-field Raman microscopy method. Different from most SERS imaging

summarize in Table 1 take-home messages that are considered to be highly important for practical bioanalytical SERS experiments. 7.2. Challenges and Outlooks

In addition to the reliability issue discussed above, many fundamental questions remain to be solved in bioanalytical SERS. Is it still possible to achieve single-molecule detection in a complex biological system? What is the highest achievable spatiotemporal resolution in bioanalytical SERS? In the following section, we will briefly address these challenges and potential areas of study. 7.2.1. Sensitivity. SERS has been shown to possess singlemolecule sensitivity for both resonant and nonresonant molecules.3,4,278,279 However, it would be fascinating if singlemolecule detection sensitivity can also be achieved in a complex biological system. To achieve this goal, it is necessary to optimize the electromagnetic field enhancement exerted on the molecule and to minimize the interference of other species in the sample. Le Ru et al. proposed a minimum SERS EF of 1011 to obtain the single-molecule SERS signal for nonresonant small molecules (with a Raman cross section of ca. 10−30 cm2/sr).37,280 In fact, such an enhancement can be easily achieved in a plasmoncoupled system, such as nanoparticle dimer or nanoparticleoverfilm systems. Therefore, it is no longer a big challenge in the SERS field to further increase the enhancement factor, since a dimer can already provide single-molecule sensitivity for an even nonresonant adenine molecule. However, as the 1011 enhancement is limited to a very small volume (∼10−18 to that of the total volume) of the gap of two nanoparticles, it is more important and also challenging to bring the molecule of interest to the maximally enhanced region (hot spot) while preventing the irrelevant molecules in the sample from blocking the site. This is contradictory to common single-molecule SERS measurement, where the measurement was performed by diluting the solution containing only the specific analyte to an ultralow concentration that is free of interfering species. To address this issue, it is highly important to rationally design the surface structure of the hot spot, so that only the molecules of interest can be trapped. DNA origami is a potential tool to spatially arrange NPs for the generation of SERS hot spots and to precisely control the position of analyte molecules.281−283 By this method, Au NP Y


Chemical Reviews

Review

fiber with a spatial resolution of 10 nm.311 These two methods rely on the diffusion of the molecules in and out of the “hot spots” and cannot actively control the SERS signal between “on” and “off” states. It would be possible to achieve the active control of the two states by designing photosensitive linkers between plasmonic nanostructures. In this way, the photoexcitation of the linker will lead to the change of the distance between nanostructures and tune the plasmonic coupling. Thereby, the super-resolution SERS imaging becomes possible in bioimaging. (3) Up to now, super-resolution SERS microscopy on the basis of the principle of stimulated emission depletion (STED) has not been reported yet. There was a report on using the switch-off behavior of a plasmonic nanoparticle scattering (similar to STED) to achieve super-resolution imaging at a spatial resolution λ/5 by Chu et al.312 They found that excitation with a high power 592 nm laser could lead to a decrease of the scattering intensity at 543 nm for a single Au nanoparticle. They believe that this reversible on−off switching is related to the change of the local dielectric constant of the nanoparticle as a result of the photothermal effect. We believe with the further improvement of SERS in sensitivity, selectivity, reproducibility, and time and spatial resolution, SERS will find more important applications in biological and medical fields, which will answer interesting biological questions and solve fatal clinical problems. One such example is to utilize the super multiplex detection and versatile features of SERS to monitor the metabolism of small biomolecules.228,313

instruments relying on laser scan or stage scan, in the wide-field Raman technique, the spot size of the laser on the sample can be controllably expanded to illuminate the whole sample to a millimeter (or even centimeter) size.288,289 The signal of the desired Raman peak over the whole area passes through an acoustic optical tunable filter (AOTF) or liquid crystal tunable filter (LCTF) and is captured by an imaging detector (imaging CCD or sCMOS). Thereby, the intensity of a specific Raman peak at each point of the whole illuminating area can be obtained at one exposure. Gambhir et al. demonstrated that a wide-field Raman imaging method presented over 240-fold improvement (1.5 min vs 360 min) compared with the normal raster scan mode for small animal SERS imaging.225 Spatial Resolution. In recent years, there are also increasing demands on achieving the nanometer spatial resolution by Raman spectroscopy. TERS is apparently the most important technique that can achieve this goal. Only recently, it has been demonstrated that TERS can work in aqueous solution and the electrochemical environment.290−295 However, up to now, there is still no report on using TERS to study living cells or the intracellular environment.291,296 The main difficulty lies in the slow imaging speed and weak enhancement by using the tip alone without the strong LSPR coupling between the tip and sample. Complementary to TERS, there is a booming development of nanoscale infrared spectroscopy or microscopy, namely nano-IR, which is based on the combination of AFM with the infrared technique, using either the thermal effect of sample absorption, or the scattering signal, or the force as a result of dipole−dipole interaction between tip and sample.297−299 However, it is still a great challenge for all the nano-IR techniques to be applied to study under aqueous conditions, let alone in dynamic living cells.299−303 As an alternative to the scanning probe microscopy-based nanospectroscopic methods, there are increasing efforts in combining the super-resolution methods utilized in superresolution fluorescence imaging with Raman spectroscopy in order to improve the spatial resolution: (1) The structured illumination microscopy has been widely applied in fluorescence imaging,304,305 whereas its potential in SERS imaging has not been fully exerted. Fujita et al. developed a structured line illumination (SLI) technique for Raman imaging while retaining the fingerprint information, and they were able to improve the spatial resolution by 1.4-fold.306 However, SLI Raman microscopy usually requires 1−2 h for obtaining one SLI Raman image and has to sacrifice the time resolution for achieving a high spatial resolution. To improve the time resolution of this technique, wide-field structured illumination microscopy was developed by using a spatial light modulator (SLM) to provide a faster image rate operated at a specific Raman peak.307 (2) Borrowing the strategies in single-molecule localized microscopy (photoactivated localization microscopy and stochastic optical reconstruction microscopy),308,309 Willets et al. successfully mapped the SERS hot spots of Ag-nanoparticle aggregates with a 5 nm resolution. The key to the success is to utilize the single-molecule SERS signal and the point spread function to locate the hot spot with a high precision.310 More recently, Lindquist et al. used the blinking behavior of the SERS signal, in analogy to the fluorescence signal in stochastic optical reconstruction microscopy, to reconstruct super-resolution images of the fibril on the SERS-active nanohole chip. By altering the phase profile of the laser using an rotating optical diffuser, most of the hot spots spread across the plasmonic surface were excited, rendering the SERS image of a collagen

ASSOCIATED CONTENT Special Issue Paper

This paper is an additional review for Chem. Rev. 2018, volume 118, issue 6, “Plasmonics in Chemistry”.

AUTHOR INFORMATION Corresponding Author

*E-mail: [email protected]. ORCID

Bin Ren: 0000-0002-9821-5864 Notes

The authors declare no competing financial interest. Biographies Cheng Zong received his B.Sc. degree in Chemistry from Wuhan University in 2009 and his Ph.D. degree in Chemistry from Xiamen University in 2015 under the supervision of Prof. Bin Ren. He is a postdoctoral fellow working with Prof. Bin Ren at Xiamen University and Prof. Ji-Xin Cheng at Boston University. His current research interests include SERS in biomedical application, spectroelectrochemistry, and coherent Raman scattering microscopy. Mengxi Xu received his B.Sc. degree in Chemistry from Nanjing University in 2014 and his master degree in Chemistry from Xiamen University in 2017 under the supervision of Prof. Bin Ren. He is currently a Ph.D. student in the same group. His research interests are focused on in situ investigation of live-cell process by spontaneous Raman and surface-enhanced Raman spectroscopy. Li-Jia Xu received her B.Sc. and master degrees in Chemistry under the supervision of Prof. Bin Ren at Xiamen University in 2011 and 2014, respectively. She is now an editor of Journal of Electrochemistry. Z


Chemical Reviews

Review

BSA ATP CTAB PSS PDDAC PATP FEM PVP FIB RGD 4-Mpy MBA XRITC CCD sCMOS

Ting Wei received her B.Sc. degree in Chemistry at Central China Normal University in 2016. She is a master degree student under the supervision of Prof. Bin Ren at Xiamen University. Her current research interest is on the combined SERS and electrochemistry for bioanalysis. Xin Ma received his B.Sc. degree in Chemistry from Shandong University. He is a master student under the supervision of Prof. Bin Ren in Department of Chemistry at Xiamen University. His research interest is focused on in situ monitoring and imaging cell membrane by surfaceenhanced Raman spectroscopy. Xiao-Shan Zheng received her B.Sc. degree in Chemical Biology in 2010 from Xiamen University and her Ph.D. degree in Chemistry in 2015 from the same university under the supervision of Prof. Bin Ren on SERS-based live-cell study. She is now a postdoctoral fellow in the Department of Spectroscopy and Imaging at the Leibniz Institute of Photonic Technology (Jena, Germany) with Prof. Jürgen Popp. Her current interests are focused on SERS-based multiplex detection and biosensing.

Bovine serum albumin Adenosine-triphosphate Cetyltriethylammnonium bromide Propylene glycol alginate sodium sulfate Poly(diallyldimethylammonium chloride) p-Aminothiophenol Finite element method Polyvinylpyrrolidone Focused ion beam Arginine-glycine-aspartic acid 4-Mercaptopyridine Mercaptobenzoic acid X-Rhodamine Charge-coupled device Scientific complementary metal-oxide semiconductor

REFERENCES

Ren Hu achieved her Ph.D. in 2005 in Physical Chemistry from Xiamen University, China. She took a postdoctoral training on single cell electrochemistry with Prof. Christian Amatore at the Ecole Normale Supérieure de Paris. She is now a senior engineer in the State Key Laboratory of Physical Chemistry of Solid Surfaces in Xiamen University. Her current research interests include the mechanisms of regulated exocytosis, spectroelectrochemistry, and biomaterials.

(1) Fleischmann, M.; Hendra, P. J.; McQuillan, A. J. Raman Spectra of Pyridine Adsorbed at a Silver Electrode. Chem. Phys. Lett. 1974, 26, 163−166. (2) Jeanmaire, D. L.; Van Duyne, R. P. Surface Raman Spectroelectrochemistry: Part I. Heterocyclic, Aromatic, and Aliphatic Amines Adsorbed on the Anodized Silver Electrode. J. Electroanal. Chem. Interfacial Electrochem. 1977, 84, 1−20. (3) Kneipp, K.; Wang, Y.; Kneipp, H.; Perelman, L. T.; Itzkan, I.; Dasari, R. R.; Feld, M. S. Single Molecule Detection Using SurfaceEnhanced Raman Scattering (SERS). Phys. Rev. Lett. 1997, 78, 1667− 1670. (4) Nie, S.; Emory, S. R. Probing Single Molecules and Single Nanoparticles by Surface-Enhanced Raman Scattering. Science 1997, 275, 1102−1106. (5) Camden, J. P.; Dieringer, J. A.; Wang, Y.; Masiello, D. J.; Marks, L. D.; Schatz, G. C.; Van Duyne, R. P. Probing the Structure of SingleMolecule Surface-Enhanced Raman Scattering Hot Spots. J. Am. Chem. Soc. 2008, 130, 12616−12617. (6) Blackie, E. J.; Le Ru, E. C.; Etchegoin, P. G. Single-Molecule Surface-Enhanced Raman Spectroscopy of Nonresonant Molecules. J. Am. Chem. Soc. 2009, 131, 14466−14472. (7) Grubisha, D. S.; Lipert, R. J.; Park, H.-Y.; Driskell, J.; Porter, M. D. Femtomolar Detection of Prostate-Specific Antigen: an Immunoassay Based on Surface-Enhanced Raman Scattering and Immunogold Labels. Anal. Chem. 2003, 75, 5936−5943. (8) Li, X.; Ye, S.; Luo, X. Sensitive SERS Detection of miRNA via Enzyme-Free DNA Machine Signal Amplification. Chem. Commun. 2016, 52, 10269−10272. (9) Jiang, C.; Liu, R.; Han, G.; Zhang, Z. A Chemically Reactive Raman Probe for Ultrasensitively Monitoring and Imaging the in Vivo Generation of Femtomolar Oxidative Species as Induced by AntiTumor Drugs in Living Cells. Chem. Commun. 2013, 49, 6647−6649. (10) McNay, G.; Eustace, D.; Smith, W. E.; Faulds, K.; Graham, D. Surface-Enhanced Raman Scattering (SERS) and Surface-Enhanced Resonance Raman Scattering (SERRS): A Review of Applications. Appl. Spectrosc. 2011, 65, 825−837. (11) Schluecker, S. Surface-Enhanced Raman Spectroscopy: Concepts and Chemical Applications. Angew. Chem., Int. Ed. 2014, 53, 4756− 4795. (12) Vendrell, M.; Maiti, K. K.; Dhaliwal, K.; Chang, Y.-T. SurfaceEnhanced Raman Scattering in Cancer Detection and Imaging. Trends Biotechnol. 2013, 31, 249−257. (13) Lane, L. A.; Qian, X.; Nie, S. SERS Nanoparticles in Medicine: from Label-Free Detection to Spectroscopic Tagging. Chem. Rev. 2015, 115, 10489−10529. (14) Cialla-May, D.; Zheng, X. S.; Weber, K.; Popp, J. Recent Progress in Surface-Enhanced Raman Spectroscopy for Biological and Biomedical Applications: from Cells to Clinics. Chem. Soc. Rev. 2017, 46, 3945−3961.

Bin Ren received his B.Sc. (1992) and Ph.D. (1998) degrees in Chemistry from Xiamen University in 1998. He became an assistant professor in the same department right after graduation. He became an associate professor in 2000, full professor in 2004, Min-Jiang Chair Professor in 2009, and Changjiang Scholar Professor in 2016 of Xiamen University. He spent his sabbatical year as an Alexander von Humboldt fellow in the Fritz-Haber Institute MPG on TERS during 2002−2003. He is now a vice director of the State Key Laboratory of Physical Chemistry of Solid Surfaces and an associate editor of Analytical Chemistry (ACS). His current interests are focused on nanoplasmonics, surface-enhanced Raman spectroscopy, tip-enhanced Raman spectroscopy, and their application in surfaces and interfaces of electrochemical and biological systems. The group is particularly strong in developing methodologies and instruments for the analysis of chemical and biological systems.

ACKNOWLEDGMENTS The authors acknowledge the financial supports from MOST (2016YFA0200601, 2016YFC1100301, 2013CB933703,), NSFC (21633005, 21790354, 21711530704, and 21621091), and the Fundamental Research Funds for the Central Universities (20720170031). We thank several generations of postdocs and Ph.D. and master students who have made a tremendous contribution to the accumulation of important experiences while working on bioanalytical SERS: Yan Cui, Li Cui, Jia-Min Feng, Min-Xia Gao, Jia-Yi Huang, Ming-De Li, XiuMei Lin, Xiang-Dong Tian, Yan-Hui Xu, Pei Hu, and Jin-Liang Zhang. We also thank Mr. Owen Douglas Pearl from Temple University for English editing. We would also like to thank Prof. Katsumasa Fujita for kindly providing Figure 18(c). ABBREVIATIONS NPs Nanoparticles NIR Near infrared TERS Tip-enhanced Raman spectroscopy EG3 (1-Mercaptoundeca-11-yl)tri(ethylene glycol) PEG Polyethylene glycol AA


Chemical Reviews

Review

(15) Wang, Z.; Zong, S.; Wu, L.; Zhu, D.; Cui, Y. SERS-Activated Platforms for Immunoassay: Probes, Encoding Methods, and Applications. Chem. Rev. 2017, 117, 7910−7963. (16) Li, J.-F.; Zhang, Y.-J.; Ding, S.-Y.; Panneerselvam, R.; Tian, Z.-Q. Core−Shell Nanoparticle-Enhanced Raman Spectroscopy. Chem. Rev. 2017, 117, 5002−5069. (17) Nam, J.-M.; Oh, J.-W.; Lee, H.; Suh, Y. D. Plasmonic NanogapEnhanced Raman Scattering with Nanoparticles. Acc. Chem. Res. 2016, 49, 2746−2755. (18) Ding, S.-Y.; Yi, J.; Li, J.-F.; Ren, B.; Wu, D.-Y.; Panneerselvam, R.; Tian, Z.-Q. Nanostructure-Based Plasmon-Enhanced Raman Spectroscopy for Surface Analysis of Materials. Nat. Rev. Mater. 2016, 1, 16021. (19) Henry, A.-I.; Sharma, B.; Cardinal, M. F.; Kurouski, D.; Van Duyne, R. P. Surface-Enhanced Raman Spectroscopy Biosensing: In vivo Diagnostics and Multimodal Imaging. Anal. Chem. 2016, 88, 6638− 6647. (20) Zrimsek, A. B.; Chiang, N.; Mattei, M.; Zaleski, S.; McAnally, M. O.; Chapman, C. T.; Henry, A.-I.; Schatz, G. C.; Van Duyne, R. P. Single-Molecule Chemistry with Surface-and Tip-Enhanced Raman Spectroscopy. Chem. Rev. 2017, 117, 7583−7613. (21) Kennedy, B. J.; Spaeth, S.; Dickey, M.; Carron, K. T. Determination of the distance dependence and experimental effects for modified SERS substrates based on self-assembled monolayers formed using alkanethiols. J. Phys. Chem. B 1999, 103, 3640−3646. (22) Masango, S. S.; Hackler, R. A.; Large, N.; Henry, A.-I.; McAnally, M. O.; Schatz, G. C.; Stair, P. C.; Van Duyne, R. P. High-Resolution Distance Dependence Study of Surface-Enhanced Raman Scattering Enabled by Atomic Layer Deposition. Nano Lett. 2016, 16, 4251−4259. (23) Yonzon, C. R.; Haynes, C. L.; Zhang, X.; Walsh, J. T.; Van Duyne, R. P. A Glucose Biosensor Based on Surface-Enhanced Raman Scattering: Improved Partition Layer, Temporal Stability, Reversibility, and Resistance to Serum Protein Interference. Anal. Chem. 2004, 76, 78−85. (24) Abalde-Cela, S.; Hermida-Ramón, J. M.; Contreras-Carballada, P.; De Cola, L.; Guerrero-Martínez, A.; Alvarez-Puebla, R. A.; LizMarzán, L. M. SERS Chiral Recognition and Quantification of Enantiomers through Cyclodextrin Supramolecular Complexation. ChemPhysChem 2011, 12, 1529−1535. (25) Fraire, J. C.; Sueldo Ocello, V. N.; Allende, L. G.; Veglia, A. V.; Coronado, E. A. Toward the Design of Highly Stable Small Colloidal SERS Substrates with Supramolecular Host−Guest Interactions for Ultrasensitive Detection. J. Phys. Chem. C 2015, 119, 8876−8888. (26) Xu, J. Y.; Wang, J.; Kong, L. T.; Zheng, G. C.; Guo, Z.; Liu, J. H. SERS Detection of Explosive Agent by Macrocyclic Compound Functionalized Triangular Gold Nanoprisms. J. Raman Spectrosc. 2011, 42, 1728−1735. (27) Barrow, S. J.; Kasera, S.; Rowland, M. J.; del Barrio, J.; Scherman, O. A. Cucurbituril-Based Molecular Recognition. Chem. Rev. 2015, 115, 12320−12406. (28) Campos, A. R.; Gao, Z.; Blaber, M. G.; Huang, R.; Schatz, G. C.; Van Duyne, R. P.; Haynes, C. L. Surface-Enhanced Raman Spectroscopy Detection of Ricin B Chain in Human Blood. J. Phys. Chem. C 2016, 120, 20961−20969. (29) Neumann, O.; Zhang, D.; Tam, F.; Lal, S.; Wittung-Stafshede, P.; Halas, N. J. Direct Optical Detection of Aptamer Conformational Changes Induced by Target Molecules. Anal. Chem. 2009, 81, 10002− 10006. (30) He, L.; Rodda, T.; Haynes, C. L.; Deschaines, T.; Strother, T.; Diez-Gonzalez, F.; Labuza, T. P. Detection of a Foreign Protein in Milk Using Surface-Enhanced Raman Spectroscopy Coupled with AntibodyModified Silver Dendrites. Anal. Chem. 2011, 83, 1510−1513. (31) Bonham, A. J.; Braun, G.; Pavel, I.; Moskovits, M.; Reich, N. O. Detection of Sequence-Specific Protein-DNA Interactions via Surface Enhanced Resonance Raman Scattering. J. Am. Chem. Soc. 2007, 129, 14572−14573. (32) Li, J. F.; Huang, Y. F.; Ding, Y.; Yang, Z. L.; Li, S. B.; Zhou, X. S.; Fan, F. R.; Zhang, W.; Zhou, Z. Y.; Ren, B. Shell-Isolated NanoparticleEnhanced Raman Spectroscopy. Nature 2010, 464, 392−395.

(33) Lin, L.; Tian, X.; Hong, S.; Dai, P.; You, Q.; Wang, R.; Feng, L.; Xie, C.; Tian, Z. Q.; Chen, X. A Bioorthogonal Raman Reporter Strategy for SERS Detection of Glycans on Live Cells. Angew. Chem., Int. Ed. 2013, 52, 7266−7271. (34) Drescher, D.; Zeise, I.; Traub, H.; Guttmann, P.; Seifert, S.; Büchner, T.; Jakubowski, N.; Schneider, G.; Kneipp, J. In Situ Characterization of SiO2 Nanoparticle Biointeractions Using BrightSilica. Adv. Funct. Mater. 2014, 24, 3765−3775. (35) Xu, H.; Bjerneld, E. J.; Aizpurua, J.; Apell, P.; Gunnarsson, L.; Petronis, S.; Kasemo, B.; Larsson, C.; Hook, F.; Kall, M. Interparticle Coupling Effects in Surface-Enhanced Raman Scattering. Proc. SPIE 2001, 4258, 35−42. (36) Zhu, W.; Esteban, R.; Borisov, A. G.; Baumberg, J. J.; Nordlander, P.; Lezec, H. J.; Aizpurua, J.; Crozier, K. B. Quantum Mechanical Effects in Plasmonic Structures with Subnanometre Gaps. Nat. Commun. 2016, 7, 11495. (37) Le Ru, E. C.; Etchegoin, P. G. Single-Molecule Surface-Enhanced Raman Spectroscopy. Annu. Rev. Phys. Chem. 2012, 63, 65−87. (38) Wang, Y.; Tang, L.-J.; Jiang, J.-H. Surface-Enhanced Raman Spectroscopy-Based, Homogeneous, Multiplexed Immunoassay with Antibody-Fragments-Decorated Gold Nanoparticles. Anal. Chem. 2013, 85, 9213−9220. (39) Li, M.; Cushing, S. K.; Zhang, J.; Suri, S.; Evans, R.; Petros, W. P.; Gibson, L. F.; Ma, D.; Liu, Y.; Wu, N. Three-Dimensional Hierarchical Plasmonic Nano-Architecture Enhanced Surface-Enhanced Raman Scattering Immunosensor for Cancer Biomarker Detection in Blood Plasma. ACS Nano 2013, 7, 4967−4976. (40) Kim, N. H.; Lee, S. J.; Moskovits, M. Aptamer-Mediated SurfaceEnhanced Raman Spectroscopy Intensity Amplification. Nano Lett. 2010, 10, 4181−4185. (41) Li, M.; Zhang, J.; Suri, S.; Sooter, L. J.; Ma, D.; Wu, N. Detection of Adenosine Triphosphate with an Aptamer Biosensor Based on Surface-Enhanced Raman Scattering. Anal. Chem. 2012, 84, 2837−2842. (42) He, Y.; Yang, X.; Yuan, R.; Chai, Y. Off” to “On” SurfaceEnhanced Raman Spectroscopy Platform with Padlock Probe-Based Exponential Rolling Circle Amplification for Ultrasensitive Detection of MicroRNA 155. Anal. Chem. 2017, 89, 2866−2872. (43) Fang, Y.; Seong, N.-H.; Dlott, D. D. Measurement of the Distribution of Site Enhancements in Surface-Enhanced Raman Scattering. Science 2008, 321, 388−392. (44) Itoh, T.; Yoshida, K.; Biju, V.; Kikkawa, Y.; Ishikawa, M.; Ozaki, Y. Second Enhancement in Surface-Enhanced Resonance Raman Scattering Revealed by an Analysis of Anti-Stokes and Stokes Raman Spectra. Phys. Rev. B: Condens. Matter Mater. Phys. 2007, 76, 085405. (45) Lin, K.-Q.; Yi, J.; Zhong, J.-H.; Hu, S.; Liu, B.-J.; Liu, J.-Y.; Zong, C.; Lei, Z.-C.; Wang, X.; Aizpurua, J. Plasmonic Photoluminescence for Recovering Native Chemical Information from Surface-Enhanced Raman Scattering. Nat. Commun. 2017, 8, 14891. (46) Lin, X.-M.; Cui, Y.; Xu, Y.-H.; Ren, B.; Tian, Z.-Q. SurfaceEnhanced Raman Spectroscopy: Substrate-Related Issues. Anal. Bioanal. Chem. 2009, 394, 1729−1745. (47) Bantz, K. C.; Meyer, A. F.; Wittenberg, N. J.; Im, H.; Kurtulus, O.; Lee, S. H.; Lindquist, N. C.; Oh, S.-H.; Haynes, C. L. Recent progress in SERS biosensing. Phys. Chem. Chem. Phys. 2011, 13, 11551−11567. (48) Fan, M.; Andrade, G. F. S.; Brolo, A. G. A review on the fabrication of substrates for surface enhanced Raman spectroscopy and their applications in analytical chemistry. Anal. Chim. Acta 2011, 693, 7−25. (49) Chen, H.; Shao, L.; Li, Q.; Wang, J. Gold Nanorods and Their Plasmonic Properties. Chem. Soc. Rev. 2013, 42, 2679−2724. (50) McLellan, J. M.; Li, Z.-Y.; Siekkinen, A. R.; Xia, Y. The SERS Activity of a Supported Ag Nanocube Strongly Depends on its Orientation Relative to Laser Polarization. Nano Lett. 2007, 7, 1013− 1017. (51) Sherry, L. J.; Chang, S.-H.; Schatz, G. C.; Van Duyne, R. P.; Wiley, B. J.; Xia, Y. Localized Surface Plasmon Resonance Spectroscopy of Single Silver Nanocubes. Nano Lett. 2005, 5, 2034−2038. (52) Panikkanvalappil, S. R.; James, M.; Hira, S. M.; Mobley, J.; Jilling, T.; Ambalavanan, N.; El-Sayed, M. A. Hyperoxia Induces Intracellular Acidification in Neonatal Mouse Lung Fibroblasts: Real-Time AB


Chemical Reviews

Review

Investigation Using Plasmonically Enhanced Raman Spectroscopy. J. Am. Chem. Soc. 2016, 138, 3779−3788. (53) Sun, Y.; Wiederrecht, G. P. Surfactantless Synthesis of Silver Nanoplates and Their Application in SERS. Small 2007, 3, 1964−1975. (54) Sherry, L. J.; Jin, R.; Mirkin, C. A.; Schatz, G. C.; Van Duyne, R. P. Localized Surface Plasmon Resonance Spectroscopy of Single Silver Triangular Nanoprisms. Nano Lett. 2006, 6, 2060−2065. (55) Wu, H.-L.; Tsai, H.-R.; Hung, Y.-T.; Lao, K.-U.; Liao, C.-W.; Chung, P.-J.; Huang, J.-S.; Chen, I.-C.; Huang, M. H. A Comparative Study of Gold Nanocubes, Octahedra, and Rhombic Dodecahedra as Highly Sensitive SERS Substrates. Inorg. Chem. 2011, 50, 8106−8111. (56) Fales, A. M.; Yuan, H.; Vo-Dinh, T. Silica-Coated Gold Nanostars for Combined Surface-Enhanced Raman Scattering (SERS) Detection and Singlet-Oxygen Generation: a Potential Nanoplatform for Theranostics. Langmuir 2011, 27, 12186−12190. (57) Barbosa, S.; Agrawal, A.; Rodríguez-Lorenzo, L.; Pastoriza-Santos, I.; Alvarez-Puebla, R. A.; Kornowski, A.; Weller, H.; Liz-Marzán, L. M. Tuning Size and Sensing Properties in Colloidal Gold Nanostars. Langmuir 2010, 26, 14943−14950. (58) Khoury, C. G.; Vo-Dinh, T. Gold Nanostars for Surface-Enhanced Raman Scattering: Synthesis, Characterization and Optimization. J. Phys. Chem. C 2008, 112, 18849−18859. (59) Yoon, I.; Kang, T.; Choi, W.; Kim, J.; Yoo, Y.; Joo, S.-W.; Park, Q.H.; Ihee, H.; Kim, B. Single nanowire on a Film as an Efficient SERSActive Platform. J. Am. Chem. Soc. 2009, 131, 758−762. (60) Jiang, Z.; Zhang, Q.; Zong, C.; Liu, B.-J.; Ren, B.; Xie, Z.; Zheng, L. Cu−Au Alloy Nanotubes with Five-Fold Twinned Structure and Their Application in Surface-Enhanced Raman Scattering. J. Mater. Chem. 2012, 22, 18192−18197. (61) Wei, W.; Li, S.; Millstone, J. E.; Banholzer, M. J.; Chen, X.; Xu, X.; Schatz, G. C.; Mirkin, C. A. Surprisingly Long-Range Surface-Enhanced Raman Scattering (SERS) on Au−Ni Multisegmented Nanowires. Angew. Chem., Int. Ed. 2009, 48, 4210−4212. (62) Xie, W.; Schlücker, S. Hot Electron-Induced Reduction of Small Molecules on Photorecycling Metal Surfaces. Nat. Commun. 2015, 6, 7570. (63) Lim, D.-K.; Jeon, K.-S.; Hwang, J.-H.; Kim, H.; Kwon, S.; Suh, Y. D.; Nam, J.-M. Highly Uniform and Reproducible Surface-Enhanced Raman Scattering from DNA-Tailorable Nanoparticles with 1-nm Interior Gap. Nat. Nanotechnol. 2011, 6, 452−460. (64) Shen, W.; Lin, X.; Jiang, C.; Li, C.; Lin, H.; Huang, J.; Wang, S.; Liu, G.; Yan, X.; Zhong, Q. Reliable Quantitative SERS Analysis Facilitated by Core−Shell Nanoparticles with Embedded Internal Standards. Angew. Chem., Int. Ed. 2015, 54, 7308−7312. (65) Lin, L.; Gu, H.; Ye, J. Plasmonic Multi-Shell Nanomatryoshka Particles as Highly Tunable SERS Tags with Built-in Reporters. Chem. Commun. 2015, 51, 17740−17743. (66) Guerrini, L.; Graham, D. Molecularly-Mediated Assemblies of Plasmonic Nanoparticles for Surface-Enhanced Raman Spectroscopy Applications. Chem. Soc. Rev. 2012, 41, 7085−7107. (67) Luo, S.-C.; Sivashanmugan, K.; Liao, J.-D.; Yao, C.-K.; Peng, H.-C. Nanofabricated SERS-active substrates for single-molecule to virus detection in vitro: A review. Biosens. Bioelectron. 2014, 61, 232−240. (68) Shiohara, A.; Wang, Y.; Liz-Marzan, L. M. Recent approaches toward creation of hot spots for SERS detection. J. Photochem. Photobiol., C 2014, 21, 2−25. (69) Jahn, M.; Patze, S.; Hidi, I. J.; Knipper, R.; Radu, A. I.; Muehlig, A.; Yueksel, S.; Peksa, V.; Weber, K.; Mayerhoefer, T.; Cialla-May, D.; Popp, J. Plasmonic nanostructures for surface enhanced spectroscopic methods. Analyst 2016, 141, 756−793. (70) Xi, W.; Shrestha, B. K.; Haes, A. J. Promoting Intra- and Intermolecular Interactions in Surface-Enhanced Raman Scattering. Anal. Chem. 2018, 90, 128−143. (71) Lin, K.-Q.; Yi, J.; Hu, S.; Liu, B.-J.; Liu, J.-Y.; Wang, X.; Ren, B. Size Effect on SERS of Gold Nanorods Demonstrated via Single Nanoparticle Spectroscopy. J. Phys. Chem. C 2016, 120, 20806−20813. (72) Bailey, M. R.; Pentecost, A. M.; Selimovic, A.; Martin, R. S.; Schultz, Z. D. Sheath-Flow Microfluidic Approach for Combined

Surface Enhanced Raman Scattering and Electrochemical Detection. Anal. Chem. 2015, 87, 4347−4355. (73) Scott, B.; Carron, K. Dynamic Surface-Enhanced Raman Spectroscopy (SERS): Extracting SERS from Normal Raman Scattering. Anal. Chem. 2012, 84, 8448−8451. (74) Asiala, S. M.; Schultz, Z. D. Label-Free in Situ Detection of Individual Macromolecular Assemblies by Surface-Enhanced Raman Scattering. Chem. Commun. 2013, 49, 4340−4342. (75) Matikainen, A.; Nuutinen, T.; Itkonen, T.; Heinilehto, S.; Puustinen, J.; Hiltunen, J.; Lappalainen, J.; Karioja, P.; Vahimaa, P. Atmospheric Oxidation and Carbon Contamination of Silver and its Effect on Surface-Enhanced Raman Spectroscopy (SERS). Sci. Rep. 2016, 6, 37192. (76) Yeo, B.-S.; Schmid, T.; Zhang, W.; Zenobi, R. A strategy to Prevent Signal Losses, Analyte Decomposition, and Fluctuating Carbon Contamination Bands in Surface-Enhanced Raman Spectroscopy. Appl. Spectrosc. 2008, 62, 708−713. (77) Huang, J.-Y.; Zong, C.; Xu, L.-J.; Cui, Y.; Ren, B. Clean and Modified Substrates for Direct Detection of Living Cells by SurfaceEnhanced Raman Spectroscopy. Chem. Commun. 2011, 47, 5738−5740. (78) Guerrini, L.; Krpetic, Z.; van Lierop, D.; Alvarez-Puebla, R. A.; Graham, D. Direct Surface-Enhanced Raman Scattering Analysis of DNA Duplexes. Angew. Chem., Int. Ed. 2015, 54, 1144−1148. (79) Alvarez-Puebla, R. A.; Agarwal, A.; Manna, P.; Khanal, B. P.; Aldeanueva-Potel, P.; Carbó-Argibay, E.; Pazos-Pérez, N.; Vigderman, L.; Zubarev, E. R.; Kotov, N. A. Gold Nanorods 3D-Supercrystals as Surface-Enhanced Raman Scattering Spectroscopy Substrates for the Rapid Detection of Scrambled Prions. Proc. Natl. Acad. Sci. U. S. A. 2011, 108, 8157−8161. (80) Larmour, I.; Faulds, K.; Graham, D. SERS Activity and Stability of the Most Frequently Used Silver Colloids. J. Raman Spectrosc. 2012, 43, 202−206. (81) Negri, P.; Marotta, N. E.; Bottomley, L. A.; Dluhy, R. A. Removal of Surface Contamination and Self-Assembled Monolayers (SAMs) from Silver (Ag) Nanorod Substrates by Plasma Cleaning with Argon. Appl. Spectrosc. 2011, 65, 66−74. (82) Xu, L.-J.; Lei, Z.-C.; Li, J.; Zong, C.; Yang, C. J.; Ren, B. Label-Free Surface-Enhanced Raman Spectroscopy Detection of DNA with SingleBase Sensitivity. J. Am. Chem. Soc. 2015, 137, 5149−5154. (83) Xu, L.-J.; Zong, C.; Zheng, X.-S.; Hu, P.; Feng, J.-M.; Ren, B. Label-Free Detection of Native Proteins by Surface-Enhanced Raman Spectroscopy Using Iodide-Modified Nanoparticles. Anal. Chem. 2014, 86, 2238−2245. (84) Jahn, I.; Ž ukovskaja, O.; Zheng, X.-S.; Weber, K.; Bocklitz, T.; Cialla-May, D.; Popp, J. Surface-Enhanced Raman Spectroscopy and Microfluidic Platforms: Challenges, Solutions and Potential Applications. Analyst 2017, 142, 1022−1047. (85) Strehle, K. R.; Cialla, D.; Rösch, P.; Henkel, T.; Köhler, M.; Popp, J. A Reproducible Surface-Enhanced Raman Spectroscopy Approach. Online SERS Measurements in a Segmented Microfluidic System. Anal. Chem. 2007, 79, 1542−1547. (86) Wu, D.-Y.; Li, J.-F.; Ren, B.; Tian, Z.-Q. Electrochemical SurfaceEnhanced Raman Spectroscopy of Nanostructures. Chem. Soc. Rev. 2008, 37, 1025−1041. (87) Crawford, A. C.; Skuratovsky, A.; Porter, M. D. Sampling Error: Impact on the Quantitative Analysis of Nanoparticle-Based SurfaceEnhanced Raman Scattering Immunoassays. Anal. Chem. 2016, 88, 6515−6522. (88) Picorel, R.; Lu, T.; Holt, R. E.; Cotton, T. M.; Seibert, M. SurfaceEnhanced Resonance Raman Scattering Spectroscopy of Bacterial Photosynthetic Membranes: Orientation of the Carotenoids of Rhodobacter Sphaeroides 2.4. 1. Biochemistry 1990, 29, 707−712. (89) Bell, S. E.; Sirimuthu, N. M. Quantitative Surface-Enhanced Raman Spectroscopy. Chem. Soc. Rev. 2008, 37, 1012−1024. (90) Kämmer, E.; Olschewski, K.; Bocklitz, T.; Rösch, P.; Weber, K.; Cialla, D.; Popp, J. A New Calibration Concept for a Reproducible Quantitative Detection Based on SERS Measurements in a Microfluidic Device Demonstrated on the Model Analyte Adenine. Phys. Chem. Chem. Phys. 2014, 16, 9056−9063. AC


Chemical Reviews

Review

(111) Dykman, L. A.; Khlebtsov, N. G. Uptake of Engineered Gold Nanoparticles into Mammalian Cells. Chem. Rev. 2014, 114, 1258− 1288. (112) Oh, N.; Park, J.-H. Endocytosis and Exocytosis of Nanoparticles in Mammalian Cells. Int. J. Nanomed. 2014, 9, 51−63. (113) Behzadi, S.; Serpooshan, V.; Tao, W.; Hamaly, M. A.; Alkawareek, M. Y.; Dreaden, E. C.; Brown, D.; Alkilany, A. M.; Farokhzad, O. C.; Mahmoudi, M. Cellular Uptake of Nanoparticles: Journey inside the Cell. Chem. Soc. Rev. 2017, 46, 4218−4244. (114) Chithrani, B. D.; Ghazani, A. A.; Chan, W. C. Determining the Size and Shape Dependence of Gold Nanoparticle Uptake into Mammalian Cells. Nano Lett. 2006, 6, 662−668. (115) Qiu, Y.; Liu, Y.; Wang, L.; Xu, L.; Bai, R.; Ji, Y.; Wu, X.; Zhao, Y.; Li, Y.; Chen, C. Surface Chemistry and Aspect Ratio Mediated Cellular Uptake of Au Nanorods. Biomaterials 2010, 31, 7606−7619. (116) Albanese, A.; Tang, P. S.; Chan, W. C. The Effect of Nanoparticle Size, Shape, and Surface Chemistry on Biological Systems. Annu. Rev. Biomed. Eng. 2012, 14, 1−16. (117) Cho, E. C.; Xie, J.; Wurm, P. A.; Xia, Y. Understanding the Role of Surface Charges in Cellular Adsorption versus Internalization by Selectively Removing Gold Nanoparticles on the Cell Surface with a I2/ KI Etchant. Nano Lett. 2009, 9, 1080−1084. (118) Verma, A.; Stellacci, F. Effect of Surface Properties on Nanoparticle−Cell Interactions. Small 2010, 6, 12−21. (119) Bechara, C.; Sagan, S. Cell-Penetrating Peptides: 20years Later, Where do We Stand? FEBS Lett. 2013, 587, 1693−1702. (120) Milletti, F. Cell-Penetrating Peptides: Classes, Origin, and Current Landscape. Drug Discovery Today 2012, 17, 850−860. (121) Copolovici, D. M.; Langel, K.; Eriste, E.; Langel, U. CellPenetrating Peptides: Design, Synthesis, and Applications. ACS Nano 2014, 8, 1972−1994. (122) Fales, A. M.; Yuan, H.; Vo-Dinh, T. Cell-Penetrating Peptide Enhanced Intracellular Raman Imaging and Photodynamic Therapy. Mol. Pharmaceutics 2013, 10, 2291−2298. (123) Hossain, M. K.; Cho, H.-Y.; Kim, K.-J.; Choi, J.-W. In Situ Monitoring of Doxorubicin Release from Biohybrid Nanoparticles Modified with Antibody and Cell-Penetrating Peptides in Breast Cancer Cells Using Surface-Enhanced Raman Spectroscopy. Biosens. Bioelectron. 2015, 71, 300−305. (124) Kang, J. W.; So, P. T.; Dasari, R. R.; Lim, D.-K. High Resolution Live Cell Raman Imaging Using Subcellular Organelle-Targeting SERSSensitive Gold Nanoparticles with Highly Narrow Intra-Nanogap. Nano Lett. 2015, 15, 1766−1772. (125) Tkachenko, A. G.; Xie, H.; Coleman, D.; Glomm, W.; Ryan, J.; Anderson, M. F.; Franzen, S.; Feldheim, D. L. Multifunctional Gold Nanoparticle− Peptide Complexes for Nuclear Targeting. J. Am. Chem. Soc. 2003, 125, 4700−4701. (126) Kang, B.; Austin, L. A.; El-Sayed, M. A. Real-Time Molecular Imaging throughout the Entire Cell Cycle by Targeted PlasmonicEnhanced Rayleigh/Raman Spectroscopy. Nano Lett. 2012, 12, 5369− 5375. (127) Liang, L.; Huang, D.; Wang, H.; Li, H.; Xu, S.; Chang, Y.; Li, H.; Yang, Y.-W.; Liang, C.; Xu, W. In Situ Surface-Enhanced Raman Scattering Spectroscopy Exploring Molecular Changes of Drug-Treated Cancer Cell Nucleus. Anal. Chem. 2015, 87, 2504−2510. (128) Chen, Y.; Bai, X.; Su, L.; Du, Z.; Shen, A.; Materny, A.; Hu, J. Combined Labelled and Label-free SERS Probes for Triplex Threedimensional Cellular Imaging. Sci. Rep. 2016, 6, 19173. (129) Chithrani, B. D.; Stewart, J.; Allen, C.; Jaffray, D. A. Intracellular Uptake, Transport, and Processing of Nanostructures in Cancer Cells. Nanomedicine 2009, 5, 118−127. (130) Cheng, L.-C.; Jiang, X.; Wang, J.; Chen, C.; Liu, R.-S. Nano−Bio Effects: Interaction of Nanomaterials with Cells. Nanoscale 2013, 5, 3547−3569. (131) Zhang, Q.; Hitchins, V. M.; Schrand, A. M.; Hussain, S. M.; Goering, P. L. Uptake of Gold Nanoparticles in Murine Macrophage Cells without Cytotoxicity or Production of Pro-Inflammatory Mediators. Nanotoxicology 2011, 5, 284−295.

(91) Zhang, D.; Xie, Y.; Deb, S. K.; Davison, V. J.; Ben-Amotz, D. Isotope Edited Internal Standard Method For Quantitative SurfaceEnhanced Raman Spectroscopy. Anal. Chem. 2005, 77, 3563−3569. (92) Subaihi, A.; Muhamadali, H.; Mutter, S. T.; Blanch, E.; Ellis, D. I.; Goodacre, R. Quantitative Detection of Codeine in Human Plasma Using Surface-Enhanced Raman Scattering via Adaptation of the Isotopic Labelling Principle. Analyst 2017, 142, 1099−1105. (93) Bell, S. E.; Sirimuthu, N. M. Rapid, Quantitative Analysis of ppm/ ppb Nicotine Using Surface-Enhanced Raman Scattering from PolymerEncapsulated Ag Nanoparticles (Gel-Colls). Analyst 2004, 129, 1032− 1036. (94) Pelaz, B.; Charron, G.; Pfeiffer, C.; Zhao, Y.; De La Fuente, J. M.; Liang, X. J.; Parak, W. J.; Del Pino, P. Interfacing Engineered Nanoparticles with Biological Systems: Anticipating Adverse Nano− Bio Interactions. Small 2013, 9, 1573−1584. (95) Soenen, S. J.; Parak, W. J.; Rejman, J.; Manshian, B. (Intra) Cellular Stability of Inorganic Nanoparticles: Effects on Cytotoxicity, Particle Functionality, and Biomedical Applications. Chem. Rev. 2015, 115, 2109−2135. (96) Nel, A. E.; Mädler, L.; Velegol, D.; Xia, T.; Hoek, E. M.; Somasundaran, P.; Klaessig, F.; Castranova, V.; Thompson, M. Understanding Biophysicochemical Interactions at the Nano−Bio Interface. Nat. Mater. 2009, 8, 543−557. (97) Walkey, C. D.; Chan, W. C. Understanding and Controlling the Interaction of Nanomaterials with Proteins in a Physiological Environment. Chem. Soc. Rev. 2012, 41, 2780−2799. (98) Lynch, I.; Dawson, K. A. Protein-Nanoparticle Interactions. Nano Today 2008, 3, 40−47. (99) Albanese, A.; Walkey, C. D.; Olsen, J. B.; Guo, H.; Emili, A.; Chan, W. C. Secreted Biomolecules Alter the Biological Identity and Cellular Interactions of Nanoparticles. ACS Nano 2014, 8, 5515−5526. (100) Cedervall, T.; Lynch, I.; Lindman, S.; Berggård, T.; Thulin, E.; Nilsson, H.; Dawson, K. A.; Linse, S. Understanding the Nanoparticle− Protein Corona Using Methods to Quantify Exchange Rates and Affinities of Proteins for Nanoparticles. Proc. Natl. Acad. Sci. U. S. A. 2007, 104, 2050−2055. (101) Lundqvist, M.; Stigler, J.; Elia, G.; Lynch, I.; Cedervall, T.; Dawson, K. A. Nanoparticle Size and Surface Properties Determine the Protein Corona with Possible Implications for Biological Impacts. Proc. Natl. Acad. Sci. U. S. A. 2008, 105, 14265−14270. (102) Freitas, D. N.; Martinolich, A. J.; Amaris, Z. N.; Wheeler, K. E. Beyond the Passive Interactions at the Nano-Bio Interface: Evidence of Cu Metalloprotein-Driven Oxidative Dissolution of Silver Nanoparticles. J. Nanobiotechnol. 2016, 14, 7. (103) Sirimuthu, N. M. S. Investigation of the Stability of Labelled Nanoparticles for SE (R) RS Measurements in Cells. Chem. Commun. 2011, 47, 4099−4101. (104) Piella, J.; Bastús, N. G.; Puntes, V. Size-Dependent Protein− Nanoparticle Interactions in Citrate-Stabilized Gold Nanoparticles: The Emergence of the Protein Corona. Bioconjugate Chem. 2017, 28, 88−97. (105) Verderio, P.; Avvakumova, S.; Alessio, G.; Bellini, M.; Colombo, M.; Galbiati, E.; Mazzucchelli, S.; Avila, J. P.; Santini, B.; Prosperi, D. Delivering Colloidal Nanoparticles to Mammalian Cells: a Nano−Bio Interface Perspective. Adv. Healthcare Mater. 2014, 3, 957−976. (106) Chithrani, B. D.; Chan, W. C. Elucidating the Mechanism of Cellular Uptake and Removal of Protein-Coated Gold Nanoparticles of Different Sizes and Shapes. Nano Lett. 2007, 7, 1542−1550. (107) Canton, I.; Battaglia, G. Endocytosis at the Nanoscale. Chem. Soc. Rev. 2012, 41, 2718−2739. (108) Rejman, J.; Oberle, V.; Zuhorn, I. S.; Hoekstra, D. SizeDependent Internalization of Particles via the Pathways of Clathrin-and Caveolae-Mediated Endocytosis. Biochem. J. 2004, 377, 159−169. (109) Drescher, D.; Kneipp, J. Nanomaterials in Complex Biological Systems: Insights from Raman Spectroscopy. Chem. Soc. Rev. 2012, 41, 5780−5799. (110) Hillaireau, H.; Couvreur, P. Nanocarriers’ Entry into the Cell: Relevance to Drug Delivery. Cell. Mol. Life Sci. 2009, 66, 2873−2896. AD


Chemical Reviews

Review

(132) Kang, B.; Mackey, M. A.; El-Sayed, M. A. Nuclear Targeting of Gold Nanoparticles in Cancer Cells Induces DNA Damage, Causing Cytokinesis Arrest and Apoptosis. J. Am. Chem. Soc. 2010, 132, 1517− 1519. (133) Falagan-Lotsch, P.; Grzincic, E. M.; Murphy, C. J. One LowDose Exposure of Gold Nanoparticles Induces Long-Term Changes in Human Cells. Proc. Natl. Acad. Sci. U. S. A. 2016, 113, 13318−13323. (134) Kim, Y.-J.; Yang, S. I.; Ryu, J.-C. Cytotoxicity and Genotoxicity of Nano-Silver in Mammalian Cell Lines. Mol. Cell. Toxicol. 2010, 6, 119− 125. (135) Foldbjerg, R.; Dang, D. A.; Autrup, H. Cytotoxicity and Genotoxicity of Silver Nanoparticles in the Human Lung Cancer Cell Line, A549. Arch. Toxicol. 2011, 85, 743−750. (136) AshaRani, P.; Low Kah Mun, G.; Hande, M. P.; Valiyaveettil, S. Cytotoxicity and Genotoxicity of Silver Nanoparticles in Human Cells. ACS Nano 2009, 3, 279−290. (137) Aioub, M.; El-Sayed, M. A. A Real-Time Surface-Enhanced Raman Spectroscopy Study of Plasmonic Photothermal Cell Death Using Targeted Gold Nanoparticles. J. Am. Chem. Soc. 2016, 138, 1258− 1264. (138) Sarina, S.; Waclawik, E. R.; Zhu, H. Photocatalysis on Supported Gold and Silver Nanoparticles under Ultraviolet and Visible Light Irradiation. Green Chem. 2013, 15, 1814−1833. (139) Xiao, Q.; Jaatinen, E.; Zhu, H. Direct Photocatalysis for Organic Synthesis by Using Plasmonic-Metal Nanoparticles Irradiated with Visible Light. Chem. - Asian J. 2014, 9, 3046−3064. (140) Huang, Y. F.; Zhang, M.; Zhao, L. B.; Feng, J. M.; Wu, D. Y.; Ren, B.; Tian, Z. Q. Activation of Oxygen on Gold and Silver Nanoparticles Assisted by Surface Plasmon Resonances. Angew. Chem., Int. Ed. 2014, 53, 2353−2357. (141) Watanabe, T.; Kawanami, O.; Katoh, H.; Honda, K.; Nishimura, Y.; Tsuboi, M. SERS Study of Molecular Adsorption: Some Nucleic Acid Bases on Ag Electrodes. Surf. Sci. 1985, 158, 341−351. (142) Chen, S.-P.; Hosten, C. M.; Vivoni, A.; Birke, R. L.; Lombardi, J. R. SERS Investigation of NAD+ Adsorbed on a Silver Electrode. Langmuir 2002, 18, 9888−9900. (143) Otto, C.; Hoeben, F.; Greve, J. Surface-Enhanced Raman Scattering of the Complexes of Silver with Adenine and dAMP. J. Raman Spectrosc. 1991, 22, 791−796. (144) Cotton, T. M.; Schultz, S. G.; Van Duyne, R. P. SurfaceEnhanced Resonance Raman Scattering from Cytochrome C and Myoglobin Adsorbed on a Silver Electrode. J. Am. Chem. Soc. 1980, 102, 7960−7962. (145) Negri, P.; Schultz, Z. D. Online SERS Detection of the 20 Proteinogenic L-Amino Acids Separated by Capillary Zone Electrophoresis. Analyst 2014, 139, 5989−5998. (146) Barhoumi, A.; Zhang, D.; Tam, F.; Halas, N. J. Surface-Enhanced Raman Spectroscopy of DNA. J. Am. Chem. Soc. 2008, 130, 5523−5529. (147) Singhal, K.; Kalkan, A. K. Surface-Enhanced Raman Scattering Captures Conformational Changes of Single Photoactive Yellow Protein Molecules under Photoexcitation. J. Am. Chem. Soc. 2010, 132, 429−431. (148) Kneipp, K.; Kneipp, H.; Kartha, V. B.; Manoharan, R.; Deinum, G.; Itzkan, I.; Dasari, R. R.; Feld, M. S. Detection and Identification of a Single DNA Base Molecule Using Surface-Enhanced Raman Scattering (SERS). Phys. Rev. E: Stat. Phys., Plasmas, Fluids, Relat. Interdiscip. Top. 1998, 57, R6281−R6284. (149) Ma, K.; Yuen, J. M.; Shah, N. C.; Walsh, J. T.; Glucksberg, M. R.; Van Duyne, R. P. In Vivo, Transcutaneous Glucose Sensing Using Surface-Enhanced Spatially Offset Raman Spectroscopy: Multiple Rats, Improved Hypoglycemic Accuracy, Low Incident Power, and Continuous Monitoring for Greater than 17 Days. Anal. Chem. 2011, 83, 9146−9152. (150) Lemler, P.; Premasiri, W.; DelMonaco, A.; Ziegler, L. NIR Raman Spectra of Whole Human Blood: Effects of Laser-Induced and in Vitro Hemoglobin Denaturation. Anal. Bioanal. Chem. 2014, 406, 193− 200.

(151) Doty, K. C.; McLaughlin, G.; Lednev, I. K. A Raman “Spectroscopic Clock” for Bloodstain Age Determination: the First Week After Deposition. Anal. Bioanal. Chem. 2016, 408, 3993−4001. (152) Premasiri, W.; Lee, J.; Ziegler, L. Surface-Enhanced Raman Scattering of Whole Human Blood, Blood Plasma and Red Blood Cells: Cellular Processes and Bioanalytical Sensing. J. Phys. Chem. B 2012, 116, 9376−9386. (153) Kingsmore, S. F. Multiplexed Protein Measurement: Technologies and Applications of Protein and Antibody Arrays. Nat. Rev. Drug Discovery 2006, 5, 310−321. (154) Nolan, G. P. What’s Wrong with Drug Screening Today. Nat. Chem. Biol. 2007, 3, 187−191. (155) Tessler, L. A.; Reifenberger, J. G.; Mitra, R. D. Protein Quantification in Complex Mixtures by Solid Phase Single-Molecule Counting. Anal. Chem. 2009, 81, 7141−7148. (156) Ross, C. A.; Poirier, M. A. Protein Aggregation and Neurodegenerative Disease. Nat. Med. 2004, 10 Suppl, S10−17. (157) Wackerbarth, H.; Klar, U.; Gunther, W.; Hildebrandt, P. Novel Time-Resolved Surface-Enhanced (Resonance) Raman Spectroscopic Technique for Studying the Dynamics of Interfacial Processes: Application to the Electron Transfer Reaction of Cytochrome C at a Silver Electrode. Appl. Spectrosc. 1999, 53, 283−291. (158) Soldatova, A. V.; Ibrahim, M.; Olson, J. S.; Czernuszewicz, R. S.; Spiro, T. G. New Light on NO Bonding in Fe(III) Heme Proteins from Resonance Raman Spectroscopy and DFT Modeling. J. Am. Chem. Soc. 2010, 132, 4614−4625. (159) Feng, M.; Tachikawa, H. Surface-Enhanced Resonance Raman Spectroscopic Characterization of the Protein Native Structure. J. Am. Chem. Soc. 2008, 130, 7443−7448. (160) Xu, H.; Bjerneld, E. J.; Käll, M.; Börjesson, L. Spectroscopy of Single Hemoglobin Molecules by Surface Enhanced Raman Scattering. Phys. Rev. Lett. 1999, 83, 4357−4360. (161) Grabbe, E. S.; Buck, R. P. Surface-Enhanced Raman Spectroscopic Investigation of Human Immunoglobulin G Adsorbed on a Silver Electrode. J. Am. Chem. Soc. 1989, 111, 8362−8366. (162) Dick, L. A.; Haes, A. J.; Van Duyne, R. P. Distance and Orientation Dependence of Heterogeneous Electron Transfer: A Surface-Enhanced Resonance Raman Scattering Study of Cytochrome c Bound to Carboxylic Acid Terminated Alkanethiols Adsorbed on Silver Electrodes. J. Phys. Chem. B 2000, 104, 11752−11762. (163) Zhou, Z.; Huang, G. G.; Kato, T.; Ozaki, Y. Experimental Parameters for the SERS of Nitrate Ion for Label-Free SemiQuantitative Detection of Proteins and Mechanism for Proteins to Form SERS Hot sites: a SERS Study. J. Raman Spectrosc. 2011, 42, 1713−1721. (164) Han, X. X.; Huang, G. G.; Zhao, B.; Ozaki, Y. Label-Free Highly Sensitive Detection of Proteins in Aqueous Solutions Using SurfaceEnhanced Raman Scattering. Anal. Chem. 2009, 81, 3329−3333. (165) Keskin, S.; Ç ulha, M. Label-Free Detection of Proteins from Dried-Suspended Droplets Using Surface-Enhanced Raman Scattering. Analyst 2012, 137, 2651−2657. (166) Huang, G. G.; Han, X. X.; Hossain, M. K.; Ozaki, Y. Development of a Heat-Induced Surface-Enhanced Raman Scattering Sensing Method For Rapid Detection of Glutathione in Aqueous Solutions. Anal. Chem. 2009, 81, 5881−5888. (167) Han, X. X.; Jia, H. Y.; Wang, Y. F.; Lu, Z. C.; Wang, C. X.; Xu, W. Q.; Zhao, B.; Ozaki, Y. Analytical Technique for Label-Free MultiProtein Detection Based on Western Blot and Surface-Enhanced Raman Scattering. Anal. Chem. 2008, 80, 2799−2804. (168) Ruan, W.; Ji, W.; Xue, X.; Cui, Y.; Chen, L.; Zhou, T.; Niu, L.; Li, X.; Zhang, J.; Zhao, B. SERS Detection of Proteins on Micropatterned Protein-Mediated Sandwich Substrates. J. Raman Spectrosc. 2011, 42, 1492−1496. (169) Matteini, P.; Cottat, M.; Tavanti, F.; Panfilova, E.; Scuderi, M.; Nicotra, G.; Menziani, M. C.; Khlebtsov, N.; de Angelis, M.; Pini, R. SiteSelective Surface-Enhanced Raman Detection of Proteins. ACS Nano 2017, 11, 918−926. AE


Chemical Reviews

Review

(170) Bell, S. E. J.; Sirimuthu, N. M. S. Surface-enhanced Raman spectroscopy (SERS) for sub-micromolar detection of DNA/RNA mononucleotides. J. Am. Chem. Soc. 2006, 128, 15580−15581. (171) Barhoumi, A.; Halas, N. J. Label-Free Detection of DNA Hybridization Using Surface Enhanced Raman Spectroscopy. J. Am. Chem. Soc. 2010, 132, 12792−12793. (172) Torres-Nunez, A.; Faulds, K.; Graham, D.; Alvarez-Puebla, R. A.; Guerrini, L. Silver Colloids as Plasmonic Substrates for Direct LabelFree Surface-Enhanced Raman Scattering Analysis of DNA. Analyst 2016, 141, 5170−5180. (173) Stuart, D. A.; Yuen, J. M.; Shah, N.; Lyandres, O.; Yonzon, C. R.; Glucksberg, M. R.; Walsh, J. T.; Van Duyne, R. P. In Vivo Glucose Measurement by Surface-Enhanced Raman Spectroscopy. Anal. Chem. 2006, 78, 7211−7215. (174) Yuen, J. M.; Shah, N. C.; Walsh, J. T.; Glucksberg, M. R.; Van Duyne, R. P. Transcutaneous Glucose Sensing by Surface-Enhanced Spatially Offset Raman Spectroscopy in a Rat Model. Anal. Chem. 2010, 82, 8382−8385. (175) Hu, P.; Zheng, X.-S.; Zong, C.; Li, M.-H.; Zhang, L.-Y.; Li, W.; Ren, B. Drop-Coating Deposition and Surface-Enhanced Raman Spectroscopies (DCDRS and SERS) Provide Complementary Information of Whole Human Tears. J. Raman Spectrosc. 2014, 45, 565−573. (176) Hsu, P.-H.; Chiang, H. K. Surface-Enhanced Raman Spectroscopy for Quantitative Measurement of Lactic Acid at Physiological Concentration in Human Serum. J. Raman Spectrosc. 2010, 41, 1610− 1614. (177) Yan, B.; Reinhard, B. r. M. Identification of Tumor Cells through Spectroscopic Profiling of the Cellular Surface Chemistry. J. Phys. Chem. Lett. 2010, 1, 1595−1598. (178) Zhang, Y.; Ye, X.; Xu, G.; Jin, X.; Luan, M.; Lou, J.; Wang, L.; Huang, C.; Ye, J. Identification and Distinction of Non-Small-Cell Lung Cancer Cells by Intracellular SERS Nanoprobes. RSC Adv. 2016, 6, 5401−5407. (179) Lin, J.; Chen, R.; Feng, S.; Li, Y.; Huang, Z.; Xie, S.; Yu, Y.; Cheng, M.; Zeng, H. Rapid Delivery of Silver Nanoparticles into Living Cells by Electroporation for Surface-Enhanced Raman Spectroscopy. Biosens. Bioelectron. 2009, 25, 388−394. (180) Jarvis, R. M.; Law, N.; Shadi, I. T.; O’Brien, P.; Lloyd, J. R.; Goodacre, R. Surface-Enhanced Raman Scattering from Intracellular and Extracellular Bacterial Locations. Anal. Chem. 2008, 80, 6741−6746. (181) Shamsaie, A.; Jonczyk, M.; Sturgis, J.; Robinson, J. P.; Irudayaraj, J. Intracellularly Grown Gold Nanoparticles as Potential SurfaceEnhanced Raman Scattering Probes. J. Biomed. Opt. 2007, 12, 020502. (182) Wang, H. H.; Liu, C. Y.; Wu, S. B.; Liu, N. W.; Peng, C. Y.; Chan, T. H.; Hsu, C. F.; Wang, J. K.; Wang, Y. L. Highly Raman-Enhancing Substrates Based on Silver Nanoparticle Arrays with Tunable Sub-10 nm Gaps. Adv. Mater. 2006, 18, 491−495. (183) Liu, B.-W.; Yao, X.; Zhang, L.; Lin, H.-X.; Chen, S.; Zhong, J.-H.; Liu, S.; Wang, L.; Ren, B. Efficient Platform for Flexible Engineering of Superradiant, Fano-Type, and Subradiant Resonances. ACS Photonics 2015, 2, 1725−1731. (184) Hatab, N. A.; Hsueh, C.-H.; Gaddis, A. L.; Retterer, S. T.; Li, J.H.; Eres, G.; Zhang, Z.; Gu, B. Free-Standing Optical Gold Bowtie Nanoantenna with Variable Gap Size for Enhanced Raman Spectroscopy. Nano Lett. 2010, 10, 4952−4955. (185) Jensen, T. R.; Malinsky, M. D.; Haynes, C. L.; Van Duyne, R. P. Nanosphere Lithography: Tunable Localized Surface Plasmon Resonance Spectra of Silver Nanoparticles. J. Phys. Chem. B 2000, 104, 10549−10556. (186) Sivashanmugan, K.; Liao, J.-D.; You, J.-W.; Wu, C.-L. FocusedIon-Beam-Fabricated Au/Ag Multilayered Nanorod Array as SERSActive Substrate for Virus Strain Detection. Sens. Actuators, B 2013, 181, 361−367. (187) Zheng, X.-S.; Hu, P.; Zhong, J.-H.; Zong, C.; Wang, X.; Liu, B.-J.; Ren, B. Laser Power Dependent Surface-Enhanced Raman Spectroscopic Study of 4-Mercaptopyridine on Uniform Gold NanoparticleAssembled Substrates. J. Phys. Chem. C 2014, 118, 3750−3757.

(188) Vitol, E. A.; Orynbayeva, Z.; Bouchard, M. J.; Azizkhan-Clifford, J.; Friedman, G.; Gogotsi, Y. In Situ Intracellular Spectroscopy with Surface-Enhanced Raman Spectroscopy (SERS)-Enabled Nanopipettes. ACS Nano 2009, 3, 3529−3536. (189) Lussier, F.; Brulé, T.; Vishwakarma, M.; Das, T.; Spatz, J. P.; Masson, J.-F. Dynamic-SERS Optophysiology: a Nanosensor for Monitoring Cell Secretion Events. Nano Lett. 2016, 16, 3866−3871. (190) Jarvis, R. M.; Goodacre, R. Characterisation and Identification of Bacteria Using SERS. Chem. Soc. Rev. 2008, 37, 931−936. (191) Chen, P.; Cui, L.; Zhang, K. Surface-Enhanced Raman Spectroscopy Monitoring the Development of Dual-Species Biofouling on Membrane Surfaces. J. Membr. Sci. 2015, 473, 36−44. (192) Marotta, N. E.; Bottomley, L. A. Surface-Enhanced Raman Scattering of Bacterial Cell Culture Growth Media. Appl. Spectrosc. 2010, 64, 601−606. (193) Premasiri, W. R.; Gebregziabher, Y.; Ziegler, L. D. On the Difference between Surface-Enhanced Raman Scattering (SERS) Spectra of Cell Growth Media and Whole Bacterial Cells. Appl. Spectrosc. 2011, 65, 493−499. (194) Premasiri, W. R.; Lee, J. C.; Sauer-Budge, A.; Théberge, R.; Costello, C. E.; Ziegler, L. D. The Biochemical Origins of the SurfaceEnhanced Raman Spectra of Bacteria: a Metabolomics Profiling by SERS. Anal. Bioanal. Chem. 2016, 408, 4631−4647. (195) Ranjith Premasiri, W.; Lemler, P.; Chen, Y.; Gebregziabher, Y.; Ziegler, L. D. Sers Analysis of Bacteria, Human Blood, and Cancer Cells: A Metabolomic and Diagnostic Tool. Frontiers of Surface-Enhanced Raman Scattering: Single Nanoparticles and Single Cells 2014, 257−283. (196) Emory, S. R.; Jensen, R. A.; Wenda, T.; Han, M.; Nie, S. Reexamining the Origins of Spectral Blinking in Single-Molecule and Single-Nanoparticle SERS. Faraday Discuss. 2006, 132, 249−259. (197) Kneipp, J.; Kneipp, H.; McLaughlin, M.; Brown, D.; Kneipp, K. In Vivo Molecular Probing of Cellular Compartments with Gold Nanoparticles and Nanoaggregates. Nano Lett. 2006, 6, 2225−2231. (198) Huefner, A.; Kuan, W.-L.; Müller, K. H.; Skepper, J. N.; Barker, R. A.; Mahajan, S. Characterization and Visualization of Vesicles in the Endo-Lysosomal Pathway with Surface-Enhanced Raman Spectroscopy and Chemometrics. ACS Nano 2016, 10, 307−316. (199) Bando, K.; Smith, N. I.; Ando, J.; Fujita, K.; Kawata, S. Analysis of Dynamic SERS Spectra Measured with a Nanoparticle During Intracellular Transportation in 3D. J. Opt. 2015, 17, 114023. (200) Huang, K.-C.; Bando, K.; Ando, J.; Smith, N. I.; Fujita, K.; Kawata, S. 3D SERS (Surface-Enhanced Raman Scattering) Imaging of Intracellular Pathways. Methods 2014, 68, 348−353. (201) Huang, J.; Zong, C.; Shen, H.; Liu, M.; Chen, B.; Ren, B.; Zhang, Z. Mechanism of Cellular Uptake of Graphene Oxide Studied by Surface-Enhanced Raman Spectroscopy. Small 2012, 8, 2577−2584. (202) Huang, J.; Zong, C.; Shen, H.; Cao, Y.; Ren, B.; Zhang, Z. Tracking the Intracellular Drug Release from Graphene Oxide Using Surface-Enhanced Raman Spectroscopy. Nanoscale 2013, 5, 10591− 10598. (203) Evan, G. I.; Vousden, K. H. Proliferation, Cell Cycle and Apoptosis in Cancer. Nature 2001, 411, 342−348. (204) Austin, L. A.; Kang, B.; El-Sayed, M. A. A New Nanotechnology Technique for Determining Drug Efficacy Using Targeted Plasmonically Enhanced Single Cell Imaging Spectroscopy. J. Am. Chem. Soc. 2013, 135, 4688−4691. (205) Medema, J. P. Cancer Stem Cells: the Challenges ahead. Nat. Cell Biol. 2013, 15, 338−344. (206) Sander, P. R.; Hau, P.; Koch, S.; Schütze, K.; Bogdahn, U.; Kalbitzer, H. R.; Aigner, L. Stem Cell Metabolic and Spectroscopic Profiling. Trends Biotechnol. 2013, 31, 204−213. (207) Huefner, A.; Kuan, W.-L.; Barker, R. A.; Mahajan, S. Intracellular SERS Nanoprobes for Distinction of Different Neuronal Cell Types. Nano Lett. 2013, 13, 2463−2470. (208) El-Said, W. A.; Kim, S. U.; Choi, J.-W. Monitoring in Vitro Neural Stem Cell Differentiation Based on Surface-Enhanced Raman Spectroscopy Using a Gold Nanostar Array. J. Mater. Chem. C 2015, 3, 3848−3859. AF


Chemical Reviews

Review

(209) Dijkstra, R. J.; Scheenen, W. J.; Dam, N.; Roubos, E. W.; Ter Meulen, J. Monitoring Neurotransmitter Release Using SurfaceEnhanced Raman Spectroscopy. J. Neurosci. Methods 2007, 159, 43−50. (210) Xie, W.; Wang, L.; Zhang, Y.; Su, L.; Shen, A.; Tan, J.; Hu, J. Nuclear Targeted Nanoprobe for Single Living Cell Detection by Surface-Enhanced Raman Scattering. Bioconjugate Chem. 2009, 20, 768−773. (211) Cao, Y. C.; Jin, R. C.; Nam, J. M.; Thaxton, C. S.; Mirkin, C. A. Raman dye-labeled nanoparticle probes for proteins. J. Am. Chem. Soc. 2003, 125, 14676−14677. (212) Han, X. X.; Zhao, B.; Ozaki, Y. Surface-enhanced Raman scattering for protein detection. Anal. Bioanal. Chem. 2009, 394, 1719− 1727. (213) Graham, D.; Mallinder, B. J.; Smith, W. E. Detection and identification of labeled DNA by surface enhanced resonance Raman scattering. Biopolymers 2000, 57, 85−91. (214) Vo-Dinh, T.; Allain, L. R.; Stokes, D. L. Cancer gene detection using surface-enhanced Raman scattering (SERS). J. Raman Spectrosc. 2002, 33, 511−516. (215) von Maltzahn, G.; Centrone, A.; Park, J.-H.; Ramanathan, R.; Sailor, M. J.; Hatton, T. A.; Bhatia, S. N. SERS-Coded Gold Nanorods as a Multifunctional Platform for Densely Multiplexed Near-infrared Imaging and Photothermal Heating. Adv. Mater. 2009, 21, 3175. (216) Kneipp, J.; Kneipp, H.; Rajadurai, A.; Redmond, R. W.; Kneipp, K. Optical probing and imaging of live cells using SERS labels. J. Raman Spectrosc. 2009, 40, 1−5. (217) Kim, J.-H.; Kim, J.-S.; Choi, H.; Lee, S.-M.; Jun, B.-H.; Yu, K.-N.; Kuk, E.; Kim, Y.-K.; Jeong, D. H.; Cho, M.-H.; Lee, Y.-S. Nanoparticle probes with surface enhanced Raman spectroscopic tags for cellular cancer targeting. Anal. Chem. 2006, 78, 6967−6973. (218) Song, J.; Zhou, J.; Duan, H. Self-Assembled Plasmonic Vesicles of SERS-Encoded Amphiphilic Gold Nanoparticles for Cancer Cell Targeting and Traceable Intracellular Drug Delivery. J. Am. Chem. Soc. 2012, 134, 13458−13469. (219) Samanta, A.; Maiti, K. K.; Soh, K.-S.; Liao, X.; Vendrell, M.; Dinish, U. S.; Yun, S.-W.; Bhuvaneswari, R.; Kim, H.; Rautela, S.; Chung, J.; Olivo, M.; Chang, Y.-T. Ultrasensitive Near-Infrared Raman Reporters for SERS-Based In Vivo Cancer Detection. Angew. Chem., Int. Ed. 2011, 50, 6089−6092. (220) Kong, K. V.; Lam, Z.; Goh, W. D.; Leong, W. K.; Olivo, M. Metal Carbonyl-Gold Nanoparticle Conjugates for Live-Cell SERS Imaging. Angew. Chem., Int. Ed. 2012, 51, 9796−9799. (221) Song, Z.-L.; Chen, Z.; Bian, X.; Zhou, L.-Y.; Ding, D.; Liang, H.; Zou, Y.-X.; Wang, S.-S.; Chen, L.; Yang, C.; Zhang, X.-B.; Tan, W. Alkyne-Functionalized Superstable Graphitic Silver Nanoparticles for Raman Imaging. J. Am. Chem. Soc. 2014, 136, 13558−13561. (222) Yin, Y.; Li, Q.; Ma, S.; Liu, H.; Dong, B.; Yang, J.; Liu, D. Prussian Blue as a Highly Sensitive and Background-Free Resonant Raman Reporter. Anal. Chem. 2017, 89, 1551. (223) Ma, S.; Li, Q.; Yin, Y.; Yang, J.; Liu, D. Interference-Free SurfaceEnhanced Raman Scattering Tags for Single-Cell Molecular Imaging with a High Signal-to-Background Ratio. Small 2017, 13, 1603340. (224) Chen, Y.; Ren, J.-Q.; Zhang, X.-G.; Wu, D.-Y.; Shen, A.-G.; Hu, J.-M. Alkyne-Modulated Surface-Enhanced Raman Scattering-Palette for Optical Interference-Free and Multiplex Cellular Imaging. Anal. Chem. 2016, 88, 6115−6119. (225) Bohndiek, S. E.; Wagadarikar, A.; Zavaleta, C. L.; Van de Sompel, D.; Garai, E.; Jokerst, J. V.; Yazdanfar, S.; Gambhir, S. S. A Small Animal Raman Instrument for Rapid, Wide-Area, Spectroscopic Imaging. Proc. Natl. Acad. Sci. U. S. A. 2013, 110, 12408−12413. (226) Maiti, K. K.; Dinish, U. S.; Samanta, A.; Vendrell, M.; Soh, K. S.; Park, S. J.; Olivo, M.; Chang, Y. T. Multiplex Targeted in Vivo Cancer Detection Using Sensitive Near-Infrared SERS Nanotags. Nano Today 2012, 7, 85−93. (227) Dinish, U. S.; Balasundaram, G.; Chang, Y.-T.; Olivo, M. Actively Targeted in Vivo Multiplex Detection of Intrinsic Cancer Biomarkers Using Biocompatible SERS Nanotags. Sci. Rep. 2015, 4, 4075.

(228) Wei, L.; Chen, Z.; Shi, L.; Long, R.; Anzalone, A. V.; Zhang, L.; Hu, F.; Yuste, R.; Cornish, V. W.; Min, W. Super-Multiplex Vibrational Imaging. Nature 2017, 544, 465−470. (229) Jaworska, A.; Wojcik, T.; Malek, K.; Kwolek, U.; Kepczynski, M.; Ansary, A. A.; Chlopicki, S.; Baranska, M. Rhodamine 6G Conjugated to Gold Nanoparticles as Labels for Both SERS and Fluorescence Studies on Live Endothelial Cells. Microchim. Acta 2015, 182, 119−127. (230) Zheng, X.-S.; Hu, P.; Cui, Y.; Zong, C.; Feng, J.-M.; Wang, X.; Ren, B. BSA-Coated Nanoparticles for Improved SERS-Based Intracellular pH Sensing. Anal. Chem. 2014, 86, 12250−12257. (231) Bassi, B.; Taglietti, A.; Galinetto, P.; Marchesi, N.; Pascale, A.; Cabrini, E.; Pallavicini, P.; Dacarro, G. Tunable Coating of Gold Nanostars: Tailoring Robust SERS Labels for Cell Imaging. Nanotechnology 2016, 27, 265302. (232) Fasolato, C.; Giantulli, S.; Silvestri, I.; Mazzarda, F.; Toumia, Y.; Ripanti, F.; Mura, F.; Luongo, F.; Costantini, F.; Bordi, F.; Postorino, P.; Domenici, F. Folate-Based Single Cell Screening using SurfaceEnhanced Raman Microimaging. Nanoscale 2016, 8, 17304−17313. (233) Kuestner, B.; Gellner, M.; Schuetz, M.; Schoeppler, F.; Marx, A.; Stroebel, P.; Adam, P.; Schmuck, C.; Schluecker, S. SERS Labels for Red Laser Excitation: Silica-Encapsulated SAMs on Tunable Gold/Silver Nanoshells. Angew. Chem., Int. Ed. 2009, 48, 1950−1953. (234) Zhang, Y.; Qian, J.; Wang, D.; Wang, Y.; He, S. Multifunctional Gold Nanorods with Ultrahigh Stability and Tunability for in Vivo Fluorescence Imaging, SERS Detection, and Photodynamic Therapy. Angew. Chem., Int. Ed. 2013, 52, 1148−1151. (235) Wang, Y.; Chen, L.; Liu, P. Biocompatible Triplex Ag@ SiO2@ mTiO2 Core−Shell Nanoparticles for Simultaneous Fluorescence-SERS Bimodal Imaging and Drug Delivery. Chem. - Eur. J. 2012, 18, 5935− 5943. (236) Zong, S.; Wang, Z.; Chen, H.; Yang, J.; Cui, Y. Surface-Enhanced Raman Scattering Traceable and Glutathione Responsive Nanocarrier for the Intracellular Drug Delivery. Anal. Chem. 2013, 85, 2223−2230. (237) Huang, J.; Kim, K. H.; Choi, N.; Chon, H.; Lee, S.; Choo, J. Preparation of Silica-Encapsulated Hollow Gold Nanosphere Tags Using Layer-by-Layer Method for Multiplex Surface-Enhanced Raman Scattering Detection. Langmuir 2011, 27, 10228−10233. (238) Song, J.; Duan, B.; Wang, C.; Zhou, J.; Pu, L.; Fang, Z.; Wang, P.; Lim, T. T.; Duan, H. SERS-Encoded Nanogapped Plasmonic Nanoparticles: Growth of Metallic Nanoshell by Templating RedoxActive Polymer Brushes. J. Am. Chem. Soc. 2014, 136, 6838−6841. (239) Gandra, N.; Singamaneni, S. Bilayered Raman-Intense Gold Nanostructures with Hidden Tags (BRIGHTs) for High-Resolution Bioimaging. Adv. Mater. 2013, 25, 1022−1027. (240) Gao, Y.; Li, Y.; Wang, Y.; Chen, Y.; Gu, J.; Zhao, W.; Ding, J.; Shi, J. Controlled Synthesis of Multilayered Gold Sanoshells for Enhanced Photothermal Therapy and SERS Detection. Small 2015, 11, 77−83. (241) Ochsner, M. Photophysical and Photobiological Processes in the Photodynamic Therapy of Tumours. J. Photochem. Photobiol., B 1997, 39, 1−18. (242) Castano, A. P.; Mroz, P.; Hamblin, M. R. Photodynamic Therapy and Anti-Tumour Immunity. Nat. Rev. Cancer 2006, 6, 535−545. (243) Zhang, Y.; Zou, Y.; Liu, F.; Xu, Y.; Wang, X.; Li, Y.; Liang, H.; Chen, L.; Chen, Z.; Tan, W. Stable Graphene-Isolated-Au-Nanocrystal for Accurate and Rapid Surface Enhancement Raman Scattering Analysis. Anal. Chem. 2016, 88, 10611−10616. (244) Zhang, Y.; Qiu, Y.; Lin, L.; Gu, H.; Xiao, Z.; Ye, J. Ultraphotostable Mesoporous Silica-Coated Gap-Enhanced Raman Tags (GERTs) for High-Speed Bioimaging. ACS Appl. Mater. Interfaces 2017, 9, 3995−4005. (245) Li, D.-W.; Qu, L.-L.; Hu, K.; Long, Y.-T.; Tian, H. Monitoring of Endogenous Hydrogen Sulfide in Living Cells Using Surface-Enhanced Raman Scattering. Angew. Chem., Int. Ed. 2015, 54, 12758−12761. (246) Cao, Y.; Li, D.-W.; Zhao, L.-J.; Liu, X.-Y.; Cao, X.-M.; Long, Y.-T. Highly Selective Detection of Carbon Monoxide in Living Cells by Palladacycle Carbonylation-Based Surface Enhanced Raman Spectroscopy Nanosensors. Anal. Chem. 2015, 87, 9696−9701. (247) Qu, L.-L.; Li, D.-W.; Qin, L.-X.; Mu, J.; Fossey, J. S.; Long, Y.-T. Selective and Sensitive Detection of Intracellular O-2(center dot-) AG


Chemical Reviews

Review

Using Au NPs/Cytochrome c as SERS Nanosensors. Anal. Chem. 2013, 85, 9549−9555. (248) Wang, W.; Zhang, L.; Li, L.; Tian, Y. A Single Nanoprobe for Ratiometric Imaging and Biosensing of Hypochlorite and Glutathione in Live Cells Using Surface-Enhanced Raman Scattering. Anal. Chem. 2016, 88, 9518−9523. (249) Cui, J.; Hu, K.; Sun, J.-J.; Qu, L.-L.; Li, D.-W. SERS Nanoprobes for the Monitoring of Endogenous Nitric Oxide in Living Cells. Biosens. Bioelectron. 2016, 85, 324−330. (250) Peng, R.; Si, Y.; Deng, T.; Zheng, J.; Li, J.; Yang, R.; Tan, W. A Novel SERS Nanoprobe for the Ratiometric Imaging of Hydrogen Peroxide in Living Cells. Chem. Commun. 2016, 52, 8553−8556. (251) Gu, X.; Wang, H.; Schultz, Z. D.; Camden, J. P. Sensing Glucose in Urine and Serum and Hydrogen Peroxide in Living Cells by Use of a Novel Boronate Nanoprobe Based on Surface-Enhanced Raman Spectroscopy. Anal. Chem. 2016, 88, 7191−7197. (252) Wang, Y.; Deng, X.; Liu, J.; Tang, H.; Jiang, J. Surface enhanced Raman scattering based sensitive detection of histone demethylase activity using a formaldehyde-selective reactive probe. Chem. Commun. 2013, 49, 8489−8491. (253) Sun, F.; Bai, T.; Zhang, L.; Ella-Menye, J.-R.; Liu, S.; Nowinski, A. K.; Jiang, S.; Yu, Q. Sensitive and Fast Detection of Fructose in Complex Media via Symmetry Breaking and Signal Amplification Using Surface-Enhanced Raman Spectroscopy. Anal. Chem. 2014, 86, 2387− 2394. (254) Pazos, E.; Garcia-Algar, M.; Penas, C.; Nazarenus, M.; Torruella, A.; Pazos-Perez, N.; Guerrini, L.; Eugenio Vazquez, M.; Garcia-Rico, E.; Mascarenas, J. L.; Alvarez-Puebla, R. A. Surface-Enhanced Raman Scattering Surface Selection Rules for the Proteomic Liquid Biopsy in Real Samples: Efficient Detection of the Oncoprotein c-MYC. J. Am. Chem. Soc. 2016, 138, 14206−14209. (255) Kho, K. W.; Dinish, U. S.; Kumar, A.; Olivo, M. Frequency Shifts in SERS for Biosensing. ACS Nano 2012, 6, 4892−4902. (256) Talley, C. E.; Jusinski, L.; Hollars, C. W.; Lane, S. M.; Huser, T. Intracellular pH sensors based on surface-enhanced Raman scattering. Anal. Chem. 2004, 76, 7064−7068. (257) Kneipp, J.; Kneipp, H.; Wittig, B.; Kneipp, K. One- and twophoton excited optical pH probing for cells using surface-enhanced Raman and hyper-Raman nanosensors. Nano Lett. 2007, 7, 2819−2823. (258) Pallaoro, A.; Braun, G. B.; Reich, N. O.; Moskovits, M. Mapping Local pH in Live Cells Using Encapsulated Fluorescent SERS Nanotags. Small 2010, 6, 618−622. (259) Auchinvole, C. A.; Richardson, P.; McGuinnes, C.; Mallikarjun, V.; Donaldson, K.; McNab, H.; Campbell, C. J. Monitoring Intracellular Redox Potential Changes Using SERS Nanosensors. ACS Nano 2012, 6, 888−896. (260) Jamieson, L. E.; Jaworska, A.; Jiang, J.; Baranska, M.; Harrison, D.; Campbell, C. Simultaneous Intracellular Redox Potential and pH Measurements in Live Cells Using SERS Nanosensors. Analyst 2015, 140, 2330−2335. (261) Søndergaard, R. V.; Christensen, N. M.; Henriksen, J. R.; Kumar, E. P.; Almdal, K.; Andresen, T. L. Facing the Design Challenges of Particle-Based Nanosensors for Metabolite Quantification in Living Cells. Chem. Rev. 2015, 115, 8344−8378. (262) Schluecker, S.; Kuestner, B.; Punge, A.; Bonfig, R.; Marx, A.; Stroebel, P. Immuno-Raman microspectroscopy: In situ detection of antigens in tissue specimens by surface-enhanced Raman scattering. J. Raman Spectrosc. 2006, 37, 719−721. (263) Kong, K.; Rowlands, C. J.; Varma, S.; Perkins, W.; Leach, I. H.; Koloydenko, A. A.; Williams, H. C.; Notingher, I. Diagnosis of Tumors during Tissue-Conserving Surgery with Integrated Autofluorescence and Raman Scattering Microscopy. Proc. Natl. Acad. Sci. U. S. A. 2013, 110, 15189−15194. (264) Jeong, S.; Kim, Y.-i.; Kang, H.; Kim, G.; Cha, M. G.; Chang, H.; Jung, K. O.; Kim, Y.-H.; Jun, B.-H.; Hwang, D. W.; Lee, Y.-S.; Youn, H.; Lee, Y.-S.; Kang, K. W.; Lee, D. S.; Jeong, D. H. Fluorescence-Raman Dual Modal Endoscopic System for Multiplexed Molecular Diagnostics. Sci. Rep. 2015, 5,10.1038/srep09455.

(265) Cui, Y.; Zheng, X.-S.; Ren, B.; Wang, R.; Zhang, J.; Xia, N.-S.; Tian, Z.-Q. Au@ Organosilica Multifunctional Nanoparticles for the Multimodal Imaging. Chem. Sci. 2011, 2, 1463−1469. (266) Huang, J.; Guo, M.; Ke, H.; Zong, C.; Ren, B.; Liu, G.; Shen, H.; Ma, Y.; Wang, X.; Zhang, H. Rational Design and Synthesis of γFe2O3@ Au Magnetic Gold Nanoflowers for Efficient Cancer Theranostics. Adv. Mater. 2015, 27, 5049−5056. (267) Kircher, M. F.; de la Zerda, A.; Jokerst, J. V.; Zavaleta, C. L.; Kempen, P. J.; Mittra, E.; Pitter, K.; Huang, R.; Campos, C.; Habte, F.; Sinclair, R.; Brennan, C. W.; Mellinghoff, I. K.; Holland, E. C.; Gambhir, S. S. A Brain Tumor Molecular Imaging Strategy Using a New TripleModality MRI-Photoacoustic-Raman Nanoparticle. Nat. Med. 2012, 18, 829−U235. (268) Wang, Z.; Zong, S.; Chen, H.; Wang, C.; Xu, S.; Cui, Y. SERSFluorescence Joint Spectral Encoded Magnetic Nanoprobes for Multiplex Cancer Cell Separation. Adv. Healthcare Mater. 2014, 3, 1889−1897. (269) Carrouee, A.; Allard-Vannier, E.; Meme, S.; Szeremeta, F.; Beloeil, J.-C.; Chourpa, I. Sensitive Trimodal Magnetic Resonance Imaging-Surface-Enhanced Resonance Raman Scattering-Fluorescence Detection of Cancer Cells with Stable Magneto-Plasmonic Nanoprobes. Anal. Chem. 2015, 87, 11233−11241. (270) von Maltzahn, G.; Centrone, A.; Park, J. H.; Ramanathan, R.; Sailor, M. J.; Hatton, T. A.; Bhatia, S. N. SERS-Coded Gold Nanorods as a Multifunctional Platform for Densely Multiplexed Near-Infrared Imaging and Photothermal Heating. Adv. Mater. 2009, 21, 3175−3180. (271) Yigit, M. V.; Zhu, L.; Ifediba, M. A.; Zhang, Y.; Carr, K.; Moore, A.; Medarova, Z. Noninvasive MRI-SERS Imaging in Living Mice Using an Innately Bimodal Nanomaterial. ACS Nano 2011, 5, 1056−1066. (272) Sha, M. Y.; Xu, H.; Natan, M. J.; Cromer, R. Surface-Enhanced Raman Scattering Tags for Rapid and Homogeneous Detection of Circulating Tumor Cells in the Presence of Human Whole Blood. J. Am. Chem. Soc. 2008, 130, 17214−17215. (273) Hu, F.; Zhang, Y.; Chen, G.; Li, C.; Wang, Q. Double-Walled Au Nanocage/SiO2 Nanorattles: Integrating SERS Imaging, Drug Delivery and Photothermal Therapy. Small 2015, 11, 985−993. (274) Loo, C.; Lin, A.; Hirsch, L.; Lee, M. H.; Barton, J.; Halas, N. J.; West, J.; Drezek, R. Nanoshell-enabled photonics-based imaging and therapy of cancer. Technol. Cancer Res. Treat. 2004, 3, 33−40. (275) Loo, C.; Lowery, A.; Halas, N. J.; West, J.; Drezek, R. Immunotargeted nanoshells for integrated cancer imaging and therapy. Nano Lett. 2005, 5, 709−711. (276) Huang, X.; Neretina, S.; El-Sayed, M. A. Gold Nanorods: from Synthesis and Properties to Biological and Biomedical Applications. Adv. Mater. 2009, 21, 4880−4910. (277) Huang, X.; El-Sayed, I. H.; El-Sayed, M. A. In Cancer Nanotechnology: Methods and Protocols; Grobmyer, S. R., Moudgil, B. M., Eds.; 2010; Vol. 624. (278) Blackie, E. J.; Ru, E. C. L.; Etchegoin, P. G. Single-molecule surface-enhanced Raman spectroscopy of nonresonant molecules. J. Am. Chem. Soc. 2009, 131, 14466−14472. (279) Maruyama, Y.; Ishikawa, M.; Futamata, M. Surface-Enhanced Raman Scattering of Single Adenine Molecules on Silver Colloidal Particles. Chem. Lett. 2001, 30, 834−835. (280) Etchegoin, P. G.; Le Ru, E. A Perspective on Single Molecule SERS: Current Status and Future Challenges. Phys. Chem. Chem. Phys. 2008, 10, 6079−6089. (281) Prinz, J.; Schreiber, B.; Olejko, L.; Oertel, J.; Rackwitz, J.; Keller, A.; Bald, I. DNA Origami Substrates for Highly Sensitive SurfaceEnhanced Raman Scattering. J. Phys. Chem. Lett. 2013, 4, 4140−4145. (282) Pilo-Pais, M.; Watson, A.; Demers, S.; LaBean, T. H.; Finkelstein, G. Surface-Enhanced Raman Scattering Plasmonic Enhancement Using DNA Origami-Based Complex Metallic Nanostructures. Nano Lett. 2014, 14, 2099−2104. (283) Kuehler, P.; Roller, E.-M.; Schreiber, R.; Liedl, T.; Lohmueller, T.; Feldmann, J. Plasmonic DNA-Origami Nanoantennas for SurfaceEnhanced Raman Spectroscopy. Nano Lett. 2014, 14, 2914−2919. (284) Thacker, V. V.; Herrmann, L. O.; Sigle, D. O.; Zhang, T.; Liedl, T.; Baumberg, J. J.; Keyser, U. F. DNA origami based assembly of gold AH


Chemical Reviews

Review

nanoparticle dimers for surface-enhanced Raman scattering. Nat. Commun. 2014, 5, 10.1038/ncomms4448. (285) Etchegoin, P. G.; Lacharmoise, P. D.; Le Ru, E. Influence of Photostability on Single-Molecule Surface Enhanced Raman Scattering Enhancement Factors. Anal. Chem. 2009, 81, 682−688. (286) Etchegoin, P.; Le Ru, E.; Maher, R.; Cohen, L. Enhancement Factor Averaging and the Photostability of Probes in SERS Vibrational Pumping. Phys. Chem. Chem. Phys. 2007, 9, 4923−4929. (287) Ando, J.; Fujita, K.; Smith, N. I.; Kawata, S. Dynamic SERS Imaging of Cellular Transport Pathways with Endocytosed Gold Nanoparticles. Nano Lett. 2011, 11, 5344−5348. (288) Stewart, S.; Priore, R. J.; Nelson, M. P.; Treado, P. J. Raman Imaging. Annu. Rev. Anal. Chem. 2012, 5, 337−360. (289) Zheng, X.; Zong, C.; Xu, M.; Wang, X.; Ren, B. Raman Imaging from Microscopy to Nanoscopy, and to Macroscopy. Small 2015, 11, 3395−3406. (290) Schmid, T.; Yeo, B.-S.; Leong, G.; Stadler, J.; Zenobi, R. Performing Tip-Enhanced Raman Spectroscopy in Liquids. J. Raman Spectrosc. 2009, 40, 1392−1399. (291) Zeng, Z.-C.; Huang, S.-C.; Wu, D.-Y.; Meng, L.-Y.; Li, M.-H.; Huang, T.-X.; Zhong, J.-H.; Wang, X.; Yang, Z.-L.; Ren, B. Electrochemical Tip-Enhanced Raman Spectroscopy. J. Am. Chem. Soc. 2015, 137, 11928−11931. (292) Kurouski, D.; Mattei, M.; Van Duyne, R. P. Probing Redox Reactions at the Nanoscale with Electrochemical Tip-Enhanced Raman Spectroscopy. Nano Lett. 2015, 15, 7956−7962. (293) Sabanes, N. M.; Driessen, L. M. A.; Domke, K. F. Versatile SideIllumination Geometry for Tip-Enhanced Raman Spectroscopy at Solid/Liquid Interfaces. Anal. Chem. 2016, 88, 7108−7114. (294) Mattei, M.; Kang, G.; Goubert, G.; Chulha, D. V.; Schatz, G. C.; Jensen, L.; Van Duyne, R. P. Tip-Enhanced Raman Voltammetry: Coverage Dependence and Quantitative Modeling. Nano Lett. 2017, 17, 590−596. (295) Sabanes, N. M.; Ohto, T.; Andrienko, D.; Nagata, Y.; Domke, K. F. Electrochemical TERS Elucidates Potential-Induced Molecular Reorientation of Adenine/Au(111). Angew. Chem., Int. Ed. 2017, 56, 9796−9801. (296) Khanal, D.; Kondyurin, A.; Hau, H.; Knowles, J. C.; Levinson, O.; Ramzan, I.; Fu, D.; Marcott, C.; Chrzanowski, W. Biospectroscopy of Nanodiamond-Induced Alterations in Conformation of Intra-and Extracellular Proteins: A Nanoscale IR Study. Anal. Chem. 2016, 88, 7530−7538. (297) Hillenbrand, R.; Taubner, T.; Keilmann, F. Phonon-Enhanced Light-Matter Interaction at the Nanometre Scale. Nature 2002, 418, 159−162. (298) Nowak, D.; Morrison, W.; Wickramasinghe, H. K.; Jahng, J.; Potma, E.; Wan, L.; Ruiz, R.; Albrecht, T. R.; Schmidt, K.; Frommer, J.; Sanders, D. P.; Park, S. Nanoscale Chemical Imaging by Photoinduced Force Microscopy. Sci. Adv. 2016, 2, e1501571. (299) Dazzi, A.; Prater, C. B. AFM-IR: Technology and Applications in Nanoscale Infrared Spectroscopy and Chemical Imaging. Chem. Rev. 2017, 117, 5146−5173. (300) Olschewski, K.; Kämmer, E.; Stöckel, S.; Bocklitz, T.; DeckertGaudig, T.; Zell, R.; Cialla-May, D.; Weber, K.; Deckert, V.; Popp, J. A Manual and an Automatic TERS Based Virus Discrimination. Nanoscale 2015, 7, 4545−4552. (301) Bailo, E.; Deckert, V. Tip-Enhanced Raman Spectroscopy of Single RNA Strands: Towards a Novel Direct-Sequencing Method. Angew. Chem., Int. Ed. 2008, 47, 1658−1661. (302) Pozzi, E. A.; Sonntag, M. D.; Jiang, N.; Klingsporn, J. M.; Hersam, M. C.; Van Duyne, R. P. Tip-Enhanced Raman Imaging: an Emergent Tool for Probing Biology at the Nanoscale. ACS Nano 2013, 7, 885−888. (303) Baldassarre, L.; Giliberti, V.; Rosa, A.; Ortolani, M.; Bonamore, A.; Baiocco, P.; Kjoller, K.; Calvani, P.; Nucara, A. Mapping the Amide I Absorption in Single Bacteria and Mammalian Cells with Resonant Infrared Nanospectroscopy. Nanotechnology 2016, 27, 075101.

(304) Gustafsson, M. G. Surpassing the Lateral Resolution Limit by a Factor of Two Using Structured Illumination Microscopy. J. Microsc. 2000, 198, 82−87. (305) Gustafsson, M. G. Nonlinear Structured-Illumination Microscopy: Wide-Field Fluorescence Imaging with Theoretically Unlimited Resolution. Proc. Natl. Acad. Sci. U. S. A. 2005, 102, 13081−13086. (306) Watanabe, K.; Palonpon, A. F.; Smith, N. I.; Kasai, A.; Hashimoto, H.; Kawata, S.; Fujita, K. Structured Line Illumination Raman Microscopy. Nat. Commun. 2015, 6, 10095. (307) Chen, H.; Wang, S.; Zhang, Y.; Yang, Y.; Fang, H.; Zhu, S.; Yuan, X. Structured Illumination for Wide-Field Raman Imaging of Cell Membranes. Opt. Commun. 2017, 402, 221−225. (308) Betzig, E.; Patterson, G. H.; Sougrat, R.; Lindwasser, O. W.; Olenych, S.; Bonifacino, J. S.; Davidson, M. W.; Lippincott-Schwartz, J.; Hess, H. F. Imaging Intracellular Fluorescent Proteins at Nanometer Resolution. Science 2006, 313, 1642−1645. (309) Rust, M. J.; Bates, M.; Zhuang, X. Sub-Diffraction-Limit Imaging by Stochastic Optical Reconstruction Microscopy (STORM). Nat. Methods 2006, 3, 793−796. (310) Weber, M. L.; Willets, K. A. Correlated Super-Resolution Optical and Structural Studies of Surface-Enhanced Raman Scattering Hot Spots in Silver Colloid Aggregates. J. Phys. Chem. Lett. 2011, 2, 1766−1770. (311) Olson, A. P.; Ertsgaard, C. T.; Elliott, S. N.; Lindquist, N. C. Super-Resolution Chemical Imaging with Plasmonic Substrates. ACS Photonics 2016, 3, 329−336. (312) Wu, H.-Y.; Huang, Y.-T.; Shen, P.-T.; Lee, H.; Oketani, R.; Yonemaru, Y.; Yamanaka, M.; Shoji, S.; Lin, K.-H.; Chang, C.-W. Ultrasmall All-Optical Plasmonic Switch and its Application to Superresolution Imaging. Sci. Rep. 2016, 6, 24293. (313) Li, J.; Condello, S.; Thomes-Pepin, J.; Ma, X.; Xia, Y.; Hurley, T. D.; Matei, D.; Cheng, J.-X. Lipid Desaturation is a Metabolic Marker and Therapeutic Target of Ovarian Cancer Stem Cells. Cell Stem Cell 2017, 20, 303−314.

AI


Surface-Enhanced Raman Spectroscopy for ... - ACS Publications

Recommend Documents