SERS Quantification and Characterization of Proteins and Other

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SERS quantification and characterization of proteins and other biomolecules Neus Feliu, Moustapha Hassan, Eduardo Garcia Rico, Daxiang Cui, Wolfgang J Parak, and Ramon A. Alvarez-Puebla Langmuir, Just Accepted Manuscript • DOI: 10.1021/acs.langmuir.7b01567 • Publication Date (Web): 21 Aug 2017 Downloaded from http://pubs.acs.org on August 22, 2017

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SERS quantification and characterization of proteins and other biomolecules

Neus Feliu,1,2,* Moustapha Hassan,2 Eduardo Garcia Rico,3,4,5,6 Daxiang Cui,7 Wolfgang Parak 1,7,8

, Ramon Alvarez-Puebla,9,10,*

1

Fachbereich Physik, Philipps Universität Marburg, Marburg (Germany)

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Department of Laboratory Medicine (LABMED), Karolinska Institutet, Stockholm (Sweden)

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Fundacion de Investigacion HM Hospitales, San Bernardo 101, 28015 Madrid (Spain)

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Centro Integral Oncologico Clara Campal (CIOCC), Oña 10, 28050 Madrid (Spain)

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Servicio de Oncologia Clinica, Hospital Universitario HM Torrelodones, Castillo de Olivares s/n, 28250 Torrelodones (Spain)

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School of Medicine, San Pablo CEU, Calle Julián Romea, 18, 28003 Madrid (Spain).

7

Institute of Nano Biomedicine and Engineering, Key Laboratory for Thin Film and Microfabrication Technology of the Ministry of Education, Department of Instrument Science and Engineering, School of Electronic Information and Electrical Engineering, National Center for Translational Medicine, Shanghai Jiao Tong University, Shanghai (China)

8

Fachbereich Physik und Chemie, Universität Hamburg, Harmburg (Germany)

9

Departamento de Química Física e Inorgánica, Universitat Rovira i Virgili, Carrer de Marcellí Domingo s/n, 43007 Tarragona (Spain)

10

ICREA, Passeig Lluís Companys 23, 08010 Barcelona (Spain)

* corresponding authors: [email protected]; [email protected]

ACS Paragon Plus Environment

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Abstract: Changes in protein expression levels and protein structure may indicate genomic mutations and may be relate to some diseases. Therefore, the precise quantification and characterization of proteins can be used for the disease diagnosis. Compared with several other alternative methods, surface-enhanced Raman scattering (SERS) spectroscopy is regarded as an excellent choice for the quantification and structural characterization of proteins. Herein, we review the main advance of using plasmonic nanostructures as SERS sensing platform for this purpose. Three design approaches, including direct SERS, indirect SERS, and SERS-encoded nanoparticles are discussed in the direction of developing new precise approaches of quantification and characterization of proteins. While this review is focused on proteins, in order to highlight concepts of SERS-based sensors also detection of other biomolecules will be discussed.

KEYWORDS: SERS, Protein characterization, Protein quantification and Protein imaging.


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Introduction Proteins are large biopolymers with molecular weights ranging from some thousands (aprotinin) to nearly one million (α2-macroglobulin) Dalton. These macromolecules are formed by one or more chains of linearly aligned amino acids bonded through peptide bonds. Proteins are responsible for a large variety of biological functions including structural, immunological, metabolic, or catalytic activity, signaling, or transporting. Proteins are organized in four hierarchical levels of structure (Figure 1). The primary structure is defined by the amino acid composition and sequence within the polymeric chain. Based on the formation of hydrogenbonds, local geometrical conformation originates as from the primary structure. In general, there are two main elements of such secondary structure: α-helixes and β-sheets. As secondary structures are local, the same protein may present different secondary structure conformations in different regions. The ternary structure is defined by the association of the different parts of the protein with itself (i.e. folding) by means of the formation of hydrophobic cores, salt bridges and/or hydrogen- and disulfide-bonds. Finally, the quaternary structure relates to the association of a protein subunit to other protein subunits, metal organic complexes, nucleic acids, and other cofactors to form the functional protein. Concentration change of a given protein in cells (i.e. over- or underexpression by up- or downregulation of gene expression) can indicate a genomic misregulation. This can be strongly related to disease, such as for oncoproteins as c-jun, c-fos or c-myc in cancer.1 Also changes in the protein structure may cause diseases. Changes in the primary structure of proteins may indicate a genomic mutation (i.e. errors in the gene related to the codification of these proteins). In fact, a protein with a different primary structure may be regarded as different protein. Changes in the secondary structure may cause biological malfunction of the proteins. For example, many


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diseases are related to the inadequate folding of certain parts of functional proteins.2, 3 This case is typical, for example, in the case of amyloid diseases (including Alzheimer, Parkinson, Huntington, Creutzfeldt-Jakob, fatal familial insomnia and many others), where a biofunctional α-helix domain is substituted by a misfolded but more thermodynamically stable β-sheet domain.4 On the other hand, many proteins change their conformations, involving mostly the ternary and quaternary structures, to perform their biological function (i.e. allosteric proteins such as hemoglobin or enzymes). Thus, the understanding of the conformational dynamics of many proteins is of key importance to understanding their biochemical role and thus, their biofunctionality.

Figure 1. Levels of the protein structure. Primary structure: amino acid composition and sequence. Secondary structure: local folding into α-helixes or β-sheets. Tertiary structure: folding of the whole protein subunit. Quaternary structure: interaction between the protein subunit with other protein subunits or cofactors.

Chemical composition and structure of proteins may be characterized at different levels. First, in preparative steps, the given protein should be isolated and purified before being characterized concerning its identification, post-translational modifications, structure, and functions. Protein can be extracted from tissues after pulverization in liquid nitrogen. The isolation relies on the disruption of the tissues/cells containing the protein (if required), followed


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by precipitation, differential solubilization, and ultracentrifugation. The purification may be carried out by using various chromatography methods, such as size-exclusion, ion-exchange, hydrophobic-interaction, or electrophoresis. The primary structure (composition and sequence) is commonly determined using Edman degradation protein sequencers,5 and mass spectrometry (MS) with previous proteolytic steps.6 Protein conformation, at the different levels of structure, is generally studied by single-crystal x-ray diffraction (XRD),7 nuclear magnetic resonance (NMR)8, Mößbauer spectroscopy,9, 10 and Raman spectroscopies11 combined with theoretical methods (either parametrized or ab initio).12, 13 Although apart from yielding the static structure of proteins in protein crystals, time-resolved XRD can also provide important information such as conformational dynamics and protein interactions.14 XRD however requires crystalizing of the protein, which results in unrealistically high protein concentrations. To solve these drawbacks, spectroscopic methods can be used to study structural conformation. As an example, ultraviolet resonance Raman (UVRR) is a powerful tool for studying structure and dynamics of proteins since the 1980s.15 However, despite its signal enhancement, around 5 orders of magnitude higher as compared with the one of normal Raman scattering, the sensitivity of UVRR is still below that required to monitor proteins in biological concentrations. Spectroscopy techniques such as Raman/UVRR, NMR require pure samples to perform the analysis, which imposes additional experimental challenges. Identification and quantification of proteins in complex biological fluids, such as blood, is normally performed by using immunological techniques. These methods are based on the exquisite specificity of antibodies for their target proteins. Labeled antibodies provide a means to selectively mark a specific protein so that it can be isolated, quantified, or visualized. Among the immunological methods, the most common technique is the enzyme-linked immunosorbent


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assay (ELISA).16 An enzyme, that can react with a colorless substrate to produce a colored product, is covalently linked to a specific antibody that recognizes the target antigen (protein). If the antigen is present, the antibody-enzyme complex will bind to it, and the enzyme component of the antibody-enzyme complex will catalyze the reaction, generating the colored product. The presence of the colored product and its intensity indicates the presence of the antigen and its concentration, respectively. ELISA can quantify amounts of less than one nanogram of a protein. However, it is expensive, time-consuming, and usually monoplex. If the presence of a given protein needs to be detected in a pool containing a myriad of other proteins, Western Blots (WB)17 can be used as well. In general, the sample is run electrophoretically on a sodium dodecyl sulfate (SDS) polyacrylamide gel and then separated proteins along the gel matrix are stained with labeled antibodies. As in the case of ELISA, the WB method is tedious, lengthy and expensive. Biochemical determinations are often performed in tubes or gels. However, most proteins display their function as part of the physical structure of a cell or tissue. In this context, the use of fluorescence-labeled antibodies provides a powerful method for localizing the target protein within biological context under a fluorescence microscope.18, 19 Although the use of fluorescence for bioimaging, and related advantages or disadvantages, will be discussed later, in general, the low spectral structure and broadness of the bands in fluorescence spectra significantly limits the number of color-labels that can be used simultaneously. Among several other alternative methods, in recent years, surface-enhanced Raman scattering (SERS) spectroscopy20 has emerged as an excellent choice for the detection, quantification, and characterization of proteins. Herein, we will discuss the late developments in SERS technology with special emphasis on the quantification and characterization of proteins as


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well potential application. To outline conceptual highlights however also the detection of other biological molecules will be described in the form of selected examples.

Surface-enhanced Raman scattering (SERS) spectroscopy The application of nanostructured materials toward the development of novel detection techniques with improved sensitivity and/or simplified and faster applicability has rapidly become an appealing alternative to other technologies. Among them, SERS is a powerful analytical technique that has already proven to be particularly effective in chemical biology and medicine.21,

22

Essentially, SERS can be described as the amplified Raman scattering by the

presence of a plasmonic structure (most often metallic nanostructures) in the close vicinity of the target analyte. In such a case, the main cause of the excitation of the molecular vibrational levels is the collective oscillation of the conduction electrons in the metal, upon excitation with the appropriate light, which generates an ultra-strong electromagnetic near-field in the proximity of the nanostructure surface (known as localized surface plasmon resonances, LSPRs). As Raman scattering, SERS provides a complex spectral pattern that contains all the compositional and structural characteristics of the target analyte with an extreme experimental flexibility. SERS can be carried out over a wide spectral range, is insensitive to water and, in many cases, requires no sample preparation. Recent spectacular advances in nanofabrication techniques fueled the development of a large variety of rationally designed SERS substrates with optimized, uniform, and reproducible response.20 This successfully translated the spectacular analytical potential of SERS to reliable, widely accepted, and commercially viable sensing applications. The dependence of LSPRs with parameters such as size, shape, composition, and surrounding medium provides multiple possibilities for tuning the optical response and thus, optimizing the


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SERS performance of the plasmonic nanostructure for a specific application. In conjunction with the control of the signal amplification provided by the optical enhancer, a key step in the practical implementation to sensing applications (including SERS) is the appropriate chemical functionalization of the “bare” metallic (i.e. plasmonic) surface necessary to impart the required selectivity and/or sensitivity towards the target analyte, especially in complex media. Three design approaches are commonly used to devise plasmonic nanostructures as SERS sensing platforms: (i) direct SERS; (ii) indirect SERS; and, (iii) SERS-encoded particles. These approaches will be discussed in detail below and are briefly summarized in Table 1. The selection of one or another heavily depends on the type of application and the expected output results.


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Table 1: Overview of different sensing strategies to detect proteins using SERS and examples described in the article SERS approach

Advantages

Challenges

Applications & approaches

Reference

I) Direct SERS sensing

In general, is the simplest way of SERS application

The complexity of the matrix (Raman signals) may impair the efficiency of the analysis

Direct SERS ultradetection

24-31

In general, requires the isolation of the sample

Combines the ultrasensitive competences of SERS, with the direct acquisition of the vibrational spectrum of the protein

Typically, the target analyte should be close contact with the plasmonic materials

Direct SERS detection by capillary-driven surface-enhanced Raman Scattering

34-35

Direct detection of targets

Direct SERS by metal NPdeposited 2 D nanosheets

45-47

Usually carried out with biomacromolecules with high specify and affinity for their targets

23

Low SERS cross-section of proteins

37-39

Single-molecular detection level Time, and cost for a quantification assay needed for the clinical practice

II) Indirect SERS sensing

Indirect detection of targets (by the spectroscopic alterations in the chemoreceptor SERS spectrum upon binding the target protein)

Cross-contaminations of other species should be avoided For the target protein the chemosensor should be present at high affinity and selectivity

Multiplex ability In general, indirect SERS sensing produce less complex and enhanced Raman signals compared with those of direct SERS sensing methods

In general, the chemosensor needs to present a high SERS cross-section to permit the determination of the proteins in minute amounts

56- 62 64- 68

Internal labeling with molecular springs.

82-87

External labeling with molecular beacons.

Colloidal particles functionalized with the chemosensor require colloidal stability in the environment of interest

Great potential and efficiency

Typically, ultradetection of large molecules is limit due to present small SERS activity

III) SERS encoded particles (SEPs)

Potential for HTS multiplexed measurements of proteins in biological matrices.

Maintenance of the colloidal stability

SEPs on liquid samples

93 98-106

Elicit aggregation in biological fluids Possible integration microfluidics

on

chips

or

Potential to generate big libraries of encoded NPs High photostability

122-127

Avoid leaking of the SERS probe Functionalization / bioconjugation

Imaging of cells and tissues with SEPs

Reproducibility of SERs signals in biological fluids

Allow NIR excitations (suitable for cell sand tissue) Good contrast and sensitivity Potential of multiplexing imaging Conjugation with, aptames, nucleic acid, antibodies, etc. is possible. providing specificity and selectivity of target


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Direct SERS sensing Direct sensing is the simplest way of SERS application. In this approach, the SERS spectrum of the target analyte, in close contact with the plasmonic material, is directly acquired. Direct sensing combines the ultrasensitive capabilities of SERS, down to the single molecule detection in some cases, with the direct acquisition of the structural information contained in the vibrational spectrum of the protein. Direct SERS presents two major limitations for protein analysis. The first is related to the low SERS cross-section of proteins.23 The second is associated with the intrinsic complexity of the matrix (i.e. biological fluids such as blood, saliva, cell, tissue lysates, etc.), where the target protein is usually present at a low concentration (~pg/mL) versus the myriad of other components present in the fluid. Regardless, the direct sensing of proteins presents still several key applications such ultra-sensitive detection in purified samples and the subsequent characterization of protein conformation and dynamics under biological conditions.

Direct SERS ultra-detection. In general, SERS ultradetection of proteins requires the isolation of the sample, in the same way as previously discussed for other conventional techniques such as XRD, NMR, or UVRRS. In the case of SERS, however, concentrations of the analyte can be decreased by several orders of magnitude, facilitating the processing of the sample, while observation can be achieved at conditions not far from the biological ones in conventional instruments that use visible or near-infrared (NIR) lasers. In fact, single molecule detection has been demonstrated with a variety of proteins including hemoglobin,24 green25 and yellow26 protein, cytochrome C,27, 28 horseradish peroxidase,29 abrin,30 EGFR,31 and others. In


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most of the cases, this single-molecule level of detection is achieved by adding the resonance Raman (RR) enhancing effect of the protein to the regular electromagnetic enhancing factor provided by the plasmonic material in SERS. This phenomenon, called surface enhanced resonance Raman scattering (SERRS), requires the overlapping of the highest occupied molecular orbital and lowest unoccupied molecular orbital (HOMO-LUMO) band of the protein, the localized surface plasmon resonance (LSPR), and the excitation laser.32 Unfortunately, although most of the proteins present their HOMO-LUMO bands at the UV, the most effective plasmonic materials, gold and silver, present their LSPR from the blue to the NIR region.33 Ultrasensitive detection can be also achieved by using extremely efficient plasmonic nanostructures that can amplify the Raman signal several orders of magnitude as compared with conventional colloids or thin films. Examples of this can be found in the ultradetection of Creutzfeldt-Jakob disease (CJD) prions with nanorod supercrystals (Figure 2A,B),34, 35 or the detection of small bifunctional proteins that bind two particles.36 In the first case, CJD prions have an extraordinary affinity for gold due to the presence of the -Met-Lys-His-Met- fragment that promotes a strong coordination with the plasmonic surface. This, together with the increase in the electromagnetic field due to the strong plasmonic coupling in the colloidal supercrystal, allows for the determination and further classification of the CJD prions in the pM regime in complex biomixtures such as serum (Figure 2C-L). The second case is based on the generation of an interparticle gap (electromagnetic hot spot) sandwiching the target protein. This situation, however, is only feasible when proteins fulfill the following conditions: (i) amino acids with great affinity to gold or silver (i.e. Cys, Met, Hys or Lys) must be exposed at the surface of the protein; (ii) these molecular moieties must be available for reaction with the plasmonic surface; and (iii) their relative positions in the protein must be close enough to yield small gaps with


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strong electromagnetic coupling (normally ≤ 2 nm), while effectively bridging the nanoparticles (NPs). Notably, these requirements necessary for the direct ultradetection of proteins, in either of the methods, are very restrictive and, thus, only of use with a very limited number of targets.

Figure 2. Scanning electron microscopy (SEM) images of the (A) edge and (B) top view of a nanorod supercrystal. Schemes showing the prion mutation and detection limits in bovine serum. (C) Biologically active (PrPC α-helix) and (D) scrambled (PrPSC β-sheet) prions; the fragment corresponding to 106–126 peptide is highlighted in green. SERS spectra of (E) PrPC α -helix and (F) PrPSC (scrambled). (G–K) Detection limits of PrPSC∶PrPC (1∶99) in bovine serum at 10−6, 10−7, 10−8, 10−9, and 10−10 M in total prion, respectively; and(L) bovine serum. Adapted with permission from ref. 35. Copyright 2011 National Academy of Sciences.

Direct SERS detection for serum protein biomarkers can be realized by capillary-driven surface-enhanced Raman Scattering (SERS)-based microfluidic chips without the isolation of proteins.30 As shown in Figure 3, a micropillar array substrate was etched and coated with a gold


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film by a microelectromechanical system (MEMS) process, allowing for integrating into a lateral flow test strip. A series of abrin solutions with various concentrations were detected by the prepared microfluidic chip. Results showed that the correlation between the abrin concentration and SERS signal was linear within the range of 0.1 ng/mL to 1 µg/mL. This microfluidic chip design enhanced the operability of SERS-based immunodiagnostic techniques, significantly reducing the complication and costs of preparation as compared to previous SERS-based works. Meanwhile, this design proved the superiority to conventional lateral flow test strips in respect of both, sensitivity and quantification and exhibits great potential in the diagnosis of abrin poisoning as well as on-site screening of abrin-spiked materials. Gucciardi and co-workers

37

recently reported an elegant alternative to generate highly

active plasmonic clusters in suspension that efficiently trap biomolecules at the interparticle gaps. The authors exploited the radiation pressure as the optical force to locally promote aggregation of gold nanorods in buffered solutions of proteins such as Bovine Serum Albumin (BSA) and Lysozyme (Lys), enabling their detection in the µg/mL range. Interestingly, the SERS fingerprint of protein bridging gold nanoparticle dimers has also been exploited for monitoring the change in the interparticle distance that takes place when the linker protein is exposed to strongly enhanced electric fields.38


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Figure 3. Capilary-driven SERS-based microfluidic chip for the detection of abrin. (A) schematics of a lateral flow test strip with integrated micropillar chip; (B) SEM picture of the micropillar array; (C) SERS detection results; and, (D) standard linear curve between the SERS signal and the concentration of abrin. Adapted with permission from ref. 30. Direct SERS detection could also be performed by metal NP-deposited 2 D nanosheets.39 As shown in Figure 4, a breath analysis approach based on a surface-enhanced Raman scattering (SERS) sensor was developed to detect volatile organic compound (VOC) biomarkers associated with gastric cancer. This example demonstrates, that detection can be extended from proteins to other biologically relevant molecules. Utilizing hydrazine vapor adsorbed on a graphene oxide (GO) film, a clean SERS sensor was prepared by in situ formation of gold Ns on reduced graphene oxide (RGO). RGO could selectively adsorb and enrich biomarkers from breath, and the Au NPs dispersed on the RGO remarkably enhanced the SERS signal of the adsorbed biomarkers. The approach has successfully distinguished different simulated breath samples and


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200 breath samples of clinical patients including healthy persons, early and advanced gastric cancer patients with a sensitivity of higher than 83% and a specificity of more than 92%.

Figure 4. Schematic picture of a SERS sensor and overview of the processes involved in the breath. Adapted with permission from ref. 39. Copyright 2016 American Chemical Society.

Protein conformation and dynamics. As previously mentioned, direct SERS offers a methodology for the characterization of protein dynamics and conformational changes under different biological conditions. It is important to note that, for this class of studies, ultradetection is not the goal, although, in many cases, investigations are performed at the nM level (or below). First approaches for elucidating the conformation of proteins date from the late eighties but extend until today.40-45 These works built upon the surface selection rules previously determined by Moskovits’ group using small molecules.46, 47 Essentially, within this approach, the normal Raman spectrum of a protein is compared with its SERS spectrum. In SERS, the relative intensity of a given vibrational mode has a close dependency with the electromagnetic surface vector (perpendicular to the plasmonic surface). Thus, those modes aligned with the surface


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vector will be further enhanced as compared with those perpendicular to it. With this idea in mind, a close comparison between the Raman and SERS spectra gives rise to a reasonable picture of the orientation of the target analyte on the plasmonic surface (Figure 5A).46, 47 These basic static studies of surface orientation have been evolved in dynamic studies of the allosteric transitions of proteins as a function of temperature48 (even at the single molecule level),49 radiation,50 pH,51 metallic ion concentration,52 redox conditions,53 or even the presence of other proteins and cofactors.45,

54

Nowadays, SERS elucidation of the dynamics of conformational

changes is refined by coupling the experimental spectroscopy with molecular simulations (i.e. molecular dynamics),12 which largely facilitates the interpretation of the vibrational-structural correlation enlightening the biological role of the specimen under study.53-55 For example, surface-enhanced Raman spectroscopy along with molecular dynamics simulation has demonstrated the possibility of understanding drug binding to therapeutic proteins (Figure 5B).

Figure 5. (A) (a) Normal Raman spectrum and molecular modelling of cytochrome C (10-3 M). SERS spectra (10-6 M) and molecular modelling of cytochrome C on (b) a bare Au nanohole


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array, (c) a positively charged surface (−NH2), and (d) a negatively charged surface (−COOH). The arrows indicate the directions of the dipole of cytochrome-C. Adapted with permission from ref. 43. Copyright 2007 American Chemical Society. (B) SERS study of the specific binding of felodipine (a drug for high blood pressure) to Aurora A (kinase). (a) SERS spectrum of Aurora A (black) and Aurora A complexed with felodipine (red). The change in position of modes and the appearance of new modes are indicated by blue arrows in A, while amide I bands are highlighted in the inset. (b) Conformational clustering histogram generated from molecular docking of felodipine to Aurora A. Red arrows represent the conformations of felodipine bound to the hinge pocket (first site), whereas black arrows represent binding over the N-terminal pocket (second site). (c) The bound configuration of felodipine to Aurora A. The residues colored in grey are in hydrophobic interaction with felodipine. Felodipine is hydrogen bonded to Aurora A through residue Tyr-212 (dotted line). The carbon, oxygen, nitrogen, and chlorine atoms are colored in yellow, red, blue, and green, respectively. The inset shows the felodipine (blue) attached to the surface of Aurora A near the hinge region. Adapted with permission from ref. 54. Copyright 2014 National Academy of Sciences.

Indirect SERS sensing Although it has been demonstrated that direct SERS characterization of proteins may offer excellent tools for structural biology, most of the times this method requires the purification of the targets. This clearly increases the complexity, time, and cost for a quantification assay as required in the biochemical characterization or the clinical practice. A possible solution for measuring proteins directly in their biological matrices relies on the functionalization of the plasmonic materials with chemical species (chemoreceptors) displaying high binding affinity and specificity for the target protein.23 In this approach, detection is determined by the spectroscopic alterations in the chemoreceptor SERS spectrum upon binding the target protein.56 Thus, the concentration of a given analyte is indirectly obtained through the observation of the spectral changes induced by the analyte on the chemosensor attached to the plasmonic surface. For other analytes, especially ions and other small molecules, indirect SERS is carried out with thiol or amino-dyes as chemoreceptors. In such cases, the measurable vibrational change in the chemosensor is closely related to the electronic redistribution in the chromophore structure upon complexation with the analyte.57-61 Notably, for the quantification of large


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macromolecules such as proteins directly in their biological matrixes, some basic conditions need to be met. First, the chemosensor must present a high affinity and selectivity for the target protein to avoid cross-contaminations of other species present in the crude solution. Also, the chemosensor needs to present a high SERS cross-section that will permit the determination of the proteins in minute amounts. Finally, but not less important, the characteristics of plasmonic surface should be considered. Colloidal particles functionalized with the chemosensor require maintaining their colloidal stability in a very demanding environment with high viscosity and ionic strengths.62 Although many small molecules can selectively recognize proteins (i.e. estrogens and thyroid hormones, hormones, α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid or muscarinic and nicotinic acids), very few examples can be found in the literature where they have been employed as chemosensors for indirect SERS sensing. For example, Alzheimer amyloid oligomers have been quantified by exploiting the affinity of these proteins for Al3+, which was previously coordinated to 4-mercaptobenzoic acid.56 Further, the folate receptor has been studied by using mixtures of folic acid and 4-aminobezenethiol.63 In both cases, vibrational changes of the chemosensor upon complexation with the protein relied on the relative change of the orientation of the molecule versus the plasmonic surface, which is discussed in detail bellow. Most commonly, indirect sensing is usually carried out with biomacromolecules with high specify and affinity for their targets (i.e. peptides, antibodies or aptamers). Although this approach offers the best alternative in terms of selectivity and affinity,64-66 these large molecules are often characterized by a remarkable small SERS activity, which severely limits their application for ultradetection. Regardless, many alternatives have been developed to address this problem, which all rely on the covalent conjugation of a small molecule with a high SERS crosssection to the biomacromolecular chemosensor. Broadly speaking, the SERS-active small


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molecule can be either (i) conjugated to one of the terminal moieties of the receptor to undergo a structural modification upon the biorecognition event that results in a change of its SERS spectral pattern (internal labeling); or (ii) anchored to the biomolecule at a site which drastically modifies its position with respect to the metal surface as a consequence of the target interaction thus leading to a detectable change of the absolute SERS intensity (external labeling). Internal labeling with molecular springs. In the case of internal labeling, the SERSactive small molecules act as a bridge between the plasmonic surface and the chemosensor, and they are referred to as molecular springs. The molecular spring are usually aromatic thiols with a para substitution that allows the conjugation of peptides, antibodies or aptamers employed as chemosensor.64,

67, 68

Since the target size is usually enormous as compared with the

chemosensor, the conjugation imposes the reorientation of the molecular springs as compared with the plasmonic surface, giving rise to a large set of different perturbations on the SERS spectra of the molecular springs, ranging from subtle shifts of the vibrational features67 to the appearance of new bands.68 To approach the challenge of interpreting such variations, the example of the quantification of the oncoprotein c-MYC is useful (Figure 6). In this case, the chemosensor is composed by 4-mercapto-N-methylbenzamide (MMB) coupled with a synthetic peptide (H1) known to have an extraordinary affinity and selectivity for c-MYC (the corresponding complex is referred to as MB-H1).69, 70 Figure 6A shows the Raman and SERS spectra of MMB, and the SERS spectra of MB-H1 before and after the complexation with c-MYC. The comparison of the four spectra is informative about the constraints imposed by the molecular orientation and the electric field polarization at the surface. This lays the foundation for the vibrational analysis of the functional MMB group incorporated into the macro MB-H1 structure, before and after the


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interaction with the target. The SERS spectra of MMB and MB-H1 display similar vibrational patterns, but with some differences in relative intensities. This result points toward a slight change of the molecular orientation of the mercaptobenzene group on the silver surface, when it is coupled with a larger molecule as H1, in full agreement with the surface selection rules.46, 47 Such perturbation is exacerbated upon binding with the very large protein C-Myc. Assuming a slightly simplified C2v symmetry for the mercaptobenzene group, the vibrational modes can be classified into in-plane (ip) a1 and b2 modes and out-of-plane (oop) a2 and b1 modes. On the other hand, considering that the surface electric field, , effectively has only a normal component (Z direction in Figure 6B),71 the intensity of a vibrational mode is proportional to the square of scalar product of the electric field and the dipole moment derivative of the mode, ∕ .72 ∝

= cos

(1)

Hereby α is the angle between and ∕ . We define θ as the tilt angle of the z-axis of the mercaptobenzene unit with the surface normal (Z), and χ as the twist angle of the molecular plane around the z-axis (which is 0° when y is parallel to the surface). Then, by considering that the ip a1 and b2 modes have dipole moment derivatives along the z- and y-axes, respectively, and the oop b1 modes have dipole moment derivatives perpendicular to the phenyl ring (along the xaxis), the molecular-fixed axis system xyz can be correlated with the experimental axis system XYZ by the two Eulerian angles θ and χ. The intensities of a1, b1 and b2 can be then represented as follows from equation (1):73, 74 ∝

(2)

∝ !" χ

(3)

∝ !" !" χ

(4)


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Hereby I0 represents the intrinsic intensity of the corresponding mode without the surface effects (i.e., normal Raman spectrum). Thus θ+90º, which describes the angle Ag-S-C, and χ, which describes the orientation of the phenyl ring against the silver surface, can be calculated as follows: %" χ = %" θ =

&'( & * ')

(5)

&') & * '( &') & * ,)

(6)

&,) & * ') -./ ( 0

Finally, by assigning the bands to their vibrational modes as a1 (1022 cm–1, ip CCH deformation), b2 (1075 cm–1, ip CCH deformation), and b1 (756 cm–1, oop CCH deformation)754 and substituting their corresponding intensities from the Raman and SERS spectra (Figure 6A) in equations (5) and (6), the variation of the angles can be inferred (Figure 6C). For MMB, the low intensity of the oop CCH deformation indicates a perpendicular orientation of the ring against the surface. This is consistent with the obtained value for χ close to 90º. Notably, the addition of H1 to MMB decreases this value slightly. Importantly, this effect becomes remarkable when MB-H1 interacts with c-MYC because of its massive size (57 kDa). In the case of the Ag-S-C angle, θ+90º, MMB shows a value of 166º, consistent with the experimental data,76, 77 which decreases, pushing the ring against the surface, as H1 or c-MYC are present. Similar approaches have been used for the determination of α-fetoprotein and Glypican-3,78, serum albumin,79 p53 and EGFR80 or A1AT.81


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Figure 6. (A) Raman spectrum of MMB and SERS spectra of MMB, SiO2@Ag@MB-H1, and SiO2@Ag@MB-H1 in presence of c-MYC. (B) Model used in the estimation of the molecular orientation and the directions of dipole moment changes of a1, b1, and b2 modes. Experimental and molecular systems are represented by XYZ and xyz axes, respectively. (C) Variations of the molecular orientation of the phenyl ring with respect to the surface, χ, and the angle Ag-S-C, θ+90º, for MMB, SiO2@Ag@MB-H1, and SiO2@Ag@MB-H1 in presence of c-MYC. Adapted with permission from ref. 68. Copyright 2016 American Chemical Society.

External labeling with molecular beacons. Classically, molecular beacons (MBs) are fragments of nucleic acids with a stem-and-loop structure doubly labeled with a fluorophore and a quencher group on each end. In the absence of targets, MBs act as switches that are normally closed by the stem part (in the “off” position) without observed fluorescence background because of quenching. However, upon binding with their targets, conformational changes in the MB open the hairpin, and fluorescence is turned “on”. MBs are characterized by simple operation and high sensitivity and specificity.82 By substituting one of the fluorophores by a plasmonic surface, either a NP or a thin film, the SERS signal of the other fluorophore can be monitored as a function of the MB interaction with the target. This approach has been demonstrated by the analysis of DNA/RNA,83-85 small molecules,86, 87 and ion metals. Although it has not been extensively applied for proteins, the few examples available in the literature


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predict a huge potentiality also in the application to these targets. For example, the quantitative detection of cytochrome C was achieved with a triplex switch DNA structure bound to gold NP films (Figure 7A).88 In this case, the thiolated oligonucleotide conjugated with a SERS-active molecule (carboxy-X-rhodamine, ROX) forms a rigid triplex structure on the gold surface with a thrombin-binding aptamer. In the presence of cytochrome C, the aptamer binds the protein promoting approximation of the ROX to the plasmonic surface with the subsequent increase of SERS intensity. More complex systems, comprising more than one plasmonic surface, have been also designed. Common in all of them is the presence of NPs already functionalized with a SERS code that increases its signal as it is collapsed against another plasmonic surface due to the presence of the target protein. Examples of this are the detection of mucin with coded gold nanospheres on gold nanorods (Figure 7B),89 prostate specific antigen (PSA) with coded gold nanospheres on bigger gold spheres,90 or aflatoxin B1 with coded gold nanospheres on gold nanostars.91 Finally, complex plasmonic constructs that generate ultrastrong electromagnetic hot spots have been also developed. A beautiful example of that is the fabrication of NP tetramers using aptamers selective for the target protein as the NP linkers.92 The simplest version of this configuration uses just one selective aptamer, giving rise to detection limits at the attomolar regime for PSA (Figure 7C). In a more complex configuration three of the NPs are coded with three different Raman labels and each of them is linked to another nanosphere without coding with an aptamer selective for a different target (Figure 7D). When one of the proteins is present, the naked NP collapses close to the corresponding coded NP. Notably, if two of the target proteins are present, the naked NP approaches both of the corresponding coded spheres, giving rise to two different SERS signals that identify the presence of each of the protein targets. Analogous behavior is followed when three of the target proteins are present.


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Figure 7. (A) Schematic illustration of the aptasensor based on a triplex switch for SERS detection of cytochrome C. Adapted with permission from ref. 88. Copyright 2012 Royal Society of Chemistry. (B) Scheme of the SERS aptasensor for the detection of Mucin-1 based on Au nanorod–AgNP core–satellite assemblies. Adapted with permission from ref. 89. Copyright 2015 Royal Society of Chemistry. (C) Scheme of AgNP tetramer self-assembled by DNA frame for SERS analysis of biomarkers. Ag-tetramer-mediated singlet SERS assay for PSA, AgNPs were modified with 4-adenosine triphosphate, PSA aptamers were inserted in each side of DNA frame. (D) SERS encoded multiple Ag-tetramer for the triplex detection of biomarkers (PSA, thrombin, and mucin-1). Three AgNPs in each tetramer were modified with aminothiophenol (ATP), nitrothiophenol (NTP) and methoxybenzyl mercaptan (MATT), respectively, and three selective aptamers were inserted in three sides of the DNA frame, respectively. Adapted with permission from ref. 92. Copyright 2015 Willey-VCH.

SERS encoded particles Besides the most traditional direct and indirect strategies for SERS, an increasing interest nowadays originates in the design of so-called SERS encoded particles (SEPs), which integrate multiple SERS applications into single plasmonic NPs. Typically, SEPs are hybrid materials consisting of a plasmonic core encoded with specific molecules, with a high SERS cross-section, and enveloped in a protective shell that provides both biocompatibility and colloidal stability,


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and targeting function. Thus, in this case, SERS identifies a functionality added onto the surface of the NP, typically an antibody or aptamer, by the SERS spectrum provided by the plasmonic core and the encoding molecule.93 SEPs show great potential for high-throughput multiplexed measurements of proteins in biological matrices. These NPs can be applied either in liquid samples or solid tissues. Further, SEPs allow for their integration on chips or microfluidics. SEPs on liquid samples. Since the pioneering concept of using SEPs for the analysis of biomolecules,94,

95

both the complexity and application of SERS encoded NPs have notably

increased within the scope of proteomics.96 In liquid solutions, SEPs are commonly used to monitor and quantify the presence of dissolved proteins and cells through their corresponding membrane protein receptors. Notably, since the SERS spectrum of a SEP does not change upon reaction with its target, usually direct detection of proteins by SEPs in solution is not possible. Thus, as the most common alternative, protein quantification is performed emulating fluorescent immunoassays.97 In a typical configuration (Figure 8A), one or several capture antibodies or aptamers are immobilized on a solid support acting as a reactive strip. Then, the reactive strip is contacted with the fluid of interest, where the target proteins (if present) will bind their correspondent capture antibodies or aptamers. In the last step, the reacted target proteins are exposed upon immersion of the reactive strip into a solution containing all the correspondent detection antibodies attached to the SEPs. The presence and quantification of the target proteins is demonstrated by the presence of the SERS signal assigned to the corresponding detection antibody or aptamer and its intensity, respectively.98 This approach can be modified by, for example, depositing the capture moieties on encoded NPs, exposing these NPs to the solution and, after reaction with the target proteins, exposing them to the detection antibodies or aptamers labeled with a fluorophore. Notably, this method can be either implemented on reactive strips99


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(Figure 8B) or, if the NPs are large enough to be individually discerned, by an optical microscope, in solution100,

101

(Figure 8C). Note, that in this later case, the NPs need to be

cleaned by sedimentation or centrifugation before the SERS readout, in order to avoid false positives due to the excess of fluorescent labels. One way to bypass the cleaning, thus improving the readout speed while simplifying the system, consists in depositing the capturing moieties on magnetic NPs while the detection moieties are deposit on the SEPs. In this way, after applying a magnetic field, the magnetic-plasmonic aggregates induced by the presence of the proteinic antigen can be separated and studied by SERS (Figure 8D).102

Figure 8. (A) Cartoon of the sequence of steps required for conducting a typical multiplexed assay using encoded particles functionalized with aptamers. Adapted with permission from ref.98 Copyright 2010 Willey-VCH. (B) Identification of pathogen antigens by Raman spectroscopy in tetraplex assays. (a) optical microscopy images of the self-assembled array; (b) fluorescent readout of the same array, to visualize which beads are bound to their target antigen; and, (c) identity of the beads by Raman spectroscopy and thus the target pathogen, as determined from the barcode (the colors corresponding to the barcode were assigned arbitrarily). Adapted with permission from ref.99. Copyright 2008 Willey-VCH. (C) (a) Fluorescence emission spectra of


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AF 594 and AF 488, bound to the antibody (Ab) and the antigen (Ag), respectively. (b) SERS spectra of benzenethiol (BT), nitrobenzenethiol (NBT), and hydroxybenzenethiol (HBT) upon excitation with a 785-nm laser line. (c) Images from a small area of the substrate with a random distribution of encoded capsules. The leftmost image is an optical micrograph, while the other three are SERS mappings obtained by illumination with the three different laser lines, as indicated. Adapted with permission from ref. 100. Copyright 2009 American Chemical Society. (D)Detection of the Tau protein by using a combination of SEPs and magnetic NPs labelled with selective antibodies. The presence of Tau in the solution cross-links the SEPs with the magnetic particles. After application of a magnetic field, all magnetic particles are removed from the solution, the SERS mapping of the magnetic materials reveals the presence of the of the Tau protein due to the presence of the linked SEPs. Adapted with permission from ref. 102. Copyright 2013 American Chemical Society.

Notably, due to the small size of soluble proteins with respect to the SEPs, all the previous examples require extra labeling (i.e. fluorescence, magnetism, positional encoding on a surface, etc.) to demonstrate the reaction between the NP and the target. However, SEPs can be used as well to identify and quantify the presence of bigger objects such as prokaryotic and eukaryotic in biofluids. In this scenario, the positive event is defined by the presence of SERS signals when analyzing the cells due to the specific complexation of the SEPs (upon functionalization with the appropriate antibodies or aptamers) on specific bacterial or cell protein-based membrane receptors.103-105 Recent advances in the microfabrication have led to the development of novel microflow systems for bio-particle separation and analysis. Implementation of microfluidics and SEPs provides the ability to manage and integrate chemical and biological components into a single platform, offering the opportunity for developing portable, autonomous, and disposable devices capable of performing real-time detection, unprecedented accuracies, and simultaneous analysis of different analytes in a single device.106 Regarding the field of bacterial detection and quantification in the diagnostics of infectious diseases the goal is the identification of the infectious agent by complete bypassing of the cultivation step, allowing for drastic decrease in the diagnosis time. Thus, posteriorly to the


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reaction of SEPs with their respective bacteria, first approaches relayed in the concentration of the SEP-bacteria complex before the SERS analysis, mostly based on microfluidic dielectrophoresis (DEP),107-111 where non-uniform electric fields are exerted on dielectric particles, including cells and microorganisms, to control their location. For example, E. coli coated with SEPs was captured and concentrated on a nanoelectrode array placed at the bottom of a microfluidic chip (Figure 9A).109 The SERS signal was successfully measured during DEP capture with a single colony forming unit (cfu) sensitivity in buffered solutions. Typically, the bacteria and antibody-SEP solutions were mixed together and incubated overnight at 4 °C. Then, several centrifugation/washing cycles were applied to remove the excess of unbound SEPs, before the analysis. Bacteria detection was also successfully performed in more complex media spiked with 5 × 105 cfu/mL E. coli cells. Further, DEP microfluidic devices have been developed for trapping individual microorganisms in a defined location in space for their in situ interrogation with a confocal micro-Raman system.110 Here, buffered suspensions of two bacteria (Salmonella enterica and Neisseria lactamica) were mixed and incubated with SEPs for 1 h at room temperature, before being submitted to multiple centrifugation/washing cycles to eliminate unbound NPs prior to DEP−Raman analysis. The practical detection limit with a 10 min measurement time was estimated to be 70 cfu/mL, while the total assay time including sample pre-treatment was less than 2 h. Alternatives based on three-epitope detection scheme have been developed to avoid the antibody-antigen binding failures that may occur in the one-epitope setup, thus, improving the detection specificity and signal enhancement by reducing the missbinding.111 Here, three different SEPs are conjugated with three monoclonal antibodies binding to three different membrane receptors. Buffered suspensions of E. Coli, pre-concentrated via a DEP-microfluidic device, are then incubated with the SEPs. SERS analysis is performed on


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droplets of sample solutions placed on a gold-coated microscope slide. Under this set-up, only SERS signals consisting of the superimposed contributions of the different SEPs are associated with positive recognition events, reporting detection limits down to 1 cfu/mL. Although the issue of sensitivity has been addressed by some of these methods, only small volumes (~microliters) of samples, which are normally not relevant for clinical diagnosis, can be investigated in a rational amount of time. Notably, in all the previous examples, mixing the bacteria with the antibody-functionalized SEPs induce the accumulation of the SEPs at the bacteria membrane. Thus, by designating an especial SEP with a small coating and a small number of antibodies per NPs is possible creating dense arrays of inter-particle gaps on the surface of a given bacteria (Figure 9B). This scheme allows for the generation of highly efficient electromagnetic hot spots in which the SERS signal is exponentially amplified by several orders of magnitude relative to the dispersed particles. Under this scenario, the sample can be directly pumped through a microfluidics channel, where a backscattered detecting laser continuously monitors

the

liquid

stream,

therefore

removing

the

need

of

time-consuming

centrifugation/washing cycles prior to the SERS analysis. In fact, positive events associated with a NP-coated cfu traversing the laser focus generate SERS intensities well above the background of dispersed encoded NPs. For demonstration three different bacteria (S. aureus, E. coli, and S. agalactiae) were quantified at a pace of 13 minutes per mL of blood or serum and at concentrations ranging from units to tens of cfu/mL, with results consistent to those of the conventional bacterial culture.105, 112


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Figure 9. (A) (a) Outline of the DEP capture of the bacteria coated with SEPs for Raman detection. A representative TEM of E. coli attached with SEPs is also included. (b) Optical microscope image taken under 4× magnification, showing the microfluidics channel and the active square at the center. (c) SERS intensity from the samples with the bacterial concentrations


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in the 5 to 1.0 ×109 cfu/mL range (DEP capture time = 50 s). The inset shows a 100 µm diameter laser focal spot aligned with a 200 µm × 200 µm active DEP area. Figure adapted with permission from ref. 109. Copyright 2015 Royal Society of Chemistry. (B) (a) Conceptual view of microorganism detection system. Antibody-conjugated SEPs (1) are mixed in a vessel with the sample fluid (2). The presence of one of the targeted bacteria promotes the accumulation of the corresponding antibody-matching SEPs on its membrane until full coverage is achieved, generating electromagnetic hot spots (3). Then, the mixture is circulated through a millifluidic channel with a pump (4) and investigated with a 785 nm laser (5) to record the SERS signal (6). (b) System performance for contaminated blood samples and comparison with bacterial cultures. The blood sample was spiked with a combination of three different bacteria and concentrations (S. aureus, E. coli, and S. agalactiae). Top: Correlation was calculated between a temporal series of spectra collected over 270 ms intervals and the SERS reference of the SEPs. Large correlation values reveal the passage of an individual cfu. Middle: Bacterial cultures (24–48 hours) for the microorganism inoculated in the blood samples (white spots correspond to cfu). Bottom: Comparison of the bacteria concentrations (cfu/mL) as determined by the optical system (open squares) for the sample contaminated with three pathogens versus traditional cultures (open circles). Averages over three runs of both MODS and culture experiments are shown by the corresponding solid symbols. Figure adapted with permission from ref. 112.

Similar demonstrations have been carried out on eukaryotic cells. Although still not so many, in the recent years, these analyses are gaining special relevance for the quantification of circulating tumor cells in liquid biopsies. Since the seminal article by Natan’s group,113 only a few works reported the detection of circulating tumor cells (CTCs) by using SERS encoded NPs.114-119 All of them employed SEPs with a spherical gold nucleus functionalized with different chemosensors (antibodies, aptamers, or small molecules). Very recently, the determination of CTCs on SERS-microfluidic chips was proposed, using a flow-focusing device and SERS encoded NPs comprising polydispersed silver NP aggregates (Figure 10).120,

121

While

significant improvements were obtained in terms of automation of CTC detection, the achieved sensitivity remained very far from that required for real applications. Overall, the current body of work is limited to our knowledge to no more than three membrane markers (insufficient for reliable diagnostics) and was performed solely on lab solutions (blood samples spiked with known amounts of a specific type of CTCs), rather than on real samples. The detection schemes


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are discontinuous, largely complex, and with slow turnaround, which makes them unsuitable for rapid and automated diagnosis. Thus, further efforts will be required to transform the SERSmicrofluidic techniques into a device with utility in real life for cancer diagnosis. We propose that these efforts should be oriented into the generation of a new family of encoded particles with increased electromagnetic efficiency, while preserving homogenous signals for quantitative determination; and, into the development of new sorting microfluidic devices with the ability of screening large volumes of sample (at least 8 mL) in a convenient time.


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Figure 10. (A) Graphical depiction of a microfluidic device for circulating tumor cell detection with SERS. Cells, prelabeled with a cocktail of SEPs containing cancer-specific NPs and a control are injected into the device, where they are flow-focused before passing through the Raman laser. An image of the flow focusing device is shown, where the buffer solution has been dyed in green, while the polystyrene particles have been labelled in orange. (B) The upper panel shows the principal component (PC1) scores for spectra from two data sets (SEP-labeled cancerous and normal cells, green dots; and unlabeled noncancerous cells, black dots), returned by the gating principal component analysis (PCA) model generated to gate spectra showing peaks associated with SEPs (high scores on PC1) over those showing only spectral contributions


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associated with polydimethylsiloxane (PDMS) of the chip (PC1 scores around 0). A gating threshold (red horizontal line) was chosen based on the upper 95% confidence limit of the gPC1 scores and was adjusted manually depending on the signal/noise of the spectra around that value. The lower panel shows a series of spectra collected over approximately 2 s, corresponding to the time fraction highlighted in the yellow box in the upper panel. Spectra associated with events below the gating threshold, showing only PDMS-related bands, are depicted in black, and spectra with SEP-associated peaks and PC1 scores above the gating threshold are shown in red. Figure adapted with permission from ref. 120. Copyright 2015 American Chemical society.

Imaging of cells and tissues with SEPs. The most popular technique for imaging of protein receptors in cells and tissues is by far confocal fluorescence aided by dye-labeled antibodies.62 Confocal fluorescence is capable of imaging the area of sample in milliseconds with an adequate spatial resolution. However, this technique, as fluorescence spectroscopy, suffers from broad and low structured spectral features. Thus, in confocal fluorescence typically only three or four different dyes can be used, in order to reduce cross-talk in-between the different channels. In contrast, imaging with SEPs offers virtually an unlimited number of different codes that could be used simultaneously, thus, paving the road of real multiplex imaging.122 SERS imaging with SEPs has been extensively used in the characterization of cells with special emphasis in those related with cancer.123 In fact, SERS imaging allows not only for the qualitative localization of ther SEPs in the membrane124,

125

but also for quantitative

determination126-128 of those protein-based receptors (Figure 11).129 Also, SEPs have been used for the visual study of the protein dynamics with in a living cell126, 130 and for the classification and phenotyping of cells in a complex mixture.128, 129 Analogously, to the cell imaging, during the last 10 years many protocols have been standardized for the SERS imaging of tissues. These techniques are of special relevance in cancer as many of them emulate the conventional immunohistochemistry diagnosis (Figure 12).128, 131, 132 Further, SERS has been extended to the bioimaging of tumors in living animals,133,

134

and recently some approaches are being


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developed for real time imaging of tissues during surgical interventions, allowing thus the surgeon to make fast decisions based on the knowledge of the nature of the tissue in real time.135137

Figure 11. (A) Schematic diagram and Raman spectra for the preparation of SEPs. A color was assigned to a non-overlapping peak from each SERS spectrum as follows: Blue: AuNR/Ag/4MBA/anti-EpCAM; Red: AuNR/Ag/PNTP/anti-IGF-1 Receptor β; Green: AuNR/Ag/PATP/anti-CD44; and, Magenta: AuNR/Ag/4MSTP/anti-Keratin18. Abbreviations are as follows: 4MBA: 4-mercaptobenzoic acid, PNTP: p-nitrobenzoic acid, PATP: paminobenzoic acid, 4MSTP: 4-(methylsulfanyl) thiophenol, AuNR: gold nanorods and AuNR/Ag: silver coated gold nanorods. (B) Schematics of breast cancer cell surface targeting by the four SEPS and the SERS detection technique. (C) Schematics of 2D multi-color SERS data correlation with the SEPs distribution on the cell surface. Figure adapted with permission from ref.129


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Figure 12. SERS imaging, with 0.5-mm spatial resolution, of tumor-xenograft specimens stained with a mixture of three SEPs (EGFR-NPs, HER2-NPs and isotype-NPs). (A) Photograph of resected tumor xenografts and normal tissue. (B) A multiplexed image generated by overlaying the ratiometric images of EGFR-NPs/isotype-NPs (plotted with a green color-map) and HER2NPs/isotype-NPs (plotted with a red color-map). Images showing the concentration ratio of (C) EGFR-NPs/isotype-NPs and (D) HER2-NPs/isotype-NPs. The bottom plots show the correlation between the SERS measurements of a particular tissue specimen (in C, D) and the corresponding fluorescence ratio from flow-cytometry experiments with the cell lines used to generate the various tumor xenografts. The scale bars represent 2 mm. Figure adapted with permission from ref. 128.


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Unfortunately, in contrast to confocal fluorescence (sample image is acquired simultaneously), conventional Raman systems perform images point by point (or line by line in the modern Raman instruments) with the subsequent delay in the image acquisition. Further, the necessity of concentrating the laser on a small area of the sample, defined by the focusing objective, may damage the sample. Thus, the parameters, such as wavelength and power of laser and spectral acquisition time, play important roles in Raman images. Thus, the strategies based on fluorescence combining with SERS can improve the time and reduce the sample exposure to the laser.138-141 This alternative allows for the fast localization of the area of interest with fluorescence and then a deeper study of that area with SERS. In general, SEPs are poised to make a deep impact on cellular imaging, including in immunohistochemistry due to their narrow and complex spectral features. However, to fully extract their enormous potential further advances in hardware, software and nanofabrication are required. First, Raman systems capable of global imaging of large areas while maintaining the spectral resolution would allow for a considerable increase in the acquisition speed. This, can also be supported with more brilliant NPs that can be imaged at ms temporal resolution. Finally, software would be of equally importance. To take the maximum advantage of the multiplexing potential of SEPs the spectral images need to be deconvoluted to generate the real composition of the global spectra. SERS detection has been used for in vivo real time Raman imaging of cancer cells and drug delivery.142 As shown in Figure 13, anticancer drug (mitoxantrone, MTX) conjugated gold nanostars were used for efficient plasmonic-tunable Raman/Fourier transform infrared (FTIR) spectroscopy imaging, to simultaneously evaluate the anticancer drug scattering and the Raman scattering molecular vibration signals in living cells. This system directly tracked in real-time the delivery and release of an anticancer drug from gold nanostars in single living cells and in mice


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(healthy and lung cancer mice models), revealing a strong accumulation in the heart of healthy mice 5 min after administration and infiltration in the tumor site of lung cancer mice 5 h after systemic injection. This in vivo SERS detection method holds a great promise for image-guided cancer chemotherapy. In order to improve the read-out, novel SERS nanoantennas were developed. Gold NPs with 90 nm in diameter were prepared and modified with DTTC(3,3'Diethylthiatricarbocyaniniodid) Raman reporter, and then entrapped by poly(ethylene glycol) (PEG) polymers and conjugated with a food-and-drug administration (FDA) permitted antibodydrug conjugate -Cetuximab (Erbitux (R)) - that specifically targets EGFR and turns off a main signalling cascade for cancer cells to proliferate and survive. Resultant Cetuximab-SERS gold nanoantennas presented a high Raman signal both in cancer cells and in mice-bearing xenograft tumours. Moreover, the Raman detection signal exhibited simultaneously extensive tumor growth inhibition in mice, making these gold nanoantennas good candidates for cancer nanotheranostics.143


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Figure 13. In vivo FTIR and SERS detection of mitoxantrone-nanostars (MTX-NS) in a lung cancer mice model (n = 6 animals). (A) Bioluminescent imaging of C57BL/6 mice bearing human Calu-1 xenograft tumor with luciferase activity as a measure for the tumor burden. (B) ATR-FTIR imaging of the lung tumor tissue for mice treated with MTX-NS. Arrows represent tumoral clones in the lung. Attenuated total reflection Fourier transform infrared spectroscopy (ATR-FTIR) imaging of the lung tumor tissue of mice treated with MTX-NS after 0.5 (C) and 5 h (D) after administration are shown. The scale bars correspond to 200 mm. (E) SERS mapping image showing a laser beam focusing on the anatomical location of the lung tumor tissue (400 mm × 400 mm) based on the intensity of the band at 1573 cm-1. (F) SERS spectra obtained from three different tumor tissue sites (a, b and c). SERS spectra were measured at 785 nm excitation with 2-s signal integration. The spectra were background subtracted and shifted for better visualization. The colors and letters of the spectra correspond to the colors in (E). The highlighted band at ~1300 cm-1 is a characteristic band of the MTX-NS, associated with aromatic C-C stretching of the MTX. Adapted with permission from ref. 142. Copyright 2016 Elsevier.


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Epidermal growth factor receptor (EGFR) gene mutation is very general for patients with lung cancer, and is closely associated with the sensitivity to small-molecule tyrosine kinase inhibitors (TKIs). Sea-urchin-like Au NPs were prepared with an average diameter of ca. 90 nm, composed of 15-nm nanospikes.31 Due to the abundant sharp nanospikes, the enhancement factor was 1.97×107. After sea-urchin-like Au NPs were modified with crystal violet (CV), PEG, and EGFR mutation specific antibody, the resultant nanoprobes exhibited excellent SERS activity. Also, targeting of EGFR mutation sites on lung cancer cells was achieved. The SERS signal intensity at 1617 cm−1 of CV was linear correlated with the number of H1650 lung cancer cells, and the detection limit was 25 cells/mL suspension. SERS measurement based on sea-urchin-like Au NPs were an efficient method for EGFR mutation detection in lung cancer cells, and could predict gene typing of clinical lung cancer. SEPs have been developed for simultaneous targeted imaging, tumor boundary identification, and photothermal therapy. EGFR monoclonal antibody-conjugated Au@Ag nanorods decorated with 5,5'-Dithiobis-(2-nitrobenzoic acid), DTNB, (EGFR-Au@AgNR SEPs) were prepared and characterized.144 In vitro experiment showed that EGFR-Au@AgNR SEPs could target and enter into gastric cancer MGC803 cells. The silver nano-film layer on the surface of the gold nanorods remarkably enhanced the SERS signal, photoacoustic imaging efficacy, and photothermal conversion efficiency of the nanorods. As observed in Figure 14, in vivo experiments showed that the SEPs could actively target gastric cancer cells at 2 h postinjection. They distributed in the tumor site, exhibited enhanced SERS signals to display clearly tumor boundary, and enhanced photoacoustic imaging to display clearly tumor boundaries.


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Figure 14. (A) SERS spectra of AuNPs, Au@AgNRs, EGFr-Au@AgNRs mix with 5,5'Dithiobis-(2-nitrobenzoic acid) (DTNB) under 1 W/cm2 laser irradiation: (a) animal control; (b) Au NPs; (c) Au@AgNPs; (d) gastric control; and (e) EGFR-Au@AgNPs in gastric cancer tissues (collection time 30 s). (B) MGC803 gastric cancer-bearing nude mouse model. (C) Tumor site under 1 W/cm2 laser irradiation. (D) Collected tumor tissues for nude mice models. Figure adapted with permission from ref. 144

Conclusions and Outlook SERS technology provides a novel emerging chance for the quantification and characterization of proteins, speeding up their exploration of structure and function, while developing novel non-labeled medical diagnosis technology. Nanostructures such as gold or silver colloids, 2D nano-sheets, etc. can markedly enhance the Raman scattering signal of proteins, down to the single molecule detection level in some cases. The potential molecular mechanism is associated with LSPR and the formation of hotspots. Up to date, novel strategies such as direct SERS detection, indirect SERS detection, and SERS-encoded nanoparticle-based detection have been reported. Their potential in applications such as SERS imaging of in vivo tumor biomarkers and SERS quantification detection of protein biomarkers has been positively explored. To date, many of the existing literature still demonstrate concepts in lab samples with few reports associated to the SERS detection of proteins in biological conditions. However,


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although the single and multiplex detection of relevant proteins in real biofluids and solid samples (tissues) is still challenging, field advances at high velocity, with many new discoveries almost at a daily basis. In summary, although SERS technology for protein quantification and characterization faces many challenges, SERS combined with nanotechnology has exhibited attracting technological prospects, and will dramatically advance our ability to understand the chemical biology of proteins while developing novel series of SERS-based technology, which will eventually help to promote the application of SERS in other fields.

AUTHOR INFORMATION Corresponding Author E-mails: [email protected]; [email protected] Notes The authors declare no competing financial interest. Acknowledgements This work was funded by the Spanish Ministerio de Economia y Competitividad (CTQ201459808R), the Generalitat of Catalonia (AGAUR 2014 054), the HM Hospitales Group and the German Research Foundation (DFG project DFG PA 794/28-1). N.F. acknowledges funding from the Swedish Governmental Agency for Innovation Systems (Vinnova). .


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