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Feb 28, 2017 - Raman Scattering CO-Nanotags for Logical. Multiplex Detection of Vascular Disease-. Related Biomarkers. Tianxun Gong,. †,#. Zi-Yao Ho...
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Optical Interference-Free Surface-Enhanced Raman Scattering CO-Nanotags for Logical Multiplex Detection of Vascular DiseaseRelated Biomarkers Tianxun Gong,†,# Zi-Yao Hong,⊥,# Ching-Hsiang Chen,‡ Cheng-Yen Tsai,⊥ Lun-De Liao,§ and Kien Voon Kong*,⊥ †

State Key Laboratory of Electronic Thin Films and Integrated Devices, University of Electronic Science and Technology of China, Chengdu, 610054, P. R. China ‡ Sustainable Energy Development Center, National Taiwan University of Science and Technology, Taipei, 10607, Taiwan § Institute of Biomedical Engineering and Nanomedicine, National Health Research Institutes, 35 Keyen Road, Zhunan, Miaoli Country, 35053, Taiwan ⊥ Department of Chemistry, National Taiwan University, Taipei, 10617, Taiwan S Supporting Information *

ABSTRACT: Matrix metalloproteinases (MMPs), specifically MMP-2, MMP-7, and MMP-9, have been discovered to be linked to many forms of vascular diseases such as stroke, and their detection is crucial to facilitate clinical diagnosis. In this work, we prepared a class of optical interference-free SERS nanotags (CO-nanotags) that can be used for the purpose of multiplex sensing of different MMPs. Multiplex detection with the absence of cross-talk was achieved by using CO-nanotags with individual tunable intrinsic Raman shifts of CO in the 1800−2200 cm−1 region determined by the metal core and ligands of the metal carbonyl complex. Boolean logic was used as well to simultaneously probe for two proteolytic inputs. Such nanotags offer the advantages of convenient detection of target nanotags and high sensitivity as validated in the ischemia rat model. KEYWORDS: surface-enhanced Raman spectroscopy, biosensors, nanotags, nanopillars, metalloproteinases, stroke, vascular diseases

T

of vascular diseases. Rapid and sensitive detection of multiple MMPs is crucial to diagnosing stroke to not only expedite prognosis but also shed light on treatments and therapies for strokes. Although various methods have been used for MMP detection, surface-enhanced Raman spectroscopy (SERS) has proven to be a promising tool for chemical sensing. SERS-based biosensors have several advantages over SPR biosensors, including (i) labelfree detection, (ii) excellent reproducibility, (iii) more reliable, multiplex capabilities due to Raman spectral fingerprinting, and (iv) much higher sensitivity.9,10 The Raman signals of probes anchored onto gold or silver nanostructured surfaces can be enhanced by several orders of magnitude (typically 106−1014). This signal enhancement has been the basis for chemical sensing

he increasing incidence of stroke has mainly been attributed to the increasing aging human population. However, stroke is no longer a disease of the elderly working adults are just as susceptible. Stroke occurs when the blood supply to an area of the brain is interrupted. Permanent brain damage and even death may result due to a lack of oxygen delivery to brain cells.1,2 Therefore, early diagnosis and prompt treatment better ensure the survivability of the patient. Studies have found that matrix metalloproteinases (MMPs), specifically MMP-2, MMP-7, and MMP-9, play significant roles in the degradation of extracellular matrix components and changes in cell-to-cell interactions.3,4 Their association with vascular disease, tumor growth, invasion, and metastasis has been a hot topic for healthcare professionals and researchers alike.5 MMP-9 has been found in elevated plasma levels in ischemic stroke, suggesting its involvement in the pathogenesis of brain ischemia, and it could be an indicator of ischemic conditions.6,7 A relationship between MMP-2, MMP-7, and chronic stroke lesions has also been reported.8 Therefore, MMPs are closely correlated with a variety © 2017 American Chemical Society

Received: February 2, 2017 Accepted: February 28, 2017 Published: February 28, 2017 3365

DOI: 10.1021/acsnano.7b00733 ACS Nano 2017, 11, 3365−3375

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Figure 1. (A) Infrared spectra of tungsten, molybdenum compounds and CO-nanotags. (B) SERS spectra of CO-nanotags. (C) The syngenic effect of bonding of the CO ligand to a metal atom. (D) SERS spectra of CO-nanotags over 7 days in 10% serum: magenta = MoCO-, aqua = WCO-, red = Mopph3CO-, green = Wpph3CO-, and blue = WPCy3CO-nanotags.

applications at lower concentrations at better detection limits,11 as exemplified in DNA detection,12 and intracellular molecule detection.13 DNA detection works by the detection of SERS signal of the phosphate backbone of DNA with an iodidemodified silver nanoparticle, resulting in detection of DNA with single-base resolution.12 Intracellular hydrogen sulfide (HS) detection with 4-acetamidobenzenesulfonyl azide functionalized gold nanoparticles has been demonstrated by both the Li group and Long group, and showed high sensitivity and excellent selectivity for HS.13 However, to date, no SERS-based probe for the highly sensitive multiplex detection of multiple MMPs (i.e., MMP-2, MMP-7, and MMP-9) has been reported. The absence of such a platform is partly due to the easy masking of Raman signals of reporter molecules by other contributions such as other biomolecules in the fingerprint region of 400−1800 cm−1. In addition, multiplex detection of these biomarkers can allow clinicians to monitor multiple biomarkers and establish any relationship between them, thus facilitating accurate diagnoses. One potential solution to the problem of interference is the use of metal carbonyl-based probes.14−16 The application of metal carbonyl compounds in biological settings already covers a

wide range of applications, from biological immunoassay and bioimaging to metal-based pharmaceuticals and CO therapy (CO release molecules).17−23 A particularly functional characteristic of metal carbonyl compounds is the strong CO stretching vibrations in the mid-IR (1800−2200 cm−1), a region relatively free of interference from the absorbance of biomolecules. One recent application making use of this characteristic is live cell imaging, which uses a metal carbonyl-nanoparticle (MC-NP) conjugate as an SERS probe.14 It is sufficiently sensitive to track the usually small concentrations of MMPs present during the early stages of stroke. This study is the demonstration of using metal carbonyl conjugate nanotags on an SERS-based platform to ensure a logical multiplexed detection of MMPs that is efficient, rapid, and sensitive and will significantly enhance diagnosis of vascular diseases.

RESULTS AND DISCUSSION Molydenum and Tungsten Carbonyl-Based CO Nanotags. We considered carbonyls of two types of inexpensive metal: tungsten and molybdenum. Abstraction of halide from Cp(CO)3MoX (X = halide) leads to surface-bound CpMo3366

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Figure 2. (A) (left to right) TEM image of MoCO-nanotags, TEM image of aggregated MoCO-nanotags, SEM image of leaned nanopillars, and SEM image of MoCO-nanotags clustered on leaned nanopillars. Scale bar: 100 nm. (B) Simulated electric field distribution of powder nanoparticles and nanopillars. (C) SEM images of nanopillars with CO-nanotags and schematic representation of the interaction of nanotags on nanopillars. Scale bar: 100 nm. (D) CO intensity enhanced by formation of nanotag, aggregated nanotags, and clustered nanotags on nanopillars. 3367

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ACS Nano (CO)3, which has been studied using a range of in situ techniques.24−27 In our case, surface-bound CpMo(CO)3 on gold nanoparticles was observed. The CO stretching region of the IR spectrum showed that the bands due to starting material (2038 and 1966 cm−1) had been cleanly replaced by two peaks at lower frequencies (1959 and 1878 cm−1) (Figure 1A). The IR spectra of the CO nanotags displayed a lower frequency, indicating a weakened C−O bond resulting from the binding of metal carbonyl compounds onto gold nanoparticles. As the CO signal is a sensitive probe for coordinating the geometry of compounds, the molecular structure of the metal carbonyl compounds bound to the gold nanoparticles remained similar to those envisaged by the same IR band pattern. A similar reaction was observed for CpW(CO)3I, where the CpW(CO)3 unit was bounded on the nanoparticle surface, as evidenced by the CO stretching (2028 and 1930 cm−1 shifted to 1947 and 1859 cm−1). Both CO nanotags showed distinct SERS signals in the ∼2000 cm−1 region (MoCO nanotag = 2028 (s) and 1,949 (w) cm−1 and W CO nanotag = 2023 (s) and 1947 (w) cm−1 (s = strong; w = weak)) (Figure 1B). However, these CO peaks were not optimum for multiplex detection due to the closeness of the peaks. The CO in the metal carbonyl was a sensitive probe for the electron density on the metal center. The CO position of the metal carbonyl was inversely correlated with the strength of the π bond between the metal and carbon (Figure 1C). An increase in electron density on a metal center led to greater back π-bonding to the CO ligands.28 As more electron density was pumped into the formally empty carbonyl π* orbital, the C−O bond was weakened; this, in return, increased the strength of the M-CO bond by making it more like a double bond. Thus, to increase the electron density on the metal center, we replaced a CO ligand with a phosphine ligand, which was a σ donor ligand on the tungsten and molybdenum compounds (CpW(CO)2PPh3I and CpMo(CO)2PPh3I). Compared with the CO ligand, the triphenylphosphine (PPh3) was a stronger sigma donor but a weaker π-acceptor ligand (Figure 1C). The IR CO signals of both phosphine compounds were evidently blue-shifted (CpMo(CO)2PPh3I = 1961 and 1881 cm−1 and CpW(CO)2PPh3I = 1950 and 1862 cm−1) due to the increased back π-bonding ability of the metal center to the CO ligands. As shown in Figure 1B, both (Mopph3CO nanotag = 1962 (s) and 1882 (w) cm−1 and Wpph3 CO nanotag = 1955 (s) and 1876 (w) cm−1) showed distinct SERS signals in the lower field region compared with the Mo CO and WCO nanotags. We used a multiplex assay to measure multiple analytes simultaneously in a single run. Using the same principle to fine-tune the CO signals of metal carbonyls, it is possible to perform multiplex sensing with more than two targets in an optical interference-free region. According to the Tollman plot, tricyclohexylphosphine (PCy3) is a stronger σ donor than PPh3.29 As depicted in Figure 1B, CpW(CO)2PCy3I conjugated on the gold nanoparticles to form Wpcy3 CO nanotags, leading to SERS CO signals in a lower field, and the CO peaks in the IR spectrum shifted further down to the lower field and showed a distinct SERS signal at ∼1900 cm−1 (1927 (s) and 1856 (w) cm−1). We have demonstrated that organometallic chemistry could be used to fine-tune the SERS nanotag signal. We also tested the stability of the CO nanotags in serum. Any signs of decomposition of the metal carbonyl on the gold nanoparticle surface would have easily been picked up as a change in the CO signal intensity. In the presence of serum, we observed no significant change in the characteristic CO vibrational peaks (Figure 1D). As the TEM images show (Figure

2A), the CO nanotags were well dispersed and showed no aggregation even after 30 days. However, the CO nanotags with bulky phosphine ligands had low signal intensities of ∼20% (Figure 2D). The steric effect of the ligands PPh3 and PCy3 might have been the main cause, which also decreased the binding ability of the metal center to the gold nanoparticles. Even so, the signal-to-noise ratio was still high overall. MoCO, Wpph3CO, and Wpcy3 CO nanotags were ideal candidates for the application of multiplex detection, where interfering cross-talk between CO signals could largely be avoided. Consequently, signals could be identified easily. SERS Properties of CO Nanotags. Nanoparticle aggregation of noble metals is attractive for SERS sensors due to the strong electromagnetic field enhancements that arise at the interparticle junctions upon interaction with visible radiation. We functionalized one of the CO nanotags (the MoCO naontag) with biotin and mixed them with MoCO nanotags that functionalized with NeutrAvidin, and observed an aggregation of MoCO nanotags (Figure 2A). The CO nanotags exhibited a greater increase in intensity of the SERS CO stretching vibration signal when the CO nanotag aggregation took place. As depicted in Figure 2D, the CO intensity of all of the CO nanotags increased by six orders of magnitude (MoCO = 6.7 × 106, WCO = 7.2 × 106, Moppph3 CO = 3.2 × 106, Wpph3CO = 3.6 × 106, and Wpcy3CO = 1.1 6 × 10 ). We used a SERS-active substrate to further enhance the CO intensity of the CO nanotags. Previous demonstrations showed that freestanding nanopillars coated with either gold or silver could act as effective SERS substrates.30,31 Here, we present the use of nanopillar substrates. A gold-coated nanopillar (gold coated on the nanopillar and its base) was used because of its relative stability and because it was not easy to oxidize as silver. We functionalized the nanopillar with NeutrAvidin-thiol and incubated it with the mixture of biotin- and NeutrAvidin-CO nanotags. Figure 2A depicts the nanotags aggregated and clustered around and in between the nanopillar structures, achieving an even higher SERS enhancement of the CO. Nanopillars are known to form microsized nanopillar clusters by leaning toward one another due to the surface tension between them during incubation and washing.31,32 In Figure 2B, a simulated electric field distribution of the nanopillar shows that the size of the hot spot increases when the nanotags cluster with the nanopillar. Compared with nonaggregated and aggregated CO nanotags, the aggregation of CO nanotags on the nanopillar led to an approximate 2-fold enhancement due to the combination of hot spots from the nanotags and nanopillars. The nanoparticles remained clustered on the nanopillars over time, and could still be observed in the same state even after six months. The interaction of nanotags with the top oval structure layer before the nanopillars leaned was a plausible mechanism for the nanoparticles clustered on the oval layer, which involved the size of the clustered nanoparticles and the leaning effect of the nanopillars. We did not observe any single nanotag trapped with the leaned nanopillar. Instead, we observed only clustered nanotags trapped with the postleaned nanopillars, perhaps because the nanopillars were brought to lean when the clustered nanoparticles were trapped at the nanopillar. Nontrapping nanoparticles were also observed (Figure 2C) due to the direct interaction of nanotags with the base of the nanopillar substrate. We expected the corresponding SERS signal of the nontrapping nanoparticles to be lower than that of the clustered nanoparticles trapped in the postleaned pillars, as evidenced by the simulation 3368

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Scheme 1. Schematic for the Cleave-and-Bind Mechanism for the Logical Multiplex Detection of MMPs on Nanopillar Chip

able to separate nanoparticles from aggregation.33,34 The MMP substrate peptide−PEG is cleaved only in the presence of the corresponding MMP enzyme. This allows for binding between the biotin-NeutrAvidin of the nanotag and the now exposed nanotags. As demonstrated in the MMP-2 detection, the population of the hydrodynamic radius increased in as soon as 10 min after adding MMP-2 protease (Supporting Information, Figure S1). The coverage density of the peptide−PEG was also estimated. As the peptide−PEG reached its peak at 1220 cm−1 (CH2 twisting vibrations of PEG, Supporting Information, Figure S2), we were able to use this peak to measure the concentration of PEG from unreacted peptide−PEG molecules left behind in the process (supernatant). The unreacted amount was used to substrate the original amount of peptide−PEG. The average numbers of peptide−PEG per nanotag were 1310 ± 430, 1250 ± 300, and 1210 ± 230 for the MMP-2-MoCO, MMP7-Wpph3CO, and MMP-9-Wpcy3CO nanotags, respectively. The coverage of peptide−PEG was less than the reported value33,34 because part of the surface of the gold nanoparticle was already covered with molybdenum and tungsten compounds and biotin. To improve specificity, respective MMP substrate peptide− PEGs were also immobilized on a nanopillar chip. Therefore, the binding of nanotags to the chip depended on the cleaving event on the nanotags and chip. The distribution of the peptide−PEGs on the nanopillar chip was examined by SERS mapping of the strong Raman peak originating from the PEG. The SERS mapping of the distribution of the peak intensity of the peptide−

results. Due to the combination of hotspots of both the nanotags and nanopillars, the EM field was 4.5-fold (nonaggregated nanotags) and 1.67-fold stronger than that of the nontrapping nanoparticles (Figure 2B and Supporting Information, Figure S3; nanotags vs nanotags clustered on the nanopillar). When the extent of the nanoparticle aggregation greatly increased, the CO signal further increased, due mainly to an increase in the SERS effect of the nanoparticle-clustered nanopillars caused by a thick nanoparticle layer that formed on top of the nanopillars (Figure 2C). Multiplex Detection with Functionalized CO Nanotags and Nanopillar Substrate. Relying on the advantages of the nanoparticles and nanopillar substrates, we developed a lowvolume and highly sensitive SERS-based biosensor used for the multiplex detection and quantification of MMPs. A nanopillar substrate 0.3 cm × 0.3 cm in size was used for the assay (Figure 5A(ii)). This size of substrate can provide 3000 sample spots for measurement (with laser spot size of ∼1 μm2) and requires only 5 μL of a sample volume to cover the surface of the substrate for biosensing. We used a cleave-and-bind mechanism for multiplex detection (Scheme 1). The MoCO, Wpph3CO, and Wpcy3CO nanotags were conjugated with biotin and NeutrAvidin, upon coating with MMP-2, MMP-7, and MMP-9 substrate peptidePEG, respectively. In the absence of MMPs, biotin, and NeutrAvidin functionalized CO nanotags were unable to bind to each other due to their conjugated MMP substrate peptide− PEG. The molecule weight of PEG is 20 000 kDa, which makes it 3369

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Figure 3. (A) Bright-field image of nanopillar chips and SERS mapping images. (Scale bar = 10 μm). (B) SEM images: (i) leaned nanopillars, (ii) MMP-2 substrate peptide-MoCO-nanotag clustered with nanopillars, (iii) MMP-7 substrate peptide-Wpph3CO-nanotag clustered with nanopillars, (iv) MMP-9 substrate peptide-Wpcy3CO-nanotag clustered with nanopillars, (v) logical “OR” detection, and (vi) logical “AND” detection. (Scale bar = v100 nm).

PEGs on the chip is shown in red in Figure 3A. Clear PEG and peptide peaks were observed, indicating successful conjugation of the MMP substrate peptides on the nanopillars. This mapping result confirmed that the respective peptide−PEGs were distributed uniformly on the SERS substrate. In contrast, the PEG peak intensity disappeared after incubation of the substrate with the respective MMP enzymes, indicating a majority of the peptide had already been cleaved by the enzyme. CO nanotags were incubated on a nanopillar chip; as a result, we observed a strong CO signal. As shown in Figure 3B, large amounts of COnanotags trapped within nanopillars were observed for MMPs (Figure 3B,ii−iv) and logical detection (Figure 3B,v,vi). This is further support of the postleaned nanopillars mechanism in which nanopillars are brought to lean before clustered COnanotags trapped at the nanopillar tips. The specificity of the nanotags was also tested; however, the spectrum for the peptide−PEG signals remained unchanged when the nanotags were incubated with nonspecific enzymes and other potential interfering substances such as glucose, bovine serum albumin,

and thrombin. Moreover, the detection of MMP enzymes was assessed in the presence of potential interfering substances. The recovery range was calculated at >80% (MMP-2:91%; MMP7:87%; and MMP-9:82%), revealing acceptable selectivity.35 The results indicated that the nanotags and nanopillars had a pronounced selectivity for MMP-2, MMP-7, and MMP-9 enzymes over the other species tested. Boolean Logic Detection for Monitoring Biomarkers of Acute Ischemic Lesions and Chronic Lesions. MMP-9 is known to be expressed after stroke and mainly increases in acute ischemic lesions,36 whereas MMP-2 and MMP-7 have been shown to increase in chronic lesions.8,34 In this study, the cleaveand-bind mechanism was extended to logical multiplex detection, as a potentially useful approach to monitoring stroke recovery. In the logical “OR” system, a clustering of nanotags on the nanopillar structures, actuated in the presence of MMP-9 (biomarker for acute ischemic lesions) and the proteases of either MMP-2 or MMP-7 (biomarkers for chronic lesions). This was accomplished by synthesizing tandem MMP-2-MMP-7 3370

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Figure 4. (A) Spectra and images output of logical detection. (B) Simultaneous detection (“AND”) of various concentration of MMP-2, MMP-7, and MMP-9 in the presence of 1% of serum. (C) Plot represents the intensity of CO stretching frequency: (red ●) MMP-2, (magenta ■) MMP-7, and (green ▲) MMP-9.

Table 1. Comparison of Various Biosensors method

[1] fluorescence

[2] upconversion FRET

[3] optical refractivity

[4] electrochemical

[5] SERS

[6] SERS

MMPs LOD (ng/mL) detection range (ng/mL) time (min) ref

MMP-2 2.3 0−3.5 90 40

MMP-2 0.01 0.01−0.5 120 41

MMP-2 and MMP-9 0.17 0.17−264 >120 42

MMP-2 0.00015 0.00015−50 240 43

MMP-2 0.002

MMP-2 and MMP-7

peptide substrates consisting of both cleavage motifs in series. A tandem MMP-2-MMP-7 peptide substrate encoded with a Mo CO nanotag and coated with NeutrAvidin served as a “binder,” and Wpcy3CO nanotags coated with MMP-9 substrate peptide and biotin served as “receptors.” Similarly, the nanopillar substrate was immobilized with respective peptide−PEG and NeutrAvidin-thiol. In the presence of two proteases, MMP-2 (or MMP-7) and MMP-9, the attached tandem MMP-2-MMP-7-peptidePEG and MMP-9-peptide-PEG from the nanotags and SERS substrate could be completely cleaved off, thus allowing for nanotag−substrate interaction. Spectrally, a dual-peaked CO signal was observed, as also demonstrated in the SERS mapping (Figures 3A and 4A). In the logical “AND” system, a MMP-2, MMP-7, and MMP-9 substrate peptide encoded with MoCO, Wppph3CO, and Wpcy3CO nanotags, respectively, was coated with biotin (serving as the “binder”). Similarly, the nanopillar substrate was coated with NeutrAvidin (serving as the “receptor”). Again, respective MMPs peptide−PEGs were also immobilized on a nanopillar chip to improve specificity. In the absence of any proteases, the respective attached peptide−PEG from the nanotags and the SERS substrate could not be completely cleaved off, preventing interaction. However, in the presence of three proteases (MMP2, MMP-7, and MMP-9), the attached PEG polymers were completely removed, allowing for nanotag-substrate interaction, and subsequently three CO signal peaks from 1900 to 2100 cm−1

180 44

1000−40000 300 45

were observed. Both logical tests therefore served as quick tests to rule out other MMPs and monitor the recovery progress of stroke patients by detecting biomarkers of acute ischemic and chronic lesions simultaneously. To validate our mechanism for enzymatic detection, we conducted a study to detect and quantitatively determine the concentrations of MMP-2, MMP-7, and MMP-9 enzymes in a logical “AND” system. As the concept of quantifying enzyme concentrations is based on how many nanotags are permitted by peptide cleavages to bind onto a nanopillar, the intensity of relevant target CO peaks can accurately indicate the concentrations. No internal standard was used, as the CO nanotags served as a standard for measurement and we compared the different numbers of aggregated nanotags with the same reporter molecules. Foreign-substance MMPs changed the enhancing efficiency of the standard CO signal by changing the extent of the aggregation of the nanotags and the number of nanotags bounded on the nanopillar substrate. As such, the intention was to quantify the “strength of interaction” of the nanotags in the presence of the MMP coating layer and enzyme. We assessed assay recovery for MMPs using standard additions methodology to characterize the performance of the assay in serum (Supporting Information, Table S1). Ten and hundred-fold dilution (as suggested by the literature (1:10)37 and commercial MMPs kits (1:100)) generated a similar level of recovery. The average coefficient of variation (CV) ranged from 4.6% to 5.2%. 3371

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ACS Nano Table 2. Comparison of MMPs Assays Mo

method concn added (ng/mL) concn found (ng/mL) recovery (%) time (hour) mean ± SD (N = 10) CV (%)

CO-nanotag (MMP-2)

Wpph3

CO-nanotag (MMP-7)

Wpcy3

CO-nanotag (MMP-9)

commercial MMP-2 assay

commercial MMP-7 assay

commercial MMP-9 assay

10

10

10

10

10

10

9.2

8.7

8.2

9.1

9.4

9.3

92% 2 5 ± 0.23

87% 2 5 ± 0.47

82% 2 5 ± 0.29

91% 3−6 5 ± 0.13

94% 3.5 5 ± 0.18

93% 3−6 5 ± 0.21

4.6

9.4

5.8

2.6

3.6

4.2

Undiluted serum MMP-2 samples had recoveries of only 31%. The CV was found to be 43% which is beyond the acceptable range of variation (acceptable range: 20%).38 We believed that this is attributed to the low volume of reaction buffer in the samples. A hundred-fold serum dilution was used in subsequent experiments. We observed a positive correlation between the CO peak intensities and enzyme concentrations, as shown in Figure 4B,C. Using this method, we determined that the detection limit of the MMPs was 0.05 ng/mL for MMP-2, 0.05 ng/mL for MMP-7, and 0.1 ng/mL for MMP-9. With reference to the plot, we observed that our platform had a detection range of 0.05−20 μg/mL, which covered the physiological concentration range of MMP-2, MMP-7, and MMP-9 (serum level of MMP-2:100−200 ng/mL, MMP-7:5−10 ng/mL, and MMP-9:320−1,000 ng/ mL).39 We conducted a simple comparison with the literature results (published from 2012 to 2015) on MMP bioassay methods (Table 1). Although methods 1, 2, and 3 had lower limits of detection, our method exhibited a broader detection range that covered the MMP physiological concentrations. Compared with method 4 and other SERS assays (methods 5 and 6), our method had a shorter detection time (120 min) and a greater sensitivity than that of method 6. None of the methods demonstrated used a multiplex detection (≥3) of MMPs. We also compared the precision of our method with that of commercial assays. As shown in Table 2, our method had a similar limit of detection to that of the Elisa assay and an acceptable precision. Plasma from a cortical thrombosis induction (PTI) rat model was used to validate the mechanism of our nanotags. Studies have proposed that the plasma level of MMPs is a useful biomarker for assessing pathological events in the brain. Here, we examined MMPs in blood from the brain using a rat model of acute focal cerebral ischemia to demonstrate the potential practicality of our biosensor. Ischemia-afflicted rats are known to express a higher concentration of MMPs than normal rats.46 We collected plasma 1 h after induced stroke and tested it using our logical “AND” biosensing platform. Three CO peaks with different intensities were obtained from the assay (Figure 5A). For comparison, we performed statistical analysis using one-way analysis of variance, which showed that the expression of MMPs varied significantly. MMP-9 had a high level of expression in the control and stroke objects. Significantly greater expressions of MMP-2 and MMP-9 in the stroke object compared with the control object were observed. Statistical analysis revealed no significant variation in MMP-7 in either object. The samples were also examined using commercial kits and showed consistency with our method. It has recently been reported that the expression of MMP-2 and MMP9 is increased in the brain tissues of the stroke object, as well as in plasma.47 Therefore, we believe that MMP-2 and MMP-9 are potential biomarkers for diagnosis of stroke that not only

Figure 5. (A) (i) Cortical thrombosis induction in rat and (ii) nanopillar chip. (B) Detection (mean ± S.D.) of MMPs from plasma (one-way Anova followed by Tukey test; * = p < 0.05; ** p = 0.01, *** P ≤ 0.001) (n = 6).

expedite prognosis but also shed light on treatments and therapies for strokes. We also evaluated our results with a commercial Elisa MMP assay. The efficacy of CO nanotags in matrix metalloproteinase detection was successfully demonstrated.

CONCLUSIONS We have identified three optical interference-free nanotags that can circumvent spectral cross-talk in a noncompeting region (1800−2200 cm−1). The advantage of using optical interferencefree nanotags allows users to readily isolate the target analyte peak from other nonessential contributions, allowing for robust analysis. It can also sensitively detect MMP-2, MMP-7, and MMP-9 over a wide range of concentrations. Given the complementary advantages of this assay, we envision that metal carbonyls may find promising application in the biomolecular quantification of biocatalytic reactions. The 3372

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ACS Nano

purchased from Nektar Therapeutics for conjugation with the MMP substrate peptide via lysine; 1 mM of MMP2 peptide (G-K-G-P-L-G-VR-G-C-CONH2), 1 mM of MMP7 peptide (GK-G-V-P-L-S-L-T-M-GC−CONH2), MMP2−MMP7 substrate peptide (G-K-G-V-P-L-S-L-TM-Ahx-G-P-L-G-V-R-G-C−CONH2; Ahx is aminohexanoic acid) and MMP-9 peptide (G-K-P-G-C(Me)-H-A-L-C-CONH2) were reacted with PEG in PBS + 0.005 M EDTA pH 7.2 for 24 h. Peptide−PEG substrate was added into the substrate and incubated for 2 h. To prepare the receptor in the substrate, we mixed the substrate (coated with biotin) with NeutrAvidin (5 mg/mL in PBS solution, Life Technologies) for 3 h. After a 3-h incubation period, we washed the substrate with water to remove the excess NeutrAvidin. Electromagnetic Simulation. A Lenovo desktop computer with an Intel(R) Core(TM)2 Quad CPU Q9650 at 3.00 GHz with 8 GB RAM was used to perform high-mesh-density simulations of the nanoparticles. The operating platform was 64-bit Windows 7 Professional. To simulate the plasmonic properties of the gold nanoparticles, we used an RF extended module under COMSOL Multiphysics. The desired particle size and 3D shape were drawn in draw mode using the Cartesian coordinate system. The boundary conditions and perfectly matched layer were also defined in draw mode. Simulation duration for a single nanoparticle took about 4 h. Detection of MMPs. The chip and nanotags were separately incubated with MMP enzyme solution (in the range of concentration of 40−0.00001 μg/mL using buffered solutions containing 50 mM Tris-Cl, 5 mM CaCl2 and 0.005% Brij-35 at pH 7.4.) at 37 °C for 2 h. The chip was then rinsed with water and the nanotags were loaded. After a 0.5-h incubation period, the chip was rinsed again to remove any unbound nanotags, and SERS measurement was performed. Buffer solutions containing 1% serum were used for detection in the presence of serum. For the specificity study, instead of the MMP enzyme, the chip and nanotags were incubated with 1 ng/mL of glucose (Sigmal-Aldrich), bovine serum albumin (Invitrogen), thrombin (Sigmal-Aldrich), or MMP-3 (Sigmal-Aldrich). For the MMPs in plasma, sampled blood was centrifuged at 4500 rpm for 30 min within 5 min, and plasma was collected and stored at −80 °C. The MMP levels in the plasma samples were then used to conduct measurements according to the aforementioned procedure. Estimation of CO Peak Enhancement. We estimated the enhancement of the CO vibration peak intensity by comparing the intensity of the CO peak for the metal carbonyls and the CO nanotags as follows: Enhancement = (Cmetal carbonyl × ICO nanotags)/(CCO nanotags × Imetal carbonyl), where Cmetal carbonyl and CCO nanotags are the concentration and Imetal carbonyl and ICO nanotags are the corresponding normal Raman and SERS intensities for the metal carbonyl and CO nanotags, respectively. For the normal Raman, we estimated the probed volume as a cylinder with a diameter of 25 μm as the diameter of the focused laser and a height of 1 μm as the focus depth of the laser. We estimated the concentration of metal carbonyls in the CO nanotags by using ICP−MS to measure the concentration of molybdenum or tungsten elements from unreacted metal carbonyls left behind in the process (supernatant). The unreacted amount was used to substrate the original amount of metal carbonyls. The amount was divided by the number of gold nanoparticles, which we determined based on the peak optical density and BBInternational UK product data sheet. The number of metal carbonyls per gold nanoparticles was ∼1000 (MoCO nanotags = 1256 ± 350, WCO nanotags = 1230 ± 466, Mopph3CO nanotags = 912 ± 421, Wpph3 CO nanotags = 934 ± 211 and Wpcy3CO nanotags = 789 ± 311). The number of nanoparticles under the focused laser spot was ∼127 (cylinder volume of the focused laser spot, 490 μm3). Using this information, we calculated the concentration of metal carbonyl on the nanoparticles under the focused laser spot. For the Raman measurement (50 mM of metal carbonyl to generate ∼300 Raman counts), the concentration of metal carbonyl was ∼24.5 fmole with the same volume of the focused laser spot. We estimated the enhancement factor by substituting these values into the enhancement equation. Photothrombosis Technique for Focal Ischemia Induction. Male Wistar rats weighing 250−300 g (BioLASCO Taiwan Co., Ltd., Taipei, Taiwan) were used in this study. Six rats were used altogether. All of the experimental procedures conducted were approved by the

positive results from our study using a PTI rat model further demonstrate its feasibility for clinical use.

METHODS General Procedure. All chemical synthesis manipulations were carried out using standard Schlenk techniques under an argon or nitrogen atmosphere. Tungsten and molybdenum compounds were prepared according to the reported procedure: (CpW(CO)3I,48 CpMo(CO)3I,49 CpW(CO)2PPh3I,50 CpW(CO)2PCy3I,51 CpMo(CO)2PPH3I).50 All other chemicals were purchased from other commercial sources and used as supplied. We obtained the IR spectra using a Thermo Scientific Nicolet iS5N FT-NIR spectrometer. The Raman spectral measurements were carried out using a Renishaw In Via Raman (UK) microscope with a Peltier cooled CCD detector and an excitation wavelength at 633 nm, where the laser excitation was directed onto the sample via a 50× objective lens (with a confocal pinhole 25 μm in diameter), and the exposure time was set at 10 s for all of the measurements. All Raman spectra were processed using WiRE 4.3 software. Before each measurement, the instrument was calibrated using the standard Raman spectrum of silicon, whose Raman peak is centered at 520 cm−1. For each sample, 50 SERS spectra were acquired over a 60 μm × 60 μm area with a 10-μm interval (3.5 mW laser power). The average of the 50 spectra was used for analysis. The CO spectra were presented at baseline using a polynomial multipoint fitting function and curve fitting function provided by the Renishaw WiRE 4.3 software. The Raman intensities of the peaks were taken as the height above the baseline. For the SERS mapping, a controlled XY translation stage with a Renishaw inVia Raman microscope was used to acquire 3600 SERS spectra within the scan area of 60 μm × 60 μm with an acquisition grid with a 1-μm step size. The Raman results were also verified using another fully automated Raman system (UniDRON model, UniNanoTech Co. Ltd.). The hydrodynamic size and critical micelle concentration of the prepared micelles were determined using a Brookhaven dynamic light scattering instrument at 90° (632.8 nm) using non-negative least-squares (NNLS) analysis. Transmission electron microscope (TEM) and scanning electron microscope images were recorded on a Hitachi H-7100 and KEOL-JSM-7600F, respectively. The TEM samples were prepared by placing a drop of the nanoparticles onto a carbon-coated Cu grid. Preparation of CO Nanotags. Freshly prepared solutions (100 μM, 1 μL) of metal carbonyl compounds in ethanol were mixed with 60 nm gold colloids (2.6 × 1010 particles/mL, BBInternational UK) in ethanol. After a 2-day incubation period, the excess metal carbonyl was removed by centrifugation (10 000 rpm, 2 min). Shorter incubation periods, incomplete reactions, and excess metal carbonyl typically interfere with the consistency of the SERS CO signal (e.g., site reactions with subsequent incubation material protein or PEG to generate CO species, which have different CO signals that complicate SERS measurement). Thus, to ensure quality control of the CO nanotags, we quantified the number of metal carbonyls bound on the nanoparticles (refer to the “Estimation of CO Peak Enhancement” section). We performed an IR or Raman scan to confirm the binding of the tungsten or molybdenum compounds. The CO nanotag pellet was resuspended in 1 mL of DI water for subsequent bioconjugation. The nanotags were then incubated with 50 μM of biotin-thiol (Nanocs) solution for 30 min. The excess biotin-thiol was removed by centrifugation. Peptide−PEG substrate was added into the solution and incubated for 2 h. To prepare the receptor nanotag, we mixed nanotags conjugated with biotin-thiol with NeutrAvidin (5 mg/mL in PBS solution, Life Technologies) for 3 h. After a 3-h incubation period, we centrifuged the nanotags with water to remove the excess NeutrAvidin. Preparation of Chip. A nanopillar chip was gold coated according to the reported procedure.30,52 The gold mixture was then added on the chip and incubated for 6 h to create a peptide bind on the chip through thiol−gold interaction. The substrate was incubated with 50 μM of biotin−thiol (Nanocs) solution for 30 min. The excess biotin−thiol was removed by washing. Amine-reactive 20 kDa mPEG SMB reagents (methoxy polyethylene glycol-succimidyl α methylbutanoate) were 3373

DOI: 10.1021/acsnano.7b00733 ACS Nano 2017, 11, 3365−3375

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ACS Nano

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Institutional Animal Care and Use Committee of the National Health Research Institutes, Taiwan. The animals were housed at an animal care facility under constant temperature and humidity conditions, and were provided free access to food and water. The animals were anesthetized with isoflurane (1−5% in oxygen flow) for the whole surgery period and α-chloralose (60−80 mg/kg bolus and 25−40 mg/kg/h maintenance, intraperitoneal) accompanied by meloxicam (1 mg/kg, subcutaneous) for the experiential period and mounted on a custom-made, acrylic stereotaxic head holder to reduce motion artifacts. The body temperature of each rat was measured via a rectal probe and maintained at 37 ± 0.5 °C by a self-regulating thermal plate (TCAT-2 Temperature Controller, Physitemp Instruments, Inc., New Jersey, USA). A skin incision was made over the skull to expose the bregma landmark. To facilitate PA imaging and PTI induction, a cranial window approximately 3 mm (AP) × 4 mm (ML) in size, centered at the bregma, was made with a high-speed drill while keeping the dura intact. The interaural line and bregma reference were used to position the rat’s head in the fPAM system in subsequent experiments. Focal ischemia was induced using the photothrombosis method, targeting a selected cortical arteriole, which is a distal branch of the middle cerebral artery at the right hemisphere S1FL cortical region. We injected the photosensitizer Rose Bengal (Na+ salt, R3877; Sigma-Aldrich, Singapore), which was diluted to 10 mg/mL in HEPES-buffered saline, into the tail vein at 0.2 mL/100 g of rat body weight infused over 2 min. The cortical blood vessel selected for occlusion was subsequently illuminated with a 10 mW, 532 nm continuous wave (CW) laser light (MGM-20; Beta Electronics). The CW laser light was focused on the selected cerebral vessel in the right S1FL region for 15 min until a stable clot was formed. The mechanism for clot formation occurred via generation of singlet oxygen (after illumination), which damaged the endothelial cell membrane, resulting in subsequent platelet aggregation and thrombus formation to interrupt blood flow in the selected blood vessel. An ischemic region was then formed, including the irreversibly damaged infarct (ischemic core) and salvageable tissue (ischemic penumbra).

ASSOCIATED CONTENT S Supporting Information *

The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acsnano.7b00733. Dynamic light scattering analysis of nanotags. Additional SERS spectra of MMPs peptide−PEG, simulated electric field distribution, and percentage of recovery of assays in various serum concentrations (PDF)

AUTHOR INFORMATION Corresponding Author

*E-mail: [email protected]. ORCID

Tianxun Gong: 0000-0001-9383-3666 Kien Voon Kong: 0000-0002-5910-6497 Author Contributions #

T.G. and Z.-Y.H. contributed equally to this work.

Notes

The authors declare no competing financial interest.

ACKNOWLEDGMENTS Financial support from Ministry of Science and Technology (MOST), Taiwan (Grant No. 104C3562-1) and National Health Research Institutes (Grant No. 05A1-BNPP15-014) is gratefully acknowledged. REFERENCES (1) Furlan, A. J. Endovascular therapy for stroke  It’s about Time. N. Engl. J. Med. 2015, 372, 2347−2349. 3374

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