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SERS Detection of Ricin B-Chain via N-Acetyl-Galactosamine Glycopolymers Victoria M Szlag, Matthew J Styles, Lindsey Rebecca Madison, Antonio R. Campos, Bharat S Wagh, Dustin Sprouse, George C. Schatz, Theresa M. Reineke, and Christy L. Haynes ACS Sens., Just Accepted Manuscript • DOI: 10.1021/acssensors.6b00209 • Publication Date (Web): 26 May 2016 Downloaded from http://pubs.acs.org on May 28, 2016
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SERS Detection of Ricin B-Chain via N-Acetyl-Galactosamine Glycopolymers Victoria M. Szlag‡a, Matthew J. Styles‡a, Lindsey R. Madisonb, Antonio R. Camposa, Bharat Wagha, Dustin Sprousea, George C. Schatz b, Theresa M. Reineke*a, and Christy L. Haynes*a a. Department of Chemistry, University of Minnesota, 207 Pleasant Street SE, Minneapolis, Minnesota 55455, United States b. Department of Chemistry and International Institute for Nanotechnology, Northwestern University, 2145 Sheridan Road, Evanston, Illinois 60208 United States
Electronic Supplementary Information (ESI) available. ABSTRACT: A novel sensing scheme is exemplified through the detection of ricin B-chain (RBC) in water and liquid food matrices: surface-enhanced Raman Spectroscopy (SERS) coupled with an N-acetyl-galactosamine glycopolymer capture layer. The sensing scheme’s detection limit was well below that of the predicted oral exposure limit. Theoretical predictions of the normal Raman spectrum of the glycomonomer give insight to polymer-RBC intermolecular interactions. Keywords: Ricin, Surface Enhanced Raman Spectroscopy, Glycopolymers, Film Over Nanospheres, DFT Modeling
This work demonstrates a novel protein sensing scheme, combining the molecular specificity of surface-enhanced Raman spectroscopy (SERS) and the multivalent biological affinity of glycopolymers (polymers with pendant saccharide units). Diverging from apta- and immuno- assays and their issues with cross reactivity,1 recent research has focused on more accurate chemical analysis for the direct detection of proteins of interest, including Raman spectroscopy.2 By performing Raman spectroscopy in the presence of plasmonic nanoscale metal features (SERS), one can achieve the molecular “finger print” provided by Raman, circumvent the innately poor Raman scattering cross-section, and access ultra-low concentration sensitivity even in complex aqueous matrices. In SERS, incident light can excite the conduction electrons of the metal features, generating a signal-enhancing electromagnetic (EM) field that typically extends less than 10 nanometers from the substrate surface, though the range is specific to the plasmonic substrate being used.3 Conjugating the metal substrates with target-capture agents offers a means to retain a target within this signal-enhancing EM field. The majority of SERS protein sensors use antibodies or aptamers as capture agents.4–6 These biological capture agents are redundant for proteins with intrinsic affinities, such as lectins (proteins that bind a specific sugar), and their designed specificity is unnecessarily costly and laborious to develop and mass produce. To this end we present the use of glycopolymers as a novel capture agent for lectins. Synthetic glycopolymers combine numerous benefits, such as biological recognition, increased affinity (due to multivalency),7 and applicability to multiple lectin targets. Additionally, our synthetic methods provide control over polymer chain length, reactive end groups, and the opportunity for further synthetic optimization.
Ricin, a highly toxic (oral LD50 of 20 mg/kg) protein found in castor beans (Ricinus communis),8 was the chosen target in this proof-of-concept work. Ricin has been found all over the world9 including the US, Iraq, and Afghanistan.10,11 Ricin can be used to contaminate food or drink as it is stable in ambient conditions and resistant to heat and denaturants, such as chloride.12 The mechanism of toxicity involves both the A and B chains of this heterodimeric protein. The B-chain is a lectin, which controls epithelial cell adhesion and endocytosis via extracellular glycoprotein binding. The A-chain attacks the 28S rRNA of the 60 S ribosome subunit13 - halting protein synthesis and causing apoptosis.14 When separate, the two ricin subunits are benign, making the ricin Bchain (RBC) lectin an excellent low risk candidate for studying sensing methods. Previous work has demonstrated a hydrogen bonding-based association between the C3 and C4 hydroxyls of N-acetyl-galactosamine and the polar residues of RBC’s sugar binding site 2.15 To exploit this natural interaction and incorporate the saccharide into a polymer affinity agent, N-acetyl-galactamine was synthetically modified at the C1 hydroxyl with a methacrylamido group for reversible addition-fragmentation chain transfer (RAFT) polymerization (synthesis details are in the supplementary information, SI).16 RAFT is a popular controlled radical polymerization technique that utilizes a chain transfer agent (CTA) to control the length and dispersity of chains in the polymer mixture. The CTA used is a trithiocarbonate that is also able to chemisorb to gold, making this a convenient anchoring chemistry for SERS.17,18 Short polymer chain lengths of approximately 10 N-acetylgalactosamine ethyl methacrylamide (NAGEMA) repeat units were targeted and we obtained an average of 9-10 repeats (Mn 3.2-3.6 kDa, Table S-1) to provide enhanced binding via multivalency and ensure that the capture layer does not extend past the enhancing EM field. This polymer length ensures a capture layer that is less than 3 nm thick. Fabrication of the sensor is illustrated in Figure 1. The plasmonic film-over-nanospheres (FONs) were made following a previously published procedure.19 The FONs were submerged in purified polymer dissolved in ultra-pure water for sensor fabrication. The pNAGEMA attachment was verified using SERS. The polymer spectrum was identified by strong to moderate intensity Raman bands at 278, 361, 414, 501, 514, 845, 886, 979, 996, 1027, 1086, 1231, and 1285 cm-1 shift – tentative band assignments are included in Table 1. A representative SERS spectrum for the pNAGEMA attached to the FONs is shown in Figure 2
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Figure 1: (I) Silica nanospheres, were drop-coated and self-assembled on a silicon wafer creating a packed sphere mask. (II) 120 nm of gold was deposited onto the nanosphere template, and substrates with a localized surface plasmon resonance (LSPR) λmax between 735780 nm were utilized. (III) The Au FONs were immersed in a 1 mM polymer solution for eighteen hours to allow attachment by chemisorption through the trithiocarbonate of the polymer to the gold. (blue curve). The glycopolymer shares a number of peaks with other mono- and poly- saccharides such as galactosamine and chitin.20 When comparing Raman spectra of mono- and polysaccharides, a broadening of Raman scattering peaks is observed due to the large number of linked sugars.20 The computational prediction of the NAGEMA spectrum (Figure 2, black curve) using DFT-based methodologies described by Jensen et al.21 provides a means for Raman peak assignment (Table S-3). From these assignments we can elucidate how the polymer interacts with RBC. Specifically, many of the ring distortion peaks, indicated by dashed lines, are shown to change upon incubation with RBC, a result consistent with the N-acetyl-galactosamines confined to the RBC binding pocket. In this proof-of-concept work, sensing experiments were conducted by incubating the pNAGEMA-modified FONs in the desired RBC or control solution for six hours, with constant mixing via an orbital shaker (corresponding bare FON controls are included in SI, Figure S-3). Control solutions contained 2mercaptoethanol at the same concentration as present in the RBC solutions to prevent the formation of disulfide bonds between RBC proteins. Post-incubation, the FONs were rinsed with DI water and dried under nitrogen. The localized surface plasmon resonance (LSPR) and SERS spectra were then measured. For all conditions acquired in water, a red-shift in the LSPR λmax is measured using extinction spectroscopy (SI Table 2), an expected change due to the increased refractive index of adsorbed species on the sensor surface.22
Changes in the collected SERS spectra are subtle until the SERS spectrum of the glycopolymer is subtracted from the postRBC incubation spectrum (Fig 3A). Seen in the Raman difference spectrum, several peak intensities increase. The spectral changes that are independent of the negative control (Figure S-3) are labeled (a-g). Using previously measured Raman spectra of RBC and its cyclic amino acids (which have the largest scattering cross-section) from literature,20,23,24 we are able to discern the likely molecular origin of the spectral changes. The signal at 1280 cm-1 shift (a) is assigned to the unstructured coil of RBC, and the signal at 1088 cm-1 shift (c) is attributed to C-C and C-N stretching vibrations within the protein, which overlays similar C (ring)N (amino) and C (ring)-O (methacrylamide) stretching in the polymer. While these signals are typical in Raman analysis of any random coil proteins, here, the co-location with polymer peaks makes them qualitative indicators of RBC. The increases at 990 cm-1 shift (d) and 1024 cm-1 shift (e) are from phenylalanine and overlap with sugar ring distortions and C-O stretches. Vibrations from tyrosine and tryptophan contribute to the increases seen between 830-880 cm-1 shift (f) and that at 1190 cm-1 shift (b). In both polymer and protein, the 830 cm-1 shift region is occupied by peaks due to ring distortions. In this region, the overlap of these makes quantitative analysis of band intensity difficult. The addition and orientation of RBC, as well as the resulting polymer displacement, lead to complicated peak intensity changes. Highlighted in Fig 3A and Fig 3B, is an emerging peak in the 700 cm-1 shift region (g). Literature precedent attributes this peak to tyrosine and tryptophan vibrations. Table 1. The experimental shift and theorized origin of the indicated peaks in Figure 2.
Figure 2. Comparison of experimental pNAGEMA spectrum (blue, top) and computed NAGEMA spectrum (black, bottom). The experimental spectrum was collected with a 785 nm diode laser with 3 mW power over 30 seconds.
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Figure 3. Spectral differences due to the presence of RBC: (A) representative difference spectrum demonstrating changes (a-g) due to RBC, (B) difference spectra of varying concentrations of RBC in the 670-750 cm-1 shift region, (C) quantification of the increased amplitude at 700 cm-1 shift with increasing RBC concentration, including the calculated association constant (Ka), and limits of detection (LOD) and quantification (LOQ). While all the previously mentioned peak intensity increases can be attributed to RBC features, the 700 cm-1 shift region (g) is unobscured by vibrations from the polymer, making it the optimal portion of the spectrum for quantification. The peak appears to be concentration dependent and is clearly not a result of the 2mercaptoethanol present in the negative control RBC buffer (Fig 3B). Using the difference due to incubation with RBC, the limit of detection (LOD) and limit of quantification (LOQ) are calculated to be 0.02 µg/mL RBC and 0.08 µg/mL RBC, respectively (for calculation methods, see SI). Therefore, detection can occur well below the 6 µg/mL estimated to be dangerous to an adult by oral ingestion over 24 hours of exposure.14 Plotting the increased amplitude of this peak against RBC concentration yields a Langmuir type plot that is nonlinear past 1.0 µg/mL RBC. At higher levels, the sensor may be utilized for simple “yes/no” detection. The shape of the plot indicates that at higher concentrations, the sensor is saturated. By fitting this plot to the Langmuir equation (Equation S-1), we can calculate an apparent association constant (Ka) for the lectin-saccharide interaction. The derived Ka of 6.8 x 107 M-1 suggests strong, specific binding. Similar results were obtained from surface plasmon imaging studies on the lectin jacalin and surface bound galactose (Ka of 2.2 x 107 M-1) by Smith et al.25 The strong binding seen between the glycopolymers and RBC and the real-world risk of contaminated food items prompted us to investigate our sensor’s efficacy in apple juice with mixing, and stagnant orange juice at RBC concentrations relevant to oral exposure (3 µg/mL and 10 µg/mL, respectively), seen in Figure 4 (individual FON spectra available in SI Fig S-5 and S-6). The juices were spiked with RBC or the equivalent concentration of
buffer, and each condition was performed in triplicate. Initial data analysis of RBC exposures in juice utilized principle component analysis (PCA) of the raw spectra. PCA is a statistical procedure that dimensionally reduces a data set with a large number of variables (such as spectral points across multiple conditions) and can be applied in a qualitative manner to visualize variance and outliers, even in complex spectra. The PCA of the control and spiked juice conditions (Fig 4 A and C) reveal that there is variance in the spectra that correlates with the presence of RBC. Because the SERS signal measured from the FON substrates post-juice incubation was so low, all juice data were normalized by the maximum of the pNAGEMA spectrum to generate meaningful difference spectra. In juice, the buffer, as well as the RBC, spectra contain many of the peaks that were exclusive to RBC in DI water (Fig 3 A c, e-g). This can be attributed to the sensor undergoing some non-specific binding with native juice proteins having similar residue vibrations. However, the peak increase at 1280 cm-1 shift, associated with the random coil of the B chain, is still only seen in the RBC-spiked juice experiments and not observed in the control. Also unique to the RBC difference spectra are the changes seen in the 615-630 cm-1 shift region. Peaks in this range have been previously assigned to RBC’s cysteine C-S stretching,4 but vibrations from 2- mercaptoethanol may be seen in this region (600-660 cm-1 shift).26 Both spiked juices demonstrate an increase peak intensity at 380 cm-1 shift indicating a conformational change in chemisorbed polymer. The observed 10 cm-1 shift to higher energy is of polymer peaks that originate from molecule-wide bending, with significant ring distortions through C bending. In conclusion, a novel N-acetyl-galactosamine glycopolymer was synthesized and used, in conjunction with FONs, as a capture layer in the detection of RBC via SERS. In comparison to recently reported SERS ricin sensing techniques (see Table S4), this is the first report utilizing the naturally selective binding of ricin to Nacetyl-galactosamine for SERS detection. Computational modeling afforded a good fit with experimental SERS spectra, enabling the assignment of polymer peaks and insight into RBCpNAGEMA interactions. Our proof of concept RBC detection was sufficiently sensitive for bio-terror prevention purposes in food matrices. The quantitative concentration dependence seen at
Figure 4. Detection of RBC in juice: PCA plots of raw spectra from RBC (purple) and buffer (orange) in apple and orange juices are shown in (A) and (C), respectively. Averaged difference spectra of RBC (3 µg/mL) (purple) and buffer (orange) in apple juice, and RBC (10 µg/mL) and buffer in orange juice can be seen in (B) and (D), respectively.
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700 cm-1 shift band in simple media has a LOD (20 ng/ mL) well below the toxic limit for oral exposure and comparable to those reported in the works of He et al and Tang et al, 10 and 8.9 ng/mL respectively.13, 26. Unlike several of the other literature reports of ricin SERS sensors (Table S-4), this technique has a quantitative range, and many qualitative spectral changes are preserved in the presence of complex food matrices. Those seen at 1280, 615-630, and 380 cm-1 shifts agree with past RBC SERS work, allowing for the detection of RBC in fruit juices. While the incubation time of 6 hours presented herein exceeds the 0.5-1.5 hour detection times of reported SERS ricin sensors, the speed and simplicity of SERS and the high RBC-pNAGEMA Ka should allow for improvement. Finally, unlike other published ricin SERS sensing schemes, the capture agent presented herein can be directly applied to other applications such as liver targeted gene delivery16 or the sensing of other lectins of interest, such as those relevant to food allergens. Work is ongoing to determine the sensor’s sensitivity to lectin identity, competitive selectivity between RBC and other lectin targets, and the reversibility, and thus reusability.
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ASSOCIATED CONTENT Supporting Information
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Electronic Supplementary Information (ESI) available: [monomer and polymer synthesis and characterization, LSPR shifts, computational methods, and spectral analysis].
AUTHOR INFORMATION
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Corresponding Author Email:
[email protected] Author Contributions
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‡These authors contributed equally. (18)
ACKNOWLEDGMENT This work was partially supported by the MRSEC program of the National Science Foundation under Award DMR-0819885 at the University of Minnesota. The SEM images were taken in the University of Minnesota I.T. Characterization Facility, which receives partial support from NSF through the NNIN program. LM and GCS were supported by the MRSEC program at Northwestern University under Award DMR-1121262. We thank Zhe Gao for her assistance with the SEM images.
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