Antibody-Free Discrimination of Protein Biomarkers in Human Serum

Oct 19, 2018 - Antibody-Free Discrimination of Protein Biomarkers in Human Serum Based ... structures can be discriminated with the aid of hierarchica...
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Antibody-Free Discrimination of Protein Biomarkers in Human Serum Based on Surface-Enhanced Raman Spectroscopy Hao Ma, Xiaoying Sun, Lei Chen, Xiao Xia Han, Bing Zhao, Hui Lu, and Chengyan He Anal. Chem., Just Accepted Manuscript • DOI: 10.1021/acs.analchem.8b03701 • Publication Date (Web): 19 Oct 2018 Downloaded from http://pubs.acs.org on October 20, 2018

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Analytical Chemistry

Antibody-Free Discrimination of Protein Biomarkers in Human Serum Based on Surface-Enhanced Raman Spectroscopy Hao Ma1, Xiaoying Sun2, Lei Chen3, Xiao Xia Han1*, Bing Zhao1, Hui Lu4 and Chengyan He2* 1. State Key Laboratory of Supramolecular Structure and Materials, Jilin University, Changchun 130012, P. R. China. 2. China-Japan Union Hospital of Jilin University, Changchun 130033, P. R. China. 3. Key Laboratory of Preparation and Applications of Environmental Friendly Materials (Jilin Normal University), Ministry of Education, Changchun, 130103, P. R. China. 4. School of Biological Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester M13 9PT, UK. ABSTRACT: Protein biomarkers are very important indicators of diseases and have great potential in cancer early diagnosis. The majority of detection methods for protein biomarkers currently rely on specific capture antibodies or aptamers with chemiluminescent and fluorescent labels. Here, an antibody-free strategy for discrimination of versatile proteins is proposed based on surfaceenhanced Raman spectroscopy. The SERS spectral variation of a linker molecule, perylenetetra carboxylic acid (PTCA) is found to directly correlate with the protein types, according to which protein biomarkers even homologous proteins with very similar molecular structures can be discriminated with the aid of hierarchical cluster analysis. Furthermore, the feasibility of the proposed approach has been proved in early liver cancer diagnosis with clinical samples. All the results indicate that PTCA as a universal SERS probe has great potential in rapid, accurate and direct protein biomarker discrimination in cancer diagnosis.

Protein biomarkers are very important indicators and often measured and evaluated to examine normal and abnormal biological conditions in diseases.1,2 Currently the majority of detection methods for protein biomarkers are based on specific antibodies with chemiluminescent and fluorescent labels.3-7 However, the high cost in the producing process limits the applications of antibodies especially for monoclonal antibodies. Aptamers with higher stability and relatively lower cost than antibodies have attracted increasing interest in recent years.8,9 However one specific aptamer is required for each biomarker, leading to a longer lead time for aptamer screening and only a few effective aptamers are now available, which limits its wide applications in clinical diagnosis. Surface-enhanced Raman scattering (SERS) spectroscopy has been proved to be powerful for ultrasensitive label-free protein identification.10,11 Our previous studies indicate that the proteins with cofactors (like hemes and flavins), can be easily identified via surface-enhanced resonance Raman scattering (SERRS) spectroscopy,12-14 but it is still challenging for SERS to discriminate those proteins without cofactors in complicated biological samples. The SERS spectral reproducibility is of great importance for reliable biological detection. There are three general strategies for improving the reproducibility: introduction of an internal or external standard, uniformity of SERS-active substrates for reproducible SERS intensity and the usage of band frequency shifts (or variation). Silver nanoparticles modified with silicon on solid support prepared by He et al.15-17 displayed highly sensitive and reproducible SERS signals owing to external standards and highly ordered substrates. They are useful for accurate quantification of heavy metal ions and detection of biomolecules. On the other hand, in recent years SERS frequency shifts have been

found to be capable of displaying much better spectral reproducibility than band intensities,18-20 which significantly improved the accuracy of SERS in analytical chemistry. more recent studies suggested that symmetry breaking of some small SERS molecules like 4-mercaptophenylboronic acid (4MPBA) and 4-mercaptobenzoic acid (4-MBA) are sensitive to the binding molecules, which would be useful as a novel SERS probe for versatile protein discrimination.21-23 The frequency shift-based approach allows high spectral reproducibility on commonly-used SERS substrates like Ag colloid and self-assembled Ag films. However, it is still difficult to use one band shift for accurate discrimination of target molecules with similar structures.

Figure 1. Schematic diagram of the self-assembled chip (A), (B) SERS spectra of the chips binding with versatile proteins and (C) spectral details of the dotted area in (B)

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Figure 2. (A) Calculation results of PTCA and PTCA bonding with NHS and protein. (B) Scattering diagram for the two identifiers(intensity ratio and frequency shift) of spectral changes with 11 protein samples. Each data point represents an average of nine measurements, and the error bar indicates the standard deviation; (C) Illustration of the possible CT mechanism of the Ag/PTCA/Protein assembly.

To tackle the challenge of antibody-free discrimination of protein biomarkers, here a linker molecule, perylenetetra carboxylic acid (PTCA) is used for the first time to probe the bound target proteins by SERS spectroscopy. Density functional theory (DFT) calculation was performed to explore symmetry breaking of PTCA with binding molecules. In combination with the symmetry breaking and frequency shifts of the linker, ten proteins (5 simple proteins and 5 proteins with cofactors) with diverse molecular weight and structure are discriminated with the aid of hierarchical cluster analysis (HCA). Moreover, the feasibility of the proposed approach for the identification of clinical biomarkers is examined in alphafetoprotein (AFP)-containing human serums from the patients with hepatocellular carcinoma (HCC). Here, a label-free, SERS based method for discrimination of protein biomarkers is for the first time developed. In comparison with classic approaches like chemiluminescent and fluorescent assays, the proposed method is low-cost and time-saving (without antibody or aptamer preparation procedure). Moreover, it is highly reproducible and selective with a discrimination ability even for homologous proteins, which is impossible for previous methods of SERS-based protein detection.” A self-assembled silver nanoparticle chip was prepared (Figure S1). PTCA was attached to the silver surface through weak Ag–O bonds and was used as a linker molecule to capture target proteins via an amido linkage.24 As shown in Figure S2, the band at 550 cm-1 corresponds to out-of-plane of b1 vibration of PTCA. After being activated by EDC/NHS, a new peak emerged at 537 cm-1 due to the formation of NHS group, and it induced a frequency shift from 1568.2 to 1570.4 cm-1. Additionally, a new peak emerged at 1343 cm-1, which are consistent with a new tensor of DFT results. To test if the two SERS bands are protein dependent, ten proteins (bovine serum albumin, BSA; pepsin, Pep; egg white albumin, EA; trypsin, Try; hemoglobin, Hem; horseradish peroxidase, HRP; myoglobin, Myo; cytochrome C, Cyt c; glucose oxidase, GO; lysozyme, Lys) were examined. It is noted that the relative intensity between the bands 537 and 550 cm-1 varies among the six model proteins as shown in Figure 1B. At the same time, protein binding also induced frequency shifts ranging from 1567.0 to 1569.3 cm-1, which are also dependent on protein types.

To interpret the observed phenomenon, density functional theory calculation was performed to identify the expected vibrations. All the calculations were under B3LYP/6311++G** level by the Gaussian 09 program.25 With the consideration of isotope effect, we tried to figure out the effect of protein weight to the vibrations. As shown in Figure 2A, we found that the attached protein indeed can induce symmetry breaking since several new vibration tensors (like those at 500, 1063 cm-1 and 1343 cm-1) emerged in the dotted regions, which are consistent with the observed experimental spectra. However, we found that the SERS spectra exhibited almost no difference when the proteins with different weights were tested (data not shown). Thus, it was deduced that there should be another factor to be blamed for it. From the experimental data, we also found that the frequency shifts were independent on the protein weights. For instance, the molecule weights of GO and Try are respectively 150 kDa and 24 kDa, but both of two proteins displayed similar frequency shifts as shown in Figure 2B. Additionally, repeated measurements showed excellent reproducibility, which indicated that the binding condition of each protein was almost the same every time. Our previous study suggested that the observed frequency shifts should be attributed to a polarizability change of PTCA, rather than a pressure-induced effect.26,27 Accordingly, we speculate that different proteins should have preferred binding sites to the PTCA molecules, and thus the amino acid residues around PTCA are protein-dependent, resulting in the specific polarizability changes of the PTCA. Moreover, it is worth noting that it is reasonable that one carboxyl group of PTCA captures a protein via the amido bond formation, and the other carboxyl group should have intramolecular interaction with the amino acid residues around it. The intramolecular interaction sites of the attached protein are protein-dependent, which also affect the polarizability of PTCA. Both of two factors are attributed to a specific frequency shift of one certain protein. Hence, to a large extent, the polarizability changes of the PTCA reflex unique characters of proteins, which is the reason why frequency shifts can be used as an identifier for the bound protein discrimination. Moreover, the intensity ratio variation might also originate from the protein-induced polarizability changes.

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Analytical Chemistry Our recent results demonstrate that PTCA is a sensitive probe of charge transfer (CT), and its vibronic mode of b1 can be enhanced dramatically through a CT resonance.24 In the present system, the relative intensity between the vibronic b1 bands 537 and 550 cm-1 is protein-dependent, which indicates this intensity ratio might be attributed to different energy level of intramolecular interaction sites. With this consideration, we propose a possible CT mechanism involving two CT processes of CTPTCA→Protein and CTAg→PTCA in this system.28 As shown in Figure 2C, the fermi level of Ag, HOMO and LUMO of PTCA are plotted according to our previous work.24,29 To plot the energy levels of HOMO and LUMO of the amino acid residues, we performed a laser wavelength-dependent study in different Ag/PTCA/Protein assemblies. When under laser excitations of 633 nm, the SERS signals around 537, 550 cm-1 were enhanced but with lower CT degree than those at excitation of 785 nm (Figure S4), which indicated that the energy gaps between HOMO of PTCA and LUMO of the amino acid residues are lower than 1.96 eV and the CT from PTCA to the target protein is possibly resonant with the 785 nm laser excitation. Moreover, both of two transitions are off-resonance in this system with the 633 nm excitation. Hence, the intensity of b1 peaks can be represented as follows: I = BPTCA→Protein + CAg→PTCA. Furthermore, we can predict the intensity ratio using the following expression according to the Herzberg al condition need be further optimized. Teller selection rules:29-31 

    ∙          ∙          ∙    

Briefly,  represents the molecular electronic transition of PTCA from the HOMO to the LUMO.  represents electronic transition from the Fermi level of Ag to the LUMO.  represents electronic transition from HOMO to the LUMO of the amino acid residues. Also, the value of ,  , and  are known value. This is to say, the intensity ratio of two relevant peaks are function of the energy gaps of HOMO and LUMO of the amino acid residues ( ), which is protein-dependent. This is the reason why the intensity ratio can be used as an identifier for the bound protein discrimination. To test if the spectral variation of the PTCA is useful for protein discrimination, Here, we transformed the spectral changes into a two-dimensional plot with two identifiers, relative intensity ratios and frequency shifts. As shown in Figure 2B, the horizontal ordinate represents frequency shifts of the peak at 1570 cm-1, and the vertical ordinate is the intensity ratio of I550/(I550+I537). After plotting all the cases of proteins, respective groups were found in the scattering diagram. It is noted that those proteins without cofactors like EA and Lys are distinguishable from the hemo proteins like Hem, GO and Cyt c, suggesting that there is a possibility for the proposed approach to discriminate versatile proteins. Moreover, a surprising finding here is, the SERS spectral variation of the human serum (complicated and mixed biosamples) is also reproducible, which is very important and will provides convenience for determination of protein biomarkers in clinical samples. We observed the Raman intensity ratio I550/(I550+I537) was independent of protein concentration after immersed for 4 h for both EA and BSA, when protein binding was stable. However, when the immersion time was less than 4 h, the intensity ratios were protein concentration-dependent (Figure S2C), which could be used for protein

Figure 3. HCA for spectral changes of seven proteins at four concentrations (A: 20 µM, B: 10 µM, C: 5 µM, D: 1uM). All the four dendrograms were based on the matrix (7 proteins × 3 chips × 3 points with five controls).

quantification, but the experimental condition need be further optimized. Generally, it is difficult for Raman spectroscopy to distinguish homologous proteins since they have very similar molecular structures (Figure S4). Direct contact of such proteins with SERS-active materials is usually suffering from poor spectral reproducibility because protein molecules have different orientations on substrate surfaces.32 Thus, currently none of these SERS-based methods are capable of discriminating homologous proteins. A remarkable finding here is the proposed approach is able to distinguish two homologous proteins, BSA and alpha-fetoprotein (AFP). As shown in Figure 2B, the two proteins are both well discriminated in the scattering diagram. As discussed above, the SERS spectral variation of the PTCA is only sensitive to the binding groups about around its carboxyl groups, and thus the difference in the SERS spectra of the two proteins probably originated from their preferred binding groups. The discrimination ability of the chips was further tested by sensing seven proteins (Pep, Lys, Myo, EA, Hem, BSA, and Try) at four concentrations (1, 5, 10 and 20 µM). The frequency shifts are independent on the protein concentration in the range of 1-10 µM. It is interesting that the chips remain the discrimination ability for proteins at higher concentration of 20 µM (Figure 3), although the band frequencies are further upshifted which is probably attributed to the formation of protein dimer or tetramer (Figure S5). We used hierarchical cluster analysis (HCA), a model statistical classification method, to study the similarity of spectra change with different proteins.33 From the HCA dendrograms (Figure 3), it is noted that the spectral change was aligned with each protein group and almost all the seven proteins are clearly identified, which confirmed the feasibility of the proposed approach for protein discrimination. To further verify its discriminant ability in hybrid system, the chip was employed to test AFP, a typical biomarker for HCC diagnosis. We found that the SERS spectral variation is both AFP and human serum dependent, and more importantly, there is almost no overlap between the spectral changes of AFP and human serum (Figure 2B). Accordingly, AFP at different concentrations (5, 20, 100 and 600 ng/mL) in normal serum was examined. As shown in Figure S5, all these AFPs can be detected by the SERS spectra based on the variation

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Experimental details; SEM image of the self-assembled silver chip; Raman spectrum of Ag/PTCA and Ag/PTCA-NHS; immersing time course of I550/(I550+I537) changes of BSA and EA at different concentrations; SERS spectra of the chips binding with versatile proteins at 785 nm and degrees of CT (ρ ) at 633, 785 nm; Normal Raman spectra of BSA and AFP; BSA concentrationdependent SERS spectra on the PTCA-modified chips; SERS spectra of the PTCA-modified chips with AFP in PBS and in serum, and the detection curves; SERS spectra of the PTCA modified chips with EA and BSA in the serum and PBS.

AUTHOR INFORMATION Corresponding Author *[email protected] (X.X.H); [email protected] （C.Y.H）

Author Contributions The manuscript was written through contributions of all authors. All authors have given approval to the final version of the manuscript. Figure 4. (A) SERS spectra of the chips with (a) Pure AFP, (b) Patients serum, (c) Normal serum; (B) Zoomed-in image of the dotted area in (A); (C) test results of 21 clinical samples using the proposed SERS-based chips compared with the diagnosis results.

range shown in Figure 2B. The result indicated that the AFP had a relatively higher affinity to the chip among other proteins in the serum, and it also demonstrated that the sensitivity of the proposed method is high enough to identify 5 ng/mL of AFP in human serum. The selectivity of proposed chips was further confirmed by examining the SERS spectra of the chips for detection of AFP, EA and BSA in serum (Figure S6 and S7). Furthermore, 21 clinical samples with different AFP concentrations were tested (detail information is summarized in the supporting information). Typically, compared with the normal serum, the patient serums displayed different trends in intensity ratios and frequency shifts (Figure 4A). The serums from normal people or patients diagnosed as cancer or benign diseases were tested. As shown in Figure 4C, it is possible to discriminate the patients with liver cancer according to the intensity ratios and frequency shifts of the PTCA. Compared with diagnosis results, the accuracy of the proposed method is 90.5%, which is useful for rapid HCC diagnosis. In summary, we found that symmetry breaking and frequency shifts happened with PTCA when it bound to proteins and the SERS spectral variation was protein-dependent. Accordingly, an antibody-free approach for protein discrimination has been established. Without high-cost and time– consuming process for antibody preparation, protein biomarkers even homologous proteins can be identified indirectly by the spectral changes of the PTCA even in human serum. Given its good reproducibility and accuracy, we strongly believe that this “proof-of-principle” research will significantly promote the applications of SERS in biomedicine. Moreover, synthesizing novel symmetric rigid SERS probes to further improve the differentiability of the proposed method in real biosystems is now in progress in our research group.

ASSOCIATED CONTENT Supporting Information The Supporting Information is available free of charge on the ACS Publications website.

ACKNOWLEDGMENT This work was supported by the National Natural Science Foundation (Grant Nos. 81572082, 21773080, 21711540292 and 21773079) of P. R. China.

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