Gold Nanoparticle Probe-Assisted Antigen-Counting Chip Using SEM

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Biological and Medical Applications of Materials and Interfaces

A Gold Nanoparticle Probe-Assisted Antigen-Counting Chip using SEM Xin Zhou, Chih-Tsung Yang, Qiaoshu Xu, Zhichao Lou, Zhengfeng Xu, Benjamin Thierry, and Ning Gu ACS Appl. Mater. Interfaces, Just Accepted Manuscript • DOI: 10.1021/acsami.8b19055 • Publication Date (Web): 24 Jan 2019 Downloaded from http://pubs.acs.org on January 25, 2019

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ACS Applied Materials & Interfaces

A Gold Nanoparticle Probe-Assisted Antigen-Counting Chip using SEM Xin Zhoua*, Chih-Tsung Yangb, Qiaoshu Xuc, Zhichao Loud, Zhengfeng Xue, Benjamin Thierryb, Ning Guc a

Institute of Comparative Medicine, Jiangsu Co-innovation Center for Prevention and Control of Important Animal Infectious Diseases and Zoonoses, Joint International Research Laboratory of Agriculture and Agri-Product Safety, the Ministry of Education of China, Yangzhou University, Yangzhou 225009, China. b Future

Industries Institute and ARC Centre of Excellence in Convergent Bio and Nano Science and Technology, Mawson Lakes Campus, University of South Australia, South Australia 5095, Australia. c State

Key Laboratory of Bioelectronics, Jiangsu Key Laboratory of Biomaterials and Devices, School of Biological Science and Medical Engineering, Southeast University, Nanjing 210009, China. d College

of Materials Science and Engineering, Nanjing Forestry University, Nanjing 210037,

China. e Center

of Medical Genetics, Obstetrics and Gynecology Hospital Affiliated to Nanjing

Medical University, Nanjing 210029, China.

Keywords: Protein biomarker, Gold nanoparticle probes, Carcinoembryonic antigen, Counting chip, Scanning electron microscope (SEM)

ABSTRACT Currently it remains challenging to count protein-biomarker molecules presents in a small droplet of biological samples. Herein, we propose a gold nanoparticle (GNP) probe-assisted sandwichcounting strategy that relies on a GNP probe, an antibody functionalized chip to “count” antigen molecules using Scanning Electron Microscope (SEM). Both standard Carcinoembryonic antigen (CEA) and two real CEA-related tumor samples (tumor tissues and serum) were assayed to demonstrate the proof-of-concept of the counting strategy. Results show that our method is excellently correlative with ELISA assay widely used in clinic for antigen or antibody detection and 1

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the limit of detection (LOD) of our enumeration strategy reach down to 0.045 ng/mL, which is ~40 times more sensitive than the conventional ELISA. Therefore, our GNP probe-assisted sandwichcounting strategy has the potential to be used for quantification of protein biomarkers at ultra-low concentration in early tumor specimens and detection of target proteins in much diluted concentration. 1. Introduction The expression level of protein biomarkers provides valuable diagnostic and prognostic information relevant to the development of malignant diseases. Precise quantification of protein biomarkers associated with a specific disease is routinely used to monitor patients' response to therapy and determine whether the cancer has progressed or recurred. Presently, there are two mainstream protein assays routinely used in the clinical environment, namely enzyme-linked immuno-sorbent assay (ELISA) for soluble markers and immunohistochemistry (IHC) for tissue samples.1 ELISA is widely used due to its simplicity but is only capable of quantifying relative amounts of the target proteins. On the other hand, IHC plays an important role in determining the expression of specific antigen in pathological examination of tissue sections, which provides important insight about the malignant degree of the tumor but no digital information about expression levels. To address the shortcomings of the standard methods, many protein biomarker quantification technologies have been reported: For example, Malmstrom et al. developed a label-free protein quantification but this mass spectrometry based absolute quantitative approach requires large instruments.2 Schmidt et al. reported a protein assay platform capable of detecting tuberculosis antigen with a sensitivity down to 1.8 pg/mL utilizing a total internal reflection technology.3 However this method requires a sophisticated total internal reflection device as well as a highly trained technician. In recent years, 2


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nanomaterials-based analytical platforms for digital detection of protein biomarkers have been intensively developed.4-8 These platforms have the potential of counting protein molecules of interest with a clinical samples with ultra-sensitivity. Biomolecule functionalized nanoparticles are capable of capturing single protein biomarkers, and therefore have the potential to allow for counting the target proteins with a sample. Among these nanomaterials for digital protein analysis, GNPs are extensively employed for the digital detection of proteins due to their outstanding optical properties, excellent chemical stability, the existence of robust synthesis protocols, and the availability of well-established bio-functionalization routes. We have previously reported on the development of rapid and sensitive digital quantification methods for biomarkers including DNAs and proteins. For example, a GNPs assisted bio-mineralization chip could achieve ultrasensitive naked-eye detection of DNA.9 Despite its merits, this approach requires a number of tedious steps for signal amplification and must be precisely operated in order to obtain satisfactory signal-to-noise ratio. We have also developed a gene-engineered T7 phage as a “oneto-one” signal transfer tool for counting single miRNA molecule (adaptable for the enumeration of proteins), taking advantage of the phage monoclonal plaque formation feature.10 Nevertheless, this counting strategy is not applicable to high-throughput assays due to the need for phage development on its host culture Petri dish. Recently there have been major advances in the miniaturization of scanning electron microscopy (SEM),11-13 and simple to operate yet performant benchtop instruments are now commercially available. Compared with other electron microscopy technologies, SEM is characterized by its rapidity, large scanning range and facility of operation. A chip format methodology, allowing direct counting of protein biomarker molecules with ultrahigh sensitivity and medium throughput, has the 3



potential to allow for digital detection of target proteins within clinical samples once integrated into an automatic SEM system by using the traceable characteristics of GNP probes.14-17 Owing to their high electron density, colloidal GNPs are commonly employed as tracers in electron microscopic imaging of biological samples.18-20 Herein, we propose a GNP probe-assisted antigen-counting strategy to quantify biomarker molecules in vitro. Our strategy includes three steps as illustrated in Scheme 1 and relies on: 1) Functionalized GNPs; 2) Antibody modified silicon chip, which are prepared by standard chemical modification; 3) SEM for the quantification step. Here, we used the CEA antigen, which is highly expressed in tissue samples of colorectal cancer patients and is the preferred prognostic biomarker,21 as a model protein biomarker to validate the proposed GNP probeassisted counting chip. Furthermore, the strategy was employed to count another cancer-associated protein marker Alpha-fetoprotein (AFP) in the interfering protein condition demonstrating the clinical applicability of our platform.

Scheme 1. Schematic of GNP probe-assisted SEM-counting chip. (a) GNP probe preparation. (b)

Functionalization of the chip with antibodies. (c) The procedures for counting antigen molecules using GNP probe-assisted SEM-counting chip. 2. Experimental details 4


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2.1 Materials and instruments CEA, Anti-CEA antibodies and the CEA ELISA Kit were provided by Shanghai Linc-Bio Science Co., Ltd. AFP, anti-AFP monoclonal antibodies were obtained by US Abcam. Anti-AFP polyclonal antibodies were provided by Beijing Bioss Co., Ltd. Protein A coated gold nanoparticles were supplied by Creative Diagnostics (US). Bovine serum albumin (BSA) and plastic well plates were provided by Corning and silicon slices were provided by Nanjing Keygen Biotech. Co., Ltd. Human serum albumin (HSA) and gamma globulin were purchased from Solarbo Co. LTD. Concentrated sulfuric acid, absolute ethyl alcohol and hydrogen peroxide were purchased from Sinopharm Chemical Reagent Co., Ltd. 3-Aminopropyltriethoxysilane, glutaraldehyde, Phosphate Buffered Saline (PBS), Tween-20, and enzyme-labeled second antibody were all purchased from SigmaAldrich. Millipore quality water (18.25 MΩcm−1) was supplied with a Milli-Q Plus water system. Centrifuge used in experiments is the Eppendorf 5810 R. Scanning electron microscopy (SEM) images were obtained using a HITACHI S-4800 system with an acceleration voltage of 15.0 kV and 50k magnification. Transmission Electron Microscope (TEM) images were obtained using a Holland Philips Tecnai-12. Tissues were homogenized using a Precellys24 homogenizer. The amount of GNPs in each image scanned by SEM was counted with DT2000 (a counting software, Nanjing Dongtu digital technology Co. LTD). CEA content in serum was also determined by Electrogenerated chemiluminescence (ECL) with Architect i2000. 2.2 Experimental 2.2.1 Preparation of anti-CEA modified silicon chips First, silicon chips were bio-functionalized with antibody probes based on the literature.22 Briefly, silicon chips (~0.2 cm2) were immersed in a freshly made solution containing hydrogen peroxide 5



and concentrated sulfuric acid at volume ratio of 1:1 for 1 h, followed by washing six times with deionized water. The chips were immediately immersed in a solution containing 15 mL of anhydrous ethanol and 1 mL of 3-Aminopropyltriethoxysilane (APTES) for 2 h. Following thorough rinse with ethanol and deionized water, the chips were further activated using 10 % glutaraldehyde with gentle shaking for 1 h.23 Antibody-immobilized chips were finally obtained by immersion in a CEA antibody solution (containing 10 % glycerol, 20 μg/mL of CEA antibody) for 4 h at 37 C, followed by blocking with BSA (2 mg/mL) for 1 h and rinsing three times with PBST (5 % Tween20 in PBS). Antibody functionalized chips were stored at 4 oC until used. 2.2.2 Preparation of biofunctionalized gold nanopaprticle probes The GNP probes were prepared by mixing 1 mL of protein A conjugated GNPs with a diameter of ~15 nm at ~1 nM with 10 μL of CEA antibody. In order to identify the optimal modification of GNP probes with a sufficient number of antibody molecules and with suitable colloidal dispersibility and stability, we tested three different concentrations (1, 2 and 4 μg/μL) of antibodies during the incubation step with the protein A modified GNP. After incubation for 2 h at room temperature, the functionalized GNP probes were washed three times with PBS by centrifugation at 13,000 rpm for 10 min to remove the unattached CEA antibodies. 2.2.3 Preparation of GNP probe-assisted counting chip for the detection of CEA 100 μL of either CEA antigen solutions at different concentrations (0, 0.09, 0.36, 1.8, 3.6 and 9 ng/mL in PBS buffer) or real samples were dropped on the CEA antibodies immobilized chips in 96-well plate and kept under gentle shaking at 37 C for 1 h. The chips were then washed five times with PBST. Finally 100 μL of the GNP probes at 1 nM was added at 37 C for 1 h to complete the sandwich immunoassay. The chips were then thoroughly rinsed with PBS prior to being subject to 6


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SEM counting. The assay procedure for the detection of the tumor marker Alpha-fetoprotein (AFP) is similar to that for CEA. 2.2.4 Procedures for ELISA sandwich immunoassays The ELISA experiments were performed following the standard protocol provided by the company. A calibration curve was generated by analyzing standard samples containing 0, 20, 40, 80, 200, 500 and 1000 ng/mL of CEA antigen with the ELISA kit. A CEA sample solution from standard or real samples was added on the anti-CEA modified chip and incubated at 37 C for 45 min. Then, the second anti-CEA antibody labeled with horseradish peroxidase (HRP) was added to the anti-CEA modified silicon chip and incubated at 37 C for another 45 min and was then washed with PBST three times to remove the non-bound antibodies. The subsequent reaction was developed by adding the enzyme substrate to the solution and incubating for 15 min at room temperature. Finally, the color solution was stopped with termination buffer before being subjected to UV-Vis absorbance measurement. The CEA proteins extracted from cancer and para-carcinoma tissues were diluted and analyzed with the ELISA kit. 2.2.5 Preparation of clinical samples for SEM counting Tumor tissues and para-carcinoma tissues were collected after obtaining informed consent as approved by the institutional Review Board of Medical College of Yangzhou University. The extraction of proteins from tissues was carried out following the standard protocol. Briefly, the tumor and para-carcinomas tissues were dissected on ice. 400 μL of freshly prepared extraction buffer, which was prepared by mixing 1 mL of RIPA buffer with 10 μL of PMSF, was added to the cancer or para-carcinomas tissues, and these tissues were homogenized using a homogenizer to ensure that tissues were completely dissociated prior to proceeding to the next step. The lysates 7



were then incubated on ice for 10 minutes with periodically pipetting and then centrifuged at 14,000 g for 10 min. The supernatants were collected for analysis. The serum was prepared by placing a blood sample on ice for 60 min, allowing coagulation of the collected blood sample. Then the serum solution was collected from the coagulated blood by centrifugation at 3000 rpm at 4 C for 10 min and stored at -80 C until use. It is noteworthy that the blood sample was given by one of co-authors as a part of routine health checkup at the health clinic of Yangzhou University, in which the blood sample was kept for the experiments. 2.2.6 Antigen concentration determined by GNP-assisted protein counting strategy The concentration of CEA (ng/mL) in spiked or real samples assayed with GNP-assisted protein counting strategy were determined by counting the value of GNP probes multiplied by correlation coefficient. The CEA counting Correlation Coefficient value is calculated as follows: When the SEM images were taken under 50 k magnification (the area of each field of view is 10 μm2). The concentration value (ng/mL) of CEA in samples = Total molars of GNP probes per mL

× molecular weight = Counting value of GNP probes averaged from 10 field of views × 2*106 (0.2 cm2 area of chip is 2 million times 10 μm2 of each field of view) × 10 (1 mL = 10 times 100 μL of sample volume)/6.02*1023(molar value))× 180*103 (CEA molecule mass is 180 KDa) × 50% (slope of the calibration curve between antigen concentration and SEM counting value means caption) = Counting value × 0.01196 = Counting value × Correlation Coefficient. Therefore, the CEA counting Correlation Coefficient = 0.01196. For AFP counting Correlation Coefficient, the calculated method is the same as stated above except that molecular mass is 70 KDa, the AFP counting Correlation Coefficient is 0.00465. 3. Results and discussion 8


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3.1 Optimization of anti-CEA modified GNP probes To demonstrate the successful immobilization of functional CEA antibodies on the chips, chipbased immunoassay was first examined using a standard ELISA in a 96-well plate. The absorbance values (Table S1) were recorded at 450 nm with a UV-Vis spectrometer. As expected, the results confirmed that the chips were successfully modified with anti-CEA and have the ability to capture the CEA antigen from the sample. The anti-CEA modified GNP probes exhibit an intense red color similar to GNPs (Figure 1(a)), which is associated with the localized surface plasmon resonance (LSPR) band at around 520 nm (Figure S1). The apparent decrease of the LSPR band intensity after functionalization is attributed to decreased particle concentration because of the sample loss during the centrifugation steps. The GNP probes were stored in 4 oC for one week to test the colloidal stability of GNP probes. We found that the GNP probes incubated with antibodies at 4 μg/μL significantly precipitated (Figure 1(b), GNP probes-3), on the other hand, GNP probes generated from GNPs incubated with antibodies at 1 μg/μL and 2 μg/μL maintained good dispersion (Figure 1(b), GNP probes-1 and GNP probes-2), similar to that of the native GNPs (Figure 1(a), GNPs). TEM images also confirmed that GNPs (Figure 1(c)), GNP probes-1 (Figure 1(d)) and GNP probes-2 (Figure 1(e)) were all mono-dispersed but the GNP probes-3 (Figure 1(f)) generated from GNPs incubated with antibodies at 4 μg/μL displayed significant aggregation. Furthermore, we compared the capture efficiency of the two GNP probes with good dispersibility (GNP probes-1 and probes-2) using CEA functionalized chip. The process of CEA-modified chip is similar to the procedure of CEA antibody-immobilized chip described above. The experimental data is shown in Figure S2. The results show that the average number of GNP probes 1 originated from GNPs incubated with 1 μg/μL (16, Figure S2a) is 9



significantly lower than that of GNP probes-2 generated from GNPs incubated with antibody at 2 μg/μL (41, Figure S2b), strongly suggesting that GNP probes-2 has the optimal capture efficiency of CEA antigen. Notably, the optimization of anti-CEA concentration is not trivial as a subtle balance is required to prevent GNP probes aggregation which would lead to false positive results in the enumeration of GNPs using the GNP probe-assisted counting method. Therefore we selected GNP probes-2 which displayed good stability and capture efficiency as the GNP probes for all subsequent experiments.

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Figure 1. (a) Macrographs of GNPs and GNP probes. GNPs: the protein A functionalized GNP; GNP probe 1: GNP were generated from 1 mL of protein A conjugated GNPs at ~1 nM with 10 μL of CEA antibody at a concentration of 1 μg/μL. GNP probe 2: GNP were generated from 1 mL of protein A conjugated GNPs at ~1 nM with 10 μL of CEA antibody at a concentration of 2 μg/μL; GNP probe 3: GNPs were generated from 1 mL of protein A conjugated GNPs at ~1 nM with 10 μL of CEA antibody at a concentration of 4 μg/μL. (b) GNP and three GNP probes after being stored for one week at 4 oC. TEM images of GNP and three GNP probes：The protein A functionalized GNP (c) ; GNP probes were generated from 1 mL of protein A conjugated GNPs at ~1 nM with 10 μL of CEA antibody at a concentration of 1 μg/μL(d), 2 μg/μL(e) and 4 μg/μL(f), respectively. Scale bar: 200 nm.

3.2 Quantification of anti-CEA molecules attached on single GNP To examine how many antibody molecules were attached on the surface of each GNP probe, the GNP probes were collected and washed three times by centrifugation at 13,000 rpm for 10 min, 11



following by treatment with sodium dodecyl sulfate−polyacrylamide and gel electrophoresis (SDSPAGE). Data presented in Figure 2 (column c) confirms the successful conjugation of the GNPs with the CEA antibodies as shown by the interaction of protein A. By comparing the grey value of column b containing 2 μg of CEA antibodies with that of column c containing 1 mL of GNP probes (~6.0×1011 particles/mL), we can conclude that one GNP is covered with ~70 CEA antibody molecules.

Figure 2. SDS-PAGE analysis of GNP probes. Column a, Protein Marker; Column b, 2 μg CEA antibody; Column c, 100 μL of GNP probes at 1 nM; Column d: 100 μL of as-synthesized GNP at 1 nM.

3.3 Qualitative analysis of GNP probe-assisted counting chip with AFM AFM is a powerful tool to characterize the surface morphologies of chip-based sandwich immunoassay.24, 25 In this work, AFM was employed to qualitatively validate the recognition of antibodies functionalized chip with GNP (100 μL, 1 nM) probes in the presence of CEA at a higher 12


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concentration (100 μL, 1 nM). As compared with the bare silicon surface (Figure 3a-b), the surface of CEA antibodies immobilized chip (Figure 3c) was covered with particle-like shallow spots. The enlargement picture (Figure 3d) shows that one CEA antibody molecule with a relatively large size (molecular weight is ~120 KDa) locates near to two small size BSA molecules (~60 KDa). Figure 3e clearly shows the significant morphological changes of the sandwich chip resulted from the attachment of the GNP probes as compared with that of CEA molecules or BSA, which can be correlated to the presence of bright spots with approximately 15 nm in height (Figure 3f).

Figure 3. AFM analysis of chip-based sandwich immunoassay (a) Image of bare silicon wafer surface. (b) The cross-section profile of the dashed black line in Figure 3a. (c) AFM image of CEA antibodyfunctionalized surface. (d) The enlarged AFM images of the selected area in Figure 3c. (e) AFM image of the captured protein labeling with GNP probes. (f) The cross-section profile of the dashed blue line in Figure 3e.

3.4 GNP probe-assisted sandwich-counting of CEA in PBS After validation of the chip-based sandwich immunoassay with ELISA and AFM, we next investigated the feasibility of the proposed concept of counting the standard CEA molecules with 13



SEM. It is worth noting that a white dot of picture scanned by SEM represents a GNP probe, and a GNP probe surrogates a captured CEA molecule under these conditions. The number of captured CEA antigen molecules can be simply obtained by multiplying the mean number of white spots associated to the GNP probes in 10 randomly chosen SEM fields of views in triplicate independent experiments by two hundred thousand (the area of each silicon sample is approximately two million times that of a single field of view). In the proof-of-concept experiment, CEA molecules spiked at different concentrations were quantified with the GNP probe-assisted protein-counting strategy. The number of GNP particles on the silicon chip was strongly correlated with the increase in CEA concentrations as shown in Figure 4a-f. The negative controls included the chips modified with CEA antibodies (Figure 4a) and other antibodies (Figure S3). The limit of detection (LOD) of the assay was determined by classically extrapolating the calibration curve with three times the standard deviation of the background signal as depicted in Figure 4g.25 The data suggest that the SEM counting technique with its LOD = 0.045 ng/mL is 40-fold more sensitive than the standard colorimetric ELISA (Table S2 shows that the LOD of the CEA ELISA assay is approximately 1.8 ng/mL with the commercial ELISA kit). The LODs of standard commercial CEA ELISA kits are in the range of the clinical cut-off value (5 ng/mL), and therefore, CL automatic instrument with higher sensitivities are used clinically to detect CEA, rather than using simpler colorimetric ELISA. However, such instruments and equipment require large number of samples to be run in a costeffective fashion. A benefit of the proposed GNP-assisted counting strategy approach is that it can be performed using cost-effective and user-friendly benchtop SEM platforms, and in turn could be performed efficiently even in the case of small number of samples, allowing for the results to be quickly returned to the treating doctors, which will benefit the patients. Besides the cost-saving 14


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advantage, our platform is capable of detecting ultra-low number of CEA molecules, with 100 μL of 0.045 ng/mL being roughly equivalent to 1×107 molecules, implying the strong affinity and suitable orientation of the CEA antibody adsorbed on the protein A immobilized GNP probes. The concentrations of the CEA can be easily quantified by counting the number of particles on the SEM images with image analysis software, providing a facile way for the detection of CEA at extremely low concentration. Additionally, three chips were assayed with three different CEA concentrations (0, 0.36, and 1.8 ng/mL) to validate the reproducibility of the GNP probe-assisted counting method. The coefficient of variation (Table S3) of our platform was determined to be between 0.91 ~ 6.6, which demonstrates the good reproducibility of the GNP probe-assisted sandwich-counting method for the detection of CEA. As compared with the literature with regards to the detection of CEA, our strategy is 40 times more sensitive than GNP incorporated with ELISA methodology26 and 12 times more sensitive than state-of-the-art surface plasmon resonance biosensor.27,28

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Figure 4. SEM images in the presence of pure CEA at different concentrations (a) without CEA. (b) 0.09 ng/mL. (c) 0.36 ng/mL. (d) 1.8 ng/mL. (e) 3.6 ng/mL. (f) 9 ng/mL. (g) Comparison of calibration curves of SEM counting versus ELISA. Number of GNP particles averaged from ten SEM images of GNP probe-assisted counting chips at five concentrations. Scale bar: 1000 nm.

3.5 GNP probe-assisted sandwich-counting of CEA in serum and spiked AFP samples Following the validation of the GNP probe-assisted protein-counting chip strategy using standard CEA samples, we next investigated the selectivity of assay using HSA and gamma globulin (one of 16


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globulins) as interfering protein molecules because HSA and globulin account for more than 80 % of the total protein content in human serum.29 To this end, three samples containing low concentrations of CEA at 0 ng/mL (sample-1), 0.36 ng/mL (sample-2) and 1.8 ng/mL (sample-3) spiked in high concentrations of interfering proteins (4 % HSA and 2 % gamma globulin) were prepared. The samples were then assayed with the GNP probe-assisted protein-counting strategy. Three representative SEM images of the corresponding samples are shown in Figure 5. The control sample in Figure 5a clearly confirmed that there was only very low adsorption (1.6 of GNP particles per field of view averaged from 10 fields of views) in the absence of the CEA antigen even in the presence of high concentration of interfering proteins. The amounts of GNP probes averaged from 10 SEM field of views for sample-2 (Figure 5b) and sample-3 (Figure 5c) were 32 and 153, respectively. The calculated concentrations are 32 multiplied by 0.01196 (Correlation Coefficient, see 2.2.6 in Experimental section) for sample-2 (0.38 ng/mL) and 153 multiplied by 0.01196 for sample-3 (1.83 ng/mL). The CEA concentrations were obtained by interpolation of the counted GNPs into the SEM counting calibration curve (Figure 4g) for sample-2 (0.38 ng/mL) and sample3 (1.83 ng/mL), in excellent agreement with the true concentration of the samples (0.36 ng/mL and 1.8 ng/ml respectively). In addition, the assay was employed to quantify AFP, another tumor marker molecule.30 Two samples were spiked with 0.5 ng/mL and 2 ng/mL of AFP, respectively, in 2 % HAS for analysis. The experimental results also demonstrated the good reproducibility under interfering protein condition (Table S4). From these experiments, we can conclude that the GNP probe-assisted protein-counting strategy has excellent selectivity in addition to its remarkable sensitivity, which can meet the requirement for clinical analysis.

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Figure 5. Selectivity investigation of the GNP probes-assisted protein-counting strategy. Representative SEM images of CEA antibodies immobilized chip incubated with GNP probes and for different CEA concentrations in presence of interfering proteins (4 % HSA and 2 % globulin). (a) Sample-1 (0 ng/mL CEA). (b) Sample-2 (0.36 ng/mL CEA). (c) Sample-3 (1.8 ng/mL CEA). (d) The selectivity counting number of GNP for three CEA samples with high concentration of interfering proteins. Averaged GNP probes obtained from ten fields of views for sample-1, sample-2 and sample-3 (1.6, 32 and 153, respectively). Scale bars in images a-c: 500 nm. 3.6 GNP probe-assisted counting of CEA in cancer patients’ tissues and serum Finally, we aimed to demonstrate the clinical relevance of the proposed assay using clinical samples. A tumor tissue and a para-carcinomas nearby tissue were obtained from a colorectal cancer patient and quantified using the optimized method. To evaluate the accuracy of the counting platform, we first assayed these clinical samples with ELISA, which were performed following the standard antigen assay protocol. The measured UV-Vis absorbance values were then inserted into the ELISA calibration curve (Figure 4g) to obtain the CEA protein concentrations of 687 ng/mL for cancer tissue and 4.60 ng/mL for para-carcinoma tissue (these values were averaged from three independent measurements). Next, the solutions extracted from the tumor and nearby tissues (para-carcinoma

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tissue) were tested with the SEM counting platform. The data presented in Figure 6 indicates that the CEA protein concentration was 577.6 ng/mL for the cancer tissue and 4.20 ng/mL for the paracarcinoma tissue. Notably, the ratio of CEA concentration in tumor vs para-carcinoma tissues analyzed by ELISA and the GNP probe-assisted counting method was 149 and 137.5, respectively, demonstrating good correlations between the proposed counting platforms and the standard ELISA. In addition, we also investigated if the counting strategy is appropriate for quantifying the biomarker in serum samples because the serum CEA content is an important index for patients with colorectal cancer after surgical resection31 and is significantly related to metastatic tissue in recurrence patients.32 A blood sample from a healthy control (5.0 mL) was obtained from the health clinic of the Yangzhou University and the CEA concentration in the serum sample was determined. The calculated value (3.7 ng/mL) from counting number (Figure 6e) was found to be consistent with that obtained with ECL immunoassay with automated analysis system (3.24 ng/mL). Notably, one can easily finds that there is no particle aggregation in the SEM images for the detection of CEA in the clinical samples, suggesting our GNP probes are stable and robust and can be used under clinical conditions.

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Figure 6. Representative SEM images of GNP probe-assisted counting chips for tumor tissues, paracarcinoma tissues and serum at different dilutions. The average number of GNP probes per field of 20


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view is 477 and 244 for tumor tissues at 200-fold (a) and 400-fold (b) dilutions. (c) The average number of GNP probes per field of view is 146 for para-carcinoma tissues at 5-fold dilution. (d) The average number of GNP probes per field of view is 67 for para-carcinoma tissues at 10-fold dilution. (e) The average number of GNP probes per field of view is 119 for serum at 5-fold dilution. (f) The average number of GNP probes per field of view is 64 for serum at 10-fold dilution. (g) Enumeration of GNP for three real samples with our counting method. These average values are all averaged from randomly selected ten field of views. Scale bar: 1000 nm. 4. Conclusion A simple and ultra-sensitive GNP probe-assisted antigen counting strategy was successfully demonstrated. This method provides absolute quantification of cancer protein biomarkers and is compatible with the development of high throughput diagnostic and prognostic assays. The proofof-concept of this GNP probe-assisted counting method reported here using CEA (a tumor biomarker molecule) as a target of interest demonstrated excellent sensitivity, with a LOD down to 0.045 ng/mL. In addition, the GNP probe-assisted counting method was compared with ELISA using clinical samples and provided comparable measurements. The positive level of CEA in clinical sample is above 5 ng/mL, indicating the compatibility of the novel assay with current clinical practice. Furthermore, we have also successfully detected another tumor-marker AFP to demonstrate the wide applicability of the counting strategy. The platform makes full use of the advantages that single GNP can be easily imaged by SEM and embrace the powerful scanning ability (imaging many samples on the stage at one time) and it could also be employed for validating new biomarkers in early stage cancer tissues.33. Based on these results, the proposed GNP probeassisted SEM-counting chip platform paves the way for the development of an automated quantitative system for counting a panel of cancer biomarkers, especially considering the continuous improvement and miniaturization of SEM integrated with automatic scanning technique and counting analysis software. ASSSOCIATED CONTENT 21



Supporting Information The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acsami.xxxxxxx. Determination of anti-CEA antibody functionalized Chip (Table S1), UV-Vis spectra of GNP and GNP probes (Figure S1), investigation on the capture efficiencies of two GNP probes (Figure S2), LOD determination of CEA standard samples by ELISA (Table S2), reproducibility of GNP probe-assisted counting method (Table S3) and another tumor marker AFP samples assay with GNP probe-assisted counting method (Table S4), investigation on the cross-reaction between CEA anti-bodies immobilized chip and AFP samples (Figure S3).

AUTHOR INFORMATION Corresponding Author *Email: [email protected]

ORCID Xin Zhou: 0000-0003-2515-704X Chih-Tsung Yang: 0000-0003-4878-7589 Zhichao Lou: 0000-0002-0532-6902 Zhengfeng Xu: 0000-0002-7824-7578 Benjamin Thierry: 0000-0002-6757-2842 Ning Gu: 0000-0003-0047-337X Author Contributions Xin Zhou conceived the experiments, supervised the research project, performed the experiments, interpreted the data and wrote the manuscript. Chih-Tsung Yang participated in the design and discussion of all the experimental details and analyze some of the data with Xin Zhou, and wrote

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the manuscript. Qiaoshu Xu performed some of experiments. Zhichao Lou performed the AFM experiments. Zhengfeng Xu interpreted the data of tumor tissues and para-carcinoma tissues and revised the manuscript. Benjamin Thierry and Ning Gu participated in experiments discussion and revised the manuscript. Notes The authors declare no competing financial interest. ACKNOWLEDGMENTS We thank Mr. Chong Chen for SEM operation. This work was supported by the National Natural Science Foundation of China (31870989), the Start-up Fund provided by Yangzhou University (5020/137011016), A Project Funded by the Priority Academic Program Development of Jiangsu Higher Education Institution (PAPD) and the National Natural Science Foundation of China (81770236).

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(Table of Contents Graphic) Biomarker molecules in a small droplet sandwiched by antibody-chip and gold nanoparticle probes, forming clear “white spots” under SEM, therefore can be counted by software.

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Gold Nanoparticle Probe-Assisted Antigen-Counting Chip Using SEM

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