Microarray surface enhanced Raman scattering based immunosensor for multiplexing detection of mycotoxin in foodstuff

Sensors and Actuators B 266 (2018) 115–123

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Sensors and Actuators B: Chemical journal homepage: www.elsevier.com/locate/snb

Microarray surface enhanced Raman scattering based immunosensor for multiplexing detection of mycotoxin in foodstuff Yu Li a , Qian Chen b , Xuefang Xu c , Yongpeng Jin a , Yuan Wang a , Liying Zhang a , Wenjun Yang a , Lidong He d , Xiaoyu Feng e , Yiqiang Chen a,∗ a

State Key Laboratory of Animal Nutrition, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China Department of Cancer Genetics and Epigenetics, City of Hope National Medical Center, 1500 East Duarte Road, Duarte, CA 91010, USA c State Key Laboratory for Infectious Disease Prevention and Control, National Institute for Communicable Diseases Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing 102206, China d Department of Chemistry and Biochemistry, Florida State University, Tallahassee, FL, USA e Beijing Centers for Disease Control and Prevention, Beijing 100112, China b

a r t i c l e

i n f o

Article history: Received 23 December 2017 Received in revised form 5 March 2018 Accepted 11 March 2018 Available online 14 March 2018 Keywords: Surface enhanced Raman scattering Immunoassay Sensor Mycotoxin Multiplex Foodstuff

a b s t r a c t A surface enhanced Raman scattering (SERS) based immunosensor was developed for the detection of three mycotoxins (aflatoxin B1 , AFB1 ; zearalenone, ZEA; ochratoxin A, OTA) in foodstuff. Gold nanoparticles (GNPs) were labeled with 5,5-dithiobis(succinimidyl-2-nitrobenzoate) (DSNB) as Raman reporter and covalently linked with anti-mycotoxin antibodies as SERS nanoprobes, while AFB1 -BSA, ZEA-BSA, and OTA-BSA conjugates were covalently linked onto micro-array gold surface as corresponding capture addresses. This design allows three independent immunoreactions multiplexed on a single gold chip. After optimization, the limits of detection of the developed assay are 0.061–0.066 ␮g/kg for AFB1 , 0.53–0.57 ␮g/kg for ZEA, and 0.26–0.29 ␮g/kg for OTA in foodstuff. The spiked experiments presented an acceptable assay accuracy with recovery of 83.8%–108.1% and a reasonable assay precision with variation of coefficient less than 15%. Furthermore, the analysis of actual samples by our method demonstrated consistent results by comparison with conventional instrumental analysis. These results indicate that the developed SERS immunosensor can be a promising tool for simultaneously and rapidly monitoring multiple-mycotoxin levels in foodstuff. © 2018 Elsevier B.V. All rights reserved.

1. Introduction Mycotoxin is a type of toxic secondary metabolite produced by fungi on agricultural product in the field and during storage [1,2]. There are several hundreds of mycotoxins identified at present, which exhibit great structural diversity and demonstrate a variety of chemical and physicochemical properties [1]. Mycotoxins are potent toxins and can cause many adverse effects on humans and animals, such as cytotoxicity, nephrotoxicity, neurotoxicity, carcinogenicity, mutagenicity, immunosuppressive and estrogenic effects [1–3]. Therefore, their contamination in foodstuff has been considered as a potential threat to human health. To ensure consumer’s health, maximum tolerable levels of major mycotoxins such as aflatoxin (AFB1 ), zearalenone (ZEA), and ochratoxin A (OTA) in foodstuff have been established by countries of the world [4,5].

∗ Corresponding author. E-mail address: [email protected] (Y. Chen). https://doi.org/10.1016/j.snb.2018.03.040 0925-4005/© 2018 Elsevier B.V. All rights reserved.

A number of analytical methods have been developed for the detection of mycotoxins in various samples [6,7]. These methods can be divided into instrumental analysis and immunoassay. The former is often performed in laboratories with high accuracy and precision, while the latter is generally used for rapid detection in a non-laboratory environment. Instrumental methods are typically represented by liquid chromatography (LC) [8] and LC coupled with tandem mass spectrometry (LC–MS/MS) [9,10]. However, these methods require sophisticated equipment, highly skilled personnel, and generally take hours or days to obtain results, which limits their applications in common laboratories. The requirement for timely monitoring mycotoxin contamination in food industry has demanded more rapid and cost-effective methods, therefore, immunoassay including enzyme immunoassay [11–13], lateral flow immunoassay [14–16], together with some novel immunosensors [17–19] have been developed for mycotoxin detection. Nevertheless, most of these immunoassays can only detect a single mycotoxin at one time. Because mycotoxins often co-occur in crops [20], simultaneous detection of multiple

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mycotoxins is preferred to monitor mycotoxin contamination in foodstuff more effectively. Surface enhanced Raman scattering (SERS) based immunosensor acts as a good alternative for multiplexing, rapid, and highly sensitive detection of mycotoxin. It is a novel immunosensing platform which combines SERS labeling technique and antigen-antibody interaction. The origin of SERS arises from the electromagnetic enhancement and chemical enhancement of Raman label adsorbing onto the surface of roughened coinage metals, e.g. gold or silver nanoparticle [21]. SERS labeling has several advantages: First, Raman spectrum has strong molecular characteristics (1/10 to 1/100 narrower than fluorescence), and therefore it is very suitable for multiplex labeled immunoassay. Second, single wavelength light can excite multiple Raman label, which can beneficial for the multiplexing SERS readout. In addition, Raman label is not prone to self-quenching, and thus increasing the amount of Raman label leads to higher Raman signal and better assay sensitivities [22]. In recent years, SERS-based immunosensor has been introduced into the field of biomedicine (e.g., for diagnosis of cancer biomarker [23] and virus antigens [24]) and the field of food safety. Zhu et al. [25] developed a SERS immunoassay for highly sensitive detection of clenbuterol, which demonstrates that SERS-based immunosensor owns great potential in the detection of small molecules based on competitive immunoassay format. Subsequently, many researchers have separately developed several SERS-based immunosensors for the detection of zearalenone (ZEA) [26], chloramphenicol [27], ochratoxin A (OTA) [28], and salbutamol [29] in different sample matrixes. However, there was no study on developing a SERS-based immunosensor for the multiplexing detection of small molecules. To our knowledge, this is the first microarray-based SERS immunosensor for the simultaneous detection of three major mycotoxins in foodstuff. The method validation of this immunosensor was also presented. 2. Experimental 2.1. Chemicals Chemical standards of AFB1 , ZEA and OTA, bovine serum albumin (BSA), chloroauric acid were purchased from Sigma-Aldrich (St. Louis, USA). (3,3 -dithiobis[sulfosuccinimidylpropionate]) (DTSSP) was purchased from Pierce Biotechnology (Rockford, IL, USA). Goat anti-mouse IgG was obtained from Beijing Dingguo Changsheng Biotechnology Co. Ltd. (Beijing, China). De-ionized water was pre-

pared using a water purification system (Millipore, Bedford, USA). Other chemical reagents were bought from Beijing Regent Corporation (Beijing, China). 5,5-Dithiobis(succinimidyl-2-nitrobenzoate) (DSNB) was synthesized according to a previously reported procedure [30]. The synthesis of AFB1 -BSA, ZEA-BSA and OTA-BSA conjugates and the preparation of respective monoclonal antibodies (mAbs) were described in supplementary material. 2.2. Synthesis of gold nanoparticles (GNPs) GNPs were synthesized according to the method of Frens [31] with some modifications. Briefly, 100 mL of 0.01% (m/v) chloroauric acid in water was heated to boiling, then 1.2 mL of 1.0% trisodium citrate (w/v) was added into the solution. After reaction under constant stirring for 15 min, the solution was cooled at room temperature, and de-ionized water was complemented to the initial volume of 100 mL. The obtained GNPs solution is stable at 4 ◦ C for at least three months. The particle size of GNPs was then determined by transmission electron microscopy (TEM, JEOL USA Inc., Peabody, USA). 2.3. Preparation of SERS nanoprobes SERS nanoprobes were prepared according to the procedure of Granger et al. [32] with some modifications. Briefly, 10 mL of 36 nm GNPs as prepared above was mixed with 400 ␮L of 50 mM borate buffer (pH 8.5), followed by the addition of 200 ␮L 1 mM DSNB in acetonitrile. After 0.5 h reaction at ambient temperature, appropriate volumes of 1.0 mg/mL mAbs (anti-AFB1 , anti-ZEA or anti-OTA) were added and reacted for 1 h with mild agitation. Finally, 1 mL of 10% BSA in 2.0 mM borate buffer was used for blocking any uncoated sites on GNP surface. To remove excessive reagent, these suspensions were centrifuged at 8000g for 10 min. The resuspension and centrifugation steps were then repeated twice and finally the precipitate was re-suspended in 10.0 mM phosphate buffer (pH 7.4) containing 1% BSA. The three SERS nanoprobes were then mixed at a volume ratio of 2:2:1 (anti-AFB1 : anti-ZEA: antiOTA) and ready for use. 2.4. Hydrodynamic size determination Nano ZS Zetasizer (Malvern Instruments Ltd., Worcestershire, UK) was used to determine the hydrodynamic sizes of GNPs and SERS nanoprobes. Three repeats for each measurement were

Fig. 1. Schematic illustration of multiplex SERS-based immunosensor.

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performed at room temperature. The hydrodynamic size was calculated from the translation diffusion coefficient, which was measured by dynamic light scattering and then applied to StokeskT , where d(H) is hydrodynamic Einstein equation: d(H) = 3˘D

diameter, k is Boltzmann’s constant, T is absolute temperature, ␩ is viscosity, and D is translational diffusion coefficient [33]. 2.5. Preparation of capture address

The capture addresses were prepared on a 1 × 1 cm glass slide which was previously coated with a 100 nm depth gold surface by vacuum evaporation. Briefly, a parafilm mask with a 2 × 2 array of 2.0 mm dia. holes was gently pressed and was then thermally sealed onto the gold surface, which provides an uncoated gold area surrounded by a hydrophobic barrier to confine droplets of aqueous fluids (Fig. 1). The gold substrate, namely the glass slide with four capture addresses, was then fixed onto a 24-well plate well by double faced adhesive tape, then 1.0 mL of 2.0 mM DTSSP dissolved in citrate buffer (10.0 mM, pH 5.0) was added into each plate well, which was then incubated at room temperature for 1 h. After rinsing the gold substrates with citrate buffer for two times, 8 ␮L of capture antigen (5.0 ␮g/mL, AFB1 -BSA, ZEA-BSA or OTA-BSA) or goat anti-mouse antibody (1.0 ␮g/mL) in phosphate buffer saline (PBS, 10.0 mM, pH 7.4) were added onto respective DTSSP modified capture addresses as shown in Fig. 1, and the 24-well plate were allowed to incubate at 37 ◦ C for 2 h in a humidity chamber. Each gold substrate was subsequently rinsed with 10.0 mM PBST, followed by exposure to 1.0% BSA solution at 37 ◦ C for 1 h. Finally, the substrates were rinsed with 10.0 mM PBST and ready for use. 2.6. SERS immunosensing assay Five hundred microliter of standard solution or sample solution and 500 ␮L of SERS nanoprobes were successively added into plate well containing capture substrate, and then the 24-well plate was incubated at 37 ◦ C for 1 h. After a washing step with PBST, the capture substrate was dried at 37 ◦ C for 15 min, and then the Raman spectra was collected with a SmartRaman Spectrometer (Thermo Fisher Scientific, Madison, WI, USA). The spectrometer is equipped with a 30 mW, 632.8 nm He-Ne laser, a thermoelectrically cooled CCD detector, and an OMMIC software suit. A 10 × objective was used to produce a 5 ␮m diameter laser spot. The signal integration time was 2 s, with an average of 10 measurements collected at different locations on each capture address. The collected Raman spectra ranged from 3500 to 50 cm−1 , and the signal at 1334 cm−1 was used for quantification analysis. 2.7. Sample pretreatment and analysis Aliquots (5.0 g) of ground samples (corn, rice and wheat) were weighed and transferred to 50 mL polypropylene centrifuge tubes. After that, 25 mL of 70% (v/v) methanol aqueous solution was added and vortexed for 2 min for sufficient extraction. The solution was then centrifuged at 8000g for 5 min, and 1 mL of the supernatant was mixed with 9 mL of PBS (10 mM, containing 0.15 M sodium chloride, pH 7.4). Finally, the mixture was applied to the SERS-based immunosening assay. For spiked experiment, mycotoxin standard solutions were added to blank samples to produce spiked concentrations of 0.2, 1, and 5 ␮g/kg for AFB1 , 1, 5 and 25 ␮g/kg for ZEA, 0.5, 2.5 and 10 ␮g/kg for OTA, respectively. After treated as described above, the obtained sample solution was applied to the multiplex SERSbased immunoassay. For real sample analysis, 16 actual samples collected from markets were treated as above and then measured

Fig. 2. Typical Raman spectrum of DSNB modified SERS nanoprobe.

by the developed SERS immunoassay and LC–MS/MS analysis [9]. The analytical results by the two methods were compared. 3. Results and discussion 3.1. Preparation of capture substrate The preparation process of capture substrate was demonstrated in Fig. S1 (Supplementary material). Each capture substrate contains three antigen addresses and one control address, which forms a 2 × 2 microarray. Three independent immunoreactions can occur on respective antigen addresses. To prevent the cross-adsorption of antigens onto other capture addresses, DTSSP was used to covalently link mycotoxin-BSA conjugate to respective capture address. DTSSP is a water-soluble cross-linker that contains a central disulfide bond and two sulfo-NHS ester ends [34]. The disulfide bond of DTSSP can firstly interact with gold surface by forming Au-S bond, and the sulfo-NHS ester ends of DTSSP can react with the primary amine of coating antigen at pH 7.4 to form a stable amide bonds. Finally, surplus reactive sites of DTSSP on gold surface can then be blocked by the amino groups of BSA (Fig. S1, Supplementary material). Because antibody-antigen interaction is prone to be influenced by solvent environment such as pH value and ionic concentration, one control address covalently linked with goat antimouse antibody was introduced to verify if the immunoassay was properly performed. 3.2. Preparation of SERS nanoprobe To prepare SERS nanoprobe, GNPs were synthesized by reducing chloroauric acid with citrate solution, and their size was measured to be 36 nm by TEM. The GNPs were firstly modified with a layer of DSNB by Au-S bond, and the NHS ester of DSNB can react with the amine groups of antibody to produce a stable amide bond and thus form an antibody layer (Fig. S2, Supplementary material). DSNB has been widely used as Raman label because it is a bi-functional reagent which can stably linked with both GNPs and antibody. Furthermore, it can produce strong characteristic SERS signal [35]. As shown in Fig. 2, the characteristic bands of DSNB in SERS spectrum mainly include 1334, 1058 and 1556 cm−1 . According to literature [36,37], the band at 1334 cm−1 is assigned to the symmetric stretch (vs (NO2 )) for the nitro group of DSNB, whereas those at 1058 and 1556 cm−1 would arise from aromatic ring modes of the label. As the band of 1334 cm−1 is the strongest feature in the spectrum, the intensity of vs (NO2 ) was selected for the quantitative analysis in the SERS immunoassay. To further evaluate the SERS enhancement effect of GNPs, the concentration of DSNB adsorbed on GNPs was measured, and the Raman intensities of DSNB-GNP conjugate and free DSNB were compared (Supplementary material). The result indicated that the concentration of DSNB adsorbed on 36 nm GNP (OD526nm = 1.0) is about 0.87 ␮M. The DSNB-GNP conjugate at this

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Fig. 3. The effect of added antibody concentration on hydrodynamic sizes (A) of SERS nanoprobes (GNP-DSNB-Ab), Raman intensities and inhibition rates (B-D) of SERS RI , where RI represents the Raman intensity resulted from standard mycotoxin solution, RI0 represents the immunoassay (n = 3). Inhibition rates were expressed as 1 − RI0 Raman intensity resulted from blank solution. The concentrations of standard solution were 10 pg/mL, 100 pg/mL and 100 pg/mL for AFB1 , ZEA and OTA, respectively.

concentration can produce strong SERS signal with intensity of 1246 a.u. at 1334 cm−1 . However, free DSNB at this concentration cannot produce any measurable signal. These results demonstrated that GNPs have greatly enhanced the Raman intensity of DSNB. Because a single DSNB-modified GNP can covalently link with several antibodies, SERS nanoprobe works like a multivalent antibody (Fig. 1). In theory, when reacting with multivalent antigen, the apparent affinity constant (Ka) of multivalent antibody can be expressed as: Ka = (K1 )n , where n is the number of antigen binding sites, K1 is the intrinsic affinity constant of individual antibody [38]. The study of Safenkova et al. [39] also proved that the affinity of the interaction between antigen and Ab-GNP conjugates is one to three orders magnitude higher than that of the interaction between antigen and free antibody depending on the sizes of GNPs. To further confirm that the surface antibody densities of SERS nanoprobe would affect its apparent affinity and in turn would influence SERS immunoassay sensitivity, we systematically investigated the relationship between the surface antibody density and SERS assay sensitivity in this study. As shown in Fig. 3A, with the increase of added antibody concentration in 1.0 mL of 36 nm GNPs (OD526nm = 1.0), the hydrodynamic sizes of all three SERS nanoprobes (GNP-DSNB-Ab conjugates) also increase corresponding to higher surface antibody densities on respective SERS nanoprobes. However, the hydrodynamic sizes of the SERS nanoprobes reach a plateau at certain antibody concentrations (20, 20 and 10 ␮g/mL for AFB1 , ZEA, and OTA, respectively), indicating that the reactive sits on GNPs were almost saturated by the antibodies. Fig. 3B–D shows that with the increase of added antibody concentration, the Raman intensities of SERS immunoassay were significantly increased, while the SERS immunoassay sensitivities, expressed by inhibition rates, were dramatically decreased in the certain range. When the antibody concentration is saturated (as shown in Fig. 3A), both the Raman intensities and assay sensitivities remained constant. These results are consistent with our expectation that the added antibody concentration for preparing SERS nanoprobe can significantly

affect SERS immunoassay sensitivity by changing the surface antibody density of SERS nanoprobe. Comprehensively considering the Raman intensities and assay sensitivities, the final antibody concentrations for the preparation of SERS nanoprobes were determined to be 5, 10 and 5 ␮g/mL GNPs, respectively. After the covalently linkage of antibody on DSNB modified GNP, BSA was used to block the unreactive sites on GNP and the prepared SERS nanoprobe was dispensed in PBS containing 1% BSA for longtime storage stability. To evaluate the effect of BSA on the SERS immunosensing assay, the SERS nanoprobes were resuspended in PBS and PBS containing 1% BSA, respectively, and they were then applied to the detection of two actual samples. The result in Table S1 shows that the addition of BSA did not make significant effect on the analytical results. 3.3. SERS immunosensing assay The incubation time of SERS nanoprobe and capture substrate directly determined the immunosensing turn-around time and thus it was firstly optimized. As shown in Fig. 4, a measurable SERS signal can be obtained after incubation for 5 min. The Raman intensity of SERS-based immunoassay increases over time until a plateau after 60 min incubation. Therefore we selected 60 min as the incubation time of this immunoassay. Because mycotoxins are all small molecules, a competitive immunoassay format was used in this study where mycotoxin molecule and capture antigen compete for the limited amount of antibody on SERS nanoprobe. The concentration of mycotoxin in sample was quantified by the SERS signal from the bound SERS nanoprobe (Fig. 1). Fig. 5 shows the SERS spectra and the corresponding dose-response plot. The intensities of all spectral features decrease as the levels of mycotoxin increase. This trend follows the expectation for a competitive immunoassay. When higher concentration of mycotoxin exists in sample, fewer SERS nanoprobes would bind with the capture antigen, and thus SERS signal would decrease, which also confirmed that the spectral features origi-

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Fig. 4. Effect of incubation time on the Raman intensity of SERS immunoassay.

nate from SERS nanoprobes. According to the SERS intensities in Fig. 5, it is estimated that about 95.6%, 85.2% and 94.6% of SERS nanoprobes were displaced from capture addresses by 1000 pg/mL of AFB1 , 10000 pg/mL of ZEA and 5000 pg/mL of OTA, respectively. Fig. 6 exhibited the actual substrates to construct the calibration curve. The SERS intensities of each capture address in substrates were acquired. The dose-response curve was then established by plotting the intensity of vs (NO2 ) (1334 cm−1 ), the strongest feature in each spectrum, against the logarithmic value of mycotoxin concentration (Fig. 5). The average intensity from spectra was collected from ten different locations on each capture address. The signal demonstrates a linear decrease with a logarithmic increase in mycotoxin concentration. The linear detection ranges for AFB1 , ZEA, and OTA were measured to be around 1–1000 pg/mL, 10–10000 pg/mL, and 5–5000 pg/mL, respectively. The detection specificity of the multiplex SERS-based immunosensor was then investigated. The results indicated that with the increased concentration of a single mycotoxin, the SERS signal on respective capture address decreased, while the SERS signals on the other two capture addresses remained unchanged (Fig. 7A–C). This indicates that simultaneous detection of the three mycotoxins does not interfere with each other. Furthermore, despite of negative or positive sample, SERS signals of control address remain at 1329 ± 54 a.u. (Fig. 7A–C), indicating that the SERS immunoassay was performed properly. Furthermore, when one specific SERS nanoprobe was absent in the mixture of SERS nanoprobes, the SERS signal of respective antigen address remained acceptable low level at 35 ± 10 a.u. (Fig. 7D), which implied that there was no significant cross-adsorption of SRES nanoprobes onto other antigen addresses. In addition, when GNPs, GNP-BSA conjugate, GNP-DSNB-BSA conjugate, and GNP-Ab conjugates were individually applied to antigen addresses, no measurable signals were obtained, demonstrating there were no significant non-specific adsorption for this immunoassay. For the evaluation of the potential interference of nitrite and heavy metals on the SERS immunosensing assay, 100 mg/kg of nitrite, 20 mg/kg of lead, chromium and cadmium, which were much higher than the tolerable limits set by China [40], were respectively spiked into two actual samples and the samples were then analyzed by the developed SERS immunosensing assay. The result showed that these substances would not pose significant interference on the assay accuracy of this assay (Table S1). 3.4. Method validation To validate the developed multiplex immunoassay, a spiked recovery experiment was performed. Blank corn, rice, and wheat samples were spiked with a series concentration of mycotoxins and analyzed by the developed SERS-based immunosensor. The

Fig. 5. SERS spectra and dose-response curves plotted from results of multiplex SERS-based immunosensor for AFB1 (A), ZEA (B) and OTA (C).

assay sensitivity of this immunosensor was evaluated by limit of detection (LOD) which was defined as the concentration of mycotoxin that results in 10% decline in SERS signal compared to blank sample. The LOD values were calculated to be 0.061–0.066 ␮g/kg for AFB1 , 0.53–0.57 ␮g/kg for ZEA, and 0.26–0.29 ␮g/kg for OTA in foodstuff (Table S2), which were far below the tolerable limits set by authorities [4,5]. Furthermore, the assay sensitivities are comparable to or better than most of SERS-based immunosensor and other biosensors for the detection of mycotoxin (Table 1), except that Li et al. [42] developed a SERS aptasensor for AFB1 and Liu et al. [26] reported a SERS immunoassay for ZEA with higher sensitivity than that of our assay. However, these two methods and most of other immunosensors can only detect one target mycotoxin. In

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Fig. 6. Typical micro-array SERS substrate for constructing the calibration curve.

Fig. 7. The specificity of multiplex SERS-based immunosensor for AFB1 , ZEA and OTA (n = 3). Fig. 4A–C shows the change of SERS signal on three capture addresses with the increased concentration of AFB1 (A), ZEA (B) and OTA (C) respectively; Fig. 4D shows the SERS signal of each capture address in the absence of corresponding SERS nanoprobe.

contrast, our developed SERS-based immunosensing assay has a multiplexing detection capability for three mycotoxins with high assay sensitivity. The assay accuracy and precision of this immunosensor were also evaluated by the spiked recovery experiment. The results showed that at the spiked concentrations of 0.2–5 ␮g/kg for AFB1 , 1–25 ␮g/kg for ZEA, and 0.5–10 ␮g/kg for OTA, the recoveries ranged from 83.8%-108.1% with variations of coefficient (CV) less than 15% (Table 2), demonstrating that the multiplex SERS-based immunosensor can be used for sample analysis. To further validate the developed method, 16 actual samples were analyzed by

the developed immunosensor and LC–MS/MS method [9], respectively. As shown in Table 3, ten samples were measured to be negative by the developed SERS-based immunosensor which were confirmed by LC–MS/MS analysis, indicating that there were no false negative results for this batch of actual sample analysis. Six samples were found to contaminate with more than one mycotoxin (Table 3). Plotting of the LC–MS/MS analysis (y axis) and the SERS-based immunosensor (x axis) showed a great correlation between these two methods with the linear regression equation y = 0.9939x-0.4688 (R2 = 0.9978) (Fig. 8). One corn sample and one wheat sample from the six positive samples were measured to

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Table 1 Brief literature review of SERS-based and other immunosensor for mycotoxin. Method

Analyte

LOD

Linear range

Reference

SERS-based immunoassay SERS-based aptasensor SERS-based aptasensor SERS-based aptasensor SERS-based aptasensor

AFB1 AFB1 AFB1 AFB1 AFB1 OTA ZEA AFB1 AFB1 ZEA OTA OTA

0.1 ng/mL 0.4 fg/mL 0.036 ng/mL 0.54 pg/mL 0.03 ng/mL 0.006 ng/mL 1 pg/mL 0.01 ng/mL 1 ng/mL 0.48 ng/mL 0.25 ng/mL

1–105 ng/mL 1 × 10−6 –1 ng/mL 0.01–100 ng/mL 0.001–10 ng/mL 0.05–100 ng/mL 0.01–100 ng/mL 1–1000 pg/mL Not provided Not provided

Ko et al. [41] Li et al. [42] Chen et al. [43] Yang et al. [44] Zhao et al. [28]

0.005 ng/mL

0.2–40

Bianoco et al. [46]

SERS-based immunoassay Planar waveguide-based immunosensor SPI and SCI-based biosensor

SPR-based biosensor

Liu et al. [26] Nabok et al. [17] Orlov et al. [45]

Table 2 Spiked recoveries of mycotoxins in samples measured by the multiplex SERS-based immunosensor (n = 4). Analyte

Spiked concentration (␮g/kg)

AFB1

0.2 1 5 1 5 25 0.5 2.5 10

ZEA

OTA

Rice

Corn

Wheat

Recovery (%)

CV (%)

Recovery (%)

CV (%)

Recovery (%)

CV (%)

101.4 97.3 100.2 99.5 92.4 83.8 106.7 102.5 91.2

13.7 11.2 9.7 9.1 11.5 7.2 9.1 8.3 9.5

97.7 103.3 94.3 105.9 102.5 98.7 99.1 98.3 89.3

10.3 8.8 7.5 11.8 9.7 8.5 10.5 11.0 8.3

108.1 95.9 101.2 102.9 97.7 95.4 100.2 97.5 85.7

14.7 12.9 9.5 13.6 12.0 9.8 12.7 13.2 8.0

Table 3 Detection results of mycotoxin in real samples by SERS-based immunosensor and LC–MS/MS method. Sample No.

1

2

3

4

5

6

7

8

Sample type SERS (␮g/kg) LC–MS/MS (␮g/kg) Sample No. Sample type SERS (␮g/kg)

Corn –

Corn ZEA, 32.4 ZEA, 35.1 10 Rice

Corn

Corn ZEA, 102.7 ZEA, 101.1 12 Rice

Corn

Corn AFB1 , 5.7 AFB1 , 4.9 14 Wheat

Corn

Corn

15 Wheat OTA, 7.8

16 Wheat

OTA, 7.1

–

LC–MS/MS (␮g/kg) (␮g/kg)

9 Corn AFB1 , 14.5; ZEA, 44.4 AFB1 , 11.7; ZEA, 43.1

11 Rice

13 Wheat AFB1 , 2.6; ZEA, 9.4 AFB1 , 2.3; ZEA, 9.1

–, negative; +, positive

Fig. 8. Comparison of analytical results by SERS immunoassay (x axis) and LC–MS/MS method (y axis) for actual samples.

contain both AFB1 and ZEA. For these co-contamination cases, the developed multiplex SERS-based immunosensor is advantageous to simplex immunoassay because it can further reduce assay time and increase detection efficiency. Furthermore, to evaluate the stability of this SERS-based immunosensing assay, SERS nanoprobes and capture substrates were stored at 4 ◦ C for 2 months and were applied to SERS immunoassay for the same two actual samples

Fig. 9. The analytical result of two actual samples by the SERS-based immunoassay in the period of 8 weeks. AFB1 and ZEA exist in the same sample, OTA exists in another sample.

(stored at 4 ◦ C) once a week. The results showed that the measured values from each week were consistent with each other (Fig. 9), demonstrating that this SERS immunoassay can be stable at 4 ◦ C for at least 2 months. Therefore, the developed multiplex SERS

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Biography Yiqiang Chen is an associate professor in State Key Laboratory of Animal Nutrition, College of Animal Science and Technology, China Agricultural University. He received a Ph.D degree in veterinary pharmacology and toxicology from China Agricultural University, and then worked as a postdoctoral fellow for 2.5 years in Department of Chemistry, University of Utah. In 2013, he came back to China Agricultural University as a faculty member. His recent research focus on the development of SERS-based immunosensor for rapidly monitoring chemical contaminants in animal feed and food.