A Calibration Curve Implanted Enzyme-Linked Immunosorbent Assay for Simultaneously Quantitative Determination of Multiplex Mycotoxins in Cereal Samples, Soybean and Peanut
Abstract
:1. Introduction
2. Results and Discussion
2.1. The Principles of the Developed Method
2.2. C-ELISA Calibration Curve
2.3. Optimization of Sample Pretreatment in C-ELISA Assay
2.4. Specificity Evaluation
2.5. Comparison with HPLC
3. Conclusions
4. Experimental Section
4.1. Materials and Reagents
4.2. Equipment
4.3. Optimization of C-ELISA Standard Curve
4.4. The Designed Analysis Software
4.5. Sample Preparation for C-ELISA Assay
4.6. Detection of Samples by C-ELISA
4.7. Specificity Evaluation
4.8. Detection of Samples by HPLC
4.9. Data Analysis
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
- Wang, Y.; Ning, B.; Peng, Y.; Bai, J.; Liu, M.; Fan, X.; Sun, Z.; Lv, Z.; Zhou, C.; Gao, Z. Application of suspension array for simultaneous detection of four different mycotoxins in corn and peanut. Biosens. Bioelectron. 2013, 41, 391–396. [Google Scholar] [CrossRef]
- Deng, G.; Xu, K.; Sun, Y.; Chen, Y.; Zheng, T.; Li, J. High sensitive immunoassay for multiplex mycotoxin detection with photonic crystal microsphere suspension array. Anal. Chem. 2013, 85, 2833–2840. [Google Scholar] [CrossRef]
- Yue, S.; Jie, X.; Wei, L.; Bin, C.; Dou Dou, W.; Yi, Y.; QingXia, L.; JianLin, L.; TieSong, Z. Simultaneous detection of Ochratoxin A and fumonisin B1 in cereal samples using an aptamer–photonic crystal encoded suspension Array. Anal. Chem. 2014, 86, 11797–11802. [Google Scholar] [CrossRef] [PubMed]
- Chen, Y.; Meng, X.; Zhu, Y.; Shen, M.; Lu, Y.; Cheng, J.; Xu, Y. Rapid detection of four mycotoxins in corn using a microfluidics and microarray-based immunoassay system. Talanta 2018, 186, 299–305. [Google Scholar] [CrossRef] [PubMed]
- Chauhan, R.; Singh, J.; Sachdev, T.; Basu, T.; Malhotra, B.D. Recent advances in mycotoxins detection. Biosens. Bioelectron. 2016, 81, 532–545. [Google Scholar] [CrossRef] [PubMed]
- Turner, N.W.; Subrahmanyam, S.; Piletsky, S.A. Analytical methods for determination of mycotoxins: A review. Anal. Chim. Acta 2009, 632, 168–180. [Google Scholar] [CrossRef]
- Van den Meersche, T.; Pamel, E.V.; Poucke, C.V.; Herman, L.; Heyndrickx, M.; Rasschaert, G.; Daeseleire, E. Development, validation and application of an ultra high performance liquid chromatographic-tandem mass spectrometric method for the simultaneous detection and quantification of five different classes of veterinary antibiotics in swine manure. J. Chromatogr. A 2016, 1429, 248–257. [Google Scholar] [CrossRef] [PubMed]
- Van Pamel, E.; Verbeken, A.; Vlaemynck, G.; De Boever, J.; Daeseleire, E. Ultrahigh-performance liquid chromatographic–tandem mass spectrometric multimycotoxin method for quantitating 26 mycotoxins in maize silage. J. Agric. Food Chem. 2011, 59, 9747–9755. [Google Scholar] [CrossRef]
- Xu, J.; Li, W.; Liu, R.; Yang, Y.; Lin, Q.; Xu, J.; Shen, P.; Zheng, Q.; Zhang, Y.; Han, Z.; et al. Ultrasensitive low-background multiplex mycotoxin chemiluminescence immunoassay by silica-hydrogel photonic crystal microsphere suspension arrays in cereal samples. Sens. Actuators B Chem. 2016, 232, 577–584. [Google Scholar] [CrossRef]
- Zhang, Z.; Hu, X.; Zhang, Q.; Li, P. Determination for multiple mycotoxins in agricultural products using HPLC-MS/MS via a multiple antibody immunoaffinity column. J. Chromatogr. B 2016, 1021, 145–152. [Google Scholar] [CrossRef] [PubMed]
- Al-Taher, F.; Banaszewski, K.; Jackson, L.; Zweigenbaum, J.; Ryu, D.; Cappozzo, J. Rapid method for the determination of multiple mycotoxins in wines and beers by LC-MS/MS using a stable isotope dilution assay. J. Agric. Food Chem. 2013, 61, 2378–2384. [Google Scholar] [CrossRef] [PubMed]
- Van Pamel, E.; Vlaemynck, G.; Heyndrickx, M.; Herman, L.; Verbeken, A.; Daeseleire, E. Mycotoxin production by pure fungal isolates analysed by means of an UHPLC-MS/MS multi-mycotoxin method with possible pitfalls and solutions for patulin producing isolates. Mycotoxin Res. 2011, 27, 37. [Google Scholar] [CrossRef] [PubMed]
- Olsson, J.; Börjesson, T.; Lundstedt, T.; Schnürer, J. Detection and quantification of ochratoxin A and deoxynivalenol in barley grains by GC-MS and electronic nose. Int. J. Food Microbiol. 2002, 72, 203–214. [Google Scholar] [CrossRef]
- Liu, R.; Li, W.; Cai, T.; Deng, Y.; Ding, Z.; Liu, Y.; Zhu, X.; Wang, X.; Liu, J.; Liang, B.; et al. TiO2 nanolayer-enhanced fluorescence for simultaneous multiplex mycotoxin detection by aptamer microarrays on a porous silicon surface. ACS Appl. Mater. Interfaces 2018, 10, 14447–14453. [Google Scholar] [CrossRef] [PubMed]
- Wang, Y.; Liu, N.; Ning, B.; Liu, M.; Lv, Z.; Sun, Z.; Peng, Y.; Chen, C.; Li, J.; Gao, Z. Simultaneous and rapid detection of six different mycotoxins using an immunochip. Biosens. Bioelectron. 2012, 34, 44–50. [Google Scholar] [CrossRef] [PubMed]
- Foubert, A.; Beloglazova, N.V.; Gordienko, A.; Tessier, M.D.; Drijvers, E.; Hens, Z.; De Saeger, S. Development of a rainbow lateral flow immunoassay for the simultaneous detection of four mycotoxins. J. Agric. Food Chem. 2017, 65, 7121–7130. [Google Scholar] [CrossRef]
- Song, S.; Liu, N.; Zhao, Z.; Njumbe Ediage, E.; Wu, S.; Sun, C.; De Saeger, S.; Wu, A. Multiplex lateral flow immunoassay for mycotoxin determination. Anal. Chem. 2014, 86, 4995–5001. [Google Scholar] [CrossRef]
- Yan, J.X.; Hu, W.J.; You, K.H.; Ma, Z.E.; Xu, Y.; Li, Y.P.; He, Q.H. Biosynthetic mycotoxin conjugate mimetics-mediated green strategy for multiplex mycotoxin immunochromatographic assay. J. Agric. Food Chem. 2020, 68, 2193–2200. [Google Scholar] [CrossRef]
- Hou, S.; Ma, J.; Cheng, Y.; Wang, H.; Sun, J.; Yan, Y. One-step rapid detection of fumonisin B1, dexyonivalenol and zearalenone in grains. Food Control 2020, 117, 107107. [Google Scholar] [CrossRef]
- Zhou, Q.; Tang, D. Recent advances in photoelectrochemical biosensors for analysis of mycotoxins in food. TrAC Trend. Anal. Chem. 2020, 124, 115814. [Google Scholar] [CrossRef]
- Urusov, A.E.; Zherdev, A.V.; Petrakova, A.V.; Sadykhov, E.G.; Koroleva, O.V.; Dzantiev, B.B. Rapid multiple immunoenzyme assay of mycotoxins. Toxins 2015, 7, 238–254. [Google Scholar] [CrossRef] [PubMed]
- Shen, P.; Li, W.; Liu, Y.; Ding, Z.; Deng, Y.; Zhu, X.; Jin, Y.; Li, Y.; Li, J.; Zheng, T. High-throughput low-background G-quadruplex aptamer chemiluminescence assay for ochratoxin A using a single photonic crystal microsphere. Anal. Chem. 2017, 89, 11862–11868. [Google Scholar] [CrossRef] [PubMed]
- Yang, Y.; Li, W.; Shen, P.; Liu, R.; Li, Y.; Xu, J.; Zheng, Q.; Zhang, Y.; Li, J.; Zheng, T. Aptamer fluorescence signal recovery screening for multiplex mycotoxins in cereal samples based on photonic crystal microsphere suspension array. Sens. Actuators B: Chem. 2017, 248, 351–358. [Google Scholar] [CrossRef]
- Xu, K.; Sun, Y.; Li, W.; Xu, J.; Cao, B.; Jiang, Y.; Zheng, T.; Li, J.; Pan, D. Multiplex chemiluminescent immunoassay for screening of mycotoxins using photonic crystal microsphere suspension array. Analyst 2014, 139, 771–777. [Google Scholar] [CrossRef] [PubMed]
- Zhang, X.; Yu, X.; Wen, K.; Li, C.; Mujtaba Mari, G.; Jiang, H.; Shi, W.; Shen, J.; Wang, Z. Multiplex lateral flow immunoassays based on amorphous carbon nanoparticles for detecting three fusarium mycotoxins in maize. J. Agric. Food Chem. 2017, 65, 8063–8071. [Google Scholar] [CrossRef]
- Li, J.; Macdonald, J. Multiplexed lateral flow biosensors: Technological advances for radically improving point-of-care diagnoses. Biosens. Bioelectron. 2016, 83, 177–192. [Google Scholar] [CrossRef]
Analytes | Standard Curve | IC50 (ng/g) | LOD/(ng/g) | Working Range/ (ng/g) |
---|---|---|---|---|
AFB1 | yAFB1 = −45.851x + 96.820, R2 = 0.991 | 0.093 | 0.03 | 0.03~0.81 |
ZEN | y ZEN = −47.158x + 25.200, R2 = 0.987 | 3.38 | 1.00 | 1.00~27.00 |
DON | yDON = −43.846x − 6.077, R2 = 0.962 | 17.70 | 5.00 | 5.00~135.00 |
Analytes | Spiked Concentration (ng/g) | CV (%) | 0.1 mol/L Tris-HCL | 0.1 mol/L PBS | 0.1 mol/L PB | ||||||
---|---|---|---|---|---|---|---|---|---|---|---|
Recovery (%) | False Positive Rate (%) | False Negative Rate (%) | Recovery (%) | False Positive Rate (%) | False Negative Rate (%) | Recovery (%) | False Positive Rate (%) | False Negative Rate (%) | |||
ZEN | 100 | 0.9~1.1 | 65~95 | 0 | 11 | 85~115 | 1 | 0 | 83~116 | 6 | 0 |
300 | 68~97 | 85~114 | 85~115 | ||||||||
600 | 65~99 | 81~119 | 81~119 | ||||||||
DON | 200 | 1.3~1.7 | 68~96 | 0 | 15 | 85~116 | 2 | 0 | 81~115 | 9 | 0 |
1000 | 67~99 | 84~115 | 82~116 | ||||||||
2000 | 65~99 | 81~119 | 85~119 | ||||||||
AFB1 | 1 | 5.1~5.2 | 63~93 | 0 | 18 | 85~119 | 1 | 0 | 85~115 | 7 | 0 |
5 | 68~99 | 81~115 | 85~119 | ||||||||
20 | 66~100 | 85~115 | 81~114 |
Analytes | IC50 (ng/g) | S | Analytes | IC50 (ng/g) | S | Analytes | IC50 (ng/g) | S |
---|---|---|---|---|---|---|---|---|
AFB1 | 0.093 | 100 | ZEN | 3.38 | 100 | DON | 18.89 | 100 |
AFB2 | 0.76 | 12.2 | ZEA | 27.7 | 12.2 | 3A-DON | 20.67 | 91.4 |
AFG1 | 0.87 | 10.7 | ZAA | 42.3 | 7.9 | 15-ADON | 23.65 | 79.9 |
AFG2 | 0.98 | 9.5 | DON | >5000 | <0.1 | AFB1 | >10000 | <0.1 |
AFM1 | 1.75 | 5.3 | T2 | >5000 | <0.1 | AFM1 | >10000 | <0.1 |
AFM2 | 1.97 | 4.7 | OTA | >5000 | <0.1 | AFG1 | >10000 | <0.1 |
ZEN | >1000 | <0.01 | AFB1 | >5000 | <0.1 | ZEN | >10000 | <0.1 |
DON | >1000 | <0.01 | AFM1 | >5000 | <0.1 | T2 | >10000 | <0.1 |
OTA | >1000 | <0.01 | AFG1 | >5000 | <0.1 | OTA | >10000 | <0.1 |
Sample | C-ELISA (μg/kg) | HPLC(μg/kg) | ||||
---|---|---|---|---|---|---|
ZEN | DON | AFB1 | ZEN | DON | AFB1 | |
S2 | ND | ND | 5.6 ± 0.07 | ND | ND | 6.2 ± 0.02 |
S4 | 423.2 ± 0.08 | ND | ND | 412.2 ± 0.19 | ND | ND |
S5 | ND | 956.2 ± 0.11 | ND | ND | 935.3 ± 0.25 | ND |
S8 | 263.2 ± 0.12 | ND | ND | 265.2 ± 0.13 | ND | ND |
S15 | ND | ND | 4.6 ± 0.03 | ND | ND | 4.2 ± 0.06 |
S23 | 412.3 ± 0.16 | ND | ND | 423.2 ± 0.16 | ND | ND |
S29 | ND | ND | 3.2 ± 0.08 | ND | ND | 3.6 ± 0.07 |
S1, S3, S6, S7, S9~S14, S16~S22 S24~S28, S30 | ND | ND | ND | ND | ND | ND |
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. |
© 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
Share and Cite
Wu, Y.; Yu, J.; Li, F.; Li, J.; Shen, Z. A Calibration Curve Implanted Enzyme-Linked Immunosorbent Assay for Simultaneously Quantitative Determination of Multiplex Mycotoxins in Cereal Samples, Soybean and Peanut. Toxins 2020, 12, 718. https://doi.org/10.3390/toxins12110718
Wu Y, Yu J, Li F, Li J, Shen Z. A Calibration Curve Implanted Enzyme-Linked Immunosorbent Assay for Simultaneously Quantitative Determination of Multiplex Mycotoxins in Cereal Samples, Soybean and Peanut. Toxins. 2020; 12(11):718. https://doi.org/10.3390/toxins12110718
Chicago/Turabian StyleWu, Yuxiang, Jinzhi Yu, Feng Li, Jianlin Li, and Zhiqiang Shen. 2020. "A Calibration Curve Implanted Enzyme-Linked Immunosorbent Assay for Simultaneously Quantitative Determination of Multiplex Mycotoxins in Cereal Samples, Soybean and Peanut" Toxins 12, no. 11: 718. https://doi.org/10.3390/toxins12110718
APA StyleWu, Y., Yu, J., Li, F., Li, J., & Shen, Z. (2020). A Calibration Curve Implanted Enzyme-Linked Immunosorbent Assay for Simultaneously Quantitative Determination of Multiplex Mycotoxins in Cereal Samples, Soybean and Peanut. Toxins, 12(11), 718. https://doi.org/10.3390/toxins12110718