- Email: [email protected]
Cellular automata-based modeling and risk assessment of genetically modified crops with Bacillus thuringiensis (bt) genes
S248
Abstracts / Journal of Biotechnology 136S (2008) S247–S251
probes complementary to internal segments of the NAIMA products. The procedure has been applied to test in a multiplex fashion feed and food samples containing several transgenic lines; and it has shown to provide quantitative data on the transgenic contents in a range of 0.1 to 25%. Short NAIMA amplification was required to get linear signal (less than 60 min). Simultaneous short hybridization ( 1 h) of reference material and unknown sample amplified by NAIMA method and labelled with two different dyes allows microarraybased detection of GMO targets with high sensitivity. This method allows multiple identification and quantification of the GM content in the sample in a short time. NAIMA-MA procedure allows high throughput DNA target identification and quantification in a multiplex fashion in an on-chip format. The concept successfully demonstrated for GMO diagnostics could easily be adapted to domains where diagnostics rely on DNA based sequence detection.
on grids of the middle tier; and A was placed on each lattice of the lower tier. The relations among these species were described and evolved through long term scales according to a set of rules, which were assigned based on literature data and could be applied iteratively. This research may provide a prospective methodology for assessment of GM risks.
Acknowledgments
References
This study was financially supported by the European Commission through the Integrated project Co-Extra, contract no. 007158, under the 6th Framework Programme, priority 5, food quality and safety and by the Slovenian research agency (contract no. P4-0165).
Keywords: Cellular automata modeling; Risk analysis; Genetically modified (GM) crops Acknowledgments The authors acknowledge the financial support provided by the National R&D Project of Transgenic Crops of Ministry of Science and Technology of China (JY03-B-18-02), Dalian Municipal Science and Technology Program (2007B10NC137), and Key Laboratory of Industrial Ecology and Environmental Engineering (Dalian).
Andow, D.A., Lövei, G.L., Arpaia, S., 2006. Ecological risk assessment for Bt crops. Nat. Biotechnol. 24 (7), 749–751. Roh, J.Y., Choi, J.Y., Li, M.S., Jin, B.R., Je, Y.H., 2007. Bacillus thuringiensis as a specific, safe, and effective tool for insect pest control. J. Microbiol. Biotechnol. 17 (4), 547–559. Wolfram, S., 2002. A New Kind of Science. Wolfram Media, Champaign, IL.
References doi:10.1016/j.jbiotec.2008.07.528 Guatelli, J.C., Whitfield, K.M., Kwoh, D.Y., Barringer, K.J., Richman, D.D., Gingeras, T.R., 1990. Isothermal, in vitro amplification of nucleic acids by a multienzyme reaction modeled after retroviral replication. Proc. Natl. Acad. Sci. U.S.A. 87, 1874–1878. ˇ Morisset, D., Stebih, D., Cankar, K., Zˇ el, J., Gruden, K., 2008. Alternative DNA amplification methods to PCR and their application in GMO detection: a review. Eur. Food Res. Technol. (Online first).
doi:10.1016/j.jbiotec.2008.07.527 IV4-O-010 Cellular automata-based modeling and risk assessment of genetically modified crops with Bacillus thuringiensis (bt) genes Yang Jun 1,3,∗ , He Ming-feng 2,∗ , Yang De-li 3 1 Department of Bioscience and Biotechnology, Dalian University of Technology, Linggong Road 2, Dalian, 116024, PR China 2 Department of Applied Mathematics, Dalian University of Technology, Linggong Road 2, Dalian, 116024, PR China 3 School of Management, Dalian University of Technology, Linggong Road 2, Dalian, 116024, PR China
E-mail addresses: [email protected] (J. Yang), [email protected] (M.-f. He). Risk analysis is a critically important control procedure for conditions assessment and decision-making. The prediction of risk in genetically modified (GM) biological system is particularly hard because its complexity with multiple spatial or temporal scales. Cellular automata (CA) provide a potential modeling and simulation framework for such a dynamic system. In this paper, a mini-ecosystem contains four species, bt transgenic crop (A), target pest (B), non-target pest (C) and predator (D) were defined and a three-tier of L × L random cellular automaton with periodic boundary was constructed. D and vacant space were randomly placed on grids of the upper tier; B, C and vacant space were randomly placed
∗ Corresponding authors. Tel.: +86 411 84709687.
IV4-P-002 GMDD: A database of GMO detection methods Wei Dong 1 , Litao Yang 1 , Banghyun Kim 2 , Gijs A. Kleter 3 , Hans J.P. Marvin 3 , Wanqi Liang 1 , Dabing Zhang 1,∗ 1
GMO Detection Laboratory, School of life Science and Biotechnology, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai 200240, PR China 2 Korea Food & Drug Administration, 194 Tongiliro, Eunpyung-gu, Seoul 122-704, Republic of Korea 3 RIKILT – Institute of Food Safety, Wageningen University and Research Center, Bornsesteeg 45, NL-6708 PD Wageningen, The Netherlands E-mail address: [email protected] (D. Zhang). Since more than one hundred events of genetically modified organisms (GMOs) have been developed and approved for commercialization in global area, the GMO analysis methods are essential for the enforcement of GMO labelling regulations (Anklam et al., 2002). Protein and nucleic acid-based detection techniques have been developed and utilized for GMOs identification and quantification (Holst-Jensen et al., 2003; Farid, 2002). However, the information for harmonization and standardization of GMO analysis methods at global level is needed. GMO detection method database (GMDD) has collected almost all the previous developed and reported GMOs detection methods, which have been grouped by different strategies (screen-, gene-, construct-, and event-specific), and also provide a user-friendly search service of the detection methods by GMO event name, exogenous gene, or protein information, etc. In this database, users can obtain the sequences of exogenous integration, which will facilitate PCR primers and probes designing. Also the information on endogenous genes, certified reference materials, reference molecules, and the validation status of developed methods is included in this database. Furthermore, registered users can also submit new detection methods and sequences to this database, and the newly submitted information will be released soon after being checked.
Abstracts / Journal of Biotechnology 136S (2008) S247–S251
probes complementary to internal segments of the NAIMA products. The procedure has been applied to test in a multiplex fashion feed and food samples containing several transgenic lines; and it has shown to provide quantitative data on the transgenic contents in a range of 0.1 to 25%. Short NAIMA amplification was required to get linear signal (less than 60 min). Simultaneous short hybridization ( 1 h) of reference material and unknown sample amplified by NAIMA method and labelled with two different dyes allows microarraybased detection of GMO targets with high sensitivity. This method allows multiple identification and quantification of the GM content in the sample in a short time. NAIMA-MA procedure allows high throughput DNA target identification and quantification in a multiplex fashion in an on-chip format. The concept successfully demonstrated for GMO diagnostics could easily be adapted to domains where diagnostics rely on DNA based sequence detection.
on grids of the middle tier; and A was placed on each lattice of the lower tier. The relations among these species were described and evolved through long term scales according to a set of rules, which were assigned based on literature data and could be applied iteratively. This research may provide a prospective methodology for assessment of GM risks.
Acknowledgments
References
This study was financially supported by the European Commission through the Integrated project Co-Extra, contract no. 007158, under the 6th Framework Programme, priority 5, food quality and safety and by the Slovenian research agency (contract no. P4-0165).
Keywords: Cellular automata modeling; Risk analysis; Genetically modified (GM) crops Acknowledgments The authors acknowledge the financial support provided by the National R&D Project of Transgenic Crops of Ministry of Science and Technology of China (JY03-B-18-02), Dalian Municipal Science and Technology Program (2007B10NC137), and Key Laboratory of Industrial Ecology and Environmental Engineering (Dalian).
Andow, D.A., Lövei, G.L., Arpaia, S., 2006. Ecological risk assessment for Bt crops. Nat. Biotechnol. 24 (7), 749–751. Roh, J.Y., Choi, J.Y., Li, M.S., Jin, B.R., Je, Y.H., 2007. Bacillus thuringiensis as a specific, safe, and effective tool for insect pest control. J. Microbiol. Biotechnol. 17 (4), 547–559. Wolfram, S., 2002. A New Kind of Science. Wolfram Media, Champaign, IL.
References doi:10.1016/j.jbiotec.2008.07.528 Guatelli, J.C., Whitfield, K.M., Kwoh, D.Y., Barringer, K.J., Richman, D.D., Gingeras, T.R., 1990. Isothermal, in vitro amplification of nucleic acids by a multienzyme reaction modeled after retroviral replication. Proc. Natl. Acad. Sci. U.S.A. 87, 1874–1878. ˇ Morisset, D., Stebih, D., Cankar, K., Zˇ el, J., Gruden, K., 2008. Alternative DNA amplification methods to PCR and their application in GMO detection: a review. Eur. Food Res. Technol. (Online first).
doi:10.1016/j.jbiotec.2008.07.527 IV4-O-010 Cellular automata-based modeling and risk assessment of genetically modified crops with Bacillus thuringiensis (bt) genes Yang Jun 1,3,∗ , He Ming-feng 2,∗ , Yang De-li 3 1 Department of Bioscience and Biotechnology, Dalian University of Technology, Linggong Road 2, Dalian, 116024, PR China 2 Department of Applied Mathematics, Dalian University of Technology, Linggong Road 2, Dalian, 116024, PR China 3 School of Management, Dalian University of Technology, Linggong Road 2, Dalian, 116024, PR China
E-mail addresses: [email protected] (J. Yang), [email protected] (M.-f. He). Risk analysis is a critically important control procedure for conditions assessment and decision-making. The prediction of risk in genetically modified (GM) biological system is particularly hard because its complexity with multiple spatial or temporal scales. Cellular automata (CA) provide a potential modeling and simulation framework for such a dynamic system. In this paper, a mini-ecosystem contains four species, bt transgenic crop (A), target pest (B), non-target pest (C) and predator (D) were defined and a three-tier of L × L random cellular automaton with periodic boundary was constructed. D and vacant space were randomly placed on grids of the upper tier; B, C and vacant space were randomly placed
∗ Corresponding authors. Tel.: +86 411 84709687.
IV4-P-002 GMDD: A database of GMO detection methods Wei Dong 1 , Litao Yang 1 , Banghyun Kim 2 , Gijs A. Kleter 3 , Hans J.P. Marvin 3 , Wanqi Liang 1 , Dabing Zhang 1,∗ 1
GMO Detection Laboratory, School of life Science and Biotechnology, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai 200240, PR China 2 Korea Food & Drug Administration, 194 Tongiliro, Eunpyung-gu, Seoul 122-704, Republic of Korea 3 RIKILT – Institute of Food Safety, Wageningen University and Research Center, Bornsesteeg 45, NL-6708 PD Wageningen, The Netherlands E-mail address: [email protected] (D. Zhang). Since more than one hundred events of genetically modified organisms (GMOs) have been developed and approved for commercialization in global area, the GMO analysis methods are essential for the enforcement of GMO labelling regulations (Anklam et al., 2002). Protein and nucleic acid-based detection techniques have been developed and utilized for GMOs identification and quantification (Holst-Jensen et al., 2003; Farid, 2002). However, the information for harmonization and standardization of GMO analysis methods at global level is needed. GMO detection method database (GMDD) has collected almost all the previous developed and reported GMOs detection methods, which have been grouped by different strategies (screen-, gene-, construct-, and event-specific), and also provide a user-friendly search service of the detection methods by GMO event name, exogenous gene, or protein information, etc. In this database, users can obtain the sequences of exogenous integration, which will facilitate PCR primers and probes designing. Also the information on endogenous genes, certified reference materials, reference molecules, and the validation status of developed methods is included in this database. Furthermore, registered users can also submit new detection methods and sequences to this database, and the newly submitted information will be released soon after being checked.