Synthetic biology : modelling genetic circuits of quorum sensing, metal biosensors and biological amplifiers
Synthetic biology is one of the new frontiers in research. It distinguished itself through the quantification of biological interactions that enables genetic circuit modelling for a better understanding of the system. In this study, the genetic circuit models of biosensors (quorum sensing, metal sen...
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| Format: | Final Year Project (FYP) |
| Language: | English |
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2015
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| Online Access: | http://hdl.handle.net/10356/65072 |
| _version_ | 1811695589667110912 |
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| author | Tay, Pei Wen |
| author2 | Poh Chueh Loo |
| author_facet | Poh Chueh Loo Tay, Pei Wen |
| author_sort | Tay, Pei Wen |
| collection | NTU |
| description | Synthetic biology is one of the new frontiers in research. It distinguished itself through the quantification of biological interactions that enables genetic circuit modelling for a better understanding of the system. In this study, the genetic circuit models of biosensors (quorum sensing, metal sensors) and biological amplifiers (gain-tunable genetic amplifier) were constructed in-silico to study its detection efficacy and gain tuning amplification capabilities. Modelling is performed based on ODE representations of the biological processes and the parameters associated are derived primarily from literature along with the experimental data. Genetic circuits are drawn using MATLAB Simulink and sensitivity analysis were ran to identify the sensitive parameters. From this study, the models of quorum sensing, gold metal sensing and arsenic tunable gain amplifier are successfully validated with the experimental based modelling from their respectively literatures. The model of quorum sensing model has displayed a good dynamic range within 1.0e-7 to 1.0e1M AHL which reflects the detection capabilities of experimental model in the AHL range of 1.0e-6 to 1.0e4M. Likewise for the model of the gold metal sensing, a similar gold detection range from 8e-9M up to 8e-6M is also reflected as in the experimental model. Furthermore, the model of arsenic metal-tunable gain amplifier displayed a wide tuning range up to 98.62% signal reduction with a similar linearity profile as in the experimental model. Finally via its assembly with previously validated gold metal sensing, a wide tuning control up to 99.99% signal reduction and modularity are also displayed as in the experimental model. |
| first_indexed | 2024-10-01T07:25:52Z |
| format | Final Year Project (FYP) |
| id | ntu-10356/65072 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T07:25:52Z |
| publishDate | 2015 |
| record_format | dspace |
| spelling | ntu-10356/650722023-03-03T15:39:07Z Synthetic biology : modelling genetic circuits of quorum sensing, metal biosensors and biological amplifiers Tay, Pei Wen Poh Chueh Loo School of Chemical and Biomedical Engineering DRNTU::Engineering::Bioengineering DRNTU::Engineering DRNTU::Science::Medicine::Biomedical engineering DRNTU::Science::Medicine::Biosensors DRNTU::Science::Biological sciences::Genetics DRNTU::Science DRNTU::Engineering::Computer science and engineering::Computer applications::Life and medical sciences DRNTU::Engineering::Computer science and engineering::Computing methodologies::Simulation and modeling DRNTU::Engineering::Computer science and engineering::Theory of computation::Computation by abstract devices DRNTU::Science::Biological sciences::Molecular biology DRNTU::Science::Biological sciences::Microbiology::Bacteria DRNTU::Science::Biological sciences::Microbiology::Microorganisms Synthetic biology is one of the new frontiers in research. It distinguished itself through the quantification of biological interactions that enables genetic circuit modelling for a better understanding of the system. In this study, the genetic circuit models of biosensors (quorum sensing, metal sensors) and biological amplifiers (gain-tunable genetic amplifier) were constructed in-silico to study its detection efficacy and gain tuning amplification capabilities. Modelling is performed based on ODE representations of the biological processes and the parameters associated are derived primarily from literature along with the experimental data. Genetic circuits are drawn using MATLAB Simulink and sensitivity analysis were ran to identify the sensitive parameters. From this study, the models of quorum sensing, gold metal sensing and arsenic tunable gain amplifier are successfully validated with the experimental based modelling from their respectively literatures. The model of quorum sensing model has displayed a good dynamic range within 1.0e-7 to 1.0e1M AHL which reflects the detection capabilities of experimental model in the AHL range of 1.0e-6 to 1.0e4M. Likewise for the model of the gold metal sensing, a similar gold detection range from 8e-9M up to 8e-6M is also reflected as in the experimental model. Furthermore, the model of arsenic metal-tunable gain amplifier displayed a wide tuning range up to 98.62% signal reduction with a similar linearity profile as in the experimental model. Finally via its assembly with previously validated gold metal sensing, a wide tuning control up to 99.99% signal reduction and modularity are also displayed as in the experimental model. Bachelor of Engineering (Chemical and Biomolecular Engineering) 2015-06-12T10:05:27Z 2015-06-12T10:05:27Z 2015 2015 Final Year Project (FYP) http://hdl.handle.net/10356/65072 en Nanyang Technological University 100 p. application/pdf |
| spellingShingle | DRNTU::Engineering::Bioengineering DRNTU::Engineering DRNTU::Science::Medicine::Biomedical engineering DRNTU::Science::Medicine::Biosensors DRNTU::Science::Biological sciences::Genetics DRNTU::Science DRNTU::Engineering::Computer science and engineering::Computer applications::Life and medical sciences DRNTU::Engineering::Computer science and engineering::Computing methodologies::Simulation and modeling DRNTU::Engineering::Computer science and engineering::Theory of computation::Computation by abstract devices DRNTU::Science::Biological sciences::Molecular biology DRNTU::Science::Biological sciences::Microbiology::Bacteria DRNTU::Science::Biological sciences::Microbiology::Microorganisms Tay, Pei Wen Synthetic biology : modelling genetic circuits of quorum sensing, metal biosensors and biological amplifiers |
| title | Synthetic biology : modelling genetic circuits of quorum sensing, metal biosensors and biological amplifiers |
| title_full | Synthetic biology : modelling genetic circuits of quorum sensing, metal biosensors and biological amplifiers |
| title_fullStr | Synthetic biology : modelling genetic circuits of quorum sensing, metal biosensors and biological amplifiers |
| title_full_unstemmed | Synthetic biology : modelling genetic circuits of quorum sensing, metal biosensors and biological amplifiers |
| title_short | Synthetic biology : modelling genetic circuits of quorum sensing, metal biosensors and biological amplifiers |
| title_sort | synthetic biology modelling genetic circuits of quorum sensing metal biosensors and biological amplifiers |
| topic | DRNTU::Engineering::Bioengineering DRNTU::Engineering DRNTU::Science::Medicine::Biomedical engineering DRNTU::Science::Medicine::Biosensors DRNTU::Science::Biological sciences::Genetics DRNTU::Science DRNTU::Engineering::Computer science and engineering::Computer applications::Life and medical sciences DRNTU::Engineering::Computer science and engineering::Computing methodologies::Simulation and modeling DRNTU::Engineering::Computer science and engineering::Theory of computation::Computation by abstract devices DRNTU::Science::Biological sciences::Molecular biology DRNTU::Science::Biological sciences::Microbiology::Bacteria DRNTU::Science::Biological sciences::Microbiology::Microorganisms |
| url | http://hdl.handle.net/10356/65072 |
| work_keys_str_mv | AT taypeiwen syntheticbiologymodellinggeneticcircuitsofquorumsensingmetalbiosensorsandbiologicalamplifiers |