微生物生態系統在維持地球生物圈和生命體扮演著關鍵的角色。許多研究已經表明環境和微生物生態系統間的錯綜複雜的交互關係，但是自然微生物生態系統的複雜性和架構仍舊需要被明確的說明與討論。在我們的研究中，我們利用細胞間的傳訊建構了一個可調控的共生生態系統來提供不同程度的互利共生行為。在這裡，我們提供了有效的設計方法學來設計共生生態系統來達到控制此系統的族群密度比例。利用系統化的設計方法搭配動態數學模型，我們提供了準確的數學分析預測生物系統的系統共生行為。有著合成共生態系統良好特性化的動態元件和詳細的數學分析，我們可以從共生生態系統的基因網路，環境效果，和系統行為中發現自然的運作和複雜的互動關係。儘管有著內部參數的變動和環境的干擾，我們根據不同的啟動子-核糖體元件庫及穩態的共生生態系統模型，開發了一個設計程序從相對應的元件庫來選擇一組最適當的啟動子-核糖體元件組以及相對應的適當可執行範圍的誘導物濃度來達到一個強健的合成共生生態系統有著期望的互利共生行為。因此，根據本文的設計流程，我們相信我們所提出的使用者為導向的可調控共生生態系統可以在快速發展的合成生物學中作為建構更為複雜的微生物生態系統的框架。

Microbial ecosystem plays a key role in maintaining Earth’s biosphere and supporting lives. Many researches have shown interaction between environment and microbial ecosystem, but the complexity and structure of natural microbial ecosystem still need to be clearly described. In this study, we construct a controllable symbiosis ecosystem to provide different levels of mutualistic behaviors through cell-cell communication. With the well-characterized kinetic components and the detailed mathematical analysis of the synthetic symbiosis ecosystem, we can provide insights into the natural functions and the complex interactions among the genetic networks, environmental effect, and system behavior of symbiosis ecosystem. Based on different promoter-RBS libraries and steady state model of symbiosis of ecosystem, we develop a design procedure to select a set of adequate promoter-RBS components from the corresponding libraries to achieve a robust synthetic symbiosis ecosystem with a desired mutualistic behavior despite intrinsic parametric variations and environmental disturbances. Therefore, we believe that the proposed controllable symbiosis ecosystem may acts as a chassis for constructing more complicated microbial ecosystem in the fast growing field of synthetic biology.

摘要 i
Abstract ii
致謝 iii
Content iv
List of Figures v
List of Tables v
Introduction 1
Design methodology of the synthetic symbiosis ecosystem 7
2.1 Construction of antibiotic resistance circuits 8
2.2 Design of symbiosis ecosystem circuits 10
2.3 Dynamic models of antibiotic resistance circuits 12
2.4 Dynamic models of symbiosis ecosystem 15
2.5 Identification of characterization of promoter-RBS components 18
2.6 Design specifications of symbiosis ecosystem via a library based searching method 23
The design example of mutualistic behaviors of symbiosis ecosystem in silico and with the verification of experimental results in vivo 27
3.1 Design examples of symbiosis ecosystem in silico 27
3.2 The validation of experimental results in vivo 30
Discussion 33
Conclusion 36
Reference 37
Figures 41
Tables 51
Supplementary Information 56
A. Dynamic model of antibiotic resistance circuit 56
B. Supplementary Figures 58
C. Material and Method 59
Growth medium and measurements 59
List of Figures
Figure 1. Schemes of the synthetic symbiosis ecosystem in this study 41
Figure 2. The structure of separated two parts of synthetic symbiosis ecosystem 43
Figure 3. Scheme of circuit PRhl and the GFP intensity measurement 44
Figure 4. Scheme of circuit PLas and the GFP intensity measurement 45
Figure 5. Scheme of synthetic antibiotic resistance circuit with the activator-regulated promoter PRhl and the population density measurement 46
Figure 6. Scheme of synthetic antibiotic resistance circuit with the activator-regulated promoter PLas and the population density measurement 47
Figure 7. Response functions of genetic circuit pRhl, PLas, and their corresponding antibiotic resistance circuits with well-identified kinetic parameters through Genetic Algorithm searching 48
Figure 8. The comparison of simulation results and experimental data to verify with an adequate set of constitutive promoter-RBS components and chloramphenicol concentration from Table 6 49

List of Tables
Table 1. Kinetic strengths of constitutive promoter-RBS components defined in E. coli MG1655 51
Table 2. Kinetic parameters of activator-regulated promoter-RBS component, PRhl and PLas in E. coli MG1655 52
Table 3. Kinetic parameters of the dynamic equations for protein expression in this study 53
Table 4. Nine cross combinations of mutualistic components of Symbiosis ecosystem with different kinetic strengths of appointed promoter-RBS components 54
Table 5. The results of three desired mutualistic population density proportion of Symbiosis ecosystem with three adequate sets of promoter-RBS components and the concentration of chloramphenicol 54
Table 6. The results of desired cell population density proportion under the 100000 runs of Monte Carlo simulation 55
Table 7. The comparison of simulation results and experimental data of cell population density ratio and the corresponding percentage of error 55

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