The concept of reengineering and rewiring of pathways and gene regulatory networks for novel uses, and sometimes for mimicking natural systems for various uses in various disciplines gradually acquired the name 0́−synthetic biology0́+. Synthetic biology, with foundations rooted in multiple disciplines like biological engineering, molecular biology, genetic engineering, and systems biology to name a few, is a new approach towards developing applications for solving current global problems in areas of food, agricultural, environmental, health (Weber et al., 2008) and alternative energy. A synthetic biology approach was used to develop a positive feedback base gene regulatory circuit in E.coli. Positive feedback is a common mechanism used in the regulation of many gene circuits as it can amplify the response to inducers and also generate binary outputs and hysteresis. In the context of electrical circuit design, positive feedback is most often employed in the design of amplifiers. Similar approaches may therefore be applied to design modular amplifier for the design of synthetic gene circuits and cell-based sensors. A modular positive feedback circuit was developed that can function as a genetic signal amplifier, heightening the sensitivity to inducer signals as well as increasing maximum expression levels without the need for an external cofactor. The design utilizes a constitutively active, autoinducer-independent variant of the quorum-sensing regulator LuxR. The ability of the positive feedback module to separately amplify the output of a one-component tetracycline sensor and a two-component aspartate sensor was experimentally tested and validated. In each case, the positive feedback module amplified the response to the respective inducers, both with regards to the gain and sensitivity. The advantage of this design is that the actual feedback mechanism depends only on a single gene and does not require any other modulation. Furthermore, this circuit can amplify any transcriptional signal, not just one encoded within the circuit or as inducer concentration. As our design is modular, it can potentially be used as a component in the design of more complex synthetic gene circuits.

Many potential applications of synthetic and systems biology are relevant to the challenges associated with the detection, surveillance, and responses to emerging and re-emerging infectious diseases. On March 14 and 15, 2011, the Institute of Medicine's (IOM's) Forum on Microbial Threats convened a public workshop in Washington, DC, to explore the current state of the science of synthetic biology, including its dependency on systems biology; discussed the different approaches that scientists are taking to engineer, or reengineer, biological systems; and discussed how the tools and approaches of synthetic and systems biology were being applied to mitigate the risks associated with emerging infectious diseases. The Science and Applications of Synthetic and Systems Biology is organized into sections as a topic-by-topic distillation of the presentations and discussions that took place at the workshop. Its purpose is to present information from relevant experience, to delineate a range of pivotal issues and their respective challenges, and to offer differing perspectives on the topic as discussed and described by the workshop participants. This report also includes a collection of individually authored papers and commentary.

Positive feedback is a common mechanism in genetic circuits and can be used to achieve amplification, bistability, and hysteresis. Positive feedback mechanisms have been employed in numerous synthetic biology applications, including in the development of a modular positive feedback-based gene amplifier by Nistala et al. [1]. The modular design potentially enables use as a component in more complex synthetic gene networks, thus helping to achieve the oft-stated goal of designing well-characterized components that can be used in diverse synthetic biology applications. The positive feedback-based gene amplifier provides amplification of the maximum expression level of a gene product, and increased sensitivity to the inducer. However, the initial analysis by Nistala et al. did not demonstrate that this particular positive feedback mechanism can produce a hysteretic response to an inducer, i.e. exhibit memory of a prior stimulus. Positive feedback in a genetic circuit potentially, but not necessarily, leads to bistability, and a bistable circuit will produce some degree of hysteresis [2]. Therefore, the purpose of this research was to determine under what conditions, if any, the modular positive feedback-based gene amplifier will produce a hysteretic response. A modular gene amplifier with well-characterized hysteretic properties will potentially be a useful asset for synthetic biologists designing more complex networks out of simpler components. A simple mathematical model of gene expression in a positive-feedback system is used predict the conditions for bistability and hysteresis versus a simple graded response. Experiments are performed on the positive feedback-based tetracycline sensor in E. coli using green fluorescent protein (GFP) to measure expression level of the gene product. In the experiments, cells are placed in solutions of various inducer concentrations and grown to a steady-state level of GFP expression. Cells are then resuspended in solutions of lower inducer concentrations and allowed to reach steady state. Hysteresis is observed if the steady-state GFP level depends on the prior induction level of the cell culture. This research shows that the modular positive feedback-based gene amplifier is capable of producing a hysteretic response to a stimulus. The magnitude of the hysteretic response depended on the dilution ratio used to inoculate the cultures. Additionally, the magnitude of the hysteretic response depended partially on the final induction level of the culture, as higher induction levels resulted in a larger proportion of cells exhibiting a high level of GFP fluorescence. The cultures with induction history exhibited bistable GFP expression at all inducer concentrations. Cells exhibiting low GFP fluorescence grew at a faster rate than cells exhibiting high GFP fluorescence. This suggests that low dilution ratios provide more time for cells expressing at a low level to grow before the culture is saturated, and therefore make up a larger proportion of the final culture producing a smaller hysteretic response. These results provide a deeper understanding of the properties of the modular positive feedback-based gene amplifier and the conditions for hysteresis.

The rapid expansion of synthetic biology is due to the design and construction of synthetic gene networks that have opened many new avenues in fundamental and applied research. Synthetic Gene Networks: Methods and Protocols provides the necessary information to design and construct synthetic gene networks in different host backgrounds. Divided into four convenient sections, this volume focuses on design concepts to devise synthetic gene networks and how mathematical models can be applied to the predictable engineering of desired network features. The volume continues by highlighting the construction and validation of biologic tools, describing strategies to optimize and streamline the host cell for optimized network performance, and covering how optimally designed gene networks can be implemented in a large variety of host cells ranging from bacteria over yeast and insect cells to plant and mammalian cell culture. Written in the successful Methods in Molecular BiologyTM series format, chapters include introductions to their respective topics, lists of the necessary materials and reagents, step-by-step, readily reproducible protocols, and notes on troubleshooting and avoiding known pitfalls. Authoritative and easily accessible, Synthetic Gene Networks: Methods and Protocols serves as an invaluable resource for established biologists, engineers, and computer scientists or novices just entering into the rapidly growing field of synthetic biology

The essential introduction to the principles and applications of feedback systems—now fully revised and expanded This textbook covers the mathematics needed to model, analyze, and design feedback systems. Now more user-friendly than ever, this revised and expanded edition of Feedback Systems is a one-volume resource for students and researchers in mathematics and engineering. It has applications across a range of disciplines that utilize feedback in physical, biological, information, and economic systems. Karl Åström and Richard Murray use techniques from physics, computer science, and operations research to introduce control-oriented modeling. They begin with state space tools for analysis and design, including stability of solutions, Lyapunov functions, reachability, state feedback observability, and estimators. The matrix exponential plays a central role in the analysis of linear control systems, allowing a concise development of many of the key concepts for this class of models. Åström and Murray then develop and explain tools in the frequency domain, including transfer functions, Nyquist analysis, PID control, frequency domain design, and robustness. Features a new chapter on design principles and tools, illustrating the types of problems that can be solved using feedback Includes a new chapter on fundamental limits and new material on the Routh-Hurwitz criterion and root locus plots Provides exercises at the end of every chapter Comes with an electronic solutions manual An ideal textbook for undergraduate and graduate students Indispensable for researchers seeking a self-contained resource on control theory

The current advances in sequencing, data mining, DNA synthesis, cloning, in silico modeling, and genome editing have opened a new field of research known as Synthetic Genomics. The main goal of this emerging area is to engineer entire synthetic genomes from scratch using pre-designed building blocks obtained by chemical synthesis and rational design. This has opened the possibility to further improve our understanding of genome fundamentals by considering the effect of the whole biological system on biological function. Moreover, the construction of non-natural biological systems has allowed us to explore novel biological functions so far not discovered in nature. This book summarizes the current state of Synthetic Genomics, providing relevant examples in this emerging field.

This book provides an accessible introduction to the principles and tools for modeling, analyzing, and synthesizing biomolecular systems. It begins with modeling tools such as reaction-rate equations, reduced-order models, stochastic models, and specific models of important core processes. It then describes in detail the control and dynamical systems tools used to analyze these models. These include tools for analyzing stability of equilibria, limit cycles, robustness, and parameter uncertainty. Modeling and analysis techniques are then applied to design examples from both natural systems and synthetic biomolecular circuits. In addition, this comprehensive book addresses the problem of modular composition of synthetic circuits, the tools for analyzing the extent of modularity, and the design techniques for ensuring modular behavior. It also looks at design trade-offs, focusing on perturbations due to noise and competition for shared cellular resources. Featuring numerous exercises and illustrations throughout, Biomolecular Feedback Systems is the ideal textbook for advanced undergraduates and graduate students. For researchers, it can also serve as a self-contained reference on the feedback control techniques that can be applied to biomolecular systems. Provides a user-friendly introduction to essential concepts, tools, and applications Covers the most commonly used modeling methods Addresses the modular design problem for biomolecular systems Uses design examples from both natural systems and synthetic circuits Solutions manual (available only to professors at press.princeton.edu) An online illustration package is available to professors at press.princeton.edu