Molecular BioSystems

doi: 10.1039/b910874mpmid: N/A

doi: 10.1039/b910875kpmid: N/A

doi: 10.1039/b910876apmid: N/A

Benenson, Yaakov

doi: 10.1039/b902484kpmid: 19562106

Biocomputers are man-made biological networks whose goal is to probe and control biological hosts—cells and organisms—in which they operate. Their key design features, informed by computer science and engineering, are programmability, modularity and versatility. While still a work in progress, biocomputers will eventually enable disease diagnosis and treatment with single-cell precision, lead to "designer" cell functions for biotechnology, and bring about a new generation of biological measurement tools. This review describes the intellectual foundation of the "biocomputer" concept as well as surveys the state of the art in the field.

Loakes, David; Holliger, Philipp

doi: 10.1039/b904024bpmid: 19562107

The total synthesis of a simple cell is in many ways the ultimate challenge in synthetic biology. Outlined eight years ago in a visionary article by Szostak et al. (J. W. Szostak, D. P. Bartel and P. L. Luisi, Nature, 2001, 409, 387), the chances of success seemed remote. However, recent progress in nucleic acid chemistry, directed evolution and membrane biophysics have brought the prospect of a simple synthetic cell with life-like properties such as growth, division, heredity and evolution within reach. Success in this area will not only revolutionize our understanding of abiogenesis but provide a fertile test-bed for models of prebiotic chemistry and early evolution. Last but not least, a robust “living” protocell may provide a versatile and safe chassis for embedding synthetic devices and systems.

Tanouchi, Yu; Pai, Anand; You, Lingchong

doi: 10.1039/b901584cpmid: 19562108

A major flavor of synthetic biology is the creation of artificial gene circuits to perform user-defined tasks. One aspect of this area is to realize ever-increasingly more complicated circuit behavior. Such efforts have led to the identification and evaluation of design strategies that enable robust control of dynamics in single cells and in cell populations. On the other hand, there is increasing emphasis on using artificial systems programmed by simple circuits to explore fundamental biological questions of broad significance.

Agapakis, Christina M.; Silver, Pamela A.

doi: 10.1039/b901484epmid: 19562109

Synthetic biology has been used to describe many biological endeavors over the past thirty years—from designing enzymes and in vitro systems, to manipulating existing metabolisms and gene expression, to creating entirely synthetic replicating life forms. What separates the current incarnation of synthetic biology from the recombinant DNA technology or metabolic engineering of the past is an emphasis on principles from engineering such as modularity, standardization, and rigorously predictive models. As such, synthetic biology represents a new paradigm for learning about and using biological molecules and data, with applications in basic science, biotechnology, and medicine. This review covers the canonical examples as well as some recent advances in synthetic biology in terms of what we know and what we can learn about the networks underlying biology, and how this endeavor may shape our understanding of living systems.

Tian, Jingdong; Ma, Kuosheng; Saaem, Ishtiaq

doi: 10.1039/b822268cpmid: 19562110

The emerging field of synthetic biology is generating insatiable demands for synthetic genes, which far exceed existing gene synthesis capabilities. This review discusses the current methods of chemical DNA synthesis and gene assembly, as well as the latest engineering tools, technologies and trends which could potentially lead to breakthroughs in the development of accurate, low-cost and high-throughput gene synthesis technology. The capability of generating unlimited supplies of DNA molecules of any sequence or size will transform biomedical research in the near future.

Papapostolou, David; Howorka, Stefan

doi: 10.1039/b902440apmid: 19562111

Many biologically relevant structures are formed by the self-assembly of identical protein units. Examples include virus capsids or cytoskeleton components. Synthetic biology can harness these bottom-up assemblies and expand their scope for applications in cell biology and biomedicine. Nanobiotechnology and materials science also stand to gain from assemblies with unique nanoscale periodicity. In these disciplines, the soft scaffolds can serve as templates to produce new metallic or inorganic materialsof predefined dimensions. This review article describes how the structure and function of biological assemblies has inspired researchers to develop engineered systems with designed properties for new biomolecular applications.

Carrera, Javier; Rodrigo, Guillermo; Jaramillo, Alfonso

doi: 10.1039/b904400kpmid: 19562112

The development of the technology to synthesize new genomes and to introduce them into hosts with inactivated wild-type chromosome opens the door to new horizons in synthetic biology. Here it is of outmost importance to harness the ability of using computational design to predict and optimize a synthetic genome before attempting its synthesis. The methodology to computationally design a genome is based on an optimization that computationally mimics genome evolution. The biggest bottleneck lies on the use of an appropriate fitness function. This fitness function, usually cell growth, relies on the ability to quantitatively model the biochemical networks of the cell at the genome scale using parameters inferred from high-throughput data. Computational methods integrating such models in a common multilayer design platform can be used to automatically engineer synthetic genomes under physiological specifications. We describe the current state-of-the-art on automated methods for engineering or re-engineering synthetic genomes. We restrict ourselves to global models of metabolism, transcription and DNA structure. Although we are still far from the de novo computational genome design, it is important to collect all relevant work towards this goal. Finally, we discuss future perspectives about the practicability of an automated methodology for such computational design of synthetic genomes.