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BackgroundSelf‐sustained oscillations are a ubiquitous and vital phenomenon in living systems. From primitive single‐cellular bacteria to the most sophisticated organisms, periodicities have been observed in a broad spectrum of biological processes such as neuron firing, heart beats, cell cycles, circadian rhythms, etc. Defects in these oscillators can cause diseases from insomnia to cancer. Elucidating their fundamental mechanisms is of great significance to diseases, and yet challenging, due to the complexity and diversity of these oscillators. ResultsApproaches in quantitative systems biology and synthetic biology have been most effective by simplifying the systems to contain only the most essential regulators. Here, we will review major progress that has been made in understanding biological oscillators using these approaches. The quantitative systems biology approach allows for identification of the essential components of an oscillator in an endogenous system. The synthetic biology approach makes use of the knowledge to design the simplest,de novooscillators in both live cells and cell‐free systems. These synthetic oscillators are tractable to further detailed analysis and manipulations. ConclusionWith the recent development of biological and computational tools, both approaches have made significant achievements.
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A new era of Synthetic Biology - microbial community design
Abstract Synthetic biology conceptualises biological complexity as a network of biological parts, devices and systems with predetermined functionalities, and has had a revolutionary impact on fundamental and applied research. With the unprecedented ability to synthesise and transfer any DNA and RNA across organisms, the scope of synthetic biology is expanding and being recreated in previously unimaginable ways. The field has matured to a level where highly complex networks, such as artificial communities of synthetic organisms can be constructed. In parallel, computational biology became an integral part of biological studies, with computational models aiding the unravelling of the escalating complexity and emerging properties of biological phenomena. However, there is still a vast untapped potential for the complete integration of modelling into the synthetic design process, presenting exciting opportunities for scientific advancements. Here, we first highlight the most recent advances in computer-aided design of microbial communities. Next, we propose that such a design can benefit from an organism-free modular modelling approach that places its emphasis on modules of organismal function towards the design of multi-species communities. We argue for a shift in perspective from single organism-centred approaches to emphasising the functional contributions of organisms within the community. By assembling synthetic biological systems using modular computational models with mathematical descriptions of parts and circuits, we can tailor organisms to fulfil specific functional roles within the community. This approach aligns with synthetic biology strategies and presents exciting possibilities for the design of artificial communities.
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- Award ID(s):
- 1845463
- PAR ID:
- 10524018
- Publisher / Repository:
- Oxford University Press
- Date Published:
- Journal Name:
- Synthetic Biology
- ISSN:
- 2397-7000
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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