Artificial assembly of a minimal cell.
ABSTRACT Synthetic Biology approaches can assemble and/or reconstruct cell parts in synthetic compartments. A minimal cell as a model for early living cells can be artificially constructed in the laboratory resuming the main properties of a basic cell living system: a synthetic cell compartment or liposome to host a minimal metabolism based on protein synthesis, and a shell and core reproduction mechanism, all in an artificial cell assembly and remaining in the realm of minimal living. It is becoming realistic to construct artificial cells, starting from a minimal cell assembly, and deliver cell-like bioreactors to synthesize pure proteins/enzymes or isolate single pathways. These artificial cell-like systems could perform different tasks in antimicrobial drug development, drug delivery and diagnostic applications.
- SourceAvailable from: Charles Eric Hodgman[Show abstract] [Hide abstract]
ABSTRACT: Cell-free synthetic biology is emerging as a powerful approach aimed to understand, harness, and expand the capabilities of natural biological systems without using intact cells. Cell-free systems bypass cell walls and remove genetic regulation to enable direct access to the inner workings of the cell. The unprecedented level of control and freedom of design, relative to in vivo systems, has inspired the rapid development of engineering foundations for cell-free systems in recent years. These efforts have led to programmed circuits, spatially organized pathways, co-activated catalytic ensembles, rational optimization of synthetic multi-enzyme pathways, and linear scalability from the micro-liter to the 100-liter scale. It is now clear that cell-free systems offer a versatile test-bed for understanding why nature's designs work the way they do and also for enabling biosynthetic routes to novel chemicals, sustainable fuels, and new classes of tunable materials. While challenges remain, the emergence of cell-free systems is poised to open the way to novel products that until now have been impractical, if not impossible, to produce by other means.Metabolic Engineering 09/2011; 14(3):261-9. DOI:10.1016/j.ymben.2011.09.002 · 8.26 Impact Factor
- [Show abstract] [Hide abstract]
ABSTRACT: Lipid vesicles are often used as compartment structures for preparing cell-like systems and models of protocells, the hypothetical precursor structures of the first cells at the origin of life. Although the various artificially made vesicle systems are already remarkably complex, they are still very different from and much simpler than any known living cell. Nevertheless, the preparation and study of the structure and the dynamics of functionalized vesicle systems may contribute to a better understanding of biological cells, in particular of the essential features of a living cell that are not found in the non-living form of matter. The study of protocell models may possibly lead to a better understanding of the origin of the first cells. To avoid misunderstanding in this field of research, it would be useful if generally accepted definitions of terms like "artificial cells," "synthetic cells," "minimal cells," "protocells," and "primitive cells" exist. Editor's suggested further reading in BioEssaysSynthetic cells and organelles: compartmentalization strategies Abstract.BioEssays 04/2010; 32(4):296-303. DOI:10.1002/bies.200900141 · 4.84 Impact Factor
- [Show abstract] [Hide abstract]
ABSTRACT: Metabolic networks perform some of the most fundamental functions in living cells, including energy transduction and building block biosynthesis. While these are the best characterized networks in living systems, understanding their evolutionary history and complex wiring constitutes one of the most fascinating open questions in biology, intimately related to the enigma of life's origin itself. Is the evolution of metabolism subject to general principles, beyond the unpredictable accumulation of multiple historical accidents? Here we search for such principles by applying to an artificial chemical universe some of the methodologies developed for the study of genome scale models of cellular metabolism. In particular, we use metabolic flux constraint-based models to exhaustively search for artificial chemistry pathways that can optimally perform an array of elementary metabolic functions. Despite the simplicity of the model employed, we find that the ensuing pathways display a surprisingly rich set of properties, including the existence of autocatalytic cycles and hierarchical modules, the appearance of universally preferable metabolites and reactions, and a logarithmic trend of pathway length as a function of input/output molecule size. Some of these properties can be derived analytically, borrowing methods previously used in cryptography. In addition, by mapping biochemical networks onto a simplified carbon atom reaction backbone, we find that properties similar to those predicted for the artificial chemistry hold also for real metabolic networks. These findings suggest that optimality principles and arithmetic simplicity might lie beneath some aspects of biochemical complexity.PLoS Computational Biology 04/2010; 6(4):e1000725. DOI:10.1371/journal.pcbi.1000725 · 4.83 Impact Factor