Potential impact of synthetic biology on the development of microbial systems for the production of renewable fuels and chemicals

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Current Opinion in Biotechnology (Impact Factor: 7.12). 06/2009; 20(3):325-9. DOI: 10.1016/j.copbio.2009.04.003
Source: PubMed


Synthetic biology leverages advances in computational biology, molecular biology, protein engineering, and systems biology to design, synthesize, and assemble genetic elements for manipulating cell phenotypes. This emerging field is founded on a vast amount of gene sequence data available in public databases and our ability to rapidly and inexpensively synthesize DNA fragments of sufficient length to encode full-length genes, enzymes, metabolic pathways, and even entire genomes. Several thousand genetic elements encoding enzymes, reporters, repressors, activators, promoters, terminators, ribosome binding sites, signaling devices, and measurement systems are now available for engineering microbes. In addition to facilitating rational design, these new tools allow us to create and harness genetic diversity in combinatorial approaches to rapidly optimize metabolic pathways. As such, synthetic biology holds great promise for accelerating the development of microbial systems for the production of renewable fuels and chemicals.

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    • "Particularly, engineered microbes have been extensively used to produce therapeutic proteins, industrial enzymes, small molecular pharmaceuticals, chemicals, biofuels, and materials. Review articles focusing on engineering microbes as cell factories are also available (Picataggio, 2009; Gowen and Fong, 2011). "
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    ABSTRACT: Systems biology is an inter-disciplinary science that studies the complex interactions and the collective behavior of a cell or an organism. Synthetic biology, as a technological subject, combines biological science and engineering, allowing the design and manipulation of a system for certain applications. Both systems and synthetic biology have played important roles in the recent development of microbial platforms for energy, materials, and environmental applications. More importantly, systems biology provides the knowledge necessary for the development of synthetic biology tools, which in turn facilitates the manipulation and understanding of complex biological systems. Thus, the combination of systems and synthetic biology has huge potential for studying and engineering microbes, especially to perform advanced tasks, such as producing biofuels. Although there have been very few studies in integrating systems and synthetic biology, existing examples have demonstrated great power in extending microbiological capabilities. This review focuses on recent efforts in microbiological genomics, transcriptomics, proteomics, and metabolomics, aiming to fill the gap between systems and synthetic biology.
    Frontiers in Microbiology 07/2013; 4:211. DOI:10.3389/fmicb.2013.00211 · 3.99 Impact Factor
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    • "In the last decades they have attracted attention due to their potential to obtain commercially interesting products, such as biofuels and pharmaceuticals. Advances in metabolic engineering and synthetic biology based on gene sequence, biochemical and physiological data in public databases together with the constant improvement of mathematical tools can help speed the development of desirable phenotypes for production of several interesting bio-products (Picataggio, 2009). "
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    ABSTRACT: Chapter 1 In this work, we present a parameter estimation problem for Dynamic Flux Balance Analysis to study the production of ethanol by a mutant strain of the cyanobacterium Synechocystis sp. PCC 6803, as well as experimental data. This modified strain harbors the genes pdc and adhB from Zymomonas mobilis. The model includes two major components: (1) a dynamic model with mass balances for biomass, ethanol, nitrate, phosphate, internal nitrogen and phosphorus, and (2) a steady state genome-scale metabolic Linear Problem (LP) model. The biomass equation includes limiting functions for temperature and kinetics of growth inhibition by ethanol toxicity. Limitation of light by biomass accumulation is also taken into account. We formulate the dynamic parameter estimation problem with a weighted least-squares objective function, subject to dynamic mass balance equations at the bioreactor level and the intracellular LP model. The problem is solved in GAMS through a simultaneous optimization approach. The data sets for parameter estimation were obtained in experiments performed over 73 hours in batch liquid cultures. Numerical results provide useful insights on the ethanol production by the genetically modified strain within the context of genomic-scale cyanobacterial metabolism.
    03/2013; 32. DOI:10.3303/CET1332160
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    • "Additionally, worth mentioning is the possibility of creating a sulfur deprived environment inside the chloroplast by impairing the sulfate transport systems (Chen et al., 2005; Lindberg and Melis, 2008), and generation of strains with truncated light-harvesting chlorophyll antenna size (Melis, 2009). Further possibilities for an efficient hydrogen production process in the future, using molecular biology and gene modifications, might be within the field of synthetic biology (Picataggio, 2009), see also the Section " Summary and perspectives " . Even if the majority of research on hydrogen production by sulfur deprivation has been performed on Chlamydomonas reinhardtii, other wild type species of green algae have also been explored in this respect and found to produce hydrogen under these conditions (Chader et al., 2009; Guan et al., 2004; Meuser et al., 2009; Skjånes et al., 2008; Timmins et al., 2009a). "
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    ABSTRACT: Full text: Green microalgae for several decades have been produced for commercial exploitation, with applications ranging from health food for human consumption, aquaculture and animal feed, to coloring agents, cosmetics and others. Several products from green algae which are used today consist of secondary metabolites that can be extracted from the algal biomass. The best known examples are the carotenoids astaxanthin and β-carotene, which are used as coloring agents and for health-promoting purposes. Many species of green algae are able to produce valuable metabolites for different uses; examples are antioxidants, several different carotenoids, polyunsaturated fatty acids, vitamins, anticancer and antiviral drugs. In many cases, these substances are secondary metabolites that are produced when the algae are exposed to stress conditions linked to nutrient deprivation, light intensity, temperature, salinity and pH. In other cases, the metabolites have been detected in algae grown under optimal conditions, and little is known about optimization of the production of each product, or the effects of stress conditions on their production. Some green algae have shown the ability to produce significant amounts of hydrogen gas during sulfur deprivation, a process which is currently studied extensively worldwide. At the moment, the majority of research in this field has focused on the model organism, Chlamydomonas reinhardtii, but other species of green algae also have this ability. Currently there is little information available regarding the possibility for producing hydrogen and other valuable metabolites in the same process. This study aims to explore which stress conditions are known to induce the production of different valuable products in comparison to stress reactions leading to hydrogen production. Wild type species of green microalgae with known ability to produce high amounts of certain valuable metabolites are listed and linked to species with ability to produce hydrogen during general anaerobic conditions, and during sulfur deprivation. Species used today for commercial purposes are also described. This information is analyzed in order to form a basis for selection of wild type species for a future multi-step process, where hydrogen production from solar energy is combined with the production of valuable metabolites and other commercial uses of the algal biomass.
    Critical Reviews in Biotechnology 07/2012; 33(2). DOI:10.3109/07388551.2012.681625 · 7.18 Impact Factor
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