Synthetic Biology: Tools to Design, Build, and Optimize Cellular Processes

The general central dogma frames the emergent properties of life, which make biology both necessary and difficult to engineer. In a process engineering paradigm, each biological process stream and process unit is heavily influenced by regulatory interactions and interactions with the surrounding environment. Synthetic biology is developing the tools and methods that will increase control over these interactions, eventually resulting in an integrative synthetic biology that will allow ground-up cellular optimization. In this review, we attempt to contextualize the areas of synthetic biology into three tiers: (1) the process units and associated streams of the central dogma, (2) the intrinsic regulatory mechanisms, and (3) the extrinsic physical and chemical environment. Efforts at each of these three tiers attempt to control cellular systems and take advantage of emerging tools and approaches. Ultimately, it will be possible to integrate these approaches and realize the vision of integrative synthetic biology when cells are completely rewired for biotechnological goals. This review will highlight progress towards this goal as well as areas requiring further research

Development of systematic and combinatorial approaches for the metabolic engineering of microorganisms

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Chemical Engineering, 2006.Includes bibliographical references (p. 243-261).Explorations and optimizations through the genomic space are a daunting undertaking given the complexity and size of the possible search space. To approach this problem, systematic and combinatorial approaches were employed for the engineering of cellular phenotype in Escherichia coli. Initially, a computational method based on global cellular stoichiometry was employed to identify single and multiple gene knockout targets for lycopene production in E. coli. These targets led to substantial increases in lycopene production, but were limited in scope due to the nature of these models. Therefore, these approaches and targets were complemented with combinatorial searches to identify unknown and regulatory targets. When combined, these searches led to further increases of lycopene production and allowed for the visualization of the resulting metabolic landscape. A more exhaustive search was conducted in the background of eight genotypes which resulted in the formulation of the gene knockout search network. This network enables the investigation into how phenotype optimization is biased by search strategy.(cont.) Collectively, these results demonstrated that despite the complexity and nonlinearity of genotype-phenotype spaces, most of the significant phenotypes were controlled and regulated by a small subset of key "gateway" nodes. Often, the mutations and genotypes incurred in altering global cellular phenotypes are not necessarily additive and can be quite non-linear. Effective probing of a metabolic landscape requires not only gene deletions, but also the varying (or tuning) of expression level for a gene of interest. Through promoter engineering, a library of promoters of varying strength were obtained through mutagenesis of a constitutive promoter. A multi-faceted characterization of the library, especially at the single-cell level to ensure homogeneity, permitted quantitative assessment correlating the effect of gene expression levels to improved growth and product formation phenotypes in E. coli. Integration of these promoters into the chromosome can allow for a quantitative, accurate assessment and tuning of genetic control. Collectively, quantitative phenotype-genotype analysis illustrated that optimal gene expression levels are variable and dependent on the genetic background of the strain.(cont.) As a result, tools such as promoter engineering, which allow for a wide range of expression levels, constitutes an integral platform for functional genomics, synthetic biology, and metabolic engineering endeavors. Finally, multiple genetic modifications are necessary to unlock latent cellular potential. However, the capacity to make these meaningful modifications has remained an elusive task for cellular and metabolic engineering. The tool of global Transcription Machinery Engineering (gTME) allows one to explore a vastly unexplored, expanded search space in a high throughput manner by evaluating multiple, simultaneous gene alterations in order to improve complex cellular phenotypes. Through the alteration of key proteins involved in global transcription, cells may be reprogrammed for phenotypes of interest. Results in phenotype optimization using gTME outperformed traditional approaches to these problems, exceeding, in a matter of weeks, benchmarks achieved through decades of research. Through gTME, it is now possible to unlock complex phenotypes regulated by multiple genes which would be very unlikely to reach by the relatively inefficient, iterative gene-by-gene search strategies.(cont.) The concept of gTME is generic and provides access points for diverse transciptome modifications broadly impacting phenotypes of higher organisms too, as further studies with yeast amply demonstrate. On the basis of these studies, combinatorial methods are generally more powerful in obtaining a given cellular objective than systematic methods due to their ability to make broader perturbations. However, properly designed search strategies which make use of both systematic and combinatorial approaches may be the best route for optimizing phenotypes.by Hal Alper.Ph.D

A condition-specific codon optimization approach for improved heterologous gene expression in Saccharomyces cerevisiae

All authors are with the Department of Chemical Engineering, The University of Texas at Austin, 200 E Dean Keeton St. Stop C0400, Austin, TX 78712, USA -- Hal S. Alper is with the Institute for Cellular and Molecular Biology, The University of Texas at Austin, 2500 Speedway Avenue, Austin, TX 78712, USA -- Amanda M. Lanza Current Address: Bristol-Myers Squibb, Biologics Development, 35 South Street, Hopkinton, MA 01748, USABackground: Heterologous gene expression is an important tool for synthetic biology that enables metabolic engineering and the production of non-natural biologics in a variety of host organisms. The translational efficiency of heterologous genes can often be improved by optimizing synonymous codon usage to better match the host organism. However, traditional approaches for optimization neglect to take into account many factors known to influence synonymous codon distributions. Results: Here we define an alternative approach for codon optimization that utilizes systems level information and codon context for the condition under which heterologous genes are being expressed. Furthermore, we utilize a probabilistic algorithm to generate multiple variants of a given gene. We demonstrate improved translational efficiency using this condition-specific codon optimization approach with two heterologous genes, the fluorescent protein-encoding eGFP and the catechol 1,2-dioxygenase gene CatA, expressed in S. cerevisiae. For the latter case, optimization for stationary phase production resulted in nearly 2.9-fold improvements over commercial gene optimization algorithms. Conclusions: Codon optimization is now often a standard tool for protein expression, and while a variety of tools and approaches have been developed, they do not guarantee improved performance for all hosts of applications. Here, we suggest an alternative method for condition-specific codon optimization and demonstrate its utility in Saccharomyces cerevisiae as a proof of concept. However, this technique should be applicable to any organism for which gene expression data can be generated and is thus of potential interest for a variety of applications in metabolic and cellular engineering.Chemical EngineeringInstitute for Cellular and Molecular [email protected]

Optimizing pentose utilization in yeast: the need for novel tools and approaches

Hexose and pentose cofermentation is regarded as one of the chief obstacles impeding economical conversion of lignocellulosic biomass to biofuels. Over time, successful application of traditional metabolic engineering strategy has produced yeast strains capable of utilizing the pentose sugars (especially xylose and arabinose) as sole carbon sources, yet major difficulties still remain for engineering simultaneous, exogenous sugar metabolism. Beyond catabolic pathways, the focus must shift towards non-traditional aspects of cellular engineering such as host molecular transport capability, catabolite sensing and stress response mechanisms. This review highlights the need for an approach termed 'panmetabolic engineering', a new paradigm for integrating new carbon sources into host metabolic pathways. This approach will concurrently optimize the interdependent processes of transport and metabolism using novel combinatorial techniques and global cellular engineering. As a result, panmetabolic engineering is a whole pathway approach emphasizing better pathways, reduced glucose-induced repression and increased product tolerance. In this paper, recent publications are reviewed in light of this approach and their potential to expand metabolic engineering tools. Collectively, traditional approaches and panmetabolic engineering enable the reprogramming of extant biological complexity and incorporation of exogenous carbon catabolism

Engineered xylose transporters with reduced glucose inhibition

Provided herein are compositions and methods useful for reducing glucose inhibition in transporting xylose, arabinose and other monosaccharides, into a yeast cell.Board of Regents, University of Texas Syste

Compositions and methods for lipid production

Described herein, inter alia, are compositions, oleagnious organisms, and methods useful for producing lipids, lipid precursors, and/or oleochemicals.Board of Regents, University of Texas Syste

RNA-aptamers-in-droplets (RAPID) high-throughput screening for secretory phenotypes.

Synthetic biology and metabolic engineering seek to re-engineer microbes into living foundries for the production of high value chemicals. Through a design-build-test cycle paradigm, massive libraries of genetically engineered microbes can be constructed and tested for metabolite overproduction and secretion. However, library generation capacity outpaces the rate of high-throughput testing and screening. Well plate assays are flexible but with limited throughput, whereas droplet microfluidic techniques are ultrahigh-throughput but require a custom assay for each target. Here we present RNA-aptamers-in-droplets (RAPID), a method that greatly expands the generality of ultrahigh-throughput microfluidic screening. Using aptamers, we transduce extracellular product titer into fluorescence, allowing ultrahigh-throughput screening of millions of variants. We demonstrate the RAPID approach by enhancing production of tyrosine and secretion of a recombinant protein in Saccharomyces cerevisiae by up to 28- and 3-fold, respectively. Aptamers-in-droplets affords a general approach for evolving microbes to synthesize and secrete value-added chemicals.Screening libraries of genetically engineered microbes for secreted products is limited by the available assay throughput. Here the authors combine aptamer-based fluorescent detection with droplet microfluidics to achieve high throughput screening of yeast strains engineered for enhanced tyrosine or streptavidin production