Nathan Crook

Design of synthetic yeast promoters via tuning of nucleosome architecture

Model-based design of biological parts is a critical goal of synthetic biology, especially for eukaryotes. Here we demonstrate that nucleosome architecture can play a role in defining yeast promoter activity and utilize a computationally-guided approach that can enable both the redesign of endogenous promoter sequences and the de novo design of synthetic promoters. Initially, we use our approach to reprogram native promoters for increased expression and evaluate their performance in various genetic contexts. Increases in expression ranging from 1.5 to nearly 6-fold in a plasmid-based system and up to 16-fold in a genomic context were obtained. Next, we demonstrate that, in a single design cycle, it is possible to create functional, purely synthetic yeast promoters that achieve substantial expression levels (within the top sixth percentile among native yeast promoters). In doing so, this work establishes a unique DNA-level specification of promoter activity and demonstrates predictive design of synthetic parts.

Optimization of a yeast RNA interference system for controlling gene expression and enabling rapid metabolic engineering.

Reduction of endogenous gene expression is a fundamental operation of metabolic engineering, yet current methods for gene knockdown (i.e., genome editing) remain laborious and slow, especially in yeast. In contrast, RNA interference allows facile and tunable gene knockdown via a simple plasmid transformation step, enabling metabolic engineers to rapidly prototype knockdown strategies in multiple strains before expending significant cost to undertake genome editing. Although RNAi is naturally present in a myriad of eukaryotes, it has only been recently implemented in Saccharomyces cerevisiae as a heterologous pathway and so has not yet been optimized as a metabolic engineering tool. In this study, we elucidate a set of design principles for the construction of hairpin RNA expression cassettes in yeast and implement RNA interference to quickly identify routes for improvement of itaconic acid production in this organism. The approach developed here enables rapid prototyping of knockdown strategies and thus accelerates and reduces the cost of the design-build-test cycle in yeast.

Improved Product-Per-Glucose Yields in P450-Dependent Propane Biotransformations Using Engineered Escherichia coli

P450‐dependent biotransformations in Escherichia coli are attractive for the selective oxidation of organic molecules using mild and sustainable procedures. The overall efficiency of these processes, however, relies on how effectively the NAD(P)H cofactors derived from oxidation of the carbon source are utilized inside the cell to support the heterologous P450‐catalyzed reaction. In this work, we investigate the use of metabolic and protein engineering to enhance the product‐per‐glucose yield (YPPG) in whole‐cell reactions involving a proficient NADPH‐dependent P450 propane monooxygenase prepared by directed evolution [P450PMOR2; Fasan et al. (2007); Angew Chem Int Ed 46:8414–8418]. Our studies revealed that the metabolism of E. coli (W3110) is able to support only a modest propanol:glucose molar ratio (YPPG ∼ 0.5) under aerobic, non‐growing conditions. By altering key processes involved in NAD(P)H metabolism of the host, considerable improvements of this ratio could be achieved. A metabolically engineered E. coli strain featuring partial inactivation of the endogenous respiratory chain (Δndh) combined with removal of two fermentation pathways (ΔadhE, Δldh) provided the highest YPPG (1.71) among the strains investigated, enabling a 230% more efficient utilization of the energy source (glucose) in the propane biotransformation compared to the native E. coli strain. Using an engineered P450PMOR2 variant which can utilize NADPH and NADH with equal efficiency, we also established that dual cofactor specificity of the P450 enzyme can provide an appreciable improvement in YPPG. Kinetic analyses suggest, however, that much more favorable parameters (KM, kcat) for the NADH‐driven reaction are required to effectively compete with the hosts endogenous NADH‐utilizing enzymes. Overall, the metabolic/protein engineering strategies described here can be of general value for improving the performance of NAD(P)H‐dependent whole‐cell biotransformations in E. coli. Biotechnol. Bioeng. 2011; 108:500–510.

Innovation at the intersection of synthetic and systems biology.

The promises of modern biotechnology hinge upon the hope that we can understand microscopic cellular complexity and in doing so create novel function. In this regard, the fields of systems and synthetic biology are important for accelerating both our understanding of biological systems and our ability to quantitatively engineer cells. At the nexus of these two fields is a unique synergy that can help attain these goals. Thus, the next greatest advances in biology and biotechnology are arising at the intersection of the top-down systems approach and the bottom-up synthetic approach. Collectively, these developments enable the precise control of cellular state for systems studies and the discovery of novel parts, control strategies, and interactions for the design of robust synthetic function. This review seeks to highlight this activity as well as provide a perspective for future directions. Combining these efforts can provide novel insights into cellular function and lead to robust, novel synthetic design.

Re-engineering multicloning sites for function and convenience

Multicloning sites (MCSs) in standard expression vectors are widely used and thought to be benign, non-interacting elements that exist for mere convenience. However, MCSs impose a necessary distance between promoter elements and genes of interest. As a result, the choice of cloning site defines the genetic context and may introduce significant mRNA secondary structure in the 5′-untranslated region leading to strong translation inhibition. Here, we demonstrate the first performance-based assessment of MCSs in yeast, showing that commonly used MCSs can induce dramatic reductions in protein expression, and that this inhibition is highly promoter and gene dependent. In response, we develop and apply a novel predictive model of structure-based translation inhibition to design improved MCSs for significantly higher and more consistent protein expression. In doing so, we were able to minimize the inhibitory effects of MCSs with the yeast TEF, CYC and GPD promoters. These results highlight the non-interchangeable nature of biological parts and represent the first complete, global redesign of a genetic circuit of such widespread importance as a multicloning site. The improved translational control offered by these designed MCSs is paramount to obtaining high titers of heterologous proteins in eukaryotes and to enabling precise control of genetic circuits.

Structure-guided directed evolution of highly selective p450-based magnetic resonance imaging sensors for dopamine and serotonin.

New tools that allow dynamic visualization of molecular neural events are important for studying the basis of brain activity and disease. Sensors that permit ligand-sensitive magnetic resonance imaging (MRI) are useful reagents due to the noninvasive nature and good temporal and spatial resolution of MR methods. Paramagnetic metalloproteins can be effective MRI sensors due to the selectivity imparted by the protein active site and the ability to tune protein properties using techniques such as directed evolution. Here, we show that structure-guided directed evolution of the active site of the cytochrome P450-BM3 heme domain produces highly selective MRI probes with submicromolar affinities for small molecules. We report a new, high-affinity dopamine sensor as well as the first MRI reporter for serotonin, with which we demonstrate quantification of neurotransmitter release in vitro. We also present a detailed structural analysis of evolved cytochrome P450-BM3 heme domain lineages to systematically dissect the molecular basis of neurotransmitter binding affinity, selectivity, and enhanced MRI contrast activity in these engineered proteins.

In vivo continuous evolution of genes and pathways in yeast

Directed evolution remains a powerful, highly generalizable approach for improving the performance of biological systems. However, implementations in eukaryotes rely either on in vitro diversity generation or limited mutational capacities. Here we synthetically optimize the retrotransposon Ty1 to enable in vivo generation of mutant libraries up to 1.6 × 107 l−1 per round, which is the highest of any in vivo mutational generation approach in yeast. We demonstrate this approach by using in vivo-generated libraries to evolve single enzymes, global transcriptional regulators and multi-gene pathways. When coupled to growth selection, this approach enables in vivo continuous evolution (ICE) of genes and pathways. Through a head-to-head comparison, we find that ICE libraries yield higher-performing variants faster than error-prone PCR-derived libraries. Finally, we demonstrate transferability of ICE to divergent yeasts, including Kluyveromyces lactis and alternative S. cerevisiae strains. Collectively, this work establishes a generic platform for rapid eukaryotic-directed evolution across an array of target cargo.

Using Flux Balance Analysis to Guide Microbial Metabolic Engineering

Metabolic engineers modify biological systems through the use of modern molecular biology tools in order to obtain desired phenotypes. However, due to the extreme complexity and interconnectedness of metabolism in all organisms, it is often difficult to a priori predict which changes will yield the optimal results. Flux balance analysis (FBA) is a mathematical approach that uses a genomic-scale metabolic network models to afford in silico prediction and optimization of metabolic changes. In particular, a genome-scale approach can help select gene targets for knockout and overexpression. This approach can be used to help expedite the strain engineering process. Here, we give an introduction to the use of FBA and provide details for its implementation in a microbial metabolic engineering context.

Linking yeast Gcn5p catalytic function and gene regulation using a quantitative, graded dominant mutant approach.

Establishing causative links between protein functional domains and global gene regulation is critical for advancements in genetics, biotechnology, disease treatment, and systems biology. This task is challenging for multifunctional proteins when relying on traditional approaches such as gene deletions since they remove all domains simultaneously. Here, we describe a novel approach to extract quantitative, causative links by modulating the expression of a dominant mutant allele to create a function-specific competitive inhibition. Using the yeast histone acetyltransferase Gcn5p as a case study, we demonstrate the utility of this approach and (1) find evidence that Gcn5p is more involved in cell-wide gene repression, instead of the accepted gene activation associated with HATs, (2) identify previously unknown gene targets and interactions for Gcn5p-based acetylation, (3) quantify the strength of some Gcn5p-DNA associations, (4) demonstrate that this approach can be used to correctly identify canonical chromatin modifications, (5) establish the role of acetyltransferase activity on synthetic lethal interactions, and (6) identify new functional classes of genes regulated by Gcn5p acetyltransferase activity—all six of these major conclusions were unattainable by using standard gene knockout studies alone. We recommend that a graded dominant mutant approach be utilized in conjunction with a traditional knockout to study multifunctional proteins and generate higher-resolution data that more accurately probes protein domain function and influence.