Increasing diterpene yield with a modular metabolic engineering system in E. coli: comparison of MEV and MEP isoprenoid precursor pathway engineering

Engineering biosynthetic pathways in heterologous microbial host organisms offers an elegant approach to pathway elucidation via the incorporation of putative biosynthetic enzymes and characterization of resulting novel metabolites. Our previous work in Escherichia coli demonstrated the feasibility of a facile modular approach to engineering the production of labdane-related diterpene (20 carbon) natural products. However, yield was limited (<0.1 mg/L), presumably due to reliance on endogenous production of the isoprenoid precursors dimethylallyl diphosphate and isopentenyl diphosphate. Here, we report incorporation of either a heterologous mevalonate pathway (MEV) or enhancement of the endogenous methyl erythritol phosphate pathway (MEP) with our modular metabolic engineering system. With MEP pathway enhancement, it was found that pyruvate supplementation of rich media and simultaneous overexpression of three genes (idi, dxs, and dxr) resulted in the greatest increase in diterpene yield, indicating distributed metabolic control within this pathway. Incorporation of a heterologous MEV pathway in bioreactor grown cultures resulted in significantly higher yields than MEP pathway enhancement. We have established suitable growth conditions for diterpene production levels ranging from 10 to >100 mg/L of E. coli culture. These amounts are sufficient for nuclear magnetic resonance analyses, enabling characterization of enzymatic products and hence, pathway elucidation. Furthermore, these results represent an up to >1,000-fold improvement in diterpene production from our facile, modular platform, with MEP pathway enhancement offering a cost effective alternative with reasonable yield. Finally, we reiterate here that this modular approach is expandable and should be easily adaptable to the production of any terpenoid natural product

Two-photon dual imaging platform for in vivo monitoring cellular oxidative stress in liver injury

Oxidative stress reflects an imbalance between reactive oxygen species (ROS) and antioxidants, which has been reported as an early unifying event in the development and progression of various diseases and as a direct and mechanistic indicator of treatment response. However, highly reactive and short-lived nature of ROS and antioxidant limited conventional detection agents, which are influenced by many interfering factors. Here, we present a two-photon sensing platform for in vivo dual imaging of oxidative stress at the single cell-level resolution. This sensing platform consists of three probes, which combine the turn-on fluorescent transition-metal complex with different specific responsive groups for glutathione (GSH), hydrogen peroxide (H2O2) and hypochlorous acid (HOCl). By combining fluorescence intensity imaging and fluorescence lifetime imaging, these probes totally remove any possibility of crosstalk from in vivo environmental or instrumental factors, and enable accurate localization and measurement of the changes in ROS and GSH within the liver. This precedes changes in conventional biochemical and histological assessments in two distinct experimental murine models of liver injury. The ability to monitor real-time cellular oxidative stress with dual-modality imaging has significant implications for high-accurate, spatially configured and quantitative assessment of metabolic status and drug response

Refactoring of a Synthetic Raspberry Ketone Pathway with EcoFlex

Background: A key focus of synthetic biology is to develop microbial or cell-free based biobased routes to value-added chemicals such as fragrances. Originally, we developed the EcoFlex system, a Golden Gate toolkit, to study genes/pathways flexibly using Escherichia coli heterologous expression. In this current work, we sought to use EcoFlex to optimise a synthetic raspberry ketone biosynthetic pathway. Raspberry ketone is a high-value (~£20,000 kg-1) fine chemical farmed from raspberry (Rubeus rubrum) fruit.Results: By applying a synthetic biology led design-build-test-learn cycle approach, we refactor the raspberry ketone pathway from a low level of productivity (0.2 mg/L), to achieve a 65-fold (12.9 mg/L) improvement in production. We perform this optimisation at the prototype level (using microtiter plate cultures) with E. coli DH10, as a routine cloning host. The use of E. coli DH10 facilitates the Golden Gate cloning process for the screening of combinatorial libraries. In addition, we also newly establish a novel colour-based phenotypic screen to identify productive clones quickly from solid/liquid culture. Conclusions: Our findings provide a stable raspberry ketone pathway that relies upon a natural feedstock (L-tyrosine) and uses only constitutive promoters to control gene expression. In conclusion we demonstrate the capability of EcoFlex for fine-tuning a model fine chemical pathway and provide a range of newly characterised promoter tools gene expression in E. coli

Integrated high-content quantification of intracellular ROS levels and mitochondrial morphofunction

Oxidative stress arises from an imbalance between the production of reactive oxygen species (ROS) and their removal by cellular antioxidant systems. Especially under pathological conditions, mitochondria constitute a relevant source of cellular ROS. These organelles harbor the electron transport chain, bringing electrons in close vicinity to molecular oxygen. Although a full understanding is still lacking, intracellular ROS generation and mitochondrial function are also linked to changes in mitochondrial morphology. To study the intricate relationships between the different factors that govern cellular redox balance in living cells, we have developed a high-contentmicroscopy-based strategy for simultaneous quantification of intracellular ROS levels and mitochondrial morphofunction. Here, we summarize the principles of intracellular ROS generation and removal, and we explain the major considerations for performing quantitative microscopy analyses of ROS and mitochondrial morphofunction in living cells. Next, we describe our workflow, and finally, we illustrate that a multiparametric readout enables the unambiguous classification of chemically perturbed cells as well as laminopathy patient cells

Genetically programmed chiral organoborane synthesis

Recent advances in enzyme engineering and design have expanded nature’s catalytic repertoire to functions that are new to biology. However, only a subset of these engineered enzymes can function in living systems. Finding enzymatic pathways that form chemical bonds that are not found in biology is particularly difficult in the cellular environment, as this depends on the discovery not only of new enzyme activities, but also of reagents that are both sufficiently reactive for the desired transformation and stable in vivo. Here we report the discovery, evolution and generalization of a fully genetically encoded platform for producing chiral organoboranes in bacteria. Escherichia coli cells harbouring wild-type cytochrome c from Rhodothermus marinus8 (Rma cyt c) were found to form carbon–boron bonds in the presence of borane–Lewis base complexes, through carbene insertion into boron–hydrogen bonds. Directed evolution of Rma cyt c in the bacterial catalyst provided access to 16 novel chiral organoboranes. The catalyst is suitable for gram-scale biosynthesis, providing up to 15,300 turnovers, a turnover frequency of 6,100 h^(–1), a 99:1 enantiomeric ratio and 100% chemoselectivity. The enantiopreference of the biocatalyst could also be tuned to provide either enantiomer of the organoborane products. Evolved in the context of whole-cell catalysts, the proteins were more active in the whole-cell system than in purified forms. This study establishes a DNA-encoded and readily engineered bacterial platform for borylation; engineering can be accomplished at a pace that rivals the development of chemical synthetic methods, with the ability to achieve turnovers that are two orders of magnitude (over 400-fold) greater than those of known chiral catalysts for the same class of transformation. This tunable method for manipulating boron in cells could expand the scope of boron chemistry in living systems

A saturated map of common genetic variants associated with human height

Common single-nucleotide polymorphisms (SNPs) are predicted to collectively explain 40-50% of phenotypic variation in human height, but identifying the specific variants and associated regions requires huge sample sizes(1). Here, using data from a genome-wide association study of 5.4 million individuals of diverse ancestries, we show that 12,111 independent SNPs that are significantly associated with height account for nearly all of the common SNP-based heritability. These SNPs are clustered within 7,209 non-overlapping genomic segments with a mean size of around 90 kb, covering about 21% of the genome. The density of independent associations varies across the genome and the regions of increased density are enriched for biologically relevant genes. In out-of-sample estimation and prediction, the 12,111 SNPs (or all SNPs in the HapMap 3 panel(2)) account for 40% (45%) of phenotypic variance in populations of European ancestry but only around 10-20% (14-24%) in populations of other ancestries. Effect sizes, associated regions and gene prioritization are similar across ancestries, indicating that reduced prediction accuracy is likely to be explained by linkage disequilibrium and differences in allele frequency within associated regions. Finally, we show that the relevant biological pathways are detectable with smaller sample sizes than are needed to implicate causal genes and variants. Overall, this study provides a comprehensive map of specific genomic regions that contain the vast majority of common height-associated variants. Although this map is saturated for populations of European ancestry, further research is needed to achieve equivalent saturation in other ancestries.A large genome-wide association study of more than 5 million individuals reveals that 12,111 single-nucleotide polymorphisms account for nearly all the heritability of height attributable to common genetic variants