Computational Design of Auxotrophy-Dependent Microbial Biosensors for Combinatorial Metabolic Engineering Experiments

Combinatorial approaches in metabolic engineering work by generating genetic diversity in a microbial population followed by screening for strains with improved phenotypes. One of the most common goals in this field is the generation of a high rate chemical producing strain. A major hurdle with this approach is that many chemicals do not have easy to recognize attributes, making their screening expensive and time consuming. To address this problem, it was previously suggested to use microbial biosensors to facilitate the detection and quantification of chemicals of interest. Here, we present novel computational methods to: (i) rationally design microbial biosensors for chemicals of interest based on substrate auxotrophy that would enable their high-throughput screening; (ii) predict engineering strategies for coupling the synthesis of a chemical of interest with the production of a proxy metabolite for which high-throughput screening is possible via a designed bio-sensor. The biosensor design method is validated based on known genetic modifications in an array of E. coli strains auxotrophic to various amino-acids. Predicted chemical production rates achievable via the biosensor-based approach are shown to potentially improve upon those predicted by current rational strain design approaches. (A Matlab implementation of the biosensor design method is available via http://www.cs.technion.ac.il/~tomersh/tools)

Experimental design-aided systematic pathway optimization of glucose uptake and deoxyxylulose phosphate pathway for improved amorphadiene production

Artemisinin is a potent antimalarial drug; however, it suffers from unstable and insufficient supply from plant source. Here, we established a novel multivariate-modular approach based on experimental design for systematic pathway optimization that succeeded in improving the production of amorphadiene (AD), the precursor of artemisinin, in Escherichia coli. It was initially found that the AD production was limited by the imbalance of glyceraldehyde 3-phosphate (GAP) and pyruvate (PYR), the two precursors of the 1-deoxy-d-xylulose-5-phosphate (DXP) pathway. Furthermore, it was identified that GAP and PYR could be balanced by replacing the phosphoenolpyruvate (PEP)-dependent phosphotransferase system (PTS) with the ATP-dependent galactose permease and glucose kinase system (GGS) and this resulted in fivefold increase in AD titer (11 to 60 mg/L). Subsequently, the experimental design-aided systematic pathway optimization (EDASPO) method was applied to systematically optimize the transcriptional expressions of eight critical genes in the glucose uptake and the DXP and AD synthesis pathways. These genes were classified into four modules and simultaneously controlled by T7 promoter or its variants. A regression model was generated using the four-module experimental data and predicted the optimal expression ratios among these modules, resulting in another threefold increase in AD titer (60 to 201 mg/L). This EDASPO method may be useful for the optimization of other pathways and products beyond the scope of this study.Singapore-MIT Alliance for Research and Technology (SMART

Combining Genotype Improvement and Statistical Media Optimization for Isoprenoid Production in E. coli

Isoprenoids are a large and diverse class of compounds that includes many high value natural products and are thus in great demand. To meet the increasing demand for isoprenoid compounds, metabolic engineering of microbes has been used to produce isoprenoids in an economical and sustainable manner. To achieve high isoprenoid yields using this technology, the availability of metabolic precursors feeding the deoxyxylulose phosphate (DXP) pathway, responsible for isoprenoid biosynthesis, has to be optimized. In this study, phosphoenolpyruvate, a vital DXP pathway precursor, was enriched by deleting the genes encoding the carbohydrate phosphotransferase system (PTS) in E. coli. Production of lycopene (a C40 isoprenoid) was maximized by optimizing growth medium and culture conditions. In optimized conditions, the lycopene yield from PTS mutant was seven fold higher than that obtained from the wild type strain. This resulted in the highest reported specific yield of lycopene produced from the DXP pathway in E. coli to date (20,000 µg/g dry cell weight). Both the copy number of the plasmid encoding the lycopene biosynthetic genes and the expression were found to be increased in the optimized media. Deletion of PTS together with a similar optimization strategy was also successful in enhancing the production of amorpha-1,4-diene, a distinct C15 isoprenoid, suggesting that the approaches developed herein can be generally applied to optimize production of other isoprenoids.Singapore-MIT Allianc