A kinetic-based approach to understanding heterologous mevalonate pathway function in E. coli

Changing biosynthesis of terpenoid percursors in rice through synthetic biology

Many highly valued chemicals in the pharmaceutical, biotechnological, cosmetic, and biomedical industries belong to the terpenoid family. Biosynthesis of these chemicals relies on polymerization of Isopentenyl di-phosphate (IPP) and/or dimethylallyl diphosphate (DMAPP) monomers, which plants synthesize using two alternative pathways: a cytosolic mevalonic acid (MVA) pathway and a plastidic methyleritritol-4-phosphate (MEP) pathway. As such, developing plants for use as a platform to use IPP/DMAPP and produce high value terpenoids is an important biotechnological goal. Still, IPP/DMAPP are the precursors to many plant developmental hormones. This creates severe challenges in redirecting IPP/DMAPP towards production of non-cognate plant metabolites. A potential solution to this problem is increasing the IPP/DMAPP production flux in planta. Here, we aimed at discovering, understanding, and predicting the effects of increasing IPP/DMAPP production in plants through modelling. We used synthetic biology to create rice lines containing an additional ectopic MVA biosynthetic pathway for producing IPP/DMAPP. The rice lines express three alternative versions of the additional MVA pathway in the plastid, in addition to the normal endogenous pathways. We collected data for changes in macroscopic and molecular phenotypes, gene expression, isoprenoid content, and hormone abundance in those lines. To integrate the molecular and macroscopic data and develop a more in depth understanding of the effects of engineering the exogenous pathway in the mutant rice lines, we developed and analyzed data-centric, line-specific, multilevel mathematical models. These models connect the effects of variations in hormones and gene expression to changes in macroscopic plant phenotype and metabolite concentrations within the MVA and MEP pathways of WT and mutant rice lines. Our models allow us to predict how an exogenous IPP/DMAPP biosynthetic pathway affects the flux of terpenoid precursors. We also quantify the long-term effect of plant hormones on the dynamic behavior of IPP/DMAPP biosynthetic pathways in seeds, and predict plant characteristics, such as plant height, leaf size, and chlorophyll content from molecular data. In addition, our models are a tool that can be used in the future to help in prioritizing re-engineering strategies for the exogenous pathway in order to achieve specific metabolic goals.

Kinetic characterization and modelling of sequentially entrapped enzymes in 3D-printed PMMA microfluidic reactors for the synthesis of amorphadiene via the isopentenol utilization pathway

The development of cascade cell-free systems reduces the requirement for extensive metabolic engineering and optimization to increase in vivo pathway flux. For continuous operation and increased stability, direct enzyme entrapment during reactor fabrication by 3D-printing allows for simple immobilization procedures without enzyme-specific optimization. In this work, the isopentenol utilization pathway (IUP) was selected for the synthesis of amorphadiene, an anti-malaria drug precursor, using a 3D-printed, sequentially immobilized, microfluidic reactor. As an initial proof-of-concept, alkaline phosphatase (ALP) was entrapped in a poly(methyl methacrylate) (PMMA)-based matrix during stereolithographic 3D-printing and was kinetically characterized. No significant shift of the kinetically modelled substrate binding affinity was observed during immobilization and continuous operation of an entrapped ALP microfluidic reactor displayed high stability. The IUP enzymes retained moderate activity during entrapment (6.6-9.6 %) relative to the free enzyme solutions, however the sequentially immobilized IUP microfluidic reactor was severely limited by low pathway flux due to the use of stereolithographic 3D-printing which significantly diluted enzyme concentrations for printing. Although this study demonstrated the use of additive manufacturing for the synthesis of amorphadiene using a complex five-enzyme cascade microfluidic reactor, stereolithographic enzyme entrapment remains limited in scope and dependent on advancements to additive manufacturing technologies. This article is protected by copyright. All rights reserved.

Metabolic Engineering of Escherichia coli for Production of α-Santalene, a Precursor of Sandalwood Oil

α-Santalene belongs to a class of natural compounds with many physiological functions and medical applications. Advances in metabolic engineering enable non-native hosts (e.g., Escherichia coli) to produce α-santalene, the precursor of sandalwood oil. However, imbalances in enzymatic activity often result in a metabolic burden on hosts and repress the synthetic capacity of the desired product. In this work, we manipulated ribosome binding sites (RBSs) to optimize an α-santalene synthetic operon in E. coli, and the best engineered E. coli NA-IS_3D strain could produce α-santalene at a titer of 412 mg·L^-1. Concerning the observation of the inverse correlation between indole synthesis and α-santalene production, this study speculated that indole-associated amino acid metabolism would be competitive to the synthesis of α-santalene rather than indole toxicity itself. The deletion of tnaA could lead to a 1.5-fold increase in α-santalene production to a titer of 599 mg·L^-1 in E. coli tnaA^- NA-IS_3D. Our results suggested that the optimization of RBS sets of the synthetic module and attenuation of the competitive pathway are promising approaches for improving the production of terpenoids including α-santalene.

Metabolic engineering strategies for sesquiterpene production in microorganism

Sesquiterpenes are a large variety of terpene natural products, widely existing in plants, fungi, marine organisms, insects, and microbes. Value-added sesquiterpenes are extensively used in industries such as: food, drugs, fragrances, and fuels. With an increase in market demands and the price of sesquiterpenes, the biosynthesis of sesquiterpenes by microbial fermentation methods from renewable feedstocks is acquiring increasing attention. Synthetic biology provides robust tools of sesquiterpene production in microorganisms. This review presents a summary of metabolic engineering strategies on the hosts and pathway engineering for sesquiterpene production. Advances in synthetic biology provide new strategies on the creation of desired hosts for sesquiterpene production. Especially, metabolic engineering strategies for the production of sesquiterpenes such as: amorphadiene, farnesene, bisabolene, and caryophyllene are emphasized in: Escherichia coli, Saccharomyces cerevisiae, and other microorganisms. Challenges and future perspectives of the bioprocess for translating sesquiterpene production into practical industrial work are also discussed.

Metabolic engineering and synthetic biology for isoprenoid production in Escherichia coli and Saccharomyces cerevisiae

Isoprenoids, often called terpenoids, are the most abundant and highly diverse family of natural organic compounds. In plants, they play a distinct role in the form of photosynthetic pigments, hormones, electron carrier, structural components of membrane, and defence. Many isoprenoids have useful applications in the pharmaceutical, nutraceutical, and chemical industries. They are synthesized by various isoprenoid synthase enzymes by several consecutive steps. Recent advancement in metabolic engineering and synthetic biology has enabled the production of these isoprenoids in the heterologous host systems like Escherichia coli and Saccharomyces cerevisiae. Both heterologous systems have been engineered for large-scale production of value-added isoprenoids. This review article will provide the detailed description of various approaches used for engineering of methyl-D-erythritol-4-phosphate (MEP) and mevalonate (MVA) pathway for synthesizing isoprene units (C₅) and ultimate production of diverse isoprenoids. The review particularly highlighted the efforts taken for the production of C₅-C₂₀ isoprenoids by metabolic engineering techniques in E. coli and S. cerevisiae over a decade. The challenges and strategies are also discussed in detail for scale-up and engineering of isoprenoids in the heterologous host systems.Key points• Isoprenoids are beneficial and valuable natural products.• E. coli and S. cerevisiae are the promising host for isoprenoid biosynthesis.• Emerging techniques in synthetic biology enabled the improved production.• Need to expand the catalogue and scale-up of un-engineered isoprenoids. Metabolic engineering and synthetic biology for isoprenoid production in Escherichia coli and Saccharomyces cerevisiae.

Regulatory molecule cAMP changes cell fitness of the engineered Escherichia coli for terpenoids production

Terpenoids are a class of natural compounds with many important functions and applications. They are synthesized from a long synthetic pathway of isoprenyl unit coupling with the myriads of terpene synthases. Owing to the catalytic divergence of terpenoids synthesis, microbial production of terpenoids is compromised to the complexity of pathway engineering and suffers from the metabolic engineering burden. In this work, the adaptive Escherichia coli HP variant exhibited a general cell fitness in terpenoid synthesis. Especially, it could yield taxadiene of 193.2 mg/L in a test tube culture, which is a five-fold increase over the production in the wild type E. coli DH5α. Mutational analyses indicated that IS10 insertion in adenylate cyclase CyaA (CyaA_HP) resulted in lowering intracellular cyclic AMP (cAMP), which could regulate its receptor protein CRP to rewire cell metabolism and contributed to the improved cell fitness. Our results suggested a way to manipulate cell fitness for terpenoids production and other products.

The transition of Rhodobacter sphaeroides into a microbial cell factory

Microbial cell factories are the workhorses of industrial biotechnology and improving their performances can significantly optimize industrial bioprocesses. Microbial strain engineering is often employed for increasing the competitiveness of bio‐based product synthesis over more classical petroleum‐based synthesis. Recently, efforts for strain optimization have been standardized within the iterative concept of “design‐build‐test‐learn” (DBTL). This approach has been successfully employed for the improvement of traditional cell factories like Escherichia coli and Saccharomyces cerevisiae. Within the past decade, several new‐to‐industry microorganisms have been investigated as novel cell factories, including the versatile α‐proteobacterium Rhodobacter sphaeroides. Despite its history as a laboratory strain for fundamental studies, there is a growing interest in this bacterium for its ability to synthesize relevant compounds for the bioeconomy, such as isoprenoids, poly‐β‐hydroxybutyrate, and hydrogen. In this study, we reflect on the reasons for establishing R. sphaeroides as a cell factory from the perspective of the DBTL concept. Moreover, we discuss current and future opportunities for extending the use of this microorganism for the bio‐based economy. We believe that applying the DBTL pipeline for R. sphaeroides will further strengthen its relevance as a microbial cell factory. Moreover, the proposed use of strain engineering via the DBTL approach may be extended to other microorganisms that have not been critically investigated yet for industrial applications.

Heterologous Metabolic Pathways: Strategies for Optimal Expression in Eukaryotic Hosts

Heterologous pathways are linked series of biochemical reactions occurring in a host organism after the introduction of foreign genes. Incorporation of metabolic pathways into host organisms is a major strategy used to increase the production of valuable secondary metabolites. Unfortunately, simple introduction of the pathway genes into the heterologous host in most cases does not result in successful heterologous expression. Extensive modification of heterologous genes and the corresponding enzymes on many different levels is required to achieve high target metabolite production rates. This review summarizes the essential techniques used to create heterologous biochemical pathways, with a focus on the key challenges arising in the process and the major strategies for overcoming them.

Metabolic engineering of Escherichia coli for the production of isoprenoids

Metabolic engineering is the practice of using directed genetic manipulations to rewire cellular metabolism primarily with the aim to transform the organism into a single-celled chemical factory. Using biological processes, we can produce more complex chemicals in a more sustainable way. This is particularly important for chemicals which are hard to synthesize using traditional chemistry. However, cells have evolved for growth and must be engineered to produce a single chemical at commercially viable levels. This review focuses on the strategies used to rewire cellular metabolism to produce chemicals using isoprenoid production in Escherichia coli as an example that illustrates many of the challenges faced in metabolic engineering.

Cell-free biosynthesis of limonene using enzyme-enriched Escherichia coli lysates

Isoprenoids are an attractive class of metabolites for enzymatic synthesis from renewable substrates. However, metabolic engineering of microorganisms for monoterpenoid production is limited by the need for time-consuming, and often non-intuitive, combinatorial tuning of biosynthetic pathway variations to meet design criteria. Towards alleviating this limitation, the goal of this work was to build a modular, cell-free platform for construction and testing of monoterpenoid pathways, using the fragrance and flavoring molecule limonene as a model. In this platform, multiple Escherichia coli lysates, each enriched with a single overexpressed pathway enzyme, are mixed to construct the full biosynthetic pathway. First, we show the ability to synthesize limonene from six enriched lysates with mevalonate substrate, an adenosine triphosphate (ATP) source, and cofactors. Next, we extend the pathway to use glucose as a substrate, which relies on native metabolism in the extract to convert glucose to acetyl-CoA along with three additional enzymes to convert acetyl-CoA to mevalonate. We find that the native E. coli farnesyl diphosphate synthase (IspA) is active in the lysate and diverts flux from the pathway intermediate geranyl pyrophospahte to farnesyl pyrophsophate and the byproduct farnesol. By adjusting the relative levels of cofactors NAD+, ATP and CoA, the system can synthesize 0.66 mM (90.2 mg l-1) limonene over 24 h, a productivity of 3.8 mg l-1 h-1. Our results highlight the flexibility of crude lysates to sustain complex metabolism and, by activating a glucose-to-limonene pathway with 9 heterologous enzymes encompassing 20 biosynthetic steps, expands an approach of using enzyme-enriched lysates for constructing, characterizing and prototyping enzymatic pathways.

Application of targeted mass spectrometry in bottom-up proteomics for systems biology research

The enormous diversity of proteoforms produces tremendous complexity within cellular proteomes, facilitates intricate networks of molecular interactions, and constitutes a formidable analytical challenge for biomedical researchers. Currently, quantitative whole-proteome profiling often relies on non-targeted liquid chromatography-mass spectrometry (LC-MS), which samples proteoforms broadly, but can suffer from lower accuracy, sensitivity, and reproducibility compared with targeted LC-MS. Recent advances in bottom-up proteomics using targeted LC-MS have enabled previously unachievable identification and quantification of target proteins and posttranslational modifications within complex samples. Consequently, targeted LC-MS is rapidly advancing biomedical research, especially systems biology research in diverse areas that include proteogenomics, interactomics, kinomics, and biological pathway modeling. With the recent development of targeted LC-MS assays for nearly the entire human proteome, targeted LC-MS is positioned to enable quantitative proteomic profiling of unprecedented quality and accessibility to support fundamental and clinical research. Here we review recent applications of bottom-up proteomics using targeted LC-MS for systems biology research. SIGNIFICANCE: Advances in targeted proteomics are rapidly advancing systems biology research. Recent applications include systems-level investigations focused on posttranslational modifications (such as phosphoproteomics), protein conformation, protein-protein interaction, kinomics, proteogenomics, and metabolic and signaling pathways. Notably, absolute quantification of metabolic and signaling pathway proteins has enabled accurate pathway modeling and engineering. Integration of targeted proteomics with other technologies, such as RNA-seq, has facilitated diverse research such as the identification of hundreds of "missing" human proteins (genes and transcripts that appear to encode proteins but direct experimental evidence was lacking).

Flux-Enabled Exploration of the Role of Sip1 in Galactose Yeast Metabolism

¹³C metabolic flux analysis (¹³C MFA) is an important systems biology technique that has been used to investigate microbial metabolism for decades. The heterotrimer Snf1 kinase complex plays a key role in the preference Saccharomyces cerevisiae exhibits for glucose over galactose, a phenomenon known as glucose repression or carbon catabolite repression. The SIP1 gene, encoding a part of this complex, has received little attention, presumably, because its knockout lacks a growth phenotype. We present a fluxomic investigation of the relative effects of the presence of galactose in classically glucose-repressing media and/or knockout of SIP1 using a multi-scale variant of ¹³C MFA known as 2-Scale ¹³C metabolic flux analysis (2S-¹³C MFA). In this study, all strains have the galactose metabolism deactivated (gal1Δ background) so as to be able to separate the metabolic effects purely related to glucose repression from those arising from galactose metabolism. The resulting flux profiles reveal that the presence of galactose in classically glucose-repressing conditions, for a CEN.PK113-7D gal1Δ background, results in a substantial decrease in pentose phosphate pathway (PPP) flux and increased flow from cytosolic pyruvate and malate through the mitochondria toward cytosolic branched-chain amino acid biosynthesis. These fluxomic redistributions are accompanied by a higher maximum specific growth rate, both seemingly in violation of glucose repression. Deletion of SIP1 in the CEN.PK113-7D gal1Δ cells grown in mixed glucose/galactose medium results in a further increase. Knockout of this gene in cells grown in glucose-only medium results in no change in growth rate and a corresponding decrease in glucose and ethanol exchange fluxes and flux through pathways involved in aspartate/threonine biosynthesis. Glucose repression appears to be violated at a 1/10 ratio of galactose-to-glucose. Based on the scientific literature, we may have conducted our experiments near a critical sugar ratio that is known to allow galactose to enter the cell. Additionally, we report a number of fluxomic changes associated with these growth rate increases and unexpected flux profile redistributions resulting from deletion of SIP1 in glucose-only medium.

Production of jet fuel precursor monoterpenoids from engineered Escherichia coli

Monoterpenes (C₁₀ isoprenoids) are the main components of essential oils and are possible precursors for many commodity chemicals and high energy density fuels. Monoterpenes are synthesized from geranyl diphosphate (GPP), which is also the precursor for the biosynthesis of farnesyl diphosphate (FPP). FPP biosynthesis diverts the carbon flux from monoterpene production to C₁₅ products and quinone biosynthesis. In this study, we tested a chromosomal mutation of Escherichia coli's native FPP synthase (IspA) to improve GPP availability for the production of monoterpenes using a heterologous mevalonate pathway. Monoterpene production at high levels required not only optimization of GPP production but also a basal level of FPP to maintain growth. The optimized strains produced two jet fuel precursor monoterpenoids 1,8-cineole and linalool at the titer of 653 mg/L and 505 mg/L, respectively, in batch cultures with 1% glucose. The engineered strains developed in this work provide useful resources for the production of high-value monoterpenes. Biotechnol. Bioeng. 2017;114: 1703-1712. © 2017 Wiley Periodicals, Inc.

Bacterial Production of Pinene by a Laboratory-Evolved Pinene-Synthase

Successful feeding of the substrate geranylpyrophosphate (GPP) to monoterpene synthase is critical to the efficient microbial production of monoterpenes. Overexpression of GPP synthases, metabolic channeling from GPP synthase to terpene synthases, and down-tuning of endogenous competitors have been successfully used to increase the production of monoterpene. Nevertheless, the production of monoterpenes has remained considerably lower than that of hemi-/sesqui-terpenoids. We tested whether it is effective to improve the cellular activity of monoterpene synthases. To this end, we developed a high-throughput screening system to monitor for elevated GPP consumption. Through a single round of mutagenesis and screening, we isolated a pinene synthase variant that outperformed the wild-type (parent) enzyme in multiple contexts in Escherichia coli and cyanobacteria. The purified variant exhibited drastically altered metal dependency, enabling to keep the activity in the cytosol that is manganese-deficient. Coexpression of this variant with mevalonate pathway enzymes, isopentenylpyrophosphate isomerase, and GPP synthase yielded 140 mg/L pinene in a flask culture.

Semisupervised Gaussian Process for Automated Enzyme Search

Synthetic biology is today harnessing the design of novel and greener biosynthesis routes for the production of added-value chemicals and natural products. The design of novel pathways often requires a detailed selection of enzyme sequences to import into the chassis at each of the reaction steps. To address such design requirements in an automated way, we present here a tool for exploring the space of enzymatic reactions. Given a reaction and an enzyme the tool provides a probability estimate that the enzyme catalyzes the reaction. Our tool first considers the similarity of a reaction to known biochemical reactions with respect to signatures around their reaction centers. Signatures are defined based on chemical transformation rules by using extended connectivity fingerprint descriptors. A semisupervised Gaussian process model associated with the similar known reactions then provides the probability estimate. The Gaussian process model uses information about both the reaction and the enzyme in providing the estimate. These estimates were validated experimentally by the application of the Gaussian process model to a newly identified metabolite in Escherichia coli in order to search for the enzymes catalyzing its associated reactions. Furthermore, we show with several pathway design examples how such ability to assign probability estimates to enzymatic reactions provides the potential to assist in bioengineering applications, providing experimental validation to our proposed approach. To the best of our knowledge, the proposed approach is the first application of Gaussian processes dealing with biological sequences and chemicals, the use of a semisupervised Gaussian process framework is also novel in the context of machine learning applied to bioinformatics. However, the ability of an enzyme to catalyze a reaction depends on the affinity between the substrates of the reaction and the enzyme. This affinity is generally quantified by the Michaelis constant KM. Therefore, we also demonstrate using Gaussian process regression to predict KM given a substrate-enzyme pair.

Characterizing Strain Variation in Engineered E. coli Using a Multi-Omics-Based Workflow

Understanding the complex interactions that occur between heterologous and native biochemical pathways represents a major challenge in metabolic engineering and synthetic biology. We present a workflow that integrates metabolomics, proteomics, and genome-scale models of Escherichia coli metabolism to study the effects of introducing a heterologous pathway into a microbial host. This workflow incorporates complementary approaches from computational systems biology, metabolic engineering, and synthetic biology; provides molecular insight into how the host organism microenvironment changes due to pathway engineering; and demonstrates how biological mechanisms underlying strain variation can be exploited as an engineering strategy to increase product yield. As a proof of concept, we present the analysis of eight engineered strains producing three biofuels: isopentenol, limonene, and bisabolene. Application of this workflow identified the roles of candidate genes, pathways, and biochemical reactions in observed experimental phenomena and facilitated the construction of a mutant strain with improved productivity. The contributed workflow is available as an open-source tool in the form of iPython notebooks.

Synthetic and systems biology for microbial production of commodity chemicals

The combination of synthetic and systems biology is a powerful framework to study fundamental questions in biology and produce chemicals of immediate practical application such as biofuels, polymers, or therapeutics. However, we cannot yet engineer biological systems as easily and precisely as we engineer physical systems. In this review, we describe the path from the choice of target molecule to scaling production up to commercial volumes. We present and explain some of the current challenges and gaps in our knowledge that must be overcome in order to bring our bioengineering capabilities to the level of other engineering disciplines. Challenges start at molecule selection, where a difficult balance between economic potential and biological feasibility must be struck. Pathway design and construction have recently been revolutionized by next-generation sequencing and exponentially improving DNA synthesis capabilities. Although pathway optimization can be significantly aided by enzyme expression characterization through proteomics, choosing optimal relative protein expression levels for maximum production is still the subject of heuristic, non-systematic approaches. Toxic metabolic intermediates and proteins can significantly affect production, and dynamic pathway regulation emerges as a powerful but yet immature tool to prevent it. Host engineering arises as a much needed complement to pathway engineering for high bioproduct yields; and systems biology approaches such as stoichiometric modeling or growth coupling strategies are required. A final, and often underestimated, challenge is the successful scale up of processes to commercial volumes. Sustained efforts in improving reproducibility and predictability are needed for further development of bioengineering.

The potential of the mevalonate pathway for enhanced isoprenoid production

The cytosol-localised mevalonic acid (MVA) pathway delivers the basic isoprene unit isopentenyl diphosphate (IPP). In higher plants, this central metabolic intermediate is also synthesised by the plastid-localised methylerythritol phosphate (MEP) pathway. Both MVA and MEP pathways conspire through exchange of intermediates and regulatory interactions. Products downstream of IPP such as phytosterols, carotenoids, vitamin E, artemisinin, tanshinone and paclitaxel demonstrate antioxidant, cholesterol-reducing, anti-ageing, anticancer, antimalarial, anti-inflammatory and antibacterial activities. Other isoprenoid precursors including isoprene, isoprenol, geraniol, farnesene and farnesol are economically valuable. An update on the MVA pathway and its interaction with the MEP pathway is presented, including the improvement in the production of phytosterols and other isoprenoid derivatives. Such attempts are for instance based on the bioengineering of microbes such as Escherichia coli and Saccharomyces cerevisiae, as well as plants. The function of relevant genes in the MVA pathway that can be utilised in metabolic engineering is reviewed and future perspectives are presented.

Kinetic modeling of cell metabolism for microbial production

Kinetic models of cellular metabolism are important tools for the rational design of metabolic engineering strategies and to explain properties of complex biological systems. The recent developments in high-throughput experimental data are leading to new computational approaches for building kinetic models of metabolism. Herein, we briefly survey the available databases, standards and software tools that can be applied for kinetic models of metabolism. In addition, we give an overview about recently developed ordinary differential equations (ODE)-based kinetic models of metabolism and some of the main applications of such models are illustrated in guiding metabolic engineering design. Finally, we review the kinetic modeling approaches of large-scale networks that are emerging, discussing their main advantages, challenges and limitations.

Rites of passage: requirements and standards for building kinetic models of metabolic phenotypes

The overarching ambition of kinetic metabolic modeling is to capture the dynamic behavior of metabolism to such an extent that systems and synthetic biology strategies can reliably be tested in silico. The lack of kinetic data hampers the development of kinetic models, and most of the current models use ad hoc reduced stoichiometry or oversimplified kinetic rate expressions, which may limit their predictive strength. There is a need to introduce the community-level standards that will organize and accelerate the future developments in this area. We introduce here a set of requirements that will ensure the model quality, we examine the current kinetic models with respect to these requirements, and we propose a general workflow for constructing models that satisfy these requirements.

Improving prediction fidelity of cellular metabolism with kinetic descriptions

Several modeling frameworks for describing and redirecting cellular metabolism have been developed keeping pace with the rapid development in high-throughput data generation and advances in metabolic engineering techniques. The incorporation of kinetic information within stoichiometry-only modeling techniques offers potential advantages for improved phenotype prediction and consequently more precise computational strain design. In addition to substrate-level kinetic regulatory information, the integration of a number of additional layers of regulation at the transcription, translation, and post-translation levels is sought after by many research groups. However, the practical integration of these complex biological processes into a unified framework amenable to design remains an ongoing challenge.

Metabolic engineering for the high-yield production of isoprenoid-based C₅ alcohols in E. coli

Branched five carbon (C₅) alcohols are attractive targets for microbial production due to their desirable fuel properties and importance as platform chemicals. In this study, we engineered a heterologous isoprenoid pathway in E. coli for the high-yield production of 3-methyl-3-buten-1-ol, 3-methyl-2-buten-1-ol, and 3-methyl-1-butanol, three C₅ alcohols that serve as potential biofuels. We first constructed a pathway for 3-methyl-3-buten-1-ol, where metabolite profiling identified NudB, a promiscuous phosphatase, as a likely pathway bottleneck. We achieved a 60% increase in the yield of 3-methyl-3-buten-1-ol by engineering the Shine-Dalgarno sequence of nudB, which increased protein levels by 9-fold and reduced isopentenyl diphosphate (IPP) accumulation by 4-fold. To further optimize the pathway, we adjusted mevalonate kinase (MK) expression and investigated MK enzymes from alternative microbes such as Methanosarcina mazei. Next, we expressed a fusion protein of IPP isomerase and the phosphatase (Idi1~NudB) along with a reductase (NemA) to diversify production to 3-methyl-2-buten-1-ol and 3-methyl-1-butanol. Finally, we used an oleyl alcohol overlay to improve alcohol recovery, achieving final titers of 2.23 g/L of 3-methyl-3-buten-1-ol (~70% of pathway-dependent theoretical yield), 150 mg/L of 3-methyl-2-buten-1-ol, and 300 mg/L of 3-methyl-1-butanol.