Nutrient assimilation is the first step that allows biological systems to proliferate and produce value-added products. Yet, implementation of heterologous catabolic pathways has so far relied on constitutive gene expression without consideration for global regulatory systems that may enhance nutrient assimilation and cell growth. In contrast, natural systems prefer nutrient-responsive gene regulation (called regulons) that control multiple cellular functions necessary for cell survival and growth. Here, in Saccharomyces cerevisiae, by partially- and fully uncoupling galactose (GAL)-responsive regulation and metabolism, we demonstrate the significant growth benefits conferred by the GAL regulon. Next, by adapting the various aspects of the GAL regulon for a non-native nutrient, xylose, we build a semi-synthetic regulon that exhibits higher growth rate, better nutrient consumption, and improved growth fitness compared to the traditional and ubiquitous constitutive expression strategy. This work provides an elegant paradigm to integrate non-native nutrient catabolism with native, global cellular responses to support fast growth.

Extending the host substrate range of industrially relevant microbes, such as Saccharomyces cerevisiae, has been a highly-active area of research since the conception of metabolic engineering. Yet, rational strategies that enable non-native substrate utilization in this yeast without the need for combinatorial and/or evolutionary techniques are underdeveloped. Herein, this review focuses on pentose metabolism in S. cerevisiae as a case study to highlight the challenges in this field. In the last three decades, work has focused on expressing exogenous pentose metabolizing enzymes as well as endogenous enzymes for effective pentose assimilation, growth, and biofuel production. The engineering strategies that are employed for pentose assimilation in this yeast are reviewed, and compared with metabolism and regulation of native sugar, galactose. In the case of galactose metabolism, multiple signals regulate and aid growth in the presence of the sugar. However, for pentoses that are non-native, it is unclear if similar growth and regulatory signals are activated. Such a comparative analysis aids in identifying missing links in xylose and arabinose utilization. While research on pentose metabolism have mostly concentrated on pathway level optimization, recent transcriptomics analyses highlight the need to consider more global regulatory, structural, and signaling components.

Engineering synthetic heterotrophy (i.e., growth on non-native substrates) is key to efficient bio-based valorization of various renewable (e.g., lignocellulosic biomass) and waste (e.g., plastics) substrates. Among these, engineering hemicellulosic pentose utilization has been well-explored in Saccharomyces cerevisiae (yeast) over several decades but genetic factors that constrain maximum growth rate remain elusive. Through a systematic analysis (flux balancing, directed evolution, functional genomics, and network modeling), we find that once global regulatory response is appropriately remodeled, wild-type-like growth profiles can be achieved with minimal metabolic engineering effort. This indicates that intrinsic yeast metabolism is highly adaptable to growth on non-native substrates. We identified that extrinsic factors – specifically, genes that direct flux of pentoses into central carbon metabolism – are rate limiting. We also find that deletion of endogenous genes to promote growth demonstrate inconsistent outcomes that are genetic-context- and condition-dependent. For the most part, these knockouts also lead to deleterious pleiotropic effects that decrease the robustness of strains against inhibitors commonly found in lignocellulosic hydrolysate. Thus, perturbation of intrinsic factors (e.g., metabolic, regulatory genes) provides incremental and inconsistent benefits at best and at worst, is detrimental. Not only do the findings and approach described here expedite the design-build-test cycle but also simplifies the engineering process. Overall, this work provides insight into the limitations and pitfalls to realizing efficient synthetic heterotrophy and provides a novel paradigm to engineer the same.

BackgroundIncreasing understanding of metabolic and regulatory networks underlying microbial physiology has enabled creation of progressively more complex synthetic biological systems for biochemical, biomedical, agricultural, and environmental applications. However, despite best efforts, confounding phenotypes still emerge from unforeseen interplay between biological parts, and the design of robust and modular biological systems remains elusive. Such interactions are difficult to predict when designing synthetic systems and may manifest during experimental testing as inefficiencies that need to be overcome. Despite advances in tools and methodologies for strain engineering, there remains a lack of tools that can systematically identify incompatibilities between the native metabolism of the host and its engineered modifications.ResultsTransforming organisms such as Escherichia coli into microbial factories is achieved via a number of engineering strategies, used individually or in combination, with the goal of maximizing the production of chosen target compounds. One technique relies on suppressing or overexpressing selected genes; another involves on introducing heterologous enzymes into a microbial host. These modifications steer mass flux towards the set of desired metabolites but may create unexpected interactions. In this work, we develop a computational method, termed Metabolic Disruption Workflow (MDFlow), for discovering interactions and network disruption arising from enzyme promiscuity – the ability of enzymes to act on a wide range of molecules that are structurally similar to their native substrates. We apply MDFlow to two experimentally verified cases where strains with essential genes knocked out are rescued by interactions resulting from overexpression of one or more other genes. We then apply MDFlow to predict and evaluate a number of putative promiscuous reactions that can interfere with two heterologous pathways designed for 3-hydroxypropic acid (3-HP) production.ConclusionsUsing MDFlow, we can identify putative enzyme promiscuity and the subsequent formation of unintended and undesirable byproducts that are not only disruptive to the host metabolism but also to the intended end-objective of high biosynthetic productivity and yield. In addition, we show how enzyme promiscuity can potentially be responsible for the adaptability of cells to the disruption of essential pathways in terms of biomass growth.

Increasing understanding of metabolic and regulatory networks underlying microbial physiology has enabled creation of progressively more complex synthetic biological systems for biochemical, biomedical, agricultural, and environmental applications. However, despite best efforts, confounding phenotypes still emerge from unforeseen interplay between biological parts, and the design of robust and modular biological systems remains elusive. Such interactions are difficult to predict when designing synthetic systems and may manifest during experimental testing as inefficiencies that need to be overcome. Transforming organisms such as Escherichia coli into microbial factories is achieved via several engineering strategies, used individually or in combination, with the goal of maximizing the production of chosen target compounds. One technique relies on suppressing or overexpressing selected genes; another involves introducing heterologous enzymes into a microbial host. These modifications steer mass flux towards the set of desired metabolites but may create unexpected interactions. In this work, we develop a computational method, termed M etabolic D isruption Work flow ( MDFlow ), for discovering interactions and network disruptions arising from enzyme promiscuity – the ability of enzymes to act on a wide range of molecules that are structurally similar to their native substrates. We apply MDFlow to two experimentally verified cases where strains with essential genes knocked out are rescued by interactions resulting from overexpression of one or more other genes. We demonstrate how enzyme promiscuity may aid cells in adapting to disruptions of essential metabolic functions. We then apply MDFlow to predict and evaluate a number of putative promiscuous reactions that can interfere with two heterologous pathways designed for 3-hydroxypropionic acid (3-HP) production. Using MDFlow , we can identify putative enzyme promiscuity and the subsequent formation of unintended and undesirable byproducts that are not only disruptive to the host metabolism but also to the intended end-objective of high biosynthetic productivity and yield. As we demonstrate, MDFlow provides an innovative workflow to systematically identify incompatibilities between the native metabolism of the host and its engineered modifications due to enzyme promiscuity.