Media Robustness and Scalability of Phosphate Regulated Promoters Useful for Two-Stage Autoinduction in E. coli

Scalable, robust, high-throughput expression & purification of nanobodies enabled by 2-stage dynamic control

Nanobodies are single-domain antibody fragments that have garnered considerable use as diagnostic and therapeutic agents as well as research tools. However, obtaining pure VHHs, like many proteins, can be laborious and inconsistent. High level cytoplasmic expression in E. coli can be challenging due to improper folding and insoluble aggregation caused by reduction of the conserved disulfide bond. We report a systems engineering approach leveraging engineered strains of E. coli, in combination with a two-stage process and simplified downstream purification, enabling improved, robust, soluble cytoplasmic nanobody expression, as well as rapid cell autolysis and purification. This approach relies on the dynamic control over the reduction potential of the cytoplasm, incorporates lysis enzymes for purification, and can also integrate dynamic expression of protein folding catalysts. Collectively, the engineered system results in more robust growth and protein expression, enabling efficient scalable nanobody production, and purification from high throughput microtiter plates, to routine shake flask cultures and larger instrumented bioreactors. We expect this system will expedite VHH development.

Accelerating Genetic Sensor Development, Scale-up, and Deployment Using Synthetic Biology

Living cells are exquisitely tuned to sense and respond to changes in their environment. Repurposing these systems to create engineered biosensors has seen growing interest in the field of synthetic biology and provides a foundation for many innovative applications spanning environmental monitoring to improved biobased production. In this review, we present a detailed overview of currently available biosensors and the methods that have supported their development, scale-up, and deployment. We focus on genetic sensors in living cells whose outputs affect gene expression. We find that emerging high-throughput experimental assays and evolutionary approaches combined with advanced bioinformatics and machine learning are establishing pipelines to produce genetic sensors for virtually any small molecule, protein, or nucleic acid. However, more complex sensing tasks based on classifying compositions of many stimuli and the reliable deployment of these systems into real-world settings remain challenges. We suggest that recent advances in our ability to precisely modify nonmodel organisms and the integration of proven control engineering principles (e.g., feedback) into the broader design of genetic sensing systems will be necessary to overcome these hurdles and realize the immense potential of the field.

2-Stage microfermentations

Cell based factories can be engineered to produce a wide variety of products. Advances in DNA synthesis and genome editing have greatly simplified the design and construction of these factories. It has never been easier to generate hundreds or even thousands of cell factory strain variants for evaluation. These advances have amplified the need for standardized, higher throughput means of evaluating these designs. Toward this goal, we have previously reported the development of engineered E. coli strains and associated 2-stage production processes to simplify and standardize strain engineering, evaluation and scale up. This approach relies on decoupling growth (stage 1), from production, which occurs in stationary phase (stage 2). Phosphate depletion is used as the trigger to stop growth as well as induce heterologous expression. Here, we describe in detail the development of protocols for the evaluation of engineered E. coli strains in 2-stage microfermentations. These protocols are readily adaptable to the evaluation of strains producing a wide variety of protein as well as small molecule products. Additionally, by detailing the approach to protocol development, these methods are also adaptable to additional cellular hosts, as well as other 2-stage processes with various additional triggers.

Functional expansion of the natural inorganic phosphorus starvation response system in Escherichia coli

Phosphorus, an indispensable nutrient, plays an essential role in cell composition, metabolism, and signal transduction. When inorganic phosphorus (Pi) is scarce, the Pi starvation response in E. coli is activated to increase phosphorus acquisition and drive the cells into a non-growing state to reduce phosphorus consumption. In the six decades of research history, the initiation, output, and shutdown processes of the Pi starvation response have been extensively studied. Simultaneously, Pi starvation has been used in biosensor development, recombinant protein production, and natural product biosynthesis. In this review, we focus on the output process and the applications of the Pi starvation response that have not been summarized before. Meanwhile, based on the current status of mechanistic studies and applications, we propose practical strategies to develop the natural Pi starvation response into a multifunctional and standardized regulatory system in four aspects, including response threshold, temporal expression, intensity range, and bifunctional regulation, which will contribute to its broader application in more fields such as industrial production, medical analysis, and environmental protection.

The Growth Dependent Design Constraints of Transcription-Factor-Based Metabolite Biosensors

Metabolite biosensors based on metabolite-responsive transcription factors are key synthetic biology components for sensing and precisely controlling cellular metabolism. Biosensors are often designed under laboratory conditions but are deployed in applications where cellular growth rate differs drastically from its initial characterization. Here we asked how growth rate impacts the minimum and maximum biosensor outputs and the dynamic range, which are key metrics of biosensor performance. Using LacI, TetR, and FadR-based biosensors in Escherichia coli as models, we find that the dynamic range of different biosensors have different growth rate dependencies. We developed a kinetic model to explore how tuning biosensor parameters impact the dynamic range growth rate dependence. Our modeling and experimental results revealed that the effects to dynamic range and its growth rate dependence are often coupled, and the metabolite transport mechanisms shape the dynamic range-growth rate response. This work provides a systematic understanding of biosensor performance under different growth rates, which will be useful for predicting biosensor behavior in broad synthetic biology and metabolic engineering applications.

Simple Scalable Protein Expression and Extraction Using Two-stage Autoinducible Cell Autolysis and DNA/RNA Autohydrolysis in Escherichia coli

Recombinant protein expression is extensively used in biological research. Despite this, current protein expression and extraction methods are not readily scalable or amenable for high-throughput applications. Optimization of protein expression conditions using traditional methods, reliant on growth-associated induction, is non-trivial. Similarly, protein extraction methods are predominantly restricted to chemical methods, and mechanical methods reliant on expensive specialized equipment more tuned for large-scale applications. In this article, we outline detailed protocols for the use of an engineered autolysis/autohydrolysis E. coli strain, in two-stage fermentations in shake-flasks. This two-stage fermentation protocol does not require optimization of expression conditions and results in high protein titers. Cell lysis in an engineered strain is tightly controlled and only triggered post-culture by addition of a 0.1% detergent solution. Upon cell lysis, a nuclease digests contaminating host oligonucleotides, which facilitates sample handling. This method has been validated for use at different scales, from microtiter plates to instrumented bioreactors. Graphic abstract: Two-stage protein expression, cell autolysis and DNA/RNA autohydrolysis. Reprinted with permission from Menacho-Melgar et al. (2020a). Copyright 2020 John Wiley and Sons.

OUP accepted manuscript

Optimization of metabolism to maximize production of bio-based chemicals must consistently balance cellular resources for biocatalyst growth and desired compound synthesis. This mini-review discusses synthetic biology strategies for dynamically controlling expression of genes to enable dual-phase fermentations in which growth and production are separated into dedicated phases. Emphasis is placed on practical examples which can be reliably scaled to commercial production with the current state of technology. Recent case studies are presented, and recommendations are provided for environmental signals and genetic control circuits.

Optimization of phosphate-limited autoinduction broth for two-stage heterologous protein expression in Escherichia coli

Autoinducible, two-stage protein expression leveraging phosphate-inducible promoters has been recently shown to enable not only high protein titers but also consistent performance across scales from screening systems (microtiter plates) to instrumented bioreactors. However, to date, small-scale production using microtiter plates and shake flasks relies on a complex autoinduction broth (AB) that requires making numerous media components, not all amenable to autoclaving. In this report, the authors develop a simpler media formulation (AB-2) with just a few autoclavable components. AB-2 is robust to small changes in its composition and performs equally, if not better, than AB across different scales. AB-2 will facilitate the adoption of phosphate-limited two-stage protein expression protocols.

Two-stage dynamic deregulation of metabolism improves process robustness & scalability in engineered E. coli

We report that two-stage dynamic control improves bioprocess robustness as a result of the dynamic deregulation of central metabolism. Dynamic control is implemented during stationary phase using combinations of CRISPR interference and controlled proteolysis to reduce levels of central metabolic enzymes. Reducing the levels of key enzymes alters metabolite pools resulting in deregulation of the metabolic network. Deregulated networks are less sensitive to environmental conditions improving process robustness. Process robustness in turn leads to predictable scalability, minimizing the need for traditional process optimization. We validate process robustness and scalability of strains and bioprocesses synthesizing the important industrial chemicals alanine, citramalate and xylitol. Predictive high throughput approaches that translate to larger scales are critical for metabolic engineering programs to truly take advantage of the rapidly increasing throughput and decreasing costs of synthetic biology.

Dynamic Control of Metabolism

Metabolic engineering reprograms cells to synthesize value-added products. In doing so, endogenous genes are altered and heterologous genes can be introduced to achieve the necessary enzymatic reactions. Dynamic regulation of metabolic flux is a powerful control scheme to alleviate and overcome the competing cellular objectives that arise from the introduction of these production pathways. This review explores dynamic regulation strategies that have demonstrated significant production benefits by targeting the metabolic node corresponding to a specific challenge. We summarize the stimulus-responsive control circuits employed in these strategies that determine the criterion for actuating a dynamic response and then examine the points of control that couple the stimulus-responsive circuit to a shift in metabolic flux.

Substrate-activated expression of a biosynthetic pathway in Escherichia coli

Microbes can facilitate production of valuable chemicals more sustainably than traditional chemical processes in many cases: they utilize renewable feedstocks, require less energy intensive process conditions, and perform a variety of chemical reactions using endogenous or heterologous enzymes. In response to the metabolic burden imposed by production pathways, chemical inducers are frequently used to initiate gene expression after the cells have reached sufficient density. While chemically inducible promoters are a common research tool used for pathway expression, they introduce a compound extrinsic to the process along with the associated costs. We developed an expression control system for a biosynthetic pathway for the production of d-glyceric acid that utilizes galacturonate as both the inducer and the substrate, thereby eliminating the need for an extrinsic chemical inducer. Activation of expression in response to the feed is actuated by a galacturonate-responsive transcription factor biosensor. We constructed variants of the galacturonate biosensor with a heterologous transcription factor and cognate hybrid promoter, and selected for the best performer through fluorescence characterization. We showed that native E. coli regulatory systems do not interact with our biosensor and favorable biosensor response exists in the presence and absence of galacturonate consumption. We then employed the control circuit to regulate the expression of the heterologous genes of a biosynthetic pathway for the production d-glyceric acid that was previously developed in our lab. Productivity via substrate-induction with our control circuit was comparable to IPTG-controlled induction and significantly outperformed a constitutive expression control, producing 2.13 ± 0.03 g L^-1  d-glyceric acid within 6 h of galacturonate substrate addition. This work demonstrated feed-activated pathway expression to be an attractive control strategy for more readily scalable microbial biosynthesis.

The bioprocess TEA calculator: An online technoeconomic analysis tool to evaluate the commercial competitiveness of potential bioprocesses

Techno-economic analysis connects R&D, engineering, and business. By linking process parameters to financial metrics, it allows researchers to understand the factors controlling the potential success of their technologies. In particular, metabolic and bioprocess engineering, as disciplines, are aimed at engineering cells to synthesize products with an ultimate goal of commercial deployment. As a result it is critical to be able to understand the potential impact of strain engineering strategies and lab scale results on commercial potential. To date, while numerous techno-economic models have been developed for a wide variety of bioprocesses, they have either required process engineering expertise to adapt and/or use or do not directly connect financial outcomes to potential strain engineering results. Despite the clear value of techno-economic analysis, these challenges have made it inaccessible to many researchers. I have developed this online calculator (https://bioprocesstea.com OR http://bioprocess-tea-calculator.herokuapp.com/) to make the basic capabilities of early-stage techno-economic analysis of bioprocesses readily accessible. The tool, currently focused on aerobic fermentation processes, can be used to understand the impact of fermentation level metrics on the commercial potential of a bioprocess for the production of a wide variety of organic molecules. Using the calculator, I review the commercially relevant targets for an aerobic bioprocess for the production of diethyl malonate.

Dynamic control over feedback regulatory mechanisms improves NADPH flux and xylitol biosynthesis in engineered E. coli

We report improved NADPH flux and xylitol biosynthesis in engineered E. coli. Xylitol is produced from xylose via an NADPH dependent reductase. We utilize 2-stage dynamic metabolic control to compare two approaches to optimize xylitol biosynthesis, a stoichiometric approach, wherein competitive fluxes are decreased, and a regulatory approach wherein the levels of key regulatory metabolites are reduced. The stoichiometric and regulatory approaches lead to a 20-fold and 90-fold improvement in xylitol production, respectively. Strains with reduced levels of enoyl-ACP reductase and glucose-6-phosphate dehydrogenase, led to altered metabolite pools resulting in the activation of the membrane bound transhydrogenase and an NADPH generation pathway, consisting of pyruvate ferredoxin oxidoreductase coupled with NADPH dependent ferredoxin reductase, leading to increased NADPH fluxes, despite a reduction in NADPH pools. These strains produced titers of 200 g/L of xylitol from xylose at 86% of theoretical yield in instrumented bioreactors. We expect dynamic control over the regulation of the membrane bound transhydrogenase as well as NADPH production through pyruvate ferredoxin oxidoreductase to broadly enable improved NADPH dependent bioconversions or production via NADPH dependent metabolic pathways.

Escherichia coli Cas1/2 Endonuclease Complex Modifies Self-Targeting CRISPR/Cascade Spacers Reducing Silencing Guide Stability

CRISPR-based interference has become common in various applications from genetic circuits to dynamic metabolic control. In E. coli, the native CRISPR Cascade system can be utilized for silencing by deletion of the cas3 nuclease along with expression of guide RNA arrays, where multiple genes can be silenced from a single transcript. We notice the loss of spacer sequences from guide arrays utilized for dynamic silencing. We report that unstable guide arrays are due to expression of the Cas1/2 endonuclease complex. We propose a model wherein basal Cas1/2 endonuclease activity results in the loss of spacers from guide arrays. Subsequently, mutant guide arrays can be amplified through selection. Replacing a constitutive promoter driving Cascade complex expression with a tightly controlled inducible promoter improves guide array stability, while minimizing leaky gene silencing. Additionally, these results demonstrate the potential of Cas1/2 mediated guide deletion as a mechanism to avoid CRISPR based autoimmunity.

Low-Cost, Large-Scale Production of the Anti-viral Lectin Griffithsin

Griffithsin, a broad-spectrum antiviral lectin, has potential to prevent and treat numerous viruses including HIV, HCV, HSV, SARS-CoV, and SARS-CoV-2. For these indications, the annual demand for Griffithsin could reach billions of doses and affordability is paramount. We report the lab-scale validation of a bioprocess that supports production volumes of >20 tons per year at a cost of goods sold below $3,500/kg. Recombinant expression in engineered E. coli enables Griffithsin titers ∼2.5 g/L. A single rapid precipitation step provides > 90% yield with 2-, 3-, and 4-log reductions in host cell proteins, endotoxin, and nucleic acids, respectively. Two polishing chromatography steps remove residual contaminants leading to pure, active Griffithsin. Compared to a conventional one this process shows lower costs and improved economies of scale. These results support the potential of biologics in very large-scale, cost-sensitive applications such as antivirals, and highlight the importance of bioprocess innovations in enabling these applications.