The effect of metabolic stress on genome stability of a synthetic biology chassis Escherichia coli K12 strain

Harnessing microbial heterogeneity for improved biosynthesis fueled by synthetic biology

Metabolic engineering-driven microbial cell factories have made great progress in the efficient bioproduction of biochemical and recombinant proteins. However, the low efficiency and robustness of microbial cell factories limit their industrial applications. Harnessing microbial heterogeneity contributes to solving this. In this review, the origins of microbial heterogeneity and its effects on biosynthesis are first summarized. Synthetic biology-driven tools and strategies that can be used to improve biosynthesis by increasing and reducing microbial heterogeneity are then systematically summarized. Next, novel single-cell technologies available for unraveling microbial heterogeneity and facilitating heterogeneity regulation are discussed. Furthermore, a combined workflow of increasing genetic heterogeneity in the strain-building step to help in screening highly productive strains - reducing heterogeneity in the production process to obtain highly robust strains (IHP-RHR) facilitated by single-cell technologies was proposed to obtain highly productive and robust strains by harnessing microbial heterogeneity. Finally, the prospects and future challenges are discussed.

Emergent digital bio-computation through spatial diffusion and engineered bacteria

Biological computing is a promising field with potential applications in biosafety, environmental monitoring, and personalized medicine. Here we present work on the design of bacterial computers using spatial patterning to process information in the form of diffusible morphogen-like signals. We demonstrate, mathematically and experimentally, that single, modular, colonies can perform simple digital logic, and that complex functions can be built by combining multiple colonies, removing the need for further genetic engineering. We extend our experimental system to incorporate sender colonies as morphogen sources, demonstrating how one might integrate different biochemical inputs. Our approach will open up ways to perform biological computation, with applications in bioengineering, biomaterials and biosensing. Ultimately, these computational bacterial communities will help us explore information processing in natural biological systems.

"Metabolic burden" explained: stress symptoms and its related responses induced by (over)expression of (heterologous) proteins in Escherichia coli

BACKGROUND

Engineering bacterial strains to redirect the metabolism towards the production of a specific product has enabled the development of industrial biotechnology. However, rewiring the metabolism can have severe implications for a microorganism, rendering cells with stress symptoms such as a decreased growth rate, impaired protein synthesis, genetic instability and an aberrant cell size. On an industrial scale, this is reflected in processes that are not economically viable.

MAIN TEXT

In literature, most stress symptoms are attributed to "metabolic burden", however the actual triggers and stress mechanisms involved are poorly understood. Therefore, in this literature review, we aimed to get a better insight in how metabolic engineering affects Escherichia coli and link the observed stress symptoms to its cause. Understanding the possible implications that chosen engineering strategies have, will help to guide the reader towards optimising the envisioned process more efficiently.

CONCLUSION

This review addresses the gap in literature and discusses the triggers and effects of stress mechanisms that can be activated when (over)expressing (heterologous) proteins in Escherichia coli. It uncovers that the activation of the different stress mechanisms is complex and that many are interconnected. The reader is shown that care has to be taken when (over)expressing (heterologous) proteins as the cell's metabolism is tightly regulated.

The Causes for Genomic Instability and How to Try and Reduce Them Through Rational Design of Synthetic DNA

Genetic engineering has revolutionized our ability to manipulate DNA and engineer organisms for various applications. However, this approach can lead to genomic instability, which can result in unwanted effects such as toxicity, mutagenesis, and reduced productivity. To overcome these challenges, smart design of synthetic DNA has emerged as a promising solution. By taking into consideration the intricate relationships between gene expression and cellular metabolism, researchers can design synthetic constructs that minimize metabolic stress on the host cell, reduce mutagenesis, and increase protein yield. In this chapter, we summarize the main challenges of genomic instability in genetic engineering and address the dangers of unknowingly incorporating genomically unstable sequences in synthetic DNA. We also demonstrate the instability of those sequences by the fact that they are selected against conserved sequences in nature. We highlight the benefits of using ESO, a tool for the rational design of DNA for avoiding genetically unstable sequences, and also summarize the main principles and working parameters of the software that allow maximizing its benefits and impact.

Fighting the battle against evolution: designing genetically modified organisms for evolutionary stability

Synthetic biology has made significant progress in many areas, but a major challenge that has received limited attention is the evolutionary stability of synthetic constructs made of heterologous genes. The expression of these constructs in microorganisms, that is, production of proteins that are not necessary for the organism, is a metabolic burden, leading to a decrease in relative fitness and make the synthetic constructs unstable over time. This is a significant concern for the synthetic biology community, particularly when it comes to bringing this technology out of the laboratory. In this review, we discuss the issue of evolutionary stability in synthetic biology and review the available tools to address this challenge.

Engineering biology in the face of uncertainty

Combining engineering and biology surely must be a route to delivering solutions to the world's most pressing problems in depleting resources, energy and the environment. Engineers and biologists have long recognized the power in coupling their disciplines and have evolved a healthy variety of approaches to realizing technologies. Yet recently, there has been a movement to narrow the remit of engineering biology. Its definition as 'the application of engineering principles to the design of biological systems' ought to encompass a broad church. However, the emphasis is firmly on construction '…of novel biological devices and systems from standardized artificial parts' within cells. Thus, engineering biology has become synonymous with synthetic biology, despite the many longstanding technologies that use natural microbial communities. The focus on the nuts and bolts of synthetic organisms may be deflecting attention from the significant challenge of delivering solutions at scale, which cuts across all engineering biology, synthetic and natural. Understanding, let alone controlling, every component of an engineered system is an unrealistic goal. To realize workable solutions in a timely manner we must develop systematic ways of engineering biology in the face of the uncertainties that are inherent in biological systems and that arise through lack of knowledge.

Engineering eukaryote-like regulatory circuits to expand artificial control mechanisms for metabolic engineering in Saccharomyces cerevisiae

Temporal control of heterologous pathway expression is critical to achieve optimal efficiency in microbial metabolic engineering. The broadly-used GAL promoter system for engineered yeast (Saccharomyces cerevisiae) suffers from several drawbacks; specifically, unintended induction during laboratory development, and unintended repression in industrial production applications, which decreases overall production capacity. Eukaryotic synthetic circuits have not been well examined to address these problems. Here, we explore a modularised engineering method to deploy new genetic circuits applicable for expanding the control of GAL promoter-driven heterologous pathways in S. cerevisiae. Trans- and cis- modules, including eukaryotic trans-activating-and-repressing mechanisms, were characterised to provide new and better tools for circuit design. A eukaryote-like tetracycline-mediated circuit that delivers stringent repression was engineered to minimise metabolic burden during strain development and maintenance. This was combined with a novel 37 °C induction circuit to relief glucose-mediated repression on the GAL promoter during the bioprocess. This delivered a 44% increase in production of the terpenoid nerolidol, to 2.54 g L^-1 in flask cultivation. These negative/positive transcriptional regulatory circuits expand global strategies of metabolic control to facilitate laboratory maintenance and for industry applications.

Contextual dependencies expand the re-usability of genetic inverters

The implementation of Boolean logic circuits in cells have become a very active field within synthetic biology. Although these are mostly focussed on the genetic components alone, the context in which the circuit performs is crucial for its outcome. We characterise 20 genetic NOT logic gates in up to 7 bacterial-based contexts each, to generate 135 different functions. The contexts we focus on are combinations of four plasmid backbones and three hosts, two Escherichia coli and one Pseudomonas putida strains. Each gate shows seven different dynamic behaviours, depending on the context. That is, gates can be fine-tuned by changing only contextual parameters, thus improving the compatibility between gates. Finally, we analyse portability by measuring, scoring, and comparing gate performance across contexts. Rather than being a limitation, we argue that the effect of the genetic background on synthetic constructs expands functionality, and advocate for considering context as a fundamental design parameter.

Adaptive Evolution in Producing Microtiter Cultivations Generates Genetically Stable Escherichia coli Production Hosts for Continuous Bioprocessing

The production of recombinant proteins usually reduces cell fitness and the growth rate of producing cells. The growth disadvantage favors faster-growing non-producer mutants. Therefore, continuous bioprocessing is hardly feasible in Escherichia coli due to the high escape rate. The stability of E. coli expression systems under long-term production conditions and how metabolic load triggered by recombinant gene expression influences the characteristics of mutations are investigated. Iterated fed-batch-like microbioreactor cultivations are conducted under production conditions. The easy-to-produce green fluorescent protein (GFP) and a challenging antigen-binding fragment (Fab) are used as model proteins, and BL21(DE3) and BL21^Q strains as expression hosts. In comparative whole-genome sequencing analyses, mutations that allowed cells to grow unhindered despite recombinant protein production are identified. A T7 RNA polymerase expression system is only conditionally suitable for long-term cultivation under production conditions. Mutations leading to non-producers occur in either the T7 RNA polymerase gene or the T7 promoter. The host RNA polymerase-based BL21^Q expression system remains stable in the production of GFP in long-term cultivations. For the production of Fab, mutations in lacI of the BL21^Q derivatives have positive effects on long-term stability. The results indicate that adaptive evolution carried out with genome-integrated E. coli expression systems in microtiter cultivations under industrial-relevant production conditions is an efficient strain development tool for production hosts.

Plasmid Design for Tunable Two-Enzyme Co-Expression Promotes Whole-Cell Production of Cellobiose

Catalyst development for biochemical cascade reactions often follows a "whole-cell-approach" in which a single microbial cell is made to express all required enzyme activities. Although attractive in principle, the approach can encounter limitations when efficient overall flux necessitates precise balancing between activities. This study shows an effective integration of major design strategies from synthetic biology to a coherent development of plasmid vectors, enabling tunable two-enzyme co-expression in E. coli, for whole-cell-production of cellobiose. An efficient transformation of sucrose and glucose into cellobiose by a parallel (countercurrent) cascade of disaccharide phosphorylases requires the enzyme co-expression to cope with large differences in specific activity of cellobiose phosphorylase (14 U mg^-1 ) and sucrose phosphorylase (122 U mg^-1 ). Mono- and bicistronic co-expression strategies controlling transcription, transcription-translation coupling or plasmid replication are analyzed for effect on activity and stable producibility of the whole-cell-catalyst. A key role of bom (basis of mobility) for plasmid stability dependent on the ori is reported and the importance of RBS (ribosome binding site) strength is demonstrated. Whole cell catalysts show high specific rates (460 µmol cellobiose min^-1  g^-1 dry cells) and performance metrics (30 g L^-1 ; ∼82% yield; 3.8 g L^-1 h^-1 overall productivity) promising for cellobiose production.

From Microbial Communities to Distributed Computing Systems

A distributed biological system can be defined as a system whose components are located in different subpopulations, which communicate and coordinate their actions through interpopulation messages and interactions. We see that distributed systems are pervasive in nature, performing computation across all scales, from microbial communities to a flock of birds. We often observe that information processing within communities exhibits a complexity far greater than any single organism. Synthetic biology is an area of research which aims to design and build synthetic biological machines from biological parts to perform a defined function, in a manner similar to the engineering disciplines. However, the field has reached a bottleneck in the complexity of the genetic networks that we can implement using monocultures, facing constraints from metabolic burden and genetic interference. This makes building distributed biological systems an attractive prospect for synthetic biology that would alleviate these constraints and allow us to expand the applications of our systems into areas including complex biosensing and diagnostic tools, bioprocess control and the monitoring of industrial processes. In this review we will discuss the fundamental limitations we face when engineering functionality with a monoculture, and the key areas where distributed systems can provide an advantage. We cite evidence from natural systems that support arguments in favor of distributed systems to overcome the limitations of monocultures. Following this we conduct a comprehensive overview of the synthetic communities that have been built to date, and the components that have been used. The potential computational capabilities of communities are discussed, along with some of the applications that these will be useful for. We discuss some of the challenges with building co-cultures, including the problem of competitive exclusion and maintenance of desired community composition. Finally, we assess computational frameworks currently available to aide in the design of microbial communities and identify areas where we lack the necessary tools.

A quantitative method for proteome reallocation using minimal regulatory interventions

Engineering resource allocation in biological systems is an ongoing challenge. Organisms allocate resources for ensuring survival, reducing the productivity of synthetic biology functions. Here we present a new approach for engineering the resource allocation of Escherichia coli by rationally modifying its transcriptional regulatory network. Our method (ReProMin) identifies the minimal set of genetic interventions that maximizes the savings in cell resources. To this end, we categorized transcription factors according to the essentiality of its targets and we used proteomic data to rank them. We designed the combinatorial removal of transcription factors that maximize the release of resources. Our resulting strain containing only three mutations, theoretically releasing 0.5% of its proteome, had higher proteome budget, increased production of an engineered metabolic pathway and showed that the regulatory interventions are highly specific. This approach shows that combining proteomic and regulatory data is an effective way of optimizing strains using conventional molecular methods.

Key Challenges in Designing CHO Chassis Platforms

Following the success of and the high demand for recombinant protein-based therapeutics during the last 25 years, the pharmaceutical industry has invested significantly in the development of novel treatments based on biologics. Mammalian cells are the major production systems for these complex biopharmaceuticals, with Chinese hamster ovary (CHO) cell lines as the most important players. Over the years, various engineering strategies and modeling approaches have been used to improve microbial production platforms, such as bacteria and yeasts, as well as to create pre-optimized chassis host strains. However, the complexity of mammalian cells curtailed the optimization of these host cells by metabolic engineering. Most of the improvements of titer and productivity were achieved by media optimization and large-scale screening of producer clones. The advances made in recent years now open the door to again consider the potential application of systems biology approaches and metabolic engineering also to CHO. The availability of a reference genome sequence, genome-scale metabolic models and the growing number of various “omics” datasets can help overcome the complexity of CHO cells and support design strategies to boost their production performance. Modular design approaches applied to engineer industrially relevant cell lines have evolved to reduce the time and effort needed for the generation of new producer cells and to allow the achievement of desired product titers and quality. Nevertheless, important steps to enable the design of a chassis platform similar to those in use in the microbial world are still missing. In this review, we highlight the importance of mammalian cellular platforms for the production of biopharmaceuticals and compare them to microbial platforms, with an emphasis on describing novel approaches and discussing still open questions that need to be resolved to reach the objective of designing enhanced modular chassis CHO cell lines.

Experimental Challenges for Reduced Genomes: The Cell Model Escherichia coli

Genome reduction, as a top-down approach to obtain the minimal genetic information essential for a living organism, has been conducted with bacterial cells for decades. The most popular and well-studied cell models for genome reduction are Escherichia coli strains. As the previous literature intensively introduced the genetic construction and application of the genome-reduced Escherichia coli strains, the present review focuses the design principles and compares the reduced genome collections from the specific viewpoint of growth, which represents a fundamental property of living cells and is an important feature for their biotechnological application. For the extended simplification of the genomic sequences, the approach of experimental evolution and concern for medium optimization are newly proposed. The combination of the current techniques of genomic construction and the newly proposed methodologies could allow us to acquire growing Escherichia coli cells carrying the extensively reduced genome and to address the question of what the minimal genome essential for life is.

Engineering and modification of microbial chassis for systems and synthetic biology

Engineering and modifying synthetic microbial chassis is one of the best ways not only to unravel the fundamental principles of life but also to enhance applications in the health, medicine, agricultural, veterinary, and food industries. The two primary strategies for constructing a microbial chassis are the top-down approach (genome reduction) and the bottom-up approach (genome synthesis). Research programs on this topic have been funded in several countries. The 'Minimum genome factory' (MGF) project was launched in 2001 in Japan with the goal of constructing microorganisms with smaller genomes for industrial use. One of the best examples of the results of this project is E. coli MGF-01, which has a reduced-genome size and exhibits better growth and higher threonine production characteristics than the parental strain [1]. The 'cell factory' project was carried out from 1998 to 2002 in the Fifth Framework Program of the EU (European Union), which tried to comprehensively understand microorganisms used in the application field. One of the outstanding results of this project was the elucidation of proteins secreted by Bacillus subtilis, which was summarized as the 'secretome' [2]. The GTL (Genomes to Life) program began in 2002 in the United States. In this program, researchers aimed to create artificial cells both in silico and in vitro, such as the successful design and synthesis of a minimal bacterial genome by John Craig Venter's group [3]. This review provides an update on recent advances in engineering, modification and application of synthetic microbial chassis, with particular emphasis on the value of learning about chassis as a way to better understand life and improve applications.