Engineered promoters enable constant gene expression at any copy number in bacteria

The Quest for Stability during Times of Change

Experimental tools that are designed to perturb biological functions are often used to understand how cells change over time. However, in two recent papers, Segall-Shapiro et al. (2018; in Nature Biotechnology) and Rullan et al. (2018; in this issue of Molecular Cell) present tools engineered to keep cells the same. Both tools achieve perfect adaptation, that is, the ability to hold a value, in this case gene expression, constant over time despite disruptions and disturbances. Together, these papers highlight how influential dynamics can be when shaping biological functions, even when the goal is to stay constant.

CopySwitch-in vivo Optimization of Gene Copy Numbers for Heterologous Gene Expression in Bacillus subtilis

The Gram-positive bacterium Bacillus subtilis has long been used as a host for production and secretion of industrially relevant enzymes like amylases and proteases. It is imperative for optimal efficiency, to balance protein yield and correct folding. While there are numerous ways of doing so on protein or mRNA level, our approach aims for the underlying number of coding sequences. Gene copy numbers are an important tuning valve for the optimization of heterologous gene expression. While some genes are best expressed from many gene copies, for other genes, medium or even single copy numbers are the only way to avoid formation of inclusion bodies, toxic gene dosage effects or achieve desired levels for metabolic engineering. In order to provide a simple and robust method to address above-mentioned issues in the Gram-positive bacterium Bacillus subtilis, we have developed an automatable system for the tuning of heterologous gene expression based on the host's intrinsic natural competence and homologous recombination capabilities. Strains are transformed with a linearized, low copy number plasmid containing an antibiotic resistance marker and homology regions up- and downstream of the gene of interest. Said gene is copied onto the vector, rendering it circular and replicative and thus selectable. We could show an up to 3.6-fold higher gfp (green fluorescent protein) expression and up to 1.3-fold higher mPLC (mature phospholipase C) expression after successful transformation. Furthermore, the plasmid-borne gfp expression seems to be more stable, since over the whole cultivation period the share of fluorescent cells compared to all measured cells is consistently higher. A major benefit of this method is the ability to work with very large regions of interest, since all relevant steps are carried out in vivo and are thus far less prone to mechanical DNA damage.

Prediction and characterization of promoters and ribosomal binding sites of Zymomonas mobilis in system biology era

BACKGROUND

Zymomonas mobilis is a model bacterial ethanologen with many systems biology studies reported. Besides lignocellulosic ethanol production, Z. mobilis has been developed as a platform for biochemical production through metabolic engineering. However, identification and rigorous understanding of the genetic origins of cellular function, especially those based in non-coding region of DNA, such as promoters and ribosomal binding sites (RBSs), are still in its infancy. This knowledge is crucial for the effective application of Z. mobilis to new industrial applications of biotechnology for fuels and chemicals production.

RESULTS

In this study, we explored the possibility to systematically predict the strength of promoters based on systems biology datasets. The promoter strength was clustered based on the expression values of downstream genes (or proteins) from systems biology studies including microarray, RNA-Seq and proteomics. Candidate promoters with different strengths were selected for further characterization, which include 19 strong, nine medium, and ten weak ones. A dual reporter-gene system was developed which included appropriate reporter genes. These are the opmCherry reporter gene driven by the constitutive PlacUV5 promoter for calibration, and EGFP reporter gene driven by candidate promoters for quantification. This dual reporter-gene system was confirmed using the inducible promoter, Ptet, which was used to determine the strength of these predicted promoters with different strengths. In addition, the dual reporter-gene system was applied to determine four synthetic RBSs with different translation initiation rates based on the prediction from bioinformatics server RBS calculator. Our results showed that the correlations between the prediction and experimental results for the promoter and RBS strength are relatively high, with R ² values more than 0.7 and 0.9, respectively.

CONCLUSIONS

This study not only identified and characterized 38 promoters and four RBSs with different strengths for future metabolic engineering in Z. mobilis, but also established a flow cytometry-based dual reporter-gene system to characterize genetic elements including, but not limited to the promoters and RBSs studied in this work. This study also suggested the feasibility of predicting and selecting candidate genetic elements based on omics datasets and bioinformatics tools. Moreover, the dual reporter-gene system developed in this study can be utilized to characterize other genetic elements of Z. mobilis, which can also be applied to other microorganisms.

Chasing bacterial chassis for metabolic engineering: a perspective review from classical to non-traditional microorganisms

The last few years have witnessed an unprecedented increase in the number of novel bacterial species that hold potential to be used for metabolic engineering. Historically, however, only a handful of bacteria have attained the acceptance and widespread use that are needed to fulfil the needs of industrial bioproduction - and only for the synthesis of very few, structurally simple compounds. One of the reasons for this unfortunate circumstance has been the dearth of tools for targeted genome engineering of bacterial chassis, and, nowadays, synthetic biology is significantly helping to bridge such knowledge gap. Against this background, in this review, we discuss the state of the art in the rational design and construction of robust bacterial chassis for metabolic engineering, presenting key examples of bacterial species that have secured a place in industrial bioproduction. The emergence of novel bacterial chassis is also considered at the light of the unique properties of their physiology and metabolism, and the practical applications in which they are expected to outperform other microbial platforms. Emerging opportunities, essential strategies to enable successful development of industrial phenotypes, and major challenges in the field of bacterial chassis development are also discussed, outlining the solutions that contemporary synthetic biology-guided metabolic engineering offers to tackle these issues.

A quasi-integral controller for adaptation of genetic modules to variable ribosome demand

The behavior of genetic circuits is often poorly predictable. A gene’s expression level is not only determined by the intended regulators, but also affected by changes in ribosome availability imparted by expression of other genes. Here we design a quasi-integral biomolecular feedback controller that enables the expression level of any gene of interest (GOI) to adapt to changes in available ribosomes. The feedback is implemented through a synthetic small RNA (sRNA) that silences the GOI’s mRNA, and uses orthogonal extracytoplasmic function (ECF) sigma factor to sense the GOI’s translation and to actuate sRNA transcription. Without the controller, the expression level of the GOI is reduced by 50% when a resource competitor is activated. With the controller, by contrast, gene expression level is practically unaffected by the competitor. This feedback controller allows adaptation of genetic modules to variable ribosome demand and thus aids modular construction of complicated circuits.

Competition for shared cellular resources often renders genetic circuits poorly predictable. Here the authors design a biomolecular quasi-integral controller that allows gene expression to adapt to variable demand in translation resources.

Scaling up genetic circuit design for cellular computing: advances and prospects

Synthetic biology aims to engineer and redesign biological systems for useful real-world applications in biomanufacturing, biosensing and biotherapy following a typical design-build-test cycle. Inspired from computer science and electronics, synthetic gene circuits have been designed to exhibit control over the flow of information in biological systems. Two types are Boolean logic inspired TRUE or FALSE digital logic and graded analog computation. Key principles for gene circuit engineering include modularity, orthogonality, predictability and reliability. Initial circuits in the field were small and hampered by a lack of modular and orthogonal components, however in recent years the library of available parts has increased vastly. New tools for high throughput DNA assembly and characterization have been developed enabling rapid prototyping, systematic in situ characterization, as well as automated design and assembly of circuits. Recently implemented computing paradigms in circuit memory and distributed computing using cell consortia will also be discussed. Finally, we will examine existing challenges in building predictable large-scale circuits including modularity, context dependency and metabolic burden as well as tools and methods used to resolve them. These new trends and techniques have the potential to accelerate design of larger gene circuits and result in an increase in our basic understanding of circuit and host behaviour.

Controlling and exploiting cell-to-cell variation in metabolic engineering

Individual cells within a population can display diverse phenotypes due to differences in their local environment, genetic variation, and stochastic expression of genes. Understanding this cell-to-cell variation is important for metabolic engineering applications because variability can impact production. For instance, recent studies have shown that production can be highly heterogeneous among engineered cells, and strategies that manage this diversity improve yields of biosynthetic products. These results suggest the potential of controlling variation as a novel approach towards improving performance of engineered cells. In this review, we focus on identifying the origins of cell-to-cell variation in metabolic engineering applications and discuss recent developments on strategies that can be employed to diminish, accept, or even exploit cell-to-cell variation.

High-resolution studies of lysis-lysogeny decision-making in bacteriophage lambda

Cellular decision-making guides complex development such as cell differentiation and disease progression. Much of our knowledge about decision-making is derived from simple models, such as bacteriophage lambda infection, in which lambda chooses between the vegetative lytic fate and the dormant lysogenic fate. This paradigmatic system is broadly understood but lacking mechanistic details, partly due to limited resolution of past studies. Here, we discuss how modern technologies have enabled high-resolution examination of lambda decision-making to provide new insights and exciting possibilities in studying this classical system. The advent of techniques for labeling specific DNA, RNA, and proteins in cells allows for molecular-level characterization of events in lambda development. These capabilities yield both new answers and new questions regarding how the isolated lambda genetic circuit acts, what biological events transpire among phages in their natural context, and how the synergy of simple phage macromolecules brings about complex behaviors.

Coupling of DNA Replication and Negative Feedback Controls Gene Expression for Cell-Fate Decisions

Cellular decision-making arises from the expression of genes along a regulatory cascade, which leads to a choice between distinct phenotypic states. DNA dosage variations, often introduced by replication, can significantly affect gene expression to ultimately bias decision outcomes. The bacteriophage lambda system has long served as a paradigm for cell-fate determination, yet the effect of DNA replication remains largely unknown. Here, through single-cell studies and mathematical modeling we show that DNA replication drastically boosts cI expression to allow lysogenic commitment by providing more templates. Conversely, expression of CII, the upstream regulator of cI, is surprisingly robust to DNA replication due to the negative autoregulation of the Cro repressor. Our study exemplifies how living organisms can not only utilize DNA replication for gene expression control but also implement mechanisms such as negative feedback to allow the expression of certain genes to be robust to dosage changes resulting from DNA replication.