Development of Design Rules for Reliable Antisense RNA Behavior in E. coli

A portable regulatory RNA array design enables tunable and complex regulation across diverse bacteria

A lack of composable and tunable gene regulators has hindered efforts to engineer non-model bacteria and consortia. Toward addressing this, we explore the broad-host potential of small transcription activating RNA (STAR) and propose a design strategy to achieve tunable gene control. First, we demonstrate that STARs optimized for E. coli function across different Gram-negative species and can actuate using phage RNA polymerase, suggesting that RNA systems acting at the level of transcription are portable. Second, we explore an RNA design strategy that uses arrays of tandem and transcriptionally fused RNA regulators to precisely alter regulator concentration from 1 to 8 copies. This provides a simple means to predictably tune output gain across species and does not require access to large regulatory part libraries. Finally, we show RNA arrays can be used to achieve tunable cascading and multiplexing circuits across species, analogous to the motifs used in artificial neural networks.

A portable regulatory RNA array design enables tunable and complex regulation across diverse bacteria

A lack of composable and tunable gene regulators has hindered efforts to engineer non-model bacteria and consortia. To address this, we explore the broad-host potential of small transcription activating RNA (STAR) and propose a novel design strategy to achieve tunable gene control. First, we demonstrate that STARs optimized for E. coli function across different Gram-negative species and can actuate using phage RNA polymerase, suggesting that RNA systems acting at the level of transcription are portable. Second, we explore a novel RNA design strategy that uses arrays of tandem and transcriptionally fused RNA regulators to precisely alter regulator concentration from 1 to 8 copies. This provides a simple means to predictably tune output gain across species and does not require access to large regulatory part libraries. Finally, we show RNA arrays can be used to achieve tunable cascading and multiplexing circuits across species, analogous to the motifs used in artificial neural networks.

Engineering and adaptive laboratory evolution of Escherichia coli for improving methanol utilization based on a hybrid methanol assimilation pathway

Engineering Escherichia coli for efficient methanol assimilation is important for developing methanol as an emerging next-generation feedstock for industrial biotechnology. While recent attempts to engineer E. coli as a synthetic methylotroph have achieved great success, most of these works are based on the engineering of the prokaryotic ribulose monophosphate (RuMP) pathway. In this study, we introduced a hybrid methanol assimilation pathway which consists of prokaryotic methanol dehydrogenase (Mdh) and eukaryotic xylulose monophosphate (XuMP) pathway enzyme dihydroxyacetone synthase (Das) into E. coli and reprogrammed E. coli metabolism to improve methanol assimilation by combining rational design and adaptive laboratory evolution. By deletion and down-regulation of key genes in the TCA cycle and glycolysis to increase the flux toward the cyclic XuMP pathway, methanol consumption and the assimilation of methanol to biomass were significantly improved. Further improvements in methanol utilization and cell growth were achieved via adaptive laboratory evolution and a final evolved strain can grow on methanol with only 0.1 g/L yeast extract as co-substrate. ¹³C-methanol labeling assay demonstrated significantly higher labeling in intracellular metabolites in glycolysis, TCA cycle, pentose phosphate pathway, and amino acids. Transcriptomics analysis showed that the expression of fba, dhak, and part of pentose phosphate pathway genes were highly up-regulated, suggesting that the rational engineering strategies and adaptive evolution are effective for activating the cyclic XuMP pathway. This study demonstrated the feasibility and provided new strategies to construct synthetic methylotrophy of E. coli based on the hybrid methanol assimilation pathway with Mdh and Das.

Faecal carriage of ESBL producing and colistin resistant Escherichia coli in avian species over a 2-year period (2017-2019) in Zimbabwe

Introduction

Extended spectrum beta-lactamase (ESBL) producing Escherichia coli have become widespread among food producing animals. These strains serve as a reservoir of antibiotic resistance genes (ARGs) and act as a possible source of infection to humans as transmission can occur by direct or indirect contact.

Methods

This study investigated the faecal carriage of ESBL producing and colistin resistant E. coli in poultry over a 2-year period (2017-2019) from Zimbabwe. A total of 21 ESBL positive isolates from poultry cloacal specimens were selected for whole genome sequencing from animal E. coli isolates bio-banked at the National Microbiology Reference laboratory using phenotypic susceptibility testing results from the National Escherichia coli Surveillance Program to provide representation of different geographical regions and year of isolation. Cloacal swabs were collected from 3000 broiler live birds from farm 1 and from farm 2, 40 backyard chickens and 10 ducks were sampled. Antimicrobial susceptibility and ESBL testing were performed as per Clinical Laboratory Standards Institute guidelines. Whole genome sequencing of ESBL producing isolates was used to determine sequence types (STs), ARGs, and phylogroups.

Results

Twenty-one of the included E. coli isolates were confirmed as ESBL producers. Three defined sequence type clonal complexes (CCs) were identified (ST10CC, ST155CC and ST23CC), with ST10CC associated with the most antibiotic resistant profile. The ESBL phenotype was linked to the presence of either cefotaximase-Munich-14 (CTX-M-14) or CTX-M-79. Plasmid mediated quinolone resistant determinants identified were qnrB19 and qnrS1 and one ST10CC isolate from farm 1 broiler chickens harbored a mobile colistin resistance gene (mcr-1). Phylogenetic groups most identified were B1, A and unknown.

Discussions

The avian ESBL producing E. coli belonged to a diverse group of strains. The detection of several ARGs highlights the importance of implementing enhanced control measures to limit the spread in animals, environment, and humans. This is the first report of mcr-1 in Zimbabwe, which further underscores the importance of the One Health approach to control the spread and development of AMR.

High-throughput design of bacterial anti-sense RNAs using CAREng

Summary

Short RNA (sRNA) modulation of gene expression is an increasingly popular tool for bacterial functional genomics. Antisense pairing between an sRNA and a target messenger RNA results in post-transcriptional down-regulation of a specific gene and can thus be used both for investigating individual gene function and for large-scale genetic screens. sRNAs have several advantages over knockout libraries in studies of gene function, including inducibility, the capacity to interrogate essential genes and easy portability to multiple genetic backgrounds. High-throughput, systematic design of antisense RNAs will increase the efficiency and repeatability of sRNA screens. To this end, we present CAREng, the Computer-Automated sRNA Engineer. CAREng designs antisense RNAs for all coding sequences in a given genome, while checking for potential off-targets.

Availability and implementation

CAREng is available as a Python script and through a web portal (https://caren.carleton.ca).

Supplementary information

Supplementary data are available at Bioinformatics Advances online.

Overcoming Leak Sensitivity in CRISPRi Circuits Using Antisense RNA Sequestration and Regulatory Feedback

The controlled binding of the catalytically dead CRISPR nuclease (dCas) to DNA can be used to create complex, programmable transcriptional genetic circuits, a fundamental goal of synthetic biology. This approach, called CRISPR interference (CRISPRi), is advantageous over existing methods because the programmable nature of CRISPR proteins in principle enables the simultaneous regulation of many different targets without crosstalk. However, the performance of dCas-based genetic circuits is limited by both the sensitivity to leaky repression within CRISPRi logic gates and retroactive effects due to a shared pool of dCas proteins. By utilizing antisense RNAs (asRNAs) to sequester gRNA transcripts as well as CRISPRi feedback to self-regulate asRNA production, we demonstrate a mechanism that suppresses unwanted repression by CRISPRi and improves logical gene circuit function in Escherichia coli. This improvement is particularly pronounced during stationary expression when CRISPRi circuits do not achieve the expected regulatory dynamics. Furthermore, the use of dual CRISPRi/asRNA inverters restores the logical performance of layered circuits such as a double inverter. By studying circuit induction at the single-cell level in microfluidic channels, we provide insight into the dynamics of antisense sequestration of gRNA and regulatory feedback on dCas-based repression and derepression. These results demonstrate how CRISPRi inverters can be improved for use in more complex genetic circuitry without sacrificing the programmability and orthogonality of dCas proteins.

An Easy-to-Use Plasmid Toolset for Efficient Generation and Benchmarking of Synthetic Small RNAs in Bacteria

Synthetic biology approaches life from the perspective of an engineer. Standardized and de novo design of genetic parts to subsequently build reproducible and controllable modules, for example, for circuit design, is a key element. To achieve this, natural systems and elements often serve as a blueprint for researchers. Regulation of protein abundance is controlled at DNA, mRNA, and protein levels. Many tools for the activation or repression of transcription or the destabilization of proteins are available, but easy-to-handle minimal regulatory elements on the mRNA level are preferable when translation needs to be modulated. Regulatory RNAs contribute considerably to regulatory networks in all domains of life. In particular, bacteria use small regulatory RNAs (sRNAs) to regulate mRNA translation. Slowly, sRNAs are attracting the interest of using them for broad applications in synthetic biology. Here, we promote a "plug and play" plasmid toolset to quickly and efficiently create synthetic sRNAs to study sRNA biology or their application in bacteria. We propose a simple benchmarking assay by targeting the acrA gene of Escherichia coli and rendering cells sensitive toward the β-lactam antibiotic oxacillin. We further highlight that it may be necessary to test multiple seed regions and sRNA scaffolds to achieve the desired regulatory effect. The described plasmid toolset allows quick construction and testing of various synthetic sRNAs based on the user's needs.

Model-Based Design of Synthetic Antisense RNA for Predictable Gene Repression

Our enhanced understanding of RNA folding and function has increased the use of small RNA regulators. Among these RNA regulators, synthetic antisense RNA (asRNA) is designed to contain an RNA sequence complementary to the target mRNA sequence, and the formation of double-stranded RNA (dsRNA) facilitates gene repression due to dsRNA degradation or prevention of ribosome access to the mRNA. Despite the simple complementarity rule, however, predictably tunable repression has been challenging when synthetic asRNAs are used. Here, the protocol for model-based asRNA design is described. This model can predict synthetic asRNA-mediated repression efficiency using two parameters: the change in free energy of complex formation (ΔG_CF) and percent mismatch of the target binding region (TBR). The model has been experimentally validated in both Gram-positive and Gram-negative bacteria as well as for target genes in both plasmids and chromosomes. These asRNAs can be created by simply replacing the TBR sequence with one that is complementary to the target mRNA sequence of interest. In principle, this protocol can be applied to design and build asRNAs for predictable gene repression in various contexts, including multiple target genes and organisms, making asRNAs predictably tunable regulators for broad applications.

A modular RNA interference system for multiplexed gene regulation

The rational design and realisation of simple-to-use genetic control elements that are modular, orthogonal and robust is essential to the construction of predictable and reliable biological systems of increasing complexity. To this effect, we introduce modular Artificial RNA interference (mARi), a rational, modular and extensible design framework that enables robust, portable and multiplexed post-transcriptional regulation of gene expression in Escherichia coli. The regulatory function of mARi was characterised in a range of relevant genetic contexts, demonstrating its independence from other genetic control elements and the gene of interest, and providing new insight into the design rules of RNA based regulation in E. coli, while a range of cellular contexts also demonstrated it to be independent of growth-phase and strain type. Importantly, the extensibility and orthogonality of mARi enables the simultaneous post-transcriptional regulation of multi-gene systems as both single-gene cassettes and poly-cistronic operons. To facilitate adoption, mARi was designed to be directly integrated into the modular BASIC DNA assembly framework. We anticipate that mARi-based genetic control within an extensible DNA assembly framework will facilitate metabolic engineering, layered genetic control, and advanced genetic circuit applications.

RNA Structure Prediction, Analysis, and Design: An Introduction to Web-Based Tools

Understanding RNA structure has become critical in the study of RNA in their roles as mediators of biological processes. To aid in these studies, computational algorithms that utilize thermodynamics have been developed to predict RNA secondary structure. Due to the importance of intermolecular interactions, the algorithms have been expanded to determine and predict RNA-RNA hybridization. This chapter discusses popular webservers with the tools for RNA secondary structure prediction, RNA-RNA hybridization, and design. We address key features that distinguish common-functioning programs and their purposes for the interests of the user. Ultimately, we hope this review elucidates web-based tools researchers may take advantage of in their investigations of RNA structure and function.

Molecular epidemiology of extended-spectrum beta-lactamase-producing extra-intestinal pathogenic Escherichia coli strains over a 2-year period (2017-2019) from Zimbabwe

This study was designed to characterize extended-spectrum beta-lactamase (ESBL)-producing extra-intestinal pathogenic Escherichia coli (E.coli) (ExPEC) associated with urinary tract infections in nine different geographic regions of Zimbabwe over a 2-year period (2017-2019). A total of 48 ESBL-positive isolates from urine specimen were selected for whole-genome sequencing from 1246 Escherichia coli isolates biobanked at the National Microbiology Reference laboratory using phenotypic susceptibility testing results from the National Escherichia coli Surveillance Programme to provide representation of different geographical regions and year of isolation. The majority of ESBL E. coli isolates produced cefotaximase-Munich (CTX-M)-15, CTX-M-27, and CTX-M-14. In this study, sequence types (ST) 131 and ST410 were the most predominant antimicrobial-resistant clones and responsible for the increase in ESBL-producing E. coli strains since 2017. Novel ST131 complex strains were recorded during the period 2017 to 2018, thus showing the establishment and evolution of this antimicrobial-resistant ESBL clone in Zimbabwe posing an important public health threat. Incompatibility group F plasmids were predominant among ST131 and ST410 isolates with the following replicons recorded most frequently: F1:A2:B20 (9/19, 47%), F2:A1: B (5/19, 26%), and F1:A1:B49 (8/13, 62%). The results indicate the need for continuous tracking of different ESBL ExPEC clones on a global scale, while targeting specific STs (e.g. ST131 and ST410) through control programs will substantially decrease the spread of ESBLs among ExPEC.

Targeting riboswitches with synthetic small RNAs for metabolic engineering

Our growing knowledge of the diversity of non-coding RNAs in natural systems and our deepening knowledge of RNA folding and function have fomented the rational design of RNA regulators. Based on that knowledge, we designed and implemented a small RNA tool to target bacterial riboswitches and activate gene expression (rtRNA). The synthetic rtRNA is suitable for regulation of gene expression both in cell-free and in cellular systems. It targets riboswitches to promote the antitermination folding regardless the cognate metabolite concentration. Therefore, it prevents transcription termination increasing gene expression up to 103-fold. We successfully used small RNA arrays for multiplex targeting of riboswitches. Finally, we used the synthetic rtRNAs to engineer an improved riboflavin producer strain. The easiness to design and construct, and the fact that the rtRNA works as a single genome copy, make it an attractive tool for engineering industrial metabolite-producing strains.

Recent advances in engineering of microbial cell factories for intelligent pH regulation and tolerance

pH regulation is a serious concern in the industrial fermentation process as pH adjustment heavily utilizes acid/base and pollutes the environment. Under pH-stress conditions, microbial growth and production of valuable target products may be severely affected. Furthermore, some strains generating acidic or alkaline products require self pH regulation and increased tolerance against pH-stress. For pH control, synthetic biology has provided advanced engineering approaches to construct robust and more intelligent microbial strains, exhibiting tolerance to pH-stress to cope with limitations of pH regulation. This study reviewed the current progress of advanced strain evolution strategies to engineer pH-stress tolerant strains via synthetic biology. In addition, a large number of pH-responsive elements, including promoters, riboswitches, and some proteins have been investigated and applied for construction of pH-responsive genetic circuits and intelligent pH-responsive microbial strains.

Development of antisense RNA-mediated quantifiable inhibition for metabolic regulation

Trans-regulating elements such as noncoding RNAs are crucial in modifying cells, and has shown broad application in synthetic biology, metabolic engineering and RNA therapies. Although effective, titration of the regulatory levels of such elements is less explored. Encouraged by the need of fine-tuning cellular functions, we studied key parameters of the antisense RNA design including oligonucleotide length, targeting region and relative dosage to achieve differentiated inhibition. We determined a 30-nucleotide configuration that renders efficient and robust inhibition. We found that by targeting the core RBS region proportionally, quantifiable inhibition levels can be rationally obtained. A mathematic model was established accordingly with refined energy terms and successfully validated by depicting the inhibition levels for genomic targets. Additionally, we applied this fine-tuning approach for 4-hydroxycoumarin biosynthesis by simultaneous and quantifiable knockdown of multiple targets, resulting in a 3.58-fold increase in titer of the engineered strain comparing to that of the non-regulated. We believe the developed tool is broadly compatible and provides an extra layer of control in modifying living systems.

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Achieved quantifiable asRNA inhibition by varying core RBS coverage.

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Developed and validated a mathematical model for quantifiable inhibition.

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Improved 4-hydroxycoumarin biosynthesis by 3.58 folds with multiplexed inhibition.

Modulation of Bacterial Fitness and Virulence Through Antisense RNAs

Regulatory RNAs contribute to gene expression control in bacteria. Antisense RNAs (asRNA) are a class of regulatory RNAs that are transcribed from opposite strands of their target genes. Typically, these untranslated transcripts bind to cognate mRNAs and rapidly regulate gene expression at the post-transcriptional level. In this article, we review asRNAs that modulate bacterial fitness and increase virulence. We chose examples that underscore the variety observed in nature including, plasmid- and chromosome-encoded asRNAs, a riboswitch-regulated asRNA, and asRNAs that require other RNAs or RNA-binding proteins for stability and activity. We explore how asRNAs improve bacterial fitness and virulence by modulating plasmid acquisition and maintenance, regulating transposon mobility, increasing resistance against bacteriophages, controlling flagellar production, and regulating nutrient acquisition. We conclude with a brief discussion on how this knowledge is helping to inform current efforts to develop new therapeutics.

An Effective Method for Specific Gene Silencing in Escherichia coli Using Artificial Small RNA

Knockdown or silencing of a specific gene presents a powerful strategy for elucidating gene function in a variety of organisms. To date, efficient silencing methods have been established in eukaryotes, but not bacteria. In this chapter, an efficient and versatile gene silencing method using artificial small RNA (afsRNA) is described. For this purpose, target-recognizing sequences were introduced in specially designed RNA scaffolds to exist as single-stranded stretches in afsRNA. The translation initiation region of target genes was used as the sequence for afsRNA recognition, based on the theory that this site is usually highly accessible to ribosomes, and therefore, possibly, afsRNA. Two genes transcribed as monocistrons were tested with our protocol. Both genes were effectively silenced by their cognate afsRNAs.

Gene silencing with CRISPRi in bacteria and optimization of dCas9 expression levels

The catalytic null mutant of the Cas9 endonuclease from the bacterial CRISPR immune system, known as dCas9, can be guided by a small RNA to bind DNA sequences of interest and block gene transcription in a strategy known as CRISPRi. This powerful gene silencing method has already been used in a large number of species and in high throughput screens. Here we provide detailed design rules, methods and novel vectors to perform CRISPRi experiments in S. aureus and in E. coli, using the well characterized dCas9 protein from S. pyogenes. In particular, we describe a vector based on plasmid pC194 which is broadly used in Firmicutes, as well as a vector based on the very broad host-range rolling circle plasmid pLZ12, reported to replicate in both Firmicutes and Proteobacteria. A potential caveat of adapting dCas9 tools to various bacterial species is that dCas9 was shown to be toxic when expressed too strongly. We describe a method to optimize the expression level of dCas9 in order to avoid toxicity while ensuring strong on-target repression activity. We demonstrate this method by optimizing a pLZ12 based vector originally developed for S. aureus so that it can work in E. coli. This article should provide all the resources required to perform CRISPRi experiments in a broad range of bacterial species.

Recent advances in genetic engineering tools based on synthetic biology

Genome-scale engineering is a crucial methodology to rationally regulate microbiological system operations, leading to expected biological behaviors or enhanced bioproduct yields. Over the past decade, innovative genome modification technologies have been developed for effectively regulating and manipulating genes at the genome level. Here, we discuss the current genome-scale engineering technologies used for microbial engineering. Recently developed strategies, such as clustered regularly interspaced short palindromic repeats (CRISPR)-Cas9, multiplex automated genome engineering (MAGE), promoter engineering, CRISPR-based regulations, and synthetic small regulatory RNA (sRNA)-based knockdown, are considered as powerful tools for genome-scale engineering in microbiological systems. MAGE, which modifies specific nucleotides of the genome sequence, is utilized as a genome-editing tool. Contrastingly, synthetic sRNA, CRISPRi, and CRISPRa are mainly used to regulate gene expression without modifying the genome sequence. This review introduces the recent genome-scale editing and regulating technologies and their applications in metabolic engineering.

Modulating Responses of Toehold Switches by an Inhibitory Hairpin

The toehold switch consists of a cis-repressing switch RNA hairpin and a trans-acting trigger RNA. The binding of the trigger RNA to an unpaired toehold sequence of the switch hairpin allows for a branch migration process, exposing the start codon and ribosome binding site for translation initiation. In this work, we demonstrate that responses of toehold switches can be modulated by introducing an inhibitory hairpin that shortens the length of the unpaired toehold region. First, we investigated the effect of the toehold region length on output gene expression and showed that the second trigger RNA, which binds to the inhibitory hairpin, is necessary for output gene activation when the hairpin-to-hairpin spacing is short. Second, the apparent Hill coefficient was found generally to increase with decreasing hairpin-to-hairpin spacing or increasing hairpin number. This work expands the utility of toehold switches by providing a new way to modulate their response.

Establishing a Multivariate Model for Predictable Antisense RNA-Mediated Repression

Recent advances in our understanding of RNA folding and functions have facilitated the use of regulatory RNAs such as synthetic antisense RNAs (asRNAs) to modulate gene expression. However, despite the simple and universal complementarity rule, predictable asRNA-mediated repression is still challenging due to the intrinsic complexity of native asRNA-mediated gene regulation. To address this issue, we present a multivariate model, based on the change in free energy of complex formation (Δ G_CF) and percent mismatch of the target binding region, which can predict synthetic asRNA-mediated repression efficiency in diverse contexts. First, 69 asRNAs that bind to multiple target mRNAs were designed and tested to create the predictive model. Second, we showed that the same model is effective predicting repression of target genes in both plasmids and chromosomes. Third, using our model, we designed asRNAs that simultaneously modulated expression of a toxin and its antitoxin to demonstrate tunable control of cell growth. Fourth, we tested and validated the same model in two different biotechnologically important organisms: Escherichia coli Nissle 1917 and Bacillus subtilis 168. Last, multiple parameters, including target locations, the presence of an Hfq binding site, GC contents, and gene expression levels, were revisited to define the conditions under which the multivariate model should be used for accurate prediction. Together, 434 different strain-asRNA combinations were tested, validating the predictive model in a variety of contexts, including multiple target genes and organisms. The result presented in this study is an important step toward achieving predictable tunability of asRNA-mediated repression.

Synthetic Biology of Small RNAs and Riboswitches

In bacteria and archaea, small RNAs (sRNAs) regulate complex networks through antisense interactions with target mRNAs in trans, and riboswitches regulate gene expression in cis based on the ability to bind small-molecule ligands. Although our understanding and characterization of these two important regulatory RNA classes is far from complete, these RNA-based mechanisms have proven useful for a wide variety of synthetic biology applications. Besides classic and contemporary applications in the realm of metabolic engineering and orthogonal gene control, this review also covers newer applications of regulatory RNAs as biosensors, logic gates, and tools to determine RNA-RNA interactions. A separate section focuses on critical insights gained and challenges posed by fundamental studies of sRNAs and riboswitches that should aid future development of synthetic regulatory RNAs.

Regulatory non-coding sRNAs in bacterial metabolic pathway engineering

Non-coding RNAs (ncRNAs) are versatile and powerful controllers of gene expression that have been increasingly linked to cellular metabolism and phenotype. In bacteria, identified and characterized ncRNAs range from trans-acting, multi-target small non-coding RNAs to dynamic, cis-encoded regulatory untranslated regions and riboswitches. These native regulators have inspired the design and construction of many synthetic RNA devices. In this work, we review the design, characterization, and impact of ncRNAs in engineering both native and exogenous metabolic pathways in bacteria. We also consider the opportunities afforded by recent high-throughput approaches for characterizing sRNA regulators and their corresponding networks to showcase their potential applications and impact in engineering bacterial metabolism.

CRISPR-Cas9/Cas12a biotechnology and application in bacteria

CRISPR-Cas technologies have greatly reshaped the biology field. In this review, we discuss the CRISPR-Cas with a particular focus on the associated technologies and applications of CRISPR-Cas9 and CRISPR-Cas12a, which have been most widely studied and used. We discuss the biological mechanisms of CRISPR-Cas as immune defense systems, recently-discovered anti-CRISPR-Cas systems, and the emerging Cas variants (such as xCas9 and Cas13) with unique characteristics. Then, we highlight various CRISPR-Cas biotechnologies, including nuclease-dependent genome editing, CRISPR gene regulation (including CRISPR interference/activation), DNA/RNA base editing, and nucleic acid detection. Last, we summarize up-to-date applications of the biotechnologies for synthetic biology and metabolic engineering in various bacterial species.

Exploring of the feature space of de novo developed post-transcriptional riboregulators

Metabolic engineering increasingly depends upon RNA technology to customly rewire the metabolism to maximize production. To this end, pure riboregulators allow dynamic gene repression without the need of a potentially burdensome coexpressed protein like typical Hfq binding small RNAs and clustered regularly interspaced short palindromic repeats technology. Despite this clear advantage, no clear general design principles are available to de novo develop repressing riboregulators, limiting the availability and the reliable development of these type of riboregulators. Here, to overcome this lack of knowledge on the functionality of repressing riboregulators, translation inhibiting RNAs are developed from scratch. These de novo developed riboregulators explore features related to thermodynamical and structural factors previously attributed to translation initiation modulation. In total, 12 structural and thermodynamic features were defined of which six features were retained after removing correlations from an in silico generated riboregulator library. From this translation inhibiting RNA library, 18 riboregulators were selected using a experimental design and subsequently constructed and co-expressed with two target untranslated regions to link the translation inhibiting RNA features to functionality. The pure riboregulators in the design of experiments showed repression down to 6% of the original protein expression levels, which could only be partially explained by a ordinary least squares regression model. To allow reliable forward engineering, a partial least squares regression model was constructed and validated to link the properties of translation inhibiting RNA riboregulators to gene repression. In this model both structural and thermodynamic features were important for efficient gene repression by pure riboregulators. This approach enables a more reliable de novo forward engineering of effective pure riboregulators, which further expands the RNA toolbox for gene expression modulation.

To allow reliable forward engineering of microbial cell factories, various metabolic engineering efforts rely on RNA-based technology. As such, programmable riboregulators allow dynamic control over gene expression. However, no clear design principles exist for de novo developed repressing riboregulators, which limits their applicability. Here, various engineering principles are identified and computationally explored. Subsequently, various design criteria are used in an experimental design, which were explored in an in vivo study. This resulted in a regression model that enables a more reliable computational design of repression small RNAs.

Dynamics of Bacterial Gene Regulatory Networks

The ability of bacterial cells to adjust their gene expression program in response to environmental perturbation is often critical for their survival. Recent experimental advances allowing us to quantitatively record gene expression dynamics in single cells and in populations coupled with mathematical modeling enable mechanistic understanding on how these responses are shaped by the underlying regulatory networks. Here, we review how the combination of local and global factors affect dynamical responses of gene regulatory networks. Our goal is to discuss the general principles that allow extrapolation from a few model bacteria to less understood microbes. We emphasize that, in addition to well-studied effects of network architecture, network dynamics are shaped by global pleiotropic effects and cell physiology.

Multilevel Regulation of Bacterial Gene Expression with the Combined STAR and Antisense RNA System

Synthetic small RNA regulators have emerged as a versatile tool to predictably control bacterial gene expression. Owing to their simple design principles, small size, and highly orthogonal behavior, these engineered genetic parts have been incorporated into genetic circuits. However, efforts to achieve more sophisticated cellular functions using RNA regulators have been hindered by our limited ability to integrate different RNA regulators into complex circuits. Here, we present a combined RNA regulatory system in Escherichia coli that uses small transcription activating RNA (STAR) and antisense RNA (asRNA) to activate or deactivate target gene expression in a programmable manner. Specifically, we demonstrated that the activated target output by the STAR system can be deactivated by expressing two different types of asRNAs: one binds to and sequesters the STAR regulator, affecting the transcription process, while the other binds to the target mRNA, affecting the translation process. We improved deactivation efficiencies (up to 96%) by optimizing each type of asRNA and then integrating the two optimized asRNAs into a single circuit. Furthermore, we demonstrated that the combined STAR and asRNA system can control gene expression in a reversible way and can regulate expression of a gene in the genome. Lastly, we constructed and simultaneously tested two A AND NOT B logic gates in the same cell to show sophisticated multigene regulation by the combined system. Our approach establishes a methodology for integrating multiple RNA regulators to rationally control multiple genes.

A Modular Genetic System for High-Throughput Profiling and Engineering of Multi-Target Small RNAs

RNA biology and RNA engineering are subjects of growing interest due to recent advances in our understanding of the diverse cellular functions of RNAs, including their roles as genetic regulators. The noncoding small RNAs (sRNAs) of bacteria are a fundamental basis of regulatory control that can regulate gene expression via antisense base-pairing to one or more target mRNAs. The sRNAs can be customized to generate a range of mRNA translation rates and stabilities. The sRNAs can be applied as a platform for metabolic engineering, to control expression of genes of interest by following relatively straightforward design rules (Kushwaha et al., ACS Synth Biol 5:795-809, 2016). However, the ab initio design of functional sRNAs to precise specifications of gene control is not yet possible. Consequently, there is a need for tools to rapidly profile uncharacterized sRNAs in vivo, to screen sRNAs against "new/novel" targets, and (in the case of metabolic engineering) to develop engineered sRNAs for regulatory function against multiple desired mRNA targets. To address this unmet need, we previously constructed a modular genetic system for assaying sRNA activity in vivo against specifiable mRNA sequences, using microtiter plate assays for high-throughput productivity. This sRNA design platform consists of three modular plasmids: one plasmid contains an inducible sRNA and the RNA chaperone Hfq; the second contains an inducible fluorescent reporter protein and a LacY mutant transporter protein for inducer molecules; and the third plasmid contains a second inducible fluorescent reporter protein. The second reporter gene makes it possible to screen for sRNA regulators that have activity against multiple mRNAs. We describe the protocol for engineering sRNAs with novel regulatory activity using this system. This sRNA prototyping regimen could also be employed for validating predicted mRNA targets of uncharacterized, naturally occurring sRNAs or for testing hypotheses about the predicted roles of genes, including essential genes, in cellular metabolism and other processes, by using customized antisense sRNAs to knock down or tune down gene expression.

Molecular Toolkit for Gene Expression Control and Genome Modification in Rhodococcus opacus PD630

Rhodococcus opacus PD630 is a non-model Gram-positive bacterium that possesses desirable traits for lignocellulosic biomass conversion. In particular, it has a relatively rapid growth rate, exhibits genetic tractability, produces high quantities of lipids, and can tolerate and consume toxic lignin-derived aromatic compounds. Despite these unique, industrially relevant characteristics, R. opacus has been underutilized because of a lack of reliable genetic parts and engineering tools. In this work, we developed a molecular toolbox for reliable gene expression control and genome modification in R. opacus. To facilitate predictable gene expression, a constitutive promoter library spanning ∼45-fold in output was constructed. To improve the characterization of available plasmids, the copy numbers of four heterologous and nine endogenous plasmids were determined using quantitative PCR. The molecular toolbox was further expanded by screening a previously unreported antibiotic resistance marker (HygR) and constructing a curable plasmid backbone for temporary gene expression (pB264). Furthermore, a system for genome modification was devised, and three neutral integration sites were identified using a novel combination of transcriptomic data, genomic architecture, and growth rate analysis. Finally, the first reported system for targeted, tunable gene repression in Rhodococcus was developed by utilizing CRISPR interference (CRISPRi). Overall, this work greatly expands the ability to manipulate and engineer R. opacus, making it a viable new chassis for bioproduction from renewable feedstocks.

Design rules of synthetic non-coding RNAs in bacteria

One of the long-term goals of synthetic biology is to develop designable genetic parts with predictable behaviors that can be utilized to implement diverse cellular functions. The discovery of non-coding RNAs and their importance in cellular processing have rapidly attracted researchers' attention towards designing functional non-coding RNA molecules. These synthetic non-coding RNAs have simple design principles governed by Watson-Crick base pairing, but exhibit increasingly complex functions. Importantly, due to their specific and modular behaviors, synthetic non-coding RNAs have been widely adopted to modulate transcription and translation of target genes. In this review, we summarize various design rules and strategies employed to engineer synthetic non-coding RNAs. Specifically, we discuss how RNA molecules can be transformed into powerful regulators and utilized to control target gene expression. With the establishment of generalizable non-coding RNA design rules, the research community will shift its focus to RNA regulators from protein regulators.

Rational Modular RNA Engineering Based on In Vivo Profiling of Structural Accessibility

Bacterial small RNAs (sRNAs) have been established as powerful parts for controlling gene expression. However, development and application of engineered sRNAs has primarily focused on regulating novel synthetic targets. In this work, we demonstrate a rational modular RNA engineering approach that uses in vivo structural accessibility measurements to tune the regulatory activity of a multisubstrate sRNA for differential control of its native target network. Employing the CsrB global sRNA regulator as a model system, we use published in vivo structural accessibility data to infer the contribution of its local structures (substructures) to function and select a subset for engineering. We then modularly recombine the selected substructures, differentially representing those of presumed high or low functional contribution, to build a library of 21 CsrB variants. Using fluorescent translational reporter assays, we demonstrate that the CsrB variants achieve a 5-fold gradient of control of well-characterized Csr network targets. Interestingly, results suggest that less conserved local structures within long, multisubstrate sRNAs may represent better targets for rational engineering than their well-conserved counterparts. Lastly, mapping the impact of sRNA variants on a signature Csr network phenotype indicates the potential of this approach for tuning the activity of global sRNA regulators in the context of metabolic engineering applications.

The Timing of Transcriptional Regulation in Synthetic Gene Circuits

Transcription factors and their target promoters are central to synthetic biology. By arranging these components into novel gene regulatory circuits, synthetic biologists have been able to create a wide variety of phenotypes, including bistable switches, oscillators, and logic gates. However, transcription factors (TFs) do not instantaneously regulate downstream targets. After the gene encoding a TF is turned on, the gene must first be transcribed, the transcripts must be translated, and sufficient TF must accumulate in order to bind operator sites of the target promoter. The time to complete this process, here called the "signaling time," is a critical aspect in the design of dynamic regulatory networks, yet it remains poorly characterized. In this work, we measured the signaling time of two TFs in Escherichia coli commonly used in synthetic biology: the activator AraC and the repressor LacI. We found that signaling times can range from a few to tens of minutes, and are affected by the expression rate of the TF. Our single-cell data also show that the variability of the signaling time increases with its mean. To validate these signaling time measurements, we constructed a two-step genetic cascade, and showed that the signaling time of the full cascade can be predicted from those of its constituent steps. These results provide concrete estimates for the time scales of transcriptional regulation in living cells, which are important for understanding the dynamics of synthetic transcriptional gene circuits.

A Genetic Tool to Quantify trans-Translation Activity in Vivo

In bacteria, trans-translation is the main quality control mechanism for rescuing ribosomes arrested during translation. This key process is universally conserved and plays a critical role in the viability and virulence of many pathogens. We developed a reliable in vivo double-fluorescence reporter system for the simultaneous quantification of both trans-translation and the associated proteolysis activities in bacteria. The assay was validated using mutant bacteria lacking tmRNA, SmpB, and the ClpP protease. Both antisense tmRNA-binding RNA and a peptide mimicking the SmpB C-terminal tail proved to be potent inhibitors of trans-translation in vivo. The double-fluorescent reporter was also tested with KKL-35, an oxadiazole derivative that is supposed to be a promising trans-translation inhibitor, and it surprisingly turns out that trans-translation is not the only target of KKL-35 in vivo.

Optimization of a novel biophysical model using large scale in vivo antisense hybridization data displays improved prediction capabilities of structurally accessible RNA regions

Current approaches to design efficient antisense RNAs (asRNAs) rely primarily on a thermodynamic understanding of RNA–RNA interactions. However, these approaches depend on structure predictions and have limited accuracy, arguably due to overlooking important cellular environment factors. In this work, we develop a biophysical model to describe asRNA–RNA hybridization that incorporates in vivo factors using large-scale experimental hybridization data for three model RNAs: a group I intron, CsrB and a tRNA. A unique element of our model is the estimation of the availability of the target region to interact with a given asRNA using a differential entropic consideration of suboptimal structures. We showcase the utility of this model by evaluating its prediction capabilities in four additional RNAs: a group II intron, Spinach II, 2-MS2 binding domain and glgC 5΄ UTR. Additionally, we demonstrate the applicability of this approach to other bacterial species by predicting sRNA–mRNA binding regions in two newly discovered, though uncharacterized, regulatory RNAs.

Enabling complex genetic circuits to respond to extrinsic environmental signals

Genetic circuits have the potential to improve a broad range of metabolic engineering processes and address a variety of medical and environmental challenges. However, in order to engineer genetic circuits that can meet the needs of these real-world applications, genetic sensors that respond to relevant extrinsic and intrinsic signals must be implemented in complex genetic circuits. In this work, we construct the first AND and NAND gates that respond to temperature and pH, two signals that have relevance in a variety of real-world applications. A previously identified pH-responsive promoter and a temperature-responsive promoter were extracted from the E. coli genome, characterized, and modified to suit the needs of the genetic circuits. These promoters were combined with components of the type III secretion system in Salmonella typhimurium and used to construct a set of AND gates with up to 23-fold change. Next, an antisense RNA was integrated into the circuit architecture to invert the logic of the AND gate and generate a set of NAND gates with up to 1168-fold change. These circuits provide the first demonstration of complex pH- and temperature-responsive genetic circuits, and lay the groundwork for the use of similar circuits in real-world applications. Biotechnol. Bioeng. 2017;114: 1626-1631. © 2017 Wiley Periodicals, Inc.