Putting RNA to work: Translating RNA fundamentals into biotechnological engineering practice

Dynamic feedback regulation for efficient membrane protein production using a small RNA-based genetic circuit in Escherichia coli

BACKGROUND

Membrane proteins (MPs) are an important class of molecules with a wide array of cellular functions and are part of many metabolic pathways. Despite their great potential-as therapeutic drug targets or in microbial cell factory optimization-many challenges remain for efficient and functional expression in a host such as Escherichia coli.

RESULTS

A dynamically regulated small RNA-based circuit was developed to counter membrane stress caused by overexpression of different MPs. The best performing small RNAs were able to enhance the maximum specific growth rate with 123%. On culture level, the total MP production was increased two-to three-fold compared to a system without dynamic control. This strategy not only improved cell growth and production of the studied MPs, it also suggested the potential use for countering metabolic burden in general.

CONCLUSIONS

A dynamically regulated feedback circuit was developed that can sense metabolic stress caused by, in casu, the overexpression of an MP and responds to it by balancing the metabolic state of the cell and more specifically by downregulating the expression of the MP of interest. This negative feedback mechanism was established by implementing and optimizing simple-to-use genetic control elements based on post-transcriptional regulation: small non-coding RNAs. In addition to membrane-related stress when the MP accumulated in the cytoplasm as aggregates, the sRNA-based feedback control system was still effective for improving cell growth but resulted in a decreased total protein production. This result suggests promiscuity of the MP sensor for more than solely membrane stress.

Synthetic negative feedback circuits using engineered small RNAs

Negative feedback is known to enable biological and man-made systems to perform reliably in the face of uncertainties and disturbances. To date, synthetic biological feedback circuits have primarily relied upon protein-based, transcriptional regulation to control circuit output. Small RNAs (sRNAs) are non-coding RNA molecules that can inhibit translation of target messenger RNAs (mRNAs). In this work, we modelled, built and validated two synthetic negative feedback circuits that use rationally-designed sRNAs for the first time. The first circuit builds upon the well characterised tet-based autorepressor, incorporating an externally-inducible sRNA to tune the effective feedback strength. This allows more precise fine-tuning of the circuit output in contrast to the sigmoidal, steep input–output response of the autorepressor alone. In the second circuit, the output is a transcription factor that induces expression of an sRNA, which inhibits translation of the mRNA encoding the output, creating direct, closed-loop, negative feedback. Analysis of the noise profiles of both circuits showed that the use of sRNAs did not result in large increases in noise. Stochastic and deterministic modelling of both circuits agreed well with experimental data. Finally, simulations using fitted parameters allowed dynamic attributes of each circuit such as response time and disturbance rejection to be investigated.

Role of Helicity in DNA Hairpin Folding Dynamics

We study hairpin folding dynamics by means of extensive molecular dynamics simulations, with particular attention paid to the influence of helicity on the folding time. We find that the dynamical exponent α in the anomalous scaling n(t)∼t^{1/α} of the hairpin length n with time changes from 1.6 (≃1+ν, where ν is the Flory exponent) to 1.2 (≃2ν) in three dimensions, when duplex helicity is removed. The relation α=2ν in rotationless hairpin folding is further verified in two dimensions (ν=0.75) and for a ghost chain (ν=0.5). Our findings suggest that the folding dynamics in long helical chains is governed by the duplex dynamics, contrasting the earlier understanding based on the stem-flower picture of unpaired segments. We propose a scaling argument for α=1+ν in helical chains, assuming that duplex relaxation required for orientational positioning of the next pair of bases is the rate-limiting process.

Synthetic switch-based baculovirus for transgene expression control and selective killing of hepatocellular carcinoma cells

Baculovirus (BV) holds promise as a vector for anticancer gene delivery to combat the most common liver cancer-hepatocellular carcinoma (HCC). However, in vivo BV administration inevitably results in BV entry into non-HCC normal cells, leaky anticancer gene expression and possible toxicity. To improve the safety, we employed synthetic biology to engineer BV for transgene expression regulation. We first uncovered that miR-196a and miR-126 are exclusively expressed in HCC and normal cells, respectively, which allowed us to engineer a sensor based on distinct miRNA expression signature. We next assembled a synthetic switch by coupling the miRNA sensor and RNA binding protein L7Ae for translational repression, and incorporated the entire device into a single BV. The recombinant BV efficiently entered HCC and normal cells and enabled cis-acting transgene expression control, by turning OFF transgene expression in normal cells while switching ON transgene expression in HCC cells. Using pro-apoptotic hBax as the transgene, the switch-based BV selectively killed HCC cells in separate culture and mixed culture of HCC and normal cells. These data demonstrate the potential of synthetic switch-based BV to distinguish HCC and non-HCC normal cells for selective transgene expression control and killing of HCC cells.

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.

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.

Applicability of a computational design approach for synthetic riboswitches

Riboswitches have gained attention as tools for synthetic biology, since they enable researchers to reprogram cells to sense and respond to exogenous molecules. In vitro evolutionary approaches produced numerous RNA aptamers that bind such small ligands, but their conversion into functional riboswitches remains difficult. We previously developed a computational approach for the design of synthetic theophylline riboswitches based on secondary structure prediction. These riboswitches have been constructed to regulate ligand-dependent transcription termination in Escherichia coli. Here, we test the usability of this design strategy by applying the approach to tetracycline and streptomycin aptamers. The resulting tetracycline riboswitches exhibit robust regulatory properties in vivo. Tandem fusions of these riboswitches with theophylline riboswitches represent logic gates responding to two different input signals. In contrast, the conversion of the streptomycin aptamer into functional riboswitches appears to be difficult. Investigations of the underlying aptamer secondary structure revealed differences between in silico prediction and structure probing. We conclude that only aptamers adopting the minimal free energy (MFE) structure are suitable targets for construction of synthetic riboswitches with design approaches based on equilibrium thermodynamics of RNA structures. Further improvements in the design strategy are required to implement aptamer structures not corresponding to the calculated MFE state.

An inhibitory RNA aptamer against the lambda cI repressor shows transcriptional activator activity in vivo

RNA aptamers are one of the promising components for constructing artificial genetic circuits. In this study, we developed a transcriptional activator based on an RNA aptamer against one of the most frequently applied repressor proteins, lambda phage cI. In vitro selection (Systematic Evolution of Ligands by EXponential enrichment) and following in vivo screening identified an RNA aptamer with the intended transcriptional activator activity from an RNA pool containing a 40-nucleotide long random region. Quantitative analysis showed a 35-fold elevation of reporter expression upon aptamer expression. These results suggest that the diversity of artificial transcriptional activators can be extended by employing RNA aptamers against repressor proteins to broaden the parts for constructing genetic circuits.

Retargeting a Dual-Acting sRNA for Multiple mRNA Transcript Regulation

Multitargeting small regulatory RNAs (sRNAs) represent a potentially useful tool for metabolic engineering applications. Natural multitargeting sRNAs govern bacterial gene expression by binding to the translation initiation regions of protein-coding mRNAs through base pairing. We designed an Escherichia coli based genetic system to create and assay dual-acting retargeted-sRNA variants. The variants can be assayed for coordinate translational regulation of two alternate mRNA leaders fused to independent reporter genes. Accordingly, we began with the well-characterized E. coli native DsrA sRNA. The merits of using DsrA include its well-characterized separation of function into two independently folded stem-loop domains, wherein alterations at one stem do not necessarily abolish activity at the other stem. Expression of the sRNA and each reporter mRNA was independently controlled by small inducer molecules, allowing precise quantification of the regulatory effects of each sRNA:mRNA interaction in vivo with a microtiter plate assay. Using this system, we semirationally designed DsrA variants screened in E. coli for their ability to regulate key mRNA leader sequences from the Clostridium acetobutylicum n-butanol synthesis pathway. To coordinate intervention at two points in a metabolic pathway, we created bifunctional sRNA prototypes by combining sequences from two singly retargeted DsrA variants. This approach constitutes a platform for designing sRNAs to specifically target arbitrary mRNA transcript sequences, and thus provides a generalizable tool for retargeting and characterizing multitarget sRNAs for metabolic engineering.

3rd congress on applied synthetic biology in Europe (Costa da Caparica, Portugal, February 2016)

The third meeting organised by the European Federation of Biotechnology (EFB) on advances in Applied Synthetic Biotechnology in Europe (ASBE) was held in Costa da Caparica, Portugal, in February 2016. Abundant novel applications in synthetic biology were described in the six sessions of the meeting, which was divided into technology and tools for synthetic biology (I, II and III), bionanoscience, biosynthetic pathways and enzyme synthetic biology, and metabolic engineering and chemical manufacturing. The meeting presented numerous methods for the development of novel synthetic strains, synthetic biological tools and synthetic biology applications. With the aid of synthetic biology, production costs of chemicals, metabolites and food products are expected to decrease, by generating sustainable biochemical production of such resources. Also, such synthetic biological advances could be applied for medical purposes, as in pharmaceuticals and for biosensors. Recurrent, linked themes throughout the meeting were the shortage of resources, the world's transition into a bioeconomy, and how synthetic biology is helping tackle these issues through cutting-edge technologies. While there are still limitations in synthetic biology research, innovation is propelling the development of technology, the standardisation of synthetic biological tools and the use of suitable host organisms. These developments are laying a foundation to providing a future where cutting-edge research could generate potential solutions to society's pressing issues, thus incentivising a transition into a bioeconomy.

Designing Synthetic Flexible Gene Regulation Networks Using RNA Devices in Cyanobacteria

In recent years, studies on the development of gene regulation tools in cyanobacteria have been extensively conducted toward efficient production of valuable chemicals. However, there is considerable scope for improving the economic feasibility of production. To improve a recently reported gene induction system using anhydrotetracycline (aTc)-TetR and an endogenous gene repression system using small antisense RNA in the filamentous nitrogen-fixing cyanobacterium Anabaena sp. PCC 7120 (Anabaena), we constructed a positive feedback loop, in which gfp and a small antisense RNA for tetR are controlled by an aTc-inducible promoter. GFP expression in this improved system was higher and longer than the system lacking tetR repression. In addition, by using TetR aptamer and a riboswitch, we succeeded in achieving a superior and longer induction of GFP expression even under high-light conditions. Hence, efficient gene induction systems were established in Anabaena by designing a gene regulation network using RNA-based tools.

Tailor-made transcriptional biosensors for optimizing microbial cell factories

Monitoring cellular behavior and eventually properly adapting cellular processes is key to handle the enormous complexity of today's metabolic engineering questions. Hence, transcriptional biosensors bear the potential to augment and accelerate current metabolic engineering strategies, catalyzing vital advances in industrial biotechnology. The development of such transcriptional biosensors typically starts with exploring nature's richness. Hence, in a first part, the transcriptional biosensor architecture and the various modi operandi are briefly discussed, as well as experimental and computational methods and relevant ontologies to search for natural transcription factors and their corresponding binding sites. In the second part of this review, various engineering approaches are reviewed to tune the main characteristics of these (natural) transcriptional biosensors, i.e., the response curve and ligand specificity, in view of specific industrial biotechnology applications, which is illustrated using success stories of transcriptional biosensor engineering.

Using RNA as Molecular Code for Programming Cellular Function

RNA is involved in a wide-range of important molecular processes in the cell, serving diverse functions: regulatory, enzymatic, and structural. Together with its ease and predictability of design, these properties can lead RNA to become a useful handle for biological engineers with which to control the cellular machinery. By modifying the many RNA links in cellular processes, it is possible to reprogram cells toward specific design goals. We propose that RNA can be viewed as a molecular programming language that, together with protein-based execution platforms, can be used to rewrite wide ranging aspects of cellular function. In this review, we catalogue developments in the use of RNA parts, methods, and associated computational models that have contributed to the programmability of biology. We discuss how RNA part repertoires have been combined to build complex genetic circuits, and review recent applications of RNA-based parts and circuitry. We explore the future potential of RNA engineering and posit that RNA programmability is an important resource for firmly establishing an era of rationally designed synthetic biology.

Determination of the Specificity Landscape for Ribonuclease P Processing of Precursor tRNA 5' Leader Sequences

Maturation of tRNA depends on a single endonuclease, ribonuclease P (RNase P), to remove highly variable 5' leader sequences from precursor tRNA transcripts. Here, we use high-throughput enzymology to report multiple-turnover and single-turnover kinetics for Escherichia coli RNase P processing of all possible 5' leader sequences, including nucleotides contacting both the RNA and protein subunits of RNase P. The results reveal that the identity of N(-2) and N(-3) relative to the cleavage site at N(1) primarily control alternative substrate selection and act at the level of association not the cleavage step. As a consequence, the specificity for N(-1), which contacts the active site and contributes to catalysis, is suppressed. This study demonstrates high-throughput RNA enzymology as a means to globally determine RNA specificity landscapes and reveals the mechanism of substrate discrimination by a widespread and essential RNA-processing enzyme.

RNA-based gene circuits for cell regulation

A major goal of synthetic biology is to control cell behavior. RNA-mediated genetic switches (RNA switches) are devices that serve this purpose, as they can control gene expressions in response to input signals. In general, RNA switches consist of two domains: an aptamer domain, which binds to an input molecule, and an actuator domain, which controls the gene expression. An input binding to the aptamer can cause the actuator to alter the RNA structure, thus changing access to translation machinery. The assembly of multiple RNA switches has led to complex gene circuits for cell therapies, including the selective killing of pathological cells and purification of cell populations. The inclusion of RNA binding proteins, such as L7Ae, increases the repertoire and precision of the circuit. In this short review, we discuss synthetic RNA switches for gene regulation and their potential therapeutic applications.