Antisense transcription as a tool to tune gene expression

Dynamic and Static Regulation of Nicotinamide Adenine Dinucleotide Phosphate: Strategies, Challenges, and Future Directions in Metabolic Engineering

Reduced nicotinamide adenine dinucleotide phosphate (NADPH) is a crucial cofactor in metabolic networks. The efficient regeneration of NADPH is one of the limiting factors for productivity in biotransformation processes. To date, many metabolic engineering tools and static regulation strategies have been developed to regulate NADPH regeneration. However, traditional static regulation methods often lead to the NADPH/NADP+ imbalance, causing disruptions in cell growth and production. These methods also fail to provide real-time monitoring of intracellular NADP(H) or NADPH/NADP+ levels. In recent years, various biosensors have been developed for the detection, monitoring, and dynamic regulate of the intracellular NADP(H) levels or the NADPH/NADP+ balance. These NADPH-related biosensors are mainly used in the cofactor engineering of bacteria, yeast, and mammalian cells. This review analyzes and summarizes the NADPH metabolic regulation strategies from both static and dynamic perspectives, highlighting current challenges and potential solutions, and discusses future directions for the advanced regulation of the NADPH/NADP+ balance.

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

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

MetJ-Based Mutually Interfering SAM-ON/SAM-OFF Biosensors

SAM (S-adenosylmethionine) is an important metabolite that operates as a major donor of methyl groups and is a controller of various physiological processes. Its availability is also believed to be a major bottleneck in the biological production of numerous high-value metabolites. Here, we constructed SAM-sensing systems using MetJ, an SAM-dependent transcriptional regulator, as a core component. SAM is a corepressor of MetJ, which suppresses the MetJ promoter with an increasing cellular concentration of SAM (SAM-OFF sensor). The application of transcriptional interference and evolutionary tuning effectively inverted its response, yielding a SAM-ON sensor (signal increases with increasing SAM concentration). By linking two genes encoding fluorescent protein reporters in such a way that their transcription events interfere with each other's and by placing one of them under the control of MetJ, we could increase the effective signal-to-noise ratio of the SAM sensor while decreasing the batch-to-batch deviation in signal output, likely by canceling out the growth-associated fluctuation in translational resources. By taking the ratio of SAM-ON/SAM-OFF signals and by resetting the default pool size of SAM, we could rapidly identify SAM synthetase (MetK) mutants with increased cellular activity from a random library. The strategy described herein should be widely applicable for identifying activity mutants, which would be otherwise overlooked because of the strong homeostasis of metabolic networks.

CRISPR-dCas13a system for programmable small RNAs and polycistronic mRNA repression in bacteria

Bacterial small RNAs (sRNAs) function in post-transcriptional regulatory responses to environmental changes. However, the lack of eukaryotic RNA interference-like machinery in bacteria has limited the systematic engineering of RNA repression. Here, we report the development of clustered regularly interspaced short palindromic repeats (CRISPR)-guided dead CRIPSR-associated protein 13a (dCas13a) ribonucleoprotein that utilizes programmable CRISPR RNAs (crRNAs) to repress trans-acting and cis-acting sRNA as the target, altering regulatory mechanisms and stress-related phenotypes. In addition, we implemented a modular loop engineering of the crRNA to promote modular repression of the target gene with 92% knockdown efficiency and a single base-pair mismatch specificity. With the engineered crRNAs, we achieved targetable single-gene repression in the polycistronic operon. For metabolic application, 102 crRNAs were constructed in the biofoundry and used for screening novel knockdown sRNA targets to improve lycopene (colored antioxidant) production in Escherichia coli. The CRISPR-dCas13a system will assist as a valuable systematic tool for the discovery of novel sRNAs and the fine-tuning of bacterial RNA repression in both scientific and industrial applications.

Using design of experiments to guide genetic optimization of engineered metabolic pathways

Design of experiments (DoE) is a term used to describe the application of statistical approaches to interrogate the impact of many variables on the performance of a multivariate system. It is commonly used for process optimization in fields such as chemical engineering and material science. Recent advances in the ability to quantitatively control the expression of genes in biological systems open up the possibility to apply DoE for genetic optimization. In this review targeted to genetic and metabolic engineers, we introduce several approaches in DoE at a high level and describe instances wherein these were applied to interrogate or optimize engineered genetic systems. We discuss the challenges of applying DoE and propose strategies to mitigate these challenges.

ONE-SENTENCE SUMMARY

This is a review of literature related to applying Design of Experiments for genetic optimization.

Taming CRISPRi: Dynamic range tuning through guide RNA diversion

CRISPRi is a powerful technique to repress gene expression in a targeted and highly efficient manner. However, this potency is a double-edged sword in inducible systems, as even leaky expression of guide RNA results in a repression phenotype, complicating applications such as dynamic metabolic engineering. We evaluated three methods to enhance the controllability of CRISPRi by modulating the level of free and DNA-bound guide RNA complexes. Overall repression can be attenuated through rationally designed mismatches in the reversibility determining region of the guide RNA sequence; decoy target sites can selectively modulate repression at low levels of induction; and the implementation of feedback control not only enhances the linearity of induction, but broadens the dynamic range of the output as well. Furthermore, feedback control significantly enhances the recovery rate after induction is removed. Used in combination, these techniques enable the fine-tuning of CRISPRi to meet restrictions imposed by the target and match the input signal required for induction.

Improved RNA stability estimation indicates that transcriptional interference is frequent in diverse bacteria

We used stochastic simulations and experimental data from E. coli, K. aerogenes, Synechococcus PCC 7002 and Synechocystis PCC 6803 to provide evidence that transcriptional interference via the collision mechanism is likely a prevalent mechanism for bacterial gene regulation. Rifampicin time-series data can be used to globally monitor and quantify collision between sense and antisense transcription-complexes. Our findings also highlight that transcriptional events, such as differential RNA decay, partial termination, and internal transcriptional start sites often deviate from gene annotations. Consequently, within a single gene annotation, there exist transcript segments with varying half-lives and transcriptional properties. To address these complexities, we introduce 'rifi', an R-package that analyzes transcriptomic data from rifampicin time series. 'rifi' employs a dynamic programming-based segmentation approach to identify individual transcripts, enabling accurate assessment of RNA stability and detection of diverse transcriptional events.

Antisense transcription and its roles in adaption to environmental stress in E. coli

It has been reported that a highly varying proportion (1% ∼ 93%) of genes in various prokaryotes have antisense RNA (asRNA) transcription. However, the extent of the pervasiveness of asRNA transcription in the well-studied E. coli K12 strain has thus far been an issue of debate. Furthermore, very little is known about the expression patterns and functions of asRNAs under various conditions. To fill these gaps, we determined the transcriptomes and proteomes of E. coli K12 at multiple time points in five culture conditions using strand-specific RNA-seq, differential RNA-seq, and quantitative mass spectrometry methods. To reduce artifacts of possible transcriptional noise, we identified asRNA using stringent criteria with biological replicate verification and transcription start sites (TSSs) information included. We identified a total of 660 asRNAs, which were generally short and largely condition-dependently transcribed. We found that the proportions of the genes which had asRNA transcription highly depended on the culture conditions and time points. We classified the transcriptional activities of the genes in six transcriptional modes according to their relative levels of asRNA to mRNA. Many genes changed their transcriptional modes at different time points of the culture conditions, and such transitions can be described in a well-defined manner. Intriguingly, the protein levels and mRNA levels of genes in the sense-only/sense-dominant mode were moderately correlated, but the same was not true for genes in the balanced/antisense-dominant mode, in which asRNAs were at a comparable or higher level to mRNAs. These observations were further validated by western blot on candidate genes, where an increase in asRNA transcription diminished gene expression in one case and enhanced it in another. These results suggest that asRNAs may directly or indirectly regulate translation by forming duplexes with cognate mRNAs. Thus, asRNAs may play an important role in the bacterium's responses to environmental changes during growth and adaption to different environments.

IMPORTANCE

The cis -antisense RNA (asRNA) is a type of understudied RNA molecules in prokaryotes, which is believed to be important in regulating gene expression. Our current understanding of asRNA is constrained by inconsistent reports about its identification and properties. These discrepancies are partially caused by a lack of sufficient samples, biological replicates, and culture conditions. This study aimed to overcome these disadvantages and identified 660 putative asRNAs using integrated information from strand-specific RNA-seq, differential RNA-seq, and mass spectrometry methods. In addition, we explored the relative expression between asRNAs and sense RNAs and investigated asRNA regulated transcriptional activity changes over different culture conditions and time points. Our work strongly suggests that asRNAs may play a crucial role in bacterium's responses to environmental changes during growth and adaption to different environments.

Genetic and environmental perturbations alter the rhythmic expression pattern of a circadian long non-coding RNA, Per2AS, in mouse liver

Background: Long non-coding RNAs (lncRNAs) play a wide variety of biological roles without encoding a protein. Although the functions of many lncRNAs have been uncovered in recent years, the regulatory mechanism of lncRNA expression is still poorly understood despite that the expression patterns of lncRNAs are much more specific compared to mRNAs. Here, we investigated the rhythmic expression of Per2AS, a novel lncRNA that regulates circadian rhythms. Given that Per2AS expression is antiphasic to Period2 ( Per2), a core circadian clock gene, and transcribed from the antisense strand of Per2, we hypothesized that the rhythmic Per2AS expression is driven either by its own promoter or by the rhythmic Per2 transcription via transcriptional interference. Methods: We leveraged existing circadian RNA-seq datasets and analyzed the expression patterns of Per2AS and Per2 in response to the genetic or environmental disruption of the circadian rhythm in mouse liver. We tested our hypotheses by comparing the changes in the expression patterns of Per2AS and Per2. Conclusions: We found that, in some cases, Per2AS expression is independently controlled by other circadian transcription factors. In other cases, the pattern of expression change is consistent with both transcriptional interference and independent regulation hypotheses. Although additional experiments will be necessary to distinguish these possibilities, findings from this work contribute to a deeper understanding of the mechanism of how the expression of lncRNA is regulated.

Genetic context effects can override canonical cis regulatory elements in Escherichia coli

Recent experiments have shown that in addition to control by cis regulatory elements, the local chromosomal context of a gene also has a profound impact on its transcription. Although this chromosome-position dependent expression variation has been empirically mapped at high-resolution, the underlying causes of the variation have not been elucidated. Here, we demonstrate that 1 kb of flanking, non-coding synthetic sequences with a low frequency of guanosine and cytosine (GC) can dramatically reduce reporter expression compared to neutral and high GC-content flanks in Escherichia coli. Natural and artificial genetic context can have a similarly strong effect on reporter expression, regardless of cell growth phase or medium. Despite the strong reduction in the maximal expression level from the fully-induced reporter, low GC synthetic flanks do not affect the time required to reach the maximal expression level after induction. Overall, we demonstrate key determinants of transcriptional propensity that appear to act as tunable modulators of transcription, independent of regulatory sequences such as the promoter. These findings provide insight into the regulation of naturally occurring genes and an independent control for optimizing expression of synthetic biology constructs.

Synthetic neuromorphic computing in living cells

Computational properties of neuronal networks have been applied to computing systems using simplified models comprising repeated connected nodes, e.g., perceptrons, with decision-making capabilities and flexible weighted links. Analogously to their revolutionary impact on computing, neuro-inspired models can transform synthetic gene circuit design in a manner that is reliable, efficient in resource utilization, and readily reconfigurable for different tasks. To this end, we introduce the perceptgene, a perceptron that computes in the logarithmic domain, which enables efficient implementation of artificial neural networks in Escherichia coli cells. We successfully modify perceptgene parameters to create devices that encode a minimum, maximum, and average of analog inputs. With these devices, we create multi-layer perceptgene circuits that compute a soft majority function, perform an analog-to-digital conversion, and implement a ternary switch. We also create a programmable perceptgene circuit whose computation can be modified from OR to AND logic using small molecule induction. Finally, we show that our approach enables circuit optimization via artificial intelligence algorithms.

The regulon of Brucella abortus two-component system BvrR/BvrS reveals the coordination of metabolic pathways required for intracellular life

Brucella abortus is a facultative intracellular pathogen causing a severe zoonotic disease worldwide. The two-component regulatory system (TCS) BvrR/BvrS of B. abortus is conserved in members of the Alphaproteobacteria class. It is related to the expression of genes required for host interaction and intracellular survival. Here we report that bvrR and bvrS are part of an operon composed of 16 genes encoding functions related to nitrogen metabolism, DNA repair and recombination, cell cycle arrest, and stress response. Synteny of this genomic region within close Alphaproteobacteria members suggests a conserved role in coordinating the expression of carbon and nitrogen metabolic pathways. In addition, we performed a ChIP-Seq analysis after exposure of bacteria to conditions that mimic the intracellular environment. Genes encoding enzymes at metabolic crossroads of the pentose phosphate shunt, gluconeogenesis, cell envelope homeostasis, nucleotide synthesis, cell division, and virulence are BvrR/BvrS direct targets. A 14 bp DNA BvrR binding motif was found and investigated in selected gene targets such as virB1, bvrR, pckA, omp25, and tamA. Understanding gene expression regulation is essential to elucidate how Brucella orchestrates a physiological response leading to a furtive pathogenic strategy.

Automated model-predictive design of synthetic promoters to control transcriptional profiles in bacteria

Transcription rates are regulated by the interactions between RNA polymerase, sigma factor, and promoter DNA sequences in bacteria. However, it remains unclear how non-canonical sequence motifs collectively control transcription rates. Here, we combine massively parallel assays, biophysics, and machine learning to develop a 346-parameter model that predicts site-specific transcription initiation rates for any σ70 promoter sequence, validated across 22132 bacterial promoters with diverse sequences. We apply the model to predict genetic context effects, design σ70 promoters with desired transcription rates, and identify undesired promoters inside engineered genetic systems. The model provides a biophysical basis for understanding gene regulation in natural genetic systems and precise transcriptional control for engineering synthetic genetic systems.

The context matrix: Navigating biological complexity for advanced biodesign

Synthetic biology offers many solutions in healthcare, production, sensing and agriculture. However, the ability to rationally engineer synthetic biosystems with predictable and robust functionality remains a challenge. A major reason is the complex interplay between the synthetic genetic construct, its host, and the environment. Each of these contexts contains a number of input factors which together can create unpredictable behaviours in the engineered biosystem. It has become apparent that for the accurate assessment of these contextual effects a more holistic approach to design and characterisation is required. In this perspective article, we present the context matrix, a conceptual framework to categorise and explore these contexts and their net effect on the designed synthetic biosystem. We propose the use and community-development of the context matrix as an aid for experimental design that simplifies navigation through the complex design space in synthetic biology.

Transcriptional Interference in Toehold Switch-Based RNA Circuits

Gene regulation based on regulatory RNA is an important mechanism in cells and is increasingly used for regulatory circuits in synthetic biology. Toehold switches are rationally designed post-transcriptional riboregulators placed in the 5' untranslated region of mRNA molecules. In the inactive state of a toehold switch, the ribosome-binding site is inaccessible to the ribosome. In the presence of a trigger RNA molecule, protein production is turned on. Using antisense RNA against trigger molecules (antitrigger RNA), gene expression can also be switched off again. We here study the utility of antisense transcription in this context, which enables a particularly compact circuit design. Our circuits utilize two inducible promoters that separately regulate trigger and antitrigger transcription, whereas their cognate toehold switch, regulating the expression of a reporter protein, is transcribed from a constitutive promoter. We explore various design options for the arrangement of the promoters and demonstrate that the resulting dynamic behavior is influenced by transcriptional interference (TI) effects depending on the promoter distance. Our experimental results are consistent with previous findings that enhanced local RNA polymerase concentrations due to active promoters in close proximity lead to an increase in transcriptional activity of the strongest promoter in the circuits. We observed that the range of this effect is larger when the participating promoters are stronger. Based on this insight, we combined two promoter arrangements for the realization of a genetic circuit comprised of two toehold switches, two triggers, and two antitriggers that function as a two-input two-output logic gate.

An Antisense RNA Fine-Tunes Gene Expression of the Type II MazEF Toxin-Antitoxin System

Despite their ubiquitous nature, few antisense RNAs have been functionally characterized, and this class of RNAs is considered by some to be transcriptional noise. Here, we report that an antisense RNA (asRNA), aMEF (antisense mazEF), functions as a dual regulator for the type II toxin-antitoxin (TA) system mazEF. Unlike type I TA systems and many other regulatory asRNAs, aMEF stimulates the synthesis and translation of mazEF rather than inhibition and degradation. Our data indicate that a double-stranded RNA intermediate and RNase III are not necessary for aMEF-dependent regulation of mazEF expression. The lack of conservation of asRNA promoters has been used to support the hypothesis that asRNAs are spurious transcriptional noise and nonfunctional. We demonstrate that the aMEF promoter is active and functional in Escherichia coli despite poor sequence conservation, indicating that the lack of promoter sequence conservation should not be correlated with functionality. IMPORTANCE Next-generation RNA sequencing of numerous organisms has revealed that transcription is widespread across the genome, termed pervasive transcription, and does not adhere to annotated gene boundaries. The function of pervasive transcription is enigmatic and has generated considerable controversy as to whether it is transcriptional noise or biologically relevant. Antisense transcription is one class of pervasive transcription that occurs from the DNA strand opposite an annotated gene. Relatively few pervasively transcribed asRNAs have been functionally characterized, and their regulatory roles or lack thereof remains unknown. It is important to study examples of these asRNAs and determine if they are functional regulators. In this study, we elucidate the function of an asRNA (aMEF) demonstrating that pervasive transcripts can be functional.

Interplay between non-coding RNA transcription, stringent phenotype and antibiotic production in Streptomyces

While in recent years the key role of non-coding RNAs (ncRNAs) in regulation of gene expression has become increasingly evident, their interaction with the global regulatory circuits is still obscure. Here we analyzed the structure and organization of the transcriptome of Streptomyces ambofaciens, the producer of spiramycin. We identified ncRNAs including 45 small-RNAs (sRNAs) and 119 antisense-RNAs (asRNAs I) that appear transcribed from dedicated promoters. Some sRNAs and asRNAs are unprecedented in Streptomyces, and were predicted to target mRNAs encoding proteins involved in transcription, translation, ribosomal structure and biogenesis, and regulation of morphological and biochemical differentiation. We then compared ncRNA expression in three strains: i.) the wild type strain; ii.) an isogenic pirA-defective mutant with central carbon metabolism imbalance, "relaxed" phenotype, and repression of antibiotic production; iii.) a pirA-derivative strain harboring a "stringent" RNA polymerase that suppresses pirA-associated phenotypes. Data indicated that expression of most ncRNAs was correlated to the stringent/relaxed phenotype suggesting novel effector mechanisms of the stringent response.

Predicting bacterial promoter function and evolution from random sequences

Predicting function from sequence is a central problem of biology. Currently, this is possible only locally in a narrow mutational neighborhood around a wildtype sequence rather than globally from any sequence. Using random mutant libraries, we developed a biophysical model that accounts for multiple features of σ⁷⁰ binding bacterial promoters to predict constitutive gene expression levels from any sequence. We experimentally and theoretically estimated that 10–20% of random sequences lead to expression and ~80% of non-expressing sequences are one mutation away from a functional promoter. The potential for generating expression from random sequences is so pervasive that selection acts against σ⁷⁰-RNA polymerase binding sites even within inter-genic, promoter-containing regions. This pervasiveness of σ⁷⁰-binding sites implies that emergence of promoters is not the limiting step in gene regulatory evolution. Ultimately, the inclusion of novel features of promoter function into a mechanistic model enabled not only more accurate predictions of gene expression levels, but also identified that promoters evolve more rapidly than previously thought.

The Identification of MATE Antisense Transcripts in Soybean Using Strand-Specific RNA-Seq Datasets

Natural antisense transcripts (NATs) have been generally reported as negative regulators of their sense counterparts. Multidrug and toxic compound extrusion (MATE) proteins mediate the transport of various substrates. Although MATEs have been identified genome-wide in various plant species, their transcript regulators remain unclear. Here, using the publicly available strand-specific RNA-seq datasets of Glycine soja (wild soybean) which have the data from various tissues including developing pods, developing seeds, embryos, cotyledons and hypocotyls, roots, apical buds, stems, and flowers, we identified 35 antisense transcripts of MATEs from 28 gene loci after transcriptome assembly. Spearman correlation coefficients suggested the positive expression correlations of eight MATE antisense and sense transcript pairs. By aligning the identified transcripts with the reference genome of Glycine max (cultivated soybean), the MATE antisense and sense transcript pairs were identified. Using soybean C08 (Glycine max), in developing pods and seeds, the positive correlations between MATE antisense and sense transcript pairs were shown by RT-qPCR. These findings suggest that soybean antisense transcripts are not necessarily negative transcription regulators of their sense counterparts. This study enhances the existing knowledge on the transcription regulation of MATE transporters by uncovering the previously unknown MATE antisense transcripts and their potential synergetic effects on sense transcripts.

A positive Selection Escherichia Coli Recombinant Protein Expression Vector for One-Step Cloning

We introduce OLIVAR ( O rientation se L ection of I nsert in V ector through A ntisense R eporter) as a novel selection strategy for the insertion of protein-coding genes into vector backbones. As a proof-of-concept, we have engineered a plasmid vector, pGRASS ( G reen fluorescent protein R eporter from A ntisense promoter-based S creening S ystem), for gene cloning in E. coli. With pGRASS, positive clones can be effortlessly distinguished from negative clones after blunt-end cloning. The vector not only screens clones with an insert but also for its correct orientation. The design further allows for the expression of recombinant protein from the T7 promoter in an appropriate host bacterium. With this vector, we are able to reduce the entire cloning workflow into a single step involving a 2-h reaction at room temperature. We believe that our cloning-cum-screening system presented here is extremely cost-effective and straightforward and can be applied to other vector systems and domains such as phage display and library construction.

Overlapping genes in natural and engineered genomes

Modern genome-scale methods that identify new genes, such as proteogenomics and ribosome profiling, have revealed, to the surprise of many, that overlap in genes, open reading frames and even coding sequences is widespread and functionally integrated into prokaryotic, eukaryotic and viral genomes. In parallel, the constraints that overlapping regions place on genome sequences and their evolution can be harnessed in bioengineering to build more robust synthetic strains and constructs. With a focus on overlapping protein-coding and RNA-coding genes, this Review examines their discovery, topology and biogenesis in the context of their genome biology. We highlight exciting new uses for sequence overlap to control translation, compress synthetic genetic constructs, and protect against mutation.

DNA supercoiling-mediated collective behavior of co-transcribing RNA polymerases

Multiple RNA polymerases (RNAPs) transcribing a gene have been known to exhibit collective group behavior, causing the transcription elongation rate to increase with the rate of transcription initiation. Such behavior has long been believed to be driven by a physical interaction or ‘push’ between closely spaced RNAPs. However, recent studies have posited that RNAPs separated by longer distances may cooperate by modifying the DNA segment under transcription. Here, we present a theoretical model incorporating the mechanical coupling between RNAP translocation and the DNA torsional response. Using stochastic simulations, we demonstrate DNA supercoiling-mediated long-range cooperation between co-transcribing RNAPs. We find that inhibiting transcription initiation can slow down the already recruited RNAPs, in agreement with recent experimental observations, and predict that the average transcription elongation rate varies non-monotonically with the rate of transcription initiation. We further show that while RNAPs transcribing neighboring genes oriented in tandem can cooperate, those transcribing genes in divergent or convergent orientations can act antagonistically, and that such behavior holds over a large range of intergenic separations. Our model makes testable predictions, revealing how the mechanical interplay between RNAPs and the DNA they transcribe can govern transcriptional dynamics.

Importance of the 5' regulatory region to bacterial synthetic biology applications

The field of synthetic biology is evolving at a fast pace. It is advancing beyond single-gene alterations in single hosts to the logical design of complex circuits and the development of integrated synthetic genomes. Recent breakthroughs in deep learning, which is increasingly used in de novo assembly of DNA components with predictable effects, are also aiding the discipline. Despite advances in computing, the field is still reliant on the availability of pre-characterized DNA parts, whether natural or synthetic, to regulate gene expression in bacteria and make valuable compounds. In this review, we discuss the different bacterial synthetic biology methodologies employed in the creation of 5' regulatory regions - promoters, untranslated regions and 5'-end of coding sequences. We summarize methodologies and discuss their significance for each of the functional DNA components, and highlight the key advances made in bacterial engineering by concentrating on their flaws and strengths. We end the review by outlining the issues that the discipline may face in the near future.

The fate of notch-1 transcript is linked to cell cycle dynamics by activity of a natural antisense transcript

A core imprint of metazoan life is that perturbations of cell cycle are offset by compensatory changes in successive cellular generations. This trait enhances robustness of multicellular growth and requires transmission of signaling cues within a cell lineage. Notably, the identity and mode of activity of transgenerational signals remain largely unknown. Here we report the discovery of a natural antisense transcript encoded in exon 25 of notch-1 locus (nAS25) by which mother cells control the fate of notch-1 transcript in daughter cells to buffer against perturbations of cell cycle. The antisense transcript is transcribed at G1 phase of cell cycle from a bi-directional E2F1-dependent promoter in the mother cell where the titer of nAS25 is calibrated to the length of G1. Transmission of the antisense transcript from mother to daughter cells stabilizes notch-1 sense transcript in G0 phase of daughter cells by masking it from RNA editing and resultant nonsense-mediated degradation. In consequence, nAS25-mediated amplification of notch-1 signaling reprograms G1 phase in daughter cells to compensate for the altered dynamics of the mother cell. The function of nAS25/notch-1 in integrating G1 phase history of the mother cell into that of daughter cells is compatible with the predicted activity of a molecular oscillator, slower than cyclins, that coordinates cell cycle within cell lineage.

Modular tuning engineering and versatile applications of genetically encoded biosensors

Genetically encoded biosensors have a diverse range of detectable signals and potential applications in many fields, including metabolism control and high-throughput screening. Their ability to be used in situ with minimal interference to the bioprocess of interest could revolutionize synthetic biology and microbial cell factories. The performance and functions of these biosensors have been extensively studied and have been rapidly improved. We review here current biosensor tuning strategies and attempt to unravel how to obtain ideal biosensor functions through experimental adjustments. Strategies for expanding the biosensor input signals that increases the number of detectable compounds have also been summarized. Finally, different output signals and their practical requirements for biotechnology and biomedical applications and environmental safety concerns have been analyzed. This in-depth review of the responses and regulation mechanisms of genetically encoded biosensors will assist to improve their design and optimization in various application scenarios.

Interplay between Non-Coding RNA Transcription, Stringent/Relaxed Phenotype and Antibiotic Production in Streptomyces ambofaciens

While in recent years the key role of non-coding RNAs (ncRNAs) in the regulation of gene expression has become increasingly evident, their interaction with the global regulatory circuits is still obscure. Here we analyzed the structure and organization of the transcriptome of Streptomyces ambofaciens, the producer of spiramycin. We identified ncRNAs including 45 small-RNAs (sRNAs) and 119 antisense-RNAs (asRNAs I) that appear transcribed from dedicated promoters. Some sRNAs and asRNAs are unprecedented in Streptomyces and were predicted to target mRNAs encoding proteins involved in transcription, translation, ribosomal structure and biogenesis, and regulation of morphological and biochemical differentiation. We then compared ncRNA expression in three strains: (i) the wild-type strain; (ii) an isogenic pirA-defective mutant with central carbon metabolism imbalance, “relaxed” phenotype, and repression of antibiotic production; and (iii) a pirA-derivative strain harboring a “stringent” RNA polymerase that suppresses pirA-associated phenotypes. Data indicated that the expression of most ncRNAs was correlated to the stringent/relaxed phenotype suggesting novel effector mechanisms of the stringent response.

Bacterial Nosocomial Infections: Multidrug Resistance as a Trigger for the Development of Novel Antimicrobials

Nosocomial bacterial infections are associated with high morbidity and mortality, posing a huge burden to healthcare systems worldwide. The ongoing COVID-19 pandemic, with the raised hospitalization of patients and the increased use of antimicrobial agents, boosted the emergence of difficult-to-treat multidrug-resistant (MDR) bacteria in hospital settings. Therefore, current available antibiotic treatments often have limited or no efficacy against nosocomial bacterial infections, and novel therapeutic approaches need to be considered. In this review, we analyze current antibacterial alternatives under investigation, focusing on metal-based complexes, antimicrobial peptides, and antisense antimicrobial therapeutics. The association of new compounds with older, commercially available antibiotics and the repurposing of existing drugs are also revised in this work.

Topologies of synthetic gene circuit for optimal fold change activation

Computations widely exist in biological systems for functional regulations. Recently, incoherent feedforward loop and integral feedback controller have been implemented into Escherichia coli to achieve a robust adaptation. Here, we demonstrate that an indirect coherent feedforward loop and mutual inhibition designs can experimentally improve the fold change of promoters, by reducing the basal level while keeping the maximum activity high. We applied both designs to six different promoters in E. coli, starting with synthetic inducible promoters as a proof-of-principle. Then, we examined native promoters that are either functionally specific or systemically involved in complex pathways such as oxidative stress and SOS response. Both designs include a cascade having a repressor and a construct of either transcriptional interference or antisense transcription. In all six promoters, an improvement of up to ten times in the fold change activation was observed. Theoretically, our unitless models show that when regulation strength matches promoter basal level, an optimal fold change can be achieved. We expect that this methodology can be applied in various biological systems for biotechnology and therapeutic applications.

Data-Driven and in Silico-Assisted Design of Broad Host-Range Minimal Intrinsic Terminators Adapted for Bacteria

Efficient transcription termination relying on intrinsic terminators is critical to maintain cell fitness by avoiding unwanted read-through in bacteria. Natural intrinsic terminator (NIT) typically appears in mRNA as a hairpin followed by approximately eight conserved uridines (U-tract) at the 3' terminus. Owing to their simple structure, small size, and protein independence, assorted NITs have been redesigned as robust tools to construct gene circuits. However, most NITs exert functions to adapt to their physiological requirements rather than the demand for building synthetic gene circuits, rendering uncertain working performance when they are constructed intact in synthetic gene circuits. Here, rather than modifying NITs, we established a data-driven and in silico-assisted (DISA) design framework to forward engineer minimal intrinsic terminators (MITs). By comprehensively analyzing 75 natural intrinsic terminators from Bacillus subtilis, we revealed that two pivotal features, the length of the U-tract and the thermodynamics of the terminator hairpin, were involved in the sequence-activity relationship (SAR) of termination efficiency (TE). As per the SAR, we leveraged DISA to fabricate an array of MITs composed of in silico-assisted designed minimal hairpins and fixed U-tracts. Most of these MITs exhibited high TE in diverse Gram-positive and Gram-negative bacteria. In contrast, the TEs of the NITs were highly varied in different hosts. Moreover, TEs of MITs were flexibly tuned over a wide range by modulating the length of the U-tract. Overall, these results demonstrate an efficient framework to forward design functional and broad host-range terminators independent of tedious and iterative screening of mutagenesis libraries of natural terminators.

Comparison of bias and resolvability in single-cell and single-transcript methods

Single-cell and single-transcript measurement methods have elevated our ability to understand and engineer biological systems. However, defining and comparing performance between methods remains a challenge, in part due to the confounding effects of experimental variability. Here, we propose a generalizable framework for performing multiple methods in parallel using split samples, so that experimental variability is shared between methods. We demonstrate the utility of this framework by performing 12 different methods in parallel to measure the same underlying reference system for cellular response. We compare method performance using quantitative evaluations of bias and resolvability. We attribute differences in method performance to steps along the measurement process such as sample preparation, signal detection, and choice of measurand. Finally, we demonstrate how this framework can be used to benchmark different methods for single-transcript detection. The framework we present here provides a practical way to compare performance of any methods.

Antisense peptide nucleic acid inhibits the growth of KPC-producing Klebsiella pneumoniae strain

Klebsiella pneumoniae causes common and severe hospital- and community-acquired infections with a high incidence of multidrug resistance (MDR) and mortality. In this study, we investigated the ability of the antisense peptide nucleic acids (PNA) conjugated to the (KFF)3K cell-penetrating peptide (CPP) to target the gyrA KPC-producing K. pneumoniae and inhibit bacterial growth in vitro. The inhibitory effect on gyrA gene was evaluated by measuring 16s gene amplification in KPC-producing K. pneumoniae treated with the antisense PNA conjugate. The hemolytic property of the antisense PNA conjugate was accessed toward mice red blood cells. Finally, molecular modeling and dynamics simulations analyses in aqueous solutions were performed to predict the PNA conformation alone in contact with DNA (gyrA gene sequence). PNA was capable of inhibiting bacterial growth at 50 μM, also reducing 16S gene amplification in 96.7%. Besides, PNA presented low hemolytic activity (21.1% hemolysis) at this same concentration. Bioinformatics analysis demonstrated that the structure of the PNA is stable in water without major changes in its secondary structure. The ability of PNA and its conjugated CPP ((KFF)3K) to inhibit bacterial growth demonstrates the potential of this new class of antibacterial agents, encouraging further in vivo studies to confirm its therapeutic efficacy.

Read between the lines: Diversity of non-translational selection pressures on local codon usage

Protein coding genes can contain specific motifs within their nucleotide sequence that function as a signal for various biological pathways. The presence of such sequence motifs within a gene can have beneficial or detrimental effects on the phenotype and fitness of an organism, and this can lead to the enrichment or avoidance of this sequence motif. The degeneracy of the genetic code allows for the existence of alternative synonymous sequences that exclude or include these motifs, while keeping the encoded amino acid sequence intact. This implies that locally, there can be a selective pressure for preferentially using a codon over its synonymous alternative in order to avoid or enrich a specific sequence motif. This selective pressure could -in addition to mutation, drift and selection for translation efficiency and accuracy- contribute to shape the codon usage bias. In this review, we discuss patterns of avoidance of (or enrichment for) the various biological signals contained in specific nucleotide sequence motifs: transcription and translation initiation and termination signals, mRNA maturation signals, and antiviral immune system targets. Experimental data on the phenotypic or fitness effects of synonymous mutations in these sequence motifs confirm that they can be targets of local selection pressures on codon usage. We also formulate the hypothesis that transposable elements could have a similar impact on codon usage through their preferred integration sequences. Overall, selection on codon usage appears to be a combination of a global selection pressure imposed by the translation machinery, and a patchwork of local selection pressures related to biological signals contained in specific sequence motifs.

Engineering Transcriptional Interference through RNA Polymerase Processivity Control

Antisense transcription is widespread in all kingdoms of life and has been shown to influence gene expression through transcriptional interference (TI), a phenomenon in which one transcriptional process negatively influences another in cis. The processivity, or uninterrupted transcription, of an RNA polymerase (RNAP) is closely tied to levels of antisense transcription in bacterial genomes, but its influence on TI, while likely important, is not well-characterized. Here, we show that TI can be tuned through processivity control via three distinct antitermination strategies: the antibiotic bicyclomycin, phage protein Psu, and ribosome-RNAP coupling. We apply these methods toward TI and tune ribosome-RNAP coupling to produce 38-fold transcription-level gene repression due to both RNAP collisions and antisense RNA interference. We then couple protein roadblock and TI to design minimal genetic NAND and NOR logic gates. Together, these results show the importance of processivity control for strong TI and demonstrate TI's potential for synthetic biology.

Hopping and Flipping of RNA Polymerase on DNA during Recycling for Reinitiation after Intrinsic Termination in Bacterial Transcription

Two different molecular mechanisms, sliding and hopping, are employed by DNA-binding proteins for their one-dimensional facilitated diffusion on nonspecific DNA regions until reaching their specific target sequences. While it has been controversial whether RNA polymerases (RNAPs) use one-dimensional diffusion in targeting their promoters for transcription initiation, two recent single-molecule studies discovered that post-terminational RNAPs use one-dimensional diffusion for their reinitiation on the same DNA molecules. Escherichia coli RNAP, after synthesizing and releasing product RNA at intrinsic termination, mostly remains bound on DNA and diffuses in both forward and backward directions for recycling, which facilitates reinitiation on nearby promoters. However, it has remained unsolved which mechanism of one-dimensional diffusion is employed by recycling RNAP between termination and reinitiation. Single-molecule fluorescence measurements in this study reveal that post-terminational RNAPs undergo hopping diffusion during recycling on DNA, as their one-dimensional diffusion coefficients increase with rising salt concentrations. We additionally find that reinitiation can occur on promoters positioned in sense and antisense orientations with comparable efficiencies, so reinitiation efficiency depends primarily on distance rather than direction of recycling diffusion. This additional finding confirms that orientation change or flipping of RNAP with respect to DNA efficiently occurs as expected from hopping diffusion.

Genetic circuit characterization by inferring RNA polymerase movement and ribosome usage

To perform their computational function, genetic circuits change states through a symphony of genetic parts that turn regulator expression on and off. Debugging is frustrated by an inability to characterize parts in the context of the circuit and identify the origins of failures. Here, we take snapshots of a large genetic circuit in different states: RNA-seq is used to visualize circuit function as a changing pattern of RNA polymerase (RNAP) flux along the DNA. Together with ribosome profiling, all 54 genetic parts (promoters, ribozymes, RBSs, terminators) are parameterized and used to inform a mathematical model that can predict circuit performance, dynamics, and robustness. The circuit behaves as designed; however, it is riddled with genetic errors, including cryptic sense/antisense promoters and translation, attenuation, incorrect start codons, and a failed gate. While not impacting the expected Boolean logic, they reduce the prediction accuracy and could lead to failures when the parts are used in other designs. Finally, the cellular power (RNAP and ribosome usage) required to maintain a circuit state is calculated. This work demonstrates the use of a small number of measurements to fully parameterize a regulatory circuit and quantify its impact on host.

The Ongoing Quest to Crack the Genetic Code for Protein Production

Understanding the genetic design principles that determine protein production remains a major challenge. Although the key principles of gene expression were discovered 50 years ago, additional factors are still being uncovered. Both protein-coding and non-coding sequences harbor elements that collectively influence the efficiency of protein production by modulating transcription, mRNA decay, and translation. The influences of many contributing elements are intertwined, which complicates a full understanding of the individual factors. In natural genes, a functional balance between these factors has been obtained in the course of evolution, whereas for genetic-engineering projects, our incomplete understanding still limits optimal design of synthetic genes. However, notable advances have recently been made, supported by high-throughput analysis of synthetic gene libraries as well as by state-of-the-art biomolecular techniques. We discuss here how these advances further strengthen understanding of the gene expression process and how they can be harnessed to optimize protein production.

Comparative transcriptomic analysis of Rickettsia conorii during in vitro infection of human and tick host cells

BACKGROUND

Pathogenic Rickettsia species belonging to the spotted fever group are arthropod-borne, obligate intracellular bacteria which exhibit preferential tropism for host microvascular endothelium in the mammalian hosts, resulting in disease manifestations attributed primarily to endothelial damage or dysfunction. Although rickettsiae are known to undergo evolution through genomic reduction, the mechanisms by which these pathogens regulate their transcriptome to ensure survival in tick vectors and maintenance by transovarial/transstadial transmission, in contrast to their ability to cause debilitating infections in human hosts remain unknown. In this study, we compare the expression profiles of rickettsial sRNAome/transcriptome and determine the transcriptional start sites (TSSs) of R. conorii transcripts during in vitro infection of human and tick host cells.

RESULTS

We performed deep sequencing on total RNA from Amblyomma americanum AAE2 cells and human microvascular endothelial cells (HMECs) infected with R. conorii. Strand-specific RNA sequencing of R. conorii transcripts revealed the expression 32 small RNAs (Rc_sR's), which were preferentially expressed above the limit of detection during tick cell infection, and confirmed the expression of Rc_sR61, sR71, and sR74 by quantitative RT-PCR. Intriguingly, a total of 305 and 132 R. conorii coding genes were differentially upregulated (> 2-fold) in AAE2 cells and HMECs, respectively. Further, enrichment for primary transcripts by treatment with Terminator 5'-Phosphate-dependent Exonuclease resulted in the identification of 3903 and 2555 transcription start sites (TSSs), including 214 and 181 primary TSSs in R. conorii during the infection to tick and human host cells, respectively. Seventy-five coding genes exhibited different TSSs depending on the host environment. Finally, we also observed differential expression of 6S RNA during host-pathogen and vector-pathogen interactions in vitro, implicating an important role for this noncoding RNA in the regulation of rickettsial transcriptome depending on the supportive host niche.

CONCLUSIONS

In sum, the findings of this study authenticate the presence of novel Rc_sR's in R. conorii, reveal the first evidence for differential expression of coding transcripts and utilization of alternate transcriptional start sites depending on the host niche, and implicate a role for 6S RNA in the regulation of coding transcriptome during tripartite host-pathogen-vector interactions.

Are Antisense Proteins in Prokaryotes Functional?

Many prokaryotic RNAs are transcribed from loci outside of annotated protein coding genes. Across bacterial species hundreds of short open reading frames antisense to annotated genes show evidence of both transcription and translation, for instance in ribosome profiling data. Determining the functional fraction of these protein products awaits further research, including insights from studies of molecular interactions and detailed evolutionary analysis. There are multiple lines of evidence, however, that many of these newly discovered proteins are of use to the organism. Condition-specific phenotypes have been characterized for a few. These proteins should be added to genome annotations, and the methods for predicting them standardized. Evolutionary analysis of these typically young sequences also may provide important insights into gene evolution. This research should be prioritized for its exciting potential to uncover large numbers of novel proteins with extremely diverse potential practical uses, including applications in synthetic biology and responding to pathogens.

Precision design of stable genetic circuits carried in highly-insulated E. coli genomic landing pads

Genetic circuits have many applications, from guiding living therapeutics to ordering process in a bioreactor, but to be useful they have to be genetically stable and not hinder the host. Encoding circuits in the genome reduces burden, but this decreases performance and can interfere with native transcription. We have designed genomic landing pads in Escherichia coli at high-expression sites, flanked by ultrastrong double terminators. DNA payloads >8 kb are targeted to the landing pads using phage integrases. One landing pad is dedicated to carrying a sensor array, and two are used to carry genetic circuits. NOT/NOR gates based on repressors are optimized for the genome and characterized in the landing pads. These data are used, in conjunction with design automation software (Cello 2.0), to design circuits that perform quantitatively as predicted. These circuits require fourfold less RNA polymerase than when carried on a plasmid and are stable for weeks in a recA+ strain without selection. This approach enables the design of synthetic regulatory networks to guide cells in environments or for applications where plasmid use is infeasible.

Universal Actuator for Efficient Silencing of Escherichia coli Genes Based on Convergent Transcription Resistant to Rho-Dependent Termination

Dynamic control is a distinguished strategy in modern metabolic engineering, in which inducible convergent transcription is an attractive approach for conditional gene silencing. Instead of a simple strong "reverse" (r-) promoter, a three-component actuator has been developed for constitutive genes silencing. These actuators, consisting of r-promoters with different strengths, the ribosomal transcription antitermination-inducing sequence rrnG-AT, and the RNase III processing site, were inserted into the 3'-UTR of three E. coli metabolic genes. Second and third actuator components were important to improve the effectiveness and robustness of the approach. The maximal silencing folds achieved for gltA, pgi, and ppc were approximately 7, 11, and >100, respectively. Data were analyzed using a simple model that considered RNA polymerase (RNAP) head-on collisions as the unique reason for gene silencing and continued transcription after collision with only one of two molecules. It was previously established that forward (f-) RNAP with a trailing ribosome was approximately 13-times more likely to continue transcription after head-on collision than untrailed r-RNAP which is sensitive to Rho-dependent transcription termination (RhoTT). According to the current results, this bias in complex stabilities decreased to no more than (3.0-5.7)-fold if r-RNAP became resistant to RhoTT. Therefore, the developed constitutive actuator could be considered as an improved tool for controlled gene expression mainly due to the transfer of r-transcription into a state that is resistant to potential termination and used as the basis for the design of tightly regulated actuators for the achievement of conditional silencing.

Sense-antisense miRNA pairs constitute an elaborate reciprocal regulatory circuit

Antisense transcription of protein-coding genes has been increasingly recognized as an important regulatory mechanism of gene expression. However, less is known about the extent and importance of antisense transcription of noncoding genes. Here, we investigate the breadth and dynamics of antisense transcription of miRNAs, a class of important noncoding RNAs. Because the antisense transcript of a miRNA is likely to form a hairpin suitable as the substrate of ADARs, which convert adenosine to inosine in double-stranded RNAs, we used A-to-I RNA editing as ultrasensitive readout for antisense transcription of the miRNAs. Through examining the unstranded targeted RNA-seq libraries covering all miRNA loci in 25 types of human tissues, we identified 7275 editing events located in 81% of the antisense strand of the miRNA loci, thus uncovering the previously unknown prevalent antisense transcription of the miRNAs. We found that antisense transcripts are tightly regulated, and a substantial fraction of miRNAs and their antisense transcripts are coexpressed. Sense miRNAs have been shown to down-regulate the coexpressed antisense transcripts, whereas the act of antisense transcription, rather than the transcripts themselves, regulates the expression of sense miRNAs. RNA editing tends to decrease the miRNA accessibility of the antisense transcripts, therefore protecting them from being degraded by the sense-mature miRNAs. Altogether, our study reveals the landscape of antisense transcription and editing of miRNAs, as well as a previously unknown reciprocal regulatory circuit of sense-antisense miRNA pairs.

Prevalence of small base-pairing RNAs derived from diverse genomic loci

Small RNAs (sRNAs) that act by base-pairing have been shown to play important roles in fine-tuning the levels and translation of their target transcripts across a variety of model and pathogenic organisms. Work from many different groups in a wide range of bacterial species has provided evidence for the importance and complexity of sRNA regulatory networks, which allow bacteria to quickly respond to changes in their environment. However, despite the expansive literature, much remains to be learned about all aspects of sRNA-mediated regulation, particularly in bacteria beyond the well-characterized Escherichia coli and Salmonella enterica species. Here we discuss what is known, and what remains to be learned, about the identification of regulatory base-pairing RNAs produced from diverse genomic loci including how their expression is regulated. This article is part of a Special Issue entitled: RNA and gene control in bacteria edited by Dr. M. Guillier and F. Repoila.

Programming Escherichia coli to function as a digital display

Synthetic genetic circuits offer the potential to wield computational control over biology, but their complexity is limited by the accuracy of mathematical models. Here, we present advances that enable the complete encoding of an electronic chip in the DNA carried by Escherichia coli (E. coli). The chip is a binary-coded digit (BCD) to 7-segment decoder, associated with clocks and calculators, to turn on segments to visualize 0-9. Design automation is used to build seven strains, each of which contains a circuit with up to 12 repressors and two activators (totaling 63 regulators and 76,000 bp DNA). The inputs to each circuit represent the digit to be displayed (encoded in binary by four molecules), and output is the segment state, reported as fluorescence. Implementation requires an advanced gate model that captures dynamics, promoter interference, and a measure of total power usage (RNAP flux). This project is an exemplar of design automation pushing engineering beyond that achievable "by hand", essential for realizing the potential of biology.

A minimum set of regulators to thrive in the ocean

Marine cyanobacteria of the genus Prochlorococcus thrive in high cell numbers throughout the euphotic zones of the world's subtropical and tropical oligotrophic oceans, making them some of the most ecologically relevant photosynthetic microorganisms on Earth. The ecological success of these free-living phototrophs suggests that they are equipped with a regulatory system competent to address many different stress situations. However, Prochlorococcus genomes are compact and streamlined, with the majority encoding only five different sigma factors, five to six two-component systems and eight types of other transcriptional regulators. Here, we summarize the existing information about the functions of these protein regulators, about transcriptomic responses to defined stress conditions, and discuss the current knowledge about riboswitches, RNA-based regulation and the roles of certain metabolites as co-regulators. We focus on the best-studied isolate, Prochlorococcus MED4, but extend to other strains and ecotypes when appropriate, and we include some information gained from metagenomic and metatranscriptomic analyses.

Alternative transcription cycle for bacterial RNA polymerase

RNA polymerases (RNAPs) transcribe genes through a cycle of recruitment to promoter DNA, initiation, elongation, and termination. After termination, RNAP is thought to initiate the next round of transcription by detaching from DNA and rebinding a new promoter. Here we use single-molecule fluorescence microscopy to observe individual RNAP molecules after transcript release at a terminator. Following termination, RNAP almost always remains bound to DNA and sometimes exhibits one-dimensional sliding over thousands of basepairs. Unexpectedly, the DNA-bound RNAP often restarts transcription, usually in reverse direction, thus producing an antisense transcript. Furthermore, we report evidence of this secondary initiation in live cells, using genome-wide RNA sequencing. These findings reveal an alternative transcription cycle that allows RNAP to reinitiate without dissociating from DNA, which is likely to have important implications for gene regulation.

Synthetic Biology Enables Programmable Cell-Based Biosensors

Cell-based biosensors offer cheap, portable and simple methods of detecting molecules of interest but have yet to be truly adopted commercially. Issues with their performance and specificity initially slowed the development of cell-based biosensors. With the development of rational approaches to tune response curves, the performance of biosensors has rapidly improved and there are now many biosensors capable of sensing with the required performance. This has stimulated an increased interest in biosensors and their commercial potential. However the reliability, long term stability and biosecurity of these sensors are still barriers to commercial application and public acceptance. Research into overcoming these issues remains active. Here we present the state-of-the-art tools offered by synthetic biology to allow construction of cell-based biosensors with customisable performance to meet the real world requirements in terms of sensitivity and dynamic range and discuss the research progress to overcome the challenges in terms of the sensor stability and biosecurity fears.

Synthetic metabolic computation in a bioluminescence-sensing system

Bioluminescence is visible light produced and emitted by living cells using various biological systems (e.g. luxCDABE cassette). Today, this phenomenon is widely exploited in biological research, biotechnology and medical applications as a quantitative technique for the detection of biological signals. However, this technique has mostly been used to detect a single input only. In this work, we re-engineered the complex genetic structure of luxCDABE cassette to build a biological unit that can detect multi-inputs, process the cellular information and report the computation results. We first split the luxCDABE operon into several parts to create a genetic circuit that can compute a soft minimum in living cells. Then, we used the new design to implement an AND logic function with better performance as compared to AND logic functions based on protein-protein interactions. Furthermore, by controlling the reverse reaction of the luxCDABE cassette independently from the forward reaction, we built a comparator with a programmable detection threshold. Finally, we applied the redesigned cassette to build an incoherent feedforward loop that reduced the unwanted crosstalk between stress-responsive promoters (recA, katG). This work demonstrates the construction of genetic circuits that combine regulations of gene expression with metabolic pathways, for sensing and computing in living cells.

Simultaneous repression of multiple bacterial genes using nonrepetitive extra-long sgRNA arrays

Engineering cellular phenotypes often requires the regulation of many genes. When using CRISPR interference, coexpressing many single-guide RNAs (sgRNAs) triggers genetic instability and phenotype loss, due to the presence of repetitive DNA sequences. We stably coexpressed 22 sgRNAs within nonrepetitive extra-long sgRNA arrays (ELSAs) to simultaneously repress up to 13 genes by up to 3,500-fold. We applied biophysical modeling, biochemical characterization and machine learning to develop toolboxes of nonrepetitive genetic parts, including 28 sgRNA handles that bind Cas9. We designed ELSAs by combining nonrepetitive genetic parts according to algorithmic rules quantifying DNA synthesis complexity, sgRNA expression, sgRNA targeting and genetic stability. Using ELSAs, we created three highly selective phenotypes in Escherichia coli, including redirecting metabolism to increase succinic acid production by 150-fold, knocking down amino acid biosynthesis to create a multi-auxotrophic strain and repressing stress responses to reduce persister cell formation by 21-fold. ELSAs enable simultaneous and stable regulation of many genes for metabolic engineering and synthetic biology applications.