Beyond membrane permeability: A role for the small RNA MicF in regulation of chromosome replication and partitioning.

Small regulatory RNAs (sRNA) have been shown to play a large role in the management of stress responses in Escherichia coli and other bacteria. sRNAs act post-transcriptionally on target mRNA through an imperfect base pairing mechanism to regulate downstream protein expression. The imperfect base pairing allows a single sRNA to bind and regulate a variety mRNA targets which can form intricate regulatory networks that connect different physiological processes for the cell's response. Upon exposure to antimicrobials and superoxide generating agents, the MicF sRNA in E. coli has been shown to regulate a small set of genes involved in the management of membrane permeability. Currently, it is unknown whether MicF acts on other processes to mediate the response to these agents. Using an sRNA interaction prediction tool, we identified genes in E. coli that are potentially regulated by MicF. Through subsequent analysis using a sfGFP-based reporter-gene fusion, we have validated two novel targets of MicF regulation: SeqA, a negative modulator of DNA replication, and ObgE, a GTPase crucial for chromosome partitioning. Importantly, the interaction between MicF and these target mRNAs is contingent upon the presence of the RNA chaperone protein, Hfq. Furthermore, our findings affirm the role of MicF's conserved 5' seed pairing region in initiating these regulatory interactions. Our study suggests that, beyond its established role in membrane permeability management, MicF exerts control over chromosome dynamics in response to distinct environmental cues, implicating a more multifaceted regulatory function in bacterial stress adaptation.

Identifying Antisense Oligonucleotides to Disrupt Small RNA Regulated Antibiotic Resistance via a Cell-Free Transcription-Translation Platform.

Bacterial small RNAs (sRNAs) regulate many important physiological processes in cells, including antibiotic resistance and virulence genes, through base-pairing interactions with mRNAs. Antisense oligonucleotides (ASOs) have great potential as therapeutics against bacterial pathogens by targeting sRNAs such as MicF, which regulates outer membrane protein OmpF expression and limits the permeability of antibiotics. Here we devised a cell-free transcription-translation (TX-TL) assay to identify ASO designs that sufficiently sequester MicF. ASOs were then ordered as peptide nucleic acids conjugated to cell-penetrating peptides (CPP-PNA) to allow for effective delivery into bacteria. Subsequent minimum inhibitory concentration (MIC) assays demonstrated that simultaneously targeting the regions of MicF responsible for sequestering the start codon and the Shine-Dalgarno sequence of ompF with two different CPP-PNAs synergistically reduced the MIC for a set of antibiotics. This investigation offers a TX-TL-based approach to identify novel therapeutic candidates to combat intrinsic sRNA-mediated antibiotic resistance mechanisms.

Identifying antisense oligonucleotides to disrupt small RNA regulated antibiotic resistance via a cell-free transcription-translation platform.

Bacterial small RNAs (sRNAs) regulate many important physiological processes in cells including antibiotic resistance and virulence genes through base pairing interactions with mRNAs. Antisense oligonucleotides (ASOs) have great potential as therapeutics against bacterial pathogens by targeting sRNAs such as MicF, which regulates outer membrane protein OmpF expression and limits permeability of antibiotics. Here, we devise a cell-free transcription-translation (TX-TL) assay to identify ASO designs that sufficiently sequester MicF. ASOs were then ordered as peptide nucleic acids conjugated to cell-penetrating peptides (CPP-PNA) to allow for effective delivery into bacteria. Subsequent minimum inhibitory concentration (MIC) assays demonstrated that simultaneously targeting the regions of MicF responsible for sequestering the start codon and the Shine-Dalgarno sequence of ompF with two different CPP-PNAs synergistically reduced the MIC for a set of antibiotics. This investigation offers a TX-TL based approach to identify novel therapeutic candidates to combat intrinsic sRNA-mediated antibiotic resistance mechanisms.

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.

Cell-Free Paper-Based Analysis of Gut Microbiota and Host Biomarkers.

The gut microbiome and its interactions with the host have been shown to affect several aspects of human health and disease. Investigations to elucidate these mechanisms typically involve sequence analysis of fecal samples. To support these studies, we present methods to design RNA toehold switch sensors to detect microbial and host transcripts. The sensors are embedded in paper-based, cell-free reactions that enable affordable and rapid analysis of microbiome samples.

Towards detection of SARS-CoV-2 RNA in human saliva: A paper-based cell-free toehold switch biosensor with a visual bioluminescent output.

The COVID-19 pandemic has illustrated the global demand for rapid, low-cost, widely distributable and point-of-care nucleic acid diagnostic technologies. Such technologies could help disrupt transmission, sustain economies and preserve health and lives during widespread infection. In contrast, conventional nucleic acid diagnostic procedures require trained personnel, complex laboratories, expensive equipment, and protracted processing times. In this work, lyophilized cell-free protein synthesis (CFPS) and toehold switch riboregulators are employed to develop a promising paper-based nucleic acid diagnostic platform activated simply by the addition of saliva. First, to facilitate distribution and deployment, an economical paper support matrix is identified and a mass-producible test cassette designed with integral saliva sample receptacles. Next, CFPS is optimized in the presence of saliva using murine RNase inhibitor. Finally, original toehold switch riboregulators are engineered to express the bioluminescent reporter NanoLuc in response to SARS-CoV-2 RNA sequences present in saliva samples. The biosensor generates a visible signal in as few as seven minutes following administration of 15 µL saliva enriched with high concentrations of SARS-CoV-2 RNA sequences. The estimated cost of this test is less than 0.50 USD, which could make this platform readily accessible to both the developed and developing world. While additional research is needed to decrease the limit of detection, this work represents important progress toward developing a diagnostic technology that is rapid, low-cost, distributable and deployable at the point-of-care by a layperson.

Bacterial metabolic state more accurately predicts antibiotic lethality than growth rate.

Growth rate and metabolic state of bacteria have been separately shown to affect antibiotic efficacy1-3. However, the two are interrelated as bacterial growth inherently imposes a metabolic burden4; thus, determining individual contributions from each is challenging5,6. Indeed, faster growth is often correlated with increased antibiotic efficacy7,8; however, the concurrent role of metabolism in that relationship has not been well characterized. As a result, a clear understanding of the interdependence between growth and metabolism, and their implications for antibiotic efficacy, are lacking9. Here, we measured growth and metabolism in parallel across a broad range of coupled and uncoupled conditions to determine their relative contribution to antibiotic lethality. We show that when growth and metabolism are uncoupled, antibiotic lethality uniformly depends on the bacterial metabolic state at the time of treatment, rather than growth rate. We further reveal a critical metabolic threshold below which antibiotic lethality is negligible. These findings were general for a wide range of conditions, including nine representative bactericidal drugs and a diverse range of Gram-positive and Gram-negative species (Escherichia coli, Acinetobacter baumannii and Staphylococcus aureus). This study provides a cohesive metabolic-dependent basis for antibiotic-mediated cell death, with implications for current treatment strategies and future drug development.

BioBits™ Explorer: A modular synthetic biology education kit.

Hands-on demonstrations greatly enhance the teaching of science, technology, engineering, and mathematics (STEM) concepts and foster engagement and exploration in the sciences. While numerous chemistry and physics classroom demonstrations exist, few biology demonstrations are practical and accessible due to the challenges and concerns of growing living cells in classrooms. We introduce BioBits™ Explorer, a synthetic biology educational kit based on shelf-stable, freeze-dried, cell-free (FD-CF) reactions, which are activated by simply adding water. The FD-CF reactions engage the senses of sight, smell, and touch with outputs that produce fluorescence, fragrances, and hydrogels, respectively. We introduce components that can teach tunable protein expression, enzymatic reactions, biomaterial formation, and biosensors using RNA switches, some of which represent original FD-CF outputs that expand the toolbox of cell-free synthetic biology. The BioBits™ Explorer kit enables hands-on demonstrations of cutting-edge science that are inexpensive and easy to use, circumventing many current barriers for implementing exploratory biology experiments in classrooms.

A low-cost paper-based synthetic biology platform for analyzing gut microbiota and host biomarkers.

There is a need for large-scale, longitudinal studies to determine the mechanisms by which the gut microbiome and its interactions with the host affect human health and disease. Current methods for profiling the microbiome typically utilize next-generation sequencing applications that are expensive, slow, and complex. Here, we present a synthetic biology platform for affordable, on-demand, and simple analysis of microbiome samples using RNA toehold switch sensors in paper-based, cell-free reactions. We demonstrate species-specific detection of mRNAs from 10 different bacteria that affect human health and four clinically relevant host biomarkers. We develop a method to quantify mRNA using our toehold sensors and validate our platform on clinical stool samples by comparison to RT-qPCR. We further highlight the potential clinical utility of the platform by showing that it can be used to rapidly and inexpensively detect toxin mRNA in the diagnosis of Clostridium difficile infections.

Engineering a Functional Small RNA Negative Autoregulation Network with Model-Guided Design.

RNA regulators are powerful components of the synthetic biology toolbox. Here, we expand the repertoire of synthetic gene networks built from these regulators by constructing a transcriptional negative autoregulation (NAR) network out of small RNAs (sRNAs). NAR network motifs are core motifs of natural genetic networks, and are known for reducing network response time and steady state signal. Here we use cell-free transcription-translation (TX-TL) reactions and a computational model to design and prototype sRNA NAR constructs. Using parameter sensitivity analysis, we design a simple set of experiments that allow us to accurately predict NAR function in TX-TL. We transfer successful network designs into Escherichia coli and show that our sRNA transcriptional network reduces both network response time and steady-state gene expression. This work broadens our ability to construct increasingly sophisticated RNA genetic networks with predictable function.

Rapid, Low-Cost Detection of Zika Virus Using Programmable Biomolecular Components.

The recent Zika virus outbreak highlights the need for low-cost diagnostics that can be rapidly developed for distribution and use in pandemic regions. Here, we report a pipeline for the rapid design, assembly, and validation of cell-free, paper-based sensors for the detection of the Zika virus RNA genome. By linking isothermal RNA amplification to toehold switch RNA sensors, we detect clinically relevant concentrations of Zika virus sequences and demonstrate specificity against closely related Dengue virus sequences. When coupled with a novel CRISPR/Cas9-based module, our sensors can discriminate between viral strains with single-base resolution. We successfully demonstrate a simple, field-ready sample-processing workflow and detect Zika virus from the plasma of a viremic macaque. Our freeze-dried biomolecular platform resolves important practical limitations to the deployment of molecular diagnostics in the field and demonstrates how synthetic biology can be used to develop diagnostic tools for confronting global health crises. PAPERCLIP.

Using in-cell SHAPE-Seq and simulations to probe structure-function design principles of RNA transcriptional regulators.

Antisense RNA-mediated transcriptional regulators are powerful tools for controlling gene expression and creating synthetic gene networks. RNA transcriptional repressors derived from natural mechanisms called attenuators are particularly versatile, though their mechanistic complexity has made them difficult to engineer. Here we identify a new structure-function design principle for attenuators that enables the forward engineering of new RNA transcriptional repressors. Using in-cell SHAPE-Seq to characterize the structures of attenuator variants within Escherichia coli, we show that attenuator hairpins that facilitate interaction with antisense RNAs require interior loops for proper function. Molecular dynamics simulations of these attenuator variants suggest these interior loops impart structural flexibility. We further observe hairpin flexibility in the cellular structures of natural RNA mechanisms that use antisense RNA interactions to repress translation, confirming earlier results from in vitro studies. Finally, we design new transcriptional attenuators in silico using an interior loop as a structural requirement and show that they function as desired in vivo. This work establishes interior loops as an important structural element for designing synthetic RNA gene regulators. We anticipate that the coupling of experimental measurement of cellular RNA structure and function with computational modeling will enable rapid discovery of structure-function design principles for a diverse array of natural and synthetic RNA regulators.

A renaissance in RNA synthetic biology: new mechanisms, applications and tools for the future.

Since our ability to engineer biological systems is directly related to our ability to control gene expression, a central focus of synthetic biology has been to develop programmable genetic regulatory systems. Researchers are increasingly turning to RNA regulators for this task because of their versatility, and the emergence of new powerful RNA design principles. Here we review advances that are transforming the way we use RNAs to engineer biological systems. First, we examine new designable RNA mechanisms that are enabling large libraries of regulators with protein-like dynamic ranges. Next, we review emerging applications, from RNA genetic circuits to molecular diagnostics. Finally, we describe new experimental and computational tools that promise to accelerate our understanding of RNA folding, function and design.

Characterizing and prototyping genetic networks with cell-free transcription-translation reactions.

A central goal of synthetic biology is to engineer cellular behavior by engineering synthetic gene networks for a variety of biotechnology and medical applications. The process of engineering gene networks often involves an iterative 'design-build-test' cycle, whereby the parts and connections that make up the network are built, characterized and varied until the desired network function is reached. Many advances have been made in the design and build portions of this cycle. However, the slow process of in vivo characterization of network function often limits the timescale of the testing step. Cell-free transcription-translation (TX-TL) systems offer a simple and fast alternative to performing these characterizations in cells. Here we provide an overview of a cell-free TX-TL system that utilizes the native Escherichia coli TX-TL machinery, thereby allowing a large repertoire of parts and networks to be characterized. As a way to demonstrate the utility of cell-free TX-TL, we illustrate the characterization of two genetic networks: an RNA transcriptional cascade and a protein regulated incoherent feed-forward loop. We also provide guidelines for designing TX-TL experiments to characterize new genetic networks. We end with a discussion of current and emerging applications of cell free systems.

Creating small transcription activating RNAs.

We expanded the mechanistic capability of small RNAs by creating an entirely synthetic mode of regulation: small transcription activating RNAs (STARs). Using two strategies, we engineered synthetic STAR regulators to disrupt the formation of an intrinsic transcription terminator placed upstream of a gene in Escherichia coli. This resulted in a group of four highly orthogonal STARs that had up to 94-fold activation. By systematically modifying sequence features of this group, we derived design principles for STAR function, which we then used to forward engineer a STAR that targets a terminator found in the Escherichia coli genome. Finally, we showed that STARs could be combined in tandem to create previously unattainable RNA-only transcriptional logic gates. STARs provide a new mechanism of regulation that will expand our ability to use small RNAs to construct synthetic gene networks that precisely control gene expression.

Rapidly characterizing the fast dynamics of RNA genetic circuitry with cell-free transcription-translation (TX-TL) systems.

RNA regulators are emerging as powerful tools to engineer synthetic genetic networks or rewire existing ones. A potential strength of RNA networks is that they may be able to propagate signals on time scales that are set by the fast degradation rates of RNAs. However, a current bottleneck to verifying this potential is the slow design-build-test cycle of evaluating these networks in vivo. Here, we adapt an Escherichia coli-based cell-free transcription-translation (TX-TL) system for rapidly prototyping RNA networks. We used this system to measure the response time of an RNA transcription cascade to be approximately five minutes per step of the cascade. We also show that this response time can be adjusted with temperature and regulator threshold tuning. Finally, we use TX-TL to prototype a new RNA network, an RNA single input module, and show that this network temporally stages the expression of two genes in vivo.

The centrality of RNA for engineering gene expression.

Synthetic biology holds promise as both a framework for rationally engineering biological systems and a way to revolutionize how we fundamentally understand them. Essential to realizing this promise is the development of strategies and tools to reliably and predictably control and characterize sophisticated patterns of gene expression. Here we review the role that RNA can play towards this goal and make a case for why this versatile, designable, and increasingly characterizable molecule is one of the most powerful substrates for engineering gene expression at our disposal. We discuss current natural and synthetic RNA regulators of gene expression acting at key points of control--transcription, mRNA degradation, and translation. We also consider RNA structural probing and computational RNA structure predication tools as a way to study RNA structure and ultimately function. Finally, we discuss how next-generation sequencing methods are being applied to the study of RNA and to the characterization of RNA's many properties throughout the cell.

A modular strategy for engineering orthogonal chimeric RNA transcription regulators.

Antisense RNA transcription attenuators are a key component of the synthetic biology toolbox, with their ability to serve as building blocks for both signal integration logic circuits and transcriptional cascades. However, a central challenge to building more sophisticated RNA genetic circuitry is creating larger families of orthogonal attenuators that function independently of each other. Here, we overcome this challenge by developing a modular strategy to create chimeric fusions between the engineered transcriptional attenuator from plasmid pT181 and natural antisense RNA translational regulators. Using in vivo gene expression assays in Escherichia coli, we demonstrate our ability to create chimeric attenuators by fusing sequences from five different translational regulators. Mutagenesis of these functional attenuators allowed us to create a total of 11 new chimeric attenutaors. A comprehensive orthogonality test of these culminated in a 7 × 7 matrix of mutually orthogonal regulators. A comparison between all chimeras tested led to design principles that will facilitate further engineering of orthogonal RNA transcription regulators, and may help elucidate general principles of non-coding RNA regulation. We anticipate that our strategy will accelerate the development of even larger families of orthogonal RNA transcription regulators, and thus create breakthroughs in our ability to construct increasingly sophisticated RNA genetic circuitry.