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Cotranscriptionally encoded RNA strand displacement (ctRSD) circuits are an emerging tool for programmable molecular computation with potential applications spanningin vitrodiagnostics to continuous computation inside living cells. In ctRSD circuits, RNA strand displacement components are continuously produced togetherviatranscription. These RNA components can be rationally programmed through base pairing interactions to execute logic and signaling cascades. However, the small number of ctRSD components characterized to date limits circuit size and capabilities. Here, we characterize 220 ctRSD gate sequences, exploring different input, output, and toehold sequences and changes to other design parameters, including domain lengths, ribozyme sequences, and the order in which gate strands are transcribed. This characterization provides a library of sequence domains for engineering ctRSD components,i.e., a toolkit, enabling circuits with up to four-fold more inputs than previously possible. We also identify specific failure modes and systematically develop design approaches that reduce the likelihood of failure across different gate sequences. Lastly, we show ctRSD gate design is robust to changes in transcriptional encoding, opening a broad design space for applications in more complex environments. Together, these results deliver an expanded toolkit and design approaches for building ctRSD circuits that will dramatically extend capabilities and potential applications.

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., Rammohan et al. propose a generalizable framework for performing multiple methods in parallel using split samples, so that experimental variability is defined and compared between methods. Their framework provides a practical solution for benchmarking and comparing the performance of any method, illustrated by analysing single-cell and single-transcript methods.

Precise engineering of biological systems requires quantitative, high-throughput measurements, exemplified by progress in directed evolution. New approaches allow high-throughput measurements of phenotypes and their corresponding genotypes. When integrated into directed evolution, these quantitative approaches enable the precise engineering of biological function. At the same time, the increasingly routine availability of large, high-quality data sets supports the integration of machine learning with directed evolution. Together, these advances herald striking capabilities for engineering biology.

Genomically minimal cells, such as JCVI-syn3.0 and JCVI-syn3A, offer an empowering framework to study relationships between genotype and phenotype. With a polygenic basis, the fundamental physiological process of cell division depends on multiple genes of known and unknown function in JCVI-syn3A. A physical description of cellular mechanics can further understanding of the contributions of genes to cell division in this genomically minimal context. We review current knowledge on genes in JCVI-syn3A contributing to two physical parameters relevant to cell division, namely, the surface-area-to-volume ratio and membrane curvature. This physical view of JCVI-syn3A may inform the attribution of gene functions and conserved processes in bacterial physiology, as well as whole-cell models and the engineering of synthetic cells.

DNA templates for protein production remain an unexplored source of variability in the performance of cell-free expression (CFE) systems. To characterize this variability, we investigated the effects of two common DNA extraction methodologies, a postprocessing step and manual versus automated preparation on protein production using CFE. We assess the concentration of the DNA template, the quality of the DNA template in terms of physical damage and the quality of the DNA solution in terms of purity resulting from eight DNA preparation workflows. We measure the variance in protein titer and rate of protein production in CFE reactions associated with the biological replicate of the DNA template, the technical replicate DNA solution prepared with the same workflow and the measurement replicate of nominally identical CFE reactions. We offer practical guidance for preparing and characterizing DNA templates to achieve acceptable variability in CFE performance.

Performance variability is a common challenge in cell-free protein production and hinders a wider adoption of these systems for both research and biomanufacturing. While the inherent stochasticity and complexity of biology likely contributes to variability, other systematic factors may also play a role, including the source and preparation of the cell extract, the composition of the supplemental reaction buffer, the facility at which experiments are conducted, and the human operator (Cole et al. ACS Synth Biol 8:2080-2091, 2019). Variability in protein production could also arise from differences in the DNA template-specifically the amount of functional DNA added to a cell-free reaction and the quality of the DNA preparation in terms of contaminants and strand breakage. Here, we present protocols and suggest best practices optimized for DNA template preparation and quantitation for cell-free systems toward reducing variability in cell-free protein production.

Engineered molecular circuits that process information in biological systems could address emerging human health and biomanufacturing needs. However, such circuits can be difficult to rationally design and scale. DNA-based strand displacement reactions have demonstrated the largest and most computationally powerful molecular circuits to date but are limited in biological systems due to the difficulty in genetically encoding components. Here, we develop scalable co-transcriptional RNA strand displacement (ctRSD) circuits that are rationally programmed via base pairing interactions. ctRSD addresses the limitations of DNA-based strand displacement circuits by isothermally producing circuit components via transcription. We demonstrate the programmability of ctRSD in vitro by implementing logic and amplification elements, and multi-layer signaling cascades. Further, we show ctRSD kinetics are accurately predicted by a simple model of coupled transcription and strand displacement, enabling model-driven design. We envision ctRSD will enable rational design of powerful molecular circuits that operate in biological systems, including living cells.

Cell-free gene expression (CFE) emerged as an alternative approach to living cells for specific applications in protein synthesis and labelling for structural biology and proteomics studies. CFE has since been repurposed as a versatile technology for synthetic biology and bioengineering. However, taking full advantage of this technology requires in-depth understanding of its fundamental workflow beyond existing protocols. This Primer provides new practitioners with a comprehensive, detailed and actionable guide to best practices in CFE, to inform research in the laboratory at the state of the art. We focus on Escherichia coli-based CFE systems, which remain the primary platform for efficient CFE. Producing proteins, biomanufacturing therapeutics, developing sensors and prototyping genetic circuits illustrate the broader utility and opportunities provided by this practical introduction to CFE. With its extensive functionality and portability, CFE is becoming a powerful and enabling research tool for biotechnology. Cell-free gene expression is useful for expressing proteins with post-translational modifications, with special folding requirements and whose expression is difficult in prokaryotic systems. Garenne et al. outline the best practices for the expression of proteins in a cell-free environment.

Genome-scale engineering holds great potential to impact science, industry, medicine, and society, and recent improvements in DNA synthesis have enabled the manipulation of megabase genomes. However, coordinating and integrating the workflows and large teams necessary for gigabase genome engineering remains a considerable challenge. We examine this issue and recommend a path forward by: 1) adopting and extending existing representations for designs, assembly plans, samples, data, and workflows; 2) developing new technologies for data curation and quality control; 3) conducting fundamental research on genome-scale modeling and design; and 4) developing new legal and contractual infrastructure to facilitate collaboration., Genome-scale engineering requires the integration of a wide range of in silico and in vivo technologies, as well data management procedures and legal infrastructure. Here the authors provide a list of recommendations to address these challenges.

Recent advances in non-equilibrium statistical mechanics and single-molecule measurements have enabled the determination of equilibrium free energies from non-equilibrium work measurements for fluctuating systems ranging from biological molecules to quantum oscillators. However, for many important non-equilibrium processes, it is difficult or impossible to apply and measure the work required to drive the system through the relevant conformational changes. Here, we show that it is possible, with an appropriate extrapolation to infinite temporal scale and zero spatial scale, to determine equilibrium free energies, without work measurement, by analysing the stochastic trajectories of single biomolecules or other nanoscale, fluctuating systems as they spontaneously relax from a non-equilibrium initial state. We validate the method with simulations and demonstrate its application by determining the free-energy profile for DNA molecules in a structured nanofluidic environment with an experimental protocol that mimics many natural processes with energy injection followed by thermal relaxation.

This article reports a process for rapidly prototyping nanofluidic devices, particularly those comprising slits with microscale widths and nanoscale depths, in silicone. This process consists of designing a nanofluidic device, fabricating a photomask, fabricating a device mold in epoxy photoresist, molding a device in silicone, cutting and punching a molded silicone device, bonding a silicone device to a glass substrate, and filling the device with aqueous solution. By using a bilayer of hard and soft silicone, we have formed and filled nanofluidic slits with depths of less than 400 nm and aspect ratios of width to depth exceeding 250 without collapse of the slits. An important attribute of this article is that the description of this rapid prototyping process is very comprehensive, presenting context and details which are highly relevant to the rational implementation and reliable repetition of the process. Moreover, this process makes use of equipment commonly found in nanofabrication facilities and research laboratories, facilitating the broad adaptation and application of the process. Therefore, while this article specifically informs users of the Center for Nanoscale Science and Technology (CNST) at the National Institute of Standards and Technology (NIST), we anticipate that this information will be generally useful for the nanofabrication and nanofluidics research communities at large, and particularly useful for neophyte nanofabricators and nanofluidicists.

There has been much interest in the dimensional properties of double-stranded DNA (dsDNA) confined to nanoscale environments as a problem of fundamental importance in both biological and technological fields. This has led to a series of measurements by fluorescence microscopy of single dsDNA molecules under confinement to nanofluidic slits. Despite the efforts expended on such experiments and the corresponding theory and simulations of confined polymers, a consistent description of changes of the radius of gyration of dsDNA under strong confinement has not yet emerged. Here, we perform molecular dynamics (MD) simulations to identify relevant factors that might account for this inconsistency. Our simulations indicate a significant amplification of excluded volume interactions under confinement at the nanoscale due to the reduction of the effective dimensionality of the system. Thus, any factor influencing the excluded volume interaction of dsDNA, such as ionic strength, solution chemistry, and even fluorescent labels, can greatly influence the dsDNA size under strong confinement. These factors, which are normally less important in bulk solutions of dsDNA at moderate ionic strengths because of the relative weakness of the excluded volume interaction, must therefore be under tight control to achieve reproducible measurements of dsDNA under conditions of dimensional reduction. By simulating semi-flexible polymers over a range of parameter values relevant to the experimental systems and exploiting past theoretical treatments of the dimensional variation of swelling exponents and prefactors, we have developed a novel predictive relationship for the in-plane radius of gyration of long semi-flexible polymers under slit-like confinement. Importantly, these analytic expressions allow us to estimate the properties of dsDNA for the experimentally and biologically relevant range of contour lengths that is not currently accessible by state-of-the-art MD simulations.

Gradient elution isotachophoresis (GEITP) was demonstrated for DNA purification, concentration, and quantification from crude samples, represented here by soiled buccal swabs, with minimal sample preparation prior to human identification using STR analysis. During GEITP, an electric field applied across leading and trailing electrolyte solutions resulted in isotachophoretic focusing of DNA at the interface between these solutions, while a pressure-driven counterflow controlled the movement of the interface from the sample reservoir into a microfluidic capillary. This counterflow also prevented particulates from fouling or clogging the capillary and reduced or eliminated contamination of the delivered DNA by PCR inhibitors. On-line DNA quantification using laser-induced fluorescence compared favorably with quantitative PCR measurements and potentially eliminates the need for quantitative PCR prior to STR analysis. GEITP promises to address the need for a rapid and robust method to deliver DNA from crude samples to aid the forensic community in human identification.

Designing and building a minimal genome A goal in biology is to understand the molecular and biological function of every gene in a cell. One way to approach this is to build a minimal genome that includes only the genes essential for life. In 2010, a 1079-kb genome based on the genome of Mycoplasma mycoides (JCV-syn1.0) was chemically synthesized and supported cell growth when transplanted into cytoplasm. Hutchison III et al. used a design, build, and test cycle to reduce this genome to 531 kb (473 genes). The resulting JCV-syn3.0 retains genes involved in key processes such as transcription and translation, but also contains 149 genes of unknown function. Science , this issue p. 10.1126/science.aad6253

Quantitative size measurements of single linear and circular DNA molecules in nanofluidic slitlike confinement are reported. A novel experimental method using DNA entropophoresis down a nanofluidic staircase implemented comprehensive variation of slitlike confinement around d ≈ 2p, where d is the slit depth and p is the persistence length, throughout the transition from strong to moderate confinement. A new numerical analysis approximated and corrected systematic imaging errors. Together, these advances enabled the first measurement of an experimental scaling relation between the in-plane radius of gyration, R∥, and d, yielding R∥ ∼ d–1/6 for all DNA samples investigated. This differs from the theoretical scaling relation, Re ∼ d–1/4, for the root-mean-square end-to-end size, Re. The use of different labeling ratios also allowed a new test of the influence of fluorescent labels on DNA persistence length. These results improve understanding of the basic physical behavior of polymers confined to nanofluidic...

We observed the free diffusion of individual 10 kbp, (1/2)λ (24.2 kbp), and λ (48.5 kbp) double-stranded deoxyribonucleic acid (DNA) molecules in fused-silica nanoslits with depths from 541 to 24 nm using epifluorescence video microscopy. Diffusivity, D, scaled with nanoslit depth, h, according to D ∝ hα, where α was 0.47 ± 0.05, 0.51 ± 0.06, and 0.47 ± 0.05 for 10 kbp, (1/2)λ, and λ DNA, respectively, in disagreement with the value of two-thirds predicted by blob theory. We observed no change in scaling behavior for h less than the persistence length of DNA, as predicted by reflecting rod theory. The scaling of D with DNA length, N, followed D ∝ N−1, indicating hydrodynamic screening in accordance with Rouse dynamics. Our results establish these scaling exponents for smaller h and greater DNA confinement than previous studies.

We have used the flow characteristics of an electrospinning jet to elongate and fix DNA molecules. We embedded and observed fluorescently labeled lambda bacteriophage DNA molecules in polyethylene oxide nanofibers. The embedded DNA molecules were imaged using fluorescence microscopy and found to be stretched to lengths approaching the full dyed contour length.

INTRODUCTION Cells respond to their environment, make decisions, build structures, and coordinate tasks. Underlying these processes are computational operations performed by networks of regulatory proteins that integrate signals and control the timing of gene expression. Harnessing this capability is critical for biotechnology projects that require decision-making, control, sensing, or spatial organization. It has been shown that cells can be programmed using synthetic genetic circuits composed of regulators organized to generate a desired operation. However, the construction of even simple circuits is time-intensive and unreliable. RATIONALE Electronic design automation (EDA) was developed to aid engineers in the design of semiconductor-based electronics. In an effort to accelerate genetic circuit design, we applied principles from EDA to enable increased circuit complexity and to simplify the incorporation of synthetic gene regulation into genetic engineering projects. We used the hardware description language Verilog to enable a user to describe a circuit function. The user also specifies the sensors, actuators, and “user constraints file” (UCF), which defines the organism, gate technology, and valid operating conditions. Cello (www.cellocad.org) uses this information to automatically design a DNA sequence encoding the desired circuit. This is done via a set of algorithms that parse the Verilog text, create the circuit diagram, assign gates, balance constraints to build the DNA, and simulate performance. RESULTS Cello designs circuits by drawing upon a library of Boolean logic gates. Here, the gate technology consists of NOT/NOR logic based on repressors. Gate connection is simplified by defining the input and output signals as RNA polymerase (RNAP) fluxes. We found that the gates need to be insulated from their genetic context to function reliably in the context of different circuits. Each gate is isolated using strong terminators to block RNAP leakage, and input interchangeability is improved using ribozymes and promoter spacers. These parts are varied for each gate to avoid breakage due to recombination. Measuring the load of each gate and incorporating this into the optimization algorithms further reduces evolutionary pressure. Cello was applied to the design of 60 circuits for Escherichia coli , where the circuit function was specified using Verilog code and transformed to a DNA sequence. The DNA sequences were built as specified with no additional tuning, requiring 880,000 base pairs of DNA assembly. Of these, 45 circuits performed correctly in every output state (up to 10 regulators and 55 parts). Across all circuits, 92% of the 412 output states functioned as predicted. CONCLUSION Our work constitutes a hardware description language for programming living cells. This required the co-development of design algorithms with gates that are sufficiently simple and robust to be connected by automated algorithms. We demonstrate that engineering principles can be applied to identify and suppress errors that complicate the compositions of larger systems. This approach leads to highly repetitive and modular genetics, in stark contrast to the encoding of natural regulatory networks. The use of a hardware-independent language and the creation of additional UCFs will allow a single design to be transformed into DNA for different organisms, genetic endpoints, operating conditions, and gate technologies.

A complex entropy gradient for confined DNA molecules was engineered for the first time. Following the second law of thermodynamics, this enabled the directed self-transport and self-concentration of DNA molecules. This new nanofluidic method is termed entropophoresis. As implemented in experiments, long DNA molecules were dyed with cyanine dimers, dispersed in a high ionic strength buffer, and confined by a nanofluidic channel with a depth profile approximated by a staircase function. The staircase step depths spanned the transition from strong to moderate confinement. The diffusion of DNA molecules across slitlike steps was ratcheted by entropic forces applied at step edges, so that DNA molecules descended and collected at the bottom of the staircase, as observed by fluorescence microscopy. Different DNA morphologies, lengths, and stoichiometric base pair to dye molecule ratios were tested and determined to influence the rate of transport by entropophoresis. A model of ratcheted diffusion was used to interpret a shifting balance of forces applied to linear DNA molecules of standard length in a complex free energy landscape. Related metrics for the overall and optimum performance of entropophoresis were developed. The device and method reported here transcend current limitations in nanofluidics and present new possibilities in polymer physics, biophysics, separation science, and lab-on-a-chip technology.

Gradient elution moving boundary electrophoresis (GEMBE) is a robust, continuous injection separation technique that uses electrophoresis to drive electrically charged analytes into a capillary or microfluidic channel for detection, while opposing electroosmosis and controlled variable pressure-driven flow prevent other sample components-for example, cells, proteins, or particulates in complex samples that can interfere with analysis-from entering the channel. This work expands the sample-in/answer-out analytical capabilities of GEMBE for complex samples by demonstrating the quantitative analysis of anions, implementing aqueous background electrolyte (BGE) solutions at neutral pH, and introducing the use of additives to the sample solution to optimize performance. Dirt was analyzed quantitatively, with the sole preparatory step of suspension in an aqueous BGE solution at neutral pH, for dissolved chloride, nitrite, nitrate, sulfate, and oxalate using GEMBE with capacitively-coupled contactless conductivity detection. In addition to altering the pH of the BGE solution, optimization of the analysis of dirt and whole blood was achieved using various commercially available additives. These results, taken together with previous demonstrations of GEMBE for the analysis of complex samples, underscore the uncomplicated versatility of GEMBE, facilitate effective analysis of biological complex samples using BGE solutions at physiological pH, and offer a sufficient set of techniques and tools to build a foundation for the analysis of a broad range of complex samples.

Sample-in answer-out analytical tools remain the goal of much lab on a chip research, but miniaturized methods capable of examining minimally prepared samples have proven elusive. Complex samples, including whole milk, various types of dirt and leaves, coal fly ash, and blood serum, were analyzed quantitatively for dissolved potassium, calcium, sodium, magnesium, lithium, and melamine using gradient elution moving boundary electrophoresis (GEMBE) and contactless conductivity detection with the single preparatory step of dilution or suspension in sample buffer. GEMBE is a simple, robust analytical technique, well-suited to microfluidic analysis of complex samples containing material, such as particulates or proteins, that would confound the majority of other microfluidic techniques. GEMBE utilizes electrophoretic flow to drive electrically charged analytes into a microfluidic channel or capillary for detection, while opposing electro-osmotic and variable pressure-driven flows prevent the remainder of the sample from entering the channel. Contactless conductivity detection further simplifies device construction and operation, positioning GEMBE for inexpensive and facile multiplexed implementation outside laboratory settings.

A nonequilibrium regime of size-based separation was observed experimentally for double-stranded deoxyribonucleic acid (DNA) molecules with lengths below 1 kbp moving electrokinetically through nanofluidic nanoslit arrays. The breakdown of Ogston sieving was supplanted at higher electric fields to recover rapid separation with a reversed elution order and elution times one to two orders of magnitude faster than with Ogston sieving at lower fields. A simple kinetic model describes the experimental results.

Nanofluidic devices have typically explored a design space of patterns limited by a single nanoscale structure depth. A method is presented here for fabricating nanofluidic structures with complex three-dimensional (3D) surfaces, utilizing a single layer of grayscale photolithography and standard integrated circuit manufacturing tools. This method is applied to construct nanofluidic devices with numerous (30) structure depths controlled from approximately 10 to approximately 620 nm with an average standard deviation of 1 cm. A prototype 3D nanofluidic device is demonstrated that implements size exclusion of rigid nanoparticles and variable nanoscale confinement and deformation of biomolecules.

We have used the flow characteristics of an electrospinning jet to elongate and fix DNA molecules. We embedded and observed fluorescently labeled lambda bacteriophage DNA molecules in polyethylene oxide nanofibers. The embedded DNA molecules were imaged using fluorescence microscopy and found to be stretched to lengths approaching the full dyed contour length.

A method termed 'nanoglassblowing' is presented for fabricating integrated microfluidic and nanofluidic devices with gradual depth changes and wide, shallow nanochannels. This method was used to construct fused silica channels with out-of-plane curvature of channel covers from over ten micrometers to a few nanometers, nanochannel aspect ratios smaller than 2 × 10(-5):1 (depth:width), and nanochannel depths as shallow as 7 nm. These low aspect ratios and shallow channel depths would be difficult to form otherwise without collapse of the channel cover, and the gradual changes in channel depth eliminate abrupt free energy barriers at the transition from microfluidic to nanofluidic regions. Devices were characterized with atomic force microscopy (AFM), white light interferometry, scanned height measurements, fluorescence intensity traces, and single molecule analysis of double-stranded deoxyribonucleic acid (DNA) velocity and conformation. Nanochannel depths and aspect ratios formed by nanoglassblowing allowed measurements of the radius of gyration, R(g), of single λ DNA molecules confined to slit-like nanochannels with depths, d, ranging from 11 nm to 507 nm. Measurements of R(g) as a function of d agreed qualitatively with the scaling law R(g)∝d(-0.25) predicted by Brochard for nanochannel depths from 36 nm to 156 nm, while measurements of R(g) in 11 nm and 507 nm deep nanochannels deviated from this prediction.

The authors have used electrospun polyethylene oxide nanofibers as sacrificial templates to form nanofluidic channels in polydimethylsiloxane (PDMS). By depositing fibers on silicon templates incorporating larger structures, the authors demonstrate that these nanochannels can be integrated easily with microfluidics. They use fluorescence microscopy to image channels filled with dye solution. The utility of the hybrid micro- and nanofluidic PDMS structures for single molecule observation and manipulation was demonstrated by introducing single molecules of λ-DNA into the channels. This nanofabrication technique allows the simple construction of integrated micro- and nanofluidic PDMS structures without lithographic nanofabrication techniques.

Nanofluidic slits are used to investigate surface interactions during electrophoresis between DNA molecules and channel walls. The channels have vertical dimensions of 19 and 70nm and contain no sieving matrix. Size-dependent mobility is observed for DNA in the 19nm channels. We present a model for double stranded DNA mobility in the nanochannels that accurately predicts the size dependence of the DNA mobility in the range of 2000–10000bp. Due to surface interactions, the DNA mobility in the nanochannels scales as N−1∕2. These results suggest that the notion of free solution DNA electrophoresis breaks down due to surface interactions in nanoscale environments.

The authors have electrospun fluorescently labeled DNA molecules into nanofibers with diameters of approximately 27nm. They were able to image the nanofibers via fluorescence microscopy, scanning electron microscopy, and atomic force microscopy. Fibers were deposited over prepatterned features such as electrodes and trenches, allowing future measurement and manipulation of the DNA nanofibers. As an example of such a measurement, they have used an atomic force microscope to measure the Young’s modulus of a single DNA nanofiber.