Characterization of 582 natural and synthetic terminators and quantification of their design constraints

Synthetic biology outside the cell: linking computational tools to cell-free systems

As mathematical models become more commonly integrated into the study of biology, a common language for describing biological processes is manifesting. Many tools have emerged for the simulation of in vivo synthetic biological systems, with only a few examples of prominent work done on predicting the dynamics of cell-free synthetic systems. At the same time, experimental biologists have begun to study dynamics of in vitro systems encapsulated by amphiphilic molecules, opening the door for the development of a new generation of biomimetic systems. In this review, we explore both in vivo and in vitro models of biochemical networks with a special focus on tools that could be applied to the construction of cell-free expression systems. We believe that quantitative studies of complex cellular mechanisms and pathways in synthetic systems can yield important insights into what makes cells different from conventional chemical systems.

Quantitative bacterial transcriptomics with RNA-seq

RNA sequencing has emerged as the premier approach to study bacterial transcriptomes. While the earliest published studies analyzed the data qualitatively, the data are readily digitized and lend themselves to quantitative analysis. High-resolution RNA sequence (RNA-seq) data allows transcriptional features (promoters, terminators, operons, among others) to be pinpointed on any bacterial transcriptome. Once the transcriptome is mapped, the activity of transcriptional features can be quantified. Here we highlight how quantitative transcriptome analysis can reveal biological insights and briefly discuss some of the challenges to be faced by the field of bacterial transcriptomics in the near future.

Rational experiment design for sequencing-based RNA structure mapping

Structure mapping is a classic experimental approach for determining nucleic acid structure that has gained renewed interest in recent years following advances in chemistry, genomics, and informatics. The approach encompasses numerous techniques that use different means to introduce nucleotide-level modifications in a structure-dependent manner. Modifications are assayed via cDNA fragment analysis, using electrophoresis or next-generation sequencing (NGS). The recent advent of NGS has dramatically increased the throughput, multiplexing capacity, and scope of RNA structure mapping assays, thereby opening new possibilities for genome-scale, de novo, and in vivo studies. From an informatics standpoint, NGS is more informative than prior technologies by virtue of delivering direct molecular measurements in the form of digital sequence counts. Motivated by these new capabilities, we introduce a novel model-based in silico approach for quantitative design of large-scale multiplexed NGS structure mapping assays, which takes advantage of the direct and digital nature of NGS readouts. We use it to characterize the relationship between controllable experimental parameters and the precision of mapping measurements. Our results highlight the complexity of these dependencies and shed light on relevant tradeoffs and pitfalls, which can be difficult to discern by intuition alone. We demonstrate our approach by quantitatively assessing the robustness of SHAPE-Seq measurements, obtained by multiplexing SHAPE (selective 2'-hydroxyl acylation analyzed by primer extension) chemistry in conjunction with NGS. We then utilize it to elucidate design considerations in advanced genome-wide approaches for probing the transcriptome, which recently obtained in vivo information using dimethyl sulfate (DMS) chemistry.

Multi-input CRISPR/Cas genetic circuits that interface host regulatory networks

Genetic circuits require many regulatory parts in order to implement signal processing or execute algorithms in cells. A potentially scalable approach is to use dCas9, which employs small guide RNAs (sgRNAs) to repress genetic loci via the programmability of RNA:DNA base pairing. To this end, we use dCas9 and designed sgRNAs to build transcriptional logic gates and connect them to perform computation in living cells. We constructed a set of NOT gates by designing five synthetic Escherichia coli σ70 promoters that are repressed by corresponding sgRNAs, and these interactions do not exhibit crosstalk between each other. These sgRNAs exhibit high on-target repression (56- to 440-fold) and negligible off-target interactions (< 1.3-fold). These gates were connected to build larger circuits, including the Boolean-complete NOR gate and a 3-gate circuit consisting of four layered sgRNAs. The synthetic circuits were connected to the native E. coli regulatory network by designing output sgRNAs to target an E. coli transcription factor (malT). This converts the output of a synthetic circuit to a switch in cellular phenotype (sugar utilization, chemotaxis, phage resistance).

Functional optimization of gene clusters by combinatorial design and assembly

Large microbial gene clusters encode useful functions, including energy utilization and natural product biosynthesis, but genetic manipulation of such systems is slow, difficult and complicated by complex regulation. We exploit the modularity of a refactored Klebsiella oxytoca nitrogen fixation (nif) gene cluster (16 genes, 103 parts) to build genetic permutations that could not be achieved by starting from the wild-type cluster. Constraint-based combinatorial design and DNA assembly are used to build libraries of radically different cluster architectures by varying part choice, gene order, gene orientation and operon occupancy. We construct 84 variants of the nifUSVWZM operon, 145 variants of the nifHDKY operon, 155 variants of the nifHDKYENJ operon and 122 variants of the complete 16-gene pathway. The performance and behavior of these variants are characterized by nitrogenase assay and strand-specific RNA sequencing (RNA-seq), and the results are incorporated into subsequent design cycles. We have produced a fully synthetic cluster that recovers 57% of wild-type activity. Our approach allows the performance of genetic parts to be quantified simultaneously in hundreds of genetic contexts. This parallelized design-build-test-learn cycle, which can access previously unattainable regions of genetic space, should provide a useful, fast tool for genetic optimization and hypothesis testing.

Integration of microfluidics into the synthetic biology design flow

One goal of synthetic biology is to design and build genetic circuits in living cells for a range of applications. Major challenges in these efforts include increasing the scalability and robustness of engineered biological systems and streamlining and automating the synthetic biology workflow of specification-design-assembly-verification. We present here a summary of the advances in microfluidic technology, particularly microfluidic large scale integration, that can be used to address the challenges facing each step of the synthetic biology workflow. Microfluidic technologies allow precise control over the flow of biological content within microscale devices, and thus may provide more reliable and scalable construction of synthetic biological systems. The integration of microfluidics and synthetic biology has the capability to produce rapid prototyping platforms for characterization of genetic devices, testing of biotherapeutics, and development of biosensors.

Unique nucleotide sequence-guided assembly of repetitive DNA parts for synthetic biology applications

Recombination-based DNA construction methods, such as Gibson assembly, have made it possible to easily and simultaneously assemble multiple DNA parts, and they hold promise for the development and optimization of metabolic pathways and functional genetic circuits. Over time, however, these pathways and circuits have become more complex, and the increasing need for standardization and insulation of genetic parts has resulted in sequence redundancies--for example, repeated terminator and insulator sequences--that complicate recombination-based assembly. We and others have recently developed DNA assembly methods, which we refer to collectively as unique nucleotide sequence (UNS)-guided assembly, in which individual DNA parts are flanked with UNSs to facilitate the ordered, recombination-based assembly of repetitive sequences. Here we present a detailed protocol for UNS-guided assembly that enables researchers to convert multiple DNA parts into sequenced, correctly assembled constructs, or into high-quality combinatorial libraries in only 2-3 d. If the DNA parts must be generated from scratch, an additional 2-5 d are necessary. This protocol requires no specialized equipment and can easily be implemented by a student with experience in basic cloning techniques.

Advances and computational tools towards predictable design in biological engineering

The design process of complex systems in all the fields of engineering requires a set of quantitatively characterized components and a method to predict the output of systems composed by such elements. This strategy relies on the modularity of the used components or the prediction of their context-dependent behaviour, when parts functioning depends on the specific context. Mathematical models usually support the whole process by guiding the selection of parts and by predicting the output of interconnected systems. Such bottom-up design process cannot be trivially adopted for biological systems engineering, since parts function is hard to predict when components are reused in different contexts. This issue and the intrinsic complexity of living systems limit the capability of synthetic biologists to predict the quantitative behaviour of biological systems. The high potential of synthetic biology strongly depends on the capability of mastering this issue. This review discusses the predictability issues of basic biological parts (promoters, ribosome binding sites, coding sequences, transcriptional terminators, and plasmids) when used to engineer simple and complex gene expression systems in Escherichia coli. A comparison between bottom-up and trial-and-error approaches is performed for all the discussed elements and mathematical models supporting the prediction of parts behaviour are illustrated.

Unprecedented high-resolution view of bacterial operon architecture revealed by RNA sequencing

We analyzed the transcriptome of Escherichia coli K-12 by strand-specific RNA sequencing at single-nucleotide resolution during steady-state (logarithmic-phase) growth and upon entry into stationary phase in glucose minimal medium. To generate high-resolution transcriptome maps, we developed an organizational schema which showed that in practice only three features are required to define operon architecture: the promoter, terminator, and deep RNA sequence read coverage. We precisely annotated 2,122 promoters and 1,774 terminators, defining 1,510 operons with an average of 1.98 genes per operon. Our analyses revealed an unprecedented view of E. coli operon architecture. A large proportion (36%) of operons are complex with internal promoters or terminators that generate multiple transcription units. For 43% of operons, we observed differential expression of polycistronic genes, despite being in the same operons, indicating that E. coli operon architecture allows fine-tuning of gene expression. We found that 276 of 370 convergent operons terminate inefficiently, generating complementary 3′ transcript ends which overlap on average by 286 nucleotides, and 136 of 388 divergent operons have promoters arranged such that their 5′ ends overlap on average by 168 nucleotides. We found 89 antisense transcripts of 397-nucleotide average length, 7 unannotated transcripts within intergenic regions, and 18 sense transcripts that completely overlap operons on the opposite strand. Of 519 overlapping transcripts, 75% correspond to sequences that are highly conserved in E. coli (>50 genomes). Our data extend recent studies showing unexpected transcriptome complexity in several bacteria and suggest that antisense RNA regulation is widespread.

We precisely mapped the 5′ and 3′ ends of RNA transcripts across the E. coli K-12 genome by using a single-nucleotide analytical approach. Our resulting high-resolution transcriptome maps show that ca. one-third of E. coli operons are complex, with internal promoters and terminators generating multiple transcription units and allowing differential gene expression within these operons. We discovered extensive antisense transcription that results from more than 500 operons, which fully overlap or extensively overlap adjacent divergent or convergent operons. The genomic regions corresponding to these antisense transcripts are highly conserved in E. coli (including Shigella species), although it remains to be proven whether or not they are functional. Our observations of features unearthed by single-nucleotide transcriptome mapping suggest that deeper layers of transcriptional regulation in bacteria are likely to be revealed in the future.

Efficient search, mapping, and optimization of multi-protein genetic systems in diverse bacteria

Developing predictive models of multi-protein genetic systems to understand and optimize their behavior remains a combinatorial challenge, particularly when measurement throughput is limited. We developed a computational approach to build predictive models and identify optimal sequences and expression levels, while circumventing combinatorial explosion. Maximally informative genetic system variants were first designed by the RBS Library Calculator, an algorithm to design sequences for efficiently searching a multi-protein expression space across a > 10,000-fold range with tailored search parameters and well-predicted translation rates. We validated the algorithm's predictions by characterizing 646 genetic system variants, encoded in plasmids and genomes, expressed in six gram-positive and gram-negative bacterial hosts. We then combined the search algorithm with system-level kinetic modeling, requiring the construction and characterization of 73 variants to build a sequence-expression-activity map (SEAMAP) for a biosynthesis pathway. Using model predictions, we designed and characterized 47 additional pathway variants to navigate its activity space, find optimal expression regions with desired activity response curves, and relieve rate-limiting steps in metabolism. Creating sequence-expression-activity maps accelerates the optimization of many protein systems and allows previous measurements to quantitatively inform future designs.

Principles of genetic circuit design

Cells navigate environments, communicate and build complex patterns by initiating gene expression in response to specific signals. Engineers seek to harness this capability to program cells to perform tasks or create chemicals and materials that match the complexity seen in nature. This Review describes new tools that aid the construction of genetic circuits. Circuit dynamics can be influenced by the choice of regulators and changed with expression 'tuning knobs'. We collate the failure modes encountered when assembling circuits, quantify their impact on performance and review mitigation efforts. Finally, we discuss the constraints that arise from circuits having to operate within a living cell. Collectively, better tools, well-characterized parts and a comprehensive understanding of how to compose circuits are leading to a breakthrough in the ability to program living cells for advanced applications, from living therapeutics to the atomic manufacturing of functional materials.

Large-scale de novo DNA synthesis: technologies and applications

For over 60 years, the synthetic production of new DNA sequences has helped researchers understand and engineer biology. Here we summarize methods and caveats for the de novo synthesis of DNA, with particular emphasis on recent technologies that allow for large-scale and low-cost production. In addition, we discuss emerging applications enabled by large-scale de novo DNA constructs, as well as the challenges and opportunities that lie ahead.

Integrating artificial with natural cells to translate chemical messages that direct E. coli behaviour

Previous efforts to control cellular behaviour have largely relied upon various forms of genetic engineering. Once the genetic content of a living cell is modified, the behaviour of that cell typically changes as well. However, other methods of cellular control are possible. All cells sense and respond to their environment. Therefore, artificial, non-living cellular mimics could be engineered to activate or repress already existing natural sensory pathways of living cells through chemical communication. Here we describe the construction of such a system. The artificial cells expand the senses of Escherichia coli by translating a chemical message that E. coli cannot sense on its own to a molecule that activates a natural cellular response. This methodology could open new opportunities in engineering cellular behaviour without exploiting genetically modified organisms.

The control of cellular behaviour largely relies on genetic engineering, but artificial cells could be designed to control cell processes through chemical communication. Here, the authors develop an artificial cell that is able to translate a chemical message into a signal that can be sensed by E. coli and activate a cellular response.

Control of gene expression at a bacterial leader RNA, the agn43 gene encoding outer membrane protein Ag43 of Escherichia coli

The family of agn alleles in Escherichia coli pathovars encodes autotransporters that have been implicated in biofilm formation, autoaggregation, and attachment to cells. The alleles all have long leader RNAs preceding the Ag43 translation initiation codon. Here we present an analysis of the agn43 leader RNA from E. coli K-12. We demonstrate the presence of a rho-independent transcription terminator just 28 bp upstream of the main translation start codon and show that it is functional in vitro. Our data indicate that an as-yet-unknown mechanism of antitermination of transcription must be operative in earlier phases of growth. However, as bacterial cell cultures mature, progressively fewer transcripts are able to bypass this terminator. In the K-12 leader sequence, two in-frame translation initiation codons have been identified, one upstream and the other downstream of the transcription terminator. For optimal agn43 expression, both codons need to be present. Translation from the upstream start codon leads to increased downstream agn43 expression. Our findings have revealed two novel modes of regulation of agn43 expression in the leader RNA in addition to the previously well-characterized regulation of phase variation at the agn43 promoter.

Realizing the potential of synthetic biology

Synthetic biology, despite still being in its infancy, is increasingly providing valuable information for applications in the clinic, the biotechnology industry and in basic molecular research. Both its unique potential and the challenges it presents have brought together the expertise of an eclectic group of scientists, from cell biologists to engineers. In this Viewpoint article, five experts discuss their views on the future of synthetic biology, on its main achievements in basic and applied science, and on the bioethical issues that are associated with the design of new biological systems.

Engineering reduced evolutionary potential for synthetic biology

The field of synthetic biology seeks to engineer reliable and predictable behaviors in organisms from collections of standardized genetic parts. However, unlike other types of machines, genetically encoded biological systems are prone to changes in their designed sequences due to mutations in their DNA sequences after these devices are constructed and deployed. Thus, biological engineering efforts can be confounded by undesired evolution that rapidly breaks the functions of parts and systems, particularly when they are costly to the host cell to maintain. Here, we explain the fundamental properties that determine the evolvability of biological systems. Then, we use this framework to review current efforts to engineer the DNA sequences that encode synthetic biology devices and the genomes of their microbial hosts to reduce their ability to evolve and therefore increase their genetic reliability so that they maintain their intended functions over longer timescales.

Genomic mining of prokaryotic repressors for orthogonal logic gates

Genetic circuits perform computational operations based on interactions between freely diffusing molecules within a cell. When transcription factors are combined to build a circuit, unintended interactions can disrupt its function. Here, we apply 'part mining' to build a library of 73 TetR-family repressors gleaned from prokaryotic genomes. The operators of a subset were determined using an in vitro method, and this information was used to build synthetic promoters. The promoters and repressors were screened for cross-reactions. Of these, 16 were identified that both strongly repress their cognate promoter (5- to 207-fold) and exhibit minimal interactions with other promoters. Each repressor-promoter pair was converted to a NOT gate and characterized. Used as a set of 16 NOT/NOR gates, there are >10(54) circuits that could be built by changing the pattern of input and output promoters. This represents a large set of compatible gates that can be used to construct user-defined circuits.

A wise consistency: engineering biology for conformity, reliability, predictability

The next generation of synthetic biology applications will increasingly involve engineered organisms that exist in intimate contact with humans, animals and the rest of the environment. Examples include cellular and viral approaches for maintaining and improving health in humans and animals. The need for reliable and specific function in these environments may require more complex system designs than previously. In these cases the uncertainties in the behavior of biological building blocks, their hosts and their environments present a challenge for design of predictable and safe systems. Here, we review systematic methods for the effective characterization of these uncertainties that are lowering the barriers to predictive design of reliable complex biological systems.

Design of orthogonal genetic switches based on a crosstalk map of σs, anti-σs, and promoters

Cells react to their environment through gene regulatory networks. Network integrity requires minimization of undesired crosstalk between their biomolecules. Similar constraints also limit the use of regulators when building synthetic circuits for engineering applications. Here, we mapped the promoter specificities of extracytoplasmic function (ECF) σs as well as the specificity of their interaction with anti-σs. DNA synthesis was used to build 86 ECF σs (two from every subgroup), their promoters, and 62 anti-σs identified from the genomes of diverse bacteria. A subset of 20 σs and promoters were found to be highly orthogonal to each other. This set can be increased by combining the -35 and -10 binding domains from different subgroups to build chimeras that target sequences unrepresented in any subgroup. The orthogonal σs, anti-σs, and promoters were used to build synthetic genetic switches in Escherichia coli. This represents a genome-scale resource of the properties of ECF σs and a resource for synthetic biology, where this set of well-characterized regulatory parts will enable the construction of sophisticated gene expression programs.

Synthetic promoters functional in Francisella novicida and Escherichia coli

In this work, we describe the identification of synthetic, controllable promoters that function in the bacterial pathogen Francisella novicida, a model facultative intracellular pathogen. Synthetic DNA fragments consisting of the tetracycline operator (tetO) flanked by a random nucleotide sequence were inserted into a Francisella novicida shuttle plasmid upstream of a promoterless artificial operon containing the reporter genes cat and lacZ. Fragments able to promote transcription were selected for based on their ability to drive expression of the cat gene, conferring chloramphenicol resistance. Promoters of various strengths were found, many of which were repressed in the presence of the tetracycline repressor (TetR) and promoted transcription only in the presence of the TetR inducer anhydrotetracycline. A subset of both constitutive and inducible synthetic promoters were characterized to find their induction ratios and to identify their transcription start sites. In cases where tetO was located between or downstream of the -10 and -35 regions of the promoter, control by TetR was observed. If the tetO region was upstream of the -35 region by more than 9 bp, it did not confer TetR control. We found that three of three promoters isolated in F. novicida functioned at a comparable level in E. coli; however, none of the 10 promoters isolated in E. coli functioned at a significant level in F. novicida. Our results allowed us to isolate minimal F. novicida promoters of 47 and 48 bp in length.

Genetic sensor for strong methylating compounds

Methylating chemicals are common in industry and agriculture and are often toxic, partly due to their propensity to methylate DNA. The Escherichia coli Ada protein detects methylating compounds by sensing aberrant methyl adducts on the phosphoester backbone of DNA. We characterize this system as a genetic sensor and engineer it to lower the detection threshold. By overexpressing Ada from a plasmid, we improve the sensor’s dynamic range to 350-fold induction and lower its detection threshold to 40 μM for methyl iodide. In eukaryotes, there is no known sensor of methyl adducts on the phosphoester backbone of DNA. By fusing the N-terminal domain of Ada to the Gal4 transcriptional activation domain, we built a functional sensor for methyl phosphotriester adducts in Saccharomyces cerevisiae. This sensor can be tuned to variable specifications by altering the expression level of the chimeric sensor and changing the number of Ada operators upstream of the Gal4-sensitive reporter promoter. These changes result in a detection threshold of 28 μM and 5.2-fold induction in response to methyl iodide. When the yeast sensor is exposed to different SN1 and SN2 alkylating compounds, its response profile is similar to that observed for the native Ada protein in E. coli, indicating that its native function is retained in yeast. Finally, we demonstrate that the specifications achieved for the yeast sensor are suitable for detecting methylating compounds at relevant concentrations in environmental samples. This work demonstrates the movement of a sensor from a prokaryotic to eukaryotic system and its rational tuning to achieve desired specifications.

Rapid construction of insulated genetic circuits via synthetic sequence-guided isothermal assembly

In vitro recombination methods have enabled one-step construction of large DNA sequences from multiple parts. Although synthetic biological circuits can in principle be assembled in the same fashion, they typically contain repeated sequence elements such as standard promoters and terminators that interfere with homologous recombination. Here we use a computational approach to design synthetic, biologically inactive unique nucleotide sequences (UNSes) that facilitate accurate ordered assembly. Importantly, our designed UNSes make it possible to assemble parts with repeated terminator and insulator sequences, and thereby create insulated functional genetic circuits in bacteria and mammalian cells. Using UNS-guided assembly to construct repeating promoter-gene-terminator parts, we systematically varied gene expression to optimize production of a deoxychromoviridans biosynthetic pathway in Escherichia coli. We then used this system to construct complex eukaryotic AND-logic gates for genomic integration into embryonic stem cells. Construction was performed by using a standardized series of UNS-bearing BioBrick-compatible vectors, which enable modular assembly and facilitate reuse of individual parts. UNS-guided isothermal assembly is broadly applicable to the construction and optimization of genetic circuits and particularly those requiring tight insulation, such as complex biosynthetic pathways, sensors, counters and logic gates.