Deconvolution of Gene Expression Noise into Spatial Dynamics of Transcription Factor-Promoter Interplay

Why cellular computations challenge our design principles

Biological systems inherently perform computations, inspiring synthetic biologists to engineer biological systems capable of executing predefined computational functions for diverse applications. Typically, this involves applying principles from the design of conventional silicon-based computers to create novel biological systems, such as genetic Boolean gates and circuits. However, the natural evolution of biological computation has not adhered to these principles, and this distinction warrants careful consideration. Here, we explore several concepts connecting computational theory, living cells, and computers, which may offer insights into the development of increasingly sophisticated biological computations. While conventional computers approach theoretical limits, solving nearly all problems that are computationally solvable, biological computers have the opportunity to outperform them in specific niches and problem domains. Crucially, biocomputation does not necessarily need to scale to rival or replicate the capabilities of electronic computation. Rather, efforts to re-engineer biology must recognise that life has evolved and optimised itself to solve specific problems using its own principles. Consequently, intelligently designed cellular computations will diverge from traditional computing in both implementation and application.

In Vivo Sampling of Intracellular Heterogeneity of Pseudomonas putida Enables Multiobjective Optimization of Genetic Devices

The inner physicochemical heterogeneity of bacterial cells generates three-dimensional (3D)-dependent variations of resources for effective expression of given chromosomally located genes. This fact has been exploited for adjusting the most favorable parameters for implanting a complex device for optogenetic control of biofilm formation in the soil bacterium Pseudomonas putida. To this end, a DNA segment encoding a superactive variant of the Caulobacter crescendus diguanylate cyclase PleD expressed under the control of the cyanobacterial light-responsive CcaSR system was placed in a mini-Tn5 transposon vector and randomly inserted through the chromosome of wild-type and biofilm-deficient variants of P. putida lacking the wsp gene cluster. This operation delivered a collection of clones covering a whole range of biofilm-building capacities and dynamic ranges in response to green light. Since the phenotypic output of the device depends on a large number of parameters (multiple promoters, RNA stability, translational efficacy, metabolic precursors, protein folding, etc.), we argue that random chromosomal insertions enable sampling the intracellular milieu for an optimal set of resources that deliver a preset phenotypic specification. Results thus support the notion that the context dependency can be exploited as a tool for multiobjective optimization, rather than a foe to be suppressed in Synthetic Biology constructs.

An electrogenetic toggle switch model

Synthetic biology uses molecular biology to implement genetic circuits that perform computations. These circuits can process inputs and deliver outputs according to predefined rules that are encoded, often entirely, into genetic parts. However, the field has recently begun to focus on using mechanisms beyond the realm of genetic parts for engineering biological circuits. We analyse the use of electrogenic processes for circuit design and present a model for a merged genetic and electrogenetic toggle switch operating in a biofilm attached to an electrode. Computational simulations explore conditions under which bistability emerges in order to identify the circuit design principles for best switch performance. The results provide a basis for the rational design and implementation of hybrid devices that can be measured and controlled both genetically and electronically.

A Network Approach to Genetic Circuit Designs

As genetic circuits become more sophisticated, the size and complexity of data about their designs increase. The data captured goes beyond genetic sequences alone; information about circuit modularity and functional details improves comprehension, performance analysis, and design automation techniques. However, new data types expose new challenges around the accessibility, visualization, and usability of design data (and metadata). Here, we present a method to transform circuit designs into networks and showcase its potential to enhance the utility of design data. Since networks are dynamic structures, initial graphs can be interactively shaped into subnetworks of relevant information based on requirements such as the hierarchy of biological parts or interactions between entities. A significant advantage of a network approach is the ability to scale abstraction, providing an automatic sliding level of detail that further tailors the visualization to a given situation. Additionally, several visual changes can be applied, such as coloring or clustering nodes based on types (e.g., genes or promoters), resulting in easier comprehension from a user perspective. This approach allows circuit designs to be coupled to other networks, such as metabolic pathways or implementation protocols captured in graph-like formats. We advocate using networks to structure, access, and improve synthetic biology information.

Standardization of regulatory nodes for engineering heterologous gene expression: a feasibility study

The potential of LacI/Ptrc , XylS/Pm , AlkS/PalkB , CprK/PDB3 and ChnR/PchnB regulatory nodes, recruited from both Gram-negative and Gram-positive bacteria, as the source of parts for formatting expression cargoes following the Standard European Vector Architecture (SEVA) has been examined. The five expression devices, which cover most known regulatory configurations in bacteria were assembled within exactly the same plasmid backbone and bearing the different functional segments arrayed in an invariable DNA scaffold. Their performance was then analysed in an Escherichia coli strain of reference through the readout of a fluorescence reporter gene that contained strictly identical translation signal elements. This approach allowed us to describe and compare the cognate expression systems with quantitative detail. The constructs under scrutiny diverged considerably in their capacity, expression noise, inducibility and ON/OFF ratios. Inspection of such a variance exposed the different constraints that rule the optimal arrangement of functional DNA segments in each case. The data highlighted also the ease of standardizing inducer-responsive devices subject to transcriptional activation as compared to counterparts based on repressors. The study resulted in a defined collection of formatted expression cargoes lacking any cross talk while offering a panoply of choices to potential users and help interoperability of the specific constructs.

Fast biofoundries: coping with the challenges of biomanufacturing

Biofoundries are highly automated facilities that enable the rapid and efficient design, build, test, and learn cycle of biomanufacturing and engineering biology, which is applicable to both research and industrial production. However, developing a biofoundry platform can be expensive and time consuming. A biofoundry should grow organically, starting from a basic platform but with a vision for automation, equipment interoperability, and efficiency. By thinking about strategies early in the process through process planning, simulation, and optimization, bottlenecks can be identified and resolved. Here, we provide a survey of technological solutions in biofoundries and their advantages and limitations. We explore possible pathways towards the creation of a functional, early-phase biofoundry, and strategies towards long-term sustainability.

Combinatorial pathway balancing provides biosynthetic access to 2-fluoro-cis,cis-muconate in engineered Pseudomonas putida

The wealth of bio-based building blocks produced by engineered microorganisms seldom include halogen atoms. Muconate is a platform chemical with a number of industrial applications that could be broadened by introducing fluorine atoms to tune its physicochemical properties. The soil bacterium Pseudomonas putida naturally assimilates benzoate via the ortho-cleavage pathway with cis,cis-muconate as intermediate. Here, we harnessed the native enzymatic machinery (encoded within the ben and cat gene clusters) to provide catalytic access to 2-fluoro-cis,cis-muconate (2-FMA) from fluorinated benzoates. The reactions in this pathway are highly imbalanced, leading to accumulation of toxic intermediates and limited substrate conversion. By disentangling regulatory patterns of ben and cat in response to fluorinated effectors, metabolic activities were adjusted to favor 2-FMA biosynthesis. After implementing this combinatorial approach, engineered P. putida converted 3-fluorobenzoate to 2-FMA at the maximum theoretical yield. Hence, this study illustrates how synthetic biology can expand the diversity of nature's biochemical catalysis.

Cis-Regulatory Logic Produces Gene-Expression Noise Describing Phenotypic Heterogeneity in Bacteria

Gene transcriptional process is random. It occurs in bursts and follows single-molecular kinetics. Intermittent bursts are measured based on their frequency and size. They influence temporal fluctuations in the abundance of total mRNA and proteins by generating distinct transcriptional variations referred to as “noise”. Noisy expression induces uncertainty because the association between transcriptional variation and the extent of gene expression fluctuation is ambiguous. The promoter architecture and remote interference of different cis-regulatory elements are the crucial determinants of noise, which is reflected in phenotypic heterogeneity. An alternative perspective considers that cellular parameters dictating genome-wide transcriptional kinetics follow a universal pattern. Research on noise and systematic perturbations of promoter sequences reinforces that both gene-specific and genome-wide regulation occur across species ranging from bacteria and yeast to animal cells. Thus, deciphering gene-expression noise is essential across different genomics applications. Amidst the mounting conflict, it is imperative to reconsider the scope, progression, and rational construction of diversified viewpoints underlying the origin of the noise. Here, we have established an indication connecting noise, gene expression variations, and bacterial phenotypic variability. This review will enhance the understanding of gene-expression noise in various scientific contexts and applications.

Genome-Wide Identification and Expression Analysis of SOS Response Genes in Salmonella enterica Serovar Typhimurium

A bioinformatic search for LexA boxes, combined with transcriptomic detection of loci responsive to DNA damage, identified 48 members of the SOS regulon in the genome of Salmonella enterica serovar Typhimurium. Single cell analysis using fluorescent fusions revealed that heterogeneous expression is a common trait of SOS response genes, with formation of SOS^OFF and SOS^ON subpopulations. Phenotypic cell variants formed in the absence of external DNA damage show gene expression patterns that are mainly determined by the position and the heterology index of the LexA box. SOS induction upon DNA damage produces SOS^OFF and SOS^ON subpopulations that contain live and dead cells. The nature and concentration of the DNA damaging agent and the time of exposure are major factors that influence the population structure upon SOS induction. An analogy can thus be drawn between the SOS response and other bacterial stress responses that produce phenotypic cell variants.

Subcellular Architecture of the xyl Gene Expression Flow of the TOL Catabolic Plasmid of Pseudomonas putida mt-2

Despite intensive research on the biochemical and regulatory features of the archetypal catabolic TOL system borne by pWW0 of Pseudomonas putida strain mt-2, the physical arrangement and tridimensional logic of the xyl gene expression flow remains unknown. In this work, the spatial distribution of specific xyl mRNAs with respect to the host nucleoid, the TOL plasmid, and the ribosomal pool has been investigated. In situ hybridization of target transcripts with fluorescent oligonucleotide probes revealed that xyl mRNAs cluster in discrete foci, adjacent but clearly separated from the TOL plasmid and the cell nucleoid. Also, they colocalize with ribosome-rich domains of the intracellular milieu. This arrangement was maintained even when the xyl genes were artificially relocated to different chromosomal locations. The same held true when genes were expressed through a heterologous T7 polymerase-based system, which likewise led to mRNA foci outside the DNA. In contrast, rifampin treatment, known to ease crowding, blurred the confinement of xyl transcripts. This suggested that xyl mRNAs exit from their initiation sites to move to ribosome-rich points for translation—rather than being translated coupled to transcription. Moreover, the results suggest the distinct subcellular motion of xyl mRNAs results from both innate properties of the sequences and the physical forces that keep the ribosomal pool away from the nucleoid in P. putida. This scenario is discussed within the background of current knowledge on the three-dimensional organization of the gene expression flow in other bacteria and the environmental lifestyle of this soil microorganism.

Contextual dependencies expand the re-usability of genetic inverters

The implementation of Boolean logic circuits in cells have become a very active field within synthetic biology. Although these are mostly focussed on the genetic components alone, the context in which the circuit performs is crucial for its outcome. We characterise 20 genetic NOT logic gates in up to 7 bacterial-based contexts each, to generate 135 different functions. The contexts we focus on are combinations of four plasmid backbones and three hosts, two Escherichia coli and one Pseudomonas putida strains. Each gate shows seven different dynamic behaviours, depending on the context. That is, gates can be fine-tuned by changing only contextual parameters, thus improving the compatibility between gates. Finally, we analyse portability by measuring, scoring, and comparing gate performance across contexts. Rather than being a limitation, we argue that the effect of the genetic background on synthetic constructs expands functionality, and advocate for considering context as a fundamental design parameter.

Modelling co-translational dimerization for programmable nonlinearity in synthetic biology

Nonlinearity plays a fundamental role in the performance of both natural and synthetic biological networks. Key functional motifs in living microbial systems, such as the emergence of bistability or oscillations, rely on nonlinear molecular dynamics. Despite its core importance, the rational design of nonlinearity remains an unmet challenge. This is largely due to a lack of mathematical modelling that accounts for the mechanistic basis of nonlinearity. We introduce a model for gene regulatory circuits that explicitly simulates protein dimerization-a well-known source of nonlinear dynamics. Specifically, our approach focuses on modelling co-translational dimerization: the formation of protein dimers during-and not after-translation. This is in contrast to the prevailing assumption that dimer generation is only viable between freely diffusing monomers (i.e. post-translational dimerization). We provide a method for fine-tuning nonlinearity on demand by balancing the impact of co- versus post-translational dimerization. Furthermore, we suggest design rules, such as protein length or physical separation between genes, that may be used to adjust dimerization dynamics in vivo. The design, build and test of genetic circuits with on-demand nonlinear dynamics will greatly improve the programmability of synthetic biological systems.

Exploring the synthetic biology potential of bacteriophages for engineering non-model bacteria

Non-model bacteria like Pseudomonas putida, Lactococcus lactis and other species have unique and versatile metabolisms, offering unique opportunities for Synthetic Biology (SynBio). However, key genome editing and recombineering tools require optimization and large-scale multiplexing to unlock the full SynBio potential of these bacteria. In addition, the limited availability of a set of characterized, species-specific biological parts hampers the construction of reliable genetic circuitry. Mining of currently available, diverse bacteriophages could complete the SynBio toolbox, as they constitute an unexplored treasure trove for fully adapted metabolic modulators and orthogonally-functioning parts, driven by the longstanding co-evolution between phage and host.

Synthetic control of plasmid replication enables target- and self-curing of vectors and expedites genome engineering of Pseudomonas putida

Genome engineering of non-conventional microorganisms calls for the development of dedicated synthetic biology tools. Pseudomonas putida is a Gram-negative, non-pathogenic soil bacterium widely used for metabolic engineering owing to its versatile metabolism and high levels of tolerance to different types of stress. Genome editing of P. putida largely relies on homologous recombination events, assisted by helper plasmid-based expression of genes encoding DNA modifying enzymes. Plasmid curing from selected isolates is the most tedious and time-consuming step of this procedure, and implementing commonly used methods to this end in P. putida (e.g. temperature-sensitive replicons) is often impractical. To tackle this issue, we have developed a toolbox for both target- and self-curing of plasmid DNA in Pseudomonas species. Our method enables plasmid-curing in a simple cultivation step by combining in vivo digestion of vectors by the I-SceI homing nuclease with synthetic control of plasmid replication, triggered by the addition of a cheap chemical inducer (3-methylbenzoate) to the medium. The system displays an efficiency of vector curing >90% and the screening of plasmid-free clones is greatly facilitated by the use of fluorescent markers that can be selected according to the application intended. Furthermore, quick genome engineering of P. putida using self-curing plasmids is demonstrated through genome reduction of the platform strain EM42 by eliminating all genes encoding β-lactamases, the catabolic ben gene cluster, and the pyoverdine synthesis machinery. Physiological characterization of the resulting streamlined strain, P. putida SEM10, revealed advantageous features that could be exploited for metabolic engineering.

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Plasmid-curing is the most time-consuming step in genome engineering approaches.

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We have developed a system for easy target- and self-curing of plasmid DNA.

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Synthetic control of replication and highly-specific in vivo DNA digestion were used.

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Plasmid curing with this system displays an efficiency >90% in a 24-h cultivation.

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Quick genome engineering facilitated genome reduction of P. putida.

Pathways to cellular supremacy in biocomputing

Synthetic biology uses living cells as the substrate for performing human-defined computations. Many current implementations of cellular computing are based on the “genetic circuit” metaphor, an approximation of the operation of silicon-based computers. Although this conceptual mapping has been relatively successful, we argue that it fundamentally limits the types of computation that may be engineered inside the cell, and fails to exploit the rich and diverse functionality available in natural living systems. We propose the notion of “cellular supremacy” to focus attention on domains in which biocomputing might offer superior performance over traditional computers. We consider potential pathways toward cellular supremacy, and suggest application areas in which it may be found.

Synthetic biology uses cells as its computing substrate, often based on the genetic circuit concept. In this Perspective, the authors argue that existing synthetic biology approaches based on classical models of computation limit the potential of biocomputing, and propose that living organisms have under-exploited capabilities.

A Model for the Spatiotemporal Design of Gene Regulatory Circuits †

Mathematical modeling assists the design of synthetic regulatory networks by providing a detailed mechanistic understanding of biological systems. Models that can predict the performance of a design are fundamental for synthetic biology since they minimize iterations along the design-build-test lifecycle. Such predictability depends crucially on what assumptions (i.e., biological simplifications) the model considers. Here, we challenge a common assumption when it comes to the modeling of bacterial-based gene regulation: considering negligible the effects of intracellular physical space. It is commonly assumed that molecules, such as transcription factors (TF), are homogeneously distributed inside a cell, so there is no need to model their diffusion. We describe a mathematical model that accounts for molecular diffusion and show how simulations of network performance are decisively affected by the distance between its components. Specifically, the model focuses on the search by a TF for its target promoter. The combination of local searches, via one-dimensional sliding along the chromosome, and global searches, via three-dimensional diffusion through the cytoplasm, determine TF-promoter interplay. Previous experimental results with engineered bacteria in which the distance between TF source and target was minimized or enlarged were successfully reproduced by the spatially resolved model we introduce here. This suggests that the spatial specification of the circuit alone can be exploited as a design parameter in synthetic biology to select programmable output levels.

Communicating Structure and Function in Synthetic Biology Diagrams

Biological engineers often find it useful to communicate using diagrams. These diagrams can include information both about the structure of the nucleic acid sequences they are engineering and about the functional relationships between features of these sequences and/or other molecular species. A number of conventions and practices have begun to emerge within synthetic biology for creating such diagrams, and the Synthetic Biology Open Language Visual (SBOL Visual) has been developed as a standard to organize, systematize, and extend such conventions in order to produce a coherent visual language. Here, we describe SBOL Visual version 2, which expands previous diagram standards to include new functional interactions, categories of molecular species, support for families of glyph variants, and the ability to indicate modular structure and mappings between elements of a system. SBOL Visual 2 also clarifies a number of requirements and best practices, significantly expands the collection of glyphs available to describe genetic features, and can be readily applied using a wide variety of software tools, both general and bespoke.

Physical decoupling of XylS/Pm regulatory elements and conditional proteolysis enable precise control of gene expression in Pseudomonas putida

Most of the gene expression systems available for Gram‐negative bacteria are afflicted by relatively high levels of basal (i.e. leaky) expression of the target gene(s). This occurrence affects the system dynamics, ultimately reducing the output and productivity of engineered pathways and synthetic circuits. In order to circumvent this problem, we have designed a novel expression system based on the well‐known XylS/Pm transcriptional regulator/promoter pair from the soil bacterium Pseudomonas putida mt‐2, in which the key functional elements are physically decoupled. By integrating the xylS gene into the chromosome of the platform strain KT2440, while placing the Pm promoter into a set of standard plasmid vectors, the inducibility of the system (i.e. the output difference between the induced and uninduced state) improved up to 170‐fold. We further combined this modular system with an extra layer of post‐translational control by means of conditional proteolysis. In this setup, the target gene is tagged with a synthetic motif dictating protein degradation. When the system features were characterized using the monomeric superfolder GFP as a model protein, the basal levels of fluorescence were brought down to zero (i.e. below the limit of detection). In all, these novel expression systems constitute an alternative tool to altogether suppress leaky gene expression, and they can be easily adapted to other vector formats and plugged‐in into different Gram‐negative bacterial species at the user's will.

High-Performance Biocomputing in Synthetic Biology-Integrated Transcriptional and Metabolic Circuits

Biocomputing uses molecular biology parts as the hardware to implement computational devices. By following pre-defined rules, often hard-coded into biological systems, these devices are able to process inputs and return outputs—thus computing information. Key to the success of any biocomputing endeavor is the availability of a wealth of molecular tools and biological motifs from which functional devices can be assembled. Synthetic biology is a fabulous playground for such purpose, offering numerous genetic parts that allow for the rational engineering of genetic circuits that mimic the behavior of electronic functions, such as logic gates. A grand challenge, as far as biocomputing is concerned, is to expand the molecular hardware available beyond the realm of genetic parts by tapping into the host metabolism. This objective requires the formalization of the interplay of genetic constructs with the rest of the cellular machinery. Furthermore, the field of metabolic engineering has had little intersection with biocomputing thus far, which has led to a lack of definition of metabolic dynamics as computing basics. In this perspective article, we advocate the conceptualization of metabolism and its motifs as the way forward to achieve whole-cell biocomputations. The design of merged transcriptional and metabolic circuits will not only increase the amount and type of information being processed by a synthetic construct, but will also provide fundamental control mechanisms for increased reliability.

Dynamical Task Switching in Cellular Computers

We present a scheme for implementing a version of task switching in engineered bacteria, based on the manipulation of plasmid copy numbers. Our method allows for the embedding of multiple computations in a cellular population, whilst minimising resource usage inefficiency. We describe the results of computational simulations of our model, and discuss the potential for future work in this area.

The art of vector engineering: towards the construction of next-generation genetic tools

When recombinant DNA technology was developed more than 40 years ago, no one could have imagined the impact it would have on both society and the scientific community. In the field of genetic engineering, the most important tool developed was the plasmid vector. This technology has been continuously expanding and undergoing adaptations. Here, we provide a detailed view following the evolution of vectors built throughout the years destined to study microorganisms and their peculiarities, including those whose genomes can only be revealed through metagenomics. We remark how synthetic biology became a turning point in designing these genetic tools to create meaningful innovations. We have placed special focus on the tools for engineering bacteria and fungi (both yeast and filamentous fungi) and those available to construct metagenomic libraries. Based on this overview, future goals would include the development of modular vectors bearing standardized parts and orthogonally designed circuits, a task not fully addressed thus far. Finally, we present some challenges that should be overcome to enable the next generation of vector design and ways to address it.

A synthetic microbial biosensor for high-throughput screening of lactam biocatalysts

Biocatalytic cyclization is highly desirable for efficient synthesis of biologically derived chemical substances, such as the commodity chemicals ε-caprolactam and δ-valerolactam. To identify biocatalysts in lactam biosynthesis, we develop a caprolactam-detecting genetic enzyme screening system (CL-GESS). The Alcaligenes faecalis regulatory protein NitR is adopted for the highly specific detection of lactam compounds against lactam biosynthetic intermediates. We further systematically optimize the genetic components of the CL-GESS to enhance sensitivity, achieving 10-fold improvement. Using this highly sensitive GESS, we screen marine metagenomes and find an enzyme that cyclizes ω-amino fatty acids to lactam. Moreover, we determine the X-ray crystal structure and catalytic residues based on mutational analysis of the cyclase. The cyclase is also used as a helper enzyme to sense intracellular ω-amino fatty acids. We expect this simple and accurate biosensor to have wide-ranging applications in rapid screening of new lactam-synthesizing enzymes and metabolic engineering for lactam bio-production.

An Engineered Device for Indoleacetic Acid Production under Quorum Sensing Signals Enables Cupriavidus pinatubonensis JMP134 To Stimulate Plant Growth

The environmental effects of chemical fertilizers and pesticides have encouraged the quest for new strategies to increase crop productivity with minimal impacts on the natural medium. Plant growth promoting rhizobacteria (PGPR) can contribute to this endeavor by improving fitness through better nutrition acquisition and stress tolerance. Using the neutral (non PGPR) rhizobacterium Cupriavidus pinatubonensis JMP134 as the host, we engineered a regulatory forward loop that triggered the synthesis of the phytohormone indole-3-acetic acid (IAA) in a manner dependent on quorum sensing (QS) signals. Implementation of the device in JMP134 yielded synthesis of IAA in an autoregulated manner, improving the growth of the roots of inoculated Arabidopsis thaliana. These results not only demonstrated the value of the designed genetic module, but also validated C. pinatubonensis JMP134 as a suitable vehicle for agricultural applications, as it is amenable to genetic manipulations.

Probing Intercell Variability Using Bulk Measurements

The measurement of noise is critical when assessing the design and function of synthetic biological systems. Cell-to-cell variability can be quantified experimentally using single-cell measurement techniques such as flow cytometry and fluorescent microscopy. However, these approaches are costly and impractical for high-throughput parallelized experiments, which are frequently conducted using plate-reader devices. In this paper we describe reporter systems that allow estimation of the cell-to-cell variability in a biological system's output using only measurements of a cell culture's bulk properties. We analyze one potential implementation of such a system that is based upon a fluorescent protein FRET reporter pair, finding that with typical parameters from the literature it is able to reliably estimate variability. We also briefly describe an alternate implementation based upon an activating sRNA circuit. The feasible region of parameter values for which the reporter system can function is assessed, and the dependence of its performance on both extrinsic and intrinsic noise is investigated. Experimental realization of these constructs can yield novel reporter systems that allow measurement of a synthetic gene circuit's output, as well as the intrapopulation variability of this output, at little added cost.

Standards not that standard

There is a general assent on the key role of standards in Synthetic Biology. In two consecutive letters to this journal, suggestions on the assembly methods for the Registry of standard biological parts have been described. We fully agree with those authors on the need of a more flexible building strategy and we highlight in the present work two major functional challenges standardization efforts have to deal with: the need of both universal and orthogonal behaviors. We provide experimental data that clearly indicate that such engineering requirements should not be taken for granted in Synthetic Biology.