Design of novel enzyme biocatalysts for industrial bioprocess: Harnessing the power of protein engineering, high throughput screening and synthetic biology

Biocatalysts have wider applications in various industries. Biocatalysts are generating bigger attention among researchers due to their unique catalytic properties like activity, specificity and stability. However the industrial use of many enzymes is hindered by low catalytic efficiency and stability during industrial processes. Properties of enzymes can be altered by protein engineering. Protein engineers are increasingly study the structure-function characteristics, engineering attributes, design of computational tools for enzyme engineering, and functional screening processes to improve the design and applications of enzymes. The potent and innovative techniques of enzyme engineering deliver outstanding opportunities for tailoring industrially important enzymes for the versatile production of biochemicals. An overview of the current trends in enzyme engineering is explored with important representative examples.

Synthetic Biology Enables Programmable Cell-Based Biosensors

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

Calibrating Transcriptional Activity Using Constitutive Synthetic Promoters in Mutants for Global Regulators in Escherichia coli

The engineering of synthetic circuits in cells relies on the use of well-characterized biological parts that would perform predicted functions under the situation considered, and many efforts have been taken to set biological standards that could define the basic features of these parts. However, since most synthetic biology projects usually require a particular cellular chassis and set of growth conditions, defining standards in the field is not a simple task as gene expression measurements could be affected severely by genetic background and culture conditions. In this study, we addressed promoter parameterization in bacteria in different genetic backgrounds and growth conditions. We found that a small set of constitutive promoters of different strengths controlling a short-lived GFP reporter placed in a low-copy number plasmid produces remarkably reproducible results that allow for the calibration of promoter activity over different genetic backgrounds and physiological conditions, thus providing a simple way to set standards of promoter activity in bacteria. Based on these results, we proposed the utilization of synthetic constitutive promoters as tools for calibration for the standardization of biological parts, in a way similar to the use of DNA and protein ladders in molecular biology as references for comparison with samples of interest.

Ecotoxicological bioassays of sediment leachates in a river bed flanked by decommissioned pesticide plants in Nantong City, East China

Traditionally, the toxicity of river contaminants is analyzed chemically or physically through river bed sediments. The biotoxicity of polluted sediment leachates has not caught our attention. This study aims to overcome this deficiency through a battery of biotests which were conducted to monitor comprehensive toxicity of sediment leachates for the Yaogang River in East Jiangsu Province of China, which is in close proximity to former pesticide plants. The general physical and chemical parameters of major pollutants were analyzed from river bed sediments collected at five strategic locations. The ecotoxicity analyses undertaken include overall fish (adult zebrafish) acute toxicity, luminescent bacteria (Vibrio fischeri) bioassay, and zebrafish embryo toxicity assay. Compared with the control group, sediment leachates increased the lethality, inhibited the embryos hatching and induced development abnormalities of zebrafish embryos, and inhibited the luminescence of V. fischeri. The results show that sediment leachates may assume various toxic effects, depending on the test organism. This diverse toxicity to aquatic organisms reflects their different sensitivity to sediment leachates. It is found clearly that V. fischeri was the organism which was characterized by the highest sensitivity to the sediment leachates. The complicated toxicity of leachates was not caused by one single factor but by multiple pollutants together. This indicates the need of estimations of sediment leachate not only taking into account chemical detection but also of applying the biotests to the problem. Thus, multigroup bioassays are necessary to realistically evaluate river ecological risks imposed by leachates.

Data Integration and Mining for Synthetic Biology Design

One aim of synthetic biologists is to create novel and predictable biological systems from simpler modular parts. This approach is currently hampered by a lack of well-defined and characterized parts and devices. However, there is a wealth of existing biological information, which can be used to identify and characterize biological parts, and their design constraints in the literature and numerous biological databases. However, this information is spread among these databases in many different formats. New computational approaches are required to make this information available in an integrated format that is more amenable to data mining. A tried and tested approach to this problem is to map disparate data sources into a single data set, with common syntax and semantics, to produce a data warehouse or knowledge base. Ontologies have been used extensively in the life sciences, providing this common syntax and semantics as a model for a given biological domain, in a fashion that is amenable to computational analysis and reasoning. Here, we present an ontology for applications in synthetic biology design, SyBiOnt, which facilitates the modeling of information about biological parts and their relationships. SyBiOnt was used to create the SyBiOntKB knowledge base, incorporating and building upon existing life sciences ontologies and standards. The reasoning capabilities of ontologies were then applied to automate the mining of biological parts from this knowledge base. We propose that this approach will be useful to speed up synthetic biology design and ultimately help facilitate the automation of the biological engineering life cycle.

Edwin

Characterization of gene expression is a central tenet of the synthetic biology design cycle. Sometimes it requires high-throughput approaches that allow quantification of the gene expression of different elements in diverse conditions. Recently, several large-scale studies have highlighted the importance of posttranscriptional regulation mechanisms and their impact on correlations between mRNA and protein abundance. Here, we introduce Edwin, a robotic workstation that enables the automated propagation of microbial cells and the dynamic characterization of gene expression. We developed an automated procedure that integrates customized RNA extraction and analysis into the typical high-throughput characterization of reporter gene expression. To test the system, we engineered Escherichia coli strains carrying different promoter/ gfp fusions. We validated Edwin's abilities: (1) preparation of custom cultures of microbial cells and (2) dynamic quantification of fluorescence signal and bacterial growth and simultaneous RNA extraction and analysis at different time points. We confirmed that RNA obtained during this automated process was suitable for use in qPCR analysis. Our results established that Edwin is a powerful platform for the automated analysis of microbial gene expression at the protein and RNA level. This platform could be used in a high-throughput manner to characterize not only natural regulatory elements but also synthetic ones.

Chromosomal integration of transcriptional fusions

The characterization and parameterization of promoters is crucial for the study of gene regulatory networks. While a number of techniques are available for this purpose, the use of reporter fusions integrated in the chromosome of a bacterial host affords precise quantification of transcriptional responses with high reproducibility. Here, we describe the integration of green fluorescent protein (GFP) and lacZ reporter cassettes using either mini-Tn7-based vectors or homologous chromosomal recombination to analyze gene regulation at transcriptional and post-transcriptional levels.

The Standard European Vector Architecture (SEVA) plasmid toolkit

The Standard European Vector Architecture (SEVA) toolkit is a simple and powerful resource for constructing optimal plasmid vectors based on a backbone and three interchangeable modules flanked by uncommon restriction sites. Functional modules encode several origins of replication, diverse antibiotic selection markers, and a variety of cargoes with different applications. The backbone and DNA modules have been minimized and edited for flaws in their sequence and/or functionality. A protocol for the utilization of the SEVA platform to construct transcriptional and translational fusions between a promoter under study (the arsenic-responsive Pars of Pseudomonas putida KT2440) and the reporter lacZ gene is described. The resulting plasmid collection was instrumental to measure and compare the β-galactosidase activity that report gene expression (i.e., transcription and translation) in different genetic backgrounds.

High-throughput prescreening of pharmaceuticals using a genome-wide bacterial bioreporter array

We assessed the applicability of multi-strain bacterial bioreporter bioassays to drug screening. To this end, we investigated the reactions of a panel of 15 luminescent recombinant Escherichia coli bacterial bioreporters to a library of 420 pharmaceuticals. The panel included bacterial bioreporters associated with oxidative stress, DNA damage, heat shock, and efflux of excess metals. Eighty nine drugs elicited a response from at least one of the panel members and formed distinctive clusters, some of which contained closely related drugs. In addition, we tested a group of selected nine drugs against a collection of about 2000 different fluorescent transcriptional reporters that covers the great majority of gene promoters in E. coli. The sets of induced genes were in accord with the in vitro toxicity of the tested drugs, as reflected by the response patterns of the 15-member panel, and provided more insights into their toxicity mechanisms. Facilitated by microplates and robotic systems, all assays were conducted in high-throughput. Our results thus suggest that multi-strain assemblages of bacterial bioreporters have the potential for playing a significant role in drug development alongside current in vitro toxicity tests.

Digital switching in a biosensor circuit via programmable timing of gene availability

Transient delivery of gene circuits is required in many potential applications of synthetic biology, yet pre-steady-state processes that dominate this delivery route pose significant challenges for robust circuit deployment. Here we show that site-specific recombinases can rectify undesired effects by programmable timing of gene availability in multi-gene circuits. We exemplify the concept with a proportional sensor for endogenous microRNA and show dramatic reduction in its ground state leakage thanks to desynchronization of circuit’s repressor components and their repression target. The new sensors display dynamic range of up to 1000-fold compared to 20-fold in the standard configuration. We applied the approach to classify cell types based on miRNA expression profile and measured > 200-fold output differential between positively- and negatively-identified cells. We also showed major improvement of specificity with cytotoxic output. Our study opens new venues in gene circuit design via judicious temporal control of circuits’ genetic makeup.

Synthetic biology approaches to improve biocatalyst identification in metagenomic library screening

There is a growing demand for enzymes with improved catalytic performance or tolerance to process-specific parameters, and biotechnology plays a crucial role in the development of biocatalysts for use in industry, agriculture, medicine and energy generation. Metagenomics takes advantage of the wealth of genetic and biochemical diversity present in the genomes of microorganisms found in environmental samples, and provides a set of new technologies directed towards screening for new catalytic activities from environmental samples with potential biotechnology applications. However, biased and low level of expression of heterologous proteins in Escherichia coli together with the use of non-optimal cloning vectors for the construction of metagenomic libraries generally results in an extremely low success rate for enzyme identification. The bottleneck arising from inefficient screening of enzymatic activities has been addressed from several perspectives; however, the limitations related to biased expression in heterologous hosts cannot be overcome by using a single approach, but rather requires the synergetic implementation of multiple methodologies. Here, we review some of the principal constraints regarding the discovery of new enzymes in metagenomic libraries and discuss how these might be resolved by using synthetic biology methods.

FOUNDATIONS FOR MODELING THE DYNAMICS OF GENE REGULATORY NETWORKS: A MULTILEVEL-PERSPECTIVE REVIEW

A promising alternative for unraveling the principles under which the dynamic interactions among genes lead to cellular phenotypes relies on mathematical and computational models at different levels of abstraction, from the molecular level of protein-DNA interactions to the system level of functional relationships among genes. This review article presents, under a bottom–up perspective, a hierarchy of approaches to modeling gene regulatory network dynamics, from microscopic descriptions at the single-molecule level in the spatial context of an individual cell to macroscopic models providing phenomenological descriptions at the population-average level. The reviewed modeling approaches include Molecular Dynamics, Particle-Based Brownian Dynamics, the Master Equation approach, Ordinary Differential Equations, and the Boolean logic abstraction. Each of these frameworks is motivated by a particular biological context and the nature of the insight being pursued. The setting of gene network dynamic models from such frameworks involves assumptions and mathematical artifacts often ignored by the non-specialist. This article aims at providing an entry point for biologists new to the field and computer scientists not acquainted with some recent biophysically-inspired models of gene regulation. The connections promoting intuition between different abstraction levels and the role that approximations play in the modeling process are highlighted throughout the paper.

Promoter fusions with optical outputs in individual cells and in populations

Reporter genes are widely used to quantify promoter activity, which controls production of mRNA through the interplay with RNA polymerases and transcription factors. Some of such reporters have either diffuse (lux) or focused (GFP) optical outputs that allow description of transcriptional activity in populations and in single cells. This chapter discusses the use of a dual reporter system GFP-luxCDABE that is placed in broad-host-range plasmids having origins of replication from RK2 and pBBR1. The value of this system is shown in Pseudomonas putida by characterizing the activity of the Pb promoter, which drives an operon for benzoate biodegradation in this bacterium. To this end we compare in the same cells bioluminescence as the output signal of the whole population and single cell-bound fluorescence caused by GFP expression and revealed by flow cytometry assays.

Broad spectrum detection and "barcoding" of water pollutants by a genome-wide bacterial sensor array

An approach for the rapid detection and classification of a broad spectrum of water pollutants, based on a genome-wide reporter bacterial live cell array, is proposed and demonstrated. An array of ca. 2000 Escherichia coli fluorescent transcriptional reporters was exposed to 25 toxic compounds as well as to unpolluted water, and its responses were recorded after 3 h. The 25 toxic compounds represented 5 pollutant classes: genotoxicants, metals, detergents, alcohols, and monoaromatic hydrocarbons. Identifying unique gene expression patterns, a nearest neighbour-based model detected pollutant presence and predicted class attribution with an estimated accuracy of 87%. Sensitivity and positive predictive values varied among classes, being higher for pollutant classes that were defined by mode of action than for those defined by structure only. Sensitivity for unpolluted water was 0.90 and the positive predictive value was 0.79. All pollutant classes induced the transcription of a statistically significant proportion of membrane associated genes; in addition, the sets of genes responsive to genotoxicants, detergents and alcohols were enriched with genes involved in DNA repair, iron utilization and the translation machinery, respectively. Following further development, a methodology of the type described herein may be suitable for integration in water monitoring schemes in conjunction with existing analytical and biological detection techniques.

The Standard European Vector Architecture (SEVA): a coherent platform for the analysis and deployment of complex prokaryotic phenotypes

The ‘Standard European Vector Architecture’ database (SEVA-DB, http://seva.cnb.csic.es) was conceived as a user-friendly, web-based resource and a material clone repository to assist in the choice of optimal plasmid vectors for de-constructing and re-constructing complex prokaryotic phenotypes. The SEVA-DB adopts simple design concepts that facilitate the swapping of functional modules and the extension of genome engineering options to microorganisms beyond typical laboratory strains. Under the SEVA standard, every DNA portion of the plasmid vectors is minimized, edited for flaws in their sequence and/or functionality, and endowed with physical connectivity through three inter-segment insulators that are flanked by fixed, rare restriction sites. Such a scaffold enables the exchangeability of multiple origins of replication and diverse antibiotic selection markers to shape a frame for their further combination with a large variety of cargo modules that can be used for varied end-applications. The core collection of constructs that are available at the SEVA-DB has been produced as a starting point for the further expansion of the formatted vector platform. We argue that adoption of the SEVA format can become a shortcut to fill the phenomenal gap between the existing power of DNA synthesis and the actual engineering of predictable and efficacious bacteria.

Increasing signal specificity of the TOL network of Pseudomonas putida mt-2 by rewiring the connectivity of the master regulator XylR

Prokaryotic transcription factors (TFs) that bind small xenobiotic molecules (e.g., TFs that drive genes that respond to environmental pollutants) often display a promiscuous effector profile for analogs of the bona fide chemical signals. XylR, the master TF for expression of the m-xylene biodegradation operons encoded in the TOL plasmid pWW0 of Pseudomonas putida, responds not only to the aromatic compound but also, albeit to a lesser extent, to many other aromatic compounds, such as 3-methylbenzylalcohol (3MBA). We have examined whether such a relaxed regulatory scenario can be reshaped into a high-capacity/high-specificity regime by changing the connectivity of this effector-sensing TF within the rest of the circuit rather than modifying XylR structure itself. To this end, the natural negative feedback loop that operates on xylR transcription was modified with a translational attenuator that brings down the response to 3MBA while maintaining the transcriptional output induced by m-xylene (as measured with a luxCDABE reporter system). XylR expression was then subject to a positive feedback loop in which the TF was transcribed from its own target promoters, each known to hold different input/output transfer functions. In the first case (xylR under the strong promoter of the upper TOL operon, Pu), the reporter system displayed an increased transcriptional capacity in the resulting network for both the optimal and the suboptimal XylR effectors. In contrast, when xylR was expressed under the weaker Ps promoter, the resulting circuit unmistakably discriminated m-xylene from 3MBA. The non-natural connectivity engineered in the network resulted both in a higher promoter activity and also in a much-increased signal-to-background ratio. These results indicate that the working regimes of given genetic circuits can be dramatically altered through simple changes in the way upstream transcription factors are self-regulated by positive or negative feedback loops.

It is generally taken for granted that promoters regulated by transcriptional factors (TFs) that respond to small molecules control their specificity to given effectors by tightening or relaxing the intrinsic dual interaction between the TF and the particular inducer. One such promoter is Pu, which drives expression of an operon for the biodegradation of m-xylene by the soil bacterium P. putida mt-2. While XylR, the chief TF of this system, binds this substrate and activates Pu, the same regulator responds, to a lesser extent, to 3-methylbenzylalcohol and thus also activates the promoter. This work provides evidence that such natural effector promiscuity of the system can be altogether suppressed by replacing the naturally occurring negative autoregulation loop that governs XylR expression with an equivalent positive feedback loop. Based on this result, we argue that signal specificity of a given regulatory device depends not only on the TF involved but also on TF connectivity to upstream signals and downstream targets.

Post-transcriptional Boolean computation by combining aptazymes controlling mRNA translation initiation and tRNA activation

In cellular systems environmental and metabolic signals are integrated for the conditional control of gene expression. On the other hand, artificial manipulation of gene expression is of high interest for metabolic and genetic engineering. Especially the reprogramming of gene expression patterns to orchestrate cellular responses in a predictable fashion is considered to be of great importance. Here we introduce a highly modular RNA-based system for performing Boolean logic computation at a post-transcriptional level in Escherichia coli. We have previously shown that artificial riboswitches can be constructed by utilizing ligand-dependent Hammerhead ribozymes (aptazymes). Employing RNA self-cleavage as the expression platform-mechanism of an artificial riboswitch has the advantage that it can be applied to control several classes of RNAs such as mRNAs, tRNAs, and rRNAs. Due to the highly modular and orthogonal nature of these switches it is possible to combine aptazyme regulation of activating a suppressor tRNA with the regulation of mRNA translation initiation. The different RNA classes can be controlled individually by using distinct aptamers for individual RNA switches. Boolean logic devices are assembled by combining such switches in order to act on the expression of a single mRNA. In order to demonstrate the high modularity, a series of two-input Boolean logic operators were constructed. For this purpose, we expanded our aptazyme toolbox with switches comprising novel behaviours with respect to the small molecule triggers thiamine pyrophosphate (TPP) and theophylline. Then, individual switches were combined to yield AND, NOR, and ANDNOT gates. This study demonstrates that post-transcriptional aptazyme-based switches represent versatile tools for engineering advanced genetic devices and circuits without the need for regulatory protein cofactors.

A GFP-lacZ bicistronic reporter system for promoter analysis in environmental gram-negative bacteria

Here, we describe a bicistronic reporter system for the analysis of promoter activity in a variety of Gram-negative bacteria at both the population and single-cell levels. This synthetic genetic tool utilizes an artificial operon comprising the gfp and lacZ genes that are assembled in a suicide vector, which is integrated at specific sites within the chromosome of the target bacterium, thereby creating a monocopy reporter system. This tool was instrumental for the complete in vivo characterization of two promoters, Pb and Pc, that drive the expression of the benzoate and catechol degradation pathways, respectively, of the soil bacterium Pseudomonas putida KT2440. The parameterization of these promoters in a population (using β-galactosidase assays) and in single cells (using flow cytometry) was necessary to examine the basic numerical features of these systems, such as the basal and maximal levels and the induction kinetics in response to an inducer (benzoate). Remarkably, GFP afforded a view of the process at a much higher resolution compared with standard lacZ tests; changes in fluorescence faithfully reflected variations in the transcriptional regimes of individual bacteria. The broad host range of the vector/reporter platform is an asset for the characterization of promoters in different bacteria, thereby expanding the diversity of genomic chasses amenable to Synthetic Biology methods.

Whole-cell biochips for online water monitoring

Chip-integrated luminescent recombinant reporter bacteria were combined with fluidics and light detection systems to form a real-time water biomonitor. The biomonitor was exposed to a continuous water flow for up to ten days, in the course of which it was challenged with spikes of both model toxic compounds and toxic environmental samples. All simulated contamination events were reported within 0.5-2.5 h. Furthermore, the response pattern of the reporter bacteria was indicative of the nature of the contaminating chemicals. Efforts were aimed at improving signal quality and at the development of an alarm management software. Following further research, a device of the proposed design could be implemented in monitoring networks as an early warning system against water pollution by toxic chemicals.

Attenuation of loop-receptor interactions with pseudoknot formation

RNA tetraloops can recognize receptors to mediate long-range interactions in stable natural RNAs. In vitro selected GNRA tetraloop/receptor interactions are usually more ‘G/C-rich’ than their ‘A/U-rich’ natural counterparts. They are not as widespread in nature despite comparable biophysical and chemical properties. Moreover, while AA, AC and GU dinucleotide platforms occur in natural GAAA/11 nt receptors, the AA platform is somewhat preferred to the others. The apparent preference for ‘A/U-rich’ GNRA/receptor interactions in nature might stem from an evolutionary adaptation to avoid folding traps at the level of the larger molecular context. To provide evidences in favor of this hypothesis, several riboswitches based on natural and artificial GNRA receptors were investigated in vitro for their ability to prevent inter-molecular GNRA/receptor interactions by trapping the receptor sequence into an alternative intra-molecular pseudoknot. Extent of attenuation determined by native gel-shift assays and co-transcriptional assembly is correlated to the G/C content of the GNRA receptor. Our results shed light on the structural evolution of natural long-range interactions and provide design principles for RNA-based attenuator devices to be used in synthetic biology and RNA nanobiotechnology.

Protein and RNA engineering to customize microbial molecular reporting

Nature takes advantage of the malleability of protein and RNA sequence and structure to employ these macromolecules as molecular reporters whose conformation and functional roles depend on the presence of a specific ligand (an "effector" molecule). By following nature's example, ligand-responsive proteins and RNA molecules are now routinely engineered and incorporated into customized molecular reporting systems (biosensors). Microbial small-molecule biosensors and endogenous molecular reporters based on these sensing components find a variety of applications that include high-throughput screening of biosynthesis libraries, environmental monitoring, and novel gene regulation in synthetic biology. Here, we review recent advances in engineering small-molecule recognition by proteins and RNA and in coupling in vivo ligand binding to reporter-gene expression or to allosteric activation of a protein conferring a detectable phenotype. Emphasis is placed on microbial screening systems that serve as molecular reporters and facilitate engineering the ligand-binding component to recognize new molecules.

Online monitoring of water toxicity by use of bioluminescent reporter bacterial biochips

We describe a flow-through biosensor for online continuous water toxicity monitoring. At the heart of the device are disposable modular biochips incorporating agar-immobilized bioluminescent recombinant reporter bacteria, the responses of which are probed by single-photon avalanche diode detectors. To demonstrate the biosensor capabilities, we equipped it with biochips harboring both inducible and constitutive reporter strains and exposed it to a continuous water flow for up to 10 days. During these periods we challenged the biosensor with 2-h pulses of water spiked with model compounds representing different classes of potential water pollutants, as well as with a sample of industrial wastewater. The biosensor reporter panel detected all simulated contamination events within 0.5-2.5 h, and its response was indicative of the nature of the contaminating chemicals. We believe that a biosensor of the proposed design can be integrated into future water safety and security networks, as part of an early warning system against accidental or intentional water pollution by toxic chemicals.

Implementing an OR-NOT (ORN) logic gate with components of the SOS regulatory network of Escherichia coli

Whether biological or electronic, man-engineered computation is based on logic circuits assembled with binary gates that are interconnected to perform Boolean operations. We report here the rewiring of the SOS system of Escherichia in a fashion that makes the output of both the recA and lexA promoters to faithfully follow the pattern of a binary composite OR-NOT gate (ORN) in which the inputs are DNA damage (e.g. nalidixic acid addition) and IPTG as an exogenous signal. Unlike other non-natural gates whose implementation requires changes in genes and promoters of the genome of the host cells, this ORN was brought about by the sole addition of wild-type bacteria with a plasmid encoding a module for LacI(q)-dependent expression of lexA. Specifically, we demonstrate that the interplay between native, chromosomally-encoded components of the SOS system and the extra parts engineered in such a plasmid made the desired performance to happen without any modification of the core DNA-damage response network. It is thus possible to artificially interface autonomous cell networks with a predetermined logic by means of Boolean gates built with regulatory elements already functioning in the recipient organism.

Plants: biofactories for a sustainable future?

Depletion of oil reserves and the associated effects on climate change have prompted a re-examination of the use of plant biomass as a sustainable source of organic carbon for the large-scale production of chemicals and materials. While initial emphasis has been placed on biofuel production from edible plant sugars, the drive to reduce the competition between crop usage for food and non-food applications has prompted massive research efforts to access the less digestible saccharides in cell walls (lignocellulosics). This in turn has prompted an examination of the use of other plant-derived metabolites for the production of chemicals spanning the high-value speciality sectors through to platform intermediates required for bulk production. The associated science of biorefining, whereby all plant biomass can be used efficiently to derive such chemicals, is now rapidly developing around the world. However, it is clear that the heterogeneity and distribution of organic carbon between valuable products and waste streams are suboptimal. As an alternative, we now propose the use of synthetic biology approaches to 're-construct' plant feedstocks for optimal processing of biomass for non-food applications. Promising themes identified include re-engineering polysaccharides, deriving artificial organelles, and the reprogramming of plant signalling and secondary metabolism.

The logicome of environmental bacteria: merging catabolic and regulatory events with Boolean formalisms

The regulatory and metabolic networks that rule biodegradation of pollutants by environmental bacteria are wired to the rest of the cellular physiology through both transcriptional factors and intermediary signal molecules. In this review, we examine some formalisms for describing catalytic/regulatory circuits of this sort and advocate the adoption of Boolean logic for combining transcriptional and enzymatic occurrences in the same biological system. As an example, we show how known regulatory and metabolic actions that bring about biodegradation of m-xylene by Pseudomonas putida mt-2 can be represented as clusters of binary operations and then reconstructed as a digital network. Despite the many simplifications, Boolean tools still capture the gross behaviour of the system even in the absence of kinetic constants determined experimentally. On this basis, we argue that still with a limited volume of data binary formalisms allow us to penetrate the raison d'être of extant regulatory and metabolic architectures.

Synthetic toxicology: where engineering meets biology and toxicology

This article examines the implications of synthetic biology (SB) for toxicological sciences. Starting with a working definition of SB, we describe its current subfields, namely, DNA synthesis, the engineering of DNA-based biological circuits, minimal genome research, attempts to construct protocells and synthetic cells, and efforts to diversify the biochemistry of life through xenobiology. Based on the most important techniques, tools, and expected applications in SB, we describe the ramifications of SB for toxicology under the label of synthetic toxicology. We differentiate between cases where SB offers opportunities for toxicology and where SB poses challenges for toxicology. Among the opportunities, we identified the assistance of SB to construct novel toxicity testing platforms, define new toxicity-pathway assays, explore the potential of SB to improve in vivo biotransformation of toxins, present novel biosensors developed by SB for environmental toxicology, discuss cell-free protein synthesis of toxins, reflect on the contribution to toxic use reduction, and the democratization of toxicology through do-it-yourself biology. Among the identified challenges for toxicology, we identify synthetic toxins and novel xenobiotics, biosecurity and dual-use considerations, the potential bridging of toxic substances and infectious agents, and do-it-yourself toxin production.