Synthetic Biology

Comparing photosynthetic and photovoltaic efficiencies is not a simple issue. Although both processes harvest the energy in sunlight, they operate in distinctly different ways and produce different types of products: biomass or chemical fuels in the case of natural photosynthesis and nonstored electrical current in the case of photovoltaics. In order to find common ground for evaluating energy-conversion efficiency, we compare natural photosynthesis with present technologies for photovoltaic-driven electrolysis of water to produce hydrogen. Photovoltaic-driven electrolysis is the more efficient process when measured on an annual basis, yet short-term yields for photosynthetic conversion under optimal conditions come within a factor of 2 or 3 of the photovoltaic benchmark. We consider opportunities in which the frontiers of synthetic biology might be used to enhance natural photosynthesis for improved solar energy conversion efficiency.

Synthetic biology has the potential to transform how we interact with our environment and how we approach human health. Conventional genetic engineering approaches for solving complex problems typically focus on tweaking one or a few genes. Synthetic biology, by contrast, approaches these problems from a novel, engineering-driven perspective that focuses on wholesale changes to existing cellular architectures and the construction of elaborate systems from the ground up. Synthetic biology has the potential to fabricate practical organisms that could clean hazardous waste in inaccessible places 1 , to use plants to sense chemicals and respond accordingly 2,3 , to produce clean fuel in an efficient and sustainable fashion 4 , or to recognize and destroy tumours 5 . Whether addressing an existing problem or creating new capabilities, effective solutions can be inspired by, but need not mimic, natural biological processes. Our new designs can potentially be more robust or efficient than systems that have been fashioned by evolution.

Synthetic biologists engineer complex artificial biological systems to investigate natural biological phenomena and for a variety of applications. We outline the basic features of synthetic biology as a new engineering discipline, covering examples from the latest literature and reflecting on the features that make it unique among all other existing engineering fields. We discuss methods for designing and constructing engineered cells with novel functions in a framework of an abstract hierarchy of biological devices, modules, cells, and multicellular systems. The classical engineering strategies of standardization, decoupling, and abstraction will have to be extended to take into account the inherent characteristics of biological devices and modules. To achieve predictability and reliability, strategies for engineering biology must include the notion of cellular context in the functional definition of devices and modules, use rational redesign and directed evolution for system optimization, and focus on accomplishing tasks using cell populations rather than individual cells. The discussion brings to light issues at the heart of designing complex living systems and provides a trajectory for future development.

Mycoplasma genitalium has the smallest genome of any organism that can be grown in pure culture. It has a minimal metabolism and little genomic redundancy. Consequently, its genome is expected to be a close approximation to the minimal set of genes needed to sustain bacterial life. Using global transposon mutagenesis, we isolated and characterized gene disruption mutants for 100 different nonessential protein-coding genes. None of the 43 RNA-coding genes were disrupted. Herein, we identify 382 of the 482 M. genitalium protein-coding genes as essential, plus five sets of disrupted genes that encode proteins with potentially redundant essential functions, such as phosphate transport. Genes encoding proteins of unknown function constitute 28% of the essential protein-coding genes set. Disruption of some genes accelerated M. genitalium growth. minimal cell ͉ Mycoplasma genitalium ͉ synthetic biology ͉ transposon mutagenesis Conflict of interest statement: No conflicts declared. Freely available online through the PNAS open access option.

Symbolic regression and modeling are tightly linked in many Bioinformatics, Systems and Synthetic Biology problems. In this paper we briefly overview two problems, and the approaches we have use to tackle them, that can be deemed to represent this entwining of regression and modeling, namely, the evolutionary discovery of (1) effective energy functions for protein structure prediction and (2) models that capture biological behavior at the gene, signaling and metabolic networks level. These problems are not, strictly speaking, "regression problems" but they do share several characteristics with the latter, namely, a symbolic representation of a solution is sought , this symbolic representation must be human understandable and the results obtained by the symbolic and human interpretable solution must fit the available data without over-learning.

Computation can be performed in living cells by DNA-encoded circuits that process sensory information and control biological functions. Their construction is time-intensive, requiring manual part assembly and balancing of regulator expression. We describe a design environment, Cello, in which a user writes Verilog code that is automatically transformed into a DNA sequence. Algorithms build a circuit diagram, assign and connect gates, and simulate performance. Reliable circuit design requires the insulation of gates from genetic context, so that they function identically when used in different circuits. We used Cello to design 60 circuits forEscherichia coli(880,000 base pairs of DNA), for which each DNA sequence was built as predicted by the software with no additional tuning. Of these, 45 circuits performed correctly in every output state (up to 10 regulators and 55 parts), and across all circuits 92% of the output states functioned as predicted. Design automation simplifies the in...

transcription activator-like effectors (tales) are a class of naturally occurring Dna-binding proteins found in the plant pathogen Xanthomonas sp. the Dna-binding domain of each tale consists of tandem 34-amino acid repeat modules that can be rearranged according to a simple cipher to target new Dna sequences. customized tales can be used for a wide variety of genome engineering applications, including transcriptional modulation and genome editing. Here we describe a toolbox for rapid construction of custom tale transcription factors (tale-tFs) and nucleases (talens) using a hierarchical ligation procedure. this toolbox facilitates affordable and rapid construction of custom tale-tFs and talens within 1 week and can be easily scaled up to construct tales for multiple targets in parallel. We also provide details for testing the activity in mammalian cells of custom tale-tFs and talens using quantitative reverse-transcription pcr and surveyor nuclease, respectively. the tale toolbox described here will enable a broad range of biological applications. protocol 172 | VOL.7 NO.1 | 2012 | nature protocols DNA-targeting applications (e.g., transcriptional modulator 3-5,8 , nuclease 4,7,9,11-15 , recombinase 37-39 , transposase 40,41 ).

We have constructed a synthetic ecosystem consisting of two Escherichia coli populations, which communicate bi-directionally through quorum sensing and regulate each other's gene expression and survival via engineered gene circuits. Our synthetic ecosystem resembles canonical predatorprey systems in terms of logic and dynamics. The predator cells kill the prey by inducing expression of a killer protein in the prey, while the prey rescue the predators by eliciting expression of an antidote protein in the predator. Extinction, coexistence and oscillatory dynamics of the predator and prey populations are possible depending on the operating conditions as experimentally validated by long-term culturing of the system in microchemostats. A simple mathematical model is developed to capture these system dynamics. Coherent interplay between experiments and mathematical analysis enables exploration of the dynamics of interacting populations in a predictable manner.

Living cells display complex signal processing behaviors, many of which are mediated by networks of proteins specialized for signal transduction. Here we focus on the question of how the remarkably diverse array of eukaryotic signaling circuits may have evolved. Many of the mechanisms that connect signaling proteins into networks are highly modular: The core catalytic activity of a signaling protein is physically and functionally separable from molecular domains or motifs that determine its linkage to both inputs and outputs. This high degree of modularity may make these systems more evolvable—in principle, novel circuits, and therefore highly innovative regulatory behaviors, can arise from relatively simple genetic events such as recombination, deletion, or insertion. In support of this hypothesis, recent studies show that such modular systems can be exploited to engineer nonnatural signaling proteins and pathways with novel behavior.

Antimicrobial drug development is increasingly lagging behind the evolution of antibiotic resistance, and as a result, there is a pressing need for new antibacterial therapies that can be readily designed and implemented. In this work, we engineered bacteriophage to overexpress proteins and attack gene networks that are not directly targeted by antibiotics. We show that suppressing the SOS network in Escherichia coli with engineered bacteriophage enhances killing by quinolones by several orders of magnitude in vitro and significantly increases survival of infected mice in vivo. In addition, we demonstrate that engineered bacteriophage can enhance the killing of antibiotic-resistant bacteria, persister cells, and biofilm cells, reduce the number of antibiotic-resistant bacteria that arise from an antibiotic-treated population, and act as a strong adjuvant for other bactericidal antibiotics (e.g., aminoglycosides and ␤-lactams). Furthermore, we show that engineering bacteriophage to target non-SOS gene networks and to overexpress multiple factors also can produce effective antibiotic adjuvants. This work establishes a synthetic biology platform for the rapid translation and integration of identified targets into effective antibiotic adjuvants.

Many compounds being considered as candidates for advanced biofuels are toxic to microorganisms. This introduces an undesirable trade-off when engineering metabolic pathways for biofuel production because the engineered microbes must balance production against survival. Cellular export systems, such as efflux pumps, provide a direct mechanism for reducing biofuel toxicity. To identify novel biofuel pumps, we used bioinformatics to generate a list of all efflux pumps from sequenced bacterial genomes and prioritized a subset of targets for cloning. The resulting library of 43 pumps was heterologously expressed in Escherichia coli, where we tested it against seven representative biofuels. By using a competitive growth assay, we efficiently distinguished pumps that improved survival. For two of the fuels (n-butanol and isopentanol), none of the pumps improved tolerance. For all other fuels, we identified pumps that restored growth in the presence of biofuel. We then tested a beneficial pump directly in a production strain and demonstrated that it improved biofuel yields. Our findings introduce new tools for engineering production strains and utilize the increasingly large database of sequenced genomes.

One of the important challenges in the emerging field of synthetic biology is designing artificial networks that achieve coordinated behavior in cell communities. Here we present a synthetic multicellular bacterial system where receiver cells exhibit transient gene expression in response to a long-lasting signal from neighboring sender cells. The engineered sender cells synthesize an inducer, an acyl-homoserine lactone (AHL), which freely diffuses to spatially proximate receiver cells. The receiver cells contain a pulse-generator circuit that incorporates a feed-forward regulatory motif. The circuit responds to a long-lasting increase in the level of AHL by transiently activating, and then repressing, the expression of a GFP. Based on simulation models, we engineered variants of the pulse-generator circuit that exhibit different quantitative responses such as increased duration and intensity of the pulse. As shown by our models and experiments, the maximum amplitude and timing of the pulse depend not only on the final inducer concentration, but also on its rate of increase. The ability to differentiate between various rates of increase in inducer concentrations affords the system a unique spatiotemporal behavior for cells grown on solid media. Specifically, receiver cells can respond to communication from nearby sender cells while completely ignoring communication from senders cells further away, despite the fact that AHL concentrations eventually reach high levels everywhere. Because of the resemblance to naturally occurring feed-forward motifs, the pulse generator can serve as a model to improve our understanding of such systems. synthetic biology ͉ cell-cell signaling ͉ gene regulation ͉ feed-forward

Cooperative interactions are key to diverse biological phenomena ranging from multicellularity to mutualism. Such diversity makes the ability to create and control cooperation desirable for potential applications in areas as varied as agriculture, pollutant treatment, and medicine. Here we show that persistent cooperation can be engineered by introducing a small set of genetic modifications into previously noninteracting cell populations. Specifically, we report the construction of a synthetic obligatory cooperative system, termed CoSMO (cooperation that is synthetic and mutually obligatory), which consists of a pair of nonmating yeast strains, each supplying an essential metabolite to the other strain. The behavior of the two strains in isolation, however, revealed unintended constraints that restrict cooperation, such as asymmetry in starvation tolerance and delays in nutrient release until near cell death. However, the joint system is shown mathematically and experimentally to be viable over a wide range of initial conditions, with oscillating population ratio settling to a value predicted by nutrient supply and consumption. Unexpectedly, even in the absence of explicitly engineered mechanisms to stabilize cooperation, the cooperative system can consistently develop increased ability to survive reductions in population density. Extending synthetic biology from the design of genetic circuits to the engineering of ecological interactions, CoSMO provides a quantitative system for linking processes at the cellular level to the collective behavior at the system level, as well as a genetically tractable system for studying the evolution of cooperation. mathematical modeling ͉ mutualism ͉ obligate cooperation ͉ quantitative biology ͉ synthetic ecology

Background: Biosafety is a key aspect in the international Genetically Engineered Machine (iGEM) competition, which offers student teams an amazing opportunity to pursue their own research projects in the field of Synthetic Biology. iGEM projects often involve the creation of genetically engineered bacterial strains. To minimize the risks associated with bacterial release, a variety of biosafety systems were constructed, either to prevent survival of bacteria outside the lab or to hinder horizontal or vertical gene transfer.

Systems biology approaches are extensively used to model and reverse engineer gene regulatory networks from experimental data. Conversely, synthetic biology allows ''de novo'' construction of a regulatory network to seed new functions in the cell. At present, the usefulness and predictive ability of modeling and reverse engineering cannot be assessed and compared rigorously. We built in the yeast Saccharomyces cerevisiae a synthetic network, IRMA, for in vivo ''benchmarking'' of reverse-engineering and modeling approaches. The network is composed of five genes regulating each other through a variety of regulatory interactions; it is negligibly affected by endogenous genes, and it is responsive to small molecules. We measured time series and steady-state expression data after multiple perturbations. These data were used to assess state-of-the-art modeling and reverse-engineering techniques. A semiquantitative model was able to capture and predict the behavior of the network. Reverse engineering based on differential equations and Bayesian networks correctly inferred regulatory interactions from the experimental data.

Evidence is growing that the gut microbiota modulates the host response to chemotherapeutic drugs, with three main clinical outcomes: facilitation of drug efficacy; abrogation and compromise of anticancer effects; and mediation of toxicity. The implication is that gut microbiota are critical to the development of personalized cancer treatment strategies and, therefore, a greater insight into prokaryotic co-metabolism of chemotherapeutic drugs is now required. This thinking is based on evidence from human, animal and in vitro studies that gut bacteria are intimately linked to the pharmacological effects of chemotherapies (5-fluorouracil, cyclophosphamide, irinotecan, oxaliplatin, gemcitabine, methotrexate) and novel targeted immunotherapies such as anti-PD-L1 and anti-CLTA-4 therapies. The gut microbiota modulate these agents through key mechanisms, structured as the 'TIMER' mechanistic framework: Translocation, Immunomodulation, Metabolism, Enzymatic degradation, and Reduced...

The engineering of mechanical, electrical and chemical systems is enabled by well-established frameworks for handling complexity, reliable means of probing and manipulating system states and the use of testing platforms-tools that are largely lacking in the engineering of biology. Developing properly functioning biological circuits can involve complicated protocols for DNA construction, rudimentary modelguided and rational design, and repeated rounds of trial and error followed by fine-tuning. Limitations in characterizing kinetic processes and interactions between synthetic components and other unknown constituents in vivo make troubleshooting and modeling frustrating and prohibitively time consuming. As a result, the design cycle for engineering synthetic gene networks remains slow and error prone.

Background: Direct synthesis of genes is rapidly becoming the most efficient way to make functional genetic constructs and enables applications such as codon optimization, RNAi resistant genes and protein engineering. Here we introduce a software tool that drastically facilitates the design of synthetic genes.

We give a description of a Petri net-based framework for modelling and analysing biochemical pathways, which unifies the qualitative, stochastic and continuous paradigms. Each perspective adds its contribution to the understanding of the system, thus the three approaches do not compete, but complement each other. We illustrate our approach by applying it to an extended model of the three stage cascade, which forms the core of the ERK signal transduction pathway. Consequently our focus is on transient behaviour analysis. We demonstrate how qualitative descriptions are abstractions over stochastic or continuous descriptions, and show that the stochastic and continuous models approximate each other. Although our framework is based on Petri nets, it can be applied more widely to other formalisms which are used to model and analyse biochemical networks.

Synthetic biology is interpreted as the engineering-driven building of increasingly complex biological entities for novel applications. Encouraged by progress in the design of artificial gene networks, de novo DNA synthesis and protein engineering, we review the case for this emerging discipline. Key aspects of an engineering approach are purpose-orientation, deep insight into the underlying scientific principles, a hierarchy of abstraction including suitable interfaces between and within the levels of the hierarchy, standardization, and the separation of design and fabrication. Synthetic biology investigates possibilities to implement these requirements into the process of engineering biological systems. This is illustrated on the DNA level by the implementation of engineering-inspired artificial operations such as toggle switching, oscillating, or production of spatial patterns. On the protein level, the functionally self-contained domain structure of a number of proteins suggests possibilities for essentially Lego-like recombination which can be exploited for reprogramming DNA binding domain specificities or signaling pathways. Alternatively, computational design emerges to rationally reprogram enzyme function. Finally, the increasing facility of de novo DNA synthesis -synthetic biology's system fabrication process -supplies the possibility to implement novel designs for ever more complex systems. Some of these elements have merged to realize the first tangible synthetic biology applications in the area of manufacturing of pharmaceutical compounds.

modular and orthogonal genetic logic gates are essential for building robust biologically based digital devices to customize cell signalling in synthetic biology. Here we constructed an orthogonal AnD gate in Escherichia coli using a novel hetero-regulation module from Pseudomonas syringae. The device comprises two co-activating genes hrpR and hrpS controlled by separate promoter inputs, and a σ 54 -dependent hrpL promoter driving the output. The hrpL promoter is activated only when both genes are expressed, generating digital-like AnD integration behaviour. The AnD gate is demonstrated to be modular by applying new regulated promoters to the inputs, and connecting the output to a noT gate module to produce a combinatorial nAnD gate. The circuits were assembled using a parts-based engineering approach of quantitative characterization, modelling, followed by construction and testing. The results show that new genetic logic devices can be engineered predictably from novel native orthogonal biological control elements using quantitatively in-context characterized parts.

Recent advances in DNA synthesis technology have enabled the construction of novel genetic pathways and genomic elements, furthering our understanding of system-level phenomena. The ability to synthesize large segments of DNA allows the engineering of pathways and genomes according to arbitrary sets of design principles. Here we describe a synthetic yeast genome project, Sc2.0, and the first partially synthetic eukaryotic chromosomes, Saccharomyces cerevisiae chromosome synIXR, and semi-synVIL. We defined three design principles for a synthetic genome as follows: first, it should result in a (near) wild-type phenotype and fitness; second, it should lack destabilizing elements such as tRNA genes or transposons; and third, it should have genetic flexibility to facilitate future studies. The synthetic genome features several systemic modifications complying with the design principles, including an inducible evolution system, SCRaMbLE (synthetic chromosome rearrangement and modification by loxP-mediated evolution). We show the utility of SCRaMbLE as a novel method of combinatorial mutagenesis, capable of generating complex genotypes and a broad variety of phenotypes. When complete, the fully synthetic genome will allow massive restructuring of the yeast genome, and may open the door to a new type of combinatorial genetics based entirely on variations in gene content and copy number.

Metabolic engineering for the overproduction of high-value small molecules is dependent upon techniques in directed evolution to improve production titers. The majority of small molecules targeted for overproduction are inconspicuous and cannot be readily obtained by screening. We provide a review on the development of high-throughput colorimetric, fluorescent, and growth-coupled screening techniques, enabling inconspicuous small-molecule detection. We first outline constraints on throughput imposed during the standard directed evolution workflow (library construction, transformation, and screening) and establish a screening and selection ladder on the basis of small-molecule assay throughput and sensitivity. An in-depth analysis of demonstrated screening and selection approaches for small-molecule detection is provided. Particular focus is placed on in vivo biosensor-based detection methods that reduce or eliminate in vitro assay manipulations and increase throughput. We conclude by providing our prospectus for the future, focusing on transcription factor-based detection systems as a natural microbial mode of small-molecule detection. 563 Annu. Rev. Biochem. 2010.79:563-590. Downloaded from www.annualreviews.org by University of California -San Francisco UCSF on 11/08/13. For personal use only.

Wire connections to promoter REs GOI Trans. initiation complex Pol II Tuning trans. output OUTPUT OUTPUT Operate cooperatively with other TFs Integrate input signals Specify trans. I/O relationship TF Core promoter Upstream REs TF INPUT GOI Trans. initiation complex Pol II Core promoter ZF operators AD Customizable wiring between sTFs and REs Tunable cooperativity with other TFs Trans. activation domain Modular protein interaction domains OD003644 (J.J.C.) and DP1 OD006862 (J.K.

One of the major objectives that bottom-up Synthetic Biology shares with Chemical Biology is to engineer extant biological molecules to implement novel functionalities in living systems. Proteins, due to their astonishing structural and functional versatility and to their central roles in the biology of cells, should be cornerstones of Synthetic Biology. In particular, protein amyloid cross-β assemblies constitute one of the most stable, conceptually simple, and universal macromolecular architectures ever found in Nature and thus have enormous potential to be explored. This article focuses on the concepts behind the usage of the amyloid cross-β structural framework as a Synthetic Biology part, underlining recent basic findings and ideas. The pros and the cons associated with the polymorphism and the cellular toxicity of protein amyloids are also discussed, keeping in mind the possible suitability of these protein assemblies for scaffolding novel orthogonal macromolecular devices in vivo.

The chemical properties and diversity of volatile isoprenoids lends them to a broad variety of biological roles. It also lends them to a host of biotechnological applications, both by taking advantage of their natural functions and by using them as industrial chemicals/chemical feedstocks. Natural functions include roles as insect attractants and repellents, abiotic stress protectants in pathogen defense, etc. Industrial applications include use as pharmaceuticals, flavours, fragrances, fuels, fuel additives, etc. Here we will examine the ways in which researchers have so far found to exploit volatile isoprenoids using biotechnology. Production and/or modification of volatiles using metabolic engineering in both plants and microorganisms are reviewed, including engineering through both mevalonate and methylerythritol diphosphate pathways. Recent advances are illustrated using several case studies (herbivores and bodyguards, isoprene, and monoterpene production in microbes). Systems and synthetic biology tools with particular utility for metabolic engineering are also reviewed. Finally, we discuss the practical realities of various applications in modern biotechnology, explore possible future applications, and examine the challenges of moving these technologies forward so that they can deliver tangible benefits. While this review focuses on volatile isoprenoids, many of the engineering approaches described here are also applicable to non-isoprenoid volatiles and to non-volatile isoprenoids.

Synthetic Biology requires efficient and versatile DNA assembly systems to facilitate the building of new genetic modules/ pathways from basic DNA parts in a standardized way. Here we present GoldenBraid (GB), a standardized assembly system based on type IIS restriction enzymes that allows the indefinite growth of reusable gene modules made of standardized DNA pieces. The GB system consists of a set of four destination plasmids (pDGBs) designed to incorporate multipartite assemblies made of standard DNA parts and to combine them binarily to build increasingly complex multigene constructs. The relative position of type IIS restriction sites inside pDGB vectors introduces a double loop (''braid'') topology in the cloning strategy that allows the indefinite growth of composite parts through the succession of iterative assembling steps, while the overall simplicity of the system is maintained. We propose the use of GoldenBraid as an assembly standard for Plant Synthetic Biology. For this purpose we have GB-adapted a set of binary plasmids for A. tumefaciens-mediated plant transformation. Fast GB-engineering of several multigene T-DNAs, including two alternative modules made of five reusable devices each, and comprising a total of 19 basic parts are also described.

Isoprenoid secondary metabolites are a rich source of commercial products that have not been fully explored. At present, there are isoprenoid products used in cancer therapy, the treatment of infectious diseases, and crop protection. All isoprenoids share universal prenyl diphosphate precursors synthesized via two distinct pathways. From these universal precursors, the biosynthetic pathways to specific isoprenoids diverge resulting in a staggering array of products. Taking advantage of this diversity has been the focus of much effort in metabolic engineering heterologous hosts. In addition, the engineering of the mevalonate pathway has increased levels of the universal precursors available for heterologous production. Finally, we will describe the efforts to produce to commercial terpenoids, paclitaxel and artemisinin.

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In this review, we address recent advances made in pathway engineering, directed evolution, and systems/ synthetic biology approaches employed in the production and modification of flavonoids from microbial cells. The review is divided into two major parts. In the first, various metabolic engineering and system/synthetic biology approaches used for production of flavonoids and derivatives are discussed broadly. All the manipulations/ engineering accomplished on the microorganisms since 2000 are described in detail along with the biosynthetic pathway enzymes, their sources, structures of the compounds, and yield of each product. In the second part of the review, post-modifications of flavonoids by four major reactions, namely glycosylations, methylations, hy-droxylations and prenylations using recombinant strains are described.

A highly desired part of the synthetic biology toolbox is an embedded chemical microcontroller, capable of autonomously following a logic program specified by a set of instructions, and interacting with its cellular environment. Strategies for incorporating logic in aqueous chemistry have focused primarily on implementing components, such as logic gates, that are composed into larger circuits, with each logic gate in the circuit corresponding to one or more molecular species. With this paradigm, designing and producing new molecular species is necessary to perform larger computations. An alternative approach begins by noticing that chemical systems on the small scale are fundamentally discrete and stochastic. In particular, the exact molecular counts of each molecular species present, is an intrinsically available form of information. This might appear to be a very weak form of information, perhaps quite difficult for computations to utilize. Indeed, it has been shown that error-free Turing universal computation is impossible in this setting. Nevertheless, we show a design of a chemical computer that achieves fast and reliable Turing-universal computation using molecular counts. Our scheme uses only a small number of different molecular species to do computation of arbitrary complexity. The total probability of error of the computation can be made arbitrarily small (but not zero) by adjusting the initial molecular counts of certain species. While physical implementations would be difficult, these results demonstrate that molecular counts can be a useful form of information for small molecular systems such as those operating within cellular environments.

Defining prospective pathways by which zoonoses evolve and emerge as human pathogens is critical for anticipating and controlling both natural and deliberate pandemics. However, predicting tenable pathways of animal-to-human movement has been hindered by challenges in identifying reservoir species, cultivating zoonotic organisms in culture, and isolating full-length genomes for cloning and genetic studies. The ability to design and recover pathogens reconstituted from synthesized cDNAs has the potential to overcome these obstacles by allowing studies of replication and pathogenesis without identification of reservoir species or cultivation of primary isolates. Here, we report the design, synthesis, and recovery of the largest synthetic replicating life form, a 29.

The biggest challenge for modern biology is to integrate multidisciplinary approaches towards understanding the organizational and functional complexity of biological systems at different hierarchies, starting from the subcellular molecular mechanisms (microscopic) to the functional interactions of ecological communities (macroscopic). The plant-insect interaction is a good model for this purpose with the availability of an enormous amount of information at the molecular and the ecosystem levels. Changing global climatic conditions are abruptly resetting plant-insect interactions. Integration of discretely located heterogeneous information from the ecosystem to genes and pathways will be an advantage to understand the complexity of plant-insect interactions. This review will present the recent developments in omics-based high-throughput experimental approaches, with particular emphasis on studying plant defence responses against insect attack. The review highlights the importance of using integrative systems approaches to study plant-insect interactions from the macroscopic to the microscopic level. We analyse the current efforts in generating, integrating and modelling multiomics data to understand plant-insect interaction at a systems level. As a future prospect, we highlight the growing interest in utilizing the synthetic biology platform for engineering insect-resistant plants.

Over the past decade, synthetic biology has emerged as an engineering discipline for biological systems. Compared with other substrates, biology poses a unique set of engineering challenges resulting from an incomplete understanding of natural biological systems and tools for manipulating them. To address these challenges, synthetic biology is advancing from developing proof-of-concept designs to focusing on core platforms for rational and high-throughput biological engineering. These platforms span the entire biological design cycle, including DNA construction, parts libraries, computational design tools, and interfaces for manipulating and probing synthetic circuits. The development of these enabling technologies requires an engineering mindset to be applied to biology, with an emphasis on generalizable techniques in addition to application-specific designs. This review aims to discuss the progress and challenges in synthetic biology and to illustrate areas where synthetic biology may impact biomedical engineering and human health.