Bacterial biosynthetic assembly lines, such as nonribosomal peptide synthetases (NRPSs) and polyketide synthases (PKSs), play a crucial role in the synthesis of natural products that have significant therapeutic potential. The ability to engineer these biosynthetic assembly lines offers opportunities to produce artificial nonribosomal peptides, polyketides, and their hybrids with improved properties. In this study, we introduced a synthetic NRPS variant, termed type S NRPS, which simplifies the engineering process and enables biocombinatorial approaches for generating nonribosomal peptide libraries in a parallelized high-throughput manner. However, initial generations of type S NRPSs exhibited a bottleneck that led to significantly reduced production yields. To address this challenge, we employed two optimization strategies. First, we truncated SYNZIPs from the N- and/or C-terminus of the NRPS. SYNZIPs comprise a large set of well-characterized synthetic protein interaction reagents. Second, we incorporated a structurally flexible glycine-serine linker between the NRPS protein and the attached SYNZIP, aiming to improve dynamic domain-domain interactions. Through an iterative optimization process, we achieved remarkable improvements in production yields, with titer increases of up to 55-fold compared to the nonoptimized counterparts. These optimizations successfully restored production levels of type S NRPSs to those observed in wild-type NRPSs and even surpassed them. Overall, our findings demonstrate the potential of engineering bacterial biosynthetic assembly lines for the production of artificial nonribosomal peptides. In addition, optimizing the SYNZIP toolbox can have valuable implications for diverse applications in synthetic biology, such as metabolic engineering, cell signaling studies, or engineering of other multienzyme complexes, such as PKSs.

The bioengineering of nonribosomal peptide synthetases (NRPSs) is a rapidly developing field to access natural product derivatives and new-to-nature natural products like scaffolds with changed or improved properties. However, the rational (re-)design of these often gigantic assembly-line proteins is by no means trivial and needs in-depth insights into structural flexibility, inter-domain communication, and the role of proofreading by catalytic domains-so it is not surprising that most previous rational reprogramming efforts have been met with limited success. With this practical guide, the result of nearly one decade of NRPS engineering in the Bode lab, we provide valuable insights into the strategies we have developed during this time for the successful engineering and cloning of these fascinating molecular machines.

EFSA was asked by the European Commission to evaluate synthetic biology (SynBio) developments for agri-food use in the near future and to determine whether or not they are expected to constitute potential new hazards/risks. Moreover, EFSA was requested to evaluate the adequacy of existing guidelines for risk assessment of SynBio and if updated guidance is needed. The scope of this Opinion covers food and feed risk assessment, the variety of microorganisms that can be used in the food/feed chain and the whole spectrum of techniques used in SynBio. This Opinion complements a previously adopted Opinion with the evaluation of existing guidelines for the microbial characterisation and environmental risk assessment of microorganisms obtained through SynBio. The present Opinion confirms that microbial SynBio applications for food and feed use, with the exception of xenobionts, could be ready in the European Union in the next decade. New hazards were identified related to the use or production of unusual and/or new-to-nature components. Fifteen cases were selected for evaluating the adequacy of existing guidelines. These were generally adequate for assessing the product, the production process, nutritional and toxicological safety, allergenicity, exposure and post-market monitoring. The comparative approach and a safety assessment per se could be applied depending on the degree of familiarity of the SynBio organism/product with the non-genetically modified counterparts. Updated guidance is recommended for: (i) bacteriophages, protists/microalgae, (ii) exposure to plant protection products and biostimulants, (iii) xenobionts and (iv) feed additives for insects as target species. Development of risk assessment tools is recommended for assessing nutritional value of biomasses, influence of microorganisms on the gut microbiome and the gut function, allergenic potential of new-to-nature proteins, impact of horizontal gene transfer and potential risks of living cell intake. A further development towards a strain-driven risk assessment approach is recommended.

EFSA was asked by the European Commission to consider synthetic biology developments for agri-food use in the near future and to determine if the use of this technology is expected to constitute potential risks and hazards for the environment. Moreover, EFSA was requested to evaluate the adequacy of existing guidelines for risk assessment and if updated guidance is needed. The scope of this Opinion covers viable synthetic biology microorganisms (SynBioMs) expected to be deliberately released into the environment. The evaluation was based on: (i) horizon scanning of published information, (ii) gap analysis of existing guidelines covering the scope of this mandate, and (iii) future outlooks. A horizon scan showed that SynBioM applications could be ready for deliberate release into the environment of the EU in the next decade. However, extensively engineered SynBioMs are only expected in the wider future. For the microbial characterisation and the environmental risk assessment, the existing EFSA Guidances are useful as a basis. The extent to which existing Guidances can be used depends on the familiarity of the SynBioM with non-modified organisms. Among the recommendations for updated Guidance, the range of uses of products to be assessed covering all agri-food uses and taking into account all types of microorganisms, their relevant exposure routes and receiving environments. It is suggested that new EFSA Guidances address all \'specific areas of risk\' as per Directive 2001/18/EC. No novel environmental hazards are expected for current and near future SynBioMs. However, the efficacy by which the SynBioMs interact with the environment may differ. This could lead to increased exposure and risk. Novel hazards connected with the development of xenobionts may be expected in the wider future.

Integral feedback control is commonly used in mechanical and electrical systems to achieve zero steady-state error following an external disturbance. Equivalently, in biological systems, a property known as robust perfect adaptation guarantees robustness to environmental perturbations and return to the pre-disturbance state. Previously, Briat et al proposed a biomolecular design for integral feedback control (robust perfect adaptation) called the antithetic feedback motif. The antithetic feedback controller uses the sequestration binding reaction of two biochemical species to record the integral of the error between the current and the desired output of the network it controls. The antithetic feedback motif has been successfully built using synthetic components in vivo in Escherichia coli and Saccharomyces cerevisiae cells. However, these previous synthetic implementations of antithetic feedback have not produced perfect integral feedback control due to the degradation and dilution of the two controller species. Furthermore, previous theoretical results have cautioned that integral control can only be achieved under stability conditions that not all antithetic feedback motifs necessarily fulfill. In this paper, we study how to design antithetic feedback motifs that simultaneously achieve good stability and small steady-state error properties, even as the controller species are degraded and diluted. We provide simple tuning guidelines to achieve flexible and practical synthetic biological implementations of antithetic feedback control. We use several tools and metrics from control theory to design antithetic feedback networks, paving the path for the systematic design of synthetic biological controllers.

Genetic information in genomes is ordered, arranged in such a way that it constitutes a code, the so-called cis regulatory code. The regulatory machinery of the cell, termed trans-factors, decodes and expresses this information. In this way, genomes maintain a potential repertoire of genetic programs, parts of which are executed depending on the presence of active regulators in each condition. These genetic programs, executed by the regulatory machinery, have functional units in the genome delimited by punctuation-like marks. In genetic terms, these informational phrases correspond to transcription units, which are the minimal genetic information expressed consistently from initiation to termination marks. Between the start and final punctuation marks, additional marks are present that are read by the transcriptional and translational machineries. In this work, we look at all the experimentally described and predicted genetic elements in the bacterium Escherichia coli K-12 MG1655 and define a comprehensive architectural organization of transcription units to reveal the natural genome-design and to guide the construction of synthetic genetic programs.

Mathematical modeling and numerical simulation are crucial to support design decisions in synthetic biology. Accurate estimation of parameter values is key, as direct experimental measurements are difficult and time-consuming. Insufficient data, incompatible measurements, and specialized models that lack universal parameters make this task challenging. Here, we have created a database (PAMDB) that integrates data from 135 publications that contain 118 circuits and 165 genetic parts of the bacterium Escherichia coli. We used a succinct, universal model formulation to describe the part behavior in each circuit. We introduce a constrained consensus inference method that was used to infer the value of the model parameters and evaluated its performance through cross-validation in a benchmark of 23 circuits. We discuss these results and summarize the challenges in data integration and parameter inference. This work provides a resource and a methodology that can be used as a point of reference for synthetic circuit modeling.

BACKGROUND: Model based design plays a fundamental role in synthetic biology. Exploiting modularity, i.e. using biological parts and interconnecting them to build new and more complex biological circuits is one of the key issues. In this context, mathematical models have been used to generate predictions of the behavior of the designed device. Designers not only want the ability to predict the circuit behavior once all its components have been determined, but also to help on the design and selection of its biological parts, i.e. to provide guidelines for the experimental implementation. This is tantamount to obtaining proper values of the model parameters, for the circuit behavior results from the interplay between model structure and parameters tuning. However, determining crisp values for parameters of the involved parts is not a realistic approach. Uncertainty is ubiquitous to biology, and the characterization of biological parts is not exempt from it. Moreover, the desired dynamical behavior for the designed circuit usually results from a trade-off among several goals to be optimized.
RESULTS: We propose the use of a multi-objective optimization tuning framework to get a model-based set of guidelines for the selection of the kinetic parameters required to build a biological device with desired behavior. The design criteria are encoded in the formulation of the objectives and optimization problem itself. As a result, on the one hand the designer obtains qualitative regions/intervals of values of the circuit parameters giving rise to the predefined circuit behavior; on the other hand, he obtains useful information for its guidance in the implementation process. These parameters are chosen so that they can effectively be tuned at the wet-lab, i.e. they are effective biological tuning knobs. To show the proposed approach, the methodology is applied to the design of a well known biological circuit: a genetic incoherent feed-forward circuit showing adaptive behavior.
CONCLUSIONS: The proposed multi-objective optimization design framework is able to provide effective guidelines to tune biological parameters so as to achieve a desired circuit behavior. Moreover, it is easy to analyze the impact of the context on the synthetic device to be designed. That is, one can analyze how the presence of a downstream load influences the performance of the designed circuit, and take it into account.

Chikungunya virus (CHIKV) is a mosquito-borne alphavirus that re-emerged in 2004 and has caused massive outbreaks in recent years. The lack of a licensed vaccine or treatment options emphasize the need to obtain more insight into the viral life cycle and CHIKV-host interactions. Infectious cDNA clones are important tools for such studies, and for mechanism of action studies on antiviral compounds. Existing CHIKV cDNA clones are based on a single genome from an individual clinical isolate, which is expected to have evolved specific characteristics in response to the host environment, and possibly also during subsequent cell culture passaging. To obtain a virus expected to have the general characteristics of the recent E1-226V CHIKV isolates, we have constructed a new CHIKV full-length cDNA clone, CHIKV LS3, based on the consensus sequence of their aligned genomes. Here we report the characterization of this synthetic virus and a green fluorescent protein-expressing variant (CHIKV LS3-GFP). Their characteristics were compared to those of natural strain ITA07-RA1, which was isolated during the 2007 outbreak in Italy. In cell culture the synthetic viruses displayed phenotypes comparable to the natural isolate, and in a mouse model they caused lethal infections that were indistinguishable from infections with a natural strain. Compared to ITA07-RA1 and clinical isolate NL10/152, the synthetic viruses displayed similar sensitivities to several antiviral compounds. 3-deaza-adenosine was identified as a new inhibitor of CHIKV replication. Cyclosporin A had no effect on CHIKV replication, suggesting that cyclophilins -opposite to what was found for other +RNA viruses- do not play an essential role in CHIKV replication. The characterization of the consensus sequence-based synthetic viruses and their comparison to natural isolates demonstrated that CHIKV LS3 and LS3-GFP are suitable and representative tools to study CHIKV-host interactions, screen for antiviral compounds and unravel their mode of action.