This study provides a relatively brief overview of the field of synthetic biology/engineering biology for the non-specialist reader. This is in line with one of the basic aims of the new journal Engineering Biology – which is to open up the field to a much wider audience than those currently engaged and, particularly, to people working in companies and disciplines whose technology may be relevant to the field. Consequently, the study contains some didactic material.

This study proposes a new approach to the responsible development of innovative products, processes and services by companies and organisations operating in the bioeconomy and related industry sectors. It departs from much of the recent and currently available research on responsible research and innovation in that it recognises the very different challenges faced by innovating organisations, compared to conventional approaches with a strong emphasis on upstream engagement. It attempts to move away from the politicised perspectives that have dominated many engagement initiatives on disruptive innovations like synthetic/engineering biology, and to focus on practical downstream outcomes, the extent to which they will fulfil the aspirations of ordinary citizens, and will comply with prevailing industry norms of responsible behaviour. The proposed consolidated responsible innovation framework builds on the framework developed in 2012 by the then Technology Strategy Board, implemented using the anticipate, reflect, engage and act approach devised by UK research councils. It distinguishes between routine, company-specific aspects of responsibility, expected to be addressed within an organisation's standard operating procedures, and project-specific aspects requiring regular appraisal throughout the development of an innovation. It is designed to be simple and feasible for a company to implement within a commercial environment.

Biologically engineered entities have enabled discoveries in the past decade and a half, spanning from novel routes for the syntheses of drugs and value-added products to carbon capture. The precise cellular re-programming has extended to the production of nanomaterials owing to their ever-growing demand. The primary advantage of the biological nanoparticle synthesis is the eco-friendly approach performed at ambient temperature and pressure, where the usage of harsh chemical stabilisers and capping agents is eliminated, providing ease of handling and downstream processing. Although the techniques hold great promise, many short comings hamper their scalability; thus, rendering them unsuitable for industrial applications. A fundamental understanding of the underlying mechanisms which involve various enzymes of different metabolic pathways is most crucial in surmounting these impending blocks leading to successfully engineered systems which can be tuned in accordance with the goals of specific applications. This mini review highlights the recent developments in nanoparticle synthesis that employ the use of microbial reaction vessels with specific emphasis on engineering of these biological entities such as bacteria, yeast, fungi and algae. Also presented are the challenges and future trends in this domain where novel and engineered approaches will be the most consequential.

Collagen, which is often used in healthcare materials and biomedical research, is largely extracted from animal sources. Recombinant human collagen has the potential to be a promising alternative to animal collagen which has many shortcomings, including immunogenicity and lack of biocompatibility. Currently, recombinant human collagen has been expressed in both eukaryotic and prokaryotic hosts with varying degrees of success. One issue with recombinant collagen across all hosts is the inability to achieve full length collagen with native amounts of post-translational modifications, prompting much exciting research in this direction. There has also been much effort in improving yield and biomimicry of recombinant collagen. This review discusses collagen structure and current methods for extracting animal collagen, before introducing current research in synthesising recombinant human collagen in various hosts, and finally highlighting challenges in the field.

Synthetic biology is an emerging area of research that combines the investigative nature of biology with the constructive nature of engineering. Despite the field being in its infancy, it has already aided the development of a myriad of industrially and pharmaceutically useful compounds, devices and therapies and is now being applied within the field of regenerative medicine. By combining synthetic biology with regenerative medicine, the engineering of cells and organisms offers potential avenues for applications in tissue engineering, bioprocessing, biomaterial and scaffold development, stem cell therapies and even gene therapies. This review aims to discuss how synthetic biology has been applied within these distinct areas of regenerative medicine, the challenges it faces and any future possibilities this exciting new field may hold.

A major challenge in synthetic genetic circuit development is the inter-dependency between heterologous gene expressions by circuits and host's growth rate. Increasing heterologous gene expression increases burden to the host, resulting in host growth reduction; which reduces overall heterologous protein abundance. Hence, it is difficult to design predictable genetic circuits. Here, we develop two biophysical models; one for promoter, another for RBS; to correlate heterologous gene expression and growth reduction. We model cellular resource allocation in E. coli to describe the burden, as growth reduction, caused by genetic circuits. To facilitate their uses in genetic circuit design, inputs to the model are common characteristics of biological parts [e.g. relative promoter strength (RPU) and relative ribosome binding sites strength (RRU)]. The models suggest that E. coli's growth rate reduces linearly with increasing RPU/RRU of the genetic circuits; thus, providing 2 handy models taking parts characteristics as input to estimate growth rate reduction for fine tuning genetic circuit design in silico prior to construction. Our promoter model correlates well with experiments using various genetic circuits, both single and double expression cassettes, up to a relative promoter unit of 3.7 with a 60% growth rate reduction (average R ²∼0.9).

Site-specific recombinases (SSRs) mediate efficient manipulation of DNA sequences in vitro and in vivo. In particular, serine integrases have been identified as highly effective tools for facilitating DNA inversion, enabling the design of genetic switches that are capable of turning the expression of a gene of interest on or off in the presence of a SSR protein. The functional scope of such circuitry can be extended to biological Boolean logic operations by incorporating two or more distinct integrase inputs. To date, mathematical modelling investigations have captured the dynamical properties of integrase logic gate systems in a purely qualitative manner, and thus such models are of limited utility as tools in the design of novel circuitry. Here, the authors develop a detailed mechanistic model of a two-input temporal logic gate circuit that can detect and encode sequences of input events. Their model demonstrates quantitative agreement with time-course data on the dynamics of the temporal logic gate, and is shown to subsequently predict dynamical responses relating to a series of induction separation intervals. The model can also be used to infer functional variations between distinct integrase inputs, and to examine the effect of reversing the roles of each integrase on logic gate output.

This application note describes an open-source web application software package for viewing and analysing time-course event sequences in the form of log files containing timestamps. Web pages allow the visualisation of time-course event sequences as time curves and the comparison of sequences against each other to visualise deviations between the timings of the sequences. A feature allows the analysis of the sequences by parsing selected sections with a support vector machine model that heuristically calculates a value for the likelihood of an error occurring based on the textual output in the log files. This allows quick analysis for errors in files with large numbers of log events. The software is written in ASP.NET with Visual Basic code-behind to allow it to be hosted on servers and integrated into web application frameworks.

Cells exhibit a high degree of variation in levels of gene expression, even within otherwise homogeneous populations. The standard model to describe this variation centres on a gamma distribution driven by stochastic bursts of translation. Stochastic bursting, however, cannot account for the well-established behaviour of strong transcriptional repressors. Instead, it can be shown that the very complexity of the biochemical processes involved in gene expression drives an emergent log-normal distribution of expression levels. Emergent log-normal distributions can account for the observed behaviour of transcriptional repressors, are still compatible with stochastically constrained distributions, and have important implications for both analysis of gene expression data and the engineering of biological organisms.

The synthetic biology design process has traditionally been heavily dependent upon manual searching, acquisition and integration of existing biological data. A large amount of such data is already available from Internet-based resources, but data exchange between these resources is often undertaken manually. Automating the communication between different resources can be done by the generation of computational workflows to achieve complex tasks that cannot be carried out easily or efficiently by a single resource. Computational workflows involve the passage of data from one resource, or process, to another in a distributed computing environment. In a typical bioinformatics workflow, the predefined order in which processes are invoked in a synchronous fashion and are described in a workflow definition document. However, in synthetic biology the diversity of resources and manufacturing tasks required favour a more flexible model for process execution. Here, the authors present the Protocol for Linking External Nodes (POLEN), a Cloud-based system that facilitates synthetic biology design workflows that operate asynchronously. Messages are used to notify POLEN resources of events in real time, and to log historical events such as the availability of new data, enabling networks of cooperation. POLEN can be used to coordinate the integration of different synthetic biology resources, to ensure consistency of information across distributed repositories through added support for data standards, and ultimately to facilitate the synthetic biology life cycle for designing and implementing biological systems.