BioParts-A Biological Parts Search Portal and Updates to the ICE Parts Registry Software Platform

Current approaches to genetic modification of marine bacteria and considerations for improved transformation efficiency

Marine bacteria play vital roles in symbiosis, biogeochemical cycles and produce novel bioactive compounds and enzymes of interest for the pharmaceutical, biofuel and biotechnology industries. At present, investigations into marine bacterial functions and their products are primarily based on phenotypic observations, -omic type approaches and heterologous gene expression. To advance our understanding of marine bacteria and harness their full potential for industry application, it is critical that we have the appropriate tools and resources to genetically manipulate them in situ. However, current genetic tools that are largely designed for model organisms such as E. coli, produce low transformation efficiencies or have no transfer ability in marine bacteria. To improve genetic manipulation applications for marine bacteria, we need to improve transformation methods such as conjugation and electroporation in addition to identifying more marine broad host range plasmids. In this review, we aim to outline the reported methods of transformation for marine bacteria and discuss the considerations for each approach in the context of improving efficiency. In addition, we further discuss marine plasmids and future research areas including CRISPR tools and their potential applications for marine bacteria.

An integrative database and its application for plant synthetic biology research

Plant synthetic biology research requires diverse bioparts that facilitate the redesign and construction of new-to-nature biological devices or systems in plants. Limited by few well-characterized bioparts for plant chassis, the development of plant synthetic biology lags behind that of its microbial counterpart. Here, we constructed a web-based Plant Synthetic BioDatabase (PSBD), which currently categorizes 1677 catalytic bioparts and 384 regulatory elements and provides information on 309 species and 850 chemicals. Online bioinformatics tools including local BLAST, chem similarity, phylogenetic analysis, and visual strength are provided to assist with the rational design of genetic circuits for manipulation of gene expression in planta. We demonstrated the utility of the PSBD by functionally characterizing taxadiene synthase 2 and its quantitative regulation in tobacco leaves. More powerful synthetic devices were then assembled to amplify the transcriptional signals, enabling enhanced expression of flavivirus non-structure 1 proteins in plants. The PSBD is expected to be an integrative and user-centered platform that provides a one-stop service for diverse applications in plant synthetic biology research.

Sustainable production of natural products using synthetic biology: Ginsenosides

Synthetic biology approaches offer potential for large-scale and sustainable production of natural products with bioactive potency, including ginsenosides, providing a means to produce novel compounds with enhanced therapeutic properties. Ginseng, known for its non-toxic and potent qualities in traditional medicine, has been used for various medical needs. Ginseng has shown promise for its antioxidant and neuroprotective properties, and it has been used as a potential agent to boost immunity against various infections when used together with other drugs and vaccines. Given the increasing demand for ginsenosides and the challenges associated with traditional extraction methods, synthetic biology holds promise in the development of therapeutics. In this review, we discuss recent developments in microorganism producer engineering and ginsenoside production in microorganisms using synthetic biology approaches.

Understanding neural circuit function through synaptic engineering

Synapses are a key component of neural circuits, facilitating rapid and specific signalling between neurons. Synaptic engineering - the synthetic insertion of new synaptic connections into in vivo neural circuits - is an emerging approach for neural circuit interrogation. This approach is especially powerful for establishing causality in neural circuit structure-function relationships, for emulating synaptic plasticity and for exploring novel patterns of circuit connectivity. Contrary to other approaches for neural circuit manipulation, synaptic engineering targets specific connections between neurons and functions autonomously with no user-controlled external activation. Synaptic engineering has been successfully implemented in several systems and in different forms, including electrical synapses constructed from ectopically expressed connexin gap junction proteins, synthetic optical synapses composed of presynaptic photon-emitting luciferase coupled with postsynaptic light-gated channels, and artificial neuropeptide signalling pathways. This Perspective describes these different methods and how they have been applied, and examines how the field may advance.

Automated Platform for the Plasmid Construction Process

There is a growing need for applications capable of handling large synthesis biology experiments. At the core of synthetic biology is the process of cloning and manipulating DNA as plasmids. Here, we report the development of an application named DNAda capable of writing automation instructions for any given DNA construct design generated by the J5 DNA assembly program. We also describe the automation pipeline and several useful features. The pipeline is particularly useful for the construction of combinatorial DNA assemblies. Furthermore, we demonstrate the platform by constructing a library of polyketide synthase parts, which includes 120 plasmids ranging in size from 7 to 14 kb from 4 to 7 DNA fragments.

Biofoundry Palette: Planning-Assistant Software for Liquid Handler-Based Experimentation and Operation in the Biofoundry Workflow

Lab automation has facilitated synthetic biology applications in an automated workflow, and biofoundry facilities have enabled automated high-throughput experiments of gene cloning and genome engineering to be conducted following a precise experimental design and protocol. However, before-experiment procedures in biofoundry applications have been underdetermined. We aimed to develop a Python-based planning-assistant software, namely Biofoundry Palette, for liquid handler-based experimentation and operation in the biofoundry workflow. Depending on the synthetic biology project, variable information and content information may vary; the Biofoundry Palette provides precise information for the before-experiment units for each process module in the biofoundry workflow. As a demonstration, more than 200 unique information sets, generated by Biofoundry Palette, were used in automated gene cloning or pathway construction. The information on planning and management can potentially help the operator faithfully execute the biofoundry workflow after securing the before-experiment unit, thereby lowering the risk of human errors and performing successful biofoundry operations for synthetic biology applications.

RoboMoClo: A Robotics-Assisted Modular Cloning Framework for Multiple Gene Assembly in Biofoundry

Efficient and versatile DNA assembly frameworks have had an impact on promoting synthetic biology to build complex biological systems. To accelerate system development, laboratory automation (or biofoundry) provides an opportunity to construct organisms and DNA assemblies via computer-aided design. However, a modular cloning (MoClo) system for multiple DNA assemblies limits the biofoundry workflow in terms of simplicity and feasibility by preparing the number of cloning materials such as destination vectors prior to the automation process. Herein, we propose robot-assisted MoClo (RoboMoClo) to accelerate a synthetic biology project with multiple gene expressions at the biofoundry. The architecture of the RoboMoClo framework provides a hybrid strategy of hierarchical gene assembly and iterative gene assembly, and fewer destination vectors compared with other MoClo systems. An industrial bacterium, Corynebacterium glutamicum, was used as a model host for RoboMoClo. After building a biopart library (promoter and terminator; level 0) and evaluating its features (level 1), various transcriptional directions in multiple gene assemblies (level 2) were studied using the RoboMoClo vectors. Among the constructs, the convergent construct exhibited potential transcriptional interference through the collision of RNA polymerases. To study design of experiment-guided lycopene biosynthesis in C. glutamicum (levels 1, 2, and 3), the biofoundry-assisted multiple gene assembly was demonstrated as a proof-of-concept by constructing various sub-pathway units (level 2) and pathway units (level 3) for C. glutamicum. The RoboMoClo framework provides an improved MoClo toolkit for laboratory automation in a synthetic biology application.

Escherichia coli Data-Driven Strain Design Using Aggregated Adaptive Laboratory Evolution Mutational Data

Microbes are being engineered for an increasingly large and diverse set of applications. However, the designing of microbial genomes remains challenging due to the general complexity of biological systems. Adaptive Laboratory Evolution (ALE) leverages nature’s problem-solving processes to generate optimized genotypes currently inaccessible to rational methods. The large amount of public ALE data now represents a new opportunity for data-driven strain design. This study describes how novel strain designs, or genome sequences not yet observed in ALE experiments or published designs, can be extracted from aggregated ALE data and demonstrates this by designing, building, and testing three novel Escherichia coli strains with fitnesses comparable to ALE mutants. These designs were achieved through a meta-analysis of aggregated ALE mutations data (63 Escherichia coli K-12 MG1655 based ALE experiments, described by 93 unique environmental conditions, 357 independent evolutions, and 13 957 observed mutations), which additionally revealed global ALE mutation trends that inform on ALE-derived strain design principles. Such informative trends anticipate ALE-derived strain designs as largely gene-centric, as opposed to noncoding, and composed of a relatively small number of beneficial variants (approximately 6). These results demonstrate how strain design efforts can be enhanced by the meta-analysis of aggregated ALE data.