(Re-)construction, characterization and modeling of systems for synthetic biology

Flaviolin-Like Gene Cluster Deletion Optimized the Butenyl-Spinosyn Biosynthesis Route in Saccharopolyspora pogona

Reduction and optimization of the microbial genome is an important strategy for constructing synthetic biological chassis cells and overcoming obstacles in natural product discovery and production. However, it is of great challenge to discover target genes that can be deleted and optimized due to the complicated genome of actinomycetes. Saccharopolyspora pogona can produce butenyl-spinosyn during aerobic fermentation, and its genome contains 32 different gene clusters. This suggests that there is a large amount of potential competitive metabolism in S. pogona, which affects the biosynthesis of butenyl-spinosyn. By analyzing the genome of S. pogona, six polyketide gene clusters were identified. From those, the complete deletion of clu13, a flaviolin-like gene cluster, generated a high butenyl-spinosyn-producing strain. Production of this strain was 4.06-fold higher than that of the wildtype strain. Transcriptome profiling revealed that butenyl-spinosyn biosynthesis was not primarily induced by the polyketide synthase RppA-like but was related to hypothetical protein Sp1764. However, the repression of sp1764 was not enough to explain the enormous enhancement of butenyl-spinosyn yields in S. pogona-Δclu13. After the comparative proteomic analysis of S. pogona-Δclu13 and S. pogona, two proteins, biotin carboxyl carrier protein (BccA) and response regulator (Reg), were investigated, whose overexpression led to great advantages of butenyl-spinosyn biosynthesis. In this way, we successfully discovered three key genes that obviously optimize the biosynthesis of butenyl-spinosyn. Gene cluster simplification performed in conjunction with multiomics analysis is of great practical significance for screening dominant chassis strains and optimizing secondary metabolism. This work provided an idea about screening key factors and efficient construction of production strains.

A navigation guide of synthetic biology tools for Pseudomonas putida

Pseudomonas putida is a microbial chassis of huge potential for industrial and environmental biotechnology, owing to its remarkable metabolic versatility and ability to sustain difficult redox reactions and operational stresses, among other attractive characteristics. A wealth of genetic and in silico tools have been developed to enable the unravelling of its physiology and improvement of its performance. However, the rise of this microbe as a promising platform for biotechnological applications has resulted in diversification of tools and methods rather than standardization and convergence. As a consequence, multiple tools for the same purpose have been generated, whilst most of them have not been embraced by the scientific community, which has led to compartmentalization and inefficient use of resources. Inspired by this and by the substantial increase in popularity of P. putida, we aim herein to bring together and assess all currently available (wet and dry) synthetic biology tools specific for this microbe, focusing on the last 5 years. We provide information on the principles, functionality, advantages and limitations, with special focus on their use in metabolic engineering. Additionally, we compare the tool portfolio for P. putida with those for other bacterial chassis and discuss potential future directions for tool development. Therefore, this review is intended as a reference guide for experts and new 'users' of this promising chassis.

Synthetic biology at the interface of functional genomics

Functional genomics is considered a powerful tool that helps understand the relation between an organism's genotype and possible phenotypes. Volumes of data generated on several 'omics' platforms have revealed the network complexities underlying biological processes. Systems and synthetic biology have garnered much attention because of the ability to infer and comprehend the uncertainties associated with such complexities. Also, part-wise characterization of the network components (e.g. DNA, RNA, protein) has rendered an engineering perspective in life sciences to build modular and functional devices. This approach can be used to combat one of the many concerns of the world, i.e. in the area of biomedical translational research by designing and constructing novel therapeutic devices to intervene network perturbation in a diseased state to transform to a healthy state.

Exploring the metabolic network of the epidemic pathogen Burkholderia cenocepacia J2315 via genome-scale reconstruction

BACKGROUND

Burkholderia cenocepacia is a threatening nosocomial epidemic pathogen in patients with cystic fibrosis (CF) or a compromised immune system. Its high level of antibiotic resistance is an increasing concern in treatments against its infection. Strain B. cenocepacia J2315 is the most infectious isolate from CF patients. There is a strong demand to reconstruct a genome-scale metabolic network of B. cenocepacia J2315 to systematically analyze its metabolic capabilities and its virulence traits, and to search for potential clinical therapy targets.

RESULTS

We reconstructed the genome-scale metabolic network of B. cenocepacia J2315. An iterative reconstruction process led to the establishment of a robust model, iKF1028, which accounts for 1,028 genes, 859 internal reactions, and 834 metabolites. The model iKF1028 captures important metabolic capabilities of B. cenocepacia J2315 with a particular focus on the biosyntheses of key metabolic virulence factors to assist in understanding the mechanism of disease infection and identifying potential drug targets. The model was tested through BIOLOG assays. Based on the model, the genome annotation of B. cenocepacia J2315 was refined and 24 genes were properly re-annotated. Gene and enzyme essentiality were analyzed to provide further insights into the genome function and architecture. A total of 45 essential enzymes were identified as potential therapeutic targets.

CONCLUSIONS

As the first genome-scale metabolic network of B. cenocepacia J2315, iKF1028 allows a systematic study of the metabolic properties of B. cenocepacia and its key metabolic virulence factors affecting the CF community. The model can be used as a discovery tool to design novel drugs against diseases caused by this notorious pathogen.

How to make a minimal genome for synthetic minimal cell

As a key focus of synthetic biology, building a minimal artificial cell has given rise to many discussions. A synthetic minimal cell will provide an appropriate chassis to integrate functional synthetic parts, devices and systems with functions that cannot generally be found in nature. The design and construction of a functional minimal genome is a key step while building such a cell/chassis since all the cell functions can be traced back to the genome. Kinds of approaches, based on bioinformatics and molecular biology, have been developed and proceeded to derive essential genes and minimal gene sets for the synthetic minimal genome. Experiments about streamlining genomes of model bacteria revealed genome reduction led to unanticipated beneficial properties, such as high electroporation efficiency and accurate propagation of recombinant genes and plasmids that were unstable in other strains. Recent achievements in chemical synthesis technology for large DNA segments together with the rapid development of the whole-genome sequencing, have transferred synthesis of genes to assembly of the whole genomes based on oligonucleotides, and thus created strong preconditions for synthesis of artificial minimal genome. Here in this article, we review briefly the history and current state of research in this field and summarize the main methods for making a minimal genome. We also discuss the impacts of minimized genome on metabolism and regulation of artificial cell.