SynBio, Volume 1, Issue 1 (June 2023) – 9 articles

Periodontitis, a chronic inflammatory oral condition triggered by bacteria, archaea, viruses, and eukaryotic organisms, is a well-known and widespread disease around the world. While there are effective treatments for periodontitis, there are also several shortcomings associated with its management, including limited treatment options, the risk of recurrence, and the high cost of treatment. Our goal is to develop a more efficient, systematic drug design for periodontitis before clinical trials. We work on systems drug discovery and design for periodontitis treatment via systems biology and deep learning methods. We first applied big database mining to build a candidate genome-wide genetic and epigenetic network (GWGEN), which includes a protein-protein interaction network (PPIN) and a gene regulatory network (GRN) for periodontitis and healthy control. Next, based on the unhealthy and healthy microarray data, we applied system identification and system order detection methods to remove false positives in candidate GWGENs to obtain real GWGENs for periodontitis and healthy control, respectively. After the real GWGENs were obtained, we picked out the core GWGENs based on how significant the proteins and genes were via the principal network projection (PNP) method. Finally, referring to the annotation of the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways, we built up the core signaling pathways of periodontitis and healthy control. Consequently, we investigated the pathogenic mechanism of periodontitis by comparing their core signaling pathways. By checking up on the downstream core signaling pathway and the corresponding cellular dysfunctions of periodontitis, we identified the fos proto-oncogene, AP-1 Transcription Factor Subunit (FOS), TSC Complex Subunit 2 (TSC2), Forkhead Box O1 (FOXO1), and nuclear factor kappa-light chain enhancer of activated B cells (NF-$\mathsf{\kappa }$B) as significant biomarkers on which we could find candidate molecular drugs to target. To achieve our ultimate goal of designing a combination of molecular drugs for periodontitis treatment, a deep neural network (DNN)-based drug-target interaction (DTI) model was employed. The model is trained with the existing drug-target interaction databases for the prediction of candidate molecular drugs for significant biomarkers. Finally, we filter out brucine, disulfiram, verapamil, and PK-11195 as potential molecular drugs to be combined as a multiple-molecular drug to target the significant biomarkers based on drug design specifications, i.e., adequate drug regulation ability, high sensitivity, and low toxicity. In conclusion, we investigated the pathogenic mechanism of periodontitis by leveraging systems biology methods and thoroughly developed a therapeutic option for periodontitis treatment via the prediction of a DNN-based DTI model and drug design specifications. Full article

Rheumatoid arthritis (RA) is one of the most common autoimmune diseases, affecting 0.5% to 1% of the population. It could ultimately result in joint destruction, functional decline, work disability, and enhanced mortality. Cyclic citrullinated peptide antibodies (CCP Abs) are useful biomarkers for the early detection and diagnosis of RA. In this study, we used plant viral-based expression vectors that produce rapidly large quantities of CCP-specific monoclonal antibodies. Heavy and light chain genes of a CCP monoclonal antibody (CCP mAb) were cloned from the hybridoma cell (12G1) and introduced into two separate plant viral-based expression vectors, TMV and PVX. A cyclic citrullinated peptide monoclonal antibody was produced in Nicotiana benthamiana through an Agrobacterium-mediated transient expression system. The expression of CCP mAb in tobacco plants was confirmed by dot blot, western blot analysis, and enzyme-linked immunosorbent assays (ELISA). It was shown that tobacco plants could accumulate CCP mAbs up to 0.35% of total soluble protein. Accumulated CCP mAb from infiltrated leaves was purified by protein G affinity chromatography. Immunoblot assays and ELISA showed plant-produced CCP mAbs successfully bound to a synthetic CCP peptide antigen. This system provides a fast strategy for the production of pharmaceutical CCP mAbs in tobacco plants. Full article

Covering 2009–2022. Phenylnaphthacenoid polyketides have gained significant interest in recent years owing to their potent antibacterial and anticancer activities. Notably, more than 100 members of this class of natural products have been discovered from various Streptomyces species by different research groups including ours over the last 13 years. This review summarizes the current knowledge of the discovery, chemical diversity, and bioactivity of phenylnaphthacenoid polyketides. The current review also highlights the cell factory for phenylnaphthacenoid production: (1) native strains, (2) mutant strains, (3) heterologous expression, and (4) biocatalytic halogenations. Furthermore, current challenges and future opportunities are also presented as a guide for researchers to explore them more purposefully. Full article

Synthetic biology tools have become increasingly prevalent as we look to nature for biological approaches to complex problems. With an ever-growing global population, issues of food safety and security, as well as addressing pollution and striving for sustainability are of the utmost importance. In this review, we first highlight synthetic biology techniques such as directed evolution as a toolset for protein engineering and show direct applications for food safety and security. Moreover, we offer an introduction to creative approaches for biosensor design and development and spotlight a few innovative examples. Finally, we address biomanufacturing with direct applications, as well as biomanufacturing to improve natural processes. Full article

Programmable proteins to detect, visualize, modulate, or eliminate proteins of selection in vitro and in vivo are essential to study the targets recognized and the biology that follows. The specificity of programmable proteins can be easily altered by designing their sequences and structures. The flexibility and modularity of these proteins are currently pivotal for synthetic biology and various medical applications. There exist numerous reviews of the concept and application of individual programmable proteins, such as programmable nucleases, single-domain antibodies, and other protein scaffolds. This review proposes an expanded conceptual framework of such programmable proteins based on their programmable principle and target specificity to biomolecules (nucleic acids, proteins, and glycans) and overviews their advantages, limitations, and future directions. Full article

Cutinases (EC 3.1.1.74) are widely distributed in fungi, bacteria and plants with diversified structures and properties. Besides acting on the natural substrate cutin, cutinases are the first line of natural biocatalysts to hydrolyze artificial polyesters and toxic xenobiotics such as polyethylene terephthalate (PET), polycaprolactone (PCL), polylactic acid (PLA), polyhydroxybutyl succinate (PBS), phthalate and malathion esters. Moreover, cutinases can act as promising stereoselective catalysts in esterification and transesterification reactions and present better selectivities than lipases. These pioneering studies indicate that the biotechnological application of cutinase as a powerful tool in synthetic biology deserves further investigation, for both degradation and biosynthesis towards a broader range of ester bond-containing substrates. This review summarizes the classifications and properties of cutinases from different sources and insights into the structure–function relationship of different cutinases. It also highlights the uniqueness and advantages of representative cutinases in biodegradation and biosynthesis, and then prospects the future application of natural and engineered cutinases in synthetic biology. Full article

Despite the acknowledged relevance of renewable energy sources, biofuel production supported by food-related agriculture has faced severe criticism. One way to minimize the considered negative impacts is the use of sources of non-food biomass or wastes. Synthetic biology (SB) embraces a promising complex of technologies for biofuel production from non-edible and sustainable raw materials. Therefore, it is pertinent to identify the global evolution of investments, concepts, and techniques underlying the field in support of policy formulations for sustainable bioenergy production. We mapped the SB scientific knowledge related to biofuels using software that combines information visualization methods, bibliometrics, and data mining algorithms. The United States and China have been the leading countries in developing SB technologies. The Technical University of Denmark and Tsinghua University are institutions with higher centrality and have played prominent roles besides UC Los Angeles and Delft University Technology. We identified six knowledge clusters under the terms: versatile sugar dehydrogenase, redox balance principle, sesquiterpene production, Saccharomyces cerevisiae, recombinant xylose-fermenting strain, and Clostridium saccharoperbutylacetonicum N1-4. The emerging trends refer to specific microorganisms, processes, and products. Yarrowia lipolytica, Oleaginous yeast, E. coli, Klebsiella pneumoniae, Phaeodactylum tricornutum, and Microalgae are the most prominent microorganisms, mainly from the year 2016 onward. Anaerobic digestion, synthetic promoters, and genetic analysis appear as the most relevant platforms of new processes. Improved biofuels, bioethanol, and N-butanol are at the frontier of the development of SB-derived products. Synthetic biology is a dynamic interdisciplinary field in environmentally friendly bioenergy production pushed by growing social concerns and the emergent bioeconomy. Full article

Acrylic acid (AA) is a chemical with high market value used in industry to produce diapers, paints, adhesives and coatings, among others. AA available worldwide is chemically produced mostly from petroleum derivatives. Due to its economic relevance, there is presently a need for innovative and sustainable ways to synthesize AA. In the past decade, several semi-biological methods have been developed and consist in the bio-based synthesis of 3-hydroxypropionic acid (3-HP) and its chemical conversion to AA. However, more recently, engineered Escherichia coli was demonstrated to be able to convert glucose or glycerol to AA. Several pathways have been developed that use as precursors glycerol, malonyl-CoA or β-alanine. Some of these pathways produce 3-HP as an intermediate. Nevertheless, the heterologous production of AA is still in its early stages compared, for example, to 3-HP production. So far, only up to 237 mg/L of AA have been produced from glucose using β-alanine as a precursor in fed-batch fermentation. In this review, the advances in the production of AA by engineered microbes, as well as the hurdles hindering high-level production, are discussed. In addition, synthetic biology and metabolic engineering approaches to improving the production of AA in industrial settings are presented. Full article