Reflection on the Challenges, Accomplishments, and New Frontiers of Gene DrivesRead the full article
The open access journal BioDesign Research, published in association with NAU, publishes novel research in the interdisciplinary field of biosystems design.
The editorial board, led by Xiaohan Yang (Oak Ridge National Laboratory) and Alfonso Jaramillo (University of Warwick), is comprised of experts who have made significant and well recognized contributions to the field of biodesign research.
Accepting submissions for three special issues:
• Plant BioDesign Hub (deadlines: Aug 31, 2021; Dec 31, 2022; Jun 30, 2023)
• Designing Proteins With New Folds and Function (deadline: Dec 31, 2022)
• Engineering Microbiomes for Biodesign Applications (deadline: Dec 31, 2022)
Latest ArticlesMore articles
Propagation of Recombinant Genes through Complex Microbiomes with Synthetic Mini-RP4 Plasmid Vectors
The promiscuous conjugation machinery of the Gram-negative plasmid RP4 has been reassembled in a minimized, highly transmissible vector for propagating genetically encoded traits through diverse types of naturally occurring microbial communities. To this end, the whole of the RP4-encoded transfer determinants (tra, mob genes, and origin of transfer oriT) was excised from their natural context, minimized, and recreated in the form of a streamlined DNA segment borne by an autoselective replicon. The resulting constructs (the pMATING series) could be self-transferred through a variety of prokaryotic and eukaryotic recipients employing such a rationally designed conjugal delivery device. Insertion of GFP reporter into pMATING exposed the value of this genetic tool for delivering heterologous genes to both specific mating partners and complex consortia (e.g., plant/soil rhizosphere). The results accredited the effective and functional transfer of the recombinant plasmids to a diversity of hosts. Yet the inspection of factors that limit interspecies DNA transfer in such scenarios uncovered type VI secretion systems as one of the factual barriers that check otherwise high conjugal frequencies of tested RP4 derivatives. We argue that the hereby presented programming of hyperpromiscuous gene transfer can become a phenomenal asset for the propagation of beneficial traits through various scales of the environmental microbiome.
In Vitro Nanobody Library Construction by Using Gene Designated-Region Pan-Editing Technology
Camelid single-domain antibody fragments (nanobodies) are an emerging force in therapeutic biopharmaceuticals and clinical diagnostic reagents in recent years. Nearly all nanobodies available to date have been obtained by animal immunization, a bottleneck restricting the large-scale application of nanobodies. In this study, we developed three kinds of gene designated-region pan-editing (GDP) technologies to introduce multiple mutations in complementarity-determining regions (CDRs) of nanobodies in vitro. Including the integration of G-quadruplex fragments in CDRs, which induces the spontaneous multiple mutations in CDRs; however, these mutant sequences are highly similar, resulting in a lack of sequences diversity in the CDRs. We also used CDR-targeting traditional gRNA-guided base-editors, which effectively diversify the CDRs. And most importantly, we developed the self-assembling gRNAs, which are generated by reprogrammed tracrRNA hijacking of endogenous mRNAs as crRNAs. Using base-editors guided by self-assembling gRNAs, we can realize the iteratively diversify the CDRs. And we believe the last GDP technology is highly promising in immunization-free nanobody library construction, and the full development of this novel nanobody discovery platform can realize the synthetic evolution of nanobodies in vitro.
Data-Driven Synthetic Cell Factories Development for Industrial Biomanufacturing
Revolutionary breakthroughs in artificial intelligence (AI) and machine learning (ML) have had a profound impact on a wide range of scientific disciplines, including the development of artificial cell factories for biomanufacturing. In this paper, we review the latest studies on the application of data-driven methods for the design of new proteins, pathways, and strains. We first briefly introduce the various types of data and databases relevant to industrial biomanufacturing, which are the basis for data-driven research. Different types of algorithms, including traditional ML and more recent deep learning methods, are also presented. We then demonstrate how these data-based approaches can be applied to address various issues in cell factory development using examples from recent studies, including the prediction of protein function, improvement of metabolic models, and estimation of missing kinetic parameters, design of non-natural biosynthesis pathways, and pathway optimization. In the last section, we discuss the current limitations of these data-driven approaches and propose that data-driven methods should be integrated with mechanistic models to complement each other and facilitate the development of synthetic strains for industrial biomanufacturing.
Transporter Engineering in Microbial Cell Factory Boosts Biomanufacturing Capacity
Microbial cell factories (MCFs) are typical and widely used platforms in biomanufacturing for designing and constructing synthesis pathways of target compounds in microorganisms. In MCFs, transporter engineering is especially significant for improving the biomanufacturing efficiency and capacity through enhancing substrate absorption, promoting intracellular mass transfer of intermediate metabolites, and improving transmembrane export of target products. This review discusses the current methods and strategies of mining and characterizing suitable transporters and presents the cases of transporter engineering in the production of various chemicals in MCFs.
Stoichiometric Conversion of Maltose for Biomanufacturing by In Vitro Synthetic Enzymatic Biosystems
Maltose is a natural α-(1,4)-linked disaccharide with wide applications in food industries and microbial fermentation. However, maltose has scarcely been used for in vitro biosynthesis, possibly because its phosphorylation by maltose phosphorylase (MP) yields β-glucose 1-phosphate (β-G1P) that cannot be utilized by α-phosphoglucomutase (α-PGM) commonly found in in vitro synthetic enzymatic biosystems previously constructed by our group. Herein, we designed an in vitro synthetic enzymatic reaction module comprised of MP, β-phosphoglucomutase (β-PGM), and polyphosphate glucokinase (PPGK) for the stoichiometric conversion of each maltose molecule to two glucose 6-phosphate (G6P) molecules. Based on this synthetic module, we further constructed two in vitro synthetic biosystems to produce bioelectricity and fructose 1,6-diphosphate (FDP), respectively. The 14-enzyme biobattery achieved a Faraday efficiency of 96.4% and a maximal power density of 0.6 mW/cm2, whereas the 5-enzyme in vitro FDP-producing biosystem yielded 187.0 mM FDP from 50 g/L (139 mM) maltose by adopting a fed-batch substrate feeding strategy. Our study not only suggests new application scenarios for maltose but also provides novel strategies for the high-efficient production of bioelectricity and value-added biochemicals.
Improving the Efficiency and Orthogonality of Genetic Code Expansion
The site-specific incorporation of the noncanonical amino acid (ncAA) into proteins via genetic code expansion (GCE) has enabled the development of new and powerful ways to learn, regulate, and evolve biological functions in vivo. However, cellular biosynthesis of ncAA-containing proteins with high efficiency and fidelity is a formidable challenge. In this review, we summarize up-to-date progress towards improving the efficiency and orthogonality of GCE and enhancing intracellular compatibility of introduced translation machinery in the living cells by creation and optimization of orthogonal translation components, constructing genomically recoded organism (GRO), utilization of unnatural base pairs (UBP) and quadruplet codons (four-base codons), and spatial separation of orthogonal translation.