生物设计研究(英文)最新文献

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.

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.

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.

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.

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.

The emerging plant synthetic metabolic engineering has been exhibiting great promise to produce either value-added metabolites or therapeutic proteins. However, promoters for plant pathway engineering are generally selected empirically. The quantitative characterization of plant-based promoters is essential for optimal control of gene expression in plant chassis. Here, we used N. benthamiana leaves and BY2 suspension cells to quantitatively characterize a library of plant promoters by transient expression of firefly/Renilla luciferase. We validated the dual-luciferase reporter system by examining the correlation between reporter protein and mRNA levels. In addition, we investigated the effects of terminator-promoter combinations on gene expression and found that the combinations of promoters and terminators resulted in a 326-fold difference between the strongest and weakest performance, as reflected in reporter gene expression. As a proof of concept, we used the quantitatively characterized promoters to engineer the betalain pathway in N. benthamiana. Seven selected plant promoters with different expression strengths were used orthogonally to express CYP76AD1 and DODA, resulting in a final betalain production range of 6.0-362.4 μg/g fresh weight. Our systematic approach not only demonstrates the various intensities of multiple promoter sequences in N. benthamiana and BY2 cells but also adds to the toolbox of plant promoters for plant engineering.

Advancing biotechnologies are revolutionizing not only health and medicine, but also many different sectors such as agriculture, energy, chemistry, and textiles. As synthetic biology is leveraged as a programmable platform for the creation and biodesign of high-value biological medicines, foods, and commodities, the world is facing new territory in terms of ensuring the safety and security of both novel and engineered biological organisms, as well as the biological and digital platforms in which they are designed. Biosecurity practices and policies have traditionally revolved around preventing the misuse of biological pathogens, primarily through controlling access to pathogens. The advent of biodesign capabilities, such as gene editors, gene synthesis capabilities, and genetic engineering, requires a reevaluation of traditional biosecurity policies to mitigate risks associated with such engineering of biological entities. Here, features of "Biosecurity by Design" approaches are described, including the application of risk/benefit analysis and risk mitigation, post-COVID opportunities, and ethical global norms in the progression of biodesign and growing bioeconomies.

Viral diseases have contributed significantly to worldwide morbidity and mortality throughout history. Despite the existence of therapeutic treatments for many viral infections, antiviral resistance and the threat posed by novel viruses highlight the need for an increased number of effective therapeutics. In addition to small molecule drugs and biologics, antimicrobial peptides (AMPs) represent an emerging class of potential antiviral therapeutics. While AMPs have traditionally been regarded in the context of their antibacterial activities, many AMPs are now known to be antiviral. These antiviral peptides (AVPs) have been shown to target and perturb viral membrane envelopes and inhibit various stages of the viral life cycle, from preattachment inhibition through viral release from infected host cells. Rational design of AMPs has also proven effective in identifying highly active and specific peptides and can aid in the discovery of lead peptides with high therapeutic selectivity. In this review, we highlight AVPs with strong antiviral activity largely curated from a publicly available AMP database. We then compile the sequences present in our AVP database to generate structural predictions of generic AVP motifs. Finally, we cover the rational design approaches available for AVPs taking into account approaches currently used for the rational design of AMPs.

All living organisms share similar reactions within their central metabolism to provide precursors for all essential building blocks and reducing power. To identify whether alternative metabolic routes of glycolysis can operate in E. coli, we complementarily employed in silico design, rational engineering, and adaptive laboratory evolution. First, we used a genome-scale model and identified two potential pathways within the metabolic network of this organism replacing canonical Embden-Meyerhof-Parnas (EMP) glycolysis to convert phosphosugars into organic acids. One of these glycolytic routes proceeds via methylglyoxal and the other via serine biosynthesis and degradation. Then, we implemented both pathways in E. coli strains harboring defective EMP glycolysis. Surprisingly, the pathway via methylglyoxal seemed to immediately operate in a triosephosphate isomerase deletion strain cultivated on glycerol. By contrast, in a phosphoglycerate kinase deletion strain, the overexpression of methylglyoxal synthase was necessary to restore growth of the strain. Furthermore, we engineered the "serine shunt" which converts 3-phosphoglycerate via serine biosynthesis and degradation to pyruvate, bypassing an enolase deletion. Finally, to explore which of these alternatives would emerge by natural selection, we performed an adaptive laboratory evolution study using an enolase deletion strain. Our experiments suggest that the evolved mutants use the serine shunt. Our study reveals the flexible repurposing of metabolic pathways to create new metabolite links and rewire central metabolism.

A major advancement has recently occurred in the ability to predict protein secondary structure from sequence using artificial neural networks. This new accessibility to high-quality predicted structures provides a big opportunity for the protein design community. It is particularly welcome for membrane protein design, where the scarcity of solved structures has been a major limitation of the field for decades. Here, we review the work done to date on the membrane protein design and set out established and emerging tools that can be used to most effectively exploit this new access to structures.