Biotechnology Journal最新文献

The d-amino acid oxidase (DAAO) is pivotal in obtaining optically pure l-glufosinate (l-PPT) by converting d-glufosinate (d-PPT) to its deamination product. We screened and designed a Rasamsonia emersonii DAAO (ReDAAO), making it more suitable for oxidizing d-PPT. Using Caver 3.0, we delineated three substrate binding pockets and, via alanine scanning, identified nearby key residues. Pinpointing key residues influencing activity, we applied virtual saturation mutagenesis (VSM), and experimentally validated mutants which reduced substrate binding energy. Analysis of positive mutants revealed elongated side-chain prevalence in substrate binding pocket periphery. Although computer-aided approaches can rapidly identify advantageous mutants and guide further design, the mutations obtained in the first round may not be suitable for combination with other advantageous mutations. Therefore, each round of combination requires reasonable iteration. Employing VSM-assisted screening multiple times and after four rounds of combining mutations, we ultimately obtained a mutant, N53V/F57Q/V94R/V242R, resulting in a mutant with a 5097% increase in enzyme activity compared to the wild type. It provides valuable insights into the structural determinants of enzyme activity and introduces a novel rational design procedure.

Iterative metabolic engineering of Fusarium fujikuroi has traditionally been hampered by its low homologous recombination efficiency and scarcity of genetic markers. Thus, the clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated proteins (Cas9) system has emerged as a promising tool for precise genome editing in this organism. Some integrated CRISPR/Cas9 strategies have been used to engineer F. fujikuroi to improve GA3 production capabilities, but low editing efficiency and possible genomic instability became the major obstacle. Herein, we developed a marker recyclable CRISPR/Cas9 system for scarless and multigene editing in F. fujikuroi. This system, based on an autonomously replicating sequence, demonstrated the capability of a single plasmid harboring all editing components to achieve 100%, 75%, and 37.5% editing efficiency for single, double, and triple gene targets, respectively. Remarkably, even with a reduction in homologous arms to 50 bp, we achieved a 12.5% gene editing efficiency. By employing this system, we successfully achieved multicopy integration of the truncated 3-hydroxy-3-methyl glutaryl coenzyme A reductase gene (tHMGR), leading to enhanced GA3 production. A key advantage of our plasmid-based gene editing approach was the ability to recycle selective markers through a simplified protoplast preparation and recovery process, which eliminated the need for additional genetic markers. These findings demonstrated that the single-plasmid CRISPR/Cas9 system enables rapid and precise multiple gene deletions/integrations, laying a solid foundation for future metabolic engineering efforts aimed at industrial GA3 production.

Cervical cancer (CC) remains a major cause of cancer-related mortality among women globally. Long noncoding RNAs (lncRNAs) play crucial regulatory roles in various cancers, including CC. This study investigates the function of a novel lncRNA, USP30 antisense RNA 1 (USP30-AS1), in CC tumorigenesis. We analyzed USP30-AS1 expression using RT-qPCR and conducted in vitro loss-of-function assays, as well as in vivo assays, to evaluate the effects of USP30-AS1 silencing on CC cell growth and migration. Additional mechanistic experiments, including RNA pull-down, RNA immunoprecipitation (RIP), and co-immunoprecipitation (Co-IP) assays, were performed to elucidate the regulatory mechanisms influenced by USP30-AS1. We discovered that USP30-AS1 is overexpressed in CC tissues and cells. Silencing USP30-AS1 significantly reduced cell proliferation, migration, invasion, and tumor growth. Moreover, USP30-AS1 was found to modulate the expression of ubiquitin-specific peptidase 30 (USP30) by sponging microRNA-2467-3p (miR-2467-3p) and recruiting the FUS RNA binding protein (FUS), thereby stabilizing β-catenin and activating the Wnt/β-catenin signaling pathway. These findings suggest that USP30-AS1 enhances CC cell growth and migration through the miR-2467-3p/FUS/USP30 axis, highlighting its potential as a biomarker for CC.

22(R)-hydroxycholesterol (22(R)-HCHO) is a crucial precursor of steroids biosynthesis with various biological functions. However, the production of 22(R)-HCHO is expensive and unsustainable due to chemical synthesis and extraction from plants or animals. This study aimed to construct a microbial cell factory to efficiently produce 22(R)-HCHO through systems metabolic engineering. First, we tested 7-dehydrocholesterol reductase (Dhcr7s) and cholesterol C22-hydroxylases from different sources in Saccharomyces cerevisiae, and the titer of 22(R)-HCHO reached 128.30 mg L⁻¹ in the engineered strain expressing Dhcr7 from Columba livia (ClDhcr7) and cholesterol 22-hydroxylase from Veratrum californicum (VcCyp90b27). Subsequently, the 22(R)-HCHO titer was significantly increased to 427.78 mg L⁻¹ by optimizing the critical genes involved in 22(R)-HCHO biosynthesis. Furthermore, hybrid diploids were constructed to balance cell growth and 22(R)-HCHO production and to improve stress tolerance. Finally, the engineered strain produced 2.03 g L⁻¹ of 22(R)-HCHO in a 5-L fermenter, representing the highest 22(R)-HCHO titer reported to date in engineered microbial cell factories. The results of this study provide a foundation for further applications of 22(R)-HCHO in various industrially valuable steroids.

Traditional Chinese food therapies often motivate the development of modern medicines, and learning from them will bring bright prospects. Monascus, a conventional Chinese fungus with centuries of use in the food industry, produces various metabolites, including natural pigments, lipid-lowering substances, and other bioactive ingredients. Recent Monascus studies focused on the metabolite biosynthesis mechanisms, strain modifications, and fermentation process optimizations, significantly advancing Monascus development on a lab scale. However, the advanced manufacture for Monascus is lacking, restricting its scale production. Here, the synthetic biology techniques and their challenges for engineering filamentous fungi were summarized, especially for Monascus. With further in-depth discussions of automatic solid-state fermentation manufacturing and prospects for combining synthetic biology and process intensification, the industrial scale production of Monascus will succeed with the help of Monascus improvement and intelligent fermentation control, promoting Monascus applications in food, cosmetic, agriculture, medicine, and environmental protection industries.

Therapeutic oligonucleotides (ONs) have great potential to treat many diseases due to their ability to regulate gene expression. However, the inefficiency of standard purification techniques to separate the target sequence from molecularly similar variants is hindering development of large scale ON manufacturing at a reasonable cost. Multicolumn Countercurrent Solvent Gradient Purification (MCSGP) is a valuable process able to bypass the purity-yield tradeoff typical of single-column operations, and hence to make the ON production more sustainable from both an economic and environmental point of view. However, operating close to the optimum of MCSGP can be challenging, resulting in unstable process performance and in a drift in product quality, especially when running a continuous process for extended periods where process parameters such as temperature are prone to variation. In this work, we demonstrate how greater process robustness is introduced in the design and execution of MCSGP for the purification of a 20mer single-stranded DNA sequence through the implementation of UV-based dynamic control. With this novel approach, the cyclic steady state was reached already in the third cycle and disturbances coming from fluctuations in the feed quality, loading amount and temperature were effectively compensated allowing a stable operation close to the optimum. In response to the perturbations, the controlled process kept the standard deviation on product recovery below 3.4%, while for the non-controlled process it increased up to 27.5%.

We developed a method to produce a soluble form of a single-chain fragment variable (scFv) targeting human epithelial growth factor receptor 2 (HER2) in Escherichia coli. By optimizing the orientations of the variable heavy (VH) and variable light (VL) domains and the His-tag, we identified the HL-His type antibody with the highest HER2-binding activity. Purification of HL-His yielded 40.7 mg from a 1 L culture, achieving >99% purity. The limit of detection was determined to be 2.9 ng, demonstrating high production yield, purity, and sensitivity. Moreover, we successfully labeled HER2⁺ cell lines with fluorescent dye-conjugated scFv, resulting in a significantly higher observed signal-to-background ratio, compared to that of HER2⁻ cell lines. This highlights the potential of these fluorescent scFvs as valuable probes for HER2⁺ breast cancer diagnostics. Notably, the process for the complete scFv production was streamlined and required only 4–5 days. Additionally, the product maintained its activity after freeze storage, allowing for large-scale production and a wide range of practical applications.

Modern machine learning has the potential to fundamentally change the way bioprocesses are developed. In particular, horizontal knowledge transfer methods, which seek to exploit data from historical processes to facilitate process development for a new product, provide an opportunity to rethink current workflows. In this work, we first assess the potential of two knowledge transfer approaches, meta learning and one-hot encoding, in combination with Gaussian process (GP) models. We compare their performance with GPs trained only on data of the new process, that is, local models. Using simulated mammalian cell culture data, we observe that both knowledge transfer approaches exhibit test set errors that are approximately halved compared to those of the local models when two, four, or eight experiments of the new product are used for training. Subsequently, we address the question whether experiments for a new product could be designed more effectively by exploiting existing knowledge. In particular, we suggest to specifically design a few runs for the novel product to calibrate knowledge transfer models, a task that we coin calibration design. We propose a customized objective function to identify a set of calibration design runs, which exploits differences in the process evolution of historical products. In two simulated case studies, we observed that training with calibration designs yields similar test set errors compared to common design of experiments approaches. However, the former requires approximately four times fewer experiments. Overall, the results suggest that process development could be significantly streamlined when systematically carrying knowledge from one product to the next.