Trends in biotechnology最新文献

The growing demand for N-acetylneuraminic acid (NeuAc) has driven the need for efficient and environmentally sustainable biomanufacturing processes. Microbial fermentation offers a promising route, yet optimizing cell factories with excellent phenotypes remains challenging. Here, we engineered Escherichia coli to enable high-efficiency co-utilization of glucose and glycerol. We refactored two synthetic pathways with the same start and end to enhance N-acetylmannosamine (ManNAc) precursor levels and optimized NeuAc synthase using artificial intelligence (AI) techniques and machine learning (ML) sequence mining. Subsequently, phosphoenolpyruvate (PEP) levels were boosted by capturing carbon flow from competing regeneration pathways, thus balancing the intracellular PEP:ManNAc ratio for improved NeuAc synthesis. Besides glucose, an additional carbon inlet from glycerol was opened, achieving a NeuAc titer of 70.4 g/l in fed-batch fermentation with a productivity of 1.17 g/l/h. This work demonstrates a highly efficient microbial cell factory for the biosynthesis of NeuAc and provides a versatile system engineering strategy applicable to other high-value compounds.

Sulfolobus islandicus, an emerging archaeal model organism, offers unique advantages for metabolic engineering and synthetic biology applications owing to its ability to thrive in extreme environments. Although several genetic tools have been established for this organism, the lack of well-characterized chromosomal integration sites has limited its potential as a cellular factory. Here, we systematically identified and characterized 13 artificial CRISPR RNAs targeting eight integration sites in S. islandicus using the CRISPR-COPIES pipeline and a multi-omics-informed computational workflow. We leveraged the endogenous CRISPR-Cas system to integrate the reporter gene lacS and validated heterologous expression through a β-galactosidase assay, revealing significant positional effects. As a proof of concept, we utilized these sites to genetically manipulate lipid ether composition by overexpressing glycerol dibiphytanyl glycerol tetraether (GDGT) ring synthase B (GrsB). This study expands the genetic toolbox for S. islandicus and advances its potential as a robust platform for archaeal synthetic biology and industrial biotechnology.

Prime editing is a versatile and precise genome-editing tool. Most prime editors (PEs) rely on reverse transcriptase (RT) derived from Moloney murine leukemia virus (MMLV). Here, we established a PE, pvPE, using a RT derived from a porcine endogenous retrovirus (PERV) from a Bama mini-pig. Through various optimization strategies, including RT engineering, structural modifications, and La protein fusion, we gradually upgraded to pvPE-V4. This version achieved 24.38-101.69-fold higher efficiency compared with pvPE-V1 and up to 2.39-fold higher efficiency than another upgraded PE, PE7, with significantly fewer unintended edits across multiple mammalian cell lines. We further show that nocodazole (Noc) significantly enhanced pvPE efficiency by 2.25-fold on average. Using our pvPE system, we efficiently modified three genes simultaneously in porcine fibroblasts and subsequently generated cloned pigs that could serve as valuable models for Alzheimer's disease (AD) in humans. Our results highlight the broad application prospects of pvPE systems in mammalian genome editing.

Increasingly complex biotechnology endeavours, such as creating 'unnatural' life, warrant societal discussions on their applications and embedding. We explore ways in which xenobiologists imagine their work and relate that to public views. Techno-optimist scientific perspectives contrast with more ambivalent societal ones, calling for broader, value-centred debates and collaborative engagement efforts.

Renewable methanol is a promising feedstock for the bioproduction of single cell protein (SCP) and circular chemicals. Economic implementation is, however, burdensome due to the high oxygen demands inherently associated with methanol conversion. An alternative approach in circumventing this bottleneck via paraformaldehyde is proposed and discussed.

The current biosensor inventory is inadequate for the multitude of metabolites and proteins needing detection. Assisted by new technologies and research paradigms such as multi-omics analysis and de novo protein design, emerging strategies provide a promising avenue for the development of novel, tailored genetically encoded biosensors for various applications.

Promoters are DNA sequences that govern the location, direction, and strength of gene transcription, playing a pivotal role in cellular growth and lifespan. Engineered promoters facilitate precise control of recombinant protein expression and metabolic pathway modulation for natural product biosynthesis. Traditional methods such as rational design and directed evolution have established the foundation for promoter engineering, and recent advances in deep learning (DL) have revolutionized the field. This review highlights the application of DL techniques for promoter identification, strength prediction, and de novo design using generative models. We describe how these tools are used and the impact of database quality, feature extraction, and model architecture on predictive accuracy. We discuss challenges and perspectives in developing robust models for promoter engineering.

Diagnostic sensor technologies lie at the core of the healthcare system and encompass disease screening, detection, and therapy monitoring. In past decades, many nanobiosensor technologies have emerged which rely on diverse principles using electrical, magnetic, mass-based, or photonic signal transduction methods. We provide an overview of recent and emerging nanobiosensing transduction technologies and illustrate the reported quantification capabilities for nucleic acids, proteins, and small molecules. The review assesses and compares their performance, multimodality, and multiplexing capabilities as well as their portability and throughput, among other criteria. In addition, we elaborate on demonstrated as well as envisaged medical applications of nanobiosensors. Finally, fundamental limitations such as the diffusion limit are discussed and opportunities for future research are outlined.

Carbonic anhydrase (CA) enzymes hold strong potential in new biotechnological strategies for accelerated CO₂ capture and conversion. Some CAs naturally tolerate the harsh conditions associated with carbon capture technologies; however, long-term durability, while maintaining high activity, presents significant challenges. This review offers an in-depth analysis of the CA enzymes that have been investigated for industrial carbon capture processes and highlights the key amino acids and structural features that are crucial for CA activity and stability under harsh conditions. It examines the impact of site-directed protein engineering to enhance CA efficacy and immobilization strategies. Furthermore, it addresses the challenges of scaling up CA-based technologies and offers strategies to improve their functionality. Future research directions, including artificial intelligence (AI)-driven optimization, are also discussed.

Cell freezing is critical for the long-term preservation of biological materials, but is limited by the cytotoxicity and inefficacy of conventional cryoprotective agents, such as dimethyl sulfoxide (DMSO). Here, we introduce DNA frameworks (DFs) as a nanoengineered programmable class of cryoprotectants designed to address these challenges. The DFs feature a programmable scaffolded structure offering large flexible wireframe contacts, cellular target ability, and biodegradability. Cholesterol-functionalized DFs outperformed conventional cryoprotectants in the recovery and maintenance of cellular functionality and morphology of frozen cells. Their cryoprotective mechanism enables targeted binding to the cell membrane, minimizing intracellular penetration or uptake, inhibits intracellular and extracellular ice growths, and promotes efficient post-thaw degradation to mitigate toxicity risks. By combining membrane-targeting specificity, cryoprotective efficacy, and biocompatibility, these DFs represent a transformative advance in cell cryopreservation.