Improved provenance tracking by documenting plasmids within their own sequence [0.03%]
通过记录自身序列中的质粒来改进来源追踪
Chris J Myers
Chris J Myers
In a recent article, Hernandez et al. introduced a framework for plasmid self-documentation. It uses the data storage capabilities of the DNA of a plasmid to capture either direct documentation or a reference to full documentation. The appr...
Micaela Brandão Lavender,Jasper P Groot,Annemiek Ter Heijne et al.
Micaela Brandão Lavender et al.
CH4-producing bioelectrochemical systems (BES) are a promising alternative to convert CO2 and electricity into CH4. However, not much is known about the local conditions and possible gradients at CH4-producing biocathodes, especially when u...
Microbial production of D-mannose and D-sedoheptulose with tunable ratios [0.03%]
具有可调比值的D-岩藻糖和D-庚酮糖微生物生产技术
Dileep Sai Kumar Palur,Bryant Luu,Jayce E Taylor et al.
Dileep Sai Kumar Palur et al.
Rare sugars are valuable for food and pharmaceutical applications. D-Mannose, a low-calorie sweetener, is traditionally produced via chemical extraction from plant biomass, which is unsustainable, while enzymatic methods suffer from low yie...
Computationally guided genome rewiring of Escherichia coli and its application for nanopolyethylene terephthalate (PET) biodegradation and upcycling [0.03%]
计算指导的基因组工程改造大肠杆菌及其降解和升级纳米聚对苯二甲酸乙二醇酯(PET)的应用研究
Paula Vidal,Joan Giménez-Dejoz,Laura Fernandez-Lopez et al.
Paula Vidal et al.
Numerous strategies for the biodegradation and upcycling of polyethylene terephthalate (PET) are under investigation. Here, we present a proof-of-concept study for reprogramming the Escherichia coli BL21(DE3) strain to degrade PET nanoparti...
Cell-free screening of CRISPR-Cas activity by microfluidics-assisted in vitro compartmentalization [0.03%]
基于微流体介导的体外隔室化的无细胞CRISPR-Cas活性筛选
Evgenios Bouzetos,Ketan Ashok Ganar,John van der Oost et al.
Evgenios Bouzetos et al.
CRISPR-Cas systems are responsible for antiviral immunity of prokaryotic cells and have been repurposed as powerful genome-editing tools. Cell-free gene expression has been applied for the rapid characterization of CRISPR-Cas systems in mic...
Flux sampling and context-specific genome-scale metabolic models for biotechnological applications [0.03%]
基于通量采样和上下文特定型基因组范围代谢模型的生物技术应用
Devlin C Moyer,Justin Reimertz,Juan I Fuxman Bass et al.
Devlin C Moyer et al.
Genome-scale metabolic models are used in fields ranging from metabolic engineering to drug discovery and microbiome design. Although these models are often used to predict putatively optimal states, some applications, including modeling hu...
Harnessing Streptomyces-plant interactions for agricultural natural product discovery [0.03%]
利用链霉菌-植物互作进行农业天然产物发现
Guozhong Du,Minghui Pan,Wensheng Xiang et al.
Guozhong Du et al.
Agricultural natural products (agri-NPs) from Streptomyces are a reservoir for green pesticide development, which is critical for global crop protection and food security. However, the discovery of novel agri-NPs with tailored bioactivity i...
Splice, exchange, extend: precision editing of native proteins in live cells [0.03%]
高效精准编辑活细胞内天然蛋白质的新方法
Kevin Schiefelbein,Yael David
Kevin Schiefelbein
Beyer et al. and Hua et al. developed platforms for precise chemical editing of proteins in living mammalian cells. These approaches enabled site-specific tagging at diverse protein sites without disrupting function. Demonstrated on several...
pH-modulated soluble expression of alcohol dehydrogenases in Escherichia coli using adaptive laboratory evolution [0.03%]
利用适应性实验室进化在大肠杆菌中进行pH调控的可溶性乙醇脱氢酶表达
Suraj Mital,Graham Christie,Annette Alcasabas et al.
Suraj Mital et al.
Industrial production of alcohol dehydrogenases (ADHs) is severely hampered by their propensity to form insoluble inclusion bodies during recombinant expression. This work achieves soluble expression of such historically aggregate-prone enz...
A six-tiered framework for evaluating AI models from repeatability to replaceability [0.03%]
一种六层框架用于评估AI模型的可重复性和替代性
Siqi Tian,Alicia Wan Yu Lam,Joseph Jao-Yiu Sung et al.
Siqi Tian et al.
Artificial intelligence (AI) is rapidly transforming biotechnology and medicine. But evaluating its safety, effectiveness, and generalizability is increasingly challenging, especially for complex generative models. Traditional evaluation me...