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[学术文献 ] Advancing microbial production through artificial intelligence-aided biology 进入全文
Biotechnology Advances
Microbial cell factories (MCFs) have been leveraged to construct sustainable platforms for value-added compound production. To optimize metabolism and reach optimal productivity, synthetic biology has developed various genetic devices to engineer microbial systems by gene editing, high-throughput protein engineering, and dynamic regulation. However, current synthetic biology methodologies still rely heavily on manual design, laborious testing, and exhaustive analysis. The emerging interdisciplinary field of artificial intelligence (AI) and biology has become pivotal in addressing the remaining challenges. AI-aided microbial production harnesses the power of processing, learning, and predicting vast amounts of biological data within seconds, providing outputs with high probability. With well-trained AI models, the conventional Design-Build-Test (DBT) cycle has been transformed into a multidimensional Design-Build-Test-Learn-Predict (DBTLP) workflow, leading to significantly improved operational efficiency and reduced labor consumption. Here, we comprehensively review the main components and recent advances in AI-aided microbial production, focusing on genome annotation, AI-aided protein engineering, artificial functional protein design, and AI-enabled pathway prediction. Finally, we discuss the challenges of integrating novel AI techniques into biology and propose the potential of large language models (LLMs) in advancing microbial production.
[学术文献 ] Simultaneous enhancement of multiple functional properties using evolution-informed protein design 进入全文
Nature Communications
A major challenge in protein design is to augment existing functional proteins with multiple property enhancements. Altering several properties likely necessitates numerous primary sequence changes, and novel methods are needed to accurately predict combinations of mutations that maintain or enhance function. Models of sequence co-variation (e.g., EVcouplings), which leverage extensive information about various protein properties and activities from homologous protein sequences, have proven effective for many applications including structure determination and mutation effect prediction. We apply EVcouplings to computationally design variants of the model protein TEM-1 β-lactamase. Nearly all the 14 experimentally characterized designs were functional, including one with 84 mutations from the nearest natural homolog. The designs also had large increases in thermostability, increased activity on multiple substrates, and nearly identical structure to the wild type enzyme. This study highlights the efficacy of evolutionary models in guiding large sequence alterations to generate functional diversity for protein design applications.
[学术文献 ] Utilization of low-stability variants in protein evolutionary engineering 进入全文
International Journal of Biological Macromolecules
Evolutionary engineering involves repeated mutations and screening and is widely used to modify protein functions. However, it is important to diversify evolutionary pathways to eliminate the bias and limitations of the variants by using traditionally unselected variants. In this study, we focused on low-stability variants that are commonly excluded from evolutionary processes and tested a method that included an additional restabilization step. The esterase from the thermophilic bacterium Alicyclobacillus acidocaldarius was used as a model protein, and its activity at its optimum temperature of 65 °C was improved by evolutionary experiments using random mutations by error-prone PCR. After restabilization using low-stability variants with low-temperature (37 °C) activity, several re-stabilizing variants were obtained from a large number of variant libraries. Some of the restabilized variants achieved by removing the destabilizing mutations showed higher activity than that of the wild-type protein. This implies that low-stability variants with low-temperature activity can be re-evolved for future use. This method will enable further diversification of evolutionary pathways.
[学术文献 ] High-Temperature Tolerance Protein Engineering through Deep Evolution 进入全文
BIODESIGN RESEARCH
Protein engineering aimed at increasing temperature tolerance through iterative mutagenesis and high-throughput screening is often labor-intensive. Here, we developed a deep evolution (DeepEvo) strategy to engineer protein high-temperature tolerance by generating and selecting functional sequences using deep learning models. Drawing inspiration from the concept of evolution, we constructed a high-temperature tolerance selector based on a protein language model, acting as selective pressure in the high-dimensional latent spaces of protein sequences to enrich those with high-temperature tolerance. Simultaneously, we developed a variant generator using a generative adversarial network to produce protein sequence variants containing the desired function. Afterward, the iterative process involving the generator and selector was executed to accumulate high-temperature tolerance traits. We experimentally tested this approach on the model protein glyceraldehyde 3-phosphate dehydrogenase, obtaining 8 variants with high-temperature tolerance from just 30 generated sequences, achieving a success rate of over 26%, demonstrating the high efficiency of DeepEvo in engineering protein high-temperature tolerance.
[前沿资讯 ] 中科院天津工业生物所开发面向CRISPR技术的基因组编辑自动化设计在线工具AutoESDcas 进入全文
中科院天津工业生物所
近日，中国科学院天津工业生物技术研究所生物设计中心平台实验室开发了面向CRISPR技术的基因组编辑自动化设计在线工具AutoESDcas（https://autoesdcas.biodesign.ac.cn）。该工具面向CRISPR介导的同源重组技术和Golden Gate组装技术，通过搭建自动化编辑序列设计流程，实现了基因组编辑的自动化和高通量设计；通过整合多种基因组编辑任务的设计流程，实现了对多种基因组编辑实验场景的支持；通过添加同源臂脱靶风险评估和基于脱靶分析的引物优化功能，提高了设计结果的可靠性。该工具能够自动化完成针对不同实验场景的基因组编辑实验流程所需的全套编辑序列设计。针对多个物种的数百个设计任务可在一小时内完成，尤其适用于面向高通量基因编辑平台的大规模基因组编辑设计。
[前沿资讯 ] Reversal of the histidine kinase activity by a small linker helix 进入全文
Eurekalert
Scientists have revealed new information on how red light-regulated histidine kinases function. According to the study, altering of the length of a specific ‘linker helix’ region of the protein can even reverse their enzymatic activity. The study is published in Nature Communications. An international collaboration between the groups of Dr. Heikki Takala from the University of Jyväskylä and Prof. Andreas Möglich from the University of Bayreuth have revealed key details on histidine kinase signaling. By applying modifications in their pREDusk tool, they showed how the delicate balance between kinase and phosphatase activities is fine-tuned in histidine kinase receptors. Importantly, they also revealed that certain deletions in a so-called ‘linker helix’ of the phytochrome component reverses their enzymatic activity.
