IF 4.5

mLife Pub Date : 2025-01-19 eCollection Date: 2025-02-01 DOI: 10.1002/mlf2.12155

Yujie Zhang, Wenjun Wu, Ke Huang, Fang-Jie Zhao

引用次数: 0

Complexation of CcmB with CcmACD safeguards heme translocation for cytochrome c maturation. CcmB与CcmACD的络合保护细胞色素c成熟的血红素易位。

IF 4.5

mLife Pub Date : 2025-01-06 eCollection Date: 2025-02-01 DOI: 10.1002/mlf2.12150

Yuanyou Xu, Wei Wang, Qianrou Zhang, Sirui Han, Jiahao Wang, Shihua Wu, Haichun Gao

引用次数: 0

Phospholipase PlcH is involved in the secretion of cell wall glycoproteins and contributes to the host immune response of Aspergillus fumigatus. 磷脂酶 PlcH 参与细胞壁糖蛋白的分泌，并有助于烟曲霉的宿主免疫反应。

IF 4.5

mLife Pub Date : 2024-12-26 eCollection Date: 2024-12-01 DOI: 10.1002/mlf2.12146

Jinbin Hao, Yin Guo, Hui Zhou, Haomiao Ouyang, Jinghua Yang, Wenxia Fang, Cheng Jin

{"title":"Phospholipase PlcH is involved in the secretion of cell wall glycoproteins and contributes to the host immune response of Aspergillus fumigatus.","authors":"Jinbin Hao, Yin Guo, Hui Zhou, Haomiao Ouyang, Jinghua Yang, Wenxia Fang, Cheng Jin","doi":"10.1002/mlf2.12146","DOIUrl":"10.1002/mlf2.12146","url":null,"abstract":"Glycosylphosphatidylinositol (GPI) anchoring is one of the conserved posttranslational modifications in eukaryotes that attach proteins to the plasma membrane. In fungi, in addition to plasma membrane GPI-anchored proteins (GPI-APs), some GPI-APs are specifically released from the cell membrane, secreted into the cell wall, and covalently linked to cell wall glucans as GPI-anchored cell wall proteins (GPI-CWPs). However, it remains unclear how fungal cells specifically release GPI-CWPs from their membranes. In this study, phospholipase PlcH was identified and confirmed as a phospholipase C that hydrolyzes phosphate ester bonds to release GPI-APs from the membrane of the opportunistic fungal pathogen Aspergillus fumigatus. Deletion of the plcH gene led to abnormal conidiation, polar abnormality, and increased sensitivity to antifungal drugs. In an immunocompromised mouse model, the ΔplcH mutant showed an attenuated inflammatory response and increased macrophage killing compared with the wild type. Biochemical and proteomic analyses revealed that PlcH was involved in the localization of various cell wall GPI-APs and contributed to the cell wall integrity. Our results demonstrate that PlcH can specifically recognize and release GPI-CWPs from the cell membrane, which represents a newly discovered secretory pathway of GPI-CWPs in A. fumigatus.","PeriodicalId":94145,"journal":{"name":"mLife","volume":"3 4","pages":"537-550"},"PeriodicalIF":4.5,"publicationDate":"2024-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11685838/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142916771","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Optimizing enzyme thermostability by combining multiple mutations using protein language model. 利用蛋白质语言模型结合多种突变优化酶的耐热性。

IF 4.5

mLife Pub Date : 2024-12-26 eCollection Date: 2024-12-01 DOI: 10.1002/mlf2.12151

Jiahao Bian, Pan Tan, Ting Nie, Liang Hong, Guang-Yu Yang

{"title":"Optimizing enzyme thermostability by combining multiple mutations using protein language model.","authors":"Jiahao Bian, Pan Tan, Ting Nie, Liang Hong, Guang-Yu Yang","doi":"10.1002/mlf2.12151","DOIUrl":"10.1002/mlf2.12151","url":null,"abstract":"Optimizing enzyme thermostability is essential for advancements in protein science and industrial applications. Currently, (semi-)rational design and random mutagenesis methods can accurately identify single-point mutations that enhance enzyme thermostability. However, complex epistatic interactions often arise when multiple mutation sites are combined, leading to the complete inactivation of combinatorial mutants. As a result, constructing an optimized enzyme often requires repeated rounds of design to incrementally incorporate single mutation sites, which is highly time-consuming. In this study, we developed an AI-aided strategy for enzyme thermostability engineering that efficiently facilitates the recombination of beneficial single-point mutations. We utilized thermostability data from creatinase, including 18 single-point mutants, 22 double-point mutants, 21 triple-point mutants, and 12 quadruple-point mutants. Using these data as inputs, we used a temperature-guided protein language model, Pro-PRIME, to learn epistatic features and design combinatorial mutants. After two rounds of design, we obtained 50 combinatorial mutants with superior thermostability, achieving a success rate of 100%. The best mutant, 13M4, contained 13 mutation sites and maintained nearly full catalytic activity compared to the wild-type. It showed a 10.19°C increase in the melting temperature and an ~655-fold increase in the half-life at 58°C. Additionally, the model successfully captured epistasis in high-order combinatorial mutants, including sign epistasis (K351E) and synergistic epistasis (D17V/I149V). We elucidated the mechanism of long-range epistasis in detail using a dynamics cross-correlation matrix method. Our work provides an efficient framework for designing enzyme thermostability and studying high-order epistatic effects in protein-directed evolution.","PeriodicalId":94145,"journal":{"name":"mLife","volume":"3 4","pages":"492-504"},"PeriodicalIF":4.5,"publicationDate":"2024-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11685841/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142916769","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Protein engineering in the deep learning era.

IF 4.5

mLife Pub Date : 2024-12-26 eCollection Date: 2024-12-01 DOI: 10.1002/mlf2.12157

Bingxin Zhou, Yang Tan, Yutong Hu, Lirong Zheng, Bozitao Zhong, Liang Hong

{"title":"Protein engineering in the deep learning era.","authors":"Bingxin Zhou, Yang Tan, Yutong Hu, Lirong Zheng, Bozitao Zhong, Liang Hong","doi":"10.1002/mlf2.12157","DOIUrl":"10.1002/mlf2.12157","url":null,"abstract":"Advances in deep learning have significantly aided protein engineering in addressing challenges in industrial production, healthcare, and environmental sustainability. This review frames frequently researched problems in protein understanding and engineering from the perspective of deep learning. It provides a thorough discussion of representation methods for protein sequences and structures, along with general encoding pipelines that support both pre-training and supervised learning tasks. We summarize state-of-the-art protein language models, geometric deep learning techniques, and the combination of distinct approaches to learning from multi-modal biological data. Additionally, we outline common downstream tasks and relevant benchmark datasets for training and evaluating deep learning models, focusing on satisfying the particular needs of protein engineering applications, such as identifying mutation sites and predicting properties for candidates' virtual screening. This review offers biologists the latest tools for assisting their engineering projects while providing a clear and comprehensive guide for computer scientists to develop more powerful solutions by standardizing problem formulation and consolidating data resources. Future research can foresee a deeper integration of the communities of biology and computer science, unleashing the full potential of deep learning in protein engineering and driving new scientific breakthroughs.","PeriodicalId":94145,"journal":{"name":"mLife","volume":"3 4","pages":"477-491"},"PeriodicalIF":4.5,"publicationDate":"2024-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11685842/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142916775","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

NAC4ED: A high-throughput computational platform for the rational design of enzyme activity and substrate selectivity. NAC4ED：用于合理设计酶活性和底物选择性的高通量计算平台。

IF 4.5

mLife Pub Date : 2024-12-25 eCollection Date: 2024-12-01 DOI: 10.1002/mlf2.12154

Chuanxi Zhang, Yinghui Feng, Yiting Zhu, Lei Gong, Hao Wei, Lujia Zhang

{"title":"NAC4ED: A high-throughput computational platform for the rational design of enzyme activity and substrate selectivity.","authors":"Chuanxi Zhang, Yinghui Feng, Yiting Zhu, Lei Gong, Hao Wei, Lujia Zhang","doi":"10.1002/mlf2.12154","DOIUrl":"10.1002/mlf2.12154","url":null,"abstract":"In silico computational methods have been widely utilized to study enzyme catalytic mechanisms and design enzyme performance, including molecular docking, molecular dynamics, quantum mechanics, and multiscale QM/MM approaches. However, the manual operation associated with these methods poses challenges for simulating enzymes and enzyme variants in a high-throughput manner. We developed the NAC4ED, a high-throughput enzyme mutagenesis computational platform based on the \"near-attack conformation\" design strategy for enzyme catalysis substrates. This platform circumvents the complex calculations involved in transition-state searching by representing enzyme catalytic mechanisms with parameters derived from near-attack conformations. NAC4ED enables the automated, high-throughput, and systematic computation of enzyme mutants, including protein model construction, complex structure acquisition, molecular dynamics simulation, and analysis of active conformation populations. Validation of the accuracy of NAC4ED demonstrated a prediction accuracy of 92.5% for 40 mutations, showing strong consistency between the computational predictions and experimental results. The time required for automated determination of a single enzyme mutant using NAC4ED is 1/764th of that needed for experimental methods. This has significantly enhanced the efficiency of predicting enzyme mutations, leading to revolutionary breakthroughs in improving the performance of high-throughput screening of enzyme variants. NAC4ED facilitates the efficient generation of a large amount of annotated data, providing high-quality data for statistical modeling and machine learning. NAC4ED is currently available at http://lujialab.org.cn/software/.","PeriodicalId":94145,"journal":{"name":"mLife","volume":"3 4","pages":"505-514"},"PeriodicalIF":4.5,"publicationDate":"2024-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11685835/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142916767","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Bacterial abundance and diversity in 64-74 Ma subseafloor igneous basement from the Louisville Seamount Chain. 路易斯维尔海山链 64-74 Ma 海底下火成岩基底中的细菌丰度和多样性。

IF 4.5

mLife Pub Date : 2024-12-24 eCollection Date: 2024-12-01 DOI: 10.1002/mlf2.12148

Jason B Sylvan, Benjamin J Tully, Yuki Morono, Jeffrey C Alt, Sharon L Grim, Fumio Inagaki, Anthony A P Koppers, Katrina J Edwards

{"title":"Bacterial abundance and diversity in 64-74 Ma subseafloor igneous basement from the Louisville Seamount Chain.","authors":"Jason B Sylvan, Benjamin J Tully, Yuki Morono, Jeffrey C Alt, Sharon L Grim, Fumio Inagaki, Anthony A P Koppers, Katrina J Edwards","doi":"10.1002/mlf2.12148","DOIUrl":"10.1002/mlf2.12148","url":null,"abstract":"The aquifer in the subseafloor igneous basement is a massive, continuous microbial substrate, yet sparingly little is known about life in this habitat. The work to date has focused largely on describing microbial diversity in the young basement (<10 Ma), where the basaltic crust is still porous and fluid flow through it is active. Here, we test the hypothesis that microbial life exists in subseafloor basement >65 Ma using samples collected from the Louisville Seamount Chain via seafloor drilling. Cell biomass was heterogeneous in nature, ranging from below detection to ~104 cells cm-3. Bacterial 16S rRNA genes from core samples and enrichment incubations are dominated by lineages putatively carrying out nitrogen, sulfur, and metal redox processes and hydrocarbon oxidation. Taken together, the data indicate that microbial life is indeed present in subseafloor igneous basement >65 Ma, which significantly expands the range of the subseafloor biosphere where microbial life is known to exist.","PeriodicalId":94145,"journal":{"name":"mLife","volume":"3 4","pages":"578-583"},"PeriodicalIF":4.5,"publicationDate":"2024-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11685831/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142916760","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Photosynthesis by nonphotosynthetic microorganisms via semiconductor photocatalysis. 非光合微生物通过半导体光催化进行光合作用。

IF 4.5

mLife Pub Date : 2024-12-24 eCollection Date: 2024-12-01 DOI: 10.1002/mlf2.12156

Bo Wang, Liang Shi, Anhuai Lu

引用次数: 0

Genotype-microbiome-metabolome associations in early childhood and their link to BMI. 儿童早期基因型-微生物组-代谢组关联及其与BMI的关系。

IF 4.5

mLife Pub Date : 2024-12-24 eCollection Date: 2024-12-01 DOI: 10.1002/mlf2.12153

Andrea Aparicio, Zheng Sun, Diane R Gold, Jessica A Lasky-Su, Augusto A Litonjua, Scott T Weiss, Kathleen Lee-Sarwar, Yang-Yu Liu

引用次数: 0

GRAPE-WEB: An automated computational redesign web server for improving protein thermostability. 一个自动计算重新设计的web服务器，用于提高蛋白质的热稳定性。

IF 4.5

mLife Pub Date : 2024-12-24 eCollection Date: 2024-12-01 DOI: 10.1002/mlf2.12152

Jinyuan Sun, Wenyu Shi, Zhihui Xing, Guomei Fan, Qinglan Sun, Linhuan Wu, Juncai Ma, Yinglu Cui, Bian Wu

引用次数: 0

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