Pub Date : 2024-07-25DOI: 10.1038/s41422-024-00975-8
Laura Poliseno, Martina Lanza, Pier Paolo Pandolfi
The advent of high-throughput sequencing uncovered that our genome is pervasively transcribed into RNAs that are seemingly not translated into proteins. It was also found that non-coding RNA transcripts outnumber canonical protein-coding genes. This mindboggling discovery prompted a surge in non-coding RNA research that started unraveling the functional relevance of these new genetic units, shaking the classic definition of “gene”. While the non-coding RNA revolution was still taking place, polysome/ribosome profiling and mass spectrometry analyses revealed that peptides can be translated from non-canonical open reading frames. Therefore, it is becoming evident that the coding vs non-coding dichotomy is way blurrier than anticipated. In this review, we focus on several examples in which the binary classification of coding vs non-coding genes is outdated, since the same bifunctional gene expresses both coding and non-coding products. We discuss the implications of this intricate usage of transcripts in terms of molecular mechanisms of gene expression and biological outputs, which are often concordant, but can also surprisingly be discordant. Finally, we discuss the methodological caveats that are associated with the study of bifunctional genes, and we highlight the opportunities and challenges of therapeutic exploitation of this intricacy towards the development of anticancer therapies.
{"title":"Coding, or non-coding, that is the question","authors":"Laura Poliseno, Martina Lanza, Pier Paolo Pandolfi","doi":"10.1038/s41422-024-00975-8","DOIUrl":"10.1038/s41422-024-00975-8","url":null,"abstract":"The advent of high-throughput sequencing uncovered that our genome is pervasively transcribed into RNAs that are seemingly not translated into proteins. It was also found that non-coding RNA transcripts outnumber canonical protein-coding genes. This mindboggling discovery prompted a surge in non-coding RNA research that started unraveling the functional relevance of these new genetic units, shaking the classic definition of “gene”. While the non-coding RNA revolution was still taking place, polysome/ribosome profiling and mass spectrometry analyses revealed that peptides can be translated from non-canonical open reading frames. Therefore, it is becoming evident that the coding vs non-coding dichotomy is way blurrier than anticipated. In this review, we focus on several examples in which the binary classification of coding vs non-coding genes is outdated, since the same bifunctional gene expresses both coding and non-coding products. We discuss the implications of this intricate usage of transcripts in terms of molecular mechanisms of gene expression and biological outputs, which are often concordant, but can also surprisingly be discordant. Finally, we discuss the methodological caveats that are associated with the study of bifunctional genes, and we highlight the opportunities and challenges of therapeutic exploitation of this intricacy towards the development of anticancer therapies.","PeriodicalId":9926,"journal":{"name":"Cell Research","volume":"34 9","pages":"609-629"},"PeriodicalIF":28.1,"publicationDate":"2024-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41422-024-00975-8.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141755093","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-23DOI: 10.1038/s41422-024-01005-3
Sten Eirik W Jacobsen
{"title":"Rejuvenating immunity through a balancing stem cell act.","authors":"Sten Eirik W Jacobsen","doi":"10.1038/s41422-024-01005-3","DOIUrl":"https://doi.org/10.1038/s41422-024-01005-3","url":null,"abstract":"","PeriodicalId":9926,"journal":{"name":"Cell Research","volume":" ","pages":""},"PeriodicalIF":28.1,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141751215","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-19DOI: 10.1038/s41422-024-01000-8
Can Yue, Shuo Liu, Bo Meng, Kaiyue Fan, Sijie Yang, Pan Liu, Qianhui Zhu, Xin Mao, Yuanling Yu, Fei Shao, Peng Wang, Youchun Wang, Ravindra Kumar Gupta, Yunlong Cao, Xiangxi Wang
{"title":"Deletion of V483 in the spike confers evolutionary advantage on SARS-CoV-2 for human adaptation and host-range expansion after a prolonged pandemic","authors":"Can Yue, Shuo Liu, Bo Meng, Kaiyue Fan, Sijie Yang, Pan Liu, Qianhui Zhu, Xin Mao, Yuanling Yu, Fei Shao, Peng Wang, Youchun Wang, Ravindra Kumar Gupta, Yunlong Cao, Xiangxi Wang","doi":"10.1038/s41422-024-01000-8","DOIUrl":"10.1038/s41422-024-01000-8","url":null,"abstract":"","PeriodicalId":9926,"journal":{"name":"Cell Research","volume":"34 10","pages":"739-742"},"PeriodicalIF":28.1,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41422-024-01000-8.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141726114","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-12DOI: 10.1038/s41422-024-00997-2
Jia Guo, Yun-Li Zhou, Yixin Yang, Shimeng Guo, Erli You, Xin Xie, Yi Jiang, Chunyou Mao, H. Eric Xu, Yan Zhang
Protease-activated receptors (PARs) are a unique group within the G protein-coupled receptor superfamily, orchestrating cellular responses to extracellular proteases via enzymatic cleavage, which triggers intracellular signaling pathways. Protease-activated receptor 1 (PAR1) is a key member of this family and is recognized as a critical pharmacological target for managing thrombotic disorders. In this study, we present cryo-electron microscopy structures of PAR1 in its activated state, induced by its natural tethered agonist (TA), in complex with two distinct downstream proteins, the Gq and Gi heterotrimers, respectively. The TA peptide is positioned within a surface pocket, prompting PAR1 activation through notable conformational shifts. Contrary to the typical receptor activation that involves the outward movement of transmembrane helix 6 (TM6), PAR1 activation is characterized by the simultaneous downward shift of TM6 and TM7, coupled with the rotation of a group of aromatic residues. This results in the displacement of an intracellular anion, creating space for downstream G protein binding. Our findings delineate the TA recognition pattern and highlight a distinct role of the second extracellular loop in forming β-sheets with TA within the PAR family, a feature not observed in other TA-activated receptors. Moreover, the nuanced differences in the interactions between intracellular loops 2/3 and the Gα subunit of different G proteins are crucial for determining the specificity of G protein coupling. These insights contribute to our understanding of the ligand binding and activation mechanisms of PARs, illuminating the basis for PAR1’s versatility in G protein coupling.
蛋白酶激活受体（PAR）是 G 蛋白偶联受体超家族中的一个独特群体，它通过酶裂解来协调细胞对细胞外蛋白酶的反应，从而触发细胞内的信号通路。蛋白酶激活受体 1（PAR1）是这一家族的关键成员，被认为是治疗血栓性疾病的重要药物靶点。在这项研究中，我们展示了 PAR1 在其天然系链激动剂（TA）诱导下，分别与两种不同的下游蛋白（Gq 和 Gi 杂三聚体）复合后的活化状态的冷冻电镜结构。TA 肽位于表面口袋中，通过显著的构象转变促使 PAR1 激活。与涉及跨膜螺旋 6（TM6）向外移动的典型受体激活不同，PAR1 激活的特点是 TM6 和 TM7 同时向下移动，加上一组芳香族残基的旋转。这导致了细胞内阴离子的移位，为下游 G 蛋白的结合创造了空间。我们的研究结果描述了 TA 的识别模式，并强调了 PAR 家族中第二个胞外环在与 TA 形成 β 片时的独特作用，这是其他 TA 激活受体中未观察到的特征。此外，细胞内环 2/3 与不同 G 蛋白的 Gα 亚基之间相互作用的细微差别对于确定 G 蛋白耦合的特异性至关重要。这些见解有助于我们理解 PAR 的配体结合和激活机制，阐明了 PAR1 在 G 蛋白耦合中的多功能性的基础。
{"title":"Structural basis of tethered agonism and G protein coupling of protease-activated receptors","authors":"Jia Guo, Yun-Li Zhou, Yixin Yang, Shimeng Guo, Erli You, Xin Xie, Yi Jiang, Chunyou Mao, H. Eric Xu, Yan Zhang","doi":"10.1038/s41422-024-00997-2","DOIUrl":"10.1038/s41422-024-00997-2","url":null,"abstract":"Protease-activated receptors (PARs) are a unique group within the G protein-coupled receptor superfamily, orchestrating cellular responses to extracellular proteases via enzymatic cleavage, which triggers intracellular signaling pathways. Protease-activated receptor 1 (PAR1) is a key member of this family and is recognized as a critical pharmacological target for managing thrombotic disorders. In this study, we present cryo-electron microscopy structures of PAR1 in its activated state, induced by its natural tethered agonist (TA), in complex with two distinct downstream proteins, the Gq and Gi heterotrimers, respectively. The TA peptide is positioned within a surface pocket, prompting PAR1 activation through notable conformational shifts. Contrary to the typical receptor activation that involves the outward movement of transmembrane helix 6 (TM6), PAR1 activation is characterized by the simultaneous downward shift of TM6 and TM7, coupled with the rotation of a group of aromatic residues. This results in the displacement of an intracellular anion, creating space for downstream G protein binding. Our findings delineate the TA recognition pattern and highlight a distinct role of the second extracellular loop in forming β-sheets with TA within the PAR family, a feature not observed in other TA-activated receptors. Moreover, the nuanced differences in the interactions between intracellular loops 2/3 and the Gα subunit of different G proteins are crucial for determining the specificity of G protein coupling. These insights contribute to our understanding of the ligand binding and activation mechanisms of PARs, illuminating the basis for PAR1’s versatility in G protein coupling.","PeriodicalId":9926,"journal":{"name":"Cell Research","volume":"34 10","pages":"725-734"},"PeriodicalIF":28.1,"publicationDate":"2024-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41422-024-00997-2.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141597399","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-11DOI: 10.1038/s41422-024-01001-7
Zheng Li, Ruichen Ma, Rishikesh P. Bhalerao
{"title":"Perenniality: the tale of three MADS-box genes","authors":"Zheng Li, Ruichen Ma, Rishikesh P. Bhalerao","doi":"10.1038/s41422-024-01001-7","DOIUrl":"10.1038/s41422-024-01001-7","url":null,"abstract":"","PeriodicalId":9926,"journal":{"name":"Cell Research","volume":"34 11","pages":"753-754"},"PeriodicalIF":28.1,"publicationDate":"2024-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41422-024-01001-7.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141584240","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-07-05DOI: 10.1038/s41422-024-00989-2
Peng Cheng, Cong Mao, Jin Tang, Sen Yang, Yu Cheng, Wuke Wang, Qiuxi Gu, Wei Han, Hao Chen, Sihan Li, Yaofeng Chen, Jianglin Zhou, Wuju Li, Aimin Pan, Suwen Zhao, Xingxu Huang, Shiqiang Zhu, Jun Zhang, Wenjie Shu, Shengqi Wang
Mutations in amino acid sequences can provoke changes in protein function. Accurate and unsupervised prediction of mutation effects is critical in biotechnology and biomedicine, but remains a fundamental challenge. To resolve this challenge, here we present Protein Mutational Effect Predictor (ProMEP), a general and multiple sequence alignment-free method that enables zero-shot prediction of mutation effects. A multimodal deep representation learning model embedded in ProMEP was developed to comprehensively learn both sequence and structure contexts from ~160 million proteins. ProMEP achieves state-of-the-art performance in mutational effect prediction and accomplishes a tremendous improvement in speed, enabling efficient and intelligent protein engineering. Specifically, ProMEP accurately forecasts mutational consequences on the gene-editing enzymes TnpB and TadA, and successfully guides the development of high-performance gene-editing tools with their engineered variants. The gene-editing efficiency of a 5-site mutant of TnpB reaches up to 74.04% (vs 24.66% for the wild type); and the base editing tool developed on the basis of a TadA 15-site mutant (in addition to the A106V/D108N double mutation that renders deoxyadenosine deaminase activity to TadA) exhibits an A-to-G conversion frequency of up to 77.27% (vs 69.80% for ABE8e, a previous TadA-based adenine base editor) with significantly reduced bystander and off-target effects compared to ABE8e. ProMEP not only showcases superior performance in predicting mutational effects on proteins but also demonstrates a great capability to guide protein engineering. Therefore, ProMEP enables efficient exploration of the gigantic protein space and facilitates practical design of proteins, thereby advancing studies in biomedicine and synthetic biology.
氨基酸序列的突变会引起蛋白质功能的改变。在生物技术和生物医学中，准确和无监督地预测突变效应至关重要，但这仍然是一个基本挑战。为了解决这一难题，我们在这里提出了蛋白质突变效应预测器（ProMEP），这是一种通用的、无需多序列比对的方法，可以实现突变效应的零次预测。我们开发了一个嵌入 ProMEP 的多模态深度表征学习模型，以从约 1.6 亿个蛋白质中全面学习序列和结构上下文。ProMEP 在突变效应预测方面达到了最先进的性能，并极大地提高了速度，从而实现了高效、智能的蛋白质工程。具体来说，ProMEP 准确预测了基因编辑酶 TnpB 和 TadA 的突变后果，并成功指导了高性能基因编辑工具及其工程变体的开发。TnpB 5 位点突变体的基因编辑效率高达 74.04%（野生型为 24.66%）；基于 TadA 15 位点突变体（除了 A106V/D108N 双突变使 TadA 失去脱氧腺苷脱氨酶活性外）开发的碱基编辑工具的 A-G 转换频率高达 77.27%（与之前基于 TadA 的腺嘌呤碱基编辑器 ABE8e 的 69.80% 相比），与 ABE8e 相比，旁观者和脱靶效应显著降低。ProMEP 不仅在预测突变对蛋白质的影响方面表现出卓越的性能，而且在指导蛋白质工程方面也显示出强大的能力。因此，ProMEP 能够有效探索巨大的蛋白质空间，促进蛋白质的实用设计，从而推动生物医学和合成生物学的研究。
{"title":"Zero-shot prediction of mutation effects with multimodal deep representation learning guides protein engineering","authors":"Peng Cheng, Cong Mao, Jin Tang, Sen Yang, Yu Cheng, Wuke Wang, Qiuxi Gu, Wei Han, Hao Chen, Sihan Li, Yaofeng Chen, Jianglin Zhou, Wuju Li, Aimin Pan, Suwen Zhao, Xingxu Huang, Shiqiang Zhu, Jun Zhang, Wenjie Shu, Shengqi Wang","doi":"10.1038/s41422-024-00989-2","DOIUrl":"10.1038/s41422-024-00989-2","url":null,"abstract":"Mutations in amino acid sequences can provoke changes in protein function. Accurate and unsupervised prediction of mutation effects is critical in biotechnology and biomedicine, but remains a fundamental challenge. To resolve this challenge, here we present Protein Mutational Effect Predictor (ProMEP), a general and multiple sequence alignment-free method that enables zero-shot prediction of mutation effects. A multimodal deep representation learning model embedded in ProMEP was developed to comprehensively learn both sequence and structure contexts from ~160 million proteins. ProMEP achieves state-of-the-art performance in mutational effect prediction and accomplishes a tremendous improvement in speed, enabling efficient and intelligent protein engineering. Specifically, ProMEP accurately forecasts mutational consequences on the gene-editing enzymes TnpB and TadA, and successfully guides the development of high-performance gene-editing tools with their engineered variants. The gene-editing efficiency of a 5-site mutant of TnpB reaches up to 74.04% (vs 24.66% for the wild type); and the base editing tool developed on the basis of a TadA 15-site mutant (in addition to the A106V/D108N double mutation that renders deoxyadenosine deaminase activity to TadA) exhibits an A-to-G conversion frequency of up to 77.27% (vs 69.80% for ABE8e, a previous TadA-based adenine base editor) with significantly reduced bystander and off-target effects compared to ABE8e. ProMEP not only showcases superior performance in predicting mutational effects on proteins but also demonstrates a great capability to guide protein engineering. Therefore, ProMEP enables efficient exploration of the gigantic protein space and facilitates practical design of proteins, thereby advancing studies in biomedicine and synthetic biology.","PeriodicalId":9926,"journal":{"name":"Cell Research","volume":"34 9","pages":"630-647"},"PeriodicalIF":28.1,"publicationDate":"2024-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41422-024-00989-2.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141537604","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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