Pub Date : 2024-11-14DOI: 10.1016/j.cell.2024.10.037
Tom Maniatis
Recombinant DNA technology has profoundly advanced virtually every aspect of biological and medical sciences, from basic research to biotechnology. Here, I discuss conceptual connections linking fundamental discoveries that were enabled by the technology, advances in the understanding of gene regulation in both prokaryotes and eukaryotes, and the recent FDA-approved CRISPR-based gene therapy for sickle cell anemia and β-thalassemia based on transcriptional derepression.
{"title":"From bacterial operons to gene therapy: 50 years of the journal Cell","authors":"Tom Maniatis","doi":"10.1016/j.cell.2024.10.037","DOIUrl":"https://doi.org/10.1016/j.cell.2024.10.037","url":null,"abstract":"Recombinant DNA technology has profoundly advanced virtually every aspect of biological and medical sciences, from basic research to biotechnology. Here, I discuss conceptual connections linking fundamental discoveries that were enabled by the technology, advances in the understanding of gene regulation in both prokaryotes and eukaryotes, and the recent FDA-approved CRISPR-based gene therapy for sickle cell anemia and β-thalassemia based on transcriptional derepression.","PeriodicalId":9656,"journal":{"name":"Cell","volume":"13 1","pages":""},"PeriodicalIF":64.5,"publicationDate":"2024-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142610147","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 : 2024-11-14DOI: 10.1016/j.cell.2024.10.020
Tycho E.T. Mevissen, Maximilian Kümmecke, Ernst W. Schmid, Lucas Farnung, Johannes C. Walter
In transcription-coupled nucleotide excision repair (TC-NER), stalled RNA polymerase II (RNA Pol II) binds CSB and CRL4CSA, which cooperate with UVSSA and ELOF1 to recruit TFIIH. To explore the mechanism of TC-NER, we recapitulated this reaction in vitro. When a plasmid containing a site-specific lesion is transcribed in frog egg extract, error-free repair is observed that depends on CSB, CRL4CSA, UVSSA, and ELOF1. Repair also requires STK19, a factor previously implicated in transcription recovery after UV exposure. A 1.9-Å cryo-electron microscopy structure shows that STK19 binds the TC-NER complex through CSA and the RPB1 subunit of RNA Pol II. Furthermore, AlphaFold predicts that STK19 interacts with the XPD subunit of TFIIH, and disrupting this interface impairs cell-free repair. Molecular modeling suggests that STK19 positions TFIIH ahead of RNA Pol II for lesion verification. Our analysis of cell-free TC-NER suggests that STK19 couples RNA Pol II stalling to downstream repair events.
在转录偶联核苷酸切割修复（TC-NER）中，停滞的 RNA 聚合酶 II（RNA Pol II）与 CSB 和 CRL4CSA 结合，它们与 UVSSA 和 ELOF1 合作招募 TFIIH。为了探索TC-NER的机制，我们在体外重现了这一反应。当含有位点特异性病变的质粒在蛙卵提取物中转录时，可以观察到依赖于 CSB、CRL4CSA、UVSSA 和 ELOF1 的无差错修复。修复还需要 STK19，这是一种以前与紫外线暴露后转录恢复有关的因子。1.9 埃的冷冻电镜结构显示，STK19 通过 CSA 和 RNA Pol II 的 RPB1 亚基与 TC-NER 复合物结合。此外，AlphaFold 预测 STK19 与 TFIIH 的 XPD 亚基相互作用，破坏这一界面会损害无细胞修复。分子建模表明，STK19 使 TFIIH 先于 RNA Pol II 进行病变验证。我们对无细胞 TC-NER 的分析表明，STK19 将 RNA Pol II 停顿与下游修复事件联系起来。
{"title":"STK19 positions TFIIH for cell-free transcription-coupled DNA repair","authors":"Tycho E.T. Mevissen, Maximilian Kümmecke, Ernst W. Schmid, Lucas Farnung, Johannes C. Walter","doi":"10.1016/j.cell.2024.10.020","DOIUrl":"https://doi.org/10.1016/j.cell.2024.10.020","url":null,"abstract":"In transcription-coupled nucleotide excision repair (TC-NER), stalled RNA polymerase II (RNA Pol II) binds CSB and CRL4<sup>CSA</sup>, which cooperate with UVSSA and ELOF1 to recruit TFIIH. To explore the mechanism of TC-NER, we recapitulated this reaction <em>in vitro</em>. When a plasmid containing a site-specific lesion is transcribed in frog egg extract, error-free repair is observed that depends on CSB, CRL4<sup>CSA</sup>, UVSSA, and ELOF1. Repair also requires STK19, a factor previously implicated in transcription recovery after UV exposure. A 1.9-Å cryo-electron microscopy structure shows that STK19 binds the TC-NER complex through CSA and the RPB1 subunit of RNA Pol II. Furthermore, AlphaFold predicts that STK19 interacts with the XPD subunit of TFIIH, and disrupting this interface impairs cell-free repair. Molecular modeling suggests that STK19 positions TFIIH ahead of RNA Pol II for lesion verification. Our analysis of cell-free TC-NER suggests that STK19 couples RNA Pol II stalling to downstream repair events.","PeriodicalId":9656,"journal":{"name":"Cell","volume":"62 1","pages":""},"PeriodicalIF":64.5,"publicationDate":"2024-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142610145","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 : 2024-11-14DOI: 10.1016/j.cell.2024.10.018
Diana van den Heuvel, Marta Rodríguez-Martínez, Paula J. van der Meer, Nicolas Nieto Moreno, Jiyoung Park, Hyun-Suk Kim, Janne J.M. van Schie, Annelotte P. Wondergem, Areetha D’Souza, George Yakoub, Anna E. Herlihy, Krushanka Kashyap, Thierry Boissière, Jane Walker, Richard Mitter, Katja Apelt, Klaas de Lint, Idil Kirdök, Mats Ljungman, Rob M.F. Wolthuis, Martijn S. Luijsterburg
Transcription-coupled DNA repair (TCR) removes bulky DNA lesions impeding RNA polymerase II (RNAPII) transcription. Recent studies have outlined the stepwise assembly of TCR factors CSB, CSA, UVSSA, and transcription factor IIH (TFIIH) around lesion-stalled RNAPII. However, the mechanism and factors required for the transition to downstream repair steps, including RNAPII removal to provide repair proteins access to the DNA lesion, remain unclear. Here, we identify STK19 as a TCR factor facilitating this transition. Loss of STK19 does not impact initial TCR complex assembly or RNAPII ubiquitylation but delays lesion-stalled RNAPII clearance, thereby interfering with the downstream repair reaction. Cryoelectron microscopy (cryo-EM) and mutational analysis reveal that STK19 associates with the TCR complex, positioning itself between RNAPII, UVSSA, and CSA. The structural insights and molecular modeling suggest that STK19 positions the ATPase subunits of TFIIH onto DNA in front of RNAPII. Together, these findings provide new insights into the factors and mechanisms required for TCR.
{"title":"STK19 facilitates the clearance of lesion-stalled RNAPII during transcription-coupled DNA repair","authors":"Diana van den Heuvel, Marta Rodríguez-Martínez, Paula J. van der Meer, Nicolas Nieto Moreno, Jiyoung Park, Hyun-Suk Kim, Janne J.M. van Schie, Annelotte P. Wondergem, Areetha D’Souza, George Yakoub, Anna E. Herlihy, Krushanka Kashyap, Thierry Boissière, Jane Walker, Richard Mitter, Katja Apelt, Klaas de Lint, Idil Kirdök, Mats Ljungman, Rob M.F. Wolthuis, Martijn S. Luijsterburg","doi":"10.1016/j.cell.2024.10.018","DOIUrl":"https://doi.org/10.1016/j.cell.2024.10.018","url":null,"abstract":"Transcription-coupled DNA repair (TCR) removes bulky DNA lesions impeding RNA polymerase II (RNAPII) transcription. Recent studies have outlined the stepwise assembly of TCR factors CSB, CSA, UVSSA, and transcription factor IIH (TFIIH) around lesion-stalled RNAPII. However, the mechanism and factors required for the transition to downstream repair steps, including RNAPII removal to provide repair proteins access to the DNA lesion, remain unclear. Here, we identify STK19 as a TCR factor facilitating this transition. Loss of STK19 does not impact initial TCR complex assembly or RNAPII ubiquitylation but delays lesion-stalled RNAPII clearance, thereby interfering with the downstream repair reaction. Cryoelectron microscopy (cryo-EM) and mutational analysis reveal that STK19 associates with the TCR complex, positioning itself between RNAPII, UVSSA, and CSA. The structural insights and molecular modeling suggest that STK19 positions the ATPase subunits of TFIIH onto DNA in front of RNAPII. Together, these findings provide new insights into the factors and mechanisms required for TCR.","PeriodicalId":9656,"journal":{"name":"Cell","volume":"43 1","pages":""},"PeriodicalIF":64.5,"publicationDate":"2024-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142610574","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 : 2024-11-14DOI: 10.1016/j.cell.2024.10.024
Ling-Ling Chen, V. Narry Kim
Since the introduction of the central dogma of molecular biology in 1958, various RNA species have been discovered. Messenger RNAs transmit genetic instructions from DNA to make proteins, a process facilitated by housekeeping non-coding RNAs (ncRNAs) such as small nuclear RNAs (snRNAs), ribosomal RNAs (rRNAs), and transfer RNAs (tRNAs). Over the past four decades, a wide array of regulatory ncRNAs have emerged as crucial players in gene regulation. In celebration of Cell’s 50th anniversary, this Review explores our current understanding of the most extensively studied regulatory ncRNAs—small RNAs and long non-coding RNAs (lncRNAs)—which have profoundly shaped the field of RNA biology and beyond. While small RNA pathways have been well documented with clearly defined mechanisms, lncRNAs exhibit a greater diversity of mechanisms, many of which remain unknown. This Review covers pivotal events in their discovery, biogenesis pathways, evolutionary traits, action mechanisms, functions, and crosstalks among ncRNAs. We also highlight their roles in pathophysiological contexts and propose future research directions to decipher the unknowns of lncRNAs by leveraging lessons from small RNAs.
{"title":"Small and long non-coding RNAs: Past, present, and future","authors":"Ling-Ling Chen, V. Narry Kim","doi":"10.1016/j.cell.2024.10.024","DOIUrl":"https://doi.org/10.1016/j.cell.2024.10.024","url":null,"abstract":"Since the introduction of the central dogma of molecular biology in 1958, various RNA species have been discovered. Messenger RNAs transmit genetic instructions from DNA to make proteins, a process facilitated by housekeeping non-coding RNAs (ncRNAs) such as small nuclear RNAs (snRNAs), ribosomal RNAs (rRNAs), and transfer RNAs (tRNAs). Over the past four decades, a wide array of regulatory ncRNAs have emerged as crucial players in gene regulation. In celebration of <em>Cell</em>’s 50th anniversary, this Review explores our current understanding of the most extensively studied regulatory ncRNAs—small RNAs and long non-coding RNAs (lncRNAs)—which have profoundly shaped the field of RNA biology and beyond. While small RNA pathways have been well documented with clearly defined mechanisms, lncRNAs exhibit a greater diversity of mechanisms, many of which remain unknown. This Review covers pivotal events in their discovery, biogenesis pathways, evolutionary traits, action mechanisms, functions, and crosstalks among ncRNAs. We also highlight their roles in pathophysiological contexts and propose future research directions to decipher the unknowns of lncRNAs by leveraging lessons from small RNAs.","PeriodicalId":9656,"journal":{"name":"Cell","volume":"29 1","pages":""},"PeriodicalIF":64.5,"publicationDate":"2024-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142610149","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 : 2024-11-14DOI: 10.1016/j.cell.2024.10.038
Jack F. Greenblatt, Bruce M. Alberts, Nevan J. Krogan
The identification of individual protein-protein interactions (PPIs) began more than 40 years ago, using protein affinity chromatography and antibody co-immunoprecipitation. As new technologies emerged, analysis of PPIs increased to a genome-wide scale with the introduction of intracellular tagging methods, affinity purification (AP) followed by mass spectrometry (MS), and co-fractionation MS (CF-MS). Now, combining the resulting catalogs of interactions with complementary methods, including crosslinking MS (XL-MS) and cryogenic electron microscopy (cryo-EM), helps distinguish direct interactions from indirect ones within the same or between different protein complexes. These powerful approaches and the promise of artificial intelligence applications like AlphaFold herald a future where PPIs and protein complexes, including energy-driven protein machines, will be understood in exquisite detail, unlocking new insights in the contexts of both basic biology and disease.
{"title":"Discovery and significance of protein-protein interactions in health and disease","authors":"Jack F. Greenblatt, Bruce M. Alberts, Nevan J. Krogan","doi":"10.1016/j.cell.2024.10.038","DOIUrl":"https://doi.org/10.1016/j.cell.2024.10.038","url":null,"abstract":"The identification of individual protein-protein interactions (PPIs) began more than 40 years ago, using protein affinity chromatography and antibody co-immunoprecipitation. As new technologies emerged, analysis of PPIs increased to a genome-wide scale with the introduction of intracellular tagging methods, affinity purification (AP) followed by mass spectrometry (MS), and co-fractionation MS (CF-MS). Now, combining the resulting catalogs of interactions with complementary methods, including crosslinking MS (XL-MS) and cryogenic electron microscopy (cryo-EM), helps distinguish direct interactions from indirect ones within the same or between different protein complexes. These powerful approaches and the promise of artificial intelligence applications like AlphaFold herald a future where PPIs and protein complexes, including energy-driven protein machines, will be understood in exquisite detail, unlocking new insights in the contexts of both basic biology and disease.","PeriodicalId":9656,"journal":{"name":"Cell","volume":"37 1","pages":""},"PeriodicalIF":64.5,"publicationDate":"2024-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142610151","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 : 2024-11-14DOI: 10.1016/j.cell.2024.10.033
Divyanshu Tiwari, Nabarun Roy, Arun K. Shukla
In a recently published article in Nature, Bayly-Jones et al. report the cryo-EM structures of a lysosomal cholesterol sensor, LYCHOS, also known as GPR155, which reveals a unique fusion of a plant auxin-transporter-like domain with a seven-transmembrane GPCR-like domain and elucidates mechanistic insights into cellular regulation of mTORC1 activity.
{"title":"Bound by the love for cholesterol: A transporter meets a GPCR","authors":"Divyanshu Tiwari, Nabarun Roy, Arun K. Shukla","doi":"10.1016/j.cell.2024.10.033","DOIUrl":"https://doi.org/10.1016/j.cell.2024.10.033","url":null,"abstract":"In a recently published article in <em>Nature</em>, Bayly-Jones et al. report the cryo-EM structures of a lysosomal cholesterol sensor, LYCHOS, also known as GPR155, which reveals a unique fusion of a plant auxin-transporter-like domain with a seven-transmembrane GPCR-like domain and elucidates mechanistic insights into cellular regulation of mTORC1 activity.","PeriodicalId":9656,"journal":{"name":"Cell","volume":"60 1","pages":""},"PeriodicalIF":64.5,"publicationDate":"2024-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142610152","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 : 2024-11-14DOI: 10.1016/j.cell.2024.10.035
Harry F. Noller
The ribosome, together with its tRNA substrates, links genotype to phenotype by translating the genetic information carried by mRNA into protein. During the past half-century, the structure and mechanisms of action of the ribosome have emerged from mystery and confusion. It is now evident that the ribosome is an ancient RNA-based molecular machine of staggering structural complexity and that it is fundamentally similar in all living organisms. The three central functions of protein synthesis—decoding, catalysis of peptide bond formation, and translocation of mRNA and tRNA—are based on elegant mechanisms that evolved from the properties of RNA, the founding macromolecule of life. Moreover, all three of these functions (and even life itself) seem to proceed in defiance of entropy. Protein synthesis thus appears to exploit both the energy of GTP hydrolysis and peptide bond formation to constrain the directionality and accuracy of events taking place on the ribosome.
{"title":"The ribosome comes to life","authors":"Harry F. Noller","doi":"10.1016/j.cell.2024.10.035","DOIUrl":"https://doi.org/10.1016/j.cell.2024.10.035","url":null,"abstract":"The ribosome, together with its tRNA substrates, links genotype to phenotype by translating the genetic information carried by mRNA into protein. During the past half-century, the structure and mechanisms of action of the ribosome have emerged from mystery and confusion. It is now evident that the ribosome is an ancient RNA-based molecular machine of staggering structural complexity and that it is fundamentally similar in all living organisms. The three central functions of protein synthesis—decoding, catalysis of peptide bond formation, and translocation of mRNA and tRNA—are based on elegant mechanisms that evolved from the properties of RNA, the founding macromolecule of life. Moreover, all three of these functions (and even life itself) seem to proceed in defiance of entropy. Protein synthesis thus appears to exploit both the energy of GTP hydrolysis and peptide bond formation to constrain the directionality and accuracy of events taking place on the ribosome.","PeriodicalId":9656,"journal":{"name":"Cell","volume":"10 1","pages":""},"PeriodicalIF":64.5,"publicationDate":"2024-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142610562","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 : 2024-11-13DOI: 10.1016/j.cell.2024.10.022
Suguru Nishijima, Evelina Stankevic, Oliver Aasmets, Thomas S.B. Schmidt, Naoyoshi Nagata, Marisa Isabell Keller, Pamela Ferretti, Helene Bæk Juel, Anthony Fullam, Shahriyar Mahdi Robbani, Christian Schudoma, Johanne Kragh Hansen, Louise Aas Holm, Mads Israelsen, Robert Schierwagen, Nikolaj Torp, Anja Telzerow, Rajna Hercog, Stefanie Kandels, Diënty H.M. Hazenbrink, Maja Thiele
The microbiota in individual habitats differ in both relative composition and absolute abundance. While sequencing approaches determine the relative abundances of taxa and genes, they do not provide information on their absolute abundances. Here, we developed a machine-learning approach to predict fecal microbial loads (microbial cells per gram) solely from relative abundance data. Applying our prediction model to a large-scale metagenomic dataset (n = 34,539), we demonstrated that microbial load is the major determinant of gut microbiome variation and is associated with numerous host factors, including age, diet, and medication. We further found that for several diseases, changes in microbial load, rather than the disease condition itself, more strongly explained alterations in patients’ gut microbiome. Adjusting for this effect substantially reduced the statistical significance of the majority of disease-associated species. Our analysis reveals that the fecal microbial load is a major confounder in microbiome studies, highlighting its importance for understanding microbiome variation in health and disease.
{"title":"Fecal microbial load is a major determinant of gut microbiome variation and a confounder for disease associations","authors":"Suguru Nishijima, Evelina Stankevic, Oliver Aasmets, Thomas S.B. Schmidt, Naoyoshi Nagata, Marisa Isabell Keller, Pamela Ferretti, Helene Bæk Juel, Anthony Fullam, Shahriyar Mahdi Robbani, Christian Schudoma, Johanne Kragh Hansen, Louise Aas Holm, Mads Israelsen, Robert Schierwagen, Nikolaj Torp, Anja Telzerow, Rajna Hercog, Stefanie Kandels, Diënty H.M. Hazenbrink, Maja Thiele","doi":"10.1016/j.cell.2024.10.022","DOIUrl":"https://doi.org/10.1016/j.cell.2024.10.022","url":null,"abstract":"The microbiota in individual habitats differ in both relative composition and absolute abundance. While sequencing approaches determine the relative abundances of taxa and genes, they do not provide information on their absolute abundances. Here, we developed a machine-learning approach to predict fecal microbial loads (microbial cells per gram) solely from relative abundance data. Applying our prediction model to a large-scale metagenomic dataset (<em>n</em> = 34,539), we demonstrated that microbial load is the major determinant of gut microbiome variation and is associated with numerous host factors, including age, diet, and medication. We further found that for several diseases, changes in microbial load, rather than the disease condition itself, more strongly explained alterations in patients’ gut microbiome. Adjusting for this effect substantially reduced the statistical significance of the majority of disease-associated species. Our analysis reveals that the fecal microbial load is a major confounder in microbiome studies, highlighting its importance for understanding microbiome variation in health and disease.","PeriodicalId":9656,"journal":{"name":"Cell","volume":"19 1","pages":""},"PeriodicalIF":64.5,"publicationDate":"2024-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142600990","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 : 2024-11-12DOI: 10.1016/j.cell.2024.10.032
Maria Dolores Moya-Garzon, Mengjie Wang, Veronica L. Li, Xuchao Lyu, Wei Wei, Alan Sheng-Hwa Tung, Steffen H. Raun, Meng Zhao, Laetitia Coassolo, Hashim Islam, Barbara Oliveira, Yuqin Dai, Jan Spaas, Antonio Delgado-Gonzalez, Kenyi Donoso, Aurora Alvarez-Buylla, Francisco Franco-Montalban, Anudari Letian, Catherine P. Ward, Lichao Liu, Jonathan Z. Long
β-Hydroxybutyrate (BHB) is an abundant ketone body. To date, all known pathways of BHB metabolism involve the interconversion of BHB and primary energy intermediates. Here, we identify a previously undescribed BHB secondary metabolic pathway via CNDP2-dependent enzymatic conjugation of BHB and free amino acids. This BHB shunt pathway generates a family of anti-obesity ketone metabolites, the BHB-amino acids. Genetic ablation of CNDP2 in mice eliminates tissue amino acid BHB-ylation activity and reduces BHB-amino acid levels. The most abundant BHB-amino acid, BHB-Phe, is a ketosis-inducible congener of Lac-Phe that activates hypothalamic and brainstem neurons and suppresses feeding. Conversely, CNDP2-KO mice exhibit increased food intake and body weight following exogenous ketone ester supplementation or a ketogenic diet. CNDP2-dependent amino acid BHB-ylation and BHB-amino acid metabolites are also conserved in humans. Therefore, enzymatic amino acid BHB-ylation defines a ketone shunt pathway and bioactive ketone metabolites linked to energy balance.
{"title":"A β-hydroxybutyrate shunt pathway generates anti-obesity ketone metabolites","authors":"Maria Dolores Moya-Garzon, Mengjie Wang, Veronica L. Li, Xuchao Lyu, Wei Wei, Alan Sheng-Hwa Tung, Steffen H. Raun, Meng Zhao, Laetitia Coassolo, Hashim Islam, Barbara Oliveira, Yuqin Dai, Jan Spaas, Antonio Delgado-Gonzalez, Kenyi Donoso, Aurora Alvarez-Buylla, Francisco Franco-Montalban, Anudari Letian, Catherine P. Ward, Lichao Liu, Jonathan Z. Long","doi":"10.1016/j.cell.2024.10.032","DOIUrl":"https://doi.org/10.1016/j.cell.2024.10.032","url":null,"abstract":"β-Hydroxybutyrate (BHB) is an abundant ketone body. To date, all known pathways of BHB metabolism involve the interconversion of BHB and primary energy intermediates. Here, we identify a previously undescribed BHB secondary metabolic pathway via CNDP2-dependent enzymatic conjugation of BHB and free amino acids. This BHB shunt pathway generates a family of anti-obesity ketone metabolites, the BHB-amino acids. Genetic ablation of CNDP2 in mice eliminates tissue amino acid BHB-ylation activity and reduces BHB-amino acid levels. The most abundant BHB-amino acid, BHB-Phe, is a ketosis-inducible congener of Lac-Phe that activates hypothalamic and brainstem neurons and suppresses feeding. Conversely, CNDP2-KO mice exhibit increased food intake and body weight following exogenous ketone ester supplementation or a ketogenic diet. CNDP2-dependent amino acid BHB-ylation and BHB-amino acid metabolites are also conserved in humans. Therefore, enzymatic amino acid BHB-ylation defines a ketone shunt pathway and bioactive ketone metabolites linked to energy balance.","PeriodicalId":9656,"journal":{"name":"Cell","volume":"95 1","pages":""},"PeriodicalIF":64.5,"publicationDate":"2024-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142599611","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}
Kernel dehydration rate (KDR) is a crucial production trait that affects mechanized harvesting and kernel quality in maize; however, the underlying mechanisms remain unclear. Here, we identified a quantitative trait locus (QTL), qKDR1, as a non-coding sequence that regulates the expression of qKDR1 REGULATED PEPTIDE GENE (RPG). RPG encodes a 31 amino acid micropeptide, microRPG1, which controls KDR by precisely modulating the expression of two genes, ZmETHYLENE-INSENSITIVE3-like 1 and 3, in the ethylene signaling pathway in the kernels after filling. microRPG1 is a Zea genus-specific micropeptide and originated de novo from a non-coding sequence. Knockouts of microRPG1 result in faster KDR in maize. By contrast, overexpression or exogenous application of the micropeptide shows the opposite effect both in maize and Arabidopsis. Our findings reveal the molecular mechanism of microRPG1 in kernel dehydration and provide an important tool for future crop breeding.
{"title":"A Zea genus-specific micropeptide controls kernel dehydration in maize","authors":"Yanhui Yu, Wenqiang Li, Yuanfang Liu, Yanjun Liu, Qinzhi Zhang, Yidan Ouyang, Wenya Ding, Yu Xue, Yilin Zou, Junjun Yan, Anqiang Jia, Jiali Yan, Xinfei Hao, Yujie Gou, Zhaowei Zhai, Longyu Liu, Yang Zheng, Bao Zhang, Jieting Xu, Ning Yang, Jianbing Yan","doi":"10.1016/j.cell.2024.10.030","DOIUrl":"https://doi.org/10.1016/j.cell.2024.10.030","url":null,"abstract":"Kernel dehydration rate (KDR) is a crucial production trait that affects mechanized harvesting and kernel quality in maize; however, the underlying mechanisms remain unclear. Here, we identified a quantitative trait locus (QTL), <em>qKDR1</em>, as a non-coding sequence that regulates the expression of <em>qKDR1 REGULATED PEPTIDE GENE</em> (<em>RPG</em>). <em>RPG</em> encodes a 31 amino acid micropeptide, microRPG1, which controls KDR by precisely modulating the expression of two genes, <em>ZmETHYLENE-INSENSITIVE3-like 1</em> and <em>3</em>, in the ethylene signaling pathway in the kernels after filling. microRPG1 is a <em>Zea</em> genus-specific micropeptide and originated <em>de novo</em> from a non-coding sequence. Knockouts of microRPG1 result in faster KDR in maize. By contrast, overexpression or exogenous application of the micropeptide shows the opposite effect both in maize and <em>Arabidopsis</em>. Our findings reveal the molecular mechanism of microRPG1 in kernel dehydration and provide an important tool for future crop breeding.","PeriodicalId":9656,"journal":{"name":"Cell","volume":"51 1","pages":""},"PeriodicalIF":64.5,"publicationDate":"2024-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142599612","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}
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