Pub Date : 2024-11-01DOI: 10.1038/s42003-024-07133-1
Donghoon Kang, Min June Yang, Hae-Kap Cheong, Chin-Ju Park
Forkhead box O4 (FOXO4), a human transcription factor, recognizes target DNA through its forkhead domain (FHD) while maintaining comparable binding affinity to non-target DNA. The conserved region 3 (CR3), a transactivation domain, modulates DNA binding kinetics to FHD and contributes to target DNA selection, but the underlying mechanism of this selection remains elusive. Using paramagnetic relaxation enhancement analysis, we observed a minor state of CR3 close to FHD in the presence of non-target DNA, a state absent when FHD interacts with target DNA. This minor state suggests that CR3 effectively masks the non-target DNA-binding interface on FHD. The interaction weakens significantly under high salt concentration, implying that CR3 or high salt concentrations can modulate electrostatic interactions with non-target DNA. Our 15N relaxation measurements revealed FHD’s flexibility with non-target DNA and increased rigidity with target DNA binding. Our findings offer insights into the role of FOXO4 as a transcription initiator. FOXO4 CR3 masks the non-target DNA binding interface of FHD. FHD increases flexibility with non-target DNA and rigidity with target DNA, releasing CR3. Salt modulates the rate of FHD-DNA binding, discriminating between target and non-target DNA.
叉头盒 O4（FOXO4）是一种人类转录因子，它通过其叉头结构域（FHD）识别目标 DNA，同时与非目标 DNA 保持相当的结合亲和力。保守区 3（CR3）是一个转录激活结构域，它能调节 DNA 与 FHD 的结合动力学，并有助于目标 DNA 的选择，但这种选择的潜在机制仍不清楚。通过顺磁弛豫增强分析，我们观察到 CR3 在非目标 DNA 存在时接近 FHD 的次要状态，而当 FHD 与目标 DNA 相互作用时则不存在这种状态。这种小状态表明，CR3 有效地掩盖了 FHD 上的非目标 DNA 结合界面。这种相互作用在高浓度盐下明显减弱，这意味着 CR3 或高浓度盐可以调节与非目标 DNA 的静电相互作用。我们的 15N 驰豫测量结果表明，FHD 与非目标 DNA 结合时具有柔韧性，而与目标 DNA 结合时刚性增强。我们的研究结果有助于深入了解 FOXO4 作为转录启动子的作用。
{"title":"NMR investigation of FOXO4-DNA interaction for discriminating target and non-target DNA sequences","authors":"Donghoon Kang, Min June Yang, Hae-Kap Cheong, Chin-Ju Park","doi":"10.1038/s42003-024-07133-1","DOIUrl":"10.1038/s42003-024-07133-1","url":null,"abstract":"Forkhead box O4 (FOXO4), a human transcription factor, recognizes target DNA through its forkhead domain (FHD) while maintaining comparable binding affinity to non-target DNA. The conserved region 3 (CR3), a transactivation domain, modulates DNA binding kinetics to FHD and contributes to target DNA selection, but the underlying mechanism of this selection remains elusive. Using paramagnetic relaxation enhancement analysis, we observed a minor state of CR3 close to FHD in the presence of non-target DNA, a state absent when FHD interacts with target DNA. This minor state suggests that CR3 effectively masks the non-target DNA-binding interface on FHD. The interaction weakens significantly under high salt concentration, implying that CR3 or high salt concentrations can modulate electrostatic interactions with non-target DNA. Our 15N relaxation measurements revealed FHD’s flexibility with non-target DNA and increased rigidity with target DNA binding. Our findings offer insights into the role of FOXO4 as a transcription initiator. FOXO4 CR3 masks the non-target DNA binding interface of FHD. FHD increases flexibility with non-target DNA and rigidity with target DNA, releasing CR3. Salt modulates the rate of FHD-DNA binding, discriminating between target and non-target DNA.","PeriodicalId":10552,"journal":{"name":"Communications Biology","volume":null,"pages":null},"PeriodicalIF":5.2,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s42003-024-07133-1.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142564123","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 : 2024-10-31DOI: 10.1038/s42003-024-07045-0
Christopher J. F. Cameron, Sebastian J. H. Seager, Fred J. Sigworth, Hemant D. Tagare, Mark B. Gerstein
Cryo-EM particle identification from micrographs (“picking”) is challenging due to the low signal-to-noise ratio and lack of ground truth for particle locations. State-of-the-art computational algorithms (“pickers”) identify different particle sets, complicating the selection of the best-suited picker for a protein of interest. Here, we present REliable PIcking by Consensus (REPIC), a computational approach to identifying particles common to the output of multiple pickers. We frame consensus particle picking as a graph problem, which REPIC solves using integer linear programming. REPIC picks high-quality particles even when the best picker is not known a priori or a protein is difficult-to-pick (e.g., NOMPC ion channel). Reconstructions using consensus particles without particle filtering achieve resolutions comparable to those from particles picked by experts. Our results show that REPIC requires minimal (often no) manual intervention, and considerably reduces the burden on cryo-EM users for picker selection and particle picking. Availability: https://github.com/ccameron/REPIC . Cryo-EM particle picking is difficult due to noise and no ground truth. Here, a computational method for finding consensus particles from different picking algorithms is presented. This method identifies high-quality particles with minimal user input.
{"title":"REliable PIcking by Consensus (REPIC): a consensus methodology for harnessing multiple cryo-EM particle pickers","authors":"Christopher J. F. Cameron, Sebastian J. H. Seager, Fred J. Sigworth, Hemant D. Tagare, Mark B. Gerstein","doi":"10.1038/s42003-024-07045-0","DOIUrl":"10.1038/s42003-024-07045-0","url":null,"abstract":"Cryo-EM particle identification from micrographs (“picking”) is challenging due to the low signal-to-noise ratio and lack of ground truth for particle locations. State-of-the-art computational algorithms (“pickers”) identify different particle sets, complicating the selection of the best-suited picker for a protein of interest. Here, we present REliable PIcking by Consensus (REPIC), a computational approach to identifying particles common to the output of multiple pickers. We frame consensus particle picking as a graph problem, which REPIC solves using integer linear programming. REPIC picks high-quality particles even when the best picker is not known a priori or a protein is difficult-to-pick (e.g., NOMPC ion channel). Reconstructions using consensus particles without particle filtering achieve resolutions comparable to those from particles picked by experts. Our results show that REPIC requires minimal (often no) manual intervention, and considerably reduces the burden on cryo-EM users for picker selection and particle picking. Availability: https://github.com/ccameron/REPIC . Cryo-EM particle picking is difficult due to noise and no ground truth. Here, a computational method for finding consensus particles from different picking algorithms is presented. This method identifies high-quality particles with minimal user input.","PeriodicalId":10552,"journal":{"name":"Communications Biology","volume":null,"pages":null},"PeriodicalIF":5.2,"publicationDate":"2024-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s42003-024-07045-0.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142555511","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 : 2024-10-31DOI: 10.1038/s42003-024-07110-8
Chiemela Ohanele, Jessica N. Peoples, Anja Karlstaedt, Joshua T. Geiger, Ashley D. Gayle, Nasab Ghazal, Fateemaa Sohani, Milton E. Brown, Michael E. Davis, George A. Porter Jr., Victor Faundez, Jennifer Q. Kwong
The developing mammalian heart undergoes an important metabolic shift from glycolysis towards mitochondrial oxidation that is critical to support the increasing energetic demands of the maturing heart. Here, we describe a new mechanistic link between mitochondria and cardiac morphogenesis, uncovered by studying mitochondrial citrate carrier (SLC25A1) knockout mice. Slc25a1 null embryos displayed impaired growth, mitochondrial dysfunction and cardiac malformations that recapitulate the congenital heart defects observed in 22q11.2 deletion syndrome, a microdeletion disorder involving the SLC25A1 locus. Importantly, Slc25a1 heterozygous embryos, while overtly indistinguishable from wild type, exhibited an increased frequency of these defects, suggesting Slc25a1 haploinsuffiency and dose-dependent effects. Mechanistically, SLC25A1 may link mitochondria to transcriptional regulation of metabolism through epigenetic control of gene expression to promote metabolic remodeling in the developing heart. Collectively, this work positions SLC25A1 as a novel mitochondrial regulator of cardiac morphogenesis and metabolic maturation, and suggests a role in congenital heart disease. The mitochondrial citrate carrier SLC25A1 mediates key metabolic transitions during cardiac morphogenesis through epigenetic regulation of histone acetylation, ultimately supporting structural maturation of the embryonic heart.
{"title":"The mitochondrial citrate carrier SLC25A1 regulates metabolic reprogramming and morphogenesis in the developing heart","authors":"Chiemela Ohanele, Jessica N. Peoples, Anja Karlstaedt, Joshua T. Geiger, Ashley D. Gayle, Nasab Ghazal, Fateemaa Sohani, Milton E. Brown, Michael E. Davis, George A. Porter Jr., Victor Faundez, Jennifer Q. Kwong","doi":"10.1038/s42003-024-07110-8","DOIUrl":"10.1038/s42003-024-07110-8","url":null,"abstract":"The developing mammalian heart undergoes an important metabolic shift from glycolysis towards mitochondrial oxidation that is critical to support the increasing energetic demands of the maturing heart. Here, we describe a new mechanistic link between mitochondria and cardiac morphogenesis, uncovered by studying mitochondrial citrate carrier (SLC25A1) knockout mice. Slc25a1 null embryos displayed impaired growth, mitochondrial dysfunction and cardiac malformations that recapitulate the congenital heart defects observed in 22q11.2 deletion syndrome, a microdeletion disorder involving the SLC25A1 locus. Importantly, Slc25a1 heterozygous embryos, while overtly indistinguishable from wild type, exhibited an increased frequency of these defects, suggesting Slc25a1 haploinsuffiency and dose-dependent effects. Mechanistically, SLC25A1 may link mitochondria to transcriptional regulation of metabolism through epigenetic control of gene expression to promote metabolic remodeling in the developing heart. Collectively, this work positions SLC25A1 as a novel mitochondrial regulator of cardiac morphogenesis and metabolic maturation, and suggests a role in congenital heart disease. The mitochondrial citrate carrier SLC25A1 mediates key metabolic transitions during cardiac morphogenesis through epigenetic regulation of histone acetylation, ultimately supporting structural maturation of the embryonic heart.","PeriodicalId":10552,"journal":{"name":"Communications Biology","volume":null,"pages":null},"PeriodicalIF":5.2,"publicationDate":"2024-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s42003-024-07110-8.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142555525","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 : 2024-10-31DOI: 10.1038/s42003-024-07065-w
Yue Luan, Ling Zhong, Cao Li, Xiaoyu Yue, Mengyan Ye, Jianpeng Wang, Yiping Zhu, Qin Wang
Polydactyly was recorded before 100 BCE and attracted widespread interest because of its relationship to limb health and ancestral traits in horses. However, the underlying reasons for the development of polydactyly remain unclear. To search for polydactyly-related genes, we utilize a paternal half-sib family and screen for variants that match the mode of inheritance. Through this screening process, 77 variants in 65 genes are filtered. A missense variant (EqCab3.0 chr4: <107353368> A > G) (rs1138485164) in the 3rd exon of LMBR1 is identified as a source of amino acid sequence variation. Gene editing confirms that the variant down-regulates LMBR1expression, increases the proliferative viability of mutant cells, and inhibits apoptosis. This study suggests that LMBR1 might play a role in the development of polydactyly and that the variant detected in this study is related to polydactyly in horses. However, further research is needed to determine whether a direct relationship exists. Identification of an LMBR1variant suggests a potential role in equine polydactyly development, revealing its impact on gene expression, cell proliferation, apoptosis and Shh signalling pathway.
{"title":"A dominant missense variant within LMBR1 related to equine polydactyly","authors":"Yue Luan, Ling Zhong, Cao Li, Xiaoyu Yue, Mengyan Ye, Jianpeng Wang, Yiping Zhu, Qin Wang","doi":"10.1038/s42003-024-07065-w","DOIUrl":"10.1038/s42003-024-07065-w","url":null,"abstract":"Polydactyly was recorded before 100 BCE and attracted widespread interest because of its relationship to limb health and ancestral traits in horses. However, the underlying reasons for the development of polydactyly remain unclear. To search for polydactyly-related genes, we utilize a paternal half-sib family and screen for variants that match the mode of inheritance. Through this screening process, 77 variants in 65 genes are filtered. A missense variant (EqCab3.0 chr4: <107353368> A > G) (rs1138485164) in the 3rd exon of LMBR1 is identified as a source of amino acid sequence variation. Gene editing confirms that the variant down-regulates LMBR1expression, increases the proliferative viability of mutant cells, and inhibits apoptosis. This study suggests that LMBR1 might play a role in the development of polydactyly and that the variant detected in this study is related to polydactyly in horses. However, further research is needed to determine whether a direct relationship exists. Identification of an LMBR1variant suggests a potential role in equine polydactyly development, revealing its impact on gene expression, cell proliferation, apoptosis and Shh signalling pathway.","PeriodicalId":10552,"journal":{"name":"Communications Biology","volume":null,"pages":null},"PeriodicalIF":5.2,"publicationDate":"2024-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s42003-024-07065-w.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142555304","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 : 2024-10-31DOI: 10.1038/s42003-024-07111-7
Charlotte Delrue, Mattias Hofmans, Jo Van Dorpe, Malaïka Van der Linden, Zen Van Gaever, Tessa Kerre, Marijn M. Speeckaert, Sander De Bruyne
The diagnosis of lymphomas is challenging due to their diverse histological presentations and clinical manifestations. There is a need for inexpensive tools that require minimal expertise and are accessible for routine laboratories. Contrastingly, current conventional diagnostic methods are often found only in specialized environments. Attenuated total reflection-Fourier transform infrared (ATR-FTIR) spectroscopy offers a nondestructive and user-friendly approach in the analysis of a wide range of samples. In this paper, we determined whether the technique coupled with machine learning can detect and differentiate lymphoma within lymphoid tissue samples. Tissue sections from 295 individuals diagnosed with lymphoma and 389 individuals without the disease were analyzed using ATR-FTIR spectroscopy. The resulting spectral dataset was split using a 70:30 train-test split. Partial least Squares Discriminant Analysis (PLS-DA) models were trained to distinguish non-malignant lymphoid tissue from lymphoma samples and to differentiate between subtypes. On the training set (n = 478), significant spectral differences were mainly identified in the 1800–900 cm–1 region, attributed to fundamental biochemical constituents like proteins, lipids, carbohydrates, and nucleic acids. On the independent test set (n = 206), the trained PLS-DA model achieved a promising AUC of 0.882 (95% CI: 0.881–0.884) in the differentiation between lymphoma and non-malignant lymphoid tissue. In addition, comparative analyses revealed spectral distinctions and notable clustering between the different lymphoma subtypes. This study provides valuable insights into the application of ATR-FTIR spectroscopy and machine learning in the field of lymphoma diagnosis as a non-destructive, rapid and inexpensive tool with the potential to be easily implemented in non-specialized laboratories. Partial least squares discriminant analysis (PLSDA) identifies distinct spectral variations in the fingerprint region, reflecting fundamental biochemical differences between lymphoma, nonmalignant lymphoid tissue, and their subtypes. These spectral features offer valuable insights into the application of ATR-FTIR spectroscopy and machine learning in the field of lymphoma diagnosis as a non-destructive, rapid and inexpensive tool with the potential to be easily implemented in non-specialized laboratories.
{"title":"Innovative label-free lymphoma diagnosis using infrared spectroscopy and machine learning on tissue sections","authors":"Charlotte Delrue, Mattias Hofmans, Jo Van Dorpe, Malaïka Van der Linden, Zen Van Gaever, Tessa Kerre, Marijn M. Speeckaert, Sander De Bruyne","doi":"10.1038/s42003-024-07111-7","DOIUrl":"10.1038/s42003-024-07111-7","url":null,"abstract":"The diagnosis of lymphomas is challenging due to their diverse histological presentations and clinical manifestations. There is a need for inexpensive tools that require minimal expertise and are accessible for routine laboratories. Contrastingly, current conventional diagnostic methods are often found only in specialized environments. Attenuated total reflection-Fourier transform infrared (ATR-FTIR) spectroscopy offers a nondestructive and user-friendly approach in the analysis of a wide range of samples. In this paper, we determined whether the technique coupled with machine learning can detect and differentiate lymphoma within lymphoid tissue samples. Tissue sections from 295 individuals diagnosed with lymphoma and 389 individuals without the disease were analyzed using ATR-FTIR spectroscopy. The resulting spectral dataset was split using a 70:30 train-test split. Partial least Squares Discriminant Analysis (PLS-DA) models were trained to distinguish non-malignant lymphoid tissue from lymphoma samples and to differentiate between subtypes. On the training set (n = 478), significant spectral differences were mainly identified in the 1800–900 cm–1 region, attributed to fundamental biochemical constituents like proteins, lipids, carbohydrates, and nucleic acids. On the independent test set (n = 206), the trained PLS-DA model achieved a promising AUC of 0.882 (95% CI: 0.881–0.884) in the differentiation between lymphoma and non-malignant lymphoid tissue. In addition, comparative analyses revealed spectral distinctions and notable clustering between the different lymphoma subtypes. This study provides valuable insights into the application of ATR-FTIR spectroscopy and machine learning in the field of lymphoma diagnosis as a non-destructive, rapid and inexpensive tool with the potential to be easily implemented in non-specialized laboratories. Partial least squares discriminant analysis (PLSDA) identifies distinct spectral variations in the fingerprint region, reflecting fundamental biochemical differences between lymphoma, nonmalignant lymphoid tissue, and their subtypes. These spectral features offer valuable insights into the application of ATR-FTIR spectroscopy and machine learning in the field of lymphoma diagnosis as a non-destructive, rapid and inexpensive tool with the potential to be easily implemented in non-specialized laboratories.","PeriodicalId":10552,"journal":{"name":"Communications Biology","volume":null,"pages":null},"PeriodicalIF":5.2,"publicationDate":"2024-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s42003-024-07111-7.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142555526","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 : 2024-10-30DOI: 10.1038/s42003-024-07107-3
Zhonghao Ren, Xiangxiang Zeng, Yizhen Lao, Heping Zheng, Zhuhong You, Hongxin Xiang, Quan Zou
Biomedical network learning offers fresh prospects for expediting drug repositioning. However, traditional network architectures struggle to quantify the relationship between micro-scale drug spatial structures and corresponding macro-scale biomedical networks, limiting their ability to capture key pharmacological properties and complex biomedical information crucial for drug screening and therapeutic discovery. Moreover, challenges such as difficulty in capturing long-range dependencies hinder current network-based approaches. To address these limitations, we introduce the Spatial Hierarchical Network, modeling molecular 3D structures and biological associations into a unified network. We propose an end-to-end framework, SpHN-VDA, integrating spatial hierarchical information through triple attention mechanisms to enhance machine understanding of molecular functionality and improve the accuracy of virus-drug association identification. SpHN-VDA outperforms leading models across three datasets, particularly excelling in out-of-distribution and cold-start scenarios. It also exhibits enhanced robustness against data perturbation, ranging from 20% to 40%. It accurately identifies critical motifs for binding sites, even without protein residue annotations. Leveraging reliability of SpHN-VDA, we have identified 25 potential candidate drugs through gene expression analysis and CMap. Molecular docking experiments with the SARS-CoV-2 spike protein further corroborate the predictions. This research highlights the broad potential of SpHN-VDA to enhance drug repositioning and identify effective treatments for various diseases. The Spatial Hierarchical Network model enhances drug repositioning by quantifying and integrating 3D spatial network with biomedical network information and offers interpretations from biological relationships down to atomic interactions.
{"title":"A spatial hierarchical network learning framework for drug repositioning allowing interpretation from macro to micro scale","authors":"Zhonghao Ren, Xiangxiang Zeng, Yizhen Lao, Heping Zheng, Zhuhong You, Hongxin Xiang, Quan Zou","doi":"10.1038/s42003-024-07107-3","DOIUrl":"10.1038/s42003-024-07107-3","url":null,"abstract":"Biomedical network learning offers fresh prospects for expediting drug repositioning. However, traditional network architectures struggle to quantify the relationship between micro-scale drug spatial structures and corresponding macro-scale biomedical networks, limiting their ability to capture key pharmacological properties and complex biomedical information crucial for drug screening and therapeutic discovery. Moreover, challenges such as difficulty in capturing long-range dependencies hinder current network-based approaches. To address these limitations, we introduce the Spatial Hierarchical Network, modeling molecular 3D structures and biological associations into a unified network. We propose an end-to-end framework, SpHN-VDA, integrating spatial hierarchical information through triple attention mechanisms to enhance machine understanding of molecular functionality and improve the accuracy of virus-drug association identification. SpHN-VDA outperforms leading models across three datasets, particularly excelling in out-of-distribution and cold-start scenarios. It also exhibits enhanced robustness against data perturbation, ranging from 20% to 40%. It accurately identifies critical motifs for binding sites, even without protein residue annotations. Leveraging reliability of SpHN-VDA, we have identified 25 potential candidate drugs through gene expression analysis and CMap. Molecular docking experiments with the SARS-CoV-2 spike protein further corroborate the predictions. This research highlights the broad potential of SpHN-VDA to enhance drug repositioning and identify effective treatments for various diseases. The Spatial Hierarchical Network model enhances drug repositioning by quantifying and integrating 3D spatial network with biomedical network information and offers interpretations from biological relationships down to atomic interactions.","PeriodicalId":10552,"journal":{"name":"Communications Biology","volume":null,"pages":null},"PeriodicalIF":5.2,"publicationDate":"2024-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s42003-024-07107-3.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142544173","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 : 2024-10-30DOI: 10.1038/s42003-024-07046-z
Alyssa M. Budd, Suk Yee Yong, Matthew J. Heydenrych, Benjamin Mayne, Oliver Berry, Simon Jarman
Animal age at maturity can be used as a universal and simple predictor of species extinction risk. At present, methods to estimate age at maturity are typically species-specific, limiting comparisons among species, or are infeasible due to practical constraints. To overcome this, here we develop a universal predictor of species-level age at maturity for vertebrates. We show that modelling the frequency of ‘CG’ sequences (CpG sites) in gene promoter regions yields rapid predictions of vertebrate age at maturity. Our models predict age at maturity with remarkable accuracy and generalisability, with median error rates of 30% (less than 1 year) and are robust to genome assemblies of varying quality. We generate predictions for 1912 vertebrate species for which age at maturity estimates were previously absent from public databases. The predictions can be used to help to inform management decisions for the many species for which more detailed population information is currently unavailable. A universal model to predict vertebrate species’ age at maturity using gene promoter CpG density provides critical data for conservation efforts, with predictions for 1912 species previously lacking this information.
{"title":"Universal prediction of vertebrate species age at maturity","authors":"Alyssa M. Budd, Suk Yee Yong, Matthew J. Heydenrych, Benjamin Mayne, Oliver Berry, Simon Jarman","doi":"10.1038/s42003-024-07046-z","DOIUrl":"10.1038/s42003-024-07046-z","url":null,"abstract":"Animal age at maturity can be used as a universal and simple predictor of species extinction risk. At present, methods to estimate age at maturity are typically species-specific, limiting comparisons among species, or are infeasible due to practical constraints. To overcome this, here we develop a universal predictor of species-level age at maturity for vertebrates. We show that modelling the frequency of ‘CG’ sequences (CpG sites) in gene promoter regions yields rapid predictions of vertebrate age at maturity. Our models predict age at maturity with remarkable accuracy and generalisability, with median error rates of 30% (less than 1 year) and are robust to genome assemblies of varying quality. We generate predictions for 1912 vertebrate species for which age at maturity estimates were previously absent from public databases. The predictions can be used to help to inform management decisions for the many species for which more detailed population information is currently unavailable. A universal model to predict vertebrate species’ age at maturity using gene promoter CpG density provides critical data for conservation efforts, with predictions for 1912 species previously lacking this information.","PeriodicalId":10552,"journal":{"name":"Communications Biology","volume":null,"pages":null},"PeriodicalIF":5.2,"publicationDate":"2024-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s42003-024-07046-z.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142544181","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 : 2024-10-30DOI: 10.1038/s42003-024-07098-1
Martin Holmudden, Joel Gustafsson, Yann J. K. Bertrand, Alexander Schliep, Peter Norberg
The genomic signature of an organism captures the characteristics of repeated oligonucleotide patterns in its genome 1, such as oligomer frequencies, GC content, and differences in codon usage. Viruses, however, are obligate intracellular parasites that are dependent on their host cells for replication, and information about genomic signatures in viruses has hitherto been sparse. Here, we investigate the presence and specificity of genomic signatures in 2,768 eukaryotic viral species from 105 viral families, aiming to illuminate dependencies and selective pressures in viral genome evolution. We demonstrate that most viruses have highly specific genomic signatures that often also differ significantly between species within the same family. The species-specificity is most prominent among dsDNA viruses and viruses with large genomes. We also reveal consistent dissimilarities between viral genomic signatures and those of their host cells, although some viruses present slight similarities, which may be explained by genetic adaptation to their native hosts. Our results suggest that significant evolutionary selection pressures act upon viral genomes to shape and preserve their genomic signatures, which may have implications for the field of synthetic biology in the construction of live attenuated vaccines and viral vectors. Genomic analysis of 2,768 viral species reveals conserved and distinct genome-wide differences in specific oligonucleotide patterns, so-called genomic signatures. These are likely caused by various selection pressures acting on viral genomes.
{"title":"Evolution shapes and conserves genomic signatures in viruses","authors":"Martin Holmudden, Joel Gustafsson, Yann J. K. Bertrand, Alexander Schliep, Peter Norberg","doi":"10.1038/s42003-024-07098-1","DOIUrl":"10.1038/s42003-024-07098-1","url":null,"abstract":"The genomic signature of an organism captures the characteristics of repeated oligonucleotide patterns in its genome 1, such as oligomer frequencies, GC content, and differences in codon usage. Viruses, however, are obligate intracellular parasites that are dependent on their host cells for replication, and information about genomic signatures in viruses has hitherto been sparse. Here, we investigate the presence and specificity of genomic signatures in 2,768 eukaryotic viral species from 105 viral families, aiming to illuminate dependencies and selective pressures in viral genome evolution. We demonstrate that most viruses have highly specific genomic signatures that often also differ significantly between species within the same family. The species-specificity is most prominent among dsDNA viruses and viruses with large genomes. We also reveal consistent dissimilarities between viral genomic signatures and those of their host cells, although some viruses present slight similarities, which may be explained by genetic adaptation to their native hosts. Our results suggest that significant evolutionary selection pressures act upon viral genomes to shape and preserve their genomic signatures, which may have implications for the field of synthetic biology in the construction of live attenuated vaccines and viral vectors. Genomic analysis of 2,768 viral species reveals conserved and distinct genome-wide differences in specific oligonucleotide patterns, so-called genomic signatures. These are likely caused by various selection pressures acting on viral genomes.","PeriodicalId":10552,"journal":{"name":"Communications Biology","volume":null,"pages":null},"PeriodicalIF":5.2,"publicationDate":"2024-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s42003-024-07098-1.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142544178","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 : 2024-10-30DOI: 10.1038/s42003-024-06970-4
Georgina V. Wood, Kingsley J. Griffin, Mirjam van der Mheen, Martin F. Breed, Jane M. Edgeloe, Camille Grimaldi, Antoine J. P. Minne, Iva Popovic, Karen Filbee-Dexter, Madeleine J. H. van Oppen, Thomas Wernberg, Melinda A. Coleman
A critical component of ecosystem restoration projects involves using genetic data to select source material that will enhance success under current and future climates. However, the complexity and expense of applying genetic data is a barrier to its use outside of specialised scientific contexts. To help overcome this barrier, we developed Reef Adapt ( www.reefadapt.org ), an innovative, globally applicable and expandable web platform that incorporates genetic, biophysical and environmental prediction data into marine restoration and assisted gene flow planning. The Reef Adapt tool provides maps that identify areas with populations suited to user-specified restoration/recipient sites under current and future climate scenarios. We demonstrate its versatility and practicality with four case studies of ecologically and evolutionarily diverse taxa: the habitat-forming corals Pocillopora damicornis and Acropora kenti, and macroalgae Phyllospora comosa and Ecklonia radiata. Reef Adapt is a management-ready tool to aid restoration and conservation efforts amidst ongoing habitat degradation and climate change. Aiming to accelerate research in the field of marine restoration, ‘Reef Adapt’ integrates genetic, environmental, and biophysical data to predict populations suited to ‘local’ and ‘future’ climates for marine restoration
{"title":"Reef Adapt: A tool to inform climate-smart marine restoration and management decisions","authors":"Georgina V. Wood, Kingsley J. Griffin, Mirjam van der Mheen, Martin F. Breed, Jane M. Edgeloe, Camille Grimaldi, Antoine J. P. Minne, Iva Popovic, Karen Filbee-Dexter, Madeleine J. H. van Oppen, Thomas Wernberg, Melinda A. Coleman","doi":"10.1038/s42003-024-06970-4","DOIUrl":"10.1038/s42003-024-06970-4","url":null,"abstract":"A critical component of ecosystem restoration projects involves using genetic data to select source material that will enhance success under current and future climates. However, the complexity and expense of applying genetic data is a barrier to its use outside of specialised scientific contexts. To help overcome this barrier, we developed Reef Adapt ( www.reefadapt.org ), an innovative, globally applicable and expandable web platform that incorporates genetic, biophysical and environmental prediction data into marine restoration and assisted gene flow planning. The Reef Adapt tool provides maps that identify areas with populations suited to user-specified restoration/recipient sites under current and future climate scenarios. We demonstrate its versatility and practicality with four case studies of ecologically and evolutionarily diverse taxa: the habitat-forming corals Pocillopora damicornis and Acropora kenti, and macroalgae Phyllospora comosa and Ecklonia radiata. Reef Adapt is a management-ready tool to aid restoration and conservation efforts amidst ongoing habitat degradation and climate change. Aiming to accelerate research in the field of marine restoration, ‘Reef Adapt’ integrates genetic, environmental, and biophysical data to predict populations suited to ‘local’ and ‘future’ climates for marine restoration","PeriodicalId":10552,"journal":{"name":"Communications Biology","volume":null,"pages":null},"PeriodicalIF":5.2,"publicationDate":"2024-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s42003-024-06970-4.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142544180","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}
Stimulator of interferon genes (STING) is vital in the cytosolic DNA-sensing process and critical for initiating the innate immune response, which has important functions in host defense and contributes to the pathogenesis of inflammatory diseases. Zinc finger CCCH-type antiviral protein 1 (ZC3HAV1) specifically binds the CpG dinucleotides in the viral RNAs of multiple viruses and promotes their degradation. ZAPS (ZC3HAV1 short isoform) is a potent stimulator of retinoid acid-inducible gene I (RIG-I) signaling during the antiviral response. However, how ZC3HAV1 controls STING signaling is unclear. Here, we show that ZC3HAV1 specifically potentiates STING activation by associating with STING to promote its oligomerization and translocation from the endoplasmic reticulum (ER) to the Golgi, which facilitates activation of IRF3 and NF-κB pathway. Accordingly, Zc3hav1 deficiency protects mice against herpes simplex virus-1 (HSV-1) infection- or 5,6-dimethylxanthenone-4-acetic acid (DMXAA)-induced inflammation in a STING-dependent manner. These results indicate that ZC3HAV1 is a key regulator of STING signaling, which suggests its possible use as a therapeutic target for STING-dependent inflammation. ZC3HAV1 specifically enhances STING signaling responses to activate IRF3 and NF-κB pathway provides a potential ZC3HAV1-STING-targeting strategy for the clinical management of of STING-dependent inflammatory diseases.
{"title":"ZC3HAV1 facilitates STING activation and enhances inflammation","authors":"Danhui Qin, Hui Song, Caiwei Wang, Xiaojie Ma, Yu Fu, Chunyuan Zhao, Wei Zhao, Lei Zhang, Weifang Zhang","doi":"10.1038/s42003-024-07116-2","DOIUrl":"10.1038/s42003-024-07116-2","url":null,"abstract":"Stimulator of interferon genes (STING) is vital in the cytosolic DNA-sensing process and critical for initiating the innate immune response, which has important functions in host defense and contributes to the pathogenesis of inflammatory diseases. Zinc finger CCCH-type antiviral protein 1 (ZC3HAV1) specifically binds the CpG dinucleotides in the viral RNAs of multiple viruses and promotes their degradation. ZAPS (ZC3HAV1 short isoform) is a potent stimulator of retinoid acid-inducible gene I (RIG-I) signaling during the antiviral response. However, how ZC3HAV1 controls STING signaling is unclear. Here, we show that ZC3HAV1 specifically potentiates STING activation by associating with STING to promote its oligomerization and translocation from the endoplasmic reticulum (ER) to the Golgi, which facilitates activation of IRF3 and NF-κB pathway. Accordingly, Zc3hav1 deficiency protects mice against herpes simplex virus-1 (HSV-1) infection- or 5,6-dimethylxanthenone-4-acetic acid (DMXAA)-induced inflammation in a STING-dependent manner. These results indicate that ZC3HAV1 is a key regulator of STING signaling, which suggests its possible use as a therapeutic target for STING-dependent inflammation. ZC3HAV1 specifically enhances STING signaling responses to activate IRF3 and NF-κB pathway provides a potential ZC3HAV1-STING-targeting strategy for the clinical management of of STING-dependent inflammatory diseases.","PeriodicalId":10552,"journal":{"name":"Communications Biology","volume":null,"pages":null},"PeriodicalIF":5.2,"publicationDate":"2024-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s42003-024-07116-2.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142544182","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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