Pub Date : 2024-10-21DOI: 10.1038/s42003-024-06784-4
Tsam Kiu Pun, Mona Khoshnevis, Tommy Hosman, Guy H. Wilson, Anastasia Kapitonava, Foram Kamdar, Jaimie M. Henderson, John D. Simeral, Carlos E. Vargas-Irwin, Matthew T. Harrison, Leigh R. Hochberg
Intracortical brain-computer interfaces (iBCIs) enable people with tetraplegia to gain intuitive cursor control from movement intentions. To translate to practical use, iBCIs should provide reliable performance for extended periods of time. However, performance begins to degrade as the relationship between kinematic intention and recorded neural activity shifts compared to when the decoder was initially trained. In addition to developing decoders to better handle long-term instability, identifying when to recalibrate will also optimize performance. We propose a method, “MINDFUL”, to measure instabilities in neural data for useful long-term iBCI, without needing labels of user intentions. Longitudinal data were analyzed from two BrainGate2 participants with tetraplegia as they used fixed decoders to control a computer cursor spanning 142 days and 28 days, respectively. We demonstrate a measure of instability that correlates with changes in closed-loop cursor performance solely based on the recorded neural activity (Pearson r = 0.93 and 0.72, respectively). This result suggests a strategy to infer online iBCI performance from neural data alone and to determine when recalibration should take place for practical long-term use. Detection of neural data instability offers a strategy for optimizing brain-computer interfaces.
{"title":"Measuring instability in chronic human intracortical neural recordings towards stable, long-term brain-computer interfaces","authors":"Tsam Kiu Pun, Mona Khoshnevis, Tommy Hosman, Guy H. Wilson, Anastasia Kapitonava, Foram Kamdar, Jaimie M. Henderson, John D. Simeral, Carlos E. Vargas-Irwin, Matthew T. Harrison, Leigh R. Hochberg","doi":"10.1038/s42003-024-06784-4","DOIUrl":"10.1038/s42003-024-06784-4","url":null,"abstract":"Intracortical brain-computer interfaces (iBCIs) enable people with tetraplegia to gain intuitive cursor control from movement intentions. To translate to practical use, iBCIs should provide reliable performance for extended periods of time. However, performance begins to degrade as the relationship between kinematic intention and recorded neural activity shifts compared to when the decoder was initially trained. In addition to developing decoders to better handle long-term instability, identifying when to recalibrate will also optimize performance. We propose a method, “MINDFUL”, to measure instabilities in neural data for useful long-term iBCI, without needing labels of user intentions. Longitudinal data were analyzed from two BrainGate2 participants with tetraplegia as they used fixed decoders to control a computer cursor spanning 142 days and 28 days, respectively. We demonstrate a measure of instability that correlates with changes in closed-loop cursor performance solely based on the recorded neural activity (Pearson r = 0.93 and 0.72, respectively). This result suggests a strategy to infer online iBCI performance from neural data alone and to determine when recalibration should take place for practical long-term use. Detection of neural data instability offers a strategy for optimizing brain-computer interfaces.","PeriodicalId":10552,"journal":{"name":"Communications Biology","volume":null,"pages":null},"PeriodicalIF":5.2,"publicationDate":"2024-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11494208/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142459847","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 : 2024-10-21DOI: 10.1038/s42003-024-07072-x
Ting Gong, Yu Fu, Qingde Wang, Patricia A. Loughran, Yuehua Li, Timothy R. Billiar, Zongmei Wen, Youtan Liu, Jie Fan
Sepsis-induced acute lung injury (ALI), characterized by severe hypoxemia and pulmonary leakage, remains a leading cause of mortality in intensive care units. The exacerbation of ALI during sepsis is largely attributed to uncontrolled inflammatory responses and endothelial dysfunction. Emerging evidence suggests an important role of Z-DNA binding protein 1 (ZBP1) as a sensor in innate immune to drive inflammatory signaling and cell death during infections. However, the role of ZBP1 in sepsis-induced ALI has yet to be defined. We utilized ZBP1 knockout mice and combined single-cell RNA sequencing with experimental validation to investigate ZBP1’s roles in the regulation of macrophages and lung endothelial cells during sepsis. We demonstrate that in sepsis, ZBP1 deficiency in macrophages reduces mitochondrial damage and inhibits glycolysis, thereby altering the metabolic status of macrophages. Consequently, this metabolic shift leads to a reduction in the differentiation of macrophages into pro-inflammatory states and decreases macrophage pyroptosis triggered by activation of the NLRP3 inflammasome. These changes significantly weaken the inflammatory signaling pathways between macrophages and endothelial cells and alleviate endothelial dysfunction and cellular damage. These findings reveal important roles for ZBP1 in mediating multiple pathological processes involved in sepsis-induced ALI by modulating the functional states of macrophages and endothelial cells, thereby highlighting its potential as a promising therapeutic target. ZBP1 drives inflammatory signaling in sepsis-induced acute lung injury, linking macrophage metabolic reprogramming and endothelial dysfunction, revealing its potential as a therapeutic target in critical care.
脓毒症诱发的急性肺损伤（ALI）以严重低氧血症和肺渗漏为特征，仍然是重症监护病房的主要死亡原因。脓毒症期间 ALI 的恶化主要归因于不受控制的炎症反应和内皮功能障碍。新的证据表明，Z-DNA 结合蛋白 1（ZBP1）在先天性免疫中扮演着重要的传感器角色，可在感染期间驱动炎症信号转导和细胞死亡。然而，ZBP1 在败血症诱发的 ALI 中的作用尚未明确。我们利用 ZBP1 基因敲除小鼠，结合单细胞 RNA 测序和实验验证，研究了 ZBP1 在脓毒症期间调控巨噬细胞和肺内皮细胞的作用。我们证明，在脓毒症中，巨噬细胞中 ZBP1 的缺乏会减少线粒体损伤并抑制糖酵解，从而改变巨噬细胞的代谢状态。因此，这种代谢转变导致巨噬细胞向促炎状态分化的减少，并降低了 NLRP3 炎性体激活引发的巨噬细胞脓毒症。这些变化大大削弱了巨噬细胞和内皮细胞之间的炎症信号通路，缓解了内皮功能障碍和细胞损伤。这些发现揭示了 ZBP1 通过调节巨噬细胞和内皮细胞的功能状态，在介导脓毒症诱发的 ALI 所涉及的多种病理过程中发挥的重要作用，从而凸显了其作为一个有潜力的治疗靶点的潜力。
{"title":"Decoding the multiple functions of ZBP1 in the mechanism of sepsis-induced acute lung injury","authors":"Ting Gong, Yu Fu, Qingde Wang, Patricia A. Loughran, Yuehua Li, Timothy R. Billiar, Zongmei Wen, Youtan Liu, Jie Fan","doi":"10.1038/s42003-024-07072-x","DOIUrl":"10.1038/s42003-024-07072-x","url":null,"abstract":"Sepsis-induced acute lung injury (ALI), characterized by severe hypoxemia and pulmonary leakage, remains a leading cause of mortality in intensive care units. The exacerbation of ALI during sepsis is largely attributed to uncontrolled inflammatory responses and endothelial dysfunction. Emerging evidence suggests an important role of Z-DNA binding protein 1 (ZBP1) as a sensor in innate immune to drive inflammatory signaling and cell death during infections. However, the role of ZBP1 in sepsis-induced ALI has yet to be defined. We utilized ZBP1 knockout mice and combined single-cell RNA sequencing with experimental validation to investigate ZBP1’s roles in the regulation of macrophages and lung endothelial cells during sepsis. We demonstrate that in sepsis, ZBP1 deficiency in macrophages reduces mitochondrial damage and inhibits glycolysis, thereby altering the metabolic status of macrophages. Consequently, this metabolic shift leads to a reduction in the differentiation of macrophages into pro-inflammatory states and decreases macrophage pyroptosis triggered by activation of the NLRP3 inflammasome. These changes significantly weaken the inflammatory signaling pathways between macrophages and endothelial cells and alleviate endothelial dysfunction and cellular damage. These findings reveal important roles for ZBP1 in mediating multiple pathological processes involved in sepsis-induced ALI by modulating the functional states of macrophages and endothelial cells, thereby highlighting its potential as a promising therapeutic target. ZBP1 drives inflammatory signaling in sepsis-induced acute lung injury, linking macrophage metabolic reprogramming and endothelial dysfunction, revealing its potential as a therapeutic target in critical care.","PeriodicalId":10552,"journal":{"name":"Communications Biology","volume":null,"pages":null},"PeriodicalIF":5.2,"publicationDate":"2024-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11493966/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142459827","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 : 2024-10-21DOI: 10.1038/s42003-024-06943-7
Kyle A. Sullivan, Matthew Lane, Mikaela Cashman, J. Izaak Miller, Mirko Pavicic, Angelica M. Walker, Ashley Cliff, Jonathon Romero, Xuejun Qin, Niamh Mullins, Anna Docherty, Hilary Coon, Douglas M. Ruderfer, International Suicide Genetics Consortium, VA Million Veteran Program, MVP Suicide Exemplar Workgroup, Michael R. Garvin, John P. Pestian, Allison E. Ashley-Koch, Jean C. Beckham, Benjamin McMahon, David W. Oslin, Nathan A. Kimbrel, Daniel A. Jacobson, David Kainer
Genome-wide association studies (GWAS) identify genetic variants underlying complex traits but are limited by stringent genome-wide significance thresholds. We present GRIN (Gene set Refinement through Interacting Networks), which increases confidence in the expanded gene set by retaining genes strongly connected by biological networks when GWAS thresholds are relaxed. GRIN was validated on both simulated interrelated gene sets as well as multiple GWAS traits. From multiple GWAS summary statistics of suicide attempt, a complex phenotype, GRIN identified additional genes that replicated across independent cohorts and retained biologically interrelated genes despite a relaxed significance threshold. We present a conceptual model of how these retained genes interact through neurobiological pathways that may influence suicidal behavior, and identify existing drugs associated with these pathways that would not have been identified under traditional GWAS thresholds. We demonstrate GRIN’s utility in boosting GWAS results by increasing the number of true positive genes identified from GWAS results. Using the software GRIN, GWAS results are refined by reducing false positive genes using biological network topology, allowing users to lower GWAS significance thresholds to identify additional genes associated with complex traits
{"title":"Analyses of GWAS signal using GRIN identify additional genes contributing to suicidal behavior","authors":"Kyle A. Sullivan, Matthew Lane, Mikaela Cashman, J. Izaak Miller, Mirko Pavicic, Angelica M. Walker, Ashley Cliff, Jonathon Romero, Xuejun Qin, Niamh Mullins, Anna Docherty, Hilary Coon, Douglas M. Ruderfer, International Suicide Genetics Consortium, VA Million Veteran Program, MVP Suicide Exemplar Workgroup, Michael R. Garvin, John P. Pestian, Allison E. Ashley-Koch, Jean C. Beckham, Benjamin McMahon, David W. Oslin, Nathan A. Kimbrel, Daniel A. Jacobson, David Kainer","doi":"10.1038/s42003-024-06943-7","DOIUrl":"10.1038/s42003-024-06943-7","url":null,"abstract":"Genome-wide association studies (GWAS) identify genetic variants underlying complex traits but are limited by stringent genome-wide significance thresholds. We present GRIN (Gene set Refinement through Interacting Networks), which increases confidence in the expanded gene set by retaining genes strongly connected by biological networks when GWAS thresholds are relaxed. GRIN was validated on both simulated interrelated gene sets as well as multiple GWAS traits. From multiple GWAS summary statistics of suicide attempt, a complex phenotype, GRIN identified additional genes that replicated across independent cohorts and retained biologically interrelated genes despite a relaxed significance threshold. We present a conceptual model of how these retained genes interact through neurobiological pathways that may influence suicidal behavior, and identify existing drugs associated with these pathways that would not have been identified under traditional GWAS thresholds. We demonstrate GRIN’s utility in boosting GWAS results by increasing the number of true positive genes identified from GWAS results. Using the software GRIN, GWAS results are refined by reducing false positive genes using biological network topology, allowing users to lower GWAS significance thresholds to identify additional genes associated with complex traits","PeriodicalId":10552,"journal":{"name":"Communications Biology","volume":null,"pages":null},"PeriodicalIF":5.2,"publicationDate":"2024-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11494055/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142459824","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}
Fluorescence lifetime imaging microscopy (FLIM) provides quantitative readouts of biochemical microenvironments, holding great promise for biomedical imaging. However, conventional FLIM relies on slow photon counting routines to accumulate sufficient photon statistics, restricting acquisition speeds. Here we demonstrate SparseFLIM, an intelligent paradigm for achieving high-fidelity FLIM reconstruction from sparse photon measurements. We develop a coupled bidirectional propagation network that enriches photon counts and recovers hidden spatial-temporal information. Quantitative analysis shows over tenfold photon enrichment, dramatically improving signal-to-noise ratio, lifetime accuracy, and correlation compared to the original sparse data. SparseFLIM enables reconstructing spatially and temporally undersampled FLIM at full resolution and channel count. The model exhibits strong generalization across experimental modalities including multispectral FLIM and in vivo endoscopic FLIM. This work establishes deep learning as a promising approach to enhance fluorescence lifetime imaging and transcend limitations imposed by the inherent codependence between measurement duration and information content. SparseFLIM enhances fluorescence lifetime imaging by reconstructing high-fidelity images from sparse photon data, generalizing across various imaging modalities, addressing fundamental trade-offs in FLIM to enable faster and higher-quality imaging.
{"title":"Overcoming photon and spatiotemporal sparsity in fluorescence lifetime imaging with SparseFLIM","authors":"Binglin Shen, Yuan Lu, Fangyin Guo, Fangrui Lin, Rui Hu, Feng Rao, Junle Qu, Liwei Liu","doi":"10.1038/s42003-024-07080-x","DOIUrl":"10.1038/s42003-024-07080-x","url":null,"abstract":"Fluorescence lifetime imaging microscopy (FLIM) provides quantitative readouts of biochemical microenvironments, holding great promise for biomedical imaging. However, conventional FLIM relies on slow photon counting routines to accumulate sufficient photon statistics, restricting acquisition speeds. Here we demonstrate SparseFLIM, an intelligent paradigm for achieving high-fidelity FLIM reconstruction from sparse photon measurements. We develop a coupled bidirectional propagation network that enriches photon counts and recovers hidden spatial-temporal information. Quantitative analysis shows over tenfold photon enrichment, dramatically improving signal-to-noise ratio, lifetime accuracy, and correlation compared to the original sparse data. SparseFLIM enables reconstructing spatially and temporally undersampled FLIM at full resolution and channel count. The model exhibits strong generalization across experimental modalities including multispectral FLIM and in vivo endoscopic FLIM. This work establishes deep learning as a promising approach to enhance fluorescence lifetime imaging and transcend limitations imposed by the inherent codependence between measurement duration and information content. SparseFLIM enhances fluorescence lifetime imaging by reconstructing high-fidelity images from sparse photon data, generalizing across various imaging modalities, addressing fundamental trade-offs in FLIM to enable faster and higher-quality imaging.","PeriodicalId":10552,"journal":{"name":"Communications Biology","volume":null,"pages":null},"PeriodicalIF":5.2,"publicationDate":"2024-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11494201/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142459849","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 : 2024-10-21DOI: 10.1038/s42003-024-07001-y
Hui-Sheng Li, Yu-Ting Tan, Xiao-Fei Zhang
Advancements in spatial transcriptomics have transformed our understanding of organ function and tissue microenvironment. However, accurately identifying spatial domains to depict genome heterogeneity and cellular interactions remains a challenge. In this study, we propose EnSDD (Ensemble-learning for Spatial Domain Detection), a method that ingeniously integrates eight state-of-the-art spatial domain detection methods to automatically identify spatial domains. A key innovation of EnSDD is its dynamic weighting mechanism within the ensemble learning process, which optimizes the contribution of each base model and provides a performance evaluation metric without the need for ground truth data. By leveraging the spatial domains identified through EnSDD, we incorporate the detection of domain-specific spatially variable genes and the spatial distribution of cell types, thereby providing deeper insights into tissue heterogeneity. We validate EnSDD across diverse spatial transcriptomics datasets from various tissue organizational structures. Our results demonstrate that EnSDD significantly enhances spatial domain identification accuracy, identifies genes with spatial expression patterns, and reveals domain-specific cell type enrichment patterns, offering invaluable insights into tissue spatial heterogeneity and regionalization. EnSDD, an ensemble-learning method for spatial domain detection, integrates multiple techniques to enhance identification of spatial domains in transcriptomics, revealing insights into tissue heterogeneity and cancer microenvironments.
{"title":"Enhancing spatial domain detection in spatial transcriptomics with EnSDD","authors":"Hui-Sheng Li, Yu-Ting Tan, Xiao-Fei Zhang","doi":"10.1038/s42003-024-07001-y","DOIUrl":"10.1038/s42003-024-07001-y","url":null,"abstract":"Advancements in spatial transcriptomics have transformed our understanding of organ function and tissue microenvironment. However, accurately identifying spatial domains to depict genome heterogeneity and cellular interactions remains a challenge. In this study, we propose EnSDD (Ensemble-learning for Spatial Domain Detection), a method that ingeniously integrates eight state-of-the-art spatial domain detection methods to automatically identify spatial domains. A key innovation of EnSDD is its dynamic weighting mechanism within the ensemble learning process, which optimizes the contribution of each base model and provides a performance evaluation metric without the need for ground truth data. By leveraging the spatial domains identified through EnSDD, we incorporate the detection of domain-specific spatially variable genes and the spatial distribution of cell types, thereby providing deeper insights into tissue heterogeneity. We validate EnSDD across diverse spatial transcriptomics datasets from various tissue organizational structures. Our results demonstrate that EnSDD significantly enhances spatial domain identification accuracy, identifies genes with spatial expression patterns, and reveals domain-specific cell type enrichment patterns, offering invaluable insights into tissue spatial heterogeneity and regionalization. EnSDD, an ensemble-learning method for spatial domain detection, integrates multiple techniques to enhance identification of spatial domains in transcriptomics, revealing insights into tissue heterogeneity and cancer microenvironments.","PeriodicalId":10552,"journal":{"name":"Communications Biology","volume":null,"pages":null},"PeriodicalIF":5.2,"publicationDate":"2024-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11494180/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142459829","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 : 2024-10-21DOI: 10.1038/s42003-024-07051-2
Yuhan Liu, Wenze Xun, Tao Zhao, Menglin Huang, Longhua Sun, Guilan Wen, Xiuhua Kang, Jianbin Wang, Tianyu Han
Serine is essential to maintain maximal growth and proliferation of cancer cells by providing adequate intermediate metabolites and energy. Phosphoserine aminotransferase 1 (PSAT1) is a key enzyme in de novo serine synthesis. However, little is known about the mechanisms underlying PSAT1 degradation. We found that acetylation was the switch that regulated the degradation of PSAT1 in lung adenocarcinoma (LUAD). Deacetylation of PSAT1 on Lys51 by histone deacetylase 7 (HDAC7) enhanced the interaction between PSAT1 and the deubiquitinase ubiquitin-specific processing protease 14 (USP14), leading to the deubiquitination and stabilization of PSAT1; while acetylation of PSAT1 promoted its interaction with the E3 ligase ubiquitination factor E4B (UBE4B), leading to proteasomal degradation. Acetylation of PSAT1 on Lys51 regulated serine metabolism and tumor proliferation in LUAD. Thus, acetylation and ubiquitination cooperatively regulated the protein homeostasis of PSAT1. In conclusion, our study reveals a key regulatory mechanism for maintaining PSAT1 protein homeostasis in LUAD. Acetylation and ubiquitination cooperatively regulate the protein homeostasis of PSAT1 and contribute to serine synthesis and tumorigenesis of lung adenocarcinoma.
{"title":"Interplay between acetylation and ubiquitination controls PSAT1 protein stability in lung adenocarcinoma","authors":"Yuhan Liu, Wenze Xun, Tao Zhao, Menglin Huang, Longhua Sun, Guilan Wen, Xiuhua Kang, Jianbin Wang, Tianyu Han","doi":"10.1038/s42003-024-07051-2","DOIUrl":"10.1038/s42003-024-07051-2","url":null,"abstract":"Serine is essential to maintain maximal growth and proliferation of cancer cells by providing adequate intermediate metabolites and energy. Phosphoserine aminotransferase 1 (PSAT1) is a key enzyme in de novo serine synthesis. However, little is known about the mechanisms underlying PSAT1 degradation. We found that acetylation was the switch that regulated the degradation of PSAT1 in lung adenocarcinoma (LUAD). Deacetylation of PSAT1 on Lys51 by histone deacetylase 7 (HDAC7) enhanced the interaction between PSAT1 and the deubiquitinase ubiquitin-specific processing protease 14 (USP14), leading to the deubiquitination and stabilization of PSAT1; while acetylation of PSAT1 promoted its interaction with the E3 ligase ubiquitination factor E4B (UBE4B), leading to proteasomal degradation. Acetylation of PSAT1 on Lys51 regulated serine metabolism and tumor proliferation in LUAD. Thus, acetylation and ubiquitination cooperatively regulated the protein homeostasis of PSAT1. In conclusion, our study reveals a key regulatory mechanism for maintaining PSAT1 protein homeostasis in LUAD. Acetylation and ubiquitination cooperatively regulate the protein homeostasis of PSAT1 and contribute to serine synthesis and tumorigenesis of lung adenocarcinoma.","PeriodicalId":10552,"journal":{"name":"Communications Biology","volume":null,"pages":null},"PeriodicalIF":5.2,"publicationDate":"2024-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11494179/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142459832","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 : 2024-10-21DOI: 10.1038/s42003-024-06432-x
Jerome Johnson, Bradley B. Tolar, Bilge Tosun, Yasuo Yoshikuni, Christopher A. Francis, Soichi Wakatsuki, Hasan DeMirci
The 3-hydroxypropionate/4-hydroxybutyrate (3HP/4HB) cycle from ammonia-oxidizing Thaumarchaeota is currently considered the most energy-efficient aerobic carbon fixation pathway. The Nitrosopumilus maritimus 4-hydroxybutyryl-CoA synthetase (ADP-forming; Nmar_0206) represents one of several enzymes from this cycle that exhibit increased efficiency over crenarchaeal counterparts. This enzyme reduces energy requirements on the cell, reflecting thaumarchaeal success in adapting to low-nutrient environments. Here we show the structure of Nmar_0206 from Nitrosopumilus maritimus SCM1, which reveals a highly conserved interdomain linker loop between the CoA-binding and ATP-grasp domains. Phylogenetic analysis suggests the widespread prevalence of this loop and highlights both its underrepresentation within the PDB and structural importance within the (ATP-forming) acyl-CoA synthetase (ACD) superfamily. This linker is shown to have a possible influence on conserved interface interactions between domains, thereby influencing homodimer stability. These results provide a structural basis for the energy efficiency of this key enzyme in the modified 3HP/4HB cycle of Thaumarchaeota. Structural analysis suggests the importance of linkers in stability of oligomers within the (ADP-forming) Acyl-CoA Synthetase superfamily.
{"title":"Crystal structure of the 4-hydroxybutyryl-CoA synthetase (ADP-forming) from nitrosopumilus maritimus","authors":"Jerome Johnson, Bradley B. Tolar, Bilge Tosun, Yasuo Yoshikuni, Christopher A. Francis, Soichi Wakatsuki, Hasan DeMirci","doi":"10.1038/s42003-024-06432-x","DOIUrl":"10.1038/s42003-024-06432-x","url":null,"abstract":"The 3-hydroxypropionate/4-hydroxybutyrate (3HP/4HB) cycle from ammonia-oxidizing Thaumarchaeota is currently considered the most energy-efficient aerobic carbon fixation pathway. The Nitrosopumilus maritimus 4-hydroxybutyryl-CoA synthetase (ADP-forming; Nmar_0206) represents one of several enzymes from this cycle that exhibit increased efficiency over crenarchaeal counterparts. This enzyme reduces energy requirements on the cell, reflecting thaumarchaeal success in adapting to low-nutrient environments. Here we show the structure of Nmar_0206 from Nitrosopumilus maritimus SCM1, which reveals a highly conserved interdomain linker loop between the CoA-binding and ATP-grasp domains. Phylogenetic analysis suggests the widespread prevalence of this loop and highlights both its underrepresentation within the PDB and structural importance within the (ATP-forming) acyl-CoA synthetase (ACD) superfamily. This linker is shown to have a possible influence on conserved interface interactions between domains, thereby influencing homodimer stability. These results provide a structural basis for the energy efficiency of this key enzyme in the modified 3HP/4HB cycle of Thaumarchaeota. Structural analysis suggests the importance of linkers in stability of oligomers within the (ADP-forming) Acyl-CoA Synthetase superfamily.","PeriodicalId":10552,"journal":{"name":"Communications Biology","volume":null,"pages":null},"PeriodicalIF":5.2,"publicationDate":"2024-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11494057/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142459826","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}
Post-transcriptional regulation mediated by RNA binding proteins is crucial for male germline development. Insulin-like growth factor 2 mRNA-binding protein 1 (IGF2BP1), an RNA binding protein, is specifically expressed in human and mouse male gonads and is involved in manifold biological processes and tumorigenesis. However, the function of IGF2BP1 in mammalian spermatogenesis remains poorly understood. Herein, we generated an Igf2bp1 conditional knockout mouse model using Nanos3-Cre. Germ cell deficiency of Igf2bp1 in mice caused spermatogenic defects in an age-dependent manner, resulting in decreased numbers of undifferentiated spermatogonia and increased germ cell apoptosis. Immunoprecipitation-mass spectrometry analysis revealed that ELAV-like RNA binding protein 1, a well-recognized mRNA stabilizer, interacted with IGF2BP1. Single cell RNA-sequencing showed distinct mRNA profiles in spermatogonia from conditional knockout versus wide type mice. Further research showed that IGF2BP1 plays a vital role in the modulation of spermatogenesis by regulating Lin28a mRNA, which is essential for clonal expansion of undifferentiated spermatogonia. Thus, our results highlight the crucial effects of IGF2BP1 on spermatogonia for the long-term maintenance of spermatogenesis. A study characterizes the in vivo function of RNA-binding protein IGF2BP1 during spermatogenesis and further identifies ELAVL1 as a binding partner and Lin28a mRNA as a downstream target.
{"title":"RNA-binding protein IGF2BP1 is required for spermatogenesis in an age-dependent manner","authors":"Jiaqiang Luo, Chao Yang, Shuai Xu, Zhiyong Ji, Yuxiang Zhang, Haowei Bai, Zhiwen Deng, Jiayi Liang, Yuhua Huang, Erlei Zhi, Ruhui Tian, Peng Li, Fujun Zhao, Zhi Zhou, Zheng Li, Chencheng Yao","doi":"10.1038/s42003-024-07055-y","DOIUrl":"10.1038/s42003-024-07055-y","url":null,"abstract":"Post-transcriptional regulation mediated by RNA binding proteins is crucial for male germline development. Insulin-like growth factor 2 mRNA-binding protein 1 (IGF2BP1), an RNA binding protein, is specifically expressed in human and mouse male gonads and is involved in manifold biological processes and tumorigenesis. However, the function of IGF2BP1 in mammalian spermatogenesis remains poorly understood. Herein, we generated an Igf2bp1 conditional knockout mouse model using Nanos3-Cre. Germ cell deficiency of Igf2bp1 in mice caused spermatogenic defects in an age-dependent manner, resulting in decreased numbers of undifferentiated spermatogonia and increased germ cell apoptosis. Immunoprecipitation-mass spectrometry analysis revealed that ELAV-like RNA binding protein 1, a well-recognized mRNA stabilizer, interacted with IGF2BP1. Single cell RNA-sequencing showed distinct mRNA profiles in spermatogonia from conditional knockout versus wide type mice. Further research showed that IGF2BP1 plays a vital role in the modulation of spermatogenesis by regulating Lin28a mRNA, which is essential for clonal expansion of undifferentiated spermatogonia. Thus, our results highlight the crucial effects of IGF2BP1 on spermatogonia for the long-term maintenance of spermatogenesis. A study characterizes the in vivo function of RNA-binding protein IGF2BP1 during spermatogenesis and further identifies ELAVL1 as a binding partner and Lin28a mRNA as a downstream target.","PeriodicalId":10552,"journal":{"name":"Communications Biology","volume":null,"pages":null},"PeriodicalIF":5.2,"publicationDate":"2024-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11493986/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142459850","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 : 2024-10-20DOI: 10.1038/s42003-024-07010-x
Yuhao Tan, Lida Wang, Hongyi Zhang, Mingyao Pan, Dajiang J. Liu, Xiaowei Zhan, Bo Li
Bridging the gap between genotype and phenotype in GWAS studies is challenging. A multitude of genetic variants have been associated with immune-related diseases, including cancer, yet the interpretability of most variants remains low. Here, we investigate the quantitative components in the T cell receptor (TCR) repertoire, the frequency of clusters of TCR sequences predicted to have common antigen specificity, to interpret the genetic associations of diverse human diseases. We first developed a statistical model to predict the TCR components using variants in the TRB and HLA loci. Applying this model to over 300,000 individuals in the UK Biobank data, we identified 2309 associations between TCR abundances and various immune diseases. TCR clusters predicted to be pathogenic for autoimmune diseases were significantly enriched for predicted autoantigen-specificity. Moreover, four TCR clusters were associated with better outcomes in distinct cancers, where conventional GWAS cannot identify any significant locus. Collectively, our results highlight the integral role of adaptive immune responses in explaining the associations between genotype and phenotype. Analyzing the impact of genetic variants on T cell receptor repertoire components reveals the mechanisms behind susceptibility variants in autoimmune diseases and cancers.
{"title":"Interpretable GWAS by linking clinical phenotypes to quantifiable immune repertoire components","authors":"Yuhao Tan, Lida Wang, Hongyi Zhang, Mingyao Pan, Dajiang J. Liu, Xiaowei Zhan, Bo Li","doi":"10.1038/s42003-024-07010-x","DOIUrl":"10.1038/s42003-024-07010-x","url":null,"abstract":"Bridging the gap between genotype and phenotype in GWAS studies is challenging. A multitude of genetic variants have been associated with immune-related diseases, including cancer, yet the interpretability of most variants remains low. Here, we investigate the quantitative components in the T cell receptor (TCR) repertoire, the frequency of clusters of TCR sequences predicted to have common antigen specificity, to interpret the genetic associations of diverse human diseases. We first developed a statistical model to predict the TCR components using variants in the TRB and HLA loci. Applying this model to over 300,000 individuals in the UK Biobank data, we identified 2309 associations between TCR abundances and various immune diseases. TCR clusters predicted to be pathogenic for autoimmune diseases were significantly enriched for predicted autoantigen-specificity. Moreover, four TCR clusters were associated with better outcomes in distinct cancers, where conventional GWAS cannot identify any significant locus. Collectively, our results highlight the integral role of adaptive immune responses in explaining the associations between genotype and phenotype. Analyzing the impact of genetic variants on T cell receptor repertoire components reveals the mechanisms behind susceptibility variants in autoimmune diseases and cancers.","PeriodicalId":10552,"journal":{"name":"Communications Biology","volume":null,"pages":null},"PeriodicalIF":5.2,"publicationDate":"2024-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11491462/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142459845","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 : 2024-10-20DOI: 10.1038/s42003-024-07004-9
Matilda Roos-Mattila, Pauliina Kallio, Tamara J. Luck, Minttu Polso, Romika Kumari, Piia Mikkonen, Katja Välimäki, Minna Malmstedt, Pekka Ellonen, Teijo Pellinen, Caroline A. Heckman, Harri Mustonen, Pauli A. Puolakkainen, Kari Alitalo, Olli Kallioniemi, Tuomas Mirtti, Antti S. Rannikko, Vilja M. Pietiäinen, Hanna E. Seppänen
Clear-cell renal cell carcinoma (ccRCC) is the most common origin of pancreatic metastases (PM). Distinct genomic aberrations, favorable prognosis, and clinical observations on high angiogenesis, and succeeding tyrosine kinase inhibitor (TKI) sensitivity have been reported in PM-ccRCC. However, no functional or single-cell studies have been conducted thus far. We recruited five PM-ccRCC patients and investigated the genomic, single-cell transcriptomic, and drug sensitivity profiles of their patient-derived cells (PDCs). The PM depicted both expected and novel genomic alterations. Further, the transcriptomics differed from both primary and metastatic ccRCC, with upregulations of the PI3K/mTOR and – supporting the clinical observations – angiogenesis pathways. Data integration at pathway level showed that transcriptomics explained drug sensitivities the best. Accordingly, PM-ccRCC PDCs shared sensitivity to many PI3K/mTOR inhibitors. Altogether, we show distinct genomic and transcriptomic signatures in PM-ccRCC, highlight the superiority of transcriptomics in interpreting drug sensitivities, and encourage the use of TKIs and PI3K/mTOR inhibitors in PM-ccRCC. Functional precision medicine approach reveals genomic and transcriptomic aberrations that distinguish pancreatic metastases from other types of ccRCC metastases and suggest potential therapeutic targets at the individual level.
{"title":"Distinct molecular profiles and shared drug vulnerabilities in pancreatic metastases of renal cell carcinoma","authors":"Matilda Roos-Mattila, Pauliina Kallio, Tamara J. Luck, Minttu Polso, Romika Kumari, Piia Mikkonen, Katja Välimäki, Minna Malmstedt, Pekka Ellonen, Teijo Pellinen, Caroline A. Heckman, Harri Mustonen, Pauli A. Puolakkainen, Kari Alitalo, Olli Kallioniemi, Tuomas Mirtti, Antti S. Rannikko, Vilja M. Pietiäinen, Hanna E. Seppänen","doi":"10.1038/s42003-024-07004-9","DOIUrl":"10.1038/s42003-024-07004-9","url":null,"abstract":"Clear-cell renal cell carcinoma (ccRCC) is the most common origin of pancreatic metastases (PM). Distinct genomic aberrations, favorable prognosis, and clinical observations on high angiogenesis, and succeeding tyrosine kinase inhibitor (TKI) sensitivity have been reported in PM-ccRCC. However, no functional or single-cell studies have been conducted thus far. We recruited five PM-ccRCC patients and investigated the genomic, single-cell transcriptomic, and drug sensitivity profiles of their patient-derived cells (PDCs). The PM depicted both expected and novel genomic alterations. Further, the transcriptomics differed from both primary and metastatic ccRCC, with upregulations of the PI3K/mTOR and – supporting the clinical observations – angiogenesis pathways. Data integration at pathway level showed that transcriptomics explained drug sensitivities the best. Accordingly, PM-ccRCC PDCs shared sensitivity to many PI3K/mTOR inhibitors. Altogether, we show distinct genomic and transcriptomic signatures in PM-ccRCC, highlight the superiority of transcriptomics in interpreting drug sensitivities, and encourage the use of TKIs and PI3K/mTOR inhibitors in PM-ccRCC. Functional precision medicine approach reveals genomic and transcriptomic aberrations that distinguish pancreatic metastases from other types of ccRCC metastases and suggest potential therapeutic targets at the individual level.","PeriodicalId":10552,"journal":{"name":"Communications Biology","volume":null,"pages":null},"PeriodicalIF":5.2,"publicationDate":"2024-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11490566/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142459828","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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