Pub Date : 2025-12-01DOI: 10.1016/j.jsb.2025.108266
Alexia Gobet, Rasmus Kock Flygaard
Membranes are essential components of cells and their compartments. They are composed of asymmetric phospholipid bilayers that separate different environments ensuring the physiological functioning of cells. Most phospholipids are synthesized in the endoplasmic reticulum and transported to the target membrane via various routes. Phosphatidic acid is the starting point for all lipid synthesis pathways, following either the Kennedy pathway for phosphatidylserine, phosphatidylethanolamine and phosphatidylcholine or the CDP-DAG pathway for cardiolipin, phosphatidylglycerol and phosphatidylinositol. Many of the enzymes responsible for these synthesis pathways belong to the cytidine diphosphate alcohol phosphotransferase (CDP-AP) family for which a detailed structural and functional understanding is missing. In this review, we focus on the CDP-AP protein family which is divided in two classes, defined by different structures and mechanisms. The CDP-AP members are membrane proteins, and their mode of catalysis follows a bi-bi or ping-pong mechanism. Recent studies on different CDP-AP family members are bringing new molecular insights on these essential proteins.
Teaser
CDP-alcohol phosphotransferase proteins are highly diverged in structure while their overall function in phospholipid synthesis is conserved.
{"title":"CDP-alcohol phosphotransferases: Structures and function of highly diverse sub-classes within a protein family","authors":"Alexia Gobet, Rasmus Kock Flygaard","doi":"10.1016/j.jsb.2025.108266","DOIUrl":"10.1016/j.jsb.2025.108266","url":null,"abstract":"<div><div>Membranes are essential components of cells and their compartments. They are composed of asymmetric phospholipid bilayers that separate different environments ensuring the physiological functioning of cells. Most phospholipids are synthesized in the endoplasmic reticulum and transported to the target membrane via various routes. Phosphatidic acid is the starting point for all lipid synthesis pathways, following either the Kennedy pathway for phosphatidylserine, phosphatidylethanolamine and phosphatidylcholine or the CDP-DAG pathway for cardiolipin, phosphatidylglycerol and phosphatidylinositol. Many of the enzymes responsible for these synthesis pathways belong to the cytidine diphosphate alcohol phosphotransferase (CDP-AP) family for which a detailed structural and functional understanding is missing. In this review, we focus on the CDP-AP protein family which is divided in two classes, defined by different structures and mechanisms. The CDP-AP members are membrane proteins, and their mode of catalysis follows a bi-bi or ping-pong mechanism. Recent studies on different CDP-AP family members are bringing new molecular insights on these essential proteins.</div></div><div><h3>Teaser</h3><div>CDP-alcohol phosphotransferase proteins are highly diverged in structure while their overall function in phospholipid synthesis is conserved.</div></div>","PeriodicalId":17074,"journal":{"name":"Journal of structural biology","volume":"217 4","pages":"Article 108266"},"PeriodicalIF":2.7,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145619936","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
G-quadruplexes (G4s) are non-canonical nucleic acid structures with emerging regulatory significance in bacterial gene expression. While extensively studied in eukaryotes, the roles of G4s especially two-tetrad (2G) G4s in prokaryotic systems remain greatly underexplored. In this study, we identified and characterized multiple 2G G4-forming motifs within the hfq gene of Acinetobacter baumannii, a clinically significant and highly resilient pathogen. The RNA chaperone Hfq protein plays a central role in post-transcriptional gene regulation in this organism. Using a combination of in silico prediction and biophysical techniques (NMR, CD spectroscopy, EMSA, fluorescence titration, and ITC), we determined the folding and topology of these motifs into stable G4 structures, particularly in RNA. These G4s showed high-affinity binding with BRACO-19, a known G4 ligand, and preferential interaction with full-length Hfq protein compared to its C-terminally truncated variant, underscoring the role of the glycine-rich C-terminal domain in RNA recognition. Furthermore, BRACO-19-mediated stabilization of these G4 structures resulted in significant downregulation of hfq transcript variants, especially in the glycine-rich region. Collectively, this work uncovers a novel regulatory axis involving G-quadruplexes and Hfq protein in A. baumannii, highlighting G4-Hfq interactions as potential antimicrobial targets and offering a scaffold for the broader exploration of RNA-based regulation in this pathogenic bacterium.
g -四联体（G4s）是非典型的核酸结构，在细菌基因表达中具有重要的调控意义。虽然G4s在真核生物中得到了广泛的研究，但其在原核生物系统中的作用，特别是二四元体（2G） G4s的作用仍未得到充分的探索。在这项研究中，我们鉴定并表征了鲍曼不动杆菌（Acinetobacter baumannii） hfq基因中的多个2G g4形成基序，鲍曼不动杆菌是一种具有临床意义且具有高度弹性的病原体。RNA伴侣Hfq蛋白在这种生物体的转录后基因调控中起着核心作用。利用硅预测和生物物理技术（核磁共振、CD光谱、EMSA、荧光滴定和ITC）的结合，我们确定了这些基序的折叠和拓扑结构，形成稳定的G4结构，特别是在RNA中。这些G4s与已知的G4配体BRACO-19具有高亲和力结合，并且与全长Hfq蛋白的相互作用优于其c端截断的变体，强调了富含甘氨酸的c端结构域在RNA识别中的作用。此外，braco -19介导的这些G4结构的稳定导致hfq转录物变异的显著下调，特别是在富含甘氨酸的区域。总的来说，这项工作揭示了鲍曼不动杆菌中涉及g -四plex和Hfq蛋白的一个新的调控轴，突出了G4-Hfq相互作用作为潜在的抗菌靶点，并为更广泛地探索这种致病菌中基于rna的调控提供了一个框架。
{"title":"G-Quadruplex structures within the hfq gene regulate RNA–protein interactions in Acinetobacter baumannii","authors":"Aakriti Singh , Mansee Patel , Tarun Kumar Sharma , Amit Kumar","doi":"10.1016/j.jsb.2025.108265","DOIUrl":"10.1016/j.jsb.2025.108265","url":null,"abstract":"<div><div>G-quadruplexes (G4s) are non-canonical nucleic acid structures with emerging regulatory significance in bacterial gene expression. While extensively studied in eukaryotes, the roles of G4s especially two-tetrad (2G) G4s in prokaryotic systems remain greatly underexplored. In this study, we identified and characterized multiple 2G G4-forming motifs within the hfq gene of <em>Acinetobacter baumannii</em>, a clinically significant and highly resilient pathogen. The RNA chaperone Hfq protein plays a central role in post-transcriptional gene regulation in this organism. Using a combination of in silico prediction and biophysical techniques (NMR, CD spectroscopy, EMSA, fluorescence titration, and ITC), we determined the folding and topology of these motifs into stable G4 structures, particularly in RNA. These G4s showed high-affinity binding with BRACO-19, a known G4 ligand, and preferential interaction with full-length Hfq protein compared to its C-terminally truncated variant, underscoring the role of the glycine-rich C-terminal domain in RNA recognition. Furthermore, BRACO-19-mediated stabilization of these G4 structures resulted in significant downregulation of hfq transcript variants, especially in the glycine-rich region. Collectively, this work uncovers a novel regulatory axis involving G-quadruplexes and Hfq protein in <em>A. baumannii</em>, highlighting G4-Hfq interactions as potential antimicrobial targets and offering a scaffold for the broader exploration of RNA-based regulation in this pathogenic bacterium.</div></div>","PeriodicalId":17074,"journal":{"name":"Journal of structural biology","volume":"217 4","pages":"Article 108265"},"PeriodicalIF":2.7,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145619937","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-12-01DOI: 10.1016/j.jsb.2025.108267
Mart G.F. Last , Maartje van Klaveren , Lennert Janssen , Nickels Jensen , Isabelle Jansen , Stefan Jakobs , Lenard M. Voortman , Thomas H. Sharp
Correlating super-resolution fluorescence light microscopy with cryo-electron tomography (SRcryoCLEM) is a feasible way of targeting specific proteins of interest for high-resolution cryo-electron tomography (cryoET) imaging within cells. Among different approaches for performing super-resolution fluorescence microscopy on cryogenically preserved samples, cryo-single molecule localization microscopy (cryoSMLM) offers one of the highest imaging resolutions. Thus far, applications of cryoSMLM in SRcryoCLEM have been limited to targeting a single protein structure at a time, as the available palette of cryo-compatible reversibly photoswitchable fluorescent proteins, required for cryoSMLM imaging, is severely limited. Here, we present rsTagRFP and rsEGFP2 as a compatible pair of red and green fluorescent labels that enables dual-colour cryoSMLM, and thus dual-target SRcryoCLEM, in mammalian cells. We demonstrate the simultaneous targeting and identification of two separate structures, MAP2-decorated microtubules and vimentin intermediate filaments, with 30 nm accuracy and within the same cell.
{"title":"Dual-colour super-resolution cryoCLEM in mammalian cells using the fluorescent proteins rsTagRFP and rsEGFP2","authors":"Mart G.F. Last , Maartje van Klaveren , Lennert Janssen , Nickels Jensen , Isabelle Jansen , Stefan Jakobs , Lenard M. Voortman , Thomas H. Sharp","doi":"10.1016/j.jsb.2025.108267","DOIUrl":"10.1016/j.jsb.2025.108267","url":null,"abstract":"<div><div>Correlating super-resolution fluorescence light microscopy with cryo-electron tomography (SRcryoCLEM) is a feasible way of targeting specific proteins of interest for high-resolution cryo-electron tomography (cryoET) imaging within cells. Among different approaches for performing super-resolution fluorescence microscopy on cryogenically preserved samples, cryo-single molecule localization microscopy (cryoSMLM) offers one of the highest imaging resolutions. Thus far, applications of cryoSMLM in SRcryoCLEM have been limited to targeting a single protein structure at a time, as the available palette of cryo-compatible reversibly photoswitchable fluorescent proteins, required for cryoSMLM imaging, is severely limited. Here, we present rsTagRFP and rsEGFP2 as a compatible pair of red and green fluorescent labels that enables dual-colour cryoSMLM, and thus dual-target SRcryoCLEM, in mammalian cells. We demonstrate the simultaneous targeting and identification of two separate structures, MAP2-decorated microtubules and vimentin intermediate filaments, with 30 <!--> <!-->nm accuracy and within the same cell.</div></div>","PeriodicalId":17074,"journal":{"name":"Journal of structural biology","volume":"217 4","pages":"Article 108267"},"PeriodicalIF":2.7,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145654589","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-24DOI: 10.1016/j.jsb.2025.108264
Emma Bose , Caleb Mayes , Lance Ellis , Corrine Baker , Sofia Tambalotti , Bryan Eusse , Shengwei Xiong , Yaa Pokua Osei Sarpong , Marwan Shalaby , Lucas Barry , Frank Lewis , Johnson Joseph , Talaidh Isaacs , Derik McCarthy , Dana Katz , Jingyang Wang , Victoria Zirimu , Luis Vargas , Julian Von Hofe , Glen C Aguilar , Alisha N. Jones
The RNA binding motif 15 protein (RBM15) binds both RNA and proteins to regulate a wide repertoire of processes in the cell, including the positing of N6 methyladenosine marks on RNA, the silencing of genes on the inactive X-chromosome, and even hematopoiesis. Although its C-terminal SPOC domain has been found to facilitate protein–protein interactions, the structural mechanism that underlies how its three N-terminal RNA recognition motifs (RRMs) interact with RNA remains to be elucidated. In this crowdsourced study, we bioinformatically assessed publicly available, genome-wide RNA 2D structural probing and RNA binding protein (RBP) cross-linking and immunoprecipitation (CLIP) data to identify RNAs that bind with RBM15. Binding assays reveal that the RRMs work in concert to bind stem-loop structured RNA motifs with nanomolar binding affinity. Structural modeling and nuclear magnetic resonance (NMR) spectroscopy analysis suggest that RRMs 2 and 3 are coaxially stacked to form a heterodimer; they create a sandwich-like motif around structured RNA. Altogether, this work provides insight into the structural mechanism by which RBM15 interacts with RNAs to govern biological function.
{"title":"Bioinformatic and experimental characterization of the RBM15 RNA binding protein","authors":"Emma Bose , Caleb Mayes , Lance Ellis , Corrine Baker , Sofia Tambalotti , Bryan Eusse , Shengwei Xiong , Yaa Pokua Osei Sarpong , Marwan Shalaby , Lucas Barry , Frank Lewis , Johnson Joseph , Talaidh Isaacs , Derik McCarthy , Dana Katz , Jingyang Wang , Victoria Zirimu , Luis Vargas , Julian Von Hofe , Glen C Aguilar , Alisha N. Jones","doi":"10.1016/j.jsb.2025.108264","DOIUrl":"10.1016/j.jsb.2025.108264","url":null,"abstract":"<div><div>The RNA binding motif 15 protein (RBM15) binds both RNA and proteins to regulate a wide repertoire of processes in the cell, including the positing of N6 methyladenosine marks on RNA, the silencing of genes on the inactive X-chromosome, and even hematopoiesis. Although its C-terminal SPOC domain has been found to facilitate protein–protein interactions, the structural mechanism that underlies how its three N-terminal RNA recognition motifs (RRMs) interact with RNA remains to be elucidated. In this crowdsourced study, we bioinformatically assessed publicly available, genome-wide RNA 2D structural probing and RNA binding protein (RBP) cross-linking and immunoprecipitation (CLIP) data to identify RNAs that bind with RBM15. Binding assays reveal that the RRMs work in concert to bind stem-loop structured RNA motifs with nanomolar binding affinity. Structural modeling and nuclear magnetic resonance (NMR) spectroscopy analysis suggest that RRMs 2 and 3 are coaxially stacked to form a heterodimer; they create a sandwich-like motif around structured RNA. Altogether, this work provides insight into the structural mechanism by which RBM15 interacts with RNAs to govern biological function.</div></div>","PeriodicalId":17074,"journal":{"name":"Journal of structural biology","volume":"218 1","pages":"Article 108264"},"PeriodicalIF":2.7,"publicationDate":"2025-11-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145635050","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-11DOI: 10.1016/j.jsb.2025.108261
Bo Zheng , Yibei Yu , Maonian Wu , Shaojun Zhu , Tao Wu , Cheng Qian
Cryogenic electron tomography is an important technique that enables the three-dimensional visualisation of microscopic samples. In cryogenic electron tomography, a series of two-dimensional projection images is acquired from different tilt angles of the sample and computationally reconstructed into a tomogram. The tilt range of the specimen stage is typically limited to a certain angular range. Beyond this range, the sample may become too thick for electrons to penetrate, and mechanical components such as the support grid or holder may obstruct the beam, resulting in a loss of image quality. This angular limitation leads to missing information in the reconstructed tomograms, known as the missing wedge problem. Moreover, the use of low-dose electron imaging and other experimental constraints introduces considerable noise, thereby reducing the signal-to-noise ratio of the reconstructed tomogram. In order to solve the problems of missing wedges and low signal-to-noise ratio of tomograms, the Fillnet tomogram restoration framework was designed in this study. The training pair generation module and the FFT_Unet model are specially designed in this framework to improve the accurate acquisition of three-dimensional features in tomograms. Different loss functions are also designed to improve the model’s attention to the special features of the samples.
{"title":"Fillnet: A cryogenic electron tomography restoration framework integrating FFT_Unet architecture and weight optimisation strategy","authors":"Bo Zheng , Yibei Yu , Maonian Wu , Shaojun Zhu , Tao Wu , Cheng Qian","doi":"10.1016/j.jsb.2025.108261","DOIUrl":"10.1016/j.jsb.2025.108261","url":null,"abstract":"<div><div>Cryogenic electron tomography is an important technique that enables the three-dimensional visualisation of microscopic samples. In cryogenic electron tomography, a series of two-dimensional projection images is acquired from different tilt angles of the sample and computationally reconstructed into a tomogram. The tilt range of the specimen stage is typically limited to a certain angular range. Beyond this range, the sample may become too thick for electrons to penetrate, and mechanical components such as the support grid or holder may obstruct the beam, resulting in a loss of image quality. This angular limitation leads to missing information in the reconstructed tomograms, known as the missing wedge problem. Moreover, the use of low-dose electron imaging and other experimental constraints introduces considerable noise, thereby reducing the signal-to-noise ratio of the reconstructed tomogram. In order to solve the problems of missing wedges and low signal-to-noise ratio of tomograms, the Fillnet tomogram restoration framework was designed in this study. The training pair generation module and the FFT_Unet model are specially designed in this framework to improve the accurate acquisition of three-dimensional features in tomograms. Different loss functions are also designed to improve the model’s attention to the special features of the samples.</div></div>","PeriodicalId":17074,"journal":{"name":"Journal of structural biology","volume":"217 4","pages":"Article 108261"},"PeriodicalIF":2.7,"publicationDate":"2025-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145513224","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The structure of the tailed phage is composed of an icosahedral (or elongated icosahedral) head and a spiral symmetrical tail, which are connected by a portal located at a unique vertex of the icosahedron. A series of image-processing methods and tools have been developed to address the asymmetric structures of phages. However, the structural determination in small proteins within the head and flexible proteins of tailed phages remains a significant impediment, further hindering our deep understanding of the structural biology field. In this study, we developed a data-processing strategy for tailed phage and demonstrated its efficacy with three cryo-EM datasets, including podophage T7, siphophage T1, and myophage Mu. The proposed strategy combines conventional icosahedral reconstruction with local refinement and reconstruction and consists of four key modules: icosahedral reconstruction, selection of the unique vertex of the icosahedron, local asymmetric reconstruction and refinement, and local defocus refinement. The strategy has been successfully applied to determine the asymmetric structure of a range of tailed phages, with a particular focus on resolving the small proteins (core proteins and scaffolding proteins) within the head and flexible proteins on the tail. In addition, the local defocus refinement of our strategy approaches the approximate resolution limit of the icosahedral capsid. The proposed strategy is a viable scheme for determining the asymmetric structures of tailed phages, especially in podophages.
{"title":"A data-processing strategy of asymmetric reconstruction for tailed phages by Cryo-electron Microscopy","authors":"Wenyuan Chen , Jing Zheng , Junquan Zhou , Lingpeng Cheng , Hongrong Liu","doi":"10.1016/j.jsb.2025.108262","DOIUrl":"10.1016/j.jsb.2025.108262","url":null,"abstract":"<div><div>The structure of the tailed phage is composed of an icosahedral (or elongated icosahedral) head and a spiral symmetrical tail, which are connected by a portal located at a unique vertex of the icosahedron. A series of image-processing methods and tools have been developed to address the asymmetric structures of phages. However, the structural determination in small proteins within the head and flexible proteins of tailed phages remains a significant impediment, further hindering our deep understanding of the structural biology field. In this study, we developed a data-processing strategy for tailed phage and demonstrated its efficacy with three cryo-EM datasets, including podophage T7, siphophage T1, and myophage Mu. The proposed strategy combines conventional icosahedral reconstruction with local refinement and reconstruction and consists of four key modules: icosahedral reconstruction, selection of the unique vertex of the icosahedron, local asymmetric reconstruction and refinement, and local defocus refinement. The strategy has been successfully applied to determine the asymmetric structure of a range of tailed phages, with a particular focus on resolving the small proteins (core proteins and scaffolding proteins) within the head and flexible proteins on the tail. In addition, the local defocus refinement of our strategy approaches the approximate resolution limit of the icosahedral capsid. The proposed strategy is a viable scheme for determining the asymmetric structures of tailed phages, especially in podophages.</div></div>","PeriodicalId":17074,"journal":{"name":"Journal of structural biology","volume":"217 4","pages":"Article 108262"},"PeriodicalIF":2.7,"publicationDate":"2025-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145495681","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-11-07DOI: 10.1016/j.jsb.2025.108260
Chuanyun Luo, Mark Paetzel
Type I signal peptidase (SPase I) is an essential membrane-bound enzyme that removes amino-terminal signal peptides from secretory proteins. Owing to its critical role in bacterial viability and its periplasmic accessibility, SPase I has emerged as an attractive target for antibiotic development. Arylomycins, a class of macrocyclic lipohexapeptide natural products, inhibit SPase I by binding to its active site. Previous studies have identified a key resistance determinant—a proline residue at the base of the substrate-binding groove (Pro84 in Escherichia coli SPase I)—which reduces arylomycin affinity. Here, we present the crystal structure of the E. coli SPase I P84A mutant in complex with arylomycin A2, revealing that the introduced alanine enables an additional hydrogen bond between the enzyme backbone and the arylomycin N-terminal carbonyl, thus enhancing the affinity for arylomycins. Furthermore, a newly developed preprotein-binding assay utilizing a non-cleavable version of ProOmpA Nuclease A demonstrates that substituting SPase I Pro84 with serine or leucine disrupts substrate recognition, underscoring the delicate balance between inhibitor resistance and substrate processing. These findings reveal that residue Pro84 participates in the interaction between preprotein signal peptides and the E. coli SPase I substrate-binding groove, offering a foundation for designing next-generation arylomycin analogs with improved antibacterial potency.
I型信号肽酶（SPase I）是一种必需的膜结合酶，可从分泌蛋白中去除氨基末端信号肽。由于其在细菌活力和质周可及性中的关键作用，SPase I已成为抗生素开发的一个有吸引力的靶点。芳霉素是一类大环脂六肽的天然产物，通过结合酶I的活性位点抑制酶I。先前的研究已经确定了一个关键的抗性决定因素——在底物结合槽底部的脯氨酸残基（大肠杆菌pase I中的Pro84）——它降低了阿霉素的亲和力。在这里，我们展示了theE的晶体结构。coliSPase I P84A与arylomycin A2复合物发生突变，表明引入的丙氨酸使酶主链与arylomycin n端羰基之间形成额外的氢键，从而增强了对arylomycin的亲和力。此外，一项利用不可切割版本的ProOmpA核酸酶a的新开发的蛋白前结合试验表明，用丝氨酸或亮氨酸取代SPase I Pro84会破坏底物识别，强调抑制剂抗性和底物加工之间的微妙平衡。这些发现表明，残基Pro84参与了蛋白前信号肽与大肠杆菌SPase I底物结合槽的相互作用，为设计具有更高抑菌效力的下一代阿霉素类似物奠定了基础。
{"title":"Crystal structure of Escherichia coli type I signal peptidase P84A in complex with lipopeptide antibiotic arylomycin A2","authors":"Chuanyun Luo, Mark Paetzel","doi":"10.1016/j.jsb.2025.108260","DOIUrl":"10.1016/j.jsb.2025.108260","url":null,"abstract":"<div><div>Type I signal peptidase (SPase I) is an essential membrane-bound enzyme that removes amino-terminal signal peptides from secretory proteins. Owing to its critical role in bacterial viability and its periplasmic accessibility, SPase I has emerged as an attractive target for antibiotic development. Arylomycins, a class of macrocyclic lipohexapeptide natural products, inhibit SPase I by binding to its active site. Previous studies have identified a key resistance determinant—a proline residue at the base of the substrate-binding groove (Pro84 in<!--> <em>Escherichia coli</em> <!-->SPase I)—which reduces arylomycin affinity. Here, we present the crystal structure of the<!--> <em>E. coli</em> <!-->SPase I P84A mutant in complex with arylomycin A<sub>2</sub>, revealing that the introduced alanine enables an additional hydrogen bond between the enzyme backbone and the arylomycin N-terminal carbonyl, thus enhancing the affinity for arylomycins. Furthermore, a newly developed preprotein-binding assay utilizing a non-cleavable version of ProOmpA Nuclease A demonstrates that substituting SPase I Pro84 with serine or leucine disrupts substrate recognition, underscoring the delicate balance between inhibitor resistance and substrate processing. These findings reveal that residue Pro84 participates in the interaction between preprotein signal peptides and the <em>E. coli</em> SPase I substrate-binding groove, offering a foundation for designing next-generation arylomycin analogs with improved antibacterial potency.</div></div>","PeriodicalId":17074,"journal":{"name":"Journal of structural biology","volume":"217 4","pages":"Article 108260"},"PeriodicalIF":2.7,"publicationDate":"2025-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145482362","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-30DOI: 10.1016/j.jsb.2025.108259
Heloá Estevam , Rodrigo T. Carvalho , Leonardo T. Salgado , Carolina L. Alcantara , Jessica Aguiar-Seabra , Wanderley de Souza , Narcisa L. Cunha-e-Silva , Miria G. Pereira
The LDL endocytosis provides cholesterol supply to Trypanosoma cruzi epimastigotes. Cholesterol reaches reservosomes (lysosome like organelles) being used according to cell demand or is storage in lipid droplets. But a remnant fraction remains in reservosome lumen where solidifies. In this work we investigated the crystalline properties of these cholesterol solids. First, ultrathin sections, freeze fracture and deep etching replicas suggested collectively different spatial configurations such as needles, plaques or rounded structures. Cryo-EM images showed hemi- and membrane profiles in close association with sterol solids, possibly flanking the growth of these structures. Second, the analysis in situ of parasites by polarized light microscopy pointed to the birefringence of cholesterol. In this way, we used fractions of reservosome lipid inclusions to determine the spectral signature by FTIR, and X-ray diffraction defined the crystallinity of the lipid inclusions. Additionally, our analyses showed that cholesterol was arranged in two polymorphs of anhydrous crystal. Cholesterol crystals had triclinic configuration. Polymorph 1 presented the following unit cell parameters: a = 14.21Å, b = 33.86Å, c = 10.56Å, V = 5028.8Å while the polymorph 2: a = 27.32 Å, b = 38.24 Å, c = 10.66 Å, V = 9776.98 Å. Differences in crystalline densities were also found by our group. The polymorph 1 was more packed and denser than the second crystal analyzed. The densities were estimated in 5.11 g/cm3 and 2.63 g/cm3, respectively. Third, cholesterol crystals did not impair metacyclogenesis being rapidly dismantled if parasites were kept under nutritional starvation.
低密度脂蛋白内吞作用为克氏锥虫提供胆固醇供应。胆固醇到达储存体（溶酶体类细胞器），根据细胞的需要被使用，或者储存在脂滴中。但仍有残余部分留在储层的管腔中凝固。在这项工作中，我们研究了这些胆固醇固体的结晶性质。首先，超薄切片、冷冻断裂和深蚀刻复制品表明了不同的空间结构，如针状、斑块或圆形结构。低温电镜图像显示半和膜剖面与固醇固体密切相关，可能在这些结构的侧面生长。其次，用偏振光显微镜对寄生虫的原位分析指出了胆固醇的双折射。通过这种方法，我们利用储层脂质包裹体的组分通过FTIR确定光谱特征，并用x射线衍射确定脂质包裹体的结晶度。此外，我们的分析表明，胆固醇排列在两种多态的无水晶体。胆固醇晶体呈三斜形。变形1提出以下单位细胞参数: = 14.21 a, b = 33.86 a, c = 10.56 V = 5028.8),而变形2: = 27.32 a, b = 38.24 a, c = 10.66 V = 9776.98)。我们小组还发现了晶体密度的差异。晶型1比分析的第二种晶体更密集。密度估计分别为5.11 g/cm3和2.63 g/cm3。第三，如果寄生虫处于营养饥饿状态，胆固醇晶体不会影响元胞细胞的快速分解。
{"title":"Cholesterol crystals in reservosomes of Trypanosoma cruzi","authors":"Heloá Estevam , Rodrigo T. Carvalho , Leonardo T. Salgado , Carolina L. Alcantara , Jessica Aguiar-Seabra , Wanderley de Souza , Narcisa L. Cunha-e-Silva , Miria G. Pereira","doi":"10.1016/j.jsb.2025.108259","DOIUrl":"10.1016/j.jsb.2025.108259","url":null,"abstract":"<div><div>The LDL endocytosis provides cholesterol supply to <em>Trypanosoma cruzi</em> epimastigotes. Cholesterol reaches reservosomes (lysosome like organelles) being used according to cell demand or is storage in lipid droplets. But a remnant fraction remains in reservosome lumen where solidifies. In this work we investigated the crystalline properties of these cholesterol solids. First, ultrathin sections, freeze fracture and deep etching replicas suggested collectively different spatial configurations such as needles, plaques or rounded structures. Cryo-EM images showed hemi- and membrane profiles in close association with sterol solids, possibly flanking the growth of these structures. Second, the analysis <em>in situ</em> of parasites by polarized light microscopy pointed to the birefringence of cholesterol. In this way, we used fractions of reservosome lipid inclusions to determine the spectral signature by FTIR, and X-ray diffraction defined the crystallinity of the lipid inclusions. Additionally, our analyses showed that cholesterol was arranged in two polymorphs of anhydrous crystal. Cholesterol crystals had triclinic configuration. Polymorph 1 presented the following unit cell parameters: <em>a</em> = 14.21Å, <em>b</em> = 33.86Å, <em>c</em> = 10.56Å, <em>V</em> = 5028.8Å while the polymorph 2: <em>a</em> = 27.32 Å, <em>b</em> = 38.24 Å, <em>c</em> = 10.66 Å, <em>V</em> = 9776.98 Å. Differences in crystalline densities were also found by our group. The polymorph 1 was more packed and denser than the second crystal analyzed. The densities were estimated in 5.11 g/cm<sup>3</sup> and 2.63 g/cm<sup>3</sup>, respectively. Third, cholesterol crystals did not impair metacyclogenesis being rapidly dismantled if parasites were kept under nutritional starvation.</div></div>","PeriodicalId":17074,"journal":{"name":"Journal of structural biology","volume":"217 4","pages":"Article 108259"},"PeriodicalIF":2.7,"publicationDate":"2025-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145426923","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-10-30DOI: 10.1016/j.jsb.2025.108258
Alain Morales-Martínez , Edgar Garduño , José María Carazo , Carlos Oscar S. Sorzano , José Luis Vilas
Cryo-electron tomography (cryo-ET) is a microscopy technique that enables the acquisition of 3D images of biological samples. Research in cell biology has shown that cellular processes are carried out by groups of macromolecules that interact in a crowded environment. In such an environment, where multiple biological macromolecules coexist and intertwine, semantic segmentation becomes even more challenging but crucial to understanding the structure and function of macromolecular complexes. However, manual semantic segmentation can be time-consuming, highly subjective, and prone to variability, which poses significant obstacles in studies dealing with large volumes of data. In contrast, automated algorithms such as Convolutional Neural Networks (CNNs) can process large-scale datasets with minimal human resources, thereby reducing the subjectivity associated with manual segmentation. In this work, we propose a convolutional neural network architecture that combines the features of U-Net, DeepLab, SegNet, Gated-SCNN, LSTM (Long Short-Term Memory), RNN (Recurrent Neural Network), and GAN (Generative Adversarial Network) architectures. This hybrid architecture effectively learns to identify different types of membranes and can replicate the behavior of a skilled human annotator. This system demonstrates a strong ability to segment various cellular membranes and vesicle structures.
{"title":"Membrane and vesicle structure detection in cryo-electron tomography based on deep learning","authors":"Alain Morales-Martínez , Edgar Garduño , José María Carazo , Carlos Oscar S. Sorzano , José Luis Vilas","doi":"10.1016/j.jsb.2025.108258","DOIUrl":"10.1016/j.jsb.2025.108258","url":null,"abstract":"<div><div>Cryo-electron tomography (cryo-ET) is a microscopy technique that enables the acquisition of 3D images of biological samples. Research in cell biology has shown that cellular processes are carried out by groups of macromolecules that interact in a crowded environment. In such an environment, where multiple biological macromolecules coexist and intertwine, semantic segmentation becomes even more challenging but crucial to understanding the structure and function of macromolecular complexes. However, manual semantic segmentation can be time-consuming, highly subjective, and prone to variability, which poses significant obstacles in studies dealing with large volumes of data. In contrast, automated algorithms such as Convolutional Neural Networks (CNNs) can process large-scale datasets with minimal human resources, thereby reducing the subjectivity associated with manual segmentation. In this work, we propose a convolutional neural network architecture that combines the features of U-Net, DeepLab, SegNet, Gated-SCNN, LSTM (Long Short-Term Memory), RNN (Recurrent Neural Network), and GAN (Generative Adversarial Network) architectures. This hybrid architecture effectively learns to identify different types of membranes and can replicate the behavior of a skilled human annotator. This system demonstrates a strong ability to segment various cellular membranes and vesicle structures.</div></div>","PeriodicalId":17074,"journal":{"name":"Journal of structural biology","volume":"217 4","pages":"Article 108258"},"PeriodicalIF":2.7,"publicationDate":"2025-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145424724","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In drug development, the efficacy of an antibody depends on how the antibody interacts with the target antigen. The strength of these interactions, measured through “binding affinity”, gives an indication of how successful an antibody is in neutralizing an antigen. Due to the high computational complexity of traditional techniques for binding affinity quantification, deep learning is recently employed for the task at hand. Despite the commendable improvements in deep learning-based binding affinity prediction, such approaches are highly dependent on the quality of the antibody–antigen structures and they tend to overlook the importance of capturing the evolutionary details of proteins upon mutation. Further, most of the existing datasets for the task only include antibody–antigen pairs related to one antigen variant and, thus, are not suitable for developing comprehensive data-driven approaches. To circumvent the said complexities, we first curate the largest and most generalized (i.e., including a wide array of antigen variants) datasets for antibody–antigen binding affinity prediction, consisting of more than sequence pairs, structure pairs and the corresponding continuous binding affinity values. Subsequently, we propose a novel deep geometric neural network comprising a structure-based model, which is to account atomistic-scale structural features, and a sequence-based model, which is to attribute sequential and evolutionary information, while sharing the learned information from each model through cross-attention blocks. Further, within each parallel model, we mimic the interaction space of antibodies and antigens through a set of multi-scale hierarchical attention blocks and the final latent vectors of each model are obtained by considering antibody and antigen representative vectors and the interaction vector. The proposed framework exhibited a 10% improvement in mean absolute error compared to the state-of-the-art models while showing a strong correlation () between the predictions and target values. Additionally, we extensively discuss the model optimization strategies, weight space analysis, and interpretability in a post-hoc fashion. We release our datasets and code publicly to support the development of antibody–antigen binding affinity prediction frameworks for the benefit of science and society.
{"title":"Deep geometric framework to predict antibody–antigen binding affinity","authors":"Nuwan Bandara , Dasun Premathilaka , Sachini Chandanayake , Sahan Hettiarachchi , Vithurshan Varenthirarajah , Aravinda Munasinghe , Kaushalya Madhawa , Subodha Charles","doi":"10.1016/j.jsb.2025.108257","DOIUrl":"10.1016/j.jsb.2025.108257","url":null,"abstract":"<div><div>In drug development, the efficacy of an antibody depends on how the antibody interacts with the target antigen. The strength of these interactions, measured through “binding affinity”, gives an indication of how successful an antibody is in neutralizing an antigen. Due to the high computational complexity of traditional techniques for binding affinity quantification, deep learning is recently employed for the task at hand. Despite the commendable improvements in deep learning-based binding affinity prediction, such approaches are highly dependent on the quality of the antibody–antigen structures and they tend to overlook the importance of capturing the evolutionary details of proteins upon mutation. Further, most of the existing datasets for the task only include antibody–antigen pairs related to one antigen variant and, thus, are not suitable for developing comprehensive data-driven approaches. To circumvent the said complexities, we first curate the largest and most generalized (i.e., including a wide array of antigen variants) datasets for antibody–antigen binding affinity prediction, consisting of more than <span><math><mrow><mn>100</mn><mi>K</mi></mrow></math></span> sequence pairs, <span><math><mrow><mn>8</mn><mi>K</mi></mrow></math></span> structure pairs and the corresponding continuous binding affinity values. Subsequently, we propose a novel deep geometric neural network comprising a structure-based model, which is to account atomistic-scale structural features, and a sequence-based model, which is to attribute sequential and evolutionary information, while sharing the learned information from each model through cross-attention blocks. Further, within each parallel model, we mimic the interaction space of antibodies and antigens through a set of multi-scale hierarchical attention blocks and the final latent vectors of each model are obtained by considering antibody and antigen representative vectors and the interaction vector. The proposed framework exhibited a 10% improvement in mean absolute error compared to the state-of-the-art models while showing a strong correlation (<span><math><mrow><mo>></mo><mn>0</mn><mo>.</mo><mn>87</mn></mrow></math></span>) between the predictions and target values. Additionally, we extensively discuss the model optimization strategies, weight space analysis, and interpretability in a post-hoc fashion. We release our datasets and code publicly to support the development of antibody–antigen binding affinity prediction frameworks for the benefit of science and society.</div></div>","PeriodicalId":17074,"journal":{"name":"Journal of structural biology","volume":"217 4","pages":"Article 108257"},"PeriodicalIF":2.7,"publicationDate":"2025-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145370349","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
扫码关注我们
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号