Journal of structural biology最新文献

{"title":"Deep geometric framework to predict antibody–antigen binding affinity","authors":"Nuwan Bandara ,&nbsp;Dasun Premathilaka ,&nbsp;Sachini Chandanayake ,&nbsp;Sahan Hettiarachchi ,&nbsp;Vithurshan Varenthirarajah ,&nbsp;Aravinda Munasinghe ,&nbsp;Kaushalya Madhawa ,&nbsp;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>&gt;</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":"2025-12-01","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}

{"title":"Changes in Arabidopsis thaliana seedling cell wall assembly induced by treatment with Yariv reagent – Molecular features & visualization with immunocytochemistry and a fluorescent Yariv reagent","authors":"Agata Leszczuk ,&nbsp;Nataliia Kutyrieva-Nowak ,&nbsp;Sebastian Rueda ,&nbsp;Amit Basu","doi":"10.1016/j.jsb.2025.108254","DOIUrl":"10.1016/j.jsb.2025.108254","url":null,"abstract":"<div><div>Arabinogalactan proteins (AGPs) are cell wall-plasma membrane proteins with a high level of glycosylation. The selective and high-affinity binding between AGP and the Yariv reagent has been widely used to carry out functional studies on AGPs by disrupting AGP functions using a non-genetic tool. The current work aimed to determine the molecular features of cell walls during <em>Arabidopsis thaliana</em> seed germination under conditions where AGP functions are blocked. To achieve this, we used molecular &amp; imaging methods with molecular probes and for the first time − a new tool for AGP detection − a fluorescent analogue of the Yariv reagent. The<!--> <!-->most significant changes included a decrease in the content of AGPs, due to the addition of the Yariv reagent, and subsequent changes only in the content of AGPs upon transfer from the Yariv reagent to fresh Yariv-free medium. Additionally, as a result of the presence of the Yariv reagent, changes in the molecular masses of the analysed cell wall components were observed: lack of AGPs with small molecular mass and disappearance of homogalacturonan with high molecular mass. This work provided the first example of AGP labelling using antibodies and AzYariv-Cy5, and highlights the utility of AzYariv-Cy5 as a broad-spectrum tool for AGP studies.</div></div>","PeriodicalId":17074,"journal":{"name":"Journal of structural biology","volume":"217 4","pages":"Article 108254"},"PeriodicalIF":2.7,"publicationDate":"2025-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145318232","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}

{"title":"Membrane and vesicle structure detection in cryo-electron tomography based on deep learning","authors":"Alain Morales-Martínez ,&nbsp;Edgar Garduño ,&nbsp;José María Carazo ,&nbsp;Carlos Oscar S. Sorzano ,&nbsp;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":"2025-12-01","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}

{"title":"Dual-colour super-resolution cryoCLEM in mammalian cells using the fluorescent proteins rsTagRFP and rsEGFP2","authors":"Mart G.F. Last ,&nbsp;Maartje van Klaveren ,&nbsp;Lennert Janssen ,&nbsp;Nickels Jensen ,&nbsp;Isabelle Jansen ,&nbsp;Stefan Jakobs ,&nbsp;Lenard M. Voortman ,&nbsp;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}

{"title":"Crystal structure of Escherichia coli type I signal peptidase P84A in complex with lipopeptide antibiotic arylomycin A2","authors":"Chuanyun Luo,&nbsp;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 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 <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":"2025-12-01","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}

{"title":"Fillnet: A cryogenic electron tomography restoration framework integrating FFT_Unet architecture and weight optimisation strategy","authors":"Bo Zheng ,&nbsp;Yibei Yu ,&nbsp;Maonian Wu ,&nbsp;Shaojun Zhu ,&nbsp;Tao Wu ,&nbsp;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":"2025-12-01","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}

{"title":"Crystal structure, enzymatic and thermodynamic properties of the Thermus thermophilus phage Tt72 lytic endopeptidase with unique structural signatures of thermal adaptation","authors":"Sebastian Dorawa ,&nbsp;Katarzyna Biniek-Antosiak ,&nbsp;Magdalena Bejger ,&nbsp;Anna-Karina Kaczorowska ,&nbsp;Karol Ciuchcinski ,&nbsp;Agnieszka Godlewska ,&nbsp;Magdalena Płotka ,&nbsp;Gudmundur O. Hreggvidsson ,&nbsp;Lukasz Dziewit ,&nbsp;Tadeusz Kaczorowski ,&nbsp;Wojciech Rypniewski","doi":"10.1016/j.jsb.2025.108230","DOIUrl":"10.1016/j.jsb.2025.108230","url":null,"abstract":"<div><div>We presents the discovery and molecular characterization of a novel lytic enzyme from the extremophilic <em>Thermus thermophilus</em> MAT72 phage vB_Tt72. The protein of 346-aa (MW = 39,705) functions as phage vB_Tt72 endolysin and shows low sequence identity (&lt;37 %) to members of M23 family of peptidoglycan hydrolases, except for two uncharacterized endopeptidases of <em>T. thermophilus</em> phages: φYS40 (87 %) and φTMA (88 %). The enzyme exhibits lytic activity mainly against bacteria of the genus <em>Thermus</em> and, to a lesser extent, against other Gram-negative and Gram-positive bacteria. The protein is monomeric in solution and is highly thermostable (T_m = 98.3 °C). It retains ∼ 50 % of its lytic activity after 90 min of incubation at 99 °C. Crystallographic analysis, at 2.2 Å resolution, revealed a fold characteristic of M23 metallopeptidases, accounting for 40 % of the structure. The remaining parts of the molecule are folded in a manner that was previously undescribed. The M23 fold contains a Zn²⁺ ion coordinated by a conserved His-Asp-His triad, and two conserved His residues essential for catalysis. The active site is occupied by a phosphate or a sulfate anion, while the substrate-binding groove contains a ligand, which is a fragment of <em>E. coli</em> peptidoglycan. The common sequence-based criteria failed to identify the protein as (hyper)thermophilic. It is likely that the protein’s thermal stability is owed to peculiar features of its three-dimensional structure. Instead of trimmed surface loops, observed in many thermostable proteins, the catalytic domain contains two long loops that interlace and form an α-helical bundle with its own hydrophobic core.</div></div>","PeriodicalId":17074,"journal":{"name":"Journal of structural biology","volume":"217 3","pages":"Article 108230"},"PeriodicalIF":3.0,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144522821","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}

{"title":"1-Deoxy-D-xylulose 5-phosphate synthase: structural perspectives on an essential enzyme in isoprenoid biosynthesis","authors":"Victor O. Gawriljuk ,&nbsp;Rick Oerlemans ,&nbsp;Eswar R. Reddem ,&nbsp;Robin M. Gierse ,&nbsp;Anna K.H. Hirsch ,&nbsp;Matthew R. Groves","doi":"10.1016/j.jsb.2025.108236","DOIUrl":"10.1016/j.jsb.2025.108236","url":null,"abstract":"<div><div>Isoprenoids represent one of the largest and functionally diverse class of natural products, playing essential roles in cellular processes across all domains of life. Unlike humans, many pathogenic organisms such as bacteria and protozoa produce their isoprenoid precursors through the 2-<em>C</em>-methylerythritol phosphate (MEP) pathway. 1-deoxy-D-xylulose 5-phosphate synthase (DXPS) is the first and rate-limiting enzyme of this pathway. Despite its biological importance and potential as a drug target, structural studies on DXPS were limited due to its intrinsic flexibility and difficulties in crystallisation. Recent advances, including the development of more crystallisation-friendly constructs and the application of single-particle cryo-electron microscopy (cryo-EM), have significantly expanded our structural understanding of DXPS. This review provides a comprehensive overview of the structural insights gained over the past decades, focusing on the overall architecture of DXPS, its catalytic mechanism, and emerging relevance in structure-based drug discovery.</div></div>","PeriodicalId":17074,"journal":{"name":"Journal of structural biology","volume":"217 3","pages":"Article 108236"},"PeriodicalIF":2.7,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144817032","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}

{"title":"Preferential binding as a driving mechanism of lipid domains formation","authors":"Roman Ye. Brodskii ,&nbsp;Olga V. Vashchenko","doi":"10.1016/j.jsb.2025.108226","DOIUrl":"10.1016/j.jsb.2025.108226","url":null,"abstract":"<div><div>Lipid membranes are uniquely complex biological structures with large and still undisclosed regulatory potential in many living processes caused by versatile changes in their structure while adsorption of various guest molecules (dopants). This work is devoted to exploring spontaneous dopant-driven formation of lipid domains in a monolipid membrane observed experimentally for dopants with bimodal adsorption. The work offers the results obtained for a wide range of different cases exploiting our proposed original simulation method and numerical model. The central idea of the approach is dopant binding ‘like the surroundings’, i.e. preferential binding.</div><div>The value range of the preferential binding extent was determined, where stable domains are formed and their size distribution becomes steady. The density of domain size distribution is power-law, i.e. the domain patterns possesses self-similarity. Outside this range, only one phase dominates if the extent is too large, whereas if it is too small, great dispersion of membrane was observed, so the membrane is physically homogeneous. Various neighboring as well as different methods of calculation of dopant binding probabilities are considered. The results obtained differed quantitatively but not qualitatively. The suggested model and the domain definition are similar to those used in percolation theory. Thus, the results can be applicated to percolation problems.</div><div>Grounding on analysis of literature data on domain patterns formed in various lipid systems, we suggested that the preferential binding mechanism is in line with the mechanism of preferential neighboring which is implicitly assumed in such systems irrespective of their specific nature.</div></div>","PeriodicalId":17074,"journal":{"name":"Journal of structural biology","volume":"217 3","pages":"Article 108226"},"PeriodicalIF":3.0,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144484878","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}

{"title":"Multiscale visualization of nucleolar chromatin in yeast Saccharomyces cerevisiae","authors":"Claudie Carron ,&nbsp;Sarah Danché ,&nbsp;Valdir Gomes Neto ,&nbsp;Mickaël Lelek ,&nbsp;Nana Kadidia Maiga ,&nbsp;Isabelle Léger-Silvestre ,&nbsp;Thomas Mangeat ,&nbsp;Stéphanie Balor ,&nbsp;Carla C. Oliveira ,&nbsp;Christophe Zimmer ,&nbsp;Frédéric Beckouët ,&nbsp;Christian Rouvière ,&nbsp;Benjamin Albert ,&nbsp;Sylvain Cantaloube ,&nbsp;Olivier Gadal","doi":"10.1016/j.jsb.2025.108228","DOIUrl":"10.1016/j.jsb.2025.108228","url":null,"abstract":"<div><div>Spatial organization of chromosomes is crucial for genome stability, transcription, and proper mitotic segregation. By employing a range of imaging technologies, including random illumination microscopy and single molecule localization microscopy (SMLM), we conducted an in-depth exploration of the chromatin organization in budding yeast, with optical resolutions ranging from 250 nm to 50 nm. <em>In silico</em> models based on passively moving polymer chains and local tethering to nuclear landmarks explained much of the experimental data in yeast chromatin. We compared these models with our new imaging data of the nucleoplasmic and nucleolar chromatin. Chromatin fibers observed in the nucleoplasm showed some similarity with model prediction with a resolution of 150 nm. However, we visualized local clustering of chromatin in both the nucleoplasm and nucleolus, rather than the tube-like appearance predicted by polymer chain models. In the nucleolus, local clustering of ribosomal DNA (rDNA) chromatin is consistently observed from 150 nm resolution down to 50 nm. We also observed that actively transcribed rDNA spatially segregates from bulk nucleolar chromatin. Using correlative light and electron microscopy (CLEM), we found that local rDNA clustering is forming a specific nucleolar subdomain visible in transmission electron microscopy, the yeast equivalent of metazoan fibrillar center. We conclude that nucleolar chromatin forms a distinct sub-nucleolar compartment in yeast, supporting the model of a tripartite structural organization of the yeast nucleolus.</div></div>","PeriodicalId":17074,"journal":{"name":"Journal of structural biology","volume":"217 3","pages":"Article 108228"},"PeriodicalIF":2.7,"publicationDate":"2025-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144584210","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}