Nature Protocols最新文献

{"title":"ProBac-seq, a bacterial single-cell RNA sequencing methodology using droplet microfluidics and large oligonucleotide probe sets.","authors":"Prosenjit Samanta, Samuel F Cooke, Ryan McNulty, Sahand Hormoz, Adam Rosenthal","doi":"10.1038/s41596-024-01002-1","DOIUrl":"https://doi.org/10.1038/s41596-024-01002-1","url":null,"abstract":"<p><p>Methods that measure the transcriptomic state of thousands of individual cells have transformed our understanding of cellular heterogeneity in eukaryotic cells since their introduction in the past decade. While simple and accessible protocols and commercial products are now available for the processing of mammalian cells, these existing technologies are incompatible with use in bacterial samples for several fundamental reasons including the absence of polyadenylation on bacterial messenger RNA, the instability of bacterial transcripts and the incompatibility of bacterial cell morphology with existing methodologies. Recently, we developed ProBac sequencing (ProBac-seq), a method that overcomes these technical difficulties and provides high-quality single-cell gene expression data from thousands of bacterial cells by using messenger RNA-specific probes. Here we provide details for designing large oligonucleotide probe sets for an organism of choice, amplifying probe sets to produce sufficient quantities for repeated experiments, adding unique molecular indexes and poly-A tails to produce finalized probes, in situ probe hybridization and single-cell encapsulation and library preparation. This protocol, from the probe amplification to the library preparation, requires ~7 d to complete. ProBac-seq offers several advantages over other methods by capturing only the desired target sequences and avoiding nondesired transcripts, such as highly abundant ribosomal RNA, thus enriching for signal that better informs on cellular state. The use of multiple probes per gene can detect meaningful single-cell signals from cells expressing transcripts to a lesser degree or those grown in minimal media and other environmentally relevant conditions in which cells are less active. ProBac-seq is also compatible with other organisms that can be profiled by in situ hybridization techniques.</p>","PeriodicalId":18901,"journal":{"name":"Nature Protocols","volume":null,"pages":null},"PeriodicalIF":14.8,"publicationDate":"2024-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141071605","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Reproducible mass spectrometry data processing and compound annotation in MZmine 3","authors":"Steffen Heuckeroth,&nbsp;Tito Damiani,&nbsp;Aleksandr Smirnov,&nbsp;Olena Mokshyna,&nbsp;Corinna Brungs,&nbsp;Ansgar Korf,&nbsp;Joshua David Smith,&nbsp;Paolo Stincone,&nbsp;Nicola Dreolin,&nbsp;Louis-Félix Nothias,&nbsp;Tuulia Hyötyläinen,&nbsp;Matej Orešič,&nbsp;Uwe Karst,&nbsp;Pieter C. Dorrestein,&nbsp;Daniel Petras,&nbsp;Xiuxia Du,&nbsp;Justin J. J. van der Hooft,&nbsp;Robin Schmid,&nbsp;Tomáš Pluskal","doi":"10.1038/s41596-024-00996-y","DOIUrl":"10.1038/s41596-024-00996-y","url":null,"abstract":"Untargeted mass spectrometry (MS) experiments produce complex, multidimensional data that are practically impossible to investigate manually. For this reason, computational pipelines are needed to extract relevant information from raw spectral data and convert it into a more comprehensible format. Depending on the sample type and/or goal of the study, a variety of MS platforms can be used for such analysis. MZmine is an open-source software for the processing of raw spectral data generated by different MS platforms. Examples include liquid chromatography–MS, gas chromatography–MS and MS–imaging. These data might typically be associated with various applications including metabolomics and lipidomics. Moreover, the third version of the software, described herein, supports the processing of ion mobility spectrometry (IMS) data. The present protocol provides three distinct procedures to perform feature detection and annotation of untargeted MS data produced by different instrumental setups: liquid chromatography–(IMS–)MS, gas chromatography–MS and (IMS–)MS imaging. For training purposes, example datasets are provided together with configuration batch files (i.e., list of processing steps and parameters) to allow new users to easily replicate the described workflows. Depending on the number of data files and available computing resources, we anticipate this to take between 2 and 24 h for new MZmine users and nonexperts. Within each procedure, we provide a detailed description for all processing parameters together with instructions/recommendations for their optimization. The main generated outputs are represented by aligned feature tables and fragmentation spectra lists that can be used by other third-party tools for further downstream analysis. Untargeted mass spectrometry (MS) produces complex, multidimensional data. The MZmine open-source project enables processing of spectral data from various MS platforms, e.g., liquid chromatography–MS, gas chromatography–MS, MS–imaging and ion mobility spectrometry–MS, and is specialized for metabolomics.","PeriodicalId":18901,"journal":{"name":"Nature Protocols","volume":null,"pages":null},"PeriodicalIF":13.1,"publicationDate":"2024-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141071608","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Welcoming protocols.io","authors":"","doi":"10.1038/s41596-024-01012-z","DOIUrl":"10.1038/s41596-024-01012-z","url":null,"abstract":"Springer Nature recently acquired protocols.io, an open-access platform for developing and sharing protocols, which will replace the Protocol Exchange from June 2024.","PeriodicalId":18901,"journal":{"name":"Nature Protocols","volume":null,"pages":null},"PeriodicalIF":13.1,"publicationDate":"2024-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s41596-024-01012-z.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140958489","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}

{"title":"Author Correction: PepSeq: a fully in vitro platform for highly multiplexed serology using customizable DNA-barcoded peptide libraries.","authors":"Sierra N Henson, Evan A Elko, Piotr M Swiderski, Yong Liang, Anna L Engelbrektson, Alejandra Piña, Annalee S Boyle, Zane Fink, Salvatore J Facista, Vidal Martinez, Fatima Rahee, Annabelle Brown, Erin J Kelley, Georgia A Nelson, Isaiah Raspet, Heather L Mead, John A Altin, Jason T Ladner","doi":"10.1038/s41596-024-01010-1","DOIUrl":"https://doi.org/10.1038/s41596-024-01010-1","url":null,"abstract":"","PeriodicalId":18901,"journal":{"name":"Nature Protocols","volume":null,"pages":null},"PeriodicalIF":14.8,"publicationDate":"2024-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140958365","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A template wizard for the cocreation of machine-readable data-reporting to harmonize the evaluation of (nano)materials","authors":"Nina Jeliazkova,&nbsp;Eleonora Longhin,&nbsp;Naouale El Yamani,&nbsp;Elise Rundén-Pran,&nbsp;Elisa Moschini,&nbsp;Tommaso Serchi,&nbsp;Ivana Vinković Vrček,&nbsp;Michael J. Burgum,&nbsp;Shareen H. Doak,&nbsp;Mihaela Roxana Cimpan,&nbsp;Ivan Rios-Mondragon,&nbsp;Emil Cimpan,&nbsp;Chiara L. Battistelli,&nbsp;Cecilia Bossa,&nbsp;Rositsa Tsekovska,&nbsp;Damjana Drobne,&nbsp;Sara Novak,&nbsp;Neža Repar,&nbsp;Ammar Ammar,&nbsp;Penny Nymark,&nbsp;Veronica Di Battista,&nbsp;Anita Sosnowska,&nbsp;Tomasz Puzyn,&nbsp;Nikolay Kochev,&nbsp;Luchesar Iliev,&nbsp;Vedrin Jeliazkov,&nbsp;Katie Reilly,&nbsp;Iseult Lynch,&nbsp;Martine Bakker,&nbsp;Camila Delpivo,&nbsp;Araceli Sánchez Jiménez,&nbsp;Ana Sofia Fonseca,&nbsp;Nicolas Manier,&nbsp;María Luisa Fernandez-Cruz,&nbsp;Shahzad Rashid,&nbsp;Egon Willighagen,&nbsp;Margarita D Apostolova,&nbsp;Maria Dusinska","doi":"10.1038/s41596-024-00993-1","DOIUrl":"10.1038/s41596-024-00993-1","url":null,"abstract":"Making research data findable, accessible, interoperable and reusable (FAIR) is typically hampered by a lack of skills in technical aspects of data management by data generators and a lack of resources. We developed a Template Wizard for researchers to easily create templates suitable for consistently capturing data and metadata from their experiments. The templates are easy to use and enable the compilation of machine-readable metadata to accompany data generation and align them to existing community standards and databases, such as eNanoMapper, streamlining the adoption of the FAIR principles. These templates are citable objects and are available as online tools. The Template Wizard is designed to be user friendly and facilitates using and reusing existing templates for new projects or project extensions. The wizard is accompanied by an online template validator, which allows self-evaluation of the template (to ensure mapping to the data schema and machine readability of the captured data) and transformation by an open-source parser into machine-readable formats, compliant with the FAIR principles. The templates are based on extensive collective experience in nanosafety data collection and include over 60 harmonized data entry templates for physicochemical characterization and hazard assessment (cell viability, genotoxicity, environmental organism dose-response tests, omics), as well as exposure and release studies. The templates are generalizable across fields and have already been extended and adapted for microplastics and advanced materials research. The harmonized templates improve the reliability of interlaboratory comparisons, data reuse and meta-analyses and can facilitate the safety evaluation and regulation process for (nano) materials. Community-generated online templates for harmonized data reporting ensure that data and metadata associated with experiments are findable, accessible, interoperable, reusable and compiled for consistency in experimental design and test performance.","PeriodicalId":18901,"journal":{"name":"Nature Protocols","volume":null,"pages":null},"PeriodicalIF":13.1,"publicationDate":"2024-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140958364","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Identification and validation of microbial biomarkers from cross-cohort datasets using xMarkerFinder","authors":"Wenxing Gao,&nbsp;Weili Lin,&nbsp;Qiang Li,&nbsp;Wanning Chen,&nbsp;Wenjing Yin,&nbsp;Xinyue Zhu,&nbsp;Sheng Gao,&nbsp;Lei Liu,&nbsp;Wenjie Li,&nbsp;Dingfeng Wu,&nbsp;Guoqing Zhang,&nbsp;Ruixin Zhu,&nbsp;Na Jiao","doi":"10.1038/s41596-024-00999-9","DOIUrl":"10.1038/s41596-024-00999-9","url":null,"abstract":"Microbial signatures have emerged as promising biomarkers for disease diagnostics and prognostics, yet their variability across different studies calls for a standardized approach to biomarker research. Therefore, we introduce xMarkerFinder, a four-stage computational framework for microbial biomarker identification with comprehensive validations from cross-cohort datasets, including differential signature identification, model construction, model validation and biomarker interpretation. xMarkerFinder enables the identification and validation of reproducible biomarkers for cross-cohort studies, along with the establishment of classification models and potential microbiome-induced mechanisms. Originally developed for gut microbiome research, xMarkerFinder’s adaptable design makes it applicable to various microbial habitats and data types. Distinct from existing biomarker research tools that typically concentrate on a singular aspect, xMarkerFinder uniquely incorporates a sophisticated feature selection process, specifically designed to address the heterogeneity between different cohorts, extensive internal and external validations, and detailed specificity assessments. Execution time varies depending on the sample size, selected algorithm and computational resource. Accessible via GitHub ( https://github.com/tjcadd2020/xMarkerFinder ), xMarkerFinder supports users with diverse expertise levels through different execution options, including step-to-step scripts with detailed tutorials and frequently asked questions, a single-command execution script, a ready-to-use Docker image and a user-friendly web server ( https://www.biosino.org/xmarkerfinder ). This protocol is for using xMarkerFinder, a four-stage computational framework, to enable the identification and validation of reproducible microbial biomarkers from cross-cohort studies, and establish potential microbiome-induced mechanisms.","PeriodicalId":18901,"journal":{"name":"Nature Protocols","volume":null,"pages":null},"PeriodicalIF":13.1,"publicationDate":"2024-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140922695","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"High-throughput identification of gut microbiome-dependent metabolites","authors":"Shuo Han,&nbsp;Emma R. Guiberson,&nbsp;Yuxin Li,&nbsp;Justin L. Sonnenburg","doi":"10.1038/s41596-024-00980-6","DOIUrl":"10.1038/s41596-024-00980-6","url":null,"abstract":"A significant hurdle that has limited progress in microbiome science has been identifying and studying the diverse set of metabolites produced by gut microbes. Gut microbial metabolism produces thousands of difficult-to-identify metabolites, which present a challenge to study their roles in host biology. In recent years, mass spectrometry-based metabolomics has become one of the core technologies for identifying small metabolites. However, metabolomics expertise, ranging from sample preparation to instrument use and data analysis, is often lacking in academic labs. Most targeted metabolomics methods provide high levels of sensitivity and quantification, while they are limited to a panel of predefined molecules that may not be informative to microbiome-focused studies. Here we have developed a gut microbe-focused and wide-spectrum metabolomic protocol using liquid chromatography–mass spectrometry and bioinformatic analysis. This protocol enables users to carry out experiments from sample collection to data analysis, only requiring access to a liquid chromatography–mass spectrometry instrument, which is often available at local core facilities. By applying this protocol to samples containing human gut microbial metabolites, spanning from culture supernatant to human biospecimens, our approach enables high-confidence identification of &gt;800 metabolites that can serve as candidate mediators of microbe–host interactions. We expect this protocol will lower the barrier to tracking gut bacterial metabolism in vitro and in mammalian hosts, propelling hypothesis-driven mechanistic studies and accelerating our understanding of the gut microbiome at the chemical level. This protocol presents a metabolomics method tailored for detecting and measuring gut-microbe-derived metabolites using a broad reference library of metabolite standards.","PeriodicalId":18901,"journal":{"name":"Nature Protocols","volume":null,"pages":null},"PeriodicalIF":13.1,"publicationDate":"2024-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140916405","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"TAC–TIC, a high-throughput genetics method to identify triggers or blockers of bacterial toxin–antitoxin systems","authors":"Jacob Bobonis,&nbsp;Alessio Ling Jie Yang,&nbsp;Carlos Geert Pieter Voogdt,&nbsp;Athanasios Typas","doi":"10.1038/s41596-024-00988-y","DOIUrl":"10.1038/s41596-024-00988-y","url":null,"abstract":"Toxin–antitoxin systems (TAs) are abundant in bacterial chromosomes and can arrest growth under stress, but usually remain inactive. TAs have been increasingly implicated in halting the growth of infected bacteria from bacteriophages or foreign genetic elements1,2 to protect the population (abortive infection, Abi). The vast diversity and abundance of TAs and other Abi systems3 suggest they play an important immunity role, yet what allows them to sense attack remains largely enigmatic. Here, we describe a method called toxin activation–inhibition conjugation (TAC–TIC), which we used to identify gene products that trigger or block the toxicity of phage-defending tripartite retron-TAs4. TAC–TIC employs high-density arrayed mobilizable gene-overexpression libraries, which are transferred into cells carrying the full TA system or only its toxic component, on inducible vectors. The double-plasmid transconjugants are then pinned on inducer-containing agar plates and their colony fitness is quantified to identify gene products that trigger a TA to inhibit growth (TAC), or that block it from acting (TIC). TAC–TIC is optimized for the Singer ROTOR pinning robot, but can also be used with other robots or manual pinners, and allows screening tens of thousands of genes against any TA or Abi (with toxicity) within a week. Finally, we present a dual conjugation donor/cloning strain (Escherichia coli DATC), which accelerates the construction of TAC–TIC gene-donor libraries from phages, enabling the use of TAC–TIC for identifying TA triggers and antidefense mechanisms in phage genomes. This protocol describes toxin activation–inhibition conjugation (TAC–TIC), a reverse genetics screening approach that can be used to identify triggers or blockers of bacterial toxin–antitoxin or phage immunity systems.","PeriodicalId":18901,"journal":{"name":"Nature Protocols","volume":null,"pages":null},"PeriodicalIF":13.1,"publicationDate":"2024-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140897947","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Generation of ‘semi-guided’ cortical organoids with complex neural oscillations","authors":"Michael Q. Fitzgerald,&nbsp;Tiffany Chu,&nbsp;Francesca Puppo,&nbsp;Rebeca Blanch,&nbsp;Miguel Chillón,&nbsp;Shankar Subramaniam,&nbsp;Alysson R. Muotri","doi":"10.1038/s41596-024-00994-0","DOIUrl":"10.1038/s41596-024-00994-0","url":null,"abstract":"Temporal development of neural electrophysiology follows genetic programming, similar to cellular maturation and organization during development. The emergent properties of this electrophysiological development, namely neural oscillations, can be used to characterize brain development. Recently, we utilized the innate programming encoded in the human genome to generate functionally mature cortical organoids. In brief, stem cells are suspended in culture via continuous shaking and naturally aggregate into embryoid bodies before being exposed to media formulations for neural induction, differentiation and maturation. The specific culture format, media composition and duration of exposure to these media distinguish organoid protocols and determine whether a protocol is guided or unguided toward specific neural fate. The ‘semi-guided’ protocol presented here has shorter induction and differentiation steps with less-specific patterning molecules than most guided protocols but maintains the use of neurotrophic factors such as brain-derived growth factor and neurotrophin-3, unlike unguided approaches. This approach yields the cell type diversity of unguided approaches while maintaining reproducibility for disease modeling. Importantly, we characterized the electrophysiology of these organoids and found that they recapitulate the maturation of neural oscillations observed in the developing human brain, a feature not shown with other approaches. This protocol represents the potential first steps toward bridging molecular and cellular biology to human cognition, and it has already been used to discover underlying features of human brain development, evolution and neurological conditions. Experienced cell culture technicians can expect the protocol to take 1 month, with extended maturation, electrophysiology recording, and adeno-associated virus transduction procedure options. This protocol details the generation of cortical organoids with complex neural oscillations through a ‘semi-guided’ protocol, and their functional characterization using microelectrode array measurements, calcium imaging and adeno-associated virus transduction.","PeriodicalId":18901,"journal":{"name":"Nature Protocols","volume":null,"pages":null},"PeriodicalIF":13.1,"publicationDate":"2024-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140835576","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Build and operation of a custom 3D, multicolor, single-molecule localization microscope","authors":"Rory M. Power,&nbsp;Aline Tschanz,&nbsp;Timo Zimmermann,&nbsp;Jonas Ries","doi":"10.1038/s41596-024-00989-x","DOIUrl":"10.1038/s41596-024-00989-x","url":null,"abstract":"Single-molecule localization microscopy (SMLM) enables imaging scientists to visualize biological structures with unprecedented resolution. Particularly powerful implementations of SMLM are capable of three-dimensional, multicolor and high-throughput imaging and can yield key biological insights. However, widespread access to these technologies is limited, primarily by the cost of commercial options and complexity of de novo development of custom systems. Here we provide a comprehensive guide for interested researchers who wish to establish a high-end, custom-built SMLM setup in their laboratories. We detail the initial configuration and subsequent assembly of the SMLM, including the instructions for the alignment of all the optical pathways, the software and hardware integration, and the operation of the instrument. We describe the validation steps, including the preparation and imaging of test and biological samples with structures of well-defined geometries, and assist the user in troubleshooting and benchmarking the system’s performance. Additionally, we provide a walkthrough of the reconstruction of a super-resolved dataset from acquired raw images using the Super-resolution Microscopy Analysis Platform. Depending on the instrument configuration, the cost of the components is in the range US$95,000–180,000, similar to other open-source advanced SMLMs, and substantially lower than the cost of a commercial instrument. A builder with some experience of optical systems is expected to require 4–8 months from the start of the system construction to attain high-quality three-dimensional and multicolor biological images. The buildup and operation of a custom single-molecule localization microscope with state-of-the-art performance and advanced features bridges the gap between entry-level open-source projects and costly commercial systems.","PeriodicalId":18901,"journal":{"name":"Nature Protocols","volume":null,"pages":null},"PeriodicalIF":13.1,"publicationDate":"2024-05-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140835632","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}