Cell Reports Methods最新文献_第2页

Size-reduced DREADD derivatives for AAV-assisted multimodal chemogenetic control of neuronal activity and behavior. 减小尺寸的 DREADD 衍生物，用于 AAV 辅助的神经元活动和行为的多模式化学遗传控制。

IF 4.3

Cell Reports Methods Pub Date : 2024-10-21 DOI: 10.1016/j.crmeth.2024.100881

Takahito Miyake, Kaho Tanaka, Yutsuki Inoue, Yuji Nagai, Reo Nishimura, Takehito Seta, Shumpei Nakagawa, Ken-Ichi Inoue, Emi Hasegawa, Takafumi Minamimoto, Masao Doi

{"title":"Size-reduced DREADD derivatives for AAV-assisted multimodal chemogenetic control of neuronal activity and behavior.","authors":"Takahito Miyake, Kaho Tanaka, Yutsuki Inoue, Yuji Nagai, Reo Nishimura, Takehito Seta, Shumpei Nakagawa, Ken-Ichi Inoue, Emi Hasegawa, Takafumi Minamimoto, Masao Doi","doi":"10.1016/j.crmeth.2024.100881","DOIUrl":"https://doi.org/10.1016/j.crmeth.2024.100881","url":null,"abstract":"Designer receptors exclusively activated by designer drugs (DREADDs) are engineered G-protein-coupled receptors that afford reversible manipulation of neuronal activity in vivo. Here, we introduce size-reduced DREADD derivatives miniDq and miniDi, which inherit the basic receptor properties from the Gq-coupled excitatory receptor hM3Dq and the Gi-coupled inhibitory receptor hM4Di, respectively, while being approximately 30% smaller in size. Taking advantage of the compact size of the receptors, we generated an adeno-associated virus (AAV) vector carrying both miniDq and the other DREADD family receptor (κ-opioid receptor-based inhibitory DREADD [KORD]) within the maximum AAV capacity (4.7 kb), allowing us to modulate neuronal activity and animal behavior in both excitatory and inhibitory directions using a single viral vector. We confirmed that expressing miniDq, but not miniDi, allowed activation of striatum activity in the cynomolgus monkey (Macaca fascicularis). The compact DREADDs may thus widen the opportunity for multiplexed interrogation and/or intervention in neuronal regulation in mice and non-human primates.","PeriodicalId":29773,"journal":{"name":"Cell Reports Methods","volume":null,"pages":null},"PeriodicalIF":4.3,"publicationDate":"2024-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142509373","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Adult zebrafish can learn Morris water maze-like tasks in a two-dimensional virtual reality system. 成年斑马鱼可以在二维虚拟现实系统中学习类似莫里斯水迷宫的任务。

IF 4.3

Cell Reports Methods Pub Date : 2024-10-21 Epub Date: 2024-09-23 DOI: 10.1016/j.crmeth.2024.100863

Tanvir Islam, Makio Torigoe, Yuki Tanimoto, Hitoshi Okamoto

引用次数: 0

CENCAT enables immunometabolic profiling by measuring protein synthesis via bioorthogonal noncanonical amino acid tagging. CENCAT 可通过生物正交非对称氨基酸标记测量蛋白质合成，从而进行免疫代谢分析。

IF 4.3

Cell Reports Methods Pub Date : 2024-10-21 DOI: 10.1016/j.crmeth.2024.100883

Frank Vrieling, Hendrik J P van der Zande, Britta Naus, Lisa Smeehuijzen, Julia I P van Heck, Bob J Ignacio, Kimberly M Bonger, Jan Van den Bossche, Sander Kersten, Rinke Stienstra

{"title":"CENCAT enables immunometabolic profiling by measuring protein synthesis via bioorthogonal noncanonical amino acid tagging.","authors":"Frank Vrieling, Hendrik J P van der Zande, Britta Naus, Lisa Smeehuijzen, Julia I P van Heck, Bob J Ignacio, Kimberly M Bonger, Jan Van den Bossche, Sander Kersten, Rinke Stienstra","doi":"10.1016/j.crmeth.2024.100883","DOIUrl":"https://doi.org/10.1016/j.crmeth.2024.100883","url":null,"abstract":"Cellular energy metabolism significantly contributes to immune cell function. To further advance immunometabolic research, novel methods to study the metabolism of immune cells in complex samples are required. Here, we introduce CENCAT (cellular energetics through noncanonical amino acid tagging). This technique utilizes click labeling of alkyne-bearing noncanonical amino acids to measure protein synthesis inhibition as a proxy for metabolic activity. CENCAT successfully reproduced known metabolic signatures of lipopolysaccharide (LPS)/interferon (IFN)γ and interleukin (IL)-4 activation in human primary macrophages. Application of CENCAT in peripheral blood mononuclear cells revealed diverse metabolic rewiring upon stimulation with different activators. Finally, CENCAT was used to analyze the cellular metabolism of murine tissue-resident immune cells from various organs. Tissue-specific clustering was observed based on metabolic profiles, likely driven by microenvironmental priming. In conclusion, CENCAT offers valuable insights into immune cell metabolic responses, presenting a powerful platform for studying cellular metabolism in complex samples and tissues in both humans and mice.","PeriodicalId":29773,"journal":{"name":"Cell Reports Methods","volume":null,"pages":null},"PeriodicalIF":4.3,"publicationDate":"2024-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142509371","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A deep learning framework combining molecular image and protein structural representations identifies candidate drugs for pain. 结合分子图像和蛋白质结构表征的深度学习框架可识别治疗疼痛的候选药物。

IF 4.3

Cell Reports Methods Pub Date : 2024-10-21 Epub Date: 2024-09-27 DOI: 10.1016/j.crmeth.2024.100865

Yuxin Yang, Yunguang Qiu, Jianying Hu, Michal Rosen-Zvi, Qiang Guan, Feixiong Cheng

{"title":"A deep learning framework combining molecular image and protein structural representations identifies candidate drugs for pain.","authors":"Yuxin Yang, Yunguang Qiu, Jianying Hu, Michal Rosen-Zvi, Qiang Guan, Feixiong Cheng","doi":"10.1016/j.crmeth.2024.100865","DOIUrl":"10.1016/j.crmeth.2024.100865","url":null,"abstract":"Artificial intelligence (AI) and deep learning technologies hold promise for identifying effective drugs for human diseases, including pain. Here, we present an interpretable deep-learning-based ligand image- and receptor's three-dimensional (3D)-structure-aware framework to predict compound-protein interactions (LISA-CPI). LISA-CPI integrates an unsupervised deep-learning-based molecular image representation (ImageMol) of ligands and an advanced AlphaFold2-based algorithm (Evoformer). We demonstrated that LISA-CPI achieved ∼20% improvement in the average mean absolute error (MAE) compared to state-of-the-art models on experimental CPIs connecting 104,969 ligands and 33 G-protein-coupled receptors (GPCRs). Using LISA-CPI, we prioritized potential repurposable drugs (e.g., methylergometrine) and identified candidate gut-microbiota-derived metabolites (e.g., citicoline) for potential treatment of pain via specifically targeting human GPCRs. In summary, we presented that the integration of molecular image and protein 3D structural representations using a deep learning framework offers a powerful computational drug discovery tool for treating pain and other complex diseases if broadly applied.","PeriodicalId":29773,"journal":{"name":"Cell Reports Methods","volume":null,"pages":null},"PeriodicalIF":4.3,"publicationDate":"2024-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142355423","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

iSubGen generates integrative disease subtypes by pairwise similarity assessment. iSubGen 通过成对相似性评估生成综合疾病亚型。

IF 4.3

Cell Reports Methods Pub Date : 2024-10-18 DOI: 10.1016/j.crmeth.2024.100884

Natalie S Fox, Mao Tian, Alexander L Markowitz, Syed Haider, Constance H Li, Paul C Boutros

{"title":"iSubGen generates integrative disease subtypes by pairwise similarity assessment.","authors":"Natalie S Fox, Mao Tian, Alexander L Markowitz, Syed Haider, Constance H Li, Paul C Boutros","doi":"10.1016/j.crmeth.2024.100884","DOIUrl":"https://doi.org/10.1016/j.crmeth.2024.100884","url":null,"abstract":"There are myriad types of biomedical data-molecular, clinical images, and others. When a group of patients with the same underlying disease exhibits similarities across multiple types of data, this is called a subtype. Existing subtyping approaches struggle to handle diverse data types with missing information. To improve subtype discovery, we exploited changes in the correlation-structure between different data types to create iSubGen, an algorithm for integrative subtype generation. iSubGen can accommodate any feature that can be compared with a similarity metric to create subtypes versatilely. It can combine arbitrary data types for subtype discovery, such as merging genetic, transcriptomic, proteomic, and pathway data. iSubGen recapitulates known subtypes across multiple cancers even with substantial missing data and identifies subtypes with distinct clinical behaviors. It performs equally with or superior to other subtyping methods, offering greater stability and robustness to missing data and flexibility to new data types. It is available at https://cran.r-project.org/web/packages/iSubGen.","PeriodicalId":29773,"journal":{"name":"Cell Reports Methods","volume":null,"pages":null},"PeriodicalIF":4.3,"publicationDate":"2024-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142509369","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A behavioral analysis system MCFBM enables objective inference of songbirds' attention during social interactions. 行为分析系统 MCFBM 可以客观推断鸣禽在社会互动过程中的注意力。

IF 4.3

Cell Reports Methods Pub Date : 2024-09-16 Epub Date: 2024-09-03 DOI: 10.1016/j.crmeth.2024.100844

Mizuki Fujibayashi, Kentaro Abe

引用次数: 0

3D model for human glia conversion into subtype-specific neurons, including dopamine neurons. 人类胶质细胞转化为亚型特异性神经元（包括多巴胺神经元）的三维模型。

IF 4.3

Cell Reports Methods Pub Date : 2024-09-16 Epub Date: 2024-09-04 DOI: 10.1016/j.crmeth.2024.100845

Jessica Giacomoni, Andreas Bruzelius, Mette Habekost, Janko Kajtez, Daniella Rylander Ottosson, Alessandro Fiorenzano, Petter Storm, Malin Parmar

{"title":"3D model for human glia conversion into subtype-specific neurons, including dopamine neurons.","authors":"Jessica Giacomoni, Andreas Bruzelius, Mette Habekost, Janko Kajtez, Daniella Rylander Ottosson, Alessandro Fiorenzano, Petter Storm, Malin Parmar","doi":"10.1016/j.crmeth.2024.100845","DOIUrl":"10.1016/j.crmeth.2024.100845","url":null,"abstract":"Two-dimensional neuronal cultures have a limited ability to recapitulate the in vivo environment of the brain. Here, we introduce a three-dimensional in vitro model for human glia-to-neuron conversion, surpassing the spatial and temporal constrains of two-dimensional cultures. Focused on direct conversion to induced dopamine neurons (iDANs) relevant to Parkinson disease, the model generates functionally mature iDANs in 2 weeks and allows long-term survival. As proof of concept, we use single-nucleus RNA sequencing and molecular lineage tracing during iDAN generation and find that all glial subtypes generate neurons and that conversion relies on the coordinated expression of three neural conversion factors. We also show the formation of mature and functional iDANs over time. The model facilitates molecular investigations of the conversion process to enhance understanding of conversion outcomes and offers a system for in vitro reprogramming studies aimed at advancing alternative therapeutic strategies in the diseased brain.","PeriodicalId":29773,"journal":{"name":"Cell Reports Methods","volume":null,"pages":null},"PeriodicalIF":4.3,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11440053/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142141271","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A broadly applicable method for quantifying cardiomyocyte cell division identifies proliferative events following myocardial infarction. 一种广泛适用的量化心肌细胞分裂的方法可识别心肌梗死后的增殖事件。

IF 4.3

Cell Reports Methods Pub Date : 2024-09-16 Epub Date: 2024-09-09 DOI: 10.1016/j.crmeth.2024.100860

Samantha K Swift, Alexandra L Purdy, Tyler Buddell, Jerrell J Lovett, Smrithi V Chanjeevaram, Anooj Arkatkar, Caitlin C O'Meara, Michaela Patterson

引用次数: 0

Microsynteny is a powerful front for microbial strain tracking. 微合成技术是微生物菌种追踪的强大前沿。

IF 4.3

Cell Reports Methods Pub Date : 2024-09-16 DOI: 10.1016/j.crmeth.2024.100862

Peiwen Cai, Tal Korem

引用次数: 0

A quadri-fluorescence SARS-CoV-2 pseudovirus system for efficient antigenic characterization of multiple circulating variants. 用于对多种循环变种进行高效抗原表征的四荧光 SARS-CoV-2 伪病毒系统。

IF 4.3

Cell Reports Methods Pub Date : 2024-09-16 Epub Date: 2024-09-06 DOI: 10.1016/j.crmeth.2024.100856

Jijing Chen, Zehong Huang, Jin Xiao, Shuangling Du, Qingfang Bu, Huilin Guo, Jianghui Ye, Shiqi Chen, Jiahua Gao, Zonglin Li, Miaolin Lan, Shaojuan Wang, Tianying Zhang, Jiming Zhang, Yangtao Wu, Yali Zhang, Ningshao Xia, Quan Yuan, Tong Cheng

{"title":"A quadri-fluorescence SARS-CoV-2 pseudovirus system for efficient antigenic characterization of multiple circulating variants.","authors":"Jijing Chen, Zehong Huang, Jin Xiao, Shuangling Du, Qingfang Bu, Huilin Guo, Jianghui Ye, Shiqi Chen, Jiahua Gao, Zonglin Li, Miaolin Lan, Shaojuan Wang, Tianying Zhang, Jiming Zhang, Yangtao Wu, Yali Zhang, Ningshao Xia, Quan Yuan, Tong Cheng","doi":"10.1016/j.crmeth.2024.100856","DOIUrl":"10.1016/j.crmeth.2024.100856","url":null,"abstract":"The ongoing co-circulation of multiple severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) strains necessitates advanced methods such as high-throughput multiplex pseudovirus systems for evaluating immune responses to different variants, crucial for developing updated vaccines and neutralizing antibodies (nAbs). We have developed a quadri-fluorescence (qFluo) pseudovirus platform by four fluorescent reporters with different spectra, allowing simultaneous measurement of the nAbs against four variants in a single test. qFluo shows high concordance with the classical single-reporter assay when testing monoclonal antibodies and human plasma. Utilizing qFluo, we assessed the immunogenicities of the spike of BA.5, BQ.1.1, XBB.1.5, and CH.1.1 in hamsters. An analysis of cross-neutralization against 51 variants demonstrated superior protective immunity from XBB.1.5, especially against prevalent strains such as \"FLip\" and JN.1, compared to BA.5. Our finding partially fills the knowledge gap concerning the immunogenic efficacy of the XBB.1.5 vaccine against current dominant variants, being instrumental in vaccine-strain decisions and insight into the evolutionary path of SARS-CoV-2.","PeriodicalId":29773,"journal":{"name":"Cell Reports Methods","volume":null,"pages":null},"PeriodicalIF":4.3,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11440059/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142146458","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0