{"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":"<p><p>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.</p>","PeriodicalId":29773,"journal":{"name":"Cell Reports Methods","volume":" ","pages":"100865"},"PeriodicalIF":4.3,"publicationDate":"2024-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11573792/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142355423","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}
Cell Reports MethodsPub Date : 2024-09-16Epub Date: 2024-09-03DOI: 10.1016/j.crmeth.2024.100844
Mizuki Fujibayashi, Kentaro Abe
{"title":"A behavioral analysis system MCFBM enables objective inference of songbirds' attention during social interactions.","authors":"Mizuki Fujibayashi, Kentaro Abe","doi":"10.1016/j.crmeth.2024.100844","DOIUrl":"10.1016/j.crmeth.2024.100844","url":null,"abstract":"<p><p>Understanding animal behavior is crucial in behavioral neuroscience, aiming to unravel the mechanisms driving these behaviors. A significant milestone in this field is the analysis of behavioral reactions during social interactions. Despite their importance in social learning, the behavioral aspects of these interaction are not well understood in detail due to the lack of appropriate tools. We introduce a high-precision, marker-based motion-capture system for analyzing behavior in songbirds, accurately tracking body location and head direction in multiple freely moving finches during social interaction. Focusing on zebra finches, our analysis revealed variations in eye use based on individuals presented. We also observed behavioral changes during virtual and live presentations and a conditioned-learning paradigm. Additionally, the system effectively analyzed social interactions among mice. This system provides an efficient tool for advanced behavioral analysis in small animals and offers an objective method to infer their focus of attention.</p>","PeriodicalId":29773,"journal":{"name":"Cell Reports Methods","volume":" ","pages":"100844"},"PeriodicalIF":4.3,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11440064/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142134011","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}
Cell Reports MethodsPub Date : 2024-09-16Epub Date: 2024-09-04DOI: 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":"<p><p>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.</p>","PeriodicalId":29773,"journal":{"name":"Cell Reports Methods","volume":" ","pages":"100845"},"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}
{"title":"Microsynteny is a powerful front for microbial strain tracking.","authors":"Peiwen Cai, Tal Korem","doi":"10.1016/j.crmeth.2024.100862","DOIUrl":"10.1016/j.crmeth.2024.100862","url":null,"abstract":"<p><p>Genomic diversity within species can be driven by both point mutations and larger structural variations, but so far, strain-tracking approaches have focused mostly on the former. In a recent issue of Nature Biotechnology, Ley and colleagues<sup>1</sup> introduce SynTracker, a tool designed for scalable strain tracking with microsynteny in low-coverage metagenomic settings.</p>","PeriodicalId":29773,"journal":{"name":"Cell Reports Methods","volume":"4 9","pages":"100862"},"PeriodicalIF":4.3,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11440041/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142297023","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}
Cell Reports MethodsPub Date : 2024-09-16Epub Date: 2024-09-09DOI: 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
{"title":"A broadly applicable method for quantifying cardiomyocyte cell division identifies proliferative events following myocardial infarction.","authors":"Samantha K Swift, Alexandra L Purdy, Tyler Buddell, Jerrell J Lovett, Smrithi V Chanjeevaram, Anooj Arkatkar, Caitlin C O'Meara, Michaela Patterson","doi":"10.1016/j.crmeth.2024.100860","DOIUrl":"10.1016/j.crmeth.2024.100860","url":null,"abstract":"<p><p>Cardiomyocyte proliferation is a challenging metric to assess. Current methodologies have limitations in detecting the generation of new cardiomyocytes and technical challenges that reduce widespread applicability. Here, we describe an improved cell suspension and imaging-based methodology that can be broadly employed to assess cardiomyocyte cell division in standard laboratories across a multitude of model organisms and experimental conditions. We highlight additional metrics that can be gathered from the same cell preparations to enable additional relevant analyses to be performed. We incorporate additional antibody stains to address potential technical concerns of miscounting. Finally, we employ this methodology with a dual-thymidine analog-labeling approach to a post-infarction murine model, which allowed us to robustly identify unique cycling events, such as cardiomyocytes undergoing multiple rounds of cell division.</p>","PeriodicalId":29773,"journal":{"name":"Cell Reports Methods","volume":"4 9","pages":"100860"},"PeriodicalIF":4.3,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11440799/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142297020","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}
Cell Reports MethodsPub Date : 2024-09-16Epub Date: 2024-09-10DOI: 10.1016/j.crmeth.2024.100857
An-Ping Chen, Peng Gao, Liang Lin, Preeti Ashok, Hongzhi He, Chao Ma, David Li Zou, Vincent Allain, Alex Boyne, Alexandre Juillerat, Philippe Duchateau, Armin Rath, Daniel Teper, Antonio Arulanandam, Hao-Ming Chang, Justin Eyquem, Wei Li
{"title":"An improved approach to generate IL-15<sup>+/+</sup>/TGFβR2<sup>-/-</sup> iPSC-derived natural killer cells using TALEN.","authors":"An-Ping Chen, Peng Gao, Liang Lin, Preeti Ashok, Hongzhi He, Chao Ma, David Li Zou, Vincent Allain, Alex Boyne, Alexandre Juillerat, Philippe Duchateau, Armin Rath, Daniel Teper, Antonio Arulanandam, Hao-Ming Chang, Justin Eyquem, Wei Li","doi":"10.1016/j.crmeth.2024.100857","DOIUrl":"10.1016/j.crmeth.2024.100857","url":null,"abstract":"<p><p>We present a TALEN-based workflow to generate and maintain dual-edited (IL-15<sup>+/+</sup>/TGFβR2<sup>-/-</sup>) iPSCs that produce enhanced iPSC-derived natural killer (iNK) cells for cancer immunotherapy. It involves using a cell lineage promoter for knocking in (KI) gene(s) to minimize the potential effects of expression of any exogenous genes on iPSCs. As a proof-of-principle, we KI IL-15 under the endogenous B2M promoter and show that it results in high expression of the sIL-15 in iNK cells but minimal expression in iPSCs. Furthermore, given that it is known that knockout (KO) of TGFβR2 in immune cells can enhance resistance to the suppressive TGF-β signaling in the tumor microenvironment, we develop a customized medium containing Nodal that can maintain the pluripotency of iPSCs with TGFβR2 KO, enabling banking of these iPSC clones. Ultimately, we show that the dual-edited IL-15<sup>+/+</sup>/TGFβR2<sup>-/-</sup> iPSCs can be efficiently differentiated into NK cells that show enhanced autonomous growth and are resistant to the suppressive TGF-β signaling.</p>","PeriodicalId":29773,"journal":{"name":"Cell Reports Methods","volume":"4 9","pages":"100857"},"PeriodicalIF":4.3,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11440057/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142297021","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}
Cell Reports MethodsPub Date : 2024-09-16Epub Date: 2024-09-06DOI: 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":"<p><p>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.</p>","PeriodicalId":29773,"journal":{"name":"Cell Reports Methods","volume":" ","pages":"100856"},"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}
Cell Reports MethodsPub Date : 2024-09-16Epub Date: 2024-09-05DOI: 10.1016/j.crmeth.2024.100846
Clare K Hall, Olivia M Barr, Antoine Delamare, Alex Burkholder, Alice Tsai, Yuyao Tian, Felix E Ellett, Brent M Li, Rudolph E Tanzi, Mehdi Jorfi
{"title":"Profiling migration of human monocytes in response to chemotactic and barotactic guidance cues.","authors":"Clare K Hall, Olivia M Barr, Antoine Delamare, Alex Burkholder, Alice Tsai, Yuyao Tian, Felix E Ellett, Brent M Li, Rudolph E Tanzi, Mehdi Jorfi","doi":"10.1016/j.crmeth.2024.100846","DOIUrl":"10.1016/j.crmeth.2024.100846","url":null,"abstract":"<p><p>Monocytes are critical to innate immunity, participating in chemotaxis during tissue injury, infection, and inflammatory conditions. However, the migration dynamics of human monocytes under different guidance cues are not well characterized. Here, we developed a microfluidic device to profile the migration characteristics of human monocytes under chemotactic and barotactic guidance cues while also assessing the effects of age and cytokine stimulation. Human monocytes preferentially migrated toward the CCL2 gradient through confined microchannels, regardless of donor age and migration pathway. Stimulation with interferon (IFN)-γ, but not granulocyte-macrophage colony-stimulating factor (GM-CSF), disrupted monocyte navigation through complex paths and decreased monocyte CCL2 chemotaxis, velocity, and CCR2 expression. Additionally, monocytes exhibited a bias toward low-hydraulic-resistance pathways in asymmetric environments, which remained consistent across donor ages, cytokine stimulation, and chemoattractants. This microfluidic system provides insights into the unique migratory behaviors of human monocytes and is a valuable tool for studying peripheral immune cell migration in health and disease.</p>","PeriodicalId":29773,"journal":{"name":"Cell Reports Methods","volume":" ","pages":"100846"},"PeriodicalIF":4.3,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11440068/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142146459","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}
Cell Reports MethodsPub Date : 2024-09-16Epub Date: 2024-09-09DOI: 10.1016/j.crmeth.2024.100861
Justin T Savage, Juan J Ramirez, W Christopher Risher, Yizhi Wang, Dolores Irala, Cagla Eroglu
{"title":"SynBot is an open-source image analysis software for automated quantification of synapses.","authors":"Justin T Savage, Juan J Ramirez, W Christopher Risher, Yizhi Wang, Dolores Irala, Cagla Eroglu","doi":"10.1016/j.crmeth.2024.100861","DOIUrl":"10.1016/j.crmeth.2024.100861","url":null,"abstract":"<p><p>The formation of precise numbers of neuronal connections, known as synapses, is crucial for brain function. Therefore, synaptogenesis mechanisms have been one of the main focuses of neuroscience. Immunohistochemistry is a common tool for visualizing synapses. Thus, quantifying the numbers of synapses from light microscopy images enables screening the impacts of experimental manipulations on synapse development. Despite its utility, this approach is paired with low-throughput analysis methods that are challenging to learn, and the results are variable between experimenters, especially when analyzing noisy images of brain tissue. We developed an open-source ImageJ-based software, SynBot, to address these technical bottlenecks by automating the analysis. SynBot incorporates the advanced algorithms ilastik and SynQuant for accurate thresholding for synaptic puncta identification, and the code can easily be modified by users. The use of this software will allow for rapid and reproducible screening of synaptic phenotypes in healthy and diseased nervous systems.</p>","PeriodicalId":29773,"journal":{"name":"Cell Reports Methods","volume":"4 9","pages":"100861"},"PeriodicalIF":4.3,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11440803/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142297025","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}
Cell Reports MethodsPub Date : 2024-09-16Epub Date: 2024-09-09DOI: 10.1016/j.crmeth.2024.100858
Xiwei Shan, Ai Zhang, Mitchell G Rezzonico, Ming-Chi Tsai, Carlos Sanchez-Priego, Yingjie Zhang, Michelle B Chen, Meena Choi, José Miguel Andrade López, Lilian Phu, Amber L Cramer, Qiao Zhang, Jillian M Pattison, Christopher M Rose, Casper C Hoogenraad, Claire G Jeong
{"title":"Fully defined NGN2 neuron protocol reveals diverse signatures of neuronal maturation.","authors":"Xiwei Shan, Ai Zhang, Mitchell G Rezzonico, Ming-Chi Tsai, Carlos Sanchez-Priego, Yingjie Zhang, Michelle B Chen, Meena Choi, José Miguel Andrade López, Lilian Phu, Amber L Cramer, Qiao Zhang, Jillian M Pattison, Christopher M Rose, Casper C Hoogenraad, Claire G Jeong","doi":"10.1016/j.crmeth.2024.100858","DOIUrl":"10.1016/j.crmeth.2024.100858","url":null,"abstract":"<p><p>NGN2-driven induced pluripotent stem cell (iPSC)-to-neuron conversion is a popular method for human neurological disease modeling. In this study, we present a standardized approach for generating neurons utilizing clonal, targeted-engineered iPSC lines with defined reagents. We demonstrate consistent production of excitatory neurons at scale and long-term maintenance for at least 150 days. Temporal omics, electrophysiological, and morphological profiling indicate continued maturation to postnatal-like neurons. Quantitative characterizations through transcriptomic, imaging, and functional assays reveal coordinated actions of multiple pathways that drive neuronal maturation. We also show the expression of disease-related genes in these neurons to demonstrate the relevance of our protocol for modeling neurological disorders. Finally, we demonstrate efficient generation of NGN2-integrated iPSC lines. These workflows, profiling data, and functional characterizations enable the development of reproducible human in vitro models of neurological disorders.</p>","PeriodicalId":29773,"journal":{"name":"Cell Reports Methods","volume":"4 9","pages":"100858"},"PeriodicalIF":4.3,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11440061/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142297022","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}