Małgorzata Lisowska, Erin G Worrall, Filip Zavadil-Kokas, Keith Charlton, Euan Murray, M Aiman Mohtar, Radovan Krejcir, Vaclav Hrabal, Jack Brydon, Ainhoa Gonzalez Urionabarrenetxea, David G Saliba, Mariana Grima, Umesh Kalathiya, Petr Muller, Adam Krejci, Borivoj Vojtesek, Kathryn L Ball, Robin Fahraeus, David J Argyle, Maciej Parys, Ted R Hupp
{"title":"The development of a canine single-chain phage antibody library to isolate recombinant antibodies for use in translational cancer research.","authors":"Małgorzata Lisowska, Erin G Worrall, Filip Zavadil-Kokas, Keith Charlton, Euan Murray, M Aiman Mohtar, Radovan Krejcir, Vaclav Hrabal, Jack Brydon, Ainhoa Gonzalez Urionabarrenetxea, David G Saliba, Mariana Grima, Umesh Kalathiya, Petr Muller, Adam Krejci, Borivoj Vojtesek, Kathryn L Ball, Robin Fahraeus, David J Argyle, Maciej Parys, Ted R Hupp","doi":"10.1016/j.crmeth.2025.101008","DOIUrl":"10.1016/j.crmeth.2025.101008","url":null,"abstract":"<p><p>The development of canine immunotolerant monoclonal antibodies can accelerate the invention of new medicines for both canine and human diseases. We develop a methodology to clone the naive, somatically mutated variable domain repertoire from canine B cell mRNA using 5'RACE PCR. A set of degenerate primers were then designed and used to clone variable domain genes into archival \"holding\" plasmid libraries. These archived variable domain genes were then combinatorially ligated to produce a scFv M13 phage library. Next-generation long-read and short-read DNA sequencing methodologies were developed to annotate features of the cloned library including CDR diversity and IGHV/IGKV/IGLV subfamily distribution. A synthetic immunoglobulin G was developed from this scFv library to the canine immune checkpoint receptor PD-1. This synthetic platform can be used to clone and annotate archived antibody variable domain genes for use in perpetuity in order to develop improved preclinical models for the treatment of complex human diseases.</p>","PeriodicalId":29773,"journal":{"name":"Cell Reports Methods","volume":"5 3","pages":"101008"},"PeriodicalIF":4.3,"publicationDate":"2025-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12049728/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143711486","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}
Shengyuan He, Shangqin Sun, Kun Liu, Bo Pang, Yun Xiao
{"title":"Comprehensive assessment of computational methods for cancer immunoediting.","authors":"Shengyuan He, Shangqin Sun, Kun Liu, Bo Pang, Yun Xiao","doi":"10.1016/j.crmeth.2025.101006","DOIUrl":"10.1016/j.crmeth.2025.101006","url":null,"abstract":"<p><p>Cancer immunoediting reflects the role of the immune system in eliminating tumor cells and shaping tumor immunogenicity, which leaves marks in the genome. In this study, we systematically evaluate four methods for quantifying immunoediting. In colorectal cancer samples from The Cancer Genome Atlas, we found that these methods identified 78.41%, 46.17%, 36.61%, and 4.92% of immunoedited samples, respectively, covering 92.90% of all colorectal cancer samples. Comparison of 10 patient-derived xenografts (PDXs) with their original tumors showed that different methods identified reduced immune selection in PDXs ranging from 44.44% to 60.0%. The proportion of such PDX-tumor pairs increases to 77.78% when considering the union of results from multiple methods, indicating the complementarity of these methods. We find that observed-to-expected ratios highly rely on neoantigen selection criteria and reference datasets. In contrast, HLA-binding mutation ratio, immune dN/dS, and enrichment score of cancer cell fraction were less affected by these factors. Our findings suggest integration of multiple methods may benefit future immunoediting analyses.</p>","PeriodicalId":29773,"journal":{"name":"Cell Reports Methods","volume":"5 3","pages":"101006"},"PeriodicalIF":4.3,"publicationDate":"2025-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12049729/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143711474","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 : 2025-03-24Epub Date: 2025-03-17DOI: 10.1016/j.crmeth.2025.101005
Hannah M Lynn, Jeffrey I Gordon
{"title":"Sequential co-assembly reduces computational resources and errors in metagenome-assembled genomes.","authors":"Hannah M Lynn, Jeffrey I Gordon","doi":"10.1016/j.crmeth.2025.101005","DOIUrl":"10.1016/j.crmeth.2025.101005","url":null,"abstract":"<p><p>Generating metagenome-assembled genomes from DNA shotgun sequencing datasets can demand considerable computational resources. Here, we describe a sequential co-assembly method that reduces the assembly of duplicate reads through successive application of single-node computing tools for read assembly and mapping. Using a simulated mouse microbiome DNA shotgun sequencing dataset, we demonstrated that this approach shortens assembly time, uses less memory than traditional co-assembly, and produces significantly fewer assembly errors. Applying sequential co-assembly to shotgun sequencing reads from (1) a longitudinal study of gut microbiomes from undernourished Bangladeshi children and (2) a 2.3-terabyte dataset generated from gnotobiotic mice colonized with pooled microbiomes from these children that was too large to be handled by a traditional co-assembly approach also demonstrated significant reductions in assembly time and memory requirements. These results suggest that this approach should be useful in resource-constrained settings, including in low- and middle-income countries.</p>","PeriodicalId":29773,"journal":{"name":"Cell Reports Methods","volume":" ","pages":"101005"},"PeriodicalIF":4.3,"publicationDate":"2025-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12049710/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143658873","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 : 2025-03-24Epub Date: 2025-03-17DOI: 10.1016/j.crmeth.2025.101011
Vinicius Daguano Gastaldi, Martin Hindermann, Justus B H Wilke, Anja Ronnenberg, Sahab Arinrad, Sabine Kraus, Anne-Fleur Wildenburg, Antonios Ntolkeras, Micah J Provost, Liu Ye, Yasmina Curto, Jonathan-Alexis Cortés-Silva, Umer Javed Butt, Klaus-Armin Nave, Kamilla Woznica Miskowiak, Hannelore Ehrenreich
{"title":"A comprehensive and standardized pipeline for automated profiling of higher cognition in mice.","authors":"Vinicius Daguano Gastaldi, Martin Hindermann, Justus B H Wilke, Anja Ronnenberg, Sahab Arinrad, Sabine Kraus, Anne-Fleur Wildenburg, Antonios Ntolkeras, Micah J Provost, Liu Ye, Yasmina Curto, Jonathan-Alexis Cortés-Silva, Umer Javed Butt, Klaus-Armin Nave, Kamilla Woznica Miskowiak, Hannelore Ehrenreich","doi":"10.1016/j.crmeth.2025.101011","DOIUrl":"10.1016/j.crmeth.2025.101011","url":null,"abstract":"<p><p>In rodent behavior research, observer-independent methods, such as the IntelliCage, enhance data collection in a social, and thus stress-reduced, environment. The IntelliCage system allows experimenters to create cognitive challenges for mice motivated by rewards. Given the extensive and diverse data from IntelliCage, there is a high demand for automated analysis. Here, we introduce IntelliR, a free and standardized pipeline for analyzing IntelliCage data, including a cognition index for performance comparison across challenges. IntelliR supports the automatic analysis of three challenges that cover spatial, episodic-like, and working memory with their reversal tests and can also be adapted for other designs. Results from three cohorts of adult female C57B6 mice showed improved task proficiency over time. To validate cognitive impairment detection, we used adult female NexCreERT2xRosa26-eGFP-DTA mice after neuron ablation in cortex and hippocampus, in which we observed reduced learning capabilities. IntelliR integrates easily into research, improving time management and reproducibility.</p>","PeriodicalId":29773,"journal":{"name":"Cell Reports Methods","volume":" ","pages":"101011"},"PeriodicalIF":4.3,"publicationDate":"2025-03-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12049718/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143658871","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 : 2025-02-24Epub Date: 2025-02-17DOI: 10.1016/j.crmeth.2025.100986
Chaoqun Cheng, Zijian Huang, Ruiming Zhang, Guozheng Huang, Han Wang, Likai Tang, Xiaoqin Wang
{"title":"A real-time, multi-subject three-dimensional pose tracking system for the behavioral analysis of non-human primates.","authors":"Chaoqun Cheng, Zijian Huang, Ruiming Zhang, Guozheng Huang, Han Wang, Likai Tang, Xiaoqin Wang","doi":"10.1016/j.crmeth.2025.100986","DOIUrl":"10.1016/j.crmeth.2025.100986","url":null,"abstract":"<p><p>The ability to track the positions and poses of multiple animals in three-dimensional (3D) space in real time is highly desired by non-human primate (NHP) researchers in behavioral and systems neuroscience. This capability enables the analysis of social behaviors involving multiple NHPs and supports closed-loop experiments. Although several animal 3D pose tracking systems have been developed, most are difficult to deploy in new environments and lack real-time analysis capabilities. To address these limitations, we developed MarmoPose, a deep-learning-based, real-time 3D pose tracking system for multiple common marmosets, an increasingly critical NHP model in neuroscience research. This system can accurately track the 3D poses of multiple marmosets freely moving in their home cage with minimal hardware requirements. By employing a marmoset skeleton model, MarmoPose can further optimize 3D poses and estimate invisible body locations. Additionally, MarmoPose achieves high inference speeds and enables real-time closed-loop experimental control based on events detected from 3D poses.</p>","PeriodicalId":29773,"journal":{"name":"Cell Reports Methods","volume":" ","pages":"100986"},"PeriodicalIF":4.3,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11955267/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143450180","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 : 2025-02-24Epub Date: 2025-02-17DOI: 10.1016/j.crmeth.2025.100987
Matthew J Borrelli, Bart Kolendowski, Gabriel E DiMattia, Trevor G Shepherd
{"title":"Spatiotemporal analysis of ratiometric biosensors in live multicellular spheroids using SPoRTS.","authors":"Matthew J Borrelli, Bart Kolendowski, Gabriel E DiMattia, Trevor G Shepherd","doi":"10.1016/j.crmeth.2025.100987","DOIUrl":"10.1016/j.crmeth.2025.100987","url":null,"abstract":"<p><p>Here, we describe SPoRTS, an open-source workflow for high-throughput spatiotemporal image analysis of fluorescence-based ratiometric biosensors in living spheroids. To achieve this, we have implemented a fully automated algorithm for the acquisition of line intensity profile data, ultimately enabling semi-quantitative measurement of biosensor activity as a function of distance from the center of the spheroid. We demonstrate the functionality of SPoRTS via spatial analysis of live spheroids expressing a ratiometric biosensor based on the fluorescent, ubiquitin-based cell-cycle indicator (FUCCI) system, which identifies mitotic cells. We compare this FUCCI-based SPoRTS analysis with spatially quantified immunostaining for proliferation markers, finding that the results are strongly correlated.</p>","PeriodicalId":29773,"journal":{"name":"Cell Reports Methods","volume":" ","pages":"100987"},"PeriodicalIF":4.3,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11955269/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143450254","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 : 2025-02-24Epub Date: 2025-02-14DOI: 10.1016/j.crmeth.2025.100990
Farzaneh Firoozbakht, Maria Louise Elkjaer, Diane E Handy, Rui-Sheng Wang, Zoe Chervontseva, Matthias Rarey, Joseph Loscalzo, Jan Baumbach, Olga Tsoy
{"title":"Exploring common mechanisms of adverse drug reactions and disease phenotypes through network-based analysis.","authors":"Farzaneh Firoozbakht, Maria Louise Elkjaer, Diane E Handy, Rui-Sheng Wang, Zoe Chervontseva, Matthias Rarey, Joseph Loscalzo, Jan Baumbach, Olga Tsoy","doi":"10.1016/j.crmeth.2025.100990","DOIUrl":"10.1016/j.crmeth.2025.100990","url":null,"abstract":"<p><p>The need for a deeper understanding of adverse drug reaction (ADR) mechanisms is vital for improving drug safety and repurposing. This study introduces Drug Adverse Reaction Mechanism Explainer (DREAMER), a network-based framework that uses a comprehensive knowledge graph to uncover molecular mechanisms underlying ADRs and disease phenotypes. By examining shared phenotypes of drugs and diseases and their effects on protein-protein interaction networks, DREAMER identifies proteins linked to ADR mechanisms. Applied to 649 ADRs, DREAMER identified molecular mechanisms for 67 ADRs, including ventricular arrhythmia and metabolic acidosis, and emphasized pathways like GABAergic signaling and coagulation proteins in personality disorders and intracranial hemorrhage. We further demonstrate the application of DREAMER in drug repurposing and propose sotalol, ranolazine, and diltiazem as candidate drugs to be repurposed for cardiac arrest. In summary, DREAMER effectively detects molecular mechanisms underlying phenotypes, emphasizing the importance of network-based analyses with integrative data for enhancing drug safety and accelerating the discovery of novel therapeutic strategies.</p>","PeriodicalId":29773,"journal":{"name":"Cell Reports Methods","volume":" ","pages":"100990"},"PeriodicalIF":4.3,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11955268/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143426269","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}
Yi Jiang, Haoyu Wang, Kevin M Boergens, Norman Rzepka, Fangfang Wang, Yunfeng Hua
{"title":"Efficient cell-wide mapping of mitochondria in electron microscopic volumes using webKnossos.","authors":"Yi Jiang, Haoyu Wang, Kevin M Boergens, Norman Rzepka, Fangfang Wang, Yunfeng Hua","doi":"10.1016/j.crmeth.2025.100989","DOIUrl":"10.1016/j.crmeth.2025.100989","url":null,"abstract":"<p><p>Recent technical advances in volume electron microscopy (vEM) and artificial-intelligence-assisted image processing have facilitated high-throughput quantifications of cellular structures, such as mitochondria, that are ubiquitous and morphologically diversified. A still often-overlooked computational challenge is to assign a cell identity to numerous mitochondrial instances, for which both mitochondrial and cell membrane contouring used to be required. Here, we present a vEM reconstruction procedure (called mito-SegEM) that utilizes virtual-path-based annotation to assign automatically segmented mitochondrial instances at the cellular scale, therefore bypassing the requirement of membrane contouring. The embedded toolset in webKnossos (an open-source online annotation platform) is optimized for fast annotation, visualization, and proofreading of cellular organelle networks. We demonstrate the broad applications of mito-SegEM on volumetric datasets from various tissues, including the brain, intestine, and testis, to achieve an accurate and efficient reconstruction of mitochondria in a use-dependent fashion.</p>","PeriodicalId":29773,"journal":{"name":"Cell Reports Methods","volume":"5 2","pages":"100989"},"PeriodicalIF":4.3,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11955265/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143504684","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 : 2025-02-24Epub Date: 2025-02-14DOI: 10.1016/j.crmeth.2025.100983
Iraida Sharina, Radwa Awad, Soren Cobb, Emil Martin, Sean P Marrelli, Anilkumar K Reddy
{"title":"Non-invasive real-time pulsed Doppler assessment of blood flow in mouse ophthalmic artery.","authors":"Iraida Sharina, Radwa Awad, Soren Cobb, Emil Martin, Sean P Marrelli, Anilkumar K Reddy","doi":"10.1016/j.crmeth.2025.100983","DOIUrl":"10.1016/j.crmeth.2025.100983","url":null,"abstract":"<p><p>Non-invasive and high-temporal resolution methods for characterizing blood flow in mouse cranial arteries, such as the ophthalmic artery (OphA), are lacking. We present an application of pulsed Doppler ultrasound to provide real-time, non-invasive measurement of blood flow velocity in the OphA through an identified soft tissue window in the mouse head. We confirmed the identity of the artery and mapped its origin from the internal carotid artery by a combination of microcomputed tomography (microCT) vascular imaging and transient occlusion of the internal carotid artery. Application of our approach demonstrated sex differences in the OphA vasodilative response to agonists. We also evaluated real-time flow characteristics in the OphA in response to transient carotid artery ligation. The method will provide a simple and low-cost approach for screening drugs targeting ophthalmic blood flow and can be used as a more accessible surrogate of cerebral blood flow in both acute and longitudinal imaging studies.</p>","PeriodicalId":29773,"journal":{"name":"Cell Reports Methods","volume":" ","pages":"100983"},"PeriodicalIF":4.3,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11955264/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143426276","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 : 2025-02-24Epub Date: 2025-02-14DOI: 10.1016/j.crmeth.2025.100985
Mike van Santvoort, Óscar Lapuente-Santana, Maria Zopoglou, Constantin Zackl, Francesca Finotello, Pim van der Hoorn, Federica Eduati
{"title":"Mathematically mapping the network of cells in the tumor microenvironment.","authors":"Mike van Santvoort, Óscar Lapuente-Santana, Maria Zopoglou, Constantin Zackl, Francesca Finotello, Pim van der Hoorn, Federica Eduati","doi":"10.1016/j.crmeth.2025.100985","DOIUrl":"10.1016/j.crmeth.2025.100985","url":null,"abstract":"<p><p>Cell-cell interaction (CCI) networks are key to understanding disease progression and treatment response. However, existing methods for inferring these networks often aggregate data across patients or focus on cell-type level interactions, providing a generalized overview but overlooking patient heterogeneity and local network structures. To address this, we introduce \"random cell-cell interaction generator\" (RaCInG), a model based on random graphs to derive personalized networks leveraging prior knowledge on ligand-receptor interactions and bulk RNA sequencing data. We applied RaCInG to 8,683 cancer patients to extract 643 network features related to the tumor microenvironment and unveiled associations with immune response and subtypes, enabling prediction and explanation of immunotherapy responses. RaCInG demonstrated robustness and showed consistencies with state-of-the-art methods. Our findings highlight RaCInG's potential to elucidate patient-specific network dynamics, offering insights into cancer biology and treatment responses. RaCInG is poised to advance our understanding of complex CCI s in cancer and other biomedical domains.</p>","PeriodicalId":29773,"journal":{"name":"Cell Reports Methods","volume":" ","pages":"100985"},"PeriodicalIF":4.3,"publicationDate":"2025-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11955271/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143426272","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}