Cell Reports MethodsPub Date : 2025-05-19Epub Date: 2025-05-12DOI: 10.1016/j.crmeth.2025.101047
Marc S Sherman, Thomas McMahon-Skates, Lindsey S Gaston, Sonya W Katzen, Joseph A Majzoub, Wolfram Goessling
{"title":"Harmonizing TUNEL with multiplexed iterative immunofluorescence enriches spatial contextualization of cell death.","authors":"Marc S Sherman, Thomas McMahon-Skates, Lindsey S Gaston, Sonya W Katzen, Joseph A Majzoub, Wolfram Goessling","doi":"10.1016/j.crmeth.2025.101047","DOIUrl":"10.1016/j.crmeth.2025.101047","url":null,"abstract":"<p><p>Terminal deoxynucleotidyl transferase dUTP nick-end labeling (TUNEL) is an essential tool for detecting cell death in tissues, but its compatibility with spatial proteomic methods is unknown. We evaluated variations of the TUNEL protocol for compatibility with multiple iterative labeling by antibody neodeposition (MILAN) in acetaminophen-induced hepatocyte necrosis and dexamethasone-induced adrenocortical apoptosis. Using a commercial Click-iT-based assay as a standard, TUNEL signal could be reliably produced independent of the antigen retrieval method, with tissue-specific minor differences in signal to noise. In contrast, proteinase K treatment consistently reduced or even abrogated protein antigenicity, while pressure cooker treatment enhanced protein antigenicity for the targets tested. Antibody-based TUNEL with pressure cooker retrieval could be flexibly integrated into a MILAN staining series, and first-round TUNEL was also compatible with a second spatial proteomic method, cyclic immunofluorescence (CycIF). We anticipate that this harmonization of TUNEL with spatial proteomics will enhance the spatial contextualization of cell death in complex tissues.</p>","PeriodicalId":29773,"journal":{"name":"Cell Reports Methods","volume":" ","pages":"101047"},"PeriodicalIF":4.3,"publicationDate":"2025-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144022130","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}
Cell Reports MethodsPub Date : 2025-05-19Epub Date: 2025-04-21DOI: 10.1016/j.crmeth.2025.101029
Ziling Kate Zhou, Kibeom Hong, Bo Huang, Geeta J Narlikar
{"title":"Understanding how genetically encoded tags and crowding agents affect phase separation by heterochromatin protein HP1α.","authors":"Ziling Kate Zhou, Kibeom Hong, Bo Huang, Geeta J Narlikar","doi":"10.1016/j.crmeth.2025.101029","DOIUrl":"10.1016/j.crmeth.2025.101029","url":null,"abstract":"<p><p>The heterochromatin protein HP1α (heterochromatin protein 1 alpha) phase separates in vitro and displays properties compatible with phase separation in cells. Phase separation of HP1α in cells is typically studied using genetically encoded fluorescent tags such as green fluorescent protein (GFP). Whether such tags affect the intrinsic phase separation properties of HP1α is understudied. We assessed how tag size and linker length affect phase separation by HP1α in vitro. GFP tags inhibited phase separation by HP1α. In contrast, an UnaG tag with a 16 amino acid glycine-glycine-serine (GGS) linker minimally perturbed HP1α phase separation in vitro and could be used to visualize HP1α dynamics in cells. We further investigated the effects of a commonly used crowding agent, polyethylene glycol (PEG). PEG induced phase separation of proteins with no propensity to phase separate under physiological buffer conditions and dampened the effects of HP1α mutations. Therefore, phase separation of biological macromolecules with PEG-containing crowding agents should be interpreted with caution.</p>","PeriodicalId":29773,"journal":{"name":"Cell Reports Methods","volume":" ","pages":"101029"},"PeriodicalIF":4.3,"publicationDate":"2025-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144031397","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}
Cell Reports MethodsPub Date : 2025-05-19Epub Date: 2025-04-28DOI: 10.1016/j.crmeth.2025.101031
Zijun Gao, Zhi Ling, Wenhao Liu, Keyi Han, Hongmanlin Zhang, Xuanwen Hua, Edward A Botchwey, Shu Jia
{"title":"Fluorescence microscopy through scattering media with robust matrix factorization.","authors":"Zijun Gao, Zhi Ling, Wenhao Liu, Keyi Han, Hongmanlin Zhang, Xuanwen Hua, Edward A Botchwey, Shu Jia","doi":"10.1016/j.crmeth.2025.101031","DOIUrl":"10.1016/j.crmeth.2025.101031","url":null,"abstract":"<p><p>Biological tissues, as natural scattering media, inherently disrupt structural information, presenting significant challenges for optical imaging. Complex light propagation through tissue severely degrades image quality, limiting conventional fluorescence imaging techniques to superficial depths. Extracting meaningful information from random speckle patterns is, therefore, critical for deeper tissue imaging. In this study, we present RNP (robust non-negative principal matrix factorization), an approach that enables fluorescence microscopy under diverse scattering conditions. By integrating robust feature extraction with non-negativity constraints, RNP effectively addresses challenges posed by non-sparse signals and background interference in scattering tissue environments. The framework operates on a standard epi-fluorescence platform, eliminating the need for complex instrumentation or precise alignment. The results from imaging scattered cells and tissues demonstrate substantial improvements in robustness, field of view, depth of field, and image clarity. We anticipate that RNP will become a valuable tool for overcoming scattering challenges in fluorescence microscopy and driving advancements in biomedical research.</p>","PeriodicalId":29773,"journal":{"name":"Cell Reports Methods","volume":" ","pages":"101031"},"PeriodicalIF":4.3,"publicationDate":"2025-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144038578","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}
Cell Reports MethodsPub Date : 2025-05-19Epub Date: 2025-04-28DOI: 10.1016/j.crmeth.2025.101032
Kitty B Murphy, Yuqian Ye, Maria Tsalenchuk, Alexi Nott, Sarah J Marzi
{"title":"CHAS infers cell type-specific signatures in bulk brain histone acetylation studies of neurological and psychiatric disorders.","authors":"Kitty B Murphy, Yuqian Ye, Maria Tsalenchuk, Alexi Nott, Sarah J Marzi","doi":"10.1016/j.crmeth.2025.101032","DOIUrl":"10.1016/j.crmeth.2025.101032","url":null,"abstract":"<p><p>Epigenomic profiling of the brain has largely been done on bulk tissues, limiting our understanding of cell type-specific epigenetic changes in disease states. Here, we introduce cell type-specific histone acetylation score (CHAS), a computational tool for inferring cell type-specific signatures in bulk brain H3K27ac profiles. We applied CHAS to >300 H3K27ac chromatin immunoprecipitation sequencing samples from studies of Alzheimer's disease, Parkinson's disease, autism spectrum disorder, schizophrenia, and bipolar disorder in bulk postmortem brain tissue. In addition to recapitulating known disease-associated shifts in cellular proportions, we identified cell type-specific biological insights into brain-disorder-associated regulatory variation. In most cases, genetic risk and epigenetic dysregulation targeted different cell types, suggesting independent mechanisms. For instance, genetic risk of Alzheimer's disease was exclusively enriched within microglia, while epigenetic dysregulation predominantly fell within oligodendrocyte-specific H3K27ac regions. In addition, reanalysis of the original datasets using CHAS enabled identification of biological pathways associated with each neurological and psychiatric disorder at cellular resolution.</p>","PeriodicalId":29773,"journal":{"name":"Cell Reports Methods","volume":" ","pages":"101032"},"PeriodicalIF":4.3,"publicationDate":"2025-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144050630","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}
Cell Reports MethodsPub Date : 2025-05-19Epub Date: 2025-05-12DOI: 10.1016/j.crmeth.2025.101049
Brandon P Conn, Jared L Dietze, Christian J Yee, Margaret M Hallisey, Irais Ortiz-Caraveo, Marit M van Buuren, Richard B Gaynor, Kendra C Foley, Jaewon Choi, Vikram R Juneja
{"title":"Generation of T cell responses against broad KRAS hotspot neoantigens for cell therapy or TCR discovery.","authors":"Brandon P Conn, Jared L Dietze, Christian J Yee, Margaret M Hallisey, Irais Ortiz-Caraveo, Marit M van Buuren, Richard B Gaynor, Kendra C Foley, Jaewon Choi, Vikram R Juneja","doi":"10.1016/j.crmeth.2025.101049","DOIUrl":"10.1016/j.crmeth.2025.101049","url":null,"abstract":"<p><p>Adoptive cell therapy (ACT) with T cells targeting Kirsten rat sarcoma (KRAS) neoantigens can drive anti-tumor immunity but has so far been focused on a small fraction of known KRAS neoantigens. Here, we develop a single process starting from peripheral blood that can prime and expand T cell responses ex vivo to any KRAS neoantigen based on each individual's human leukocyte antigen (HLA) profile. We conducted the process in 20 healthy donors and generated T cell responses to 46 of 47 evaluated neoantigens. We identified and cloned more than 150 KRAS T cell receptors (TCRs), with the strongest TCRs having similar potency to clinically active benchmark TCRs. T cells generated through this process were able to slow tumor growth in vitro and in vivo. The approach could be used as the basis for the development of an ex vivo primed therapeutic or to discover a library of TCRs against a broad range of KRAS neoantigens.</p>","PeriodicalId":29773,"journal":{"name":"Cell Reports Methods","volume":" ","pages":"101049"},"PeriodicalIF":4.3,"publicationDate":"2025-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144050704","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}
Cell Reports MethodsPub Date : 2025-05-19Epub Date: 2025-05-09DOI: 10.1016/j.crmeth.2025.101048
Ronnie Blazev, Barry M Zee, Hayley Peckham, Yaan-Kit Ng, Christopher T A Lewis, Chengxin Zhang, James W McNamara, Craig A Goodman, Paul Gregorevic, Julien Ochala, Frederik J Steyn, Shyuan T Ngo, Matthew P Stokes, Benjamin L Parker
{"title":"Site-specific quantification of the in vivo UFMylome reveals myosin modification in ALS.","authors":"Ronnie Blazev, Barry M Zee, Hayley Peckham, Yaan-Kit Ng, Christopher T A Lewis, Chengxin Zhang, James W McNamara, Craig A Goodman, Paul Gregorevic, Julien Ochala, Frederik J Steyn, Shyuan T Ngo, Matthew P Stokes, Benjamin L Parker","doi":"10.1016/j.crmeth.2025.101048","DOIUrl":"10.1016/j.crmeth.2025.101048","url":null,"abstract":"<p><p>UFMylation is a ubiquitin-like protein modification of Ubiquitin Fold Modifier 1 (UFM1) applied to substrate proteins and regulates several cellular processes such as protein quality control. Here, we describe the development of an antibody-based enrichment approach to immunoprecipitate remnant UFMylated peptides and identification by mass spectrometry. We used this approach to identify >200 UFMylation sites from various mouse tissues, revealing extensive modification in skeletal muscle. In vivo knockdown of the E2 ligase, UFC1, followed by enrichment and analysis of remnant UFMylated peptides quantified concomitant down-regulation and validation of a subset of modification sites, particularly myosin UFMylation. Furthermore, we show that UFMylation is increased in skeletal muscle biopsies from people living with amyotrophic lateral sclerosis (plwALS). Quantification of UFMylation sites in these biopsies with multiplexed isotopic labeling reveal prominent increases in myosin UFMylation. Our data suggest that in vivo UFMylation is more complex than previously thought.</p>","PeriodicalId":29773,"journal":{"name":"Cell Reports Methods","volume":" ","pages":"101048"},"PeriodicalIF":4.3,"publicationDate":"2025-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144013810","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}
Cell Reports MethodsPub Date : 2025-05-19Epub Date: 2025-04-28DOI: 10.1016/j.crmeth.2025.101030
Jakob Wirbel, Tessa M Andermann, Erin F Brooks, Lanya Evans, Adam Groth, Mai Dvorak, Meenakshi Chakraborty, Bianca Palushaj, Gabriella Z M Reynolds, Imani E Porter, Monzr Al Malki, Andrew Rezvani, Mahasweta Gooptu, Hany Elmariah, Lyndsey Runaas, Teng Fei, Michael J Martens, Javier Bolaños-Meade, Mehdi Hamadani, Shernan Holtan, Rob Jenq, Jonathan U Peled, Mary M Horowitz, Kathleen L Poston, Wael Saber, Leslie S Kean, Miguel-Angel Perales, Ami S Bhatt
{"title":"Accurate prediction of absolute prokaryotic abundance from DNA concentration.","authors":"Jakob Wirbel, Tessa M Andermann, Erin F Brooks, Lanya Evans, Adam Groth, Mai Dvorak, Meenakshi Chakraborty, Bianca Palushaj, Gabriella Z M Reynolds, Imani E Porter, Monzr Al Malki, Andrew Rezvani, Mahasweta Gooptu, Hany Elmariah, Lyndsey Runaas, Teng Fei, Michael J Martens, Javier Bolaños-Meade, Mehdi Hamadani, Shernan Holtan, Rob Jenq, Jonathan U Peled, Mary M Horowitz, Kathleen L Poston, Wael Saber, Leslie S Kean, Miguel-Angel Perales, Ami S Bhatt","doi":"10.1016/j.crmeth.2025.101030","DOIUrl":"10.1016/j.crmeth.2025.101030","url":null,"abstract":"<p><p>Quantification of the absolute microbial abundance in a human stool sample is crucial for a comprehensive understanding of the microbial ecosystem, but this information is lost upon metagenomic sequencing. While several methods exist to measure absolute microbial abundance, they are technically challenging and costly, presenting an opportunity for machine learning. Here, we observe a strong correlation between DNA concentration and the absolute number of 16S ribosomal RNA copies as measured by digital droplet PCR in clinical stool samples from individuals undergoing hematopoietic cell transplantation (BMT CTN 1801). Based on this correlation and additional measurements, we trained an accurate yet simple machine learning model for the prediction of absolute prokaryotic load, which showed exceptional prediction accuracy on an external cohort that includes people living with Parkinson's disease and healthy controls. We propose that, with further validation, this model has the potential to enable accurate absolute abundance estimation based on readily available sample measurements.</p>","PeriodicalId":29773,"journal":{"name":"Cell Reports Methods","volume":" ","pages":"101030"},"PeriodicalIF":4.3,"publicationDate":"2025-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144052505","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}
Cell Reports MethodsPub Date : 2025-05-19Epub Date: 2025-05-13DOI: 10.1016/j.crmeth.2025.101051
Christian Kuete Fofie, Rafael Granja-Vazquez, Vincent Truong, Patrick Walsh, Theodore Price, Swati Biswas, Gregory Dussor, Joseph Pancrazio, Benedict Kolber
{"title":"Profiling human iPSC-derived sensory neurons for analgesic drug screening using a multi-electrode array.","authors":"Christian Kuete Fofie, Rafael Granja-Vazquez, Vincent Truong, Patrick Walsh, Theodore Price, Swati Biswas, Gregory Dussor, Joseph Pancrazio, Benedict Kolber","doi":"10.1016/j.crmeth.2025.101051","DOIUrl":"10.1016/j.crmeth.2025.101051","url":null,"abstract":"<p><p>Chronic pain is a global health issue, yet effective treatments remain limited due to poor preclinical-to-human translation. To address this, we developed a high-content screening (HCS) platform using hiPSC-derived nociceptors to identify analgesics targeting the peripheral nervous system. These cells, cultured on multi-well microelectrode arrays, achieved nearly 100% active electrodes by week 2, maintaining stable activity for at least 2 weeks. After 28 days, we assessed drug effects on neuronal activity, achieving strong assay performance (robust Z' > 0.5). Pharmacological tests confirmed responses to key analgesic targets, including ion channels (Nav, Cav, Kv, and TRPV1), neurotransmitter receptors (AMPAR and GABA-R), and kinase inhibitors (tyrosine and JAK1/2). Transcriptomic analysis validated target expression, though levels differed from primary human DRG cells. The platform was used to screen over 700 natural compounds, demonstrating its potential for analgesic discovery. This HCS platform facilitates the rapid discovery of uncharacterized analgesics, reducing preclinical-to-human translation failure.</p>","PeriodicalId":29773,"journal":{"name":"Cell Reports Methods","volume":" ","pages":"101051"},"PeriodicalIF":4.3,"publicationDate":"2025-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144080953","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}
Cell Reports MethodsPub Date : 2025-05-19Epub Date: 2025-05-08DOI: 10.1016/j.crmeth.2025.101035
Changxin Wan, Yilong Qu, Zhiyou Ye, Tianbei Zhang, Huifang Ma, Ming Chen, Wenpin Hou, Zhicheng Ji
{"title":"Comparative analysis of gene regulation in single cells using Compass.","authors":"Changxin Wan, Yilong Qu, Zhiyou Ye, Tianbei Zhang, Huifang Ma, Ming Chen, Wenpin Hou, Zhicheng Ji","doi":"10.1016/j.crmeth.2025.101035","DOIUrl":"10.1016/j.crmeth.2025.101035","url":null,"abstract":"<p><p>Single-cell multi-omics is a transformative technology that measures both gene expression and chromatin accessibility in individual cells. However, most studies concentrate on a single tissue and are unable to determine whether a gene is regulated by a cis-regulatory element (CRE) in just one tissue or across multiple tissues. We developed Compass for comparative analysis of gene regulation across a large number of human and mouse tissues. Compass consists of a database, CompassDB, and an open-source R software package, CompassR. CompassDB contains processed single-cell multi-omics data of more than 2.8 million cells from hundreds of cell types. Building upon CompassDB, CompassR enables visualization and comparison of gene regulation across multiple tissues. We demonstrated that CompassR can identify CRE-gene linkages specific to a tissue type and their associated transcription factors in real examples.</p>","PeriodicalId":29773,"journal":{"name":"Cell Reports Methods","volume":" ","pages":"101035"},"PeriodicalIF":4.3,"publicationDate":"2025-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144037362","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}
Cell Reports MethodsPub Date : 2025-05-19Epub Date: 2025-05-01DOI: 10.1016/j.crmeth.2025.101033
Mao-Jan Lin, Ben Langmead, Yana Safonova
{"title":"IGLoo enables comprehensive analysis and assembly of immunoglobulin heavy-chain loci in lymphoblastoid cell lines using PacBio high-fidelity reads.","authors":"Mao-Jan Lin, Ben Langmead, Yana Safonova","doi":"10.1016/j.crmeth.2025.101033","DOIUrl":"10.1016/j.crmeth.2025.101033","url":null,"abstract":"<p><p>High-quality human genome assemblies derived from lymphoblastoid cell lines (LCLs) provide reference genomes and pangenomes for genomics studies. However, LCLs pose technical challenges for profiling immunoglobulin (IG) genes, as their IG loci contain a mixture of germline and somatically recombined haplotypes, making genotyping and assembly difficult with widely used frameworks. To address this, we introduce IGLoo, a software tool that analyzes sequence data and assemblies derived from LCLs, characterizing somatic V(D)J recombination events and identifying breakpoints and missing IG genes in the assemblies. Furthermore, IGLoo implements a reassembly framework to improve germline assembly quality by integrating information on somatic events and population structural variations in IG loci. Applying IGLoo to the assemblies from the Human Pangenome Reference Consortium, we gained valuable insights into the mechanisms, gene usage, and patterns of V(D)J recombination and the causes of assembly artifacts in the IG heavy-chain (IGH) locus, and we improved the representation of IGH assemblies.</p>","PeriodicalId":29773,"journal":{"name":"Cell Reports Methods","volume":" ","pages":"101033"},"PeriodicalIF":4.3,"publicationDate":"2025-05-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144050631","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}