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| SICyLIA-cTMT dissects redox proteome dynamics with high accuracy and depth at microgram scale |
| Sergio Lilla, Samuel Atkinson, Sonja Radau, Ulla-Maja Bailey, Atul Shahaji Deshmukh, Jiska van der Reest, Joanna Kirkpatrick, Thomas MacVicar, Sara Zanivan |
| Cysteine oxidation controls diverse signaling pathways but remains difficult to study at scale. Lilla et al. present SICyLIA-cTMT, a quantitative mass spectrometry workflow that simultaneously measures cysteine redox dynamics and protein abundance with high accuracy from minimal input. The method enhances coverage, reduces instrument time, and enables comprehensive analysis of oxidative signaling in cells and tissues. |
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| Using spatial proteomics to enhance cell type assignments in histology images |
| Monica T. Dayao, Aaron T. Mayer, Alexandro E. Trevino, Ziv Bar-Joseph |
| Dayao et al. present a deep learning approach to assign cell types in histology images by training on paired spatial proteomics data. This method enables detailed cell type identification from routine tissue slides, bridging accessible histological techniques and costly molecular imaging while providing a powerful tool for studying tissue organization. |
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| APEX2 proximity labeling of RNA in bacteria |
| Hadi Yassine, Elizabeta Sirotkin, Omer Goldberger, Vincent A. Lawal, Daniel B. Kearns, Orna Amster-Choder, Jared M. Schrader |
| Yassine et al. adapt an APEX2-based RNA proximity labeling approach that labels RNAs in both gram-negative and gram-positive bacteria. This method involves fusing an RNA-binding protein to APEX2, which rapidly labels localized RNAs on a faster timescale than the short lifetimes of RNAs in bacteria. |
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| DiffHiChIP: Identifying differential chromatin contacts from HiChIP data |
| Sourya Bhattacharyya, Daniela Salgado Figueroa, Katia Georgopoulos, Ferhat Ay |
| Bhattacharyya et al. present DiffHiChIP, a statistical framework for detecting differential chromatin loops from HiChIP data. By modeling distance decay of contacts and integrating multiple statistical models and dispersion estimation strategies, DiffHiChIP improves detection of long-range differential interactions and provides a robust tool for studying condition-specific chromatin regulation. |
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| Imaging the time course of DNA damage response at a nonrepetitive endogenous locus |
| Adam T. Rybczynski, W. Taylor Cottle, Po-Ta Chen, Jiwoong Kwon, Tiantian Shang, Yanbo Wang, Paul Meneses, Sushil Pangeni, Yeji Park, Momcilo Gavrilov, Taekjip Ha |
| Rybczynski et al. introduce a method to measure DNA repair timing at specific genomic loci using very fast CRISPR and labeling of locally denatured genomic DNA and associated repair proteins. This approach enables detailed analysis of diverse repair processes, advancing our understanding of genomic instability and its role in disease. |
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| Targeted long-read methylation analysis using hybridization capture suitable for clinical specimens |
| Keisuke Kunigo, Satoi Nagasawa, Keiko Kajiya, Yoshitaka Sakamoto, Suzuko Zaha, Yuta Kuze, Akinori Kanai, Kotaro Nomura, Masahiro Tsuboi, Genichiro Ishii, Ai Motoyoshi, Koichiro Tsugawa, Motohiro Chosokabe, Junki Koike, Ayako Suzuki, Yutaka Suzuki, Masahide Seki |
| Kunigo et al. introduce t-nanoEM, a practical method that enables high-depth, target-specific long-read methylation analysis with as little as 8 ng of DNA. They develop a pipeline for haplotype-resolved and mutated allele-specific methylation analysis and demonstrate its utility by successfully applying it to clinical breast and lung cancer samples. |
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| AIstain: Enhancing microglial phagocytosis analysis through deep learning |
| Alexander Zähringer, Janaki Manoja Vinnakota, Tobias Wertheimer, Philipp Saalfrank, Marie Follo, Florian Ingelfinger, Robert Zeiser |
| Zähringer et al. introduce AIstain, a U-Net-based deep learning approach for label-free microglial detection in live cell image cytometry. Their method outperforms fluorescence staining and common segmentation tools, enabling accurate, high-throughput phagocytosis analysis while avoiding cytotoxic dyes. |
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| A transmission electron microscopy platform for assessing mitochondrial and nuclear architecture in cardiomyocytes |
| Mara Kiessling, Juergen Gindlhuber, Amalia Sintou, Ingrid Matzer, Snježana Radulović, Viktoria Trummer-Herbst, Andonita Ajdari, Julia Voglhuber-Höller, Michael Holzer, Tristan A. Rodriguez, Gerd Leitinger, Andreas Zirlik, Donald M. Bers, Susanne Sattler, Senka Ljubojevic-Holzer |
| Kiessling et al. introduce a TEM platform and analysis workflow that consistently images the nuclear center and perinuclear mitochondria in adult cardiomyocytes, enabling automated quantification and discovery of spatially resolved remodeling. Using Drp1-deficient mice, they demonstrate the ability to detect stress-induced anomalies in nanoscale organellar architecture. |
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| An optimized click chemistry method allows visualization of proliferating neuronal progenitors in the mouse brain |
| Fei Zhao, Tomonari Hamaguchi, Ryo Egawa, Atsushi Enomoto, Kinji Ohno |
| Zhao et al. present an optimized 3D click chemistry method (C4-3D) that enables visualization of EdU-labeled proliferating cells in tissue-cleared whole mouse brains. The method is compatible with major tissue-clearing protocols and fluorescent reporters and allows precise mapping of proliferating cells to the Allen Brain Atlas enabling spatiotemporal identification of neurogenesis in development, injury, aging, and disease models. |
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| Combinatorial responsiveness of chemosensory neurons in mouse explants revealed by DynamicNeuroTracker |
| Jungsik Noh, Wen Mai Wong, Bo-Jui Chang, Gaudenz Danuser, Julian P. Meeks |
| Noh et al. present DynamicNeuronTracker, which segments single neurons despite positional jitter from tissue deformation in 3D calcium imaging. Analyzing the imaging of pheromone-sensing neurons under controlled stimulation, they identify 15 neuronal subpopulations with distinct responses to eight bile acids and steroids, revealing a pronounced bias toward estrogen and pregnanolone. |
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| EyaHOST, a modular genetic system for investigation of intercellular and tumor-host interactions in Drosophila melanogaster |
| José Teles-Reis, Ashish Jain, Dan Liu, Rojyar Khezri, Marina Gonçalves Antunes, Sofia Micheli, Alicia Alfonso Gomez, Caroline Dillard, Tor Erik Rusten |
| Teles-Reis et al. present EyaHOST, a modular Drosophila system that enables clone generation in the eye disc with independent genetic manipulation of other tissues. EyaHOST uses an Eya-KD “kick-out” system for clonal QF2-driven tumor initiation and GAL4 for organ-specific host perturbation, providing a scalable platform for dissecting tumor-host interactions. |
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| Single-cell multiomics data integration and generation with scPairing |
| Jeffrey Niu, Carlos Vasquez-Rios, Jiarui Ding |
| Niu et al. present scPairing, a deep learning tool facilitating the integration and generation of single-cell multiomics data through cell pairing. Pairing produces realistic multiomics data that can be used in downstream analyses to uncover relationships between cellular modalities. scPairing also extends to trimodal data generation. |
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| Benchmarking of human read removal strategies for viral and microbial metagenomics |
| Matthew Forbes, Duncan Y.K. Ng, Róisín M. Boggan, Andrea Frick-Kretschmer, Jillian Durham, Oliver Lorenz, Bruhad Dave, Florent Lassalle, Carol Scott, Josef Wagner, Adrianne Lignes, Fernanda Noaves, David K. Jackson, Kevin Howe, Ewan M. Harrison |
| Forbes et al. benchmark human read removal methods for viral and microbial metagenomics. Using synthetic and microbiome datasets, along with a set of benchmark methods, they demonstrate that a custom Bowtie2 configuration (“very-sensitive-local” mode with single end) with the T2T-CHM13 reference best balances host read removal and microbial integrity. |
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