Cell Reports Methods最新文献

DNA double-strand breaks (DSBs) are among the most genotoxic lesions. Investigating the cellular dynamics of repair factors during DSB repair requires methodologies that preserve both spatial and temporal information. Here, we describe a method for tracking repair progression over time at any desired genomic locus by combining DSB induction on the seconds timescale (very fast CRISPR) and genomic labeling using local genome denaturation (genome oligopaint via local denaturation fluorescence in situ hybridization [GOLDFISH]). Through protocol optimization to retain repair signatures such as γH2AX, p53-binding protein 1 (53BP1), and BRCA1, we show that the kinetics of DSB foci formation at nonrepetitive endogenous loci can be measured with minutes time resolution.

Mitochondria are central to cardiomyocyte function, and their spatial organization regulates nuclear signaling and gene transcription, holding potential for novel cardioprotective interventions. We developed a transmission electron microscopy platform optimized for resolving mitochondrial subpopulations and nuclear architecture in adult cardiomyocytes. This approach reliably captures longitudinal sections containing the center of the nucleus and perinuclear regions, enabling consistent imaging of subcellular nanostructures, assessment of pharmacological effects within the same organism, and visualization of extracellular vesicles carrying dysfunctional mitochondria. Integrated with an analysis workflow employing machine learning-based segmentation for annotation, the method allows automated quantification of mitochondrial and nuclear architecture and positioning. Using Drp1-deficient mice with impaired mitochondrial fission, we demonstrate this tool's ability to uncover nanoscale remodeling of mitochondria and nuclei under stress. Our platform overcomes challenges in electron microscopy analysis, providing a powerful resource to interrogate mitochondrial-nuclear dynamics in cardiac (patho)physiology. These insights will inform therapeutic targeting of bioenergetic failure.

Calcium fluorescence imaging enables us to investigate how individual neurons of live animals encode sensory input or drive specific behaviors. Extracting and interpreting large-scale neuronal activity from imaging data are crucial steps in harnessing this information. A significant challenge arises from uncorrectable tissue deformation, which disrupts the effectiveness of existing neuron segmentation methods. Here, we propose an open-source software, DynamicNeuronTracker (DyNT), which generates dynamic neuron masks for deforming and/or incompletely registered 3D calcium imaging data using patch-matching iterations. We demonstrate that DyNT accurately tracks densely populated neurons under positional jitters. DyNT also includes automated statistical analyses for interpreting neuronal responses to multiple sequential stimuli. We applied DyNT to analyze the responses of pheromone-sensing neurons in mice to controlled stimulation. We found that four bile acids and four sulfated steroids activated 15 subpopulations of sensory neurons with distinct combinatorial response profiles, revealing a strong bias toward detecting sulfated estrogen and pregnanolone.

Rapid, spatially controlled methods are needed to investigate RNA localization in bacterial cells. APEX2 proximity labeling was shown to be adaptable to rapid RNA labeling in eukaryotic cells and, through the fusion of APEX2 to different proteins targeted to diverse subcellular locations, has been useful to identify RNA localization in these cells. Therefore, we adapted APEX2 proximity labeling of RNA to bacterial cells by generating an APEX2 fusion to the ribonuclease (RNase) E gene, which is necessary and sufficient for bacterial ribonucleoprotein (BR)-body formation. APEX2 fusion is minimally perturbative, and RNA can be rapidly labeled on the sub-minute timescale with alkyne-phenol, outpacing the rapid speed of mRNA decay in bacteria. Alkyne-phenol provides flexibility in the overall application with copper-catalyzed click chemistry for downstream processes, such as fluorescent dye azides or biotin-azides for purification. Altogether, APEX2 proximity labeling of RNA provides a useful method for studying RNA localization in bacteria.

To detect precise DNA methylation patterns in long-read DNA sequencing analysis, an efficient target enrichment method is needed. In this study, we established t-nanoEM, a practical method that integrates a hybridization-based capture step into a long-read enzymatic methyl (EM)-seq library for nanopore sequencing. We achieved a high sequencing coverage of up to ×570 at 5 kb N50 in length. We applied this method to the long-read methylation analysis of cancers. Using breast cancer as an example, we demonstrated that the signature changes in DNA methylation occurring in local cell populations could be displayed in a haplotype-aware manner. In lung cancer, the spatial diversity in gene expression as detected by the spatial expression profiling analysis may be associated with changes in DNA methylation.

Spatial transcriptomics (ST) enables in situ analysis of gene expression patterns and spatial microenvironments. However, current ST technologies are limited by detection sensitivity and gene coverage, posing significant challenges for precise cell type annotation at the single-cell level. To address this, we present stTransfer, a method that integrates reference single-cell RNA sequencing (scRNA-seq) data with ST context using a graph autoencoder and transfer learning. This approach minimizes information transfer loss between scRNA-seq and ST datasets. Benchmark analyses on publicly available spatial transcriptomic datasets demonstrate that stTransfer outperforms existing methods in both accuracy and robustness for cell type annotation. Lastly, we apply stTransfer to annotate neuronal populations in a high-precision Stereo-seq dataset of the zebra finch optic tectum.

Hematoxylin and eosin (H&E) staining has been a standard in clinical histopathology for many decades but lacks molecular detail. Advances in multiplexed spatial proteomics imaging allow cell types and tissues to be annotated by their expression patterns as well as their morphological features. However, these technologies are at present unavailable in most clinical settings. In this work, we present a machine learning framework that leverages histopathology foundation models and paired H&E and spatial proteomic imaging data to enable enhanced cell type annotation on H&E-only datasets. We trained and evaluated our method on kidney datasets with paired H&E and spatial proteomic imaging data and found that models trained using our methods outperform models trained directly on the imaging data. We also show how our framework can be used to study biological differences between two major kidney diseases.

Cysteine oxidative modifications are critical signaling events regulating cellular functions, but their low abundance and dynamic nature pose technical challenges. We developed the SICyLIA-TMT workflow, which sequentially labels reduced and reversibly oxidized cysteines with light and heavy iodoacetamide (IAA) within the same sample. The inclusion of tandem mass tags (TMTs) enables simultaneous quantification of oxidative modification dynamics and protein levels across multiple conditions using micrograms of material. To improve the detection of low-abundance oxidized cysteines, a dedicated TMT channel serves as a carrier for heavy IAA-labeled peptides (SICyLIA-cTMT), enhancing quantification and enabling precise stoichiometry calculations. We demonstrate the workflow's applicability to cultured cells and full organs under stress. SICyLIA-cTMT achieves unprecedented depth and accuracy in redox proteome analysis while reducing mass spectrometry time. Combining SICyLIA-TMT with latest mass spectrometry technologies further halves the acquisition time without compromising coverage, improving throughput and enabling comprehensive studies of oxidative signaling.

Traumatic brain injury (TBI) is the leading environmental risk factor for neurodegenerative diseases, yet its molecular link to chronic neurodegeneration is unclear. While animal models of TBI are commonly used, emerging research suggests that induced pluripotent stem cell (iPSC)-derived brain organoids offer a promising human-specific alternative, particularly for studying processes like cryptic exon splicing. However, widespread use has been limited by methodological variability and the need for expensive and specialized equipment. To address these challenges, we developed a tabletop blast device capable of delivering highly reproducible pressure waves via a gravity-based pressure chamber. We validated the applicability of our approach by assessing the short- and long-term consequences of mechanical stress on brain organoids after pressure wave exposure. Our approach provides a controllable and reproducible method to apply complex pressure cycles on brain organoids, enabling broader accessibility for studying the mechanistic links between TBI and neurodegeneration in a human-relevant context.