Hematopoietic stem and progenitor cells (HSPCs) are known to respond to acute inflammation; however, little is understood about the dynamics and heterogeneity of these stress responses in HSPCs. Here, we performed single-cell sequencing during the sensing, response, and recovery phases of the inflammatory response of HSPCs to treatment (a total of 10,046 cells from four time points spanning the first 72 h of response) with the pro-inflammatory cytokine IFNα to investigate the HSPCs' dynamic changes during acute inflammation. We developed the essential novel computational approaches to process and analyze the resulting single-cell time series dataset. This includes an unbiased cell type annotation and abundance analysis post inflammation, tools for identification of global and cell type-specific responding genes, and a semi-supervised linear regression approach for response pseudotime reconstruction. We discovered a variety of different gene responses of the HSPCs to the treatment. Interestingly, we were able to associate a global reduced myeloid differentiation program and a locally enhanced pyroptosis activity with reduced myeloid progenitor and differentiated cells after IFNα treatment. Altogether, the single-cell time series analyses have allowed us to unbiasedly study the heterogeneous and dynamic impact of IFNα on the HSPCs.
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http://dx.doi.org/10.26508/lsa.202302309 | DOI Listing |
J Transl Med
January 2025
Division of Spine, Department of Orthopedics, Tongji Hospital affiliated to Tongji University, Tongji University School of Medicine, Shanghai, 200065, China.
Background: Ferroptosis and immune responses are critical pathological events in spinal cord injury (SCI), whereas relative molecular and cellular mechanisms remain unclear.
Methods: Micro-array datasets (GSE45006, GSE69334), RNA sequencing (RNA-seq) dataset (GSE151371), spatial transcriptome datasets (GSE214349, GSE184369), and single cell RNA sequencing (scRNA-seq) datasets (GSE162610, GSE226286) were available from the Gene Expression Omnibus (GEO) database. Through weighted gene co-expression network analysis and differential expression analysis in GSE45006, we identified differentially expressed time- and immune-related genes (DETIRGs) associated with chronic SCI and differentially expressed ferroptosis- and immune-related genes (DEFIRGs), which were validated in GSE151371.
Commun Biol
January 2025
Institute for Automation and Applied Informatics, Karlsruhe Institute of Technology, Eggenstein-Leopoldshafen, Germany.
Biomedical research increasingly relies on three-dimensional (3D) cell culture models and artificial-intelligence-based analysis can potentially facilitate a detailed and accurate feature extraction on a single-cell level. However, this requires for a precise segmentation of 3D cell datasets, which in turn demands high-quality ground truth for training. Manual annotation, the gold standard for ground truth data, is too time-consuming and thus not feasible for the generation of large 3D training datasets.
View Article and Find Full Text PDFBiophys Rep (N Y)
January 2025
UCLA-DOE Institute for Genomics and Proteomics, Department of Biological Chemistry, University of California at Los Angeles, Los Angeles, CA 90095, USA,; Department of Chemistry and Biochemistry, University of California at Los Angeles, Los Angeles, CA 90095, USA,; Department of Physiology, University of California at Los Angeles, Los Angeles, CA 90095, USA,; California Nano Systems Institute, University of California at Los Angeles, Los Angeles, CA 90095, USA,; Department of Physics, Institute for Nanotechnology and Advanced Materials, Bar-Ilan University, Ramat-Gan 52900, Israel.
Membrane potential (MP) changes can provide a simple readout of bacterial functional and metabolic state or stress levels. While several optical methods exist for measuring fast changes in MP in excitable cells, there is a dearth of such methods for absolute and precise measurements of steady-state membrane potentials (MPs) in bacterial cells. Conventional electrode-based methods for the measurement of MP are not suitable for calibrating optical methods in small bacterial cells.
View Article and Find Full Text PDFCancers (Basel)
December 2024
Division of Hematology/Oncology, Department of Internal Medicine, University of California Davis School of Medicine, University of California Davis Comprehensive Cancer Center, Sacramento, CA 95817, USA.
Patient-centered precision oncology strives to deliver individualized cancer care. In lung cancer, preclinical models and technological innovations have become critical in advancing this approach. Preclinical models enable deeper insights into tumor biology and enhance the selection of appropriate systemic therapies across chemotherapy, targeted therapies, immunotherapies, antibody-drug conjugates, and emerging investigational treatments.
View Article and Find Full Text PDFInt J Mol Sci
December 2024
Laboratory of Molecular Oncology and Innovative Therapies, Military Institute of Medicine National Research Institute, 128 Szaserów Street, 04-141 Warsaw, Poland.
Advancements in single-cell analyzis technologies, particularly single-cell RNA sequencing (scRNA-seq) and Fluorescence-Activated Cell Sorting (FACS), have enabled the analyzis of cellular diversity by providing resolutions that were not available previously. These methods enable the simultaneous analyzis of thousands of individual transcriptomes, facilitating the classification of cells into distinct subpopulations, based on transcriptomic differences, adding a new level of complexity to biomolecular and medical research. Fibroblasts, despite being one of the most abundant cell types in the human body and forming the structural backbone of tissues and organs, remained poorly characterized for a long time.
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