The ability to specifically label proteins with a wide range of optical properties and functionalities can help reveal information about protein functions and dynamics in living cells. Here, we describe a technology for covalent tethering of organic probes directly to a specially designed reporting protein expressed in live cells. The reporting protein can be used in a manner similar to green fluorescent protein, except that the fluorophore might be interchanged among a variety of standard dyes. This allows living cells to be imaged at different wavelengths without requiring changes to the underlying genetic constructs, and the colors can be rapidly switched to allow temporal analysis of protein fate. The stability of the bond permits imaging of live cells during long time periods, imaging of fixed cells, and multiplexing with different cell/protein analysis techniques. The dyes can also be exchanged with other functional molecules, such as biotin to serve as an affinity handle, or even solid supports for direct covalent immobilization. The technology complements existing methods and provides new options for cell imaging and protein analysis.
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http://dx.doi.org/10.1385/1-59745-217-3:195 | DOI Listing |
Brief Bioinform
November 2024
State Key Laboratory of Digital Medical Engineering, School of Biological Science and Medical Engineering, Southeast University, 2 Sipailou, Xuanwu District, Nanjing 210096, China.
Spatial transcriptomics technologies have been extensively applied in biological research, enabling the study of transcriptome while preserving the spatial context of tissues. Paired with spatial transcriptomics data, platforms often provide histology and (or) chromatin images, which capture cellular morphology and chromatin organization. Additionally, single-cell RNA sequencing (scRNA-seq) data from matching tissues often accompany spatial data, offering a transcriptome-wide gene expression profile of individual cells.
View Article and Find Full Text PDFEur J Nucl Med Mol Imaging
January 2025
Department of Nuclear Medicine and PET Center, The Second Affiliated Hospital of Zhejiang University School of Medicine, 88 Jiefang Road, Hangzhou, Zhejiang, 310009, China.
Discov Oncol
January 2025
Department of Neurosurgery, Changde Hospital, Xiangya School of Medicine, Central South University (The First People's Hospital of Changde City), Changde, 415003, Hunan, China.
Purpose: Glioma is the most prevalent tumor of the central nervous system. The poor clinical outcomes and limited therapeutic efficacy underscore the urgent need for early diagnosis and an optimized prognostic approach for glioma. Therefore, the aim of this study was to identify sensitive biomarkers for glioma.
View Article and Find Full Text PDFNat Commun
January 2025
Bioinformatics and computational systems biology of cancer, Institut Curie, Inserm U900, PSL Research University, Paris, France.
Immunotherapy is improving the survival of patients with metastatic non-small cell lung cancer (NSCLC), yet reliable biomarkers are needed to identify responders prospectively and optimize patient care. In this study, we explore the benefits of multimodal approaches to predict immunotherapy outcome using multiple machine learning algorithms and integration strategies. We analyze baseline multimodal data from a cohort of 317 metastatic NSCLC patients treated with first-line immunotherapy, including positron emission tomography images, digitized pathological slides, bulk transcriptomic profiles, and clinical information.
View Article and Find Full Text PDFBone Res
January 2025
National Institute of Biological Sciences, Beijing (NIBS), 102206, Beijing, China.
Tissue clearing combined with high-resolution confocal imaging is a cutting-edge approach for dissecting the three-dimensional (3D) architecture of tissues and deciphering cellular spatial interactions under physiological and pathological conditions. Deciphering the spatial interaction of leptin receptor-expressing (LepR) stromal cells with other compartments in the bone marrow is crucial for a deeper understanding of the stem cell niche and the skeletal tissue. In this study, we introduce an optimized protocol for the 3D analysis of skeletal tissues, enabling the visualization of hematopoietic and stromal cells, especially LepR stromal cells, within optically cleared bone hemisections.
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