Spatially resolved RNA and protein molecular analyses have revealed unexpected heterogeneity of cells. Metabolic analysis of individual cells complements these single-cell studies. Here, we present a three-dimensional spatially resolved metabolomic profiling framework (3D-SMF) to map out the spatial organization of metabolic fragments and protein signatures in immune cells of human tonsils. In this method, 3D metabolic profiles were acquired by time-of-flight secondary ion mass spectrometry to profile up to 189 compounds. Ion beams were used to measure sub-5-nanometer layers of tissue across 150 sections of a tonsil. To incorporate cell specificity, tonsil tissues were labeled by an isotope-tagged antibody library. To explore relations of metabolic and cellular features, we carried out data reduction, 3D spatial correlations and classifications, unsupervised K-means clustering, and network analyses. Immune cells exhibited spatially distinct lipidomic fragment distributions in lymphatic tissue. The 3D-SMF pipeline affects studying the immune cells in health and disease.
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http://dx.doi.org/10.1126/sciadv.abd0957 | DOI Listing |
Structure
January 2025
Structural Studies Division, MRC Laboratory of Molecular Biology, Cambridge CB2 0QH, UK. Electronic address:
In a recent issue of Nature Methods, Pfeil-Gardiner et al. (2024) combine electron energy-loss spectroscopy and single-particle cryoelectron microscopy to allow the spatially resolved imaging of the elemental composition of macromolecules.
View Article and Find Full Text PDFBMC Genomics
January 2025
Peking University Institute of Advanced Agricultural Sciences, Shandong Laboratory of Advanced Agriculture Sciences in Weifang, Weifang, Shandong, 261325, China.
Background: The evolution and development of flowers are biologically essential and of broad interest. Maize and sorghum have similar morphologies and phylogeny while harboring different inflorescence architecture. The difference in flower architecture between these two species is likely due to spatiotemporal gene expression regulation, and they are a good model for researching the evolution of flower development.
View Article and Find Full Text PDFNat Commun
January 2025
Center for Computational Biology, Whiting School of Engineering, Johns Hopkins University, Baltimore, MD, USA.
Spatially resolved omics (SRO) technologies enable the identification of cell types while preserving their organization within tissues. Application of such technologies offers the opportunity to delineate cell-type spatial relationships, particularly across different length scales, and enhance our understanding of tissue organization and function. To quantify such multi-scale cell-type spatial relationships, we present CRAWDAD, Cell-type Relationship Analysis Workflow Done Across Distances, as an open-source R package.
View Article and Find Full Text PDFProc Natl Acad Sci U S A
January 2025
Institute of Optical Materials and Chemical Biology, Guangxi Key Laboratory of Electrochemical Energy Materials, School of Chemistry and Chemical Engineering, Guangxi University, Nanning 530004, Guangxi, People's Republic of China.
Monitoring subcellular organelle dynamics in real time and precisely assessing membrane heterogeneity in living cells are very important for studying fundamental biological mechanisms and gaining a comprehensive understanding of cellular processes. However, there remains a shortage of effective tools for these purposes. Herein, we propose a strategy to develop the exchangeable water-sensing probeAPBD for time-lapse imaging of dynamics in cellular membrane-bound organelle morphology with structured illumination microscopy at the nanoscale.
View Article and Find Full Text PDFSci Adv
January 2025
Department of Physics, University of Arizona, Tucson, AZ 85721, USA.
Excitons, which are Coulomb bound electron-hole pairs, are composite bosons and thus at low temperature can form a superfluid state with a single well-defined amplitude and phase. We directly image this macroscopic exciton superfluid state in an hBN-separated MoSe-WSe heterostructure. At high density, we identify quasi-long-range order over the entire active area of our sample, through spatially resolved coherence measurements.
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