title: NSOM/QD-based fluorescence-topographic image fusion directly reveals nano-spatial peak-valley polarities of CD69 and CD71 activation molecules on cell-membrane fluctuations during T-cell activation.
abstract: Nano-spatial distribution of cell surface molecules on cell membrane fluctuations during T-cell activation has not been reported. In this study, we innovated application of near-field scanning optical microscopy (NSOM)/quantum dots (QDs)-based nanotechnology through three-dimensional image fusion algorithm to merge the simultaneously obtained dual-color fluorescence information and three-dimensional topography. This novel imaging system made it possible to visualize nano-spatial distribution and organization of early-activation molecules CD69 and late-activation molecules CD71 on cell-membrane fluctuations during T-cell activation. Interestingly, most CD69 molecules were clustered to form 250-500nm nano-domains polarizing predominantly in the peak of the cell-membrane fluctuations. In contrast, although CD71 molecules were also clustered as 250-500nm nano-domains, they polarized dominantly in the valley of the cell-membrane fluctuations. The peak-valley polarities of CD69 nano-domains and CD71 nano-domains implied their different functions. CD69 nano-domains polarizing on membrane-peak fluctuations might serve as transient platforms driving TCR/CD3-induced signaling and activation, whereas CD71 nano-domains distributing in the membrane-valley fluctuations appeared to facilitate iron uptake for increased metabolisms in T-cell activation. Importantly, this NSOM/QD-based fluorescence-topographic image fusion provides a powerful tool to visualize nano-spatial distribution of cell-surface molecules on cell-membrane fluctuations and enable better understanding of distribution-function relationship.
authors.affiliation: Department of Microbiology & Immunology, Center for Primate Biomedical Research, University of Illinois College of Medicine at Chicago, Chicago, IL 60612, United States. zhongly@scnu.edu.cn
authors.forename: Liyun
authors.initials: L
authors.lastname: Zhong
authors.forename: Zhun
authors.initials: Z
authors.lastname: Zhang
authors.forename: Xiaoxu
authors.initials: X
authors.lastname: Lu
authors.forename: Dan
authors.initials: D
authors.lastname: Huang
authors.forename: Crystal Y
authors.initials: CY
authors.lastname: Chen
authors.forename: Richard
authors.initials: R
authors.lastname: Wang
authors.forename: Zheng W
authors.initials: ZW
authors.lastname: Chen
mesh_terms: D000818:Animals; D015703:Antigens, CD / Q000378:metabolism* / Q000648:ultrastructure; D000945:Antigens, Differentiation, T-Lymphocyte / Q000378:metabolism* / Q000648:ultrastructure; D016764:Cell Polarity / Q000276:immunology; D022081:Cell Surface Extensions / Q000378:metabolism* / Q000648:ultrastructure; D019084:Fluorescent Antibody Technique, Indirect; D006801:Humans; D021621:Imaging, Three-Dimensional; D037181:Lectins, C-Type / Q000378:metabolism* / Q000648:ultrastructure; D008213:Lymphocyte Activation; D008253:Macaca mulatta; D021962:Membrane Microdomains / Q000648:ultrastructure; D018613:Microscopy, Confocal; D036103:Nanotechnology; D045663:Quantum Dots; D011940:Receptor Aggregation / Q000276:immunology; D011990:Receptors, Transferrin / Q000378:metabolism* / Q000648:ultrastructure; D013601:T-Lymphocytes / Q000378:metabolism* / Q000648:ultrastructure; D013997:Time Factors; D000099192:CD69 Antigens
chemical_list: D015703:Antigens, CD; D000945:Antigens, Differentiation, T-Lymphocyte; D037181:Lectins, C-Type; D011990:Receptors, Transferrin; D000099192:CD69 Antigens; C068126:CD71 antigen