Positional influence on cellular transcriptional identity revealed through spatially segmented single-cell transcriptomics

被引：5
作者：
Morse, David B. [1 ,2 ,3 ,4 ]
Michalowski, Aleksandra M. [5 ]
Ceribelli, Michele [2 ]
De Jonghe, Joachim [6 ]
Vias, Maria [7 ]
Riley, Deanna [8 ]
Davies-Hill, Theresa [8 ]
Voss, Ty [2 ]
Pittaluga, Stefania [8 ]
Muus, Christoph [3 ,4 ]
Liu, Jiamin [9 ]
Boyle, Samantha [7 ]
Weitz, David A. [3 ,10 ]
Brenton, James D. [7 ]
Buenrostro, Jason D. [11 ]
Knowles, Tuomas P. J. [1 ,12 ]
Thomas, Craig J. [2 ,13 ]
机构：
[1] Univ Cambridge, Dept Phys, Cavendish Lab, JJ Thomson Ave, Cambridge, England
[2] NIH, Div Preclin Innovat, Natl Ctr Adv Translat Sci, Bethesda, MD 20814 USA
[3] Harvard Univ, John A Paulson Sch Engn & Appl Sci, Cambridge, MA USA
[4] Broad Inst MIT & Harvard, Cambridge, MA USA
[5] NCI, Lab Canc Biol & Genet, NIH, Bethesda, MD USA
[6] Univ Cambridge, Dept Biochem, Cambridge, England
[7] Li Ka Shing Ctr, Cambridge Res Inst, Canc Res UK, Robinson Way, Cambridge, England
[8] NCI, Lab Pathol, NIH, Bethesda, MD USA
[9] NIH, Adv Imaging & Microscopy Resource, Clin Ctr, Bethesda, MD USA
[10] Harvard Univ, Dept Phys, Cambridge, MA USA
[11] Harvard Univ, Dept Stem Cell & Regenerat Biol, Cambridge, MA USA
[12] Univ Cambridge, Dept Chem, Lensfield Rd, Cambridge, England
[13] NCI, Lymphoid Malignancies Branch, NIH, Bethesda, MD 20814 USA
来源：
CELL SYSTEMS | 2023年 / 14卷 / 06期
基金：
英国惠康基金; 欧洲研究理事会; 英国生物技术与生命科学研究理事会;
关键词：
GENOME-WIDE EXPRESSION; RNA-SEQ DATA; OVARIAN-CANCER; GENE-EXPRESSION; TISSUE; SPHEROIDS; CULTURE; RECONSTRUCTION; VISUALIZATION; HETEROGENEITY;
D O I：
10.1016/j.cels.2023.05.003
中图分类号：
Q5 [生物化学]; Q7 [分子生物学];
学科分类号：
071010 ; 081704 ;
摘要：
Single-cell RNA sequencing (scRNA-seq) is a powerful technique for describing cell states. Identifying the spatial arrangement of these states in tissues remains challenging, with the existing methods requiring niche methodologies and expertise. Here, we describe segmentation by exogenous perfusion (SEEP), a rapid and integrated method to link surface proximity and environment accessibility to transcriptional identity within three-dimensional (3D) disease models. The method utilizes the steady-state diffusion kinetics of a fluorescent dye to establish a gradient along the radial axis of disease models. Classification of sample layers based on dye accessibility enables dissociated and sorted cells to be characterized by transcriptomic and regional identities. Using SEEP, we analyze spheroid, organoid, and in vivo tumor models of high-grade serous ovarian cancer (HGSOC). The results validate long-standing beliefs about the relationship between cell state and position while revealing new concepts regarding how spatially unique microenvironments influence the identity of individual cells within tumors.
引用
收藏
页码：464 / +
页数：26
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