Spatial-omics: Novel approaches to probe cell heterogeneity and extracellular matrix biology

被引:62
作者
Bingham, Grace C. [1 ]
Lee, Fred [2 ]
Naba, Alexandra [2 ,3 ]
Barker, Thomas H. [1 ]
机构
[1] Univ Virginia, Dept Biomed Engn, 415 Lane Rd, Charlottesville, VA 22903 USA
[2] Univ Illinois, Dept Physiol & Biophys, 835 S Wolcott Ave, Chicago, IL 60612 USA
[3] Univ Illinois, Chicago Canc Ctr, Chicago 835 S Wolcott Ave, Chicago, IL 60612 USA
基金
美国国家卫生研究院;
关键词
Spatial transcriptomics; spatial proteomics; matrisome; fibrosis; multiplex imaging; IDIOPATHIC PULMONARY-FIBROSIS; MESSENGER-RNA; GENE-EXPRESSION; SUBCELLULAR RESOLUTION; PROTEOMIC ANALYSIS; MASS-SPECTROMETRY; SINGLE; TISSUE; TRANSCRIPTOMICS; PROTEIN;
D O I
10.1016/j.matbio.2020.04.004
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
Complex intercellular interactions as well as biomolecular and biomechanical cues from the extracellular matrix (ECM) profoundly affect cellular functions. Traditional transcriptomic and proteomic approaches have provided insight into disease progression by identifying discrete cellular subpopulations or microenvironmental signatures characteristic of normal or pathological tissues, however these techniques do not examine how a given cellular state relates to its interactions with neighboring cells or its surrounding ECM with multipara-metric characterization (i.e. ECM alignment, mechanical forces, crosslinking, etc.). Emerging spatialomic techniques can provide high-resolution mapping of expression profiles similar to scRNA-seq and mass spectroscopy directly within tissues. The ability to preserve the spatial context of cells within samples, their cellular geometry, as well as their surrounding ECM gives spatial-omics the opportunity to interrogate previously unexplored signaling modalities, which has the potential to revolutionize ECM research and our understanding of fibrotic diseases. In this review, we present current spatial transcriptomic and proteomic techniques and discuss how they may be applied to investigate cell-ECM interactions. (c) 2020 Elsevier B.V. All rights reserved.
引用
收藏
页码:152 / 166
页数:15
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