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Grant Details

Grant Number: 1UG3CA257393-01 Interpret this number
Primary Investigator: Fan, Rong
Organization: Yale University
Project Title: High-Spatial-Resolution Ecm-Inclusive Multi-Omics Sequencing of Human Pfa and Ffpe Tissue Slides
Fiscal Year: 2020


Abstract

SUMMARY This project focuses on the accelerated development of a high-spatial-resolution sequencing technology for the co-mapping of transcriptomes and proteomes (hsrTP-seq) via deterministic barcoding in tissue, which will be validated with paraformaldehyde(PFA)-fixed and formalin-fixed paraffin-embedded (FFPE) human tissue specimens. This is a fundamentally new approach as compared to any existing spatial omics technologies. The core idea is to molecularly barcode RNAs, proteins, or other biomolecular information in tissues using a novel microfluidic in situ barcoding method. The tissue slide after barcoding remains morphologically intact but consists of a mosaic of tissue pixels, each of which has a distinct DNA barcode. The size of the pixels is as small as ~5-10μm, which is close to the size of individual cells. It is built upon the power of Illumina’s Next Generation Sequencing (NGS) systems to achieve significantly higher sample high-throughput, lower cost, and the elimination of laborious procedures for repeated single-molecule imaging as in seqFISH. It will demonstrate high-spatial-resolution (~5-10μm pixel size), high-throughput (up to 100 tissue samples flow barcoded per day per operator), and high-content (genome-wide mRNAs, proteins, and non-cellular environment). Using a panel of DNA-tagged antibodies against extracellular matrix (ECM) proteins, this approach further allows for spatial omics sequencing to include the mapping of non-cellular components, which are completely missing in scRNA- seq or current spatial transcriptomics technologies. It is uniquely suited for mapping human collagenous tissues including heart, aorta, skin, and kidney to improve our understanding of the role of ECM in normal physiology, disease and aging. We will pursue the following specific aims. In the UG3 phase, we will develop a set of new devices to significantly increase the tissue mapping area (4mmx4mm), develop a proteome-scale (~500 proteins co-analyzed) and ECM-inclusive spatial sequencing, and develop a novel tissue optimization protocol performed on the same tissue slide for hsrTP-seq, and generate a set of 3D spatial transcriptome- proteome atlas data from human heart or aorta. In the UH3 phase, we will further develop a multi-pin injection head to increase sample throughput (up to 100 samples per day) and the mapping area (1.2cmx1.2cm) for further scale up and automation, develop a new in-tissue template switching method to retain intact tissue section after hsrTP-seq for conducting other measurements on the same tissue slide and constructing 3D tissue atlas, and finally develop an optimized PFA and FFPE tissue protocol to generate the 3D multi-omics tissue atlas data (>20 tissue sections per sample) from the human heart, aorta, skin, and kidney.



Publications

Spatially Exploring RNA Biology in Archival Formalin-Fixed Paraffin-Embedded Tissues.
Authors: Bai Z. , Zhang D. , Gao Y. , Tao B. , Bao S. , Enninful A. , Zhang D. , Su G. , Tian X. , Zhang N. , et al. .
Source: bioRxiv : the preprint server for biology, 2024-02-08; , .
EPub date: 2024-02-08.
PMID: 38370833
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The technological landscape and applications of single-cell multi-omics.
Authors: Baysoy A. , Bai Z. , Satija R. , Fan R. .
Source: Nature reviews. Molecular cell biology, 2023 Oct; 24(10), p. 695-713.
EPub date: 2023-06-06.
PMID: 37280296
Related Citations

High-plex protein and whole transcriptome co-mapping at cellular resolution with spatial CITE-seq.
Authors: Liu Y. , DiStasio M. , Su G. , Asashima H. , Enninful A. , Qin X. , Deng Y. , Nam J. , Gao F. , Bordignon P. , et al. .
Source: Nature biotechnology, 2023 Oct; 41(10), p. 1405-1409.
EPub date: 2023-02-23.
PMID: 36823353
Related Citations

Spatial epigenome-transcriptome co-profiling of mammalian tissues.
Authors: Zhang D. , Deng Y. , Kukanja P. , Agirre E. , Bartosovic M. , Dong M. , Ma C. , Ma S. , Su G. , Bao S. , et al. .
Source: Nature, 2023 Apr; 616(7955), p. 113-122.
EPub date: 2023-03-15.
PMID: 36922587
Related Citations

Spatial profiling of chromatin accessibility in mouse and human tissues.
Authors: Deng Y. , Bartosovic M. , Ma S. , Zhang D. , Kukanja P. , Xiao Y. , Su G. , Liu Y. , Qin X. , Rosoklija G.B. , et al. .
Source: Nature, 2022 Sep; 609(7926), p. 375-383.
EPub date: 2022-08-17.
PMID: 35978191
Related Citations

Spatial-CITE-seq: spatially resolved high-plex protein and whole transcriptome co-mapping.
Authors: Liu Y. , DiStasio M. , Su G. , Asashima H. , Enninful A. , Qin X. , Deng Y. , Bordignon P. , Cassano M. , Tomayko M. , et al. .
Source: Research square, 2022-03-30; , .
EPub date: 2022-03-30.
PMID: 35378748
Related Citations

Spatial-CUT&Tag: Spatially resolved chromatin modification profiling at the cellular level.
Authors: Deng Y. , Bartosovic M. , Kukanja P. , Zhang D. , Liu Y. , Su G. , Enninful A. , Bai Z. , Castelo-Branco G. , Fan R. .
Source: Science (New York, N.Y.), 2022-02-11; 375(6581), p. 681-686.
EPub date: 2022-02-10.
PMID: 35143307
Related Citations

Spatial multi-omics sequencing for fixed tissue via DBiT-seq.
Authors: Su G. , Qin X. , Enninful A. , Bai Z. , Deng Y. , Liu Y. , Fan R. .
Source: STAR protocols, 2021-06-18; 2(2), p. 100532.
EPub date: 2021-05-11.
PMID: 34027489
Related Citations

High-Spatial-Resolution Multi-Omics Sequencing via Deterministic Barcoding in Tissue.
Authors: Liu Y. , Yang M. , Deng Y. , Su G. , Enninful A. , Guo C.C. , Tebaldi T. , Zhang D. , Kim D. , Bai Z. , et al. .
Source: Cell, 2020-12-10; 183(6), p. 1665-1681.e18.
EPub date: 2020-11-13.
PMID: 33188776
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