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Image-seq: spatially resolved single-cell sequencing guided by in situ and in vivo imaging

Medicine and Health

Image-seq: spatially resolved single-cell sequencing guided by in situ and in vivo imaging

C. Haase, K. Gustafsson, et al.

Explore the pioneering advancements in spatial and temporal understanding of tissue function through Image-seq technology, developed by leading researchers including Christa Haase and Karin Gustafsson. This innovative approach merges single-cell analysis with spatial organization, unveiling crucial insights in leukemia biology and beyond.

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~3 min • Beginner • English
Abstract
Tissue function depends on cellular organization. While the properties of individual cells are increasingly being deciphered using powerful single-cell sequencing technologies, understanding their spatial organization and temporal evolution remains a major challenge. Here, we present Image-seq, a technology that provides single-cell transcriptional data on cells that are isolated from specific spatial locations under image guidance, thus preserving the spatial information of the target cells. It is compatible with in situ and in vivo imaging and can document the temporal and dynamic history of the cells being analyzed. Cell samples are isolated from intact tissue and processed with state-of-the-art library preparation protocols. The technique therefore combines spatial information with highly sensitive RNA sequencing readouts from individual, intact cells. We have used both high-throughput, droplet-based sequencing as well as SMARTseq-v4 library preparation to demonstrate its application to bone marrow and leukemia biology. We discovered that DPP4 is a highly upregulated gene during early progression of acute myeloid leukemia and that it marks a more proliferative subpopulation that is confined to specific bone marrow microenvironments. Furthermore, the ability of Image-seq to isolate viable, intact cells should make it compatible with a range of downstream single-cell analysis tools including multi-omics protocols.
Publisher
Nature Methods
Published On
Nov 24, 2022
Authors
Christa Haase, Karin Gustafsson, Shenglin Mei, Shu-Chi Yeh, Dmitry Richter, Jelena Milosevic, Raphaël Turcotte, Peter V. Kharchenko, David B. Sykes, David T. Scadden, Charles P. Lin
Tags
Image-seq
cellular organization
single-cell sequencing
acute myeloid leukemia
temporal evolution
spatial information
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