Science Spotlight

Single-cell CUT&Tag to identify cell states in normal and disease tissue

From Anoop P. Patel (NE Affiliate Investigator, Human Biology), the Furlan Lab (Clinical Research Division), and the Henikoff Lab (Basic Sciences Division)

Genes turning “on” and “off”’ during development is key for cell lineage determination. The signal to switch off gene expression on delineated genomic regions is a chromatin modification: trimethyl lysine 27 of histone H3 (H3K27me3). This histone modification is the mark for polycomb group (PcG) proteins to silence gene expression. Faults in PcG-mediated silencing result in abnormal gene expression and disease, which has prompted the development of a toolbox of methods to profile chromatin landscapes. The Cleavage Under Targets and Tagmentation (CUT&Tag) method recently developed in the Henikoff Lab, was shown to provide a low-cost and efficient alternative to chromatin profiling that overcomes the limitations of earlier techniques, such as ChIP-seq and CUT&RUN. Unlike its predecessor, CUT&Tag is suitable for single cell chromatin profiling – a long-standing challenge in the field of genomics.

In new research from a multi-division, Cancer Consortium collaboration between the Human Biology (Affiliate Professor Dr. Anoop P. Patel), Basic Sciences (Henikoff Lab), and Clinical Research (Furlan Lab) Divisions, the CUT&Tag method was adapted to profile chromatin landscapes in single cells from a variety of tissues, including differentiating human embryonic stem cells (hESCs), peripheral blood mononuclear cells (PMBCs), and a set glioblastoma biopsies. Single-cell CUT&Tag (scCUT&Tag) can successfully identify dynamic changes in chromatin silencing and distinguish cell types in heterogenous tissues. To profile silenced regions in single cells, scCUT&Tag was performed using an antibody to target the H3K27me3 modification. Cell mixtures were loaded into nanowell-based or droplet-based single-cell platforms for deep sequencing. The study is now published in the journal Nature Biotechnology.

Single-cell CUT&Tag to identify cell states in normal and disease tissue
Single-cell CUT&Tag to identify cell states in normal and disease tissue Image from publication.

To profile silenced regions by CUT&Tag, an antibody against H3K27me3 is incubated with permeabilized, intact cells. Then, a secondary antibody is added, in order to increase the total number of antibodies (containing Fc regions) bound to each chromatin site. Once the excess antibody has been removed, cells are treated with Protein A-transposase (pA-Tn5) fusion protein loaded with sequencing adapters. Protein A adheres to the pre-bound antibody Fc regions, while the hyperactive transposase reacts with exposed DNA and can be activated by adding magnesium ions to “cut and paste” integrating adapters flanking sites of H3K27me3-containing nucleosomes. The tagged DNA fragments can be then used for library construction and deep sequencing.  An advantage of CUT&Tag over other chromatin profiling methods is that the entire reaction from antibody binding to adapter integration occurs within intact cells. Importantly, the transposase and chromatin fragments remain bound together and do not escape the nucleus. Thus, chromatin profiles for single cells can be generated by loading the cell mixture into the nanowell-based ICELL8 system or the droplet-based 10x Genomics microfluidics platform, which allow for PCR enrichment of DNA libraries from individual cells.

The investigators first sought to determine if single-cell chromatin landscapes were sufficient to distinguish different cell types using single-cell clustering based on H3K27me3 signal. Wu and colleagues performed CUT&Tag on human embryonic stem cells (hESCs) using an anti-H3K27me3-specific antibody and then distributed single cells for PCR library enrichment in the ICELL8 system. They compared their results to previously published H3K27me3 scCUT&Tag profiles of a leukemia cell line (K562) and hESCs. Using uniform manifold approximation (UMAP) embedding and ArchR, a software package for single-cell chromatin analysis, the investigators observed clear separation between cell types driven by differences in H3K27me3 signal.

To demonstrate that this method can profile developmental systems, the investigators looked at gene silencing during development by inducing differentiation of hESCs toward an endoderm lineage using growth factors. scCUT&Tag H3K27me3 performed in samples across 5 days post-treatment revealed dynamic changes in chromatin silencing. As differentiation progressed, endoderm markers became active and lost the H3K27me3 signal. In general, the H3K27me3 signal at marker genes inversely correlated with expression, based on published single-cell RNA sequencing datasets. Next, the investigators adapted scCUT&Tag to the 10x Genomics microfluidics platform to profile H3K27me3 in mixed peripheral blood mononuclear cells (PBMCs) collected from two healthy donors. In order to identify the major cell types in the data, the group used publicly available bulk H3K27me3 chromatin immunoprecipitation followed by sequencing (ChIP-seq) data to project the UMAP embedding generated by scCUT&Tag and used a chromatin silencing score (CSS) to identify cell-type-specific marker genes. The scCUT&Tag cluster identification by CSS successfully distinguished major cell types in unsorted PBMCs.

Finally, the group used the 10x scCUT&Tag workflow in glioblastoma biopsies from a primary sample and a matched relapse sample obtained 5 months after surgery and radiation therapy to distinguish cell types in a tumor cell cluster and determine how tissue composition changes with treatment. "In our single-cell data we observed some cells profiled resembled a stem-like state," Dr. Wu said. "This is consistent with idea that tumor evolution might induce a proneural-to-mesenchymal shift. This is cool because this would explain why so many GBMs are recurrent."

Dr. Wu credited his co-author for envisioning this project. "Two years ago, one of my in-lab mentors and co-authors (Dr. Hatice) talked about making scCUT&Tag a routine epigenome profiling procedure for clinical applications in a Fred Hutch Spotlight," he said. "I’m glad we could make it happen. I’m thrilled to see all the new findings scientist will make when they apply scCUT&Tag to their biological systems/questions."

This work was supported by grants from the Howard Hughes Medical Institute, grants from the National Institutes of Health, a Seed Network grant from the Chan-Zuckerberg Initiative, a Burroughs Wellcome Career Award for Medical Scientists and an American Cancer Society Mentored Scholar Award.

Fred Hutch/UW Cancer Consortium members Steven Henikoff, Raphael Gottardo, Patrick J Cimino, and Scott Furlan contributed to this study. 

Wu, S. J., Furlan, S. N., Mihalas, A. B., Kaya-Okur, H. S., Feroze, A. H., Emerson, S. N., Zheng, Y., Carson, K., Cimino, P. J., Keene, C. D., Sarthy, J. F., Gottardo, R., Ahmad, K., Henikoff, S., & Patel, A. P. (2021). Single-cell CUT&Tag analysis of chromatin modifications in differentiation and tumor progression. Nature biotechnology, 10.1038/s41587-021-00865-z. Advance online publication. https://doi.org/10.1038/s41587-021-00865-z

Tags

There are no tags on this page. A list of tags will appear here once there are.