Ansuman Satpathy, MD, PhD, is an Instructor in the Department of Pathology at Stanford University School of Medicine. As a postdoctoral fellow in Howard Chang’s lab, he studies immune system function and dysfunction in cancer patients. He spoke with Standard BioTools™ about developing genome sequencing methods, specifically his new transcript-indexed single-cell ATAC-seq (T-ATAC-seq) application available at Script Hub™ for pairing TCR-seq with ATAC-seq.

His research focuses on investigating single-cell and three-dimensional genome sequencing tools to study epigenetic regulation of tumor-specific T cells. Taking advantage of C1 flexibility, he used Script Builder™ software to develop the method for co-detecting two key cellular components: RNA and DNA. Satpathy highlighted the ability to flow any enzymes or chemistries to the C1 integrated fluidic circuit (IFC) inlets and then to the chamber. He pointed out that there is really no restriction to designing applications through Script Builder. “The key is that Script Builder software is easy to use,” he said. “You can design things in silico using computer modeling and then easily implement them in Script Builder.”

T-ATAC-seq application

A tool for analyzing epigenomic landscapes in clonal T cells, T-ATAC-seq has the potential to advance studies of T cell malignancy, immunity and immunotherapy. Satpathy—in collaboration with Naresha Saligrama, PhD; Jason Buenrostro, PhD; Mark Davis, PhD; and Howard Chang, MD, PhD, at Stanford University—developed the T-ATAC-seq app to sequence open chromatin sites in clonal T cells by combining targeted RNA sequencing and epigenomic sequencing. As an immunologist, he sought to pair ATAC-seq epigenome information with immune transcripts of interest. By pairing two pieces of information, he learned the sequence of the specific T cell receptor in each individual cell, and the epigenomic state of that cell.

Satpathy describes his combinatorial T-ATAC-seq method as an experimental pipeline integrating single-cell ATAC-seq with targeted TCR-seq in the same single cell. Applying T-ATAC-seq to clinical samples from T cell leukemia tissues enabled him to identify cancer clone-specific epigenomic signatures unobservable from ensemble measurements, demonstrating the value of T-ATAC-seq as a new tool for single-cell epigenomic characterization of T cells in research and future clinical applications.

Nature Medicine paper

In an April 2018 Nature Medicine paper entitled, “Transcript-indexed ATAC-seq for precision immune profiling,” Satpathy et al. describe how they combined single-cell T cell receptor (TCR) sequencing and an assay for transposase-accessible chromatin analysis to collect data on TCR specificity and the epigenomic state of individual T cells. In T cell leukemia patients, T-ATAC-seq enabled the researchers to identify leukemic and non-leukemic regulatory pathways in T cells from the same individual, separating signals arising from the malignant clone from background T cell noise.

T-ATAC-seq pairs epigenomic data with high-fidelity RNA sequence of TCR loci to provide a platform for multi-omic investigation of T cell diversity. Noting that they were able to define epigenomic signatures of clonal cancer cells missed by standard fluorescence-activated cell sorting-based (FACS) separation methods, the authors demonstrated the promise of this approach: “T-ATAC-seq represents an important technical advance towards achieving an atlas of human cell types and states in that it is able to generate genome-wide chromatin accessibility maps, while simultaneously preserving and measuring RNA sequence.”

The report characterizes T-ATAC-seq as complementary to approaches for unbiased identification of TCR ligands, enabling integration of T cell epigenomic state, TCR sequence and TCR ligands. Satpathy et al. concluded: “The application of this strategy to human diseases such as cancer and autoimmune disease, particularly in the context of immunotherapy, could be invaluable in generating comprehensive profiles of beneficial and harmful T cell responses, the regulatory networks underlying either response and the antigens that drive these networks.”

Publication findings

Satpathy et al. decided to study human T cells since it has been difficult historically to examine epigenetic states, particularly at the single-cell level in human tissues. After sorting different human CD4 T cell subtypes as defined by classical FACS markers, they used this single-cell method to gauge epigenetic variation. They found extensive variation within subtypes. For example, a small number of classically defined naive T cells—5% or 10%—look similar to subpopulations of memory or stem cell T cells. This supports prior findings suggesting that there might be a small population of stem memory cells that live in the FACS gate. The investigators reported identifying formal proof that on the epigenome-wide level, those cells had a distinct chromatin state within the rest of the naive cells.

“That’s one of the major findings we saw in healthy T cells,” Satpathy said. “In the last part of the paper we took that to a malignant T cell cancer setting where only a fraction of CD4 T cells represent the putative cancer clone. Now we can use this combined TCR-seq and ATAC-seq method to identify the epigenetic state of only the clonal cancer cells.”

Broad implications

“This method opens up a lot of possibilities in single-cell genomics, pairing different types of cellular information with epigenetic states,” Satpathy said. “We’re describing one application of TCR sequencing, but in the future, there are approaches such as CRISPR guide sequencing or other cell-identifying transcripts like B cell receptors or non-coding RNAs, marrying information from different systems and developing those technologies. That’s the immediate goal from the perspective of technology and development.”

Satpathy believes that researchers involved in Human Cell Atlas, Chan Zuckerberg Biohub and other similar consortiums also stand to benefit from this technology. “The Human Cell Atlas and CZ Biohub focus predominantly on single RNA-seq,” he said, “but looking at the epigenetic state using the methods we’ve developed in collaboration with [Standard BioTools], and other similar approaches, will be complementary and useful.”

Maximize the power of your single-cell analysis on the C1 system with access to the industry’s largest collection of single-cell genomics applications. Download the T-ATAC-seq script developed by Satpathy’s group, and find other innovative protocols on Script Hub for use with Open App™ IFCs to advance your single-cell studies.