Correlating cause and consequence in single-cell systems

A look into the epigenetics and mechanisms of action behind cancer and therapy


Jan-Philipp Mallm, PhD, focuses on how to identify best treatment options for cancer patients

Jan-Philipp Mallm, PhD, works at the German Cancer Research Center (DKFZ), where he and colleagues are interested in how they can identify best treatment options for cancer patients by analyzing single-cell information. The center aims to generate a comprehensive understanding of cancer genome regulation, with the goal of encouraging novel approaches to personalized cancer treatment.

Single-cell sequencing techniques are at the heart of Mallm’s research as the head of DKFZ’s Open Lab for single-cell sequencing (scOpenLab), which provides single-cell sequencing technologies to DKFZ researchers.

In the quest to establish processes that decipher tumor heterogeneity using single-cell genomics, transcriptomics and epigenomics approaches, Mallm was driven to use the Fluidigm C1™ platform and solid-state microfluidic devices. “The C1 system allows us to explore single cells in depth, where we could not before, in a straightforward and easy-to-set-up, all-inclusive instrument,” Mallm explains. While several systems provide good overviews of a given sample, the DKFZ community is looking deeper in an effort to understand regulation and mechanisms in cell processes. The C1 platform provides this enhanced level of detail and the flexibility to optimize custom assays to obtain the highest sensitivity possible.

Applying the C1 platform to scATAC-seq and multi-omic cell characterization

Mallm is interested in correlating open chromatin regions, particularly for promoters, through single-cell analysis. Currently, he studies different types of leukemia to investigate possible common origins in the epigenome. Comparing samples could provide clues to how cancer types relate to one another and whether they contain variable cell populations. The lab also monitors reactions in embryonic stem cells when triggered by external stimuli. This study explores the types of mechanisms that are present in each cell, any differences from cell to cell, changes in gene activation and how this is all regulated with the stem cell state.

The ability to analyze single cells and specific cell populations sheds new light into processes within each cell and in cell-to-cell interactions. To accurately calculate correlations between chromatin regions in these types of samples, a high number of insertion points is necessary to infer which promoter is open and relevant for transcription regulation of a given gene. Mallm uses single-cell ATAC-seq prepared on C1 to ensure sensitive and accurate results—not easily accomplished with single-cell analysis on other systems.

Initially, the scOpenLab tested ATAC-seq on the C1 platform with a lower throughput integrated fluidic circuit (IFC), the C1 Single-Cell Open App™ IFC. With increasing demand and optimal results, the lab moved to the high-throughput (HT) IFC, the C1 Single-Cell mRNA Seq HT, which enabled significantly increased output and better comparisons between samples. “With the HT IFC, we can compare tumor malignancies, treated-to-untreated or malignant-to-non-malignant, on the same IFC. This helps to reduce bias from IFC to IFC and allows for direct comparison of two populations,” says Mallm.

For a multi-omics approach, C1 offers the potential to analyze proteins, RNA, the epigenome and the metabolome all on one platform instead of having separate platforms for each analysis, increasing reproducibility of experiments. The closed IFC system provides a large advantage over standard 96-well or 384-well plates, in which there is expected carryover, sample interaction and/or contamination. Furthermore, each well can be inspected to determine whether it contains a single cell or a doublet. Even an empty well offers additional data about experimental robustness as a built-in control.

With scATAC-seq, Mallm emphasizes the need for many insertion sites, which not every system can provide. With the growing interest in regulation and correlation within and between cells, the higher-level sensitivity of C1 is imperative. The DKFZ also uses C1 because the system can use frozen material, allowing for reuse of tumor samples that have already been analyzed and for deeper analysis of tumor heterogeneity and epigenetic differences from tumor to tumor or within the same tumor.

Deploying highly controlled perturbations, the team discovered that calcium responses are cell type-specific and change dynamically as stem cells differentiate to diverse types of neurons. Additionally, Mayer and her colleagues observed cellular diversity not captured by single-cell mRNA sequencing alone. For example, they found a specific serotonin receptor that selectively activates radial glia cells (a type of stem cell) in the developing human brain, but not the mouse brain. Further, inhibiting this receptor in the human brain disrupts the radial glial scaffold, a mechanism for new neurons to travel to their final destination. In the study, they also show neurotransmitter signaling during neurogenesis and highlight potential mechanisms in the evolution of physiological signaling.

When used in this way, the C1 system supports the characterization of cell populations and allows identification of mechanisms, where other instruments focus purely on cell type identification and signatures. “Many different approaches can identify cell types. But if you want to understand how the cell type is different epigenetically and driven by epigenetics, this is something only C1 can tell you and is something that is more and more of interest among the cancer research community,” asserts Mallm.

Polaris is the solution to enable researchers to understand the functional heterogeneity of cell populations characterized by single-cell mRNA sequencing.

Can current research shape future endeavors?

“Taking this to the next level, using the C1 platform could give us the opportunity to gather information from RNA, protein and chromatin in just one go from the same cell. Sensitivity becomes even more crucial to obtain an individual readout for each cell in a combined protocol. The C1 system and its microfluidics would help to achieve this goal.”

“This approach is highly versatile and could be used for pretty much any organ system in any biological question in mammalian cells. I think that a great next application would be to use a different intracellular indicator, for example, for pH levels,” she said. “I think it's one of these instruments that's very nice to have downstream of assessing single-cell transcriptomics studies—especially when you have a good hypothesis—that allows you to explore functional signaling pathways at the single-cell level.”

To generate a comprehensive overview that includes genotypic influence on the transcriptome, DNA must also come into play. Single-cell DNA analysis could assist in identifying driving mutations in a population and further exploration of a mutation in the same patient over time. This type of analysis could serve to determine whether treatment drives accumulation of mutations or if a mutation originally present in the starting population expands. The ability to detect this expansion before initiating treatment could help predict whether the treatment will be tolerated and ultimately successful.

With commitment among cancer researchers to guide development of individual treatments based on a better understanding of tumor evolution and cell behavior, Mallm would like to see single-cell sequencing taken to the clinic and to the patient. The community is motivated to find ways to improve treatment and prevention, and the use of single-cell analysis could drive this bench-to-bedside translation.




For Research Use Only. Not for use in diagnostic procedures.