Vanessa Peterson, Ph.D.
**Associate Principal Scientist, Merck **
Vanessa joined Merck in 2004 and her current research focuses on discovery and validation of drug targets and biomarkers using next generation sequencing technology. She received her Ph.D. from Massachusetts Institute of Technology in chemical engineering with a minor in biology, where her research focused on detection and molecular profiling of cancer cells, specifically looking at drug treatment response, inter-patient and intra-tumor heterogeneity.
In a recent paper in Nature Biotechnology, "Multiplexed quantification of proteins and transcripts in single cells," Peterson et al. describe REAP-seq, a new assay that allows users to measure both protein and gene expression on the same single-cell sample. We got the chance to talk to lead author, Vanessa Peterson, about the ideas behind REAP-seq, the possible applications of this new technique, and how 10x technology played a part in its development.
10x: How have high-throughput single-cell analysis technologies helped address the challenges of drug target discovery and validation?
VP: I think the recent advancements in single-cell analysis technologies that have made profiling thousands of cells possible have enabled us to obtain a more complete picture of cellular heterogeneity, while providing the statistical power to more confidently analyze less abundant cell types, and to determine which cell types and states are contributing to disease progression and therapeutic response.
10x: You are lead author on a recent Nature Biotechnology paper that introduces a new RNA expression and protein sequencing assay (REAP-seq) for multiplexed single-cell gene and protein quantification. What inspired the development of this technique?
VP: My graduate school research focused on developing proteomic assays with increased multiplexing capability for clinical samples with limited numbers of cells. With flow cytometry, we were unable to measure all the protein markers of interest due to the spectral overlap limitation of fluorescent antibody labels. This motivated me to develop a method using DNA-labeled antibodies to measure hundreds of protein markers using the NanoString platform as a readout. When I finished my PhD and joined the Genome Sciences group at Merck, I shifted focus to implementing methods for single-cell and low input RNA-seq. I started to think about how I could couple the unbiased approach of RNA-seq with a highly multiplexed proteomic approach using DNA-labeled antibodies like I worked on in graduate school. When emulsion based technologies for scRNA-seq were published, including Drop-Seq and InDrop, I became interested in adding a proteomic readout to this type of platform. 10x Genomics helped make this idea a reality by providing a commercial solution that allowed us to focus efforts on developing this novel REAP-seq method, instead of building and optimizing a custom emulsion-based device.
10x: What challenges did you face during the development of REAP-seq? How did the team overcome them?
VP: One of the biggest challenges was getting a bioinformatics pipeline in place to analyze the data, as there were no available pipelines designed for this type of multi-omics analysis. I worked closely with Kelvin Zhang in the Merck Informatics IT department, and he developed a custom pipeline to generate protein expression matrices and analyze this in conjunction with the gene expression data for each cell. Experimental iteration is very difficult if you don’t have the tools in place to analyze and interpret data quickly to enable you to design and execute the next experiment.
**10x: How did 10x technology enable or facilitate the development of REAP-seq? **
VP: The 10x Chromium™ platform provided an out-of-the-box solution that was easy to get up and running, allowing us to focus efforts on developing the REAP-seq assay. The quick responding and strong technical support team at 10x Genomics also facilitated getting their scRNA-seq emulsion-based platform and Cell Ranger™ pipeline up and running in-house smoothly.
10x: What future potential applications do you see for REAP-seq for drug discovery and beyond?
VP: I definitely think a potential application for REAP-seq will be profiling clinical samples from cancer patients pre- and post-treatment to obtain insight into the key cell types and signaling pathways involved in disease progression and response to treatment. This knowledge can then be used to help design more efficacious and personalized drug treatments for patients.
10x: What do you personally find most surprising or exciting or important about your work?
VP: Before REAP-seq we would split samples and run scRNA-seq and flow cytometry separately, and were faced with the bioinformatics challenge of trying to correlate and make inferences from these two different datasets run on different cells. Running two methods also required significantly more sample mass. With REAP-seq, we now have the advantage of measuring both protein and gene expression on the exact same cell. We found this provides a better overall picture of what is going on at the cellular level and helps identify cell types and states. We also found that the protein assay had the advantage of higher detection sensitivity for lowly expressed transcripts, and also enabled measurement of post-translation modifications that cannot be obtained at the transcriptional level. The unbiased approach of scRNA-seq is powerful for discovery work and can help identify novel targets, biomarkers, cell types and states that might not have been discovered with pre-specified panels of transcripts. So having both protein and mRNA readouts on one platform allows you to "reap" from the advantages of both.
10x: Your graduate research focused on cancer cell detection and molecular profiling. How do you see single-cell genomics helping to advance this field?
VP: I think single-cell genomics can help advance this field by providing a better understanding of the cellular heterogeneity in tumor samples and immune infiltrate. This ability can provide insights into the cell types driving response, or anergic cell types associated with the tumor. Ultimately, we want to relate cellular heterogeneity with therapeutic response or disease progression. Multi-omics readouts for single cells can help us: 1) develop novel therapeutic approaches, 2) personalize medicine by determining which patients will respond or not respond to a specific drug treatment and 3) identify novel targets for drug development and design rational drug combination therapies.
10x: Are there any other notable projects that you are currently working on or plan to start in the future that you think would benefit from 10x technology?
VP: We are currently looking at fixation methods compatible with the 10x platform that would enable us to extend REAP-seq to measure intracellular proteins and signaling pathways. We are also planning to modify the DNA-labeled antibodies in the REAP-seq platform to be compatible with the new 10x 5’ scRNA-seq platform that can be coupled with TCR and BCR repertoire sequencing to get all three different readouts per cell. Another potential extension of REAP-seq could be to add it to other single-cell genomic readouts such as point mutations and copy number variations.
Read the full article in Nature Biotechnology.