Integrating Flow Cytometry and Single-Cell Transcriptomics

About the Presenter

Mario Roederer, PhD
Senior Investigator on the ImmunoTechnology Section
Chief on the Flow Cytometry Core
Chief on the Nonhuman Primate Immunogenicity Core

Webinar Summary

The immune system is comprised of incredibly diverse sets of cells, each programmed to carry out overlapping sets of effector functions. Quantifying any one function provides an incomplete view of the immune response, as information about what other responses are generated is absent. Quantifying multiple responses is far superior, but when carried out on a bulk level, loses information about cellular heterogeneity, gene programs, and a myriad of interactions that may occur at the single-cell level. Since individual cells are the atomic unit of immune function, the maximum information content is achievable only by measuring these functions independently and simultaneously on a cell-by-cell basis. For this reason, flow cytometry is a powerful technology to assess immune function in settings like vaccination and pathogenesis. Nonetheless, current flow cytometry technology is limited to measuring the expression of ~16 proteins per cell. To extend the multiplexing of gene expression measurements, we now combine single cell sorting (based on cell surface phenotype) with highly-multiplexed qPCR for 96 or more genes. We choose to quantify lymphocyte-centric genes, including those encoding transcription factors, signaling molecules, effect molecules, and regulatory molecules. On a single-cell basis, we can correlate protein expression with gene expression. Discordant results for the same gene reveal post-transcriptional regulatory mechanisms. We have identified gene signatures associated with vaccine-elicited T cells as well as with productively SIV-infected cells in vivo. This technology gives us an unprecedented view into the complexity and range of immunological functions expressed by vaccine or virus-specific immune cells. Using this approach, we can search for correlates of clinical outcome based on either: quantitative gene expression and/or cell subset representation enumerated by groups of cells sharing gene expression profiles. These analyses give us new insights into functional immune states in pathogenesis, treatment, and vaccination.

CMLE Credit: 1.0