Method Makes Large-Scale Single-Cell RNA Analysis More Accessible and Affordable

Scientists from St. Jude Children’s Research Hospital, the National Center for Genomic Analysis, and the University of Adelaide have developed a new technique called Single-Cell Transcriptomics Analysis and Multimodal Profiling through Imaging (STAMP) to address the high costs and limitations of single-cell RNA sequencing. Published in Cell, this method combines microscopy with single-cell RNA analysis, enabling the study of millions of individual cells at a fraction of the usual expense.

According to Jasmine Plummer, co-corresponding author, “It’s an order of magnitude more cost-effective and allows us to profile a million cells simultaneously, compared to tens of thousands typical of current methods, making it far more scalable.” The process involves separating cells from tissues, fixing them onto microscope slides, and then using molecules that fluoresce when bound to specific RNA sequences. This approach preserves both the shape and gene expression profile of each cell.

The researchers found that STAMP could characterize a wide variety of immune cells and distinguish between developmental stages of induced pluripotent stem cells. They estimated that analyzing immune cells from 1,000 individuals would cost $3.56 million with traditional methods, but only $75,000 using STAMP—a 47-fold reduction.

STAMP also addresses biases present in conventional single-cell RNA sequencing, which often favors spherical cells and can miss irregularly shaped types like neurons. Since STAMP is performed on slides, it avoids this shape-based bias and captures more diverse cell populations. The method maintained high sensitivity, detecting just two cancer cells among approximately 850,000 on a single slide.

Plummer noted, “Being able to profile a million cells is crucial because it only takes one cell to escape cancer treatment. We’ve shown STAMP allows us to visualize and detect these cells in a numerically advantageous and accessible way, an important feature for potential future development into clinical applications.”