Single-cell RNA sequencing, or scRNA-seq, is a powerful method that allows scientists to study the activity of individual cells. By looking at which genes are turned on or off in single cells, researchers can learn more about how the body responds to infection, disease, and development. But one major challenge with this technique is contamination from “ambient mRNA.” These are free-floating RNA molecules that do not belong to the cell being analyzed but end up getting captured during the sequencing process. This contamination can create misleading results and make it harder to draw accurate conclusions.

A team led by researchers at Queen Mary University of London explored how ambient mRNA affects single-cell data interpretation. They analyzed two large RNA sequencing datasets, one from dengue-infected patients and another from human fetal liver tissue. The researchers compared two correction tools, CellBender and SoupX, to clean up the data and remove the unwanted ambient signals.

Their results showed that before correction, ambient RNA could make it seem like certain genes or pathways were active in the wrong cell types. After correction, however, the false signals were reduced, allowing the analysis to highlight biologically meaningful pathways that were specific to the right cell populations.

Expression profiles of ambient mRNAs before and after correction

(A). UMAP plot representing the single-cell transcriptome profiles of PBMCs before (left panel) and after (right panel) ambient mRNA correction using CellBender. Cell types are annotated using Azimuth and supplemented with established canonical marker genes where relevant. (B). Violin plots showing the normalised transcription levels of the B cell-related genes in each of the non-B cell and B cell populations (comprising B cells and PCs), comparing between before and after ambient mRNA correction using CellBender

This work shows why correcting for ambient RNA is essential in single-cell research. By improving accuracy and reliability, it helps ensure that RNA sequencing delivers clear insights into how cells function in health and disease.