RNA, often called the “blueprint of life,” carries the instructions for building and operating living organisms. While much attention focuses on RNA inside cells, scientists have increasingly recognized “ambient RNA.” This free-floating genetic material exists in biological samples and is an important consideration in modern biological research, especially with advanced sequencing technologies.
Understanding Ambient RNA
Ambient RNA refers to RNA fragments freely suspended in a biological sample’s solution, not contained within intact cells. These fragments can include various types of RNA, such as messenger RNA (mRNA) and ribosomal RNA (rRNA), which are both components of a cell’s machinery. Think of it like dust particles floating in the air; biological samples contain intact cells alongside these unattached RNA molecules. These free-floating transcripts can be co-captured with cells during certain experimental procedures.
Where Ambient RNA Comes From
Ambient RNA can originate from several sources within a biological sample. A common source is cell lysis, where cells break open during sample preparation, releasing their RNA contents. This is prevalent when tissues are dissociated into single-cell suspensions.
Cells can also actively secrete RNA, sometimes within protective packages called extracellular vesicles. Environmental contamination can also introduce foreign RNA into a sample. Ambient RNA is found in various biological samples, including tissue biopsies and blood samples, which naturally contain cell-free RNA.
Why Ambient RNA Matters in Research
The presence of ambient RNA impacts advanced molecular biology techniques, such as single-cell RNA sequencing (scRNA-seq). In scRNA-seq, the goal is to measure gene expression within individual cells to understand cellular diversity. However, ambient RNA can contaminate the true gene expression profiles of cells, leading to inaccurate measurements.
This contamination introduces “noise” into the data, making it difficult to distinguish genuine biological signals from background interference. For example, if a less abundant cell type is contaminated by ambient RNA from a more abundant cell type, its true gene expression might be masked or misinterpreted. This can lead to incorrect cell type identification or biased results in experiments comparing gene expression between different conditions. In brain single-nuclei datasets, neuronal ambient RNA contamination can even cause misinterpretation and masking of cell types like glial cells.
How Scientists Address Ambient RNA
Scientists employ various strategies to detect, quantify, and reduce the effects of ambient RNA in their research. Experimental approaches involve careful sample handling to minimize cell lysis during preparation. For instance, optimizing tissue dissociation methods for specific cell types and tissues can help preserve cell integrity.
Computational methods play a large role in addressing ambient RNA after data collection. Software algorithms like SoupX, DecontX, and CellBender identify and statistically remove ambient RNA contamination from datasets. These tools often estimate the ambient RNA profile from “empty droplets” – reaction chambers with background RNA but no cells – and then use this information to correct the gene expression profiles of cell-containing droplets. While these methods are continuously improving, developing effective solutions for ambient RNA remains an active area of research.