Cell hashing is a technique in single-cell genomics. It provides a method for uniquely labeling individual cells from different biological samples. This allows researchers to pool diverse samples and analyze them together in a single experiment. This approach improves efficiency and data quality in single-cell studies.
What is Cell Hashing?
Cell hashing uses unique molecular barcodes, typically DNA-tagged antibodies, to label cells from distinct samples before pooling for single-cell sequencing. This strategy enables “multiplexing,” running multiple samples simultaneously within a single experimental run. Without cell hashing, each sample would require its own separate, dedicated run, which is less efficient.
Cell hashing involves tagging cells with specific, identifiable labels. These labels, known as hashtag oligos (HTOs), attach to ubiquitously expressed cell surface proteins. By using different HTOs for each sample, researchers can mix the labeled cells, process them together, and then computationally sort them back into their original samples after sequencing. This contrasts with traditional methods where individual samples are processed in isolation, making cell hashing an advancement for high-throughput single-cell analysis.
Why Use Cell Hashing?
Cell hashing offers several advantages in single-cell sequencing. It increases experimental throughput by allowing a greater number of samples to be processed concurrently. This multiplexing capability also leads to cost reductions in single-cell sequencing experiments, as resources are shared across multiple samples.
Multiplexing with cell hashing improves data quality by minimizing batch effects, technical variations that can arise between different experimental runs. By processing multiple samples together, cell hashing ensures that all samples experience similar experimental conditions, leading to more accurate and comparable data.
Cell hashing also provides a method for identifying and removing “doublets” or “multiplets”—instances where two or more cells are mistakenly captured as one. Doublets can compromise downstream analysis by creating artificial cell populations, and cell hashing helps identify these occurrences, enhancing data integrity.
How Cell Hashing Works
Cell hashing relies on antibodies conjugated to unique DNA oligonucleotides, often referred to as hashtag oligos (HTOs). These antibodies bind to proteins commonly found on the surface of most cell types. Before pooling, cells from each distinct biological sample are stained with a specific combination of these barcode-conjugated antibodies.
Once stained, labeled cell samples are combined into a single mixture. This pooled sample then proceeds through a standard single-cell RNA sequencing workflow.
During the sequencing process, the unique DNA barcodes from the antibodies are captured and sequenced alongside the messenger RNA molecules from within each cell. This simultaneous capture of cellular RNA and sample-specific barcodes is important.
Following sequencing, computational methods analyze the data. These methods use the unique DNA barcodes to demultiplex reads, assigning each sequenced cell back to its original biological sample. This computational sorting allows researchers to determine which cells originated from which experimental condition or individual, despite being processed together. The integration of antibody-derived barcodes with cellular transcriptomes provides a way to track and analyze individual cells within a complex, multiplexed experiment.
Applications of Cell Hashing
Cell hashing is used across various fields of biological and medical research. In drug screening, it enables researchers to test multiple drug treatments or compounds simultaneously on different cell samples. This accelerates the discovery of potential therapeutic agents and allows for efficient comparison of cellular responses.
The technique is also used in immune cell profiling, facilitating the comparison of immune responses across different individuals or conditions. Researchers can analyze how diverse immune cell populations react to stimuli or disease states.
In developmental biology, cell hashing helps track cell lineages and understand cellular differentiation by distinguishing cells from different developmental stages or genetic backgrounds. This provides insights into complex biological processes.
In disease studies, cell hashing allows for detailed comparisons between healthy and diseased tissues or for characterizing cellular heterogeneity within tumors. This contributes to a deeper understanding of disease mechanisms and the identification of potential therapeutic targets.