Antibody-oligonucleotide conjugates are seeing increased utility across a multitude of applications. Among these, one of the most powerful is CITE-seq (cellular indexing of transcriptomes and epitopes by sequencing), a method developed at the New York Genome Center’s (NYGC) Technology Innovation Lab to produce a sequenceable readout from an antibody. By allowing researchers to simultaneously generate single-cell proteomic and transcriptomic data, CITE-seq has transformed the study of complex cell populations.
Accelerating this research, TotalSeq™ reagents are BioLegend’s brand of antibody-oligonucleotide conjugates for CITE-seq. Designed for use with multiple single-cell sequencing platforms, TotalSeq™ can identify novel cell types and shed new light on previously unseen events. Adnan Y. Chowdhury, Ph.D., BioLegend’s proteogenomics product manager, explained to us the benefits of using TotalSeq™ for single-cell research.
Used to identify different cell subsets within a complex population, flow cytometry is limited by the number of fluorescent molecules that can be combined in a single experiment, in most cases as an antibody conjugate. In contrast, single-cell RNA sequencing (scRNA-seq) is not constrained by antibody reagents or fluorescent parameters, instead capturing cell subset information by reporting the transcriptomic profiles of individual cells. Yet scRNA-seq struggles to differentiate cells that are transcriptomically similar, highlighting the need for an alternative approach capable of distinguishing more cell types while at the same time comparing their transcriptomes.
“By replacing fluorophore-tagged antibodies with TotalSeq™ antibody-oligonucleotide conjugates, CITE-seq improves on the advantages of both flow cytometry and scRNA-seq,” reports Chowdhury. “With CITE-seq, researchers can use hundreds of antibodies simultaneously, significantly speeding up the search for unique markers that identify cells of interest. Moreover, the replacement of fluorophore tags with oligonucleotide barcodes allows for rapid conversion of target detection into detailed information, enabling observation of protein changes between single cells along with the transcriptome. Since protein and RNA expression don’t necessarily correlate, studying both in conjunction can deliver far greater insight into different cell types and states than either flow cytometry or scRNA-seq alone.”
Figure 1. Illustration of the original TotalSeq™-A conjugate. CITE-seq uses DNA-barcoded antibodies to convert detection of proteins into a quantitative, sequenceable readout.
“One of the main reasons that the analysis of scRNA-seq data is challenging is the high incidence of dropouts,” explains Chowdhury. “These are essentially false negative readouts that arise when the mRNA transcripts indicate moderate expression of a gene in one cell, but no expression at all in another cell of the same type. Dropout rates are increased by low gene expression and are a result of inefficient mRNA capture. By using TotalSeq™ antibody-oligonucleotide conjugates to capture proteins as an alternative to capturing mRNA, dropout rates can be considerably reduced.”
Figure 2. Reduced dropout rate of TotalSeq™ antibody-derived signal. Clustering of 5,000 CITE-seq single-cell expression profiles of PBMCs reveals distinct cell populations based on transcriptome analysis. The left panel shows global gene expression relationships among all cells, and major cell types separated based on gene expression as indicated. The panels on the right show mRNA (blue) and corresponding ADT (green) signal. Data generously provided by Marlon Stoeckius, Senior Research Scientist, New York Genome Center.
According to Chowdhury, reducing dropout rates allows researchers to benefit from improved sample clustering to more accurately identify cell populations. “CITE-seq data can be represented in flow-like biaxial plots but with much higher resolution clustering,” he says. “By incorporating both immunophenotyping and transcriptome analysis within the same experiment, distinct cell populations can be revealed that may have previously been undetectable by flow cytometry or scRNA-seq alone. We’ve successfully demonstrated in-house the combined use of over 200 TotalSeq™ antibody-oligonucleotide conjugates within a single experiment, observing no sign of an upper limit. This highlights the use of TotalSeq™ to characterize even very low abundance cell subsets within a heterogeneous population.”
In addition to characterizing complex cell populations, CITE-seq has been used to perform cell-hashing, an effective means of controlling for batch effects within a pooled sample from different donors or different experimental conditions. “By using TotalSeq™ reagents to label cells from distinct samples with hashtags before pooling them and performing CITE-seq analysis, it is possible to correlate each cell to its sample of origin while running multiple samples under identical experimental conditions,” notes Chowdhury. “A further benefit of cell hashing is that it provides robust identification of doublets. Doublet rate increases as more cells are loaded due the nature of droplet-based protocols. They are unwanted when the aim of an experiment is to perform investigation at the single-cell level, making their removal important. Using TotalSeq™ reagents to greatly reduce doublets represents a significant advance in improving data quality.”
Figure 3. Hashtag reagents help identify doublets/multiplets and control for batch effects. Four human peripheral blood leukocytes samples were stained with a panel of TotalSeq™ antibodies each and with a distinct hashtag antibody. After staining, all samples were pooled together for single-cell partitioning, library construction, and next-generation sequencing. This panel shows cell clusters based on hashtag detection. Doublet/multiplets cluster as expected between the shared singlet hashtags. Data generously provided by Marlon Stoeckius, Senior Research Scientist, New York Genome Center.
Although antibody-oligonucleotide conjugates are still seen by many researchers as an emerging class of reagents, their use is being driven by demands for increasingly multiparametric data. To support these needs, BioLegend continue to expand their TotalSeq™ range. To find out more about TotalSeq™, visit www.biolegend.com/totalseq