SAN FRANCISCO (GenomeWeb) – Researchers from the New York Genome Center have expanded upon a previous method they developed that analyzes both RNA and cell surface proteins from single cells adding the ability to analyze immune clonotypes and CRISPR perturbations.
The new method, ECCITE-seq for expanded CRISPR-compatible cellular indexing of transcriptomes and epitopes by sequencing, builds off two previously developed methods by NYGC researchers and was described in a study published in Nature Methods.
In 2017, NYGC researchers developed a method to enable analysis of transcriptomes and proteins from single-cells, dubbed CITE-seq for cellular indexing of transcriptomes and epitopes by sequencing. Then, last year, the team developed a technique they called Cell Hashing to label cells from different samples before pooling.
Sequencing multiple features from a single cell has been of growing interest, with various research groups publishing methods to analyze both CNVs and gene expression, for instance, or to combine gene expression with chromatin accessibility or genome structure. 10x Genomics has also launched its own feature barcoding assay that combines single-cell gene expression with other modalities, such as proteins or CRISPR perturbations.
In the new Nature Methods study, the team has added the ability to analyze immune clonotypes by integrating 10x Genomics' VDJ kit and the ability to detect CRISPR perturbations.
Peter Smibert, senior author of the study and manager of the NYGC Innovation Lab, said that the company BioLegend has licensed IP to develop antibody-oligonucleotide conjugates related to the method. BioLegend also sells antibody-oligo conjugates for CITE-seq.
Smibert said both the CITE-seq and Cell Hashing methods are based on 3' RNA-seq methods. But when 10x Genomics launched its immune profiling kit, which barcodes full-length cDNAs at the 5' end, Smibert said he saw an opportunity to include single-cell protein and transcriptome sequencing with immune profiling, as well as sample multiplexing by Cell Hashing.
By adjusting CITE-seq to work with the 5' method, the researchers were able to run 10x Genomics' VDJ kit for immune profiling but also detect surface proteins and gene expression. To do this, they labeled cells with oligos that were partially complementary to the gel bead-associated template switch oligos that are used in 10x' VDJ kit. Reverse transcription extends the attached oligonucleotide and associates the cell barcode and unique molecular identifier from the gel bead oligo with the antibody tag and mRNAs in the same droplet.
Next, the researchers adapted the method further so that they could directly capture guide RNAs in single cells. To do that, they took advantage of the 3' scaffold on single gRNAs and attached a reverse transcriptase primer complementary to the scaffold. The sgRNA-derived cDNAs undergo template switching in droplets resulting in a cDNA molecule tagged with the same cell barcode as the cellular mRNA.
"We tried to make a more flexible tool that people can use to capture different modalities," Smibert said.
To demonstrate the technique, the researchers first tested it on a mixture of nearly 6,000 cells consisting of human blood cells, two human T-cell lymphoma cell lines, and mouse cells, running all four samples in one experiment. The researchers used hashtags specific to human cells to distinguish the three human samples and tagged the mouse cells with gRNAs. They noted that the hashtags were also consistent with how the cells clustered based on the transcriptome data. The guide RNA tags were identified in the mouse cells and only the mouse cells, and antibodies were able to distinguish mouse from human cells. Clonotypes from the T cell antigen receptors were detected in the blood cells and lymphoma cell lines.
Next, the researchers performed a CRISPR screen and demonstrated that the method could analyze single-cell transcriptomes along with surface protein markers. To do this, the team developed a CRISPR screen that used single gRNAs to target genes encoding cell surface markers and intracellular signaling molecules, and also included two control gRNAs that did not target anything. The researchers identified 13 distinct clusters that corresponded to the 13 gRNA tags.
Smibert said that the ECCITE-seq method could be a good way to do CRISPR screens because "the multimodal readout is more sensitive for detecting phenotypes than relying on RNA alone." Previously, CRISPR screens needed to analyze around 100 cells to accurately characterize a phenotype, but with this method, that number could be brought down significantly, Smibert said. "A signature in a few cells will ultimately be a robust way of looking for phenotypic markers," he added.
Aside from CRISPR screens, Eleni Mimitou, senior research scientist in NYGC's Innovation Lab and first author of the study, said the method could also be used to do immuno-phenotyping of samples. For instance, in the study, the researchers constructed a 49-marker panel of antibodies to profile blood cells from a healthy donor and a patient with cutaneous T-cell lymphoma. They found that the transcriptome and protein data correlated well with previous results using the CITE-seq method and that they were also able to identify clonotype information from each sample.
Combining proteins with clonotypes "lets us parse out the distinct cell populations and address the differences in gene expression profiles between the malignant and the healthy cells," Mimitou said.
Smibert said that the team plans to continue developing the method by incorporating additional modalities.