NEW YORK – New technologies are pushing the cost of single-cell gene expression experiments below a cent per cell, enabling researchers to embark on projects that analyze a million cells or more.
Earlier this week, 10x Genomics announced a new format for its GEM-X Flex gene expression kits, which runs on the droplet microfluidics-based Chromium platform. The company claims this will lead to sample preparation costs of approximately $.01 per cell for runs of 2.5 million cells in total. It also announced new formats for its GEM-X 3' and 5' gene expression kits that lower per-sample costs to about $560.
Meanwhile, earlier this month, a trio of labs published a preprint on BioRxiv demonstrating proof of concept for using high-resolution spatial transcriptomics technologies to perform single-cell gene expression analysis of millions of cells at even lower costs per cell. To run this method, called Single-Cell Transcriptomics Analysis and Multimodal Profiling (STAMP), cells in suspension are fixed and permeabilized, then deposited onto a glass slide and run on one of several imaging-based spatial biology platforms, including 10x's Xenium and Bruker NanoString's CosMx. The method does not yet allow whole-transcriptome profiling but uses large panels targeting thousands of transcripts per cell instead. However, the cost per cell is approximately one half of a cent, and the method does not require additional analysis by sequencing.
"We're basically replacing what we were doing using single-cell sequencing with single-cell imaging," said Holger Heyn, an expert in single-cell analysis at Spain's National Center for Genomic Analysis (CNAG) and one of the senior authors of the preprint. His collaborators are Jasmine Plummer of St. Jude Children's Research Hospital and Luciano Martelotto of the University of Adelaide. "The main advantage is the number of cells and flexibility of multiplexing. It's a simple way to scale up the cell numbers [in an experiment] at very low cost," Heyn said.
The new methods should enable new types of cell atlas studies, something Heyn's lab is already pursuing. "Cell numbers make a difference," he said. "You want to profile as many cells as possible."
They arrive as startups have pushed ever upward the number of single-cell transcriptomes that can be analyzed. Parse Biosciences, for instance, launched its Evercode Mega kit in 2021, which can profile up to 1 million cells, while Scale Biosciences' single-cell kit, launched in late 2022, can process 500,000 cells.
"We don't want to leave that as an opening," said Michael Schnall-Levin, 10x cofounder and chief technology officer. "We want to make sure we're not leaving places where customers have needs that we're not meeting."
The new GEM-X Flex gene expression assay offers the ability to prepare up to 2.5 million single cells per run and 5 million cells per kit. The kit also offers more efficient cell loading, Schnall-Levin said, leading to lower cell input requirements and lower prices, even for those not running a million cells. He estimated that the kit offers a twofold reduction in costs "across the whole range of experiment sizes."
Still, that price point is only accessible to those running the biggest experiments, in the same way that the lowest possible sequencing prices for Illumina customers are only available on the highest-throughput instruments, like the NovaSeq X.
According to Martelotto, STAMP also works well if you're only trying to analyze dozens to a couple of hundred cells, though the economics aren't quite as good. Moreover, it can work with lower-quality samples or samples where some transcripts are more abundant than others, since it does not require PCR amplification. Because the slides can physically separate cells from different sources, it's easy to multiplex dozens of samples.
It also does not destroy the cells, allowing multimodal assays on the CosMx and Xenium platforms to be performed, as well as subsequent protein-only assays on the Akoya Biosciences PhenoCycler Fusion platform.
In its preprint, the STAMP team compared its method's capture of gene expression to the 10x Flex assay. "For the genes we're after, the correlation is good," Martelotto said.
"We're moving most of our [gene expression-based] projects to this because it's cheaper," he said. "If I wanted to only count molecules, why would I spend $4,000 for 10,000 cells when I can spend the same amount for 1 million cells?"
Plummer said she's planning to use STAMP in her CRISPR screens. "It allows me to run larger numbers of cells through drug experiments, CRISPR experiments, those kinds of things," she said.
The method also helps capture rare cell populations, where the odds of detecting a particular cell might be one in a million. "Finding a needle in a haystack is hard to do if you're only taking a portion of that haystack," Plummer said.
Other experts have noted that while the method offers lower costs, among other benefits, Xenium and CosMx are expensive instruments to obtain and maintain.
Though STAMP produces fewer molecules and genes per cell than established single-cell sequencing technologies, "it's still early days for us and the spatial devices, as well," Heyn said. He has already obtained early access to a whole-transcriptome CosMx assay. "The moment those scale to the whole transcriptome, that's the time these methods could replace single-cell sequencing," he said.