A speedier way to catalogue cells

There are some questions in biology that you would think were settled long ago. For instance: How many types of cells are there in the human body? “If you just Google this, the number everyone uses is 200,” said Jay Shendure, a geneticist at the University of Washington, USA. “But to me that seems absurdly low.”

A number of scientists like him want to build a more complete catalogue. Yet there are an estimated 37 trillion cells in the human body. The traditional ways to identify cell types — such as carefully tracing the shape of individual cells under a microscope — are too slow and crude for the job.

Jay and his colleagues recently published a report describing a speedy new method for taking such a cell census. Instead of inspecting one cell at a time, they measured the activity of genes inside 42,035 cells at once. Although still at an experimental stage, the method may become an essential tool for cataloguing every cell type in the human body, experts said. “It’s a really important piece of work,” said David M Miller, a cell biologist at Vanderbilt University, USA, who was not involved in the study. “With this approach, you can do more for a whole lot less work, and a whole lot less money.” In the laboratory, scientists easily discern the difference between, say, a muscle and a nerve cell. But these broad categories encompass many different types of cells.

Genetically speaking, all cells in the body are identical. They all carry the same 20,000 or so protein-coding genes. What distinguishes each type is the particular combination of genes the cell uses to make proteins. The first step in this process is making a copy of the gene in the form of a molecule called RNA. The cell uses the RNA molecule as a template to build a protein. Jay and his colleagues reasoned that the distinctive collection of RNA molecules floating around inside a cell could provide clues about the cell’s type. To measure that RNA, they developed a kind of molecular ‘bar coding’.

Identifying active cells

In the first step, the researchers pour thousands of cells into hundreds of miniature ‘wells’. Each well contains molecular tags that attach themselves to every RNA molecule inside the cells. The process is repeated two or more times until each cell ends up with a unique combination of tags attached to its RNA molecules. Jay and his colleagues then break open the cells and read the sequences of tags at once.

The ‘bar codes’ allow the scientists to see which genes are active in each cell. Cells of the same type should share many of those genes in common. “We came up with this scheme that allows us to look at very large numbers of cells at the same time, without ever isolating a single cell,” Jay said. He and his colleagues call their method sci-RNA-seq (short for single-cell combinatorial indexing RNA sequencing). To test it, they set out to classify every cell in a tiny worm, Caenorhabditiselegans (C elegans).

Scientists know more about C elegans’ cells than any other animal’s. In the 1960s, biologist Sydney Brenner made it a model for investigating biological development. Sydney and later generations of scientists tracked the worm’s growth from a single cell to about 1,000 cells at maturity, classifying them into types with a microscope. Eventually, scientists plucked individual cells from the worm’s body and painstakingly measured their DNA activity.

Jay and his colleagues decided to see how results from sci-RNA-seq compared to those from decades of research. They raised 1,50,000 C elegans larvae and then doused them with chemicals that broke them apart into individual cells. (Each larva has 762 cells, not counting the cells that will become eggs or sperm.) They then tagged all the RNA in the cells. With the new method, the researchers were able to identify 27 cell types that had been identified in previous studies.

Valuable findings

But the team also was able to break them down into smaller groups, each with a slightly different pattern of gene activity. They identified 40 different kinds of neurons, for example, including very rare types. In few cases, only a single such neuron develops in each worm. “I was excited because it worked extremely well — they uncovered results that will be valuable for me and for the whole field,” said Cori Bargmann, an expert on C elegans at the Rockefeller University, USA. Yet for now, sci-RNA-seq falls far short of capturing the full complexity of cell types, even in such a simple animal.

Jay and his colleagues could not match some of their clusters of neurons to a known type of cell, and they did not find most of the 118 types of neurons that earlier studies have documented. “We don’t consider this a finished project,” Jay said. Cori and her colleagues are already trying to match Jay’s results to neurons in the worm. “Of course, there is more to do, but I am pretty optimistic that this can be solved,” she said.