Imagine someone hands you a smoothie and asks you to identify everything that went into it.

You might be able to discern a hint of strawberry or the tang of yogurt. But overall it tastes like a blend of indiscernible ingredients.

Now imagine that the smoothie is made of 20,000 ground-up cells from, say, the brain.

You could run tests to determine what molecules are in the sample, which is what scientists do now. That would certainly give you useful information, but it wouldn’t tell you which cells those molecules originally came from. It would provide only an average cell profile for the whole smoothie.

And when it comes to the tissues in our bodies, averages are almost always misleading. Just as you know there isn’t an “average” food called strawbanaspinach-orangegurt, scientists know there isn’t just one cell type in the brain.


“If you take a hunk of tissue and grind it up and analyze the RNA, you have no idea if it represents what every cell in that population is doing or what no cell in the population is doing,” said Marc Kirschner, the John Franklin Enders University Professor of Systems Biology and chair of the Department of Systems Biology at Harvard Medical School. “Imagine if you had a population of men and women. If you assume everyone is an average of men and women, you [probably] wouldn’t represent a single person in that population.”

The trouble is, it’s expensive, time-consuming and tricky to characterize tissues one cell, or cell type, at a time.

Kirschner and Steven McCarroll, assistant professor of genetics at HMS, reported this week in separate papers that their labs have developed high-throughput techniques to quickly, easily and inexpensively give every cell in a sample a unique genetic barcode before it goes into the blender.

As a result, scientists can analyze complex tissues by profiling each individual cell—no averaging required.

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