Every plant, animal, and fungus is made up of an intricate amalgam of cells. Each cell type has its own unique function, life cycle, and reaction to its environment. These factors, in aggregate, inform how living things live, the way disease manifests, and why we die.

Much of this synchronous web of biology is still a mystery: There’s so much we don’t understand about how individual cells work in tandem to keep a brain firing or a cancer metastasizing.

But scientists, using a powerful technology called single-cell sequencing, have begun to peel apart the precise mechanisms of how individual cells operate. By quickly analyzing thousands — even millions — of cells in a single experiment, it’s now possible to visualize the specific cellular culprits for any given disease, how they might interact with their microscopic peers, and what molecules are involved in the process.

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“Imagine you were a biologist and didn’t have a microscope — and then I handed you one for the first time,” said Dr. Sam Behjati, a pediatric oncologist and single-cell researcher at the Wellcome Sanger Institute in Britain. “That’s how profound single-cell sequencing is. It lets us see what we haven’t seen before; it gives us a new instruction manual for life.”

Single-cell sequencing has tantalized scientists for several years. It was first described in 2009, and by 2013 earned the distinction of “Method of the Year” from Nature. Cost and technology hurdles initially kept its use at bay — but the field has begun to blossom as sequencing becomes more economical, and bioinformatic analysis becomes more reliable.

Academics and drug makers alike are increasingly looking for ways to exploit this powerful new technology. Interrogating individual cells on their identity and purpose is turning up stunning new insights on basic biology — and providing rich fodder for drug discovery.

Try to picture a mass of cancer cells. Tumors are bedeviling in their complexity: They can comprise both of mutant and healthy cell types, and operate in their own ever-expanding microenvironment.

Although it’s possible to identify tissue as cancerous by examining it under a microscope, or even by sequencing a biopsy, it’s difficult to isolate which specific cells are benign — and which might evade therapy, mutate, and lead to further metastasis.

“It’s Darwinian evolution, literally,” said Charlie Silver, CEO of Mission Bio, a biotech spinout of the University of California, San Francisco, that provides single-cell sequencing services to cancer hospitals, researchers, and pharmaceutical companies. “Cancer is not one mutation — it’s many mutations on different cells that work together to drive disease.”

Most clinical sequencing efforts work by the law of averages: Genetic analysis is conducted on entire populations of cells, so subtle differences between them aren’t clear, making it hard to to isolate the most malignant. And those subtle differences are what drive each individual cancer’s pathology.

Standard genetic analysis techniques give us some insights, but they can be murky — not unlike population surveys, as Christoph Lengauer, CEO of Celsius Therapeutics, a Cambridge, Mass., biotech, points out.

“Population surveys tell us the average American family has 1.2 children. That’s useless. That’s not helpful. Not a single family has 1.2 children,” said Lengauer, whose company is using single-cell sequencing to find new drug targets.

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Single-cell sequencing, by contrast, can indicate which family has six children, and which has just one, and a dog, he said. It’s orders of magnitude more granular.

“The value of single-cell sequencing, in this case, is the ability to look at how mutations work together to drive disease,” Silver said.

Here’s how single-cell sequencing works: A cancer biopsy is teased apart, and each of the thousands of cells is locked into its own tiny test tube on a microfluidic chip, and then treated with a series of enzymes and chemicals to coax the necessary genetic material out.

From there, the cells are tagged with their own “barcode” — a unique DNA- or RNA-based identifier that’s inserted into its genetic code. The cells are then probed for a predetermined set of variables: Scientists can check whether they carry a certain set of genes, or express specific molecules involved in disease pathogenesis.

The data are aggregated, and through the magic of machine learning scientists can use that data to sort cells by their function and characteristics. Instead of averaging the genetic profile of the tissue sample, this analysis quantifies the prevalence of each different cell type — and can isolate the outliers.

“If our customers analyze 10,000 cells from a sample, very often they’ll find a handful of these residual cells after a patient’s been treated that are still indicative of disease,” Silver said. “That’s the population that ends up relapsing and progressing.”

Mission Bio is working with top institutions around the country — including MD Anderson, Mount Sinai, the National Cancer Institute, and the Stanford Cancer Center — to pore through patient tissue samples in search of residual cancer.

Single-cell sequencing might ultimately help clinicians know whether a therapy is tailored to target the specific cell types that have gone rogue. The tool has particular implications for combination therapies, and could prove useful in clinical trial design, Silver said.

Single-cell sequencing still isn’t cheap.

10X Genomics, a biotech specializing in single-cell analysis, offers the microfluidics instruments necessary for this technology for about $75,000. It’ll cost about $1,280 — plus sequencing costs, which vary based on what’s being studied — for the necessary materials to study about 10,000 cells, said Ben Hindson, chief scientific officer of the company.

Even if the price isn’t negligible, it’s well within reach for both research labs and larger pharmaceutical companies that are interested in this technology.

“We want these instruments in all labs across the world, because we think this is how analysis should be done,” Hindson said.

The Human Cell Atlas project — an international effort to create a detailed taxonomy of every cell type in the human body — has helped raise the profile of single-cell sequencing. The project is funded in part by the Chan Zuckerberg Initiative, the effort launched by Facebook CEO Mark Zuckerberg and his wife, Dr. Priscilla Chan, aimed at curing, preventing, or managing all disease “in our children’s lifetime.”

Though the initiative is still in its nascency, scientists are already unveiling intriguing new insights into basic human biology thanks to the collaborations spawned by the Human Cell Atlas.

Ed Lein, a researcher at the Allen Institute for Brain Science, is working on unraveling the cellular makeup of the human brain. The idea is to reverse-engineer the brain’s cortex, he said, to try and understand all of the types of cells within it — and then build up an understanding of how they’re all wired together.  

Single-cell sequencing is the center point of his research. The advantage, he said, is that it allows you to measure 5,000 to 10,000 genes in each cell, and do it across many thousands of cells. The work’s been fruitful: This summer, for instance, Lein’s team announced that it used RNA sequencing on a single-cell scale to discover a new breed of neuron, dubbed the “rose hip cell” — so named because the axons, or nerve fibers, resemble a rose without its petals. The cells, which seem to exist only in humans, are thought to control how information flows from one part of the brain to others. The study analyzed just a handful of human brains, obtained postmortem, but included the analysis of thousands of cells in minute detail.

“The field has changed so dramatically, and quickly,” Lein said. “Just a few years ago, studying a couple dozen transcriptomes would be a totally reasonable study. Now, we’re getting into the realm of millions of cells for a study.”

The technique has also produced some fascinating insights in disease pathology. Take asthma, for instance: Nathan Jackson, a researcher at the Center for Genes, Environment, and Health at National Jewish Health in Denver, discovered the precise cells that misbehave during severe asthma attacks.

He assayed the cells involved in type 2-high asthma, which affects about half of the people with the disease. It’s caused by elevated levels of signaling proteins, called type 2 cytokines, which prompt the cells lining the surface of the lungs to excrete a thick mucus. This ends up triggering some of the breathing difficulties associated with asthma.

By analyzing the RNA with single-cell sequencing, Jackson and his colleagues found out the specific genes and proteins that prompt mucus production. Furthermore, they found 11 different states of these epithelial lung cells, as they changed in response to triggers in the environment,  morphing from innocuous into irritated cells that caused disease.

Though the epithelial cells were obviously studied in a lab setting, they were cross-examined with the RNA expression from the nasal swabs of 698 children with type 2-high asthma — and the findings held up.

Understanding the precise cellular processes that go awry in asthma could potentially lead to a new wave of asthma therapeutics, Jackson said. And it’s not just asthma: Identifying the pathways that lead to dysfunction in a specific cell type, such as the epithelial cells he analyzed, could allow scientists to develop drugs targeted exclusively to that particular population.

“Once this technology became available, we realized there was so much low-hanging fruit,” Jackson said. “There are so many obvious questions we can answer with single-cell sequencing.”

Celsius Therapeutics is using single-cell sequencing to drive its entire drug discovery process. Freshly launched this year with a $65 million series A round, the company is zeroing in on cancer and autoimmune disease.

“We think these are two areas where whole genome sequencing has little impact,” said CEO Langaeur.

Instead, his company is analyzing the RNA from the single cells involved in cancers and conditions like inflammatory bowel disease to find drug targets. The company’s agnostic on therapeutic modality — it’s open to both biologics and small molecule drugs — but thinks the single-cell approach will be very revealing.

Indeed, single-cell sequencing could open the door for entirely different ways of approaching drug development.

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Behjati of Wellcome Sanger made a startling observation in his own cancer research. After sequencing reams of kidney cancer cells, he has — as expected— found a litany of unique mutations. But he noticed that while the kidney cancer cells may be genetically disparate from one another, they generally behaved and looked alike. The cancer cells’ instruction manuals may have been worded differently, but the end result was more or less the same, he said. 

“On the DNA level, kidney cancers are very heterogeneous — but if you looked at the cancer on a cellular level, all the cancer cells are the same,” he said. “I think we’re getting distracted by the heterogeneity.”

So Behjati has a slightly unorthodox viewpoint on the future of drug development — using insight gleaned from his work with single-cell sequencing.

His hypothesis, when it comes to drug development, would be to focus more on the cell type and less on the intricacies of DNA and RNA that drive the mutations.

“Let’s look for drugs that change the cell type, and disrupt the cancer that way,” he said. “At the end of the day, what kills you is not the mutation, but the cancer cell.”

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