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NIH Invests $90M in Single-Cell Analysis

10/19/2012
Kelly Ray Chi

Over the next five years, the NIH will provide more than $90 million to develop single-cell analysis techniques. So, what projects have been earmarked for funding?


Over the next five years, the National Institutes of Health (NIH) plans to allocate more than $90 million for the development and application of single-cell analysis tools in areas such as immunology, neuroscience, and cancer. Supported by the NIH Common Fund, the federal agency will award 26 grants over this time period as part of its Single Cell Analysis Program (SCAP).

Natural killer (NK) cells can recognize and kill tumor cells. Here, the interactions between individual NK cells (blue) and tumor cells (red) are being monitored on an elastomeric array of 30 µm wells for cytolytic behavior and cytokine release. Source: Yvonne Yamanaka, Love Lab, Koch Institute

It’s become increasingly clear over the past few years that no two cells are alike, and that their individualities collectively may reveal new clues about human biology and disease.

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With the goal of understanding what makes each human cells unique, 15 high-risk SCAP projects will aim to develop new techniques that probe the proteomes, protein activity, genes, chromatin and other aspects of individual cells. Eight more projects will further develop and validate single-cell analysis prototype techniques for use at the bench and bedside.

“These types of technologies are clearly needed right now,” said J. Christopher Love, associate professor of chemical engineering at Massachusetts Institute of Technology in Cambridge, MA, who has received two SCAP awards.

The breadth of awarded projects for single cell technologies—from imaging to physical tools for isolating cells—is striking, he said. In addition, the crosstalk between SCAP’s investigators will allow ideas to merge together in new ways.

One of Love’s SCAP projects will focus on the development of a chip that uses arrays of sub-nanoliter-sized compartments to separate individual cells for analysis. This project may help in the analysis of small tissue samples from patients. For example, mucosal tissue samples taken to monitor HIV infection, through pinch biopsies or cytobrush samples, yield only 10,000–100,000 cells. “That is too limiting to run many conventional analytical methods on with single cell resolution,” he added.

Taking Bigger Gambles

In a higher-stakes project, Love’s group also plans to improve single cell transcriptional analysis techniques. The idea is to use DNA barcoding to trace transcripts back to individual cells, which would increasing the number of cells and endpoints that can be monitored.

Meanwhile, at the University of Texas M.D. Anderson Cancer Center, assistant professor Nicholas Navin has received $250,000 for two years for a another high-risk project. His group will develop a whole-genome sequencing method for single cells, called Cell seq. Navin and postdoc Yong Wang plan to allow a single cell to duplicate its genome, isolating it before cell cytokinesis.

With four copies of the cell’s genome, the group has a template for amplification that will generate DNA fragments that will be 10,000–15,000 base-pair in length and will then be sequenced. “Our goal is to apply the method to a human tumor sample to understand the clonal diversity within breast tumors,” said Navin.

The project is rife with challenges, starting with isolating cells and verifying that they’ve done so. So far, the group has found that isolating nuclei and then flow-sorting them works best. And to minimize loss of their precious 12 pg of starting material, the team performs all the reactions in the same tube. “You can’t have intermediate steps where you can get feedback on your sample,” said Navin.

Overall, Navin’s group is optimistic. But their funding doesn’t cover the challenge of analyzing the terabyte of information from each cell. “Each cell is a human genome project,” said Navin. “There’s a lot of data we have to analyze.”

A complete list of SCAP funded projects can be found on the NIH’s website.

Keywords:  single-cell analysis