In the spring of 2013, HSCI Affiliated Faculty member Peter Kharchenko, PhD, a computational biologist at Harvard Medical School, and Lev Silberstein, MD, PhD, a clinician at Massachusetts General Hospital, joined forces to start the first collaborative network for Boston researchers who use or are interested in using single-cell analysis as a laboratory tool.
Single cell analysis is a technique still very much in development, and Karchenko and Silberstein are hoping to speed up its effectiveness with a regular seminar series that allows scientists to present their work and share protocols. The duo spoke with HSCI about single-cell science and the goals of the Boston Single-Cell Network:
Q: What is single-cell science?
Kharchenko: Any chunk of an organism you take is going to have many cells of different types in it. When you are studying a mixture of different cells, you look at averages. But, similar to looking at average temperature in a hospital, sometimes it’s a poor indicator of what actually goes on. Maybe some of the cells are acting in different ways, but you can’t tell because you’re looking at an average. There’s recently been very substantial progress in terms of techniques that could be applied to smaller and smaller samples, and now there’s a possibility of looking at individual cells.
Q: What is the intent of the Boston Single-Cell Network?
Silberstein: It is a community building exercise. Single-cell research is very technically challenging and resource demanding. Boston is one of the very few places in the world where a single-cell community can grow rapidly. By sharing experience and expertise, people will essentially get to work together on developing new methods and solving problems.
Q: Who should be part of the Boston Single-Cell Network?
Kharchenko: Boston-area researchers who are interested in single-cell analysis. We’ve deliberately left it open and didn’t make any emphasis on any particular subfield. Right now, the most progress we’ve seen in presentations we’ve had so far has been around genomics, but we do want folks looking at this from different angles to participate.
Silberstein: While this is open to the broad scientific community, we’ve also made the decision not to open it to industry because we really want to promote an open scientific exchange.
Q: What’s the relationship between single-cell science and the clinic?
Silberstein: From a clinical point of view, there are two main applications of single-cell analysis: cancer and prenatal diagnosis. In cancer, the ability to examine individual cells and compare their genetic makeup is extremely important to understand how different cancer cells in the same patient are related to each other.
Kharchenko: Prenatal diagnosis is more direct because you actually want to get the genome and analyze potential risk factors with as few cells as possible, ideally with one cell or even with fragments of DNA that’s floating in the mother’s blood.
Q: How do you use single-cell technologies in your own research?
Silberstein: We use a single-cell approach to look at cell interactions within the bone marrow niche, which essentially regulates the behavior, proliferation, and differentiation of hematopoietic stem cells. These cells are very rare, and we’re only able to see them and reliably label them upon transplantation. Studying the niche can tell us about the signals that the surrounding cells produce to control the behavior of hematopoietic stem cells. We have already found several signals, including one molecule involved in the recovery of immature hematopoietic cells after bone marrow transplantation in mice. We are following up on this discovery by testing whether the blockade of this molecule might potentially form a useful therapeutic strategy for patients undergoing bone marrow transplantation.
Kharchenko: I’m more focused on the computational methods needed for the analysis of single-cell data. We’re realistically able to analyze thousands of cells now and look for subpopulations within them. Such analysis requires additional methods and it’s quite exciting to be able to get a more statistical view of cell state as opposed to predefined morphologically/histologically defined cell types. We’re trying to move more toward an unbiased definition of what is the transcriptional state of the cell, what are various aspects that distinguish cells within a given tissue or between tissues, and so on.
Q: Where do you see the Boston Single-Cell Network in a year?
Kharchenko: I’m looking forward to hearing about work collaborations that have been established somehow because of the network. Once we start seeing groups of labs that are collaborating on interesting topics with our help, I’ll be very happy.