Single cell genomics is, simply put, the analysis of genetic information such as a DNA sequence from a single cell. It sounds simple enough but wasn’t possible at a practical level until recently. Intricate machinery using tiny liquid-filled tubes are required to shuttle the individual cell’s contents through various chemical reactions. A more typical method is grinding up a large bulk of cells and then carrying out the genetic analysis.
The ability to peer into the DNA sequence or to get a snapshot of gene activation for individual cells has huge implication for stem cell-based therapies. The strategy that many cell therapy projects use is to transform, or differentiate, stem cells into a cell type of interest and then transplant that cell type into the body. But big safety questions go along with this strategy: Am I sure I know the exact identity of the cells to be injected? And are the cells truly all the same cell type? Jeanne Loring, a CIRM grantee who was on the panel, described this application of single cell genomics:
The stem cells start out pretty homogeneous and then become more heterogeneous as we differentiate them into the cell types we want. And so at the end of differentiation process we actually have an unknown number of different cell types. And that’s the problem, the unknown number. We know we have the cell that we want but what else is in your [cell] dish? I know this is a problem that already exists for stem cell therapies. So one of the applications of single cell genomics we want to use is a quality control analysis for cells we want to put into people for our Parkinson’s disease project.Single cell genomics also goes beyond a quality control tool for stem cells-based therapies and could enhance researchers’ understanding of the underlying mechanisms of disease. One scenario is to first take skin samples from a person with, let’s say, Parkinson’s disease and derive neurons using the induced pluripotent stem (iPS) cell technique. With this disease-in-a-dish model, researcher can use patch clamp technology to record the physiological signals from a single Parkinson's neuron. And then that single cell can be extracted for single cell genomics to study the pattern of gene activation in that one cell. This allows comparing the function of a single cell simultaneously with its gene activity to more precisely get at the causes of disease rather than relying on information from a bulk of cells which can muddy what’s really happening in the cells. As Dr. Loring as put it:
We can actually combine two different huge areas of technology that have never intersected before.Kinda sounds like a revolution to me.