Vacillating stem cells

If two roads diverged in a yellow wood, random fluctuations would influence which road stem cells traveled.

A new understanding of how stem cells choose among their possible fates could aid development of stem cell therapies for diseases, scientists say. A type of adult stem cell in bone marrow can develop along one of two paths: either the red or white blood cell lineages. Scientists have wondered why some bone marrow cells follow one path while other, seemingly identical cells go down the other.

New research shows that these bone marrow stem cells are not in fact a single, sharply defined type of cell, but rather have a blurry range of traits. Gene activity determines a cell’s biochemical traits, and for these stem cells, this genetic activity varies over a period of days. Each stem cell slowly “wanders” within the range, sometimes producing proteins that prime the cell for the red blood cell pathway, other times prepping the cell for the white blood cell option.

So a large group of stem cells will always contain a variety of cells covering this complete range of traits, distributed in a familiar bell curve.

“It’s like a cloud of mosquitoes,” explains lead scientist Sui Huang of HarvardMedicalSchool in Boston. The varied cells “kind of stay together, though each one of them is moving around” within the range of possible traits. When cues in the cells’ surroundings trigger the cells to choose a fate, each cell will follow the path that it happens to be primed for at that moment, Huang and his colleagues report May 22 in Nature.

The researchers isolated three subgroups of mouse bone marrow stem cells according to where the cells fell within the bell curve — the two edges or the middle. Surprisingly, after separation each subgroup remained for a few days in its region of the bell curve. The cells in each group took more than nine days to diversify and fill the full range of the bell curve — indicating that this variation was due to more than just “noise” in gene activity. If the bell curve was simply because of noise, this diversification would have only taken hours.

“I think it’s fantastic,” comments Mads Kaern, a systems biologist at the University of Ottawa in Canada. “If you ever want to control stem cells for clinical purposes for stem cell therapies, we have to be able to control what these cells are doing. This research really pushes this a great deal forward.”

“It’s very common that you want to create muscle progenitor cells to repair damaged muscles, but they’re really hard to get in high quantity because we don’t know how to control lineage choices appropriately yet,” Kaern says. Typically, scientists can only coax roughly 10 or 20 percent of a batch of stem cells to develop into a desired cell type, such as muscle cells. Immature stem cells implanted into a patient can grow out of control and form tumors, so for stem cell therapies to be safe, scientists must learn to convert virtually all of the stem cells in a batch.

Instead of further refining the cocktail of chemicals used to steer stem cells in the right direction, scientists could pre-sort the stem cells, selecting only those that happen to be at the correct end of the bell curve at the moment to become the desired cell type, Huang suggests.

In the study, Huang and his colleagues also noticed that the 3,000 or so genes they observed did not vary in activity independently of each other. Instead, the genes varied in a coordinated way as the cells “wandered” among the range of possible traits. This suggests that the fuzziness of that range arises from the fact that the network of interacting genes is riddled with feedback loops, which makes the network highly nonlinear, Huang says.

“If you don’t have a very highly nonlinear interaction network, then this would not be possible,” Kaern says.