Each methylation tag (horizontal line) shows variation within a crypt (each group of circles).


How many stem cells reside in a human colonic crypt and how do they divide and regenerate? According to the deterministic theory, a small number of “immortal” stem cells haunt a crypt, and when they divide, each generates a single replacement stem cell. The stochastic model, in contrast, contends that a crypt niche harbors many stem cells, and each cell division randomly generates one, two, or no new stem cells. In this model, stem cell lines may be lost over time, and “bottlenecks” will eventually develop in which all stem cells in a niche will diverge from a recent, common ancestor.

A new and clever strategy for studying stem cell dynamics, devised by Darryl Shibata and colleagues (University of Southern California, Los Angeles, CA), uses DNA methylation tags as markers of stem cell fate. The authors applied this technique to track changes in methylation patterns among stem cells in human colonic crypts and to test the two competing models of stem cell dynamics. Their conclusion: the data support the stochastic model, as demonstrated by the similarity of methylation patterns within individual crypts and the large variability in the numbers of unique tags per crypt.

These findings lend credence to the theory that crypt niches contain multiple long-lived stem cells that self-renew most of the time through asymmetric division. Loss of methylation tags occurs as random stem cells fail to generate replacements and bottlenecks develop. One implication of these bottlenecks for stem cell dynamics is that the periodic death of stem cells might eliminate potentially cancerous cells.

Perhaps the most surprising outcome, in Shibata's view, is that “a population genetics type of approach worked for human crypts,” and that epigenetic patterns, in this case methylation, can serve as a marker of cell fate. The ability to map stem cell fate in human tissues and cancer cells could offer a glimpse into the process of cell aging, by allowing the construction of cell fate maps that detail which cells survive longest. ▪


Yatabe, Y., et al. 2001. Proc. Natl. Acad. Sci. USA. 10.1073/pnas.191225998. http://www.pnas.org/cgi/content/full/191225998