Figure 3.

Microglial Population Dynamics

(A) Schematic illustration of the ¹⁴C atmospheric curve over time (Levin et al., 2010). The concentration of ¹⁴C in the genomic DNA of a cell population is dependent on the atmospheric ¹⁴C concentration (y axis). Thus, the birth date of the cell population can be read off the x axis.

(B) ¹⁴C content in the genomic DNA of human cortical microglia from donors born across six decades. Data points plotted along the x axis according to the date of birth of the donors. Close-up view of four nearly overlapping data points (gray square). The error bars represent the ¹⁴C concentration measurement error.

(C) Representation of the average age of microglia in each individual and linear regression (black line).

(D) Different models for distribution of data on the atmospheric ¹⁴C curve considering different frequencies of dividing cells. The model that best fits the data are one where most cells (>96%) renew.

(E) Considering the turnover rate, the average cell age, and the fact that all microglial cells do not divide simultaneously, we created a stochastic cell age distribution model. Our model shows that within an individual there is a distribution of cells of different ages, with some having recently renewed and others not having divided in more than 20 years (donors with infinite turnover not included).

(F) The approximate rate of microglia turnover is 0.08% a day, a low turnover rate in comparison with other immune cells (granulocytes, monocytes, and naive B cells) but a high turnover rate relative to other CNS cells (neurons in the dentate gyrus, oligodendrocytes, and cortical neurons).