Reconstruction of rat retinal progenitor cell lineages in vitro reveals a surprising degree of stochasticity in cell fate decisions - PubMed (original) (raw)
Reconstruction of rat retinal progenitor cell lineages in vitro reveals a surprising degree of stochasticity in cell fate decisions
Francisco L A F Gomes et al. Development. 2011 Jan.
Abstract
In vivo cell lineage-tracing studies in the vertebrate retina have revealed that the sizes and cellular compositions of retinal clones are highly variable. It has been challenging to ascertain whether this variability reflects distinct but reproducible lineages among many different retinal progenitor cells (RPCs) or is the product of stochastic fate decisions operating within a population of more equivalent RPCs. To begin to distinguish these possibilities, we developed a method for long-term videomicroscopy to follow the lineages of rat perinatal RPCs cultured at clonal density. In such cultures, cell-cell interactions between two different clones are eliminated and the extracellular environment is kept constant, allowing us to study the cell-intrinsic potential of a given RPC. Quantitative analysis of the reconstructed lineages showed that the mode of division of RPCs is strikingly consistent with a simple stochastic pattern of behavior in which the decision to multiply or differentiate is set by fixed probabilities. The variability seen in the composition and order of cell type genesis within clones is well described by assuming that each of the four different retinal cell types generated at this stage is chosen stochastically by differentiating neurons, with relative probabilities of each type set by their abundance in the mature retina. Although a few of the many possible combinations of cell types within clones occur at frequencies that are incompatible with a fully stochastic model, our results support the notion that stochasticity has a major role during retinal development and therefore possibly in other parts of the central nervous system.
Figures
Fig. 1.
Lineage reconstruction and cell type identification. (A) Snapshots of a time-lapse video showing a rat retinal progenitor cell (RPC) undergoing a P/D division (_t_=20:30) and a terminal D/D division (_t_=58:11) giving rise to a three-cell clone composed of an amacrine (Am), a bipolar (Bi) and a rod photoreceptor (RPh or ph) cell. Time is given in hours:minutes. (B-D) Retinal cell type identification in the clone recorded in A. In this clone, cell 4 stained for Islet1 and cell 5 stained for Pax6, identifying them as Bi and Am, respectively. The remaining cell was negative for both markers and displayed typical RPh cell morphology with a small round cell body and simple processes and showed characteristic Hoechst staining. (E) Based on the staining data in B-D and the videomicroscopy in A, the lineage tree of this clone was reconstructed. (F-I) A clone containing two RPh cells and one Müller glial cell (Mu; Pax6 negative and Islet1 negative) with distinct glial morphology, large nucleus, absence of neurites and lack of expression of neuronal markers. Scale bars: 20 μm in A; 8 μm in B-D; 20 μm in F-I.
Fig. 2.
The observed clone size distribution is reproduced by a stochastic model. The data points (blue) show the size distribution associated with the 129 clones with three or more cells. If we assume that the balance between proliferation and differentiation is determined stochastically, with RPCs dividing with a fixed probability _PPP_=0.055 of adopting P/P cell fate, _PPD_=0.221 of adopting P/D cell fate, and _PDD_=0.724 of adopting D/D cell fate, we obtain the clone size distribution given by the red curve. The error bars on the theoretical curve denote 95% confidence intervals and are a result of the finite sample size. Since the probability of adopting the P/P cell fate is small, the size distribution is close to exponential, reflecting the fact that the majority of clones can be described by a sequence of asymmetric P/D divisions terminating in a D/D division.
Fig. 3.
Müller cell-containing clones. The lineage trees of all Mu-containing clones were reconstructed. Note that with the exception of two lineages, the Mu cells are generated at the end of the lineage. Note also that only a single Mu cell is present in any lineage.
Fig. 4.
Cell cycle time does not correlate with cell fate. (A) Average cell cycle time (mean + population s.d.) of RPCs generating all the different combinations of daughter cell pairs observed in this study. A, amacrine; B, bipolar; M, Müller; P, progenitor cell; R, rod photoreceptor. (B) Average cell cycle time (mean + population s.d.) of RPCs undergoing P/P, P/D or D/D divisions. ns, not significant. (C,D) Comparison of cell cycle times of sister RPCs undergoing proliferative (P/P) versus differentiative (P/D or D/D) divisions (C), or self-renewing (P/D) versus differentiative (D/D) divisions (D). Each line represents a pair of sister RPCs.
Fig. 5.
Cell cycle time and number of divisions vary among RPC lineages. (A) Observed cell cycle time distribution (bars) together with a log-normal fit (line). The mean is 56.0 hours and population s.d. is 18.9 hours. (B) Cell cycle times of daughter RPCs plotted against the cell cycle times of their mothers reveals no discernable correlation. (C) The cell cycle time of the final two divisions of each lineage. The clones are aligned according to the cycle time of the terminal division. Note that the time of the previous mitosis is highly variable. (D) Larger clones can terminate their lineage before smaller clones. Note the overlap between the time of the final division in smaller and larger clones. Box plots show medians, 25% and 75% percentiles, and whiskers show minimum to maximum values.
Fig. 6.
A stochastic model accurately predicts the observed distribution of lineage termination times. The data (bars) show the measured distribution of lineage termination times. The line shows the predicted distribution of lineage termination times for a stochastic model in which the ratios of proliferation and differentiation are the same as that defined in Fig. 2, and the distribution of cell cycle times is taken to be log-normal with parameters chosen to fit the experimental data in Fig. 5. The curve is obtained from a Monte Carlo simulation (see Materials and methods). This comparison provides a sensitive test of the stochastic model, as deviations from it are magnified through repeated application.
References
- Cayouette M., Barres B. A., Raff M. (2003). Importance of intrinsic mechanisms in cell fate decisions in the developing rat retina. Neuron 40, 897-904 -PubMed
- Cayouette M., Poggi L., Harris W. A. (2006). Lineage in the vertebrate retina. Trends Neurosci. 29, 563-570 -PubMed
- Clayton E., Doupe D. P., Klein A. M., Winton D. J., Simons B. D., Jones P. H. (2007). A single type of progenitor cell maintains normal epidermis. Nature 446, 185-189 -PubMed
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