Stochasticity and cell fate

Abstract

Fundamental to living cells is the capacity to differentiate into subtypes with specialized attributes. Understanding the way cells acquire their fates is a major challenge in developmental biology. How cells adopt a particular fate is usually thought of as being deterministic, and in the large majority of cases it is. That is, cells acquire their fate by virtue of their lineage or their proximity to an inductive signal from another cell. In some cases, however, and in organisms ranging from bacteria to humans, cells choose one or another pathway of differentiation stochastically, without apparent regard to environment or history. Stochasticity has important mechanistic requirements. We speculate on why stochasticity is advantageous-and even critical in some circumstances-to the individual, the colony, or the species.

Figure 1. Stochastic distribution of cell fates in bacteria and in insect photoreceptors

Left panel: Fluorescence micrograph showing cells of B. subtilis containing a fusion of the coding sequence for GFP to the promoter for a gene under the control of the competence regulator ComK. The cells were visualized with a red stain. The green fluorescence reveals the subpopulation of cells that are ON for ComK. Right panel: Photograph showing a whole adult Drosophila retina whose R8 photoreceptors were stained with antibodies against the green-sensitive photopigment Rh6 (green) and the blue-sensitive photopigment Rh5 (blue).

Figure 2. Regulatory circuits exhibiting bistability

Panels A and B illustrate two kinds of regulatory circuits that can exhibit bistability. Shown in A is a positive feedback loop in which an activator (as in the example of the activator of competence ComK) stimulates the transcription of its own gene. Hypersensitivity is achieved by cooperativity among activator molecules in binding to the promoter region for the gene (not illustrated). Shown in B is a double-negative regulatory circuit in which two repressors (as in the example of the phage lambda CI and Cro repressors) antagonize the transcription of each other’s gene. Hypersensitivity is achieved by cooperativity among repressor molecules in binding to operator sites in DNA. Panel C illustrates an example of a double-negative regulatory circuit that governs the alternative neuronal ASE-L and ASE-R fate in C. elegans. In this case, the two transcriptional regulators (COG-1 and DIE-1) antagonize each other’s synthesis indirectly through the action of the micro RNAs lsy-6 and miR-273, which block the translation of the mRNAs for COG-1 and DIE-1, respectively. Neurons have the ASE-L fate when DIE-1 levels are high and COG-1 levels are low (left-hand cartoon) and the ASE-R fate when the opposite is the case (right-hand cartoon). Panel D illustrates the case of the classic example of the double-negative circuit (see panel B above) governing the alternative lytic and lysogenic states of phage lambda. When the lambda repressor CI is at high levels it represses the gene for the Cro repressor and genes involved in lytic growth (left-hand cartoon). Hence the phage is held in the dormant, lysogenic state. Conversely, when Cro is at high levels it represses the gene for CI under which condition genes involved in lytic growth are freely expressed (right-hand cartoon).

Figure 3. Cell-autonomous cell fate decisions

Panel A illustrates cell-autonomous stochasticity in a mouse olfactory neuron. The neuron expresses one olfactory receptor gene (red) to the exclusion of all others (blue, brown, dark or light green, yellow or pink), including the other allele of the ‘red’ gene. The olfactory neuron somehow instructs its target neuron in the olfactory bulb of its choice (dashed arrow). Panel B illustrates cell-autonomous stochasticity in an old world primate color vision cone photoreceptor. The choice of a cone photoreceptor to become M (green-sensitive) or L (red-sensitive) depends on the ability of a single Locus Control Region (LCR) located upstream of the L and M genes to contact one of the two genes. If the LCR contacts the M gene, the cone becomes an M cone, and similarly for the L gene. This ensures that only one gene is expressed in each cone. As the LCR-M-L cluster is located on the X chromosome, only one copy is present in males and only one is active in females, due to X-chromosome inactivation.

Figure 4. Cell-non-autonomous cell fate decisions

Panel A illustrates lateral inhibition by the Notch (LIN-12) regulatory system in which a stochastic decision by one cell prevents its neighbor(s) from making the same decision. Two neighboring epidermal cells of Drosophila start with the same potential to become neuroblasts, both initially exhibiting low Notch activity (N^+/−) (left-hand cartoon). Variations in gene expression in the precursor cells leads one cell (dark pink nucleus) to increase production of the Notch ligand Delta (red lollipop) and to decrease production of the Notch receptor (blue Y) (right-hand cartoon). This asymmetry sets in motion a self-reinforcing cycle in which one cell (N⁻) becomes less and less sensitive to the Delta ligand and more and more active in producing ligand whereas the other cell (N⁺⁺⁺) becomes more and more sensitive to ligand but less active in producing it. The N⁻ cell becomes a neuroblast while the N⁺⁺⁺ cell remains an epidermal cell. Panel B illustrates a Notch-Delta regulatory switch that is biased in one direction by gradients of signaling molecules. Two neighboring photoreceptor cells, R3 and R4, in the fly compete as in (A) to acquire their cell fate. High Notch leads to the R4 cell fate while low Notch leads to the R3 fate. Pairs of R3/R4 precursors are in a gradient of a signaling molecule (e.g. wingless, green). In each pair, the cell positioned at the polar side receives more signal than its more equatorial neighbor, thus biasing it to becoming R4. The decision is then reinforced by lateral inhibition: all equatorial cells become R3 and all polar cells become R4.