Animals are compact multicellular organisms that grow out from a single zygote cell following a complex embryonic developmental program. During development, increasingly differentiated cell types emerge through sequential rounds of cell division, giving rise from about one thousand (Caenorhabditis elegans
) to millions (Drosophila melanogaster
) or tens of trillions (humans) of isogenic cells in a fully developed animal. Moreover, these expanding and diversifying cell subpopulations perform remarkably well-defined movements in space and time, such that they arrive to appropriate locations relative to each other, ready to perform their function in the adult animal (Goldstein and Nagy, 2008
). Importantly, a few cells embed themselves into specific niches and remain partially undifferentiated, thereby becoming adult stem cells capable of replacing differentiated cells that are lost during adult life.
The tremendous population expansion that cells undergo during embryonic development poses a serious danger of error amplification, implying that stochastic cellular decision-making should be less common than in unicellular organisms, and control mechanisms should exist to suppress it during development (Arias and Hayward, 2006
). Without proper control, a random switch to an incorrect cell fate in the wrong place or at the wrong time could have detrimental consequences for the adult. For this reason, highly stochastic cell-fate choices may be restricted to specific cell types and developmental stages, such as the differentiation of adult and embryonic stem cells, or the differentiation of cells whose precise location is unimportant (such as retinal patterning and hematopoiesis).
So, given the omnipresence of noise, how precise can animal development be, and what noise control mechanisms are utilized? These questions were addressed recently by monitoring the spatial expression pattern of the gap gene hunchback
in single D. melanogaster
nuclei in response to the morphogen Bicoid (), which is asymmetrically deposited by the mother to the anterior pole of the egg (Gregor et al., 2007
). The fertilized fruit fly zygote initially does not separate into individual cells, allowing Bicoid to freely diffuse away from this pole and create an exponential anterior-posterior gradient along the dividing nuclei. Consequently, single nucleus-wide sections perpendicular to the anterior-posterior axis in the developing embryo will have practically identical, exponentially decreasing morphogen concentrations (), with a 10% drop between neighboring sections, regardless of their location in the embryo (Gregor et al., 2007
). This concentration change is successfully and reliably detected by neighboring nuclei, as indicated by their gene expression pattern (Holloway et al., 2006
). How is it possible to achieve this precision?
Cell-fate specification during lower metazoan development
Among other genes, hunchback
expression represents a critical readout of Bicoid concentration (), restricting future segments in the larva, and later the adult fly to their appropriate locations. Hunchback expression levels showed sigmoidal morphogen dependence, indicating highly cooperative activation by Bicoid (). More importantly, Hunchback had remarkably low noise levels in sets of nuclei exposed to identical morphogen concentrations, with a noise peak corresponding to the steepest region of the Hunchback dose response, where the coefficient of variation was about 20%. Assuming that hunchback
expression noise was originating from Bicoid fluctuations, the authors used the Bicoid-Hunchback dose-response data to infer the noise in Bicoid concentration as perceived by individual nuclei, and found a U-shaped error profile along the anterior-posterior axis, with a minimum coefficient of variation of 10%, consistent with earlier work (Holloway et al., 2006
). This indicates that cellular decision-making is strongly suppressed while setting up hunchback
expression along the embryo in response to Bicoid. Individual nuclei have merely 10% autonomy in deciding what Bicoid concentration is in their surroundings, and setting up the appropriate response.
Seeking to understand how neighboring nuclei could reliably detect a 10% drop in Bicoid concentration, Gregor and co-workers estimated the averaging time necessary to reduce the error that individual nuclei make in estimating Bicoid concentrations, relying solely on stochastic Bicoid binding/dissociation events to/from its DNA binding sites. The results were strikingly inconsistent with the temporal averaging hypothesis, requiring nearly two hours of averaging to reach 10% relative error. Looking for alternatives, the authors asked if spatial averaging could also contribute to noise reduction. Measuring the spatial autocorrelation of Hunchback concentration fluctuations around the mean revealed that nuclear communication indeed occurs over approximately five nuclear distances, reducing the averaging time to a single nuclear cycle (approximately three minutes). In summary, sets of neighboring nuclei talk to each other and jointly accomplish quick and accurate estimates of the local Bicoid gradient. The identity of the mediator for this nuclear communication remains elusive.
To study spatiotemporal patterns of expression for several genes during a later developmental stage (mesodermal patterning), another group applied quantitative in situ
hybridization followed by automated image processing in hundreds of fruit fly embryos (Boettiger and Levine, 2009
). Contrary to the high precision of Hunchback response to Bicoid (Gregor et al., 2007
), several genes had variable, “dotted” expression across the developing pre-mesodermal surface, indicating that gene expression can be noisy even during multicellular development. This noise was, however, transient, since by the end of the mesodermal patterning phase all cells expressed these genes at maximal level, indicating that cells can choose autonomously the time of their activation during mesodermal patterning, but have no freedom to choose their final expression level at the end of this period. Importantly, another subset of genes behaved differently from their noisy peers, and reached their full expression in concert, over a relatively short time scale. Seeking to identify mechanisms underlying this type of “synchrony” for this second subclass of genes, the authors found that their expression was typically regulated through a stalled polymerase. Moreover, one of the low-noise genes, dorsal
, had to be present in two copies for maintaining the synchrony and low noise of other genes from the second subclass. The few genes that still maintained low noise after deleting one dorsal
copy were found to have shadow enhancers – distal sequences involved in gene activation, which apparently ensure the robustness and reliability of expression for a few highly critical developmental genes. These findings indicate that noisy gene expression and stochastic cell-fate decisions would be the default even during metazoan development, if intricate regulatory mechanisms did not exist to suppress these variations, ensuring reliable patterning.
One developmental process that fully exploits cellular decision-making is the patterning of the fly’s eye. Compound fly eyes consist of hundreds of ommatidia, each of which harbor eight photoreceptors, two of which (R7 and R8) are responsible for color vision. Based on rhodopsin (Rh) expression in these photoreceptors, the corresponding ommatidia can become pale or yellow. The pale/yellow choice occurs in the photoreceptor R7 of each ommatidium: if R7 expresses Rh3 then the ommatidium becomes pale, while if it expresses Rh4, the ommatidium becomes yellow. R7’s choice is then transferred to R8 and stabilized through a positive feedback loop between the regulators warts
. Pale and yellow ommatidia are randomly localized and make up 30% and 70% of the fly eye, respectively, suggesting that their positioning results from stochastic cell-fate choices. This random patterning can be abolished by the deletion or overexpression of the transcription factor spineless
, which changes the retinal mosaic into uniformly pale and yellow, respectively (Wernet et al., 2006
Fruit fly development suggests that gene expression noise and stochastic cell-fate choices are carefully controlled and often suppressed, except when they are not disruptive for developmental patterning (Boettiger and Levine, 2009
), or when they are exploited to assign random cell fates with desired probabilities (Wernet et al., 2006
). What happens if noise suppression fails and fluctuations escape from control? This was examined by monitoring mRNA expression in single cells during C. elegans
development (Raj et al., 2010
) in a regulatory cascade composed of multiple feed-forward loops controlling the expression of elt-2
, a self-activating transcription factor critical for intestinal cell-fate specification (). After the 65-cell stage, elt-2
expression was high in all cells of all wild-type worm embryos. However, this uniform expression pattern became variable from embryo to embryo and bimodal within individual embryos after mutation of the transcription factor skn-1
, which sits at the top of the regulatory hierarchy in , and caused lack of intestinal cells in some, but not all, embryos. Similar phenomena, when genetically identical individuals carrying the same mutation show either disrupted or wild-type phenotype, are called partial penetrance.
Counting individual mRNAs in all cells of hundreds of embryos, Raj et al. observed sequential activation of the genes in during development from the top towards the bottom of the hierarchy, with med-1/2 exhibiting an early spike of expression, accompanied by a wider end-3 spike, and a prolonged, but still transient high expression period of end-1. The outcome of these gene expression events was high and stable elt-2 expression and proper intestinal cell-fate specification. By contrast, in the skn-1 mutant the expression of all genes was diminished or absent, and the majority of embryos had practically no elt-2 expression. Moreover, end-1 expression was highly variable within individual embryos, indicating that skn-1 mutations relieve pre-existing noise suppression, thereby allowing stochastic cell-fate decisions to occur. Downregulation of the histone deacetylase hda-1 partially rescued the skn-1 mutant phenotype, indicating that chromatin remodeling was one source of end-1 noise unveiled in skn-1 mutant embryos. However, deletion of upstream transcription factors other than skn-1 (i.e., med-1/2, end-3) did not cause a comparably detrimental reduction of end-1 levels. Taken together, these data suggest that these intermediate transcription factors act in a redundant fashion, buffering noise in the system and ensuring sufficiently high end-1 expression, which can then switch the elt-2 positive feedback loop to the high expression state, ensuring reliable intestinal cell-fate specification.
These examples together indicate that the noise of certain genes is suppressed and buffered by a variety of mechanisms (such as spatial and temporal averaging, stalled polymerases, and redundant regulation) during the development of lower metazoans. Consequently, cellular decision-making is generally suppressed unless specifically required for developmental patterning (as for the ommatidia of the composite fly eye) or unless it is harmless (does not interfere with the execution of the overall developmental program). Disruption of the noise control mechanisms unmasks noise and can have detrimental effects on the development of the organism. Noise control during development may resemble the apparent suppression of cellular individuality during quorum-sensing, which triggers population-wide behavior in microbes. These and similar open questions can be properly addressed in the context of social evolution theory (West et al., 2006
). On the experimental side, much remains to be discovered about the consequences of “letting noise loose” during development. For example, once the factor responsible for spatial averaging across fruit fly nuclei (Gregor et al., 2007
) is identified, it would be interesting to examine how fly development tolerates the inhibition of this inter-nuclear communication.