Stochastic and Advanced article Deterministic Decision in Article Contents . Introduction Cell Fate . Cell Fate Determination . Deterministic Cell Fate Decisions David J Menn, Arizona State University, Tempe, Arizona, USA . Stochastic Cell Fate Decisions . Synthetic Biology Approaches Xiao Wang, Arizona State University, Tempe, Arizona, USA Online posting date: 15th April 2014 From bacteria to mammals, individual cells from an iso- 2004). Stochastic differentiation can also offer functional genic population are able to assume roles resulting in benefits for a population. When in starvation conditions, phenotypic heterogeneity. The mechanisms used to make Bacillus subtilis exhibits a bet-hedging strategy in which these cell fate decisions range from highly deterministic members choose randomly between states of sporulation, diauxic growth and lysis (Suel et al., 2006; Veening et al., to essentially random. This wide range of behaviour 2008). Other stochastic decisions provide a simple method springs from the interplay of intracellular molecular of assigning labour division between associated cells, such kinetics, the topologies of underlying gene regulator as in the random differentiation of photoreceptors to dif- networks, epigenetic control mechanisms and cell– ferent colour-sensitive variants in Drosophila (Wernet environment interactions. Cells utilise these factors to et al., 2006). implement differentiation strategies such as develop- Despite this randomness, however, cell fate determina- mental rigidity, which ensures the development of key tion is often not a stochastic process. Rather, many fate structures in multicellular organisms, and bet hedging, decisions proceed in a highly deterministic manner, often the introduction of nongenetic variability to promote in response to cues from the environment or neighbouring population fitness. Because decision-making genes in cells. The transition of a fertilised oocyte into a blastocyst natural systems are integrated with myriad other demonstrates how precisely cell differentiation can be guided through multiple stages of development (Clift pathways, they can be difficult to study on their own. and Schuh, 2013). Similar deterministic developmental Synthetic biology offers a means to study cell differ- processes have been documented in early growth and entiation in vivo in a manner separated from normal body segmentation of Drosophila melanogaster due to cellular functions. transcription factor gradients (Lee and Orr-Weaver, 2003). Noise is a fact of life, arising from sources such as cell– cell signalling, intracellular molecular dynamics, and Introduction chromatin modification and packaging (Blake et al., 2003; Elowitz, 2002). Organisms have adapted to utilise or The many processes that comprise gene regulation – counteract this noisy expression in a context-dependent transcription, translation, protein and messenger ribonu- manner. Understanding the mechanisms by which they cleic acid (mRNA) degradation, etc. – are inherently sto- achieve this is of fundamental importance in under- chastic (Kaern et al., 2005). This is because, at the standing how cells make decisions. By understanding both molecular level, all cellular decisions are the result of ran- the deterministic and stochastic elements of cell decision dom molecular interactions. These stochastic interactions making, we can open up new venues in cell reprogramming can give rise to heterogeneity within an otherwise homo- and therapeutics with which scientists and engineers are genous population. In mice, which have roughly 1000 dif- only beginning to experiment. ferent olfactory receptors, stochastic differentiation provides a simple mechanism for individual sensory neu- rons to randomly express a single receptor (Mombaerts, Cell Fate Determination eLS subject area: Cell Biology Cellular adaptability and role assignment has allowed life to thrive, in both single cellular and multicellular states. How to cite: Central to this adaptability is the ability of individual Menn, David J; and Wang, Xiao (April 2014) Stochastic and cells to differentiate into specialised variants that comple- Deterministic Decision in Cell Fate. In: eLS. John Wiley & Sons, Ltd: ment each other. For example, some cells in a B. subtilis Chichester. population may transition to a state of competency, in DOI: 10.1002/9780470015902.a0025319 which they uptake foreign deoxyribonucleic acid (DNA), eLS & 2014, John Wiley & Sons, Ltd. www.els.net 1 Stochastic and Deterministic Decision in Cell Fate whereas others retain a tepid relationship with non-native Deterministic Cell Fate Decisions DNA (Maamar et al., 2007), increasing diversity to improve overall population fitness. Mating yeast adopt a We know through the observation of natural systems that mating type on cell division, determining viable mating cells are capable of deterministic differentiation. Devel- partners and promoting evolutionary diversification opmental biology is particularly rife with examples. Per- (Peisajovich et al., 2010). In multicellular organisms, stem haps one of the starkest examples is the embryonic cells differentiate into specific lineages unique to the mul- development of Caenorhabditis elegans (Sulston et al., titude of tissues and organs found throughout the body 1983). The development of C. elegans has been thoroughly (Enver et al., 2009). Whether as a means to promote traced from zygote to larva, from a single cell to exactly 671 population fitness or as a way to form the various parts of a cells, with such a rigid developmental pattern as for Sulston larger organism, cells adopt roles, resulting in phenotypic et al. to declare the process ‘essentially invariant’. The changes, which cannot be easily reversed (Balazsi et al., process is not only invariant in terms of cell count at var- 2011). ious stages but also shows remarkable time resolution. For Through the process of differentiation, cells arrive at example, under similar experimental conditions, one can their fate: a quasi-equilibrium state of gene expression expect to see exactly 28 cells and the beginning of gas- characterised by functional and phenotypic steady states. trulation 100 min after first cleavage. A large number of Cell fate is a complex phenomenon involving the balance these cells, 111 or 113 depending on the sex of the nema- of many intracellular interactions (Macarthur et al., tode, are programmed to ultimately die in the development 2009). One of the primary defining qualities of a cell fate is process, before the nematode’s hatching at 800 min after its invariance to noise, to the extent that many cell fate first cleavage. See also: Caenorhabditis elegans Embry- decisions are considered irreversible (Vierbuchen et al., ogenesis: Genetic Analysis of Cell Specification 2010). Although the advent of induced pluripotent stem On an intuitive level, deterministic embryonic develop- cells has challenged the absolute irreversibility of differ- ment makes sense. For a single fertilised egg to reliably entiated cell fates, cell fate decisions can still be considered divide into an entire multicellular organism, early pro- invariable to internal noise (Yamanaka, 2009). Without genitor cells for the various tissues would need to be placed an external force, a cell that has already differentiated to exactly, both spatially and temporally. It is no surprise then a given fate will not spontaneously dedifferentiate to a that this sort of strictly deterministic cell fate assignment is previous state. commonly observed throughout the biological world. There are two prevailing analogies for cell fate deter- Reduction in variability during development, a process mination. The first is that of the epigenetic landscape, in often referred to as canalisation or phenotypic stability, which a marble rolls down a hill containing a number of has been observed in blastocyst formation in D. melano- separate valleys (Waddington, 1957). As the marble travels gaster (Manu et al., 2009), the zebra fish dermal skeleton further down the hill, the valleys bifurcate into more and development (DeLaurier et al., 2014) and early human more specific channels. The valleys represent potential cell embryogenesis (Clift and Schuh, 2013). This lack of var- fates, their walls representing the forces at work that iation, like all cellular processes, is due to gene expression maintain a chosen fate. Cells choose fates based on the regulation. See also: Autonomous Cell Fate Specification: layout of this landscape and through random variations Overview that develop along the journey towards a final fate. The Gene expression and its regulation are inherently sto- second analogy for fate selection is that of a dynamic chastic processes (Kaern et al., 2005). Despite this, cells attractor in high-dimensional gene expression space have evolved mechanisms to reduce or ignore this noise in (Kauffman, 1969). Somewhat less intuitive than Wad- order to act in a deterministic fashion. Gene regulatory dington’s landscape, this visualisation emphasises the networks (GRNs) are the key to this behaviour (Davidson complexity of gene interactions. The state of a genetic and Levine, 2008). GRNs are, both topologically and system is represented as its location within a multi- functionally, composed of small network motifs (Alon, dimensional gene expression space: typically with more 2007), and several common motifs function to regulate the than 3 dimensions; hence, nonsimplified visualisation is noise of their output signal. Negative feedback loops have difficult or impossible. Certain