Biological noise to get a sense of direction: an analogy between chemotaxis and stress response

From the earliest studies on bacteria (Spudich and Koshland, 1976; Elowitz et al., 2002), it was soon understood that biological processes are often dominated by the stochasticity that pervades the physical world. Biological noise, here defined as the substantial cell-to-cell variation that is observed in populations of genetically identical cells, is more and more recognized as an important factor in biology, thanks to the improvement of single cell analysis techniques. The stochasticity of physical phenomena that underlie cellular processes plays an important role in the origin of noise. Noise manifests itself at different levels. At the smallest scales, the random motion of molecules affects basic cellular processes such as transcription, translation, and signal transduction. At a higher level, the topology and connectivity of biological regulatory circuits is often such that stochastic behavior is observed in the levels of specific factors. Specifically, the topology of regulatory networks can feature multiple types of feedback and feed-forward loops, which create multistability in the system and can amplify the fluctuations originating from molecular noise (Burda et al., 2011). Both of these sources of noise can result in the existence of multiple stable states in cells, each defined by specific gene and protein levels. In isogenic cellular population this produces heterogeneity amongst cells and in time as stochasticity forces transitions between the different stable states (Levine et al., 2013; Sanchez and Golding, 2013). Although there is a clear difference between noise, which does not have a unique definition, and heterogeneity at the population level, the two phenomena are closely connected (Huang, 2009). At first sight, the complexity of biological behavior would seem to require the strictest control of underlying processes, suggesting a constant evolutionary fight against the inherent disadvantages of noise. This is certainly the case, for example in the evolution of accurate proof-reading mechanisms that ensure faithful DNA replication. However, recent results also support the view that controlled levels of stochasticity are important in cells, proposing noise as a selectable trait. Already in 2004 Raser and O'Shea identified mutations both acting in cis and trans that affected the levels of gene expression noise, which is viewed as an evolvable trait (Raser and O'Shea, 2004). Ansel and colleagues later showed that the levels of expression noise in a single gene can be a heritable trait and they identified three Quantitative Trait Loci associated to it (Ansel et al., 2008). The adaptive importance of noise is exemplified in the concept of bet-hedging, according to which cells maximize their chance of survival by exploring different states in a random fashion (Fehrmann et al., 2013; Viney and Reece, 2013; Yvert et al., 2013). The positive aspects of noise manifest themselves at many levels at which noise acts. At the molecular level, a control strategy based on dynamic equilibrium of stochastic events, similar to a thermostat regulating temperature, offers more robustness and tunability in processes such as mRNA production and translation (Shalem et al., 2008; Salari et al., 2012; Sanchez and Golding, 2013). At the level of regulatory networks, topologies, and logic relations allowing oscillations and multistability contribute to higher adaptability of the organism to changing environments. It was recently shown that stress in yeast provokes a clear change in network topology, which can promote phenotype differentiation within a population (Mihalik and Csermely, 2011; Lehtinen et al., 2013). We can hypothesize that the observed loosening of the network could serve to diversify phenotypes in the different cells. Single cell monitoring of phenotypes in tissues suggests a high degree of heterogeneity even in multi-cellular organisms (Paszek et al., 2010). An important factor in cell-cell communication, NFkB (nuclear factor kappa-light-chain-enhancer of activated B cells), undergoes continuous cycles of nuclear localization, such that in a population only a fraction of the cells at any time will have high levels of this transcription factor's activity (Ashall et al., 2009). In the overall context of a tissue, this heterogeneity in activation levels of NFkB contributes to the maintenance of homeostasis and to tissue responsiveness. Thus, even at the tissue level, the presence of fluctuations in time and across cellular populations serves as a detection tool that ensures fast reaction to any changes in the tissue's condition (Paszek et al., 2010; Levine et al., 2013). Although the connections between noise at these different levels are still to be elucidated, noise pervades biological life forms across evolutionary time and there does not seem to have been a strong negative evolutionary pressure to eliminate it, with a few exceptions (Lehner, 2008). A possible generalized interpretation of the above observations is that fluctuations, and hence noise at multiple levels, are instrumental in granting a robust control strategy to organisms enabling them to adapt to changing environments. We will try to substantiate this claim through two examples that lead us to make an analogy between bacteria aiming to reach a source of food and a population of yeast aiming to reach a state of optimal growth in a varying environment.