Microbial individuality: how single-cell heterogeneity enables population level strategies
Introduction
Colonies of microbes exhibit a large degree of physiological heterogeneity at the level of individual cells. One fundamental and long acknowledged type of heterogeneity is the accumulation of genetic mutations by subgroups in the colony [1]. Another, perhaps more subtle, type of heterogeneity is the phenotypic cell-to-cell variation observed even in small isogenic colonies (i.e., when the whole population has the same genotype) and in spatially homogeneous environments [2] (Figure 1a,b).
Technologies that deliver individual cell resolution data, such as time-lapse microscopy, flow cytometry, microfluidics and single-cell RNA-seq, are being increasingly used to precisely quantify cell-to-cell heterogeneity in isogenic populations [3]. At the same time, theoreticians have developed models of this heterogeneity to understand the principles underlying it [4]. It is now apparent that single-cell heterogeneity is a widespread phenomenon, spanning many microbial taxa. Single-cell heterogeneity can manifest itself in processes as diverse as developmental programmes [5, 6••], metabolism [7••], or the partitioning of cytoplasmic content at cell division [8••, 9].
In this review we examine recent advances in characterising phenotypic heterogeneity, the regulatory mechanisms that generate it, and its functionality. Phenotypic heterogeneity may exist only as a consequence of the stochasticity inherent in biochemical interactions, or may be an adaptive trait. We must therefore test whether heterogeneity at the single-cell level provides functionality to the population (Figure 1). Only then can we properly assess phenotypic heterogeneity as a relevant microbial decision-making strategy.
Section snippets
Phenotypic heterogeneity is a widespread phenomenon
Cell-to-cell heterogeneity often reflects variation in the abundance of intracellular proteins. This variation can be inherited, and can be amplified by the biochemical circuitry or the cell cycle progression. Is cell-to-cell variation in protein abundance regulated? High-throughput measurements reveal disparities in how noisy some genes are relative to others within the same organism [10•, 11, 12]. These disparities are not arbitrary because essential genes are typically less noisy than genes
The mechanisms of phenotypic heterogeneity are diverse
Heterogeneity can be mechanistically driven by noisy gene circuits, such as stochastic pulses in the activity of regulatory factors [19]. These pulses have been shown to allow cells to alternate repeatedly between active and inactive states of key cellular processes [15, 16, 19] (Figure 3a). If stochastic pulses are not coordinated across cells, two distinct subpopulations can coexist at any given time, and there is a dynamic turnover of cells from one group to the other. For many of these
Phenotypic heterogeneity implements population level functions
While phenotypic heterogeneity hinges on the expression of single-cell individuality, understanding whether it provides a function or fitness advantage requires a careful consideration of the environmental and population dynamics. Natural environments change in unpredictable ways, and it may be energetically costly to sense the change, or to respond to it in time. One solution is for cells to switch randomly between phenotypes appropriate to each environment at a rate that matches the
Conclusion
Single-cell technologies have transformed our knowledge of microbial behaviour, allowing us to move beyond the limitations of bulk-level observations, and feed a number of exciting scientific propositions. First, noise is pervasive in the cellular environment, generating cell-to-cell heterogeneity [34]. Second, cells evolved genetic circuitry to regulate and use heterogeneity to implement single-cell level functions [14•, 16, 19]. Finally, some single-cell behaviours ought to be seen instead as
References and recommended reading
Papers of particular interest, published within the period of review, have been highlighted as:
• of special interest
•• of outstanding interest
Acknowledgements
We thank Pau Formosa-Jordan, Arijit Das, Om Patange, Stephanie Smith-Unna, José Teles, Jordi Garcia-Ojalvo and Catherine Lichten for critical reading of the manuscript and useful suggestions. The research has received funding from the European Research Council under the European Union's Seventh Framework Programme (FP/2007-2013)/ERC Grant Agreement 338060. The work in the Locke laboratory is also supported by a fellowship from the Gatsby Foundation (GAT3273/GLC).
References (60)
- et al.
Every cell is special: genome-wide studies add a new dimension to single-cell biology
Cell
(2014) - et al.
Tunable stochastic pulsing in the Escherichia coli multiple antibiotic resistance network from interlinked positive and negative feedback loops
PLoS Comput Biol
(2013) - et al.
Phosphorylated DegU manipulates cell fate differentiation in the Bacillus subtilis biofilm
J Bacteriol
(2014) - et al.
Sticking together: building a biofilm the Bacillus subtilis way
Nat Rev Microbiol
(2013) - et al.
Evolutionary systems biology: what it is and why it matters
Bioessays
(2013) - et al.
Mutations of bacteria from virus sensitivity to virus resistance
Genetics
(1943) - et al.
Enzyme induction as an all-or-none phenomenon
Proc Natl Acad Sci U S A
(1957) Noise in biology
Rep Prog Phys
(2014)- et al.
Temporal competition between differentiation programs determines cell fate choice
Mol Syst Biol
(2011) - et al.
Memory and modularity in cell-fate decision making
Nature
(2013)