When someone mentions "bet-hedging", the first thing that comes to mind is an economic investment or gambling strategy, one that maximizes a human's return on their investment. This necessitates cognitive mechanisms for decision-making and valuation. For example, a bet-hedger might keep their investments in two places (e.g a rowboat and a hang-glider). When the return on one potential source of income is exhausted (e.g. rowboat goes over the falls), the other investment can be drawn upon to pick up the slack. Overall, total losses are minimized and potential gains are maximized.
Bet-hedging as a human investment strategy. Hence the rowboat and hang-glider analogy.
But bet-hedging has also been used as a means to explain biological "decision-making" with respect to adaptive changes in genotype and/or phenotype. In this case, decision-making refers to directed changes in a lineage that emerge from stochastic mechanisms. There is no need for a set of formal cognitive mechanisms (or a designer), because in this case natural selection plays the role of a brain (e.g. information processing). In the case of biological bet-hedging, an organism hedges between two or more phenotypic/genotypic states (or behavioral strategies), one becoming predominant only when encouraged by environmental conditions.
Figure 1. A statistical view of biological bet-hedging. COURTESY: Discussion of bet-hedging and adaptation to environmental stresses in [1].
To understand how biological bet-hedging might work, we can use a Venn diagram to take a statistical view of the process (Figure 1). Some form of switching (phenotypic, genotypic) is induced by a subset of environmental stimuli. A smaller subset of positive responses are triggered by environmental stress. This relatively small resulting set of adaptive responses (switching due to an environmental stress signal) should (in theory) be the outcomes of highest fitness value.
Selection on random noise is driven by inherent oscillations in gene expression. Gene expression differences (e.g. differential gene expression) are usually thought to define distinct biological processes and cell types. However, gene expression also exhibits wide-band fluctuations [2] and "bursty" changes over time [3], even within the same process or cell type. A recent review in Science on oscillating gene expression over time (e.g. gene expression noise) and biological bet-hedging [4] discusses these mechanisms in more detail.
Figure 2. Type A transcriptional oscillations, sensu [4]. One example of genotypic bet-hedging.
The first type of bet-hedging (type A) is indirect, and involves retaining two or more context-dependent mechanisms for the expression of a single gene. In Figure 2, the successful transcription of a downstream target gene depends on the synchronized activity of two upstream transcription factors. In this case, each upstream gene fluctuates with respect to time. Only when their fluctuations become coordinated in-phaseare they capable of activating a downstream target. In fact, in order to exhibit this selective synchronization, the upstream gene expression must be oscillatory. Otherwise, the downstream gene would not be sensitive to environmental context.
Figure 3. Type B transcriptional oscillations, sensu [4]. Another example of genotypic bet-hedging.
By contrast, type B bet-hedging (direct) is a matter of selecting between alternating genotypic or phenotypic states. In this case, upstream genetic mechanisms create a bistable switch which allows the organism to switch between states given an environmental signal. In the case of stochastic bet-hedging, switching can be like a roulette wheel, in which all possible states are generated spontaneously. The most (as opposed to transient) stable states are those which are most strongly supported by the environment. This is a candidate model for how cells acquire and maintain their identity in microenvironmental niches. Yet it is also relevant to evolutionary change.
Instead of individual phenotypes being the focus of selection, perhaps the ability to switch between phenotypes itself is selected as a trait. For example, stochastic phenotype switching in bacteria results in persistence in the face of rapid environmental variation [5]. Using Pseudomonas fluorescens lineages, phenotypic switching can be experimentally evolved. In fact, the capacity for switching can be isolated to a single gene mutation (CarB), which is both sufficient and necessary for the colony switching trait.
Although stochastic switching is a single trait, it is by no means a simple one. Not only does CarB enable colony switching, but lineages that carry this mutation have a higher fitness compared to those that do not among mixed cultures in a static environment. In the experiments of [5], it took multiple rounds of selection to evolve the CarB mutant. This may also be due to enabling mutations and lineage-specific dependencies which set up the transition to a CarB mutant phenotype.
CarB mutation, examined within a single bet-hedging lineage. TOP: fitness, MIDDLE: genotypes, BOTTOM: phenotypes.
* end of Eukaryotic life, in 1.3 billion years.
* end of Prokaryotic and Archean life, in 2.8 billion years.
* end of C3 photosynthesis, in 600 million years.
* end of C4 photosynthesis, in 800 million years.
* Earth's temperature rises to 47C due to an increase in solar luminosity, in 1 billion years.
Some of the predictions are provocative, such as the extinction of the Y chromosome [7]. However, one set of predictions intersect with the literature on bet-hedging: the end of photosynthesis. What we know about the possible end of photosynthesis comes from studies [8, 9] that examine the instability and breakdown of photosynthetic reactions at high temperatures. A primary producer's photosynthesis rate becomes unstable above a threshold temperature [8]. When temperature is lowered, this rate returns to normal.
When applied in a laboratory or experienced during heat waves, severe heat stress can cause cellular damage. In fact, large-scale process-based models of photosynthesis assumes that the rate returns to normal after environmental shocks [9]. However, what happens in cases where the average temperature reaches or exceeds this threshold? In such cases, extreme temperatures are not experienced as shocks, but as the physiological set-point.
View of a "red giant" Sun from a now-barren (far future) Earth. Humans, the oceans, and perhaps all extremophiles are all gone at this point.
According to the infographic's predictions, in 0.6 to 2.8 billion that will be that (although I'm not sure why primary producers would be the first type of life to die out). Yet there might be three fundamental changes to life's complexity as we reach a red giant Sun that enable it to survive until perhaps the physical end of the Earth (and/or Sun):
* the radical restructuring of organismal physiology to suit temperatures that will approach the boiling point of water. This might include hard insulating shells, smaller areas of exposed surface, and "interesting" changes to metabolism. The hedging concept could come into play here, as the expression of genes and phenotypes associated with metabolic function in all organisms (not just single-celled ones) could fluctuate significantly across life-history.
* the radical restructuring of food webs so as to reduce any one source of primary or secondary production. Bets would be hedged in order to survive ever increasing extreme conditions. The increase of energy in the biosphere could lead to more energy being available in general. But of course there could be biospheric tradeoffs (atmospheric composition) which could limit ecological complexity. The sources of primary production would of course need to adapt to take advantage of this situation.
* the evolution of primary production itself. Like complex organisms, we should not expect photosynthesis to simply disappear. Recall that C4 photosynthesis was dominant in the Paleozoic era, only to be eclipsed by the C3 variety during the Mesozoic era. And this transition occurred despite C4 photosynthesis being more efficient than C3 in times of heat stress and draught [10]. It might turn out that a new type of hyper-efficient and multiphasic photosynthesis could evolve that takes advantage of late solar system conditions.
These points are speculative as well, but remember -- fully-functioning ecosystems that are gradually exposed to extreme conditions will likely adapt instead of coming to an abrupt end. It would be hard to transplant existing organisms (even extremophiles) into these conditions, but it might not be as hard to evolve responses to the extremities of late Earth.
[1] Mostowy, R. Evolution of Stress Response in the Face of Unreliable Environmental Signals. Rafal Mostowy blog, August 20 (2012).
[2] Eldar, A. and Elowitz, M.B. Functional roles for noise in genetic circuits. Nature, 467, 167-173 (2010).
[3] Goh, K-I. and Barabasi, A-L. Burstiness and Memory in Complex Systems. arXiv:0610233.
[4] Levine, J.H., Lin, Y., and Elowitz, M.B. Functional Roles of Pulsing in Genetic Circuits. Science, 342, 1193 (2013).
[5] Beaumont, H.J.E., Gallie, J., Kost, C., Ferguson, G.C., and Rainey, P.B. Experimental evolution of bet hedging. Nature, 462, 90-93 (2009).
[6] Timeline of the Far Future. BBC Future, January 6 (2014).
[7] This is an example of a scientific debate disguised as persistent myth in the popular press. For two perspectives (the former Y-optimist, the latter Y-pessimist), please see:
a) Hughes, J.F. et.al Strict evolutionary conservation followed rapid gene loss on human and rhesus Y chromosomes. Nature, 483, 82-86 (2012).
b) Aitken, R.J. and Marshall-Graves, J.A. Human Spermatozoa: the future of sex. Nature, 415, 963 (2002).
[8] Sage, R.F. and Kubien, D.S. The temperature response of C3 and C4 photosynthesis. Plant, Cell, and Environment, 30, 1086-1106 (2007).
[9] Huve, K., Bichele, I., Rasulov, B., and Niinemets, U. When it is too hot for Photosynthesis: heat-induced instability of photosynthesis in relation to respiratory burst, cell permeability changes and H2O2 formation. Plant, Cell, and Environment, 34, 113-126 (2011).
[10] Liu, Z., Sun, N., Yang, S., Zhao, Y., Wang, X., Hao, X., and Qiao, Z. Evolutionary transition from C3 to C4 photosynthesis and the route to C4 rice. Biologia, 68(4), 577-586 (2013).
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