Neuroendocrine control of life histories: what do we need to know to understand the evolution of phenotypic plasticity?

Almost all life histories are phenotypically plastic: that is, life-history traits such as timing of breeding, family size or the investment in individual offspring vary with some aspect of the environment, such as temperature or food availability. One approach to understanding this phenotypic plasticity from an evolutionary point of view is to extend the optimality approach to the range of environments experienced by the organism. This approach attempts to understand the value of particular traits in terms of the selection pressures that act on them either directly or owing to trade-offs due to resource allocation and other factors such as predation risk. Because these selection pressures will between environments, the predicted optimal phenotype will too. The relationship expressing the optimal phenotype for different environments is the optimal reaction norm and describes the optimal phenotypic plasticity. However, this view of phenotypic plasticity ignores the fact that the reaction norm must be underlain by some sort of control system: cues about the environment must be collected by sense organs, integrated into a decision about the appropriate life history, and a message sent to the relevant organs to implement that decision. In multicellular animals, this control mechanism is the neuroendocrine system. The central question that this paper addresses is whether the control system affects the reaction norm that evolves. This might happen in two different ways: first, the control system will create constraints on the evolution of reaction norms if it cannot be configured to produce the optimal reaction norm and second, the control system will create additional selection pressures on reaction norms if the neuroendocrine system is costly. If either of these happens, a full understanding of the way in which selection shapes reaction norms must include details of the neuroendocrine control system. This paper presents the conceptual framework needed to explain what is meant by a constraint or cost being created by the neuroendocrine system and discusses the extent to which this occurs and some possible examples. The purpose of doing this is to encourage endocrinologists to take a fresh look at neuroendocrine mechanisms and help identify the properties of the system and situations in which these generate constraints and costs that impinge on the evolution of phenotypic plasticity.     

Testing optimality with experimental evolution: lysis time in a bacteriophage

Optimality models collapse the vagaries of genetics into simple trade-offs to calculate phenotypes expected to evolve by natural selection. Optimality approaches are commonly criticized for this neglect of genetic details, but resolution of this disagreement has been difficult. The importance of genetic details may be tested by experimental evolution of a trait for which an optimality model exists and in which genetic details can be studied. Here we evolved lysis time in bacteriophage T7, a virus of Escherichia coli. Lysis time is equivalent to the age of reproduction in an organism that reproduces once and then dies. Delaying lysis increases the number of offspring but slows generation time, and this trade-off renders the optimum sensitive to environmental conditions: earlier lysis is favored when bacterial hosts are dense, later lysis is favored when hosts are sparse. In experimental adaptations, T7 evolved close to the optimum in conditions favoring early lysis but not in conditions favoring late lysis. One of the late lysis adaptations exhibited no detectable phenotypic evolution despite genetic evolution; the other evolved only partly toward the expected optimum. Overall, the lysis time of the adapted phages remained closer to their starting values than predicted by the model. From the perspective of the optimality model, the experimental conditions were expected to select changes only along the postulated trade-off, but a trait outside the trade-off evolved as well. Evidence suggests that the model's failure ultimately stems from a violation of the trade-off, rather than a paucity of mutations.     

Evolutionary engineering of Corynebacterium glutamicum

A unique feature of biotechnology is that we can harness the power of evolution to improve process performance. Rational engineering of microbial strains has led to the establishment of a variety of successful bioprocesses, but it is hampered by the overwhelming complexity of biological systems. Evolutionary engineering represents a straightforward approach for fitness‐linked phenotypes (e.g., growth or stress tolerance) and is successfully applied to select for strains with improved properties for particular industrial applications. In recent years, synthetic evolution strategies have enabled selection for increased small molecule production by linking metabolic productivity to growth as a selectable trait. This review summarizes the evolutionary engineering strategies performed with the industrial platform organism Corynebacterium glutamicum. An increasing number of recent studies highlight the potential of adaptive laboratory evolution (ALE) to improve growth or stress resistance, implement the utilization of alternative carbon sources, or improve small molecule production. Advances in next‐generation sequencing and automation technologies will foster the application of ALE strategies to streamline microbial strains for bioproduction and enhance our understanding of biological systems.     

Phenotypic plasticity as a state-dependent life-history decision

Summary A genotype is said to show phenotypic plasticity if it can produce a range of environmentally dependent phenotypes. Plasticity may or may not be adaptive. We consider plasticity as a genetically determined trait and thus find the optimal response of an animal to its environment. Various aspects of this optimal response are illustrated with examples based on reproductive effort. We investigate the selection pressure for plastic as opposed to fixed strategies. An example with spatial heterogeneity is used to compare our approach with that of Stearns and Koella (1986).     

Adaptationism and Engineering

The rights and wrongs of adaptationism areoften discussed by appeal to what I call theartefact model. Anti-adaptationistscomplain that the use of optimality modelling,reverse engineering and other techniques areindicative of a mistaken and outmoded beliefthat organisms are like well-designedartefacts. Adaptationists (e.g. Dennett 1995)respond with the assertion that viewingorganisms as though they were well designed isa fruitful, perhaps necessary research strategyin evolutionary biology. Anti-adaptationistsare right when they say that techniques likereverse engineering are liable to mislead. This fact does not undermine the artefact modelprecisely because the same techniques misleadus for the same reasons when they are appliedunreflectively to artefacts. Thoseadaptationists who hold only that it isworthwhile to investigate organisms as thoughthey were artefacts and thoseanti-adaptationists who criticise simplisticdesign models have far more in common than thelabels attached to their positions mightsuggest.     

Evolutionary optimality applied to Drosophila experiments: hypothesis of constrained reproductive efficiency

The general purpose of the paper is to test evolutionary optimality theories with experimental data on reproduction, energy consumption, and longevity in a particular Drosophila genotype. We describe the resource allocation in Drosophila females in terms of the oxygen consumption rates devoted to reproduction and to maintenance. The maximum ratio of the component spent on reproduction to the total rate of oxygen consumption, which can be realized by the female reproductive machinery, is called metabolic reproductive efficiency (MRE). We regard MRE as an evolutionary constraint. We demonstrate that MRE may be evaluated for a particular Drosophila phenotype given the fecundity pattern, the age-related pattern of oxygen consumption rate, and the longevity. We use a homeostatic model of aging to simulate a life history of a representative female fly, which describes the control strain in the long-term experiments with the Wayne State Drosophila genotype. We evaluate the theoretically optimal trade-offs in this genotype. Then we apply the Van Noordwijk-de Jong resource acquisition and allocation model, Kirkwood's disposable soma theory. and the Partridge-Barton optimality approach to test if the experimentally observed trade-offs may be regarded as close to the theoretically optimal ones. We demonstrate that the two approaches by Partridge-Barton and Kirkwood allow a positive answer to the question, whereas the Van Noordwijk-de Jong approach may be used to illustrate the optimality. We discuss the prospects of applying the proposed technique to various Drosophila experiments, in particular those including manipulations affecting fecundity.     

It is optimal to be optimistic about survival

We investigate the optimal behaviour of an organism that is unable to obtain a reliable estimate of its mortality risk. In this case, natural selection will shape behaviour to be approximately optimal given the probability distribution of mortality risks in possible environments that the organism and its ancestors encountered. The mean of this distribution is the average mortality risk experienced by a randomly selected member of the species. We show that if an organism does not know the exact mortality risk, it should act as if the risk is less than the mean risk. This can be viewed as being optimistic. We argue that this effect is likely to be general.     

Convergent Evolution of Mechanically Optimal Locomotion in Aquatic Invertebrates and Vertebrates

Examples of animals evolving similar traits despite the absence of that trait in the last common ancestor, such as the wing and camera-type lens eye in vertebrates and invertebrates, are called cases of convergent evolution. Instances of convergent evolution of locomotory patterns that quantitatively agree with the mechanically optimal solution are very rare. Here, we show that, with respect to a very diverse group of aquatic animals, a mechanically optimal method of swimming with elongated fins has evolved independently at least eight times in both vertebrate and invertebrate swimmers across three different phyla. Specifically, if we take the length of an undulation along an animal’s fin during swimming and divide it by the mean amplitude of undulations along the fin length, the result is consistently around twenty. We call this value the optimal specific wavelength (OSW). We show that the OSW maximizes the force generated by the body, which also maximizes swimming speed. We hypothesize a mechanical basis for this optimality and suggest reasons for its repeated emergence through evolution.     

A comparative method for studying adaptation to a randomly evolving environment

Most phylogenetic comparative methods used for testing adaptive hypotheses make evolutionary assumptions that are not compatible with evolution toward an optimal state. As a consequence they do not correct for maladaptation. The "evolutionary regression" that is returned is more shallow than the optimal relationship between the trait and environment. We show how both evolutionary and optimal regressions, as well as phylogenetic inertia, can be estimated jointly by a comparative method built around an Ornstein-Uhlenbeck model of adaptive evolution. The method considers a single trait adapting to an optimum that is influenced by one or more continuous, randomly changing predictor variables.     

Engineering Tools for the Development of Recombinant Lactic Acid Bacteria

Lactic acid bacteria (LAB) is mainly used in food fermentation. In addition, LAB fermentation technology has been studied in the development of industrial food additives, nutrients, or enzymes used in food processing. In the field of red biotechnology, LAB is approved and is generally recognized as a safe organism and is considered safe for biotherapeutic treatments. Recent clinical trials have demonstrated the medicinal value of therapeutic recombinant LAB and the suitability of innate mechanisms of secretion and anchoring for therapeutic applications such as antibody or vaccine production. However, the gram‐positive phenotypic trait of LAB creates challenges for genetic modifications when compared to other conventional workhorse bacteria, resulting in exclusive developments of genetic tools for engineering LAB. In this review, several distinct approaches in gene expression for engineering LAB are discussed.     

How (not) to test an optimality model

The controversy over the use of optimality models in the investigation of adaptation is long-standing. Nonetheless, little or no attention has been paid in this debate to the most important question to be asked about such models: how should the test of an optimality model be structured if the local optimality of the trait is to be assessed? Here we answer this question and describe how such a test can contribute to a test of adaptationism.     

Intraspecific competition reduces niche width in experimental populations

Intraspecific competition is believed to drive niche expansion, because otherwise suboptimal resources can provide a refuge from competition for preferred resources. Competitive niche expansion is well supported by empirical observations, experiments, and theory, and is often invoked to explain phenotypic diversification within populations, some forms of speciation, and adaptive radiation. However, some foraging models predict the opposite outcome, and it therefore remains unclear whether competition will promote or inhibit niche expansion. We conducted experiments to test whether competition changes the fitness landscape to favor niche expansion, and if competition indeed drives niche expansion as expected. Using Tribolium castaneum flour beetles fed either wheat (their ancestral resource), corn (a novel resource) or mixtures of both resources, we show that fitness is maximized on a mixed diet. Next, we show that at higher population density, the optimal diet shifts toward greater use of corn, favoring niche expansion. In stark contrast, when beetles were given a choice of resources, we found that competition caused niche contraction onto the ancestral resource. This presents a puzzling mismatch between how competition alters the fitness landscape, versus competition's effects on resource use. We discuss several explanations for this mismatch, highlighting potential reasons why optimality models might be misleading.     

Heuristic optimization of the general life history problem: A novel approach

Summary The general life history problem concerns the optimal allocation of resources to growth, survival and reproduction. We analysed this problem for a perennial model organism that decides once each year to switch from growth to reproduction. As a fitness measure we used the Malthusian parameterr, which we calculated from the Euler-Lotka equation. Trade-offs were incorporated by assuming that fecundity is size dependent, so that increased fecundity could only be gained by devoting more time to growth and less time to reproduction. To calculate numerically the optimalr for different growth dynamics and mortality regimes, we used a simplified version of the simulated annealing method. The major differences among optimal life histories resulted from different accumulation patterns of intrinsic mortalities resulting from reproductive costs. If these mortalities were accumulated throughout life, i.e. if they were senescent, a bangbang strategy was optimal, in which there was a single switch from growth to reproduction: after the age at maturity all resources were allocated to reproduction. If reproductive costs did not carry over from year to year, i.e. if they were not senescent, the optimal resource allocation resulted in a graded switch strategy and growth became indeterminate. Our numerical approach brings two major advantages for solving optimization problems in life history theory. First, its implementation is very simple, even for complex models that are analytically intractable. Such intractability emerged in our model when we introduced reproductive costs representing an intrinsic mortality. Second, it is not a backward algorithm. This means that lifespan does not have to be fixed at the begining of the computation. Instead, lifespan itself is a trait that can evolve. We suggest that heuristic algorithms are good tools for solving complex optimality problems in life history theory, in particular questions concerning the evolution of lifespan and senescence.     

The green beards of language

Language transfers information on at least three levels; (1) what is said, (2) how it is said (what language is used), and, (3) that it is said (that speaker and listener both possess the ability to use language). The use of language is a form of honest cooperation on two of these levels; not necessarily on what is said, which can be deceitful, but always on how it is said and that it is said. This means that the language encoding and decoding systems had to evolve simultaneously, through mutual fitness benefits. Theoretical problems surrounding the evolution of cooperation disappear if a recognition system is present enabling cooperating individuals to identify each other – if they are equipped with “green beards”. Here, I outline how both the biological and cultural aspects of language are bestowed with such recognition systems. The biological capacities required for language signal their presence through speech and understanding. This signaling cannot be invaded by “false green beards” because the traits and the signal of their presence are one and the same. However, the real usefulness of language comes from its potential to convey an infinite number of meanings through the dynamic handling of symbols – through language itself. But any specific language also signals its presence to others through usage and understanding. Thus, languages themselves cannot be invaded by “false green beards” because, again, the trait and the signal of its presence are one and the same. These twin green beards, in both the biological and cultural realms, are unique to language.     

The geometry of the Pareto front in biological phenotype space

When organisms perform a single task, selection leads to phenotypes that maximize performance at that task. When organisms need to perform multiple tasks, a trade‐off arises because no phenotype can optimize all tasks. Recent work addressed this question, and assumed that the performance at each task decays with distance in trait space from the best phenotype at that task. Under this assumption, the best‐fitness solutions (termed the Pareto front) lie on simple low‐dimensional shapes in trait space: line segments, triangles and other polygons. The vertices of these polygons are specialists at a single task. Here, we generalize this finding, by considering performance functions of general form, not necessarily functions that decay monotonically with distance from their peak. We find that, except for performance functions with highly eccentric contours, simple shapes in phenotype space are still found, but with mildly curving edges instead of straight ones. In a wide range of systems, complex data on multiple quantitative traits, which might be expected to fill a high‐dimensional phenotype space, is predicted instead to collapse onto low‐dimensional shapes; phenotypes near the vertices of these shapes are predicted to be specialists, and can thus suggest which tasks may be at play.     

基因工程生物的生态影响及其评价

随着基因工程技术的迅速发展,基因工程产生的生物将被广泛地应用于非受控的自然环境中,这将带来诸多的环境和生态方面的问题。本文概述了基因工程生物在非受控环境下可能产生的生态影响,提出了“基因工程生态学”这一新的应用生态学分支领域,探讨了该分支学科的概念、主要研究内容和目标,以及当前应采取的研究策略,并就发展基因工程生态学的有关问题提出了建议。     

Optimierung und ökonomisierung im kontext von evolutionstheorie und phylogenetischer rekonstruktion

The meaning of optimality and economy in phylogenetics and evolutionary biology is discussed. It can be shown that the prevailing concepts of optimality and economy are equivocal as they are not based on strict theoretical positions and as they have a variable meaning in different theoretical contexts. The ideas of optimality and economy can be considered to be identical with the expectation of a relatively simple order in a particular field of study. Although there exists no way of inferring one or several methods of solving scientific problems from the presupposed idea of economy and optimality, a lack of motivation for scientific investigations would result if the concepts of economy and optimality in nature were dropped. By reference to several examples, it is shown that the concepts of optimality and economy are only useful against the background of indispensable theories. If there is a shift from one theory to another, a restriction on the use of these concepts is necessary. Optimality and economy in the sense of operations research in engineering or economical sciences depend on the principle of minimum costs. Both theoretical concepts: technical efficiency in relation to the energy required to run a machine and profit maximation in an economical framework must be shown to be realistic assumptions. In the field of biology processes of optimization and economization are normally discussed under two different views:

1. The concept of economy is used in cases of functional adaptation when the organism makes good use of the building material which is available to fulfill one (or more) functions. The theoretical background must be seen in the energy-consuming aspect of the organism.
2. In evolutionary change and phylogeny ‘economization’ and ‘optimization’ are deduced from the evolutionary theory, and evolution is shown to produce a special kind of biological economy in biological systems (Bock & von Wahlert, 1965). The ‘Okonomie-Prinzip’ or ‘Lesrichtungskriterium’ points out the arguments needed to state a phylogenetic theory and to construct a dendrogram (Peters & Gutmann, 1971).

In every phylogenetic theory concerning the adaptational change in the evolving biological system an explanation for the function of all stages is required. Only those statements should be accepted as phylogenetic theories which are characterized by the demonstration of the process of economization in the functional relations of the evolving organism. The process of adaptation can be determined by the improved chance of some mutants to propagate their genetical information. In this process all functional systems in their interrelations — i.a. mutual dependence — and their relation with the environment add their functional efficiency to the information to be delivered to their progeny, because the more economical biological system in a certain environment will have a better chance to produce offspring. This outcome is affirmed by natural selection which works on all levels of the evolving biological systems (Gutmann & Peters 1973). Nevertheless a judgment about adaptation cannot be taken as a scale of measurement in the phylogenetic process. The conditions in the organism itself and in the environment or in the organic system alone can change in so profound a manner that the marginal conditions of the earlier stages of the process of adaptation are not the same as in the derived ones. During phylogenetic change of the evolving organism the selective strains are also continuously changing. As a consequence no state or invariant concept of economy can cover the different stages of the phylogenetic process. The pragmatical meaning of the theoretical consideration is substantiated by the example of the hydrostatic skeleton theory in which the chordates are derived from metameric worms with a fluid skeleton. Herrn Professor Dr. P. Dullemeijer sind die Verfasser für kritische Lektüre und wertovolle Hinweise zu Dank verpflichtet.     

An assessment of Gallistel's (2012) rationalistic account of extinction phenomena

Gallistel (2012) asserts that animals use rationalistic reasoning (i.e., information theory and Bayesian inference) to make decisions that underlie select extinction phenomena. Rational processes are presumed to lead to evolutionarily optimal behavior. Thus, Gallistel's model is a type of optimality theory. But optimality theory is only a theory, a theory about an ideal organism, and its predictions frequently deviate appreciably from observed behavior of animals in the laboratory and the real world. That is, behavior of animals is often far from optimal, as is evident in many behavioral phenomena. Hence, appeals to optimality theory to explain, rather than illuminate, actual behavior are misguided.     

Multi-objective behavioural mechanisms are adopted by foraging animals to achieve several optimality goals simultaneously

1. Animals foraging for resources are under a variety of selective pressures, and separate optimality models have been developed predicting the optimal reproductive strategies they should adopt. 2. In most cases, the proximate behavioural mechanisms adopted to achieve such optimality goals have been identified. This is the case, for example, for optimal patch time and sex allocation in insect parasitoids. However, behaviours modelled within this framework have mainly been studied separately, even though real animals have to optimize some behaviours simultaneously. 3. For this reason, it would be better if proximate behavioural rules were designed to attain several goals simultaneously. Despite their importance, such multi-objective proximate rules remain to be discovered. 4. Based on experiments on insect parasitoids that simultaneously examine their optimal patch time and sex allocation strategies, it is shown here that animals can adopt multi-objective behavioural mechanisms that appear consistent with the two optimal goals simultaneously. 5. Results of computer simulations demonstrate that these behavioural mechanisms are indeed consistent with optimal reproductive strategies and have thus been most likely selected over the course of the evolutionary time.