The evolution of niche width

PhD ThesisThis thesis examines the ultimate and proximate determinants of niche width, with a focus on how cognition and biological information processing may drive the evolution of niche width. Using both field and laboratory experiments I investigate how learning can alter resource use in syrphids. Modelling biological information processing using artificial neural networks I consider how various ecological factors interact and can impact information processing to determine decision accuracy (a proposed factor in the evolution of niche width). Finally the ability of artificial neural networks to overcome evolutionary dead ends due to specialisation and functional loss is examined. I found that syrphids were able to use external, inter-specific cues to alter their resource use. Specialist artificial neural networks decision accuracy was altered by the introduction of the ecological variables they were subjected to and the loss of functionality can create an evolutionary dead end scenario only in very extreme cases or under specific ecological pressures. I studied the syrphid (Episyrphus balteatus) both in the field and under laboratory conditions. There is a huge amount of literature describing how bees use scent marks to aid decision making before landing on flowers but there is currently no work on the syrphids ability to detect and utilise these scent marks. The question I posed was ‘Can syrphids modify their pattern of resource utilisation by using this scent mark information?’ The field work was carried out using motion detection cameras positioned above flowers of knapweed (Centaurea nigra). The flowers had two different treatments: one was bagged overnight to prevent pollinator access and the other was left unbagged allowing foraging insects to deplete the nectar and pollen. Visits from both conditions were recorded and compared. I found that previously bagged flowers received more visits from both bumblebees (Bombus spp.) and syrphids suggesting that syrphids could also detect when a flower was depleted without landing. iii The laboratory tests were conducted in an arena using artificial flowers. The experiment was split into a learning phase and a testing phase. I tested the syrphids ability to recognise and learn an association to two different compounds, bee scent marks or 1-Hexanol. I found that syrphids could learn to associate both bee scent marks and 1-Hexanol with negative rewards and use this information to change their foraging behaviour. I used artificial neural networks to investigate differences between the decision accuracy of specialists and generalists when foraging under ecological pressures. Previous work has shown that specialists had higher decision accuracy when non-host selection carried a mild reward and I was interested to see how ecological variables would impact this advantage. The ecological conditions I considered were search costs, resource availability and starvation. To do this I trained neural networks to recognise different numbers of binary images (hosts) over a range of positive and negative non-host rewards or punishments. The fewer hosts a network had the more specialised it was. I found that both starvation and resource availability reduced the range of non-host values across which specialist networks had a fitness advantage over generalists. Interestingly I found that introducing search costs shifts the range of non-host values where specialist advantage occurs rather than narrowing them as in the previous conditions. Specialists suffering from search costs performed better when non-host selection carried a high to intermediate punishment. Finally, I used artificial neural networks to investigate the evolutionary dead end theory. This theory states that specialist organisms will lose genetic variation and will be unable to respond as effectively to ecological change. I first trained networks as specialists. These networks were then re-trained as generalists. While re-training networks had a percentage of their weights fixed to simulate the suggested reduction in evolutionary potential of specialists. Ecological conditions in these simulations were either non-host penalties, search costs or a combination of the two. I found that networks were relatively robust to loss of evolutionary iv potential. All of the networks performed well even at intermediate (50%) weight fixation. The application of search costs reduced overall network fitness but this effect was not as pronounced as when non-host penalties were introduced. Non-host penalties had the greatest effect on the fitness of networks. These results suggest that specialisation should only become an ‘evolutionary dead end’ under very specific and severe conditions.Natural Environment Research Council (NERC

Robustness and Aging – A Systems-Level Perspective

Biosystems, 112(1): pp. 37-48The theory of robustness describes a system level property of evolutionary systems, which predicts tradeoffs of great interest for the systems biology of aging, such as accumulation of non-heritable damage, occurrence of fragilities and limitations in performance, optimized allocation of restricted resources and confined redundancies. According to the robustness paradigm cells and organisms evolved into a state of highly optimized tolerance (HOT), which provides robustness to common perturbations, but causes tradeoffs generally characterized as “robust yet fragile”. This raises the question whether the ultimate cause of aging is more than a lack of adaptation, but an inherent fragility of complex evolutionary systems. Since robustness connects to evolutionary designs, consideration of this theory provides a deeper connection between evolutionary aspects of aging, mathematical models and experimental data. In this review several mechanisms influential for aging are re-evaluated in support of robustness tradeoffs. This includes asymmetric cell division improving performance and specialization with limited capacities to prevent and repair age-related damage, as well as feedback control mechanisms optimized to respond to acute stressors, but unable to halt nor revert aging. Improvement in robustness by increasing efficiencies through cellular redundancies in larger organisms alleviates some of the damaging effects of cellular specialization, which can be expressed in allometric relationships. The introduction of the robustness paradigm offers unique insights for aging research and provides novel opportunities for systems biology endeavors

Robustness and Aging – A Systems-Level Perspective

Biosystems, 112(1): pp. 37-48The theory of robustness describes a system level property of evolutionary systems, which predicts tradeoffs of great interest for the systems biology of aging, such as accumulation of non-heritable damage, occurrence of fragilities and limitations in performance, optimized allocation of restricted resources and confined redundancies. According to the robustness paradigm cells and organisms evolved into a state of highly optimized tolerance (HOT), which provides robustness to common perturbations, but causes tradeoffs generally characterized as “robust yet fragile”. This raises the question whether the ultimate cause of aging is more than a lack of adaptation, but an inherent fragility of complex evolutionary systems. Since robustness connects to evolutionary designs, consideration of this theory provides a deeper connection between evolutionary aspects of aging, mathematical models and experimental data. In this review several mechanisms influential for aging are re-evaluated in support of robustness tradeoffs. This includes asymmetric cell division improving performance and specialization with limited capacities to prevent and repair age-related damage, as well as feedback control mechanisms optimized to respond to acute stressors, but unable to halt nor revert aging. Improvement in robustness by increasing efficiencies through cellular redundancies in larger organisms alleviates some of the damaging effects of cellular specialization, which can be expressed in allometric relationships. The introduction of the robustness paradigm offers unique insights for aging research and provides novel opportunities for systems biology endeavors

Exploring protein fitness landscapes with new high-throughput technologies

The concept of a protein’s fitness landscape – an abstract space in which related sequences are close together and matched with their fitness – is a useful tool to visualize core principles of protein evolution. Acquiring a new function, for example the laboratory evolution of an enzyme to convert an industrially relevant substrate, can be understood as a stepwise climb through a fitness landscape, reaching higher fitness (or activity) with each step (or mutation). The valleys of such a space relate to the starting points of protein engineering campaigns. Understanding this area could enlighten principles of how proteins quickly adapt in nature and help to identify starting points with a high potential for evolution, a high ‘evolvability’, speeding up protein engineering. In this study, high-throughput technologies will be developed that enable the read-out of directed evolution on a large scale, tracking the exploration of the valley of a fitness landscape: the conversion of an amino acid- to amine dehydrogenase will be investigated as a model of enzyme evolvability with a drastic change of substrate specificity. A sensitive high-throughput screening assay as well as a comprehensive sequencing read-out will be required to establish the identity of selected variants during evolution. I will first generate and characterize three different but related starting points and test their initial evolvability. Stabilizing the starting point results in increased mutational robustness, broadening the range of accepted mutations. However, increased initial stability does not necessarily correlate to higher functional improvement, hinting at a nuanced view of evolvability. A sensitive high-throughput assay is necessary to verify the full potential of the starting points and study the early steps of evolution comprehensively. Broadly applicable ultrahigh-throughput assays of enzyme function, such as absorbance-activated droplet sorting, currently lack the sensitivity of more specific fluorescence-based or low-throughput counterparts. A universal approach to increase detectability in single cell-lysate microfluidic enzyme assays is established by amplifying the enzyme content per droplet more than 10-fold via homogeneous clonal cell growth. Clonal amplification enables the sensitive and precise detection of newly introduced amine dehydrogenase activities, a feat restricted in conventional assays by low initial activity and stability. To generate a truly complete view of directed evolution in a fitness landscape, however, an equally powerful sequencing read-out is necessary to identify all selected variants. Here, unique molecular identifiers are used to increase the accuracy of nanopore sequencing to levels that can reliably distinguish point mutations. I establish an inexpensive and straightforward long read amplicon sequencing workflow which is then applied to map the trajectories of two comparative long-term directed evolution campaigns. In the parallel evolution campaigns, initial beneficial mutations are exclusive to each starting point and lead to incompatible trajectories. Beneficial mutations are scarce and large improvements are unavailable until recombination occurs and a jump through the fitness landscape is realized. The recombined variant holds high evolvability and quickly evolves to take over the population and form the most successful lineages, indicating the power of recombination as a means to innovation in protein evolution. The tools established in this thesis can help protein engineers explore fitness landscapes more economically and comprehensively. Their application to mapping full trajectories of early adaptation uncovers differences in the evolvability of homologs, potentially aiding the identification of evolvable starting points as well as strategies to increase evolvability for efficient protein engineering in the future

Robustness - a challenge also for the 21st century: A review of robustness phenomena in technical, biological and social systems as well as robust approaches in engineering, computer science, operations research and decision aiding

Notions on robustness exist in many facets. They come from different disciplines and reflect different worldviews. Consequently, they contradict each other very often, which makes the term less applicable in a general context. Robustness approaches are often limited to specific problems for which they have been developed. This means, notions and definitions might reveal to be wrong if put into another domain of validity, i.e. context. A definition might be correct in a specific context but need not hold in another. Therefore, in order to be able to speak of robustness we need to specify the domain of validity, i.e. system, property and uncertainty of interest. As proofed by Ho et al. in an optimization context with finite and discrete domains, without prior knowledge about the problem there exists no solution what so ever which is more robust than any other. Similar to the results of the No Free Lunch Theorems of Optimization (NLFTs) we have to exploit the problem structure in order to make a solution more robust. This optimization problem is directly linked to a robustness/fragility tradeoff which has been observed in many contexts, e.g. 'robust, yet fragile' property of HOT (Highly Optimized Tolerance) systems. Another issue is that robustness is tightly bounded to other phenomena like complexity for which themselves exist no clear definition or theoretical framework. Consequently, this review rather tries to find common aspects within many different approaches and phenomena than to build a general theorem for robustness, which anyhow might not exist because complex phenomena often need to be described from a pluralistic view to address as many aspects of a phenomenon as possible. First, many different robustness problems have been reviewed from many different disciplines. Second, different common aspects will be discussed, in particular the relationship of functional and structural properties. This paper argues that robustness phenomena are also a challenge for the 21st century. It is a useful quality of a model or system in terms of the 'maintenance of some desired system characteristics despite fluctuations in the behaviour of its component parts or its environment' (s. [Carlson and Doyle, 2002], p. 2). We define robustness phenomena as solution with balanced tradeoffs and robust design principles and robustness measures as means to balance tradeoffs. --

Primary and promiscuous functions coexist during evolutionary innovation through whole protein domain acquisitions

Molecular examples of evolutionary innovation are scarce and generally involve point mutations. Innovation can occur through larger rearrangements, but here experimental data is extremely limited. Integron integrases innovated from double-strand- toward single-strand-DNA recombination through the acquisition of the I2 a-helix. To investigate how this transition was possible, we have evolved integrase IntI1 to what should correspond to an early innovation state by selecting for its ancestral activity. Using synonymous alleles to enlarge sequence space exploration, we have retrieved 13 mutations affecting both I2 and the multimerization domains of IntI1. We circumvented epistasis constraints among them using a combinatorial library that revealed their individual and collective fitness effects. We obtained up to 104 -fold increases in ancestral activity with various asymmetrical trade-offs in single-strand-DNA recombination. We show that high levels of primary and promiscuous functions could have initially coexisted following I2 acquisition, paving the way for a gradual evolution toward innovation

Evolution of reproductive development in the volvocine algae

The evolution of multicellularity, the separation of germline cells from sterile somatic cells, and the generation of a male–female dichotomy are certainly among the greatest innovations of eukaryotes. Remarkably, phylogenetic analysis suggests that the shift from simple to complex, differentiated multicellularity was not a unique progression in the evolution of life, but in fact a quite frequent event. The spheroidal green alga Volvox and its close relatives, the volvocine algae, span the full range of organizational complexity, from unicellular and colonial genera to multicellular genera with a full germ–soma division of labor and male–female dichotomy; thus, these algae are ideal model organisms for addressing fundamental issues related to the transition to multicellularity and for discovering universal rules that characterize this transition. Of all living species, Volvox carteri represents the simplest version of an immortal germline producing specialized somatic cells. This cellular specialization involved the emergence of mortality and the production of the first dead ancestors in the evolution of this lineage. Volvocine algae therefore exemplify the evolution of cellular cooperation from cellular autonomy. They also serve as a prime example of the evolution of complex traits by a few successive, small steps. Thus, we learn from volvocine algae that the evolutionary transition to complex, multicellular life is probably much easier to achieve than is commonly believed

CONSTRAINTS OF THE IMAGINATION: HOW PHENOTYPES ARE SHAPED THROUGH GENETICS, THE ENVIRONMENT, AND DEVELOPMENT

Phenotypic constraints are ubiquitous throughout nature, being found throughout all stages of life and at multiple different biological levels including cellular, genetic, environmental, behavioral, evolutionary, and developmental. These constraints have shaped, not only the natural world, but the way that we perceive what is possible, or impossible, an observation made clear by François Jacob in his 1977 paper “Evolution and Tinkering”. This is reflected in the literature, repeatedly, by the regular occurrence of densely packed visualization of phenotypic space that seemingly always have large areas that go unoccupied. Despite constrained regions of space being observable across countless taxa, identifying the mechanisms of those constraints remains elusive. Given that constraints are widespread and have influenced how evolution may work, my aim was to identify mechanisms of constraint throughout multiple biological levels. Chapter one is divided into two parts, sections A and B, but largely focuses on how constraints are influenced by genetics. For this, we investigated crocc2, a protein that encodes for a structural component of the ciliary rootlet which in turn plays a major role as a mechanosensory for nearly all cells. We found dysfunctional crocc2 resulted in both dysmorphic bone development and a decrease in the plastic response potential of zebrafish (section A), as well as altered developmental trajectories in juvenile morphology, presumably due to alterations in cellular polarity and inadequate extracellular communication. Importantly, all results from this chapter point toward crocc2 play a canalizing role in the production of phenotypes at multiple life-history stages. Chapter 2 takes a different approach into understanding constrains by looking at broad ecological alterations and how those alterations may alter morphology of resident taxa. Here, we utilized the heavily altered habitat of the Tocantins River in the Amazon and the existing museum collections to evaluate how select representatives of the cichlid community had responded to such change. We found significant changes in contemporary morphology across all included cichlid species compared to their historical counterparts. These data show that alterations to the environment have resulted in changes to the local resident species, and possibly an alteration to their future evolutionary trajectories. Among the species included, one was found to have the most substantial morphological changes, which is what we followed up in the next chapter. Chapter 3 dug into the morphological changes of Satanoperca, a Geophagine cichlid with a unique feeding mechanism known as winnowing. Winnowing is a poorly understood mechanical process involving substrate manipulation. Given that anthropogenic alterations to local hydrology oft result in changes to the benthic sediment composition, we wanted to know if differing substrates was enough to induce a plastic response in winnowing fishes, and if so which traits were effected. We found significant differences across our experimental populations in both shape and disparity and present evidence in support of wide-spread integration across craniofacial traits. In addition, these data suggest that the novel anatomical structure, the epibranchial lobe, is more modular than other craniofacial traits involved in the winnowing process. Chapters 4 and 5 utilize a unique lineage of fishes, the Bramidae, to understand how developmental and evolutionary constraints are broken to produce morphological novelties. We used a combination of DNA sequences from GenBank and numerous museum specimens to illuminate constraints and determine how constraints are broken to produce complex phenotypic novelties. In Chapter 4, we found that the fanfishes had experienced greater rates of morphological evolution than other members of the Bramidae family, resulting in their occupation of an entirely novel region of phenotypic space. In Chapter 5, we elaborated on this by investigating the developmental processes involved in producing an extreme morphological novelty. The data presented in Chapter 5 provide evidence suggesting that the fanfishes have broken various constraints, resulting in prominent anatomical and morphological changes to accommodate their novel phenotype. In all, my dissertation provides examples of how constraints have shaped the variability that we see throughout life and shows examples of how constraints can be identified, what happens when they are broken, and how they work to control the pace and trajectory of evolutionary processes

Adaptation to marginal habitats

The ability to adapt to marginal habitats, in which survival and reproduction are initially poor, plays a crucial role in the evolution of ecological niches and species ranges. Adaptation to marginal habitats may be limited by genetic, developmental, and functional constraints, but also by consequences of demographic characteristics of marginal populations. Marginal populations are often sparse, fragmented, prone to local extinctions, or are demographic sinks subject to high immigration from high-quality core habitats. This makes them demographically and genetically dependent on core habitats and prone to gene flow counteracting local selection. Theoretical and empirical research in the past decade has advanced our understanding of conditions that favor adaptation to marginal habitats despite those limitations. This review is an attempt at synthesis of those developments and of the emerging conceptual framework