Abstracts:  NVTB  PhD-day  2003

No abstract available.

The viral infection cycle depends on a well-ordered sequence of events that needs to be carefully tuned in timing and magnitude. In bacteriophages a detailed qualitative understanding of the underlying biochemical mechanisms has accumulated, especially with respect to gene regulation. However, the selective forces favoring one regulatory strategy over another are largely unknown.

To improve our insights into these processes, we are developing models that link evolutionary success to the parameters of the life-cycle. These parameters can than be related to the underlying biochemical details. This top-down modeling approach allows an analysis at the phenotypic level, by well-established methods from life-history theory, without losing insight at the genetic and the biochemical level. Our combined approach addresses a general weakness of phenotypic optimality theory. Basic ingredient of an optimality analysis, namely constraints and trade-offs, are usually treated as a black box. In case of small-genome bacteriophages with a well-characterized life cycle, we aim at deriving constraints and trade-offs directly from the underlying biochemical mechanisms.

To test our model predictions we carry out experimental evolution, taking bacteriophage MS2 as a model system. In a first set of experiments, we will select on life-history traits as latency time (= generation time) and burst size (= reproductive output), to measure correlated responses on other traits. Furthermore we will distort 'optimal' gene regulation by over-expression of single viral genes from a plasmid to determine which regulation strategies can invade the population and restore the optimal regulation strategy of MS2.

Preliminary results suggest that the physiological coupling of gene products can lead to optimal strategies favoring intermediate biochemical reaction rates over a maximization of throughput in a certain pathway.

We studied the evolutionary behavior of a population of mixotrophs living in an aquatic environment. The system is characterized by full material recycling, which makes it a simple but fully functioning ecosystem. The feedback mechanisms, however, impede allopatric evolution: even under different environmental conditions the mixotrophs will evolve to the same strategy. However, a light gradient can change things. It causes the system to become spatially heterogeneous, which facilitates evolutionary branching and sympatric evolution. The mixotroph population will branch and eventually end up in separate autotrophs and heterotrophs.

With the light gradient, also other environmental properties acquire influence on the evolutionary outcomes, which makes the model more realistic. Higher mixing intensities facilitate the branching process, as long as the water column is not completely mixed. If self-shading is taken into account, higher nutrient concentrations will also facilitate branching. This may provide an additional explanation for why mixotrophs are often associated with oligotrophic systems.

Large mamalian herbivores often face an environment with a heterogeneous distribution of resources. Since these herbivores have to eat, they have to move from one patch of resource to another. My research focusses on the behavioural strategies that herbivores can adopt to find enough of a scarce resource to survive. I wil present a first simulation model that includes both naive strategies and strategies that are dependent on past experience.

Most primates have diverse diets and some field studies show that primate groups in the same habitats can have different diets. Other studies involving the introduction of captive primates to the wild show that lack of experience can lead to starvation or intoxication. This suggests that learning and in particular under social influence plays an important role in the development of individual diets in primates. We investigate this issue by comparing how individual experience and social influences contribute to diet development in simulated groups of foraging primates in a spatial environment. We investigate how different conditions select for different degrees of social and individual learning and how social and individual learning contribute to fitness. In addition we investigate how the interaction of the groups of primates with their environment shapes the context of learning and what influence this has on what is learnt. Preliminary results suggest that paying attention to social cues is adaptive in a constant environment with homogenously distributed resources. In addition, the interaction of groups with their environment appears to create a context for individual experimentation that is risky for the individual.

Cardiac arrhythmias, life-threatening disturbances in heart rhythm, often occur in people with fibrotic hearts. Fibrotic hearts contain up to 35% of connective tissue, due to ageing, infarctions or particular diseases (cardiomyopathies), whereas healthy normal hearts contain only 5% connective tissue. The connective tissue is organized in strands parallel to the muscle fiber direction and does not conduct the electrical excitation wave spreading through the heart to initiate contraction.

Intuitively it therefore seems logical that the obstacles that are formed by the connective tissue strands disrupt electrical wave propagation in the heart and lead to arrhythmias. In this talk I will demonstrate that although strandlike obstacles promote one particular kind of arrhythmia in which heart rhythm is increased, they suppress another kind of arrhythmia in which heart rhythm is increased and in addition coherent contraction is lost. We explain the latter counterintuitive effect by studying a different situation with very small obstacles and showing that obstacles do induce spirals but than slow down spiral wave dynamics thus preventing spiral breakup.

These results seem to contradict medical findings that the occurrence of fibrosis in the heart is strongly correlated with the occurrence of both types of arrhythmias. We formulate several hypotheses that might explain our contradictory findings.