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Life history theory explains how an organism’s reproductive success is driven by trade-offs among life-history traits. Organisms can have contrasting life-history strategies. For example, Chinook salmons reproduce once and then they die (semelparity), whereas Atlantic salmons reproduce several times in their lifetime (iteroparity). What is an optimal life-history strategy for a filamentous fungus? Theory predicts that based on the quality and quantity of resources and the presence of competition, a fungus can be semelparous or iteroparous.In the first part of this thesis, adaptive constraints experienced by fifteen natural isolates of A. nidulans during evolution in their natural environment have been tested. No significant correlation between growth rate and asexual spore yield was observed. Instead, there was a clear dependence of the two traits on sugar concentration and nutrient richness. Further, six natural isolates were selected for a short evolution experiment in one environment where the isolates showed most variation in growth and asexual reproduction. A negative correlation between growth rate and spore density was observed among independently evolved replicate populations that approached significance, but not between growth rate and spore yield. All changes occurred in an antagonistic fashion: increases in growth rate were associated with decreases in spore yield/density, and vice versa, indicating short-term adaptive constraints from a growth-reproduction trade-off.In the remainder of the thesis, the scope and mechanisms of adaptation in an Aspergillus Short-term Evolution eXperiment (ASEX) were tested including the role of trade-offs between growth rate and asexual reproduction. Surprisingly, asexual spore yield consistently decreased in all the populations and changes in growth rate and spore yield approached significance. The competitive fitness of the evolved populations relative to their ancestor had not improved either. However, fitness measuremen

Historically, research has focused on the mean and often neglected the variance. However, variability in nature is observable at all scales: among cells within an individual, among individuals within a population and among populations within a species. A fundamental quest in biology now is to find the mechanisms that underlie variability. Here, we investigated behavioural variability in a unique unicellular organism, Physarum polycephalum. We combined experiments and models to show that variability in cell signalling contributes to major differences in behaviour underpinning some aspects of social interactions. First, following thousands of cells under various contexts, we identified distinct behavioural phenotypes: 'slow-regular-social', 'fast-regular-social' and 'fast-irregular-asocial'. Second, coupling chemical analysis and behavioural assays we found that calcium signalling is responsible for these behavioural phenotypes. Finally, we show that differences in signalling and behaviour led to alternative social strategies. Our results have considerable implications for our understanding of the emergence of variability in living organisms., info:eu-repo/semantics/published

Historically, research has focused on the mean and often neglected the variance. However, variability in nature is observable at all scales: among cells within an individual, among individuals within a population and among populations within a species. A fundamental quest in biology now is to find the mechanisms that underlie variability. Here, we investigated behavioural variability in a unique unicellular organism, Physarum polycephalum. We combined experiments and models to show that variability in cell signalling contributes to major differences in behaviour underpinning some aspects of social interactions. First, following thousands of cells under various contexts, we identified distinct behavioural phenotypes: textquoteleftslowtextendashregulartextendashsocialtextquoteright, textquoteleftfasttextendashregulartextendashsocialtextquoteright and textquoteleftfasttextendashirregulartextendashasocialtextquoteright. Second, coupling chemical analysis and behavioural assays we found that calcium signalling is responsible for these behavioural phenotypes. Finally, we show that differences in signalling and behaviour led to alternative social strategies. Our results have considerable implications for our understanding of the emergence of variability in living organisms., info:eu-repo/semantics/published

When stimulated by a point source of cyclic AMP, a starved amoeba of Dictyostelium discoideum responds by putting out a hollow balloon-like membrane extension followed by a pseudopod. The effect of the stimulus is to influence the position where either of these protrusions is made on the cell rather than to cause them to be made. Because the pseudopod forms perpendicular to the cell surface, its location is a measure of the precision with which the cell can locate the cAMP source. Cells beyond 1 h of starvation respond non-randomly with a precision that improves steadily thereafter. A cell that is starved for 1–2 h can locate the source accurately 43% of the time; and if starved for 6–7 h, 87% of the time. The response always has a high scatter; population-level heterogeneity reflects stochasticity in single cell behaviour. From the angular distribution of the response its maximum information content is estimated to be 2–3 bits. In summary, we quantitatively demonstrate the stochastic nature of the directional response and the increase in its accuracy over time.

When stimulated by a point source of cyclic AMP, a starved amoeba of Dictyostelium discoideum responds by putting out a hollow balloon-like membrane extension followed by a pseudopod. The effect of the stimulus is to influence the position where either of these protrusions is made on the cell rather than to cause them to be made. Because the pseudopod forms perpendicular to the cell surface, its location is a measure of the precision with which the cell can locate the cAMP source. Cells beyond 1 h of starvation respond non-randomly with a precision that improves steadily thereafter. A cell that is starved for 1–2 h can locate the source accurately 43% of the time; and if starved for 6–7 h, 87% of the time. The response always has a high scatter; population-level heterogeneity reflects stochasticity in single cell behaviour. From the angular distribution of the response its maximum information content is estimated to be 2–3 bits. In summary, we quantitatively demonstrate the stochastic nature of the directional response and the increase in its accuracy over time.