We have recently shown that the rat brain Kv1.1 (RCK1) voltage-gated K+ channel is partially phosphorylated in its basal state in Xenopus oocytes and can be further phosphorylated upon treatment for a short time with a cAMP analog (Ivanina, T., Perts, T., Thornhill, W. B., Levin, G., Dascal, N., and Lotan, I. (1994) Biochemistry 33, 8786-8792). In this study, we show, by two-electrode voltage clamp analysis, that whereas treatments for a short time with various cAMP analogs do not affect the channel function, prolonged treatment with 8-bromoadenosine 3',5'-cyclic monophosphorothioate ((Sp)-8-Br-cAMPS), a membrane-permeant cAMP analog, enhances the current amplitude. It also enhances the current amplitude through a mutant channel that cannot be phosphorylated by protein kinase A activation. The enhancement is inhibited in the presence of (Rp)-8-Br-cAMPS, a membrane-permeant protein kinase A inhibitor. Concomitant SDS-polyacrylamide gel electrophoresis analysis reveals that this treatment not only brings about phosphorylation of the wild-type channel, but also increases the amounts of both wild-type and mutant channel proteins; the latter effect can be inhibited by cycloheximide, a protein synthesis inhibitor. In the presence of cycloheximide, the (Sp)-8-Br-cAMPS treatment enhances only the wild-type current amplitudes and induces accumulation of wild-type channels in the plasma membrane of the oocyte. In summary, prolonged treatment with (Sp)-8-Br-cAMPS regulates RCK1 function via two pathways, a pathway leading to enhanced channel synthesis and a pathway involving channel phosphorylation that directs channels to the plasma membrane.

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The ability to predict how multiple traits interact in determining performance is key to understanding the evolution of complex functional systems. Similar to Simpson’s adaptive landscape, which describes the fitness consequences of varying morphological traits, performance landscapes depict the performance consequences of varying morphological traits. Mapping the population’s location with respect to the topographic features of the landscape could inform us on the selective forces operating on the traits that underlie performance. Here, we used a mechanistic model derived from first principles of hydrodynamics to construct a hypothetical performance landscape for zooplankton prey capture using suction feeding. We then used the landscape to test whether a population of Chromis viridis, a coral reef zooplanktivore, is located on a performance peak or ridge based on measurements of kinematic variables recorded in-situ during undisturbed foraging. Observed trait combinations in the wild population closely matched regions of high feeding performance in the landscape, however the population was not located on a local performance peak. This sub-optimal performance was not due to constraints stemming from the observed trait correlations. The predominant directions of variation of the phenotypic traits was tangent to the ‘path of steepest ascent’ that points towards the local peak, indicating that the population does not reside on a “performance ridge”. Rather, our analysis suggests that feeding performance is constrained by stabilizing selection, possibly reflecting a balance between selection on feeding performance and mechanical or genetic constraints.

Understanding how organismal traits determine performance and ultimately fitness is a fundamental goal of evolutionary eco-morphology. However, multiple traits can interact in non-linear and context-dependent ways to affect performance, hindering efforts to place natural populations with respect to performance peaks or valleys. Here, we used an established mechanistic model of suction-feeding performance (SIFF) derived from hydrodynamic principles, to estimate a theoretical performance landscape for zooplankton prey capture. This performance space can be used to predict prey capture performance for any combination of six morphological and kinematic trait values. We then mapped in situ high-speed video observations of suction-feeding in a natural population of a coral reef zooplanktivore, Chromis viridis, onto the performance space to estimate the population's location with respect to the topography of the performance landscape. Although the kinematics of the natural population closely matched regions of high performance in the landscape, the population was not located on a performance peak. Individuals were furthest from performance peaks on the peak gape, ram speed and mouth opening speed trait axes. Moreover, we found that the trait combination in the observed population were associated with higher performance than expected by chance, suggesting that these combinations are under selection. Our results provide a framework for assessing whether natural populations occupy performance optima.