Mechanisms of convergent egg provisioning in poison frogs
Cite this dataset
Fischer, Eva K. et al. (2020). Mechanisms of convergent egg provisioning in poison frogs [Dataset]. Dryad. https://doi.org/10.5061/dryad.573n5tb3j
Parental provisioning of offspring with physiological products (nursing) occurs in many animals, yet little is known about the neuroendocrine basis of nursing in non-mammalian species. Within amphibians, maternal provisioning has evolved multiple times, with mothers of some species feeding unfertilized eggs to their developing offspring until tadpoles complete metamorphosis. We conducted field studies in Ecuador and Madagascar to ask whether convergence at the behavioral level provides similar benefits to offspring and relies on shared neural mechanisms in dendrobatid and mantellid poison frogs. At an ecological level, we found that nursing allows poison frogs to provide chemical defenses to their tadpoles in both species. At the neural level, nursing was associated with increased activity in the lateral septum and preoptic area, demonstrating recruitment of shared brain regions in the convergent evolution of nursing within frogs and across vertebrates. In contrast, only mantellids showed increased oxytocin neuron activity akin to that in nursing mammals, suggesting evolutionary versatility in molecular mechanisms. Our findings demonstrate that maternal provisioning provides similar potential benefits to offspring and relies on similar brain regions in poison frog species with convergently evolved toxicity and maternal care.
Methods are briefly summarized below and additional details can be found in the manuscript. Prior to extraction, skin samples were weighed with an analytical scale. Trophic eggs and oocytes were processed in a similar manner as skins, except that starting material was not weighed. The entire contents of each sample vial (all tissue and the methanol in which it was stored) were emptied into a sterilized Dounce homogenizer. To ensure the transfer of all materials, the empty vial was rinsed with 1 ml of methanol, which was also added to the homogenizer. We added 25 µg of D3-nicotine (Sigma-Aldrich, St Louis, MO, USA) in methanol to each sample to serve as a standard. Samples were ground with the piston ten times in the homogenizer before being transferred to a glass vial. The homogenizer was rinsed with an additional 1 ml of methanol in order to collect all residual alkaloids, and this methanol was also added to the final glass vial. Samples were stored at -20°C until further processing. Alkaloids from water samples were extracted using Oasis HLB VAC RC 30 mg extraction cartridges (Waters Corporation, Milford, Massachusetts, USA) on a vacuum manifold according to manufacturer instructions, including washes of 5% methanol and elution with 100% methanol. To avoid clogging the cartridges, debris were removed from water samples with a coarse sieve prior to processing.
Alkaloids were analyzed using liquid chromatography / tandem mass spectrometry (LC-MS/MS). Samples were run on a Thermo Q-Exactive Plus and a Phenomenex Gemini C18 3 μm 2.1 × 100 mm column (Torrance, CA, USA). Mobile phase A was composed of water with 0.1% formic acid, and mobile phase B was composed of acetonitrile with 0.1 % formic acid. The flow rate was 0.2 ml/ min. The gradient began with 0 % B for one min, then increased linearly to 100% B at 15 min, and held until 18 min. The column was then re-equilibrated to initial conditions for 3 min before the next sample. Blanks were run at regular intervals to ensure no carry over.
Alkaloids were tentatively identified by comparing this LC-MS/MS data set to a data set obtained by gas chromatography / mass spectrometry (GC/MS) from the same samples and used in a previous study exploring environmental variation and chemical defenses in the same frogs. The alkaloids detected by GC/MS in the previous study were identified using mass spectral data provided in Daly et al.. For the LC-MS/MS data in the present study, a Tracefinder (Tracefinder 4.0, ThermoFisher Scientific) library was created with the accurate mass of all frog alkaloids from the Daly database and used to identify and integrate all potential poison frog alkaloids in the samples. This allowed more sensitive detection of alkaloids in all samples compared to GC/MS and permitted us to trace which potential alkaloids were present in the various sample types. Correlation with the previous dataset for the same frogs allows us to select the mostly likely poison frog alkaloid when several candidates with the same mass were present.
National Science Foundation, Award: IOS-1557684
Bauer Fellowship from Harvard University
National Geographic Committee and Research and Exploration, Award: 9685-15
National Science Foundation Postdoctoral Fellowship in Biology, Award: DEB-1608997