DOI: 10.5061/dryad.573n5tb3j
title: Mechanisms of convergent egg provisioning in poison frogs

description: 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.
description: 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.