A predictive model to estimate total skin tetrodotoxin in the newt Taricha granulosa.

We developed a predictive model to estimate the total amount of tetrodotoxin (TTX) in the skin of individual newts (Taricha granulosa) based on measures of the amount of TTX present in dorsal skin. We found that regions of skin on a newt could be reliably differentiated using granular gland density and that patterns of variation in granular gland density matched intra-individual variation in TTX levels. Tetrodotoxin is uniformly distributed in dorsal skin and TTX levels in dorsal skin are strongly predictive of TTX levels in other regions of skin on a newt. Our model is both accurate and precise and includes the effect of body size through surface area, variation in granular gland density, as well as positional variation in toxicity apparently associated with variation in granular gland density. This technique allows us to detect patterns that would be unclear if only dorsal skin toxicity or total skin toxicity based on extracts from an entire animal were used and demonstrates that the levels of TTX present in some populations of T. granulosa are remarkably high.