Decoding sex-specific metabolomic biomarkers in the loggerhead sea turtle (Caretta caretta)
Is there a distinct metabolomic profile between male and female loggerhead turtles? Are there useful biomarkers for sex classification in this species?
The loggerhead sea turtle (Caretta caretta) is found in oceans worldwide and is classified under nine distinct population segments by the U.S. Endangered Species Act. It is also listed as vulnerable by the Convention on International Trade in Endangered Species (CITES) Appendix I. Factors such as climate change, along with other human-induced impacts, may be depleting their populations.
The loggerhead turtle, like many reptiles, is a species categorized as temperature-dependent sex determination (TSD). In this context, the molecular mechanisms behind sexual differentiation remain a mystery. Blood sampling is a minimally invasive technique used to assess sea turtle health in various contexts, including studies on wild populations, physiology, stressors, and in turtles undergoing rehabilitation for diagnosis and treatment. Early sex classification presents a conservation challenge as it impacts the welfare of this and other species.
This study aimed to assess the sex-specific effects on plasma chemistry and the metabolome of loggerhead sea turtles, and to identify potential biomarkers for early sex determination during different life stages.
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To achieve this objective, a total of 100 animals from two distinct physiological stages were used: post-hatchling animals (n=50) and juvenile animals (n=50). Each group consisted of 25 males and 25 females, forming four experimental groups: 25 female post-hatchlings, 25 male post-hatchlings, 25 female juveniles, and 25 male juveniles. The total samples were analyzed for plasma biochemistry analytes, including glucose, NEFA, albumin, and urea, among others. Additionally, a subset of randomly selected individuals underwent untargeted metabolomic analysis.
First Objective: Are there differences in the metabolome of loggerhead sea turtles?
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First, we compared specific nutritional metabolites and found no differences between sexes for any physiological stage—males and females exhibited very similar nutritional metabolism profiles, regardless of the analysis. However, the data from the untargeted metabolomics were more revealing. We observed that the metabolomes of males and females were clearly different in both physiological stages, suggesting that sex does influence the metabolome in this species (Figure 1).
Figure 1: The Principal component analyzed (PC) plot derived from multivariate analysis demonstrates a clear separation between sexes in post-hatchling animals.
Therefore, we can affirmatively answer the first question: there is an effect of sex on the metabolome in both physiological stages. However, to provide a more comprehensive analysis, we identified the metabolites responsible for these differences, which were significantly present in greater or lesser amounts in a specific sex.
However, as mentioned, this is the first of the proposed objectives/questions. Now we can ask the next one: Are there useful biomarkers for sex classification in turtles?
In this context, we need to be more stringent, as we aim to classify sex using a single metabolite—rather than the entire metabolome. To achieve this, we focused on metabolites that exhibited consistent patterns; that is, if they were significantly higher in one sex among post-hatchlings, they would continue to show the same trend in juveniles. This approach minimizes the risk of error by ensuring temporal continuity. As a result, we identified four distinct metabolites. However, for these to be considered ideal biomarkers in a hypothetical situation, we would want that all individuals exceeding certain reference values belong to one sex, while those with lower values belong to the opposite sex. This criterion is much more restrictive than simply using a mean.
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Figure 2: Example of Biomarkers.
To achieve this, we analyzed the individual values and their intensities in both groups, creating several graphs, such as the one shown in Figure 2. In this case, for the metabolite 415.20901RT9.084, we found that the values were significantly higher in females than in males (p=0.0008). Specifically, values below 1.5 allowed for the classification of 100% of males, while levels greater than 2.8 indicated 100% females. After conducting several studies of this nature and maintaining a stringent approach, this work concludes with some candidates identified as biomarkers for sex classification in the early life stages of this species.
These results can be found in the publication in Communications Biology doi:10.1038/s42003-024-07033-4.