Global metabolite profiles as predictors of physiological traits in bivalve larvae with genetically-determined differential growth rates


Meeting Abstract

13.3  Friday, Jan. 4  Global metabolite profiles as predictors of physiological traits in bivalve larvae with genetically-determined differential growth rates APPLEBAUM, S.L.*; LEE, J.W.; MANAHAN, D.T.; Univ. Southern California, Los Angeles sappleba@usc.edu

High variance in growth rates is typical for larvae of marine organisms, even when reared under similar environmental conditions. Part of this phenotypic variation within a species can likely be attributed to differential performance of specific genotypes. We conducted factorial crosses using purebred parental lines of the Pacific oyster (Crassostrea gigas) to produce larval families with contrasting growth phenotypes. Fast- and slow-growing larvae were analyzed for differences in metabolic rates, protein synthesis rates, and protein content. Additionally, metabolomic analyses were conducted to identify (i) biochemical pathways that contribute to genetically-determined differences in growth rate, and (ii) biomarkers that might predict growth phenotype. Size-specific respiration and protein synthesis rates were similar for contrasting growth phenotypes. Protein growth and depositional efficiency (ratio of protein growth to protein synthesis) were higher in faster-growing larvae. Metabolomic analyses identified over 200 different metabolites in larvae. The amounts of several essential (leucine, methionine, phenyalanine, threonine, valine), and non-essential (tyrosine) amino acids, as well as amino acid derivatives (N6-acetylysine, 5-oxoproline, 5-methylcysteine) were lower in the free amino acid pools of faster-growing phenotypes relative to slower-growing larvae. The lower amounts of proteinogenic amino acids in faster-growing larvae corresponded to lower protein turnover (i.e., higher depositional efficiencies) and support the proposal of differential protein turnover as a mechanistic basis for genetically-determined variance in growth. Further, these metabolites are putative biomarkers with the potential to predict growth phenotype.

the Society for
Integrative &
Comparative
Biology