Metabolomic profiles differ among unique genotypes of a threatened Caribbean coral

Abstract

Global threats to reefs require urgent efforts to resolve coral attributes that affect survival in a changing environment. Genetically different individuals of the same coral species are known to exhibit different responses to the same environmental conditions. New information on coral physiology, particularly as it relates to genotype, could aid in unraveling mechanisms that facilitate coral survival in the face of stressors. Metabolomic profiling detects a large subset of metabolites in an organism, and, when linked to metabolic pathways, can provide a snapshot of an organism’s physiological state. Identifying metabolites associated with desirable, genotype-specific traits could improve coral selection for restoration and other interventions. A key step toward this goal is determining whether intraspecific variation in coral metabolite profiles can be detected for species of interest, however little information exists to illustrate such differences. To address this gap, we applied untargeted 1 H-NMR and LC-MS metabolomic profiling to three genotypes of the threatened coral Acropora cervicornis . Both methods revealed distinct metabolite “fingerprints” for each genotype examined. A number of metabolites driving separation among genotypes were identified or putatively annotated. Pathway analysis suggested differences in protein synthesis among genotypes. For the first time, these data illustrate intraspecific variation in metabolomic profiles for corals in a common garden. Our results contribute to the growing body of work on coral metabolomics and suggest future work could identify specific links between phenotype and metabolite profile in corals.

A Review of Toxins from Cnidaria

“…Metabolomic studies are very scarce. Metabolomic profiling of three genetically different individuals of the same coral species, the threatened coral Acropora cervicornis [ 201 ], was performed. The data showed differences in protein synthesis among the genotypes, suggesting that different genotypes may have different abilities, related to growth and stress tolerance, to persist under present and future environmental conditions.…”

Metabolome-Based Discrimination Analysis of Shallot Landraces and Bulb Onion Cultivars Associated with Differences in the Amino Acid and Flavonoid Profiles

“…In total, 407 metabolite signals were successfully annotated in the 18 examined shallot landraces and bulb onion cultivars on the basis of MS/MS spectra, exact mass values, and RTs, as well as a MS/MS similarity matching against the NIST Mass Spectrometry Data Center and MassBank using an identification score cutoff of 70%, while 233 metabolite signals were unknown (Supplementary Tables S1). All of the 640 annotated and unknown metabolite signals were normalized using an internal standard, and the normalized data matrix was subjected to both unsupervised principal component analysis (PCA) and supervised partial least squares discriminant analysis (PLS-DA) ( Figure 1A,B). PCA provides an overview of the variation in a dataset; however, predefined treatments/classes are not involved in the PCA algorithm [14]. On the other hand, the PLS-DA algorithm includes predefined treatments/classes, and thus it can maximize the separation among genotypes and maximize the covariance between metabolite variables to enable better understanding of the factors driving genotype separation [14].…”

“…PCA provides an overview of the variation in a dataset; however, predefined treatments/classes are not involved in the PCA algorithm [14]. On the other hand, the PLS-DA algorithm includes predefined treatments/classes, and thus it can maximize the separation among genotypes and maximize the covariance between metabolite variables to enable better understanding of the factors driving genotype separation [14]. Thus, we use both PCA and PLS-DA as a more comprehensive analysis to assess the metabolomic data of shallot landraces and bulb onion cultivars ( Figure 1A,B).…”

Impaired muscle mitochondrial energetics is associated with uremic metabolite accumulation in chronic kidney disease

“…Proton( 1 H) NMR spectra were collected with the first slice of a NOESY pulse sequence (tnnoesy) (85) at room temperature. All the parameters used to acquire 1D NOESY spectra were same as reported previously(86)(87)(88), except the number of scans (256 scans in this study). Quantification of the tyrosine was performed using Chenomx NMR Suite 8.Chenomx, Inc.) and was normalized by muscle wet weight.Immunofluorescence Microscopy.…”