Response of larval Evechinus chloroticus to near-future ocean acidification: an integrated -omics analysis

Chair: Vonda Cummings

Mary A. Sewell(1), Daniel Baker(1), Michael Hudson(1), Louis Ranjard(1), Peter Tsai(1), Ramon Gallego(1), Anthony Hickey(1), Kim-Anh Lê Cao(2), Katya Ruggiero(3)

1 School of Biological Sciences, University of Auckland, Auckland 1142, New Zealand.
2 The University of Queensland Diamantina Institute, Translational Research Institute, QLD 4102, Brisbane, Australia
3 Department of Statistics, University of Auckland, Auckland 1142, New Zealand.

Background
Under the ocean acidification (OA) conditions predicted for 2100 the larval stages of temperate sea urchins exhibit developmental delay, reduced and abnormal skeletal development, alterations to metabolic rate, and a general down-regulation of gene expression. Meta-analysis of gene expression studies in four sea urchin species shows a general down-regulation of genes within energy-producing pathways, indicating metabolic depression, and genes involved in ion transport and biomineralization, but expression profiles provided limited evidence for CO2-mediated developmental delay or induction of a cellular stress response. Here, in larval Evechinus chloroticus, we used a systems biology approach (analysis of transcriptome, proteome and metabolome) together with mixOmics statistical analysis to understand the complex biological pathways affected by OA.

Methods
Samples were collected of 4-arm larvae in Control, Medium and High CO2 treatments (380, 540, 1000 µatm CO2). Transcriptomic, proteomic and metabolomic data were analysed with standard univariate statistical methods to identify differentially abundant -omic species, followed by the use of multivariate projection methods to elucidate the relationships between the data-sets.

Findings
There was significant up-regulation of gene expression between Control and Medium CO2 treatments of 51 transcripts and down-regulation of 4, with no significant differences in gene expression between the Medium and High CO2 treatments. The proteome identified over 25 proteins that were differentially expressed with CO2 treatment; a large number of these are involved in protein synthesis and energetic pathways, with the majority being down-regulated. Few metabolites showed significant differences in univariate tests; although multivariate analysis revealed associations with metabolic pathways such as the TCA cycle.

Conclusions
Integration of multiple –omics datasets from a matched set of samples can provide greater insight into how a biological system responds to OA, but can be technically-challenging and requires a complex level of interpretation. We will present a summary of our results from Evechinus chloroticus larvae.