Ocean acidification (OA) may interact with anthropogenic pollutants, such as heavy metals (HM), to represent a threat to marine organisms and ecosystems. Here, we perform a quantitative meta-analysis to examine the combined effects of OA and heavy metals on marine organisms. The results reveal predominantly additive interactions (67%), with a considerable proportion of synergistic interactions (25%) and a few antagonistic interactions (8%). The overall adverse effects of heavy metals on marine organisms were alleviated by OA, leading to a neutral impact of heavy metals in combination with OA. However, different taxonomic groups showed large variabilities in their responses, with microalgae being the most sensitive when exposed to heavy metals and OA, and having the highest proportion of antagonistic interactions. Furthermore, the variations in interaction type frequencies are related to climate regions and heavy metal properties, with antagonistic interactions accounting for the highest proportion in temperate regions (28%) and when exposed to Zn (52%). Our study provides a comprehensive insight into the interactive effects of OA and HM on marine organisms, and highlights the importance of further investigating the responses of different marine taxonomic groups from various geographic locations to the combined stress of OA and HM.

Ocean acidification is recognized as a major anthropogenic perturbation of the modern ocean. While extensive studies have been carried out to explore the short-term physiological responses of phytoplankton to ocean acidification, little is known about their lipidomic responses after a long-term ocean acidification adaptation. Here we perform the lipidomic analysis of a marine diatom Phaeodactylum tricornutum following long-term (∼400 days) selection to ocean acidification conditions. We identified a total of 476 lipid metabolites in long-term high CO2 (i.e., ocean acidification condition) and low CO2 (i.e., ambient condition) selected P. tricornutum cells. Our results further show that long-term high CO2 selection triggered substantial changes in lipid metabolites by down- and up-regulating 33 and 42 lipid metabolites. While monogalactosyldiacylglycerol (MGDG) was significantly down-regulated in the long-term high CO2 selected conditions, the majority (∼80%) of phosphatidylglycerol (PG) was up-regulated. The tightly coupled regulations (positively or negatively correlated) of significantly regulated lipid metabolites suggest that the lipid remodeling is an organismal adaptation strategy of marine diatoms to ongoing ocean acidification. Since the composition and content of lipids are crucial for marine food quality, and these changes can be transferred to high trophic levels, our results highlight the importance of determining the long-term adaptation of lipids in marine producers in predicting the ecological consequences of climate change.

Although high CO2 and warming could act interactively on marine phytoplankton, little is known about the molecular basis for this interaction on an evolutionary scale. Here we explored the adaptation to high CO2 in combination with warming in a model marine diatom Phaeodactylum tricornutum. Whole-genome re-sequencing identifies, in comparison to populations grown under control conditions, a larger genetic diversity loss and a higher genetic differentiation in the populations adapted for 2 years to warming than in those adapted to high CO2. However, this diversity loss was less under high CO2 combined with warming, suggesting that the evolution driven by warming was constrained by high CO2. By integrating genomics, transcriptomics, and physiological data, we found that the underlying molecular basis for this constraint is associated with the expression of genes involved in some key metabolic pathways or biological processes, such as the glyoxylate pathway, amino acid and fatty acid metabolism, and diel variability. Our results shed new light on the evolutionary responses of marine phytoplankton to multiple environmental changes in the context of global change and provide new insights into the molecular basis underpinning interactions among those multiple drivers.

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