The carbon dioxide induced ocean acidification (OA) process is well known to have profound effects on physiology, survival and immune responses in marine organisms, and particularly calcifiers including edible oysters. At the same time, some wild populations could develop a complex and sophisticated immune system to cope with multiple biotic and abiotic stresses, such as bacterial infections and OA, over the long period of coevolution with the environment. However, it is unclear how immunological responses and the underlying mechanisms are altered under the combined effect of OA and bacterial infection, especially in the ecologically and economically important edible oysters. Here, we collected the wild population of oyster species Crassostrea hongkongensis (the Hong Kong oyster) from their native estuarine area and carried out a bacterial challenge with the worldwide pervasive pathogen of human foodborne disease, Vibrio parahaemolyticus, to investigate the host immune responses and molecular mechanisms under the high-CO2 and low pH-driven OA conditions. The wild population had a high immune resistance to OA, but the resistance is compromised under the combined effect of OA and bacterial infection both in vivo or in vitro. We classified all transcriptomic genes based on expression profiles and functional pathways and identified the specifically switched on and off genes and pathways under combined effect. These genes and pathways were mainly involved in multiple immunological processes including pathogen recognition, immune signal transduction and effectors. This work would help understand how the immunological function and mechanism response to bacterial infection in wild populations and predict the dynamic distribution of human health-related pathogens to reduce the risk of foodborne disease under the future climate change scenario.

In order to allow full comparability with other ocean acidification data sets, the R package seacarb (Gattuso et al, 2022) was used to compute a complete and consistent set of carbonate system variables, as described by Nisumaa et al. (2010). In this dataset the original values were archived in addition with the recalculated parameters (see related PI). The date of carbonate chemistry calculation by seacarb is 2023-05-15.