© 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim. Decreasing pH due to anthropogenic CO2 inputs, called ocean acidification (OA), can make coastal environments unfavorable for oysters. This is a serious socioeconomical issue for China which supplies >70% of the world's edible oysters. Here, we present an iTRAQ-based protein profiling approach for the detection and quantification of proteome changes under OA in the early life stage of a commercially important oyster, Crassostrea hongkongensis. Availability of complete genome sequence for the pacific oyster (Crassostrea gigas) enabled us to confidently quantify over 1500 proteins in larval oysters. Over 7% of the proteome was altered in response to OA at pHNBS 7.6. Analysis of differentially expressed proteins and their associated functional pathways showed an upregulation of proteins involved in calcification, metabolic processes, and oxidative stress, each of which may be important in physiological adaptation of this species to OA. The downregulation of cytoskeletal and signal transduction proteins, on the other hand, might have impaired cellular dynamics and organelle development under OA. However, there were no significant detrimental effects in developmental processes such as metamorphic success. Implications of the differentially expressed proteins and metabolic pathways in the development of OA resistance in oyster larvae are discussed. The MS proteomics data have been deposited to the ProteomeXchange with identifiers PXD002138 (http://proteomecentral.proteomexchange.org/dataset/PXD002138).
Bibliographical noteKAUST Repository Item: Exported on 2020-10-01
Acknowledgements: We are grateful to two anonymous reviewers and the editor who offered several constructive comments and criticisms on this article. The authors would like to thank Ziniu Yu and Shu Xiao of South China Sea Institute for Oceanology for providing the oysters and larval culture facilities used in our experiments. We thank Yun Lam (City University of Hong Kong) for providing various constructive comments during the proteomics data analysis and interpretation. This study was funded by three GRF grants from the HKSAR-RGC (grant numbers: 705511P, 705112P, and 17304914).