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Metabolomics Study of Immune Responses of New Zealand Greenshell™ Mussels (Perna canaliculus) Infected with Pathogenic Vibrio sp.

Overview of attention for article published in Marine Biotechnology, April 2018
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Title
Metabolomics Study of Immune Responses of New Zealand Greenshell™ Mussels (Perna canaliculus) Infected with Pathogenic Vibrio sp.
Published in
Marine Biotechnology, April 2018
DOI 10.1007/s10126-018-9804-x
Pubmed ID
Authors

Thao V. Nguyen, Andrea C. Alfaro, Tim Young, Sridevi Ravi, Fabrice Merien

Abstract

Vibrio coralliilyticus is a bacterial pathogen which can affect a range of marine organisms, such as corals, fish and shellfish, with sometimes devastating consequences. However, little is known about the mechanisms involved in the host-pathogen interaction, especially within molluscan models. We applied gas chromatography-mass spectrometry (GC-MS)-based metabolomics to characterize the physiological responses in haemolymph of New Zealand Greenshell™ mussels (Perna canaliculus) injected with Vibrio sp. DO1 (V. coralliilyticus/neptunius-like isolate). Univariate data analyses of metabolite profiles in Vibrio-exposed mussels revealed significant changes in 22 metabolites at 6 h post-infection, compared to non-exposed mussels. Among them, 10 metabolites were up-regulated, while 12 metabolites were down-regulated in infected mussels. Multivariate analyses showed a clear distinction between infected and non-infected mussels. In addition, secondary pathway analyses indicated perturbations of the host innate immune system following infection, including oxidative stress, inflammation and disruption of the TCA cycle, change in amino acid metabolism and protein synthesis. These findings provide new insights into the pathogenic mechanisms of Vibrio infection of mussels and demonstrate our ability to detect detailed and rapid host responses from haemolymph samples using a metabolomics approach.

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Geographical breakdown

Country Count As %
Unknown 50 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 7 14%
Researcher 7 14%
Student > Master 5 10%
Student > Doctoral Student 5 10%
Other 4 8%
Other 9 18%
Unknown 13 26%
Readers by discipline Count As %
Agricultural and Biological Sciences 15 30%
Environmental Science 7 14%
Biochemistry, Genetics and Molecular Biology 6 12%
Chemistry 2 4%
Veterinary Science and Veterinary Medicine 1 2%
Other 5 10%
Unknown 14 28%