Whole transcriptome profiling of successful immune response to Vibrio infections in the oyster Crassostrea gigas by digital gene expression analysis

Abstract

The cultivated Pacific oyster Crassostrea gigas has suffered for decades large scale summer mortality phenomenon resulting from the interaction between the environment parameters, the oyster physiological and/or genetic status and the presence of pathogenic microorganisms including Vibrio species. To obtain a general picture of the molecular mechanisms implicated in C. gigas immune responsiveness to circumvent Vibrio infections, we have developed the first deep sequencing study of the transcriptome of hemocytes, the immunocompetent cells. Using Digital Gene Expression (DGE), we generated a transcript catalog of up-regulated genes from oysters surviving infection with virulent Vibrio strains (Vibrio splendidus LGP32 and V. aestuarianus LPi 02/41) compared to an avirulent one, V. tasmaniensis LMG 20012(T). For that an original experimental infection protocol was developed in which only animals that were able to survive infections were considered for the DGE approach. We report the identification of cellular and immune functions that characterize the oyster capability to survive pathogenic Vibrio infections. Functional annotations highlight genes related to signal transduction of immune response, cell adhesion and communication as well as cellular processes and defence mechanisms of phagocytosis, actin cytosqueleton reorganization, cell trafficking and autophagy, but also antioxidant and anti-apoptotic reactions. In addition, quantitative PCR analysis reveals the first identification of pathogen-specific signatures in oyster gene regulation, which opens the way for in depth molecular studies of oyster-pathogen interaction and pathogenesis. This work is a prerequisite for the identification of those physiological traits controlling oyster capacity to survive a Vibrio infection and, subsequently, for a better understanding of the phenomenon of summer mortality.

Figure 1. Kaplan-Meier survival curves of C. gigas oysters during infections with virulent Vibrio strains, V. aestuarianus LPi 02/41 or V. splendidus LGP32, and with avirulent V. tasmaniensis LMG 20012^T.

Infections for (a) construction of the hemocyte DGE libraries and (b) for gene expression exploration by qPCR analysis, with non injected oysters as control. For the two experiments, hemolymph was individually sampled from oysters that survived the infection at 96 h post-infection corresponding to the end of mortalities.

Figure 2. Gene expression analysis by qPCR.

(a) Hierarchical clustering analysis and differential expression of 18 genes from SVir library. Hemocyte gene expression profiles were analysed in biological replicates from oysters: non injected as control (C), surviving infections with avirulent V. tasmaniensis LMG 20012^T (T), with virulent V. splendidus LGP32 (S) and virulent V. aestuarianus LPi 02/41 (A). Each biological replicata was constituted by a pool of hemocyte RNA from ten oysters, and between 2 and 5 replicates were analysed for each experimental condition. Each cell in the matrix corresponds to the expression level of one gene in a sample. The intensity of the color from green to red indicates the magnitude of differential expression (see color scale at the bottom of the image). Relative expressions were calculated according the 2^−(ΔΔCt) method normalized with elongation factor-1α (EF-1α). Each value was calculated in reference to the mean of ΔCt of all conditions (relative expression = 1). The dendrograms at the top of the figures indicate relationship among experimental conditions which define clusters of conditions (CC). The dendrograms at the left of the figures indicate relationship among the profiles of the selected genes which define clusters of expression (CE), after clustering analysis using Multiple Array Viewer software. Gene #1: Inhibitor of apoptosis; #2: Baculoviral IAP repeat-containing protein 4; #3: Enhancer of kinase suppressor of Ras2; #4: Rac GTPase-activating protein1; #5: Proteasome 216S subunit, non-ATPase 11a; #6: Glyceraldhyde 3-phosphate dehydrogenase; #7: Thioredoxin; #8: C-type lectin 2 like protein; #9: Metallothionein IV; #10: F-box only protein37; #11: Cystatin B-like protein; #12: Heat shock protein 22 isoform 1; #13: L-rhamnose-binding lectin; #14: Microsomal glutathione S-tranferase; #15: Cystatin A; #16: Interferon-induced protein 44; #17: Cullin-associated and neddylation-dissociated 1. Hierarchical clustering was contructed with Multiple Array Viewer software using average linkage clustering with Pearson correlation as the default distance metric. (b) Examples of gene expression profiles defining pathogen- or challenge-specific signatures. SVir genes; line 1: similar response to both virulent strains; line 2: response induced by V. splendidus LGP32; line 3: response induced by V. aestuarianus LPi 02/41; line 4: SaVir genes. Different letters indicate significant variation between conditions (p<0.05) determined using the non-parametric multiple comparison test ANOVA of Kruskal-Wallis.

Figure 3. Functional annotation of unique ESTs differentially represented between SVir and SaVir libraries, respectively.

Categorization was based on KO terms of the Kyoto Encyclopedia of Genes and Genomes (KEGG) using KEGG Automatic Annotation Server (KAAS), and on GO terms of Biological Process using Blast2GO software.