Hemolymph microbiota and immune effectors' expressions driven by geographical rearing acclimation of the aquacultured Penaeus stylirostris

Abstract

Background: In holobiont, microbiota is known to play a central role on the health and immunity of its host. Then, understanding the microbiota, its dynamic according to the environmental conditions and its link to the immunity would help to react to potential dysbiosis of aquacultured species. While the gut microbiota is highly studied, in marine invertebrates the hemolymph microbiota is often set aside even if it remains an important actor of the hemolymph homeostasis. Indeed, the hemolymph harbors the factors involved in the animal homeostasis that interacts with the microbiota, the immunity. In the Southwest Pacific, the high economical valued shrimp Penaeus stylirostris is reared in two contrasted sites, in New Caledonia (NC) and in French Polynesia (FP).

Results: We characterized the active microbiota inhabiting the hemolymph of shrimps while considering its stability during two seasons and at a one-month interval and evidenced an important microbial variability between the shrimps according to the rearing conditions and the sites. We highlighted specific biomarkers along with a common core microbiota composed of 6 ASVs. Putative microbial functions were mostly associated with bacterial competition, infections and metabolism in NC, while they were highly associated with the cell metabolism in FP suggesting a rearing site discrimination. Differential relative expression of immune effectors measured in the hemolymph of two shrimp populations from NC and FP, exhibited higher level of expression in NC compared to FP. In addition, differential relative expression of immune effectors was correlated to bacterial biomarkers based on their geographical location.

Conclusions: Our data suggest that, in Pacific shrimps, both the microbiota and the expression of the immune effectors could have undergone differential immunostimulation according to the rearing site as well as a geographical adaptative divergence of the shrimps as an holobiont, to their rearing sites. Further, the identification of proxies such as the core microbiota and site biomarkers, could be used to guide future actions to monitor the bacterial microbiota and thus preserve the productions.

Keywords: Active microbiota; Biomarkers; Geographical divergence; Host-microbiota interactions; Immune effectors; Immunostimulation; Shrimp hemolymph.

Fig. 1

Experimental design. A. Relative position and distance of the island of New Caledonia (NC) and French Polynesia (FP) B. Schematic representation of the experimental protocol. Water and hemolymph sampling. Maps were modified from the images source available at: commons.wikimedia.org.: (World pacific 0001.svg, Blank map of New Caledonia.svg, Blank map of Tahiti.svg)

Fig. 2

Microbial diversity distribution among hemolymph and seawater samples according to the site. (A) PCoA representation of the beta diversity based on Bray-Curtis dissimilarity matrix. Ellipses regrouped 80% of the samples around the centroid per sample type (hemolymph, water) and site (NC, FP). (B) Alpha diversity based on Observed ASVs index. (C) Alpha diversity based on Pielou index. The conditions without common letter are significantly different, p-values < 0.05 according to pairwise Wilcoxon tests. Turquoise points stand for the seawater (water) samples collected in New Caledonia (NC); green lozenges for the hemolymph (Hem) samples collected in NC; purple triangle for the seawater sample collected in French Polynesia (FP); pink crosses for the hemolymph samples collected in FP

Fig. 3

Relative abundance of the 20 most abundant bacterial orders in the hemolymph samples. (A) Hemolymph samples in New Caledonia. (B) Hemolymph samples in French Polynesia. Each sample match to a given conditions corresponding to the sampling time: beginning of the experimentation (T0), 1 month later (T1) and season: warm season (WS), cold season (CS). Orders written in grey were common in both sites

Fig. 4

Specific and common ASVs. Venn diagrams showing the common ASVs and specific ASVs in: (A) the NC conditions; (B) the FP conditions; (C) comparison of the core microbiota found in NC and in FP. Sampling time: beginning of the experimentation (T0), 1 month later (T1); Season: warm season (WS), cold season (CS). For all the Venn diagrams, ASVs present in at least 75% samples were considered

Fig. 5

Biomarkers of enriched taxa at different taxonomic ranks. Biomarkers were identified by LEfSe with an LDA cutoff score of 4 for (A) NC conditions, with no biomarker in the condition NC T1 WS; (B) FP conditions; (C) each site. g__ASV55 meant the ASV55 was affiliated to an unknown genus of the Tannerellaceae family, then the g__ in front of the ASV55 indicate that it is not a stricto sensu genus. Sampling times: beginning of the experimentation (T0), 1 month later (T1); Seasons: warm season (WS), cold season (CS)

Fig. 6

Co-occurrence networks of the bacterial orders in the hemolymph samples by site. (A) in NC; (B) in FP. All co-occurrences (p-values < 0.05) identified were negatives and were represented with blue lines. Three sizes of dots were used, the smaller dots correspond to orders with only one interaction, the medium dots correspond to orders with multiple interactions and the bigger dot corresponds to the center node of interactions. In grey the 9 orders commons to both sites, the central node of each network is noted in capital letter

Fig. 7

Putative enriched functions of the microbial diversity inhabiting the hemolymph samples per condition and site. KO markers at the KEGG orthology (K.O) level 2, enriched putative functions in each site, determined by LEfSe with an LDA cutoff score of 3. The putative functions of the host associated-microbiota were identified and assigned with the R package Tax4Fun, the public prokaryote database FAPROTAX and the Silva KO references [55], according to the variables. Site: New Caledonia (NC), French Polynesia (FP)

Fig. 8

Relative expression of six immune effectors in shrimp hemocytes. Heatmap of the relative expression of each immune effector per individual shrimp sample. Four peptides: anti-LPS factor (Alf), cryptdin (Crypt), crustin (Crus), peneidin (Pen3), and two enzymes: cytosolic manganese superoxide dismutase (cMnSOD) and lysozyme (LysA). The heatmap was obtained with a 3-colors scale. The minimal, midpoint and maximal color values were set at the percentiles 5, 25 and 95 for each effector independently

Fig. 9

Correlogram based on the biomarkers and the relative expressions of the immune effectors. Heatmap of the spearman correlation coefficient comparing the relative expressions of each immune effector and the biomarkers identified in the Fig. 5. The calculations were performed for each site independantly. Four peptides: anti-LPS factor, cryptdin, crustin, peneidin, and two enzymes: cytosolic manganese superoxide dismutase and lysozyme. The heatmap was obtained with a 3-colors scale with the minimal, midpoint and maximal color values set at -0.50, 0, and 0.50. Asterix indicated significant correlations