Gut Microbiome Succession in Chinese Mitten Crab Eriocheir sinensis During Seawater-Freshwater Migration

Abstract

Biological migration is usually associated with disturbances and environmental changes that are key drivers in determining the diversity, community compositions, and function of gut microbiome. However, little is known about how gut microbiome is affected by disturbance such as salinity changes during migration from seawater to freshwater. Here, we tracked the gut microbiome succession of Chinese mitten crabs (Eriocheir sinensis) during their migrations from seawater to freshwater and afterward using 16S rDNA sequencing for 127 days, and explored the temporal patterns in microbial diversity and the underlying environmental factors. The species richness of gut microbiome showed a hump-shaped trend over time during seawater-freshwater migration. The community dissimilarities of gut microbiome increased significantly with day change. The turnover rate of gut microbiome community was higher during seawater-freshwater transition (1-5 days) than that in later freshwater conditions. Salinity was the major factor leading to the alpha diversity and community dissimilarity of gut microbiome during seawater-freshwater transition, while the host selection showed dominant effects during freshwater stage. The transitivity, connectivity, and average clustering coefficient of gut microbial co-occurrence networks showed decreased trends, while modularity increased during seawater-freshwater migration. For metabolic pathways, "Amino Acid Metabolism" and "Lipid Metabolism" were higher during seawater-freshwater transition than in freshwater. This study advances our mechanistic understanding of the assembly and succession of gut microbiota, which provides new insights into the gut ecology of other aquatic animals.

Keywords: Chinese mitten crab; gut microbiome succession during migration gut microbiome; migration; salinity; seawater–freshwater transition.

FIGURE 1

Experimental design of gut microbiome sampling of Chinese mitten crab. The sampling locations at different sampling days and salinity corresponding to each sampling day are shown.

FIGURE 2

The temporal patterns and drivers of species richness and evenness of Chinese mitten crab gut microbiome during seawater–freshwater migration. (A) The relationships between days and alpha diversity were modeled with linear and quadratic models. The better model was selected based on the lower value of Akaike’s information criterion. The significant trend of the model is shown as solid line, and the non-significant trend is shown as dotted line. (B) The abiotic factors related to richness and evenness were identified with random forest during seawater–freshwater transition (SFT) and freshwater (FW), respectively. For abiotic factors, we considered phosphate (PO₄³⁻), water temperature (WT), salinity, and ammonia nitrogen (NH${}_3^{+}$) of water.

FIGURE 3

The relationships among the community dissimilarities and day change (A); NMDS ordinations showing the structures of gut microbiome during seawater–freshwater transition (SFT) and freshwater (FW) (B); the abiotic factors related to bacterial community (C,D). The regression slopes of the linear relationships based on Gaussian generalized linear model are shown with solid lines. The relationships were statistically significant according to the Mantel test (9,999 permutations, p < 0.05) except for the bacterial communities. These factors were identified with redundancy analysis (RDA) during the seawater-freshwater transition (SFT) (C) and the freshwater stage (FW) (D). For explanatory factors, we considered phosphate (PO₄³⁻), water temperature (WT), salinity, and ammonia nitrogen (NH${}_3^{+}$) of water. Overlap among samples in panels (C,D) may due to smaller sample size. *p < 0.5; **p < 0.05; ***p < 0.01.

FIGURE 4

The relative abundance of bacterial phyla in the seawater–freshwater transition and freshwater stage (A), and temporal patterns of dominant bacterial phyla (B). The relationships between time and relative abundance were modeled with linear and quadratic models. The better model was selected based on the lower value of Akaike’s information criterion.

FIGURE 5

The co-occurrence network of gut microbiome on Chinese mitten crabs at the OTU level (A). The nodes each represent unique OTUs in the data sets. The size of each node is proportional to the number of connections (that is, degree). OTUs are colored by different phyla. The green side is positive correlation and the red side is negative correlation. The relationships between network topological properties and time for gut microbiome community were modeled with linear and quadratic models (B). The significant trend of the model is shown as solid line, and the non-significant trend is shown as dotted line. The better model was selected based on the lower value of Akaike’s information criterion.

FIGURE 6

The functional profiles and organism level phenotypes of different microbial communities over time. Phylogenetic Investigation of Communities by Reconstruction of Unobserved States (PICRUSt) analysis was performed to identify the influenced biological pathways of the influence of salinity changes on the gut microbiome of the Chinese mitten crab (A). Phenotype inference of bacterial communities from the Chinese mitten crab gut (B–E). Relative abundances of bacteria differing in Gram staining are shown in panel (C) for Gram-negative and panel (D) for Gram-positive. Relative abundances of bacteria differing in latent pathogenicity phenotypes are shown in panel (B) for oxidative stress tolerance and panel (E) for biofilm formation.