Abstract

In the Coregonus lavaretus complex may be found lacustrine sympatric pairs, which serves as an intriguing model for studying different aspects of fish evolutionary biology. One such sympatric whitefish pair inhabits Teletskoye Lake (West Siberia, Russia) and includes a “large” form (Coregonus lavaretus pidschian (Gmelin, 1789)) and a “small” form (C. l. pravdinellus (Dulkeit, 1949)). C. l. pravdinellus has a narrow trophic specialization and feeds on zooplankton, whereas the diet of C. l. pidschian is based on benthic prey. In the present study we aimed to address the question of how the gut microbial community reflects the divergence in diet of a sympatric pair of whitefish. Studied samples included the mucosa and content were collected for cardiac and pyloric stomach, anterior, middle, and posterior intestine, but only mucosa was collected for the pyloric caeca. In addition, water, sediment, macrophyte (environmental microbiota) and invertebrate (microbiota of prey) samples were collected in the same location. The V3–V4 region of the 16S rRNA genes was chosen for microbiome analysis and the software PICRUSt used to estimate the difference functional roles of the microbiota. The number of OTUs and Chao1 index in mucosa and content of cardiac and pyloric stomach were significantly different between whitefish. Significant differences were observed between whitefish for content from different parts of the intestine in terms of OTU number and Chao1 indices, whereas for mucosa from the same parts of intestine these differences were absent. No significant differences were found for diversity estimates of mucosa and content of different parts of the gut (there were a few exceptions) between whitefish. The form of whitefish and the segment of the digestive system were factors with a significant determinative effect on the structure of the microbiota from gut mucosa and content. The most dominant phyla in mucosa and content of cardiac and pyloric stomach was Proteobacteria (57.0–84.0%) for both whitefish. Throughout the intestine of C. l. pidschian the dominant phyla in mucosa were Proteobacteria (38.8%) and Firmicutes (15.6%), whereas for C. l. pravdinellus–Tenericutes (49.6%) and Proteobacteria (28.1%). For both forms, the phylum Spirochaetes was found in a significant amount (20.0–25.0%) in the mucosa of the posterior intestine. While for the content obtained from anterior, middle and posterior intestines, the dominant bacterial phyla were the same as those described for mucosa from the same parts of the intestine for both whitefish. The bacterial community of the prey and environment was significantly different from bacterial communities found for all parts of the gut mucosa for both whitefish, with the exception of the mucosa of the cardiac stomach. According to PICRUSt the highest level of differences between whitefish at the L3 level were found for the intestinal mucosa (75.3%), whereas the lowest one was registered for stomach content (38.8%).

Highlights

  • The enteric bacterial community is a complex and dynamic microbial ecosystem within the gut of animals

  • The number of OTU and Chao1 index were significantly higher in mucosa from pyloric stomach (1,068 ± 130.2 and 1,374 ± 157.1 respectively) than in mucosa from cardiac stomach (755 ± 257.5 and 897 ± 257.6 respectively)

  • In our study we aimed to address the question of how the gut microbial community reflects the divergence in diet of a sympatric pair of whitefish

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Summary

Introduction

The enteric bacterial community is a complex and dynamic microbial ecosystem within the gut of animals. These bacterial communities possess multiple different functions and play important roles in various physiological processes including disease prevention for their host (Verschuere et al, 2000; Araújo et al, 2014; Vasemägi, Visse & Kisand, 2017). It has been shown that one of the main factors that can determine and modify the qualitative (taxonomic composition) and quantitative (relative abundance of each taxa) composition of gut bacterial community is the host diet (Wu et al, 2010; Sullam et al, 2012; Bolnick et al, 2014a; Bolnick et al, 2014b; Larsen, Mohammed & Arias, 2014; Li et al, 2014a; Li et al, 2014b; Tietjen, 2014; Miyake, Ngugi & Stingl, 2015; Liu et al, 2016; Baldo et al, 2017; Kashinskaya et al, 2015; Kashinskaya et al, 2018)

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