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ARS Home » Northeast Area » Leetown, West Virginia » Cool and Cold Water Aquaculture Research » Research » Publications at this Location » Publication #363869

Research Project: Integrated Research Approaches for Improving Production Efficiency in Salmonids

Location: Cool and Cold Water Aquaculture Research

Title: Gut microbiome analysis of fast- and slow-growing Rainbow Trout (Oncorhynchus mykiss)

item SHAPAGAIN, PRATIMA - Middle Tennessee State University
item ARIVETT, BROCK - Middle Tennessee State University
item Cleveland, Beth
item WALKER, DONALD - Middle Tennessee State University
item SALEM, MOHAMED - Middle Tennessee State University

Submitted to: Frontiers in Microbiology
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 10/1/2019
Publication Date: 10/29/2019
Citation: Shapagain, P., Arivett, B., Cleveland, B.M., Walker, D., Salem, M. 2019. Gut microbiome analysis of fast- and slow-growing Rainbow Trout (Oncorhynchus mykiss). Frontiers in Microbiology. 20:788.

Interpretive Summary: Fast growth rate is one of the most valued traits in the rainbow trout industry. Therefore it is important to understand the genetic and environmental factors that regulate weight gain to optimize breeding strategies and husbandry practices that improve growth. The naturally-occuring bacteria in the rainbow trout gut, collectively defined as the microbiome, is highly responsive to environmental factors, but the role of genetics is less understood. To better understand the interaction between genetics, the microbiome, and growth rates, the microbiome was analyzed between fast- and slow-growing rainbow trout from four different families. Results indicated that there was more variation in the microbiome bacteria profile between families rather than between fast- and slow-growers. However there were bacteria taxa (types) that tended to be more prevalent in fast versus slow growers and vice versa. Collectively these data suggest that the microbiome is susceptible to genetic variation and might be considered as a contributor to family differences in rainbow trout growth performance. These findings are important understanding the profile of the "ideal microbiome" that supports fast growth in rainbow trout.

Technical Abstract: Background Diverse microbial communities colonizing the intestine of fish contribute to their growth, digestion, nutrition, and immune function. We hypothesized that the gut microbiome of rainbow trout could be associated with differential growth rates observed in fish breeding programs. If true, harnessing the functionality of this microbiome can improve profitability of aquaculture. To test this hypothesis, four full-sibling families were stocked in the same tank and fed an identical diet. Two fast-growing and two slow-growing fish were selected from each family. Five different extraction methods were used to obtain DNA from feces for 16S rRNA microbiome profiling. These methods were Promega-Maxwell, phenol-chloroform, MO-BIO, Qiagen-Blood, Qiagen-Stool. Methods were compared according to DNA integrity, cost, feasibility and inter-sample variation based on non-metric multidimensional scaling ordination (nMDS) clusters. Results Differences in DNA extraction methods result in significant variation in identification of bacteria that compose the gut microbiome. Promega-Maxwell had the lowest inter-sample variation and was therefore used for the subsequent analyses. The gut microbiome was different from that of the environment (feed and water). However, feed and ut shared a large portion of their microbiome suggesting significant contribution of the feed in shaping the gut microbiota. Beta diversity of the bacterial communities showed significant variation between breeding families but not between the fast- and slow-growing fish. An indicator analysis determined that cellulose, amylose degrading and amino acid fermenting bacteria (Clostridium, Leptotrichia and Peptostreptococcus) as indicator taxa of the fast-growing fish. In contrary, pathogenic bacteria (Corynebacterium and Paeniclostridium) were identified as slow-growing indicator taxa. Conclusion DNA extraction methodology should be taken into account for accurate profiling of the gut microbiome. Although the microbiome was not significantly different between the fast- and slow-growing fish groups, some bacterial taxa with functional implications were indicative of fish growth rate. Further studies are warranted to explore how bacteria are transmitted and potential usage of the indicator bacteria of fast-growing fish for development of probiotics that may improve fish health and growth.