- Analysis of the fecal microbiota of fast- and slow-growing rainbow trout ( Oncorhynchus mykiss. - Two fast-growing and two slow-growing fish were selected from each family for 16S rRNA microbiota profiling.. - Microbiota diversity varies with different DNA extraction methods. - Results: Differences in DNA extraction methods resulted in significant variation in the identification of bacteria that compose the gut microbiota. - Beta diversity of the bacterial communities showed significant variation between breeding families but not between the fast- and slow-growing fish. - However, an indicator analysis determined that cellulose, amylose degrading and amino acid fermenting bacteria ( Clostridium , Leptotrichia, and Peptostreptococcus ) are indicator taxa of the fast-growing fish. - In contrary, pathogenic bacteria ( Corynebacterium and Paeniclostridium ) were identified as indicator taxa for the slow-growing fish.. - Conclusion: DNA extraction methodology should be carefully considered for accurate profiling of the gut. - Although the microbiota 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. - 2019 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0. - Full list of author information is available at the end of the article. - Microorganisms making up the fish microbiota reside on the fish skin, gills, and gastrointes- tinal tract and likely play a crucial role in the growth rate, metabolism, and immunity of the fish host [4, 5].. - For example, plant and animal-based meal can widely alter the composition of the host microbiota since fish acquire their microbiota from the first-feed they eat [10–12]. - reported that microbiota of the marine species can be directly inherited from ancestors and passed from generation to generation [13]. - The gut, in particular, features a diverse microbiota contributing to the weight gain, immune de- velopment, pathogen inhibition, and various metabolic activities of the hosts [14]. - An accurate census of bacteria from fish may allow in- vestigation of the positive effects of the microbiota. - How- ever, profiling of the gut microbiome is directly influenced by many factors including the experimental design, sample collection, and processing. - DNA extraction is particularly important since microbiome analysis requires adequate quality and quantity of DNA isolated for an accurate rep- resentation of the host-microbiome [17]. - with different DNA extraction methods [18]. - In this study, we investigated how the gut microbiota of rainbow trout correlates with differential growth rates.. - Therefore, one objective of this research was to characterize the gut microbiota of rainbow trout using high-throughput DNA sequencing. - The specific objectives of our study were to determine differences in community structure of the gut microbiota between fast- and slow-growing rainbow trout and to determine if genetics plays a role in determining the gut microbiota profile. - Our results highlight differences of the gut microbiota between fish family and the bacterial taxa indicative of fast- and slow-growing rainbow trout.. - Comparison of different DNA extraction methods. - To test if profiling of the gut microbiota is directly influ- enced by the DNA extraction method, three replicate pools of the fish fecal samples were sequenced and ana- lyzed using five different extraction methods. - Within non-metric dimensional scaling ordination plots, the three-replicate samples extracted with Promega clus- tered tightly, whereas, replicate samples of the four other extraction methods were relatively more heterogeneous (Fig. - Comparative analysis of the three extraction methods revealed that Phenol- chloroform had the highest OTU richness with 649 OTUs. - Comparing the abundance of the Gram-positive and Gram-negative bac- teria, it was clear that the abundance of the Gram- positive is higher than that of the Gram-negative in all. - One of the phenol-chloroform samples did not pass the QC and was excluded from the analysis. - 2 a) nMDS representation of the fecal samples using three different extraction methods. - three DNA extraction techniques (Fig. - We decided to choose Promega for our downstream analysis of the fecal microbiota.. - Mean weight difference between fast and slow-growing fish. - The mean weight of the fast-growing fish was g, whereas, the mean weight of the slow-growing fish was g. - The mass of the fast-growing fish was significantly greater than that of the slow- growing fish when compared using one-way Mann- Whitney U test (p <. - Gut microbiota analysis of fast- and slow-growing fish Our analysis of microbial diversity based on alpha diver- sity in the fast-growing and slow-growing fish fecal sam- ples using inverse Simpson indices indicated no significant differences between fast and slow-growing fish (p >. - Both fast- and slow-growing fish possessed unique sets of OTUs and overlapping taxa (Fig. - However, an in- dicator analysis predicted that 10 OTUs were found as indicative of the growth rate (Table 2, p <. - Tepidimicrobium, Peptostreptococcus and Lachnospira- ceae_unclassified whereas, the slow-growing indicator taxa belonged to phylum Actinobacteria and Firmicutes with genera Corynebacterium and Paeniclostridium (Table 2).. - The overall taxa information of the fecal samples has been included in Additional file 1.. - In this study, the DNA extraction methodology comparison was performed to optimize the extraction methodology and apply this to the comparison of fast- and slow-growing fish gut microbiota. - The effects of the DNA extraction methods were assessed on the basis of the DNA quantity, quality and the inter-sample variation in microbial communities between replicates. - The concentration and the quality of the DNA. - MOBIO method, involves bead beat- ing to physically lyse cell wall of bacteria, increased the number of the microbial species identified but showed rela- tively high inter-sample variation among replicates. - 3 Significant difference in the mean weight of the fast-growing versus slow-growing fish used in the study. - significance of the rank body mass between the two groups was tested by a one-way Mann-Whitney U test (p <. - 4 a) nMDS representation of the fast- and slow-growing fish using Promega extraction method (stress value = 0.07). - b) Venn-diagram depicting the common and unique OTUs in fast-growing and slow-growing rainbow trout c) nMDS representation of the fish family on the basis of dissimilarity matrices (stress value = 0.07). - Most of the samples from family 1 were clustered apart from families 2, 3, and 4. - representation of the common and unique OTUs among four different families. - lysozyme enzymes, which induces lysis of the Gram- positive bacterial cell wall. - We found that specific taxa were indicators of the fish growth rate and fish breeding family. - pathogenic bacteria, whereas the indicator taxa of fast- growing fish seem to have a mutually beneficial relation- ship with the host. - Corynebacterium and Paeniclostri- dium which are known pathogens [21] were more prevalent in slow-growing fish. - Families Lachnospiraceae, Leptotrichia- ceae, Planococcaceae, and Peptostreptococcaceae belong- ing to the phylum Firmicutes were indicator taxa for the fast-growing fish in this study. - On the other hand, bacteria like Selli- monas, Clostridium, Peptostreptococcus in fast-growing fish can take part in fermentation of different amino acids, lactates and sugars [29]. - The most widely prevalent and statistically significant indicator taxa of the fast-growing fish, Peptostreptococcus and Clostridium, are more likely to be involved in amino acid fermentation that ultim- ately leads to amino acid absorption in host gut. - Leptori- chia, the most abundant taxa in the gut of all the fast- growing fish are cellulose-degrading bacteria. - Similarly, the class Enterobacteriaceae was found to be a significantly abundant taxonomical class in most of the fast-growing fish. - Although most of the microbiota were shared among the fish families, some unique taxa were characteristic for each family, which suggests that genetics is a contrib- uting factor affecting the gut microbiota. - Fish family 3 showed a higher abundance of phylum Bacteroidales with unclassified Table 2 Indicator analysis of the taxa for growth rate using Mothur. - p ≤ 0.05 indicates the significant taxa to act as indicator of the fast-growing or slow-growing fish. - Further research is needed to validate familial differences and determine the contribution of genetic and environmental factors to development of the gut microbiota.. - This study showed that DNA extraction methodology should be taken into account for accurate profiling of the gut microbiome. - Although population-level microbiota differences were not found to be significantly associated with the fish growth rate, several indicator taxa were determined in the fast- and slow-growing fish. - Tagged fish were comingled for the remainder of the grow-out period. - Fish were fed Table 3 Indicator analysis of the taxa for fish families using Mothur. - 1952 g) and two that were slow-growing (<. - Of the 16 fish se- lected for sampling, one slow-growing fish from family two exhibited morphological signs of disease during sample collection and was excluded from analysis, redu- cing the total number of samples to 15.. - 80 °C until DNA extraction. - At the end of the experi- ment, fish were euthanized with an overdose of MS-222 at a concentration of 300 mg/L.. - For comparison of extraction methods, fecal samples from 8 fast-growing and 7 slow-growing fish were pooled to- gether and DNA extraction was done in triplicate using five different extraction methods including PowerSoil®. - The individual biological replicates DNA samples extracted using the MOBIO, Promega, and Phenol-chloroform methods were used for the analysis of the gut microbiota of fast-growing versus slow-growing trout. - More detail of the DNA extraction methods is pro- vided in Additional file 2 and steps of experimental design using pooled and unpooled samples have been included in Fig. - A DNA fragment of the amplicon for each sample was ex- cised from the DNA gel with a clean, sharp scalpel and collected in nuclease-free sterile tubes. - The concentration of the gel-extracted library was assessed with a Qubit fluorometer (Invitrogen, Carlsbard, CA) and fragment size was determined using an Agilent 2100 Bioanalyzer (Agilent, Santa Clara, California). - Final qPCR-based quantification of the library was done using a KAPPA quantification kit (Roche, Pleasanton, CA). - After forming contigs, the total number of sequences were 3,972,613 the median length (371 bp) of the se- quences was determined. - Similarly, Beta diversity of fast-growing and slow-growing samples were calcu- lated using Bray-Cutis dissimilarity matrices represent- ing pairwise (sample to sample) distances to test the variation among fast and slow-growing fish. - Non-metric multidimensional scaling ordination (nMDS) was used to explore the microbial communities in the fast- growing and slow-growing fish by considering the dis- similarity distance matrices among the samples. - The statistical significance of the rank body mass be- tween the two groups was tested by a one-way Mann- Whitney U test with an alpha of p <. - a) DNA extraction comparison using pooled fecal samples from all fast- and slow- growing fish. - Three pooled fecal samples from all fast and slow-growing fish were subjected to five different DNA extraction comparisons. - b) Analysis of fecal sample (unpooled) from 8 fast and 7 slow-growing fish to study the microbial assemblages. - DNA extraction protocol. - Detailed information regarding the fast and slow-growing fish samples (weight, length, sex, condition factor).. - a) Fast- and slow- growing fish fecal sample analysis shared file Extraction technique shared file. - Beta diversity analysis result file of the fast- and slow- growing fish using PRIMER. - PERMANOVA results for fast and slow-growing fish analysis and PERMA- NOVA results for fish families.. - PERMANOVA result for DNA extraction comparison.. - a) Fast- and slow- growing fecal analysis taxonomy file Extraction techniques taxonomy file.. - This study, including the husbandry practices, analysis and euthanasia methods of the rainbow trout was submitted to and approved by the Animal Care and Use Committee of the United States Department of Agriculture, National Center for Cool and Cold Water Aquaculture (IACUC approval #098).. - Mohamed Salem is a member of the editorial board of BMC Genomics.. - Human genetics shape the gut microbiome. - Unravelling the effects of the environment and host genotype on the gut microbiome. - Analysis of the gut and gill microbiome of resistant and susceptible lines of rainbow trout (Oncorhynchus mykiss). - The gut microbiota of marine fish. - Relationship between the gut microbiome and brain function. - Characterization of the gut microbiota of three commercially valuable warmwater fish species
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