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      Dynamics of the gut microbiota in developmental stages of Litopenaeus vannamei reveal its association with body weight

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          Abstract

          Increasing evidences have revealed a close interaction between the intestinal microbes and host growth performance. The shrimp ( Litopenaeus vannamei) gut harbors a diverse microbial community, yet its associations with dietary, body weight and weaning age remain a matter of debate. In this study, we analyzed the effects of different dietary (fishmeal group (NC), krill meal group (KM)) and different growth stages (age from 42 day-old to 98 day-old) of the shrimp on the intestinal microbiota. High throughput sequencing of the 16S rRNA genes of shrimp intestinal microbes determined the novelty of bacteria in the shrimp gut microbiota and a core of 58 Operation Taxonomic Units (OTUs) was present among the shrimp gut samples. Analysis results indicated that the development of the shrimp gut microbiota is a dynamic process with three stages across the age according to the gut microbiota compositions. Furthermore, the dietary of KM group did not significantly change the intestinal microbiota of the shrimps compared with NC group. Intriguingly, compared to NC group, we observed in KM group that a fluctuation of the shrimp gut microbiota coincided with the shrimp body weight gain between weeks 6–7. Six OTUs associated with the microbiota change in KM group were identified. This finding strongly suggests that the shrimp gut microbiota may be correlated with the shrimp body weight likely by influencing nutrient uptake in the gut. The results obtained from this study potentially will be guidelines for manipulation to provide novel shrimp feed management approaches.

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          A healthy gastrointestinal microbiome is dependent on dietary diversity

          Background Like all healthy ecosystems, richness of microbiota species characterizes the GI microbiome in healthy individuals. Conversely, a loss in species diversity is a common finding in several disease states. This biome is flooded with energy in the form of undigested and partially digested foods, and in some cases drugs and dietary supplements. Each microbiotic species in the biome transforms that energy into new molecules, which may signal messages to physiological systems of the host. Scope of review Dietary choices select substrates for species, providing a competitive advantage over other GI microbiota. The more diverse the diet, the more diverse the microbiome and the more adaptable it will be to perturbations. Unfortunately, dietary diversity has been lost during the past 50 years and dietary choices that exclude food products from animals or plants will narrow the GI microbiome further. Major conclusion Additional research into expanding gut microbial richness by dietary diversity is likely to expand concepts in healthy nutrition, stimulate discovery of new diagnostics, and open up novel therapeutic possibilities.
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            Changes in intestinal bacterial communities are closely associated with shrimp disease severity.

            Increasing evidence has revealed a close association between intestinal bacterial communities and human health. However, given that host phylogeny shapes the composition of intestinal microbiota, it is unclear whether changes in intestinal microbiota structure in relation to shrimp health status. In this study, we collected shrimp and seawater samples from ponds with healthy and diseased shrimps to understand variations in bacterial communities among habitats (water and intestine) and/or health status. The bacterial communities were clustered according to the original habitat and health status. Habitat and health status constrained 14.6 and 7.7 % of the variation in bacterial communities, respectively. Changes in shrimp intestinal bacterial communities occurred in parallel with changes in disease severity, reflecting the transition from a healthy to a diseased state. This pattern was further evidenced by 38 bacterial families that were significantly different in abundance between healthy and diseased shrimps; moderate changes were observed in shrimps with sub-optimal health. In addition, within a given bacterial family, the patterns of enrichment or decrease were consistent with the known functions of those bacteria. Furthermore, the identified 119 indicator taxa exhibited a discriminative pattern similar to the variation in the community as a whole. Overall, this study suggests that changes in intestinal bacterial communities are closely associated with the severity of shrimp disease and that indicator taxa can be used to evaluate shrimp health status.
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              Integrating gut microbiota immaturity and disease-discriminatory taxa to diagnose the initiation and severity of shrimp disease.

              Increasing evidence has emerged a tight link among the gut microbiota, host age and health status. This osculating interplay impedes the definition of gut microbiome features associated with host health from that in developmental stages. Consequently, gut microbiota-based prediction of health status is promising yet not well established. Here we firstly tracked shrimp gut microbiota (N = 118) over an entire cycle of culture; shrimp either stayed healthy or progressively transitioned into severe disease. The results showed that the gut microbiota were significantly distinct over shrimp developmental stages and disease progression. Null model and phylogenetic-based mean nearest taxon distance (MNTD) analyses indicated that deterministic processes that governed gut community became less important as the shrimp aged and disease progressed. The predicted gut microbiota age (using the profiles of age-discriminatory bacterial species as independent variables) fitted well (r = 0.996; P < 0.001) with the age of healthy subjects, while this defined trend was disrupted by disease. Microbiota-for-age Z-scores (MAZ, here defined as immaturity) were relative stable among healthy shrimp, but sharply decreased when disease emerged. By distinguishing between age- and disease- discriminatory taxa, we developed a model, bacterial indicators of shrimp health status, to diagnose disease from healthy subjects with 91.5% accuracy. Notably, the relative abundances of the bacterial indicators were indicative for shrimp disease severity. These findings, in aggregate, add our understanding on the gut community assembly patterns over shrimp developmental stages and disease progression. In addition, shrimp disease initiation and severity can be accurately diagnosed using gut microbiota immaturity and bacterial indicators.
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                Author and article information

                Contributors
                yingfei.ma@siat.ac.cn
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                24 January 2019
                24 January 2019
                2019
                : 9
                : 734
                Affiliations
                [1 ]ISNI 0000000119573309, GRID grid.9227.e, Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, , Chinese Academy of Sciences, ; Shenzhen, 518000 China
                [2 ]ISNI 0000 0001 0483 7922, GRID grid.458489.c, Shenzhen Key Laboratory of Synthetic Genomics, , Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, ; Shenzhen, 518055 China
                [3 ]R&D Center, Shenzhen Alpha Group Co., Ltd, Shenzhen, 518000 China
                Article
                37042
                10.1038/s41598-018-37042-3
                6345827
                30679786
                32de608f-c813-4266-866f-0101c56061b7
                © The Author(s) 2019

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 16 April 2018
                : 28 November 2018
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