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      The queen’s gut refines with age: longevity phenotypes in a social insect model

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          Abstract

          Background

          In social insects, identical genotypes can show extreme lifespan variation providing a unique perspective on age-associated microbial succession. In honey bees, short- and long-lived host phenotypes are polarized by a suite of age-associated factors including hormones, nutrition, immune senescence, and oxidative stress. Similar to other model organisms, the aging gut microbiota of short-lived (worker) honey bees accrue Proteobacteria and are depleted of Lactobacillus and Bifidobacterium, consistent with a suite of host senescence markers. In contrast, long-lived (queen) honey bees maintain youthful cellular function with much lower expression of oxidative stress genes, suggesting a very different host environment for age-associated microbial succession.

          Results

          We sequenced the microbiota of 63 honey bee queens exploring two chronological ages and four alimentary tract niches. To control for genetic and environmental variation, we quantified carbonyl accumulation in queen fat body tissue as a proxy for biological aging. We compared our results to the age-specific microbial succession of worker guts. Accounting for queen source variation, two or more bacterial species per niche differed significantly by queen age. Biological aging in queens was correlated with microbiota composition highlighting the relationship of microbiota with oxidative stress. Queens and workers shared many major gut bacterial species, but differ markedly in community structure and age succession. In stark contrast to aging workers, carbonyl accumulation in queens was significantly associated with increased Lactobacillus and Bifidobacterium and depletion of various Proteobacteria.

          Conclusions

          We present a model system linking changes in gut microbiota to diet and longevity, two of the most confounding variables in human microbiota research. The pattern of age-associated succession in the queen microbiota is largely the reverse of that demonstrated for workers. The guts of short-lived worker phenotypes are progressively dominated by three major Proteobacteria, but these same species were sparse or significantly depleted in long-lived queen phenotypes. More broadly, age-related changes in the honey bee microbiota reflect the regulatory anatomy of reproductive host metabolism. Our synthesis suggests that the evolution of colony-level reproductive physiology formed the context for host-microbial interactions and age-related succession of honey bee microbiota.

          Electronic supplementary material

          The online version of this article (10.1186/s40168-018-0489-1) contains supplementary material, which is available to authorized users.

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          Most cited references76

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          Naive Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy.

          The Ribosomal Database Project (RDP) Classifier, a naïve Bayesian classifier, can rapidly and accurately classify bacterial 16S rRNA sequences into the new higher-order taxonomy proposed in Bergey's Taxonomic Outline of the Prokaryotes (2nd ed., release 5.0, Springer-Verlag, New York, NY, 2004). It provides taxonomic assignments from domain to genus, with confidence estimates for each assignment. The majority of classifications (98%) were of high estimated confidence (> or = 95%) and high accuracy (98%). In addition to being tested with the corpus of 5,014 type strain sequences from Bergey's outline, the RDP Classifier was tested with a corpus of 23,095 rRNA sequences as assigned by the NCBI into their alternative higher-order taxonomy. The results from leave-one-out testing on both corpora show that the overall accuracies at all levels of confidence for near-full-length and 400-base segments were 89% or above down to the genus level, and the majority of the classification errors appear to be due to anomalies in the current taxonomies. For shorter rRNA segments, such as those that might be generated by pyrosequencing, the error rate varied greatly over the length of the 16S rRNA gene, with segments around the V2 and V4 variable regions giving the lowest error rates. The RDP Classifier is suitable both for the analysis of single rRNA sequences and for the analysis of libraries of thousands of sequences. Another related tool, RDP Library Compare, was developed to facilitate microbial-community comparison based on 16S rRNA gene sequence libraries. It combines the RDP Classifier with a statistical test to flag taxa differentially represented between samples. The RDP Classifier and RDP Library Compare are available online at http://rdp.cme.msu.edu/.
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            Ror2 signaling regulates Golgi structure and transport through IFT20 for tumor invasiveness

            Signaling through the Ror2 receptor tyrosine kinase promotes invadopodia formation for tumor invasion. Here, we identify intraflagellar transport 20 (IFT20) as a new target of this signaling in tumors that lack primary cilia, and find that IFT20 mediates the ability of Ror2 signaling to induce the invasiveness of these tumors. We also find that IFT20 regulates the nucleation of Golgi-derived microtubules by affecting the GM130-AKAP450 complex, which promotes Golgi ribbon formation in achieving polarized secretion for cell migration and invasion. Furthermore, IFT20 promotes the efficiency of transport through the Golgi complex. These findings shed new insights into how Ror2 signaling promotes tumor invasiveness, and also advance the understanding of how Golgi structure and transport can be regulated.
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              Introducing mothur: open-source, platform-independent, community-supported software for describing and comparing microbial communities.

              mothur aims to be a comprehensive software package that allows users to use a single piece of software to analyze community sequence data. It builds upon previous tools to provide a flexible and powerful software package for analyzing sequencing data. As a case study, we used mothur to trim, screen, and align sequences; calculate distances; assign sequences to operational taxonomic units; and describe the alpha and beta diversity of eight marine samples previously characterized by pyrosequencing of 16S rRNA gene fragments. This analysis of more than 222,000 sequences was completed in less than 2 h with a laptop computer.
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                Author and article information

                Contributors
                520-820-7186 , kirk.anderson@ars.usda.gov
                Vincent.Ricigliano@ars.usda.gov
                Brendon.Mott@ars.usda.gov
                Duan.Copeland@ars.usda.gov
                Amy.Floyd@ars.usda.gov
                pmaes@email.arizona.edu
                Journal
                Microbiome
                Microbiome
                Microbiome
                BioMed Central (London )
                2049-2618
                18 June 2018
                18 June 2018
                2018
                : 6
                : 108
                Affiliations
                [1 ]ISNI 0000 0004 0404 0958, GRID grid.463419.d, USDA-ARS Carl Hayden Bee Research Center, ; 2000 E. Allen Rd, Tucson, AZ 85719 USA
                [2 ]ISNI 0000 0001 2168 186X, GRID grid.134563.6, Department of Microbiology, School of Animal & Comparative Biomedical Sciences, , University of Arizona, ; Tucson, AZ 85721 USA
                [3 ]ISNI 0000 0001 2168 186X, GRID grid.134563.6, Department of Entomology and Center for Insect Science, , University of Arizona, ; Tucson, AZ 85721 USA
                Article
                489
                10.1186/s40168-018-0489-1
                6006926
                29914555
                2bd7bd84-9983-493e-b430-226f70c8e2e1
                © The Author(s). 2018

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided 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 Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 22 March 2018
                : 29 May 2018
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/100007917, Agricultural Research Service;
                Award ID: 501-2022-050 017
                Award Recipient :
                Categories
                Research
                Custom metadata
                © The Author(s) 2018

                honey bees,acetobacteracaeae,bifidobacterium,parasaccharibacter apium,lactobacillus kunkeei,ileum,aging,core microbiota,bacteria,oxidative stress

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