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      Gastric Microbiota in Helicobacter pylori-Negative and -Positive Gastritis Among High Incidence of Gastric Cancer Area

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          Abstract

          Helicobacter pylori ( H. pylori) related chronic gastritis is a well-known major etiological factor for gastric cancer development. However, H. pylori-negative gastritis (HpN) is not well described. We aimed to examine gastric mucosal microbiota in HpN compared to H. pylori-positive gastritis (HpP) and H. pylori-negative non-gastritis group (control). Here, we studied 11 subjects with HpN, 40 with HpP and 24 controls. We performed endoscopy with six gastric biopsies. Comparison groups were defined based on strict histological criteria for the disease and H. pylori diagnosis. We used 16S rRNA gene amplicon sequencing to profile the gastric microbiota according to comparison groups. These results demonstrate that the HpP group had significantly lower bacterial richness by the operational taxonomic unit (OTU) counts, and Shannon and Simpson indices as compared to HpN or controls. The linear discriminant analysis effect size analysis showed the enrichment of Firmicutes, Fusobacteria, Bacteroidetes and Actinobacteria at phylum level in the HpN group. In the age-adjusted multivariate analysis, Streptococcus sp. and Haemophilus parainfluenzae were at a significantly increased risk for HpN (odds ratio 18.9 and 12.3, respectively) based on abundance. Treponema sp. was uniquely found in HpN based on occurrence. In this paper, we conclude that Streptococcus sp., Haemophilus parainfluenzae and Treponema sp. are candidate pathogenic bacterial species for HpN. These results if confirmed may have important clinical implications.

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          Short-Term Antibiotic Treatment Has Differing Long-Term Impacts on the Human Throat and Gut Microbiome

          Antibiotic administration is the standard treatment for the bacterium Helicobacter pylori, the main causative agent of peptic ulcer disease and gastric cancer. However, the long-term consequences of this treatment on the human indigenous microbiota are relatively unexplored. Here we studied short- and long-term effects of clarithromycin and metronidazole treatment, a commonly used therapy regimen against H. pylori, on the indigenous microbiota in the throat and in the lower intestine. The bacterial compositions in samples collected over a four-year period were monitored by analyzing the 16S rRNA gene using 454-based pyrosequencing and terminal-restriction fragment length polymorphism (T-RFLP). While the microbial communities of untreated control subjects were relatively stable over time, dramatic shifts were observed one week after antibiotic treatment with reduced bacterial diversity in all treated subjects in both locations. While the microbiota of the different subjects responded uniquely to the antibiotic treatment some general trends could be observed; such as a dramatic decline in Actinobacteria in both throat and feces immediately after treatment. Although the diversity of the microbiota subsequently recovered to resemble the pre treatment states, the microbiota remained perturbed in some cases for up to four years post treatment. In addition, four years after treatment high levels of the macrolide resistance gene erm(B) were found, indicating that antibiotic resistance, once selected for, can persist for longer periods of time than previously recognized. This highlights the importance of a restrictive antibiotic usage in order to prevent subsequent treatment failure and potential spread of antibiotic resistance.
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            Calypso: a user-friendly web-server for mining and visualizing microbiome–environment interactions

            Abstract Calypso is an easy-to-use online software suite that allows non-expert users to mine, interpret and compare taxonomic information from metagenomic or 16S rDNA datasets. Calypso has a focus on multivariate statistical approaches that can identify complex environment-microbiome associations. The software enables quantitative visualizations, statistical testing, multivariate analysis, supervised learning, factor analysis, multivariable regression, network analysis and diversity estimates. Comprehensive help pages, tutorials and videos are provided via a wiki page. Availability and Implementation: The web-interface is accessible via http://cgenome.net/calypso/. The software is programmed in Java, PERL and R and the source code is available from Zenodo (https://zenodo.org/record/50931). The software is freely available for non-commercial users. Contact: l.krause@uq.edu.au Supplementary information: Supplementary data are available at Bioinformatics online.
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              Stomach microbiota composition varies between patients with non-atrophic gastritis and patients with intestinal type of gastric cancer

              We aimed to characterize microbiota of the gastric mucosa as it progress to intestinal type of cancer. Study included five patients each of non-atrophic gastritis (NAG), intestinal metaplasia (IM) and intestinal-type gastric cancer (GC). Gastric tissue was obtained and DNA extracted for microbiota analyses using the microarray G3 PhyloChip. Bacterial diversity ranged from 8 to 57, and steadily decreased from NAG to IM to GC (p = 0.004). A significant microbiota difference was observed between NAG and GC based on Unifrac-presence/absence and weighted-Unifrac-abundance metrics of 283 taxa (p < 0.05). HC-AN analyses based on presence/absence of 238 taxa revealed that GC and NAG grouped apart, whereas IM overlapped with both. An ordinated analyses based on weighted-Unifrac distance given abundance of 44 taxa showing significance across categories revealed significant microbiota separation between NAG and GC. This study is the first to show a gradual shift in gastric microbiota profile from NAG to IM to GC.
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                Author and article information

                Journal
                Cancers (Basel)
                Cancers (Basel)
                cancers
                Cancers
                MDPI
                2072-6694
                10 April 2019
                April 2019
                : 11
                : 4
                : 504
                Affiliations
                [1 ]Department of Environmental and Preventive Medicine, Oita University Faculty of Medicine, 1-1 Idaigaoka, Hasama-machi, Yufu-City, Oita 879-5593, Japan; medication_bg@ 123456yahoo.com (B.G.); tmatsumoto9@ 123456oita-u.ac.jp (T.M.); azzaya2000@ 123456gmail.com (D.A.)
                [2 ]Department of Internal Medicine, Gastroenterology Unit, Mongolian National University of Medical Sciences, Zorig Street, Ulaanbaatar-14210, Mongolia; oyuntsetseg.kh@ 123456mnums.edu.mn
                [3 ]Department of Medicine, Gastroenterology and Hepatology Section, Baylor College of Medicine, 7200 Cambridge Street, Houston, TX 77030, USA; hasheme@ 123456bcm.edu
                [4 ]Alkek Center for Metagenomics and Microbiome Research, Department of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, TX 77030, USA; nadimajami@ 123456gmail.com
                [5 ]Department of Molecular Pathology, Oita University Faculty of Medicine, 1-1 Idaigaoka, Hasama-machi, Yufu-City, Oita 879-5593, Japan; tomohisa@ 123456oita-u.ac.jp
                [6 ]Global Oita Medical Advanced Research Center for Health, 1-1 Idaigaoka, Hasama-machi, Yufu-City, Oita 879-5593, Japan
                Author notes
                [* ]Correspondence: yyamaoka@ 123456oita-u.ac.jp ; Tel.: +81-97-586-5740; Fax: +81-97-586-5749
                Author information
                https://orcid.org/0000-0002-6899-1686
                https://orcid.org/0000-0002-1222-5819
                Article
                cancers-11-00504
                10.3390/cancers11040504
                6520852
                30974798
                0edc35e8-2ac7-4945-a22d-4534d99b6309
                © 2019 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 09 March 2019
                : 04 April 2019
                Categories
                Article

                helicobacter pylori,non-helicobacter pylori,gastritis,microbiota,16s rrna

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