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      Aging progression of human gut microbiota

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          Abstract

          Background

          Human gut microbiota are important for human health and have been regarded as a “forgotten organ”, whose variation is closely linked with various factors, such as host genetics, diet, pathological conditions and external environment. The diversity of human gut microbiota has been correlated with aging, which was characterized by different abundance of bacteria in various age groups. In the literature, most of the previous studies of age-related gut microbiota changes focused on individual species in the gut community with supervised methods. Here, we aimed to examine the underlying aging progression of the human gut microbial community from an unsupervised perspective.

          Results

          We obtained raw 16S rRNA sequencing data of subjects ranging from newborns to centenarians from a previous study, and summarized the data into a relative abundance matrix of genera in all the samples. Without using the age information of samples, we applied an unsupervised algorithm to recapitulate the underlying aging progression of microbial community from hosts in different age groups and identify genera associated to this progression. Literature review of these identified genera indicated that for individuals with advanced ages, some beneficial genera are lost while some genera related with inflammation and cancer increase.

          Conclusions

          The multivariate unsupervised analysis here revealed the existence of a continuous aging progression of human gut microbiota along with the host aging process. The identified genera associated to this aging process are meaningful for designing probiotics to maintain the gut microbiota to resemble a young age, which hopefully will lead to positive impact on human health, especially for individuals in advanced age groups.

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          Most cited references26

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          Extracting a Cellular Hierarchy from High-dimensional Cytometry Data with SPADE

          Multiparametric single-cell analysis is critical for understanding cellular heterogeneity. Despite recent technological advances in single-cell measurements, methods for analyzing high-dimensional single-cell data are often subjective, labor intensive and require prior knowledge of the biological system under investigation. To objectively uncover cellular heterogeneity from single-cell measurements, we present a novel computational approach, Spanning-tree Progression Analysis of Density-normalized Events (SPADE). We applied SPADE to cytometry data of mouse and human bone marrow. In both cases, SPADE organized cells in a hierarchy of related phenotypes that partially recapitulated well-described patterns of hematopoiesis. In addition, SPADE produced a map of intracellular signal activation across the landscape of human hematopoietic development. SPADE revealed a functionally distinct cell population, natural killer (NK) cells, without using any NK-specific parameters. SPADE is a versatile method that facilitates the analysis of cellular heterogeneity, the identification of cell types, and comparison of functional markers in response to perturbations.
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            Bifidobacteria and Their Role as Members of the Human Gut Microbiota

            Members of the genus Bifidobacterium are among the first microbes to colonize the human gastrointestinal tract and are believed to exert positive health benefits on their host. Due to their purported health-promoting properties, bifidobacteria have been incorporated into many functional foods as active ingredients. Bifidobacteria naturally occur in a range of ecological niches that are either directly or indirectly connected to the animal gastrointestinal tract, such as the human oral cavity, the insect gut and sewage. To be able to survive in these particular ecological niches, bifidobacteria must possess specific adaptations to be competitive. Determination of genome sequences has revealed genetic attributes that may explain bifidobacterial ecological fitness, such as metabolic abilities, evasion of the host adaptive immune system and colonization of the host through specific appendages. However, genetic modification is crucial toward fully elucidating the mechanisms by which bifidobacteria exert their adaptive abilities and beneficial properties. In this review we provide an up to date summary of the general features of bifidobacteria, whilst paying particular attention to the metabolic abilities of this species. We also describe methods that have allowed successful genetic manipulation of bifidobacteria.
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              Gut mucosal microbiome across stages of colorectal carcinogenesis

              Gut microbial dysbiosis contributes to the development of colorectal cancer (CRC). Here we catalogue the microbial communities in human gut mucosae at different stages of colorectal tumorigenesis. We analyse the gut mucosal microbiome of 47 paired samples of adenoma and adenoma-adjacent mucosae, 52 paired samples of carcinoma and carcinoma-adjacent mucosae and 61 healthy controls. Probabilistic partitioning of relative abundance profiles reveals that a metacommunity predominated by members of the oral microbiome is primarily associated with CRC. Analysis of paired samples shows differences in community configurations between lesions and the adjacent mucosae. Correlations of bacterial taxa indicate early signs of dysbiosis in adenoma, and co-exclusive relationships are subsequently more common in cancer. We validate these alterations in CRC-associated microbiome by comparison with two previously published data sets. Our results suggest that a taxonomically defined microbial consortium is implicated in the development of CRC.
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                Author and article information

                Contributors
                xucm@gatech.edu
                hqzhu@pku.edu.cn
                peng.qiu@bme.gatech.edu
                Journal
                BMC Microbiol
                BMC Microbiol
                BMC Microbiology
                BioMed Central (London )
                1471-2180
                28 October 2019
                28 October 2019
                2019
                : 19
                : 236
                Affiliations
                [1 ]ISNI 0000 0001 2256 9319, GRID grid.11135.37, Department of Biomedical Engineering, College of Engineering, Peking University, ; Beijing, 100871 China
                [2 ]ISNI 0000 0001 0941 6502, GRID grid.189967.8, Department of Biomedical Engineering, Georgia Institute of Technology and Emory University, ; Atlanta, 30332 USA
                Author information
                http://orcid.org/0000-0003-3256-0734
                Article
                1616
                10.1186/s12866-019-1616-2
                6819604
                31660868
                dbff744c-a3e2-4ef9-b838-69088a47a199
                © The Author(s) 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/), 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 2019
                : 17 October 2019
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2019

                Microbiology & Virology
                human gut microbiota,aging,sample progression discovery,16s rrna sequencing

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