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      ZIP8-Mediated Intestinal Dysbiosis Impairs Pulmonary Host Defense against Bacterial Pneumonia

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          Abstract

          Pneumococcal pneumonia is a leading cause of morbidity and mortality worldwide. An increased susceptibility is due, in part, to compromised immune function. Zinc is required for proper immune function, and an insufficient dietary intake increases the risk of pneumonia. Our group was the first to reveal that the Zn transporter, ZIP8, is required for host defense. Furthermore, the gut microbiota that is essential for lung immunity is adversely impacted by a commonly occurring defective ZIP8 allele in humans. Taken together, we hypothesized that loss of the ZIP8 function would lead to intestinal dysbiosis and impaired host defense against pneumonia. To test this, we utilized a novel myeloid-specific Zip8KO mouse model in our studies. The comparison of the cecal microbial composition of wild-type and Zip8KO mice revealed significant differences in microbial community structure. Most strikingly, upon a S. pneumoniae lung infection, mice recolonized with Zip8KO-derived microbiota exhibited an increase in weight loss, bacterial dissemination, and lung inflammation compared to mice recolonized with WT microbiota. For the first time, we reveal the critical role of myeloid-specific ZIP8 on the maintenance of the gut microbiome structure, and that loss of ZIP8 leads to intestinal dysbiosis and impaired host defense in the lung. Given the high incidence of dietary Zn deficiency and the ZIP8 variant allele in the human population, additional investigation is warranted to improve surveillance and treatment strategies.

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          Most cited references57

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          Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

          In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression. The DESeq2 package is available at http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0550-8) contains supplementary material, which is available to authorized users.
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            DADA2: High resolution sample inference from Illumina amplicon data

            We present DADA2, a software package that models and corrects Illumina-sequenced amplicon errors. DADA2 infers sample sequences exactly, without coarse-graining into OTUs, and resolves differences of as little as one nucleotide. In several mock communities DADA2 identified more real variants and output fewer spurious sequences than other methods. We applied DADA2 to vaginal samples from a cohort of pregnant women, revealing a diversity of previously undetected Lactobacillus crispatus variants.
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              phyloseq: An R Package for Reproducible Interactive Analysis and Graphics of Microbiome Census Data

              Background The analysis of microbial communities through DNA sequencing brings many challenges: the integration of different types of data with methods from ecology, genetics, phylogenetics, multivariate statistics, visualization and testing. With the increased breadth of experimental designs now being pursued, project-specific statistical analyses are often needed, and these analyses are often difficult (or impossible) for peer researchers to independently reproduce. The vast majority of the requisite tools for performing these analyses reproducibly are already implemented in R and its extensions (packages), but with limited support for high throughput microbiome census data. Results Here we describe a software project, phyloseq, dedicated to the object-oriented representation and analysis of microbiome census data in R. It supports importing data from a variety of common formats, as well as many analysis techniques. These include calibration, filtering, subsetting, agglomeration, multi-table comparisons, diversity analysis, parallelized Fast UniFrac, ordination methods, and production of publication-quality graphics; all in a manner that is easy to document, share, and modify. We show how to apply functions from other R packages to phyloseq-represented data, illustrating the availability of a large number of open source analysis techniques. We discuss the use of phyloseq with tools for reproducible research, a practice common in other fields but still rare in the analysis of highly parallel microbiome census data. We have made available all of the materials necessary to completely reproduce the analysis and figures included in this article, an example of best practices for reproducible research. Conclusions The phyloseq project for R is a new open-source software package, freely available on the web from both GitHub and Bioconductor.
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                Author and article information

                Contributors
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                Journal
                IJMCFK
                International Journal of Molecular Sciences
                IJMS
                MDPI AG
                1422-0067
                February 2022
                January 18 2022
                : 23
                : 3
                : 1022
                Article
                10.3390/ijms23031022
                79fe8aa7-6ebd-409e-af23-cdf0eb9e19c5
                © 2022

                https://creativecommons.org/licenses/by/4.0/

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