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      Fecal microbiota transplantation ameliorates atherosclerosis in mice with C1q/TNF-related protein 9 genetic deficiency

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          Abstract

          Despite the strong influence of the gut microbiota on atherosclerosis, a causal relationship between atherosclerosis pathophysiology and gut microbiota is still unverified. This study was performed to determine the impact of the gut microbiota on the pathogenesis of atherosclerosis caused by genetic deficiency. To elucidate the influence of the gut microbiota on atherosclerosis pathogenesis, an atherosclerosis-prone mouse model (C1q/TNF-related protein 9-knockout (CTRP9-KO) mice) was generated. The gut microbial compositions of CTRP9-KO and WT control mice were compared. Fecal microbiota transplantation (FMT) was performed to confirm the association between gut microbial composition and the progression of atherosclerosis. FMT largely affected the gut microbiota in both CTRP9-KO and WT mice, and all transplanted mice acquired the gut microbiotas of the donor mice. Atherosclerotic lesions in the carotid arteries were decreased in transplanted CTRP9-KO mice compared to CTRP9-KO mice prior to transplantation. Conversely, WT mice transplanted with the gut microbiotas of CTRP9-KO mice showed the opposite effect as that of CTRP9-KO mice transplanted with the gut microbiotas of WT mice. Here, we show that CTRP9 gene deficiency is related to the distribution of the gut microbiota in subjects with atherosclerosis. Transplantation of WT microbiotas into CTRP9-KO mice protected against the progression of atherosclerosis. Conversely, the transplantation of CTRP9-KO microbiotas into WT mice promoted the progression of atherosclerosis. Treating atherosclerosis by restoring gut microbial homeostasis may be an effective therapeutic strategy.

          Atherosclerosis: A role for gut microbes

          Transplanting fecal matter into the guts of mice used as a model of atherosclerosis suggests a role for gut microbes in causing, preventing and potentially treating this serious condition. Atherosclerosis is the build-up of fatty deposits in artery walls, often called hardening of the arteries. Eun Sil Kim and colleagues at Asan Medical Center, University of Ulsan College of Medicine in Seoul, South Korea, analyzed the gut microbes of mice that had been genetically altered to develop atherosclerosis. The gut microbial populations of the mice with atherosclerosis were significantly different from those of normal mice used as controls. Fecal transplantation from control mice into atherosclerotic mice halted the progression of atherosclerosis, with transplantation in the opposite direction promoting atherosclerosis. Macrophage cells of the immune system seem to be involved in the protective effect of beneficial gut microbes.

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          The SILVA ribosomal RNA gene database project: improved data processing and web-based tools

          SILVA (from Latin silva, forest, http://www.arb-silva.de) is a comprehensive web resource for up to date, quality-controlled databases of aligned ribosomal RNA (rRNA) gene sequences from the Bacteria, Archaea and Eukaryota domains and supplementary online services. The referred database release 111 (July 2012) contains 3 194 778 small subunit and 288 717 large subunit rRNA gene sequences. Since the initial description of the project, substantial new features have been introduced, including advanced quality control procedures, an improved rRNA gene aligner, online tools for probe and primer evaluation and optimized browsing, searching and downloading on the website. Furthermore, the extensively curated SILVA taxonomy and the new non-redundant SILVA datasets provide an ideal reference for high-throughput classification of data from next-generation sequencing approaches.
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            QIIME allows analysis of high-throughput community sequencing data.

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              VSEARCH: a versatile open source tool for metagenomics

              Background VSEARCH is an open source and free of charge multithreaded 64-bit tool for processing and preparing metagenomics, genomics and population genomics nucleotide sequence data. It is designed as an alternative to the widely used USEARCH tool (Edgar, 2010) for which the source code is not publicly available, algorithm details are only rudimentarily described, and only a memory-confined 32-bit version is freely available for academic use. Methods When searching nucleotide sequences, VSEARCH uses a fast heuristic based on words shared by the query and target sequences in order to quickly identify similar sequences, a similar strategy is probably used in USEARCH. VSEARCH then performs optimal global sequence alignment of the query against potential target sequences, using full dynamic programming instead of the seed-and-extend heuristic used by USEARCH. Pairwise alignments are computed in parallel using vectorisation and multiple threads. Results VSEARCH includes most commands for analysing nucleotide sequences available in USEARCH version 7 and several of those available in USEARCH version 8, including searching (exact or based on global alignment), clustering by similarity (using length pre-sorting, abundance pre-sorting or a user-defined order), chimera detection (reference-based or de novo), dereplication (full length or prefix), pairwise alignment, reverse complementation, sorting, and subsampling. VSEARCH also includes commands for FASTQ file processing, i.e., format detection, filtering, read quality statistics, and merging of paired reads. Furthermore, VSEARCH extends functionality with several new commands and improvements, including shuffling, rereplication, masking of low-complexity sequences with the well-known DUST algorithm, a choice among different similarity definitions, and FASTQ file format conversion. VSEARCH is here shown to be more accurate than USEARCH when performing searching, clustering, chimera detection and subsampling, while on a par with USEARCH for paired-ends read merging. VSEARCH is slower than USEARCH when performing clustering and chimera detection, but significantly faster when performing paired-end reads merging and dereplication. VSEARCH is available at https://github.com/torognes/vsearch under either the BSD 2-clause license or the GNU General Public License version 3.0. Discussion VSEARCH has been shown to be a fast, accurate and full-fledged alternative to USEARCH. A free and open-source versatile tool for sequence analysis is now available to the metagenomics community.
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                Author and article information

                Contributors
                tbkim@amc.seoul.kr
                jyjeong@amc.seoul.kr
                chhoonha@amc.seoul.kr
                Journal
                Exp Mol Med
                Exp Mol Med
                Experimental & Molecular Medicine
                Nature Publishing Group UK (London )
                1226-3613
                2092-6413
                3 February 2022
                3 February 2022
                February 2022
                : 54
                : 2
                : 103-114
                Affiliations
                [1 ]GRID grid.267370.7, ISNI 0000 0004 0533 4667, Department of Convergence Medicine and Asan Institute for Life Sciences, Asan Medical Center, , University of Ulsan College of Medicine, ; Seoul, Republic of Korea
                [2 ]GRID grid.413967.e, ISNI 0000 0001 0842 2126, ConveRgence mEDIcine research cenTer (CREDIT), Asan Institute for Life Sciences, Asan Medical Center, ; Seoul, Republic of Korea
                [3 ]GRID grid.267370.7, ISNI 0000 0004 0533 4667, Department of Internal Medicine, Asan Medical Center, , University of Ulsan College of Medicine, ; Seoul, Republic of Korea
                [4 ]GRID grid.267370.7, ISNI 0000 0004 0533 4667, Department of Allergy and Clinical Immunology, Asan Medical Center, , University of Ulsan College of Medicine, ; Seoul, Republic of Korea
                [5 ]GRID grid.267370.7, ISNI 0000 0004 0533 4667, Digestive Diseases Research Center, , University of Ulsan College of Medicine, ; Seoul, Republic of Korea
                Author information
                http://orcid.org/0000-0002-6578-3099
                http://orcid.org/0000-0001-7606-4340
                Article
                728
                10.1038/s12276-022-00728-w
                8894390
                35115674
                cd8a8564-f2f6-4453-9029-4c3167b3c785
                © The Author(s) 2022

                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
                : 5 June 2021
                : 20 October 2021
                : 28 October 2021
                Funding
                Funded by: FundRef https://doi.org/10.13039/501100003725, National Research Foundation of Korea (NRF);
                Award ID: 2020R1I1A2072110
                Award ID: 2021R1A6A1A03040260
                Award Recipient :
                Categories
                Article
                Custom metadata
                © The Author(s) 2022

                Molecular medicine
                atherosclerosis,experimental models of disease,mechanisms of disease
                Molecular medicine
                atherosclerosis, experimental models of disease, mechanisms of disease

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