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      Characteristics of the sputum microbiome in COPD exacerbations and correlations between clinical indices

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          Abstract

          Background

          Chronic obstructive pulmonary disease (COPD) is a prevalent, progressive respiratory disease, and acute exacerbations of COPD (AECOPD) can accelerate the deterioration of the disease. Increasing evidence suggests that airway bacterial dysbiosis is associated with AECOPD. However, the exact relationship between changes in the sputum microbiome during AECOPD and clinical indices remains unclear.

          Methods

          In this study, a total of 76 sputum samples were collected from patients with AECOPD (n = 28), stable COPD (n = 23), recovery (n = 15) and healthy controls (HCs; n = 10). The sputum microbiome profile was analysed by sequencing the V3‑V4 amplicon of the 16S rRNA (ribosomal RNA) gene.

          Results

          The bacterial diversity (Shannon and Simpson’s index) was found to be significantly decreased in the AECOPD and recovery groups when compared to that in the stable COPD and HC groups. The most dominant phylum identified in the sputum samples of AECOPD patients was Proteobacteria, accounting for 30% of the microbiome. Compared to the stable COPD groups, the relative abundances of Firmicutes and Bacteroidetes were decreased, whereas those of Proteobacteria and Actinobacteria were increased in AECOPD patients. Furthermore, discriminative bacteria, such as Haemophilus, were identified as being specific taxa in AECOPD patients. Functional analysis showed that genes involved in membrane transport and signal transduction metabolism were enriched in the AECOPD group. Importantly, the proportions of Veillonella were positively correlated with lung function, and Staphylococcus was positively correlated with inflammatory indices.

          Conclusion

          Our study revealed variations in the sputum microbiome of AECOPD (based on composition and function) in a Chinese cohort and highlighted its correlation to clinical indices. These results indicated that microbial dysbiosis may contribute to disease progression and provide microbial biomarkers for the diagnosis of AECOPD.

          Supplementary Information

          The online version contains supplementary material available at 10.1186/s12967-022-03278-x.

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          Most cited references42

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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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            MUSCLE: multiple sequence alignment with high accuracy and high throughput.

            We describe MUSCLE, a new computer program for creating multiple alignments of protein sequences. Elements of the algorithm include fast distance estimation using kmer counting, progressive alignment using a new profile function we call the log-expectation score, and refinement using tree-dependent restricted partitioning. The speed and accuracy of MUSCLE are compared with T-Coffee, MAFFT and CLUSTALW on four test sets of reference alignments: BAliBASE, SABmark, SMART and a new benchmark, PREFAB. MUSCLE achieves the highest, or joint highest, rank in accuracy on each of these sets. Without refinement, MUSCLE achieves average accuracy statistically indistinguishable from T-Coffee and MAFFT, and is the fastest of the tested methods for large numbers of sequences, aligning 5000 sequences of average length 350 in 7 min on a current desktop computer. The MUSCLE program, source code and PREFAB test data are freely available at http://www.drive5. com/muscle.
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              UPARSE: highly accurate OTU sequences from microbial amplicon reads.

              Amplified marker-gene sequences can be used to understand microbial community structure, but they suffer from a high level of sequencing and amplification artifacts. The UPARSE pipeline reports operational taxonomic unit (OTU) sequences with ≤1% incorrect bases in artificial microbial community tests, compared with >3% incorrect bases commonly reported by other methods. The improved accuracy results in far fewer OTUs, consistently closer to the expected number of species in a community.
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                Author and article information

                Contributors
                hongmeizhao@ibms.pumc.edu.cn
                wangjing@ibms.pumc.edu.cn
                xiaoyipumch@sina.com
                Journal
                J Transl Med
                J Transl Med
                Journal of Translational Medicine
                BioMed Central (London )
                1479-5876
                5 February 2022
                5 February 2022
                2022
                : 20
                : 76
                Affiliations
                [1 ]GRID grid.506261.6, ISNI 0000 0001 0706 7839, Department of Respiratory and Critical Care Medicine, , Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, ; Beijing, 100730 China
                [2 ]GRID grid.506261.6, ISNI 0000 0001 0706 7839, Department of Pathophysiology, State Key Laboratory of Medical Molecular Biology Institute of Basic Medicine, , Chinese Academy of Medical Sciences, School of Basic Medicine, Peking Union Medical College, ; Beijing, 100005 China
                Author information
                http://orcid.org/0000-0001-5315-7771
                Article
                3278
                10.1186/s12967-022-03278-x
                8818176
                35123490
                f79b5db0-ac0c-4302-8160-ab3f9da87253
                © The Author(s) 2022

                Open AccessThis 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/. 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 in a credit line to the data.

                History
                : 28 October 2021
                : 24 January 2022
                Funding
                Funded by: National Key Research and Development Program of China
                Award ID: 2018YFC1315103
                Funded by: National Key Technology R&D Program of China
                Award ID: 2013BAI09B10
                Categories
                Research
                Custom metadata
                © The Author(s) 2022

                Medicine
                chronic obstructive pulmonary disease,16s ribosomal rna gene sequencing,sputum microbiome

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