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      Comparative metagenomic analysis of human intervertebral disc nucleus pulposus and cartilaginous end plates

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          Abstract

          Study design

          The diversity of microflora inhabiting endplate (EP) and nucleus pulposus (NP) tissues of human intervertebral disc (IVD) was profiled through NGS-supported 16S rRNA amplicon sequencing. Sixteen EP and their corresponding NP were excised from the brain-dead voluntary organ donors with no clinical history of low back pain, and 12 herniated and 8 degenerated NP tissues isolated from the patients undergoing spinal surgery were subjected to study the alteration in the microbial diversity.

          Objective(s)

          To understand in normal IVD, whether the colonization of bacteria to the NP is through the EP in discs with intact annulus fibrosus. To identify significantly differing microbial population(s) between normal and diseased IVD (NP).

          Background of the study

          There is increasing evidence for subclinical infection by fastidious low, growing bacteria to be a cause of disc degeneration. Although the presence of bacteria in NP has been reported well in literature, the source of bacteria is not clearly proved as the disc is avascular in healthy condition. Documentation of similar bacterial populations in the EP and NP may add proof that bacterial inoculation of NP occurs via the EP.

          Materials and methods

          Sixteen EP and their corresponding NP excised from brain-dead voluntary organ donors with no history of back pain and 20 diseased discs collected from patients undergoing microdiscectomy/fusion surgery were used for profiling microbiome through 16S rRNA amplicon sequencing using primers specific for V1-V9 hypervariable regions. Changes in bacterial diversity and abundance were analysed to identify the key microbial populations in normal IVD NP and EP tissues and those significantly altered in diseased IVD (NP).

          Results

          NP and EP shared a similar spectrum of microbiome but with varying abundance. The five dominant phyla identified were Proteobacteria, Firmicutes, Actinobacteria, OD1, and Bacteroidetes. Proteobacteria was found to be the most abundant phyla in both NP (62%) and EP (53%) of the normal IVD. This was followed by Firmicutes (16%), Actinobacteriota (11%), OD1 (Parcubacteria) (7.6%), and Bacteroidetes (2%) in NP and Firmicutes (23.4%), OD1 (Parcubacteria) (17.6%), Actinobacteriota (2.8%), and Bacteroidetes (2.6%) in EP, respectively . Under diseased conditions, Proteobacteria (68%) was dominant when compared with other phyla. However, there was no significant difference in the abundance of Proteobacteria between the normal and diseased discs. Interestingly, the other dominant phyla such as Firmicutes (Normal-NP: 16.2%; Diseased-NP: 4.02%) and Actinobacteria (Normal-NP: 11%; Diseased-NP: 0.99%) showed a significant reduction in degenerated discs. To understand the key microbial populations that are significantly altered during disease, correlation analysis was performed among the three phyla, which revealed a negative correlation in the ratio of Actinobacteria + Firmicutes vs. Proteobacteria ( p = 0.001) in DD.

          Conclusion

          Results of our study clearly demonstrated a similar bacterial diversity but with varying abundance between the EP and NP, suggesting the existence of the endplate–nucleus pulposus axis in the normal IVD microbiome. Further, our results have indicated that the changes in the abundance of Actinobacteria + Firmicutes vs. Proteobacteria during DDD need further investigation.

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          Most cited references37

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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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              Greengenes, a Chimera-Checked 16S rRNA Gene Database and Workbench Compatible with ARB

              A 16S rRNA gene database ( http://greengenes.lbl.gov ) addresses limitations of public repositories by providing chimera screening, standard alignment, and taxonomic classification using multiple published taxonomies. It was found that there is incongruent taxonomic nomenclature among curators even at the phylum level. Putative chimeras were identified in 3% of environmental sequences and in 0.2% of records derived from isolates. Environmental sequences were classified into 100 phylum-level lineages in the Archaea and Bacteria .

                Author and article information

                Contributors
                Journal
                Front Cardiovasc Med
                Front Cardiovasc Med
                Front. Cardiovasc. Med.
                Frontiers in Cardiovascular Medicine
                Frontiers Media S.A.
                2297-055X
                28 September 2022
                2022
                : 9
                : 927652
                Affiliations
                [1] 1Department of Spine Surgery, Ganga Hospital , Coimbatore, India
                [2] 2Department of Biotechnology, Ganga Research Centre , Coimbatore, India
                [3] 3Department of Plant Biotechnology, Tamil Nadu Agricultural University , Coimbatore, India
                Author notes

                Edited by: Velmurugan Ganesan, KMCH Research Foundation, India

                Reviewed by: Dinakaran Vasudevan, SKAN Medical Research Trust, India; Chaitanya Dende, University of Texas Southwestern Medical Center, United States

                *Correspondence: Rajasekaran Shanmuganathan rajasekaran.orth@ 123456gmail.com

                This article was submitted to Cardiovascular Metabolism, a section of the journal Frontiers in Cardiovascular Medicine

                †ORCID: Rajasekaran Shanmuganathan orcid.org/0000-0001-6043-006X

                Sri Vijay Anand K S orcid.org/0000-0002-8885-5411

                Raveendran Muthurajan orcid.org/0000-0002-8803-7662

                Sharon Miracle Nayagam orcid.org/0000-0002-0812-4468

                Monica Steffi Matchado orcid.org/0000-0002-2058-7924

                Sunmathi Rajendran orcid.org/0000-0002-4239-8104

                Rishi Mugesh Kanna orcid.org/0000-0001-5817-4909

                Ajoy Prasad Shetty orcid.org/0000-0001-5885-7152

                Article
                10.3389/fcvm.2022.927652
                9554234
                36247458
                b3b0bdf8-da9f-4b77-a8a1-41abbaeaab54
                Copyright © 2022 Shanmuganathan, Tangavel, K S, Muthurajan, Nayagam, Matchado, Rajendran, Kanna and Shetty.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 24 April 2022
                : 01 September 2022
                Page count
                Figures: 7, Tables: 2, Equations: 0, References: 37, Pages: 12, Words: 6496
                Categories
                Cardiovascular Medicine
                Original Research

                intervertebral disc,disc degeneration,bacteria,microbiome,endplate,dysbiosis,next-generation sequencing

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