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We sought to characterize and assess differences in compositions of intestinal flora between patients with rheumatoid arthritis (RA) and their respective spouses. Eighty volunteers were recruited, including 30 pairs of RA patients and their spouses, and 20 healthy individuals. Fresh stool samples were collected, processed, and 16S rRNA-sequencing was performed. Data were analyzed using an operational taxonomic units-based method, and community structure assessments were performed. Community composition analysis indicated that there were similar intestinal microbiota structures in RA and in their respective spouses. Gut microbiota in spouses of RA were different from those of the healthy controls group, but these differences were not significant. We found that Blautia spp. and Streptococcus spp. were two most associated species in RA and these taxa were significantly higher in comparison to healthy controls. In contrast, our findings suggested that Roseburia spp. and Lachnoclostridium spp. were significantly lower in the RA in comparison to healthy controls. In conclusion, RA patients shared similar gut microbiota pattern with their spouses which were different from healthy individuals. The findings suggest that disturbance of the balance of gut microbiota may play an important role in the dynamics of pathogenesis of RA.
Pubmed ID: 33681234
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Repository of raw sequencing data from next generation of sequencing platforms including including Roche 454 GS System, Illumina Genome Analyzer, Applied Biosystems SOLiD System, Helicos Heliscope, Complete Genomics, and Pacific Biosciences SMRT. In addition to raw sequence data, SRA now stores alignment information in form of read placements on reference sequence. Data submissions are welcome. Archive of high throughput sequencing data,part of international partnership of archives (INSDC) at NCBI, European Bioinformatics Institute and DNA Database of Japan. Data submitted to any of this three organizations are shared among them.
View all literature mentionsAn Operational Taxonomic Unit (OTU) clustering software for 16S and other marker genes. Highly accurate OTU sequences and improved diversity measures.
View all literature mentionsA database which provides ribosome related data services to the scientific community, including online data analysis, rRNA derived phylogenetic trees, and aligned and annotated rRNA sequences. It specifically contains information on quality-controlled, aligned and annotated bacterial and archaean 16S rRNA sequences, fungal 28S rRNA sequences, and a suite of analysis tools for the scientific community. Most of the RDP tools are now available as open source packages for users to incorporate in their local workflow.
View all literature mentionsAn algorithm for detecting chimeric sequences.
View all literature mentionsSoftware Java pipeline for trimming tasks for Illumina paired end and single ended data. Flexible Trimmer for Illumina Sequence Data. Pair aware preprocessing tool optimized for Illumina next generation sequencing data. Includes several processing steps for read trimming and filtering. Operating systems Unix/Linux, Mac OS, Windows.
View all literature mentionsAn open-source software package for describing and comparing microbial communities. It incorporates the functionality of a number of computational tools, calculators, and visualization tools.
View all literature mentionsTHIS RESOURCE IS NO LONGER IN SERVICE. Documented on February 28,2023. Algorithm for high-dimensional biomarker discovery and explanation that identifies genes, pathways, or taxa characterizing the differences between two or more biological conditions. The algorithm identifies features that are statistically different among biological classes, then performs additional tests to assess whether these differences are consistent with respect to expected biological behavior. Statistical significance and biological relevance are emphasized.
View all literature mentionsSource code that infers approximately-maximum-likelihood phylogenetic trees from alignments of nucleotide or protein sequences. It uses the Jukes-Cantor or generalized time-reversible (GTR) models of nucleotide evolution and the JTT, WAG, or LG models of amino acid evolution.
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