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Gut microbiota has been demonstrated to be involved in intestinal nutrition, defense, and immunity, as well as participating in disease progression. This study was to investigate gut microbiota changes in chickens challenged with netB-positive Clostridium perfringens strain (CP1) and/or the predisposing Eimeria species (Eimeria) and fed diets with fishmeal supplementation. In addition, the effects of lauric acid, a medium-chain fatty acid (MCFA), on necrotic enteritis (NE) reduction and modulation of microbiota were evaluated. The results demonstrated that microbial communities in the jejunum were distinct from those in the cecum, and the microbial community change was more significant in jejunum. Challenge of CP1 in conjunction with Eimeria significantly reduced species diversity in jejunal microbiota, but cecal microbiota remained stable. In the jejunum, CP1 challenge increased the abundance of the genera of Clostridium sensu stricto 1, Escherichia Shigella, and Weissella, but significantly decreased the population of Lactobacillus. Eimeria infection on its own was unable to promote NE, demonstrating decrements of Clostridium sensu stricto 1 and Lactobacillus. Co-infection with CP1 and Eimeria reproduced the majority of NE lesions with significant increment of Clostridium sensu stricto 1 and reduction in Lactobacillus. The advance of changes on these two taxa increased the severity of NE lesions. Further analyses of metagenomeSeq, STAMP, and LEfSe consistently showed significant overgrowth of Clostridium sensu stricto 1 was associated with NE. The supplementation of lauric acid did not reduce NE incidence and severity but decreased the relative abundance of Escherichia Shigella. In conclusion, significant overgrowth of C. perfringens as well as other Clostridium species in Clostridium sensu stricto 1 with the decrement of Lactobacillus in the jejunum is the featured microbiota correlated with NE. Controlling proliferation of Clostridium sensu stricto 1 and manipulation of Lactobacillus in the jejunum should be the strategy to prevent NE.
Pubmed ID: 31150394
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Software environment and programming language for statistical computing and graphics. R is integrated suite of software facilities for data manipulation, calculation and graphical display. Can be extended via packages. Some packages are supplied with the R distribution and more are available through CRAN family.It compiles and runs on wide variety of UNIX platforms, Windows and MacOS.
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 mentionsHigh quality ribosomal RNA databases providing comprehensive, quality checked and regularly updated datasets of aligned small (16S/18S, SSU) and large subunit (23S/28S, LSU) ribosomal RNA (rRNA) sequences for all three domains of life (Bacteria, Archaea and Eukarya). Supplementary services include a rRNA gene aligner, online tools for probe and primer evaluation and optimized browsing, searching and downloading on the website. 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. Alignment tool, SINA, is available for download as well as available for use online.
View all literature mentionsCommercial vendor and service provider of laboratory reagents and antibodies. Supplier of scientific instrumentation, reagents and consumables, and software services.
View all literature mentionsAmerican chemical, life science and biotechnology company owned by Merck KGaA. Merger of Sigma Chemical Company and Aldrich Chemical Company. Provides organic and inorganic chemicals, building blocks, reagents, advanced materials and stable isotopes for chemical synthesis, medicinal chemistry and materials science, antibiotics, buffers, carbohydrates, enzymes, forensic tools, hematology and histology, nucleotides, proteins, peptides, amino acids and their derivatives.
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 mentionsSoftware R package to determine features that are differentially abundant between two or more groups of multiple samples. Used to address the effects of both normalization and under-sampling of microbial communities on disease association detection and testing of feature correlations.
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