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A growing body of evidence suggests that probiotic functionality is not accurately predicted by their taxonomy. Here, we have set up a study to investigate the effectiveness of two probiotic formulations containing a blend of seven bacterial species in modulating intestinal inflammation in two rodent models of colitis, induced by treating mice with 2,4,6-Trinitrobenzenesulfonic acid (TNBS) or dextran sodium sulfate (DSS). Despite the taxonomy of the bacterial species in the two probiotic formulations being similar, only one preparation (Blend 2-Vivomixx) effectively attenuated the development of colitis in both models. In the TNBS model of colitis, Blend 2 reduced the expression of pro-inflammatory genes while increasing the production of anti-inflammatory cytokines, promoting the expansion M2 macrophages and the formation of IL-10-producing Treg cells in the colon's lamina propria. In the DSS model of colitis, disease attenuation and Treg formation was observed only in mice administered with Blend 2, and this effect was associated with intestinal microbiota remodeling and increased formation of lactate, butyrate, and propionate. None of these effects were observed in mice administered with Blend 1 (VSL#3). In summary, we have shown that two probiotic mixtures obtained by combining taxonomically similar species produced with different manufacturing methods exert divergent effects in mouse models of colitis.
Pubmed ID: 30717413
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Tool used to design PCR primers from DNA sequence - often in high-throughput genomics applications. It does everything from mispriming libraries to sequence quality data to the generation of internal oligos.
View all literature mentionsTHIS RESOURCE IS NO LONGER IN SERVICE. Documented on May 5,2022.Tool that predicts interactions between transcription factors and their regulated genes from binding motifs. Understanding vertebrate development requires unraveling the cis-regulatory architecture of gene regulation. PRISM provides accurate genome-wide computational predictions of transcription factor binding sites for the human and mouse genomes, and integrates the predictions with GREAT to provide functional biological context. Together, accurate computational binding site prediction and GREAT produce for each transcription factor: 1. putative binding sites, 2. putative target genes, 3. putative biological roles of the transcription factor, and 4. putative cis-regulatory elements through which the factor regulates each target in each functional role.
View all literature mentionsTHIS RESOURCE IS NO LONGER IN SERVICE. Documented on February 23,2023.Software package for comparison and analysis of microbial communities, primarily based on high-throughput amplicon sequencing data, but also supporting analysis of other types of data. QIMME analyzes and transforms raw sequencing data generated on Illumina or other platforms to publication quality graphics and statistics.
View all literature mentionsSoftware for single-cell flow cytometry analysis. Its functions include management, display, manipulation, analysis and publication of the data stream produced by flow and mass cytometers.
View all literature mentionslaboratory mouse with name BALB/cAnNCrl from MGI.
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