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      Antibiotic-induced shifts in the mouse gut microbiome and metabolome increase susceptibility to Clostridium difficile infection

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          Abstract

          Antibiotics can have significant and long lasting effects on the gastrointestinal tract microbiota, reducing colonization resistance against pathogens including Clostridium difficile. Here we show that antibiotic treatment induces substantial changes in the gut microbial community and in the metabolome of mice susceptible to C. difficile infection. Levels of secondary bile acids, glucose, free fatty acids, and dipeptides decrease, whereas those of primary bile acids and sugar alcohols increase, reflecting the modified metabolic activity of the altered gut microbiome. In vitro and ex vivo analyses demonstrate that C. difficile can exploit specific metabolites that become more abundant in the mouse gut after antibiotics, including primary bile acid taurocholate for germination, and carbon sources mannitol, fructose, sorbitol, raffinose and stachyose for growth. Our results indicate that antibiotic-mediated alteration of the gut microbiome converts the global metabolic profile to one that favors C. difficile germination and growth.

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          Most cited references28

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          Cluster analysis and display of genome-wide expression patterns.

          A system of cluster analysis for genome-wide expression data from DNA microarray hybridization is described that uses standard statistical algorithms to arrange genes according to similarity in pattern of gene expression. The output is displayed graphically, conveying the clustering and the underlying expression data simultaneously in a form intuitive for biologists. We have found in the budding yeast Saccharomyces cerevisiae that clustering gene expression data groups together efficiently genes of known similar function, and we find a similar tendency in human data. Thus patterns seen in genome-wide expression experiments can be interpreted as indications of the status of cellular processes. Also, coexpression of genes of known function with poorly characterized or novel genes may provide a simple means of gaining leads to the functions of many genes for which information is not available currently.
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            Is Open Access

            Organization of GC/MS and LC/MS metabolomics data into chemical libraries

            Background Metabolomics experiments involve generating and comparing small molecule (metabolite) profiles from complex mixture samples to identify those metabolites that are modulated in altered states (e.g., disease, drug treatment, toxin exposure). One non-targeted metabolomics approach attempts to identify and interrogate all small molecules in a sample using GC or LC separation followed by MS or MSn detection. Analysis of the resulting large, multifaceted data sets to rapidly and accurately identify the metabolites is a challenging task that relies on the availability of chemical libraries of metabolite spectral signatures. A method for analyzing spectrometry data to identify and Qu antify I ndividual C omponents in a S ample, (QUICS), enables generation of chemical library entries from known standards and, importantly, from unknown metabolites present in experimental samples but without a corresponding library entry. This method accounts for all ions in a sample spectrum, performs library matches, and allows review of the data to quality check library entries. The QUICS method identifies ions related to any given metabolite by correlating ion data across the complete set of experimental samples, thus revealing subtle spectral trends that may not be evident when viewing individual samples and are likely to be indicative of the presence of one or more otherwise obscured metabolites. Results LC-MS/MS or GC-MS data from 33 liver samples were analyzed simultaneously which exploited the inherent biological diversity of the samples and the largely non-covariant chemical nature of the metabolites when viewed over multiple samples. Ions were partitioned by both retention time (RT) and covariance which grouped ions from a single common underlying metabolite. This approach benefitted from using mass, time and intensity data in aggregate over the entire sample set to reject outliers and noise thereby producing higher quality chemical identities. The aggregated data was matched to reference chemical libraries to aid in identifying the ion set as a known metabolite or as a new unknown biochemical to be added to the library. Conclusion The QUICS methodology enabled rapid, in-depth evaluation of all possible metabolites (known and unknown) within a set of samples to identify the metabolites and, for those that did not have an entry in the reference library, to create a library entry to identify that metabolite in future studies.
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              Determination of bacterial load by real-time PCR using a broad-range (universal) probe and primers set.

              The design and evaluation of a set of universal primers and probe for the amplification of 16S rDNA from the Domain Bacteria to estimate total bacterial load by real-time PCR is reported. Broad specificity of the universal detection system was confirmed by testing DNA isolated from 34 bacterial species encompassing most of the groups of bacteria outlined in Bergey's Manual of Determinative Bacteriology. However, the nature of the chromosomal DNA used as a standard was critical. A DNA standard representing those bacteria most likely to predominate in a given habitat was important for a more accurate determination of total bacterial load due to variations in 16S rDNA copy number and the effect of generation time of the bacteria on this number, since rapid growth could result in multiple replication forks and hence, in effect, more than one copy of portions of the chromosome. The validity of applying these caveats to estimating bacterial load was confirmed by enumerating the number of bacteria in an artificial sample mixed in vitro and in clinical carious dentine samples. Taking these parameters into account, the number of anaerobic bacteria estimated by the universal probe and primers set in carious dentine was 40-fold greater than the total bacterial load detected by culture methods, demonstrating the utility of real-time PCR in the analysis of this environment.
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                Author and article information

                Journal
                101528555
                37539
                Nat Commun
                Nat Commun
                Nature communications
                2041-1723
                30 January 2014
                2014
                20 July 2014
                : 5
                : 3114
                Affiliations
                [1 ]Department of Internal Medicine, Division of Infectious Diseases, The University of Michigan, Ann Arbor, MI, USA
                [2 ]Department of Internal Medicine, Division of Pulmonary and Critical Care Medicine, The University of Michigan, Ann Arbor, MI, USA
                [3 ]Department of Microbiology and Immunology, The University of Michigan, Ann Arbor, MI, USA
                [4 ]Department of Human Genetics, The University of Michigan, Ann Arbor, MI, USA
                Author notes
                [* ]Correspondence and requests for materials should be addressed to youngvi@ 123456umich.edu
                Article
                NIHMS549895
                10.1038/ncomms4114
                3950275
                24445449
                f6afee92-8d06-4bb8-9d3d-5c264df4dcf6

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