210 research outputs found

    Making It Last: Storage Time and Temperature Have Differential Impacts on Metabolite Profiles of Airway Samples from Cystic Fibrosis Patients.

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    Metabolites of human or microbial origin have the potential to be important biomarkers of the disease state in cystic fibrosis (CF). Clinical sample collection and storage conditions may impact metabolite abundances with clinical relevance. We measured the change in metabolite composition based on untargeted gas chromatography-mass spectrometry (GC-MS) when CF sputum samples were stored at 4°C, -20°C, or -80°C with one or two freeze-thaw cycles. Daily measurements were taken for 1 week and then weekly for 4 weeks (4°C) and 8 weeks (-20°C). The metabolites in samples stored at -20°C maintained abundances similar to those found at-80°C over the course of 8 weeks (average change in Bray-Curtis distance, 0.06 ± 0.04) and were also stable after one or two freeze-thaw cycles. However, the metabolite profiles of samples stored at 4°C shifted after 1 day and continued to change over the course of 4 weeks (average change in Bray-Curtis distance, 0.31 ± 0.12). The abundances of several amino acids and other metabolites increased with time of storage at 4°C but remained constant at -20°C. Storage temperature was a significant factor driving the metabolite composition (permutational multivariate analysis of variance: r2 = 0.32 to 0.49, P < 0.001). CF sputum samples stored at -20°C at the time of sampling maintain a relatively stable untargeted GC-MS profile. Samples should be frozen on the day of collection, as more than 1 day at 4°C impacts the global composition of the metabolites in the sample. IMPORTANCE Metabolomics has great potential for uncovering biomarkers of the disease state in CF and many other contexts. However, sample storage timing and temperature may alter the abundance of clinically relevant metabolites. To assess whether existing samples are stable and to direct future study design, we conducted untargeted GC-MS metabolomic analysis of CF sputum samples after one or two freeze-thaw cycles and storage at 4°C and -20°C for 4 to 8 weeks. Overall, storage at -20°C and freeze-thaw cycles had little impact on metabolite profiles; however, storage at 4°C shifted metabolite abundances significantly. GC-MS profiling will aid in our understanding of the CF lung, but care should be taken in studies using sputum samples to ensure that samples are properly stored

    Siri, What Should I Eat?

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    Zeevi et al. report that extensive monitoring of a human cohort for variations in dietary intake, lifestyle, host phenotype, and the gut microbiome has enabled the development of a machine-learning algorithm that accurately predicts the individual glycemic response to meals, providing an important first step toward personalized nutrition

    Viewing the human microbiome through three-dimensional glasses: integrating structural and functional studies to better define the properties of myriad carbohydrate-active enzymes

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    Metagenomics has unleashed a deluge of sequencing data describing the organismal, genetic, and transcriptional diversity of the human microbiome. To better understand the precise functions of the myriad proteins encoded by the microbiome, including carbohydrate-active enzymes, it will be critical to combine structural studies with functional analyses

    mockrobiota: a Public Resource for Microbiome Bioinformatics Benchmarking.

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    Mock communities are an important tool for validating, optimizing, and comparing bioinformatics methods for microbial community analysis. We present mockrobiota, a public resource for sharing, validating, and documenting mock community data resources, available at http://caporaso-lab.github.io/mockrobiota/. The materials contained in mockrobiota include data set and sample metadata, expected composition data (taxonomy or gene annotations or reference sequences for mock community members), and links to raw data (e.g., raw sequence data) for each mock community data set. mockrobiota does not supply physical sample materials directly, but the data set metadata included for each mock community indicate whether physical sample materials are available. At the time of this writing, mockrobiota contains 11 mock community data sets with known species compositions, including bacterial, archaeal, and eukaryotic mock communities, analyzed by high-throughput marker gene sequencing. IMPORTANCE The availability of standard and public mock community data will facilitate ongoing method optimizations, comparisons across studies that share source data, and greater transparency and access and eliminate redundancy. These are also valuable resources for bioinformatics teaching and training. This dynamic resource is intended to expand and evolve to meet the changing needs of the omics community

    The mind-body-microbial continuum

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    Our understanding of the vast collection of microbes that live on and inside us (microbiota) and their collective genes (microbiome) has been revolutionized by culture-independent “metagenomic” techniques and DNA sequencing technologies. Most of our microbes live in our gut, where they function as a metabolic organ and provide attributes not encoded in our human genome. Metagenomic studies are revealing shared and distinctive features of microbial communities inhabiting different humans. A central question in psychiatry is the relative role of genes and environment in shaping behavior. The human microbiome serves as the interface between our genes and our history of environmental exposures; explorations of our microbiomes thus offer the possibility of providing new insights into our neurodevelopment and our behavioral phenotypes by affecting complex processes such as inter- and intra personal variations in cognition, personality, mood, sleep, and eating behavior, and perhaps even a variety of neuropsychiatric diseases ranging from affective disorders to autism. Better understanding of microbiome-encoded pathways for xenobiotic metabolism also has important implications for improving the efficacy of pharmacologic interventions with neuromodulator agents

    Predicting and Manipulating Cardiac Drug Inactivation by the Human Gut Bacterium Eggerthella lenta

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    Despite numerous examples of the effects of the human gastrointestinal microbiome on drug efficacy and toxicity, there is often an incomplete understanding of the underlying mechanisms. Here, we dissect the inactivation of the cardiac drug digoxin by the gut Actinobacterium Eggerthella lenta. Transcriptional profiling, comparative genomics, and culture-based assays revealed a cytochrome-encoding operon up-regulated by digoxin, inhibited by arginine, absent in nonmetabolizing E. lenta strains, and predictive of digoxin inactivation by the human gut microbiome. Pharmacokinetic studies using gnotobiotic mice revealed that dietary protein reduces the in vivo microbial metabolism of digoxin, with significant changes to drug concentration in the serum and urine. These results emphasize the importance of viewing pharmacology from the perspective of both our human and microbial genomes.Chemistry and Chemical Biolog
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