Ontology highlight
ABSTRACT:
PROVIDER: PRJEB47889 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| ERR6896740.fastq.gz | Fastqsanger.gz | |||
| ERR6896750.fastq.gz | Fastqsanger.gz | |||
| ERR6896760.fastq.gz | Fastqsanger.gz | |||
| ERR6896770.fastq.gz | Fastqsanger.gz | |||
| ERR6896780.fastq.gz | Fastqsanger.gz |
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Project description:Opioid analgesics are frequently prescribed in the United States and worldwide. However, serious side effects such as addiction, immunosuppression and gastrointestinal symptoms limit long term use. In the current study using a chronic morphine-murine model a longitudinal approach was undertaken to investigate the role of morphine modulation of gut microbiome as a mechanism contributing to the negative consequences associated with opioids use. The results revealed a significant shift in the gut microbiome and metabolome within 24 hours following morphine treatment when compared to placebo. Morphine induced gut microbial dysbiosis exhibited distinct characteristic signatures profiles including significant increase in communities associated with pathogenic function, decrease in communities associated with stress tolerance. Collectively, these results reveal opioids-induced distinct alteration of gut microbiome, may contribute to opioids-induced pathogenesis. Therapeutics directed at these targets may prolong the efficacy long term opioid use with fewer side effects.
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Project description:High-calorie diets lead hepatic steatosis and to the development of non-alcoholic fatty liver disease (NAFLD), which can evolve over many years into the inflammatory form non-alcoholic steatohepatits (NASH) posing a risk for the development of hepatocellular carcinoma (HCC). Due to the diet and the liver alteration, the axis between liver and gut is disturbed, resulting in gut microbiome alterations. Consequently, detecting these gut microbiome alterations repre-sents a promising strategy for early NASH and HCC detection. We analyzed medical parame-ters and the fecal metaproteome of 19 healthy controls, 32 NASH, and 29 HCC patients target-ing the discovery of diagnostic biomarkers. Here, NASH and HCC resulted in increased in-flammation status and shifts within the composition of the gut microbiome. Increased abun-dance of kielin/chordin, E3 ubiquitin ligase, and nucleophosmin 1 represented valuable fecal biomarkers indicating disease-related changes in the liver. Whereas a single biomarker failed to separate NASH and HCC, machine learning-based classification algorithms provided 0.86% accuracy in distinguishing between controls, NASH, and HCC. Conclusion: Fecal metaproteomics enables early detection of NASH and HCC by providing single biomarkers and ma-chine learning-based metaprotein panels.
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