| Literature DB >> 27899923 |
Xiao Wei1, Shan Jiang1, Xiangna Zhao1, Huan Li1, Weishi Lin1, Boxing Li1, Jing Lu1, Yansong Sun1, Jing Yuan1.
Abstract
The gut flora are widely involved in the cometabolism with the host and have evident effects on the metabolic phenotype of host. This study performed a metabolome analysis of the intestinal microbiota specific for liver cirrhosis. The study population included patients with Child-Turcotte-Pugh score of A (AP, n = 5) and B (BP, n = 5), and control subjects (NM, n = 3). Metagenomic DNA from fecal microbiota was extracted followed by metagenomic sequencing through Illumina MiSeq high throughput sequencing of 16S rRNA regions. The detection of metabolites from fecal samples was performed using high-performance liquid phase chromatography and gas chromatography coupled with tandem mass spectrometry. Intestinal microbiota community and metabolite analysis both showed separation of cirrhotic patients from control participants, moreover, the microbiota-metabolite correlations changed in cirrhotic patients. Fecal microbiota from cirrhotic patients, with the reduced diversity, contained a decreased abundance of Bacteroidetes and an increased abundance of Firmicutes and Proteobacteria compared with the normal samples. Analysis of metabolome revealed a remarkable change in the metabolic potential of the microbiota in cirrhotic patients, with specific higher concentrations of amine, unsaturated fatty acid, and short-chain fatty acids, and lower concentrations of sugar alcohol and amino acid, suggesting the initial equilibrium of gut microbiota community and co-metabolism with the host were perturbed by cirrhosis. Our study illustrated the relationship between fecal microbiota composition and metabolome in cirrhotic patients, which may improve the clinical prognosis of cirrhosis.Entities:
Keywords: SCFAs; amino acid; gut microbiota; liver cirrhosis; metabolome
Year: 2016 PMID: 27899923 PMCID: PMC5110571 DOI: 10.3389/fmicb.2016.01856
Source DB: PubMed Journal: Front Microbiol ISSN: 1664-302X Impact factor: 5.640
Characteristics of the study population.
| NM | AP | BP | |||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| NM1 | NM2 | NM3 | AP1 | AP2 | AP3 | AP4 | AP5 | BP1 | BP2 | BP3 | BP4 | BP5 | |
| Sampling time | 5/1/2016 | 7/1/2016 | 5/1/2016 | 5/1/2016 | 5/1/2016 | 7/1/2016 | 7/1/2016 | 7/1/2016 | 7/1/2016 | 7/1/2016 | 7/1/2016 | 7/1/2016 | 5/1/2016 |
| Age (years) | 43 | 51 | 46 | 52 | 54 | 57 | 44 | 49 | 50 | 51 | 46 | 47 | 53 |
| Gender | Female | Male | Female | Male | Male | Male | Male | Female | Female | Male | Male | Male | Male |
| Body mass index (kg/m2) | 24.2 | 19.6 | 19.1 | 24.2 | 23.3 | 24.7 | 23.6 | 20.9 | 22.5 | 23.3 | 20.9 | 19.6 | 23.9 |
| Ascites | – | – | – | 2 | 2 | 1 | 1 | 1 | 2 | 1 | 3 | 2 | 2 |
| Prothrombin time (second) | – | – | – | 13.1 | 12.9 | 12.9 | 13.5 | 10.3 | 11.6 | 12.4 | 12.1 | 14.5 | 12.2 |
| Prothrombin time score | – | – | – | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
| Albumin (g/L) | – | – | – | 31 | 39 | 31 | 35 | 39 | 31 | 42 | 31 | 31 | 40 |
| Albumin score | – | – | – | 2 | 1 | 1 | 1 | 1 | 1 | 1 | 3 | 2 | 1 |
| Tbil (μmol/L) | – | – | – | 20.3 | 19.7 | 21.6 | 29.1 | 18.2 | 17 | 13.4 | 10.3 | 11.2 | 12.9 |
| Tbil score | – | – | – | 1 | 1 | 1 | 1 | 1 | 1 | 3 | 1 | 1 | 1 |
| Child-Turcotte-Pugh score | – | – | – | 6 | 5 | 5 | 5 | 5 | 8 | 8 | 9 | 7 | 7 |