Flux balance analysis predicts Warburg-like effects of mouse hepatocyte deficient in miR-122a.
Hua-Qing WuMei-Ling ChengJin-Mei LaiHsuan-Hui WuMeng-Chun ChenWen-Huan LiuWu-Hsiung WuPeter Mu-Hsin ChangChi-Ying F HuangAnn-Ping TsouMing-Shi ShiaoFeng-Sheng WangPublished in: PLoS computational biology (2017)
The liver is a vital organ involving in various major metabolic functions in human body. MicroRNA-122 (miR-122) plays an important role in the regulation of liver metabolism, but its intrinsic physiological functions require further clarification. This study integrated the genome-scale metabolic model of hepatocytes and mouse experimental data with germline deletion of Mir122a (Mir122a-/-) to infer Warburg-like effects. Elevated expression of MiR-122a target genes in Mir122a-/-mice, especially those encoding for metabolic enzymes, was applied to analyze the flux distributions of the genome-scale metabolic model in normal and deficient states. By definition of the similarity ratio, we compared the flux fold change of the genome-scale metabolic model computational results and metabolomic profiling data measured through a liquid-chromatography with mass spectrometer, respectively, for hepatocytes of 2-month-old mice in normal and deficient states. The Ddc gene demonstrated the highest similarity ratio of 95% to the biological hypothesis of the Warburg effect, and similarity of 75% to the experimental observation. We also used 2, 6, and 11 months of mir-122 knockout mice liver cell to examined the expression pattern of DDC in the knockout mice livers to show upregulated profiles of DDC from the data. Furthermore, through a bioinformatics (LINCS program) prediction, BTK inhibitors and withaferin A could downregulate DDC expression, suggesting that such drugs could potentially alter the early events of metabolomics of liver cancer cells.
Keyphrases
- long non coding rna
- cell proliferation
- poor prognosis
- long noncoding rna
- genome wide
- mass spectrometry
- electronic health record
- endothelial cells
- type diabetes
- big data
- single cell
- machine learning
- liquid chromatography
- stem cells
- tyrosine kinase
- insulin resistance
- adipose tissue
- high resolution
- metabolic syndrome
- dna methylation
- transcription factor
- quality improvement
- high resolution mass spectrometry