Recent Progress on Fructose Metabolism-Chrebp, Fructolysis, and Polyol Pathway

Excess fructose intake is associated with obesity, fatty liver, tooth decay, cancer, and cardiovascular diseases. Even after the ingestion of fructose, fructose concentration in the portal blood is never high; fructose is further metabolized in the liver, and the blood fructose concentration is 1/100th of the glucose concentration. It was previously thought that fructose was metabolized in the liver and not in the small intestine, but it has been reported that metabolism in the small intestine also plays an important role in fructose metabolism. Glut5 knockout mice exhibit poor fructose absorption. In addition, endogenous fructose production via the polyol pathway has also received attention; gene deletion of aldose reductase (Ar), ketohexokinase (Khk), and triokinase (Tkfc) has been found to prevent the development of fructose-induced liver lipidosis. Carbohydrate response element-binding protein (Chrebp) regulates the expression of Glut5, Khk, aldolase b, and Tkfc. We review fructose metabolism with a focus on the roles of the glucose-activating transcription factor Chrebp, fructolysis, and the polyol pathway.

Correction of gene model annotations improves isoform abundance estimates: the example of ketohexokinase ( Khk)

Next generation sequencing protocols such as RNA-seq have made the genome-wide characterization of the transcriptome a crucial part of many research projects in biology. Analyses of the resulting data provide key information on gene expression and in certain cases on exon or isoform usage. The emergence of transcript quantification software such as Salmon has enabled researchers to efficiently estimate isoform and gene expressions across the genome while tremendously reducing the necessary computational power. Although overall gene expression estimations were shown to be accurate, isoform expression quantifications appear to be a more challenging task. Low expression levels and uneven or insufficient coverage were reported as potential explanations for inconsistent estimates. Here, through the example of the ketohexokinase ( Khk) gene in mouse, we demonstrate that the use of an incorrect gene annotation can also result in erroneous isoform quantification results. Manual correction of the input Khk gene model provided a much more accurate estimation of relative Khk isoform expression when compared to quantitative PCR (qPCR measurements). In particular, removal of an unexpressed retained intron and a proper adjustment of the 5’ and 3’ untranslated regions both had a strong impact on the correction of erroneous estimates. Finally, we observed a better concordance in isoform quantification between datasets and sequencing strategies when relying on the newly generated Khk annotations. These results highlight the importance of accurate gene models and annotations for correct isoform quantification and reassert the need for orthogonal methods of estimation of isoform expression to confirm important findings.