Bader Al-Anzi, research scientist at Caltech said that removal of any one of the proteins results in an increase in cellular fat content which is analogous to obesity. He added that the obesity research field would benefit greatly if a single-cell model organism such as yeast could be used, one that can be analyzed using easy, fast and affordable methods.
Using genetic tools, the research team screened a collection of about 5,000 different mutant yeast strains and identified 94 genes that, when removed, produced yeast with increases in fat content, as measured by quantitating fat bands on thin-layer chromatography plates.
This pattern is also seen in a well-known network model in graph theory, called the Watts-Strogatz model. The researches claim that their work predicts that changing the proteins with the highest centrality scores will have a bigger effect on network output than average.
They also found that the removal of proteins with the highest predicted centrality scores produced yeast cells with a larger fat band than in yeast whose less-important proteins had been removed.
The researchers also think that their technique could be applicable to protein networks that control other cellular functions such as abnormal cell division, which can lead to cancer. The study is published in journal PLOS Computational Biology.
- » News Central
- » Popular News
- » Latest Health News
- » News Category A-Z (500+)
- » Health News and Press Release
- » News Archive
- » News Photo Gallery
- » Lifestyle and Wellness
- » Health Watch
- » Health In Focus
- » Celebrating Life
- » Breaking Health News
- » News From Other Resources
- » India Special
- » News Video Gallery
- » Medindia Exclusive - Interviews and In depth Reports