Forum for Science, Industry and Business

Sponsored by:     3M 
Search our Site:


Yeast protein network could provide insights into human obesity


A team of biologists and a mathematician have identified and characterized a network composed of 94 proteins that work together to regulate fat storage in yeast.

"Removal of any one of the proteins results in an increase in cellular fat content, which is analogous to obesity," says study coauthor Bader Al-Anzi, a research scientist at Caltech.

The "fatter" yeast cells that have had SNF4 knocked out. The larger fat droplets are colored green.

Courtesy of Patrick Arpp/Caltech

The findings, detailed in the May issue of the journal PLOS Computational Biology, suggest that yeast could serve as a valuable test organism for studying human obesity.

"Many of the proteins we identified have mammalian counterparts, but detailed examinations of their role in humans has been challenging," says Al-Anzi. "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, Al-Anzi and his research assistant Patrick Arpp 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. Other studies have shown that such "obese" yeast cells grow more slowly than normal, an indication that in yeast as in humans, too much fat accumulation is not a good thing. "A yeast cell that uses most of its energy to synthesize fat that is not needed does so at the expense of other critical functions, and that ultimately slows down its growth and reproduction," Al-Anzi says.

When the team looked at the protein products of the genes, they discovered that those proteins are physically bonded to one another to form an extensive, highly clustered network within the cell.

Such a configuration cannot be generated through a random process, say study coauthors Sherif Gerges, a bioinformatician at Princeton University, and Noah Olsman, a graduate student in Caltech's Division of Engineering and Applied Science, who independently evaluated the details of the network. Both concluded that the network must have formed as the result of evolutionary selection.

In human-scale networks, such as the Internet, power grids, and social networks, the most influential or critical nodes are often, but not always, those that are the most highly connected.

The team wondered whether the fat-storage network exhibits this feature, and, if not, whether some other characteristics of the nodes would determine which ones were most critical. Then, they could ask if removing the genes that encode the most critical nodes would have the largest effect on fat content.

To examine this hypothesis further, Al-Anzi sought out the help of a mathematician familiar with graph theory, the branch of mathematics that considers the structure of nodes connected by edges, or pathways. "When I realized I needed help, I closed my laptop and went across campus to the mathematics department at Caltech," Al-Anzi recalls. "I walked into the only office door that was open at the time, and introduced myself."

The mathematician that Al-Anzi found that day was Christopher Ormerod, a Taussky-Todd Instructor in Mathematics at Caltech. Al-Anzi's data piqued Ormerod's curiosity. "I was especially struck by the fact that connections between the proteins in the network didn't appear to be random," says Ormerod, who is also a coauthor on the study. "I suspected there was something mathematically interesting happening in this network."

With the help of Ormerod, the team created a computer model that suggested the yeast fat network exhibits what is known as the small-world property. This is akin to a social network that contains many different local clusters of people who are linked to each other by mutual acquaintances, so that any person within the cluster can be reached via another person through a small number of steps.

This pattern is also seen in a well-known network model in graph theory, called the Watts-Strogatz model. The model was originally devised to explain the clustering phenomenon often observed in real networks, but had not previously been applied to cellular networks.

Ormerod suggested that graph theory might be used to make predictions that could be experimentally proven. For example, graph theory says that the most important nodes in the network are not necessarily the ones with the most connections, but rather those that have the most high-quality connections. In particular, nodes having many distant or circuitous connections are less important than those with more direct connections to other nodes, and, especially, direct connections to other important nodes. In mathematical jargon, these important nodes are said to have a high "centrality score."

"In network analysis, the centrality of a node serves as an indicator of its importance to the overall network," Ormerod says.

"Our work predicts that changing the proteins with the highest centrality scores will have a bigger effect on network output than average," he adds. And indeed, the researchers 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 use of centrality scores to gauge the relative importance of a protein in a cellular network is a marked departure from how proteins traditionally have been viewed and studied--that is, as lone players, whose characteristics are individually assessed. "It was a very local view of how cells functioned," Al-Anzi says. "Now we're realizing that the majority of proteins are parts of signaling networks that perform specific tasks within the cell."

Moving forward, the researchers think their technique could be applicable to protein networks that control other cellular functions--such as abnormal cell division, which can lead to cancer.

"These kinds of methods might allow researchers to determine which proteins are most important to study in order to understand diseases that arise when these functions are disrupted," says Kai Zinn, a professor of biology at Caltech and the study's senior author. "For example, defects in the control of cell growth and division can lead to cancer, and one might be able to use centrality scores to identify key proteins that regulate these processes. These might be proteins that had been overlooked in the past, and they could represent new targets for drug development."


The paper is entitled "Experimental and Computational Analysis of a Large Protein Network That Controls Fat Storage Reveals the Design Principles of a Signaling Network."

Media Contact

Deborah Williams-Hedges


Deborah Williams-Hedges | EurekAlert!

Further reports about: Network connections genes humans mathematics organism proteins

More articles from Life Sciences:

nachricht First time-lapse footage of cell activity during limb regeneration
25.10.2016 | eLife

nachricht Phenotype at the push of a button
25.10.2016 | Institut für Pflanzenbiochemie

All articles from Life Sciences >>>

The most recent press releases about innovation >>>

Die letzten 5 Focus-News des innovations-reports im Überblick:

Im Focus: Etching Microstructures with Lasers

Ultrafast lasers have introduced new possibilities in engraving ultrafine structures, and scientists are now also investigating how to use them to etch microstructures into thin glass. There are possible applications in analytics (lab on a chip) and especially in electronics and the consumer sector, where great interest has been shown.

This new method was born of a surprising phenomenon: irradiating glass in a particular way with an ultrafast laser has the effect of making the glass up to a...

Im Focus: Light-driven atomic rotations excite magnetic waves

Terahertz excitation of selected crystal vibrations leads to an effective magnetic field that drives coherent spin motion

Controlling functional properties by light is one of the grand goals in modern condensed matter physics and materials science. A new study now demonstrates how...

Im Focus: New 3-D wiring technique brings scalable quantum computers closer to reality

Researchers from the Institute for Quantum Computing (IQC) at the University of Waterloo led the development of a new extensible wiring technique capable of controlling superconducting quantum bits, representing a significant step towards to the realization of a scalable quantum computer.

"The quantum socket is a wiring method that uses three-dimensional wires based on spring-loaded pins to address individual qubits," said Jeremy Béjanin, a PhD...

Im Focus: Scientists develop a semiconductor nanocomposite material that moves in response to light

In a paper in Scientific Reports, a research team at Worcester Polytechnic Institute describes a novel light-activated phenomenon that could become the basis for applications as diverse as microscopic robotic grippers and more efficient solar cells.

A research team at Worcester Polytechnic Institute (WPI) has developed a revolutionary, light-activated semiconductor nanocomposite material that can be used...

Im Focus: Diamonds aren't forever: Sandia, Harvard team create first quantum computer bridge

By forcefully embedding two silicon atoms in a diamond matrix, Sandia researchers have demonstrated for the first time on a single chip all the components needed to create a quantum bridge to link quantum computers together.

"People have already built small quantum computers," says Sandia researcher Ryan Camacho. "Maybe the first useful one won't be a single giant quantum computer...

All Focus news of the innovation-report >>>



Event News

#IC2S2: When Social Science meets Computer Science - GESIS will host the IC2S2 conference 2017

14.10.2016 | Event News

Agricultural Trade Developments and Potentials in Central Asia and the South Caucasus

14.10.2016 | Event News

World Health Summit – Day Three: A Call to Action

12.10.2016 | Event News

Latest News

3-D-printed magnets

26.10.2016 | Power and Electrical Engineering

Advanced analysis of brain structure shape may track progression to Alzheimer's disease

26.10.2016 | Health and Medicine

3-D-printed structures shrink when heated

26.10.2016 | Materials Sciences

More VideoLinks >>>