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Home | Pregnancy Timeline | News Alerts |News Archive Aug 12, 2013

 

catabolite repression

Catabolite repression directs bacteria to increase their uptake of sugar to counteract the scarcity of sugar in the environment.

Image credit:Nature






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Simple math sheds new light on how to convert glucose

One of the most basic and intensively studied processes in biology—one detailed in textbooks for decades—has gained a new level of understanding, thanks to applying simple math to a problem scientists never before thought could benefit from mathematics.

The scientists who made the discovery, published in the advance online publication of Nature, found that the “catabolite repression” process bacteria use to metabolize energy from glucose—is controlled not just by glucose, as has long been taught—but just as much by nitrogen and sulfur, available to bacteria through their growth medium.

“This is one of the most studied processes in molecular biology; it’s in every textbook,” says Terence Hwa, a professor of physics and biology at UC San Diego, who headed the team of scientists. “We showed that this process doesn’t work the way most people thought it did for the past several decades, and its purpose is different from what had generally been assumed.”

The basic phenomenon is analogous to balancing a diet. To reduce an individual's sugar uptake, common wisdom is to reduce sugar. This strategy backfires in bacteria because this increases their appetite for sugar. Catabolite repression directs bacteria to increase their uptake of sugar to counteract the scarcity of sugar in the environment. However, by working out that catabolite repression works through sensing the difference between the level of sugar and essential nutrients such as nitrogen, it is possible to drastically lower the bacteria’s appetite for sugar by simply rationing the supply of nitrogen.


Hwa and his team arrived at their surprising finding by employing a new approach called “quantitative biology,” in which scientists quantify biological data and discover mathematical patterns, which in turn guide them to develop predictive models of the underlying processes.


“This mode of research, an iterative dialogue between data quantitation and model building, has driven the progress of physics for the past several centuries, starting with Kepler’s discovery of the law of planetary motion,” explains Hwa. “However, it was long thought that biology is so laden with historical accidents which render the application of quantitative deduction intractable.

The significance of the study, according to Hwa, is that it demonstrates that the physicists’ quantitative approach can also effectively probe and explain biological processes, even a classic problem that has been heavily researched.

“Molecular biology gives us a collection of parts and interactions,” says Hwa. “But how do you make sense of those interactions? You need to examine them in their physiological context. Quantitative patterns in physiological responses, together with mathematical analysis, provide important clues that can reveal the functions of molecular components and interactions, and in this case, also pinpoint the existence of previously unknown interactions.”

“It is remarkable that after so many years of studying these cells there are more fascinating things to be discovered by simple experiments and theory,” says Krastan B. Blagoev, a program director in the National Science Foundation’s Division of Physics, which jointly funded the research with the agency’s Molecular and Cellular Biology Division.

Hwa and his team of physicists and biologists at UC San Diego are among the world’s leaders in quantitative biology, which is gaining an upsurge of interest and importance in the life sciences.

According to a recent National Academy of Sciences report, advances in quantitative biology are a necessary ingredient to ensure our nation continues to make future progress in medicine, genetics and other life science disciplines. By quantifying the complex behavior of living organisms, for example, researchers can develop reliable models that could allow them to more accurately predict processes like drug interactions before untested pharmaceuticals are used in human clinical trials. UC San Diego is in the middle of a major expansion in quantitative biology, with plans to hire 15 to 20 faculty members in this new discipline in different departments over a three-year period.

In their study, the UC San Diego scientists collaborated with colleagues at Peking University in China, the University of Marburg in Germany and the Indiana University of School of Medicine—an international research team formed six years ago with the help of a grant from the Human Frontier Science Program, headquartered in Strasbourg, France.


Biologists have long known that when glucose is the primary carbon source for cells, bacteria such as E. coli repress genes that metabolize other kinds of sugars. This catabolite repression effect is controlled by a small molecule known as “cyclic adenosine monophosphate”—or cAMP.

“Previously, it was thought that glucose uptake sets the cAMP level in the cell. But we discovered that in reality, it’s the difference between carbon uptake and the uptake of other essential nutrients such as nitrogen. So the picture now is very different.”

Terence Hwa, professor of physics and biology, UC San Diego


The UC San Diego scientists unraveled this relationship by measuring the level of cAMP and the level of enzymes that break down sugar molecules in bacterial cells against the growth rates of the bacteria, while subjecting these cells to limiting supplies of carbon, nitrogen and other compounds.

Recalls Hwa:“When we plotted our results, our jaws dropped. The levels of the sugar uptake and utilization enzymes lined up remarkably into two crossing lines when plotted with the corresponding growth rates, with the enzyme level increasing upon carbon limitation and decreasing upon nitrogen and sulfur limitation. The enzyme levels followed the simple mathematical rules like a machine.

“From the overall pattern, it is clear that there’s nothing special about glucose,” he adds. “Now we know this process is not about the preference of glucose over other carbon compounds, but rather the fine coordination of carbon uptake in the cell with other minor, but essential nutrient elements such as nitrogen and sulfur.”

Hwa points out that the physiological insights derived from simple math guided them to the strategy molecular mechanisms bacteria use to coordinate carbon metabolism with other elements. Such knowledge could be very valuable to the fermentation industry, where metabolic engineers work to rewire genetic programs of industrial microorganisms to increase their yield of desirable products, such as insulin for biomedical applications and ethanol for bioenergy.

Hwa speculates that by similarly quantifying how human metabolism deals with different types of nutrient limitations, a novel strategy may be designed to combat diseases such as obesity—which involves an imbalance of macronutrients—or even cancer—which requires a full suite of nutrients to fuel its rapid growth.

While quantitative biology papers are often filled with complicated mathematical formulas and involve heavy number crunching by computers, Hwa found the mathematics used in this discovery surprisingly simple.

“We just used line plots,” he says. “Our entire study involves just three linear equations. They’re the kind of things my 10-year-old daughter should be able to do. Quantitative biology doesn’t have to be fancy.”

Like their mathematical approach, Hwa says his team’s experiments were simple enough most of them could have been done 50 years ago. In fact, one prominent scientist was on the right track to discover the same formula nearly 40 years ago.

The Nobel-Prizewinning French scientist Jacques Monod, was the first to study the effects of catabolite repression during World War II. His study led eventually to the birth of molecular biology 20 years later. One of his papers published months after his death in 1976, questioned the standard explanation of catabolite repression—a paper long forgotten until Hwa discussed his team’s results recently with colleagues from France.

“Monod knew that something was not quite right with the standard picture of cyclic AMP,” says Hwa, who was directed to the 1976 paper. “He knew that nitrogen was having an effect on the input and he knew that somehow it was very important.”

Hwa and his team are now applying the same quantitative approaches to measure the response of bacteria to antibiotics, and cell transitions from one state to another.

Hwa: “This quantitative, physiologic approach is really underutilized in biology. Because it’s so easy to manipulate molecules, biologists as well as biophysicists tend to jump immediately to a molecular view, often decoupled from the physiological context.

Certainly the parts list is important, and we could not have gotten to the bottom of our study without all of the molecular work that had been done before. But that in of itself is not enough, because the very same parts can be put to work in different ways to make systems with very different functions.”

Abstract
The cyclic AMP (cAMP)-dependent catabolite repression effect in Escherichia coli is among the most intensely studied regulatory processes in biology. However, the physiological function(s) of cAMP signalling and its molecular triggers remain elusive. Here we use a quantitative physiological approach to show that cAMP signalling tightly coordinates the expression of catabolic proteins with biosynthetic and ribosomal proteins, in accordance with the cellular metabolic needs during exponential growth. The expression of carbon catabolic genes increased linearly with decreasing growth rates upon limitation of carbon influx, but decreased linearly with decreasing growth rate upon limitation of nitrogen or sulphur influx. In contrast, the expression of biosynthetic genes showed the opposite linear growth-rate dependence as the catabolic genes. A coarse-grained mathematical model provides a quantitative framework for understanding and predicting gene expression responses to catabolic and anabolic limitations. A scheme of integral feedback control featuring the inhibition of cAMP signalling by metabolic precursors is proposed and validated. These results reveal a key physiological role of cAMP-dependent catabolite repression: to ensure that proteomic resources are spent on distinct metabolic sectors as needed in different nutrient environments. Our findings underscore the power of quantitative physiology in unravelling the underlying functions of complex molecular signalling networks.

Other authors of the paper were UC San Diego scientists Conghui You, Hiroyuki Okano, Sheng Hui, Zhongge Zhang, Minsu Kim and Carl Gunderson; Yi-Ping Wang of Peking University in China; Peter Lenz of the University of Marburg in Germany; and Dalai Yan of the Indiana University School of Medicine in Indianapolis.

Original press release:http://www.newswise.com/articles/view/606260/?sc=dwh