Unprecedented large-scale quantitative analysis of bacterium provides detailed picture of metabolic network robustness.

Scientists at the Institute for Advanced Biosciences of Keio University located in Tsuruoka City, Japan report in an advanced on-line publication released today in Science Express, a first-of-a-kind quantitative picture of molecular components of the common intestinal bacterium E. coli. The report is due to appear in print in the April 27 issue of Science, a leading journal of original scientific research. Using multiple state-of-the-art analytical technologies, the group studied this unicellular organism at an unprecedented depth to reveal the remarkable overall robustness of its metabolic network to gene deletion and changes in growth conditions.

All cells need to convert energy sources such as simple sugars into ATP, an energy storing and exchange molecule, and other cellular building blocks that are essential for cellular growth and survival. This cellular process, called "energy metabolism" is one of the most fundamental and well-conserved in living cells and its machinery involves about 100 different genes and their encoded proteins.

Making use of a set of nearly 4000 single gene mutants in E. coli the same group previously developed (Keio collection), the researchers selected a subset of specific genes whose activity is known to be associated with the main reactions of central energy metabolism. In addition, the non-mutated or wild type cells were also grown at different rates to observe the response to such changes. An exhaustive global survey of intracellular components was then performed using the latest analytical technologies such as DNA microarrays, two-dimensional gel electrophoresis, and capillary electrophoresis mass spectrometry (CE-MS) to quantify messenger RNAs, proteins, and metabolites. The researchers also performed a more detailed and precise analysis of 85 different intracellular RNAs, 57 proteins, and about 130 metabolites representing most components of energy metabolism and simultaneously derived the metabolic fluxes through most reactions by combining quantitative measurements with a computational model of energy metabolism.

Deletion of energy metabolism genes, in most cases, did not result in large compensatory changes in the level of RNAs, proteins, or metabolites. On the other hand, while significant changes in RNA and protein levels were seen upon changes in growth rate, the overall metabolite levels remained stable. The results thus demonstrate with a level of details until now never achieved, that E. coli can use different and complementary strategies to maintain a stable metabolic state, according to the circumstances, and also compensate for mutations through functional redundancy in its metabolic network.

The CE-MS methods developed at IAB, which allow to analyze hundreds of intracellular metabolites simultaneously together with an original approach for targeted protein quantification using liquid-chromatography mass spectrometry (LC-MS) that bypasses the common but inconvenient use of isotopic labels, were instrumental in providing the level of quantitative detail necessary.

Masaru Tomita, head of the project and institute remarks "I am proud of this extraordinary and unparalleled large-scale study which was in large part made possible by combining original technologies developed at IAB in Tsuruoka with the help of the local government. I also think that the rich and peaceful natural environment where our institute is located contributed to catalyze this large team effort. We now hope to apply the fruits of this study toward medical and environmental problems and also imagine applications in the food industry."

Understanding a simple bacterium in a more systematic way is expected to have repercussions in many other organisms due to the similarities in the core components of metabolic pathways from bacteria to animals and humans. For example, eventual applications in the field of cancer biology for developing novel anti-cancer drugs targeting cellular metabolism and improvements in industrial production of alternative energy sources such as bio-ethanol or environmentally friendly bio-plastics could be imagined. In addition, computational and systems biologists around the world, attempting to understand the cell in its entirety, have long wanted to put their hands on the type of quantitative data this study provides. It is thus a significant step in the emerging field of quantitative biology that is likely to find even broader applications.