A time resolved metabolomics study: the influence of different carbon sources during growth and starvation of Bacillus subtilis.

In its natural environment, the soil, the Gram-positive model bacterium Bacillus subtilis frequently encounters nutrient limitation and other stress factors. Efficient adaptation mechanisms are necessary to cope with this wide range of environmental challenges. The ability to utilize diverse carbon sources represents a key adaptation process that allows B. subtilis to thrive in its natural habitat. To gain a comprehensive insight into the metabolism of B. subtilis, global metabolite analyses were performed during growth with glucose alone or glucose with either malate, fumarate or citrate as carbon/energy sources. Furthermore, to achieve a comprehensive coverage of a wide range of chemically different metabolites, complementary GC-MS, LC-MS and (1)H-NMR analyses were applied. This study reveals that the availability of different carbon sources results in different extracellular metabolite profiles whereas a regulated intracellular metabolite equilibrium was observed. In addition, the typical energy-starvation induced activation of the general stress sigma factor σ(B) was only observed upon entry into the stationary phase with glucose or glucose and malate as carbon sources.

Methodological approaches to help unravel the intracellular metabolome of Bacillus subtilis.

BACKGROUND: Bacillus subtilis (B. subtilis) has become widely accepted as a model organism for studies on Gram-positive bacteria. A deeper insight into the physiology of this prokaryote requires advanced studies of its metabolism. To provide a reliable basis for metabolome investigations, a validated experimental protocol is needed since the quality of the analytical sample and the final data are strongly affected by the sampling steps. To ensure that the sample analyzed precisely reflects the biological condition of interest, outside biases have to be avoided during sample preparation. RESULTS: Procedures for sampling, quenching, extraction of metabolites, cell disruption, as well as metabolite leakage were tested and optimized for B. subtilis. In particular the energy status of the bacterial cell, characterized by the adenylate energy charge, was used to evaluate sampling accuracy. Moreover, the results of the present study demonstrate that the cultivation medium can affect the efficiency of the developed sampling procedure. CONCLUSION: The final workflow presented here allows for the reproducible and reliable generation of physiological data. The method with the highest qualitative and quantitative metabolite yield was chosen, and when used together with complementary bioanalytical methods (i.e., GC-MS, LC-MS and 1H-NMR) provides a solid basis to gather information on the metabolome of B. subtilis.