Sampling for Metabolome Analysis of Microorganisms

Abstract

In the present work we investigated the most commonly applied methods used for sampling of microorganisms in the field of metabolomics in order to unravel potential sources of error previously ignored but of utmost importance for accurate metabolome analysis. To broaden the significance of our study, we investigated different Gram-negative and Gram-positive bacteria, i.e., Bacillus subtilis, Corynebacterium glutamicum, Escherichia coli, Gluconobacter oxydans, Pseudomonas putida, and Zymononas mobilis, and analyzed metabolites from different catabolic and anabolic intracellular pathways. Quenching of cells with cold methanol prior to cell separation and extraction led to drastic loss (>60%) of all metabolites tested due to unspecific leakage. Using fast filtration, Gram-negative bacteria also revealed a significant loss (>80%) when inappropriate washing solutions with low ionic strength were applied. Adapting the ionic strength of the washing solution to that of the cultivation medium could almost completely avoid this problem. Gram-positive strains did not show significant leakage independent of the washing solution. Fast filtration with sampling times of several seconds prior to extraction appears to be a suitable approach for metabolites with relatively high intracellular level and low turnover such as amino acids or TCA cycle intermediates. Comparison of metabolite levels in the culture supernatant and the cell interior revealed that the common assumption of whole broth quenching protocols attributing the metabolites found exclusively to the intracellular pools may not be valid in many cases. In such cases a differential approach correcting for medium-contained metabolites is required.

Development and application of a differential method for reliable metabolome analysis in Escherichia coli

“…Table 3 shows that 0.55 μM isoleucine still contributes to more than 30% of the total isoleucine present. In correspondence with our findings also Bolten et al (2007) detected intermediates from the glycolysis, TCA cycle and PPP in the supernatant for some bacterial species.…”

“…It has been shown that in bacterial cultures significant amounts of several central metabolites and amino acids are present in the culture filtrate (Bolten et al, 2007). These authors also showed that the applied filtration procedure could result in additional leakage of metabolites from the cells.…”

“…An alternative method for the determination of intracellular metabolites in E. coli, whereby metabolite leakage can be circumvented, is the differential method, proposed but not applied by (Mashego et al, 2007;Bolten et al, 2007;Schaub et al, 2006) which was in fact applied above to determine the intracellular metabolite amounts from the metabolite measurements in broth and culture filtrate (IC cal ).…”

“…It should be realized here that although the extracellular concentrations of most metabolic intermediates are generally much lower than the intracellular concentrations, the amounts present in the supernatant may still be very significant because the volume of the supernatant in laboratory cultivations is typically two orders of magnitude larger than the total cell volume. It has been reported that using the currently most used quenching fluid aqueous methanol (Table 1) for bacteria results in loss of intracellular metabolites due to leakage to the quenching liquid (Wittmann et al, 2004;Bolten et al, 2007). Bolten et al, method appears not to be suitable for rapid sampling in dynamic experiments and neither for steady state measurements of metabolites with short turnover times.…”

Analysis and Engineering of Metabolic Pathway Fluxes in Corynebacterium glutamicum

“…Dynamic models are also needed for dynamic labeling experiments for flux analysis as has been shown for E. coli [81]. The current progress in method development for metabolomics of C. glutamicum will surely stimulate the future generation of dynamic models for such organisms by providing extended data sets on intracellular metabolite concentrations required to derive in vivo kinetics [82][83][84][85]. For many years, dynamic macroscopic models have been used to describe dynamic phenomena of growth and production and derive control or feeding strategies for optimized bioprocesses.…”