Application of two-dimensional NMR spectroscopy to metabotyping laboratory Escherichia coli strains.

NMR Spectroscopy has been established as a major tool for identification and quantification of metabolites in a living system. Since the metabolomics era began, one-dimensional NMR spectroscopy has been intensively employed due to its simplicity and quickness. However, it has suffered from an inevitable overlap of signals, thus leading to inaccuracy in identification and quantification of metabolites. Two-dimensional (2D) NMR has emerged as a viable alternative because it can offer higher accuracy in a reasonable amount of time. We employed (1) H,(13) C-HSQC to profile metabolites of six different laboratory E. coli strains. We identified 18 metabolites and observed clustering of six strains according to their metabolites. We compared the metabolites among the strains, and found that a) the strains specialized for protein production were segregated; b) XL1-Blue separated itself from others by accumulating amino acids such as alanine, aspartate, glutamate, methionine, proline, and lysine; c) the strains specialized for cloning purpose were spread out from one another; and d) the strains originating from B strain were characterized by succinate accumulation. This work shows that 2D-NMR can be applied to identify a strain from metabolite analysis, offering a possible alternative to genetic analysis to identify E. coli strains.

Stress adaptation of Saccharomyces cerevisiae as monitored via metabolites using two-dimensional NMR spectroscopy.

Many studies on yeast metabolism are focused on its response to specific stress conditions because the results can be extended to the human medical issues. Most of those works have been accomplished through functional genomics studies. However, these changes may not show a linear correlation with protein or metabolite levels. For many organisms including yeast, the number of metabolites is far fewer than that of genes or gene products. Thus, metabolic profiling can provide a simpler yet efficient snapshot of the system's physiology. Metabolites of Saccharomyces cerevisiae under various stresses were analyzed and compared with those under the normal, unstressed growth conditions by two-dimensional NMR spectroscopy. At least 31 metabolites were identified for most of the samples. The levels of many identified metabolites showed significant increase or decrease depending on the nature of the stress. The statistical analysis produced a holistic view: different stresses were clustered and isolated from one another with the exception of high pH, heat, and oxidative stresses. This work could provide a link between the metabolite profiles and mRNA or protein profiles under representative and well-studied stress conditions.

Relationship between recombinant protein expression and host metabolome as determined by two-dimensional NMR spectroscopy.

Escherichia coli has been the most widely used host to produce large amounts of heterologous proteins. However, given an input plasmid DNA, E. coli may produce soluble protein, produce only inclusion bodies, or yield little or no protein at all. Many efforts have been made to surmount these problems, but most of them have involved time-consuming and labor-intensive trial-and-error. We hypothesized that different metabolomic fingerprints might be associated with different protein production outcomes. If so, then it might be possible to change the expression pattern by manipulating the metabolite environment. As a first step in testing this hypothesis, we probed a subset of the intracellular metabolites by partially labeling it with 13C-glucose. We tested 71 genes and identified 17 metabolites by employing the two-dimensional NMR spectroscopy. The statistical analysis showed that there existed the metabolite compositions favoring protein production. We hope that this work would help devise a systematic and predictive approach to the recombinant protein production.

Dosage Effects of Salt and pH Stresses on Saccharomyces cerevisiae as Monitored via Metabolites by Using Two Dimensional NMR Spectroscopy.

Saccharomyces cerevisiae, which is a common species of yeast, is by far the most extensively studied model of a eukaryote because although it is one of the simplest eukaryotes, its basic cellular processes resemble those of higher organisms. In addition, yeast is a commercially valuable organism for ethanol production. Since the yeast data can be extrapolated to the important aspects of higher organisms, many researchers have studied yeast metabolism under various conditions. In this report, we analyzed and compared metabolites of Saccharomyces cerevisiae under salt and pH stresses of various strengths by using two-dimensional NMR spectroscopy. A total of 31 metabolites were identified for most of the samples. The levels of many identified metabolites showed gradual or drastic increases or decreases depending on the severity of the stresses involved. The statistical analysis produced a holistic outline: pH stresses were clustered together, but salt stresses were spread out depending on the severity. This work could provide a link between the metabolite profiles and mRNA or protein profiles under representative and well studied stress conditions.

Tracing Metabolite Footsteps of Escherichia coli Along the Time Course of Recombinant Protein Expression by Two-Dimensional NMR Spectroscopy.

The recombinant expression of proteins has been the method of choice to meet the demands from proteomics and structural genomics studies. Despite its successful production of many heterologous proteins, Escherichia coli failed to produce many other proteins in their native forms. This may be related to the fact that the stresses resulting from the overproduction interfere with cellular processes. To better understand the physiological change during the overproduction phase, we profiled the metabolites along the time course of the recombinant protein expression. We identified 32 metabolites collected from different time points in the protein production phase. The stress induced by protein production can be characterized by (A) the increased usage of aspartic acid, choline, glycerol, and N-acetyllysine; and (B) the accumulation of adenosine, alanine, oxidized glutathione, glycine, N-acetylputrescine, and uracil. We envision that this work can be used to create a strategy for the production of usable proteins in large quantities.