Microbial metabolomics: welcome to the real world!

In the post-genomics era there has been a growing emphasis on understanding the metabolic consequences of engineering cells to produce desired chemicals. Proteomics measurements have improved our understanding of gene expression, and metabolomics promises to take us a step further. A consequence of the metabolome being further down the line from gene function is that the interpretation of metabolomics data reflects more closely the activities of a cell at the functional level and potentially leads to the revelation of metabolite function. This latter point is of great importance especially when we consider that a given metabolite may come from more than one metabolic pathway and may impact the cell in multiple ways. Further, by accurately quantifying the metabolome, we can begin to understand the stoichiometric significance of metabolite production. Since metabolomics was first coined, it was received with a great deal of fanfare. Like the earlier omics techniques, it was thought that comprehensive metabolomics data sets would be a staple of functional genomics analyses. That was until it was realized that the structural diversity that exists within the metabolome would make it virtually impossible, with current analytical technologies, to characterize the metabolomes of microorganisms fully. To make matters worse, the diverse chemical and physical properties within the metabolome, together with the structural differences in the cell walls of microorganisms, meant that it would be extremely difficult to establish a single sample extraction procedure that was suitable for all metabolites. Added to the fact that the recovery of metabolites would largely depend on the extraction protocol used, meant that the achievement of global metabolite analysis was not a trivial matter. Questions that should have been asked at the time were, how much of the metabolome was necessary to characterize metabolism and what aspects of metabolomics data were truly meaningful? While the goal of complete holistic metabolomics data sets is still what we aspire to achieve, at present we have softened our stance on metabolomics by focusing on local metabolite profiling. In addition to this, we have concentrated our efforts on looking for specific differences in metabolite levels in response to genetic modification, stress responses and environmental change. Even though this is a far cry from global metabolite profiling, these approaches combined with the latest analytical technologies are being used to successfully unravel gene function and to identify biomarkers and unknown metabolites. The most promising techniques that are currently employed in microbial metabolomics research are nuclear magnetic resonance (NMR), array-based mass spectrometry (MS), gas chromatography–MS (GC–MS), liquid chromatography–MS (LC–MS), and capillary electrophoresis–MS (CE–MS). Though NMR can provide high throughput fingerprinting and structural elucidation, cost, sensitivity and quantification are issues that need to be addressed if it is to compete with the MS-based technologies. While arraybased techniques, such as nanostructure-initiator MS (NIMS), are ideal for screening crude microbial extracts, developments in nano surface technology are essential if E. E. K. Baidoo J. D. Keasling (&) Physical Biosciences Division, Joint Bioenergy Institute, Lawrence Berkeley National Laboratory, Berkeley, CA, USA e-mail: jdkeasling@lbl.gov