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To gain a better understanding of how high-flux biochemical pathways adapt to environmental challenges, a research team from SCIEX and the University of California at San Diego measured the exact levels of 100 known metabolites harvested from bacteria grown under different conditions  (Table 1). Using a targeted protocol that provided broad coverage of intracellular compounds, researchers determined the absolute difference between E. coli intermediates grown in minimal and complex media and then calculated the flux of metabolites through selected pathways of interest. Assisted by a metabolic labeling strategy and a linear ion trap/triple quadrupole mass spectrometer, scientists were able to minimize the technological challenges that often impede large-scale, metabolomic studies to identify and quantitate a large number of metabolites with improved accuracy, sensitivity, and specificity without a loss in productivity.
Capturing a snapshot of a cell's contents enables scientists virtually to peer inside an organism, deepening their understanding of cellular metabolism and the adaptive responses to external stimuli. The study of metabolomics stimulates these discoveries and expands our biochemical foundation, equipping researchers with insights that will have a major impact on industrial and medical applications. With current advancements in LC-MS/MS technologies now permitting precise measurement of individual metabolites, researchers can derive the absolute flux, or the rate of turnover of molecules through intracellular pathways. And this in turn, permits the calculation of reaction constants relating to thermodynamics and enzyme kinetics, expanding the global picture of cellular metabolism and its overall regulation.
To investigate changes to bacterial metabolism resulting from varied growth conditions, researchers assembled a set of methods to quantitate intracellular intermediates: a metabolic-labeling experiment for internal standard generation for every intermediate; reverse-phase ion-pairing chromatography for reproducible separation; and a dual-scan mass spectrometry approach using a QTRAP® 5500 System for confident identification and accurate quantitation via isotope ratio determination.
A well-characterized internal standard (IS) is at the heart of every quantitative study, but obtaining multiple, pure, radiolabeled analogs for all intracellular compounds is cost-prohibitive and logistically complicated. To circumvent this roadblock, researchers used an efficient, "home-grown" method wherein bacteria were fed a uniformly labeled substrate (U-13C-glucose) until steady state equilibrium for complete isotopic enrichment [2-4]. After harvesting and extracting the cells, the composition and uniformity of the labeled biomass was verified by MS/MS and compared to scans of unlabeled metabolites. These "bio-generated" U-13C-labeled cellular intermediates were then used to define the isotopomer distribution ratios that were central to quantitating the metabolome (Figure 1).
To lay the groundwork for robust, accurate quantitation, extracts of bacterial cultures raised in minimal or complex media were spiked with IS, separated, and analyzed by MS  (Figure 1). A standard curve was also generated for each compound by spiking a range of calibrants with the metabolically labeled IS and run on the same chromatographic gradient prior to MS acquisition, permitting the concentrations of each labeled metabolite to be normalized to the calibrant. The unlabeled metabolite amount was then derived by calculating the peak-height ratios relative to the known amount of metabolically labeled IS (Figure 1), providing cellular intermediate concentrations over a broad range of physiologically-meaningful levels with good linearity and reproducibility.
Underlying every successful quantitation method is a separation strategy that effectively resolves each targeted analyte from the complex background matrix, while at the same time, finds a balance between throughput and the need for improved sensitivity for low-level metabolites. To separate extracted metabolites, a reverse-phase ion-pairing chromatography method was developed that differentiates the predominantly polar and charged species of cellular metabolism, even teasing apart difficult-to-resolve metabolic isomers (e.g., citrate and isocitrate). Recent improvements to mobile phase solvent composition were key to optimizing this approach so that even very low-levels were resolved and sensitively detected for reproducible coverage of a wide array of intracellular compounds.
By focusing on well-studied metabolic pathways where the masses and structures of intermediates are already established, a targeted method was employed that used multiple reaction monitoring (MRM) scans to detect and measure the levels of 100 analytes in one run. Tracking MRM transitions for a large number of compounds—including both labeled and unlabeled in the same sample—can slow down processing speeds, drag down the duty cycle and impact reproducibility. To improve throughput during multi-analyte detection, the targeted workflows included a time-saving feature—the Schedule MRM™ Pro Algorithm. This allowed for MRM transitions for particular analytes to be slated only when column elution was expected, reducing the need for ongoing, multi-period analysis of every analyte (Figure 2) for maximal acquisition efficiency.
Fully separating compounds of interest from a complex cellular background is very challenging, and often peaks are contaminated by co-eluting analytes that can interfere with quantitation. In these cases, relying solely on the mass derived from an MRM transition to validate a compound’s identity is not sufficient, and additional steps must be taken to ensure that a peak corresponds to the selected metabolite. To add an additional layer of authentication, the MRM detection process was coupled with two alternate scan types that either 1) further confirmed an analyte’s identity or 2) captured higher resolution MS/MS information containing an analyte’s isotopomer distribution and structural information (Figure 3).
The first scan type from the quantitative workflow (Figure 3) verifies that the intended target was measured rather than a non-specific, overlapping contaminant. Over the course of acquisition, an MRM transition detected at a pre-determined intensity level will trigger an enhanced product ion (EPI) scan via information dependent acquisition (IDA). The fingerprint of secondary ions generated by the EPI scan can be compared to a spectral library to confirm a peak’s identity. Using this method, extensive structural information can be gleaned about each analyte, and the authors were able to demonstrate how 302 MRM transitions were detected and verified to accurately quantify 100 metabolites of interest. (See example in Figure 4.)
Accurate metabolite quantitation also requires the correct identification of an analyte’s isotopomers and defining their distribution. To that end, researchers incorporated a second scan type—an enhanced resolution (ER) scan—in the qualitative workflow (Figure 3) to deliver the high-resolution mass data needed for calculating the isotopomer ratio between the labeled and unlabeled metabolites. Aided by the linear ion trap, the EPI scan generated high-resolution, secondary fragments for pinpointing the 13C-labels and confirming isotopomer identity.
Ultimately to analyze each metabolite in the bacterial extracts, multiple transitions were tracked for a single compound and its U-13C-labeled counterpart; when an MRM transition reached a predefined signal threshold, an ER scan was triggered, providing masses and peak heights for each isotopomer—and, importantly, enabling the ratios of unlabeled analytes relative to the labeled IS to be determined (Figure 5). Using these isotopomer ratios and the standard curve generated from the spiked calibrants, researchers were able to calculate the endogenous levels of 100 unlabeled metabolites from the same cellular extract over a wide range of concentrations.
Measuring the levels of intermediates in high-flux pathways is not restricted solely to bacterial studies, and SCIEX researchers have extended this approach to different micro-organisms, as well as to other mammalian tissue or cell types including neuroprogenitor stem cells, red blood cells and human and mouse plasma. Additionally, scientists have altered the combination of metabolically labeled substrates (e.g., 80% 1-13C glucose and 20% U-13C glucose) to investigate the flux of intra-organism metabolites with IDA-EPA acquisition methods that provide more extensive high-resolution structural information than what is given by typical MS/MS scans (publication forthcoming).
Fully defining an organism’s biochemical pathways by screening a large number of metabolites from the same sample allows for a greater understanding of the impact of growth conditions and environmental stresses on the intracellular metabolome and creates a more global view of the cellular regulatory processes. But in order to expand our knowledge of metabolites, scientists must have access to powerful tools that can meet the demands of separating, identifying and quantitating hundreds of varied compounds simultaneously over a broad range of concentrations. At the core of metabolomics is the ability to distill individual metabolite levels from an extremely complex background; and with so much remaining to discover, having an accurate, confident, and reproducible way to survey the entirety of a metabolome will help to more quickly advance medical and industrial discoveries into the future.
Submitted by Laura Baker, freelance science and technical writer
Figure 1 A multi-step workflow for the absolute quantitation of metabolites was employed to evaluate the bacterial metabolome.
Figure 2 An overview of the Schedule MRM Algorithm shows that a multiple reaction monitoring (MRM) scan for a particular transition is triggered only during a peak's expected elution time.
Figure 3 Two separate acquisition workflows were utilized on the QTRAP® 5500 system to enhance the identification and confirmation of metabolites. A) The quantitative workflow consisted of multiple reaction monitoring (MRM) scans coupled to an information-dependent acquisition (IDA) method, which triggered an enhanced product ion (EPI) scan for secondary fragment ion generation. B) The qualitative workflow inserted an enhanced resolution (ER) scan for the collection of high resolution mass data, which enabled the determination of an analyte’s isotopomers and its distribution. EPI data acquired after the ER scans provided fragment ions, which helped identify the location of the 13C-labels in an isotopomer.
Figure 4 A) L-glutamate (glu-L) was analyzed using Workflow A in Figure 2. Primary (blue) and secondary (green) multiple reaction monitoring (MRM) transitions for glu-L were monitored alongside the 13C-labled analog (red). Enhanced product ion (EPI) scans produced a fingerprint of secondary ions that were used to confirm the analyte’s identity. B) EPI scans that were > 90% matched to a reference scan (yellow) from a spectral library were considered equivalent.
Figure 5 (Taken from Figure 4 in "Quantitative and Qualitative Metabolomics for the Investigation of Intracellular Metabolism": A) Malic Acid was analyzed using Workflow B from Figure 3, the quantitative workflow. Enhanced resolution (ER) scans provide the high-resolution mass information needed for obtaining isotopomer ratios. Enhanced product ion (EPI) scans reveal fragmentation data that is used to verify the compound’s identity. B) High-resolution ER scans of the fully-labeled metabolite show the redistribution of the isotopomers. EPI scans of the fully-labeled standard can be used to elucidate the location of the 13C-labels.
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