High-resolution accurate mass (HRAM) for metabolomics and lipidomics
High resolution accurate mass (HRAM) systems characteristically detect minute differences in the masses of compounds that lower resolution instruments miss. As a result, a single peak reported on a lower resolution instrument is resolved as two or more peaks on a high resolution mass spectrometer.
Resolving power differs between the various mass analyzers referred to as "high resolution." TOF-based analyzers generally have a resolving power of 20-40k, while Orbitrap analyzers can reach 500k. The higher the resolving power, the more confidence can be assigned to accurate compound identification and quantitation. As a result, Orbitrap-based data are often used for creating confident mass assignments, and especially with metabolites having similar mass assignments.
The identification and quantitation of metabolites, as represented by their relevant spectral peaks (m/z), is one of the major challenges and bottlenecks of untargeted metabolomics. Given the diverse compounds found in metabolomics, many of them with similar masses, HRAM mass spectrometry is necessary for confidant peak assignment and subsequent compound identification and quantitation.
High resolving power is especially useful during isotope labeling metabolomics experiments. One particular example involves the use of labeled amines such as [15N]glutamine in chronic pain test subjects. Here, the labeled glutamine and endogenous glutamate both elute on the same reversed-phase LC column and cannot be resolved by using a resolution of 20,000 because the monoisotope of labeled glutamine (A0) is overlapped by the second isotope of glutamate (A1). As a result, quantitative measurement becomes a challenge.
Using high resolution MS, such as that found with Orbitrap mass analyzer technology, the instrument can be set at a resolution of 100,000. This leads to the resolution of two amine peaks instead of one, and each peak can subsequently be characterized.
For quantitative experiments, unambiguous results can only be obtained if sufficient resolving power is used to separate the target metabolite from any possible interferences. If the resolving power of the instrument is insufficient, false positive or false negative signal responses will be generated.
Mass spectrometry sensitivity for metabolomics: five orders of dynamic range
Metabolomics is and always has been a quantitative science. This is because there are order-of-magnitude differences in the concentrations of endogenous metabolites. As such, a mass spectrometer must be able to detect these concentration variances in order to generate data that reflect a comprehensive and meaningful view of the biological condition under study. With Orbitrap mass analyzer technology, analyte quantitation can be performed down to extremely low femtomole levels. Furthermore, analytes ranging over five orders of linear dynamic range can be easily detected, with the reslting data still achieving small coefficient of variation (CV) values.
Sensitivity and resolution: no compromise
With all mass analyzers, there is a trade-off between three major system attributes: speed, selectivity (resolution and accurate mass) and sensitivity (signal intensity). Additionally, metabolomics samples are complex and present inherent challenges due to their large dynamic range.
The key to good mass spectrometry is to minimize the magnitude of these three trade-offs as much as possible. A superior mass spectrometer generates data that feature no compromise between sensitivity and resolution.
Reproducibility of HRAM-MS for metabolomics
Because of its high sensitivity and selectivity, mass spectrometry techniques have become the method of choice for metabolomics research. To uncover meaningful answers from a large number of data sets, which is the norm with metabolomics studies, the mass spectrometer must provide accurate and reproducible data from run to run, and without the need for internal calibration.
HRAM for MS and MSn
Despite the need for fast data acquisition during metabolomics experiments, there must still be no compromise in the top quality HRAM spectra used in MS or MSn modes for confident compound identification.
Narrow precursor isolation window
Due to metabolomics studies featuring complex samples as well as sample contaminants, having a narrow precursor isolation window is vital to ensuring that the MS/MS spectra do not also contain peaks from background interferences. Such interferences, if present, then make target compound identification more difficult.
One solution to this challenge is to maintain a tight isolation window. In the example below, a tight 1-4 amu isolation window keeps transmission losses at a minimum while still limiting chemical noise interference. A high quality MS/MS spectrum of bovine heart total lipid extract (1 mg on column) is generated, with a 1 amu isolation width for enhanced specificity.
Fast polarity switching
With metabolomics compounds having diverse physico-chemical properties, a combination of separation techniques (GC, IC and LC reversed phase/HILIC) can help achieve a more comprehensive view of different biological states. Additionally, greater spectral coverage can be achieved by using both positive and negative ionization modes on the mass spectrometer. This is feasible only if fast polarity switching is also used, because faster polarity switching enables a more productive separations time scale during a single run.
MSn capabilities for metabolite structural elucidation
In untargeted metabolomics experiments, final identification of key spectral peaks is an experimental bottleneck. When such compounds cannot be confidently identified by spectral library searching, MSn offers a solution for de novo identification and structural elucidation.
MSn is usually achieved using ion traps and tribrid mass spectrometers; it is also an advanced technique, requiring that the mass spectrometer be equipped with HRAM features, fast scanning speed, and a variety of dissociation modes such as HCD and CID.
The adjacent example shows LC-MS analysis of urine accompanied by leucine and isoleucine resolution. The instrument speed (0.6 sec) is sufficient to obtain 10 full scan points across the peak. The MSn 'tree' must be obtained using a real UHPLC time scale.
Spectral libraries of various MSn levels offer spectral identification certainty. Different fragmentation modes and collision energies must be available for this approach to work.