lc-tims-tof ms/ms data analysis for screening lipids with stable isotope labeling

Screening Lipid Structures Using Stable Isotope Labeling

When analyzing lipid data, stable isotope labeling (SIL) is an effective method to assess metabolic pathways in living organisms. In this method, atoms within an analyte are replaced by stable isotopes containing 13C or 2H. These isotopes are further incorporated into precursors, which are later embedded within the fatty acids, labeling the areas in which they reside. With these isotopes, one is able to identify the distribution and metabolism of lipids, as they will contrast against the unlabeled background1. Common mass spectrometry platforms are not able to distinguish the signal coming from endogenous molecules2. The success of SIL requires the use of ultrahigh-resolution analytical tools. Liquid chromatography coupled to high-resolution trapped ion mobility spectrometry-parallel accumulation sequential fragmentation-time-of-flight tandem mass spectrometry (LC-TIMS-PASEF-TOF-MS/MS) allows the separation of labeled and nonlabelled species2. The advantage of LC-TIMS-PASEF-TOF-MS/MS analysis is that the MS signal can be filtered by the retention time (RT) and mobility, thus reducing potential interferences of endogenous molecules, as well as quantification and separation of all desired species2. In TIMS, an ion is first held stationary against a gas-mobile phase and subsequently released according to its mobility. This provides high-resolution mobilograms while operating at a lower voltage than earlier IMS instrumentation3. Mobilograms are plots of mass to charge versus drift time that can be used to distinguish between compounds based off of their drift time and amount of overlap4.
By using an additional PASEF technique, sequencing speed is greatly increased without sacrificing sensitivity5. The PASEF theory involves the accumulation of ions followed by their sequential release in the order of their mobility. This is done by accumulating ions in parallel alignment to their mobility. The accumulation in this fashion prevents ion loss. Furthermore, the precursor ion selection occurs simultaneously with the accumulation and release of the ions. With this method, PASEF selects multiple precursors in series during each TIMS scan, rather than the individual precursors per scan typical of a TIMS instrument that does not use PASEF. When the precursor ions are concurrently accumulated and released in 2 ms peaks within a TIMS scan of approximately 100 ms per frame, the signal is amplified by over one order of magnitude, therefore increasing the signal-to-noise ratio3. The PASEF addition to the TIMS increases the efficiency of the MS/MS. As the TIMS-PASEF is coupled with MS/MS, a more efficient fragmentation is possible. Unlike conventional MS/MS detection, the precursor signal is compressed from the TIMS-PASEF, and the fragment ions are detected simultaneously to the TIMS elution time and ion mobility position of the precursor3.
When acquiring data from a mass spectrometer, there are options in the scan mode desired. Data dependent acquisition (DDA) selects precursor ions from the MS1 scan based on their abundances, before fragmenting them and performing the MS2 scan. This scan mode fragments as many precursors as possible. The DDA approach is targeted, and results will depend on the ion selection3. However, DDA-PASEF often has problems in the reproducibility between replicates. While DDA is a great tool in a focused analysis, complex mixtures have greater difficulty in their data acquisition6. This is because only a small amount of ions can be monitored simultaneously3. Data independent acquisition (DIA) is a method where preselected windows of m/z are fragmented independently from their intensity, and all are scanned within the range7. With this scan mode, entire ion clouds are transmitted from the IMS to the mass spectrometer3. In proteomics studies this results in greater amounts of proteins being quantified in a shorter time span compared to DDA. In addition, DIA misses fewer m/z values compared to DDA. Therefore, this alternative has shown great improvements in data reproducibility in signal to noise ratio and better quantification than DDA. In this present work, our goal is to implement DIA to the method reported by Tose et al.2. We improved the reproducibility and intensity of signals, yielding further and more conclusive information on SIL lipids mobilization, distribution and metabolism in biological samples taking advantage of DDA and DIA acquisition.

Author Spotlight: Quantification of Complex Lipidomic Samples Using Stable Isotope Labeling

Tracing de novo Lipids using Stable Isotope Labeling LC-TIMS-TOF MS/MS

This research intends to implement more specific quantification in lipidomic samples using stable isotope labeling. This allows us to understand lipid panels and highly diverse samples from insects to humans. There currently is a gap in this field regarding the standardization of LC, TIMS, Top, MS/MS in lipidomic investigations.Here we provide a method for tracking biomass remains for this purpose. In the future, our research will involve the investigation of epigenetics and metabolomics present in the biological process using the LC team staff, MS/MS, involve DDA and DIA methods.

LC-TIMS-TOF MS/MS Data Analysis for Screening Lipids with Stable Isotope Labeling

To begin, open the data analysis software. At the top left corner, click on the file button and select open. To select the files of choice, right click on the file name and select properties.Then select calibration status. At the dropdown box, select internal calibration for the mass spectrometer. Ensure that all errors are less than one parts per million.After that, select internal mobility calibration and confirm that the error is less than one part per million. Next, right click on chromatogram and select edit chromatogram. At type, click the dropdown box and select extracted ion chromatogram.Under filter, select all MS, and for scan mode, select all to view the peaks for the molecule of interest rather than only its fragments. There are two filter options for molecule selection, masses or formula. If masses is selected, choose the theoretical M over Z of the molecule of interest, which in this case is 829.7985.If formula is selected, choose the formula for the molecule and the ion forms of interest, which in this case is ammonium. For width, select plus or minus one. For polarity, ensure that it maintains the positive mode.Under mobility, select 1.455 to 1.465 to isolate the molecule of interest and filter out molecules not falling within these values. Once the parameters are selected, click change followed by okay at the top right. After a brief time, the software will process the selections and output a chromatogram.Right click at the baseline of the origin of the peak of interest and drag while holding to the end of the peak to obtain a live mass spectrum of fragments within that retention time. Right click at the left of the screen on mobilogram and select edit mobilogram. A window named edit mobilogram traces will appear.Follow the steps demonstrated previously. For retention time, input the retention time of the peak of interest. Once the parameters are selected, click add, and okay at the top right.Wait till the software processes the selections and outputs a chromatogram. For extracting ions, repeat the steps demonstrated previously until a list of ions is formed. At the bottom of the MS window, select profile MS and fragment MS to allow a spectrum view of ions from a full scan and passive.For the spectrum view, right click and select copy compound spectra. The spectrum data that appears at the right can provide more information on the compound, such as resolution resolving power, intensity, and signal-to-noise ratio. To process the data, manually integrate the chromatogram and mobility peaks to yield valuable information on the molecule of interest.Right click find and select compounds manually chromatogram or mobilogram. Left click and highlight the desired peak. The obtained information includes retention time, area, signal-to-noise ratio, and mobility.

Research

JoVE Journal

Chemistry

Lipids are highly diverse, and small changes in lipid structures and composition can have profound effects on critical biological functions. Stable ...