Table of Contents
STEP 1
This tool can be either used in a LIMS or stand-alone. In the stand-alone mode you should either drag/drop your experimental spectrum as a tab-delimited text file or copy paste it (CTRL-V) while moving you mouse over the drop zone. The list of available mass spectra will be displayed in the table and you can simply click on one of them to display it.
STEP 2 (Automatic)
Once the experimental spectrum is uploaded, mixture automatically triggers peak picking and generates a list of experimental monoisotopic centroids. For fine-tuning of calculations, the resolution as a function of the m/z is automatically plotted and the corresponding regression curve used to adjust the peak width. Both calculations can be viewed in the Peak Picking Module. The data showed in the right represent the resolution (peak width) vs m/z in our Orbitrap Elite for the MS of inosine RNA example available from the List of experimental spectra.
STEP 3
This step is critical for a good mixture calculation. You need to define all possible “pieces” that you want to find in your experiment. Like in a puzzle, the solver is expected to put pieces together in a logical way. Let’s think about the sugar examples shown here, where one lipophilic central core should be present but you want to probe also for absence, written (C42H63O28S7)0-1). This core tends to bind between 0-7 chains (C11H22SO3) in our case. During the experiment, some labile SO3 groups may have been lost during ionization so the chain could be split in two (C11H22)0-7 and (SO3)0-7. Each of the sulfate group is negatively charged so you should specify it by indicating it this way [-1- -7]. Additionally, the molecule could also by cationized with H,Na or K positively charged. Mixture will combine all these possibilities and generate their corresponding molecular formulas. Finally mixture will subsequently try to matched theoretical to the experimental spectra. The list of all abbreviations that can be used to indicate the common functional groups is found at the top right corner of the Settings window.
STEP 4
You can filter the obtained molecular formula in step 5 by different criteria such as the charge, the experimental m/z or the unsaturation. This option was not selected for any of our examples in the list of experimental spectra.
STEP 5
In order to improve the isotopic profile matching between theoretical and experimental data, a few spectrum filters should be properly set here. First you should set the experimental relative peak intensity threshold (typically between 0.01-0.1). Second, the authorized experimental mass error in ppm (typically <5 ppm for Orbitrap mass analyzer) and third, the minimum similarity for peak matching should be set (typically between 70-80%). Check how mixture calculates Similarity here. Lastly, you should decide if the monoisotopic mass has to be present in the spectrum (which depends on the size of the compound) and set the comparison zone which should be adjusted based on the complexity of the expected isotopic pattern.
Step 6 (Optional)
Once the initial calculation is over, mixture allows you an additional post calibration step to improve mass accuracy and, therefore, similarity scores of matched ions. In order to recalibrate the data, you need first to precise the minimum number of reference peaks with a defined minimum similarity to be taken in the peak picking and recalibration module. Once defined, you click the calibrate and recalculate button and mixture reprocess the data in a few seconds. You can view the graph of errors (in Da and ppm) between found and expected after corrections and other details in the Peak picking and recalibration module at the top. Displayed graph of errors corresponds here tor our mixture-sugar example.
Resuts 1
The first view is a summarizing table named List of fragments which contains all the information about the identified molecules. You can see the molecular formula and ionization form, as well as the Molecular formula monoisotopic peak (without ionization) and the final monoisotopic mass including the charge. Another interesting values such as the ppm error, the relative abundance, the quantity, group and the similarity score are also included in this view. For any of the fragment ions, you can zoom and interact in the mass spectra view (Results 2). All the data presented in the table can be classified by any criterion with a simple click on the column header. You can also use the search bar in order to search faster an individual value or use it by range (go to glossary). You can also export the whole table as text file with Export Data button.
Resuts 2
Mass spectra window displays the experimental data (in red) overlaid with the theoretical matched ions (in blue). Identified ions are assigned and black-coded on the top. You can select a single peak in the table view (Results 1) and it is going to be highlighted in this view (in yellow). It is possible to zoom in (left button), zoom out (double left button) and show this window on the full screen (option bar at the top of the window). The content of this window can be either printed or exported as SVG file (option bar). The mixture-sugar example after recalibration is shown in the figure (left).
Resuts 3
The Info box window shows details for the table-selected ion such as its name, monoisotopic mass, variable groups composition, charge and ionization adduct. you find as well the theoretical monoisotopic mass and the closest m/z experimental data. Below this window, the assigned quantity, the number of distinct fragments found and their percentage of the total intensity are shown. The total amount of theoretically possible fragments based on selected combinations are displayed as well.
The Similarity box window displays the matching of theoretical isotopic pattern to experimental spectrum for the selected fragment with differences in the intensity of isotopologues highlighted in yellow. You can check our concept of similarity here.
