Metabolite identification

MS-DIAL

For LC-MS/MS based approach, MS-DIAL software is employed for metabolite identification using quality control samples.

Step 1 File Conversion

  • Start “AnalysisBaseFileConverter.exe”.
  • Drag & drop MS files (.d) into this program.
  • Click “Convert”.
  • The ABF files are generated in the same directory as the raw data files. (Figure 1) Figure 1

Step 2 Project Creation

2.1 Click “File” then click “New project” (Figure 2,3) Figure 2

Figure 3

2.2 Browse a folder containing ABF files (Figure 4) Figure 4

2.3 Select the details for LC-MS/MS (Figure 5)

  1. Select Ionization type
  2. Select Separation type
  3. Select MS mode type
  4. Select Data type (MS1 and MS/MS)
  5. Select Ion mode
  6. Select Target omics
  7. Click “Next” Figure 5

2.4 Importing ABF files (Figure 6,7)

  1. Select ABF files
  2. Set the file as “Quality Control (QC)”
  3. Edit injection volume (in this sample, we injected 2 uL) Figure 6

Figure 7

2.5 Setting parameters

  1. Data collection tab Mass accuracy: After the peak detection algorithm is applied along the MS axis with a very low threshold, MS-DIAL performs spectral centroiding. By default, mass spectrum of ±0.01 and ±0.05 Da range from each peak top is integrated in MS1 and MS2, respectively. Importantly, this MS2 tolerance value is also used to build the MS/MS chromatogram for a certain m/z trace. The MS/MS chromatograms are dedicated to the MS2Dec deconvolution program. Data collection parameters: You can set analysis ranges (RT, MS1 and MS/MS axis). In this demonstration, your expected data range is 0-30 min for 50-1000 Da. Figure 8

  2. Peak detection tab MS-DIAL provides two simple thresholds: minimum values for peak width and height. Peaks below these thresholds are ignored. Minimum peak width: indicates a threshold of peak width for filtering (0.1 and 0.05 are suitable for Q-TOF and Orbitrap, respectively). Smoothing method: Linear-weighted moving average is used for the peak detection as default to accurately determine the peak left- and right edges. The recommended smoothing level is 1-3. (If you already know unwanted m/z peaks because of columns or solvent contaminants, you can specify them in the Exclusion mass list). Figure 9

  3. MS2Dec tab Deconvolution parameters mean the cut-off values to reduce the MS noises. The sigma window value is highly affected by the resolution of deconvolutions. A higher value (0.7-1.0) will reduce the peak top resolutions, i.e. the number of resolved peaks will be decreased. On the other hand, a lower value (0.1-0.3) may also recognize many noise chromatographic peaks. Figure 10

  4. Identification tab MSP file is a mass spectrum file format for MS/MS spectrum that available on MS-DIAL website (http://prime.psc.riken.jp/compms/msdial/main.html#MSP). Figure 11

Figure 12

  1. Adduct tab You can tick the adduct ions and charge values to be considered. Figure 13

  2. Alignment tab Result name will be the name of each alignment shown at the pane ‘Alignment navigator’ in the main window. The RT and MS1 tolerances for peak alignment depend on your chromatographic conditions. Figure 14

Step 3: Compound Identification

The output of data filtering

  1. MS1 spectrum
  2. EIC: Extract ion chromatogram
  3. Peak property
  4. Experimental MS/MS spectrum
  5. Reference MS/MS spectrum

The metabolite searching can be carried out using either retention time (RT) or mass-to-charge (m/z) at the bottom panel. Figure 15

Human metabolome database (HMDB)

The Human Metabolome Database (HMDB) is a freely available electronic database containing detailed information about small molecule metabolites found in the human body. It is intended to be used for applications in metabolomics, clinical chemistry, biomarker discovery and general education. The database is designed to contain or link three kinds of data: 1) chemical data, 2) clinical data, and 3) molecular biology/biochemistry data. The database contains 114,193 metabolite entries including both water-soluble and lipid soluble metabolites as well as metabolites that would be regarded as either abundant (> 1 uM) or relatively rare (< 1 nM). Additionally, 5,702 protein sequences are linked to these metabolite entries. (Source: https://hmdb.ca/)

  1. Go to https://hmdb.ca/ > Click Search > Click LC-MS Search

  2. Add “m/z” > Set parameter > Click Search

  3. List of matched metabolites

  4. Description of metabolite

  5. Select MS/MS Spectra with “Experimental Conditions” to confirm fragmentation patterns of spectrum

  6. Spectrum details, spectrum view, and experimental conditions

METLIN

METLIN has multiple searching capabilities including single, batch, precursor ion, neutral loss, accurate mass, and fragment searches. The popular similarity search algorithm for unknown characterization, another METLIN search option, originated on METLIN in 2008. METLIN now includes over a million molecules ranging from lipids, steroids, plant & bacteria metabolites, small peptides, carbohydrates, exogenous drugs/metabolites, central carbon metabolites and toxicants. The metabolites and other chemical entities have been individually analyzed to provide experimental MS/MS data. (Source: https://metlin.scripps.edu/)

  1. Go to https://metlin.scripps.edu/ > Click Sign Up

  2. Create “New User Registration”

  3. Click “Simple Search”

  4. Add “m/z” > Set parameter > Click Search