BAF_Protocol_011 Metabolomics: Database Search MS-DIAL and Analysis using Metaboanalyst 6.0

Thermo RAW files are organized in two folders - one for all positive mode raw files and another for all negative mode raw files. These files will be loaded into MS-DIAL in two separate searches. Download MSP library files for Positive and Negative mode and save them in a folder in the computer you are using to perform the searches.

Open MS-DIAL

Click File -> New project

Project file path: Browse the folder with Positive or Negative raw files

Ionization type: Soft ionization (LC-MSMS)

Separation type: Chromatography (LC)

MS method type: Conventional LC/MS or data dependent MS/MS

Data type: MS1 Profile, MS/MS Centroid

Ion mode: Positive or Negative

Target omics: Metabolomics

Click "Next"

Analysis file path: browse to the folder with raw files, select all the apply for the search. Should include at least 3 blanks and 3 QC runs.

Choose the file type for each sample (Blank, QC, sample)

Class ID - add short group names for each replicate without adding numbers among replicates.

Data collection tab

Mass accuracy: MS1 tolerance 0.01 Da, MS2 tolerance 0.025 Da

• Advanced:

Data collection parameters: retention time begin 0 min, retention time end 15 min, MS1 range begin 50 Da, MS1 range end 1000 Da, MSMS range begin 50 Da, MSMS range end 1000 Da, Isotope recognition: max charge number 2.

Peak Detection tab

Peak detection parameters: minimum peak height 10000 amplitude, mass slice 0.1 Da

• Advanced:

Smoothing method: linear weighted moving average

Smoothing level: 3 scan

Minimum peak width: 5 scan

MS2Dec tab

Deconvolution parameters: sigma window value 0.5, MS2 abundance cut off 10 amplitude.

• Advanced:

Check Exclude after precursor ion

Keep the isotope ions until 0.5 Da

Check Keep the isotopic ions w/o MS2Dec

Identification tab

MSP file and MS/MS identification setting: add MSP file downloaded Positive or Negative depending on the data that you loaded in the step 04.

Retention time tolerance: 100 min, Accurate mass tolerance (MS1) 0.01 Da, Accurate mass tolerance MS/MS 0.05, Identification score cut off 80%.

• Advanced:

add txt file of an in-house library Positive or Negative depending on the data that you loaded in the step 04.

Retention time tolerance: 0.1 min, Accurate mass tolerance 0.01 Da, Identification score cut off 85%.

Check only report the top hit

Adduct tab

Check [M+H]+

Check [M+H-H2O]+

Check [2M+H]+

Alignment tab

Alignment parameters settings: Under result name add a name for the alignment file, reference file choose one of the QC runs, retention time tolerance 0.05 min, MS1 tolerance 0.015 Da

• Advanced:

Check remove feature based on blank information

Check keep "reference matched" metabolite features

Check keep ''suggested (w/o MS2)" metabolite features

Check keep removable features and assign the tag

Check Gap filling by compulsion

At the bottom

Check together with Alignment

Click "Finish" --> processing will start.

Once the search is finished, click on the name of the file that is showing at the Alignment Navigator

Click Export - Alignment result, choose a folder to save the file, check remove features from blank, and export.

Data can be loaded into Excel/R or any other software environment for further data analysis.

Data Analysis: load data into Excel, filter out: m/z match FALSE and identifcations named w/o MS2. Combine postive and negative identifications removing redundancy and save as txt file. Load the combined non-redundant data into R or the online MetaboAnalyst 6.0 tool.

MetaboAnalyst 6.0 --> statistical analysis

Upload .txt data as peak intensities (check file format), no data filtering, Sample normalization: normalization by median, Data transformation: Log transformation (base 10), no Data Scaling.

At this point there are distinct analyses that can be done, the following is provided by our core as a first-step analysis:

Chemometrics analysis: PCA, PLS-DA with importance measures using VIP.

Univariate analysis: fold change and t-test -> volcano plot (two groups comparisons).

Clustering analysis: heatmap.