ChemRICH for Lipids

Signals in a lipidomics dataset may or may not have complete structural information. Many lipid species have been annotated by a scheme using the class, carbon count and degree of saturation. For example, lipid species "PC (48:5)" can be "PC (18:0/20:5)" or "PC (18:1/20:4)". If we don't know the chain position, the naming convention is "PC (18:0_20:5)". It is difficult to get the correct SMILES codes/CID or InChiKey for every lipid species in a lipidomics dataset.

To overcome this, we can use a class level SMILES codes for all the lipids in that class. For example all the TGs with long carbon chains can be presented by one SMILES code, and TGs with short carbon chains by another SMILES code. This will be used by ChemRICH to compute the lipophilicity (xlogp by rCDK) of lipid classes, hence polar lipids are shown on the left side and non-polar lipids are showed on the right side of the ChemRICH impact plot.

The example dataset is prepared from a lipidomics analysis of liver samples from old vs young mouse (LINK). It has 35 classes (Below table). As we can see that it is not possible to get SMILES code for every identified lipid in this dataset. However, we can use class level SMILES codes as shown in the example data file to run the ChemRICH analysis.

Instructions:

You need to make a new folder "ChemRICH for Lipids" or any other preferred name in your computer and then make that folder as a working directory in the RStudio software. Then, download and copy the example dataset to this working directory. After that, run these lines of codes.

source("https://raw.githubusercontent.com/barupal/ChemRICH/master/chemrich_chemical_classes.R ")

load.ChemRICH.Packages()

run_chemrich_chemical_classes(inputfile = "chemrich_input_lipids.xlsx")

The output should look as below figure. Interestingly, in older liver, TG levels were lower in comparison to the younger counterpart.