Quantifying 13C Labelled Compounds - Targeted Approach

This tutorial demonstrates the basic methods in mzMatch that can be used to quantify the 13C labelling of a given list of compounds. A description of the final output files, and the various plots generated are also provided.

Data files

Five data files of the samples grown in 13C Glucose rich medium were recorded on Orbitrap Exactive mass spectrometer coupled to HPLC chromatography system and will be used in this tutorial. Data files (in mzXML format) are located in folder "NEG" and are organised in two sub-folders (C15 and P15) which represents two different conditions. These data files are the biological replicates of every condition. Download (zip archive, size 116 MB).

R file illustrating the complete pipeline of data processing. It includes settings and parameters for CentWave and mzMatch and all other post-treatment steps. Download


Before going any further, please note that the methods for isotope identification and quantification are based on, and depends on, the PeakML file format and the software mzmatch.R. Therefore, it is imperative to first read and follow the advanced mzmatch.R processing pipeline described at mzmatch.R tutorial until either one of the PeakML files to be processed - final_combined_related.peakml or final_combined_related_identified.peakml - is generated from the raw mzXML files containing labelling data.

Figure 1: The list of compounds to look for labelling.

	"id"	"name"				"formula"		"rt"	"follow"
	"GLU"	"D-Glucose"			"C6H12O6"		13.56	6
	"G6P"	"Glucose phosphate"		"C6H13O9P"		17.12	6
	"GAP"	"D-Glyceraldehyde 3-phosphate"	"C3H7O6P"		18.35	3
	"PEP"	"Phosphoenolpyruvate"		"C3H5O6P"		18.11	3
	"PYR"	"Pyruvate"			"C3H4O3"		6.18	3
	"MAL"	"Malate"			"C4H6O5"		15.6	2
Once the PeakML file is in place, the next step is to prepare the list of metabolites to be scanned for isotope identification, as shown in Figure 1. The first, fourth and fifth columns are not mandatory, nevertheless, the column names must be present. Columns 2 and 3 are self explanatory. Column 4 may contain the approximate standard retention time of the compound as seen on a corresponding chromatographic column. Column 5, named "follow", may be used to specify and plot the labelling of the specified number of carbons in that compound. This file has to be saved in a tab delimited text file format.


Once the PeakML file is generated and the file containing the list of compounds to look for is created, the mzmatch.R function, PeakML.Isotope.TargettedIsotopes, can be used to extract the labelling information for the given compounds. Two output files are created - a .pdf file (Figure 2) containing several plots that describe the pattern of labelling observed, and an excel file that contain either the peak area or peak height of the specified compound in all samples in the PeakML file.

Command usage from R:

		useArea =TRUE,
Figure 2: Various plots presented in the pdf file.

A) Shows the compound name, metabolic formula, mass, standard retention time if provided, and the ionisation. B) In most cases, more than one peak-set will be present in a given mass window. Each of these peak-sets will be plotted on separate pages of the pdf output. Peak-set representing a particular compound can by identified by considering its retention time. C) Unlabelled and labelled peak-sets representing each time-point/sample-group. x and y axes represent peak height and retention time, respectively. Colours are described by the legend in section A, eg., green colour represents the peak for citrate with two carbons labelled. D) Represent the area/height of the peak of each isotope in each sample, normalised to one. x and y axes represent sample and percent peak area/height, respectively. E) Represent the mean peak area/height of the peak of each isotope in each sample group. x and y axes represent sample and mean peak area/height, respectively. F) Represent the mean peak area/height of the peak of the isotope specified by the column "follow" in each sample group. x and y axes represent sample and mean peak area/height, respectively.

Other methods in PeakML.Isotope

A quick summary of the other methods in PeakML.Isotope is given below. These methods can be used for making custom mzmatch.R scripts. Detailed documentation for each method can be accessed by clicking the corresponding link.

  • PeakML.Isotope.filterPeaks: Returns location of peaks in a peak data matrix that fall in the given mass window and retention time window.

  • PeakML.Isotope.getAbunMtxList: Generates a matrix containing the relative abundance of labelled vs unlabelled isotopes based on the the mean of the peaks in each groups.

  • PeakML.Isotope.getChromData: Generates a list of lists containing mass, intensities and retentiontimes of all the isotopes in the isotopeList.

  • PeakML.Isotope.getFCMtx: Returns the trend of labelled or unlabelled carbons in the compound as specified by the “follow” parameter.

  • PeakML.Isotope.getIsotopes: This function will return location of isotope peaks in the peak data matrix that fall in the given mass window and retention time window (if provided).

  • PeakML.Isotope.getMassWindow: Returns the mass window of the isotope of the given mass.

  • PeakML.Isotope.getRatioMtxListReturns a matrix for each peak group, containing the area/height of the peak of each possible isotope in each sample (Ref. Figure 2D). Samples along the columns and isotopes along the rows.

  • PeakML.Isotope.getTrendList: Returns the trend of labelled and unlabelled carbons in the compound.

  • PeakML.Isotope.getTrendMtx: Returns the trend of labelled and unlabelled carbons in the compound, as shown Figure 2E.

  • PeakML.Isotope.plotSamples: Plots the isotopes of the specified compound as a pdf document. The pdf document in which the plots has to be placed has to be initiated prior to calling this function (Ref. Figure 2).

  • PeakML.Isotope.processTargettedIsotopesRead the compound id, name and formula from a file and process the plot for all isotopes for that compound. The resulting pdf is stored in the given filename at the given location (Ref. Figure 2).

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