PEAKS Q – Isobaric Labeling, TMT/iTRAQ


Video Dialogue

PEAKS now contains an excellent tool for quantification by isobaric labelling methods such as TMT and iTRAQ. This video will highlight some of the benefits of this tool and how to use them for your research.

Accuracy and sensitivity is a main focus of this tool. There are three important points to keep in mind to insure accurate and sensitive isobaric labelling results: supporting the most accurate methods such as multi-notch MS3, using computational methods to select only high quality spectra for protein quantification, and reliable protein significance prediction. The next important point when it comes to TMT and iTRAQ is scalability. Currently, the largest number of samples you can use in a single experiment is 10. If more samples are required in the study, multiple experiments must be compared. We will discuss how this can be done with PEAKS.

One of the main problems with isobaric labelling is interference. MS2 spectra can contain signal not only from the target precursor ion, but also interfering contaminants in the sample. Since the whole sample is labelled with the quantification tags, there is no way to separate reporter ion signal from the target and the contaminants. This is simulated by the experiment described here. A yeast digest was labeled using TMT 6plex labels in a relative dilution curve forming the ratio: 10 to 4 to 1 with the three lighter labels and back to 10 using the heavier labels. Human cell line was labelled as well, only using the 3 heaviest labels in the 6plex set to simulate interference. These figures show that using the typical MS2 quantification method the heavier label ratios of the yeast cell lysate would not follow the expected ratio due to human cell line interference. With multi-notch MS3 quantification the resulting MS3 spectrum was observed to produce ratios that closely matched the expected ratios of the yeast digest. So interference was greatly reduced.

PEAKS allows you to analyze multi-notch MS3 data easily. In this example, an 8plex experiment was set up where E.coli digest was set up to follow a 10 to 5 to 2 to 1 using the lighter labels and the reverse for the heavier labels. The four heavier labels were used to simulate contamination with the human cell culture. This is how the results appear in the PEAKS heatmap. Red indicates up regulation, green indicates down regulation. With this type of display it is easy to see that the E.coli proteins follow the expected dilution curve and the human proteins show intense signal in the heavier channels and almost no signal as expected in the lighter channels. We’ll now talk about how to set up this kind of data in PEAKS.

Setting up the project is easy. Click the create project button indicated here and add the data. Enter the enzyme, instrument, and fragmentation type of the MS2 scans. You can then click the data refinement button to proceed through the workflow. When setting up identification parameters it is not necessary to add the labelling tag as a fixed modification if using the workflow. Once you select your method in the quantification step it will automatically be added to the identification search. However, if you are not using the workflow you must remember to add it as a fixed modification. During quantification, first set up first your labelling method. This will make all of the labels appear in the experiment groups. Select all samples and add them to the right with this button. Select the mass error tolerance, in the case of MS3, high resolution mass spectrometry is typically used so a tight error tolerance can be given. Select the mass spectrometry level where the reporter ions should be found. Then select the identification cut off method. This is important for insuring that only high quality peptides will be used for protein quantification. If you chose to use a decoy database, a 1% FDR cut off is recommended. You can then click finish and let PEAKS work! It will create quantification results without any more input.

Another important step in ensuring accurate and sensitive quantification results is selecting high quality spectra. An easy to use display is essential for this so that manual inspection can be used to ensure that the quantification results are reliable. PEAKS does this by putting all the important information in one display. This is the peptide view where all the peptide quantification info can be seen in the top pane. The identification result can be seen in the middle. Then a view of the quantification labels can be seen at the bottom. If MS3 was used, this will be the MS3 scan. If MS2 was used, a zoomed in view of the labels in the MS2 scan will be shown. Also, filters can be used from the summary view to select high quality spectra using this edit button. Identification quality plays a major role in quantification, so set an identification -10lgP threshold. PEAKS also calculates a quality score which considers identification -10lgP, noise around reporter ions, and mass error of the reporter ions. Higher intensity reporter ions are also more reliable, so an intensity threshold can be set. You can set a minimum number of channels as well to prevent missing values from affecting your protein quantification results. Once these filters are set the protein display will only show supporting peptides that pass these filters. These are the high quality peptides that are used for protein ratio calculation. You also have manual control, click the checkbox in the used column to remove a peptide. This will remove it from protein ratio and significance calculation.

Quantification significance is calculated at the protein level. Select either the ANOVA or PEAKS Q significance options. Either one is a calculation of the likelihood that the observed change between conditions is significant. In either case, the -10lg of the p-value is used. So, a cut-off of 20 is suggested. You can also select a Benjamini-Hochberg cut off. Select the modified exclusion checkbox to exclude peptides with variable modifications from protein ratio calculation. Modified peptides have different ionization efficiency than unmodified ones, so we give you the option to exclude them to avoid this from having an effect on your quantification results.

The end result is a confident list of protein quantification results that can then be exported and shared with your colleagues from the summary view.

Now let’s talk about another major problem with isobaric labelling, multiplexing. Since the largest experiment you can currently run is a 10plex experiment, you are limited in the number of samples you can use. So, if more samples are required, more experiments are required. This is when a global reference standard should be used. For example, here 131 is used as a reference to link experiment 1 and 2. 131 in samples 1 and 2 are replicates, so the abundance of the peptides in these two channels should be similar. This means they can be used for inter experiment normalization. Intra experiment normalization methods are provided as well. In this case, two 6 plex experiments were combined together. This allowed us to clearly find several proteins that were consistently differentially expressed between the two experiments.

If you are using this type of experiment it can be configured once quantification is complete from this experiment settings button. From this page select the ‘all experiments’ from the select experiment drop down menu. Select the ‘perform inter experiment normalization’ checkbox, and add all but the reference channels to the right in the experiment groups section. This will insure that only the experimental samples will be shown in the heatmap. In this case, select 131 as the spiked channel for both samples. Then, click the ‘exclude spike channel for significance’ button. The reference channels are not expected to change between experiments and significance is by definition a measure of change. So, including these will negatively impact the significance score. So we give you the opportunity to remove them. The next step is to perform intra experiment normalization. Click the normalization button. From here, select auto normalization. Auto normalization sums the intensity of all reporter ion channels of all quantifiable peptides. This is then used as a global ratio within the experiment. With these options set it is now possible to compare multiple experiments with TMT or iTRAQ labeling.

Thank you for listening; if you’d like to try PEAKS Q with your own data you can request a demo.