I have two treatments; resistant and susceptible. I have to use them in control experiments with replications. How I can use iTRAQ based different labelling to those different treatments’s peptides in proteome analysis.
Hi Rudra,
is there a particular reason you wish to use iTRAQ? I only worked with TMT labels so far but I assume it works the same way as with iTRAQ. You simply label each sample with a particular label and then pool all the samples into a single one which you then can measure in a single run on the LC-MS/MS system.
It is important to be aware of some cross channel leaching which might occur during ionization. Hence, you should think carefully on how to distribute your different labels across your samples.
Here is the publication which gives good suggestions how to solve this issue:
Article Multibatch TMT Reveals False Positives, Batch Effects and Mi...
Depending on the number or replicates you have, you should decided which n-plex kit to choose. i.e. if you have 4 replicates per treatment you need at least 8 different labels to measure all your samples in a single MS run. However now you have no channel left for a standard (which I would highly recommend for a robust data normalization across runs). Tools like MSstatsTMT in fact even require a reference channel for normalization in their analysis pipeline.
Therefore you should use something like a 10- or 11-plex kit. I know that TMT kits are available up to 16-plex.
If you have more than 15 samples to measure you would need to decided which n-plex kit is best for your needs and budget. You must use a reference channel standard then throughout your MS runs to correctly normalize and integrate the data afterwards.
With 2 tags, you must run experiments in pairs. As Hannes said above, you can get multiplexed kits, but you get into a LC loading problem when running too many samples simultaneously, reducing your detection dynamic range. You can only put a fixed number of grams of protein on the LC before overloading the column, which means that total must be divided by the number of simultaneous samples, reducing the total protein from each sample. I prefer pairs or quartets. I also suggest switching the tags between the two cohorts for replication (i.e., label 1 cohort 1 vs. label 2 cohort 2, then label 2 cohort 1 and label 1 cohort 2). Its a lot more work, but you need replicates anyway for statistical confidence and it tends to eliminate those spurious false positives that stand out like beacons in PCA analysis, that no one will warn you about. Also remember that these global proteomic experiments just give you suggestions for future validation work. You generally have n 3000 individual peptide features that you are trying to discriminate. You can't really do any statistical analysis on that. Basic chemimetrics principles says a minimum of 3 independent samples for each feature being measured. This is because you need n=3 to before you can estimate the variance.
In itraq experiments, it is important to have 1 control and 3 differently treated samples or samples with different conditions (if 4-plex experiment). You should choose your control carefully and tag it with preferably 114 isobar specially if you plan to run the analysis on mascot. for itraq experiment the steps followed are very important ie 1) Extraction of protein, 2) Digestion of proteins, 3) tagging of peptides of individual samples, 3) Pooling of all 4 isotope labelled samples in similar concentration (important of quantification) 4) perform an SCX to get different fractions (min 5-10) for better coverage. 5) Use a 120-200 min run time if using LC-MS/MS preferably with a MS resolution > 30000 (if possible run the fractions in triplicates). 6) validation of your results by putting the data through a good statistical model.
The advantage of using itraq is that when you're focusing on a certain pathway/ set of differently regulated proteins in different conditions, you can easily get relative quantification with low false discovery rate and better confidence in results. In my experience, the results with itraq experiment can be basis of choosing your proteins for western blotting and it is easier to prepare pathways as well.
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