MS1 vs. MS2 (or both!)
So far, we’ve explained how mass spectrometry can provide the mass, intensity, and retention time for many molecules in a sample. However, most of the time it’s not possible to identify a molecule using only this information. So what then? This is where MS/MS comes in.
In its first pass, or MS1, a mass spectrometer will measure the mass of the whole molecule. After that, the instrument will break the molecule into smaller pieces, and measure the mass of those fragments in its second pass, MS2. This process not only gives information on the mass of the entire molecule, but will also provide information on the chemical substructures within that molecule.
MS1 and MS2 peaks for the antibiotic azithromycin
The substructure information provided in an MS2 spectrum is often referred to as a molecule’s “chemical fingerprint”. This fingerprint can be compared to the fingerprints of reference molecules to annotate unknown compounds. This process is called library matching, and you can read more about it here.
So when do you need MS2 information? The truth is that in a biological sample, there will be many small molecules with similar (or identical) MS1 masses. Thus, MS2 spectra are essential to accurately annotate metabolites in complex samples. In fact, this information is so important that Ometa Flow only uses samples with MS2 spectra.
Isomers with the same MS1 mass but different MS2 spectra
Compounds with the same molecular formula but different chemical structures are called isomers. If the chemical structures of isomers are different enough, the two compounds will produce different MS2 spectrum and can be differentiated using basic mass spectrometry. However, there are some isomers which differ only in their stereochemistry. In other words, they have the same atoms arranged in the exact same order, but their 3D orientation is different. These molecules are called stereoisomers, and since they will produce the same fragments when broken apart, they cannot be differentiated by MS2 alone.
There are several ways to collect MS2 information:
| Method | Advantages | Disadvantages | Conclusions |
|---|---|---|---|
| MS1+MS2 | MS1 and MS2 collected within same run | MS1 peaks aren't smooth, harder to integrate | Great! |
| MS1, then MS2 | Good MS1 peaks with MS2 information | 2x analysis time MS1 and MS2 peaks don't always match |
Great! |
| MS1, sometimes MS2 | Good MS1 peaks | No MS2 information for most samples | Fine for targeted metabolomics, not for untargeted metabolomics |
Detailed description:
MS1 and MS2 at the same time: Mass spectrometers can be programmed to switch between MS1 and MS2 continuously during a run. This results in linked MS2 and MS1 spectra within each sample. At Ometa Labs, we recommend going this route!
MS1 and MS2 separately: Run each sample twice, once with MS1 and once with MS1+MS2. In some ways, this method is the best of both worlds, producing beautiful MS1 peaks with MS2 information. However, it doubles the time it takes to run your samples, and it can occasionally require some guesswork to match MS2 spectra to their MS1. Ometa Flow provides workflows to merge and analyze this type of data.
MS1 on all samples and MS2 on a few: Here, a couple samples are chosen as “reference” samples and run with MS2, and that MS2 information is used to annotate MS1 peaks in all other samples. This method can work when doing targeted metabolomics, but it should not be used to do untargeted metabolomics. Basically, it assumes that your reference samples are perfectly representative of all your other samples (never a good assumption in biology) and then doesn’t collect crucial information on the majority of your dataset. Again, Ometa Flow requires MS2 for all samples. If you have data that was run in this way, only the samples with MS2 information can be used in Ometa Flow.
But isn’t MS1 more accurate??? You will occasionally hear people say that running MS1 alone produces better quality data. This is because a mass spectrometer running MS1 and MS2 together will need to switch back and forth, and during the milliseconds the instrument is gathering MS2 information, it is not measuring any new MS1 data. In general, this effect can be minimized by optimizing your instrument parameters, and we believe that collecting perfect MS1 peaks is never worth throwing out all your MS2 information. If you’re interested in further technical details on how to minimize this issue, we recommend starting with these two papers:
DDA vs. DIA When you go to your favorite mass spectrometrist and ask for MS/MS (MS1+MS2) data, their first question will be whether you want DDA or DIA. DDA and DIA stand for Data-Dependent-Acquisition and Data-Independent-Acquisition, respectively. While DIA is often preferred in the field of proteomics, DDA is currently the best choice for metabolomics. DIA can improve MS2 coverage for low-abundance molecules, but tools to analyze DIA data in metabolomics are still in their infancy. I could tell you more about the differences between these methods and their advantages/disadvantages, but unless you’re really looking to impress that mass spectrometrist, just ask for DDA.
Have more questions? Contact us.
