Adducts and Ion Mode

Let’s say you’re living your best life, trying to identify tryptophan in some samples. You can’t quite remember the mass, so you head over to your spectral library to look it up. Here, instead of finding a nice, single entry for tryptophan, you find this:

Library spectra of tryptophan.* Fun fact: none of these are the molecular weight of tryptophan (204.22 g/mol).

What? How can one molecule have so many different masses? Is my whole library wrong?

Before you flip over the periodic table, there is a good reason for these discrepancies. 

Mass spectrometers use electrical currents to move molecules around and, ultimately, to measure their mass. Thus, a molecule must have a charge in order to be manipulated and detected by the instrument. One of the most common ways to add charge is by electrospray ionization (ESI). Very simply, ESI uses a combination of voltage, vacuum, and heat to turn neutral molecules in liquid to charged ions in gas. During this process, molecules become charged by the addition or subtraction of an ion. We call this ion an adduct. 

The most common adduct is just hydrogen. Thus, most of the time your measured m/z (mass-to-charge ratio) will be the mass of the neutral molecule (M) plus or minus the mass of hydrogen (H). 

That plus or minus depends on your ion mode. Ion mode refers to whether you applied a positive or negative voltage to create ions. Positive mode applies a positive voltage, leading to positively-charged ions (M+H). Negative mode applies a negative voltage, leading to negatively-charged ions (M-H).** Ion mode is an instrument parameter, so it’s chosen when you run your samples and can’t be changed after that.

One of the most important things to remember about ion mode is that many molecules fragment differently in positive and negative mode. The same compound can produce very different MS2 spectra in different modes. This means that ion mode matters for analysis techniques that rely on MS2 spectral similarity, like molecular networking and library matching. A library spectra collected in negative mode will not match an experimental spectra collected in positive mode. 

Diagram of adduct formation using electrospray ionization in positive mode.

Which ion mode should I use?

Running your data in positive or negative mode can affect which molecules you detect. This is because molecules form ions at different rates under a positive or negative voltage. We call this ionization efficiency.*** For example, if you have a molecule that has a great ionization efficiency in positive mode, you’ll easily detect it even if it’s present in small quantities. If the same molecule has a terrible efficiency in negative mode, you may not detect it at all. 

So what does this mean for you? If there are specific molecules that you want to see, it’s worth doing some literature research to see what parameters work best for those molecules. If you just want to see everything, we suggest running in positive mode. This is not because positive mode is inherently superior, but because the majority of public libraries were collected in positive mode.**** Thus, if you’re using public libraries to annotate your spectra, you’ll likely get more annotations in positive mode.

So far, we’ve discussed hydrogen adducts, but there are many other adducts in mass spectrometry. These range from simple metal ions like M+Na or M+K to more complex ions like M+CH3COO. It’s also possible for molecules to form dimers during ionization, creating adducts such as 2M+H. The type of adducts you’ll see depends on everything from  extraction solvents to voltage to quantum mechanics. While it’s not possible to know exactly which adducts will form before you analyze your data, here are some general principles to keep in mind:

• Don’t use molecular weight to search for a compound in your data. The neutral mass (or molecular weight) of a compound is usually the least likely place to find your compound of interest.

• Don’t assume you didn’t detect a molecule because you couldn’t find its hydrogen adduct. Some molecules “prefer” specific adducts, and it’s possible your molecule of interest just doesn’t form M+/-H.

• If you’re creating a spectral library, include spectra from multiple adducts. Ometa Flow offers a workflow that automatically searches for multiple adducts of a library compound in MS/MS data and adds them to your spectral libraries.

• Keep ionization efficiency in mind. Since different molecules have different ionization efficiencies, they won’t always be detected by the mass spectrometer at the same rate. For example, in the figure above, the green and tan molecules are equally abundant in the original sample. However, since the green molecule ionizes more efficiently than the tan, green produces a much higher signal.

• Don’t compare peak areas between different molecules. Related to the previous point. If you’re looking for metabolites that are up- or down-regulated in different samples, compare the abundance of the same molecule to itself. More specifically, compare the same adduct of the same molecule (or the sum of all adducts of a molecule). You can look at metabolite ratios if you want, but remember that these ratios don’t necessarily reflect the actual concentrations in your samples. If you really need to compare the concentrations of one metabolite to another, you’ll need to run standards for each metabolite across a concentration gradient and calculate absolute concentrations. In other words, you’ll need to run targeted metabolomics. 

Ometa Flow offers several workflows that can help you identify different adducts in your mass spectrometry data. These range from a structure dashboard that will quickly calculate the mass of various adducts to workflows that identify multiple adducts of a library compound in MS/MS data. And while all these adducts can seem daunting at first, I promise that with some experience you’ll learn to…well, at least tolerate them.

*This is a best case scenario. You’ll often find many duplicate entries for a molecule, some of which are useful (eg, the same molecule run on different instruments using different settings) and some of which are not (eg, we just copy/pasted this spectra and added random characters to the name just because). But that’s a subject for its own blog post. 

**It’s also possible to run in switching mode, which switches between positive and negative mode within the same run. If you have data in this format, we highly recommend separating the positive and negative mode spectra before doing networking or annotation. Ometa Flow offers a workflow to separate data run in switching mode. 

***Fun fact: this is what mass spectrometrists are referring to when they talk about how well a molecule “flies”. Also, in the interests of accuracy, positive/negative mode isn’t the only thing that can affect ionization efficiency. Buffer conditions, temperature, and other factors can also play a role. 

****Why? Honestly, I have no idea. But about 60% of the spectra in the public libraries available in Ometa Flow were collected in positive mode, so there is definitely a skew. That said, certain fields tend to prefer certain ion modes. It’s worth checking what people in your field are using. If everyone studying sponges runs in negative mode, then you’re going to get more library annotations running sponge samples in negative mode.

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