We’re talking mass spectrometry rather than submarines, but how does it work, what are the advantages and who can benefit? We catch up with Jim Langridge (Director, Scientific Operations) and John Chipperfield (Senior Systems Evaluation Scientist) to find out.
John Chipperfield, Jim Langridge | 07/21/2017
With John Chipperfield, Senior Systems Evaluation Scientist at Waters.
SONAR is an elegant solution to a very specific problem; if you’ve got high complexity in your sample and you need more reliable information, then this is the mode for you. SONAR is a data independent acquisition mode that generates MS/MS data – at UPLC speeds – for everything in the sample indiscriminately, using a resolving quadrupole that scans rapidly over a given mass range. Essentially, SONAR enables users to quantify and identify components from a single injection. It’s actually a pretty straightforward implementation of a simple idea – it just so happens that it’s very powerful.
For users to be able to stay ahead of the game, they need to be able to achieve more with less time – and that means gaining as much information from a single analysis as possible. But there’s an important point to make here: speed is nothing without confidence and reliability. Analysts need to be able to trust their data – they need to know that they have correctly identified a given compound – and that’s a crucial issue that we aimed to address with the SONAR acquisition mode.
SONAR is an incredibly powerful qualitative technique that can generate a tremendous amount of information for a given sample – and it does this faster and much more thoroughly than you could before. But, to reiterate, you can also pull quantitative information straight out of that dataset. Importantly, it’s just as easy to process SONAR data as any other data that we produce – you can just plug it into Progenesis or UNIFI. And having listened to our customers, we’ve also made it compatible with third-party software – Skyline from the MacCoss lab, for example.
If we compare SONAR with our major competitor in the area of data independent acquisition, there’s an important distinction to make: because we can scan so fast using a resolving quadrupole, we gain selectivity and we’re able to assign fragments to precursors very accurately. But we’re also able to do it quickly enough to get the optimum number of points across a peak to enable quantification. I don’t think our competitors can match up on that particular aspect.
SONAR is a simple concept – why has it not been done before?
It is simple, but was only made possible by the work we’d done to access data independent acquisition through ion mobility on the SYNAPT platform, which demanded the development of a novel acquisition system that could acquire up to 2,000 spectra per second. For the XEVO and SONAR, we basically used the same acquisition system but, instead of using ion mobility, we used a scanning quad in front of the time-of-flight, which allows us to store data in 200 bins per quad scan. In other words, the idea is simple, but the execution was only made possible by a very talented development team!
Who’s most excited by the potential of SONAR?
Definitely the lipidomics community, where we feel there is a big opportunity in terms of an unmet need, namely increased selectivity. Lipids are very close in mass-to-charge, and there are many structural isomers. SONAR allows you to do one acquisition, but still pull those apart quite nicely. Proteomics is another big area.
We’re also starting to see it move into other areas as we further develop the technique; the mass spectrometry imaging community, for example. We actually had a presentation at ASMS 2017 based on the use of SONAR with DESI imaging.
What about outside of health science?
Environmental analysis and foodomics is a natural progression. Like most technologies, when we first develop them we apply them to the most challenging application area – in this case, proteomics, metabolomics, and lipidomics. But challenges are often mirrored in other fields. Another area that we’re starting to explore is biopharmaceutical characterization. Here, reliability and reproducibility of results is absolutely critical, which plays to the key strength of SONAR.
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