Chromatography Free: It’s Closer Than You Think

In the age of ultra-high-resolution mass spectrometry, why are we still tethered to chromatography? Chromatography not only demands significant resources and time but also poses environmental concerns, all while offering a limited separation power when compared to the capabilities of today’s mass spectrometry (MS) technology. Yet, here we are, with chromatography still embedded in our workflows. Why?

For quality control and simpler analyses, conventional methods such as HPLC-UV or GC-FID undoubtedly make sense. However, in the area of non-targeted analysis, especially for complex samples, MS is usually also coupled with chromatographic pre-separation in order to achieve the required performance. Coupling mass spectrometry with liquid or gas chromatography has long set the standard for non-targeted analysis, but given the advances in MS technology, we must ask ourselves whether this approach is still necessary.

The analysis of non-target molecules is subject to a fixed framework, such as the identification levels defined by researchers such as Emma Schymanski. Her five levels of identification culminate in levels 1 and 2, which require rigorous structural confirmation and increasingly complex MS data to achieve. While MS can provide remarkable information, it often fails in reaching these higher levels of identification in complex samples – unless chromatography steps in to bridge the gap.

Therefore, despite its many limitations, chromatography has proven to be indispensable for complex non-target analysis, as it enables the separation and identification of compounds that are difficult or impossible to distinguish using MS alone. But there are still problems. Even with ultra-high resolution MS, the signal intensity for MS/MS spectra in complex samples is often not sufficient for all signals. To effectively distinguish isobaric compounds, chromatography is often required in addition to MS/MS. However, technical difficulties arise particularly in connection with ultra-high-resolution MS instruments such as orbitraps or FT-ICR-MS. While these systems allow an ultra-high resolution, they are simply too slow to keep up with fast chromatographic separations, so the combination is not ideal.

However, there are promising alternatives on the horizon. Innovations such as the 21 Tesla FT-ICR-MS, equipped with dynamically harmonized FT-ICR cells, offer exceptional resolution and data precision. Systems such as these have demonstrated mass resolutions of up to 80,000,000 at long transient lengths. Alan Marshall's group has demonstrated the potential of this system, but in practice there are still limitations – in particular the narrow width of typical chromatographic peaks, which limits the number of data points collected, which, in addition to the initial cost of such an MS, is a major challenge for widespread application. 

Another fascinating alternative is qTOF-MS in combination with ion mobility spectrometry (IMS). Although qTOF has a lower resolution than FT-ICR-MS, coupling with IMS provides an additional dimension of separation by determining the collision cross section (CCS). This two-dimensional separation effectively compensates for the lower mass resolution of qTOF and significantly increases identification accuracy. 

The growing CCS database, recently expanded to nearly 28,000 entries by Erin Baker's team, is a harbinger of the future of non-target analysis. Coupled with modern ion mobility spectrometers, this growing resource promises to simplify and accelerate identification in non-target analysis. 

With advances such as these, we are moving towards a workflow where chromatography may no longer be required and both depth and specificity in chemical analysis are achieved without the drawbacks of traditional chromatographic techniques. However, this still requires developments in the ion source, as ion suppression – with the most commonly used electrospray ion source, this can easily be 50–90 percent without chromatographic pre-separation, preventing qualitative and, more importantly, quantitative analysis.