12 February / March 2021
It is advantageous to have the combined separation of ‘full scan’ UPLC-IM-MS. Data- independent HDMSE
acquisition, facilitates
generation of data akin to MS/MS, with production of cleaned up precursor/product ion spectra for all components in a sample. The necessity to set up targeted acquisitions and requirement to have specific prior knowledge of a sample’s components is removed.
Using four cumulative metrics precursor ion m/z, product ions m/z, tr
, and CCS; Figure 7. UPLC-IM-MS resolved marker isomers (I) isoorientin, (II) orientin, (III)isovitexin and (IV) vitexin.
CCS values can also increase the identification certainty of ‘known-unknowns’ analytes as well as ‘knowns’. UPLC-IM- CID-MS non-targeted specificity, i.e. CCS measurements and distinctive product ion spectra enabled isomers of unknown identity to be classified as 6-C or 8-C glycosides [25]. Combining retention time, CCS and accurate mass measurement (precursor and product ions), ‘known- unknowns’ enhanced specificity has been attained to facilitate authentication analysis and generate Passiflora species variant profiles, even though the precise nature of each component in molecular terms may not be known. Increased coverage and specificity have been achieved, where 255 isomer pairs were ion mobility separated and 86% of these components detected in only one of the Passiflora variants. The approach is beneficial where high purity reference standards are not available or are expensive. An example of species variant profiles separated by retention time and drift time are shown in Figure 8 for [M-H]- m/z 577.1563 isomers (C27
H30 O14
‘known/unknowns’ and reassignment to ‘knowns’, can be achieved without reliance on analytical standards and has been described in detail elsewhere [19].
Flavonoid CCS libraries can be expanded where experimental CCS information has been compared with CCS prediction values and corresponding structural product ion information compared with historical profiling information. This strategy has been used to re-assign ‘known-unknown’ isomers to ‘knowns’ and expand the known Passiflora speciation fingerprint.
Conclusion ). Identifying
UPLC-IM-MS is a gateway to targeted specificity in non-targeted data independent screening assays. The evolution of data- independent analysis to profile medicinal plant species and complex analysis in itself, has been illustrated for the phytochemical profiling of four Passiflora species. Multifactor identification confidence is achieved using four identification points, comprised of precursor ion/product ion accurate mass, retention time and CCS measurements. As with accurate mass measurements, retention time, CCS measurements are seamlessly generated, to give rise to an additional specificity enhancing descriptor for all components in a sample.
a highly specific (non-targeted) ‘known– unknown’ species dependent fingerprint is created for phytochemical profiling. A vast amount of information is used that would conventionally remain redundant. The information obtained for the additional analyte ‘unknowns’, ‘unknown’ isomers, is used to populate ‘known–unknown’ databases. The strategy is used to extend and enhance speciation profiles, without the necessity to identify all species components. CCS prediction algorithms have evolved and been used to identify ‘known-unknowns’ transforming their assignment to ‘known’. In this research increased coverage and species specificity is achieved using UPLC- IM-MS, where 255 ion mobility separated isomer pairs of ‘known-unknowns’ were detected, of which 86% were specific to one Passiflora variant. Specificity in complex sample analysis is gained through ‘known’ and ‘known-unknown’ profiling.
, m/z and IM drift time is used to separate, coeluting isobaric and isomeric components. IM as a matter of course provides separation (based on size, charge and shape) orthogonal to UPLC (hydrophobicity). Unachievable using accurate mass alone, chromatographically coeluting marker isomers have been differentiated using CCS and separation of distinctive positive/ negative isomeric product ion ratios achieved.
Routine three-dimensional resolution using tr
UPLC afforded a time efficiency gain of 66%
Figure 8. UPLC-IM-MS resolved m/z 577.16 ‘known-unknown’ marker isomers (I) Passiflora edulis, (II) Passiflora caerulea.
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