MS/MS fingerprint comparison between adjacent generations enables substructure identification: Flavonoid glycosides...

Area of Science:

• Metabolomics
• Analytical Chemistry
• Structural Biology

Background:

• Metabolite identification using MS/MS spectrum matching is limited by database constraints, often resulting in "0 hit" matches for complex structures.
• Metabolite conjugation, common in organisms, creates diverse structures composed of multiple substructures, posing challenges for current identification methods.
• Expanding database retrieval to include MS3 spectra can significantly enhance structural annotation potential by identifying these substructures.

Purpose of the Study:

• To investigate the utility of MS3 spectra for metabolite substructure identification, using flavonoid glycosides as a model system.
• To determine if the Y0+ fragment ion from flavonoid glycosides yields an MS3 spectrum comparable to the MS2 spectrum of its corresponding aglycone cation.
• To advance MS/MS spectrum matching for more comprehensive metabolite identification.

Main Methods:

• Utilized a Qtrap-MS system with a linear ion trap to generate specific MS2 and MS3 spectra by controlling excitation energy.
• Focused on the Y0+ fragment ion, derived from neutral loss of glycosyl residues from flavonoid glycosides.
• Compared MS3 spectra of Y0+ ions with MS2 spectra of aglycone cations ([A+H]+), considering both m/z and ion intensity.

Main Results:

• Glycosides with identical aglycones produced consistent MS3 spectra for their Y0+ ions.
• Distinct MS3 spectra for Y0+ ions were observed for glycosides with different or isomeric aglycones.
• Isomeric aglycones themselves generated distinguishable MS2 spectra.
• The MS3 spectra of Y0+ ions from glycosides matched the MS2 spectra of their respective aglycone cations ([A+H]+).

Conclusions:

• Fingerprint comparison between MS3 and MS2 spectra enables structural annotation of metabolite substructures.
• This approach significantly enhances MS/MS spectrum matching capabilities for identifying aglycones and other substructures within flavonoid glycosides.
• The findings pave the way for improved metabolite identification in complex biological samples.