An untargeted lipidomic approach for qualitative determination of latent fingermark glycerides using UPLC-IMS-QToF-MSE.
Amanda A FrickWeyermann CélinePublished in: The Analyst (2019)
More detailed fundamental information is required about latent fingermark composition in order to better understand fingermark properties and their impact on detection efficiency, and the physical and chemical changes that occur with time following deposition. The composition of the glyceride fraction of latent fingermark lipids in particular is relatively under-investigated due in part to their high structural variability and the limitations of the analytical methods most frequently utilised to investigate fingermark composition. Here, we present an ultra performance liquid chromatography-ion mobility spectroscopy-quadrupole time-of-flight mass spectrometry (UPLC-IMS-QToF-MSE) method to characterise glycerides in charged latent fingermarks using data-independent acquisition. Di- and triglycerides were identified in fingermark samples from a population of 10 donors, through a combination of in silico fragmentation and monitoring for fatty acid neutral losses. 23 diglycerides and 85 families of triglycerides were identified, with significant diversity in chain length and unsaturation. 21 of the most abundant triglyceride families were found to be common to most or all donors, presenting potential targets for further studies to monitor chemical and physical changes in latent fingermarks over time. Differences in relative peak intensities may be indicative of inter- and intra-donor variability. While this study represents a promising step to obtaining more in-depth information about fingermark composition, it also highlights the complex nature of these traces.
Keyphrases
- liquid chromatography
- mass spectrometry
- simultaneous determination
- fatty acid
- high resolution mass spectrometry
- ms ms
- tandem mass spectrometry
- physical activity
- high resolution
- mental health
- solid phase extraction
- systematic review
- molecular docking
- escherichia coli
- case report
- deep learning
- social media
- kidney transplantation
- big data
- loop mediated isothermal amplification
- high speed