Development of desorption electrospray mass spectrometry (DESI-MS) for analysis of ancient lipids from food residues on archaeological artefacts

Lead Research Organisation: University of York
Department Name: Chemistry


The extraction and mass spectrometric analysis of lipids from archaeological artefacts to gain information regarding the artefact is well established and beginning to be used to tackle high profile archaeological questions of international significance. To realise their full potential, such methods need to be applied to large numbers of artefacts (e.g. ceramic vessels) from a wide range of contexts and sites. However, LC- or derivatisation/GC-MS analyses of these extracts are time consuming and, since generally less than half of such extracts contain detectable lipid levels, often frustrating and wasteful. Consequently, a rapid, convenient, medium throughput approach to screening such extracts and obtaining structural information on their components would greatly facilitate analysis and allow prioritisation of samples for subsequent LC- or GC-MS analysis. DESI enables desorption and MS of analytes under ambient conditions directly from almost any surface. It is simple, sensitive, very rapid, and compatible with MS/MS approaches. We have recognised the potential of DESI-MS for archaeological applications, built a DESI source for our mass spectrometers, and shown its feasibility for lipid analysis from surfaces of typical archaeological materials. Although DESI analysis directly from artefact surfaces is appealing, it is rare that artefacts can be removed from museum collections to the MS lab for analysis. However, removal by experts of small samples of the surface of the ceramic, for extraction and GC- or LC- MS analysis is accepted. Preliminary data show successful direct DESI-MS/MS analysis of very small aliquots of such lipid extracts of archaeological ceramics, dried onto glass or into plastic 60-well plates, as well as DESI-FT-ICR-MS analysis of fatty acids in such extracts. This studentship will thus exploit the state-of-the-art mass spectrometers available in the high technology analytical facility, the York Centre of Excellence in Mass Spectrometry (CoEMS), to develop DESI-MS/MS for the rapid screening and first stage analysis of lipid extracts of archaeological artefacts. The student will optimise DESI-MS/MS for triacylgycerides, fatty acids and sterols in extracts desorbed from glass slides or multi-well plates, using medium and high resolution mass spectrometers, and determine limits of detection. We have archived over 500 lipid extracts from a wide range of ethnographic, historical and archaeological artefacts from different environments, and high temperature-GC and GC-MS data from all samples. The student will access this archive to optimise the approach, and test limits of detection. DESI-MS/MS will then be tested on selected extracts of the several hundred ceramic vessels from the Stonehenge World Heritage Site. Screening these extracts to identify samples for subsequent analysis by GC- and LC-MS will offer a massive saving in resources and investigator time, enabling deeper sampling and thus inference. Application to this high profile site will also 'showcase' the method and expose the student to the wider archaeological community and the media. The CoEMS provides a unique focus for a coherent and innovative programme of training for our PhD students in areas directly relevant to the NERC-RSC initiative, providing graduate level courses tailored specifically to the needs of PhD students working with high technology instrumentation. In addition to the outstanding networking and training opportunities of CoEMS, the student will belong to the Analytical Science and Environmental Chemistry research group, and gain enviable and unusual multidisciplinary training via membership of BioArCh, a joint venture of Archaeology, Biology and Chemistry at York. Our project partners are pioneers in the analysis of lipids from artefacts using established LC- and GC-MS approaches, and also represent the museum user community, further extending the unique training offered by this project.


10 25 50