Introduction
Ceramic vessels together with visible charred food remains (so-called foodcrusts) allow detecting the contents of ancient vessels and offer valuable insights into ancient foodways and economy. Foodcrusts can be subject to lipid residue, bulk stable isotope, proteomic, and microfossil analysis. Food-related biomolecules and microremains also absorb into ceramic surfaces, with the lipids, owing to their hydrophobic and relatively stable nature, being the most preserved. Consequently, ceramic matrices are predominantly analysed for lipid residues using various mass-spectrometry methods, but can also reveal some microfossil records.
The quantity of sample required for successful analysis varies depending on the methodology. Below are rough estimations of required samples as per the analytical method:
- microfossil analysis – 1 mg of foodcrust,
- Proteomic analysis – 10 mg of foodcrust,
- bulk stable isotope analysis (with EA-IRMS) – ca 5 mg of foodcrust;
- lipid residue analysis, ca 20 mg foodcrust; at least 0.5 g of homogenised ceramic powder for acid extraction, and around 1 g for solvent extraction.
Proteomics Data Workflow
Data Acquisition and Export
Data Processing with LC-MS
Analysis Scripts and Computational Tools (MaxQuant, MetaMorpheus
Lipid Data Workflow
In lipid analysis we usually have three steps of workflow generating a series of raw data -> interpreted data -> integrated data.
- Data Acquisition and Export (GC-FID, GC-MS, GC-SIM, GC-C-IRMS)
GC-FID and GC-MS (scan and SIM) data is generated by masshunter software.
For example, there is a sequence of measurements.
Each measurement will generate a folder containing a series of raw data (method acquisition file and data files).
GC-C-IRMS data is generated by Qtegra.
Each sequence produces a single container file (.imexp) that contains all the measurement data. It is not possible to extract individual measurements from this file. The .imexp format can only be opened with Qtegra® software.
After initial checks and corrections in Qtegra®, the relevant data is exported to .xlsx format for calibration and for general accessibility.
It's also possible to export all chromatogram data points, allowing graphs to be reconstructed in Excel (.xlsx) or ohter programs as well.
- Data Analysis and Computational Tools (Mass Hunter, Chem Station, PCA, Clustering, Omnic)
GC-FID/MS raw data is interpreted by masshunter software. We’ll identify the compounds (peaks) in each chromatogram and summarize the compound information in an Excel table (interpreted data).
The interpreted data will be further integrated by statistics or modelling (integrated data).
Data reliability/limitation of method
Quantification is a problem for statistics. Every instrument (GC-MS and GC-C-IRMS) generates data under its specific quantitative scale. We are doing qualitative and semi-quantitative analysis for GC-MS. The interpreted data is usually (1 vs 0) present/absent or the ratio/percentage of two/several compounds. But other analyses like GC-C-IRMS are quantitative, which generate accurate concentration data with exact quantified numbers (for example, 25.68 ‰ of carbon isotopes). It’s hard to do statistics when we integrate qualitative GC-MS data with other quantitative data.