Testing the efficacy and comparability of ZooMS protocols on archaeological bone

Area of Science:

• Paleoproteomics
• Zooarchaeology
• Biogeochemistry

Background:

• Collagen peptide mass fingerprinting, or Zooarchaeology by Mass Spectrometry (ZooMS), is crucial for identifying archaeological bone materials.
• Existing ZooMS protocols for collagen extraction and purification vary in efficacy, necessitating direct comparison.
• The single-pot solid-phase-enhance sample preparation (SP3) method is newly applied as a ZooMS protocol.

Purpose of the Study:

• To directly compare the effectiveness of three established ZooMS protocols and one novel SP3-based protocol.
• To evaluate different collagen extraction methods for their suitability across varying bone preservation states.
• To establish a reliable screening criterion for selecting samples with sufficient collagen for successful ZooMS analysis.

Main Methods:

• Analysis of 400 archaeological bone samples from seven sites, dating from ~500,000 to 2000 years ago.
• Application of four distinct ZooMS protocols, including three previously published methods and a new SP3-based approach.
• Utilized percent nitrogen by weight (%N) as a semi-quantitative proxy for collagen content to predict ZooMS success.

Main Results:

• Acid-based ZooMS protocols demonstrated improved success rates for bone samples with low-to-medium collagen preservation.
• A least-destructive protocol using an ammonium bicarbonate buffer proved most effective for well-preserved bones.
• A threshold of 0.26%N was identified as optimal for screening samples, maximizing successful peptide mass fingerprinting identifications.

Conclusions:

• The choice of ZooMS protocol should be tailored to the collagen preservation level of archaeological bone samples.
• Acid-based extraction methods are recommended for enhancing ZooMS identification success in poorly preserved specimens.
• Implementing a 0.26%N screening threshold can significantly optimize the efficiency of ZooMS analyses in archaeological contexts.