Session: Session 2

PAMPA: a software suite for peptide markers and taxonomic assignment in ZooMS

ZooMS (ZooArchaeology by Mass Spectrometry) provides a rapid and cost-effective method for the taxonomic identification of ancient animal remains. It is typically conducted by generating mass spectra, followed by a data treatment phase to harness the information provided by the spectra. This analytical phase, however, is an intricate multi-step process that can be both tedious and error-prone. In this study, we introduce a comprehensive software, called PAMPA (Protein Analysis by Mass Spectrometry for Ancient Species), for automating and standardizing this analysis.

The data used provided from modern species produced by the MSAP lab and public data from MALDI TOF and FTICR. PAMPA is written in Python 3.7. It is open source (https://github.com/touzet/pampa) and can be used through a user-friendly web interface featuring intuitive visualization tools for mass spectra, peptide markers  and taxonomies (https://bioinfo.univ-lille.fr/pampa/). 

PAMPA consists of three primary scripts: PAMPA LIGHT for fast and easy species identification using predefined peptide tables and taxonomies, PAMPA CLASSIFY that offers a comprehensive range of advanced options for advanced usage, PAMPA CRAFT that enables the user to define their own markers by creating custom set of peptide tables. The correlation between morphological identification and results obtained by the software is 100% for MALDI data from modern species. To facilitate decision-making, a score is given, a score above 4 identifies the family as taxonomic rank and with more than 6 peptides, the identification reaches the taxonomic rank of the genus. For archeological data from MALDI spectra, PAMPA shows a good correlation between PAMPA results and public data results. Finally, it can find new ZooMS peptide markers by homology from Fasta sequences and a table of known peptides, or use raw tryptic peptides for classification.

PAMPA is a simple and efficient workflow that facilitates the taxonomic identification of MALDI spectra.