Benchmarking the identification of a single degraded protein to explore optimal search strategies for ancient proteins

preprint · bioRxiv · 2023

preprint · bioRxiv · 2023. Ismael Rodriguez Palomo et al. Palaeoproteomics is a rapidly evolving discipline, and practitioners are constantly developing novel…
Date 2023-12-15
Type preprint
Venue bioRxiv
Publisher Cold Spring Harbor Laboratory
Contribution benchmark
DOI 10.1101/2023.12.15.571577
Citations (OpenAlex) 11

Peer-reviewed version: Benchmarking the identification of a single degraded protein to explore optimal search strategies for ancient proteins (2024-11-21, Peer Community Journal)

Abstract

Palaeoproteomics is a rapidly evolving discipline, and practitioners are constantly developing novel strategies for the analyses and interpretations of complex, degraded protein mixtures. The community has also established standards of good practice to interrogate our data. However, there is a lack of a systematic exploration of how these affect the identification of peptides, post-translational modifications (PTMs), proteins and their significance (through the False Discovery Rate) and correctness. We systematically investigated the performance of a wide range of sequencing tools and search engines in a controlled system: the experimental degradation of the single purified bovine β-lactoglobulin (BLG), heated at 95 °C and pH 7 for 0, 4 and 128 days. We target BLG since it is one of the most robust and ubiquitous proteins in the archaeological record. We tested different reference database choices, a targeted dairy protein one, and the whole bovine proteome and the three digestion options (tryptic-, semi-tryptic- and non-specific searches), in order to evaluate the effects of search space and the identification of peptides. We also explored alternative strategies, including open search that allows for the global identification of PTMs based upon wide precursor mass tolerance and de novo sequencing to boost sequence coverage. We analysed the samples using Mascot, MaxQuant, Metamorpheus, pFind, Fragpipe and DeNovoGUI (pepNovo+, DirecTag, Novor), benchmarked these tools and discuss the optimal strategy for the characterisation of ancient proteins. We also studied physicochemical properties of the BLG that correlate with bias in the identification coverage.

Authors

  1. Ismael Rodriguez Palomo · University of Cambridge
  2. Bharath Nair · University of Cambridge, University of Copenhagen
  3. Yun Chiang · University of Copenhagen, Université Côte d’Azur
  4. Joannes Dekker · University of Copenhagen, University of York
  5. Benjamin Dartigues · University of Bordeaux
  6. Meaghan Mackie · National Heritage Council, Novo Nordisk Foundation, University College Dublin, University of Cape Town, University of Copenhagen, University of Turin
  7. Miranda Evans · University of Cambridge, University of York
  8. Ruairidh Macleod · University of Cambridge
  9. Jesper V. Olsen · Novo Nordisk Foundation, University of California San Diego, University of Cape Town, University of Copenhagen
  10. Matthew James Collins · University of Cambridge, University of Copenhagen, University of York

Methods and tools

  • Degraded-protein search strategy benchmark: Benchmarks search strategies for ancient and degraded proteins on a controlled beta-lactoglobulin series, comparing database engines against de novo sequencing through DeNovoGUI (PepNovo+, DirecTag, Novor) to see which recovers coverage as degradation increases.

Data deposited

  • LC-MS/MS and PSM data from “Benchmarking the identification of a single degraded protein to explore optimal search strat (as deposited) · 10.5281/zenodo.10362061

Cites (18)

Seen in the charts

Back to the full map

Back to top