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Background Data-dependent, bottom-up proteomics is widely used for identifying proteins and peptides. However, one key challenge is that 70% of fragment ion spectra consistently fail to be assigned by conventional database searching. This ‘dark matter’ of bottom-up proteomics seems to affect fields where non-model organisms, low-abundance proteins, non-tryptic peptides, and complex modifications may be present. While palaeoproteomics may appear as a niche field, understanding and reporting unidentified ancient spectra require collaborative innovation in bioinformatics strategies. This may advance the analysis of complex datasets. Methods 14.97 million high-impact ancient spectra published in Nature and Science portfolios were mined from public repositories. Identification rates, defined as the proportion of assigned fragment ion spectra, were collected as part of deposited database search outputs or parsed using open-source python packages. Results and Conclusions We report that typically 94% of the published ancient spectra remain unidentified. This phenomenon may be caused by multiple factors, notably the limitations of database searching and the selection of user-defined reference data with advanced modification patterns. These ‘spectra without stories’ highlight the need for widespread data sharing to facilitate methodological development and minimise the loss of often irreplaceable ancient materials. Testing and validating alternative search strategies, such as open searching and de novo sequencing, may also improve overall identification rates. Hence, lessons learnt in palaeoproteomics may benefit other fields grappling with challenging data.

Bacteria play an important role in the degradation of bone material. However, much remains to be learnt about the structure of their communities in degrading bone, and how the depositional environment influences their diversity throughout the exposure period. We genetically profiled the bacterial community in an experimental series of pig bone fragments (femur and humeri) deposited at different well-defined environments in Denmark. The bacterial community in the bone fragments and surrounding depositional environment were studied over one year, and correlated with the bioerosion damage patterns observed microscopically in the bones. We observed that the bacterial communities within the bones were heavily influenced by the local microbial community, and that the general bone microbial diversity increases with time after exposure. We found the presence of several known collagenase producing bacterial groups, and also observed increases in the relative abundance of several of these in bones with tunneling. We anticipate that future analyses using shotgun metagenomics on this and similar datasets will be able to provide insights into mechanisms of microbiome driven bone degradation.

We present the analysis of an osseous finger ring from a predominantly early Neolithic context in Denmark. To characterize the artefact and identify the raw material used for its manufacture, we performed micro-computed tomography scanning, zooarchaeology by mass spectrometry (ZooMS) peptide mass fingerprinting, as well as protein sequencing by liquid chromatography tandem mass spectrometry (LC-MS/MS). We conclude that the ring was made from long bone or antler due to the presence of osteons (Haversian canals). Subsequent ZooMS analysis of collagen I and II indicated that it was made from Alces alces or Cervus elaphus material. We then used LC-MS/MS analysis to refine our species identification, confirming that the ring was made from Cervus elaphus, and to examine the rest of the proteome. This study demonstrates the potential of ancient proteomics for species identification of prehistoric artefacts made from osseous material.