Life Inside a Dinosaur Bone: a Thriving Microbiome
Bibliographic record
Abstract
Abstract Fossils were long thought to lack original organic material, but the discovery of organic molecules in fossils and sub-fossils, thousands to millions of years old, has demonstrated the potential of fossil organics to provide radical new insights into the fossil record. How long different organics can persist remains unclear, however. Non-avian dinosaur bone has been hypothesised to preserve endogenous organics including collagen, osteocytes, and blood vessels, but proteins and labile lipids are unstable during diagenesis or over long periods of time. Furthermore, bone is porous and an open system, allowing microbial and organic flux. Some of these organics within fossil bone have therefore been identified as either contamination or microbial biofilm, rather than original organics. Here, we use biological and chemical analyses of Late Cretaceous dinosaur bones and sediment matrix to show that dinosaur bone hosts a diverse microbiome. Fossils and matrix were freshly-excavated, aseptically-acquired, and then analysed using microscopy, spectroscopy, chromatography, spectrometry, DNA extraction, and 16S rRNA amplicon sequencing. The fossil organics differ from modern bone collagen chemically and structurally. A key finding is that 16S rRNA amplicon sequencing reveals that the subterranean fossil bones host a unique, living microbiome distinct from that of the surrounding sediment. Even in the subsurface, dinosaur bone is biologically active and behaves as an open system, attracting microbes that might alter original organics or complicate the identification of original organics. These results suggest caution regarding claims of dinosaur bone ‘soft tissue’ preservation and illustrate a potential role for microbial communities in post-burial taphonomy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".