Dataset Information
An ancient residue metabolomics-based method to distinguish use of closely related plant species in ancient pipes
Ontology highlight
ABSTRACT: Residues from ancient artifacts can help identify which plant species were used for their psychoactive properties, providing important information regarding the deep-time co-evolutionary relationship between plants and humans. However, relying on the presence or absence of one or several biomarkers has limited the ability to confidently connect residues to particular plants. We describe a comprehensive metabolomics-based approach that can distinguish closely related species and provide greater confidence in species use determinations. An approximately 1430-year-old pipe from central Washington State not only contained nicotine, but also had strong evidence for the smoking of Nicotiana quadrivalvis and Rhus glabra, as opposed to several other species in this pre-contact pipe. Analysis of a post-contact pipe suggested use of different plants, including the introduced trade tobacco, Nicotiana rustica. Ancient residue metabolomics provides a new frontier in archaeo-chemistry, with greater precision to investigate the evolution of drug use and similar plant-human co-evolutionary dynamics.
INSTRUMENT(S): Liquid Chromatography MS - positive - reverse phase
SUBMITTER: Korey Brownstein
PROVIDER: MTBLS890 | MetaboLights | 2020-07-21
REPOSITORIES: MetaboLights
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| MTBLS890 | Other | |||
| FILES | Other | |||
| a_MTBLS890_LC-MS_positive_reverse-phase_metabolite_profiling.txt | Txt | |||
| i_Investigation.txt | Txt | |||
| m_MTBLS890_LC-MS_positive_reverse-phase_metabolite_profiling_v2_maf.tsv | Tabular |
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Publications
An Ancient Residue Metabolomics-Based Method to Distinguish Use of Closely Related Plant Species in Ancient Pipes.
Frontiers in molecular biosciences 20200626
Residues from ancient artifacts can help identify which plant species were used for their psychoactive properties, providing important information regarding the deep-time co-evolutionary relationship between plants and humans. However, relying on the presence or absence of one or several biomarkers has limited the ability to confidently connect residues to particular plants. We describe a comprehensive metabolomics-based approach that can distinguish closely related species and provide greater c ...[more]
