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Published December 14, 2022 | Version v1
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Quality control for modern bone collagen stable carbon and nitrogen isotope measurements

Creators

  • 1. Trent University

Description

(1) Isotopic analyses of collagen, the main protein preserved in sub fossil bone and tooth, has long provided a powerful tool for the reconstruction of ancient diets and environments. Although isotopic studies of contemporary ecosystems have typically focused on more accessible tissues (e.g., muscle, hair), there is growing interest in the potential for analyses of collagen because it is often available in hard tissue archives (e.g., scales, skin, bone, tooth), allowing for enhanced long-term retrospective studies. The quality of measurements of the stable carbon and nitrogen isotopic compositions of ancient samples are subject to robust and well-established criteria for detection of contaminants and digenesis. Among these quality control (QC) criteria, the most widely utilized is the atomic C:N ratio (C:NAtomic), which for ancient samples has an acceptable range between  2.9 and 3.6. While this QC criterion was developed for ancient materials, it has increasingly being applied to collagen from modern tissues.

(2) Here we use a large survey of published collagen amino acid compositions (n = 436) from 193 vertebrate species as well as recent experimental isotopic evidence from 413 modern collagen extracts to demonstrate that the C:NAtomic range used for ancient samples is not suitable for assessing collagen quality of modern and archived historical samples.

(3) For modern tissues, collagen C:NAtomic falling outside 3.00–3.30 for fish and 3.00–3.28 for mammals and birds can produce systematically skewed isotopic compositions and may lead to significant interpretative errors. These findings are followed by a review of protocols for improving C:NAtomic criteria for modern collagen extracts.

(4) Given the tremendous conservation and environmental policy-informing potential that retrospective isotopic analyses of collagen from contemporary and archived vertebrate tissues have for addressing pressing questions about long-term environmental conditions and species behaviours, it is critical that QC criteria tailored to modern tissues are established.

Notes

The following documents are included:

Table S1. Amino acid compositions for collagen and non-collagenous proteins collected from published literature. All data are presented as residues/1000. Materials code: 1= bone, 2 = scale, 3=skin. Temperature code: 1 = cold water, 2 = warm water.

Table S2. Statistical results: Shapiro Wilks tests for C:NAtomic for different taxonomic groups.

Table S3. Results for Spearman's ρ tests for collagen δ13C grouped by ascending C:NAtomic

Table S4. Extent to which shifts C:NAtomic (resulting from lipid contamination) affect δ13C. Comparison made with data generated by recent studies (Guiry, et al. 2016; Szpak and Guiry In Prep) on the effects of collagen extractions methods on the elemental and isotopic compositions of 122 bones from 85 fish, mammal, and bird specimens from diverse taxa and environments. Four to five extraction procedures were applied to subsamples from each bone. Within each group of four to five samples per bone, the δ13C of the sample with the lowest C:NAtomic was subtracted from the δ13C of the other samples. Table shows mean difference in δ13C (Δ13C) for analyses binned into groups with ascending C:NAtomic. Spearman's ρ tests identify the point at positive shifts in Δ13C corresponding with increasing C:NAtomic become significant. Statistically significant results in bold.

Table S5. Mean amino acid compositions and corresponding C:NAtomic for vertebrate classes not shown in Table 3

ESM_References: A list of references to the data appearing in Table S1.

Funding provided by: Natural Sciences and Engineering Research Council of Canada
Crossref Funder Registry ID: http://dx.doi.org/10.13039/501100000038
Award Number: RGPIN-2020-04740

Funding provided by: Social Sciences and Humanities Research Council of Canada
Crossref Funder Registry ID: http://dx.doi.org/10.13039/501100000155
Award Number: 430-2017-01120

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