Assessing glutamine deamination in ancient parchment samples
Parchment Glutamine Index (PQI): A novel method to estimate glutamine deamidation levels in parchment collagen obtained from low-quality MALDI-TOF data
Recommendation: posted 12 September 2022, validated 30 September 2022
Data authenticity and approaches to data authentication are crucial issues in ancient protein research. The advent of modern mass spectrometry has enabled the detection of traces of ancient biomolecules contained in fossils, including protein sequences. However, detecting proteins in ancient samples does not equate to demonstrating their endogenous nature: instead, if the mechanisms that drive protein preservation and degradation are understood, then the extent of protein diagenesis can be used for evaluating preservational quality, which in turn may be related to the authenticity of the protein data.
The post-mortem deamidation of asparaginyl and glutamyl residues is a key degradation reaction, which can be assessed effectively on the basis of mass spectrometry data, and which has accrued a long history of research, both in terms of describing the mechanisms governing the reactions and with regard to the best strategies for assessing and quantifying the extent of glutamine (Gln) and asparagine (Asn) deamidation in ancient samples (Pal Chowdhury et al., 2019; Ramsøe et al., 2021, 2020; Schroeter and Cleland, 2016; Simpson et al., 2016; Solazzo et al., 2014; Welker et al., 2016; Wilson et al., 2012).
In their paper, Nair and colleagues (2022) build on this wealth of knowledge and present a tool for quantifying the extent of Gln deamidation in parchment. Parchment is a collagen-based material which can yield extraordinary insights into manuscript manufacturing practices in the past, as well as on the daily lives of the people who assembled and used them (“biocodicology”) (Fiddyment et al., 2021, 2019, 2015; Teasdale et al., 2017). Importantly, the extent of deamidation can be directly related to the quality of the parchment produced: rapid direct deamidation of Gln is induced by the liming process, therefore high extents of deamidation are linked to prolonged exposure to the high pH conditions which are typical of liming, thus implying lower-quality parchment.
Nair et al.’s approach focuses on collagen peptides which are typically detected during MALDI-TOF mass spectrometry analyses of parchment and build a simple three-step workflow able to yield an overall index of deamidation for a sample (the parchment glutamine index - PQI) 一 taking into account that different Gln residues degrade at different rates according to their micro-chemical environment. The first step involves pre-processing the MALDI spectra, since Nair et al. are specifically interested in maximising information which can be obtained by low-quality data. The second step builds on well-established methods for quantifying Q → E from MALDI-TOF data by modelling the convoluted isotope distributions (Wilson et al., 2012). Once relative rates of deamidation in selected peptides within a given sample are calculated, the third step uses a mixed effects model to combine the individual deamidation estimates and to obtain an overall estimate of the deamidation for a parchment sample (PQI).
The PQI can be used effectively for assessing parchment quality, as the authors show for the dataset from Orval Abbey. However, PQI could also have wider applications to the study of processed collagen, which is widely used in the food and pharmaceutical industries. In general, the study by Nair et al. is a welcome addition to a growing body of research on protein diagenesis, which will ultimately improve models for the assessment of the authenticity of biomolecular data in archaeology.
Chowdhury, P.M., Wogelius, R., Manning, P.L., Metz, L., Slimak, L., and Buckley, M. 2019. Collagen deamidation in archaeological bone as an assessment for relative decay rates. Archaeometry 61:1382–1398. https://doi.org/10.1111/arcm.12492
Fiddyment, S., Goodison, N.J., Brenner, E., Signorello, S., Price, K., and Collins, M.J.. 2021. Girding the loins? Direct evidence of the use of a medieval parchment birthing girdle from biomolecular analysis. bioRxiv. https://doi.org/10.1098/rsos.202055
Fiddyment,S., Holsinger, B., Ruzzier, C., Devine, A., Binois, A., Albarella, U., Fischer, R., Nichols, E., Curtis, A., Cheese, E., Teasdale, M.D., Checkley-Scott, C., Milner, S.J., Rudy, K.M., Johnson, E.J., Vnouček, J., Garrison, M., McGrory, S., Bradley, D.G., and Collins, M.J. 2015. Animal origin of 13th-century uterine vellum revealed using noninvasive peptide fingerprinting. Proc Natl Acad Sci U S A 112:15066–15071. https://doi.org/10.1073/pnas.1512264112
Fiddyment, S., Teasdale, M.D., Vnouček, J., Lévêque, É., Binois, A., and Collins, M.J. 2019. So you want to do biocodicology? A field guide to the biological analysis of parchment. Heritage Science 7:35. https://doi.org/10.1186/s40494-019-0278-6
Nair, B., Rodríguez Palomo, I., Markussen, B., Wiuf, C., Fiddyment, S., and Collins, M. Parchment Glutamine Index (PQI): A novel method to estimate glutamine deamidation levels in parchment collagen obtained from low-quality MALDI-TOF data. BiorRxiv, 2022.03.13.483627, ver. 6 peer-reviewed and recommended by Peer community in Archaeology. https://doi.org/10.1101/2022.03.13.483627
Ramsøe, A., Crispin, M., Mackie, M., McGrath, K., Fischer, R., Demarchi, B., Collins, M.J., Hendy, J., and Speller, C. 2021. Assessing the degradation of ancient milk proteins through site-specific deamidation patterns. Sci Rep 11:7795. https://doi.org/10.1038/s41598-021-87125-x
Ramsøe, A., van Heekeren, V., Ponce, P., Fischer, R., Barnes, I., Speller, C., and Collins, M.J. 2020. DeamiDATE 1.0: Site-specific deamidation as a tool to assess authenticity of members of ancient proteomes. J Archaeol Sci 115:105080. https://doi.org/10.1016/j.jas.2020.105080
Schroeter, E.R., and Cleland, T.P. 2016. Glutamine deamidation: an indicator of antiquity, or preservational quality? Rapid Commun Mass Spectrom 30:251–255. https://doi.org/10.1002/rcm.7445
Simpson, J.P., Penkman, K.E.H., and Demarchi, B. 2016. The effects of demineralisation and sampling point variability on the measurement of glutamine deamidation in type I collagen extracted from bone. J Archaeol Sci 69: 29-38. https://doi.org/10.1016/j.jas.2016.02.002
Solazzo, C., Wilson, J., Dyer, J.M., Clerens, S., Plowman, J.E., von Holstein, I., Walton Rogers, P., Peacock, E.E., and Collins, M.J. 2014. Modeling deamidation in sheep α-keratin peptides and application to archeological wool textiles. Anal Chem 86:567–575. https://doi.org/10.1021/ac4026362
Teasdale, M.D., Fiddyment, S., Vnouček, J., Mattiangeli, V., Speller, C., Binois, A., Carver, M., Dand, C., Newfield, T.P., Webb, C.C., Bradley, D.G., and Collins M.J. 2017. The York Gospels: a 1000-year biological palimpsest. R Soc Open Sci 4:170988. https://doi.org/10.1098/rsos.170988
Welker, F., Soressi, M.A., Roussel, M., van Riemsdijk, I., Hublin, J.-J., and Collins, M.J. 2016. Variations in glutamine deamidation for a Châtelperronian bone assemblage as measured by peptide mass fingerprinting of collagen. STAR: Science & Technology of Archaeological Research 3:15–27. https://doi.org/10.1080/20548923.2016.1258825
Wilson, J., van Doorn, N.L., and Collins, M.J. 2012. Assessing the extent of bone degradation using glutamine deamidation in collagen. Anal Chem 84:9041–9048. https://doi.org/10.1021/ac301333t
Beatrice Demarchi (2022) Assessing glutamine deamination in ancient parchment samples. Peer Community in Archaeology, 100019. https://doi.org/10.24072/pci.archaeo.100019
The recommender in charge of the evaluation of the article and the reviewers declared that they have no conflict of interest (as defined in the code of conduct of PCI) with the authors or with the content of the article.
Evaluation round #2
DOI or URL of the preprint: https://www.biorxiv.org/content/10.1101/2022.03.13.483627v3
Version of the preprint: v3
Author's Reply, 22 Aug 2022
Decision by Beatrice Demarchi, posted 07 Aug 2022
I have received some further comments from the reviewers. I will be happy to recommend this preprint as long as you respond to one of the reviewers concerns re the utility of the index and carefully check peptide nomenclature throughout (see below)
Reviewed by anonymous reviewer, 15 Jul 2022
Reviewed by anonymous reviewer, 26 Jul 2022
Evaluation round #1
DOI or URL of the preprint: https://www.biorxiv.org/content/10.1101/2022.03.13.483627v6
Author's Reply, 05 Jul 2022
Decision by Beatrice Demarchi, posted 19 May 2022
I have now received three reviews for your preprint entitled “PARCHMENT GLUTAMINE INDEX (PQI): A NOVEL METHOD TO ESTIMATE GLUTAMINE DEAMIDATION LEVELS IN PARCHMENT COLLAGEN OBTAINED FROM LOW-QUALITY MALDI-TOF DATA”
I am pleased to say that the reviews are mostly positive and recognise the importance of the work, and I agree with them. The reviewers raise valid points on some aspects of the manuscript, mainly concerning the choice of not screening out poorest-quality data. I share such concerns: after all, poor quality data is poor quality data, and no amount of post-acquisition work can really change that (and I agree with the reviewers that most of the data in Fig 2 looks very poor). My suggestion is that the authors provide an explanation of the reasons why looking at poor-quality data (rather than re-analysing samples in order to acquire better spectra and/or discarding the dataset) is deemed so important as to warrant a whole new application for assessing Q → E.
The other main question I have is on the reproducibility of the analytical settings across samples: the manuscript does not provide information on how the dataset was obtained, i.e. sample extraction, preparation, instrument, mass range, suppression, matrix type/concentration, operator(s), number of analytical/biological replicates, laser intensity, number of shots, etc…Maybe I could not find the information, but in any case it should be in the main text.
Another issue I would want to see addressed is that a few years ago Simpson et al published a paper demonstrating that MALDI-TOF is not ideal for Q → E because it underestimates E in peptide mixtures containing the Q and E forms (https://doi.org/10.1002/rcm.8441). While this might not be crucial if comparing relative difference between samples, I would mention this bias and justify why you still want to use MALDI, i.e you want to compare data that’s already been acquired/costs etc.
Finally, can the authors explain how they are separating the signal of parchment quality from that of time/preservation histories? The samples come from the same site, but they will have different post-production “biographies”, which may explain some of the variability observed. Can the authors comment on this? I appreciate that the focus of the manuscript is on the PQI index, but section “Applications of PQI” is a bit generic - the ms would benefit from a more nuanced interpretation of the data.
A general suggestion: refer to J. Gross’s manual for doubts on mass spectrometry terminology https://link.springer.com/book/10.1007/978-3-319-54398-7
I would ask you to revise the manuscript within one month, according to the comments of the three reviewers and the general points I made above, and to submit the revised preprint, along with a detailed point-by-point response. I shall be happy to recommend it, pending suitable revision.
Looking forward to receiving your revised manuscript.
Beatrice Demarchi (Bea)