Abstract
Skeletal remains are commonly subjected to various analyses, including DNA. As the remains are exposed to taphonomic processes after the death of the organism, their physicochemical structure undergoes alterations. The success and integrity of a DNA analysis is thus conditioned by the preservation state of the sample. In this study, ATR-FTIR spectroscopy with further data exploration was employed to characterize the physicochemical structure of the samples and its correlation with the preservation state of the DNA. The aim was to test the hypothesis that ATR-FTIR–obtained spectra contain enough information to allow classification of the samples based on the preservation of the DNA in the remains.In the study, 138 human bones and teeth originating from the 16th century BC to the 21 st century AD were used. The samples were cleaned and powdered following the established methodological procedures for DNA extraction. DNA was extracted and quantified. The samples were separated into four categories based on the amount of quantified DNA. The remaining powder was analyzed with ATR-FTIR spectroscopy and the spectra obtained were explored to extract physicochemical information. Before the exploration of the acquired data, samples were divided into groups A (n = 107) and B (n = 31). Statistical analyses and machine learning were performed on the group A samples. The protocol was then validated on the group B samples, which served to make predictions on the preservation of the DNA in the remains.The best results were achieved using a random forest learning algorithm employing either normalized spectra, second-derivative spectra, or five highest-ranked ratios. Even though overlapping remained, these findings indicate that ATR-FTIR spectroscopy with further exploration of the data has good potential as a pre-screening method for evaluating DNA preservation in skeletal remains.
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