Enhancement of protein detection on cultural heritage samples after SYPRO™ Ruby staining by optical microscopy and micro-FTIR spectroscopy.
Enhancement of protein detection on cultural heritage samples after SYPRO™ Ruby staining by optical microscopy and micro-FTIR spectroscopy.
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通过光学显微镜和显微 FTIR 光谱增强 SYPRO™ 红宝石染色后文化遗产样品的蛋白质检测。
DOI:
10.1016/j.saa.2023.123067
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发表时间:
2023
期刊:
影响因子:
--
通讯作者:
Botticelli M
中科院分区:
文献类型:
--
作者:
Botticelli M
The paper investigates SYPRO™ Ruby staining in combination with external reflection micro-FTIR spectroscopy, for the detection of proteinaceous media in paint layers on cultural heritage, from unembedded micro-fragments and samples embedded in cross-sections. Combining FTIR spectroscopy with staining helped to verify that the FTIR mapping is accurate when performed by the integration of the main amide I and II bands, despite their naturally occurrent distortions due to the specular component and material absorption/surface properties. The research filled some gaps in the published literature on SYPRO™ Ruby interaction with different Cultural Heritage materials, including identifying drawbacks, e.g. swelling mechanisms in the sample after staining. The effects of the staining were investigated on different reference samples containing rabbit skin glue (proteinaceous), and samples from cultural heritage case studies undergoing technical examination as part of research projects, where identification of protein is an important aspect of understanding the sequence of complex multi-layers within a sample. Results showed that, when external reflection µ-FTIR is performed after the staining, the contribution from amide I and II, which occurs at higher wavenumbers than in transmission or attenuated total reflection, is more resolved and therefore easier to determine. When inorganic or organic compounds are present in the same layer, variation in the position of amide bands can occur. However, they can be used for chemical mapping using simple data-treatment strategies, as validated with the positive staining. This type of data processing gives a good estimation of the protein distribution in the layers, both in terms of morphology and thickness, on mock-up samples and cross-sections from real case studies.
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