Optimization of protein extraction and ELISA immunodetection from protein-based paint models with mesoporous silica nanoparticles and MCM41

Detalhes bibliográficos
Autor(a) principal: Goyal, Aditya
Data de Publicação: 2021
Outros Autores: Salvador, Cátia, Mathe, Carole, Candeias, António, Caldeira, A. Teresa
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10174/31938
https://doi.org/Goyal AS, Salvador C, Mathe C, Candeias A, Caldeira AT (2021). Optimization of protein extraction and ELISA immunodetection from protein-based paint models with mesoporous silica nanoparticles and MCM41. The European Physical Journal Plus, 136: 691 https://doi.org/10.1140/epjp/s13360-021-01628-0
https://doi.org/10.1140/epjp/s13360-021-01628-0
Resumo: Protein-based biological materials such as albumin, casein and collagen are found in various cultural heritage (CH) artefacts. This study focuses on the study of protein binders from easel paintings media. Proteins have complex structures which are difficult to identify with non-invasive spectroscopic methods (FT-IR, Raman, UV). Immunoassays such as ELISA determine the protein’s source of origin which is necessary for art objects. To increase the detection and identification of proteins by immunoassays, the efficiency of micro-extraction of proteins from heritage materials is a crucial step. Extractions mediated by cycles of orbital agitation and ultrasonic radiation give the possibility to extract proteins from easel painting sample. In this work, protein-based paint models coupled with silica nanoparticles were used for micro-extraction. Nanoparticles possess high surface-to-volume ratios that can attach bioactive molecules such as proteins and increase the total protein recovered from microsamples. Protein extracts were quantified with Bradford Assay in the presence of Coomassie blue. The protein recovery results were statistically computed, and the SPSS analysis shows significant (p <0.05) increase in protein recovery, above 1.3 times for NPSiO2 and above 1.6 times for MCM-41. The statistical data shows evidence that silica nanoparticles intensify the total protein recovered from paint microsamples. Finally, ELISA was realized on the protein extracts to verify and compare the immunodetection of protein from the paint models with and without the use of silica nanoparticles.
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spelling Optimization of protein extraction and ELISA immunodetection from protein-based paint models with mesoporous silica nanoparticles and MCM41Protein-based biological materials such as albumin, casein and collagen are found in various cultural heritage (CH) artefacts. This study focuses on the study of protein binders from easel paintings media. Proteins have complex structures which are difficult to identify with non-invasive spectroscopic methods (FT-IR, Raman, UV). Immunoassays such as ELISA determine the protein’s source of origin which is necessary for art objects. To increase the detection and identification of proteins by immunoassays, the efficiency of micro-extraction of proteins from heritage materials is a crucial step. Extractions mediated by cycles of orbital agitation and ultrasonic radiation give the possibility to extract proteins from easel painting sample. In this work, protein-based paint models coupled with silica nanoparticles were used for micro-extraction. Nanoparticles possess high surface-to-volume ratios that can attach bioactive molecules such as proteins and increase the total protein recovered from microsamples. Protein extracts were quantified with Bradford Assay in the presence of Coomassie blue. The protein recovery results were statistically computed, and the SPSS analysis shows significant (p <0.05) increase in protein recovery, above 1.3 times for NPSiO2 and above 1.6 times for MCM-41. The statistical data shows evidence that silica nanoparticles intensify the total protein recovered from paint microsamples. Finally, ELISA was realized on the protein extracts to verify and compare the immunodetection of protein from the paint models with and without the use of silica nanoparticles.The European Physical Journal Plus2022-04-29T09:25:27Z2022-04-292021-06-25T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://hdl.handle.net/10174/31938https://doi.org/Goyal AS, Salvador C, Mathe C, Candeias A, Caldeira AT (2021). Optimization of protein extraction and ELISA immunodetection from protein-based paint models with mesoporous silica nanoparticles and MCM41. The European Physical Journal Plus, 136: 691 https://doi.org/10.1140/epjp/s13360-021-01628-0http://hdl.handle.net/10174/31938https://doi.org/10.1140/epjp/s13360-021-01628-0eng691The European Physical Journal Plus136asg@uevora.ptcscs@uevora.ptndcandeias@uevora.ptatc@uevora.pt303Goyal, AdityaSalvador, CátiaMathe, CaroleCandeias, AntónioCaldeira, A. Teresainfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-01-03T19:32:03Zoai:dspace.uevora.pt:10174/31938Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T01:21:01.225834Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Optimization of protein extraction and ELISA immunodetection from protein-based paint models with mesoporous silica nanoparticles and MCM41
title Optimization of protein extraction and ELISA immunodetection from protein-based paint models with mesoporous silica nanoparticles and MCM41
spellingShingle Optimization of protein extraction and ELISA immunodetection from protein-based paint models with mesoporous silica nanoparticles and MCM41
Goyal, Aditya
title_short Optimization of protein extraction and ELISA immunodetection from protein-based paint models with mesoporous silica nanoparticles and MCM41
title_full Optimization of protein extraction and ELISA immunodetection from protein-based paint models with mesoporous silica nanoparticles and MCM41
title_fullStr Optimization of protein extraction and ELISA immunodetection from protein-based paint models with mesoporous silica nanoparticles and MCM41
title_full_unstemmed Optimization of protein extraction and ELISA immunodetection from protein-based paint models with mesoporous silica nanoparticles and MCM41
title_sort Optimization of protein extraction and ELISA immunodetection from protein-based paint models with mesoporous silica nanoparticles and MCM41
author Goyal, Aditya
author_facet Goyal, Aditya
Salvador, Cátia
Mathe, Carole
Candeias, António
Caldeira, A. Teresa
author_role author
author2 Salvador, Cátia
Mathe, Carole
Candeias, António
Caldeira, A. Teresa
author2_role author
author
author
author
dc.contributor.author.fl_str_mv Goyal, Aditya
Salvador, Cátia
Mathe, Carole
Candeias, António
Caldeira, A. Teresa
description Protein-based biological materials such as albumin, casein and collagen are found in various cultural heritage (CH) artefacts. This study focuses on the study of protein binders from easel paintings media. Proteins have complex structures which are difficult to identify with non-invasive spectroscopic methods (FT-IR, Raman, UV). Immunoassays such as ELISA determine the protein’s source of origin which is necessary for art objects. To increase the detection and identification of proteins by immunoassays, the efficiency of micro-extraction of proteins from heritage materials is a crucial step. Extractions mediated by cycles of orbital agitation and ultrasonic radiation give the possibility to extract proteins from easel painting sample. In this work, protein-based paint models coupled with silica nanoparticles were used for micro-extraction. Nanoparticles possess high surface-to-volume ratios that can attach bioactive molecules such as proteins and increase the total protein recovered from microsamples. Protein extracts were quantified with Bradford Assay in the presence of Coomassie blue. The protein recovery results were statistically computed, and the SPSS analysis shows significant (p <0.05) increase in protein recovery, above 1.3 times for NPSiO2 and above 1.6 times for MCM-41. The statistical data shows evidence that silica nanoparticles intensify the total protein recovered from paint microsamples. Finally, ELISA was realized on the protein extracts to verify and compare the immunodetection of protein from the paint models with and without the use of silica nanoparticles.
publishDate 2021
dc.date.none.fl_str_mv 2021-06-25T00:00:00Z
2022-04-29T09:25:27Z
2022-04-29
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10174/31938
https://doi.org/Goyal AS, Salvador C, Mathe C, Candeias A, Caldeira AT (2021). Optimization of protein extraction and ELISA immunodetection from protein-based paint models with mesoporous silica nanoparticles and MCM41. The European Physical Journal Plus, 136: 691 https://doi.org/10.1140/epjp/s13360-021-01628-0
http://hdl.handle.net/10174/31938
https://doi.org/10.1140/epjp/s13360-021-01628-0
url http://hdl.handle.net/10174/31938
https://doi.org/Goyal AS, Salvador C, Mathe C, Candeias A, Caldeira AT (2021). Optimization of protein extraction and ELISA immunodetection from protein-based paint models with mesoporous silica nanoparticles and MCM41. The European Physical Journal Plus, 136: 691 https://doi.org/10.1140/epjp/s13360-021-01628-0
https://doi.org/10.1140/epjp/s13360-021-01628-0
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 691
The European Physical Journal Plus
136
asg@uevora.pt
cscs@uevora.pt
nd
candeias@uevora.pt
atc@uevora.pt
303
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dc.publisher.none.fl_str_mv The European Physical Journal Plus
publisher.none.fl_str_mv The European Physical Journal Plus
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reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
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