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Multiplatform Protein Detection and Quantification Using Glutaraldehyde-Induced Fluorescence for 3D Systems

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Abstract

Glutaraldehyde (GTA) is a dialdehyde used as biological fixative and its interaction with proteins like bovine serum albumin (BSA) has been well described. Additionally, GTA is known to induce fluorescence when interacting with BSA molecules. In this work, it is developed a new sensitive and reproducible method for BSA quantification using GTA crosslinking to endow fluorescence to BSA molecules. This method can be used with standard lab equipment, providing a low cost, fast-tracking and straightforward approach for BSA quantification. Techniques such as confocal laser scanning microscopy (CLSM) and spectrofluorometry are applied for quantitative assessment, and widefield fluorescence microscopy for qualitative assessment. Qualitative and quantitative correlations between BSA content and GTA-induced fluorescence are verified. BSA concentrations as low as 62.5 μg/mL are detected using CLSM. This method can be highly advantageous for protein quantification in three-dimensional hydrogel systems, specially to evaluate protein loading/release in protein delivery or molecular imprinting systems.

Preparation and analysis of glutaraldehyde-induced protein-fluorescence in 3D hydrogels. Alginate-methacrylate hydrogels containing varying amounts of bovine serum albumin (BSA) are prepared by photopolymerization and then incubated in glutaraldehyde solutions. Samples observation is performed using confocal laser scanning microscopy, spectrofluorometry and widefield fluorescence microscopy. Data is processed and retrieves a quantitative correlation between protein content and fluorescence levels.

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Acknowledgements

The authors would like to acknowledge FEDER - Fundo Europeu de Desenvolvimento Regional funds through the COMPETE 2020 - Operacional Programme for Competitiveness and Internationalisation (POCI), Portugal 2020, and Portuguese funds through FCT - Fundação para a Ciência e a Tecnologia/ Ministério da Ciência, Tecnologia e Ensino Superior in the framework of the Project PTDC/BBB-BIO/1889/2014, the doctoral grant SFRH/BD/129855/2017 to Mariana I Neves and the contract to Aureliana Sousa in the framework of the project “Institute for Research and innovation in Health Sciences” (POCI-01-0145-FEDER-007274). Marco Araújo gratefully acknowledges Interreg V-A Spain-Portugal (POCTEP) 2014-2020 and FEDER (0245_IBEROS_1_E) for the Postdoctoral grant.

The authors acknowledge the support of Ricardo Vidal from the Biointerfaces and Nanotechnology i3S Scientific Platform, the Bioimaging i3S Scientific Platform, member of the national infrastructure PPBI - Portuguese Platform of Bioimaging (PPBI-POCI-01-0145-FEDER-022122) and Daniela Silva from the Image, Microstructure and Microanalysis Unit (IMCROS) from the Materials Centre of the University of Porto (CEMUP). The authors thank Prof. Nuno Alves from the Centre for Rapid and Sustainable Product Development (CDRSP) of Politécnico de Leiria for the use of the photopolymerization system.

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Author notes

  1. Pedro L. Granja and Aureliana Sousa contributed equally to this work.

Authors and Affiliations

  1. i3S - Instituto de Investigação e Inovação em Saúde, Universidade do Porto, Rua Alfredo Allen 208, 4200-135, Porto, Portugal

    Mariana I. Neves, Marco Araújo, Cristina C. Barrias, Pedro L. Granja & Aureliana Sousa

  2. INEB - Instituto de Engenharia Biomédica, Universidade do Porto, Rua Alfredo Allen 208, 4200-135, Porto, Portugal

    Mariana I. Neves, Marco Araújo, Cristina C. Barrias, Pedro L. Granja & Aureliana Sousa

  3. FEUP- Faculdade de Engenharia da Universidade do Porto, Universidade do Porto, Rua Dr Roberto Frias s/n, 4200-465, Porto, Portugal

    Mariana I. Neves & Pedro L. Granja

  4. ICBAS - Instituto de Ciências Biomédicas Abel Salazar, Universidade do Porto, Rua de Jorge Viterbo Ferreira 228, 4050-313, Porto, Portugal

    Cristina C. Barrias & Pedro L. Granja

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  1. Mariana I. Neves
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  2. Marco Araújo
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  3. Cristina C. Barrias
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  5. Aureliana Sousa
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Correspondence to Aureliana Sousa.

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ESM 1

Alginate methacrylation protocol, example of Mean Gray Value measurement, statistical analysis for CLSM and spectrofluorometry results, quantifications using protein assay commercial kits, spectrofluorometry preliminary assays and minimum protein levels measured by spectrofluorometry. (DOCX 377 kb)

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Neves, M.I., Araújo, M., Barrias, C.C. et al. Multiplatform Protein Detection and Quantification Using Glutaraldehyde-Induced Fluorescence for 3D Systems. J Fluoresc 29, 1171–1181 (2019). https://doi.org/10.1007/s10895-019-02433-w

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  • DOI: https://doi.org/10.1007/s10895-019-02433-w

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