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Analytical and Bioanalytical Chemistry

, Volume 411, Issue 20, pp 5115–5126 | Cite as

Refinement of two-dimensional electrophoresis for vitreous proteome profiling using an artificial neural network

  • Fátima M. Santos
  • Tânia Albuquerque
  • Leonor M. Gaspar
  • João M. L. Dias
  • João P. Castro e Sousa
  • Alberto Paradela
  • Cândida T. Tomaz
  • Luís A. PassarinhaEmail author
Research Paper
  • 46 Downloads

Abstract

Despite technological advances, two-dimensional electrophoresis (2DE) of biological fluids, such as vitreous, remains a major challenge. In this study, artificial neural network was applied to optimize the recovery of vitreous proteins and its detection by 2DE analysis through the combination of several solubilizing agents (CHAPS, Genapol, DTT, IPG buffer), temperature, and total voltage. The highest protein recovery (94.9% ± 4.5) was achieved using 4% (w/v) CHAPS, 0.1% (v/v) Genapol, 20 mM DTT, and 2% (v/v) IPG buffer. Two iterations were required to achieve an optimized response (580 spots) using 4% (w/v) CHAPS, 0.2% (v/v) Genapol, 60 mM DTT, and 0.5% (v/v) IPG buffer at 35 kVh and 25 °C, representing a 2.4-fold improvement over the standard initial conditions of the experimental design. The analysis of depleted vitreous using the optimized protocol resulted in an additional 1.3-fold increment in protein detection over the optimal output, with an average of 761 spots detected in vitreous from different vitreoretinopathies. Our results clearly indicate the importance of combining the appropriate amount of solubilizing agents with a suitable control of the temperature and voltage to obtain high-quality gels. The high-throughput of this model provides an effective starting point for the optimization of 2DE protocols. This experimental design can be adapted to other types of matrices.

Graphical abstract

Keywords

Artificial neural network Gel-based proteomics Ocular pathologies Two-dimensional gel electrophoresis Vitreous 

Abbreviations

2DE

Two-dimensional electrophoresis

ANN

Artificial neural networks

HMW

High-molecular-weight

IAA

Iodoacetamide

IEF

Isoelectric focusing

kVh

Kilovolts hour

LMW

Low-molecular-weight

MMW

Medium-molecular-weight

Notes

Funding information

This project was supported by the University of Beira Interior—Health Sciences Research Centre (CICS). Santos FM received a fellowship (CENTRO-07-ST24-FEDER-002014) and a doctoral fellowship (SFRH/BD/112526/2015) from FCT. Gaspar LM received a fellowship from Novartis Farma-Produtos Farmacêuticos, SA. This work is supported by FEDER funds through the POCI—COMPETE 2020—Operational Programme Competitiveness and Internationalisation in Axis I—Strengthening research, technological development and innovation Project (POCI-01-0145-FEDER-007491) and National Funds by FCT—Foundation for Science and Technology Project (UID/Multi/00709/2013). This work was also supported by the Applied Molecular Biosciences Unit- UCIBIO which is financed by national funds from FCT/MCTES (UID/Multi/04378/2019). CNB-CSIC proteomics lab is a member of Proteored, PRB2-ISCIII and is supported by grant PT13/0001, of the PE I +D+i 2013–2016, funded by ISCIII and FEDER.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Research involving human participants and/or animals

The protocol for sample collection was approved by the Ethics Committee of Leiria-Pombal Hospital, Portugal (Code: CHL-15481). An informed consent from all patients was obtained in agreement with the Declaration of Helsinki.

Supplementary material

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  • Fátima M. Santos
    • 1
    • 2
    • 3
    • 4
  • Tânia Albuquerque
    • 1
  • Leonor M. Gaspar
    • 1
    • 2
  • João M. L. Dias
    • 5
  • João P. Castro e Sousa
    • 1
    • 6
  • Alberto Paradela
    • 7
  • Cândida T. Tomaz
    • 1
    • 2
  • Luís A. Passarinha
    • 1
    • 4
    Email author
  1. 1.CICS-UBI—Health Sciences Research CentreUniversity of Beira InteriorCovilhãPortugal
  2. 2.Chemistry Department, Faculty of SciencesUniversity of Beira InteriorCovilhãPortugal
  3. 3.Laboratory of Pharmacology and Toxicology—UBIMedicalUniversity of Beira InteriorCovilhãPortugal
  4. 4.UCIBIO@REQUIMTE, Departamento de Química, Faculdade de Ciências e TecnologiaUniversidade Nova de LisboaCaparicaPortugal
  5. 5.Cancer Molecular Diagnostics Laboratory, National Institute for Health Research, Biomedical Research CentreUniversity of CambridgeCambridgeUK
  6. 6.Department of OphthalmologyCentro Hospitalar de LeiriaLeiriaPortugal
  7. 7.Unidad de Proteomica, Centro Nacional de BiotecnologíaCSICMadridSpain

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