Efficient monitoring of protein ubiquitylation levels using TUBEs-based microarrays

Sonia Serna; Wendy Xolalpa; Valérie Lang; Fabienne Aillet; Patrick England; Niels Reichardt; Manuel Rodriguez

doi:10.1002/1873-3468.12289

Journal articles

Efficient monitoring of protein ubiquitylation levels using TUBEs-based microarrays

Sonia Serna ¹ Wendy Xolalpa ² Valérie Lang ² Fabienne Aillet ² Patrick England ³ Niels Reichardt ^{1, 4, *} Manuel Rodriguez ^{5, 2, 6, *}

* Corresponding author

1 CIC biomaGUNE - Centro de Investigación Cooperativa en Biomateriales

2 Inbiomed [Spain]

3 Institut Pasteur [Paris]

4 CIBER-BBN - Centro de Investigación Biomédica en Red en Bioingeniería, Biomateriales y Nanomedicina

5 ITAV - Institut des Technologies Avancées en sciences du Vivant

6 IPBS - Institut de pharmacologie et de biologie structurale

Abstract : Analyzing protein ubiquitylation changes during physiological or pathological processes is challenging due to its high reversibility and dynamic turnover of modified targets. We have developed a protein microarray to assess endogenous ubiquitylation levels from cell cultures, employing tandem ubiquitin-binding entities (TUBEs) with three or four ubiquitin-associated (UBA) domains as capture probes. Adriamycin (ADR)-stimulated MCF7 cells were used to differentiate protein ubiquitylation levels between cells that are sensitive or resistant to ADR treatment. We show that TUBEs-based microarrays can be used for the analysis of cellular processes regulated by ubiquitylation and for the detection of pathologies with aberrant ubiquitylation levels.

Keywords : Protein microarrays SPR TUBEs UBA domains ubiquitylation

Document type :

Journal articles

Domain :

Life Sciences [q-bio]

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https://hal-pasteur.archives-ouvertes.fr/pasteur-03525440
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Submitted on : Thursday, January 13, 2022 - 7:26:19 PM
Last modification on : Thursday, April 7, 2022 - 10:10:53 AM

Efficient monitoring of protein ubiquitylation levels using TUBEs-based microarrays

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Efficient monitoring of protein ubiquitylation levels using TUBEs-based microarrays

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