Proteinase-sculptured 3D-printed graphene/polylactic acid electrodes as potential biosensing platforms: Towards enzymatic modeling of 3D-printed structures

Carmen Lorena Manzanares-Palenzuela, Sona Hermanova, Zdenek Sofer, Martin Pumera

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61 Citations (Scopus)

Abstract

3D printing technologies are currently appealing for the research community due to their demonstrated versatility for different scientific applications. One of the most commonly used materials for 3D printing is polylactic acid (PLA), a biodegradable polymer that can be fully or partially digested by enzymes such as proteinase K. This work seeks to exploit PLA's biodegradability to selectively and reproducibly sculpt 3D-printed graphene/PLA surfaces to turn them into sensitive electroactive platforms. Proteinase K-catalyzed digestion of 3D-printed graphene/PLA electrodes is proposed as an environmentally friendly, highly controllable, and reproducible activation procedure of 3D-printed electrodes. Proteinase K digests PLA in a controllable fashion, exposing electroactive graphene sheets embedded within the 3D-printed structures to the solution and therefore achieving a tailorable electrode performance. A proof-of-concept biosensing application is proposed, based on the immobilization of enzyme alkaline phosphatase at the sculptured electrodes with the subsequent electrochemical detection of 1-naphthol in aqueous media. This work attempts to continue demonstrating the potential of 3D printing in electroanalytical applications, as well as to explore the exciting possibilities arising from merging biotechnological processes with these manufacturing procedures.

Original languageEnglish
Pages (from-to)12124-12131
Number of pages8
JournalNanoscale
Volume11
Issue number25
DOIs
Publication statusPublished - 2019 Jul 7

Bibliographical note

Funding Information:
This work was supported by the project Advanced Functional Nanorobots (reg. no. CZ.02.1.01/0.0/0.0/15_003/0000444 financed by the EFRR). C. L. M. P. acknowledges the financial support of the European Union’s Horizon 2020 Research and innovation programme under the Marie Skłodowska-Curie Actions IF grant agreement no. 795347. Z. S. was supported by the Czech Science Foundation (GACR no. 17-05421S). This work was created with the financial support of the Neuron Foundation for Science.

Publisher Copyright:
© 2019 The Royal Society of Chemistry.

All Science Journal Classification (ASJC) codes

  • Materials Science(all)

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