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Article: Upconversion optogenetics-driven biohybrid sensor for infrared sensing and imaging

TitleUpconversion optogenetics-driven biohybrid sensor for infrared sensing and imaging
Authors
KeywordsBiohybrid
Graphene transistor
Infrared imaging
Transient receptor potential
Upconversion optogenetics
Issue Date11-Jan-2023
PublisherElsevier
Citation
Acta Biomaterialia, 2023, v. 158, p. 747-758 How to Cite?
Abstract

Living organisms are far superior to state-of-the-art devices in visual perception as they have evolved a wide number of capabilities that encompass our most advanced technologies. By leveraging the performance of living organisms and directly interfacing them with artificial components, it can use the intricacy and metabolic efficiency of biological visual sensing within artificial machines. Inspired by the molecular basis (transient receptor potential, TRP) for infrared detection of pit-bearing organisms, we propose a TRP-like biohybrid sensor by integrating upconversion nanoparticles (UCNP) and optogenetically engineered cells on a graphene transistor for infrared sensing and imaging. The UCNP converts infrared light irradiation into blue light, the blue light activates the cells expressed with channelrhodopsin-2 (ChR2) and induces transmembrane photocurrent, and the photocurrent is detected by a biocompatible graphene transistor. Stepwise and overall experimental results show that, upon infrared light irradiation, the UCNP can rapidly mediate cellular photocurrents, which further translates into the extra output current of the graphene transistor. More notably, the response speed of the biohybrid sensor is 1∼3 orders of magnitude faster than those of TRPs heterologously expressed in cell lines in the literature, which confirms the response time advantage of the combination of UCNP and ChR2 within the sensor in place of TRPs. The biohybrid sensor can successfully image infrared targets, proving the feasibility of developing bionic infrared sensing devices by biohybrid integration of nonliving nanomaterials and biological components. This work opens up an avenue for biohybrid sensors to develop the bionic infrared vision that promisingly reproduces the functional superiority of natural organisms.


Persistent Identifierhttp://hdl.handle.net/10722/331935
ISSN
2023 Impact Factor: 9.4
2023 SCImago Journal Rankings: 1.925
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorYang, Jia-
dc.contributor.authorZu, Lipeng-
dc.contributor.authorLi, Gongxin-
dc.contributor.authorZhang, Chuang-
dc.contributor.authorGe, Zhixing-
dc.contributor.authorWang, Wenxue-
dc.contributor.authorWang, Xiaoduo-
dc.contributor.authorLiu, Bin-
dc.contributor.authorXi, Ning-
dc.contributor.authorLiu, Lianqing-
dc.date.accessioned2023-09-28T04:59:43Z-
dc.date.available2023-09-28T04:59:43Z-
dc.date.issued2023-01-11-
dc.identifier.citationActa Biomaterialia, 2023, v. 158, p. 747-758-
dc.identifier.issn1742-7061-
dc.identifier.urihttp://hdl.handle.net/10722/331935-
dc.description.abstract<div><p>Living organisms are far superior to state-of-the-art devices in visual perception as they have evolved a wide number of capabilities that encompass our most advanced technologies. By leveraging the performance of living organisms and directly interfacing them with artificial components, it can use the intricacy and metabolic efficiency of biological visual sensing within artificial machines. Inspired by the molecular basis (transient <a href="https://www.sciencedirect.com/topics/biochemistry-genetics-and-molecular-biology/receptor-potential" title="Learn more about receptor potential from ScienceDirect's AI-generated Topic Pages">receptor potential</a>, TRP) for infrared detection of pit-bearing organisms, we propose a TRP-like biohybrid sensor by integrating upconversion <a href="https://www.sciencedirect.com/topics/materials-science/nanoparticle" title="Learn more about nanoparticles from ScienceDirect's AI-generated Topic Pages">nanoparticles</a> (UCNP) and optogenetically engineered cells on a graphene transistor for infrared sensing and imaging. The UCNP converts infrared light irradiation into blue light, the blue light activates the cells expressed with channelrhodopsin-2 (ChR2) and induces transmembrane photocurrent, and the photocurrent is detected by a biocompatible graphene transistor. Stepwise and overall experimental results show that, upon infrared light irradiation, the UCNP can rapidly mediate cellular photocurrents, which further translates into the extra output current of the graphene transistor. More notably, the response speed of the biohybrid sensor is 1∼3 orders of magnitude faster than those of TRPs heterologously expressed in cell lines in the literature, which confirms the response time advantage of the combination of UCNP and ChR2 within the sensor in place of TRPs. The biohybrid sensor can successfully image infrared targets, proving the feasibility of developing <a href="https://www.sciencedirect.com/topics/chemical-engineering/bionics" title="Learn more about bionic from ScienceDirect's AI-generated Topic Pages">bionic</a> infrared sensing devices by biohybrid integration of nonliving <a href="https://www.sciencedirect.com/topics/materials-science/nanocrystalline-material" title="Learn more about nanomaterials from ScienceDirect's AI-generated Topic Pages">nanomaterials</a> and biological components. This work opens up an avenue for biohybrid sensors to develop the <a href="https://www.sciencedirect.com/topics/chemical-engineering/bionics" title="Learn more about bionic from ScienceDirect's AI-generated Topic Pages">bionic</a> infrared vision that promisingly reproduces the functional superiority of natural organisms.</p></div>-
dc.languageeng-
dc.publisherElsevier-
dc.relation.ispartofActa Biomaterialia-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.subjectBiohybrid-
dc.subjectGraphene transistor-
dc.subjectInfrared imaging-
dc.subjectTransient receptor potential-
dc.subjectUpconversion optogenetics-
dc.titleUpconversion optogenetics-driven biohybrid sensor for infrared sensing and imaging-
dc.typeArticle-
dc.identifier.doi10.1016/j.actbio.2023.01.017-
dc.identifier.scopuseid_2-s2.0-85147344118-
dc.identifier.volume158-
dc.identifier.spage747-
dc.identifier.epage758-
dc.identifier.eissn1878-7568-
dc.identifier.isiWOS:000942847200001-
dc.identifier.issnl1742-7061-

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