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Engineering genetically encoded FRET-based nanosensors for real time display of arsenic (As(3+)) dynamics in living cells
Arsenic poisoning has been a major concern that causes severe toxicological damages. Therefore, intricate and inclusive understanding of arsenic flux rates is required to ascertain the cellular concentration and establish the carcinogenetic mechanism of this toxicant at real time. The lack of suffic...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6677752/ https://www.ncbi.nlm.nih.gov/pubmed/31375744 http://dx.doi.org/10.1038/s41598-019-47682-8 |
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author | Soleja, Neha Manzoor, Ovais Khan, Parvez Mohsin, Mohd. |
author_facet | Soleja, Neha Manzoor, Ovais Khan, Parvez Mohsin, Mohd. |
author_sort | Soleja, Neha |
collection | PubMed |
description | Arsenic poisoning has been a major concern that causes severe toxicological damages. Therefore, intricate and inclusive understanding of arsenic flux rates is required to ascertain the cellular concentration and establish the carcinogenetic mechanism of this toxicant at real time. The lack of sufficiently sensitive sensing systems has hampered research in this area. In this study, we constructed a fluorescent resonance energy transfer (FRET)-based nanosensor, named SenALiB (Sensor for Arsenic Linked Blackfoot disease) which contains a metalloregulatory arsenic-binding protein (ArsR) as the As(3+) sensing element inserted between the FRET pair enhanced cyan fluorescent protein (ECFP) and Venus. SenALiB takes advantage of the ratiometic FRET readout which measures arsenic with high specificity and selectivity. SenALiB offers rapid detection response, is stable to pH changes and provides highly accurate, real-time optical readout in cell-based assays. SenALiB-676n with a binding constant (K(d)) of 0.676 × 10(−6) M is the most efficient affinity mutant and can be a versatile tool for dynamic measurement of arsenic concentration in both prokaryotes and eukaryotes in vivo in a non-invasive manner. |
format | Online Article Text |
id | pubmed-6677752 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-66777522019-08-08 Engineering genetically encoded FRET-based nanosensors for real time display of arsenic (As(3+)) dynamics in living cells Soleja, Neha Manzoor, Ovais Khan, Parvez Mohsin, Mohd. Sci Rep Article Arsenic poisoning has been a major concern that causes severe toxicological damages. Therefore, intricate and inclusive understanding of arsenic flux rates is required to ascertain the cellular concentration and establish the carcinogenetic mechanism of this toxicant at real time. The lack of sufficiently sensitive sensing systems has hampered research in this area. In this study, we constructed a fluorescent resonance energy transfer (FRET)-based nanosensor, named SenALiB (Sensor for Arsenic Linked Blackfoot disease) which contains a metalloregulatory arsenic-binding protein (ArsR) as the As(3+) sensing element inserted between the FRET pair enhanced cyan fluorescent protein (ECFP) and Venus. SenALiB takes advantage of the ratiometic FRET readout which measures arsenic with high specificity and selectivity. SenALiB offers rapid detection response, is stable to pH changes and provides highly accurate, real-time optical readout in cell-based assays. SenALiB-676n with a binding constant (K(d)) of 0.676 × 10(−6) M is the most efficient affinity mutant and can be a versatile tool for dynamic measurement of arsenic concentration in both prokaryotes and eukaryotes in vivo in a non-invasive manner. Nature Publishing Group UK 2019-08-02 /pmc/articles/PMC6677752/ /pubmed/31375744 http://dx.doi.org/10.1038/s41598-019-47682-8 Text en © The Author(s) 2019 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Soleja, Neha Manzoor, Ovais Khan, Parvez Mohsin, Mohd. Engineering genetically encoded FRET-based nanosensors for real time display of arsenic (As(3+)) dynamics in living cells |
title | Engineering genetically encoded FRET-based nanosensors for real time display of arsenic (As(3+)) dynamics in living cells |
title_full | Engineering genetically encoded FRET-based nanosensors for real time display of arsenic (As(3+)) dynamics in living cells |
title_fullStr | Engineering genetically encoded FRET-based nanosensors for real time display of arsenic (As(3+)) dynamics in living cells |
title_full_unstemmed | Engineering genetically encoded FRET-based nanosensors for real time display of arsenic (As(3+)) dynamics in living cells |
title_short | Engineering genetically encoded FRET-based nanosensors for real time display of arsenic (As(3+)) dynamics in living cells |
title_sort | engineering genetically encoded fret-based nanosensors for real time display of arsenic (as(3+)) dynamics in living cells |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6677752/ https://www.ncbi.nlm.nih.gov/pubmed/31375744 http://dx.doi.org/10.1038/s41598-019-47682-8 |
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