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A bacteria colony-based screen for optimal linker combinations in genetically encoded biosensors
BACKGROUND: Fluorescent protein (FP)-based biosensors based on the principle of intramolecular Förster resonance energy transfer (FRET) enable the visualization of a variety of biochemical events in living cells. The construction of these biosensors requires the genetic insertion of a judiciously ch...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2011
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3225322/ https://www.ncbi.nlm.nih.gov/pubmed/22074568 http://dx.doi.org/10.1186/1472-6750-11-105 |
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author | Ibraheem, Andreas Yap, Hongkin Ding, Yidan Campbell, Robert E |
author_facet | Ibraheem, Andreas Yap, Hongkin Ding, Yidan Campbell, Robert E |
author_sort | Ibraheem, Andreas |
collection | PubMed |
description | BACKGROUND: Fluorescent protein (FP)-based biosensors based on the principle of intramolecular Förster resonance energy transfer (FRET) enable the visualization of a variety of biochemical events in living cells. The construction of these biosensors requires the genetic insertion of a judiciously chosen molecular recognition element between two distinct hues of FP. When the molecular recognition element interacts with the analyte of interest and undergoes a conformational change, the ratiometric emission of the construct is altered due to a change in the FRET efficiency. The sensitivity of such biosensors is proportional to the change in ratiometric emission, and so there is a pressing need for methods to maximize the ratiometric change of existing biosensor constructs in order to increase the breadth of their utility. RESULTS: To accelerate the development and optimization of improved FRET-based biosensors, we have developed a method for function-based high-throughput screening of biosensor variants in colonies of Escherichia coli. We have demonstrated this technology by undertaking the optimization of a biosensor for detection of methylation of lysine 27 of histone H3 (H3K27). This effort involved the construction and screening of 3 distinct libraries: a domain library that included several engineered binding domains isolated by phage-display; a lower-resolution linker library; and a higher-resolution linker library. CONCLUSION: Application of this library screening methodology led to the identification of an optimized H3K27-trimethylation biosensor that exhibited an emission ratio change (66%) that was 2.3 × improved relative to that of the initially constructed biosensor (29%). |
format | Online Article Text |
id | pubmed-3225322 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2011 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-32253222011-11-29 A bacteria colony-based screen for optimal linker combinations in genetically encoded biosensors Ibraheem, Andreas Yap, Hongkin Ding, Yidan Campbell, Robert E BMC Biotechnol Research Article BACKGROUND: Fluorescent protein (FP)-based biosensors based on the principle of intramolecular Förster resonance energy transfer (FRET) enable the visualization of a variety of biochemical events in living cells. The construction of these biosensors requires the genetic insertion of a judiciously chosen molecular recognition element between two distinct hues of FP. When the molecular recognition element interacts with the analyte of interest and undergoes a conformational change, the ratiometric emission of the construct is altered due to a change in the FRET efficiency. The sensitivity of such biosensors is proportional to the change in ratiometric emission, and so there is a pressing need for methods to maximize the ratiometric change of existing biosensor constructs in order to increase the breadth of their utility. RESULTS: To accelerate the development and optimization of improved FRET-based biosensors, we have developed a method for function-based high-throughput screening of biosensor variants in colonies of Escherichia coli. We have demonstrated this technology by undertaking the optimization of a biosensor for detection of methylation of lysine 27 of histone H3 (H3K27). This effort involved the construction and screening of 3 distinct libraries: a domain library that included several engineered binding domains isolated by phage-display; a lower-resolution linker library; and a higher-resolution linker library. CONCLUSION: Application of this library screening methodology led to the identification of an optimized H3K27-trimethylation biosensor that exhibited an emission ratio change (66%) that was 2.3 × improved relative to that of the initially constructed biosensor (29%). BioMed Central 2011-11-10 /pmc/articles/PMC3225322/ /pubmed/22074568 http://dx.doi.org/10.1186/1472-6750-11-105 Text en Copyright ©2011 Ibraheem et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Ibraheem, Andreas Yap, Hongkin Ding, Yidan Campbell, Robert E A bacteria colony-based screen for optimal linker combinations in genetically encoded biosensors |
title | A bacteria colony-based screen for optimal linker combinations in genetically encoded biosensors |
title_full | A bacteria colony-based screen for optimal linker combinations in genetically encoded biosensors |
title_fullStr | A bacteria colony-based screen for optimal linker combinations in genetically encoded biosensors |
title_full_unstemmed | A bacteria colony-based screen for optimal linker combinations in genetically encoded biosensors |
title_short | A bacteria colony-based screen for optimal linker combinations in genetically encoded biosensors |
title_sort | bacteria colony-based screen for optimal linker combinations in genetically encoded biosensors |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3225322/ https://www.ncbi.nlm.nih.gov/pubmed/22074568 http://dx.doi.org/10.1186/1472-6750-11-105 |
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