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Robust red FRET sensors using self-associating fluorescent domains.

ABSTRACT: Elucidation of subcellular signaling networks by multiparameter imaging is hindered by a lack of sensitive FRET pairs spectrally compatible with the classic CFP/YFP pair. Here, we present a generic strategy to enhance the traditionally poor sensitivity of red FRET sensors by developing self-associating variants of mOrange and mCherry that allow sensors to switch between well-defined on- and off states. Requiring just a single mutation of the mFruit domain, this new FRET pair improved the dynamic range of protease sensors up to 10-fold and was essential to generate functional red variants of CFP-YFP-based Zn(2+) sensors. The large dynamic range afforded by the new red FRET pair allowed simultaneous use of differently colored Zn(2+) FRET sensors to image Zn(2+) over a broad concentration range in the same cellular compartment.

SUBMITTER: Lindenburg LH

PROVIDER: S-EPMC3826083 | biostudies-literature | 2013 Oct

REPOSITORIES: biostudies-literature

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Robust red FRET sensors using self-associating fluorescent domains.

Lindenburg Laurens H LH Hessels Anne M AM Ebberink Eduard H T M EH Arts Remco R Merkx Maarten M

ACS chemical biology 20130830 10

Elucidation of subcellular signaling networks by multiparameter imaging is hindered by a lack of sensitive FRET pairs spectrally compatible with the classic CFP/YFP pair. Here, we present a generic strategy to enhance the traditionally poor sensitivity of red FRET sensors by developing self-associating variants of mOrange and mCherry that allow sensors to switch between well-defined on- and off states. Requiring just a single mutation of the mFruit domain, this new FRET pair improved the dynamic ...[more]

PMID: 23962156

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Project description:Chromatin is a polymer complex of DNA and proteins that regulates gene expression. The three-dimensional (3D) structure and organization of chromatin controls DNA transcription and replication. High-throughput chromatin conformation capture techniques generate Hi-C maps that can provide insight into the 3D structure of chromatin. Hi-C maps can be represented as a symmetric matrix [Formula: see text], where each element represents the average contact probability or number of contacts between chromatin loci i and j. Previous studies have detected topologically associating domains (TADs), or self-interacting regions in [Formula: see text] within which the contact probability is greater than that outside the region. Many algorithms have been developed to identify TADs within Hi-C maps. However, most TAD identification algorithms are unable to identify nested or overlapping TADs and for a given Hi-C map there is significant variation in the location and number of TADs identified by different methods. We develop a novel method to identify TADs, KerTAD, using a kernel-based technique from computer vision and image processing that is able to accurately identify nested and overlapping TADs. We benchmark this method against state-of-the-art TAD identification methods on both synthetic and experimental data sets. We find that the new method consistently has higher true positive rates (TPR) and lower false discovery rates (FDR) than all tested methods for both synthetic and manually annotated experimental Hi-C maps. The TPR for KerTAD is also largely insensitive to increasing noise and sparsity, in contrast to the other methods. We also find that KerTAD is consistent in the number and size of TADs identified across replicate experimental Hi-C maps for several organisms. Thus, KerTAD will improve automated TAD identification and enable researchers to better correlate changes in TADs to biological phenomena, such as enhancer-promoter interactions and disease states.

Dataset Information

Robust red FRET sensors using self-associating fluorescent domains.

Publications

Robust red FRET sensors using self-associating fluorescent domains.

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