Dataset Information

A novel copper-chelating strategy for fluorescent proteins to image dynamic copper fluctuations on live cell surfaces.

ABSTRACT: Copper is indispensable in most aerobic organisms although it is toxic if unregulated as illustrated in many neurodegenerative diseases. To elucidate the mechanisms underlying copper release from cells, a membrane-targeting reporter which can compete with extracellular copper-binding molecules is highly desirable. However, engineering a reporter protein to provide both high sensitivity and selectivity for copper(ii) has been challenging, likely due to a lack of proper copper(ii)-chelating strategies within proteins. Here, we report a new genetically encoded fluorescent copper(ii) reporter by employing a copper-binding tripeptide derived from human serum albumin (HSA), which is one of the major copper-binding proteins in extracellular environments. Optimized insertion of the tripeptide into the green fluorescent protein leads to rapid fluorescence quenching (up to >85% change) upon copper-binding, while other metal ions have no effect. Furthermore, the high binding affinity of the reporter enables reliable copper detection even in the presence of competing biomolecules such as HSA and amyloid beta peptides. We also demonstrate that our reporter proteins can be used to visualize dynamic copper fluctuations on living HeLa cell surfaces.

SUBMITTER: Choi YA

PROVIDER: S-EPMC5811147 | biostudies-literature | 2015 Feb

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

A novel copper-chelating strategy for fluorescent proteins to image dynamic copper fluctuations on live cell surfaces.

Choi Yoon-Aa YA Keem Joo Oak JO Kim Cha Yeon CY Yoon Hye Ryeon HR Heo Won Do WD Chung Bong Hyun BH Jung Yongwon Y

Chemical science 20141119 2

Copper is indispensable in most aerobic organisms although it is toxic if unregulated as illustrated in many neurodegenerative diseases. To elucidate the mechanisms underlying copper release from cells, a membrane-targeting reporter which can compete with extracellular copper-binding molecules is highly desirable. However, engineering a reporter protein to provide both high sensitivity and selectivity for copper(ii) has been challenging, likely due to a lack of proper copper(ii)-chelating strate ...[more]

PMID: 29560216

Similar Datasets

Project description:The differentiation of induced pluripotent stem cells (iPSCs) into diverse functional cell types provides a promising solution to support drug discovery, disease modeling, and regenerative medicine. However, functional cell differentiation is currently limited by the substantial line-to-line and batch-to-batch variability, which severely impede the progress of scientific research and the manufacturing of cell products. For instance, iPSC-to-cardiomyocyte (CM) differentiation is vulnerable with great sensitivity to inappropriate doses of CHIR99021 (CHIR) that are applied in the initial stage of mesoderm differentiation. Here, by harnessing live-cell bright-field imaging and machine learning (ML), we realize real-time cell recognition in the entire differentiation process, e.g., CMs, cardiac progenitor cells (CPCs), iPSC clones, and even misdifferentiated cells. This enables non-invasive prediction of differentiation efficiency, purification of ML-recognized CMs and CPCs for reducing cell contamination, early assessment of the CHIR dose for correcting the misdifferentiation trajectory, and evaluation of initial iPSC colonies for controlling the start point of differentiation, all of which provide a more invulnerable differentiation method with resistance to variability. Moreover, with the established ML models as a readout for the chemical screen, we identify a CDK8 inhibitor to further improve the cell resistance to the overdose of CHIR. Together, this study indicates that artificial intelligence is able to guide and iteratively optimize iPSC differentiation to achieve consistently high efficiency across cell lines and batches, providing a better understanding and rational modulation of the differentiation process for functional cell manufacturing in biomedical applications. With the assistance of RNA sequencing, we transcriptomically characterize the image-recognized CPCs (IR-CPCs), the cells treated with different CHIR doses at stage I, iPSC-CM treated with or without BI-1347, and cells treated with or without BI-1347 at stage I.

Dataset Information

A novel copper-chelating strategy for fluorescent proteins to image dynamic copper fluctuations on live cell surfaces.

Publications

A novel copper-chelating strategy for fluorescent proteins to image dynamic copper fluctuations on live cell surfaces.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure