CemOrange2 fusions facilitate multifluorophore subcellular imaging in C. elegans

Area of Science:

• Molecular Biology
• Genetics
• Biophysics

Background:

• Caenorhabditis elegans (C. elegans) is a key model organism for microscopy-based gene function studies due to its genetic tractability and transparency.
• Fluorescent proteins like green fluorescent protein (GFP) enable visualization of subcellular structures and protein localization.
• Expanding the palette of fluorescent proteins facilitates multifluorophore imaging and real-time dynamic studies.

Purpose of the Study:

• To develop and characterize a novel fluorescent protein, CemOrange2, for enhanced imaging in C. elegans.
• To assess the utility of CemOrange2 for subcellular localization and colocalization studies.
• To demonstrate the application of CemOrange2 in monitoring biological pathways and studying genetic variants.

Main Methods:

• Development of a codon-optimized version of Orange2 (CemOrange2) for C. elegans.
• Creation of CemOrange2 fusion constructs with various proteins and targeting sequences.
• Confirmation of subcellular targeting via colocalization with independent markers.
• Demonstration of CemOrange2 utility in monitoring biological pathways, multiplex imaging, and analyzing a specific genetic variant.

Main Results:

• CemOrange2 was successfully codon-optimized and expressed in C. elegans.
• CemOrange2 fusion proteins exhibited distinct localization patterns, confirmed by colocalization.
• The CemOrange2 marker was distinguishable from commonly used fluorophores like GFP, YFP, and mKate2.
• CemOrange2 enabled monitoring of biological pathways, multiplex imaging, and phenotypic analysis of a human ABCA3 orthologue variant.

Conclusions:

• CemOrange2 significantly expands the available fluorescent protein toolkit for C. elegans research.
• This new marker facilitates advanced imaging techniques, including real-time multifluorophore analysis.
• CemOrange2 is a valuable tool for diverse applications in C. elegans, from basic research to disease modeling.