Flexible Cyclic Immunofluorescence (cyCIF) Using Oligonucleotide Barcoded Antibodies.

Area of Science:

• Biomedical Imaging
• Molecular Biology
• Immunology

Background:

• Highly multiplexed imaging technologies advance understanding of tumor microenvironment interactions.
• Conventional immunostaining has limitations in biomarker labeling and sensitivity.
• Existing multiplexed imaging techniques face challenges like low detection sensitivity and cell loss.

Purpose of the Study:

• To develop and optimize an oligonucleotide antibody barcoding strategy for cyclic immunofluorescence (cyCIF).
• To enhance detection efficiency of low-abundance antigens and improve signal-to-background ratios.
• To preserve tissue and fragile cell sample integrity during multiplexed imaging.

Main Methods:

• Developed and optimized an oligonucleotide antibody barcoding strategy for cyCIF.
• Utilized amplification oligonucleotides to label DNA barcoded antibodies.
• Employed in situ hybridization of fluorescently labeled oligonucleotides for signal amplification.
• Optimized staining parameters including oligonucleotide concentration, temperature, and sequence design.
• Extended barcoding to secondary antibodies for difficult-to-label primary antibodies.

Main Results:

• Achieved signal amplification and increased signal-to-background ratios.
• Demonstrated preservation of tissue and fragile cell sample integrity via UV light treatment.
• Successfully integrated amplification oligonucleotides and secondary antibody barcoding into cyCIF.
• Generated highly multiplexed images using original Ab-oligo cyCIF, novel amplification strategy, and immunofluorescence.

Conclusions:

• The optimized cyCIF strategy with oligonucleotide antibody barcoding significantly enhances detection of low-abundance antigens.
• This technique improves signal amplification and preserves sample integrity, overcoming limitations of existing methods.
• The developed method offers a flexible and robust approach for highly multiplexed imaging in biological research.