A Versatile Multiplexed Immunofluorescence Strategy for Efficient, Host-Independent, and Scalable Spatial Protein...

Area of Science:

• Spatial biology
• Immunofluorescence techniques
• Proteomics

Background:

• Current immunofluorescence (IF) methods face barriers like host-species constraints, lengthy workflows, and limited flexibility.
• Direct IF requires chemical conjugation, leading to weaker signals and fixed pairings.
• Antibody-nanobody complexes offer host independence but have inconsistent performance.

Purpose of the Study:

• To introduce umIF, a strategy leveraging macromolecular crowding to enhance IF labeling efficiency.
• To enable robust, host-independent multiplexing across diverse IF workflows.
• To improve accessibility and scalability of spatial proteomics.

Main Methods:

• Leveraging macromolecular crowding to enhance labeling efficiency in immunofluorescence.
• Utilizing antibody-nanobody complexes for host-independent multiplexing.
• Applying umIF to single- and multicycle imaging in human tissues and mouse models.

Main Results:

• umIF enhances labeling efficiency across direct, one-step, and two-step IF workflows.
• Improved detection of weak targets and robust multiplexing with antibody-nanobody complexes.
• Demonstrated umIF in human and mouse samples, revealing tissue organization in normal and disease states.

Conclusions:

• umIF is a versatile and accessible method for scalable spatial proteomics.
• The technique lowers adoption barriers for research and clinical laboratories.
• Enhances high-content spatial biology through improved IF performance.