A Versatile Multiplexed Immunofluorescence Strategy for Efficient, Host‐Independent, and Scalable Spatial Protein Profiling

Immunofluorescence (IF) remains a central method for high-content spatial biology, but current approaches face several technical barriers. Indirect two-step IF is the most widely used but constrained by host-species requirements and lengthy workflows. Direct IF avoids this constraint but requires chemical conjugation of each primary antibody to a fluorophore, resulting in weaker signals, fixed antibody-fluorophore pairings, and reduced flexibility. Antibody-nanobody complexes provide a promising host-independent solution but have been limited by inconsistent performance and reduced efficiency. Commercial spatial biology platforms achieve high-plex imaging, but many rely on costly custom reagents or specialized microfluidics instrumentation, limiting broad accessibility. We introduce umIF, a strategy that leverages macromolecular crowding to enhance labeling efficiency across diverse IF workflows. It enables robust, host-independent multiplexing with antibody-nanobody complexes, while also improving performance across direct, one-step, and two-step IF workflows, including detection of weak targets. We demonstrate both single- and multicycle umIF in human tissue samples and mouse models, revealing epithelial, stromal, immune, and epigenetic organization in normal and disease contexts. umIF provides a versatile and accessible method for scalable spatial proteomics, lowering barriers to adoption in both research and clinical laboratories.

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Publication Details

Journal
Small Methods
Published
2026-06-17
DOI
https://doi.org/10.1002/smtd.202600009
Primary Topic
Monoclonal and Polyclonal Antibodies Research
Type
article
Field-Weighted Citation Impact
0.00

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article

A Versatile Multiplexed Immunofluorescence Strategy for Efficient, Host‐Independent, and Scalable Spatial Protein Profiling

Dimitrios S. Gotsis, Rhonda M. Brand, Marc Schwartz, Tushar Talukder Showrav et al.
Small Methods
Monoclonal and Polyclonal Antibodies Research
article

A Versatile Multiplexed Immunofluorescence Strategy for Efficient, Host‐Independent, and Scalable Spatial Protein Profiling

Dimitrios S. Gotsis, Rhonda M. Brand, Marc Schwartz, Tushar Talukder Showrav, Maomao Chen, Robert E. Schoen, Hongqiang Ma, Yang Liu, Hu Zhang, Phuong Nguyen, Brenda Diergaarde, Chaojie Zhang
article en

Abstract

Immunofluorescence (IF) remains a central method for high-content spatial biology, but current approaches face several technical barriers. Indirect two-step IF is the most widely used but constrained by host-species requirements and lengthy workflows. Direct IF avoids this constraint but requires chemical conjugation of each primary antibody to a fluorophore, resulting in weaker signals, fixed antibody-fluorophore pairings, and reduced flexibility. Antibody-nanobody complexes provide a promising host-independent solution but have been limited by inconsistent performance and reduced efficiency. Commercial spatial biology platforms achieve high-plex imaging, but many rely on costly custom reagents or specialized microfluidics instrumentation, limiting broad accessibility. We introduce umIF, a strategy that leverages macromolecular crowding to enhance labeling efficiency across diverse IF workflows. It enables robust, host-independent multiplexing with antibody-nanobody complexes, while also improving performance across direct, one-step, and two-step IF workflows, including detection of weak targets. We demonstrate both single- and multicycle umIF in human tissue samples and mouse models, revealing epithelial, stromal, immune, and epigenetic organization in normal and disease contexts. umIF provides a versatile and accessible method for scalable spatial proteomics, lowering barriers to adoption in both research and clinical laboratories.

Small Methods
University of Illinois Urbana-Champaign (US), University of Pittsburgh (US), University of Pittsburgh Medical Center (US)
National Institutes of Health
Openalex Percentile: Top 7%
Monoclonal and Polyclonal Antibodies Research
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