A High-Throughput ImmunoHistoFluorescence (IHF) Method for Sub-Nuclear Protein Analysis in Tissue
The current understanding of cellular protein distribution in clinical samples is limited. This is partially due to the complexity and heterogeneity of tissues combined with the qualitative nature of analysis by immunohistochemistry (IHC). The common use of manual assessment in the clinic is time-co...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-07-01
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| Series: | Cells |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2073-4409/14/14/1109 |
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| Summary: | The current understanding of cellular protein distribution in clinical samples is limited. This is partially due to the complexity and heterogeneity of tissues combined with the qualitative nature of analysis by immunohistochemistry (IHC). The common use of manual assessment in the clinic is time-consuming and restricts both the complexity of scoring and the scale of patient tissue analysis. This has limited the transfer of biological observations into pathology and their integration into diagnostics. Immunofluorescence (IF) techniques allow detailed and high-throughput investigation of proteins in cell models, but their application to tissues has been hindered by poor antibody penetration, autofluorescence artefacts, and weak signals. With a growing focus on precision medicine, scalable techniques to investigate and analyse proteins are critically important. To address this, we generated a high-throughput ImmunoHistoFluorescence (IHF) approach, applying IF to tissue samples followed by automated acquisition and artificial intelligence (AI)-based analysis of sub-nuclear protein distribution to enable precise investigation of complex protein localization patterns. This advancement offers a method to transfer in vitro findings into human tissues to analyse protein localization patterns in physiologically relevant contexts for improved understanding of disease-driving mechanisms in patients, identification of new biomarkers, and acceleration of translational research. |
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| ISSN: | 2073-4409 |