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Credit: Modified version of an image by Elham Karimi and Simon Milette, Walsh and Quail Labs, Rosalind and Morris Goodman Cancer Institute
In an exciting recognition of cutting-edge biological research, Nature Magazine has named spatial proteomics as its Method of the Year 2024, highlighting an approach that’s transforming our understanding of biological complexity. This decision also highlights the growing awareness of the impact that proteomics can have in the scientific community.
What is spatial proteomics?
Spatial proteomics encompasses techniques that allow researchers to map proteins within their natural tissue context. Unlike traditional proteomics methods that analyse cells and proteins in isolation, spatial proteomics provides a detailed, three-dimensional view of protein distribution, interactions, and organisation within cells and tissues.
Techniques in this field include:
- Cyclic immunofluorescence (cycIF)
- Co-detection by indexing (CODEX)
- Imaging mass cytometry (IMC)
- Deep visual proteomics (DVP)
These and further immunohistochemistry-based methods allow researchers to gain detailed insights into cellular environments, revealing how proteins are organised spatially within tissues.
What makes spatial proteomics so exciting
Spatial proteomics has huge potential for improving our understanding of various biological systems. And we’re not the only ones excited by the potential of these techniques. Andreas Metousis, a PhD candidate with Prof. Matthias Mann at the Max Planck Institute of Biochemistry, has been using DVP to make a breakthrough in our understanding and potential treatment of toxic epidermal necrolysis (TEN), a severe drug-induced skin reaction. To Andreas, the development of DVP represents a significant leap forward for proteomics, combining imaging and deep learning with mass spectrometry to provide high-resolution, single-cell type resolved, spatial, and unbiased proteome analysis.
“The impact of spatial proteomics on biomedical research is profound, particularly in understanding diseases like cancer.”
It enables the examination of the tumour microenvironment and the roles that different cell types, such as immune and stromal cells, play in disease progression and therapy resistance. By illuminating these spatial interactions, spatial proteomics can guide the development of targeted therapies designed to interfere with harmful cellular behaviours or enhance beneficial ones, ultimately improving treatment outcomes.
Manuel Matzinger, Senior Core Scientist and Deputy Head of the Proteomic Technology Hub at the Campus Vienna Biocenter, is similarly excited by the possibilities. Asked about the most exciting recent developments in proteomics, Manuel describes the potential of spatially resolved proteomics at the level of few cells to subcellular resolutions, particularly for clinical research and diagnostics.
“This could mean that cellular subpopulations of a tumour could be identified and mapped back to their position within the patient or organ,” he explains. “In combination with AI-based training datasets, this information could be used to predict at a very early stage which part of the tissue is malignant or likely transitioning to be malignant and metastasise.”
“Such information at an early stage could save lives and improve quality of life, which is the most important overall goal of our research efforts.”
Study highlights in 2024
With spatial proteomics techniques rapidly evolving, there were countless exciting studies in 2024 that employ these techniques. In addition to Nordmann et al. (the one we mentioned above, in which Andreas Metousis was involved), here are three further studies that caught our attention:
A workflow tailored for archival tissue
Research by Daucke et al. has been introduced to revolutionise the analysis of Formalin-fixed paraffin-embedded (FFPE) tissues, catering to the intricate demands of spatial proteomics. FFPE tissue, widely employed for its ability to preserve biological specimens, has long posed challenges in extracting molecular information due to the need for substantial sample quantities. This limitation hampers comprehensive retrospective studies, particularly in understanding cell heterogeneity and identifying tissue-specific signatures, crucial in fields such as cancer research.
The newly devised workflow addresses these challenges with remarkable efficiency, even from ultra-low input material. Through meticulous optimisation and validation, the workflow achieves deep proteome coverage across varying sample sizes, from as low as 1,166 µm² to ∼800,000 µm², surpassing previous limitations.
The protocol’s adaptability is showcased in its compatibility with diverse archival tissues, employing stains like EpCAM and H&E. Through Laser Capture Microdissection (LCM), specific cell populations can be isolated, allowing for the identification of tissue-specific signatures and clustering of cell populations.
This transformative approach not only unlocks the potential of FFPE repositories for retrospective studies but also lays the groundwork for broader applications in cancer research and beyond. With its ease of implementation and profound insights into spatial biology, this workflow stands as a valuable tool for researchers seeking comprehensive molecular analysis of FFPE tissues.
A sample preparation workflow for laser microdissection guided ultrasensitive proteomics
An exciting new development in the field of spacial tissue proteomics by Makhmut et. al., from the Coscia lab is presented in Molecular and Cellular Proteomics. Spatial tissue proteomics, which combines whole-slide imaging, laser microdissection, and ultrasensitive mass spectrometry, is a powerful technique for linking cellular phenotypes to functional proteome states in (patho)physiology. However, to be applicable to large patient cohorts, low sample input amounts (e.g single-cell applications), loss-minimised and streamlined end-to-end workflows are crucial.
This study introduces an automated sample preparation protocol for laser microdissected samples utilising the cellenONE® robotic system, which has the capacity to process 192 samples in three hours. After laser microdissection collection directly into the proteoCHIP LF 48 or EVO 96 chip, the optimised protocol facilitates lysis, formalin de-crosslinking, and tryptic digest of low-input archival tissue samples. The seamless integration with the Evosep ONE LC system by centrifugation allows ‘on-the-fly’ sample clean-up, which is particularly pertinent for laser microdissection workflows.
The method is validated in human tonsil archival tissue, where proteomes of spatially-defined B-cell, T-cell, and epithelial microregions of 4,000 μm2 are profiled to a depth of approximately 2,000 proteins with high cell type specificity. Detailed equipment templates and experimental guidelines are provided for broad accessibility. This study is important as it enables high-throughput spatial proteomics analysis of low-input samples, facilitating insights into cellular phenotypes and proteome states in various biological contexts.
Spatial proteomics of single cells and organelles on tissue slides
With every passing year it seems as though our cellular resolution is ever increasing, giving us the ability to unravel mysteries on a smaller and smaller scale . Well, for 2024 we can enter Filter-Aided Expansion Proteomics (FAXP) to the mix for a novel and innovative way to bring us closer to understanding life at its most intricate levels. Developed by a research team out of Westlake University (China), this method is a game-changer for fields like cancer research and personalised medicine.
The Nature Communications article delves into the intricacies of hydrogel-based tissue expansion techniques and how they are being coupled with mass spectrometry (MS) to aid the rapidly developing field of spatial proteomics research. The use of filter tips enabled Dong et al. to achieve high throughput processing without the traditional limitation of sample size.
What will the future of spatial proteomics hold?
With findings like these, it’s no wonder that Nature named spatial proteomics its method of the year in 2024. It’s hard to imagine all the possibilities. Looking ahead, Andreas Metousis comments: “Spatial proteomics is a game-changer for biomedical research. As technology advances, it will continue to unravel the complexities of cellular and tissue organisation, enhancing our understanding of disease mechanisms and playing a pivotal role in personalising medicine.”
We certainly can’t wait to see it evolve.
