Spatial biology isn’t just limited to transcriptomics. In fact, a vast array of spatial proteomics platforms also exist. But how can you find the right spatial proteomics approach? In this feature, we review the different methodologies, so you can decide which is right for you.
Looking for more information on spatial technology? This feature was written using content from our recent Single-Cell and Spatial Buyer’s Guide, which you can download for FREE here.
Spatial proteomics approaches
Current methodology in the spatial proteomics field can be divided into two categories – methods that use fluorescent antibodies for protein detection and those that rely on mass spectrometry. A further division between the fluorescent methods comes down to whether the system uses conjugated antibodies (tagged with a molecular barcode for the fluorescent imaging) or regular antibodies. Mass-spectrometry methods can be divided based on whether they used metal tagged antibodies to detect targeted proteins in cells, or whether they use one of the varieties of spatial mass spectrometry imaging (SMI) methodologies for unbiased spatial proteomics. Let’s take a look at these methods in more detail.
FIGURE 1. OVERVIEW OF THE MAJOR SPATIAL PROTEOMIC METHODS. (A) Fluorescent-antibody based approaches for targeted profiling. (B) Mass Spectrometry Imaging approaches for unbiased spatial profiling. (C) Imaging Mass Cytometry approaches for targeted, fluorescence-free profiling. Source (Adapted From): Christopher, et al., 2022.
Fluorescence-Base Spatial Proteomics
Historically, spatial proteomics has been limited to fluorescent-based approaches, namely a few fluorescently-labelled antibodies via immunohistochemistry (IHC). While this approach is limited, by taking advantage of high-resolution microscopy, it has been the backbone of spatial proteomics for decades.
The principal limitation with fluorescent proteomic approaches is that the number of proteins that can be probed in one sample is limited by the number of available fluorochromes that can be used, without producing interference or bleed through. This is typically between 4 and 6.
Recent developments in cyclic immunofluorescence and conjugating antibodies with oligos or molecular barcodes has allowed for much improved multiplexing. Many of the popular spatial proteomic platforms work through this sequential imaging method. Tissue is stained either with a small selection of antibodies or a larger set of conjugated antibodies. The fluorescent marker is then added for a small set of targets, binding to the molecular barcode of specific targets or to the small selection of antibodies added. The image is then taken and the fluorescent marker or the antibodies are quenched to allow another round of this process. The process is non-destructive, and the number of runs that can be accomplished before problems emerge is limited, but relatively high, allowing for high-plex studies.
Want to compare the best tech on the market? Check out our comprehensive, free-to-download report HERE.
Mass-spec-based approaches
Imaging Mass Cytometry
Imaging Mass Cytometry (IMC) is the first of the two mass-spec based methods. It is a non-imaging-based approach for spatial proteomics that uses a similar set up to mass cytometry.
Mass cytometry is a hybrid of flow cytometry and mass spectrometry, using cytometry by time of flight (cyTOF) technology. IMC, and all mass spectrometry methods, get away from the issues of working with the fluorescent antibodies; namely spectral overlap and signal clashing with background fluorescence. The system works with heavy metal tagged antibodies instead of fluorescent ones. Once labelled with these antibodies, small areas of tissue sections are ablated, vaporising the sample and metal tags. This cloud can be analysed by mass spectrometry to determine the amounts of heavy metal ions, and hence, the protein target of interest. This approach is still targeted and is limited to a set number of targets, around 40.
There are two platforms for metal-tagged antibody-based approaches; the Hyperion Imaging system from Standard BioTools and the MIBIscope system from Ionpath, which you can read more about in the Single-Cell and Spatial Buyer’s Guide.
Mass-spectrometry Imaging
The second mass-spec approach is mass-spectrometry imaging (MSI). MSI is often confused with IMC, but it does not require heavy-isotope derived antibody labelling. Similar to IMC, in this method, laser ablation is used to ionise individual pixels of a sample. Every pixel hence has a label-free spectrum, meaning unbiased, deeper coverage of molecules compared to the targeted IMC approach. Furthermore, the limited availability of thoroughly-validated antibodies hampers all other approaches, but not MSI.
Most successful mass-spec approaches use laser microdissection for tissue microsampling. However, methods such as LESA-MS and MALDI-TOF tends to result in a low-efficiency of protein detection. Instead, MS-based bottom-up proteomics, where digested peptides were separated with liquid chromatography (LC), fragmented, and detected by MS, have become the gold standard for protein studies. With state-of-the-art LC-MS instrumentation, nearly the entire human proteome can be detected from cell and tissue specimens.
Single-cell or subcellular resolution for MSI has proved challenging, and the technique is mostly used for macroscopic imaging. Most successful MSI spatial proteomic approaches utilise hybrid MS set ups to achieve this, such as MALDI with orbitrap analysers. One example is Deep Visual Proteomics, which combines artificial-intelligence-driven image analysis of cellular phenotypes with automated single-cell or single-nucleus laser microdissection and ultra-high sensitivity mass spectrometry. However, this approach still fails to achieve subcellular resolution, hovering around 20 µm. Another example is DUV-LA-nanoPOTS, coupling nanoPOTS methodology with deep ultraviolet laser ablation, which has profiled over 1000 proteins at at <10 µm resolution.
Once again, you can compare the available tech options for this approach in our FREE Single-Cell and Spatial Buyer’s Guide.
References
Christopher, J.A., Geladaki, A., Dawson, C.S., Vennard, O.L. & Lilley, K.S. Subcellular Transcriptomics and Proteomics: A Comparative Methods Review. Molecular & Cellular Proteomics 21(2022).
Barreby, E. et al. Human resident liver myeloid cells protect against metabolic stress in obesity. Nat Metab 5, 1188-1203 (2023).
Verhoeven, B.M. et al. The immune cell atlas of human neuroblastoma. Cell Rep Med 3, 100657 (2022).
Taylor, M.J., Lukowski, J.K. & Anderton, C.R. Spatially Resolved Mass Spectrometry at the Single Cell: Recent Innovations in Proteomics and Metabolomics. Journal of the American Society for Mass Spectrometry 32, 872-894 (2021).
Xiang, P. et al. Spatial Proteomics toward Subcellular Resolution by Coupling Deep Ultraviolet Laser Ablation with Nanodroplet Sample Preparation. ACS Measurement Science Au 3, 459-468 (2023).
Mund, A. et al. Deep Visual Proteomics defines single-cell identity and heterogeneity. Nature Biotechnology 40, 1231-1240 (2022).
Williams, S.M. et al. Automated Coupling of Nanodroplet Sample Preparation with Liquid Chromatography–Mass Spectrometry for High-Throughput Single-Cell Proteomics. Analytical Chemistry 92, 10588-10596 (2020).
Piyadasa, H., Angelo, M. & Bendall, S.C. Spatial proteomics of tumor microenvironments reveal why location matters. Nature Immunology 24, 565-566 (2023).
