Spatial multiomics: Integrating imaging and LC/MS for enhanced biomolecular analysis

Innovative instruments and workflows allow researchers to apply spatial omics data from matrix-assisted laser desorption ionization (MALDI) imaging on tissue samples with liquid chromatography/trapped ion mobility time-of-flight mass spectrometry (LC-TIMS-TOF MS) experiments. They take advantage of improved spatial resolution, the integration of photocleavable mass tags (AmberGen) in MALDI imaging, and increased speed and sensitivity in LC/MS analysis, enhancing overall performance.

Many research groups suggest that this approach might result in translating research workflows into clinical applications.

The emergence of multiomics

In recent years, large-scale genomic sequencing has been enhanced with a multiomic / systems-level approach combining the genome with, for example, ribonucleic acid (RNA) transcription (transcriptomics), proteins/peptides (proteomics), lipids (lipidomics), and metabolites (metabolomics).

This allows gene information to be considered together with complementary datasets to develop a more systemic understanding of diseases or other phenotypes of interest. MS has become a cornerstone of omics analysis, with advances in instrumentation, sample preparation, software-guided workflows, and data processing capabilities establishing its position as the go-to technique.

More recently, innovations in TIMS-TOF MS technology have led to its increased adoption. This adds an orthogonal separation dimension that enhances the ability to resolve isobaric species and improves confidence in molecular identification during biological molecule separation, identification, and quantitation.

Despite the power and popularity of MS, the technique does not provide information about the in situ location, behavior, and physical distribution of the molecules under analysis, which prevents researchers from directly overlaying the MS data with the tissues or cells of interest.

Commercial MALDI guided imaging combined with MS systems that enabled the import and co-registration of other imaging modalities, such as fluorescence or histopathology, became available in 2005 (Bruker). Mass spectrometry imaging (MSI) has subsequently been described as ‘painting molecular pictures.’ ¹

It has served as a spatial omics ‘bridge’ between molecular analysis and imaging. Advancements in instrumentation and methodology have since allowed researchers to routinely investigate the precise locations of molecules of interest within tissue sections – and even within individual cells.

MSI is integrated with LC/MS in two main workflows: one where MSI guides LC/MS by targeting specific areas of interest within tissue sections for detailed analysis and another where findings from LC/MS are used to inform MSI for the validation of a panel of biomarkers, facilitating rapid and multiplexed screening. Here, we highlight two example workflows.

Workflow example 1: revealing molecular pathways that change as a cancer progresses

A recent study² combined sub-micron-resolution microscopy, image analysis for single-cell phenotyping based on artificial intelligence (AI), automated laser microdissection (LMD/LCM), and analysis with an ultra-sensitive proteomics workflow using LC/MS. The autosampler was configured for sample pick-up from 384-well plates, enabling high-throughput analysis of low volume samples.

The research employed software to coordinate scanning and LMD microscopes. Cellular or subcellular objects of interest were selected by AI before being subjected to automated LMD and proteomic profiling.

The researchers found that several things were key to achieving high sample throughput without compromising sensitivity: accurate definition of single-cell boundaries and cell classes; the transfer of the automatically defined features into proteomic samples ready for analysis; and robust, automated sample preparation workflows.

Workflow example 2: improving understanding of the role of immune cell infiltration in cardiac arrest

Spatial omics of acute myocardial infarction (MI), more commonly known as a heart attack, was studied in a multiomics workflow using timsTOF technology to reveal a novel mode of immune cell infiltration.³

The precise changes in tissue architecture following an MI attack are poorly understood. Researchers used a combination of imaging-based transcriptomics (spatial transcriptomics, often referred to as molecular cartography) and antibody-based highly multiplexed imaging (sequential immunofluorescence) to evaluate cell-type compositions and changes at subcellular resolution.

The analysis identified a novel mode of leukocyte accumulation in the heart. The underlying mechanisms driving this previously unknown infiltration route were analyzed using Deep Visual Proteomics (DVP), an unbiased spatial proteomic analysis. This enabled the identification of specific proteomic markers and pathways that were crucial to understanding this novel infiltration.

The approach led to the development of the first spatial map of acute murine MI with subcellular resolution. Furthermore, DVP was used to identify von Willebrand Factor (vWF) as a mediator of inflammation 24 hours post-MI – a previously unknown route of immune infiltration.

MSI supports multiomics research

Researchers are starting to explore proofs of concept for translating multiomics findings into a clinical context, paving the way for enhanced disease understanding and, in the longer term, improved diagnostics and targeted personalized treatment strategies.

The latest high-performance MALDI-TOF technology for MS-based tissue imaging plays a key role in this context. Integrating MALDI-TOF technology into a spatial biology workflow allows for pinpointing protein location and activity, building a greater understanding of both healthy and diseased tissue environments.

By adopting a comprehensive approach from sample preparation to post-processing analysis, this new integrated ecosystem is poised to transform research in neuroscience, infectious disease and oncology, and, in the longer term, drive new insights that will help to understand diseases in a more comprehensive way.

This contributed article is authored by Pascal Steffen-Lockhauserbäumer, Global Product Manager for timsTOF at Bruker Daltonics.

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References

¹ Schwamborn, K.; Caprioli, R. M. MALDI Imaging Mass Spectrometry-Painting Molecular Pictures. Mol. Oncol. 2010, 4 (6), 529–538. https://doi.org/10.1016/j.molonc.2010.09.002.

² Mund, A., Coscia, F., Kriston, A., Hollandi, R., Kovács, F., Brunner, A.-D., Migh, E., Schweizer, L., Santos, A., Bzorek, M., Naimy, S., Rahbek-Gjerdrum, L. M., Dyring-Andersen, B., Bulkescher, J., Lukas, C., Eckert, M. A., Lengyel, E., Gnann, C., Lundberg, E., Horvath, P., and Mann, M. (2022) Deep Visual Proteomics defines single-cell identity and heterogeneity. Nature Biotechnology 2022, 1–10.

³ Wünnemann, F, Sicklinger, F, Bestak, K, Nimo, J, Thiemann, T, Amrute, J, Nordbeck, M, Hartmann, N, Ibarra-Arellano, M. A, Tanevski, J, Heine, C, Frey, N, Lavine, K. J, Coscia, F, Saez-Rodriguez, J, Leuschner, F, Schapiro, D. Spatial omics of acute myocardial infarction reveals a novel mode of immune cell infiltration, bioRxiv preprint doi: https://doi.org/10.1101/2024.05.20.594955; this version posted May 21, 2024. https://www.biorxiv.org/content/10.1101/2024.05.20.594955v1.full.pdf