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To better understand cell-to-cell heterogeneity, advanced analytical tools are in a growing demand for elucidating chemical compositions of each cell within a population. However, the progress of single-cell chemical analysis has been restrained by the limitations of small cell volumes and minute cellular concentrations. Here, we present a rapid and sensitive method for investigating the lipid profiles of isolated single cells using infrared matrix-assisted laser desorption electrospray ionization mass spectrometry (IR-MALDESI-MS). In this work, HeLa cells were dispersed onto a glass slide, and the cellular contents were ionized by IR-MALDESI and measured using a Q-Exactive HF-X mass spectrometer. Importantly, this approach does not require extraction and/or enrichment of analytes prior to MS analysis. Using this approach, 45 distinct lipid species, predominantly phospholipids, were detected and putatively annotated from the single HeLa cells. The proof-of-concept study demonstrates the feasibility and efficacy of IR-MALDESI-MS for rapid lipidomic profiling of single cells, which provides an important basis for future work on differentiation between normal and diseased cells at various developmental states, which can offer new insights into cellular metabolic pathways and pathological processes.Although not yet accomplished, we believe this approach can be readily used as an assessment tool to compare the number of identified species during source evolution and method optimization (intra-laboratory), and also disclose the complementary nature of different direct analytical approaches for the coverage of different types of endogenous analytes (inter-laboratory).

Introduction Muscle invasive bladder cancer (MIBC) is an advanced stage of bladder cancer which poses a severe threat to life. Cancer development is usually accompanied by remarkable alterations in cell metabolism, and hence deep insights into MIBC at the metabolomic level can facilitate the understanding of the biochemical mechanisms involved in the cancer development and progression. Methods In this proof-of-concept study, the optimal cutting temperature (OCT)-embedded MIBC samples were first washed with pure water to remove the polymer compounds which could cause severe signal suppression during mass spectrometry. Further, the tissue sections were analyzed by infrared matrix-assisted laser desorption electrospray ionization mass spectrometry imaging (IR-MALDESI MSI), providing an overview on the spatially resolved metabolomic profiles. ResultsThe MSI data enabled the discrimination between not only the cancerous and normal tissues, but also the subregions within a tissue section associated with different disease states. Using t-Distributed Stochastic Neighbor Embedding (t-SNE), the hyperdimensional MSI data was mapped into a two-dimensional space to visualize the spectral similarity, providing evidence that metabolomic alterations might have occurred outside the histopathological tumor border. Least absolute shrinkage and selection operator (LASSO) was further employed to classify sample pathology in a pixel-wise manner, yielding excellent prediction sensitivity and specificity up to 96% based on the statistically characteristic spectral features. ConclusionThe results demonstrate great promise of IR-MALDESI MSI to identify molecular changes derived from cancer and unveil tumor heterogeneity, which can potentially promote the discovery of clinically relevant biomarkers and allow for applications in precision medicine.