A growing appreciation of the importance of cellular metabolism together with recent revelations concerning the extent of cell-cell heterogeneity demand performing metabolic characterization of individual cells. We present SpaceM, an open-source method for in situ single-cell metabolomics that detects >100 metabolites from >1,000 individual cells/hour together with a fluorescence based read-out and morpho-spatial features. We validated SpaceM by predicting the cell types of co-cultured human epithelial cells and mouse fibroblasts. We used SpaceM to show that stimulating human hepatocytes with fatty acids led to the emergence of two co-existing subpopulations outlined by distinct cellular metabolic states. Inducing inflammation with the cytokine IL-17A perturbs the balance of these states in a process dependent on NF-κB signalling. The metabolic-state markers were reproduced in a pre-clinical in vivo murine model of non-alcoholic steatohepatitis. We anticipate SpaceM to be broadly applicable for investigations of diverse cellular models and to democratize single-cell metabolomics.

Accumulation of DNA damage is intricately linked to aging, aging-related diseases and progeroid syndromes such as Cockayne syndrome (CS). Free radicals from endogenous oxidative energy metabolism can damage DNA, however the potential of acute or chronic DNA damage to modulate cellular and/or organismal energy metabolism remains largely unexplored. We modeled chronic endogenous genotoxic stress using a DNA repair-deficient Csa−/−|Xpa−/− mouse model of CS. Exogenous genotoxic stress was modeled in mice in vivo and primary cells in vitro treated with different genotoxins giving rise to diverse spectrums of lesions, including ultraviolet radiation, intrastrand crosslinking agents and ionizing radiation. Both chronic endogenous and acute exogenous genotoxic stress increased mitochondrial fatty acid oxidation (FAO) on the organismal level, manifested by increased oxygen consumption, reduced respiratory exchange ratio, progressive adipose loss and increased FAO in tissues ex vivo. In multiple primary cell types, the metabolic response to different genotoxins manifested as a cell-autonomous increase in oxidative phosphorylation (OXPHOS) subsequent to a transient decline in steady-state NAD+ and ATP levels, and required the DNA damage sensor PARP-1 and energy-sensing kinase AMPK. We conclude that increased FAO/OXPHOS is a general, beneficial, adaptive response to DNA damage on cellular and organismal levels, illustrating a fundamental link between genotoxic stress and energy metabolism driven by the energetic cost of DNA damage. Our study points to therapeutic opportunities to mitigate detrimental effects of DNA damage on primary cells in the context of radio/chemotherapy or progeroid syndromes.

Lipidomics requires the accurate annotation of lipids in complex samples to enable determination of their biological relevance. We demonstrate that unintentional in-source fragmentation (ISF, common in lipidomics) generates ions that have identical masses to other lipids. Lysophosphatidylcholines (LPC), for example, generate in-source fragments with the same mass as free fatty acids and lysophosphatidylethanolamines (LPE). The misannotation of in-source fragments as true lipids is particularly insidious in complex matrices since most masses are initially unannotated and comprehensive lipid standards are unavailable. Indeed, we show such LPE/LPC misannotations are incorporated in the data submitted to the NIST interlaboratory comparison exercise. Computer simulations exhaustively identified potential misannotations. The selection of in-source fragments of highly-abundant lipids as features, instead of the correct recognition of trace lipids, can potentially lead to: (i) missing the biologically relevant lipids (i.e., a false negative), and/or; (ii) incorrect assignation of a phenotype to an incorrect lipid (i.e., false positive). When ISF is not eliminated in the negative ion mode, ~40% of the 100 most abundant masses corresponding to unique phospholipids measured in plasma were artifacts from ISF. We show that chromatographic separation and ion intensity considerations assist in distinguishing precursor ions from in-source fragments, suggesting ISF may be especially problematic when complex samples are analyzed via shotgun lipidomics. We also conduct a systematic evaluation of ESI source parameters on a Exactive equipped with a HESI-II source with the objective of obtaining uniformly appropriate source conditions for a wide range of lipids, while, at the same time, reducing in-source fragmentation.