Monitoring macrophage metabolism in response to nanoparticle exposure provides new insights into biological outcomes, such as inflammation or toxicity, and supports the design of tailored nanomedicines. This paper describes the metabolic signature of macrophages exposed to nanoparticles ranging in diameter from 100 to 125 nm and made from silk, poly(lactic‐co‐glycolic acid) or silica. Nanoparticles of this size and type are currently at various stages of preclinical and clinical development for drug delivery applications. 1H NMR analysis of cell extracts and culture media is used to quantify the changes in the intracellular and extracellular metabolomes of macrophages in response to nanoparticle exposure. Increased glycolytic activity, an altered tricarboxylic acid cycle, and reduced ATP generation are consistent with a proinflammatory phenotype. Furthermore, amino acids possibly arising from autophagy, the creatine kinase/phosphocreatine system, and a few osmolytes and antioxidants emerge as important players in the metabolic reprogramming of macrophages exposed to nanoparticles. This metabolic signature is a common response to all nanoparticles tested; however, the direction and magnitude of some variations are clearly nanoparticle specific, indicating material‐induced biological specificity. Overall, metabolic reprogramming of macrophages can be achieved with nanoparticle treatments, modulated through the choice of the material, and monitored using 1H NMR metabolomics.

Metabolism changes extensively during the normal proliferation and differentiation of mammalian cells, and in cancer and inflammatory diseases. Since changes in the metabolic network reflect interactions between genetic, epigenetic and environmental changes, it is helpful to study the flow of label from isotopically labelled precursors into other metabolites rather than static metabolite levels. For this Nuclear Magnetic Resonance (NMR) spectroscopy is an attractive technique as it can quantify site-specific label incorporation. However, for applications using human cells and cell lines, the challenge is to optimize the process to maximize sensitivity and reproducibility. Here we present a new framework to analyze metabolism in mammalian cell lines and primary cells, covering the workflow from the preparation of cells to the acquisition and analysis of NMR spectra. We have applied this new approach in hematological and liver cancer cell lines and confirm the feasibility of tracer-based metabolism in primary liver cells.

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