Fig. 4: Potential mechanisms for integration of techniques discussed.

A Temporal analysis of immunometabolism. In mice, time-stamping and in vivo nutrient uptake might be combined to gain understanding of how the metabolism of tissue-resident innate lymphocytes changes with the length of time they are within a tissue. With this format, flow cytometry and scRNA-seq platforms can be integrated to gain insight into the transcriptome and metabolic features, including in vivo uptake, of immune cells of interest and correlate this with cellular location at the time of sample retrieval. While spatial information is mostly lost in this approach, the in vivo uptake data will reflect whether a given cell had access to the click-nutrient and this will be impacted by the tissue architecture and competition for the click-nutrient between cells. B Spatial and temporal analysis of immunometabolism. This approach relies on the use of tissue sections where adjacent sections are processed for spatial metabolomics (top) or multiparametric immunofluorescence (bottom). In human samples this approach might be used to generate information about the metabolome of the tissue section and how spatial metabolite levels relate to the location of innate lymphocytes, identified using immunofluorescence in an adjacent tissue section. With advances in multiparametric immunofluorescence, metabolic features of innate lymphocytes could be measured using antibodies specific to metabolic machinery (nutrient transporters, enzymes) or metabolic signalling molecules (such as mTORC1 signalling components). In mice, the time-stamping and in vivo nutrient uptake approaches described in (A) could be added to the protocol, though this would add additional complexity to the multiparametric immunofluorescence. There are significant challenges involved in optimising such an experimental setup. This figure was created in BioRender. Finlay (2024) https://BioRender.com/b20j926.