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Single-cell technologies have revolutionized our ability to probe some of the most important questions in metabolism research. Here, we highlight innovative use of single-cell technology in studies published in Nature Metabolism.
Buglakova et al. present 13C-SpaceM, a method that combines stable isotope tracing with imaging mass spectrometry thus enabling spatial analysis of lipid dynamics with near-single-cell resolution in tissues.
This study reports the mouse islet atlas, a curated resource integrating scRNA-seq data of over 300,000 cells from nine datasets, covering pancreas development, homeostasis and disease states.
Spatial metabolomics has matured and is driving innovation in mass spectrometry, metabolomics and spatial omics. With exciting discoveries, complementary capabilities and increasing accessibility, it has secured its place in the spatial biology toolbox, showing promise in biology, medicine and pharmacology.
Subcellular quantitative analysis has been a long-standing goal of mass spectrometry imaging, but was originally thought to be unattainable. However, recent advances have made organelle-level absolute quantification through mass spectrometry imaging a reality, thanks to the development of nano secondary ion mass spectrometry.
Miller et al. use fast thermal preservation and mass spectrometry imaging to reveal rapid neuron-layer metabolic responses to stimulation within a brain slice. Stimulation increases glucose use and converts spent ATP into metabolic fuel, via inosine.
Single-cell transcriptomic analysis of progenitor cells from human adipose depots reveals an adipogenic and a structural branch of cells, the latter named SWAT cells and shown to display a multipotent phenotype.
Single-cell transcriptomic analysis of human multipotent progenitor cells reveals that upon adipogenic stimulation, Wnt signaling regulates the generation of functional multipotent mesenchymal progenitors, named structural Wnt-regulated adipose tissue resident cells, which maintain the progenitor pool.
Steuernagel and Lam et al. present HypoMap, an integrated reference atlas of the murine hypothalamus based on 384,925 hypothalamic cells from publicly available single-cell sequencing datasets.
Understanding dynamic metabolic changes in complex biological samples often overlooks heterogeneity in cell composition. Wang et al. combine mass spectrometry imaging, isotope tracing, and multiplexed immunofluorescence microscopy to study metabolic dynamics in the kidney upon ischemia–reperfusion.
Fasolino et al. provide insights into ductal cell roles and type 1 diabetes pathogenesis using a pancreatic islet single-cell atlas generated by the Human Pancreas Analysis Program.
A combination of single-cell approaches, lineage tracing and metabolomics is used to characterize the changes to intestinal stem cell function in the small intestine that underlie intestinal maladaptation in mice fed an obesogenic diet.
Wu, Harrison and colleagues visualize lactate production at subcellular resolution in migrating endothelial cells and identify hotspots of glycolytic activity, mediated by RhoA and the glucose transporter SLC2A3, that couple cellular energy metabolism with cytoskeleton remodelling and cell motility.
Few technologies have changed the language and approach of biological research as dramatically and pervasively as single-cell technology, which has joined lipidomics, GFP, ChIP–seq and CRISPR–Cas in the pantheon of biotechnology. Here, we reflect on the influence of single-cell technology on metabolism research, some of which can be found in our new Collection on Single-cell technology in metabolism, featuring articles published in Nature Metabolism.
Shamsi et al. identify vascular smooth muscle cells marked by expression of Trpv1 as a part of the cellular lineage of brown and beige fat. Cold stimulates the expansion and differentiation of Trpv1-expressing progenitors to highly thermogenic adipocytes.
Ludwig et al. map transcription and chromatin accessibility in single cells across the brainstem dorsal vagal complex, thereby identifying neuronal populations, including some that control feeding.
Choi et al. highlight the centrality of glycolysis in squamous cell carcinoma, revealing the glycolysis-dampening tumour suppressor role of Sirt6, and identifying a subset of highly glycolytic tumour-propagating cells with elevated antioxidant capacity.
Newman et al. explore the origins of myofibroblasts in atherosclerotic fibrous caps, finding that while composed of cells from multiple origins, smooth muscle cells predominate and are required for long-term plaque stability.
Previously, liver zonation was analysed statically, and liver chronobiology was analysed at the tissue level. Using single-cell RNA-seq and single-molecule FISH, Droin et al. study the interplay between liver gene regulation in space and time at the sub-lobular scale.
Osteoclasts are the body’s exclusive bone-resorbing cells; however, their differentiation trajectory remains unclear. Using single-cell RNA sequencing, Tsukasaki et al. provide a comprehensive road map of osteoclastogenesis, unveiling stepwise molecular events underlying osteoclast cell fate transitions.
By using single-cell transcriptomics, Weng et al. reveal complex temporal gene control during pancreatic beta-cell differentiation from human embryonic stem cells, allowing for the construction of a unique lineage tree and optimization of differentiation protocols.
Levy et al. report a method to measure transcriptional coordination between cells in single-cell RNA sequencing data and demonstrate that transcriptional dysregulation between cells is a general phenomenon in ageing and is associated with genetic damage.
Using holistic and reductionist approaches, Karunakaran et al. identify a causal association between higher expression of RIPK1 (a central regulator of inflammatory cell function) and the risk of obesity. RIPK1 induces activation of proinflammatory signalling in adipose tissue, promoting the accumulation of macrophages that drive metabolic inflammation and obesity simultaneously.
Adipose tissue varies depending on localization. Vijay et al. perform single-cell RNA sequencing in multiple adipose tissue depots from obese individuals and identify distinct subpopulations of endothelial cells, immune cells and pre-adipocytes.
The liver is a heterogeneous organ organized in lobules that are radially polarized. The use of single-cell spatial transcriptomics has revealed that half of hepatic genes are differentially expressed across the lobule. Ben-Moshe et al. show how a multi-omics approach, which consists of transcriptomics, micro RNA profiling and proteomics, allows for characterization of liver heterogeneity with higher resolution.