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Review
. 2020 Nov 3;32(5):710-725.
doi: 10.1016/j.cmet.2020.09.013. Epub 2020 Oct 6.

Immunometabolism in the Single-Cell Era

Maxim N Artyomov  1 , Jan Van den Bossche  2
Affiliations
Review

Immunometabolism in the Single-Cell Era

Maxim N Artyomov et al. Cell Metab. .

Abstract

Emerging research has identified metabolic pathways that are crucial for the proper regulation of immune cells and how, when deranged, they can cause immune dysfunction and disease progression. However, due to technical limitations such insights have relied heavily on bulk measurements in immune cells, often activated in vitro. But with the emergence of single-cell applications, researchers can now estimate the metabolic state of individual immune cells in clinical samples. Here, we review these single-cell techniques and their ability to validate common principles in immunometabolism, while also revealing context-dependent metabolic heterogeneity within the immune cell compartment. We also discuss current gaps and limitations, as well as identify future opportunities to move the field forward toward the development of therapeutic targets and improved diagnostic capabilities.

Keywords: CyTOF mass cytometry; flow cytometry; immunology; immunometabolism; metabolism; next-generation immunometabolism; single-cell RNA-sequencing; spatiotemporal.

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Conflict of interest statement

Declaration of interests

The authors declare no competing interests.

Figures

Figure 1 –
Figure 1 –. Key metabolic pathways in immune cell subtypes.
A. Overview of the most important metabolic pathways regulating immune cells, including the metabolic targets that were used in recent single-cell profiling approaches. B. Summary of the metabolic characteristics and needs of various immune cell subsets as detailed in the text and as reviewed earlier elsewhere (O’Neill et al., 2016; Van den Bossche et al., 2017).
Figure 2 –
Figure 2 –. Expression of some key metabolic genes in intratumoral immune cells based on published single-cell transcriptomics data.
A–B. The behavior of some key metabolic genes is shown in immune cells of mouse sarcomas that were treated with either anti-PD1/anti-CTLA4 immune checkpoint blockade antibodies or with control antibody (Gubin et al., 2018). To do so, we created a direct visualization of the indicated genes from the associated published dataset (GSE119352).
Figure 3 –
Figure 3 –
Hypothetical technology development perspective in the context of single-cell immunometabolism applications.
See this image and copyright information in PMC

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