Immunometabolism and natural killer cell responses

O’Brien, Katie; Finlay, David K.

doi:10.1038/s41577-019-0139-2

Cited by 308 publications

(310 citation statements)

References 100 publications

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“…It serves as a further example to the power of studying single-cell heterogeneity within seemingly homogenous populations (here, Th17n), which allowed us to identify a novel regulator that would have otherwise been missed at a population level (here, a comparison of Th17p and Th17n). The computational prediction and the data corroborating it also demonstrate that despite the common assumption that glycolysis promotes proinflammatory functions in Th17 cells and other immune compartments [2], [3], [83]- [87], the role of glycolysis in induction of pro-inflammatory phenotypes may more nuanced [88], [89].…”

Section: Discussionsupporting

confidence: 56%

In Silico Modeling of Metabolic State in Single Th17 Cells Reveals Novel Regulators of Inflammation and Autoimmunity

Wagner¹,

Wang

DeTomaso³

et al. 2020

Preprint

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Cellular metabolism, a key regulator of immune responses, is difficult to study with current technologies in individual cells Here, we present Compass, an algorithm to characterize the metabolic state of cells based on single-cell RNA-Seq and flux balance analysis. We applied Compass to associate metabolic states with functional variability (pathogenic potential) amongst Th17 cells and recovered a metabolic switch between glycolysis and fatty acid oxidation, akin to known differences between Th17 and Treg cells, as well as novel targets in amino-acid pathways, which we tested through targeted metabolic assays. Compass further predicted a particular glycolytic reaction (phosphoglycerate mutase -PGAM) that promotes an anti-inflammatory Th17 phenotype, contrary to the common understanding of glycolysis as pro-inflammatory. We demonstrate that PGAM inhibition leads non-pathogenic Th17 cells to adopt a pro-inflammatory transcriptome and induce autoimmunity in vivo. Compass is broadly applicable for characterizing metabolic states of cells and relating metabolic heterogeneity to other cellular phenotypes. / 27 RESULTS Compass -an algorithm for comprehensive characterization of single-cell metabolismWe reasoned that even though the mRNA expression of individual enzymes does not necessarily provide an accurate proxy for their metabolic activity, a global analysis the entire metabolic network (as enabled by RNA-Seq) in the context of a large sample set (as offered by single cell genomics) coupled with strict criteria for hypotheses testing, would provide an effective framework for predicting cellular metabolic status of the cell. This led us to develop the Compass algorithm, which integrates scRNA-Seq profiles with prior knowledge of the metabolic network to infer a metabolic state of the cell (Figure 1A).The metabolic network is encoded in a Genome-Scale Metabolic Model (GSMM) that includes reaction stoichiometry, biochemical constraints such as reaction irreversibility and nutrient availability, and gene-enzyme-reaction associations. Here, we use Recon2, which comprises of 7,440 reactions and 2,626 unique metabolites [41]. To explore the metabolic capabilities of each cell, Compass solves a series of constraint-based optimization problems (formalized as linear programs) that produce a set of numeric scores, one per reaction (Methods). Intuitively, the score of each reaction in each cell reflects how well adjusted is the cell's overall transcriptome to maintaining high flux through that reaction. Henceforth, we refer to the scores as quantifying the "potential activity" of a metabolic reaction (or "activity" in short when it is clear from the context that Compass predictions are discussed).Compass belongs to the family of Flux Balance Analysis (FBA) algorithms that model metabolic fluxes, namely the rate by which chemical reactions convert substrates to products and apply constrained optimization methods to find flux distributions that satisfy desired properties (a flux distribution is an assignment of flux value to ever...

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Section: Discussionsupporting

confidence: 56%

In Silico Modeling of Metabolic State in Single Th17 Cells Reveals Novel Regulators of Inflammation and Autoimmunity

Wagner¹,

Wang

DeTomaso³

et al. 2020

Preprint

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“…Both DC and NK cells require c-Myc for metabolic reprogramming with activation, but HIF-1α dependency is stimuli-dependent for NK cells. 243 NK cell activation, via natural killer receptor (NKR) stimulation, required increased glycolysis. By contrast, IL-12 and IL-18 combined initiated IFN-γ production without increasing glycolysis or OXPHOS, and prolonged IL-15 treatment bypassed the glycolytic requirement for NKR-mediated activation.…”

Section: Natural Killer Cell Metabolismmentioning

confidence: 99%

“…244 As with other immune cells, mTOR is considered an important regulator of NK metabolic reprogramming, and mTORC1 is linked to NK maturation and activation. 243,245 Productive IAV infection of epithelial cells induced PI3K/mTOR/Akt signaling, resulting in mTORC1 directly phosphorylating S6 kinase, thereby activating a translational regulator that increases mRNA biogenesis, translational initiation, and elongation. 28 However, NK cell activation activated mTORC1 independent of PI3K-Akt through nutrient sensing and sterol regulatory element-binding protein (SERBP) activation.…”

Section: Il-15 Signaling In Nk Cells Was Concentration-dependent Lowmentioning

confidence: 99%

Fueling influenza and the immune response: Implications for metabolic reprogramming during influenza infection and immunometabolism

Bahadoran

Bezavada

Smallwood

2020

Immunological Reviews

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The metabolic impact of influenza A virus (IAV) infections on immune cells remains largely uncharacterized. However, much is known about the metabolism of IAV infection and immunometabolism. Thus, we will consider four main factors: the metabolic requirements of influenza virus, metabolic reprogramming of immune cells that are mobilized to fight IAV infection, the impact of systemic or local metabolism on the infection and immune response, and vice versa. We will also address the interplay of metabolism and cytokines with a focus on those relevant to IAV infections. Finally, we will limit information on immunometabolism to key cell types critical to fighting IAV infection. We will relate this information to the unique metabolic demands on immune cells and discuss how their translocation through nutrient diverse and changing environments may affect their functions in IAV infection. | ME TABOLIS M AND THE LUNG MICROENVIRONMENT | Steady-state metabolismUnder aerobic conditions, cells sustain themselves catabolically using glycolytic carbons to fuel the tricarboxylic acid (TCA) cycle. AbstractRecent studies support the notion that glycolysis and oxidative phosphorylation are rheostats in immune cells whose bioenergetics have functional outputs in terms of their biology. Specific intrinsic and extrinsic molecular factors function as molecular potentiometers to adjust and control glycolytic to respiratory power output. In many cases, these potentiometers are used by influenza viruses and immune cells to support pathogenesis and the host immune response, respectively. Influenza virus infects the respiratory tract, providing a specific environmental niche, while immune cells encounter variable nutrient concentrations as they migrate in response to infection. Immune cell subsets have distinct metabolic programs that adjust to meet energetic and biosynthetic requirements to support effector functions, differentiation, and longevity in their ever-changing microenvironments. This review details how influenza coopts the host cell for metabolic reprogramming and describes the overlap of these regulatory controls in immune cells whose function and fate are dictated by metabolism. These details are contextualized with emerging evidence of the consequences of influenzainduced changes in metabolic homeostasis on disease progression. K E Y W O R D Shost pathogen, immune response, Immunometabolism, Influenza, metabolism, viral infection, virus | 141 BAHADORAN et Al.

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“…Scatter has been used as an indicator of metabolic alteration in NK cells (Castro et al, 2018) and we found that side scatter increased in NK cells from the livers of obese mice ( Figure 5a). NK cells use mTOR for nutrient sensing and it also has an important role in immune regulation (O'Brien and Finlay, 2019). The phosphorylation of ribosomal S6 protein (pS6) is used as an indicator of mTORC1 signaling and we found that pS6 was increased in NK cells freshly isolated from the livers of obese compared to lean mice (Figure 5b).…”

Section: Nk Cells In Obese Mice Are Metabolically Reprogrammedmentioning

confidence: 87%

“…NK cell-derived ILC1-like cells in tumors produce angiogenic and growth factors (Gao et al, 2017), so it is tempting to speculate that the ILC1-like cells we see emerging from the NK cell population in the obese liver may have a similar reparative effect. It has been suggested that NK cell metabolism could be targeted to prevent cancer (O'Brien and Finlay, 2019). In the light of recent findings that NK cells are less cytotoxic in obesity, and that this is at least partially mediated by metabolic changes, it might be tempting to consider using such treatments as a way to break the well-established link between cancer and obesity (Park et al, 2014).…”

Section: Discussionmentioning

confidence: 99%

TGFβ in the obese liver mediates conversion of NK cells to a less cytotoxic ILC1-like phenotype

Cuff

Sillito

Dertschnig

et al. 2019

Preprint

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The liver contains both NK cells and their less cytotoxic relatives, ILC1. Here, we investigate the role of NK cells and ILC1 in the obesity-associated condition, non-alcoholic fatty liver disease (NAFLD). In the livers of mice suffering from NAFLD, NK cells are less able to degranulate, express lower levels of perforin and are less able to kill cancerous target cells than those from healthy animals. This is associated with a decreased ability to kill cancer cells in vivo. On the other hand, we find that perforin-deficient mice suffer from less severe NAFLD, suggesting that this reduction in NK cell cytotoxicity may be protective in the obese liver, albeit at the cost of increased susceptibility to cancer. The decrease in cytotoxicity is associated with a shift towards a transcriptional profile characteristic of ILC1, increased expression of the ILC1-associated proteins CD200R1 and CD49a, and an altered metabolic profile mimicking that of ILC1. We show that the conversion of NK cells to this less cytotoxic phenotype is at least partially mediated by TGFβ, which is expressed at high levels in the obese liver. Finally, we show that reduced cytotoxicity is also a feature of NK cells in the livers of human NAFLD patients.

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Immunometabolism and natural killer cell responses

Cited by 308 publications

References 100 publications

In Silico Modeling of Metabolic State in Single Th17 Cells Reveals Novel Regulators of Inflammation and Autoimmunity

In Silico Modeling of Metabolic State in Single Th17 Cells Reveals Novel Regulators of Inflammation and Autoimmunity

Fueling influenza and the immune response: Implications for metabolic reprogramming during influenza infection and immunometabolism

TGFβ in the obese liver mediates conversion of NK cells to a less cytotoxic ILC1-like phenotype

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