Inverse Data-Driven Modeling and Multiomics Analysis Reveals Phgdh as a Metabolic Checkpoint of Macrophage Polarization and Proliferation

Wilson, Jayne Louise; Nägele, Thomas; Linke, Monika; Demel, Florian; Fritsch, Stephanie Deborah; Mayr, Hannah Katharina; Cai, Zheng-Nan; Karl, Katharina; Sun, Xiaoliang; Fragner, Lena; Miller, Anne; Haschemi, Arvand; Popa, Alexandra; Bergthaler, Andréas; Hengstschläger, Markus; Weichhart, Thomas; Weckwerth, Wolfram

doi:10.1016/j.celrep.2020.01.011

Cited by 57 publications

(71 citation statements)

References 53 publications

(79 reference statements)

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“…To investigate regulation of metabolism, reaction elasticities were calculated based on a method for inverse data driven modelling, which connects metabolite variance information with a metabolic network 29,30 . Metabolite data from the 6 °C condition of two subsets representing cold and warm Q1 climate were used for this approach.…”

Section: Resultsmentioning

confidence: 99%

Plasticity of the primary metabolome in 241 cold grown Arabidopsis thaliana accessions and its relation to natural habitat temperature

Weiszmann

Clauw

Jagoda

et al. 2020

Preprint

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In the present study, 241 natural accessions of Arabidopsis thaliana were grown under two different temperature regimes, 16 °C and 6 °C, and growth parameters were recorded together with metabolite profiles to investigate the natural variation in metabolic responses and growth rates. Primary metabolism and growth rates of accessions significantly differed between accessions and both growth conditions. Relative growth rates showed high correlations to specific metabolite pools. Metabolic distances based on whole metabolite profiles were built from principal component centroids between both growth setups. Genomic prediction using ridge-regression best linear unbiased prediction (rrBLUP) revealed a significant prediction accuracy of metabolite profiles in both conditions and metabolic distances, which suggests a tight relationship between genome and primary metabolome. GWAS analysis revealed significantly associated SNPs for a number of metabolites, especially for fumarate metabolism at low temperature. A highly significant correlation was observed between metabolic distances and maximum temperature in the original growth habitat between January and March. Inverse data-driven modelling revealed that metabolic pathway regulation and metabolic reaction elasticities distinguish accessions originating from warm and cold growth habitats.

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Section: Resultsmentioning

confidence: 99%

Plasticity of the primary metabolome in 241 cold grown Arabidopsis thaliana accessions and its relation to natural habitat temperature

Weiszmann

Clauw

Jagoda

et al. 2020

Preprint

Self Cite

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“…M2 formation is induced by IL-4 and IL-13 cytokines that activate Akt, preventing the stabilization of HIF-1a [89,90]. The phosphoglycerate dehydrogenase, the rate-limiting enzyme in de novo serine biosynthesis from glucose, is also required for M2 polarization [91]. In addition, M2 macrophages require glutamine to carry out their function since glutamine deprivation impairs M2 but not M1 polarization.…”

Section: The Glycolytic Players Of the Inflammatory Responsementioning

confidence: 99%

Glycolysis – a key player in the inflammatory response

et al. 2020

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The inflammatory response involves the activation of several cell types to fight insults caused by a plethora of agents, and to maintain the tissue homoeostasis. On the one hand, cells involved in the pro-inflammatory response, such as inflammatory M1 macrophages, Th1 and Th17 lymphocytes or activated microglia, must rapidly provide energy to fuel inflammation, which is essentially accomplished by glycolysis and high lactate production. On the other hand, regulatory T cells or M2 macrophages, which are involved in immune regulation and resolution of inflammation, preferentially use fatty acid oxidation through the TCA cycle as a main source for energy production. Here, we discuss the impact of glycolytic metabolism at the different steps of the inflammatory response. Finally, we review a wide variety of molecular mechanisms which could explain the relationship between glycolytic metabolites and the pro-inflammatory phenotype, including signalling events, epigenetic remodelling, post-transcriptional regulation and post-translational modifications. Inflammatory processes are a common feature of many age-associated diseases, such as cardiovascular and neurodegenerative disorders. The finding that immunometabolism could be a master regulator of inflammation broadens the avenue for treating inflammation-related pathologies through the manipulation of the vascular and immune cell metabolism.

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“…15,51 M2 macrophages also express elevated levels of 3-phosphoglycerate dehydrogenase that channels glycolytic intermediates into serine, glycine and folate one-carbon metabolism. 52 These metabolic shifts may promote Leishmania growth in a number of ways. First, the shift toward more efficient mitochondrial respiration may allow the accumulation of intracellular pools of glucose in the host cell which promotes amastigote growth.…”

Section: Host Central Carbon Metabolismmentioning

confidence: 99%

“…Although the metabolic reprogramming of Leishmania ‐infected macrophages has not been examined in detail, IL‐4‐mediated polarization of macrophages is associated with increased mitochondrial biogenesis, and the operation of a complete tricarboxylic acid cycle, which is supported by increased glutaminolysis and fatty acid β‐oxidation 15,51 . M2 macrophages also express elevated levels of 3‐phosphoglycerate dehydrogenase that channels glycolytic intermediates into serine, glycine and folate one‐carbon metabolism 52 . These metabolic shifts may promote Leishmania growth in a number of ways.…”

Section: Impact Of Macrophage Metabolism On Intracellular Leishmania mentioning

confidence: 99%

Immunometabolism of Leishmania granulomas

Saunders

McConville

2020

Immunol Cell Biol

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Leishmania are parasitic protists that cause a spectrum of diseases in humans characterized by the formation of granulomatous lesions in the skin or other tissues, such as liver and spleen. The extent to which Leishmania granulomas constrain or promote parasite growth is critically dependent on the host Thelper type 1/T-helper type 2 immune response and the localized functional polarization of infected and noninfected macrophages toward a classically (M1) or alternatively (M2) activated phenotype. Recent studies have shown that metabolic reprograming of M1 and M2 macrophages underpins the capacity of these cells to act as permissive or nonpermissive host reservoirs, respectively. In this review, we highlight the metabolic requirements of Leishmania amastigotes and the evidence that these parasites induce and/or exploit metabolic reprogramming of macrophage metabolism. We also focus on recent studies highlighting the role of key macrophage metabolic signaling pathways, such as mechanistic target of rapamycin, adenosine monophosphate-activated protein kinase and peroxisome proliferator receptor gamma in regulating the pathological progression of Leishmania granulomas. These studies highlight the intimate connectivity between Leishmania and host cell metabolism, the need to investigate these interactions in vivo and the potential to exploit host cell metabolic signaling pathways in developing new host-directed therapies.

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Inverse Data-Driven Modeling and Multiomics Analysis Reveals Phgdh as a Metabolic Checkpoint of Macrophage Polarization and Proliferation

Abstract: Highlights d Metabolomics and inverse modeling reveal a Tsc2/mTORC1dependent checkpoint in macrophages d M2 macrophages have high Phgdh activity d Phgdh activity promotes M2 polarization d Phgdh activity supports macrophage proliferation

Cited by 57 publications

References 53 publications

Plasticity of the primary metabolome in 241 cold grown Arabidopsis thaliana accessions and its relation to natural habitat temperature

Plasticity of the primary metabolome in 241 cold grown Arabidopsis thaliana accessions and its relation to natural habitat temperature

Glycolysis – a key player in the inflammatory response

Immunometabolism of Leishmania granulomas

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