Impairment of Glycolysis-Derived l-Serine Production in Astrocytes Contributes to Cognitive Deficits in Alzheimer’s Disease

Douce, Juliette Le; Maugard, Marianne; Veran, Julien; Matos, Marco; Jégo, Pierrick; Vigneron, Pierre-Antoine; Faivre, Émilie; Toussay, Xavier; Vandenberghe, Michel; Balbastre, Yaël; Piquet, Juliette; Guiot, Elvire; Tran, Nguyet Thuy; Taverna, Myriam; Marinesco, Stéphane; Koyanagi, Ayumi; Furuya, Shigeki; Gaudin-Guérif, Mylène; Goutal, Sébastien; Ghettas, Aurélie; Pruvost, Alain; Bémelmans, Alexis; Gaillard, Marie Claude; Cambon, Karine; Stimmer, Lev; Sazdovitch, Véronique; Duyckaerts, Charles; Knott, Graham; Hérard, Anne Sophie; Delzescaux, Thierry; Hantraye, Philippe; Brouillet, Emmanuel; Cauli, Bruno; Oliet, Stéphane H. R.; Panatier, Aude; Bonvento, Gilles

doi:10.1016/j.cmet.2020.02.004

Cited by 167 publications

(108 citation statements)

References 71 publications

(70 reference statements)

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“…Astrocytic L-serine was proposed to regulate NMDAR activity to sustain D-serine production by neurons [91] that J o u r n a l P r e -p r o o f would thus explain the altered synaptic plasticity observed in AD. The deficits of functional plasticity in the hippocampus and memory impairments in these 3xTg-AD mice [84] are rescued by long-term treatments with either D-or L-serine, confirming the view of severe metabolic dysfunction as a leading hallmark and cause of AD as previously proposed (see [92]).…”

Section: D-serine In Alzheimer's Diseasesupporting

confidence: 83%

“…Indeed, observations from two transgenic mice models have extended the debate into the preclinical field on how D-serine contributes to AD. In fact, a decreased synthesis of L-serine from glucose though PHGDH astrocytic enzyme has recently been reported in 3xTg-AD mice [84]. Astrocytic L-serine was proposed to regulate NMDAR activity to sustain D-serine production by neurons [91] that J o u r n a l P r e -p r o o f would thus explain the altered synaptic plasticity observed in AD.…”

Section: D-serine In Alzheimer's Diseasementioning

confidence: 97%

“…Therefore, the elevation of its extracellular RNA may argue for an increase of D-serine brain level during presymptomatic stage of the disease.Similarly, this issue does not make consensus in the field of preclinical investigations ([78,[84][85][86], seeTable 1). In fact, an increase of D-serine levels in hippocampal tissues hasbeen observed in several animal models of AD, including those with intracerebroventricular injections of soluble oligomers of the Aβ peptide (Aβo) and genetic strains bearing several mutations associated with familiar forms of AD [78].…”

mentioning

confidence: 99%

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d-serine in physiological and pathological brain aging

Ploux

Freret

Billard

2021

Biochimica et Biophysica Acta (BBA) - Proteins and Proteomics

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Section: D-serine In Alzheimer's Diseasesupporting

confidence: 83%

Section: D-serine In Alzheimer's Diseasementioning

confidence: 97%

mentioning

confidence: 99%

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d-serine in physiological and pathological brain aging

Ploux

Freret

Billard

2021

Biochimica et Biophysica Acta (BBA) - Proteins and Proteomics

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“…The metabolism of the brain is realized by a joint effort of all cell types including neurons, glial cells as well as cells constituting the blood vessels. Almost all aspects of metabolism in the brain involve several types of cells, including energy metabolism (Pellerin and Magistretti, 1994;Guzmán and Blázquez, 2001; Barros and Deitmer, 2010;Nave, 2010a;Hirrlinger and Nave, 2014;Barros et al, 2018b;Díaz-García and Yellen, 2019;Vicente-Gutierrez et al, 2019;Zuend et al, 2020), and neurotransmitter metabolism (van den Berg et al, 1978;Waagepetersen et al, 2003;Bak et al, 2006;Le Douce et al, 2020). Furthermore, brain cells are structurally intermingled, heavily interdigitating their numerous cellular processes (Somjen, 1988;Grosche et al, 1999;Bushong et al, 2002;Nave, 2010b).…”

Section: Introductionmentioning

confidence: 99%

A Dual Nanosensor Approach to Determine the Cytosolic Concentration of ATP in Astrocytes

Köhler

Schmidt

Fülle

et al. 2020

Front. Cell. Neurosci.

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Adenosine triphosphate (ATP) is the central energy carrier of all cells and knowledge on the dynamics of the concentration of ATP ([ATP]) provides important insights into the energetic state of a cell. Several genetically encoded fluorescent nanosensors for ATP were developed, which allow following the cytosolic [ATP] at high spatial and temporal resolution using fluorescence microscopy. However, to calibrate the fluorescent signal to [ATP] has remained challenging. To estimate basal cytosolic [ATP] ([ATP] 0) in astrocytes, we here took advantage of two ATP nanosensors of the ATeam-family (ATeam1.03; ATeam1.03YEMK) with different affinities for ATP. Altering [ATP] by external stimuli resulted in characteristic pairs of signal changes of both nanosensors, which depend on [ATP] 0. Using this dual nanosensor strategy and epifluorescence microscopy, [ATP] 0 was estimated to be around 1.5 mM in primary cultures of cortical astrocytes from mice. Furthermore, in astrocytes in acutely isolated cortical slices from mice expressing both nanosensors after stereotactic injection of AAV-vectors, 2-photon microscopy revealed [ATP] 0 of 0.7 mM to 1.3 mM. Finally, the change in [ATP] induced in the cytosol of cultured cortical astrocytes by application of azide, glutamate, and an increased extracellular concentration of K + were calculated as −0.50 mM, −0.16 mM, and 0.07 mM, respectively. In summary, the dual nanosensor approach adds another option for determining the concentration of [ATP] to the increasing toolbox of fluorescent nanosensors for metabolites. This approach can also be applied to other metabolites when two sensors with different binding properties are available.

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“…We found that glucose, glycolytic and TCA cycle substrates, and glutathione are among the top accumulated metabolites. Suppressed glycolysis and dysfunctional TCA cycle that may lead to increased glucose and other intermediate metabolites, and elevated glutathione in response to reactive oxygen species, have been reported in AD (Atamna and Frey II 2007; Mandal et al 2019; Le Douce et al 2020). On the other hand, molecules involve in DNA synthesis and valine/leucine/isoleucine metabolism are most depleted in the AD neuron cells, which are consistent to the recently reported observations of suppressed DNA synthesis and valine metabolism in AD (Yurov et al 2011; Polis and Samson 2020).…”

Section: Resultsmentioning

confidence: 98%

A graph neural network model to estimate cell-wise metabolic flux using single cell RNA-seq data

Alghamdi

Chang

Dang

et al. 2020

Preprint

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The metabolic heterogeneity, and metabolic interplay between cells and their microenvironment have been known as significant contributors to disease treatment resistance. Our understanding of the intra-tissue metabolic heterogeneity and cooperation phenomena among cell populations is unfortunately quite limited, without a mature single cell metabolomics technology. To mitigate this knowledge gap, we developed a novel computational method, namely scFEA (single cell Flux Estimation Analysis), to infer single cell fluxome from single cell RNA-sequencing (scRNA-seq) data. scFEA is empowered by a comprehensively reorganized human metabolic map as focused metabolic modules, a novel probabilistic model to leverage the flux balance constraints on scRNA-seq data, and a novel graph neural network based optimization solver. The intricate information cascade from transcriptome to metabolome was captured using multi-layer neural networks to fully capitulate the non-linear dependency between enzymatic gene expressions and reaction rates. We experimentally validated scFEA by generating an scRNA-seq dataset with matched metabolomics data on cells of perturbed oxygen and genetic conditions. Application of scFEA on this dataset demonstrated the consistency between predicted flux and metabolic imbalance with the observed variation of metabolites in the matched metabolomics data. We also applied scFEA on publicly available single cell melanoma and head and neck cancer datasets, and discovered different metabolic landscapes between cancer and stromal cells. The cell-wise fluxome predicted by scFEA empowers a series of downstream analysis including identification of metabolic modules or cell groups that share common metabolic variations, sensitivity evaluation of enzymes with regards to their impact on the whole metabolic flux, and inference of cell-tissue and cell-cell metabolic communications.

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Impairment of Glycolysis-Derived l-Serine Production in Astrocytes Contributes to Cognitive Deficits in Alzheimer’s Disease

Cited by 167 publications

References 71 publications

d-serine in physiological and pathological brain aging

d-serine in physiological and pathological brain aging

A Dual Nanosensor Approach to Determine the Cytosolic Concentration of ATP in Astrocytes

A graph neural network model to estimate cell-wise metabolic flux using single cell RNA-seq data

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