Adam, Martina

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Switching from astrocytic neuroprotection to neurodegeneration by cytokine stimulation

2017-01, Efremova, Liudmila, Kranaster, Petra, Adam, Martina, Gutbier, Simon, Schildknecht, Stefan, Leist, Marcel

Astrocytes, the largest cell population in the human brain, are powerful inflammatory effectors. Several studies have examined the interaction of activated astrocytes with neurons, but little is known yet about human neurotoxicity under such situations and about strategies of neuronal rescue. To address this question, immortalized murine astrocytes (IMA) were combined with human LUHMES neurons and stimulated with an inflammatory (TNF, IL-1) cytokine mix (CM). Neurotoxicity was studied both in co-cultures and in monocultures after transfer of conditioned medium from activated IMA. Interventions with >20 drugs were used to profile the model system. Control IMA supported neurons and protected them from neurotoxicants. Inflammatory activation reduced this protection, and prolonged exposure of co-cultures to CM triggered neurotoxicity. Neither the added cytokines nor the release of NO from astrocytes were involved in this neurodegeneration. The neurotoxicity-mediating effect of IMA was faithfully reproduced by human astrocytes. Moreover, glia-dependent toxicity was also observed, when IMA cultures were stimulated with CM, and the culture medium was transferred to neurons. Such neurotoxicity was prevented when astrocytes were treated by p38 kinase inhibitors or dexamethasone, whereas such compounds had no effect when added to neurons. Conversely, treatment of neurons with five different drugs, including resveratrol and CEP1347, prevented toxicity of astrocyte supernatants. Thus, the sequential IMA-LUHMES neuroinflammation model is suitable for separate profiling of both glial-directed and directly neuroprotective strategies. Moreover, direct evaluation in co-cultures of the same cells allows for testing of therapeutic effectiveness in more complex settings, in which astrocytes affect pharmacological properties of neurons.


Prevention of the degeneration of human dopaminergic neurons in an astrocyte co-culture system allowing endogenous drug metabolism

2015-08, Efremova, Liudmila, Schildknecht, Stefan, Adam, Martina, Pape, Regina, Gutbier, Simon, Hanf, Benjamin, Bürkle, Alexander, Leist, Marcel

Background and purpose
Few neuropharmacological model systems use human neurons. Moreover, available test systems rarely reflect functional roles of co-cultured glial cells. There is no human in vitro counterpart of the widely used 1-methyl-4-phenyl-tetrahydropyridine (MPTP) mouse model of Parkinson's disease.

Experimental Approach
We generated such a model by growing an intricate network of human dopaminergic neurons on a dense layer of astrocytes. In these co-cultures, MPTP was metabolized to 1-methyl-4-phenyl-pyridinium (MPP+) by the glial cells, and the toxic metabolite was taken up through the dopamine transporter into neurons. Cell viability was measured biochemically and by quantitative neurite imaging, siRNA techniques were also used.

Key Results
We initially characterized the activation of PARP. As in mouse models, MPTP exposure induced (poly-ADP-ribose) synthesis and neurodegeneration was blocked by PARP inhibitors. Several different putative neuroprotectants were then compared in mono-cultures and co-cultures. Rho kinase inhibitors worked in both models; CEP1347, ascorbic acid or a caspase inhibitor protected mono-cultures from MPP+ toxicity, but did not protect co-cultures, when used alone or in combination. Application of GSSG prevented degeneration in co-cultures, but not in mono-cultures. The surprisingly different pharmacological profiles of the models suggest that the presence of glial cells, and the in situ generation of the toxic metabolite MPP+ within the layered cultures played an important role in neuroprotection.

Conclusions and Implications
Our new model system is a closer model of human brain tissue than conventional cultures. Its use for screening of candidate neuroprotectants may increase the predictiveness of a test battery.