The pro-inflammatory cytokine tumor necrosis factor α (TNFα) tunes the capacity of neurons to express synaptic plasticity. It remains, however, unclear how TNFα mediates synaptic positive (=change) and negative (=stability) feedback mechanisms. We assessed effects of TNFα on microglia activation and synaptic transmission onto CA1 pyramidal neurons of mouse organotypic entorhino–hippocampal tissue cultures. TNFα mediated changes in excitatory and inhibitory neurotransmission in a concentration-dependent manner, where low concentration strengthened glutamatergic neurotransmission via synaptic accumulation of GluA1-only-containing AMPA receptors and higher concentration increased inhibition. The latter induced the synaptic accumulation of GluA1-only-containing AMPA receptors as well. However, activated, pro-inflammatory microglia mediated a homeostatic adjustment of excitatory synapses, that is, an initial increase in excitatory synaptic strength at 3 h returned to baseline within 24 h, while inhibitory neurotransmission increased. In microglia-depleted tissue cultures, synaptic strengthening triggered by high levels of TNFα persisted and the impact of TNFα on inhibitory neurotransmission was still observed and dependent on its concentration. These findings underscore the essential role of microglia in TNFα-mediated synaptic plasticity. They suggest that pro-inflammatory microglia mediate synaptic homeostasis, that is, negative feedback mechanisms, which may affect the ability of neurons to express further plasticity, thereby emphasizing the importance of microglia as gatekeepers of synaptic change and stability.

Transcriptome analysis

Tissue cultures (n = 3) were transferred as one sample into 250 μL RNAlater (Thermo Fisher Scientific, Cat# AM7020) and stored at −20°C. RNA was isolated after homogenization with TRIzol (Thermo Fisher Scientific, Cat# 15596018) using the Direct-zol RNA Microprep-Kit (Zymo Research, Freiburg im Breisgau, Germany, Cat# R2061) according to the manufacturer's instructions. RNA was eluted in 50 μL water and precipitated with 0.75 M ammonium-acetate and 10 μg glycogen (Thermo Fisher Scientific, Cat# R0551) by adding 125 μL ethanol (100%). Samples were incubated at −80°C overnight and consecutively centrifuged for 30 min at 4°C. Pellets were washed with 70% ethanol, centrifuged again and dried. Finally, pellets were dissolved in water for further processing. RNA concentration and integrity were consecutively analyzed by capillary electrophoresis using a Fragment Analyzer (Advanced Analytical Technologies, Inc., Ankeny, IA, USA) and the Agilent RNA 6000 Pico Kit (Agilent, Cat# 5067-1513). RNA samples with RNA integrity numbers (RIN) > 8.0 were further processed with the Affymetrix WT Plus kit and hybridized to Clariom S mouse arrays (Thermo Fisher Scientific, Cat# 902931) as described by the manufacturer. Briefly, labeled fragments were hybridized to arrays for 16 h at 45°C, 60 rpm in a GeneChip™ Hybridization Oven (Thermo Fisher Scientific). After washing and staining, the arrays were scanned with the Affymetrix GeneChip Scanner 3000 7G (Thermo Fisher Scientific). CEL files were produced from the raw data with Affymetrix GeneChip Command Console Software Version 4.1.2 (Thermo Fisher Scientific). CEL files were processed with the Oligo R package and RNA and intensity were normalized using Robust Multichip Average method. A linear-model-based analysis, limma R package (Ritchie et al., 2015), was used to identify differentially regulated genes. An adjusted p-value (Benjamini & Hochberg) below 0.05 was considered as significant. Gene-set enrichment analysis was done using GSEA 4.1.0 (Mootha et al., 2003; Subramanian et al., 2005), Cytoscape (Shannon et al., 2003) and custom R-scripts to produce heatmaps.

Transcriptome Analysis Console 4.0 (Applied Biosystems).

R-4.3.1, oligo R package, limma R package, GSEA 4.1.0.