PA exposure changes the transcriptional profile without modifying the neuronal morphology
To characterize the morphological consequences and neurite integrity after 24 h of exposure to PA, we first performed a qualitative analysis of the distribution of the cytoskeletal protein MAP2 in the hippocampal neurons (Fig. 1a). As shown, the MAP2 immunodetection was located mainly in the neurites, scarcely found in the neuronal soma and we did not observe evident effects on the neuronal morphology with 100 and 200 µM PA compared to the control condition. However, neurons exposed to 300 µM of PA showed a slight increase in the concentration of MAP2 into the soma and a fragmented pattern in the localization of this protein, suggesting dendritic blebbing. This distribution of MAP2 is consistent with the induction of localized swelling and may indicate toxic effects of PA at concentrations above of 300 µM. To estimate the neuronal lipid content after PA exposure we stained neurons with Oil Red. Spectrophotometric quantification showed that PA caused an increase in the neuronal content of lipid droplets (Fig. 1b), demonstrating the uptake and metabolization of this saturated fatty acid by hippocampal neurons. Hence, considering this effect and previous viability assays  we continued the experiments with the dose of 200 µM PA.
Given that the fatty acids per se can alter gene regulation in periphery cells and knowing that PA has pleiotropic effects, we then asked to what extent hippocampal neurons modify their transcriptomic profile after PA exposure. By RNAseq after 24 h of 200 μM PA, since different mapping methods can have different transcript detection sensitivities , we mapped sequences to both the rat’s genome and transcriptome. In addition, for each mapping and gene quantification method, we used two well established methods (DEseq2 and edgeR) for differential expression analyses, making a total of 4 different pipelines. This multiple analysis showed that the gene expression was not drastically altered (Fig. 2) and it revealed a total of 45 upregulated and 30 downregulated genes (Fig. 2a, b) in at least one pipeline. Genes such as Anptl4, Ugt8, Hmgcs2, Ccl2, and Insig1 were shared between the different pipelines (Supplementary Table 1), which suggest that these genes are strongly affected in the neurons by PA.
Clustering of differentially expressed genes (DEGs) showed that each experimental condition in a group behaves with a similar expression pattern (Fig. 2a) and suggests that the exposure to PA can cluster experimental conditions into two different groups but that between individuals, there are specific changes and alterations. Furthermore, as shown in the differential expression analysis (Fig. 2c, d), not only protein-coding genes are deregulated by this exposure but also long non-coding intergenic RNAs (LincRNAs) and small nuclear RNAs (snRNAs). All together these findings demonstrate that PA exposure is sufficient to induce changes in the transcriptional profile of neurons; suggesting that cellular mechanisms, even those involved in nuclear function, are being altered.
Changes in neuronal lipid metabolism and inflammatory pathways are induced by PA
To determine the biological processes and the DEGs that are modified after the PA exposure, we performed pathway enrichment analyses. Gene Ontology (GO) enrichment analysis (Fig. 3a) showed that among the top 20 functionally enriched biological processes the chemokine-mediated signaling pathway, fatty acid and chemokine responses, cholesterol biosynthetic pathway and insulin function were altered during this exposure, indicating that these processes are importantly involved in the neuronal response to PA.
In order to determine the relationships between enriched GO terms and DEGs, we constructed an interaction network using the clusterProfiler R package (Fig. 3c). We observe that the network forms a single connected component, pointing that most genes are GO-terms closely related and work together in similar processes. In this regard, Hmgcs2 and Insig1 are part of an important node for energy metabolism since it is known they are involved in the response to fatty acid, insulin, starvation, and cholesterol biosynthesis. The interaction network also showed that genes, such as Ccl2, involved in the cellular response to chemokines and the chemokine-mediated signaling pathway are related to lipid metabolism. These results suggest that PA might be altering the neuronal energy metabolism, particularly the lipid metabolism, and the inflammatory response through the induction of specific genes that are linked to both processes.
To further confirm and unravel some other biological processes affected by the exposure of neurons to PA, we performed the same enrichment analysis with Reactome  pathways (Fig. 4). This analysis confirmed the GO categories previously found not only by showing metabolism of lipids and the fatty acid cycle as important responsive pathways in neurons after PA exposure, but also revealed additional deregulated processes such as ion-channel transport and, strikingly, mitochondrial fatty acid beta-oxidation (Fig. 4a, b). The analysis of the interaction network showed that multiple genes involved in lipid metabolism are deregulated, such as Ugt8, Cyp51, Acot1 and Echs1, suggesting that the metabolism of lipids is one of the most relevant biological processes activated in response to PA (Fig. 4c). Furthermore, Echs1 and Acot1, also link the lipid metabolism with the mitochondrial beta-oxidation (Fig. 4c), which portraits them as important effectors in both processes. Overall, together GO and Reactome enrichment analyses and the interaction networks strongly indicate that PA is affecting mainly lipid utilization pathways, which is interesting and unexpected because they are believed to be not completely active in neurons.
Genes dependent on PPAR signaling and lipid metabolism are deregulated in neurons
GO term and pathway enrichment have the disadvantage that only DEGs are considered, however other relevant processes may be driven by subtle changes in multiple genes of the same biological pathway. In order to elucidate these, we performed Gene Set Enrichment Analysis (GSEA) which takes into account the whole list genes, both on KEGG  pathways (Fig. 5) and GO term gene sets (Supplementary Fig. 1). First, we found that after PA exposure the IL-17, TNF and MAPK signaling pathways are deregulated (Fig. 5). Suggesting that PA triggers inflammatory components in neurons. It is also shown that the fatty acid metabolism and catabolism (Fig. 5 and Supplementary Fig. 1), PPAR signaling pathway, the synthesis of ketone bodies (Fig. 5), cholesterol biosynthetic and metabolic processes (Supplementary Fig. 1) are likewise affected. This result indicates that neurons have lipid metabolism elements that sense and respond to a high dose of saturated fatty acids. Additionally, this analysis showed that PA can affect general cellular and biological processes like apoptosis and cellular senescence (Fig. 5), as well as specific neuronal processes like ensheathment of neurons and axons, axonogenesis and regulation of neurotransmitter levels (Supplementary Fig. 1).
In order to validate the results obtained by the RNAseq and to show that the PPAR signaling pathway is responding to the PA stimulus, we analyzed 4 genes by qRT-PCR. Hmgsc2 and Angptl4 are two genes implicated in lipid metabolism and regulated by the PPAR signaling pathway. Their mRNA quantification by qRT-PCR showed that both genes (Fig. 6a, b) are significantly increased in the hippocampal neurons that were exposed to 200 μM PA compared to the control condition. On the other hand, Ugt8 and Rnf145, two other genes implicated in lipid metabolism but not regulated by the PPAR signaling pathway were downregulated (Fig. 6c, d). Overall, these results and the presence of lipid bodies (Fig. 1b) demonstrate that when exposed to PA, neurons modify their transcriptional profile affecting the lipid metabolism through signaling pathways that are known to respond to fatty acid stimulus in periphery cells.