Transcriptional and metabolic effects of aspartate-glutamate carrier isoform 1 (AGC1) downregulation in mouse oligodendrocyte precursor cells (OPCs)

Abstract

Aspartate-glutamate carrier isoform 1 (AGC1) is a carrier responsible for the export of mitochondrial aspartate in exchange for cytosolic glutamate and is part of the malate-aspartate shuttle, essential for the balance of reducing equivalents in the cells. In the brain, mutations in SLC25A12 gene, encoding for AGC1, cause an ultra-rare genetic disease, reported as a neurodevelopmental encephalopathy, whose symptoms include global hypomyelination, arrested psychomotor development, hypotonia and seizures. Among the biological components most affected by AGC1 deficiency are oligodendrocytes, glial cells responsible for myelination processes, and their precursors [oligodendrocyte progenitor cells (OPCs)]. The AGC1 silencing in an in vitro model of OPCs was documented to cause defects of proliferation and differentiation, mediated by alterations of histone acetylation/deacetylation. Disrupting AGC1 activity could possibly reduce the availability of acetyl groups, leading to perturbation of many biological pathways, such as histone modifications and fatty acids formation for myelin production. Here, we explore the transcriptome of mouse OPCs partially silenced for AGC1, reporting results of canonical analyses (differential expression) and pathway enrichment analyses, which highlight a disruption in fatty acids synthesis from both a regulatory and enzymatic stand. We further investigate the cellular effects of AGC1 deficiency through the identification of most affected transcriptional networks and altered alternative splicing. Transcriptional data were integrated with differential metabolite abundance analysis, showing downregulation of several amino acids, including glutamine and aspartate. Taken together, our results provide a molecular foundation for the effects of AGC1 deficiency in OPCs, highlighting the molecular mechanisms affected and providing a list of actionable targets to mitigate the effects of this pathology.

Keywords: Mitochondria; Neurodevelopment; Oligodendrocytes; Omics analysis; SLC25A12/aralar1/AGC1 deficiency; White matter disorder.

Fig. 1

Western blots and relative densitometries of AGC1 and AGC2 in Oli-Neu cells (a, b). GAPDH was used as control and for endogenous normalization. Values are mean ± standard error of the mean (s.e.m.) of at least three independent experiments; ***p < 0.001, **p < 0.01, *p < 0.05, compared with control Oli-Neu; Student’s t-test. Principal component analysis (PCA) of control and kdAGC1 samples gene expression data based on rlog-normalized reads values (c). SLC25A12 (AGC1) and SLC25A13 (AGC2) expression values [transcripts per million (TPMs)] with respective fold changes and significance levels (d, e)

Fig. 2

Volcano plot of kdAGC1 samples versus control (a). The X axis represents the magnitude of the change in expression levels, while the Y axis represents the significance of the change. Significance threshold was set to p adjusted < 0.05. Points in red are genes that are both significant and show |log₂FC| > 1, while blue points indicate genes that are significant and have |log₂FC| < 1. Points in gray represent genes that do not pass both thresholds. Enrichment score values (“combined score”) and significance levels for the top ten scoring Gene Ontology pathways obtained from gene set enrichment analysis (GSEA) (b). Scaled TPM values heatmap of a panel of genes that resulted as significant form differential gene expression analysis, for which log₂FC and p adjusted values are reported on the right of the heatmap (c)

Fig. 3

Western blot and relative densitometries of FASN (a, b), ACSS1 (a, c), and precursor and cleaved SREBP1 (a, d, e) expression in Oli-Neu cells; GAPDH was used for endogenous normalization. Confocal microscopy images (f) in Oli-Neu cells; nuclei were labelled with DAPI. Scale bar, 20 µm; 100× objective. Reverse transcription real-time PCR analysis (g). GAPDH were used as endogenous controls. Values are mean ± standard deviation (SD) of at least three independent experiments; ***p < 0.001, **p < 0.01, *P < 0.05, compared with control Oli-Neu; Student’s t-test

Fig. 4

Western blot and relative densitometries of FASN (a, b), ACSS1 (a, c), and precursor and cleaved SREBP1 (a, d, e) expression in AGC1^+/− and AGC1^+/+ neurospheres; GAPDH was used for endogenous normalization. Confocal microscopy images (f) in neurospheres; nuclei were labeled with DAPI. Scale bar 50 µm; 60 × objective. Reverse transcription real-time PCR analysis (g). GAPDH were used as endogenous controls. Values are mean ± standard deviation (SD) of at least three independent experiments; ***p < 0.001, **p < 0.01, *p < 0.05, compared with AGC1^+/+ control neurospheres Student’s t-test

Fig. 5

Master regulator analysis of PROX1 and SMARCC2 in two different networks (frontal cortex and hippocampus) showing the most significant transcription factors with differentially activated networks in kdAGC1 versus control (a). The upper bar shows the symbol of the tested master regulator, its normalized enrichment score (NES), with its cell colored in red for activated regulons and blue for downregulated regulons, and the associated adjusted p value. The barcode graph indicates the distribution of activated (red bars) and repressed (blue bars) targets of a master regulator. Target genes are ranked from left to right from most downregulated to most upregulated according to kdAGC1 versus control signature. The plot on the right shows the most significantly altered targets of a master regulator’s regulon, with a line indicating the master regulator as an activator (arrowhead) or a repressor (blunted end) and the color on the target showing whether it is upregulated (red) or downregulated (blue) in the signature. Local splicing variations (LSVs) graph of PMP22 and RARG showing on the left the splicing events relative to a specific exon and on the right the values of the most relevant events’ ΔPSI values (b). Violin plots express the expected dPSI values, with values above 0 representing a prevalence of the splicing event in kdAGC1 samples, while values below 0 represent a prevalence in control samples. Bar graph showing concentrations (ng/mL) and relative error bars in kdAGC1 and control samples. Metabolites are sorted left to right according to increasing p values (*p < 0.05; c). Significance levels are reported with asterisks. Reported p values were corrected using the Benjamini–Hochberg method. Separated analysis and graphs of metabolites quantification for cell pellets and media are in Additional file 5: Figs. S5 and S6