Editor's evaluation: APOE expression and secretion are modulated by mitochondrial dysfunction

Field: Biochemistry, Genetics and Molecular Biology (Life Sciences)

Full text Figures and data Side by side Abstract Editor's evaluation Introduction Results Discussion Materials and methods Data availability References Decision letter Author response Article and author information Metrics Abstract Mitochondria influence cellular function through both cell-autonomous and non-cell autonomous mechanisms, such as production of paracrine and endocrine factors. Here, we demonstrate that mitochondrial regulation of the secretome is more extensive than previously appreciated, as both genetic and pharmacological disruption of the electron transport chain caused upregulation of the Alzheimer’s disease risk factor apolipoprotein E (APOE) and other secretome components. Indirect disruption of the electron transport chain by gene editing of SLC25A mitochondrial membrane transporters as well as direct genetic and pharmacological disruption of either complexes I, III, or the copper-containing complex IV of the electron transport chain elicited upregulation of APOE transcript, protein, and secretion, up to 49-fold. These APOE phenotypes were robustly expressed in diverse cell types and iPSC-derived human astrocytes as part of an inflammatory gene expression program. Moreover, age- and genotype-dependent decline in brain levels of respiratory complex I preceded an increase in APOE in the 5xFAD mouse model. We propose that mitochondria act as novel upstream regulators of APOE-dependent cellular processes in health and disease. Editor's evaluation This study presents compelling evidence that ApoE is upregulated in various models of mitochondrial respiratory chain dysfunction. The work is of fundamental interest for those studying neurodegeneration and the role of ApoE in Alzheimer's disease; future work will be needed to reveal the molecular basis of this dramatic phenotype. https://doi.org/10.7554/eLife.85779.sa0 Decision letter eLife's review process Introduction Mitochondria are necessary for maintaining cellular and organismal health and function by generating energy and serving as hubs for diverse metabolic and signaling pathways (Nunnari and Suomalainen, 2012). The majority of the mitochondrial functions described so far are cell-autonomous. However, mitochondria are also capable of influencing cellular function from a distance in a non-cell-autonomous manner. These non-cell-autonomous mechanisms, mostly elicited after cellular or mitochondrial damage, encompass intercellular transfer of mitochondria to secretion of endocrine and paracrine factors (D’Acunzo et al., 2021; Durieux et al., 2011; Hayakawa et al., 2016; Liu et al., 2021). These secreted factors include proteins encoded in the nuclear genome, such as alpha-fetoprotein, inflammatory cytokines and type I interferons, and growth factor mitokines (Bar-Ziv et al., 2020; Chung et al., 2017; Dhir et al., 2018; Durieux et al., 2011; Jett et al., 2022; Kim et al., 2013; Riley and Tait, 2020; Shimada et al., 2012; West et al., 2015). A second class of non-cell-autonomous factors are mitochondrially derived peptides, encoded in the mitochondrial genome (Kim et al., 2017). Mitokines and mitochondrially derived peptides modulate cell survival, metabolic and lipid homeostasis, body weight, longevity, and aging, a primary risk factor for cognitive decline in humans (Chung et al., 2017; Flippo and Potthoff, 2021; Klaus and Ost, 2020; Mullican et al., 2017; Tsai et al., 2018). In models of Alzheimer’s disease, the mitochondrially derived peptide humanin can reduce apoptosis, inflammation, accumulation of plaque-forming Aβ peptides, and cognitive deficits (Hashimoto et al., 2001; Tajima et al., 2005; Yen et al., 2013). The ability of factors encoded in the nuclear and mitochondrial genomes to regulate inflammation, lipid metabolism, aging, and Alzheimer’s disease mechanisms suggests that mitochondrial-dependent modulation of protein secretion could modify neurological disease pathogenesis prior to cell death. Here, we sought to identify proteins whose expression and secretion are modulated by mitochondrial function through an unbiased interrogation of human transcriptomes and proteomes. We focused our attention on factors whose expression is sensitive to mutations affecting the inner mitochondrial membrane citrate transporter SLC25A1 and the ADP-ATP transporter SLC25A4 (ANT1). We chose these mitochondrial transporters because they have been genetically implicated in neurodevelopment, brain metabolism, psychiatric disease, and neurodegeneration (Balaraju et al., 2020; Chaouch et al., 2014; Edvardson et al., 2013; Gokhale et al., 2019; Akita et al., 2018; Lin-Hendel et al., 2016; Nota et al., 2013; Rigby et al., 2022; Siciliano et al., 2003). For example, SLC25A1 is a causal gene in two genetic diseases: a severe neurometabolic disease (combined D-2- and L-2-hydroxyglutaric aciduria) and a congenital myasthenic syndrome presenting with intellectual disability (Balaraju et al., 2020; Chaouch et al., 2014; Nota et al., 2013) (OMIM 615182–618197). In addition, SLC25A1 is part of the chromosomal interval deleted in 22q11.2 deletion syndrome, a microdeletion syndrome associated with neurodevelopmental, psychiatric, and neurodegenerative diseases (Butcher et al., 2013; Schneider et al., 2014; Zinkstok et al., 2019). SLC25A1 has been implicated as a hub factor underlying a mitochondrial protein network, which includes SLC25A4, that is disrupted in 22q11.2 deletion syndrome cells (Gokhale et al., 2019). Since SLC25A1 and SLC25A4 coprecipitate (Gokhale et al., 2019), we hypothesized the existence of common downstream secretory and mitochondrial targets elicited by their mutation. We discovered that loss of SLC25A1 or SLC25A4 affected the secreted proteome as well as the mitochondrially annotated proteome. Apolipoprotein E (APOE) was among the secreted factors whose expression was increased in both SLC25A1 and SLC25A4 mutants. We focused on APOE since it is the main carrier of lipids and cholesterol in the brain (Mahley, 2016) and it is tied to cognitive function, neuroinflammation, and neurological disease risk (Belloy et al., 2019; Lanfranco et al., 2021; O’Donoghue et al., 2018; Parhizkar and Holtzman, 2022). Importantly, the APOE4 allele is known as the strongest genetic risk factor for sporadic Alzheimer’s disease (Belloy et al., 2019). We found that APOE expression was increased by mutations of mitochondrial SLC25A transporters, which indirectly compromised the integrity of the electron transport chain, and was also increased by directly mutagenizing either assembly factors or subunits of complexes I, III, and IV of the electron transport chain. While the APOE4 allele is thought to cause mitochondrial dysfunction in Alzheimer’s disease (Area-Gomez et al., 2020; Chen et al., 2011; Mahley, 2023; Orr et al., 2019; Tambini et al., 2016; Yin et al., 2020), our study places mitochondria upstream of APOE, uncovering a novel function for these multifaceted organelles. Results Genetic disruption of inner mitochondrial membrane transporters alters the secretome Our goal was to identify secreted factors whose expression is modulated by genetic defects in nuclear-encoded mitochondrial genes. We hypothesized that changes in the secretome would affect the capacity of conditioned media to support cell growth in a genotype-dependent manner. Thus, we applied conditioned media from wild-type (SLC25A1+) and SLC25A1-null HAP1 cells (SLC25A1Δ) to cells from both genotypes and measured cell growth. We used this near-haploid human leukemia cell line since it has a short doubling time, and thus rapid protein turnover, making it well-suited to rapidly respond to changes in subproteomes, such as the secretome and mitoproteome. We dialyzed conditioned media from wild-type and SLC25A1Δ cells to exclude effects of metabolites, pH, and small peptides present in media (Figure 1A). Dialyzed conditioned media from wild-type and SLC25A1Δ cells supported wild-type cell growth (Figure 1A). Wild-type cells similarly responded to dialyzed media from both genotypes, increasing growth by 50% as compared to non-dialyzed media (Figure 1A compare columns 1, 3 and 2, 4). In contrast, while SLC25A1Δ cells fed with wild-type dialyzed conditioned media doubled in number (Figure 1A, compare columns 5 and 7), dialyzed conditioned media from SLC25A1Δ cells fed onto themselves did not support their growth as compared to media from wild-type cells (Figure 1A compare columns 7–8 and 6–8). These results suggest that wild-type cells and SLC25A1Δ cells condition media differently. Figure 1 Download asset Open asset The secreted and mitochondrial proteomes are Modified by Inner Mitochondrial Membrane Transporter Mutants. (A) Cell number determinations of wild-type (columns 1–4) and SLC25A1-null HAP1 cells (SLC25A1Δ, columns 5–8) grown in the presence of conditioned media from each genotype. Conditioned media was applied to cells for 48 hr before (columns 1, 2, 5, and 6) or after dialysis (columns 3, 4, 7, and 8). Cell number was determined by Alamar blue cell viability assay. FU, Normalized Alamar Blue Fluorescence Units. Mean ± SEM, n=5, Two-Way ANOVA followed by Benjamini, Krieger and Yekutieli corrections. (B–C) Volcano plots of TMT proteomic data from wild-type HAP1 cells (n=3), SLC25A1Δ (B, n=3 for two independent CRISPR clones), and SLC25A4Δ mutants (C, n=3), depicted are log10 p values and log2 fold of change. (D) Principal component analysis and 2D-tSNE analyses of datasets in B-C. (E) Hierarchical clustering of all proteome hits where differential expression is significant with an α<0.001 in at least one mutant genotype. (F–G) Volcano plots of RNAseq data from wild-type HAP1 cells (n=4), SLC25A1Δ (B, n=4 for one independent CRISPR clone), and SLC25A4Δ mutants (C, n=4), depicted are log10 p values and log2 fold of change. (H) PCA and 2D-tSNE analyses of datasets in F-G. Subject grouping was determined by k-means clustering. (I) Hierarchical clustering of all RNAseq hits where differential expression is significant with an α=0.001 in at least one mutant genotype. (J) Venn diagram of protein and transcript hits shared by SLC25A1Δ and SLC25A4Δ mutants. Twenty-seven shared protein and RNA hits are annotated to either the human secretome (orange font) or annotated to Mitocarta 3.0 (green font). CROT was downregulated and upregulated in SLC25A1Δ and SLC25A4Δ mutants, respectively. (K) Venn diagram of protein hits in SLC25A1Δ and SLC25A4Δ mutants annotated in Mitocarta 3.0. (L) Venn diagram of protein hits in SLC25A1Δ and SLC25A4Δ mutants annotated in the Human Secretome (Uhlén et al., 2019). (M) Hierarchical clustering of all proteins annotated to the human secretome across genotypes. (N) Magnitude of compromise in secreted and mitochondrial proteomes in SLC25A1Δ and SLC25A4Δ mutants. p value was calculated with exact hypergeometric probability. (O–P) Gene ontology analysis of proteome (O) and transcriptome (P) in SLC25A1Δ and SLC25A4Δ mutants. Overlapping and mutant-specific ontologies are color-coded by percent of contribution >50% to an ontological category. Gray represents ontologies where all three mutants similarly contribute hits. To identify compositional differences between wild-type and SLC25A1Δ conditioned media, we analyzed the proteome and transcriptome of SLC25A1Δ cells (Figure 1B, D–F–). Fetal bovine serum in media prevented us from a direct analysis of the conditioned media by mass spectrometry. We annotated the SLC25A1Δ proteome and transcriptome with the human secretome database (Uhlén et al., 2019) and the Mitocarta 3.0 knowledgebase (Rath et al., 2021) to comprehensively identify differences in secreted factors and the consequences of the SLC25A1 mutation on mitochondria. We simultaneously analyzed the proteome and transcriptome of SLC25A4Δ cells to determine whether changes in the SLC25A1Δ proteome and transcriptome resulted specifically from the loss of SLC25A1 or could be generalized to another inner mitochondrial membrane transporter (Figure 1C and G). We selected SLC25A4, as it encodes an ADP-ATP translocator that interacts with SLC25A1 (Gokhale et al., 2019). Tandem mass tagging mass spectrometry and RNAseq revealed that SLC25A1Δ cells underwent more extensive changes of their proteome and transcriptome than SLC25A4Δ cells (compare Figure 1B with C and F with G). For example, 668 proteins significantly changed their expression in SLC25A1Δ cells compared to 110 proteins in SLC25A4Δ cells (log2 fold of change of 0.5 and p<0.05, Figure 1B and C). Similarly, the SLC25A1Δ transcriptome was represented by 2433 transcripts whose expression was changed in SLC25A1-null cells, a fourfold difference compared to the 560 transcripts found in SLC25A4Δ cells (log2 fold of change of 1 and p<0.001, Figure 1F and G). Principal component analysis and 2D-tSNE analysis indicated that the whole measured proteome and transcriptome of SLC25A1Δ cells diverged strongly from wild-type cells, while SLC25A4Δ cells were more closely related to wild-type cells than SLC25A1Δ cells (Figure 1D and H). The same outcome was obtained by unsupervised clustering when considering proteins and transcripts significantly changed in at least one of these genotypes (Figure 1E, I), as SLC25A4Δ clustered with wild-type cells rather than SLC25A1Δ cells. Despite the abundance of altered gene products in these SLC25A1Δ and SLC25A4Δ datasets, there was limited overlap in proteomes and transcriptomes, with only 84 proteins and 385 mRNAs shared by both genotypes (Figure 1J). Notably, the congruency of the shared proteomes and transcriptomes reached only 0.9% of all the gene products whose expression was modified. This represents 27 proteins and transcripts similarly modified in SLC25A1Δ and SLC25A4Δ datasets (Figure 1J). Of these 27 common hits, one was annotated to mitochondria, FASTKD2, and five were annotated to the secreted human proteome, including soluble proteins such as apolipoprotein E (APOE) and cytokine receptor-like factor 1 (CRLF1; Elson et al., 1998; Wernette-Hammond et al., 1989; Figure 1J). APOE protein and transcript were among the most upregulated factors in both SLC25A1Δ and SLC25A4Δ cells (Figure 1B–C and F–G). Close to 10% of all the SLC25A1Δ and SLC25A4Δ proteome hits were proteins annotated to mitochondria, with a discrete overlap of 10 mitochondrial proteins between these two mutant genotypes, mostly downregulated constituents of complex III of the electron transport chain (Figure 1K, UQCRB11, UQCRB, UQCRC2, and UQCRQ) as well as a factor required for the assembly of respiratory supercomplexes, COX7A2L (Figure 1K; Lobo-Jarne et al., 2018). The enrichment of secreted proteome annotated proteins was modest yet significant in SLC25A1Δ and SLC25A4Δ cells. Surprisingly, this degree of enrichment in components of the secretome was comparable to the enrichment of Mitocarta 3.0 annotated proteins in both mitochondrial mutants (Figure 1L, M and N). These results show that mutations affecting two inner mitochondrial membrane transporters, SLC25A1 and SLC25A4, similarly affect the secreted and mitochondrial proteomes. We analyzed SLC25A1Δ and SLC25A4Δ datasets for additional commonalities at the ontological level, using the ClueGO tool to annotate datasets based on genotype and whether a factor was up- or down-regulated. The annotated datasets were used to simultaneously query the KEGG, REACTOME and GO CC databases. The proteome and transcriptome of both mutants identified developmental ontologies as shared terms, irrespective of whether factors were up- or down-regulated (Figure 1O–P gray nodes and Supplementary file 1; tissue development GO:0009888, Bonferroni corrected P=1.9E-26 and 2.3E-11 for the transcriptome and proteome, respectively). However, there were ontologies that stood out by their genotype- and up-regulation-dependent specificity. For instance, the most prominent ontology annotated to up-regulated SLC25A1Δ proteome and transcriptome hits was steroid biosynthesis (KEGG:00100, Bonferroni corrected P=3.6E-8 and 1.9E-8 for the transcriptome and proteome, respectively; Figure 1O–P). However, the expression of genes annotated to sterol biosynthesis ontologies was not modified in SLC25A4Δ mutants, even though the proteome and transcriptome of SLC25A4Δ cells showed increased expression of APOE, a cholesterol transport lipoprotein. These findings suggest that expression of APOE and other hits common between these two mutant genotypes occurs independently from modifications in cholesterol synthesis pathways. APOE expression is uncoupled from changes in cholesterol synthesis pathways We focused on APOE and the sterol biosynthesis pathways to validate our proteome and transcriptome data. We also determined whether cholesterol synthesis pathways correlated with increased APOE expression in SLC25A1Δ and SLC25A4Δ cells. Electrochemical MesoScale ELISA determinations of APOE with a human-specific antibody revealed increased APOE in cell lysates and conditioned media from SLC25A1Δ and SLC25A4Δ cells (Figure 2A and Figure 2—figure supplement 1; Chikkaveeraiah et al., 2012; Gaiottino et al., 2013). APOE protein expression and secretion into media were increased ~5–20 times in two CRISPR SLC25A1Δ clones and SLC25A4Δ cells (Figure 2A compare column 1 with 2–4 and Figure 2—figure supplement 1 compare columns 1, 3, and 5 with 7, 9, and 11). APOE signal in complete media unexposed to cells was undetectable (Figure 2A compare media columns 1 with 5). APOE present in media and cells was sensitive to protein synthesis inhibition with cycloheximide (Figure 2—figure supplement 1 compare columns 1–2 and 7–8) and to disruption of the secretory pathway with brefeldin A (Figure 2—figure supplement 1 compare columns 3–4 and 9–10). Additionally, the lysosome protease inhibitor E-64 minimally affected APOE levels; thus, making unlikely the contribution of lysosomes to the genotype-dependent differences in APOE levels (Figure 2—figure supplement 1 compare columns 5–6 and 11–12). We confirmed the increased levels of APOE in cells by immunoblot with a different APOE antibody. We used recombinant human APOE as a standard (Figure 2B). To exclude that an APOE expression increase was a haploid HAP1 cell peculiarity, we confirmed the increased levels of APOE in the diploid human neuroblastoma cell line SH-SY5Y where we CRISPRed out the SLC25A1 gene (Figure 2C SLC25A1Δ/Δ). Much like HAP1 cells, SLC25A1Δ/Δ cells increased secretion of APOE by ~fourfold, in both cells and conditioned media, compared with wild-type cells (Figure 2C, compare lanes 1 and 2). These results reveal a robust upregulation of both cellular and secreted APOE across mutant cell types. Figure 2 with 1 supplement see all Download asset Open asset APOE transcripts and protein are upregulated independent from cholesterol levels in SLC25A1 and SLC25A4 mutants. (A) MesoScale electrochemiluminescence solid phase ELISA determinations of human APOE in wild-type (column 1), SLC25A1Δ (columns 2 and 3), and SLC25A4Δ (column 4) HAP1 mutant cell lysates and conditioned media. Two independent SLC25A1Δ clones were tested (columns 2–3). Column 5 depicts complete media not exposed to cells. n=4. (B) APOE immunoblot of cellular extracts from wild-type, SLC25A1Δ, and SLC25A4Δ HAP1 mutant cells. HSP90 was used as a loading control. Lane 4 presents recombinant human APOE (rAPOE). In bold is the predicted molecular weight of rAPOE. (C) MesoScale ELISA measurements of human APOE in wild-type and SLC25A1Δ/Δ SH-SY5Y mutant cell lysates and conditioned media. (D–F) qRT-PCR quantification of APOE, sterol metabolism annotated genes, and housekeeping controls (VAMP2 and RPS20) in wild-type and diverse mutant cell lines. (D) and (E) show transcript levels in SLC25A1Δ and SLC25A4Δ HAP1 mutant cells, respectively. (F) depicts transcript levels in SLC25A1Δ/Δ SH-SY5Y mutant cells. All data are expressed as transcript ratio between mutant and wild-type. n=3 for D-F. (G–I) Volcano plots of positive mode untargeted lipidomics performed in SLC25A1Δ, SLC25A4Δ, and SLC25A1Δ/Δ mutant HAP1 and SH-SY5Y cells and their controls. Upper inserts present the distribution of cholesterol ester and triglyceride species marked by triangles. Depicted are log10 p values and log2 fold of change. n=4 per clone for the two SLC25A1Δ clones, n=4 for SLC25A4Δ, and n=4 for SLC25A1Δ/Δ. (J). Total cellular levels of free cholesterol (Ch), cholesterol ester (ChE), and triglycerides (TG) in wild-type, SLC25A1Δ, and SLC25A4Δ HAP1 cells. (K). Total cellular levels of free cholesterol (Ch), cholesterol ester (ChE), and triglycerides (TG) in wild-type and SLC25A1Δ/Δ SH-SY5Y cells. Average ± SEM, One-way ANOVA followed by Bonferroni or Holm-Šydák’s (D–F) multiple corrections, or unpaired t-test (K). See available source data for (B). Figure 2—source data 1 Original blots. https://cdn.elifesciences.org/articles/85779/elife-85779-fig2-data1-v2.zip Download elife-85779-fig2-data1-v2.zip Figure 2—source data 2 Original blots. https://cdn.elifesciences.org/articles/85779/elife-85779-fig2-data2-v2.zip Download elife-85779-fig2-data2-v2.zip If APOE expression depends on modifications in cholesterol pathways then the expression of genes annotated to cholesterol metabolism and cholesterol content should be similarly modified in SLC25A1Δ and SLC25A1Δ/Δ cells. We measured the transcript levels of APOE and genes involved in cholesterol uptake and synthesis, in SLC25A1Δ, SLC25A4Δ, and SLC25A1Δ/Δ cells. We focused on the LDL receptor (LDLR), as well as cholesterol synthesis enzymes, ACAT2, MSMO1 and HMGCR, the latter the of the cholesterol synthesis pathway and et al., 2013). We chose these genes as upregulated hits from the transcriptome of SLC25A1Δ cells. We used and as housekeeping gene controls (Figure APOE increased in all three mutant cells. In contrast, the expression of cholesterol synthesis pathway genes was increased in SLC25A1Δ (Figure not in SLC25A4Δ and SLC25A1Δ/Δ cells (Figure and The upregulation of cholesterol synthesis pathway genes resulted in a significant increase of cholesterol and all species content in SLC25A1Δ cells, as determined by mass spectrometry (Figure and and other measured lipid were in wild-type and SLC25A1Δ cells (Figure and In contrast, cholesterol and species were not modified in SLC25A4Δ (Figure and and SLC25A1Δ/Δ cells (Figure and even though the expression of APOE was upregulated to the same in all these mutant cells. These results unlikely the that increased APOE expression is to an upregulation of cholesterol synthesis pathways. of the electron transport chain complexes I and III APOE expression We our attention to common defects in SLC25A1Δ and SLC25A4Δ HAP1 cells that could the increased expression of A shared in both mutants was a in the levels of complex III subunits and the assembly factor COX7A2L (Figure We hypothesized that defects in the integrity of the electron transport chain could the increased levels of To this we determined the effects of SLC25A1 and SLC25A4 mutations on the of the electron transport chain by blue we assembly factors and subunits of complexes I and III and and IV of the electron transport chain and and measured APOE levels et al., 2018; et al., 2022; et al., et al., We determined the of the increased APOE by studying mutants in three human cell and which in including their genetic of and tissue of We measured the expression of electron transport chain subunits by in HAP1 cells. We found that even though complex III was affected in both SLC25A1Δ and SLC25A4Δ cells and and Figure supplement the most was in the expression of complex I subunits in SLC25A1Δ cells (Figure We the integrity of respiratory chain complexes in SLC25A1Δ cells by blue and (Figure We performed immunoblot analysis of respiratory complex subunits with subunits that in respiratory complexes et al., 2018; et al., 2021). These revealed that the most subunits were those from complexes I and III (Figure We then analyzed respiratory complexes by blue and found expression of molecular weight complexes UQCRC2, and which to subunits of the respiratory complexes I, III, and (Figure showed that molecular weight respiratory complexes subunits of complexes I and III were in SLC25A1Δ cells (Figure Similarly, SLC25A4Δ HAP1 cells levels of complex III subunits (Figure supplement thus affecting the of complex in blue (Figure supplement The of the SLC25A4 mutation on APOE expression was not to a in the SLC25A4 transport as the SLC25A4 inhibitor did not increase the levels of APOE (Figure supplement compare columns 1 with 2 and 3), even at that mitochondrial to the same as the SLC25A4 mutation (Figure supplement and 2013). Figure 3 with 3 see all Download asset Open asset The integrity of respiratory chain complex I is required to APOE (A) of respiratory complex subunits in wild-type and SLC25A1Δ HAP1 cells by TMT mass spectrometry. clustering (B) with antibody in mitochondrial from wild-type and SLC25A1Δ cells. (C) Blue of mitochondrial from wild-type and SLC25A1Δ cells. are and with I, III, and (D) Blue followed by then immunoblot with I, III, and in mitochondrial from wild-type and SLC25A1Δ cells. APOE and APOE MesoScale ELISA analysis in wild-type and HAP1 cells. In APOE was measured with two APOE and APOE MesoScale ELISA analysis in wild-type and HAP1 cells. or transcripts were used as controls in F and All qRT-PCR data are expressed as ratio between mutant and wild-type. to ± ANOVA followed by multiple or unpaired t-test with I, and in E and show of and the (K) SLC25A1Δ cells are more sensitive to than wild-type HAP1 cells. type and SLC25A1Δ cells were exposed to or increasing of cellular was measured for after using Data are to in the of Average ± SEM, Gray significant differences between wild-type and SLC25A1Δ cells as determined by multiple unpaired followed by with the APOE qRT-PCR and APOE MesoScale ELISA in wild-type and SLC25A1Δ HAP1 cells, with or was used in to was used in MesoScale ELISA (columns 1–4) and transcripts (columns 5–8) were used as housekeeping controls. All qRT-PCR data are expressed as ratio between mutant and wild-type. Average ± SEM, One-way ANOVA followed by multiple See available source data for and C). Figure data 1 Original and blots. Download Figure data 2 Original and blots. Download The loss of integrity in complexes I and III in SLC25A1Δ and SLC25A4Δ HAP1 cells suggest that respiratory chain defects could be for the increased expression of We tested this by complexes I and III using genetic and pharmacological (Figure 3 and Figure supplement 2). We genetically complex I assembly and function by either or or by using the complex I inhibitor A (Figure supplement et al., encodes protein 3, a of complex I necessary for complex I assembly and et al., et al., 2021). encodes complex assembly factor 7, a necessary for the