Impaired mitochondrial bioenergetics in macrophages can drive hyperinflammatory cytokine production, but whether this is caused by inherited mtDNA mutations is unknown. Here, we address this important question using a multi-omic approach that integrates super-resolution imaging and metabolic analyses to profile macrophages from a mouse model of mitochondrial disease caused by a heteroplasmic mutation (m.5019A>G) in the mitochondrial tRNA for alanine. These m.5019A>G macrophages exhibit defects in respiratory chain complexes and oxidative phosphorylation (OxPhos) due to decreased intra-mitochondrial translation. To adapt to this metabolic stress, mitochondrial fusion, reductive glutamine metabolism, and aerobic glycolysis are all increased. Upon inflammatory activation, type I interferon (IFN-I) release is enhanced, while the production of pro-inflammatory cytokines and oxylipins are restrained in m.5019A>G macrophages. Finally, an in vivo endotoxemia model using m.5019A>G mice reveal elevated IFN-I levels and sickness behaviour. In conclusion, our study identifies an unexpected imbalance in innate immune signalling in response to a pathogenic mtDNA mutation, with important implications for the progression of pathology in patients with mtDNA diseases. Data from this study that is included in this Dryad submission is as follows: 1. Label-free proteomic analysis of non-stimulated (non-stim) or lipopolysacchride (LPS)-stimulated (6 h) WT and m.5019A>G murine bone marrow-derived macrophages (BMDMs). Five to seven biological replicates per condition. 2. RNA sequencing of non-stim or LPS-stimulated (1 h) WT and m.5019A>G murine bone marrow-derived macrophages (BMDMs). Three biological replicates per condition.

Proteomic analysis

Cell pellets were lysed, reduced and alkylated in 50 µl of 6 M Gu-HCl, 200 mM Tris-HCl pH 8.5, 10 mM TCEP, 15 mM chloroacetamide by probe sonication and heating to 95ºC for 5 mins. Protein concentration was measured by a Bradford assay and initially digested with LysC (Wako) with an enzyme to substrate ratio of 1/200 for 4 h at 37 ºC. Subsequently, the samples were diluted 10-fold with water and digested with porcine trypsin (Promega) at 37ºC overnight. Samples were acidified to 1% TFA, cleared by centrifugation (16,000 g at RT) and approximately 20 µg of the sample was desalted using a Stage-tip. Eluted peptides were lyophilized, resuspended in 0.1% TFA/water and the peptide concentration was measured by A280 on a nanodrop instrument (Thermo). The sample was diluted to 2 µg/ 5 µl for subsequent analysis.

The tryptic peptides were analyzed on a Fusion Lumos mass spectrometer connected to an Ultimate Ultra3000 chromatography system (both Thermo Scientific, Germany) incorporating an autosampler. 2 µg of de-salted peptides were loaded onto a 50 cm emitter packed with 1.9 µm ReproSil-Pur 200 C18-AQ (Dr Maisch, Germany) using a RSLC-nano uHPLC systems connected to a Fusion Lumos mass spectrometer (both Thermo, UK). Peptides were separated by a 140 min linear gradient from 5% to 30% acetonitrile, 0.5% acetic acid. The mass spectrometer was operated in DIA mode, acquiring a MS 350-1650 Da at 120k resolution followed by MS/MS on 45 windows with 0.5 Da overlap (200-2000 Da) at 30k with a NCE setting of 27.

Raw files were analysed and quantified by searching against the Uniprot Mus Musculus data base using DIA-NN 1.8 (https://github.com/vdemichev/DiaNN). Library-free search was selected, and the precursor ion spectra were generated from the FASTA file using the deep learning option. Default settings were used throughout apart from using “Robust LC (high precision)”. In brief, Carbamidomethylation was specified as fixed modification while acetylation of protein N-termini was specified as variable. Peptide length was set to minimum 7 amino acids, precursor FDR was set to 1%.  Subsequently, missing values were replaced by a normal distribution (1.8 π shifted with a distribution of 0.3 π) in order to allow the following statistical analysis.  Protein-wise linear models combined with empirical Bayes statistics are used for the differential expression analyses. We use the Bioconductor package limma to carry out the analysis as previously described⁶⁷. Heatmaps were generated using Morpheus software from the Broad Institute.

RNA sequencing

RNA isolation was carried using RNeasy^® ^Plus kit (74136, Qiagen) following manufacturer’s suggestions and eluted RNA was purified using RNA Clean & Concentrator Kits (Zymo Research). RNA-seq samples libraries were prepared by Cambridge Genomic Services (CGS) using TruSeq Stranded mRNA (Illumina) following the manufacturer’s description. For the sequencing, the NextSeq 75 cycle high output kit (Illumina) was used and samples spiked in with 1% PhiX. The samples were run using NextSeq 500 sequencer (Illumina). Differential Gene Expression Analysis was done using the counted reads and the R package edgeR version 3.26.5 (R version 3.6.1) for the pairwise comparisons.