Tag: Risk factors

  • Fetal hepatocytes protect the HSPC genome via fetuin-A

    Fetal hepatocytes protect the HSPC genome via fetuin-A

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    Human tissue acquisition

    Human fetal liver tissues and cord blood samples were obtained from Tongji Hospital, Tongji University School of Medicine, Shanghai, China, with written informed consent from the parents and approval from the Medical Ethics Committee (k-w-2010-010) of Tongji Hospital. Fetal developmental age was estimated from measurements of crown–rump length and compared with a standard growth chart42. Plasma from infant patients with leukaemia and benign patients was obtained from Shanghai Children’s Medical Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China, with written informed consent from guardians of the patients and approval from the Medical Ethics Committee (SCMCIRB-K2024163-1) of the Shanghai Children’s Medical Center.

    Mice

    B6.129P2-Gt(ROSA)26Sortm1(DTA)Lky/J, B6.Cg-Tg(Alb-cre)21Mgn/J, B6.Cg-Gt(ROSA)26Sortm14(CAG-tdTomato)Hze/J, C57BL/6J (B6-Ly5.2) and C57BL/6JGpt-Fetua-knockout (cas9) mice were maintained and bred in a pathogen-free facility in ventilated cages, a maximum of six mice per cage, on a 12-h day–night cycle, at 20–26 °C and 30–70% humidity, in compliance with the US National Institutes of Health Guide for the Care and Use of Laboratory Animals. For embryo collection, 8–10-week-old male and female mice were mated at night and then separated the next morning; the time of separation was considered E0.5. For colony-forming cell assays, whole-genome sequencing and leukaemic models, 3-week-old mice were used. Male and female mice were used in all experiments. Mice were placed into groups depending on their gestational days and genotypes; when possible, mice were randomized and the group allocation was blinded. No sample size calculation was performed. All animal experiments were approved by the Institutional Animal Care and Use Committees of Shanghai Jiao Tong University School of Medicine, Shanghai, China.

    Isolation of human HSPCs

    Liver tissues were processed immediately after isolation. The tissues were dissected into single-cell suspensions, and mononuclear cells were then separated using Ficoll density gradient centrifugation. Lineage-positive cells were depleted using the MagniSort Human Haematopoietic Lineage Depletion Kit (8804-6836-74, Thermo Fisher). Lineage-negative (Lin) cells were incubated with a combination of biotin-labelled lineage antibodies (to CD2, CD3, CD10, CD11b, CD14, CD16, CD19, CD56, CD123 and CD235a; 8804-6836-74, Invitrogen) and FITC-labelled CD34 (581; 555821, BD). After 15 min at 4 °C, the cells were washed with PBS, suspended in magnetic bead selection buffer (MACS; PBS, 2 mM EDTA and 0.5% BSA), and then incubated with streptavidin–phycoerythrin (12-4317-87, Thermo Fisher). After 10 min at room temperature, the cells were washed and suspended in IMDM (12440053, Thermo Fisher) supplemented with 1% BSA. Lin and CD34+ HSPCs were subjected to flow cytometry on an Aria III flow cytometer (BD), and the data were collected using BD FACSDiva (V8.0.3). The HSPCs were cultured in StemSpan medium (09650, Stem Cell) supplemented with 10 ng ml−1 IL-6 (200-06, PeproTech), 10 ng ml−1 IL-3 (200-03, PeproTech), 10 ng ml−1 stem cell factor (SCF; 300-07, PeproTech) and 10 ng ml−1 Flt3 (300-19, PeproTech) at a concentration of 1 × 105 per millilitre for further experiments.

    Isolation of mouse HSPCs

    Pregnant mice were anaesthetized and euthanized by cervical dislocation. Placentas, fetal livers or bone tissues were then dissected into single-cell suspensions. Subsequently, the cells were incubated with biotin-labelled monoclonal antibodies targeting haematopoietic lineage markers (including B220, CD3, Gr-1 and Ter119; 88-7774-75, Thermo Fisher). After incubation, the cells were washed with MACS buffer and stained with streptavidin-conjugated magnetic beads (558451, BD). Following a 20-min incubation at 4 °C, the cells were washed again and resuspended in MACS buffer. Lineage-positive cells were depleted using a magnetic system. The Lin cells were then incubated with biotin-labelled lineage markers (88-7774-75, Thermo Fisher), phycoerythrin–Cy7-labelled Sca-1 (D7; 25-5981-82, Thermo Fisher), APC-labelled Kit antibodies (2B8; 17-1171-82, Thermo Fisher), phycoerythrin-labelled CD150 (mShad150; 12-1502-82, Thermo Fisher) and FITC-labelled CD48 antibodies (HM48-1; 11-0481-82, Thermo Fisher). After a 15-min incubation at 4 °C, the cells were washed with PBS and resuspended in MACS buffer. Streptavidin–phycoerythrin (12-4317-87, Thermo Fisher) or streptavidin–APC–Cy7 (405208, BioLegend) was added to the cells, which were then incubated for 10 min at room temperature. The cells were then washed and resuspended in IMDM supplemented with 1% BSA. LSK cells, lineage-negative, Sca-l-positive, Kit-positive, CD150-positive and CD48-negative cells (LT-HSCs), lineage-negative, Sca-l-positive, Kit-positive, CD150-negative and CD48-negative cells (ST-HSCs), and lineage-negative, Sca-l-positive, Kit-positive, CD150-negative and CD48-positive cells (MPPs) were flow-sorted according the gating strategy in Supplementary Fig. 1 in the Aria III flow cytometer (BD), and the data were collected using BD FACSDiva (v8.0.3). The HSPCs were cultured in StemSpan medium (09650, Stem Cell) supplemented with 10 ng ml−1 IL-6 (216-16, PeproTech), 10 ng ml−1 IL-3 (213-13, PeproTech) and 10 ng ml−1 SCF (250-03, PeproTech) at a concentration of 1 × 105 per millilitre for further experiments.

    Isolation and culture of mouse fetal hepatocytes

    To obtain Alb-Cre;ROSA26-LSL-tdTomato fetuses, we cross-mated B6.Cg-Tg(Alb-cre)21Mgn/J and B6.Cg-Gt(ROSA)26Sortm14(CAG-tdTomato)Hze/J mice. Fetal livers were then removed at E12.5 or E16.5 and digested with 0.6 mg ml−1 collagenase IV (17104019, Thermo Fisher) in Hank’s balanced salt solution for 20 min at 37 °C. The digestion reaction was halted using cold PBS, and the mixture was subsequently centrifuged at 500 rpm for 5 min. Magnetic cell sorting (558451, BD) was used to remove blood cells expressing Ter119, B220, CD3, Gr-1 and Mac-1. Tomato-positive hepatocytes were flow-sorted using an MoFlo Astrios flow cytometer, and the data were collected using Summit (v6.3.1.16945; Beckman Coulter). The isolated hepatocytes were precultured in StemSpan medium (09650, Stem Cell) supplemented with hepatocyte growth supplement (1:100; 5201, ScienCell), 2 ng ml−1 IL-6 and 5% FBS (F2442, Sigma; referred to as SHIF) for 4 h. After removing the medium and non-adherent cells, the adherent hepatocytes were cultured in the same medium without FBS (referred to as SHI) for 20 h. The supernatant from the cultured fetal hepatocytes (referred to as conditioned SHI or co-SHI) was collected for further experiments.

    Comet assay

    The HSPCs at different development stages and HSPCs cultured with or without FetuA (100 μg ml−1; 10318-H08H, SinoBiological) or ML216 (25 mΜ; S0469, Selleck) were treated with 20 μM etoposide (341205, Merck Millipore) for 30 min and then collected for the comet assay. A CometAssay kit from TREVIGEN (4250-050-k, R&D) was utilized to assess DNA damage. The alkaline method was utilized using the following steps: (1) 5,000 cells were mixed with 50 µl of melted LMAgarose (4250-050-02, R&D) at 37 °C and then pipetted onto a CometSlide; (2) the cells were then gelled for 3–5 min at 4 °C in the dark, followed by lysis with 4 °C lysis solution for 1 h; (3) the CometSlide was immersed in an alkaline unwinding solution (200 mM NaOH and 1 mM EDTA, pH > 13) for 1 h at 4 °C in the dark, and electrophoresis was conducted in the same solution at 20 V and 300 mA for 30 min at 4 °C); (4) the slides were washed twice with ddH2O for 5 min each, followed by washing with 70% ethanol for 5 min, and the slides were then dried at room temperature overnight; and (5) the dried agarose was stained with SYBR Green I (A25742, Thermo Fisher) nucleic acid gel stain for 30 min. Images were acquired with Las X (v4.7) on a Leica TCS Stellaris8 STED Microscope at ×20 resolution and analysed using OpenComet software (v1.3.1).

    Immunofluorescence staining of cells

    Human HSPCs treated with 80 µM etoposide (341205, Merck Millipore) for 30 min; mouse HSPCs treated with 20 µM etoposide for 30 min, 500 J m2 ultraviolet radiation B (UVB) irradiation; human HSPCs cultured with or without FetuA (100 μg ml−1; 10318-H08H, SinoBiological) for 2 h and then treated with 80 µM etoposide; mouse HSPCs cultured with co-SHI or hepatocytes for 2 h and then treated with 20 µM etoposide; and mouse HSPCs pre-treated with or without TLR4 antibody (1:50; 53-9041-80, Thermo Fisher) at 4 °C for 30 min and then cultured with or without FetuA (100 μg ml−1; 50093-M08H, SinoBiological) for 2 h and thereafter treated with 20 µM etoposide were collected. These cells were then spun onto slides and fixed in 4% PFA for 10 min. After treatment with PBS containing 2% serum, 1% BSA and 0.2% Triton X-100, the cells were directly stained with primary antibodies overnight at 4 °C. Subsequently, the sections were stained with secondary antibodies for 1 h at room temperature. Phosphor-histone H2AX (Ser13; 20E3) rabbit monoclonal antibody (1:400; 9718S) was acquired from Cell Signaling Technology (CST), and TLR4 antibody (1:200; ab13556), mouse FetuA antibody (EPR17839-163; 1:100; ab187051) and p-RPA (phospho S33; 1:200; ab211877) were obtained from Abcam. Human FetuA antibody (1F6B9; 1:100; 66094-1-Ig) was obtained from Proteintech. The MYD88 (E11; 1:400; sc-74532) antibody was acquired from Santa Cruz. Images were acquired with ZEN (v2.3) on a Zeiss 880 Microscope at ×20 resolution or ×63 resolution, and analysed using ImageJ (v1.52p) and HALO (v3.6.4134).

    Immunofluorescence staining of whole-mount tissues

    Fetal livers and placentas were fixed in 4% PFA for 30 min, washed with PBS for 2–3 h, and stained with primary antibodies (diluted in PBS containing 1% BSA, 2% FCS and 0.5% Triton X-100) for 1–3 days. The tissues were then incubated with secondary antibodies for 2 h. Anti-mouse CD117 (Kit, ACK2; 1:50; 14-1172-85) was acquired from Thermo Fisher, and phospho-histone H2AX (Ser139; 20E3; 1:400; 9718S) rabbit monoclonal antibody was obtained from CST. Images were acquired with Las X (v4.7) on a Leica TCS Stellaris8 STED Microscope at ×20 resolution, and analysed using Image J (v1.52p) and Imaris (v9.0.1).

    Immunofluorescence staining of tissue sections

    Human or mouse placenta, fetal liver and bone tissues were fixed in 4% PFA for 30–60 min at room temperature (placenta and fetal liver tissues) or 5 h at 4 °C (bone tissues), dehydrated in 15% and 30% sucrose, and embedded in optimal cutting temperature compound at −20 °C. The tissues were then sectioned (20–25 μm) using a cryostat. The tissue sections were stained with primary antibodies for 6–12 h at 4 °C in PBS containing 1% BSA, 2% FCS and 0.5% Triton X-100. The sections were incubated with secondary antibodies for 1 h at room temperature. CD48–FITC (HM48-1; 1:100, 11-0481-82) was acquired from Thermo Fisher. APC-anti-lineage (Ter119 (1:400, 116212), Gr-1 (1:400, 108412), Mac-1 (1:400, 101212), B220 (1:400, 103212), CD3 (1:100, 100236), CD150-BV421 (SLAM; 1:100, 115925) and CD41-APC (MWReg30; 1:400, 133913)) were acquired from BioLegend. Kit goat monoclonal antibody (Gln25–Thr519; Ala207Glu; 1;400, AF1356) and anti-human serum albumin antibody (MAB1455; 1:200, 188835) were acquired from R&D. E-cadherin rabbit monoclonal antibody (24E10; 1:200, 3195T) and phospho-histone H2AX (Ser139; 20E3; 1:400, 9718S) rabbit monoclonal antibodies were acquired from CST. Laminin monoclonal antibody (1:200, ab11575), mouse FetuA antibody (EPR17839-163; 1:400, ab187051) and CD34 antibody (EP373Y; 1:100, ab81289) were acquired from Abcam. CD45–FITC (104; 1:100, MCD45201) was acquired from Invitrogen. Nestin antibody (1:50, AN205-1) was acquired from Beyotime. E-cadherin antibody (DECAM-1; 1:200, sc-59778) was acquired from Santa Cruz. CD144 antibody (1:200, 550548) and Sca-1 antibody (D7; 1:200, 557403) were acquired from BD. Human FetuA antibody (1F6B9; 1:200, 66094-1-Ig) was acquired from Proteintech. Images were acquired with ZEN (v2.3) on a Zeiss 880 Microscope at ×20 resolution or ×63 resolution, and analysed using ImageJ (v1.52p), Imaris (v9.0.1) and HALO (v3.6.4134).

    Colony-forming cell assay

    The assay was performed in a semi-solid methycellulose medium (03434, Stem Cell Technologies) following the technical manual. In brief, the sorted HSPCs were plated in methycellulose in a 35-mm dish (200 cells per dish). Cultures were incubated at 37 °C in a humidified incubator (more than 95%) with 5% CO2 in the air. The colonies were scored under a microscope 10–12 days post-plating. Replating was performed by pooling total cells from primary cultures and inoculating 104 cells into fresh methycellulose medium.

    Metaphase chromosome preparation and FISH

    Bone marrow Lin cells were incubated with 0.05 μg ml−1 colcemid for 1 h at 37 °C and then centrifuged at 400g for 10 min. The cells were suspended in 1 ml of hypotonic solution (0.075 M KCl) for 30 min at 37 °C, and the reaction was stopped by the addition of freshly prepared fixative solution (3:1 methanol:glacial acetic acid). The cells were then subjected to three rounds of fixative changes. After that, the cells were dropped onto slides and allowed to dry at room temperature. Two-colour FISH was performed using whole-chromosome probes for mouse chromosome 4 (FITC; D-1404-050-FI, MetaSysterms) and chromosome 6 (Texas red; D-1406-050-OR, MetaSysterms), and counterstaining was performed with DAPI-Antifade solution. Images were acquired with Las X (v4.7) on a Leica TCS Stellaris8 STED Microscope at ×20 resolution and analysed using Image J (v1.52p).

    Mouse models of leukaemia

    Three-week-old mice were intraperitoneally injected with 80 mg kg−1 N-ethyl-N-nitrosourea (ENU; N3385, Sigma) four times, which was administered twice a week, and the mice were monitored by daily observation of leukaemic symptoms and signs including fired hair, white toes, swollen lymph nodes and loss of body weight, and weekly measurement of leukaemia-like cells by Gimsa staining of peripheral blood smears. Once these appeared, the animals were killed, and the disease of leukaemia was determined by exhibition of enlarged spleens and lymph nodes, increased proportions of immature Lin cells in the bone marrow and leukaemic cell infiltration in spleens and bone marrow shown by haematoxylin and eosin staining of the tissue sections.

    Western blot

    After treatment with or without FetuA (100 μg ml−1; 50093-M08H, SinoBiological) for 2 h, mouse HSPCs (LSK) were lysed and blotted with bZIP antibody and their phosphorylated forms. After treatment with or without FetuA (100 μg ml−1; 50093-M08H, SinoBiological) and the bZIP inhibitor SR11032 (2 mM; HY-15870, MedChemExpress) for 6 h, mouse Lin haematopoietic cells were lysed and blotted with BLM antibody. The cells were lysed using SDS lysis buffer. The lysates were then separated on SDS-polyacrylamide gels and transferred to nitrocellulose membranes (Bio-Rad). Western blotting was carried out using the following primary antibodies: FetuA (1:2,000), JunB (1:1,000), phosphorylated JunB (p-JunB; 1:1,000), Jun (1:1,000), p-Jun (1:1,000), Fosl1 (1:10,000), p-Fosl1 (1:1,000), BLM (1:500) and laminB1 (1:2,000). The membranes were incubated overnight at 4 °C with primary antibodies. After rinsing to remove any unbound primary antibody, the membranes were exposed to a horseradish peroxidase-conjugated secondary antibody at room temperature for 1 h. The secondary antibody was detected using chemiluminescence (WBKLS0500, Merck Millipore). The following primary antibodies were used: anti-p-JunB (Thr102/Thr104; 8053S) and anti-p-Fosl1 (S265; 3880S) from CST and anti-JunB (EPR6518; ab128878), anti-Fosl1 (ab232745), anti-p-Jun (phospho S63; ab32385), anti-Jun (EP693Y; ab40766), anti-laminB1 (EPR8985; ab133741) and anti-FetuA (EPR17839-163; ab187051) from Abcam, and anti-BLM (B-4; sc-365753) from Santa Cruz. The intensity of bands was measured using ImageJ (v1.52p). For gel source data, see Supplementary Fig. 2.

    Mass spectrometry analysis

    SHI and co-SHI media, E12.5 and E16.5 fetal liver tissues and bone marrow plasma samples from infants were collected for data-independent acquisition tandem mass spectrometry (DIA MS/MS) analysis. The medium samples were treated with 2% SDS buffer containing 50 mM dithiothreitol for 20 min at room temperature and then boiled at 100 °C for 5 min. The protein samples were alkylated in the dark at room temperature for 1 h by adding 200 mM iodoacetamide. To precipitate the proteins, a 5× volume of pre-cooled acetone was used overnight at −20 °C. The tissue samples were diluted with 50 mM NH4HCO3 and centrifuged three times at 20 °C and 14,000g using YM-10 filter units. The protein lysates were reduced for 1 h at room temperature with a final concentration of 10 mM dithiothreitol and then alkylated for 1 h in the dark at room temperature with a final concentration of 55 mM iodoacetamide. The protein mixtures were exchanged with 50 mM NH4HCO3 by centrifugation at 20 °C and 14,000g three times. The protein precipitates were digested overnight at 37 °C at a protein-to-enzyme ratio of 50:1 with trypsin. Tryptic peptides were collected by centrifugation at 20 °C and 14,000g for 20 min. The peptides were then treated with 1% trifluoroacetic acid, purified using C18 Ziptips and eluted with 0.1% trifluoroacetic acid in 50–70% acetonitrile. The eluted peptides were dried using a SpeedVac (Thermo Savant) and resuspended in 1% formic acid and 5% acetonitrile. Before analysis, indexed retention time (iRT) peptides (Biognosys) were spiked into the samples following the manufacturer’s instructions. The pooled digestates were dried using a SpeedVac (Thermo Savant) and resuspended in 5% ACN in 0.05 M ammonium formate. The digested peptides were fractionated using high-pH reversed-phase separation on a Dionex ultra-high-performance liquid chromatography (Thermo Scientific) with a 2.1 × 150 mm ethylene-bridged hybrid (BEH) C18 3-μm column at 40 °C, with a flow rate of 0.2 ml min−1 and a 60-min ACN gradient (5–30%) in 5 mM ammonium formate (pH 10). Fractions were collected at 1-min intervals and pooled at various intervals, resulting in up to 12 fractions. The samples were dried and resuspended in 1% formic acid and 5% acetonitrile. Data-dependent acquisition (DDA) analysis was conducted on an Orbitrap Fusion LUMOS mass spectrometer (Thermo Fisher Scientific) connected to an Easy-nLC 1200 via an Easy Spray (Thermo Fisher Scientific). The peptide mixtures were loaded onto a self-packed analytical PicoFrit column (75 μm × 40 cm) with an integrated spray tip (New Objective) packed with ReproSil-Pur 120A C18-AQ 1.9 μm (Dr. Maisch GmbH). The peptides were separated using a 120-min linear gradient from 95% solvent A (0.1% formic acid, 2% acetonitrile and 98% water) to 28% solvent B (0.1% formic acid and 80% acetonitrile) at a flow rate of 250 nl min−1 at 50 °C. The mass spectrometer was operated in positive-ion mode and used the data-dependent mode with a specialized cycle time (3S) to automatically switch between MS and MS/MS scans. A full MS scan from 350 to 1,500 m/z was acquired at a resolution of R = 120,000 (defined at m/z = 400). MS/MS scans were performed at a resolution of 30,000, with an isolation window of 4 Da and higher-energy collisional dissociation fragmentation with a collision energy of 30 ± 5%. Dynamic exclusion was set to 30 s. Sequences were identified using the mouse UniProt fasta database (53,099 entries, downloaded on 4 November 2018) with default parameters. The digestion enzyme used was a specific trypsin enzyme with two missed specialized cleavages. Carbamidomethyl of cysteine was set as a fixed modification, and oxidation of methionine was set as a variable modification. The iRTs derived from median iRTs across all DDA runs were calculated. Fragment ions for the targeted data analysis were selected from 300 to 1,800 m/z, with a minimal relative intensity set to more than 5% and a fragment ion number greater than 3. The false discovery rate (FDR) was set to 1% for protein and peptide spectrum matches. Protein inference was performed using the ID Picker algorithm integrated within the Spectronaut software. DIA MS/MS acquisition was performed using the same liquid chromatography-MS systems and liquid chromatography linear gradient method as DDA. For MS/MS acquisition, the DIA method was set with 50 variable isolation windows based on the full-width at half-maximum and constructed using the respective DDA data. The full scan was set at a resolution of 1,200,000 over a m/z range of 350–1,500, followed by DIA scans at a resolution of 30,000. The collision energy (CE), auto gate control (AGC) and maximal injection time were set to 30 ± 5%, 1 × 106 and 54 ms, respectively. The DIA raw files were analysed using Spectronaut X (Biognosys). The retention time prediction type was set to dynamic iRT, and a correction factor was applied for window 1. Interference correction at the MS2 level was enabled. Systematic variance was normalized using a local normalization strategy. The FDR was estimated using the mProphet approach and set to 1% at the peptide precursor and protein levels. Protein intensity was calculated by summing the intensities of their respective peptides, which were measured using the peak areas of their fragment ions in MS2 and multiplied by a factor based on the total sample volume of each sample. All the results were filtered with a Q value cut-off of 0.01 (corresponding to a 1% FDR).

    Intraplacental injection of FetuA

    The pregnant mice were anaesthetized using 3.5% chloral hydrate and then secured onto a heating pad with all four legs immobilized. The abdominal surface was shaved and disinfected with 75% alcohol. A longitudinal incision measuring 1–1.5 cm in length was made on the abdominal skin, and the peritoneum was cut. Cotton gauze was placed around the incision. One uterine horn was carefully exposed and pulled out using blunt forceps onto gauze soaked in PBS. The uterus was held in place with blunt forceps, and recombinant FetuA (10 μg per 15 μl each) was injected into the placenta. After the injection, the uterus was carefully returned to the abdomen, ensuring that it was positioned exactly as before. The peritoneum was closed with a haemostat. Two hours later, 5 mg kg−1 etoposide was administered through intraperitoneal injection. The fetuses were harvested after 1 h and fixed for immunofluorescence assays.

    ATAC-seq library preparation and sequencing

    ATAC-seq libraries were prepared as previously described43. In brief, HSPCs were lysed using lysis buffer containing 10 mM Tris-HCl (pH 7.4), 10 mM NaCl, 3 mM MgCl2 and 0.1% IGEPAL CA-630 for 10 min before being spun at 4 °C to obtain nuclear preparations. The supernatant was discarded, and the nuclei were then incubated with Tn5 transposome and tagmentation buffer at 37 °C for 30 min (Vazyme). The resulting tagmentation products were purified and amplified using PCR. PCR amplification involved ten cycles under the following conditions: 72 °C for 5 min; 98 °C for 30 s; thermocycling at 98 °C for 10 s, 63 °C for 30 s and 72 °C for 1 min; and 72 °C for 5 min. The libraries were purified using a PCR purification kit (28004, Qiagen), and the fragments were enriched using 0.5× and 1.0× VAHTS DNA Clean Beads (N412-01, Vazyme) after amplification.

    ATAC-seq data processing

    All reads were aligned to the mm10 genome using the Burrows-Wheeler Aligner (BWA-MEM) after trimming the adapter sequences with Trim_Galore (v0.6.7). Low-quality reads were filtered out, whereas PCR duplicates and reads mapped to the mitochondria or the Y chromosome were discarded. The remaining reads on the left were shifted (+4/−5) to correct Tn5 enzyme insertions based on the read strands. Peak calling was performed using MACS2 (v2.2.6) with the following options: -f BAM, -g mm, –nomodel, –shift -100 and –extsize 200. The samples were normalized using the bamCoverage function from deepTools (v3.5.1) to visualize the signal in IGV (v2.7.0).

    Quality control of ATAC-seq data was conducted, and correlation analysis was performed using deepTools (v3.5.1). The fragment distribution was generated using ATAC-seq QC (v1.14.4). The peak atlas was obtained by expanding the peak summit by ±500 bp, and differential peaks were identified using DESeq2 (v1.26.0). DNA-binding factor motifs were analysed by determining the motifs in the differential peaks using HOMER (v4.11). ATAC signals were visualized as a heatmap using the complexHeatmap package (v2.2.0).

    RNA-seq and analysis

    Total RNA was extracted from cultured or non-cultured HSPCs using Tri Pure Isolation Reagent (11667157001) from Roche following the manufacturer’s instructions. The quality of the RNA was assessed using the Fragment Analyser platform. High-quality samples were chosen for library construction using the Illumina TruSeq RNA Prep Kit (20015949). The libraries were subsequently sequenced on the Illumina HiSeq4000 platform, generating 2 × 150 bp paired-end reads. To process the raw data, Trim Galore (v0.6.7) was used with the following parameters: ‘–quality 20 –fastqc –length 20 –stringency 1’. The resulting clean reads were then aligned to the mouse reference genome (mm10) using hisat2 (v2.2.1). GENCODE annotations (gencode.vM25.annotation.gtf; downloaded in April 2021) and HTSeq-count (v0.13.5) were used to assign the aligned reads to genes. Subsequently, the counts were normalized to fragments per kilobase of transcript per million mapped reads (FPKM), and log(FPKM + 1) was utilized to analyse the overall similarity or dissimilarity between the samples.

    Cut&Tag library preparation and sequencing

    The Hyperactive Universal Cut&Tag Assay Kit for Illumina Pro (TD904, Vazyme) was used in this study. In summary, 1 × 105 LSK cells treated with or without FetuA were collected and washed in 500 µl of wash buffer. The cells were then resuspended in 100 µl of wash buffer. Subsequently, 10 µl of concanavalin A-coated magnetic beads were activated and added to 1 × 105 cells. The cells were incubated at room temperature for 10 min, after which the supernatant was removed. The resulting bead-bound cells were resuspended in 50 µl of antibody buffer. Next, 1 µl of Jun rabbit monoclonal antibody (60A8; 9165T, CST), JunB rabbit monoclonal antibody (C37F9; 3753S, CST) or Fosl1 mouse monoclonal antibody (C-12; sc-28310, Santa Cruz) was added and incubated with the bead-bound cells overnight at 4 °C with rotation. The supernatant was then removed, and the bead-bound cells were resuspended in 50 µl of dig-wash buffer containing goat anti-rabbit IgG antibody (Ab207-01-AA, Vazyme) or goat anti-mouse IgG antibody (Ab208-01-AA, Vazyme; diluted 1:100). This mixture was incubated at room temperature for 1 h. The bead-bound cells were washed three times with 200 µl of dig-wash buffer to remove any unbound antibodies. Next, 2 µl of the pA-Tn5 adapter complex was diluted in 98 µl of dig-300 buffer and mixed with the bead-bound cells. The mixture was subjected to rotation at room temperature for 1 h. The bead-bound cells were washed three times with 200 µl of dig-300 buffer to eliminate any unbound pA-Tn5 protein. The cells were then resuspended in 50 µl of tagmentation buffer and incubated at 37 °C for 1 h. To terminate the tagmentation reaction, 2 µl of SDS was added to the cells and incubated for an additional 10 min at 55 °C. The tagmentation products were purified using DNA Extract Beads Pro and eluted in 15 µl of nuclease-free water. For generation of the sequencing libraries, the DNA tagments were mixed with a universal i5 primer and a unique i7 primer and amplified using 2× Cut &Tag amplification mix. The resulting PCR products were purified using VAHTS DNA lean beads (N411, Vazym), and subsequently analysed using an Agilent 2100 Bioanalyzer and Illumina Novaseq 6000.

    Cut&Tag data processing

    Cut&Tag reads were aligned to the mm10 genome with Bowtie2 (v2.3.5.1) using the following parameters: –end-to-end –very-sensitive –no-mixed –no-discordant –phred33 -I 10 -X 700. Duplicate reads were removed with Picard (v2.25.5). The track files were made with the bamCoverage command from deepTools (v3.5.1). Cut&Tag peaks were called using MACS2 (v2.2.6). The distribution of Cut&Tag peaks was annotated with the R package ChIPseeker (v1.22.1).

    R-loop staining

    HSPCs from E12.5 placenta, E12.5 fetal liver, E16.5 fetal liver or E12.5 FL-HSPCs with or without FetuA (100 μg ml−1; 50093-M08H, SinoBiological) or ML216 (25 mΜ; S0469, Selleck) treatment for 2 h were collected. The cells were spun onto slides, fixed in 4% PFA for 10 min and washed three times with PBS. After permeabilization with PBS containing 0.3% Triton X-100 for 10 min at room temperature, the cells were washed three times with PBS and then blocked with PBS containing 2% serum, 1% BSA and 0.2% Triton X-100 for 1 h at 37 °C. Immunofluorescence experiments with the dRNH1 protein were performed as previously described33. In brief, the cells were incubated with 30 μl dRNH1 (0.24 mg ml−1) for 1 h at 37 °C, followed by three washes with PBS. The cells were then incubated with 1 μg ml−1 DAPI for 10 min. For immunofluorescence experiments with the GST-His6-2×HBD protein32, the cells were incubated with 30 μl GST-His6-2×HBD (2 μg ml−1) overnight at 4 °C. After three washes with PBS, the cells were stained with an anti-HisTag monoclonal antibody (AMC0149; 1:400; AE003, ABclonal) for 1 h at room temperature, followed by three washes with PBS. The cells were then stained with a rabbit anti-mouse IgG antibody (1:400; SPA231, Solarbio) for 1 h at room temperature. After three washes with PBS, the cells were incubated with 1 μg ml−1 DAPI for 10 min. Images were acquired using a Zeiss 880 microscope, and the signal intensity was measured using HALO (v3.6.4134).

    R-loop Cut&Tag library preparation and sequencing

    The R-loop Cut&Tag library was prepared following protocols previously described32 with minor modifications. For this experiment, the Hyperactive Universal Cut&Tag Assay Kit for Illumina (TD903, Vazyme) was utilized. In brief, 1 × 105 cells were gently pipetted and washed twice in 500 µl of wash buffer. Then, 10 µl of concanavalin A-coated magnetic beads was activated and added to the 1 × 105 cells, followed by incubation at room temperature for 10 min. The supernatant was then removed, and the bead-bound cells were resuspended in 90 µl of antibody buffer. Subsequently, 10 µl of recombinant GST-His6-2×HBD (0.2 mg ml−1) protein was added and the mixture was incubated with the bead-bound cells overnight at 4 °C with rotation. After two washes with dig-wash buffer, the samples were incubated with an anti-HisTag monoclonal antibody (AMC0149; 1:400; AE003, ABclonal) for 1 h at room temperature, followed by incubation with a rabbit anti-mouse IgG antibody (final concentration, 10 µg ml−1; SPA231, Solarbio) for 1 h at room temperature. Unbound antibodies were removed by three brief washes with 200 µl of dig-wash buffer. To facilitate tagmentation, 2 µl of a pA-Tn5 adapter complex was diluted in 98 µl of dig-300 buffer and mixed with bead-bound cells, which were then rotated at room temperature for 1 h. After three washes in 200 µl of dig-300 buffer to remove unbound pA-Tn5 protein, the cells were resuspended in 50 µl of tagmentation buffer and incubated at 37 °C for 1 h. The tagmentation reaction was stopped by adding 1.8 µl of 0.5 M ethylenediaminetetraacetic acid, 0.6 µl of 10% SDS, 5 µl of nuclease-free water and 1 µl of proteinase K (20 mg ml−1), and further incubated at 55 °C for 60 min. Following purification with 1× DNA clean beads (Vazyme Biotech), the resulting tagmentation products were eluted in 10 µl of nuclease-free water. For the strand displacement reaction, the eluent was mixed with 10 U of Bst 2.0 WarmStart DNA polymerase (M0538, NEB) in 1× Q5 polymerase reaction buffer and incubated at 65 °C for 30 min. The reaction was then halted by incubation at 80 °C for 20 min. To generate the sequencing libraries, the mixture was combined with a universal i5 primer and a uniquely barcoded i7 primer and subsequently amplified using Q5 high-fidelity master mix (M0491, NEB). The libraries were size selected with 0.56–0.85× DNA clean beads and subjected to analysis using an Agilent 2100 Bioanalyzer and Illumina PE150 sequencing.

    R-loop Cut&Tag data processing

    The Cut&Tag data were processed as previously described32. In summary, Cut&Tag reads were aligned to the mm10 genome using Bowtie2 (v2.3.5.1), allowing for uniquely mapped reads with up to two mismatches. The aligned reads were normalized to the total number of reads (reads per million). Subsequently, track files were generated using the bamCoverage command from deepTools (v3.5.1). Cut&Tag peaks were called using MACS2 (v2.2.6), and the distribution of Cut&Tag peaks was annotated using the R package ChIPseeker (v1.22.1). The average coverage was used to create metaplots within the indicated windows. Gene Ontology enrichment analysis was performed using clusterProfiler (v3.14.3), and circus-plots were generated using circlise (v0.4.8).

    Whole-genome sequencing of mouse HSPCs

    Genomic DNA was extracted using the QIAamp DNA Mini Kit (51304, Qiagen) following the manufacturer’s protocol. Whole-genome sequencing was conducted as previously described44. In brief, short-insert 350-bp genomic libraries were constructed following Illumina library protocols, and sequencing was performed on an Illumina NovaSeq 6000 platform using 150-base paired-end reads, achieving an average coverage of 30×. The sequence data were mapped to the mouse genome reference mm10 using the BWA-MEM algorithm. Unmapped reads and PCR-derived duplicates were excluded from the analysis. Insertions and deletions (indels) and structural variants were called using the Pindel and BreakDancer algorithms, respectively, as described elsewhere45,46. The group treated with saline was used as germline control.

    Cell cycle analysis of mouse HSPCs by combining Hoechst and pyronin Y

    The cells were harvested from E12.5 placenta, E12.5 fetal liver and E16.5 fetal liver samples, and lineage-positive cells were depleted using a magnetic system. The Lin cells or Lin cells cultured with or without FetuA (100 μg ml−1; 50093-M08H, SinoBiological) or ML216 (25 mM; S0469, Selleck) for 2 h were collected. The cells were then suspended in 1 ml of StemSpan medium (09650, Stem Cell). Hochest33342 (10 µg ml−1; b2261-25mg, Sigma) and verapamil (50 µM; M14204, AbMole) were added to the cell suspension. The mixture was thoroughly mixed and incubated at 37 °C for 60 min in the dark. Subsequently, 5 µl of 100 µg ml−1 pyronin Y (213519-1g, Sigma) was directly added to the cells, followed by continuous incubation at 37 °C for another 15 min in the dark. After centrifugation at 300g for 5 min at 4 °C, the cells were suspended in MACS buffer and incubated with biotin-labelled lineage markers (88-7774-75, Thermo Fisher), FITC-labelled Sca-1 (E13-161.7; 122506, BioLegend) and APC-labelled Kit antibodies (2B8; 17-1171-82, Thermo Fisher). Following a 15-min incubation at 4 °C, the cells were washed with PBS, suspended in MACS buffer and incubated with streptavidin–APC–Cy7 (405208, BioLegend). After another 15 min at 4 °C, the cells were washed and resuspended in MACS buffer. The samples were analysed using a Beckman cytoFLEX LX, and the data were analysed using FlowJo (v10).

    DNA synthesis analysis of mouse HSPCs by EdU

    Pregnant mice were administered intraperitoneal injections of 100 mg kg−1 EdU (CX000, CellularLab) 2 h before being killed. Cells were collected from E12.5 placenta, E12.5 fetal liver and E16.5 fetal liver and subjected to lineage-positive cell depletion using a magnetic system. The cells were then incubated with biotin-labelled lineage markers (88-7774-75, Thermo Fisher), phycoerythrin–Cy7-labelled Sca-1 (D7; 25-5981-82, Thermo Fisher) and APC-labelled Kit (2B8; 17-1171-82, Thermo Fisher) antibodies. After 15 min at 4 °C, the cells were washed with PBS, suspended in MACS buffer and incubated with streptavidin–phycoerythrin. EdU was detected using the EdU Cell Proliferation Kit with Alexa Fluor 488 (CX002, CellularLab) following the manufacturer’s instructions. The samples were analysed on a Beckman cytoFLEX LX, and the data were analysed using FlowJo (v10).

    Cell cycle analysis of mouse HSCs and MPPs by Ki67

    Harvested cells from E12.5 placenta, E12.5 fetal liver and E16.5 fetal liver were subjected to lineage-positive cell depletion using a magnetic system. The cells were incubated with biotin-labelled lineage markers (88-7774-75, Thermo Fisher), phycoerythrin–Cy7-labelled Sca-1 (D7; 25-5981-82, Thermo Fisher), APC-labelled Kit (2B8; 17-1171-82, Thermo Fisher), phycoerythrin-labelled CD150 (mShad150; 12-1502-82, Thermo Fisher) and APC–Cy7-labelled CD48 (HM48-1; 103431, BioLegend) antibodies. Following a 15-min incubation at 4 °C, the cells were washed with PBS, suspended in MACS buffer and then incubated with streptavidin–Percpcy5.5. After another 15 min at 4 °C, the cells were fixed and permeabilized with Foxp3/Transcription Factor Staining Buffer Set Kit (00-5523-00, Invitrogen) according to the manufacturer’s instructions. Subsequently, the samples were incubated with FITC-labelled Ki67 (SolA15; 11-5698-80, Thermo Fisher). After a 30-min incubation at 4 °C, the cells were washed with permeabilization buffer and analysed using a Beckman CytoFLEX LX, and the data were analysed using FlowJo (v10).

    RNA synthesis analysis of mouse HSPCs by ethyluridine

    Pregnant mice were injected intraperitoneally with 50 mg kg−1 ethyluridine (2469–25 mg, Lumiprobe) 1 h before being killed. Cells were collected from E12.5 placenta, E12.5 fetal liver and E16.5 fetal liver and subjected to lineage-positive cell depletion using a magnetic system. The cells were then incubated with biotin-labelled lineage markers (88-7774-75, Thermo Fisher), FITC-labelled Sca-1 (E13-161.7; 122506, BioLegend) and APC-labelled Kit (2B8; 17-1171-82, Thermo Fisher) antibodies. After 15 min at 4 °C, the cells were washed with PBS, suspended in MACS buffer and incubated with streptavidin–APC–Cy7 (405208, BioLegend). The ethyluridine was stained using the Cell-Light EU Apollo567 RNA Imaging Kit (C10316-1, RIBOBIO) according to the manufacturer’s instructions. The samples were analysed on a Beckman cytoFLEX LX, and the data were analysed using FlowJo (v10).

    Statistics

    Statistics analyses were performed using R (v.3.6.3) and GraphPad Prism (v.9.5). n Denotes biological replicates. For violin plots in all panels, the median and quartiles are shown. For boxplots, the mean ± s.d. is shown. For boxplots in Fig. 5c and Extended Data Fig. 9e,i, the median and quartiles are shown. For boxplots in Fig. 5d and Extended Data Fig. 3b, the boxes delimit the minima and maxima, and the horizontal line represents the mean. For survival analysis, the long-rank test was used to compare the difference between groups. For correlation analysis, the Pearson test was used. For comparing two groups, the unpaired Student’s t-tests and Wilcoxon tests were used. P < 0.05 was considered to be significant.

    Reporting summary

    Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article.

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  • Gut microbiota carcinogen metabolism causes distal tissue tumours

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    Animal experiments

    Two-month-old C57BL/6J mice (Jackson Laboratory and Charles River) housed in the animal facility of the University of Split School of Medicine were used for all conventional mouse experiments. Two-month-old germ-free C57BL/6J mice housed in the animal facility of the European Molecular Biology Laboratory (EMBL) were used for all gnotobiotic mouse experiments. Animals were kept in individually ventilated cages with autoclaved bedding (Mucedola), with a 12-h light–dark cycle, controlled temperature (21–24 °C) and humidity (30%–70%), and ad libitum access to food (γ-irradiated, Ssniff-Spezialdiäten) and autoclaved water. Male mice were used in all experiments unless specified otherwise. All mouse experiments were approved by the local institutional animal care and use committee (The University of Split, School of Medicine, Animal Welfare Committee and EMBL Institutional Animal Care and Use Committee) and the national regulating authorities (Republic of Croatia Ministry of Agriculture, Veterinary and Food Safety Directorate; permit numbers 525-10/0255-14-4, 525-10/0255-15-5, 525-10/0543-21-8, 525-09/566-22-2 and 21-002_HD_MZ). All mice were randomly allocated into experimental groups; blinding was not carried out, except for the pathohistological analysis. No sample size calculation was carried out. The general status of the animals including behaviour, appearance and body weight was monitored. If signs of pain, suffering or weight loss of more than 20% were observed, humane end points were applied. Those limits were not exceeded in any of the experiments. For ex vivo BBN conversion experiments and 16S rRNA sequencing using conventional mice, contents from the three parts of the small intestine, caecum, large intestine and rectum were collected from five mice of each sex. One half of each sample was frozen at −80 °C in 20% glycerol, and the other half was frozen at −80 °C and used for 16S rRNA amplicon sequencing. For liquid chromatography-coupled mass spectrometry (LC–MS) quantification, tissues collected were directly frozen at −80 °C until further processing.

    Chemicals

    Chemicals used in this study are listed in Supplementary Table 49.

    Long- and short-term nitrosamine treatments with conventional or germ-free mice

    Male conventional mice were randomly assigned to the ABX–BBN or BBN group. The ABX–BBN group received 100 µg ml−1 neomycin, 100 µg ml−1 metronidazole, 50 µg ml−1 streptomycin, 67.7 µg ml−1 penicillin (all from Sigma-Aldrich) and 50 µg ml−1 vancomycin (Pharma Swiss) in drinking water that was supplied fresh weekly. Following 2 months of treatment, the ABX mixture was changed to 1,000 µg ml−1 streptomycin, 170 μg ml−1 gentamicin (Krka), 125 μg ml−1 ciprofloxacin (MCE) and 1,000 µg ml−1 bacitracin (Sigma-Aldrich), to prevent development and overgrowth of resistant bacterial strains23. The ABX–BBN group received ABX 2 weeks before starting the BBN treatment, and were kept on ABX for the remainder of the experiment.

    For gnotobiotic mouse experiments, male germ-free mice were inoculated by oral gavage with 100–250 µl microbial community culture or single bacterial isolate culture for 4 days. The ABX–BBN group would receive the first ABX mixture for 2 weeks before starting BBN treatment for 10 days. During BBN treatment, the second ABX mixture was used for the ABX–BBN group.

    Monitoring of the impact of ABX treatment on the gut microbiota was carried out using a combination of colony-forming unit (CFU) counting and 16S rRNA amplicon sequencing (microbiome composition). For CFU counting, faecal pellets from both groups were diluted (1 g in 10 ml) in PBS and homogenized by vortexing. Decimal dilutions (10−1 to 10−9) were prepared and grown on blood agar (TSA, 10% blood) at 37 °C under aerobic and anaerobic conditions prepared with gas packs (AnaeroGen; Thermo Fisher). CFUs were calculated using two successive dilutions. For 16S rRNA sequencing, faecal pellets were collected from mice and DNA was extracted using the PowerSoil Kit (QIAGEN). Sequencing was carried out on an Illumina platform generating 250-base-pair (bp) paired-end sequences of the V4 region.

    After checking the effects of ABX, we gave both groups of mice the nitrosamines (0.05% BBN and 2.87 mM EHBN, DBN and PBN) in drinking water. BBN was administered for 12 weeks, after which the chemical was removed from the drinking water for 8 weeks. PBN was administered for 17 weeks, whereas EHBN and DBN were administered for 20 weeks6,24.

    For tissue collection, mice treated with BBN and EHBN were euthanized by inhalation of CO2, and intestinal contents, liver, kidney, urinary bladder and plasma were collected and frozen at −80 °C until further analyses. Bladder tissues were cut in half longitudinally, half of which was frozen for metabolomics quantification and the other half was fixed for histopathology analyses.

    For monitoring urinary and faecal excretion, 24-h urine and faecal samples from mice treated with all chemicals were collected using metabolic cages (Techniplast). Mice were placed inside cages supplied with food and water (supplemented with nitrosamines with or without ABX for respective groups) for 24 h and faecal material and urine was collected from the collection tubes as well as from the surfaces of the cages. Samples were weighed and stored at −80 °C until further analyses.

    Pharmacokinetics experiment

    Fifty conventional mice of both sexes were randomly assigned to the ABX–BBN or BBN group. The ABX–BBN group was given a mix of ABX (neomycin, metronidazole, streptomycin, penicillin and vancomycin at the same concentrations as described above) for 2 weeks before receiving BBN. Both groups of mice were given a single dose of BBN (50 mg per kg body weight) by oral gavage and euthanized after 1, 3, 6 and 9 h (five mice per time point, per group) and intestinal contents, liver, gallbladder, kidneys and plasma were collected, weighed, snap frozen in liquid nitrogen and stored at −80 °C until further analysis.

    Collection and preparation of human microbiome samples

    Patients were recruited from the Gastroenterology Department at University Hospital of Split between March and August 2020. The study was approved by the ethics committee of the University Hospital of Split (permit number 2181-147-01/06/M.S.-20-4) and the University of Split School of Medicine (permit number: Ur. br. 2181-198-03-04-20-00400) and all participants gave informed consent before participation in the study.

    Faecal samples were collected from 12 patients undergoing gastroenterological analysis for different medical conditions. Exclusion criteria for all patients included in the study were: usage of ABX one month before sample collection and presence of malignant pathology of the analysed tissues.

    Half of the sample volume was mixed with glycerol (20% final concentration) and stored at −80 °C to conserve viable microorganisms for subsequent in vitro BBN conversion assays. The remaining sample volume was directly stored at −80 °C for DNA extraction (PowerSoil Kit, QIAGEN) and 16S rRNA sequencing.

    Histological analysis

    Following euthanization of mice, the bladders were collected and medially cut into equal halves using a scalpel. One half was immediately frozen in liquid nitrogen and kept for subsequent analysis. The other half was immersed in neutral-buffered formalin (10%) for 24 h. Following fixation, tissues were dehydrated using a series of ethanol dilutions (75%, 90%, 95% and three times 100%, for 1 h each), cleared with xylene (three series for 30 min each) and finally embedded in paraffin (immersed in two series of paraffin for 1 h each and embedded in a third series of paraffin). Embedded tissues were then cut into 5-μm sections with a microtome (RM2125 RTS, Leica) and stained with haematoxylin (Sigma) and eosin (Merck) for microscopical examination. Blinded histological assessment was carried out by researchers and by a trained pathologist.

    HEP-G2 cell line experiment

    HEP-G2 cells were treated at 70% confluence with either BBN (0.05%) or BBN (0.05%) plus ABX mixture (containing vancomycin, streptomycin, metronidazole, neomycin and penicillin (in the same concentrations as in the mouse experiment)) in DMEM medium (Sigma-Aldrich) with 10% FBS (PAA Laboratories) for 24 h. Cells were pelleted (300 rcf, 3 min) and supernatant was used for BBN and BCPN measurements by high-performance liquid chromatography (PerkinElmer series 200) as described previously25. HEP-G2 (ACC-180) cells were obtained from the DSMZ (German Collection of Microorganisms and Cell Cultures).

    Ex vivo and in vitro BBN conversion assays

    CFU of ex vivo microbial communities were determined as described above. To isolate single ex vivo communities, bacterial cultures at different dilutions were streaked onto brain heart infusion (BHI) blood plates, and incubated under anaerobic, microaerobic and aerobic oxygen conditions and incubated at 37 °C for 24–48 h. Between 24 and 48 single colonies were then randomly picked from dilution plates when possible. The full-length DNA of the 16S rRNA gene of each isolate was PCR-amplified using the 27f (5′-AGAGTTTGATCATGGCTCA-3′) and 1492r (5′-TACGGTTACCTTGTTACGACTT-3′) primer pair and sent for Sanger sequencing (Eurofins; Supplementary Tables 50 and 51). Type strains from the German Culture Collection (DKFZ) or the American Type Culture Collection (ATCC) were streaked onto BHI blood plates and allowed to grow for 1–2 days before use.

    Intestinal and faecal samples obtained from mice and humans were grown as ex vivo microbial communities and single bacterial isolates and strains were grown as axenic cultures at 37 °C under 0% (anaerobic, Coy chamber), 10% (microaerobic, Coy chamber) and 21% (aerobic, incubator) oxygen conditions in BHI-S medium (37.0 g BHI broth, 5 g yeast extract supplemented with l-cysteine HCl, haemin and vitamin K1 in 1 l distilled water) or modified GAM (MGAM) broth (HyServe, catalogue number 5433) for 2 h for communities to prevent overgrowth of strains in microbial communities or overnight for axenic cultures. Cultures were then treated with 10 μM BBN after mixing with an equal volume of twofold-diluted BHI-S medium to allow further exponential growth. A 20 µl volume of the treated culture was collected after 0, 4, 8, 12 and 24 h of BBN incubation and immediately frozen in a 96-well V-bottom storage plate (Fisher Scientific, catalogue number 10304513), and sealed with aluminium foil at −80 °C for storage until further processing. To ensure even oxygen distribution in each well under microaerobic and aerobic conditions, the assays were carried out on an orbital plate shaker (Thermo Shaker PHMP) at 600 r.p.m.

    16S rRNA sequencing

    DNA was isolated from mouse and human samples using the QIAGEN PowerSoil kit and quantified on Qubit (Thermo Fisher Scientific). DNA library preparation and sequencing were carried out as described before26. In brief, for the first PCR reaction, 5–20 ng of DNA was amplified for 25 to 30 cycles with KAPA or Q5 (BioLabs) master mix with primers for the variable region V4 of the 16S rRNA gene (forward: 5′-GTGCCAGCMGCCGCGGTAA-3′; reverse: 5′-GGACTACHVGGGTWTCTAA-3′)27. For the second PCR reaction, 1 μl or 2 μl, depending on the PCR product band width on the gel, of the first PCR product was mixed with primers (NEXTFLEX 16S V1-V3 Amplicon-Seq Kit, PerkinElmer), and KAPA or Q5 (Biolabs) master mix and amplified for 25 cycles. After pooling, the library was cleaned with the AMPure XS kit (Beckman) with 0.75× ratio according to the manufacturer’s protocol. All samples were paired-end sequenced with 250-bp read lengths on the Illumina MiSeq platform at the Genomics Core Facility of EMBL Heidelberg.

    Raw data quality was assessed using FastQC v0.11.5 and raw data were imported in QIIME2 v2020.8 for downstream analysis28. Samples were checked for adapter contamination with cutadapt29 and passed to dada230 for denoising, dereplication and chimera filtering; a feature table describing the distribution of reads in each sample among the identified ASVs was created, together with a representative sequence for each of the ASVs. The representative sequences identified for each ASV were used to create a fragment insertion tree using sepp31. The feature table and the built insertion tree were used to compute α- and β-diversity metrics, separately for mice and humans.

    DNA sequences of the whole 16S rRNA gene (V1–V9) from isolated bacteria obtained by Sanger sequencing were also imported into QIIME v2020.8, together with their corresponding taxonomy, as derived from the ACT service32. When possible, ACT taxonomy was further detailed at species level (if not already present) by directly aligning complete sequences to the 16S–/ITS reference database using BLAST33, only if a percentage identity of >99% could be detected over an alignment length of minimum 700 bp. ASV representative sequences were aligned to these full-length 16S rRNA sequences using vsearch34 with the following parameters: –p-maxaccepts ‘all’, –p-perc-identity 0.98, –p-query-cov 0.98, –p-top-hits-only True. Representative sequences not aligned to any Sanger sequence were assigned a taxonomy with a pre-fitted sklearn-based classifier35, trained over the Greengenes 13_8 99% operational taxonomic unit full-length sequences. The feature table and taxonomy thus obtained were exported to plain tsv files, to be imported into R 4.0.0 (https://www.R-project.org/).

    All ASVs found in mouse and human samples were respectively aligned with mafft36 and used to construct a phylogeny with fasttree237. The phylogenetic tree was exported in Newick format and imported into iTOL38 for visualization and tree annotation.

    Whole-genome sequencing

    Bacterial isolates were grown in liquid culture overnight, and DNA was extracted with PowerSoil kit (QIAGEN). Libraries for whole-genome sequencing were prepared using the MagicPrep NGS system with 40 μl of 100 ng DNA. High-throughput sequencing was carried out with MiSeq Reagent Kit v2 Micro, resulting in 155-bp-long paired-ends reads. Sample quality was assessed using FastQC v0.11.939 and MultiQC 1.1240; sample reads were trimmed for both quality and length using Trimmomatic 0.3941 with the following options: removal of TruSeq adapters sequences; sliding window trimming, clipping the read once the average quality within the window (4 bp) falls below 20; finally, drop the read if it is shorter than 38 bp (Supplementary Table 35). Subsequently, reads were de novo-assembled using Spades v3.15.342, and the quality of assembly was assessed using QUAST v5.0.243.

    Three different approaches were used to assess species assignation: a k-mer-based approach, using kraken v2.0.744; a marker gene approach, using gtdbtk v2.1.145; a 16S-based approach, using mTAGs v1.0.446. All three approaches agreed in classifying all isolates as Escherichia or EscherichiaShigella.

    All assemblies were therefore annotated using Prokka v1.1347 with the genus Escherichia as Organism details. Annotation results were passed to Roary v3.7.048 for pangenomic analysis. The 7 isolates shared 3,277 core genes over a total of 7,606 genes (Supplementary Table 36). Pangenome results were visualized with Phandango v1.3.049, and the tree built from accessory genome presence absence was visualized using iTOL v650.

    Sample preparation for LC–MS measurements

    Sample preparation for LC–MS measurements was carried out as previously described5. In brief, for liquid tissues (that is, urine and plasma), 20 µl of the samples was subjected to a freeze–thaw cycle before the addition of 100 µl of acetonitrile/methanol (1:1), and 5 µl of 8 µM of internal standard, warfarin, was added to each sample. Samples were incubated at −20 °C for 30 min before centrifugation at 4 °C at 4,500 r.p.m. for 15 min. A 10 µl volume of the supernatant was diluted with 10 µl of water before LC–MS measurements. For solid tissues (that is, intestine, kidney, liver and bladder), samples were homogenized with 3-mm tungsten carbide beads (QIAGEN, catalogue number 69989) in 300–400 µl of acetonitrile/methanol (1:1) containing 320 nM internal standard by 5 min bead-beating at 30 Hz on a QIAGEN TissueLyser II. After 30 min incubation at −20 °C and 15 min centrifugation at 4 °C and 10,000 rcf, 10 µl of the supernatant was diluted with water at 1:1 or more before LC–MS measurements.

    Quantification of BBN and BBN metabolites by LC–MS

    Chromatographic separation was carried out on a 3.0 mm × 10 cm Poroshell120 HPHC18 column with 1.9 µM particle size (Agilent Technologies) mounted on an Agilent 1290 Infinity II LC system coupled to a 6550 iFunnel qToF mass spectrometer. The column temperature was maintained at 45 °C. The mobile phase was composed of A: water with 0.1% formic acid; and B: methanol with 0.1% formic acid. A 5 μl volume of each sample was injected at 0.6 ml min−1 flow rate starting from 5% mobile phase B followed by a linear gradient to 95% over 5.5 min. The column was allowed to re-equilibrate to starting conditions for 1.1 min before each sample injection. The mass spectrometer was operated in both negative and positive scanning mode (50–1,700 m/z) with the following source parameters: VCap, 3,500 V; nozzle voltage, 2,000 V; gas temperature, 275 °C; drying gas, 13 l min−1; nebulizer, 45 psi; sheath gas temperature, 275 °C; sheath gas flow, 12 l min−1, fragmentor, 365 V. Online mass calibration was carried out using a second ionization source and a constant flow (2 ml min−1) of reference mass solvent (purine m/z = 121.0509 and hexakis m/z = 922.0098 for positive mode, betaine m/z = 112.9856 and hexakis m/z = 1033.9881 for negative mode). Standard curves for BBN and BCPN were obtained by serial-diluting each compound in water at twofold from 10 µM to 4.9 nM.

    The MassHunter Qualitative Analysis software (Agilent Technologies, v10.0) was used to determine the retention time for all compounds to enable targeted analysis and quantification. Peak integration was carried out in MassHunter Quantitative Analysis software (Agilent Technologies, v10.0) with the following settings: mass tolerance = 20 ppm; peak filter at signal-to-noise ratio = 2; and retention time tolerance of 0.5 min. All statistical analyses and plotting were carried out in RStudio (v4.2.0) after exporting the data files from MassHunter Quantitative Analysis software. BBN and BCPN concentrations were calculated using the recorded calibration curves and the signals of the internal standard. In brief, the area of the internal standard warfarin in each sample was divided by the median area of warfarin across all samples in the same tissue to obtain the correction factor for each sample, which was then used to normalize the areas for the targeted compounds in each sample. Total drug amounts in each intestinal compartment were calculated using the corresponding total sample weight.

    Reporting summary

    Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article.

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  • Ancestral allele of DNA polymerase gamma modifies antiviral tolerance

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    Ethical aspects

    Human samples were collected and used with informed consent, according to the Helsinki Declaration and approved by the Ethical Review Board of Kuopio University Central Hospital (410/2019). Animal experimental procedures were approved by the Animal Experimental Board of Finland (ESAVI/689/4.10.07/2015 and ESAVI/3686/2021). Patient and control materials included fibroblasts (established from skin biopsies from individuals’ forearms), blood and autopsy-derived brain samples. Control samples were from voluntary healthy individuals (fibroblasts and sera) and, for brains, from people who died acutely with a non-central-nervous-system-disease cause. Autopsy sample collection was approved by the governmental office for social topics and health.

    Antibodies, antisera and kits

    Information of the antibodies and oligonucleotide sequences is provided in Supplementary Table 6. Enzyme-linked immunosorbent assay (ELISA) kits for mouse IFNα all subtypes (42115-1), mouse IFNβ (42410-1), mouse IL-6 (BMS603HS), human IL-6 (BMS213HS) and human TNF (HSTA00E) and the CellTiter-Glo Luminescent Cell Viability Assay kit (Promega) were commercially purchased, and assays were performed according to the manufacturer’s instructions.

    MIRAS mouse generation

    MIRAS knock-in mice were generated and maintained in the C57BL/6JOlaHsd background carrying two variants homologous to mutations of patients with MIRAS on mouse chromosome 7 (NCBI Reference Sequence: NC_000073.7): c.2177G>C into exon 13 (p.W726S); c.3362A>G into exon 21 (p.E1121G). In brief, the pL253 construct carrying exons 4–22 of the Polg1 genomic region carrying the MIRAS variants was transfected into embryonic stem (ES) cells by electroporation and homologous recombination introduced to the endogenous gene. ES clones with successful recombination were selected based on neomycin resistance. The mutations were confirmed using Southern blot hybridization, PCR and DNA sequencing (DNA-seq). Correct ES clones were injected into blastocysts and implanted into pseudopregnant female mice. Lines with verified germ-line transmission were crossed with mice expressing FLP recombinase to remove the neomycin cassette. The correct genotypes of MIRAS mice were confirmed by DNA-seq. The genotypes were born in Mendelian frequencies, with no gross phenotypic differences between the groups. Mice were housed in controlled rooms at 22 °C under a 12 h–12 h light–dark cycle and with ad libitum access to food and water, and were regularly monitored for weight and food consumption. Further details are provided in Extended Data Fig. 6.

    Cell culture and transfection

    Human primary dermal fibroblasts (of the first 8 passages; ±2 passage difference across cell lines of different individuals) that were genetically screened for MIRAS point mutations (by DNA-seq) were used for analyses. Fibroblasts were cultured in DMEM (Lonza; with 4.5 g l−1 glucose) supplemented with 10% (v/v) heat-inactivated FBS (Lonza), 50 U ml−1 penicillin–streptomycin (Gibco), 0.05 mg ml−1 uridine (Calbiochem) and 2 mM GlutaMAX (Gibco) at 37 °C under 5% CO2, with fresh medium replaced every 2 days, and were tested negative for mycoplasma. Transfection of synthetic dsDNA50 and dsRNA (poly(I:C), Sigma-Aldrich) was performed using FuGENE HD transfection reagent (Promega). In brief, around 2 × 105 cells were plated onto six-well dishes the day before transfection and transfected with 2.5 μg of dsDNA or dsRNA per well with a 1:2 ratio of nucleic acid:transfection reagent, according to the manufacturer’s instructions (sequence details are provided in Supplementary Table 6). For expression of RIG-I or MAVS, fibroblasts were transfected with pcDNA3.1(+)-Flag containing RIG-I (N) or MAVS51 before poly(I:C) transfection 24 h later and incubated for another 7 h before collection.

    Patient genetic mutation correction in iPSCs

    For MIRAS POLG1 genetic correction, electroporation with CRISPR–Cas9 system components was performed as previously described52. We used high-efficiency gRNA and a dsDNA donor template including the desired correction along with a novel restriction site for SalI (GˆTCGAC). A total of 55 monoclonal colonies was individually screened by SalI digestion and successful correction was validated by Sanger sequencing. The chromosomal integrity was confirmed by G-banding performed by Anàlisis Mèdiques Barcelona. A list of the gRNA, donor template and primers for top-six off-target Sanger sequencing (CRISPOR, https://benchling.com) is provided in Supplementary Table 6.

    Differentiation of iPSCs into iFLCs

    Induced pluripotent stem cells (iPSCs) were cultured on Matrigel-coated (Corning) plates in E8 medium (Thermo Fisher Scientific) until 90–100% confluency, then split and plated in suspension in ultra-low attachment plates containing hES medium without basic fibroblast growth factor (bFGF) and supplemented with 5 µM ROCK inhibitor (Y-27632, Selleckchem). The medium without ROCK inhibitor was refreshed every other day until day 14, when the aggregates were plated onto gelatin-coated plates containing DMEM/F12 + 20% FBS (Thermo Fisher Scientific) to allow for expansion. The cells were kept for at least 5 passages to obtain induced fibroblast-like cells (iFLCs).

    qPCR

    RNA from cells was extracted using the RNeasy kit (Qiagen) according to the manufacturer’s instructions. For tissues, homogenization was first performed with ceramic beads using Precellys 24 homogenizer (Precellys) before RNA extraction using the Trizol/chloroform method followed by purification using the RNeasy kit. DNase-treated RNA (normalized across samples) was used for cDNA synthesis using the Maxima first-strand cDNA synthesis kit (Thermo Fisher Scientific) before qPCR using SensiFAST SYBR No-ROX kit (Bioline) and primers (details in Supplementary Table 6) according to the manufacturer’s instructions. The amplification level of the assayed gene (2–4 technical replicates per controls and patients) was normalized to ACTB and analysed using the \({2}^{-\Delta \Delta {C}_{{\rm{t}}}}\) method. mtDNA qPCR was performed on DNA extracted using the DNeasy blood and tissue kit (Qiagen) as described above and previously53 and normalized to nuclear ACTB or B2M. For viral RNA analyses, TBEV NS5 RNA54 or murine hepatitis virus55 RNA amount was detected using primers and Taqman probes against the targeted viral genome, using the TaqMan Fast Virus 1-Step Master Mix (Thermo Fisher Scientific) according to the manufacturer’s instructions. The copy number for TBEV NS5 RNA was determined using a standard curve generated by serial dilution of TBEV-isolated NS5 RNA. Details of the primers are provided in Supplementary Table 6.

    Cytosolic extraction and detection of cytosolic mtRNA/mtDNA

    Pelleted cells were resuspended in isolation buffer (20 mM HEPES-KOH pH 7.6, 220 mM mannitol, 70 mM sucrose, 1 mM EDTA, 1× protease inhibitor (Thermo Fisher Scientific)) and divided into two equal fractions: fraction 1, purify total cellular RNA or DNA; and fraction 2, subcellular fractionation to isolate cytosolic RNA or DNA. In brief, fraction 2 was homogenized in around 900 μl of suspension buffer in a handheld Dounce tissue homogenizer with glass pestle (~15 strokes). The homogenate was centrifuged at 800 g for 5 min at 4 °C and the resulting supernatant was centrifuged at 12,000 g for 10 min at 4 °C. The supernatants were collected and centrifuged at 17,000 g for 15 min at 4 °C to purify the cytosolic fraction. The whole-cell (fraction 1) and cytosolic (of fraction 2) fractions were subjected to DNA or RNA purification using the RNeasy Kit or DNAeasy Blood and Tissue Kit (Qiagen) and eluted into an equal volume of water. RNA eluate was treated with DNase before cDNA production. Equal volume of cDNA or DNA eluate were used for qPCR using nuclear gene primers (ACTB or B2M) or mitochondrial genome-specific primers (MT-CYB and MT-CO1). mtDNA/RNA abundance in whole cells served as normalization controls for their values obtained from cytosolic fractions18. The purity of cytosolic fraction was examined by western blotting.

    In vivo BrdU labelling and south-western analyses

    Mice receiving an intraperitoneal injection of 300 μg of BrdU (BD Biosiences) per gram of mouse weight were euthanized 24 h after injection. DNA was isolated by routine phenol–chloroform extraction. XhoI-digested DNA was separated using agarose gel electrophoresis and blotted onto Hybond N+ membranes (Amersham) as described previously53. Immunodetection was performed using anti-BrdU antibodies, and total mtDNA was detected using Southern hybridization as described previously56.

    Viral stocks and infections of fibroblasts

    The European subtype of TBEV was isolated from human neuroblastoma cells (SK-N-SH; passage 1) infected with tick collected in Finland57; SARS-CoV-2 was isolated from a patient with COVID-19 on human non-small cell lung cancer (Calu-1) cells58, passaged on African green monkey kidney (Vero E6) cells expressing type II membrane serine protease 2 (TMRSS2) via lentivirus transduction59; the KOS strain of herpes simplex virus 1, HSV-160, was passaged on Vero cells. SK-N-SH (https://www.atcc.org/products/htb-11), Calu-1 (https://www.atcc.org/products/htb-54), Vero E6 (https://www.atcc.org/products/crl-1586) and Vero (https://www.atcc.org/products/ccl-81) cells were purchased from ATCC. The virus work was performed under bio-safety level 3 (BSL-3) conditions for TBEV and SARS-CoV-2 and under BSL-2 conditions for HSV-1. The ability of viruses to infect fibroblasts was tested by inoculating cells grown on a 96-well plate with serially ten-fold diluted virus stocks and the optimal viral dilution was selected based on the dilution showing the most prominent difference in infected cells number between wild-type control and MIRAS cells using immunofluorescence.

    For fibroblast infection, around 2 × 105 fibroblast cells were grown on six-well plates the day before (or ~1 × 105 iFLCs 2 days before) being inoculated with 500 µl of 1:20 diluted TBEV, 1:10 diluted SARS-CoV-2 or 1:5,000 diluted HSV-1 (multiplicity of infection (MOI) of ~0.1–1). After 1 h (at 37 °C, 5% CO2), the inocula were removed, the cells were washed twice with conditioned medium, 3 ml of fresh medium was added to each well and the plates were incubated at 37 °C under 5% CO2 for 6, 24 or 48 h. Non-treated cells that were plated simultaneously alongside those subjected to viral infection were used as the uninfected control. At the end of incubation, the cells were washed twice with PBS and were lysed in RIPA buffer (50 mM Tris, 150 mM NaCl, 1% Triton X-100, 0.1% SDS, 0.5% sodium deoxycholate, pH 8.0) supplemented with EDTA-free protease inhibitor cocktail (Roche), at 150 µl per well for western blotting analyses. For DNA/RNA analyses, 60 µl of RIPA lysate was mixed with TRIzol Reagent (Thermo Fisher Scientific) before DNA or RNA extraction and RT–qPCR or qPCR as described in relevant Methods section. For the immunofluorescence assay, infected cells were fixed with 4% paraformaldehyde (PFA, in PBS) and incubated for 15 min at room temperature. The cells were washed once with PBS, permeabilized for 5 min at room temperature with Tris-buffered saline, pH 7.4 supplemented with 0.25% Triton X-100 and 3% (w/v) of bovine serum albumin, and replaced with PBS. Virus inactivation was confirmed by UV-inactivation with a dose of 500 mJ cm−2 before incubation with primary antibodies and processed as described below.

    Immunofluorescence microscopy

    The PFA-fixed viral-infected cells were stained with primary antibodies (Supplementary Table 6) overnight at 4 °C and for 1 h at room temperature with secondary antibodies. Three washes with PBS were included between each step. Coverslips were mounted with VECTASHIELD anti-fade mounting medium containing DAPI (Vector Laboratories). Images were acquired using the Zeiss AxioImager epifluorescence microscope. Quantification of the immunofluorescence signal was performed using CellProfiler (v.4.2.6)61.

    Gel electrophoresis and western blotting

    Cells lysed in RIPA buffer (150 mM NaCl, 1% Triton X-100, 0.5% sodium deoxycholate, 0.1% SDS, 50 mM Tris-Cl, pH 8.0) were measured for protein concentration using the BCA assay (Pierce) and equal amounts of protein samples were resuspended into SDS–PAGE loading dye (50 mM Tris-Cl, pH 6.8, 100 mM dithiothreitol, 2% (w/v) sodium dodecyl sulphate, 10% (w/v) glycerol, 0.1% (w/v) bromophenol blue), boiled for 5–10 min at 95 °C before SDS–PAGE analysis using the 4–20% gradient gel (Bio-Rad) according to the manufacturer’s instructions.

    For mitochondrial protein analyses, mitochondria were isolated from tissue using differential centrifugation as described previously62. The clarified mitochondrial pellets were resuspended into buffer (20 mM HEPES-KOH pH 7.6, 220 mM mannitol, 70 mM sucrose, 1 mM EDTA) and analysed using SDS–PAGE, or solubilized using 1% (w/v) n-dodecyl-β-d-maltoside (DDM) in 1.5 M α-amino n-caproic acid for 30 min on ice for blue-native (BN) electrophoresis analysis. DDM-solubilized samples were centrifuged at 20,000g for 20 min at 4 °C. The clarified supernatants were measured for protein concentration using the BCA assay and equal amounts of protein samples were mixed with BN loading dye (0.25% (w/v) Coomassie blue G250 (MP Biomedicals), 75 mM α-amino n-caproic acid) before BN electrophoresis using cathode buffer (50 mM tricine, 15 mM Bis-Tris, pH 7.0, 0.02% (w/v) Coomassie blue G250) and anode buffer (50 mM Bis-Tris, pH 7.0) on self-casted 1-mm-thick 5–12% gradient polyacrylamide gels. Separation part of the gel was prepared by mixing solution of 5 and 12% acrylamide (acrylamide:bisacrylamide 37.5:1) in 0.5 M α-amino n-caproic acid, 50 mM Bis-Tris (pH 7.0), 11 or 20% (w/v) glycerol, 0.027% ammonium persulfate, 0.1% TEMED. Separation gel was overlayed with a 4% acrylamide stacking gel solution as described above (no glycerol; but 0.084% ammonium persulfate, 0.17% TEMED).

    After electrophoresis, gels were transferred onto 0.45 μm PVDF membranes using a semidry transfer (SDS–PAGE) or wet transfer (BN-PAGE) apparatus (Bio-Rad) before western blotting using the desired antibodies (details are provided in Supplementary Table 6). Images were obtained using ChemiDoc XRS+ imaging machine (Bio-Rad) and signals were quantified using Image Lab (v.6.1.0 build 7; Bio-Rad) according to the manufacturer’s instructions. The protein-of-interest signal was normalized to the loading control signal in the sample.

    Mouse behavioural analyses

    Treadmill

    An Exer-6M treadmill (Columbus Instrument) was used as described previously63. The tests were completed as a set of five independent trials over 1 h. The running time was counted when the mouse stopped for five continuous seconds and did not continue.

    Rotarod

    The rotating rod system (Rota-Rod; Ugo Basile, 47600) with a PVC drum (diameter of 44 mm) was used as described previously64. The animals were trained for three consecutive days before the test.

    Footprint analyses to detect ataxia

    Mouse feet were painted with non-toxic washable paint (separate colours for hind- and forelimbs) and the mouse was allowed to walk through a tunnel on paper. The stride length and width were measured. Scoring data were obtained using at least two consecutive steps from each foot.

    Infection of mice, histology and immunohistochemistry

    Mice were transported to the BSL-3 facility and acclimatized to individually ventilated biocontainment cages (ISOcage; Scanbur) for 7 days before being inoculated intraperitoneally with 1,000 plaque-forming units of TBEV. Mice were euthanized at the indicated days after infection and sera were collected for cytokine analyses using commercially purchased ELISA kits (see the ‘Antibodies, antisera and kits’ section). For DNA, RNA or protein analyses (see the relevant Methods section), tissues were collected into TRIzol Reagent (Thermo Fisher Scientific). For histology, liver samples were fixed in cold 4% (v/v) PFA in PBS and incubated in PBS supplemented with 30% (w/v) sucrose at 4 °C for 3 days before routine embedding in OCT compound and trimmed into sections with a thickness of 6–8 μm for haematoxylin and eosin or ORO staining according to the standard protocol65. For immunohistochemical staining, liver sections were stained with the following antibodies: CD3 (T cell marker), CD4 (helper T cell marker), CD8b (cytotoxic T cell marker) or CD68 (macrophage marker) using the ImmPRESS HRP goat anti-rat IgG (Mouse Adsorbed) Polymer Kit (Vector Laboratories, MP-7444), and with haematoxylin counterstaining according to the manufacturer’s instructions. Liver inflammation severity was semi-quantitatively scored and the total number of immune cell infiltrations was quantified from three unique visual fields at ×5 magnification (15,370,559 μm2 per view) per mouse liver section. The area (μm2) of the largest infiltrate detected per view was measured using ImageJ (2.0.0-rc-69/1.52n; https://imagej.net/ij/). Liver ORO and CD protein signal was quantified using CellProfiler (v.4.2.6)61 after pixel classification using ilastik (v.1.3.3)66.

    For brain histology, brain halves (cut in midline) were fixed in PFA for 48 h, then stored in 70% (v/v) alcohol until processing. They were trimmed and routinely paraffin-wax embedded. Consecutive sections (3–4 µm) were prepared and stained with haematoxylin and eosin or subjected to immunohistochemical staining for TBEV antigen, CD3 (T cell marker), CD45R/B220 (B cell marker) and IBA1 (marker of macrophages and microglial cells), according to previously published protocols67,68. Mouse brain GABAergic marker staining was performed using GAD67 and GABRB2 antibodies followed by blinded semi-quantitative scoring by A.P. (neuropathologist). Details of the antibodies are provided in Supplementary Table 6.

    Bulk RNA-seq analysis

    RNA-seq was performed at the Biomedicum Functional Genomics Unit (University of Helsinki) according to the Drop-seq protocol as described previously69,70. A total of 10 ng of extracted RNA was used as the starting material. The quality of the sequencing libraries was assessed using the TapeStation DNA High Sensitivity Assay (Agilent). The libraries were sequenced on the Illumina NextSeq 500 system70. For read alignment and generation of digital expression data, raw sequencing data were inspected using FastQC and multiQC71,72. Subsequently, reads were filtered to remove low-quality reads and reads shorter than 20 bp using Trimmomatic73. Reads passing the filter were then processed further using Drop-seq tools according to the pipeline described69 (v.2.3.0). In brief, the raw, filtered read libraries were converted to sorted BAM files using Picard tools (http://broadinstitute.github.io/picard). This was followed by tagging reads with sample specific barcodes and unique molecular identifiers (UMIs). Tagged reads were then trimmed for 5′ adapters and 3′ poly A tails. Alignment ready reads were converted from BAM-formatted files to fastq files that were used as an input for STAR aligner74. Alignments were performed using the GRCm38 (mouse) reference genome and GENCODE mouse release 28 or the GRCh38 (human) reference genome and GENCODE human release 33 comprehensive gene annotation files75 with default STAR settings. After the alignment, the uniquely aligned reads were sorted and merged with the previous unaligned tagged BAM file to regain barcodes and UMIs that were lost during the alignment step. Next, annotation tags were added to the aligned and barcode-tagged BAM files to complete the alignment process. Finally, Drop-seq tools were used to detect and correct systematic synthesis errors present in sample barcode sequences. Digital expression matrices were then created by counting the total number of unique UMI sequences (UMI sequences that differ by only a single base were merged together) for each transcript. Differential expression analysis was performed with DESeq2 (using the default settings) in the R environment76.

    Untargeted metabolomics

    Metabolites were extracted from 20 mg of mouse cerebral cortex in hot ethanol. In brief, frozen samples were homogenized in 0.5 ml 70% (v/v) ethanol with ceramic beads using a Precellys 24 homogenizer (Precellys). Before and after homogenization, the samples were kept frozen (at ≤−20 °C). The samples were transferred to a 15 ml tube with washing using 0.5 ml of 70% (v/v) ethanol. To each tube, we added 7 ml of 70% (v/v) ethanol that was preheated at 75 °C, immediately vortexed and placed the sample into a water bath at 75 °C for 1 min followed vortexing once. The content was cooled down in cold bath at −20 °C before being centrifuged for 10 min (4 °C). The clear supernatant was transferred to a new tube and stored at −80 °C until analysis using mass spectrometry (MS).

    Untargeted metabolite profiling was performed using flow injection analysis on the Agilent 6550 QTOF instrument (Agilent) using negative ionization, 4 GHz high-resolution acquisition and scanning in MS1 mode between m/z 50 and m/z 1,000 at 1.4 Hz. The solvent was 60:40 isopropanol:water supplemented with 1 mM NH4F at pH 9.0, as well as 10 nM hexakis(1H,1H,3H-tetrafluoropropoxy)phosphazine and 80 nM taurochloric acid for online mass calibration. The seven batches were analysed sequentially. Within each batch, the injection sequence was randomized. Data were acquired in profile mode, centroided and analysed using MATLAB (MathWorks). Missing values were filled by recursion in the raw data. After identification of consensus centroids across all of the samples, ions were putatively annotated by accurate mass and isotopic patterns. Starting from the HMDB v.4.0 database, we generated a list of expected ions including deprotonated, fluorinated and all major adducts found under these conditions. All formulas matching the measured mass within a mass tolerance of 0.001 Da were enumerated. As this method does not use chromatographic separation or in-depth MS2 characterization, it is not possible to distinguish between compounds with an identical molecular formula. The confidence of annotation reflects level 4 but, in practice, in the case of intermediates of primary metabolism, it is higher because they are the most abundant metabolites in cells. The resulting data matrix included 1,943 ions that could be matched to deprotonated metabolites listed in HMDB v.3.0.

    Proteomics

    Protein was extracted from 50 mg of frozen brain autopsy samples using TRIzol Reagent (Thermo Fisher Scientific) according to the manufacturer’s instructions. Extracted protein pellets were resuspended into 100 μl of buffer containing 6 M urea, 50 mM ammonium bicarbonate, pH 8 and boiled for 5–10 min at 95 °C. The protein concentration was estimated using the BCA assay (Pierce) and equal amounts of protein samples were aggregated on amine beads77. For on-bead digestion, 50 mm ammonium bicarbonate buffer was added to the beads. Proteins were reduced with 10 mM DTT for 30 min at 37 °C and alkylated with 20 mM IAA for 30 min at room temperature in dark, after which 0.5 µg of trypsin was added, and trypsin digestion was performed overnight at 37 °C. Beads were separated using a magnet, the supernatant was transferred to new tube and acidified, and the tryptic peptides were desalted using C18 StageTips for MS analysis. Liquid chromatography coupled with tandem MS (LC–MS/MS) analysis of the resulting peptides was performed using the Easy nLC1000 liquid chromatography system (Thermo Electron) coupled to a QExactive HF Hybrid Quadrupole-Orbitrap mass spectrometer (Thermo Electron) with a nanoelectrospray ion source (EasySpray, Thermo Electron). The LC separation of peptides was performed using the EasySpray C18 analytical column (2 µm particle size, 100 Å, 75 μm inner diameter and 25 cm length; Thermo Fisher Scientific). Peptides were separated over a 90 min gradient from 2% to 30% (v/v) acetonitrile in 0.1% (v/v) formic acid, after which the column was washed using 90% (v/v) acetonitrile in 0.1% (v/v) formic acid for 20 min (flow rate 0.3 μl min−1). All LC–MS/MS analyses were operated in data-dependent mode where the most intense peptides were automatically selected for fragmentation by high-energy collision-induced dissociation. For data analysis, raw files from LC–MS/MS analyses were submitted to MaxQuant (v.1.6.7.0)78 for peptide/protein identification and label-free quantification. Parameters were as follows: carbamidomethyl (C) was set as a fixed modification; protein N-acetylation and methionine oxidation as variable modifications; first search error window of 20 ppm and main search error of 6 ppm; the trypsin without proline restriction enzyme option was used, with two allowed miscleavages; minimal unique peptides was set to one; and the FDR allowed was 0.01 (1%) for peptide and protein identification. The UniProt human database (September 2018) was used for the database searches. MaxQuant output files (proteinGroups.txt) were loaded into Perseus (v.1.6.1.3)79 for further data filtering and statistical analysis. Identifications from potential contaminants and reversed sequences were removed, and normalized intensities (LFQ) were log10-transformed. Next, a criteria of at least 50% valid values in at least one group was used to filter the results. All zero intensity values were replaced using noise values of the normal distribution of each sample. Protein abundances were compared using a two-sample Student’s t-test with P < 0.05 as the criteria for a statistically significant difference between the two groups.

    Functional and pathway enrichment analyses

    Qiagen Ingenuity Pathway Analyses (Qiagen; https://digitalinsights.qiagen.com/IPA), g:Profiler80 (https://biit.cs.ut.ee/gprofiler) toolset and KEGG database81 were used for the analyses of transcriptome, metabolome and/or proteome datasets. For immune pathway analyses, we further used the manually curated InnateDB database82 (https://www.innatedb.com/index.jsp).

    Genotype–phenotype association analyses

    Analyses were performed on the data from the FinnGen study, a large-scale genomics initiative that has analysed Finnish Biobank samples and correlated genetic variation with health data to understand disease mechanisms and predispositions6. The mixed-model logistic regression method SAIGE (R package developed with Rcpp for genome-wide association tests in large-scale datasets and biobanks) was used for association analysis and included the following covariates in the model: sex, age, genotyping batch and ten principle components. These results are from 3,095 end points, 16,962,023 variants and 309,154 individuals in data freeze 7 (https://r7.finngen.fi/).

    Statistical analyses

    Statistical analyses as described in the figure legends were performed either using Microsoft Excel v.16.80, GraphPad Prism v.10.1.1 for macOS (GraphPad, www.graphpad.com) or using toolsets as indicated in the respective figure legends and in relevant method sections. GraphPad Prism v.10.1.1 as described above was used to create box and whisker plots using the standard five-number summary: minimum, lower quartile (25th percentile), median (50th percentile), upper quartile (75th percentile) and maximum, with whiskers extending down to the minimum and up to the maximum value; bar charts show the mean ± s.e.m. The datapoints for each value are superimposed on the plot. No statistical methods were used to predetermine the sample size. Sample sizes were chosen to ensure adequate power and to account for potential interindividual/animal, gender and age variance (age- and sex-matched samples were used as controls). The number of biologically independent mouse or human samples is described in the respective figure legends.

    Reporting summary

    Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article.

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    Human samples

    Human samples came from the Milieu Intérieur cohort, which was approved by the Comité de Protection des Personnes–Ouest 6 on 13 June 2012, and by the French Agence Nationale de Sécurité du Médicament (ANSM) on 22 June 2012. The study is sponsored by Institut Pasteur (Pasteur ID-RCB Number: 2012-A00238-35) and was conducted as a single-centre interventional study without an investigational product. The original protocol was registered under ClinicalTrials.gov (study no. NCT01699893). The samples and data used in this study were formally established as the Milieu Intérieur biocollection (NCT03905993), with approvals by the Comité de Protection des Personnes–Sud Méditerranée and the Commission Nationale de l’Informatique et des Libertés (CNIL) on 11 April 2018. Donors gave written informed consent. The 1,000 donors of the Milieu Intérieur cohort were recruited by BioTrial to be composed of healthy individuals of the same genetic background (Western European) and to have 100 women and 100 men from each decade of life between 20 and 69 years of age. Donors were selected based on various inclusion and exclusion criteria that were previously described12. In brief, donors were required to have no history or evidence of severe, chronic or recurrent pathological conditions, neurological or psychiatric disorders, alcohol abuse, recent use of drugs, recent vaccine administration and recent use of immune modulatory agents. To avoid the influence of hormonal fluctuations in women, pregnant and peri-menopausal women were not included. To avoid genetic stratification in the study population, the recruitment of donors was restricted to individuals whose parents and grandparents were born in Metropolitan France. Additionally, we formally checked how the genetic background of the donors could affect cytokine levels by performing association tests between the first 20 genetic principal components out of the PCA on the individual genotypes and each of the induced cytokines in each stimulation. Although PC1 had significant association with IL-10 (Benjamini–Yekutieli adjusted P value < 0.05), we found that the first 20 principal components showed no significant associations with cytokine responses at the P value threshold (Benjamini–Yekutieli adjusted P value < 0.01) we use throughout this study. To illustrate the homogeneity of the genetic structure of the 1,000 individuals of the Milieu Intérieur cohort, a PCA was performed with EIGENSTRAT41 on 261,827 independent SNPs and 1,723 individuals, which include the 1,000 Milieu Intérieur donors together with 723 individuals from a selection of 36 populations originating from North Africa, the Near East, as well as western and northern Europe42 is shown, similarly to what was previously performed3. PC1 versus PC2, PC1 versus PC3 and PC2 versus PC3 are displayed as well as a bar plot of the variance explained by the first 20 components of the PCA (Extended Data Fig. 9b). Unless otherwise stated, all displayed results have been performed on the 955 individuals of the cohort who gave consent to share their data publicly, in order to ensure easy reproducibility of the results.

    TruCulture whole-blood stimulations

    TruCulture whole-blood stimulations were performed in a standardized way as previously described4,43. Briefly, tubes were prepared in batch with the indicated stimulus, resuspended in a volume of 2 ml buffered medium, and maintained at −20 °C until time of use. Stimuli used in this study were LPS derived from E. coli O111:B4 (Invivogen), E. coli O111:B4 (Invivogen), C. albicans (Invivogen), vaccine-grade poly I:C (Invivogen), live Bacillus Calmette-Guerin (Immucyst, Sanofi Pasteur), live H1N1 attenuated influenza A/PR8 (IAV) (Charles River), SEB (Bernhard Nocht Institute), CD3 + CD28 (R&D Systems and Beckman Coulter), and cytokines TNF (Miltenyi Biotech), IL-1β (Peprotech) and IFNγ (Boehringer Ingelheim). One millilitre of whole blood was distributed into each of the prewarmed TruCulture tubes, inserted into a dry block incubator, and maintained at 37 °C room air for 22 h. At the end of the incubation period, tubes were opened, and a valve was inserted in order to separate the sedimented cells from the supernatant and to stop the stimulation reaction. Liquid supernatants were aliquoted and immediately frozen at −80 °C until the time of use.

    Luminex multi-analyte profiling

    Supernatants from TruCulture tubes were analysed by Rules Based Medicine using the Luminex xMAP technology. Samples were analysed according to the Clinical Laboratory Improvement Amendments (CLIA) guidelines. The lower limit of quantification (LLOQ) was determined as previously described43, and is the lowest concentration of an analyte in a sample that can be reliably detected and at which the total error meets CLIA requirements for laboratory accuracy. The 13 cytokines (CXCL5, CSF2, IFNγ, IL-1β, TNF, IL-2, IL-6, IL-8, IL-10, IL-12p70, IL-13, IL-17 and IL-23), which were measured in this study, were selected to best capture broad immune response variability. Among 109 analytes initially tested, these are the ones that captured the maximum variance following stimulation with the 4 stimuli (LPS, BCG, poly I:C and SEB) that showed the most distinct immune responses among 27 stimuli tested on a subset of 25 individuals of the Milieu Intérieur cohort.

    Principal components analysis

    The PCA in Extended Data Fig. 1 was created in R 4.2.1 using the FactoMineR 2.8 package. The data were log-transformed and by default scaled to unit and missing values were imputed by the mean of the variable.

    Cytokine induction visualization

    Cytokines were considered induced if the absolute value of their median concentration in the stimulated condition was 30%-fold of their concentration in the null condition. Standardized log mean differences were computed as follows (mean(concentration of the cytokine in the stimulated condition) − mean(concentration of the cytokine in the null condition))/s.d.((concentration of the cytokine in the stimulated condition) − (concentration of the cytokine in the null condition)) and the corresponding heat map was generated with heatmaply 1.0.0 and dendextend 1.13.12 with ‘complete’ clustering method and ‘euclidean’ distance in R version 4.2.1.

    Identification of CD3 + CD28 non-responders

    Levels of cytokines that we focused on are low to undetectable in the non-stimulated condition, and cytokine induction is generally homogenous within this healthy population of individuals, with no clear distinguishable groups of responders and non-responders, except for anti-CD3 + CD28 stimulation (Extended Data Fig. 2). For the anti-CD3 + CD28 stimulation, we identified through k-means clustering a group of 705 individuals that responded to the stimulation and a group of 295 individual did not. This lack of response of 295 individuals is explained by a FcγRIIA polymorphism (rs1801274) that was previously described as preventing response to this anti-CD3 + CD28 stimulation28 (Extended Data Fig. 9). All statistical analyses on anti-CD3 + CD28 stimulations in this study were thus performed on the responders only.

    eCRF criteria association tests with induced cytokines

    Variables were extracted from the eCRF filled by the donors with the help of a physician. To limit biases in associations, categorical variables had to have at least 5% of individuals in at least half of the categorical levels to be considered for association tests. Such categoricalvariables or numerical ones were tested for associations with the log-transformed induced cytokine levels in each stimulation through LRTs, using age, sex and the technical variable batchID (corresponding to two batches of TruCulture tubes produced at different periods of time) as covariates: the LRT compared the models lm(cytokine ~ variable + age + sex + batchID) with lm(cytokine ~ age + sex + batchID), followed by Benjamini–Yekutieli multiple testing correction applied to the whole heat maps, so taking into account the tests made for the 136 CRF variables with all the induced cytokines in a specific stimulation. For Extended Data Figs. 4 and 5, the models compared were lm(cytokine ~ age + sex + batchID) with lm(cytokine ~ sex + batchID) for age and lm(cytokine ~ sex + batchID) with lm(cytokine ~ age + batchID) for sex. P values of association tests were represented using ggplot2 3.2.1 in R 3.6.0. Adjusted P values on the box plots were computed with the wilcox.test function, correcting for multiple testing. Versions of the box plots and scatter plots made on the residuals after regression on age, sex and batchID are displayed on Extended Data Fig. 6d–f.

    Effect size plots

    Linear regression models were estimated in each stimulation using the log-transformed induced cytokine levels as outcome and age, sex, batchID, and the covariates of interest (for example, smoking status) as predictor variables. Interactions with the covariates of interest were considered when indicated. Exponential of the regression coefficient estimates, and their 95% confidence interval were plotted. When the covariate of interest is of categorical nature, each level of the variable is shown independently, considering the one specified as the reference. When the P value of the t-test testing if the coefficient estimate is different from zero is <0.01, it is plotted in black, otherwise it is plotted in grey. If the LRT comparing the regression with and without the variable of interest in the model with a Chi-square test is significant with a Benjamini–Yekutieli adjusted P value < 0.01, a red star is added above the effect size value and interval.

    Cell subset association tests

    Acquisition of flow cytometry data was detailed previously3. Association tests with log-transformed values of induced cytokines in each stimulation were performed as for the eCRF criteria association tests using log-transformed raw counts of cell subsets for each donor. P values of significance are indicated with asterisks as follows: *P < 0.05; **P < 0.01; ***P < 0.001.

    DNA methylation association tests

    CpG methylation profiles were generated using the Infinium MethylationEPIC BeadChip (Illumina) on genomic DNA treated with sodium bisulfite (Zymo Research) for 958 individuals of the Milieu Intérieur cohort as described19. Associations between the DNA methylation levels for the CpG sites located within 1 Mb of each cytokine gene transcription start site (TSS) and the levels of log-transformed induced cytokines in each stimulation, adjusting for age, sex, technical variable batchID and major immune cell population counts for each stimulation, were tested through LRT and identified CpG sites weakly associated with IL-17 in LPS (cg09582880), IL-2 in C. albicans (cg17850932 and cg25065535) and IL-8 in influenza (cg16468729) stimulations (FDR adjusted P value of LRT < 0.05) (Extended Data Fig. 10). These effects were mild compared with the identified associated genetic variants and the other associated variables identified in this study but are considered in the final global models (Fig. 5). CpG sites with DNA methylation levels that are directly affected by smoking have been selected as described19.

    Heat maps showing effects of covariates

    To test if the levels of some covariates, such as cell subsets, plasma proteins or DNA methylation probes, could modify the observed association of a variable, such as smoking status, with the log-transformed induced levels of cytokines in each stimulation, we compared with a LRT for each cytokine in each stimulation the model considering both the variable of interest and the covariate of interest (with interactions) plus the usual covariates age, sex and the technical covariate batchID, with a model containing all the covariates but not the variable of interest, followed by a Benjamini–Yekutieli multiple testing adjustment on the whole heat maps. For example, for Fig. 3a, the variable of interest was smoking status and the covariate of interest was each cell subset, so we compared lm(cytokine ~ smoking status × cell subset + age + sex + batchID) with lm(cytokine ~ cell subset + age + sex + batchID). When the LRT is significant, it means adding the variable of interest to the model improves the fit to the cytokine levels. For BMI-related variables, these do not improve the fit to both IL-2 and CXCL5 when T cell subsets are passed as covariates, showing that our approach is powered to identify cellular associations with effects on CXCL5 levels when present.

    pQTL analyses

    Protocols and quality-control filters for genome-wide SNP genotyping are detailed in ref. 3. In brief, the 1,000 Milieu Intérieur donors were genotyped on both the HumanOmniExpress-24 and the HumanExome-12 BeadChips (Illumina), which include 719,665 SNPs and 245,766 exonic SNPs, respectively. Average concordance rate between the two genotyping arrays was 99.99%. The final dataset included 732,341 high-quality polymorphic SNPs. After genotype imputation and quality-control filters, 11,395,554 SNPs were further filtered for minor allele frequencies > 5%, yielding a dataset composed of 1,000 donors and 5,699,237 SNPs for pQTL mapping. pQTL analyses were performed using the MatrixEQTL44 2.2 R package. SNPs were considered as cis-acting pQTLs if they were located within 1 Mb of the TSS of the gene, otherwise they were considered as trans-pQTLs. Protein expression data of the 1,000 individuals were log-transformed prior to pQTL analysis. Bonferonni correction for multiple testing (adjusted P value < 0.05) was applied to the results. We used detection thresholds of 10−3 for cis-pQTLs and 10−5 for trans-pQTLs and age, sex and the technical covariate batchID, as well as a main associated cell subset (monocytes for LPS, E. coli and C. albicans stimulations, CD4pos for SEB, CD8posEMRA for anti-CD3 + CD28, CD45pos for BCG, cDC3 for poly I:C, CD3pos for influenza, CD45pos for TNF, none for null, IL-1β and IFNγ) as covariates. SNPs associated with IFNγ in IFNγ stimulation, with IL-1β in IL-1β stimulation and with TNF in TNF stimulation were disregarded because each of these cytokines were respectively added to the TruCulture tubes and thus do not reflect endogenous secretion. To test the novelty of our pQTL results, we studied the SomaLogic plasma protein pQTL database20, for both cis– and trans-pQTLs listed in Table 1. This dataset allowed testing associations for CXCL5, IFNγ, IL-1β, IL-2, IL-6, IL-10 and IL-12a. Significant associations were identified between the variants rs352045 (cis), rs2393969 (trans), rs10822168 (trans) and the protein CXCL5 (respective FDR adjusted P = 3.02 × 10−10, P = 0.01 and P = 0.022), between rs35345753 (cis), rs62449491 (cis) and IL-6 (respective FDR adjusted P = 4.17 × 10−3 and P = 0.017) and between rs3775291 (trans) and IL-12A (FDR adjusted P = 0.049). To test associations for SNPs in linkage disequilibrium with the SNPs originally referenced in Table 1, we used a dataset of linkage disequilibrium from the ensemble database with similar ancestries as the Milieu Intérieur cohort (1000GENOMES:phase_3:CEU: Utah residents with Northern and Western European ancestry). To be inclusive, SNPs with a r2 > 0.2 were selected as associated alleles and underwent the same analysis as the one performed with the SNPs of reference. SNPs that came out as significant are those in linkage disequilibrium with the SNP referenced in Table 1 that is significantly associated with the corresponding protein. In addition, we also screened eQTL results. We compared our pQTL results with the eQTLs reported in our previous work based on nanostring transcriptomic data for common cytokines (CSF2, IFNγ, IL-1β, TNF, IL-2, IL-6, IL-8, IL-10, IL-12p70, IL-13, IL-17 and IL-23) and stimulations (E. coli, C. albicans, influenza, BCG, and SEB)4, which identified 2 main loci: the TLR1/6/10 locus and the CR1 locus. Association of variants referenced in Table 1 were found in the GTEx consortium database for rs1518110 and IL-10 (FDR adjusted P = 4.3 × 10−9), for rs352045 (cis) and CXCL5 (FDR adjusted P = 9.2 × 10−23) in whole blood and for rs143060887 (cis) and IL-12A (FDR adjusted P = 0.000076). Significant associations between rs352045 and CXCL5 and between rs1518110 and IL-10 were also found in the eQTLgen catalogue.

    Computation of variance explained

    For each stimulation, all the variables associated with at least one induced cytokine were considered to compute the percentage of each induced cytokine variance explained by each associated variable (q value < 0.05) with the R package relaimpo 2.2.3 and plotted with the R package ggplot2 3.2.1. The R2 contribution averaged over orderings among regressors was computed using the lmg type in the calc.relimp function of the relaimpo R package. For this analysis log-transformed induced cytokine data and log-transformed raw counts of cell subsets were used, as well as data for cis– and trans-associated SNPs and methylation probes. For each stimulation, all associated cis-pQTLs (rs352045, rs143060887, rs62449491 and rs1518110 for LPS; rs352045 for anti-CD3 + CD28, rs352045, rs62449491 and rs113845942 for poly I:C; rs352045 and rs35345753 for influenza), and trans-pQTLs (rs3764613 for LPS; rs4833095 for E. coli; rs11936050 for SEB; rs1801274 for anti-CD3 + CD28; rs4833095, rs72636686 and rs10013453 for BCG; rs10779330 and rs11117956 for C. albicans; rs3775291 and rs10822168 for poly I:C), as well as methylation probes (cg09582880 for LPS; cg25065535 for C. albicans, cg17850932 for poly I:C and cg16468729 for influenza) and a main associated cell subset (monocytes for LPS, E. coli and C. albicans stimulations, CD4pos for SEB, CD8posEMRA for anti-CD3 + CD28, CD45pos for BCG, cDC3 for poly I:C, CD3pos for influenza) were considered in the models.

    Reporting summary

    Further information on research design is available in the Nature Portfolio Reporting Summary linked to this article.

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