Novel coenzyme Q6 genetic variant increases susceptibility to pneumococcal disease | Nature Immunology

Nature Immunology (2024)Cite this article 1 Altmetric Metrics details Acute lower respiratory tract infection (ALRI) remains a major worldwide cause of childhood mortality, compelling innovation in

Nature Immunology (2024)Cite this article

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Acute lower respiratory tract infection (ALRI) remains a major worldwide cause of childhood mortality, compelling innovation in prevention and treatment. Children in Papua New Guinea (PNG) experience profound morbidity from ALRI caused by Streptococcus pneumoniae. As a result of evolutionary divergence, the human PNG population exhibits profound genetic variation and diversity. To address unmet health needs of children in PNG, we tested whether genetic variants increased ALRI morbidity. Whole-exome sequencing of a pilot child cohort identified homozygosity for a novel single-nucleotide variant (SNV) in coenzyme Q6 (COQ6) in cases with ALRI. COQ6 encodes a mitochondrial enzyme essential for biosynthesis of ubiquinone, an electron acceptor in the electron transport chain. A significant association of SNV homozygosity with ALRI was replicated in an independent ALRI cohort (P = 0.036). Mice homozygous for homologous mouse variant Coq6 exhibited increased mortality after pneumococcal lung infection, confirming causality. Bone marrow chimeric mice further revealed that expression of variant Coq6 in recipient (that is, nonhematopoietic) tissues conferred increased mortality. Variant Coq6 maintained ubiquinone biosynthesis, while accelerating metabolic remodeling after pneumococcal challenge. Identification of this COQ6 variant provides a genetic basis for increased pneumonia susceptibility in PNG and establishes a previously unrecognized role for the enzyme COQ6 in regulating inflammatory-mediated metabolic remodeling.

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The COQ6DY variant has been deposited to ClinVar, accession no RCV004698891.1, release date 9 September 2024. Publicly available databases used in the present study include GnomAD (formerly known as ExAC; https://gnomad.broadinstitute.org), AlphaFold (https://alphafold.ebi.ac.uk) and UniProt (https://www.uniprot.org). The UniProt unique identifier for human COQ6 is Q9Y2Z9 and for mouse COQ6 Q8R1S0. There are no restrictions on availability of data shown here. Source data are provided with this paper.

No customized code was used in this manuscript. Software programs are either commercially or publicly available.

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Funding was provided by the National Institutes of Health (NIH)/National Institute of Allergy and Infectious Diseases (NIAID) (grant nos. R01 AI139540 and R21 AI142723), NIH/National Heart, Lung, and Blood Institute (grant no. R01 HL177453) and the Children’s Discovery Institute (grant nos. PD-II-2013-295, PD-II-2014-366 and PD-II-2018-742) (all to S.C.M.). E.C.W. was supported by the NIH (grant no. T32 AI007172). Funding was provided by the NIH/NIAID (grant no. R01 AI036478) to J.W.K. The GTAC is partially supported by the National Cancer Institute Cancer Center (support grant no. P30 CA91842 to the Siteman Cancer Center) and by the Institute for Clinical and Translational Science/Clinical and Translational Science Awards (grant no. UL1TR000448 from the National Center for Research Resources (NCRR)), a component of the NIH and NIH Roadmap for Medical Research. The Diabetes Research Center at WUSM is supported by the NIH (grant no. P30 DK020579). This publication is solely the responsibility of the authors and does not necessarily represent the official view of the NCRR or the NIH. Our deepest thanks go to all participants who consented to take part in our studies and to the many team members who contributed. We thank D. Lehmann for her support of our partnership with PNGIMR and for her critical review of the manuscript. We also thank D. Kreamalmeyer for technical support of our animal program. Our eternal and most profound gratitude go to P. Tarr for his superb mentorship, which encompasses the ideal mix of infectious enthusiasm, sage advice and insistent goading, without which this manuscript might not have been written. We thank the donors to the St. Louis Children’s Hospital Foundation and the Children’s Discovery Institute. We thank the GTAC in the Department of Genetics at WUSM for help with genomic analysis. This manuscript presents research conducted by an equal partnership between researchers at PNGIMR and researchers at WUSM throughout the research process, including study design, study implementation, data ownership, intellectual property and authorship. The equal partnership is shown by inclusion of two co-senior authors (W.S.P. and S.C.M.). As determined in collaboration with researchers in PNG, the research is highly relevant to PNG. Roles and responsibilities were agreed among collaborators ahead of the conduct of the research. Capacity building included an exchange of research staff, with E.C.W. traveling to PNGIMR for 2 weeks and S.J. to WUSM for a month during the conduct of the research. The human studies performed in PNG were approved in advance by the PNGIMR IRB and the PNG MRAC. Potential risks to study participants (potential privacy violation owing to acquisition of genetic material) were disclosed in study consent forms and risks ameliorated by provision of deidentified samples only to WUSM researchers (WUSM researchers retain genetic information and PNGIMR researchers retain personally identifying information, such that no researcher can ‘pair’ potentially personally identifying information with the genetic information). Potential benefits derived from this research will be shared among coauthors. Biological materials obtained in PNG were divided, with half of each sample being sent to WUSM for analysis and half retained by PNGIMR researchers for their own use.

Brian J. DeBosch

Present address: Department of Pediatrics, Division of Gastroenterology, Hepatology & Nutrition, Indiana University School of Medicine, Indianapolis, IN, USA

These authors contributed equally: William S. Pomat, Sharon Celeste Morley.

Department of Pediatrics, Division of Infectious Diseases, Washington University School of Medicine, St. Louis, MO, USA

Emma C. Walker, Elizabeth M. Todd, Xue Lin, Michelle Bryant, Emily Krone, Rashmi Ramani, Taylor P. Green, Edgar P. Anaya, Julie Y. Zhou & Sharon Celeste Morley

Program in Immunology, Division of Biological and Biomedical Sciences, Washington University School of Medicine, St. Louis, MO, USA

Emma C. Walker & Sharon Celeste Morley

Infection and Immunity Unit, Papua New Guinea Institute of Medical Research, Goroka, Papua New Guinea

Sarah Javati, John-Paul Matlam, Lapule Yuasi & William S. Pomat

Department of Medicine, Division of Infectious Diseases, Washington University School of Medicine, St. Louis, MO, USA

Pallavi Chandra & Jennifer A. Philips

Department of Pediatrics, Division of Hematology–Oncology, Washington University School of Medicine, St. Louis, MO, USA

Katherine A. Alexander, R. Spencer Tong & Todd E. Druley

Department. of Pediatrics, Division of Critical Care Medicine, Washington University School of Medicine, St. Louis, MO, USA

Sebastian Boluarte, Fan Yang & Regina A. Clemens

Department of Biochemistry and Molecular Biophysics, Washington University School of Medicine, St. Louis, MO, USA

Lina Greenberg & Michael J. Greenberg

Departments of Developmental Biology and Medicine, Cardiovascular Division, Washington University School of Medicine, St. Louis, MO, USA

Jeanne M. Nerbonne

Department of Molecular Microbiology, Washington University School of Medicine, St. Louis, MO, USA

Jennifer A. Philips

Division of Comparative Medicine, Research Animal Diagnostic Laboratory, Washington University School of Medicine, St. Louis, MO, USA

Leslie D. Wilson

Department of Pediatrics, Division of Nephrology and Department of Cell Biology and Physiology, Washington University School of Medicine, St. Louis, MO, USA

Carmen M. Halabi

Department of Pediatrics, Division of Gastroenterology, Hepatology and Nutrition, Washington University School of Medicine, St. Louis, MO, USA

Brian J. DeBosch

Wesfarmers Centre for Vaccines and Infectious Diseases, Telethon Kids Institute and School of Medicine, University of Western Australia, Nedlands, Western Australia, Australia

Christopher C. Blyth & William S. Pomat

Department of Infectious Diseases, Perth Children’s Hospital, Nedlands, Western Australia, Australia

Christopher C. Blyth

Department of Microbiology, PathWest Laboratory Medicine, QEII Medical Centre, Nedlands, Western Australia, Australia

Christopher C. Blyth

Center for Global Health & Diseases, School of Medicine, Case Western Reserve University, Cleveland, OH, USA

James W. Kazura

Dept. of Pathology and Immunology, Washington University School of Medicine, St. Louis, MO, USA

Sharon Celeste Morley

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E.C.W., W.S.P. and S.C.M. conceived the project. E.C.W., M.B., E.T., X.L. and S.C.M. curated the data. E.C.W., M.B. and S.C.M. did the formal analysis. S.C.M. acquired the funding. E.C.W., S.J., E.M.T., J.P.M., M.B., R.R., X.L., P.C., E.K., L.G., L.W., S.B., F.Y., J.N., M.J.G., R.C., C.M.H., B.J.D., T.P.G., E.P.A., J.Y.Z., K.A.A., R.S.T. and L.Y. carried out the investigations. E.C.W., E.M.T., R.R., P.C., E.K., L.G., L.W., S.B., F.Y., J.N., M.J.G., R.C., C.M.H., B.J.D., J.A.P., C.C.B. and T.E.D. provided the methodology. J.A.P., C.C.B., T.E.D., J.W.K., W.S.P. and S.C.M. administered the project. J.W.K., W.S.P. and S.C.M. provided the resources. J.A.P., M.J.G., R.C., T.E.D., J.W.K., W.S.P. and S.C.M. supervised the project. S.C.M. validated the project. E.C.W., R.C. and S.C.M. visualized the project. E.C.W. and S.C.M. wrote the original manuscript. All authors reviewed and edited the manuscript. E.C.W. and S.C.M. wrote the major revisions to the manuscript.

Correspondence to Sharon Celeste Morley.

T.E.D. had no financial conflicts of interest during the years in which he contributed to the project (2018 and earlier). He is currently employed by Mission Bio, Inc. and serves as a scientific advisor for RhoDx, Inc. The other authors declare no competing interests.

Nature Immunology thanks Navdeep Chandel, Ruben Martinez-Barricarte and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Peer reviewer reports are available. Primary Handling Editor: L. A. Dempsey, in collaboration with the Nature Immunology team.

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a. Complete protein sequences of human and mouse COQ6 aligned using Clustal O. ‘*’ indicates identical amino acid residues, ‘:’ indicates conservation between amino acids with strongly similar properties. b. The predicted 3D structure of mouse COQ6 indicates that D316 resides in a similar location in an α-helix as human D308 and forms a hydrogen bond with nearby H311. Graphic is a screenshot obtained from AlphaFold, provided as freely available for both academic and commercial use under Creative Commons Attribution 4.0 (CC-BY 4.0) license terms.

Flow cytometry data from a. BAL fluid, b. lung, c. blood, d. spleen, e. inguinal lymph nodes, and f. thymus, quantifying major leukocyte populations. We also quantify total number of cells per tissue. Data from 2-4 independent experiments, each symbol represents value from one animal, line at median, (n) given underneath x-axis labels. P-value determined by Mann-Whitney (two-tailed).

Source data

a. Percentage of AMs and PMNs identified by flow cytometry in BAL fluid of matched WT and DY mice 4 dpi. b. Equivalent concentrations of TNFα, IL-1α, IFNγ and IL-10 in BAL fluid of Sp-challenged WT and DY mice 4 dpi. (a,b) Each symbol represents value from one animal, line at median, 95% CI shown, p-values determined by Mann-Whitney(two-tailed), data combined from two independent experiments, (n) given below x-axis labels. c. Percentage of intracellular bacteria killed in one hour by BMDMs derived from WT (solid) or DY (blue) mice. Each symbol represents the average of triplicate technical samples derived from one experiment. Data are derived from 4 independent experiments (biological replicates), line at median, P-value determined by Mann-Whitney (two-tailed). d. CellRox fluorescence in BMDMs from WT (grey) or DY (blue) mice 3 h after Sp infection in vitro. Total cellular ROS production was measured by CellRox fluorescence, with contribution of mtROS to total ROS defined by mitoTEMPO inhibition. BMDMs incubated with CellRox with MitoTEMPO (squares; 10 µM), NAC (triangles;10 mM) or without either inhibitor (circles). Maximum ROS signal was determined by incubating BMDMs with tBHP (dark grey); background fluorescence measured on BMDMs with no CellRox added (light grey). MFI acquired by microscopy. Whiskers show 1–99% confidence interval, with boxes showing 25–75% confidence intervals and lines at median. Outliers shown as individual symbols, each representing value from one cell, n given below x-axis. P-values determined by Kruskal-Wallis (p < 0.0001) followed by selected pairwise comparisons with Dunn’s adjustment for multiple comparisons. e. WT or DY mice received MitoSox via i.t. instillation 30 m prior to i.t. instillation of DDAO-labeled Sp. BAL lavage was performed on animals 30 min after Sp challenge and MitoSox MFI of AMs measured by flow cytometry. Data shown as ratio of MFI (infected AMs):MFI (uninfected AMs). Each symbol represents value from one mouse, data from 3 independent experiments, p-value determined by Mann-Whitney (two-tailed). In two experiments, one control mouse and two infected animals were used.

Source data

a. Flow cytometric analysis of BAL fluid and whole lung homogenates obtained from WT◄WT.1 and DY◄WT.1 chimeric mice 72 hpi revealed >98% of all hematopoeitic (CD45+) cells were marked as CD45.2 (donor), with equivalent or increased AM, PMN, or monocyte populations derived from DY donors. b. Schematic of reconstitution of CD45.2+ WT or DY mice with bone marrow cells derived from CD45.1+ WT (WT.1) mice. Mice were challenged with Sp eight weeks after reconstitution. c. Flow cytometric analysis revealed >98% of CD45+ cells in BAL fluid of infected chimeric mice were donor-derived (CD45.1+), with proportionally fewer recipient hematopoeitic cells (CD45.2+) remaining in WT.1◄DY chimeric mice. Similar numbers of CD45.1+ cells were observed in BAL fluid from WT.1◄WT and WT.1◄DY mice. d. Of the recipient CD45.2+ cells remaining in BAL fluid from infected chimeras, virtually none were AMs or PMNs; most were CD3+. e. Total cell numbers of circulating CD45.2+ cells in blood from WT.1◄WT and WT.1◄DY chimeric mice, revealing that the majority of remaining recipient CD45.2+ cells were CD3+. f. Wet:dry weight ratio of and Evans Blue infiltration into BAL fluid of female chimeric WT.1◄WT or WT.1◄DY mice 72 hpi. (a,c,d,e,f) Each symbol represents value from one animal, line at median, 95% CI shown, p-values determined by Mann-Whitney (two-tailed), data combined from two (b,c,d,f) or seven (e) independent experiments, (n) given below x-axis labels.

Source data

Immunoblot of mitochondria (normalized to total protein; 40 µg each sample) from hearts of indicated mice, illuminated using the LiCOR Odyssey system. Representative of three independent immunoblots. The entire immunoblot is shown.

Source data

a. Representative images of transmission electron micrographs of fixed AMs harvested from WT or DY mice. AMs were either uninfected or infected in vitro with Sp prior to fixation. Mitochondria are indicated in boxes. Scale bars = 500 nm. b. Quantification of mitochondrial numbers per cell, area of each mitochondria, and circularity of each mitochondria (perfect circle = 1, line = 0). Each symbol represents values for a cell (number) or for a mitochondrion (area and circularity). Median with 95% CI shown, (n) given below x-axis labels, p-value determined by Kruskal-Wallis followed by adjustment for multiple comparisons for pairwise analyses.

Source data

Cytosolic calcium was measured by confocal microscopy in Fluo-4 loaded BMDMs (a,b) and AMs (c,d) treated with pneumolysin. a. Peak amplitude of calcium signals from WT (grey) and DY (blue) BMDMs from a representative experiment of three independent experiments. b. Average peak calcium signal from n = 3 experiments. c. Peak amplitude of calcium signals from WT (grey) and DY (blue) AMs from three independent experiments (each experiment shown). d. Average peak calcium signal from n = 3 experiments. e. Representative kinetic calcium tracing from BMDMs stimulated with ionomycin (400nM). f. Peak amplitude of calcium signals from > 100 WT and DY BMDMs stimulated with ionomycin. g,h,i. Calcium flux measured by flow cytometry in Indo-1 loaded AMs. g. Representative kinetic calcium tracing from AMs stimulated with ionomycin (100nM) first in calcium-free media (arrow) to induce ER store release. 1mM CaCl2 was added at 120s as indicated by the darker blue bar to allow extracellular store-operated calcium entry (SOCE). h. Area under the curve (AUC) of ER store release (30–120s) and i. SOCE (150–450s) segments from n = 7 experiments. (a,c,f) Each symbol represents value from one cell, line at median, 95% CI shown. N=number of cells, given below each x-axis. (b,d,h,i) Each symbol represents average value for all cells analyzed in each experiment; bars show mean ± SD. N=number of experiments, given below x-axis. e) Each symbol shows mean ± SEM of all WT (gray) or DY (blue) cells analyzed in one representative experiment. Data were analyzed using unpaired Mann-Whitney (two-tailed) (a, c, h-i) or paired Wilcoxon rank test (two-tailed) (b, d).

Source data

Ventricular cardiomyocytes were isolated from WT and DY mice. Individual cells were loaded with the calcium fluorescent indicator, FLUOFORTE. Cells were paced at 1 Hz and fluorescence was recorded at 100 Hz by epifluorescence microscopy. We observed no statistically significant differences (P > 0.05; see raw data file for exact P values) in a. the maximal fluorescence, proportional to the amount of calcium released, b. the time to rise to 50% of the peak fluorescence during a calcium transient, or c. the time to decay by 50% of the peak fluorescence during a calcium transient. Data were analyzed using a 2-way ANOVA followed by a post-hoc Tukey’s multiple comparison test for each condition. N = 55 WT – PLY, 50 WT + PLY, 59 DY – PLY, and 54 DY + PLY cardiomyocytes collected over 2 days from two mice.

Source data

Side scatter (SSC) x forward scatter (FSC) used to exclude debris. SSC-A x SSC-H used to gate on singlets/exclude doublets. CD45.1 x CD45.2 used to identify all CD45+ cells (two examples shown; one from CD45.1+ recipient and one from CD45.2+ recipient) and exclude non-hematopoietic cells. SSC x CD45.1+ (or CD45.2+, not shown) used to separate donor and recipient cells. Gating on live/singlets/all CD45/CD45.1+, CD11b x Ly6G is then used to identify PMNs. Gating on live/singlets/all CD45/CD45.1+, CD11c x CD64 is used to identify macrophages, followed by CD11c x SiglecF to identify AMs.

Supplementary Results, Discussion, Methods, References and Figs. 1–3. Source data for CRISPR generation of DY mouse.

Calcium flux in WT BMDMs induced by PLY. Confocal imaging of calcium responses in Fluo-4-loaded WT BMDMs stimulated with PLY (added at 4 min). Supporting video for Extended Data Fig. 7a,b. Scale bar, 50 mm.

Calcium flux in DY BMDMs induced by PLY. Confocal imaging of calcium responses in Fluo-4-loaded DY BMDMs stimulated with PLY (added at 4 min). Supporting video for Extended Data Fig. 7a,b. Scale bar, 50 mm.

Calcium flux in WT AMs induced by PLY. Confocal imaging of calcium responses in Fluo-4-loaded WT AMs stimulated with PLY (added at 4 min). Supporting video for Extended Data Fig. 7c,d. Scale bar, 50 mm.

Calcium flux in DY AMs induced by PLY. Confocal imaging of calcium responses in Fluo-4-loaded DY AMs stimulated with PLY (added at 4 min). Supporting video for Extended Data Fig. 7c,d. Scale bar, 50 mm.

Source data for Supplementary Fig. 1.

Source data for Supplementary Fig. 3.

Sanger sequencing results, results from replication cohort including age and biological sex of individuals, and ddPCR results from deidentified samples.

Original microscope images.

Excel spreadsheet of all numerical data.

Original images obtained of plate.

Excel spreadsheet of all numerical data.

PNG file of original image obtained from LI-COR ODYSSEY system.

Original images obtained from TEM.

Excel spreadsheet of all numerical data.

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Walker, E.C., Javati, S., Todd, E.M. et al. Novel coenzyme Q6 genetic variant increases susceptibility to pneumococcal disease. Nat Immunol (2024). https://doi.org/10.1038/s41590-024-01998-4

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Received: 06 February 2024

Accepted: 30 September 2024

Published: 04 November 2024

DOI: https://doi.org/10.1038/s41590-024-01998-4

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