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Inflammation induced by influenza virus impairs human innate immune control of pneumococcus

Nature Immunology volume 19, pages 1299–1308 (2018)Cite this article

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Abstract

Colonization of the upper respiratory tract by pneumococcus is important both as a determinant of disease and for transmission into the population. The immunological mechanisms that contain pneumococcus during colonization are well studied in mice but remain unclear in humans. Loss of this control of pneumococcus following infection with influenza virus is associated with secondary bacterial pneumonia. We used a human challenge model with type 6B pneumococcus to show that acquisition of pneumococcus induced early degranulation of resident neutrophils and recruitment of monocytes to the nose. Monocyte function was associated with the clearance of pneumococcus. Prior nasal infection with live attenuated influenza virus induced inflammation, impaired innate immune function and altered genome-wide nasal gene responses to the carriage of pneumococcus. Levels of the cytokine CXCL10, promoted by viral infection, at the time pneumococcus was encountered were positively associated with bacterial load.

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Fig. 1: LAIV-pneumococcus co-infection leads to excessive proinflammatory responses that are associated with increased pneumococcal load and impaired monocyte recruitment.
Fig. 2: Neutrophil function is impaired following LAIV administration.
Fig. 3: Monocyte recruitment following pneumococcal colonization is impaired during LAIV co-infection.
Fig. 4: Pneumococcus-specific responses are induced following colonization, which is impaired by LAIV co-infection.
Fig. 5: Nasal transcriptomics following LAIV–S. pneumoniae co-infection (n = 35).
Fig. 6: CEMiTool applied to control cohort: module M1.
Fig. 7: CEMiTool applied to control group: module M3.
Fig. 8: CEMiTool applied to LAIV.

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Data availability

Raw RNA sequencing data have been deposited in the Gene Expression Omnibus repository, accession number GSE117580. All other underlying data are provided in the manuscript.

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Acknowledgements

S.B.G. and D.M.F. are supported by the Medical Research Council (grant MR/M011569/1), the Bill and Melinda Gates Foundation (grant OPP1117728) and the National Institute for Health Research Local Comprehensive Research Network. Flow cytometric acquisition was performed on a BD LSR II funded by a Wellcome Trust Multi-User Equipment Grant (104936/Z/14/Z). S.P.J. received support from the Royal Society of Tropical Medicine and Hygiene for NanoString analysis. H.I.N. is supported by the São Paulo Research Foundation (FAPESP; grants 2013/08216-2 and 2012/19278-6). We thank all volunteers for participating in this study, and R. Robinson, C. Lowe, L. Lazarova, K. Piddock and I. Wheeler for clinical support. We also acknowledge M. Mina for his input in study design.

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  1. These authors contributed equally: Simon P. Jochems and Fernando Marcon

Authors and Affiliations

  1. Department of Clinical Sciences, Liverpool School of Tropical Medicine, Liverpool, UK

    Simon P. Jochems, Beatriz F. Carniel, Mark Holloway, Elena Mitsi, Emma Smith, Jenna F. Gritzfeld, Carla Solórzano, Jesús Reiné, Sherin Pojar, Elissavet Nikolaou, Esther L. German, Angie Hyder-Wright, Helen Hill, Caz Hales, Hugh Adler, Seher Zaidi, Victoria Connor, Stephen B. Gordon, Jamie Rylance & Daniela M. Ferreira

  2. Department of Clinical and Toxicological Analyses, School of Pharmaceutical Sciences, University of São Paulo, São Paolo, Brazil

    Fernando Marcon & Helder I. Nakaya

  3. Royal Liverpool and Broadgreen University Hospital, Liverpool, UK

    Angie Hyder-Wright, Helen Hill, Caz Hales & Victoria Connor

  4. Centre for Inflammation Research, University of Edinburgh, Edinburgh, UK

    Wouter A. A. de Steenhuijsen Piters & Debby Bogaert

  5. Department of Paediatric Immunology and Infectious Diseases, University Medical Center Utrecht, Utrecht, The Netherlands

    Wouter A. A. de Steenhuijsen Piters & Debby Bogaert

  6. Department of Medical Microbiology, University Medical Center Utrecht, Utrecht, The Netherlands

    Wouter A. A. de Steenhuijsen Piters & Debby Bogaert

  7. Malawi-Liverpool-Wellcome Trust Clinical Research Programme, Blantyre, Malawi

    Stephen B. Gordon

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Contributions

S.P.J. contributed to conceiving, designing, performing and analyzing experiments and writing the paper. F.M. and H.I.N. contributed to analyzing experiments and writing the paper. B.F.C., M.H., E.M., E.S., J.F.G., C.S., J.Reiné, S.P., E.N., E.L.G., W.A.A.d.S.P. and D.B. contributed to conducting and analyzing experiments. A.H.-W., H.H., C.H., H.A., S.Z., V.C., J.Rylance and S.B.G. contributed to sample collection and/or designing the study. D.M.F. contributed to conceiving, designing and analyzing experiments, designing the study and writing the paper. All authors have read and approved the manuscript.

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Correspondence to Simon P. Jochems, Helder I. Nakaya or Daniela M. Ferreira.

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Integrated supplementary information

Supplementary Figure 1 Pneumococcal load in the LAIV and control cohorts.

Mean and standard error of log-transformed carriage load (colony-forming units (CFU)/mL nasal wash) for carriage+ volunteers (defined by detection of S. pneumoniae at any timepoint) are shown for the control carriage+ group (green, n = 24 subjects) and LAIV carriage+ group (orange, n = 25). Load for samples with undetectable pneumococcal load was set at 0.1 CFU/mL nasal wash.

Supplementary Figure 2 CXCL10 concentrations are increased by virus infection.

(a), Concentrations of CXCL10 at day 0 in the LAIV cohort, measured by Luminex in nasosorption (n = 77). (b), Concentrations of CXCL10 at day 5 to S. pneumoniae inoculation in a cohort with known viral URT state measured by ELISA (n = 82). Oropharyngeal swabs collected 5 d before S. pneumoniae inoculation were assessed for a viral multiplex PCR panel for detection of influenza A and B (n = 0), respiratory syncytial virus (n = 2), human metapneumovirus (n = 0), human rhinovirus (n = 12), parainfluenza viruses 1–4 (n = 1), and coronaviruses OC43, NL63, 229E, and HKU1 (n = 5). Individual volunteers are shown and box plots depict median and interquartile ranges, with whiskers extending to 1.5 × interquartile range or maximum value, per group. *P = 0.017, **P = 6.2 × 10–5 by two-tailed Mann–Whitney test.

Supplementary Figure 3 Nasal granulocyte numbers over time and baseline immune cell composition.

(a), Numbers of granulocytes, predominantly neutrophils based on CD16 expression, at the nasal mucosa. Median and interquartile range are shown for cell numbers normalized to numbers of epithelial cells for control carriage+ (n = 24), control carriage– (n = 37), LAIV carriage+ (n = 25) and LAIV carriage– (n = 30) groups. The x axis shows days relative to inoculation. (b), Absolute numbers of cells observed per nasal sample (median and IQR are shown for 117 subjects at baseline).

Supplementary Figure 4 Flow cytometry gating strategy and longitudinal levels of nasal T cells and monocytes.

(a), Gating strategy of nasal cells for one representative volunteer. (b), Numbers of T cells at the nasal mucosa. Median and interquartile range are shown for cell numbers normalized to numbers of epithelial cells for control carriage+ (n = 24), control carriage– (n = 37), LAIV carriage+ (n = 25) and LAIV carriage– (n = 30) groups. The x axis shows days relative to inoculation. (c), Median and interquartile range of monocyte numbers in the control group over time with carriage detected by classical microbiology (carriage+, n = 24), molecular methods only (lytA+, n = 16) or not at all (carriage–, n = 22). *P = 0.038 at day 2 and P = 0.030 at day 29, **P = 0.002 by two-tailed Wilcoxon paired non-parametric test.

Supplementary Figure 5 Monocyte recruitment associates with CCL2 concentration and is reproducible in an independent volunteer cohort.

(a), Spearman’s correlation between the 30 measured cytokines and nasal monocyte numbers for each timepoint (n = 73). The length of the bar depicts the rho value, cyan bars represent cytokines that correlate significantly at all days, red bars associate for a specific day, and transparent red bars are not significantly associated for that day. (b), Monocyte numbers over time in those volunteers who most upregulate CCL2, IFN-γ, IL-6 or TNF at day 2 (top quartile FC induction, n = 17 versus below top quartile, n = 56) or not. *P = 0.028 by two-tailed Mann–Whitney test of monocyte number area under curve of inducers and non-inducers. (c), Numbers of monocytes and CCL2 in a second, independent cohort of seven carriers without any vaccination. Symbols represent individual subjects, with color corresponding to day relative to S. pneumoniae inoculation. The effects of CCL2 on monocyte numbers by generalized linear regression analysis are shown, correcting for repeated individual measurements.

Supplementary Figure 6 Nasal cell responses to in vitro stimulation with pneumococcus.

Whole nasal cells were collected 29 d after S. pneumoniae inoculation and stimulated for 18 h with heat-killed pneumococcus (n = 48). Supernatant was collected and the concentrations of 30 cytokines were measured by Luminex. Four cytokines were not measured above the limit of detection (IL-2, IL-4, MIG and eotaxin), and these were excluded from analysis. (a), Responses for all measured cytokines for the four groups are shown. (b), Production in carriage– volunteers subdivided into those who had very low carriage loads, detectable only by molecular methods (lytA+, n = 9), or not at all (carriage–, n = 5). The dotted line indicates a twofold increase over the unstimulated control. The median and interquartile range of FC to unstimulated are shown An asterisk indicates significantly induced cytokines (shown in red) (FC > 2, q < 0.05, two-tailed paired Wilcoxon test followed by Benjamini–Hochberg correction).

Supplementary Figure 7 Immune mechanisms associating with control of S. pneumoniae carriage and their disruption by LAIV.

Carriage in the absence of influenza leads to quick degranulation of nasal neutrophils followed by recruitment of monocytes to the nose, associating with the start of clearance. Influenza infection leads to inflammation, impairing this innate control of carriage.

Supplementary information

Supplementary Text and Figures (download PDF )

Supplementary Figures 1–7 and Supplementary Tables 2 and 3

Reporting Summary (download PDF )

Supplementary Data 1

CEMiTool report of control group

Supplementary Data 2

CEMiTool report of LAIV group

Supplementary Table 1 (download XLSX )

Cytokine induction following LAIV or control vaccination

Supplementary Table 4 (download XLSX )

List of differentially expressed genes

Supplementary Table 5 (download XLSX )

List of pathways

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Jochems, S.P., Marcon, F., Carniel, B.F. et al. Inflammation induced by influenza virus impairs human innate immune control of pneumococcus. Nat Immunol 19, 1299–1308 (2018). https://doi.org/10.1038/s41590-018-0231-y

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