Type I IFN exacerbates disease in tuberculosis-susceptible mice by inducing neutrophil-mediated lung inflammation and NETosis

Tuberculosis (TB) is a leading cause of mortality due to infectious disease, but the factors determining disease progression are unclear. Transcriptional signatures associated with type I IFN signalling and neutrophilic inflammation were shown to correlate with disease severity in mouse models of TB. Here we show that similar transcriptional signatures correlate with increased bacterial loads and exacerbate pathology during Mycobacterium tuberculosis infection upon GM-CSF blockade. Loss of GM-CSF signalling or genetic susceptibility to TB (C3HeB/FeJ mice) result in type I IFN-induced neutrophil extracellular trap (NET) formation that promotes bacterial growth and promotes disease severity. Consistently, NETs are present in necrotic lung lesions of TB patients responding poorly to antibiotic therapy, supporting the role of NETs in a late stage of TB pathogenesis. Our findings reveal an important cytokine-based innate immune effector network with a central role in determining the outcome of M. tuberculosis infection.We thank Xuemei Wu (Laboratory of Immunoregulation and Infection, The Francis Crick Institute) for her help in coordinating all the breeding and maintenance of the mice used in this study. We thank Jean Langhorne (Malaria Immunology Laboratory, The Francis Crick Institute) and Ilaria Malanchi (Tumour-Host Interaction Laboratory, The Francis Crick Institute) for the Ifnarfl/fl and the MRP8-Cre mice, respectively. We thank Akul Singhania and Olivier Tabone (Laboratory of Immunoregulation and Infection, The Francis Crick Institute) for critical discussion and input regarding RNA-Seq analyses. We thank Alan Sher (National Institute of Allergy and Infectious Diseases, NIH) and Paulo Vieira (Institut Pasteur) for discussion and critical reading of the manuscript. We thank The Francis Crick Institute Biological Services for animal husbandry and technical support; Advanced Sequencing Facility and Bioinformatics and Biostatistics Science Technology Platforms for helping with sequence sample processing and analyses; and Experimental Histopathology for their work in preparing lung sections for histological analyses. This study was funded by The Francis Crick Institute which receives its core funding from Cancer Research UK (FC001126, FC001999, FC001129), the UK Medical Research Council (FC001126, FC001999, FC001129), and the Wellcome Trust (FC001126, FC001999, FC001129); before that by the UK Medical Research Council (MRC U117565642); and by the European Research Council (294682-TB-PATH). The collection of human lung tissue samples for this study was funded by the Spanish Government-FEDER Funds through CP13/00174, CPII18/00031 and PI16/01511 grants, and the CIBER Enfermedades Respiratorias Network; and by the Spanish Society of Pneumology and Thoracic Surgery (SEPAR) through grant 16/023. A.O’G., L.M-T., P.J.S., E.S. and S.H. were supported by The Francis Crick Institute which receives its core funding from Cancer Research UK (FC001126), the UK Medical Research Council (FC001126), and the Wellcome Trust (FC001126); before that by the UK Medical Research Council (MRC U117565642). S.L.P., A.S-B., and E.H. were funded by the Royal Veterinary College and The Francis Crick Institute. M.S. was funded by grants POCI-01-0145-FEDER-028955, and by FCT through Estimulo Individual ao Emprego Científico. K.L.F. was funded by FCT PhD scholarship SFRH/BD/114405/2016